protein sequence coverage: Topics by WorldWideScience.org

Sample records for protein sequence coverage

Dynamics of domain coverage of the protein sequence universe

Science.gov (United States)

2012-01-01

Background The currently known protein sequence space consists of millions of sequences in public databases and is rapidly expanding. Assigning sequences to families leads to a better understanding of protein function and the nature of the protein universe. However, a large portion of the current protein space remains unassigned and is referred to as its “dark matter”. Results Here we suggest that true size of “dark matter” is much larger than stated by current definitions. We propose an approach to reducing the size of “dark matter” by identifying and subtracting regions in protein sequences that are not likely to contain any domain. Conclusions Recent improvements in computational domain modeling result in a decrease, albeit slowly, in the relative size of “dark matter”; however, its absolute size increases substantially with the growth of sequence data. PMID:23157439
Dynamics of domain coverage of the protein sequence universe

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Rekapalli Bhanu

2012-11-01

Full Text Available Abstract Background The currently known protein sequence space consists of millions of sequences in public databases and is rapidly expanding. Assigning sequences to families leads to a better understanding of protein function and the nature of the protein universe. However, a large portion of the current protein space remains unassigned and is referred to as its “dark matter”. Results Here we suggest that true size of “dark matter” is much larger than stated by current definitions. We propose an approach to reducing the size of “dark matter” by identifying and subtracting regions in protein sequences that are not likely to contain any domain. Conclusions Recent improvements in computational domain modeling result in a decrease, albeit slowly, in the relative size of “dark matter”; however, its absolute size increases substantially with the growth of sequence data.
Aspects of coverage in medical DNA sequencing

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Wilson Richard K

2008-05-01

Full Text Available Abstract Background DNA sequencing is now emerging as an important component in biomedical studies of diseases like cancer. Short-read, highly parallel sequencing instruments are expected to be used heavily for such projects, but many design specifications have yet to be conclusively established. Perhaps the most fundamental of these is the redundancy required to detect sequence variations, which bears directly upon genomic coverage and the consequent resolving power for discerning somatic mutations. Results We address the medical sequencing coverage problem via an extension of the standard mathematical theory of haploid coverage. The expected diploid multi-fold coverage, as well as its generalization for aneuploidy are derived and these expressions can be readily evaluated for any project. The resulting theory is used as a scaling law to calibrate performance to that of standard BAC sequencing at 8× to 10× redundancy, i.e. for expected coverages that exceed 99% of the unique sequence. A differential strategy is formalized for tumor/normal studies wherein tumor samples are sequenced more deeply than normal ones. In particular, both tumor alleles should be detected at least twice, while both normal alleles are detected at least once. Our theory predicts these requirements can be met for tumor and normal redundancies of approximately 26× and 21×, respectively. We explain why these values do not differ by a factor of 2, as might intuitively be expected. Future technology developments should prompt even deeper sequencing of tumors, but the 21× value for normal samples is essentially a constant. Conclusion Given the assumptions of standard coverage theory, our model gives pragmatic estimates for required redundancy. The differential strategy should be an efficient means of identifying potential somatic mutations for further study.
Alternative Enzymes Lead to Improvements in Sequence Coverage and PTM Analysis

Science.gov (United States)

Hooper, Kyle; Rosenblatt, Michael; Urh, Marjeta; Saveliev, Sergei; Hosfield, Chris; Kobs, Gary; Ford, Michael; Jones, Richard; Amunugama, Ravi; Allen, David; Brazas, Robert

2013-01-01

The profiling of proteins using biological mass spectrometry (bottom up proteomics) most commonly requires trypsin. Trypsin is advantageous in that it produces peptides of optimal charge and size. However, for applications in which the proteins under investigation are part of a complex mixture or not isolated at high levels (i.e. low ng from an immunoprecipitation), sequence coverage is rarely complete. In addition, we have found that in several cases, like phosphorylation, acetylation, and methylation, alternative proteases are required to prepare peptides suitable for MS detection. This poster will provide specific examples which demonstrate this observation. For example, the application of a combined Trypsin/ Lys-C mixture reduces the number of missed cleavages by more than 3-fold producing samples with lower CV's (for biological replicates). The mixture is also well-suited for the complete proteolysis of hydrophobic, compact proteins. The addition of chymotrypsin and elastase has been found to be useful for identifying phosphorylation sites on proteins, especially on sequences where the site of phosphorylation inhibits trypsin (i.e. proximal to K or R). Many epigenetic applications have focused on histone modifications, like lysine acetylation and arginine methylation. Alternative proteases like Asp-N, Glu-C, and chymotrypsin have been especially useful given the fact that the modified K and R residues are resistant to c-terminal cleavage by trypsin. Finally, in the case of serum profiling, the addition of the endoglycosidase, PNGase F has been found to improve sequence coverage due to the removal of N-linked glycans.
Protein-Level Integration Strategy of Multiengine MS Spectra Search Results for Higher Confidence and Sequence Coverage.

Science.gov (United States)

Zhao, Panpan; Zhong, Jiayong; Liu, Wanting; Zhao, Jing; Zhang, Gong

2017-12-01

Multiple search engines based on various models have been developed to search MS/MS spectra against a reference database, providing different results for the same data set. How to integrate these results efficiently with minimal compromise on false discoveries is an open question due to the lack of an independent, reliable, and highly sensitive standard. We took the advantage of the translating mRNA sequencing (RNC-seq) result as a standard to evaluate the integration strategies of the protein identifications from various search engines. We used seven mainstream search engines (Andromeda, Mascot, OMSSA, X!Tandem, pFind, InsPecT, and ProVerB) to search the same label-free MS data sets of human cell lines Hep3B, MHCCLM3, and MHCC97H from the Chinese C-HPP Consortium for Chromosomes 1, 8, and 20. As expected, the union of seven engines resulted in a boosted false identification, whereas the intersection of seven engines remarkably decreased the identification power. We found that identifications of at least two out of seven engines resulted in maximizing the protein identification power while minimizing the ratio of suspicious/translation-supported identifications (STR), as monitored by our STR index, based on RNC-Seq. Furthermore, this strategy also significantly improves the peptides coverage of the protein amino acid sequence. In summary, we demonstrated a simple strategy to significantly improve the performance for shotgun mass spectrometry by protein-level integrating multiple search engines, maximizing the utilization of the current MS spectra without additional experimental work.
IdentiCS – Identification of coding sequence and in silico reconstruction of the metabolic network directly from unannotated low-coverage bacterial genome sequence

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Zeng An-Ping

2004-08-01

Full Text Available Abstract Background A necessary step for a genome level analysis of the cellular metabolism is the in silico reconstruction of the metabolic network from genome sequences. The available methods are mainly based on the annotation of genome sequences including two successive steps, the prediction of coding sequences (CDS and their function assignment. The annotation process takes time. The available methods often encounter difficulties when dealing with unfinished error-containing genomic sequence. Results In this work a fast method is proposed to use unannotated genome sequence for predicting CDSs and for an in silico reconstruction of metabolic networks. Instead of using predicted genes or CDSs to query public databases, entries from public DNA or protein databases are used as queries to search a local database of the unannotated genome sequence to predict CDSs. Functions are assigned to the predicted CDSs simultaneously. The well-annotated genome of Salmonella typhimurium LT2 is used as an example to demonstrate the applicability of the method. 97.7% of the CDSs in the original annotation are correctly identified. The use of SWISS-PROT-TrEMBL databases resulted in an identification of 98.9% of CDSs that have EC-numbers in the published annotation. Furthermore, two versions of sequences of the bacterium Klebsiella pneumoniae with different genome coverage (3.9 and 7.9 fold, respectively are examined. The results suggest that a 3.9-fold coverage of the bacterial genome could be sufficiently used for the in silico reconstruction of the metabolic network. Compared to other gene finding methods such as CRITICA our method is more suitable for exploiting sequences of low genome coverage. Based on the new method, a program called IdentiCS (Identification of Coding Sequences from Unfinished Genome Sequences is delivered that combines the identification of CDSs with the reconstruction, comparison and visualization of metabolic networks (free to download
Architectures and Functional Coverage of Protein-Protein Interfaces

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Tuncbag, Nurcan; Gursoy, Attila; Guney, Emre; Nussinov, Ruth; Keskin, Ozlem

2008-01-01

The diverse range of cellular functions is performed by a limited number of protein folds existing in nature. One may similarly expect that cellular functional diversity would be covered by a limited number of protein-protein interface architectures. Here, we present 8205 interface clusters, each representing unique interface architecture. This dataset of protein-protein interfaces is analyzed and compared with older datasets. We observe that the number of both biological and crystal interfaces increase significantly compared to the number of PDB entries. Further, we find that the number of distinct interface architectures grows at a much faster rate than the number of folds and is yet to level off. We further analyze the growth trend of the functional coverage by constructing functional interaction networks from interfaces. The functional coverage is also found to steadily increase. Interestingly, we also observe that despite the diversity of interface architectures, some are more favorable and frequently used, and of particular interest, those are the ones which are also preferred in single chains. PMID:18620705
Shotgun protein sequencing.

Energy Technology Data Exchange (ETDEWEB)

Faulon, Jean-Loup Michel; Heffelfinger, Grant S.

2009-06-01

A novel experimental and computational technique based on multiple enzymatic digestion of a protein or protein mixture that reconstructs protein sequences from sequences of overlapping peptides is described in this SAND report. This approach, analogous to shotgun sequencing of DNA, is to be used to sequence alternative spliced proteins, to identify post-translational modifications, and to sequence genetically engineered proteins.
Front-End Electron Transfer Dissociation Coupled to a 21 Tesla FT-ICR Mass Spectrometer for Intact Protein Sequence Analysis

Science.gov (United States)

Weisbrod, Chad R.; Kaiser, Nathan K.; Syka, John E. P.; Early, Lee; Mullen, Christopher; Dunyach, Jean-Jacques; English, A. Michelle; Anderson, Lissa C.; Blakney, Greg T.; Shabanowitz, Jeffrey; Hendrickson, Christopher L.; Marshall, Alan G.; Hunt, Donald F.

2017-09-01

High resolution mass spectrometry is a key technology for in-depth protein characterization. High-field Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) enables high-level interrogation of intact proteins in the most detail to date. However, an appropriate complement of fragmentation technologies must be paired with FTMS to provide comprehensive sequence coverage, as well as characterization of sequence variants, and post-translational modifications. Here we describe the integration of front-end electron transfer dissociation (FETD) with a custom-built 21 tesla FT-ICR mass spectrometer, which yields unprecedented sequence coverage for proteins ranging from 2.8 to 29 kDa, without the need for extensive spectral averaging (e.g., 60% sequence coverage for apo-myoglobin with four averaged acquisitions). The system is equipped with a multipole storage device separate from the ETD reaction device, which allows accumulation of multiple ETD fragment ion fills. Consequently, an optimally large product ion population is accumulated prior to transfer to the ICR cell for mass analysis, which improves mass spectral signal-to-noise ratio, dynamic range, and scan rate. We find a linear relationship between protein molecular weight and minimum number of ETD reaction fills to achieve optimum sequence coverage, thereby enabling more efficient use of instrument data acquisition time. Finally, real-time scaling of the number of ETD reactions fills during method-based acquisition is shown, and the implications for LC-MS/MS top-down analysis are discussed. [Figure not available: see fulltext.
Scoring protein relationships in functional interaction networks predicted from sequence data.

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Gaston K Mazandu

Full Text Available UNLABELLED: The abundance of diverse biological data from various sources constitutes a rich source of knowledge, which has the power to advance our understanding of organisms. This requires computational methods in order to integrate and exploit these data effectively and elucidate local and genome wide functional connections between protein pairs, thus enabling functional inferences for uncharacterized proteins. These biological data are primarily in the form of sequences, which determine functions, although functional properties of a protein can often be predicted from just the domains it contains. Thus, protein sequences and domains can be used to predict protein pair-wise functional relationships, and thus contribute to the function prediction process of uncharacterized proteins in order to ensure that knowledge is gained from sequencing efforts. In this work, we introduce information-theoretic based approaches to score protein-protein functional interaction pairs predicted from protein sequence similarity and conserved protein signature matches. The proposed schemes are effective for data-driven scoring of connections between protein pairs. We applied these schemes to the Mycobacterium tuberculosis proteome to produce a homology-based functional network of the organism with a high confidence and coverage. We use the network for predicting functions of uncharacterised proteins. AVAILABILITY: Protein pair-wise functional relationship scores for Mycobacterium tuberculosis strain CDC1551 sequence data and python scripts to compute these scores are available at http://web.cbio.uct.ac.za/~gmazandu/scoringschemes.
PANTHER version 6: protein sequence and function evolution data with expanded representation of biological pathways

OpenAIRE

Mi, Huaiyu; Guo, Nan; Kejariwal, Anish; Thomas, Paul D.

2006-01-01

PANTHER is a freely available, comprehensive software system for relating protein sequence evolution to the evolution of specific protein functions and biological roles. Since 2005, there have been three main improvements to PANTHER. First, the sequences used to create evolutionary trees are carefully selected to provide coverage of phylogenetic as well as functional information. Second, PANTHER is now a member of the InterPro Consortium, and the PANTHER hidden markov Models (HMMs) are distri...
Pigs in sequence space: A 0.66X coverage pig genome survey based on shotgun sequencing

DEFF Research Database (Denmark)

Wernersson, Rasmus; Schierup, M.H.; Jorgensen, F.G.

2005-01-01

sequences (0.66X coverage) from the pig genome. The data are hereby released (NCBI Trace repository with center name "SDJVP", and project name "Sino-Danish Pig Genome Project") together with an initial evolutionary analysis. The non-repetitive fraction of the sequences was aligned to the UCSC human...
Microwave-assisted acid and base hydrolysis of intact proteins containing disulfide bonds for protein sequence analysis by mass spectrometry.

Science.gov (United States)

Reiz, Bela; Li, Liang

2010-09-01

Controlled hydrolysis of proteins to generate peptide ladders combined with mass spectrometric analysis of the resultant peptides can be used for protein sequencing. In this paper, two methods of improving the microwave-assisted protein hydrolysis process are described to enable rapid sequencing of proteins containing disulfide bonds and increase sequence coverage, respectively. It was demonstrated that proteins containing disulfide bonds could be sequenced by MS analysis by first performing hydrolysis for less than 2 min, followed by 1 h of reduction to release the peptides originally linked by disulfide bonds. It was shown that a strong base could be used as a catalyst for microwave-assisted protein hydrolysis, producing complementary sequence information to that generated by microwave-assisted acid hydrolysis. However, using either acid or base hydrolysis, amide bond breakages in small regions of the polypeptide chains of the model proteins (e.g., cytochrome c and lysozyme) were not detected. Dynamic light scattering measurement of the proteins solubilized in an acid or base indicated that protein-protein interaction or aggregation was not the cause of the failure to hydrolyze certain amide bonds. It was speculated that there were some unknown local structures that might play a role in preventing an acid or base from reacting with the peptide bonds therein. 2010 American Society for Mass Spectrometry. Published by Elsevier Inc. All rights reserved.
A Poisson hierarchical modelling approach to detecting copy number variation in sequence coverage data

OpenAIRE

Sep?lveda, Nuno; Campino, Susana G; Assefa, Samuel A; Sutherland, Colin J; Pain5, Arnab; Clark, Taane G

2013-01-01

BACKGROUND: The advent of next generation sequencing technology has accelerated efforts to map and catalogue copy number variation (CNV) in genomes of important micro-organisms for public health. A typical analysis of the sequence data involves mapping reads onto a reference genome, calculating the respective coverage, and detecting regions with too-low or too-high coverage (deletions and amplifications, respectively). Current CNV detection methods rely on statistical assumptions (e.g., a Poi...
A Poisson hierarchical modelling approach to detecting copy number variation in sequence coverage data

KAUST Repository

Sepúlveda, Nuno

2013-02-26

Background: The advent of next generation sequencing technology has accelerated efforts to map and catalogue copy number variation (CNV) in genomes of important micro-organisms for public health. A typical analysis of the sequence data involves mapping reads onto a reference genome, calculating the respective coverage, and detecting regions with too-low or too-high coverage (deletions and amplifications, respectively). Current CNV detection methods rely on statistical assumptions (e.g., a Poisson model) that may not hold in general, or require fine-tuning the underlying algorithms to detect known hits. We propose a new CNV detection methodology based on two Poisson hierarchical models, the Poisson-Gamma and Poisson-Lognormal, with the advantage of being sufficiently flexible to describe different data patterns, whilst robust against deviations from the often assumed Poisson model.Results: Using sequence coverage data of 7 Plasmodium falciparum malaria genomes (3D7 reference strain, HB3, DD2, 7G8, GB4, OX005, and OX006), we showed that empirical coverage distributions are intrinsically asymmetric and overdispersed in relation to the Poisson model. We also demonstrated a low baseline false positive rate for the proposed methodology using 3D7 resequencing data and simulation. When applied to the non-reference isolate data, our approach detected known CNV hits, including an amplification of the PfMDR1 locus in DD2 and a large deletion in the CLAG3.2 gene in GB4, and putative novel CNV regions. When compared to the recently available FREEC and cn.MOPS approaches, our findings were more concordant with putative hits from the highest quality array data for the 7G8 and GB4 isolates.Conclusions: In summary, the proposed methodology brings an increase in flexibility, robustness, accuracy and statistical rigour to CNV detection using sequence coverage data. 2013 Seplveda et al.; licensee BioMed Central Ltd.
A Poisson hierarchical modelling approach to detecting copy number variation in sequence coverage data.

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Sepúlveda, Nuno; Campino, Susana G; Assefa, Samuel A; Sutherland, Colin J; Pain, Arnab; Clark, Taane G

2013-02-26

The advent of next generation sequencing technology has accelerated efforts to map and catalogue copy number variation (CNV) in genomes of important micro-organisms for public health. A typical analysis of the sequence data involves mapping reads onto a reference genome, calculating the respective coverage, and detecting regions with too-low or too-high coverage (deletions and amplifications, respectively). Current CNV detection methods rely on statistical assumptions (e.g., a Poisson model) that may not hold in general, or require fine-tuning the underlying algorithms to detect known hits. We propose a new CNV detection methodology based on two Poisson hierarchical models, the Poisson-Gamma and Poisson-Lognormal, with the advantage of being sufficiently flexible to describe different data patterns, whilst robust against deviations from the often assumed Poisson model. Using sequence coverage data of 7 Plasmodium falciparum malaria genomes (3D7 reference strain, HB3, DD2, 7G8, GB4, OX005, and OX006), we showed that empirical coverage distributions are intrinsically asymmetric and overdispersed in relation to the Poisson model. We also demonstrated a low baseline false positive rate for the proposed methodology using 3D7 resequencing data and simulation. When applied to the non-reference isolate data, our approach detected known CNV hits, including an amplification of the PfMDR1 locus in DD2 and a large deletion in the CLAG3.2 gene in GB4, and putative novel CNV regions. When compared to the recently available FREEC and cn.MOPS approaches, our findings were more concordant with putative hits from the highest quality array data for the 7G8 and GB4 isolates. In summary, the proposed methodology brings an increase in flexibility, robustness, accuracy and statistical rigour to CNV detection using sequence coverage data.
A Poisson hierarchical modelling approach to detecting copy number variation in sequence coverage data

KAUST Repository

Sepú lveda, Nuno; Campino, Susana G; Assefa, Samuel A; Sutherland, Colin J; Pain, Arnab; Clark, Taane G

2013-01-01

Background: The advent of next generation sequencing technology has accelerated efforts to map and catalogue copy number variation (CNV) in genomes of important micro-organisms for public health. A typical analysis of the sequence data involves mapping reads onto a reference genome, calculating the respective coverage, and detecting regions with too-low or too-high coverage (deletions and amplifications, respectively). Current CNV detection methods rely on statistical assumptions (e.g., a Poisson model) that may not hold in general, or require fine-tuning the underlying algorithms to detect known hits. We propose a new CNV detection methodology based on two Poisson hierarchical models, the Poisson-Gamma and Poisson-Lognormal, with the advantage of being sufficiently flexible to describe different data patterns, whilst robust against deviations from the often assumed Poisson model.Results: Using sequence coverage data of 7 Plasmodium falciparum malaria genomes (3D7 reference strain, HB3, DD2, 7G8, GB4, OX005, and OX006), we showed that empirical coverage distributions are intrinsically asymmetric and overdispersed in relation to the Poisson model. We also demonstrated a low baseline false positive rate for the proposed methodology using 3D7 resequencing data and simulation. When applied to the non-reference isolate data, our approach detected known CNV hits, including an amplification of the PfMDR1 locus in DD2 and a large deletion in the CLAG3.2 gene in GB4, and putative novel CNV regions. When compared to the recently available FREEC and cn.MOPS approaches, our findings were more concordant with putative hits from the highest quality array data for the 7G8 and GB4 isolates.Conclusions: In summary, the proposed methodology brings an increase in flexibility, robustness, accuracy and statistical rigour to CNV detection using sequence coverage data. 2013 Seplveda et al.; licensee BioMed Central Ltd.
Combining modularity, conservation, and interactions of proteins significantly increases precision and coverage of protein function prediction

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Sers Christine T

2010-12-01

Full Text Available Abstract Background While the number of newly sequenced genomes and genes is constantly increasing, elucidation of their function still is a laborious and time-consuming task. This has led to the development of a wide range of methods for predicting protein functions in silico. We report on a new method that predicts function based on a combination of information about protein interactions, orthology, and the conservation of protein networks in different species. Results We show that aggregation of these independent sources of evidence leads to a drastic increase in number and quality of predictions when compared to baselines and other methods reported in the literature. For instance, our method generates more than 12,000 novel protein functions for human with an estimated precision of ~76%, among which are 7,500 new functional annotations for 1,973 human proteins that previously had zero or only one function annotated. We also verified our predictions on a set of genes that play an important role in colorectal cancer (MLH1, PMS2, EPHB4 and could confirm more than 73% of them based on evidence in the literature. Conclusions The combination of different methods into a single, comprehensive prediction method infers thousands of protein functions for every species included in the analysis at varying, yet always high levels of precision and very good coverage.
Single-base resolution and long-coverage sequencing based on single-molecule nanomanipulation

International Nuclear Information System (INIS)

An Hongjie; Huang Jiehuan; Lue Ming; Li Xueling; Lue Junhong; Li Haikuo; Zhang Yi; Li Minqian; Hu Jun

2007-01-01

We show new approaches towards a novel single-molecule sequencing strategy which consists of high-resolution positioning isolation of overlapping DNA fragments with atomic force microscopy (AFM), subsequent single-molecule PCR amplification and conventional Sanger sequencing. In this study, a DNA labelling technique was used to guarantee the accuracy in positioning the target DNA. Single-molecule multiplex PCR was carried out to test the contamination. The results showed that the two overlapping DNA fragments isolated by AFM could be successfully sequenced with high quality and perfect contiguity, indicating that single-base resolution and long-coverage sequencing have been achieved simultaneously
Protein sequence comparison and protein evolution

Energy Technology Data Exchange (ETDEWEB)

Pearson, W.R. [Univ. of Virginia, Charlottesville, VA (United States). Dept. of Biochemistry

1995-12-31

This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. This tutorial examines how the information conserved during the evolution of a protein molecule can be used to infer reliably homology, and thus a shared proteinfold and possibly a shared active site or function. The authors start by reviewing a geological/evolutionary time scale. Next they look at the evolution of several protein families. During the tutorial, these families will be used to demonstrate that homologous protein ancestry can be inferred with confidence. They also examine different modes of protein evolution and consider some hypotheses that have been presented to explain the very earliest events in protein evolution. The next part of the tutorial will examine the technical aspects of protein sequence comparison. Both optimal and heuristic algorithms and their associated parameters that are used to characterize protein sequence similarities are discussed. Perhaps more importantly, they survey the statistics of local similarity scores, and how these statistics can both be used to improve the selectivity of a search and to evaluate the significance of a match. They them examine distantly related members of three protein families, the serine proteases, the glutathione transferases, and the G-protein-coupled receptors (GCRs). Finally, the discuss how sequence similarity can be used to examine internal repeated or mosaic structures in proteins.

Pigs in sequence space: A 0.66X coverage pig genome survey based on shotgun sequencing

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Li Wei

2005-05-01

Full Text Available Abstract Background Comparative whole genome analysis of Mammalia can benefit from the addition of more species. The pig is an obvious choice due to its economic and medical importance as well as its evolutionary position in the artiodactyls. Results We have generated ~3.84 million shotgun sequences (0.66X coverage from the pig genome. The data are hereby released (NCBI Trace repository with center name "SDJVP", and project name "Sino-Danish Pig Genome Project" together with an initial evolutionary analysis. The non-repetitive fraction of the sequences was aligned to the UCSC human-mouse alignment and the resulting three-species alignments were annotated using the human genome annotation. Ultra-conserved elements and miRNAs were identified. The results show that for each of these types of orthologous data, pig is much closer to human than mouse is. Purifying selection has been more efficient in pig compared to human, but not as efficient as in mouse, and pig seems to have an isochore structure most similar to the structure in human. Conclusion The addition of the pig to the set of species sequenced at low coverage adds to the understanding of selective pressures that have acted on the human genome by bisecting the evolutionary branch between human and mouse with the mouse branch being approximately 3 times as long as the human branch. Additionally, the joint alignment of the shot-gun sequences to the human-mouse alignment offers the investigator a rapid way to defining specific regions for analysis and resequencing.
HIV protein sequence hotspots for crosstalk with host hub proteins.

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Mahdi Sarmady

Full Text Available HIV proteins target host hub proteins for transient binding interactions. The presence of viral proteins in the infected cell results in out-competition of host proteins in their interaction with hub proteins, drastically affecting cell physiology. Functional genomics and interactome datasets can be used to quantify the sequence hotspots on the HIV proteome mediating interactions with host hub proteins. In this study, we used the HIV and human interactome databases to identify HIV targeted host hub proteins and their host binding partners (H2. We developed a high throughput computational procedure utilizing motif discovery algorithms on sets of protein sequences, including sequences of HIV and H2 proteins. We identified as HIV sequence hotspots those linear motifs that are highly conserved on HIV sequences and at the same time have a statistically enriched presence on the sequences of H2 proteins. The HIV protein motifs discovered in this study are expressed by subsets of H2 host proteins potentially outcompeted by HIV proteins. A large subset of these motifs is involved in cleavage, nuclear localization, phosphorylation, and transcription factor binding events. Many such motifs are clustered on an HIV sequence in the form of hotspots. The sequential positions of these hotspots are consistent with the curated literature on phenotype altering residue mutations, as well as with existing binding site data. The hotspot map produced in this study is the first global portrayal of HIV motifs involved in altering the host protein network at highly connected hub nodes.
Genome-wide profiling of DNA-binding proteins using barcode-based multiplex Solexa sequencing.

Science.gov (United States)

Raghav, Sunil Kumar; Deplancke, Bart

2012-01-01

Chromatin immunoprecipitation (ChIP) is a commonly used technique to detect the in vivo binding of proteins to DNA. ChIP is now routinely paired to microarray analysis (ChIP-chip) or next-generation sequencing (ChIP-Seq) to profile the DNA occupancy of proteins of interest on a genome-wide level. Because ChIP-chip introduces several biases, most notably due to the use of a fixed number of probes, ChIP-Seq has quickly become the method of choice as, depending on the sequencing depth, it is more sensitive, quantitative, and provides a greater binding site location resolution. With the ever increasing number of reads that can be generated per sequencing run, it has now become possible to analyze several samples simultaneously while maintaining sufficient sequence coverage, thus significantly reducing the cost per ChIP-Seq experiment. In this chapter, we provide a step-by-step guide on how to perform multiplexed ChIP-Seq analyses. As a proof-of-concept, we focus on the genome-wide profiling of RNA Polymerase II as measuring its DNA occupancy at different stages of any biological process can provide insights into the gene regulatory mechanisms involved. However, the protocol can also be used to perform multiplexed ChIP-Seq analyses of other DNA-binding proteins such as chromatin modifiers and transcription factors.
Novel algorithms for protein sequence analysis

NARCIS (Netherlands)

Ye, Kai

2008-01-01

Each protein is characterized by its unique sequential order of amino acids, the so-called protein sequence. Biology”s paradigm is that this order of amino acids determines the protein”s architecture and function. In this thesis, we introduce novel algorithms to analyze protein sequences. Chapter 1
Somatosensory neuron types identified by high-coverage single-cell RNA-sequencing and functional heterogeneity

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Li, Chang-Lin; Li, Kai-Cheng; Wu, Dan; Chen, Yan; Luo, Hao; Zhao, Jing-Rong; Wang, Sa-Shuang; Sun, Ming-Ming; Lu, Ying-Jin; Zhong, Yan-Qing; Hu, Xu-Ye; Hou, Rui; Zhou, Bei-Bei; Bao, Lan; Xiao, Hua-Sheng; Zhang, Xu

2016-01-01

Sensory neurons are distinguished by distinct signaling networks and receptive characteristics. Thus, sensory neuron types can be defined by linking transcriptome-based neuron typing with the sensory phenotypes. Here we classify somatosensory neurons of the mouse dorsal root ganglion (DRG) by high-coverage single-cell RNA-sequencing (10 950 ± 1 218 genes per neuron) and neuron size-based hierarchical clustering. Moreover, single DRG neurons responding to cutaneous stimuli are recorded using an in vivo whole-cell patch clamp technique and classified by neuron-type genetic markers. Small diameter DRG neurons are classified into one type of low-threshold mechanoreceptor and five types of mechanoheat nociceptors (MHNs). Each of the MHN types is further categorized into two subtypes. Large DRG neurons are categorized into four types, including neurexophilin 1-expressing MHNs and mechanical nociceptors (MNs) expressing BAI1-associated protein 2-like 1 (Baiap2l1). Mechanoreceptors expressing trafficking protein particle complex 3-like and Baiap2l1-marked MNs are subdivided into two subtypes each. These results provide a new system for cataloging somatosensory neurons and their transcriptome databases. PMID:26691752
Fully immunized child: coverage, timing and sequencing of routine immunization in an urban poor settlement in Nairobi, Kenya.

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Mutua, Martin Kavao; Kimani-Murage, Elizabeth; Ngomi, Nicholas; Ravn, Henrik; Mwaniki, Peter; Echoka, Elizabeth

2016-01-01

More efforts have been put in place to increase full immunization coverage rates in the last decade. Little is known about the levels and consequences of delaying or vaccinating children in different schedules. Vaccine effectiveness depends on the timing of its administration, and it is not optimal if given early, delayed or not given as recommended. Evidence of non-specific effects of vaccines is well documented and could be linked to timing and sequencing of immunization. This paper documents the levels of coverage, timing and sequencing of routine childhood vaccines. The study was conducted between 2007 and 2014 in two informal urban settlements in Nairobi. A total of 3856 children, aged 12-23 months and having a vaccination card seen were included in analysis. Vaccination dates recorded from the cards seen were used to define full immunization coverage, timeliness and sequencing. Proportions, medians and Kaplan-Meier curves were used to assess and describe the levels of full immunization coverage, vaccination delays and sequencing. The findings indicate that 67 % of the children were fully immunized by 12 months of age. Missing measles and third doses of polio and pentavalent vaccine were the main reason for not being fully immunized. Delays were highest for third doses of polio and pentavalent and measles. About 22 % of fully immunized children had vaccines in an out-of-sequence manner with 18 % not receiving pentavalent together with polio vaccine as recommended. Results show higher levels of missed opportunities and low coverage of routine childhood vaccinations given at later ages. New strategies are needed to enable health care providers and parents/guardians to work together to increase the levels of completion of all required vaccinations. In particular, more focus is needed on vaccines given in multiple doses (polio, pentavalent and pneumococcal conjugate vaccines).
AD-LIBS: inferring ancestry across hybrid genomes using low-coverage sequence data.

Science.gov (United States)

Schaefer, Nathan K; Shapiro, Beth; Green, Richard E

2017-04-04

Inferring the ancestry of each region of admixed individuals' genomes is useful in studies ranging from disease gene mapping to speciation genetics. Current methods require high-coverage genotype data and phased reference panels, and are therefore inappropriate for many data sets. We present a software application, AD-LIBS, that uses a hidden Markov model to infer ancestry across hybrid genomes without requiring variant calling or phasing. This approach is useful for non-model organisms and in cases of low-coverage data, such as ancient DNA. We demonstrate the utility of AD-LIBS with synthetic data. We then use AD-LIBS to infer ancestry in two published data sets: European human genomes with Neanderthal ancestry and brown bear genomes with polar bear ancestry. AD-LIBS correctly infers 87-91% of ancestry in simulations and produces ancestry maps that agree with published results and global ancestry estimates in humans. In brown bears, we find more polar bear ancestry than has been published previously, using both AD-LIBS and an existing software application for local ancestry inference, HAPMIX. We validate AD-LIBS polar bear ancestry maps by recovering a geographic signal within bears that mirrors what is seen in SNP data. Finally, we demonstrate that AD-LIBS is more effective than HAPMIX at inferring ancestry when preexisting phased reference data are unavailable and genomes are sequenced to low coverage. AD-LIBS is an effective tool for ancestry inference that can be used even when few individuals are available for comparison or when genomes are sequenced to low coverage. AD-LIBS is therefore likely to be useful in studies of non-model or ancient organisms that lack large amounts of genomic DNA. AD-LIBS can therefore expand the range of studies in which admixture mapping is a viable tool.
Camps 2.0: exploring the sequence and structure space of prokaryotic, eukaryotic, and viral membrane proteins.

Science.gov (United States)

Neumann, Sindy; Hartmann, Holger; Martin-Galiano, Antonio J; Fuchs, Angelika; Frishman, Dmitrij

2012-03-01

Structural bioinformatics of membrane proteins is still in its infancy, and the picture of their fold space is only beginning to emerge. Because only a handful of three-dimensional structures are available, sequence comparison and structure prediction remain the main tools for investigating sequence-structure relationships in membrane protein families. Here we present a comprehensive analysis of the structural families corresponding to α-helical membrane proteins with at least three transmembrane helices. The new version of our CAMPS database (CAMPS 2.0) covers nearly 1300 eukaryotic, prokaryotic, and viral genomes. Using an advanced classification procedure, which is based on high-order hidden Markov models and considers both sequence similarity as well as the number of transmembrane helices and loop lengths, we identified 1353 structurally homogeneous clusters roughly corresponding to membrane protein folds. Only 53 clusters are associated with experimentally determined three-dimensional structures, and for these clusters CAMPS is in reasonable agreement with structure-based classification approaches such as SCOP and CATH. We therefore estimate that ∼1300 structures would need to be determined to provide a sufficient structural coverage of polytopic membrane proteins. CAMPS 2.0 is available at http://webclu.bio.wzw.tum.de/CAMPS2.0/. Copyright © 2011 Wiley Periodicals, Inc.
Expanded microbial genome coverage and improved protein family annotation in the COG database.

Science.gov (United States)

Galperin, Michael Y; Makarova, Kira S; Wolf, Yuri I; Koonin, Eugene V

2015-01-01

Microbial genome sequencing projects produce numerous sequences of deduced proteins, only a small fraction of which have been or will ever be studied experimentally. This leaves sequence analysis as the only feasible way to annotate these proteins and assign to them tentative functions. The Clusters of Orthologous Groups of proteins (COGs) database (http://www.ncbi.nlm.nih.gov/COG/), first created in 1997, has been a popular tool for functional annotation. Its success was largely based on (i) its reliance on complete microbial genomes, which allowed reliable assignment of orthologs and paralogs for most genes; (ii) orthology-based approach, which used the function(s) of the characterized member(s) of the protein family (COG) to assign function(s) to the entire set of carefully identified orthologs and describe the range of potential functions when there were more than one; and (iii) careful manual curation of the annotation of the COGs, aimed at detailed prediction of the biological function(s) for each COG while avoiding annotation errors and overprediction. Here we present an update of the COGs, the first since 2003, and a comprehensive revision of the COG annotations and expansion of the genome coverage to include representative complete genomes from all bacterial and archaeal lineages down to the genus level. This re-analysis of the COGs shows that the original COG assignments had an error rate below 0.5% and allows an assessment of the progress in functional genomics in the past 12 years. During this time, functions of many previously uncharacterized COGs have been elucidated and tentative functional assignments of many COGs have been validated, either by targeted experiments or through the use of high-throughput methods. A particularly important development is the assignment of functions to several widespread, conserved proteins many of which turned out to participate in translation, in particular rRNA maturation and tRNA modification. The new version of the
Functional Coverage of the Human Genome by Existing Structures, Structural Genomics Targets, and Homology Models.

Directory of Open Access Journals (Sweden)

2005-08-01

Full Text Available The bias in protein structure and function space resulting from experimental limitations and targeting of particular functional classes of proteins by structural biologists has long been recognized, but never continuously quantified. Using the Enzyme Commission and the Gene Ontology classifications as a reference frame, and integrating structure data from the Protein Data Bank (PDB, target sequences from the structural genomics projects, structure homology derived from the SUPERFAMILY database, and genome annotations from Ensembl and NCBI, we provide a quantified view, both at the domain and whole-protein levels, of the current and projected coverage of protein structure and function space relative to the human genome. Protein structures currently provide at least one domain that covers 37% of the functional classes identified in the genome; whole structure coverage exists for 25% of the genome. If all the structural genomics targets were solved (twice the current number of structures in the PDB, it is estimated that structures of one domain would cover 69% of the functional classes identified and complete structure coverage would be 44%. Homology models from existing experimental structures extend the 37% coverage to 56% of the genome as single domains and 25% to 31% for complete structures. Coverage from homology models is not evenly distributed by protein family, reflecting differing degrees of sequence and structure divergence within families. While these data provide coverage, conversely, they also systematically highlight functional classes of proteins for which structures should be determined. Current key functional families without structure representation are highlighted here; updated information on the "most wanted list" that should be solved is available on a weekly basis from http://function.rcsb.org:8080/pdb/function_distribution/index.html.
Sequencing Larger Intact Proteins (30-70 kDa) with Activated Ion Electron Transfer Dissociation

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Riley, Nicholas M.; Westphall, Michael S.; Coon, Joshua J.

2018-01-01

The analysis of intact proteins via mass spectrometry can offer several benefits to proteome characterization, although the majority of top-down experiments focus on proteoforms in a relatively low mass range (AI-ETD) to proteins in the 30-70 kDa range. AI-ETD leverages infrared photo-activation concurrent to ETD reactions to improve sequence-informative product ion generation. This method generates more product ions and greater sequence coverage than conventional ETD, higher-energy collisional dissociation (HCD), and ETD combined with supplemental HCD activation (EThcD). Importantly, AI-ETD provides the most thorough protein characterization for every precursor ion charge state investigated in this study, making it suitable as a universal fragmentation method in top-down experiments. Additionally, we highlight several acquisition strategies that can benefit characterization of larger proteins with AI-ETD, including combination of spectra from multiple ETD reaction times for a given precursor ion, multiple spectral acquisitions of the same precursor ion, and combination of spectra from two different dissociation methods (e.g., AI-ETD and HCD). In all, AI-ETD shows great promise as a method for dissociating larger intact protein ions as top-down proteomics continues to advance into larger mass ranges. [Figure not available: see fulltext.
Building a model: developing genomic resources for common milkweed (Asclepias syriaca) with low coverage genome sequencing.

Science.gov (United States)

Straub, Shannon C K; Fishbein, Mark; Livshultz, Tatyana; Foster, Zachary; Parks, Matthew; Weitemier, Kevin; Cronn, Richard C; Liston, Aaron

2011-05-04

Milkweeds (Asclepias L.) have been extensively investigated in diverse areas of evolutionary biology and ecology; however, there are few genetic resources available to facilitate and compliment these studies. This study explored how low coverage genome sequencing of the common milkweed (Asclepias syriaca L.) could be useful in characterizing the genome of a plant without prior genomic information and for development of genomic resources as a step toward further developing A. syriaca as a model in ecology and evolution. A 0.5× genome of A. syriaca was produced using Illumina sequencing. A virtually complete chloroplast genome of 158,598 bp was assembled, revealing few repeats and loss of three genes: accD, clpP, and ycf1. A nearly complete rDNA cistron (18S-5.8S-26S; 7,541 bp) and 5S rDNA (120 bp) sequence were obtained. Assessment of polymorphism revealed that the rDNA cistron and 5S rDNA had 0.3% and 26.7% polymorphic sites, respectively. A partial mitochondrial genome sequence (130,764 bp), with identical gene content to tobacco, was also assembled. An initial characterization of repeat content indicated that Ty1/copia-like retroelements are the most common repeat type in the milkweed genome. At least one A. syriaca microread hit 88% of Catharanthus roseus (Apocynaceae) unigenes (median coverage of 0.29×) and 66% of single copy orthologs (COSII) in asterids (median coverage of 0.14×). From this partial characterization of the A. syriaca genome, markers for population genetics (microsatellites) and phylogenetics (low-copy nuclear genes) studies were developed. The results highlight the promise of next generation sequencing for development of genomic resources for any organism. Low coverage genome sequencing allows characterization of the high copy fraction of the genome and exploration of the low copy fraction of the genome, which facilitate the development of molecular tools for further study of a target species and its relatives. This study represents a first
Advancing Eucalyptus genomics: identification and sequencing of lignin biosynthesis genes from deep-coverage BAC libraries

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Kudrna David

2011-03-01

Full Text Available Abstract Background Eucalyptus species are among the most planted hardwoods in the world because of their rapid growth, adaptability and valuable wood properties. The development and integration of genomic resources into breeding practice will be increasingly important in the decades to come. Bacterial artificial chromosome (BAC libraries are key genomic tools that enable positional cloning of important traits, synteny evaluation, and the development of genome framework physical maps for genetic linkage and genome sequencing. Results We describe the construction and characterization of two deep-coverage BAC libraries EG_Ba and EG_Bb obtained from nuclear DNA fragments of E. grandis (clone BRASUZ1 digested with HindIII and BstYI, respectively. Genome coverages of 17 and 15 haploid genome equivalents were estimated for EG_Ba and EG_Bb, respectively. Both libraries contained large inserts, with average sizes ranging from 135 Kb (Eg_Bb to 157 Kb (Eg_Ba, very low extra-nuclear genome contamination providing a probability of finding a single copy gene ≥ 99.99%. Libraries were screened for the presence of several genes of interest via hybridizations to high-density BAC filters followed by PCR validation. Five selected BAC clones were sequenced and assembled using the Roche GS FLX technology providing the whole sequence of the E. grandis chloroplast genome, and complete genomic sequences of important lignin biosynthesis genes. Conclusions The two E. grandis BAC libraries described in this study represent an important milestone for the advancement of Eucalyptus genomics and forest tree research. These BAC resources have a highly redundant genome coverage (> 15×, contain large average inserts and have a very low percentage of clones with organellar DNA or empty vectors. These publicly available BAC libraries are thus suitable for a broad range of applications in genetic and genomic research in Eucalyptus and possibly in related species of Myrtaceae
Use of designed sequences in protein structure recognition.

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Kumar, Gayatri; Mudgal, Richa; Srinivasan, Narayanaswamy; Sandhya, Sankaran

2018-05-09

Knowledge of the protein structure is a pre-requisite for improved understanding of molecular function. The gap in the sequence-structure space has increased in the post-genomic era. Grouping related protein sequences into families can aid in narrowing the gap. In the Pfam database, structure description is provided for part or full-length proteins of 7726 families. For the remaining 52% of the families, information on 3-D structure is not yet available. We use the computationally designed sequences that are intermediately related to two protein domain families, which are already known to share the same fold. These strategically designed sequences enable detection of distant relationships and here, we have employed them for the purpose of structure recognition of protein families of yet unknown structure. We first measured the success rate of our approach using a dataset of protein families of known fold and achieved a success rate of 88%. Next, for 1392 families of yet unknown structure, we made structural assignments for part/full length of the proteins. Fold association for 423 domains of unknown function (DUFs) are provided as a step towards functional annotation. The results indicate that knowledge-based filling of gaps in protein sequence space is a lucrative approach for structure recognition. Such sequences assist in traversal through protein sequence space and effectively function as 'linkers', where natural linkers between distant proteins are unavailable. This article was reviewed by Oliviero Carugo, Christine Orengo and Srikrishna Subramanian.
Building a model: developing genomic resources for common milkweed (Asclepias syriaca with low coverage genome sequencing

Directory of Open Access Journals (Sweden)

Weitemier Kevin

2011-05-01

Full Text Available Abstract Background Milkweeds (Asclepias L. have been extensively investigated in diverse areas of evolutionary biology and ecology; however, there are few genetic resources available to facilitate and compliment these studies. This study explored how low coverage genome sequencing of the common milkweed (Asclepias syriaca L. could be useful in characterizing the genome of a plant without prior genomic information and for development of genomic resources as a step toward further developing A. syriaca as a model in ecology and evolution. Results A 0.5× genome of A. syriaca was produced using Illumina sequencing. A virtually complete chloroplast genome of 158,598 bp was assembled, revealing few repeats and loss of three genes: accD, clpP, and ycf1. A nearly complete rDNA cistron (18S-5.8S-26S; 7,541 bp and 5S rDNA (120 bp sequence were obtained. Assessment of polymorphism revealed that the rDNA cistron and 5S rDNA had 0.3% and 26.7% polymorphic sites, respectively. A partial mitochondrial genome sequence (130,764 bp, with identical gene content to tobacco, was also assembled. An initial characterization of repeat content indicated that Ty1/copia-like retroelements are the most common repeat type in the milkweed genome. At least one A. syriaca microread hit 88% of Catharanthus roseus (Apocynaceae unigenes (median coverage of 0.29× and 66% of single copy orthologs (COSII in asterids (median coverage of 0.14×. From this partial characterization of the A. syriaca genome, markers for population genetics (microsatellites and phylogenetics (low-copy nuclear genes studies were developed. Conclusions The results highlight the promise of next generation sequencing for development of genomic resources for any organism. Low coverage genome sequencing allows characterization of the high copy fraction of the genome and exploration of the low copy fraction of the genome, which facilitate the development of molecular tools for further study of a target species
Improving accuracy of protein-protein interaction prediction by considering the converse problem for sequence representation

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Wang Yong

2011-10-01

Full Text Available Abstract Background With the development of genome-sequencing technologies, protein sequences are readily obtained by translating the measured mRNAs. Therefore predicting protein-protein interactions from the sequences is of great demand. The reason lies in the fact that identifying protein-protein interactions is becoming a bottleneck for eventually understanding the functions of proteins, especially for those organisms barely characterized. Although a few methods have been proposed, the converse problem, if the features used extract sufficient and unbiased information from protein sequences, is almost untouched. Results In this study, we interrogate this problem theoretically by an optimization scheme. Motivated by the theoretical investigation, we find novel encoding methods for both protein sequences and protein pairs. Our new methods exploit sufficiently the information of protein sequences and reduce artificial bias and computational cost. Thus, it significantly outperforms the available methods regarding sensitivity, specificity, precision, and recall with cross-validation evaluation and reaches ~80% and ~90% accuracy in Escherichia coli and Saccharomyces cerevisiae respectively. Our findings here hold important implication for other sequence-based prediction tasks because representation of biological sequence is always the first step in computational biology. Conclusions By considering the converse problem, we propose new representation methods for both protein sequences and protein pairs. The results show that our method significantly improves the accuracy of protein-protein interaction predictions.
An Enumerative Combinatorics Model for Fragmentation Patterns in RNA Sequencing Provides Insights into Nonuniformity of the Expected Fragment Starting-Point and Coverage Profile.

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Prakash, Celine; Haeseler, Arndt Von

2017-03-01

RNA sequencing (RNA-seq) has emerged as the method of choice for measuring the expression of RNAs in a given cell population. In most RNA-seq technologies, sequencing the full length of RNA molecules requires fragmentation into smaller pieces. Unfortunately, the issue of nonuniform sequencing coverage across a genomic feature has been a concern in RNA-seq and is attributed to biases for certain fragments in RNA-seq library preparation and sequencing. To investigate the expected coverage obtained from fragmentation, we develop a simple fragmentation model that is independent of bias from the experimental method and is not specific to the transcript sequence. Essentially, we enumerate all configurations for maximal placement of a given fragment length, F, on transcript length, T, to represent every possible fragmentation pattern, from which we compute the expected coverage profile across a transcript. We extend this model to incorporate general empirical attributes such as read length, fragment length distribution, and number of molecules of the transcript. We further introduce the fragment starting-point, fragment coverage, and read coverage profiles. We find that the expected profiles are not uniform and that factors such as fragment length to transcript length ratio, read length to fragment length ratio, fragment length distribution, and number of molecules influence the variability of coverage across a transcript. Finally, we explore a potential application of the model where, with simulations, we show that it is possible to correctly estimate the transcript copy number for any transcript in the RNA-seq experiment.
Genomic Selection Using Genotyping-By-Sequencing Data with Different Coverage Depth in Perennial Ryegrass

DEFF Research Database (Denmark)

Cericola, Fabio; Fé, Dario; Janss, Luc

2015-01-01

the diagonal elements by estimating the amount of genetic variance caused by the reduction of the coverage depth. Secondly we developed a method to scale the relationship matrix by taking into account the overall amount of pairwise non-missing loci between all families. Rust resistance and heading date were......Genotyping by sequencing (GBS) allows generating up to millions of molecular markers with a cost per sample which is proportional to the level of multiplexing. Increasing the sample multiplexing decreases the genotyping price but also reduces the numbers of reads per marker. In this work we...... investigated how this reduction of the coverage depth affects the genomic relationship matrices used to estimated breeding value of F2 family pools in perennial ryegrass. A total of 995 families were genotyped via GBS providing more than 1.8M allele frequency estimates for each family with an average coverage...
SVM-Prot 2016: A Web-Server for Machine Learning Prediction of Protein Functional Families from Sequence Irrespective of Similarity.

Science.gov (United States)

Li, Ying Hong; Xu, Jing Yu; Tao, Lin; Li, Xiao Feng; Li, Shuang; Zeng, Xian; Chen, Shang Ying; Zhang, Peng; Qin, Chu; Zhang, Cheng; Chen, Zhe; Zhu, Feng; Chen, Yu Zong

2016-01-01

Knowledge of protein function is important for biological, medical and therapeutic studies, but many proteins are still unknown in function. There is a need for more improved functional prediction methods. Our SVM-Prot web-server employed a machine learning method for predicting protein functional families from protein sequences irrespective of similarity, which complemented those similarity-based and other methods in predicting diverse classes of proteins including the distantly-related proteins and homologous proteins of different functions. Since its publication in 2003, we made major improvements to SVM-Prot with (1) expanded coverage from 54 to 192 functional families, (2) more diverse protein descriptors protein representation, (3) improved predictive performances due to the use of more enriched training datasets and more variety of protein descriptors, (4) newly integrated BLAST analysis option for assessing proteins in the SVM-Prot predicted functional families that were similar in sequence to a query protein, and (5) newly added batch submission option for supporting the classification of multiple proteins. Moreover, 2 more machine learning approaches, K nearest neighbor and probabilistic neural networks, were added for facilitating collective assessment of protein functions by multiple methods. SVM-Prot can be accessed at http://bidd2.nus.edu.sg/cgi-bin/svmprot/svmprot.cgi.
Strategies in protein sequencing and characterization: Multi-enzyme digestion coupled with alternate CID/ETD tandem mass spectrometry

Energy Technology Data Exchange (ETDEWEB)

Nardiello, Donatella; Palermo, Carmen, E-mail: carmen.palermo@unifg.it; Natale, Anna; Quinto, Maurizio; Centonze, Diego

2015-01-07

Highlights: • Multi-enzyme digestion for protein sequencing and characterization by CID/ETD. • Simultaneous use of trypsin/chymotrypsin for the maximization of sequence. • Identification of PTMs, sequence variants and species-specific residues. • Increase of accuracy in sequence assignments by orthogonal fragmentation techniques. - Abstract: A strategy based on a simultaneous multi-enzyme digestion coupled with electron transfer dissociation (ETD) and collision-induced dissociation (CID) was developed for protein sequencing and characterization, as a valid alternative platform in ion-trap based proteomics. The effect of different proteolytic procedures using chymotrypsin, trypsin, a combination of both, and Lys-C, was carefully evaluated in terms of number of identified peptides, protein coverage, and score distribution. A systematic comparison between CID and ETD is shown for the analysis of peptides originating from the in-solution digestion of standard caseins. The best results were achieved with a trypsin/chymotrypsin mix combined with CID and ETD operating in alternating mode. A post-database search validation of MS/MS dataset was performed, then, the matched peptides were cross checked by the evaluation of ion scores, rank, number of experimental product ions, and their relative abundances in the MS/MS spectrum. By integrated CID/ETD experiments, high quality-spectra have been obtained, thus allowing a confirmation of spectral information and an increase of accuracy in peptide sequence assignments. Overlapping peptides, produced throughout the proteins, reduce the ambiguity in mapping modifications between natural variants and animal species, and allow the characterization of post translational modifications. The advantages of using the enzymatic mix trypsin/chymotrypsin were confirmed by the nanoLC and CID/ETD tandem mass spectrometry of goat milk proteins, previously separated by two-dimensional gel electrophoresis.

Nonlinear deterministic structures and the randomness of protein sequences

CERN Document Server

Huang Yan Zhao

2003-01-01

To clarify the randomness of protein sequences, we make a detailed analysis of a set of typical protein sequences representing each structural classes by using nonlinear prediction method. No deterministic structures are found in these protein sequences and this implies that they behave as random sequences. We also give an explanation to the controversial results obtained in previous investigations.
Determination of genetic relatedness from low-coverage human genome sequences using pedigree simulations.

Science.gov (United States)

Martin, Michael D; Jay, Flora; Castellano, Sergi; Slatkin, Montgomery

2017-08-01

We develop and evaluate methods for inferring relatedness among individuals from low-coverage DNA sequences of their genomes, with particular emphasis on sequences obtained from fossil remains. We suggest the major factors complicating the determination of relatedness among ancient individuals are sequencing depth, the number of overlapping sites, the sequencing error rate and the presence of contamination from present-day genetic sources. We develop a theoretical model that facilitates the exploration of these factors and their relative effects, via measurement of pairwise genetic distances, without calling genotypes, and determine the power to infer relatedness under various scenarios of varying sequencing depth, present-day contamination and sequencing error. The model is validated by a simulation study as well as the analysis of aligned sequences from present-day human genomes. We then apply the method to the recently published genome sequences of ancient Europeans, developing a statistical treatment to determine confidence in assigned relatedness that is, in some cases, more precise than previously reported. As the majority of ancient specimens are from animals, this method would be applicable to investigate kinship in nonhuman remains. The developed software grups (Genetic Relatedness Using Pedigree Simulations) is implemented in Python and freely available. © 2017 John Wiley & Sons Ltd.
Nucleation phenomena in protein folding: the modulating role of protein sequence

International Nuclear Information System (INIS)

Travasso, Rui D M; FaIsca, Patricia F N; Gama, Margarida M Telo da

2007-01-01

For the vast majority of naturally occurring, small, single-domain proteins, folding is often described as a two-state process that lacks detectable intermediates. This observation has often been rationalized on the basis of a nucleation mechanism for protein folding whose basic premise is the idea that, after completion of a specific set of contacts forming the so-called folding nucleus, the native state is achieved promptly. Here we propose a methodology to identify folding nuclei in small lattice polymers and apply it to the study of protein molecules with a chain length of N = 48. To investigate the extent to which protein topology is a robust determinant of the nucleation mechanism, we compare the nucleation scenario of a native-centric model with that of a sequence-specific model sharing the same native fold. To evaluate the impact of the sequence's finer details in the nucleation mechanism, we consider the folding of two non-homologous sequences. We conclude that, in a sequence-specific model, the folding nucleus is, to some extent, formed by the most stable contacts in the protein and that the less stable linkages in the folding nucleus are solely determined by the fold's topology. We have also found that, independently of the protein sequence, the folding nucleus performs the same 'topological' function. This unifying feature of the nucleation mechanism results from the residues forming the folding nucleus being distributed along the protein chain in a similar and well-defined manner that is determined by the fold's topological features
WildSpan: mining structured motifs from protein sequences

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Chen Chien-Yu

2011-03-01

Full Text Available Abstract Background Automatic extraction of motifs from biological sequences is an important research problem in study of molecular biology. For proteins, it is desired to discover sequence motifs containing a large number of wildcard symbols, as the residues associated with functional sites are usually largely separated in sequences. Discovering such patterns is time-consuming because abundant combinations exist when long gaps (a gap consists of one or more successive wildcards are considered. Mining algorithms often employ constraints to narrow down the search space in order to increase efficiency. However, improper constraint models might degrade the sensitivity and specificity of the motifs discovered by computational methods. We previously proposed a new constraint model to handle large wildcard regions for discovering functional motifs of proteins. The patterns that satisfy the proposed constraint model are called W-patterns. A W-pattern is a structured motif that groups motif symbols into pattern blocks interleaved with large irregular gaps. Considering large gaps reflects the fact that functional residues are not always from a single region of protein sequences, and restricting motif symbols into clusters corresponds to the observation that short motifs are frequently present within protein families. To efficiently discover W-patterns for large-scale sequence annotation and function prediction, this paper first formally introduces the problem to solve and proposes an algorithm named WildSpan (sequential pattern mining across large wildcard regions that incorporates several pruning strategies to largely reduce the mining cost. Results WildSpan is shown to efficiently find W-patterns containing conserved residues that are far separated in sequences. We conducted experiments with two mining strategies, protein-based and family-based mining, to evaluate the usefulness of W-patterns and performance of WildSpan. The protein-based mining mode
HomPPI: a class of sequence homology based protein-protein interface prediction methods

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Dobbs Drena

2011-06-01

Full Text Available Abstract Background Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate. Results We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes, including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based inference of interface residues in a query protein sequence. Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface residues. We present two variants of HomPPI: (i NPS-HomPPI (Non partner-specific HomPPI, which can be used to predict interface residues of a query protein in the absence of knowledge of the interaction partner; and (ii PS-HomPPI (Partner-specific HomPPI, which can be used to predict the interface residues of a query protein with a specific target protein. Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein interface residues in a given protein, with an average correlation coefficient (CC of 0.76, sensitivity of 0.83, and specificity of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier, PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of
Protein 3D structure computed from evolutionary sequence variation.

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Debora S Marks

Full Text Available The evolutionary trajectory of a protein through sequence space is constrained by its function. Collections of sequence homologs record the outcomes of millions of evolutionary experiments in which the protein evolves according to these constraints. Deciphering the evolutionary record held in these sequences and exploiting it for predictive and engineering purposes presents a formidable challenge. The potential benefit of solving this challenge is amplified by the advent of inexpensive high-throughput genomic sequencing.In this paper we ask whether we can infer evolutionary constraints from a set of sequence homologs of a protein. The challenge is to distinguish true co-evolution couplings from the noisy set of observed correlations. We address this challenge using a maximum entropy model of the protein sequence, constrained by the statistics of the multiple sequence alignment, to infer residue pair couplings. Surprisingly, we find that the strength of these inferred couplings is an excellent predictor of residue-residue proximity in folded structures. Indeed, the top-scoring residue couplings are sufficiently accurate and well-distributed to define the 3D protein fold with remarkable accuracy.We quantify this observation by computing, from sequence alone, all-atom 3D structures of fifteen test proteins from different fold classes, ranging in size from 50 to 260 residues, including a G-protein coupled receptor. These blinded inferences are de novo, i.e., they do not use homology modeling or sequence-similar fragments from known structures. The co-evolution signals provide sufficient information to determine accurate 3D protein structure to 2.7-4.8 Å C(α-RMSD error relative to the observed structure, over at least two-thirds of the protein (method called EVfold, details at http://EVfold.org. This discovery provides insight into essential interactions constraining protein evolution and will facilitate a comprehensive survey of the universe of
Protein Function Prediction Based on Sequence and Structure Information

KAUST Repository

Smaili, Fatima Z.

2016-05-25

The number of available protein sequences in public databases is increasing exponentially. However, a significant fraction of these sequences lack functional annotation which is essential to our understanding of how biological systems and processes operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching these predicted models, using global and local similarities, through three independent enzyme commission (EC) and gene ontology (GO) function libraries. The method was tested on 250 “hard” proteins, which lack homologous templates in both structure and function libraries. The results show that this method outperforms the conventional prediction methods based on sequence similarity or threading. Additionally, our method could be improved even further by incorporating protein-protein interaction information. Overall, the method we use provides an efficient approach for automated functional annotation of non-homologous proteins, starting from their sequence.
GuiTope: an application for mapping random-sequence peptides to protein sequences.

Science.gov (United States)

Halperin, Rebecca F; Stafford, Phillip; Emery, Jack S; Navalkar, Krupa Arun; Johnston, Stephen Albert

2012-01-03

Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC) at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.
GuiTope: an application for mapping random-sequence peptides to protein sequences

Directory of Open Access Journals (Sweden)

Halperin Rebecca F

2012-01-01

Full Text Available Abstract Background Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. Results GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. Conclusions GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.
MIPS: a database for genomes and protein sequences.

Science.gov (United States)

Mewes, H W; Frishman, D; Güldener, U; Mannhaupt, G; Mayer, K; Mokrejs, M; Morgenstern, B; Münsterkötter, M; Rudd, S; Weil, B

2002-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) continues to provide genome-related information in a systematic way. MIPS supports both national and European sequencing and functional analysis projects, develops and maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences, and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the databases for the comprehensive set of genomes (PEDANT genomes), the database of annotated human EST clusters (HIB), the database of complete cDNAs from the DHGP (German Human Genome Project), as well as the project specific databases for the GABI (Genome Analysis in Plants) and HNB (Helmholtz-Netzwerk Bioinformatik) networks. The Arabidospsis thaliana database (MATDB), the database of mitochondrial proteins (MITOP) and our contribution to the PIR International Protein Sequence Database have been described elsewhere [Schoof et al. (2002) Nucleic Acids Res., 30, 91-93; Scharfe et al. (2000) Nucleic Acids Res., 28, 155-158; Barker et al. (2001) Nucleic Acids Res., 29, 29-32]. All databases described, the protein analysis tools provided and the detailed descriptions of our projects can be accessed through the MIPS World Wide Web server (http://mips.gsf.de).
Prediction of Protein Hotspots from Whole Protein Sequences by a Random Projection Ensemble System

Directory of Open Access Journals (Sweden)

Jinjian Jiang

2017-07-01

Full Text Available Hotspot residues are important in the determination of protein-protein interactions, and they always perform specific functions in biological processes. The determination of hotspot residues is by the commonly-used method of alanine scanning mutagenesis experiments, which is always costly and time consuming. To address this issue, computational methods have been developed. Most of them are structure based, i.e., using the information of solved protein structures. However, the number of solved protein structures is extremely less than that of sequences. Moreover, almost all of the predictors identified hotspots from the interfaces of protein complexes, seldom from the whole protein sequences. Therefore, determining hotspots from whole protein sequences by sequence information alone is urgent. To address the issue of hotspot predictions from the whole sequences of proteins, we proposed an ensemble system with random projections using statistical physicochemical properties of amino acids. First, an encoding scheme involving sequence profiles of residues and physicochemical properties from the AAindex1 dataset is developed. Then, the random projection technique was adopted to project the encoding instances into a reduced space. Then, several better random projections were obtained by training an IBk classifier based on the training dataset, which were thus applied to the test dataset. The ensemble of random projection classifiers is therefore obtained. Experimental results showed that although the performance of our method is not good enough for real applications of hotspots, it is very promising in the determination of hotspot residues from whole sequences.
Gene Unprediction with Spurio: A tool to identify spurious protein sequences.

Science.gov (United States)

Höps, Wolfram; Jeffryes, Matt; Bateman, Alex

2018-01-01

We now have access to the sequences of tens of millions of proteins. These protein sequences are essential for modern molecular biology and computational biology. The vast majority of protein sequences are derived from gene prediction tools and have no experimental supporting evidence for their translation. Despite the increasing accuracy of gene prediction tools there likely exists a large number of spurious protein predictions in the sequence databases. We have developed the Spurio tool to help identify spurious protein predictions in prokaryotes. Spurio searches the query protein sequence against a prokaryotic nucleotide database using tblastn and identifies homologous sequences. The tblastn matches are used to score the query sequence's likelihood of being a spurious protein prediction using a Gaussian process model. The most informative feature is the appearance of stop codons within the presumed translation of homologous DNA sequences. Benchmarking shows that the Spurio tool is able to distinguish spurious from true proteins. However, transposon proteins are prone to be predicted as spurious because of the frequency of degraded homologs found in the DNA sequence databases. Our initial experiments suggest that less than 1% of the proteins in the UniProtKB sequence database are likely to be spurious and that Spurio is able to identify over 60 times more spurious proteins than the AntiFam resource. The Spurio software and source code is available under an MIT license at the following URL: https://bitbucket.org/bateman-group/spurio.
Structure and Sequence Search on Aptamer-Protein Docking

Science.gov (United States)

Xiao, Jiajie; Bonin, Keith; Guthold, Martin; Salsbury, Freddie

2015-03-01

Interactions between proteins and deoxyribonucleic acid (DNA) play a significant role in the living systems, especially through gene regulation. However, short nucleic acids sequences (aptamers) with specific binding affinity to specific proteins exhibit clinical potential as therapeutics. Our capillary and gel electrophoresis selection experiments show that specific sequences of aptamers can be selected that bind specific proteins. Computationally, given the experimentally-determined structure and sequence of a thrombin-binding aptamer, we can successfully dock the aptamer onto thrombin in agreement with experimental structures of the complex. In order to further study the conformational flexibility of this thrombin-binding aptamer and to potentially develop a predictive computational model of aptamer-binding, we use GPU-enabled molecular dynamics simulations to both examine the conformational flexibility of the aptamer in the absence of binding to thrombin, and to determine our ability to fold an aptamer. This study should help further de-novo predictions of aptamer sequences by enabling the study of structural and sequence-dependent effects on aptamer-protein docking specificity.
AlignMe—a membrane protein sequence alignment web server

Science.gov (United States)

Stamm, Marcus; Staritzbichler, René; Khafizov, Kamil; Forrest, Lucy R.

2014-01-01

We present a web server for pair-wise alignment of membrane protein sequences, using the program AlignMe. The server makes available two operational modes of AlignMe: (i) sequence to sequence alignment, taking two sequences in fasta format as input, combining information about each sequence from multiple sources and producing a pair-wise alignment (PW mode); and (ii) alignment of two multiple sequence alignments to create family-averaged hydropathy profile alignments (HP mode). For the PW sequence alignment mode, four different optimized parameter sets are provided, each suited to pairs of sequences with a specific similarity level. These settings utilize different types of inputs: (position-specific) substitution matrices, secondary structure predictions and transmembrane propensities from transmembrane predictions or hydrophobicity scales. In the second (HP) mode, each input multiple sequence alignment is converted into a hydrophobicity profile averaged over the provided set of sequence homologs; the two profiles are then aligned. The HP mode enables qualitative comparison of transmembrane topologies (and therefore potentially of 3D folds) of two membrane proteins, which can be useful if the proteins have low sequence similarity. In summary, the AlignMe web server provides user-friendly access to a set of tools for analysis and comparison of membrane protein sequences. Access is available at http://www.bioinfo.mpg.de/AlignMe PMID:24753425
The relationship of protein conservation and sequence length

Directory of Open Access Journals (Sweden)

Panchenko Anna R

2002-11-01

Full Text Available Abstract Background In general, the length of a protein sequence is determined by its function and the wide variance in the lengths of an organism's proteins reflects the diversity of specific functional roles for these proteins. However, additional evolutionary forces that affect the length of a protein may be revealed by studying the length distributions of proteins evolving under weaker functional constraints. Results We performed sequence comparisons to distinguish highly conserved and poorly conserved proteins from the bacterium Escherichia coli, the archaeon Archaeoglobus fulgidus, and the eukaryotes Saccharomyces cerevisiae, Drosophila melanogaster, and Homo sapiens. For all organisms studied, the conserved and nonconserved proteins have strikingly different length distributions. The conserved proteins are, on average, longer than the poorly conserved ones, and the length distributions for the poorly conserved proteins have a relatively narrow peak, in contrast to the conserved proteins whose lengths spread over a wider range of values. For the two prokaryotes studied, the poorly conserved proteins approximate the minimal length distribution expected for a diverse range of structural folds. Conclusions There is a relationship between protein conservation and sequence length. For all the organisms studied, there seems to be a significant evolutionary trend favoring shorter proteins in the absence of other, more specific functional constraints.
MIPS: a database for protein sequences and complete genomes.

Science.gov (United States)

Mewes, H W; Hani, J; Pfeiffer, F; Frishman, D

1998-01-01

The MIPS group [Munich Information Center for Protein Sequences of the German National Center for Environment and Health (GSF)] at the Max-Planck-Institute for Biochemistry, Martinsried near Munich, Germany, is involved in a number of data collection activities, including a comprehensive database of the yeast genome, a database reflecting the progress in sequencing the Arabidopsis thaliana genome, the systematic analysis of other small genomes and the collection of protein sequence data within the framework of the PIR-International Protein Sequence Database (described elsewhere in this volume). Through its WWW server (http://www.mips.biochem.mpg.de ) MIPS provides access to a variety of generic databases, including a database of protein families as well as automatically generated data by the systematic application of sequence analysis algorithms. The yeast genome sequence and its related information was also compiled on CD-ROM to provide dynamic interactive access to the 16 chromosomes of the first eukaryotic genome unraveled. PMID:9399795
Low-coverage MiSeq next generation sequencing reveals the mitochondrial genome of the Eastern Rock Lobster, Sagmariasus verreauxi.

Science.gov (United States)

Doyle, Stephen R; Griffith, Ian S; Murphy, Nick P; Strugnell, Jan M

2015-01-01

The complete mitochondrial genome of the Eastern Rock lobster, Sagmariasus verreauxi, is reported for the first time. Using low-coverage, long read MiSeq next generation sequencing, we constructed and determined the mtDNA genome organization of the 15,470 bp sequence from two isolates from Eastern Tasmania, Australia and Northern New Zealand, and identified 46 polymorphic nucleotides between the two sequences. This genome sequence and its genetic polymorphisms will likely be useful in understanding the distribution and population connectivity of the Eastern Rock Lobster, and in the fisheries management of this commercially important species.
Can Natural Proteins Designed with ‘Inverted’ Peptide Sequences Adopt Native-Like Protein Folds?

Science.gov (United States)

Sridhar, Settu; Guruprasad, Kunchur

2014-01-01

We have carried out a systematic computational analysis on a representative dataset of proteins of known three-dimensional structure, in order to evaluate whether it would possible to ‘swap’ certain short peptide sequences in naturally occurring proteins with their corresponding ‘inverted’ peptides and generate ‘artificial’ proteins that are predicted to retain native-like protein fold. The analysis of 3,967 representative proteins from the Protein Data Bank revealed 102,677 unique identical inverted peptide sequence pairs that vary in sequence length between 5–12 and 18 amino acid residues. Our analysis illustrates with examples that such ‘artificial’ proteins may be generated by identifying peptides with ‘similar structural environment’ and by using comparative protein modeling and validation studies. Our analysis suggests that natural proteins may be tolerant to accommodating such peptides. PMID:25210740
A novel approach to sequence validating protein expression clones with automated decision making

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Mohr Stephanie E

2007-06-01

Full Text Available Abstract Background Whereas the molecular assembly of protein expression clones is readily automated and routinely accomplished in high throughput, sequence verification of these clones is still largely performed manually, an arduous and time consuming process. The ultimate goal of validation is to determine if a given plasmid clone matches its reference sequence sufficiently to be "acceptable" for use in protein expression experiments. Given the accelerating increase in availability of tens of thousands of unverified clones, there is a strong demand for rapid, efficient and accurate software that automates clone validation. Results We have developed an Automated Clone Evaluation (ACE system – the first comprehensive, multi-platform, web-based plasmid sequence verification software package. ACE automates the clone verification process by defining each clone sequence as a list of multidimensional discrepancy objects, each describing a difference between the clone and its expected sequence including the resulting polypeptide consequences. To evaluate clones automatically, this list can be compared against user acceptance criteria that specify the allowable number of discrepancies of each type. This strategy allows users to re-evaluate the same set of clones against different acceptance criteria as needed for use in other experiments. ACE manages the entire sequence validation process including contig management, identifying and annotating discrepancies, determining if discrepancies correspond to polymorphisms and clone finishing. Designed to manage thousands of clones simultaneously, ACE maintains a relational database to store information about clones at various completion stages, project processing parameters and acceptance criteria. In a direct comparison, the automated analysis by ACE took less time and was more accurate than a manual analysis of a 93 gene clone set. Conclusion ACE was designed to facilitate high throughput clone sequence
The SWISS-PROT protein sequence data bank: current status.

OpenAIRE

Bairoch, A; Boeckmann, B

1994-01-01

SWISS-PROT is an annotated protein sequence database established in 1986 and maintained collaboratively, since 1988, by the Department of Medical Biochemistry of the University of Geneva and the EMBL Data Library. The SWISS-PROT protein sequence data bank consist of sequence entries. Sequence entries are composed of different lines types, each with their own format. For standardization purposes the format of SWISS-PROT follows as closely as possible that of the EMBL Nucleotide Sequence Databa...

Performance Evaluation of NIPT in Detection of Chromosomal Copy Number Variants Using Low-Coverage Whole-Genome Sequencing of Plasma DNA

DEFF Research Database (Denmark)

Liu, Hongtai; Gao, Ya; Hu, Zhiyang

2016-01-01

, including 33 CNVs samples and 886 normal samples from September 1, 2011 to May 31, 2013, were enrolled in this study. The samples were randomly rearranged and blindly sequenced by low-coverage (about 7M reads) whole-genome sequencing of plasma DNA. Fetal CNVs were detected by Fetal Copy-number Analysis...
Partial sequence determination of metabolically labeled radioactive proteins and peptides

International Nuclear Information System (INIS)

Anderson, C.W.

1982-01-01

The author has used the sequence analysis of radioactive proteins and peptides to approach several problems during the past few years. They, in collaboration with others, have mapped precisely several adenovirus proteins with respect to the nucleotide sequence of the adenovirus genome; identified hitherto missed proteins encoded by bacteriophage MS2 and by simian virus 40; analyzed the aminoterminal maturation of several virus proteins; determined the cleavage sites for processing of the poliovirus polyprotein; and analyzed the mechanism of frameshifting by excess normal tRNAs during cell-free protein synthesis. This chapter is designed to aid those without prior experience at protein sequence determinations. It is based primarily on the experience gained in the studies cited above, which made use of the Beckman 890 series automated protein sequencers
Correlation between protein sequence similarity and x-ray diffraction quality in the protein data bank.

Science.gov (United States)

Lu, Hui-Meng; Yin, Da-Chuan; Ye, Ya-Jing; Luo, Hui-Min; Geng, Li-Qiang; Li, Hai-Sheng; Guo, Wei-Hong; Shang, Peng

2009-01-01

As the most widely utilized technique to determine the 3-dimensional structure of protein molecules, X-ray crystallography can provide structure of the highest resolution among the developed techniques. The resolution obtained via X-ray crystallography is known to be influenced by many factors, such as the crystal quality, diffraction techniques, and X-ray sources, etc. In this paper, the authors found that the protein sequence could also be one of the factors. We extracted information of the resolution and the sequence of proteins from the Protein Data Bank (PDB), classified the proteins into different clusters according to the sequence similarity, and statistically analyzed the relationship between the sequence similarity and the best resolution obtained. The results showed that there was a pronounced correlation between the sequence similarity and the obtained resolution. These results indicate that protein structure itself is one variable that may affect resolution when X-ray crystallography is used.
Taxonomic colouring of phylogenetic trees of protein sequences

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Andrade-Navarro Miguel A

2006-02-01

Full Text Available Abstract Background Phylogenetic analyses of protein families are used to define the evolutionary relationships between homologous proteins. The interpretation of protein-sequence phylogenetic trees requires the examination of the taxonomic properties of the species associated to those sequences. However, there is no online tool to facilitate this interpretation, for example, by automatically attaching taxonomic information to the nodes of a tree, or by interactively colouring the branches of a tree according to any combination of taxonomic divisions. This is especially problematic if the tree contains on the order of hundreds of sequences, which, given the accelerated increase in the size of the protein sequence databases, is a situation that is becoming common. Results We have developed PhyloView, a web based tool for colouring phylogenetic trees upon arbitrary taxonomic properties of the species represented in a protein sequence phylogenetic tree. Provided that the tree contains SwissProt, SpTrembl, or GenBank protein identifiers, the tool retrieves the taxonomic information from the corresponding database. A colour picker displays a summary of the findings and allows the user to associate colours to the leaves of the tree according to any number of taxonomic partitions. Then, the colours are propagated to the branches of the tree. Conclusion PhyloView can be used at http://www.ogic.ca/projects/phyloview/. A tutorial, the software with documentation, and GPL licensed source code, can be accessed at the same web address.
Semi-Supervised Learning for Classification of Protein Sequence Data

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Brian R. King

2008-01-01

Full Text Available Protein sequence data continue to become available at an exponential rate. Annotation of functional and structural attributes of these data lags far behind, with only a small fraction of the data understood and labeled by experimental methods. Classification methods that are based on semi-supervised learning can increase the overall accuracy of classifying partly labeled data in many domains, but very few methods exist that have shown their effect on protein sequence classification. We show how proven methods from text classification can be applied to protein sequence data, as we consider both existing and novel extensions to the basic methods, and demonstrate restrictions and differences that must be considered. We demonstrate comparative results against the transductive support vector machine, and show superior results on the most difficult classification problems. Our results show that large repositories of unlabeled protein sequence data can indeed be used to improve predictive performance, particularly in situations where there are fewer labeled protein sequences available, and/or the data are highly unbalanced in nature.
Sequence motifs in MADS transcription factors responsible for specificity and diversification of protein-protein interaction.

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Aalt D J van Dijk

Full Text Available Protein sequences encompass tertiary structures and contain information about specific molecular interactions, which in turn determine biological functions of proteins. Knowledge about how protein sequences define interaction specificity is largely missing, in particular for paralogous protein families with high sequence similarity, such as the plant MADS domain transcription factor family. In comparison to the situation in mammalian species, this important family of transcription regulators has expanded enormously in plant species and contains over 100 members in the model plant species Arabidopsis thaliana. Here, we provide insight into the mechanisms that determine protein-protein interaction specificity for the Arabidopsis MADS domain transcription factor family, using an integrated computational and experimental approach. Plant MADS proteins have highly similar amino acid sequences, but their dimerization patterns vary substantially. Our computational analysis uncovered small sequence regions that explain observed differences in dimerization patterns with reasonable accuracy. Furthermore, we show the usefulness of the method for prediction of MADS domain transcription factor interaction networks in other plant species. Introduction of mutations in the predicted interaction motifs demonstrated that single amino acid mutations can have a large effect and lead to loss or gain of specific interactions. In addition, various performed bioinformatics analyses shed light on the way evolution has shaped MADS domain transcription factor interaction specificity. Identified protein-protein interaction motifs appeared to be strongly conserved among orthologs, indicating their evolutionary importance. We also provide evidence that mutations in these motifs can be a source for sub- or neo-functionalization. The analyses presented here take us a step forward in understanding protein-protein interactions and the interplay between protein sequences and
How Many Protein Sequences Fold to a Given Structure? A Coevolutionary Analysis.

Science.gov (United States)

Tian, Pengfei; Best, Robert B

2017-10-17

Quantifying the relationship between protein sequence and structure is key to understanding the protein universe. A fundamental measure of this relationship is the total number of amino acid sequences that can fold to a target protein structure, known as the "sequence capacity," which has been suggested as a proxy for how designable a given protein fold is. Although sequence capacity has been extensively studied using lattice models and theory, numerical estimates for real protein structures are currently lacking. In this work, we have quantitatively estimated the sequence capacity of 10 proteins with a variety of different structures using a statistical model based on residue-residue co-evolution to capture the variation of sequences from the same protein family. Remarkably, we find that even for the smallest protein folds, such as the WW domain, the number of foldable sequences is extremely large, exceeding the Avogadro constant. In agreement with earlier theoretical work, the calculated sequence capacity is positively correlated with the size of the protein, or better, the density of contacts. This allows the absolute sequence capacity of a given protein to be approximately predicted from its structure. On the other hand, the relative sequence capacity, i.e., normalized by the total number of possible sequences, is an extremely tiny number and is strongly anti-correlated with the protein length. Thus, although there may be more foldable sequences for larger proteins, it will be much harder to find them. Lastly, we have correlated the evolutionary age of proteins in the CATH database with their sequence capacity as predicted by our model. The results suggest a trade-off between the opposing requirements of high designability and the likelihood of a novel fold emerging by chance. Published by Elsevier Inc.
Predicting the tolerated sequences for proteins and protein interfaces using RosettaBackrub flexible backbone design.

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Colin A Smith

Full Text Available Predicting the set of sequences that are tolerated by a protein or protein interface, while maintaining a desired function, is useful for characterizing protein interaction specificity and for computationally designing sequence libraries to engineer proteins with new functions. Here we provide a general method, a detailed set of protocols, and several benchmarks and analyses for estimating tolerated sequences using flexible backbone protein design implemented in the Rosetta molecular modeling software suite. The input to the method is at least one experimentally determined three-dimensional protein structure or high-quality model. The starting structure(s are expanded or refined into a conformational ensemble using Monte Carlo simulations consisting of backrub backbone and side chain moves in Rosetta. The method then uses a combination of simulated annealing and genetic algorithm optimization methods to enrich for low-energy sequences for the individual members of the ensemble. To emphasize certain functional requirements (e.g. forming a binding interface, interactions between and within parts of the structure (e.g. domains can be reweighted in the scoring function. Results from each backbone structure are merged together to create a single estimate for the tolerated sequence space. We provide an extensive description of the protocol and its parameters, all source code, example analysis scripts and three tests applying this method to finding sequences predicted to stabilize proteins or protein interfaces. The generality of this method makes many other applications possible, for example stabilizing interactions with small molecules, DNA, or RNA. Through the use of within-domain reweighting and/or multistate design, it may also be possible to use this method to find sequences that stabilize particular protein conformations or binding interactions over others.
Protein structure determination by exhaustive search of Protein Data Bank derived databases.

Science.gov (United States)

Stokes-Rees, Ian; Sliz, Piotr

2010-12-14

Parallel sequence and structure alignment tools have become ubiquitous and invaluable at all levels in the study of biological systems. We demonstrate the application and utility of this same parallel search paradigm to the process of protein structure determination, benefitting from the large and growing corpus of known structures. Such searches were previously computationally intractable. Through the method of Wide Search Molecular Replacement, developed here, they can be completed in a few hours with the aide of national-scale federated cyberinfrastructure. By dramatically expanding the range of models considered for structure determination, we show that small (less than 12% structural coverage) and low sequence identity (less than 20% identity) template structures can be identified through multidimensional template scoring metrics and used for structure determination. Many new macromolecular complexes can benefit significantly from such a technique due to the lack of known homologous protein folds or sequences. We demonstrate the effectiveness of the method by determining the structure of a full-length p97 homologue from Trichoplusia ni. Example cases with the MHC/T-cell receptor complex and the EmoB protein provide systematic estimates of minimum sequence identity, structure coverage, and structural similarity required for this method to succeed. We describe how this structure-search approach and other novel computationally intensive workflows are made tractable through integration with the US national computational cyberinfrastructure, allowing, for example, rapid processing of the entire Structural Classification of Proteins protein fragment database.
CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction

KAUST Repository

Cui, Xuefeng

2016-06-15

Motivation: Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment, threading and alignment-free methods, protein homology detection remains a challenging open problem. Recently, network methods that try to find transitive paths in the protein structure space demonstrate the importance of incorporating network information of the structure space. Yet, current methods merge the sequence space and the structure space into a single space, and thus introduce inconsistency in combining different sources of information. Method: We present a novel network-based protein homology detection method, CMsearch, based on cross-modal learning. Instead of exploring a single network built from the mixture of sequence and structure space information, CMsearch builds two separate networks to represent the sequence space and the structure space. It then learns sequence–structure correlation by simultaneously taking sequence information, structure information, sequence space information and structure space information into consideration. Results: We tested CMsearch on two challenging tasks, protein homology detection and protein structure prediction, by querying all 8332 PDB40 proteins. Our results demonstrate that CMsearch is insensitive to the similarity metrics used to define the sequence and the structure spaces. By using HMM–HMM alignment as the sequence similarity metric, CMsearch clearly outperforms state-of-the-art homology detection methods and the CASP-winning template-based protein structure prediction methods.
EST2Prot: Mapping EST sequences to proteins

Directory of Open Access Journals (Sweden)

Lin David M

2006-03-01

Full Text Available Abstract Background EST libraries are used in various biological studies, from microarray experiments to proteomic and genetic screens. These libraries usually contain many uncharacterized ESTs that are typically ignored since they cannot be mapped to known genes. Consequently, new discoveries are possibly overlooked. Results We describe a system (EST2Prot that uses multiple elements to map EST sequences to their corresponding protein products. EST2Prot uses UniGene clusters, substring analysis, information about protein coding regions in existing DNA sequences and protein database searches to detect protein products related to a query EST sequence. Gene Ontology terms, Swiss-Prot keywords, and protein similarity data are used to map the ESTs to functional descriptors. Conclusion EST2Prot extends and significantly enriches the popular UniGene mapping by utilizing multiple relations between known biological entities. It produces a mapping between ESTs and proteins in real-time through a simple web-interface. The system is part of the Biozon database and is accessible at http://biozon.org/tools/est/.
Adaptive compressive learning for prediction of protein-protein interactions from primary sequence.

Science.gov (United States)

Zhang, Ya-Nan; Pan, Xiao-Yong; Huang, Yan; Shen, Hong-Bin

2011-08-21

Protein-protein interactions (PPIs) play an important role in biological processes. Although much effort has been devoted to the identification of novel PPIs by integrating experimental biological knowledge, there are still many difficulties because of lacking enough protein structural and functional information. It is highly desired to develop methods based only on amino acid sequences for predicting PPIs. However, sequence-based predictors are often struggling with the high-dimensionality causing over-fitting and high computational complexity problems, as well as the redundancy of sequential feature vectors. In this paper, a novel computational approach based on compressed sensing theory is proposed to predict yeast Saccharomyces cerevisiae PPIs from primary sequence and has achieved promising results. The key advantage of the proposed compressed sensing algorithm is that it can compress the original high-dimensional protein sequential feature vector into a much lower but more condensed space taking the sparsity property of the original signal into account. What makes compressed sensing much more attractive in protein sequence analysis is its compressed signal can be reconstructed from far fewer measurements than what is usually considered necessary in traditional Nyquist sampling theory. Experimental results demonstrate that proposed compressed sensing method is powerful for analyzing noisy biological data and reducing redundancy in feature vectors. The proposed method represents a new strategy of dealing with high-dimensional protein discrete model and has great potentiality to be extended to deal with many other complicated biological systems. Copyright © 2011 Elsevier Ltd. All rights reserved.
Heap: a highly sensitive and accurate SNP detection tool for low-coverage high-throughput sequencing data

KAUST Repository

Kobayashi, Masaaki

2017-04-20

Recent availability of large-scale genomic resources enables us to conduct so called genome-wide association studies (GWAS) and genomic prediction (GP) studies, particularly with next-generation sequencing (NGS) data. The effectiveness of GWAS and GP depends on not only their mathematical models, but the quality and quantity of variants employed in the analysis. In NGS single nucleotide polymorphism (SNP) calling, conventional tools ideally require more reads for higher SNP sensitivity and accuracy. In this study, we aimed to develop a tool, Heap, that enables robustly sensitive and accurate calling of SNPs, particularly with a low coverage NGS data, which must be aligned to the reference genome sequences in advance. To reduce false positive SNPs, Heap determines genotypes and calls SNPs at each site except for sites at the both ends of reads or containing a minor allele supported by only one read. Performance comparison with existing tools showed that Heap achieved the highest F-scores with low coverage (7X) restriction-site associated DNA sequencing reads of sorghum and rice individuals. This will facilitate cost-effective GWAS and GP studies in this NGS era. Code and documentation of Heap are freely available from https://github.com/meiji-bioinf/heap (29 March 2017, date last accessed) and our web site (http://bioinf.mind.meiji.ac.jp/lab/en/tools.html (29 March 2017, date last accessed)).
Design of Protein Multi-specificity Using an Independent Sequence Search Reduces the Barrier to Low Energy Sequences.

Directory of Open Access Journals (Sweden)

Alexander M Sevy

2015-07-01

Full Text Available Computational protein design has found great success in engineering proteins for thermodynamic stability, binding specificity, or enzymatic activity in a 'single state' design (SSD paradigm. Multi-specificity design (MSD, on the other hand, involves considering the stability of multiple protein states simultaneously. We have developed a novel MSD algorithm, which we refer to as REstrained CONvergence in multi-specificity design (RECON. The algorithm allows each state to adopt its own sequence throughout the design process rather than enforcing a single sequence on all states. Convergence to a single sequence is encouraged through an incrementally increasing convergence restraint for corresponding positions. Compared to MSD algorithms that enforce (constrain an identical sequence on all states the energy landscape is simplified, which accelerates the search drastically. As a result, RECON can readily be used in simulations with a flexible protein backbone. We have benchmarked RECON on two design tasks. First, we designed antibodies derived from a common germline gene against their diverse targets to assess recovery of the germline, polyspecific sequence. Second, we design "promiscuous", polyspecific proteins against all binding partners and measure recovery of the native sequence. We show that RECON is able to efficiently recover native-like, biologically relevant sequences in this diverse set of protein complexes.
Nonlinear analysis of sequence symmetry of beta-trefoil family proteins

Energy Technology Data Exchange (ETDEWEB)

Li Mingfeng [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Huang Yanzhao [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Xu Ruizhen [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Xiao Yi [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China)]. E-mail: yxiao@mail.hust.edu.cn

2005-07-01

The tertiary structures of proteins of beta-trefoil family have three-fold quasi-symmetry while their amino acid sequences appear almost at random. In the present paper we show that these amino acid sequences have hidden symmetries in fact and furthermore the degrees of these hidden symmetries are the same as those of their tertiary structures. We shall present a modified recurrence plot to reveal hidden symmetries in protein sequences. Our results can explain the contradiction in sequence-structure relations of proteins of beta-trefoil family.
Expansion for the Brachylophosaurus canadensis Collagen I Sequence and Additional Evidence of the Preservation of Cretaceous Protein.

Science.gov (United States)

Schroeter, Elena R; DeHart, Caroline J; Cleland, Timothy P; Zheng, Wenxia; Thomas, Paul M; Kelleher, Neil L; Bern, Marshall; Schweitzer, Mary H

2017-02-03

Sequence data from biomolecules such as DNA and proteins, which provide critical information for evolutionary studies, have been assumed to be forever outside the reach of dinosaur paleontology. Proteins, which are predicted to have greater longevity than DNA, have been recovered from two nonavian dinosaurs, but these results remain controversial. For proteomic data derived from extinct Mesozoic organisms to reach their greatest potential for investigating questions of phylogeny and paleobiology, it must be shown that peptide sequences can be reliably and reproducibly obtained from fossils and that fragmentary sequences for ancient proteins can be increasingly expanded. To test the hypothesis that peptides can be repeatedly detected and validated from fossil tissues many millions of years old, we applied updated extraction methodology, high-resolution mass spectrometry, and bioinformatics analyses on a Brachylophosaurus canadensis specimen (MOR 2598) from which collagen I peptides were recovered in 2009. We recovered eight peptide sequences of collagen I: two identical to peptides recovered in 2009 and six new peptides. Phylogenetic analyses place the recovered sequences within basal archosauria. When only the new sequences are considered, B. canadensis is grouped more closely to crocodylians, but when all sequences (current and those reported in 2009) are analyzed, B. canadensis is placed more closely to basal birds. The data robustly support the hypothesis of an endogenous origin for these peptides, confirm the idea that peptides can survive in specimens tens of millions of years old, and bolster the validity of the 2009 study. Furthermore, the new data expand the coverage of B. canadensis collagen I (a 33.6% increase in collagen I alpha 1 and 116.7% in alpha 2). Finally, this study demonstrates the importance of reexamining previously studied specimens with updated methods and instrumentation, as we obtained roughly the same amount of sequence data as the
Correlated mutations in protein sequences: Phylogenetic and structural effects

Energy Technology Data Exchange (ETDEWEB)

Lapedes, A.S. [Los Alamos National Lab., NM (United States). Theoretical Div.]|[Santa Fe Inst., NM (United States); Giraud, B.G. [C.E.N. Saclay, Gif/Yvette (France). Service Physique Theorique; Liu, L.C. [Los Alamos National Lab., NM (United States). Theoretical Div.; Stormo, G.D. [Univ. of Colorado, Boulder, CO (United States). Dept. of Molecular, Cellular and Developmental Biology

1998-12-01

Covariation analysis of sets of aligned sequences for RNA molecules is relatively successful in elucidating RNA secondary structure, as well as some aspects of tertiary structure. Covariation analysis of sets of aligned sequences for protein molecules is successful in certain instances in elucidating certain structural and functional links, but in general, pairs of sites displaying highly covarying mutations in protein sequences do not necessarily correspond to sites that are spatially close in the protein structure. In this paper the authors identify two reasons why naive use of covariation analysis for protein sequences fails to reliably indicate sequence positions that are spatially proximate. The first reason involves the bias introduced in calculation of covariation measures due to the fact that biological sequences are generally related by a non-trivial phylogenetic tree. The authors present a null-model approach to solve this problem. The second reason involves linked chains of covariation which can result in pairs of sites displaying significant covariation even though they are not spatially proximate. They present a maximum entropy solution to this classic problem of causation versus correlation. The methodologies are validated in simulation.
Comparative analyses of two Geraniaceae transcriptomes using next-generation sequencing.

Science.gov (United States)

Zhang, Jin; Ruhlman, Tracey A; Mower, Jeffrey P; Jansen, Robert K

2013-12-29

Organelle genomes of Geraniaceae exhibit several unusual evolutionary phenomena compared to other angiosperm families including accelerated nucleotide substitution rates, widespread gene loss, reduced RNA editing, and extensive genomic rearrangements. Since most organelle-encoded proteins function in multi-subunit complexes that also contain nuclear-encoded proteins, it is likely that the atypical organellar phenomena affect the evolution of nuclear genes encoding organellar proteins. To begin to unravel the complex co-evolutionary interplay between organellar and nuclear genomes in this family, we sequenced nuclear transcriptomes of two species, Geranium maderense and Pelargonium x hortorum. Normalized cDNA libraries of G. maderense and P. x hortorum were used for transcriptome sequencing. Five assemblers (MIRA, Newbler, SOAPdenovo, SOAPdenovo-trans [SOAPtrans], Trinity) and two next-generation technologies (454 and Illumina) were compared to determine the optimal transcriptome sequencing approach. Trinity provided the highest quality assembly of Illumina data with the deepest transcriptome coverage. An analysis to determine the amount of sequencing needed for de novo assembly revealed diminishing returns of coverage and quality with data sets larger than sixty million Illumina paired end reads for both species. The G. maderense and P. x hortorum transcriptomes contained fewer transcripts encoding the PLS subclass of PPR proteins relative to other angiosperms, consistent with reduced mitochondrial RNA editing activity in Geraniaceae. In addition, transcripts for all six plastid targeted sigma factors were identified in both transcriptomes, suggesting that one of the highly divergent rpoA-like ORFs in the P. x hortorum plastid genome is functional. The findings support the use of the Illumina platform and assemblers optimized for transcriptome assembly, such as Trinity or SOAPtrans, to generate high-quality de novo transcriptomes with broad coverage. In addition
Comparison of two next-generation sequencing kits for diagnosis of epileptic disorders with a user-friendly tool for displaying gene coverage, DeCovA

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Sarra Dimassi

2015-12-01

Full Text Available In recent years, molecular genetics has been playing an increasing role in the diagnostic process of monogenic epilepsies. Knowing the genetic basis of one patient's epilepsy provides accurate genetic counseling and may guide therapeutic options. Genetic diagnosis of epilepsy syndromes has long been based on Sanger sequencing and search for large rearrangements using MLPA or DNA arrays (array-CGH or SNP-array. Recently, next-generation sequencing (NGS was demonstrated to be a powerful approach to overcome the wide clinical and genetic heterogeneity of epileptic disorders. Coverage is critical for assessing the quality and accuracy of results from NGS. However, it is often a difficult parameter to display in practice. The aim of the study was to compare two library-building methods (Haloplex, Agilent and SeqCap EZ, Roche for a targeted panel of 41 genes causing monogenic epileptic disorders. We included 24 patients, 20 of whom had known disease-causing mutations. For each patient both libraries were built in parallel and sequenced on an Ion Torrent Personal Genome Machine (PGM. To compare coverage and depth, we developed a simple homemade tool, named DeCovA (Depth and Coverage Analysis. DeCovA displays the sequencing depth of each base and the coverage of target genes for each genomic position. The fraction of each gene covered at different thresholds could be easily estimated. None of the two methods used, namely NextGene and Ion Reporter, were able to identify all the known mutations/CNVs displayed by the 20 patients. Variant detection rate was globally similar for the two techniques and DeCovA showed that failure to detect a mutation was mainly related to insufficient coverage.
Deep sequencing methods for protein engineering and design.

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Wrenbeck, Emily E; Faber, Matthew S; Whitehead, Timothy A

2017-08-01

The advent of next-generation sequencing (NGS) has revolutionized protein science, and the development of complementary methods enabling NGS-driven protein engineering have followed. In general, these experiments address the functional consequences of thousands of protein variants in a massively parallel manner using genotype-phenotype linked high-throughput functional screens followed by DNA counting via deep sequencing. We highlight the use of information rich datasets to engineer protein molecular recognition. Examples include the creation of multiple dual-affinity Fabs targeting structurally dissimilar epitopes and engineering of a broad germline-targeted anti-HIV-1 immunogen. Additionally, we highlight the generation of enzyme fitness landscapes for conducting fundamental studies of protein behavior and evolution. We conclude with discussion of technological advances. Copyright © 2016 Elsevier Ltd. All rights reserved.

Biophysical and structural considerations for protein sequence evolution

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Grahnen Johan A

2011-12-01

Full Text Available Abstract Background Protein sequence evolution is constrained by the biophysics of folding and function, causing interdependence between interacting sites in the sequence. However, current site-independent models of sequence evolutions do not take this into account. Recent attempts to integrate the influence of structure and biophysics into phylogenetic models via statistical/informational approaches have not resulted in expected improvements in model performance. This suggests that further innovations are needed for progress in this field. Results Here we develop a coarse-grained physics-based model of protein folding and binding function, and compare it to a popular informational model. We find that both models violate the assumption of the native sequence being close to a thermodynamic optimum, causing directional selection away from the native state. Sampling and simulation show that the physics-based model is more specific for fold-defining interactions that vary less among residue type. The informational model diffuses further in sequence space with fewer barriers and tends to provide less support for an invariant sites model, although amino acid substitutions are generally conservative. Both approaches produce sequences with natural features like dN/dS Conclusions Simple coarse-grained models of protein folding can describe some natural features of evolving proteins but are currently not accurate enough to use in evolutionary inference. This is partly due to improper packing of the hydrophobic core. We suggest possible improvements on the representation of structure, folding energy, and binding function, as regards both native and non-native conformations, and describe a large number of possible applications for such a model.
MIPS: a database for protein sequences, homology data and yeast genome information.

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Mewes, H W; Albermann, K; Heumann, K; Liebl, S; Pfeiffer, F

1997-01-01

The MIPS group (Martinsried Institute for Protein Sequences) at the Max-Planck-Institute for Biochemistry, Martinsried near Munich, Germany, collects, processes and distributes protein sequence data within the framework of the tripartite association of the PIR-International Protein Sequence Database (,). MIPS contributes nearly 50% of the data input to the PIR-International Protein Sequence Database. The database is distributed on CD-ROM together with PATCHX, an exhaustive supplement of unique, unverified protein sequences from external sources compiled by MIPS. Through its WWW server (http://www.mips.biochem.mpg.de/ ) MIPS permits internet access to sequence databases, homology data and to yeast genome information. (i) Sequence similarity results from the FASTA program () are stored in the FASTA database for all proteins from PIR-International and PATCHX. The database is dynamically maintained and permits instant access to FASTA results. (ii) Starting with FASTA database queries, proteins have been classified into families and superfamilies (PROT-FAM). (iii) The HPT (hashed position tree) data structure () developed at MIPS is a new approach for rapid sequence and pattern searching. (iv) MIPS provides access to the sequence and annotation of the complete yeast genome (), the functional classification of yeast genes (FunCat) and its graphical display, the 'Genome Browser' (). A CD-ROM based on the JAVA programming language providing dynamic interactive access to the yeast genome and the related protein sequences has been compiled and is available on request. PMID:9016498
Formatt: Correcting protein multiple structural alignments by incorporating sequence alignment

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Daniels Noah M

2012-10-01

Full Text Available Abstract Background The quality of multiple protein structure alignments are usually computed and assessed based on geometric functions of the coordinates of the backbone atoms from the protein chains. These purely geometric methods do not utilize directly protein sequence similarity, and in fact, determining the proper way to incorporate sequence similarity measures into the construction and assessment of protein multiple structure alignments has proved surprisingly difficult. Results We present Formatt, a multiple structure alignment based on the Matt purely geometric multiple structure alignment program, that also takes into account sequence similarity when constructing alignments. We show that Formatt outperforms Matt and other popular structure alignment programs on the popular HOMSTRAD benchmark. For the SABMark twilight zone benchmark set that captures more remote homology, Formatt and Matt outperform other programs; depending on choice of embedded sequence aligner, Formatt produces either better sequence and structural alignments with a smaller core size than Matt, or similarly sized alignments with better sequence similarity, for a small cost in average RMSD. Conclusions Considering sequence information as well as purely geometric information seems to improve quality of multiple structure alignments, though defining what constitutes the best alignment when sequence and structural measures would suggest different alignments remains a difficult open question.
Single-molecule protein sequencing through fingerprinting: computational assessment

Science.gov (United States)

Yao, Yao; Docter, Margreet; van Ginkel, Jetty; de Ridder, Dick; Joo, Chirlmin

2015-10-01

Proteins are vital in all biological systems as they constitute the main structural and functional components of cells. Recent advances in mass spectrometry have brought the promise of complete proteomics by helping draft the human proteome. Yet, this commonly used protein sequencing technique has fundamental limitations in sensitivity. Here we propose a method for single-molecule (SM) protein sequencing. A major challenge lies in the fact that proteins are composed of 20 different amino acids, which demands 20 molecular reporters. We computationally demonstrate that it suffices to measure only two types of amino acids to identify proteins and suggest an experimental scheme using SM fluorescence. When achieved, this highly sensitive approach will result in a paradigm shift in proteomics, with major impact in the biological and medical sciences.
Single-molecule protein sequencing through fingerprinting: computational assessment

International Nuclear Information System (INIS)

Yao, Yao; Docter, Margreet; Van Ginkel, Jetty; Joo, Chirlmin; De Ridder, Dick

2015-01-01

Proteins are vital in all biological systems as they constitute the main structural and functional components of cells. Recent advances in mass spectrometry have brought the promise of complete proteomics by helping draft the human proteome. Yet, this commonly used protein sequencing technique has fundamental limitations in sensitivity. Here we propose a method for single-molecule (SM) protein sequencing. A major challenge lies in the fact that proteins are composed of 20 different amino acids, which demands 20 molecular reporters. We computationally demonstrate that it suffices to measure only two types of amino acids to identify proteins and suggest an experimental scheme using SM fluorescence. When achieved, this highly sensitive approach will result in a paradigm shift in proteomics, with major impact in the biological and medical sciences. (paper)
CoverageAnalyzer (CAn: A Tool for Inspection of Modification Signatures in RNA Sequencing Profiles

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Ralf Hauenschild

2016-11-01

Full Text Available Combination of reverse transcription (RT and deep sequencing has emerged as a powerful instrument for the detection of RNA modifications, a field that has seen a recent surge in activity because of its importance in gene regulation. Recent studies yielded high-resolution RT signatures of modified ribonucleotides relying on both sequence-dependent mismatch patterns and reverse transcription arrests. Common alignment viewers lack specialized functionality, such as filtering, tailored visualization, image export and differential analysis. Consequently, the community will profit from a platform seamlessly connecting detailed visual inspection of RT signatures and automated screening for modification candidates. CoverageAnalyzer (CAn was developed in response to the demand for a powerful inspection tool. It is freely available for all three main operating systems. With SAM file format as standard input, CAn is an intuitive and user-friendly tool that is generally applicable to the large community of biomedical users, starting from simple visualization of RNA sequencing (RNA-Seq data, up to sophisticated modification analysis with significance-based modification candidate calling.
Prediction of Protein Structural Classes for Low-Similarity Sequences Based on Consensus Sequence and Segmented PSSM

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Yunyun Liang

2015-01-01

Full Text Available Prediction of protein structural classes for low-similarity sequences is useful for understanding fold patterns, regulation, functions, and interactions of proteins. It is well known that feature extraction is significant to prediction of protein structural class and it mainly uses protein primary sequence, predicted secondary structure sequence, and position-specific scoring matrix (PSSM. Currently, prediction solely based on the PSSM has played a key role in improving the prediction accuracy. In this paper, we propose a novel method called CSP-SegPseP-SegACP by fusing consensus sequence (CS, segmented PsePSSM, and segmented autocovariance transformation (ACT based on PSSM. Three widely used low-similarity datasets (1189, 25PDB, and 640 are adopted in this paper. Then a 700-dimensional (700D feature vector is constructed and the dimension is decreased to 224D by using principal component analysis (PCA. To verify the performance of our method, rigorous jackknife cross-validation tests are performed on 1189, 25PDB, and 640 datasets. Comparison of our results with the existing PSSM-based methods demonstrates that our method achieves the favorable and competitive performance. This will offer an important complementary to other PSSM-based methods for prediction of protein structural classes for low-similarity sequences.
Inverse statistical physics of protein sequences: a key issues review.

Science.gov (United States)

Cocco, Simona; Feinauer, Christoph; Figliuzzi, Matteo; Monasson, Rémi; Weigt, Martin

2018-03-01

In the course of evolution, proteins undergo important changes in their amino acid sequences, while their three-dimensional folded structure and their biological function remain remarkably conserved. Thanks to modern sequencing techniques, sequence data accumulate at unprecedented pace. This provides large sets of so-called homologous, i.e. evolutionarily related protein sequences, to which methods of inverse statistical physics can be applied. Using sequence data as the basis for the inference of Boltzmann distributions from samples of microscopic configurations or observables, it is possible to extract information about evolutionary constraints and thus protein function and structure. Here we give an overview over some biologically important questions, and how statistical-mechanics inspired modeling approaches can help to answer them. Finally, we discuss some open questions, which we expect to be addressed over the next years.
Ultra-fast evaluation of protein energies directly from sequence.

Directory of Open Access Journals (Sweden)

Gevorg Grigoryan

2006-06-01

Full Text Available The structure, function, stability, and many other properties of a protein in a fixed environment are fully specified by its sequence, but in a manner that is difficult to discern. We present a general approach for rapidly mapping sequences directly to their energies on a pre-specified rigid backbone, an important sub-problem in computational protein design and in some methods for protein structure prediction. The cluster expansion (CE method that we employ can, in principle, be extended to model any computable or measurable protein property directly as a function of sequence. Here we show how CE can be applied to the problem of computational protein design, and use it to derive excellent approximations of physical potentials. The approach provides several attractive advantages. First, following a one-time derivation of a CE expansion, the amount of time necessary to evaluate the energy of a sequence adopting a specified backbone conformation is reduced by a factor of 10(7 compared to standard full-atom methods for the same task. Second, the agreement between two full-atom methods that we tested and their CE sequence-based expressions is very high (root mean square deviation 1.1-4.7 kcal/mol, R2 = 0.7-1.0. Third, the functional form of the CE energy expression is such that individual terms of the expansion have clear physical interpretations. We derived expressions for the energies of three classic protein design targets-a coiled coil, a zinc finger, and a WW domain-as functions of sequence, and examined the most significant terms. Single-residue and residue-pair interactions are sufficient to accurately capture the energetics of the dimeric coiled coil, whereas higher-order contributions are important for the two more globular folds. For the task of designing novel zinc-finger sequences, a CE-derived energy function provides significantly better solutions than a standard design protocol, in comparable computation time. Given these advantages
ProteinSplit: splitting of multi-domain proteins using prediction of ordered and disordered regions in protein sequences for virtual structural genomics

International Nuclear Information System (INIS)

Wyrwicz, Lucjan S; Koczyk, Grzegorz; Rychlewski, Leszek; Plewczynski, Dariusz

2007-01-01

The annotation of protein folds within newly sequenced genomes is the main target for semi-automated protein structure prediction (virtual structural genomics). A large number of automated methods have been developed recently with very good results in the case of single-domain proteins. Unfortunately, most of these automated methods often fail to properly predict the distant homology between a given multi-domain protein query and structural templates. Therefore a multi-domain protein should be split into domains in order to overcome this limitation. ProteinSplit is designed to identify protein domain boundaries using a novel algorithm that predicts disordered regions in protein sequences. The software utilizes various sequence characteristics to assess the local propensity of a protein to be disordered or ordered in terms of local structure stability. These disordered parts of a protein are likely to create interdomain spacers. Because of its speed and portability, the method was successfully applied to several genome-wide fold annotation experiments. The user can run an automated analysis of sets of proteins or perform semi-automated multiple user projects (saving the results on the server). Additionally the sequences of predicted domains can be sent to the Bioinfo.PL Protein Structure Prediction Meta-Server for further protein three-dimensional structure and function prediction. The program is freely accessible as a web service at http://lucjan.bioinfo.pl/proteinsplit together with detailed benchmark results on the critical assessment of a fully automated structure prediction (CAFASP) set of sequences. The source code of the local version of protein domain boundary prediction is available upon request from the authors
Rapid identification of sequences for orphan enzymes to power accurate protein annotation.

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Kevin R Ramkissoon

Full Text Available The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the "back catalog" of enzymology--"orphan enzymes," those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC database alone. In this study, we demonstrate how this orphan enzyme "back catalog" is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology's "back catalog" another powerful tool to drive accurate genome annotation.
Rapid Identification of Sequences for Orphan Enzymes to Power Accurate Protein Annotation

Science.gov (United States)

Ojha, Sunil; Watson, Douglas S.; Bomar, Martha G.; Galande, Amit K.; Shearer, Alexander G.

2013-01-01

The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the “back catalog” of enzymology – “orphan enzymes,” those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC) database alone. In this study, we demonstrate how this orphan enzyme “back catalog” is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis) to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology’s “back catalog” another powerful tool to drive accurate genome annotation. PMID:24386392
A comparison of genotyping-by-sequencing analysis methods on low-coverage crop datasets shows advantages of a new workflow, GB-eaSy.

Science.gov (United States)

Wickland, Daniel P; Battu, Gopal; Hudson, Karen A; Diers, Brian W; Hudson, Matthew E

2017-12-28

Genotyping-by-sequencing (GBS), a method to identify genetic variants and quickly genotype samples, reduces genome complexity by using restriction enzymes to divide the genome into fragments whose ends are sequenced on short-read sequencing platforms. While cost-effective, this method produces extensive missing data and requires complex bioinformatics analysis. GBS is most commonly used on crop plant genomes, and because crop plants have highly variable ploidy and repeat content, the performance of GBS analysis software can vary by target organism. Here we focus our analysis on soybean, a polyploid crop with a highly duplicated genome, relatively little public GBS data and few dedicated tools. We compared the performance of five GBS pipelines using low-coverage Illumina sequence data from three soybean populations. To address issues identified with existing methods, we developed GB-eaSy, a GBS bioinformatics workflow that incorporates widely used genomics tools, parallelization and automation to increase the accuracy and accessibility of GBS data analysis. Compared to other GBS pipelines, GB-eaSy rapidly and accurately identified the greatest number of SNPs, with SNP calls closely concordant with whole-genome sequencing of selected lines. Across all five GBS analysis platforms, SNP calls showed unexpectedly low convergence but generally high accuracy, indicating that the workflows arrived at largely complementary sets of valid SNP calls on the low-coverage data analyzed. We show that GB-eaSy is approximately as good as, or better than, other leading software solutions in the accuracy, yield and missing data fraction of variant calling, as tested on low-coverage genomic data from soybean. It also performs well relative to other solutions in terms of the run time and disk space required. In addition, GB-eaSy is built from existing open-source, modular software packages that are regularly updated and commonly used, making it straightforward to install and maintain
Complete cDNA sequence coding for human docking protein

Energy Technology Data Exchange (ETDEWEB)

Hortsch, M; Labeit, S; Meyer, D I

1988-01-11

Docking protein (DP, or SRP receptor) is a rough endoplasmic reticulum (ER)-associated protein essential for the targeting and translocation of nascent polypeptides across this membrane. It specifically interacts with a cytoplasmic ribonucleoprotein complex, the signal recognition particle (SRP). The nucleotide sequence of cDNA encoding the entire human DP and its deduced amino acid sequence are given.
Designing sequence to control protein function in an EF-hand protein.

Science.gov (United States)

Bunick, Christopher G; Nelson, Melanie R; Mangahas, Sheryll; Hunter, Michael J; Sheehan, Jonathan H; Mizoue, Laura S; Bunick, Gerard J; Chazin, Walter J

2004-05-19

The extent of conformational change that calcium binding induces in EF-hand proteins is a key biochemical property specifying Ca(2+) sensor versus signal modulator function. To understand how differences in amino acid sequence lead to differences in the response to Ca(2+) binding, comparative analyses of sequence and structures, combined with model building, were used to develop hypotheses about which amino acid residues control Ca(2+)-induced conformational changes. These results were used to generate a first design of calbindomodulin (CBM-1), a calbindin D(9k) re-engineered with 15 mutations to respond to Ca(2+) binding with a conformational change similar to that of calmodulin. The gene for CBM-1 was synthesized, and the protein was expressed and purified. Remarkably, this protein did not exhibit any non-native-like molten globule properties despite the large number of mutations and the nonconservative nature of some of them. Ca(2+)-induced changes in CD intensity and in the binding of the hydrophobic probe, ANS, implied that CBM-1 does undergo Ca(2+) sensorlike conformational changes. The X-ray crystal structure of Ca(2+)-CBM-1 determined at 1.44 A resolution reveals the anticipated increase in hydrophobic surface area relative to the wild-type protein. A nascent calmodulin-like hydrophobic docking surface was also found, though it is occluded by the inter-EF-hand loop. The results from this first calbindomodulin design are discussed in terms of progress toward understanding the relationships between amino acid sequence, protein structure, and protein function for EF-hand CaBPs, as well as the additional mutations for the next CBM design.
Prediction of protein-protein interaction sites in sequences and 3D structures by random forests.

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Mile Sikić

2009-01-01

Full Text Available Identifying interaction sites in proteins provides important clues to the function of a protein and is becoming increasingly relevant in topics such as systems biology and drug discovery. Although there are numerous papers on the prediction of interaction sites using information derived from structure, there are only a few case reports on the prediction of interaction residues based solely on protein sequence. Here, a sliding window approach is combined with the Random Forests method to predict protein interaction sites using (i a combination of sequence- and structure-derived parameters and (ii sequence information alone. For sequence-based prediction we achieved a precision of 84% with a 26% recall and an F-measure of 40%. When combined with structural information, the prediction performance increases to a precision of 76% and a recall of 38% with an F-measure of 51%. We also present an attempt to rationalize the sliding window size and demonstrate that a nine-residue window is the most suitable for predictor construction. Finally, we demonstrate the applicability of our prediction methods by modeling the Ras-Raf complex using predicted interaction sites as target binding interfaces. Our results suggest that it is possible to predict protein interaction sites with quite a high accuracy using only sequence information.
Sequencing of 50 human exomes reveals adaptation to high altitude

DEFF Research Database (Denmark)

Yi, Xin; Liang, Yu; Huerta-Sanchez, Emilia

2010-01-01

Residents of the Tibetan Plateau show heritable adaptations to extreme altitude. We sequenced 50 exomes of ethnic Tibetans, encompassing coding sequences of 92% of human genes, with an average coverage of 18x per individual. Genes showing population-specific allele frequency changes, which repres...... in genetic adaptation to high altitude.......Residents of the Tibetan Plateau show heritable adaptations to extreme altitude. We sequenced 50 exomes of ethnic Tibetans, encompassing coding sequences of 92% of human genes, with an average coverage of 18x per individual. Genes showing population-specific allele frequency changes, which...... represent strong candidates for altitude adaptation, were identified. The strongest signal of natural selection came from endothelial Per-Arnt-Sim (PAS) domain protein 1 (EPAS1), a transcription factor involved in response to hypoxia. One single-nucleotide polymorphism (SNP) at EPAS1 shows a 78% frequency...
Comparative analysis of the prion protein gene sequences in African lion.

Science.gov (United States)

Wu, Chang-De; Pang, Wan-Yong; Zhao, De-Ming

2006-10-01

The prion protein gene of African lion (Panthera Leo) was first cloned and polymorphisms screened. The results suggest that the prion protein gene of eight African lions is highly homogenous. The amino acid sequences of the prion protein (PrP) of all samples tested were identical. Four single nucleotide polymorphisms (C42T, C81A, C420T, T600C) in the prion protein gene (Prnp) of African lion were found, but no amino acid substitutions. Sequence analysis showed that the higher homology is observed to felis catus AF003087 (96.7%) and to sheep number M31313.1 (96.2%) Genbank accessed. With respect to all the mammalian prion protein sequences compared, the African lion prion protein sequence has three amino acid substitutions. The homology might in turn affect the potential intermolecular interactions critical for cross species transmission of prion disease.
Repeat Sequence Proteins as Matrices for Nanocomposites

Energy Technology Data Exchange (ETDEWEB)

Drummy, L.; Koerner, H; Phillips, D; McAuliffe, J; Kumar, M; Farmer, B; Vaia, R; Naik, R

2009-01-01

Recombinant protein-inorganic nanocomposites comprised of exfoliated Na+ montmorillonite (MMT) in a recombinant protein matrix based on silk-like and elastin-like amino acid motifs (silk elastin-like protein (SELP)) were formed via a solution blending process. Charged residues along the protein backbone are shown to dominate long-range interactions, whereas the SELP repeat sequence leads to local protein/MMT compatibility. Up to a 50% increase in room temperature modulus and a comparable decrease in high temperature coefficient of thermal expansion occur for cast films containing 2-10 wt.% MMT.
Exploring the Arabidopsis Proteome: Influence of Protein Solubilization Buffers on Proteome Coverage

KAUST Repository

Marondedze, Claudius; Wong, Aloysius Tze; Groen, Arnoud; Serano, Natalia Lorena Gorron; Jankovic, Boris R.; Lilley, Kathryn; Gehring, Christoph A; Thomas, Ludivine

2014-01-01

The study of proteomes provides new insights into stimulus-specific responses of protein synthesis and turnover, and the role of post-translational modifications at the systems level. Due to the diverse chemical nature of proteins and shortcomings in the analytical techniques used in their study, only a partial display of the proteome is achieved in any study, and this holds particularly true for plant proteomes. Here we show that different solubilization and separation methods have profound effects on the resulting proteome. In particular, we observed that the type of detergents employed in the solubilization buffer preferentially enriches proteins in different functional categories. These include proteins with a role in signaling, transport, response to temperature stimuli and metabolism. This data may offer a functional bias on comparative analysis studies. In order to obtain a broader coverage, we propose a two-step solubilization protocol with first a detergent-free buffer and then a second step utilizing a combination of two detergents to solubilize proteins.

Exploring the Arabidopsis Proteome: Influence of Protein Solubilization Buffers on Proteome Coverage

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Claudius Marondedze

2014-12-01

Full Text Available The study of proteomes provides new insights into stimulus-specific responses of protein synthesis and turnover, and the role of post-translational modifications at the systems level. Due to the diverse chemical nature of proteins and shortcomings in the analytical techniques used in their study, only a partial display of the proteome is achieved in any study, and this holds particularly true for plant proteomes. Here we show that different solubilization and separation methods have profound effects on the resulting proteome. In particular, we observed that the type of detergents employed in the solubilization buffer preferentially enriches proteins in different functional categories. These include proteins with a role in signaling, transport, response to temperature stimuli and metabolism. This data may offer a functional bias on comparative analysis studies. In order to obtain a broader coverage, we propose a two-step solubilization protocol with first a detergent-free buffer and then a second step utilizing a combination of two detergents to solubilize proteins.
Exploring the Arabidopsis Proteome: Influence of Protein Solubilization Buffers on Proteome Coverage

KAUST Repository

Marondedze, Claudius

2014-12-31

The study of proteomes provides new insights into stimulus-specific responses of protein synthesis and turnover, and the role of post-translational modifications at the systems level. Due to the diverse chemical nature of proteins and shortcomings in the analytical techniques used in their study, only a partial display of the proteome is achieved in any study, and this holds particularly true for plant proteomes. Here we show that different solubilization and separation methods have profound effects on the resulting proteome. In particular, we observed that the type of detergents employed in the solubilization buffer preferentially enriches proteins in different functional categories. These include proteins with a role in signaling, transport, response to temperature stimuli and metabolism. This data may offer a functional bias on comparative analysis studies. In order to obtain a broader coverage, we propose a two-step solubilization protocol with first a detergent-free buffer and then a second step utilizing a combination of two detergents to solubilize proteins.
Analysis of long-range correlation in sequences data of proteins

OpenAIRE

ADRIANA ISVORAN; LAURA UNIPAN; DANA CRACIUN; VASILE MORARIU

2007-01-01

The results presented here suggest the existence of correlations in the sequence data of proteins. 32 proteins, both globular and fibrous, both monomeric and polymeric, were analyzed. The primary structures of these proteins were treated as time series. Three spatial series of data for each sequence of a protein were generated from numerical correspondences between each amino acid and a physical property associated with it, i.e., its electric charge, its polar character and its dipole moment....
Sequence analysis reveals how G protein-coupled receptors transduce the signal to the G protein.

NARCIS (Netherlands)

Oliveira, L.; Paiva, P.B.; Paiva, A.C.; Vriend, G.

2003-01-01

Sequence entropy-variability plots based on alignments of very large numbers of sequences-can indicate the location in proteins of the main active site and modulator sites. In the previous article in this issue, we applied this observation to a series of well-studied proteins and concluded that it
Peptide Pattern Recognition for high-throughput protein sequence analysis and clustering

DEFF Research Database (Denmark)

Busk, Peter Kamp

2017-01-01

Large collections of protein sequences with divergent sequences are tedious to analyze for understanding their phylogenetic or structure-function relation. Peptide Pattern Recognition is an algorithm that was developed to facilitate this task but the previous version does only allow a limited...... number of sequences as input. I implemented Peptide Pattern Recognition as a multithread software designed to handle large numbers of sequences and perform analysis in a reasonable time frame. Benchmarking showed that the new implementation of Peptide Pattern Recognition is twenty times faster than...... the previous implementation on a small protein collection with 673 MAP kinase sequences. In addition, the new implementation could analyze a large protein collection with 48,570 Glycosyl Transferase family 20 sequences without reaching its upper limit on a desktop computer. Peptide Pattern Recognition...
Elman RNN based classification of proteins sequences on account of their mutual information.

Science.gov (United States)

Mishra, Pooja; Nath Pandey, Paras

2012-10-21

In the present work we have employed the method of estimating residue correlation within the protein sequences, by using the mutual information (MI) of adjacent residues, based on structural and solvent accessibility properties of amino acids. The long range correlation between nonadjacent residues is improved by constructing a mutual information vector (MIV) for a single protein sequence, like this each protein sequence is associated with its corresponding MIVs. These MIVs are given to Elman RNN to obtain the classification of protein sequences. The modeling power of MIV was shown to be significantly better, giving a new approach towards alignment free classification of protein sequences. We also conclude that sequence structural and solvent accessible property based MIVs are better predictor. Copyright © 2012 Elsevier Ltd. All rights reserved.
High coverage of the complete mitochondrial genome of the rare Gray's beaked whale (Mesoplodon grayi) using Illumina next generation sequencing.

Science.gov (United States)

Thompson, Kirsten F; Patel, Selina; Williams, Liam; Tsai, Peter; Constantine, Rochelle; Baker, C Scott; Millar, Craig D

2016-01-01

Using an Illumina platform, we shot-gun sequenced the complete mitochondrial genome of Gray's beaked whale (Mesoplodon grayi) to an average coverage of 152X. We performed a de novo assembly using SOAPdenovo2 and determined the total mitogenome length to be 16,347 bp. The nucleotide composition was asymmetric (33.3% A, 24.6% C, 12.6% G, 29.5% T) with an overall GC content of 37.2%. The gene organization was similar to that of other cetaceans with 13 protein-coding genes, 2 rRNAs (12S and 16S), 22 predicted tRNAs and 1 control region or D-loop. We found no evidence of heteroplasmy or nuclear copies of mitochondrial DNA in this individual. Beaked whales within the genus Mesoplodon are rarely seen at sea and their basic biology is poorly understood. These data will contribute to resolving the phylogeography and population ecology of this speciose group.
Predicting membrane protein types by fusing composite protein sequence features into pseudo amino acid composition.

Science.gov (United States)

Hayat, Maqsood; Khan, Asifullah

2011-02-21

Membrane proteins are vital type of proteins that serve as channels, receptors, and energy transducers in a cell. Prediction of membrane protein types is an important research area in bioinformatics. Knowledge of membrane protein types provides some valuable information for predicting novel example of the membrane protein types. However, classification of membrane protein types can be both time consuming and susceptible to errors due to the inherent similarity of membrane protein types. In this paper, neural networks based membrane protein type prediction system is proposed. Composite protein sequence representation (CPSR) is used to extract the features of a protein sequence, which includes seven feature sets; amino acid composition, sequence length, 2 gram exchange group frequency, hydrophobic group, electronic group, sum of hydrophobicity, and R-group. Principal component analysis is then employed to reduce the dimensionality of the feature vector. The probabilistic neural network (PNN), generalized regression neural network, and support vector machine (SVM) are used as classifiers. A high success rate of 86.01% is obtained using SVM for the jackknife test. In case of independent dataset test, PNN yields the highest accuracy of 95.73%. These classifiers exhibit improved performance using other performance measures such as sensitivity, specificity, Mathew's correlation coefficient, and F-measure. The experimental results show that the prediction performance of the proposed scheme for classifying membrane protein types is the best reported, so far. This performance improvement may largely be credited to the learning capabilities of neural networks and the composite feature extraction strategy, which exploits seven different properties of protein sequences. The proposed Mem-Predictor can be accessed at http://111.68.99.218/Mem-Predictor. Copyright Â© 2010 Elsevier Ltd. All rights reserved.
The HMMER Web Server for Protein Sequence Similarity Search.

Science.gov (United States)

Prakash, Ananth; Jeffryes, Matt; Bateman, Alex; Finn, Robert D

2017-12-08

Protein sequence similarity search is one of the most commonly used bioinformatics methods for identifying evolutionarily related proteins. In general, sequences that are evolutionarily related share some degree of similarity, and sequence-search algorithms use this principle to identify homologs. The requirement for a fast and sensitive sequence search method led to the development of the HMMER software, which in the latest version (v3.1) uses a combination of sophisticated acceleration heuristics and mathematical and computational optimizations to enable the use of profile hidden Markov models (HMMs) for sequence analysis. The HMMER Web server provides a common platform by linking the HMMER algorithms to databases, thereby enabling the search for homologs, as well as providing sequence and functional annotation by linking external databases. This unit describes three basic protocols and two alternate protocols that explain how to use the HMMER Web server using various input formats and user defined parameters. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.
Quantiprot - a Python package for quantitative analysis of protein sequences.

Science.gov (United States)

Konopka, Bogumił M; Marciniak, Marta; Dyrka, Witold

2017-07-17

The field of protein sequence analysis is dominated by tools rooted in substitution matrices and alignments. A complementary approach is provided by methods of quantitative characterization. A major advantage of the approach is that quantitative properties defines a multidimensional solution space, where sequences can be related to each other and differences can be meaningfully interpreted. Quantiprot is a software package in Python, which provides a simple and consistent interface to multiple methods for quantitative characterization of protein sequences. The package can be used to calculate dozens of characteristics directly from sequences or using physico-chemical properties of amino acids. Besides basic measures, Quantiprot performs quantitative analysis of recurrence and determinism in the sequence, calculates distribution of n-grams and computes the Zipf's law coefficient. We propose three main fields of application of the Quantiprot package. First, quantitative characteristics can be used in alignment-free similarity searches, and in clustering of large and/or divergent sequence sets. Second, a feature space defined by quantitative properties can be used in comparative studies of protein families and organisms. Third, the feature space can be used for evaluating generative models, where large number of sequences generated by the model can be compared to actually observed sequences.
Osteocalcin protein sequences of Neanderthals and modern primates.

Science.gov (United States)

Nielsen-Marsh, Christina M; Richards, Michael P; Hauschka, Peter V; Thomas-Oates, Jane E; Trinkaus, Erik; Pettitt, Paul B; Karavanic, Ivor; Poinar, Hendrik; Collins, Matthew J

2005-03-22

We report here protein sequences of fossil hominids, from two Neanderthals dating to approximately 75,000 years old from Shanidar Cave in Iraq. These sequences, the oldest reported fossil primate protein sequences, are of bone osteocalcin, which was extracted and sequenced by using MALDI-TOF/TOF mass spectrometry. Through a combination of direct sequencing and peptide mass mapping, we determined that Neanderthals have an osteocalcin amino acid sequence that is identical to that of modern humans. We also report complete osteocalcin sequences for chimpanzee (Pan troglodytes) and gorilla (Gorilla gorilla gorilla) and a partial sequence for orangutan (Pongo pygmaeus), all of which are previously unreported. We found that the osteocalcin sequences of Neanderthals, modern human, chimpanzee, and orangutan are unusual among mammals in that the ninth amino acid is proline (Pro-9), whereas most species have hydroxyproline (Hyp-9). Posttranslational hydroxylation of Pro-9 in osteocalcin by prolyl-4-hydroxylase requires adequate concentrations of vitamin C (l-ascorbic acid), molecular O(2), Fe(2+), and 2-oxoglutarate, and also depends on enzyme recognition of the target proline substrate consensus sequence Leu-Gly-Ala-Pro-9-Ala-Pro-Tyr occurring in most mammals. In five species with Pro-9-Val-10, hydroxylation is blocked, whereas in gorilla there is a mixture of Pro-9 and Hyp-9. We suggest that the absence of hydroxylation of Pro-9 in Pan, Pongo, and Homo may reflect response to a selective pressure related to a decline in vitamin C in the diet during omnivorous dietary adaptation, either independently or through the common ancestor of these species.
Sequence protein identification by randomized sequence database and transcriptome mass spectrometry (SPIDER-TMS): from manual to automatic application of a 'de novo sequencing' approach.

Science.gov (United States)

Pascale, Raffaella; Grossi, Gerarda; Cruciani, Gabriele; Mecca, Giansalvatore; Santoro, Donatello; Sarli Calace, Renzo; Falabella, Patrizia; Bianco, Giuliana

Sequence protein identification by a randomized sequence database and transcriptome mass spectrometry software package has been developed at the University of Basilicata in Potenza (Italy) and designed to facilitate the determination of the amino acid sequence of a peptide as well as an unequivocal identification of proteins in a high-throughput manner with enormous advantages of time, economical resource and expertise. The software package is a valid tool for the automation of a de novo sequencing approach, overcoming the main limits and a versatile platform useful in the proteomic field for an unequivocal identification of proteins, starting from tandem mass spectrometry data. The strength of this software is that it is a user-friendly and non-statistical approach, so protein identification can be considered unambiguous.
On the relationship between residue structural environment and sequence conservation in proteins.

Science.gov (United States)

Liu, Jen-Wei; Lin, Jau-Ji; Cheng, Chih-Wen; Lin, Yu-Feng; Hwang, Jenn-Kang; Huang, Tsun-Tsao

2017-09-01

Residues that are crucial to protein function or structure are usually evolutionarily conserved. To identify the important residues in protein, sequence conservation is estimated, and current methods rely upon the unbiased collection of homologous sequences. Surprisingly, our previous studies have shown that the sequence conservation is closely correlated with the weighted contact number (WCN), a measure of packing density for residue's structural environment, calculated only based on the C α positions of a protein structure. Moreover, studies have shown that sequence conservation is correlated with environment-related structural properties calculated based on different protein substructures, such as a protein's all atoms, backbone atoms, side-chain atoms, or side-chain centroid. To know whether the C α atomic positions are adequate to show the relationship between residue environment and sequence conservation or not, here we compared C α atoms with other substructures in their contributions to the sequence conservation. Our results show that C α positions are substantially equivalent to the other substructures in calculations of various measures of residue environment. As a result, the overlapping contributions between C α atoms and the other substructures are high, yielding similar structure-conservation relationship. Take the WCN as an example, the average overlapping contribution to sequence conservation is 87% between C α and all-atom substructures. These results indicate that only C α atoms of a protein structure could reflect sequence conservation at the residue level. © 2017 Wiley Periodicals, Inc.
SAAS: Short Amino Acid Sequence - A Promising Protein Secondary Structure Prediction Method of Single Sequence

Directory of Open Access Journals (Sweden)

Zhou Yuan Wu

2013-07-01

Full Text Available In statistical methods of predicting protein secondary structure, many researchers focus on single amino acid frequencies in α-helices, β-sheets, and so on, or the impact near amino acids on an amino acid forming a secondary structure. But the paper considers a short sequence of amino acids (3, 4, 5 or 6 amino acids as integer, and statistics short sequence's probability forming secondary structure. Also, many researchers select low homologous sequences as statistical database. But this paper select whole PDB database. In this paper we propose a strategy to predict protein secondary structure using simple statistical method. Numerical computation shows that, short amino acids sequence as integer to statistics, which can easy see trend of short sequence forming secondary structure, and it will work well to select large statistical database (whole PDB database without considering homologous, and Q3 accuracy is ca. 74% using this paper proposed simple statistical method, but accuracy of others statistical methods is less than 70%.
Computational identification of MoRFs in protein sequences.

Science.gov (United States)

Malhis, Nawar; Gsponer, Jörg

2015-06-01

Intrinsically disordered regions of proteins play an essential role in the regulation of various biological processes. Key to their regulatory function is the binding of molecular recognition features (MoRFs) to globular protein domains in a process known as a disorder-to-order transition. Predicting the location of MoRFs in protein sequences with high accuracy remains an important computational challenge. In this study, we introduce MoRFCHiBi, a new computational approach for fast and accurate prediction of MoRFs in protein sequences. MoRFCHiBi combines the outcomes of two support vector machine (SVM) models that take advantage of two different kernels with high noise tolerance. The first, SVMS, is designed to extract maximal information from the general contrast in amino acid compositions between MoRFs, their surrounding regions (Flanks), and the remainders of the sequences. The second, SVMT, is used to identify similarities between regions in a query sequence and MoRFs of the training set. We evaluated the performance of our predictor by comparing its results with those of two currently available MoRF predictors, MoRFpred and ANCHOR. Using three test sets that have previously been collected and used to evaluate MoRFpred and ANCHOR, we demonstrate that MoRFCHiBi outperforms the other predictors with respect to different evaluation metrics. In addition, MoRFCHiBi is downloadable and fast, which makes it useful as a component in other computational prediction tools. http://www.chibi.ubc.ca/morf/. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Preliminary Genomic Characterization of Ten Hardwood Tree Species from Multiplexed Low Coverage Whole Genome Sequencing.

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Margaret Staton

Full Text Available Forest health issues are on the rise in the United States, resulting from introduction of alien pests and diseases, coupled with abiotic stresses related to climate change. Increasingly, forest scientists are finding genetic/genomic resources valuable in addressing forest health issues. For a set of ten ecologically and economically important native hardwood tree species representing a broad phylogenetic spectrum, we used low coverage whole genome sequencing from multiplex Illumina paired ends to economically profile their genomic content. For six species, the genome content was further analyzed by flow cytometry in order to determine the nuclear genome size. Sequencing yielded a depth of 0.8X to 7.5X, from which in silico analysis yielded preliminary estimates of gene and repetitive sequence content in the genome for each species. Thousands of genomic SSRs were identified, with a clear predisposition toward dinucleotide repeats and AT-rich repeat motifs. Flanking primers were designed for SSR loci for all ten species, ranging from 891 loci in sugar maple to 18,167 in redbay. In summary, we have demonstrated that useful preliminary genome information including repeat content, gene content and useful SSR markers can be obtained at low cost and time input from a single lane of Illumina multiplex sequence.
MannDB – A microbial database of automated protein sequence analyses and evidence integration for protein characterization

Directory of Open Access Journals (Sweden)

Kuczmarski Thomas A

2006-10-01

Full Text Available Abstract Background MannDB was created to meet a need for rapid, comprehensive automated protein sequence analyses to support selection of proteins suitable as targets for driving the development of reagents for pathogen or protein toxin detection. Because a large number of open-source tools were needed, it was necessary to produce a software system to scale the computations for whole-proteome analysis. Thus, we built a fully automated system for executing software tools and for storage, integration, and display of automated protein sequence analysis and annotation data. Description MannDB is a relational database that organizes data resulting from fully automated, high-throughput protein-sequence analyses using open-source tools. Types of analyses provided include predictions of cleavage, chemical properties, classification, features, functional assignment, post-translational modifications, motifs, antigenicity, and secondary structure. Proteomes (lists of hypothetical and known proteins are downloaded and parsed from Genbank and then inserted into MannDB, and annotations from SwissProt are downloaded when identifiers are found in the Genbank entry or when identical sequences are identified. Currently 36 open-source tools are run against MannDB protein sequences either on local systems or by means of batch submission to external servers. In addition, BLAST against protein entries in MvirDB, our database of microbial virulence factors, is performed. A web client browser enables viewing of computational results and downloaded annotations, and a query tool enables structured and free-text search capabilities. When available, links to external databases, including MvirDB, are provided. MannDB contains whole-proteome analyses for at least one representative organism from each category of biological threat organism listed by APHIS, CDC, HHS, NIAID, USDA, USFDA, and WHO. Conclusion MannDB comprises a large number of genomes and comprehensive protein
Nonlinear analysis of sequence repeats of multi-domain proteins

Energy Technology Data Exchange (ETDEWEB)

Huang Yanzhao [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Li Mingfeng [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Xiao Yi [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China)]. E-mail: lmf_bill@sina.com

2007-11-15

Many multi-domain proteins have repetitive three-dimensional structures but nearly-random amino acid sequences. In the present paper, by using a modified recurrence plot proposed by us previously, we show that these amino acid sequences have hidden repetitions in fact. These results indicate that the repetitive domain structures are encoded by the repetitive sequences. This also gives a method to detect the repetitive domain structures directly from amino acid sequences.
The SWISS-PROT protein sequence data bank

OpenAIRE

Bairoch, Amos; Boeckmann, Brigitte

1992-01-01

SWISS-PROT is an annotated protein sequence database established in 1986 and maintained collaboratively, since 1988, by the Department of Medical Biochemistry of the University of Geneva and the EMBL Data Library
Using sequence similarity networks for visualization of relationships across diverse protein superfamilies.

Directory of Open Access Journals (Sweden)

Holly J Atkinson

Full Text Available The dramatic increase in heterogeneous types of biological data--in particular, the abundance of new protein sequences--requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity--GPCRs and kinases from humans, and the crotonase superfamily of enzymes--we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships.

Using sequence similarity networks for visualization of relationships across diverse protein superfamilies.

Science.gov (United States)

Atkinson, Holly J; Morris, John H; Ferrin, Thomas E; Babbitt, Patricia C

2009-01-01

The dramatic increase in heterogeneous types of biological data--in particular, the abundance of new protein sequences--requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity--GPCRs and kinases from humans, and the crotonase superfamily of enzymes--we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships.
PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.

Directory of Open Access Journals (Sweden)

Huilin Wang

Full Text Available X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed 'PredPPCrys' using the support vector machine (SVM. Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I. Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II, which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization
Sequence-based prediction of protein-binding sites in DNA: comparative study of two SVM models.

Science.gov (United States)

Park, Byungkyu; Im, Jinyong; Tuvshinjargal, Narankhuu; Lee, Wook; Han, Kyungsook

2014-11-01

As many structures of protein-DNA complexes have been known in the past years, several computational methods have been developed to predict DNA-binding sites in proteins. However, its inverse problem (i.e., predicting protein-binding sites in DNA) has received much less attention. One of the reasons is that the differences between the interaction propensities of nucleotides are much smaller than those between amino acids. Another reason is that DNA exhibits less diverse sequence patterns than protein. Therefore, predicting protein-binding DNA nucleotides is much harder than predicting DNA-binding amino acids. We computed the interaction propensity (IP) of nucleotide triplets with amino acids using an extensive dataset of protein-DNA complexes, and developed two support vector machine (SVM) models that predict protein-binding nucleotides from sequence data alone. One SVM model predicts protein-binding nucleotides using DNA sequence data alone, and the other SVM model predicts protein-binding nucleotides using both DNA and protein sequences. In a 10-fold cross-validation with 1519 DNA sequences, the SVM model that uses DNA sequence data only predicted protein-binding nucleotides with an accuracy of 67.0%, an F-measure of 67.1%, and a Matthews correlation coefficient (MCC) of 0.340. With an independent dataset of 181 DNAs that were not used in training, it achieved an accuracy of 66.2%, an F-measure 66.3% and a MCC of 0.324. Another SVM model that uses both DNA and protein sequences achieved an accuracy of 69.6%, an F-measure of 69.6%, and a MCC of 0.383 in a 10-fold cross-validation with 1519 DNA sequences and 859 protein sequences. With an independent dataset of 181 DNAs and 143 proteins, it showed an accuracy of 67.3%, an F-measure of 66.5% and a MCC of 0.329. Both in cross-validation and independent testing, the second SVM model that used both DNA and protein sequence data showed better performance than the first model that used DNA sequence data. To the best of
Analysis of long-range correlation in sequences data of proteins

Directory of Open Access Journals (Sweden)

ADRIANA ISVORAN

2007-04-01

Full Text Available The results presented here suggest the existence of correlations in the sequence data of proteins. 32 proteins, both globular and fibrous, both monomeric and polymeric, were analyzed. The primary structures of these proteins were treated as time series. Three spatial series of data for each sequence of a protein were generated from numerical correspondences between each amino acid and a physical property associated with it, i.e., its electric charge, its polar character and its dipole moment. For each series, the spectral coefficient, the scaling exponent and the Hurst coefficient were determined. The values obtained for these coefficients revealed non-randomness in the series of data.
Automatic discovery of cross-family sequence features associated with protein function

Directory of Open Access Journals (Sweden)

Krings Andrea

2006-01-01

Full Text Available Abstract Background Methods for predicting protein function directly from amino acid sequences are useful tools in the study of uncharacterised protein families and in comparative genomics. Until now, this problem has been approached using machine learning techniques that attempt to predict membership, or otherwise, to predefined functional categories or subcellular locations. A potential drawback of this approach is that the human-designated functional classes may not accurately reflect the underlying biology, and consequently important sequence-to-function relationships may be missed. Results We show that a self-supervised data mining approach is able to find relationships between sequence features and functional annotations. No preconceived ideas about functional categories are required, and the training data is simply a set of protein sequences and their UniProt/Swiss-Prot annotations. The main technical aspect of the approach is the co-evolution of amino acid-based regular expressions and keyword-based logical expressions with genetic programming. Our experiments on a strictly non-redundant set of eukaryotic proteins reveal that the strongest and most easily detected sequence-to-function relationships are concerned with targeting to various cellular compartments, which is an area already well studied both experimentally and computationally. Of more interest are a number of broad functional roles which can also be correlated with sequence features. These include inhibition, biosynthesis, transcription and defence against bacteria. Despite substantial overlaps between these functions and their corresponding cellular compartments, we find clear differences in the sequence motifs used to predict some of these functions. For example, the presence of polyglutamine repeats appears to be linked more strongly to the "transcription" function than to the general "nuclear" function/location. Conclusion We have developed a novel and useful approach for
Protein sequences from mastodon and Tyrannosaurus rex revealed by mass spectrometry.

Science.gov (United States)

Asara, John M; Schweitzer, Mary H; Freimark, Lisa M; Phillips, Matthew; Cantley, Lewis C

2007-04-13

Fossilized bones from extinct taxa harbor the potential for obtaining protein or DNA sequences that could reveal evolutionary links to extant species. We used mass spectrometry to obtain protein sequences from bones of a 160,000- to 600,000-year-old extinct mastodon (Mammut americanum) and a 68-million-year-old dinosaur (Tyrannosaurus rex). The presence of T. rex sequences indicates that their peptide bonds were remarkably stable. Mass spectrometry can thus be used to determine unique sequences from ancient organisms from peptide fragmentation patterns, a valuable tool to study the evolution and adaptation of ancient taxa from which genomic sequences are unlikely to be obtained.
Structural insights and ab initio sequencing within the DING proteins family

International Nuclear Information System (INIS)

Elias, Mikael; Liebschner, Dorothee; Gotthard, Guillaume; Chabriere, Eric

2011-01-01

DING proteins constitute a recently discovered protein family that is ubiquitous in eukaryotes. The structural insights and the physiological involvements of these intriguing proteins are hereby deciphered. DING proteins constitute an intriguing family of phosphate-binding proteins that was identified in a wide range of organisms, from prokaryotes and archae to eukaryotes. Despite their seemingly ubiquitous occurrence in eukaryotes, their encoding genes are missing from sequenced genomes. Such a lack has considerably hampered functional studies. In humans, these proteins have been related to several diseases, like atherosclerosis, kidney stones, inflammation processes and HIV inhibition. The human phosphate binding protein is a human representative of the DING family that was serendipitously discovered from human plasma. An original approach was developed to determine ab initio the complete and exact sequence of this 38 kDa protein by utilizing mass spectrometry and X-ray data in tandem. Taking advantage of this first complete eukaryotic DING sequence, a immunohistochemistry study was undertaken to check the presence of DING proteins in various mice tissues, revealing that these proteins are widely expressed. Finally, the structure of a bacterial representative from Pseudomonas fluorescens was solved at sub-angstrom resolution, allowing the molecular mechanism of the phosphate binding in these high-affinity proteins to be elucidated
Structural insights and ab initio sequencing within the DING proteins family

Energy Technology Data Exchange (ETDEWEB)

Elias, Mikael, E-mail: mikael.elias@weizmann.ac.il [Weizmann Institute of Science, Rehovot (Israel); Liebschner, Dorothee [CRM2, Nancy Université (France); Gotthard, Guillaume; Chabriere, Eric [AFMB, Université Aix-Marseille II (France)

2011-01-01

DING proteins constitute a recently discovered protein family that is ubiquitous in eukaryotes. The structural insights and the physiological involvements of these intriguing proteins are hereby deciphered. DING proteins constitute an intriguing family of phosphate-binding proteins that was identified in a wide range of organisms, from prokaryotes and archae to eukaryotes. Despite their seemingly ubiquitous occurrence in eukaryotes, their encoding genes are missing from sequenced genomes. Such a lack has considerably hampered functional studies. In humans, these proteins have been related to several diseases, like atherosclerosis, kidney stones, inflammation processes and HIV inhibition. The human phosphate binding protein is a human representative of the DING family that was serendipitously discovered from human plasma. An original approach was developed to determine ab initio the complete and exact sequence of this 38 kDa protein by utilizing mass spectrometry and X-ray data in tandem. Taking advantage of this first complete eukaryotic DING sequence, a immunohistochemistry study was undertaken to check the presence of DING proteins in various mice tissues, revealing that these proteins are widely expressed. Finally, the structure of a bacterial representative from Pseudomonas fluorescens was solved at sub-angstrom resolution, allowing the molecular mechanism of the phosphate binding in these high-affinity proteins to be elucidated.
Solving Classification Problems for Large Sets of Protein Sequences with the Example of Hox and ParaHox Proteins

Directory of Open Access Journals (Sweden)

Stefanie D. Hueber

2016-02-01

Full Text Available Phylogenetic methods are key to providing models for how a given protein family evolved. However, these methods run into difficulties when sequence divergence is either too low or too high. Here, we provide a case study of Hox and ParaHox proteins so that additional insights can be gained using a new computational approach to help solve old classification problems. For two (Gsx and Cdx out of three ParaHox proteins the assignments differ between the currently most established view and four alternative scenarios. We use a non-phylogenetic, pairwise-sequence-similarity-based method to assess which of the previous predictions, if any, are best supported by the sequence-similarity relationships between Hox and ParaHox proteins. The overall sequence-similarities show Gsx to be most similar to Hox2–3, and Cdx to be most similar to Hox4–8. The results indicate that a purely pairwise-sequence-similarity-based approach can provide additional information not only when phylogenetic inference methods have insufficient information to provide reliable classifications (as was shown previously for central Hox proteins, but also when the sequence variation is so high that the resulting phylogenetic reconstructions are likely plagued by long-branch-attraction artifacts.
Protein Science by DNA Sequencing: How Advances in Molecular Biology Are Accelerating Biochemistry.

Science.gov (United States)

Higgins, Sean A; Savage, David F

2018-01-09

A fundamental goal of protein biochemistry is to determine the sequence-function relationship, but the vastness of sequence space makes comprehensive evaluation of this landscape difficult. However, advances in DNA synthesis and sequencing now allow researchers to assess the functional impact of every single mutation in many proteins, but challenges remain in library construction and the development of general assays applicable to a diverse range of protein functions. This Perspective briefly outlines the technical innovations in DNA manipulation that allow massively parallel protein biochemistry and then summarizes the methods currently available for library construction and the functional assays of protein variants. Areas in need of future innovation are highlighted with a particular focus on assay development and the use of computational analysis with machine learning to effectively traverse the sequence-function landscape. Finally, applications in the fundamentals of protein biochemistry, disease prediction, and protein engineering are presented.
An algorithm to find all palindromic sequences in proteins

Indian Academy of Sciences (India)

2013-01-20

Jan 20, 2013 ... 1976; Karrer and Gall 1976; Vogt and Braun 1976) and (iii) in the formation of hairpin loops in the newly transcribed RNA. Palindromic sequences are observed in various classes of proteins like histones (Cheng et al. 1989), prion proteins (Sulkowski 1992; Kazim 1993),. DNA-binding proteins (Suzuki 1992; ...
Overview of recurrent chromosomal losses in retinoblastoma detected by low coverage next generation sequencing

Science.gov (United States)

García-Chequer, A.J.; Méndez-Tenorio, A.; Olguín-Ruiz, G.; Sánchez-Vallejo, C.; Isa, P.; Arias, C.F.; Torres, J.; Hernández-Angeles, A.; Ramírez-Ortiz, M.A.; Lara, C.; Cabrera-Muñoz, M.L.; Sadowinski-Pine, S.; Bravo-Ortiz, J.C.; Ramón-García, G.; Diegopérez-Ramírez, J.; Ramírez-Reyes, G.; Casarrubias-Islas, R.; Ramírez, J.; Orjuela, M.A.; Ponce-Castañeda, M.V.

2016-01-01

Genes are frequently lost or gained in malignant tumors and the analysis of these changes can be informative about the underlying tumor biology. Retinoblastoma is a pediatric intraocular malignancy, and since deletions in chromosome 13 have been described in this tumor, we performed genome wide sequencing with the Illumina platform to test whether recurrent losses could be detected in low coverage data from DNA pools of Rb cases. An in silico reference profile for each pool was created from the human genome sequence GRCh37p5; a chromosome integrity score and a graphics 40 Kb window analysis approach, allowed us to identify with high resolution previously reported non random recurrent losses in all chromosomes of these tumors. We also found a pattern of gains and losses associated to clear and dark cytogenetic bands respectively. We further analyze a pool of medulloblastoma and found a more stable genomic profile and previously reported losses in this tumor. This approach facilitates identification of recurrent deletions from many patients that may be biological relevant for tumor development. PMID:26883451
3D representations of amino acids—applications to protein sequence comparison and classification

Directory of Open Access Journals (Sweden)

Jie Li

2014-08-01

Full Text Available The amino acid sequence of a protein is the key to understanding its structure and ultimately its function in the cell. This paper addresses the fundamental issue of encoding amino acids in ways that the representation of such a protein sequence facilitates the decoding of its information content. We show that a feature-based representation in a three-dimensional (3D space derived from amino acid substitution matrices provides an adequate representation that can be used for direct comparison of protein sequences based on geometry. We measure the performance of such a representation in the context of the protein structural fold prediction problem. We compare the results of classifying different sets of proteins belonging to distinct structural folds against classifications of the same proteins obtained from sequence alone or directly from structural information. We find that sequence alone performs poorly as a structure classifier. We show in contrast that the use of the three dimensional representation of the sequences significantly improves the classification accuracy. We conclude with a discussion of the current limitations of such a representation and with a description of potential improvements.
Sequence- and interactome-based prediction of viral protein hotspots targeting host proteins: a case study for HIV Nef.

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Mahdi Sarmady

Full Text Available Virus proteins alter protein pathways of the host toward the synthesis of viral particles by breaking and making edges via binding to host proteins. In this study, we developed a computational approach to predict viral sequence hotspots for binding to host proteins based on sequences of viral and host proteins and literature-curated virus-host protein interactome data. We use a motif discovery algorithm repeatedly on collections of sequences of viral proteins and immediate binding partners of their host targets and choose only those motifs that are conserved on viral sequences and highly statistically enriched among binding partners of virus protein targeted host proteins. Our results match experimental data on binding sites of Nef to host proteins such as MAPK1, VAV1, LCK, HCK, HLA-A, CD4, FYN, and GNB2L1 with high statistical significance but is a poor predictor of Nef binding sites on highly flexible, hoop-like regions. Predicted hotspots recapture CD8 cell epitopes of HIV Nef highlighting their importance in modulating virus-host interactions. Host proteins potentially targeted or outcompeted by Nef appear crowding the T cell receptor, natural killer cell mediated cytotoxicity, and neurotrophin signaling pathways. Scanning of HIV Nef motifs on multiple alignments of hepatitis C protein NS5A produces results consistent with literature, indicating the potential value of the hotspot discovery in advancing our understanding of virus-host crosstalk.
Sequence-based prediction of protein protein interaction using a deep-learning algorithm.

Science.gov (United States)

Sun, Tanlin; Zhou, Bo; Lai, Luhua; Pei, Jianfeng

2017-05-25

Protein-protein interactions (PPIs) are critical for many biological processes. It is therefore important to develop accurate high-throughput methods for identifying PPI to better understand protein function, disease occurrence, and therapy design. Though various computational methods for predicting PPI have been developed, their robustness for prediction with external datasets is unknown. Deep-learning algorithms have achieved successful results in diverse areas, but their effectiveness for PPI prediction has not been tested. We used a stacked autoencoder, a type of deep-learning algorithm, to study the sequence-based PPI prediction. The best model achieved an average accuracy of 97.19% with 10-fold cross-validation. The prediction accuracies for various external datasets ranged from 87.99% to 99.21%, which are superior to those achieved with previous methods. To our knowledge, this research is the first to apply a deep-learning algorithm to sequence-based PPI prediction, and the results demonstrate its potential in this field.
Prediction of protein hydration sites from sequence by modular neural networks

DEFF Research Database (Denmark)

Ehrlich, L.; Reczko, M.; Bohr, Henrik

1998-01-01

The hydration properties of a protein are important determinants of its structure and function. Here, modular neural networks are employed to predict ordered hydration sites using protein sequence information. First, secondary structure and solvent accessibility are predicted from sequence with two...... separate neural networks. These predictions are used as input together with protein sequences for networks predicting hydration of residues, backbone atoms and sidechains. These networks are teined with protein crystal structures. The prediction of hydration is improved by adding information on secondary...... structure and solvent accessibility and, using actual values of these properties, redidue hydration can be predicted to 77% accuracy with a Metthews coefficient of 0.43. However, predicted property data with an accuracy of 60-70% result in less than half the improvement in predictive performance observed...
Protein Function Prediction Based on Sequence and Structure Information

KAUST Repository

Smaili, Fatima Z.

2016-01-01

operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching
In Silico Characterization of Pectate Lyase Protein Sequences from Different Source Organisms

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Amit Kumar Dubey

2010-01-01

Full Text Available A total of 121 protein sequences of pectate lyases were subjected to homology search, multiple sequence alignment, phylogenetic tree construction, and motif analysis. The phylogenetic tree constructed revealed different clusters based on different source organisms representing bacterial, fungal, plant, and nematode pectate lyases. The multiple accessions of bacterial, fungal, nematode, and plant pectate lyase protein sequences were placed closely revealing a sequence level similarity. The multiple sequence alignment of these pectate lyase protein sequences from different source organisms showed conserved regions at different stretches with maximum homology from amino acid residues 439–467, 715–816, and 829–910 which could be used for designing degenerate primers or probes specific for pectate lyases. The motif analysis revealed a conserved Pec_Lyase_C domain uniformly observed in all pectate lyases irrespective of variable sources suggesting its possible role in structural and enzymatic functions.
Sequence alignment reveals possible MAPK docking motifs on HIV proteins.

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Perry Evans

Full Text Available Over the course of HIV infection, virus replication is facilitated by the phosphorylation of HIV proteins by human ERK1 and ERK2 mitogen-activated protein kinases (MAPKs. MAPKs are known to phosphorylate their substrates by first binding with them at a docking site. Docking site interactions could be viable drug targets because the sequences guiding them are more specific than phosphorylation consensus sites. In this study we use multiple bioinformatics tools to discover candidate MAPK docking site motifs on HIV proteins known to be phosphorylated by MAPKs, and we discuss the possibility of targeting docking sites with drugs. Using sequence alignments of HIV proteins of different subtypes, we show that MAPK docking patterns previously described for human proteins appear on the HIV matrix, Tat, and Vif proteins in a strain dependent manner, but are absent from HIV Rev and appear on all HIV Nef strains. We revise the regular expressions of previously annotated MAPK docking patterns in order to provide a subtype independent motif that annotates all HIV proteins. One revision is based on a documented human variant of one of the substrate docking motifs, and the other reduces the number of required basic amino acids in the standard docking motifs from two to one. The proposed patterns are shown to be consistent with in silico docking between ERK1 and the HIV matrix protein. The motif usage on HIV proteins is sufficiently different from human proteins in amino acid sequence similarity to allow for HIV specific targeting using small-molecule drugs.
Feature Selection and the Class Imbalance Problem in Predicting Protein Function from Sequence

NARCIS (Netherlands)

Al-Shahib, A.; Breitling, R.; Gilbert, D.

2005-01-01

Abstract: When the standard approach to predict protein function by sequence homology fails, other alternative methods can be used that require only the amino acid sequence for predicting function. One such approach uses machine learning to predict protein function directly from amino acid sequence

Functional analysis of bipartite begomovirus coat protein promoter sequences

International Nuclear Information System (INIS)

Lacatus, Gabriela; Sunter, Garry

2008-01-01

We demonstrate that the AL2 gene of Cabbage leaf curl virus (CaLCuV) activates the CP promoter in mesophyll and acts to derepress the promoter in vascular tissue, similar to that observed for Tomato golden mosaic virus (TGMV). Binding studies indicate that sequences mediating repression and activation of the TGMV and CaLCuV CP promoter specifically bind different nuclear factors common to Nicotiana benthamiana, spinach and tomato. However, chromatin immunoprecipitation demonstrates that TGMV AL2 can interact with both sequences independently. Binding of nuclear protein(s) from different crop species to viral sequences conserved in both bipartite and monopartite begomoviruses, including TGMV, CaLCuV, Pepper golden mosaic virus and Tomato yellow leaf curl virus suggests that bipartite begomoviruses bind common host factors to regulate the CP promoter. This is consistent with a model in which AL2 interacts with different components of the cellular transcription machinery that bind viral sequences important for repression and activation of begomovirus CP promoters
Protein sequencing via nanopore based devices: a nanofluidics perspective

Science.gov (United States)

Chinappi, Mauro; Cecconi, Fabio

2018-05-01

Proteins perform a huge number of central functions in living organisms, thus all the new techniques allowing their precise, fast and accurate characterization at single-molecule level certainly represent a burst in proteomics with important biomedical impact. In this review, we describe the recent progresses in the developing of nanopore based devices for protein sequencing. We start with a critical analysis of the main technical requirements for nanopore protein sequencing, summarizing some ideas and methodologies that have recently appeared in the literature. In the last sections, we focus on the physical modelling of the transport phenomena occurring in nanopore based devices. The multiscale nature of the problem is discussed and, in this respect, some of the main possible computational approaches are illustrated.
UET: a database of evolutionarily-predicted functional determinants of protein sequences that cluster as functional sites in protein structures.

Science.gov (United States)

Lua, Rhonald C; Wilson, Stephen J; Konecki, Daniel M; Wilkins, Angela D; Venner, Eric; Morgan, Daniel H; Lichtarge, Olivier

2016-01-04

The structure and function of proteins underlie most aspects of biology and their mutational perturbations often cause disease. To identify the molecular determinants of function as well as targets for drugs, it is central to characterize the important residues and how they cluster to form functional sites. The Evolutionary Trace (ET) achieves this by ranking the functional and structural importance of the protein sequence positions. ET uses evolutionary distances to estimate functional distances and correlates genotype variations with those in the fitness phenotype. Thus, ET ranks are worse for sequence positions that vary among evolutionarily closer homologs but better for positions that vary mostly among distant homologs. This approach identifies functional determinants, predicts function, guides the mutational redesign of functional and allosteric specificity, and interprets the action of coding sequence variations in proteins, people and populations. Now, the UET database offers pre-computed ET analyses for the protein structure databank, and on-the-fly analysis of any protein sequence. A web interface retrieves ET rankings of sequence positions and maps results to a structure to identify functionally important regions. This UET database integrates several ways of viewing the results on the protein sequence or structure and can be found at http://mammoth.bcm.tmc.edu/uet/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
Candidate mosaic proteins for a pan-filoviral cytotoxic T-Cell lymphocyte vaccine

Energy Technology Data Exchange (ETDEWEB)

Fenimore, Paul W [Los Alamos National Laboratory; Fischer, William M [Los Alamos National Laboratory; Kuiken, Carla [Los Alamos National Laboratory; Foley, Brian T [Los Alamos National Laboratory; Thurmond, J R [Los Alamos National Laboratory; Yusim, K [Los Alamos National Laboratory; Korber, B T [Los Alamos National Laboratory

2008-01-01

than is possible with a wild-type protein, (2) reducing the number of low-prevalence k-mers minimizes the likelihood of undesirable immunodominance, and (3) excluding exogenous k-mers will result in mosaic proteins whose processing for presentation is close to what occurs with wild-type proteins. The first and second applications of the mosaic method were to HIV and Hepatitis C Virus (HCV). HIV is the virus with the largest number of known sequences, and consequently a plethora of information for the CTL vaccine designer to incorporate into their mosaics. Experience with HIV and HCV mosaics supports the validity of the three conjectures above. The available FILV sequences are probably closer to the minimum amount of information needed to make a meaningful mosaic vaccine candidate. There were 532 protein sequences in the National Institutes of Health GenPept database in November 2007 when our reference set was downloaded. These sequences come from both Ebola and Marburg viruses (EBOV and MARV), representing transcripts of all 7 genes. The coverage of viral diversity by the 7 genes is variable, with genes 1 (nucleoprotein, NP), 4 (glycoprotein, GP; soluble glycoprotein, sGP) and 7 (polymerase, L) giving the best coverage. Broadly-protective vaccine candidates for diverse viruses, such as HIV or Hepatitis C virus (HCV) have required pools of antigens. FILV is similar in this regard. While we have designed CTL mosaic proteins using all 7 types of filoviral proteins, only NP, GP and L proteins are reported here. If it were important to include other proteins in a mosaic CTL vaccine, additional sequences would be required to cover the space of known viral diversity.
CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction

KAUST Repository

Cui, Xuefeng; Lu, Zhiwu; Wang, Sheng; Jing-Yan Wang, Jim; Gao, Xin

2016-01-01

Motivation: Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment
Improving pairwise comparison of protein sequences with domain co-occurrence

Science.gov (United States)

Gascuel, Olivier

2018-01-01

Comparing and aligning protein sequences is an essential task in bioinformatics. More specifically, local alignment tools like BLAST are widely used for identifying conserved protein sub-sequences, which likely correspond to protein domains or functional motifs. However, to limit the number of false positives, these tools are used with stringent sequence-similarity thresholds and hence can miss several hits, especially for species that are phylogenetically distant from reference organisms. A solution to this problem is then to integrate additional contextual information to the procedure. Here, we propose to use domain co-occurrence to increase the sensitivity of pairwise sequence comparisons. Domain co-occurrence is a strong feature of proteins, since most protein domains tend to appear with a limited number of other domains on the same protein. We propose a method to take this information into account in a typical BLAST analysis and to construct new domain families on the basis of these results. We used Plasmodium falciparum as a case study to evaluate our method. The experimental findings showed an increase of 14% of the number of significant BLAST hits and an increase of 25% of the proteome area that can be covered with a domain. Our method identified 2240 new domains for which, in most cases, no model of the Pfam database could be linked. Moreover, our study of the quality of the new domains in terms of alignment and physicochemical properties show that they are close to that of standard Pfam domains. Source code of the proposed approach and supplementary data are available at: https://gite.lirmm.fr/menichelli/pairwise-comparison-with-cooccurrence PMID:29293498
Discriminating Microbial Species Using Protein Sequence Properties and Machine Learning

NARCIS (Netherlands)

Shahib, Ali Al-; Gilbert, David; Breitling, Rainer

2007-01-01

Much work has been done to identify species-specific proteins in sequenced genomes and hence to determine their function. We assumed that such proteins have specific physico-chemical properties that will discriminate them from proteins in other species. In this paper, we examine the validity of this
Protein secondary structure prediction for a single-sequence using hidden semi-Markov models

Directory of Open Access Journals (Sweden)

Borodovsky Mark

2006-03-01

Full Text Available Abstract Background The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algorithms: Single-sequence prediction algorithms imply that information about other (homologous proteins is not available, while algorithms of the second type imply that information about homologous proteins is available, and use it intensively. The single-sequence algorithms could make an important contribution to studies of proteins with no detected homologs, however the accuracy of protein secondary structure prediction from a single-sequence is not as high as when the additional evolutionary information is present. Results In this paper, we further refine and extend the hidden semi-Markov model (HSMM initially considered in the BSPSS algorithm. We introduce an improved residue dependency model by considering the patterns of statistically significant amino acid correlation at structural segment borders. We also derive models that specialize on different sections of the dependency structure and incorporate them into HSMM. In addition, we implement an iterative training method to refine estimates of HSMM parameters. The three-state-per-residue accuracy and other accuracy measures of the new method, IPSSP, are shown to be comparable or better than ones for BSPSS as well as for PSIPRED, tested under the single-sequence condition. Conclusions We have shown that new dependency models and training methods bring further improvements to single-sequence protein secondary structure prediction. The results are obtained under cross-validation conditions using a dataset with no pair of sequences having significant sequence similarity. As new sequences are added to the database it is possible to augment the dependency structure and obtain even higher accuracy. Current and future advances should contribute to the improvement of function prediction for orphan proteins inscrutable
Adhesive proteins of stalked and acorn barnacles display homology with low sequence similarities.

Directory of Open Access Journals (Sweden)

Jaimie-Leigh Jonker

Full Text Available Barnacle adhesion underwater is an important phenomenon to understand for the prevention of biofouling and potential biotechnological innovations, yet so far, identifying what makes barnacle glue proteins 'sticky' has proved elusive. Examination of a broad range of species within the barnacles may be instructive to identify conserved adhesive domains. We add to extensive information from the acorn barnacles (order Sessilia by providing the first protein analysis of a stalked barnacle adhesive, Lepas anatifera (order Lepadiformes. It was possible to separate the L. anatifera adhesive into at least 10 protein bands using SDS-PAGE. Intense bands were present at approximately 30, 70, 90 and 110 kilodaltons (kDa. Mass spectrometry for protein identification was followed by de novo sequencing which detected 52 peptides of 7-16 amino acids in length. None of the peptides matched published or unpublished transcriptome sequences, but some amino acid sequence similarity was apparent between L. anatifera and closely-related Dosima fascicularis. Antibodies against two acorn barnacle proteins (ab-cp-52k and ab-cp-68k showed cross-reactivity in the adhesive glands of L. anatifera. We also analysed the similarity of adhesive proteins across several barnacle taxa, including Pollicipes pollicipes (a stalked barnacle in the order Scalpelliformes. Sequence alignment of published expressed sequence tags clearly indicated that P. pollicipes possesses homologues for the 19 kDa and 100 kDa proteins in acorn barnacles. Homology aside, sequence similarity in amino acid and gene sequences tended to decline as taxonomic distance increased, with minimum similarities of 18-26%, depending on the gene. The results indicate that some adhesive proteins (e.g. 100 kDa are more conserved within barnacles than others (20 kDa.
Relationships between residue Voronoi volume and sequence conservation in proteins.

Science.gov (United States)

Liu, Jen-Wei; Cheng, Chih-Wen; Lin, Yu-Feng; Chen, Shao-Yu; Hwang, Jenn-Kang; Yen, Shih-Chung

2018-02-01

Functional and biophysical constraints can cause different levels of sequence conservation in proteins. Previously, structural properties, e.g., relative solvent accessibility (RSA) and packing density of the weighted contact number (WCN), have been found to be related to protein sequence conservation (CS). The Voronoi volume has recently been recognized as a new structural property of the local protein structural environment reflecting CS. However, for surface residues, it is sensitive to water molecules surrounding the protein structure. Herein, we present a simple structural determinant termed the relative space of Voronoi volume (RSV); it uses the Voronoi volume and the van der Waals volume of particular residues to quantify the local structural environment. RSV (range, 0-1) is defined as (Voronoi volume-van der Waals volume)/Voronoi volume of the target residue. The concept of RSV describes the extent of available space for every protein residue. RSV and Voronoi profiles with and without water molecules (RSVw, RSV, VOw, and VO) were compared for 554 non-homologous proteins. RSV (without water) showed better Pearson's correlations with CS than did RSVw, VO, or VOw values. The mean correlation coefficient between RSV and CS was 0.51, which is comparable to the correlation between RSA and CS (0.49) and that between WCN and CS (0.56). RSV is a robust structural descriptor with and without water molecules and can quantitatively reflect evolutionary information in a single protein structure. Therefore, it may represent a practical structural determinant to study protein sequence, structure, and function relationships. Copyright © 2017 Elsevier B.V. All rights reserved.
The genome of flax (Linum usitatissimum) assembled de novo from short shotgun sequence reads.

Science.gov (United States)

Wang, Zhiwen; Hobson, Neil; Galindo, Leonardo; Zhu, Shilin; Shi, Daihu; McDill, Joshua; Yang, Linfeng; Hawkins, Simon; Neutelings, Godfrey; Datla, Raju; Lambert, Georgina; Galbraith, David W; Grassa, Christopher J; Geraldes, Armando; Cronk, Quentin C; Cullis, Christopher; Dash, Prasanta K; Kumar, Polumetla A; Cloutier, Sylvie; Sharpe, Andrew G; Wong, Gane K-S; Wang, Jun; Deyholos, Michael K

2012-11-01

Flax (Linum usitatissimum) is an ancient crop that is widely cultivated as a source of fiber, oil and medicinally relevant compounds. To accelerate crop improvement, we performed whole-genome shotgun sequencing of the nuclear genome of flax. Seven paired-end libraries ranging in size from 300 bp to 10 kb were sequenced using an Illumina genome analyzer. A de novo assembly, comprised exclusively of deep-coverage (approximately 94× raw, approximately 69× filtered) short-sequence reads (44-100 bp), produced a set of scaffolds with N(50) =694 kb, including contigs with N(50)=20.1 kb. The contig assembly contained 302 Mb of non-redundant sequence representing an estimated 81% genome coverage. Up to 96% of published flax ESTs aligned to the whole-genome shotgun scaffolds. However, comparisons with independently sequenced BACs and fosmids showed some mis-assembly of regions at the genome scale. A total of 43384 protein-coding genes were predicted in the whole-genome shotgun assembly, and up to 93% of published flax ESTs, and 86% of A. thaliana genes aligned to these predicted genes, indicating excellent coverage and accuracy at the gene level. Analysis of the synonymous substitution rates (K(s) ) observed within duplicate gene pairs was consistent with a recent (5-9 MYA) whole-genome duplication in flax. Within the predicted proteome, we observed enrichment of many conserved domains (Pfam-A) that may contribute to the unique properties of this crop, including agglutinin proteins. Together these results show that de novo assembly, based solely on whole-genome shotgun short-sequence reads, is an efficient means of obtaining nearly complete genome sequence information for some plant species. © 2012 The Authors. The Plant Journal © 2012 Blackwell Publishing Ltd.
Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics

Science.gov (United States)

Faye, Ibrahima; Samir, Brahim Belhaouari; Md Said, Abas

2014-01-01

Bioinformatics has been an emerging area of research for the last three decades. The ultimate aims of bioinformatics were to store and manage the biological data, and develop and analyze computational tools to enhance their understanding. The size of data accumulated under various sequencing projects is increasing exponentially, which presents difficulties for the experimental methods. To reduce the gap between newly sequenced protein and proteins with known functions, many computational techniques involving classification and clustering algorithms were proposed in the past. The classification of protein sequences into existing superfamilies is helpful in predicting the structure and function of large amount of newly discovered proteins. The existing classification results are unsatisfactory due to a huge size of features obtained through various feature encoding methods. In this work, a statistical metric-based feature selection technique has been proposed in order to reduce the size of the extracted feature vector. The proposed method of protein classification shows significant improvement in terms of performance measure metrics: accuracy, sensitivity, specificity, recall, F-measure, and so forth. PMID:25045727
On the dynamical incompleteness of the Protein Data Bank.

Science.gov (United States)

Marino-Buslje, Cristina; Monzon, Alexander Miguel; Zea, Diego Javier; Fornasari, María Silvina; Parisi, Gustavo

2017-08-02

Major scientific challenges that are beyond the capability of individuals need to be addressed by multi-disciplinary and multi-institutional consortia. Examples of these endeavours include the Human Genome Project, and more recently, the Structural Genomics (SG) initiative. The SG initiative pursues the expansion of structural coverage to include at least one structural representative for each protein family to derive the remaining structures using homology modelling. However, biological function is inherently connected with protein dynamics that can be studied by knowing different structures of the same protein. This ensemble of structures provides snapshots of protein conformational diversity under native conditions. Thus, sequence redundancy in the Protein Data Bank (PDB) (i.e. crystallization of the same protein under different conditions) is therefore an essential input contributing to experimentally based studies of protein dynamics and providing insights into protein function. In this work, we show that sequence redundancy, a key concept for exploring protein dynamics, is highly biased and fundamentally incomplete in the PDB. Additionally, our results show that dynamical behaviour of proteins cannot be inferred using homologous proteins. Minor to moderate changes in sequence can produce great differences in dynamical behaviour. Nonetheless, the structural and dynamical incompleteness of the PDB is apparently unrelated concepts in SG. While the first could be reversed by promoting the extension of the structural coverage, we would like to emphasize that further focused efforts will be needed to amend the incompleteness of the PDB in terms of dynamical information content, essential to fully understand protein function. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Binning metagenomic contigs by coverage and composition

NARCIS (Netherlands)

Alneberg, J.; Bjarnason, B.S.; Bruijn, de I.; Schirmer, M.; Quick, J.; Ijaz, U.Z.; Lahti, L.M.; Loman, N.J.; Andersson, A.F.; Quince, C.

2014-01-01

Shotgun sequencing enables the reconstruction of genomes from complex microbial communities, but because assembly does not reconstruct entire genomes, it is necessary to bin genome fragments. Here we present CONCOCT, a new algorithm that combines sequence composition and coverage across multiple
Investigating Correlation between Protein Sequence Similarity and Semantic Similarity Using Gene Ontology Annotations.

Science.gov (United States)

Ikram, Najmul; Qadir, Muhammad Abdul; Afzal, Muhammad Tanvir

2018-01-01

Sequence similarity is a commonly used measure to compare proteins. With the increasing use of ontologies, semantic (function) similarity is getting importance. The correlation between these measures has been applied in the evaluation of new semantic similarity methods, and in protein function prediction. In this research, we investigate the relationship between the two similarity methods. The results suggest absence of a strong correlation between sequence and semantic similarities. There is a large number of proteins with low sequence similarity and high semantic similarity. We observe that Pearson's correlation coefficient is not sufficient to explain the nature of this relationship. Interestingly, the term semantic similarity values above 0 and below 1 do not seem to play a role in improving the correlation. That is, the correlation coefficient depends only on the number of common GO terms in proteins under comparison, and the semantic similarity measurement method does not influence it. Semantic similarity and sequence similarity have a distinct behavior. These findings are of significant effect for future works on protein comparison, and will help understand the semantic similarity between proteins in a better way.
Sequence heterogeneity accelerates protein search for targets on DNA

International Nuclear Information System (INIS)

Shvets, Alexey A.; Kolomeisky, Anatoly B.

2015-01-01

The process of protein search for specific binding sites on DNA is fundamentally important since it marks the beginning of all major biological processes. We present a theoretical investigation that probes the role of DNA sequence symmetry, heterogeneity, and chemical composition in the protein search dynamics. Using a discrete-state stochastic approach with a first-passage events analysis, which takes into account the most relevant physical-chemical processes, a full analytical description of the search dynamics is obtained. It is found that, contrary to existing views, the protein search is generally faster on DNA with more heterogeneous sequences. In addition, the search dynamics might be affected by the chemical composition near the target site. The physical origins of these phenomena are discussed. Our results suggest that biological processes might be effectively regulated by modifying chemical composition, symmetry, and heterogeneity of a genome
Sequence heterogeneity accelerates protein search for targets on DNA

Energy Technology Data Exchange (ETDEWEB)

Shvets, Alexey A.; Kolomeisky, Anatoly B., E-mail: tolya@rice.edu [Department of Chemistry and Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005 (United States)

2015-12-28

The process of protein search for specific binding sites on DNA is fundamentally important since it marks the beginning of all major biological processes. We present a theoretical investigation that probes the role of DNA sequence symmetry, heterogeneity, and chemical composition in the protein search dynamics. Using a discrete-state stochastic approach with a first-passage events analysis, which takes into account the most relevant physical-chemical processes, a full analytical description of the search dynamics is obtained. It is found that, contrary to existing views, the protein search is generally faster on DNA with more heterogeneous sequences. In addition, the search dynamics might be affected by the chemical composition near the target site. The physical origins of these phenomena are discussed. Our results suggest that biological processes might be effectively regulated by modifying chemical composition, symmetry, and heterogeneity of a genome.
Protein sequences clustering of herpes virus by using Tribe Markov clustering (Tribe-MCL)

Science.gov (United States)

Bustamam, A.; Siswantining, T.; Febriyani, N. L.; Novitasari, I. D.; Cahyaningrum, R. D.

2017-07-01

The herpes virus can be found anywhere and one of the important characteristics is its ability to cause acute and chronic infection at certain times so as a result of the infection allows severe complications occurred. The herpes virus is composed of DNA containing protein and wrapped by glycoproteins. In this work, the Herpes viruses family is classified and analyzed by clustering their protein-sequence using Tribe Markov Clustering (Tribe-MCL) algorithm. Tribe-MCL is an efficient clustering method based on the theory of Markov chains, to classify protein families from protein sequences using pre-computed sequence similarity information. We implement the Tribe-MCL algorithm using an open source program of R. We select 24 protein sequences of Herpes virus obtained from NCBI database. The dataset consists of three types of glycoprotein B, F, and H. Each type has eight herpes virus that infected humans. Based on our simulation using different inflation factor r=1.5, 2, 3 we find a various number of the clusters results. The greater the inflation factor the greater the number of their clusters. Each protein will grouped together in the same type of protein.
A machine learning approach for the identification of odorant binding proteins from sequence-derived properties

Directory of Open Access Journals (Sweden)

Suganthan PN

2007-09-01

Full Text Available Abstract Background Odorant binding proteins (OBPs are believed to shuttle odorants from the environment to the underlying odorant receptors, for which they could potentially serve as odorant presenters. Although several sequence based search methods have been exploited for protein family prediction, less effort has been devoted to the prediction of OBPs from sequence data and this area is more challenging due to poor sequence identity between these proteins. Results In this paper, we propose a new algorithm that uses Regularized Least Squares Classifier (RLSC in conjunction with multiple physicochemical properties of amino acids to predict odorant-binding proteins. The algorithm was applied to the dataset derived from Pfam and GenDiS database and we obtained overall prediction accuracy of 97.7% (94.5% and 98.4% for positive and negative classes respectively. Conclusion Our study suggests that RLSC is potentially useful for predicting the odorant binding proteins from sequence-derived properties irrespective of sequence similarity. Our method predicts 92.8% of 56 odorant binding proteins non-homologous to any protein in the swissprot database and 97.1% of the 414 independent dataset proteins, suggesting the usefulness of RLSC method for facilitating the prediction of odorant binding proteins from sequence information.
Aligning protein sequence and analysing substitution pattern using ...

Indian Academy of Sciences (India)

Prakash

Aligning protein sequences using a score matrix has became a routine but valuable method in modern biological ..... the amino acids according to their substitution behaviour ...... which may cause great change (e.g. prolonging the helix) in.

Chaos game representation of functional protein sequences, and simulation and multifractal analysis of induced measures

International Nuclear Information System (INIS)

Zu-Guo, Yu; Qian-Jun, Xiao; Long, Shi; Jun-Wu, Yu; Anh, Vo

2010-01-01

Investigating the biological function of proteins is a key aspect of protein studies. Bioinformatic methods become important for studying the biological function of proteins. In this paper, we first give the chaos game representation (CGR) of randomly-linked functional protein sequences, then propose the use of the recurrent iterated function systems (RIFS) in fractal theory to simulate the measure based on their chaos game representations. This method helps to extract some features of functional protein sequences, and furthermore the biological functions of these proteins. Then multifractal analysis of the measures based on the CGRs of randomly-linked functional protein sequences are performed. We find that the CGRs have clear fractal patterns. The numerical results show that the RIFS can simulate the measure based on the CGR very well. The relative standard error and the estimated probability matrix in the RIFS do not depend on the order to link the functional protein sequences. The estimated probability matrices in the RIFS with different biological functions are evidently different. Hence the estimated probability matrices in the RIFS can be used to characterise the difference among linked functional protein sequences with different biological functions. From the values of the D q curves, one sees that these functional protein sequences are not completely random. The D q of all linked functional proteins studied are multifractal-like and sufficiently smooth for the C q (analogous to specific heat) curves to be meaningful. Furthermore, the D q curves of the measure μ based on their CGRs for different orders to link the functional protein sequences are almost identical if q ≥ 0. Finally, the C q curves of all linked functional proteins resemble a classical phase transition at a critical point. (cross-disciplinary physics and related areas of science and technology)
The SBASE protein domain library, release 8.0: a collection of annotated protein sequence segments.

Science.gov (United States)

Murvai, J; Vlahovicek, K; Barta, E; Pongor, S

2001-01-01

SBASE 8.0 is the eighth release of the SBASE library of protein domain sequences that contains 294 898 annotated structural, functional, ligand-binding and topogenic segments of proteins, cross-referenced to most major sequence databases and sequence pattern collections. The entries are clustered into over 2005 statistically validated domain groups (SBASE-A) and 595 non-validated groups (SBASE-B), provided with several WWW-based search and browsing facilities for online use. A domain-search facility was developed, based on non-parametric pattern recognition methods, including artificial neural networks. SBASE 8.0 is freely available by anonymous 'ftp' file transfer from ftp.icgeb.trieste.it. Automated searching of SBASE can be carried out with the WWW servers http://www.icgeb.trieste.it/sbase/ and http://sbase.abc. hu/sbase/.
The nucleotide sequence of human transition protein 1 cDNA

Energy Technology Data Exchange (ETDEWEB)

Luerssen, H; Hoyer-Fender, S; Engel, W [Universitaet Goettingen (West Germany)

1988-08-11

The authors have screened a human testis cDNA library with an oligonucleotide of 81 mer prepared according to a part of the published nucleotide sequence of the rat transition protein TP 1. They have isolated a cDNA clone with the length of 441 bp containing the coding region of 162 bp for human transition protein 1. There is about 84% homology in the coding region of the sequence compared to rat. The human cDNA-clone encodes a polypeptide of 54 amino acids of which 7 are different to that of rat.
Rapid evolution of the sequences and gene repertoires of secreted proteins in bacteria.

Directory of Open Access Journals (Sweden)

Teresa Nogueira

Full Text Available Proteins secreted to the extracellular environment or to the periphery of the cell envelope, the secretome, play essential roles in foraging, antagonistic and mutualistic interactions. We hypothesize that arms races, genetic conflicts and varying selective pressures should lead to the rapid change of sequences and gene repertoires of the secretome. The analysis of 42 bacterial pan-genomes shows that secreted, and especially extracellular proteins, are predominantly encoded in the accessory genome, i.e. among genes not ubiquitous within the clade. Genes encoding outer membrane proteins might engage more frequently in intra-chromosomal gene conversion because they are more often in multi-genic families. The gene sequences encoding the secretome evolve faster than the rest of the genome and in particular at non-synonymous positions. Cell wall proteins in Firmicutes evolve particularly fast when compared with outer membrane proteins of Proteobacteria. Virulence factors are over-represented in the secretome, notably in outer membrane proteins, but cell localization explains more of the variance in substitution rates and gene repertoires than sequence homology to known virulence factors. Accordingly, the repertoires and sequences of the genes encoding the secretome change fast in the clades of obligatory and facultative pathogens and also in the clades of mutualists and free-living bacteria. Our study shows that cell localization shapes genome evolution. In agreement with our hypothesis, the repertoires and the sequences of genes encoding secreted proteins evolve fast. The particularly rapid change of extracellular proteins suggests that these public goods are key players in bacterial adaptation.
Cloning and sequence analysis of cDNA coding for rat nucleolar protein C23

International Nuclear Information System (INIS)

Ghaffari, S.H.; Olson, M.O.J.

1986-01-01

Using synthetic oligonucleotides as primers and probes, the authors have isolated and sequenced cDNA clones encoding protein C23, a putative nucleolus organizer protein. Poly(A + ) RNA was isolated from rat Novikoff hepatoma cells and enriched in C23 mRNA by sucrose density gradient ultracentrifugation. Two deoxyoligonuleotides, a 48- and a 27-mer, were synthesized on the basis of amino acid sequence from the C-terminal half of protein C23 and cDNA sequence data from CHO cell protein. The 48-mer was used a primer for synthesis of cDNA which was then inserted into plasmid pUC9. Transformed bacterial colonies were screened by hybridization with 32 P labeled 27-mer. Two clones among 5000 gave a strong positive signal. Plasmid DNAs from these clones were purified and characterized by blotting and nucleotide sequence analysis. The length of C23 mRNA was estimated to be 3200 bases in a northern blot analysis. The sequence of a 267 b.p. insert shows high homology with the CHO cDNA with only 9 nucleotide differences and an identical amino acid sequence. These studies indicate that this region of the protein is highly conserved
Integrated analysis of RNA-binding protein complexes using in vitro selection and high-throughput sequencing and sequence specificity landscapes (SEQRS).

Science.gov (United States)

Lou, Tzu-Fang; Weidmann, Chase A; Killingsworth, Jordan; Tanaka Hall, Traci M; Goldstrohm, Aaron C; Campbell, Zachary T

2017-04-15

RNA-binding proteins (RBPs) collaborate to control virtually every aspect of RNA function. Tremendous progress has been made in the area of global assessment of RBP specificity using next-generation sequencing approaches both in vivo and in vitro. Understanding how protein-protein interactions enable precise combinatorial regulation of RNA remains a significant problem. Addressing this challenge requires tools that can quantitatively determine the specificities of both individual proteins and multimeric complexes in an unbiased and comprehensive way. One approach utilizes in vitro selection, high-throughput sequencing, and sequence-specificity landscapes (SEQRS). We outline a SEQRS experiment focused on obtaining the specificity of a multi-protein complex between Drosophila RBPs Pumilio (Pum) and Nanos (Nos). We discuss the necessary controls in this type of experiment and examine how the resulting data can be complemented with structural and cell-based reporter assays. Additionally, SEQRS data can be integrated with functional genomics data to uncover biological function. Finally, we propose extensions of the technique that will enhance our understanding of multi-protein regulatory complexes assembled onto RNA. Copyright © 2016 Elsevier Inc. All rights reserved.
Next-Generation Sequencing for Binary Protein-Protein Interactions

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Bernhard eSuter

2015-12-01

Full Text Available The yeast two-hybrid (Y2H system exploits host cell genetics in order to display binary protein-protein interactions (PPIs via defined and selectable phenotypes. Numerous improvements have been made to this method, adapting the screening principle for diverse applications, including drug discovery and the scale-up for proteome wide interaction screens in human and other organisms. Here we discuss a systematic workflow and analysis scheme for screening data generated by Y2H and related assays that includes high-throughput selection procedures, readout of comprehensive results via next-generation sequencing (NGS, and the interpretation of interaction data via quantitative statistics. The novel assays and tools will serve the broader scientific community to harness the power of NGS technology to address PPI networks in health and disease. We discuss examples of how this next-generation platform can be applied to address specific questions in diverse fields of biology and medicine.
Exploring sequence characteristics related to high-level production of secreted proteins in Aspergillus niger.

Directory of Open Access Journals (Sweden)

Bastiaan A van den Berg

Full Text Available Protein sequence features are explored in relation to the production of over-expressed extracellular proteins by fungi. Knowledge on features influencing protein production and secretion could be employed to improve enzyme production levels in industrial bioprocesses via protein engineering. A large set, over 600 homologous and nearly 2,000 heterologous fungal genes, were overexpressed in Aspergillus niger using a standardized expression cassette and scored for high versus no production. Subsequently, sequence-based machine learning techniques were applied for identifying relevant DNA and protein sequence features. The amino-acid composition of the protein sequence was found to be most predictive and interpretation revealed that, for both homologous and heterologous gene expression, the same features are important: tyrosine and asparagine composition was found to have a positive correlation with high-level production, whereas for unsuccessful production, contributions were found for methionine and lysine composition. The predictor is available online at http://bioinformatics.tudelft.nl/hipsec. Subsequent work aims at validating these findings by protein engineering as a method for increasing expression levels per gene copy.
Sequence variability is correlated with weak immunogenicity in Streptococcus pyogenes M protein

Science.gov (United States)

Lannergård, Jonas; Kristensen, Bodil M; Gustafsson, Mattias C U; Persson, Jenny J; Norrby-Teglund, Anna; Stålhammar-Carlemalm, Margaretha; Lindahl, Gunnar

2015-01-01

The M protein of Streptococcus pyogenes, a major bacterial virulence factor, has an amino-terminal hypervariable region (HVR) that is a target for type-specific protective antibodies. Intriguingly, the HVR elicits a weak antibody response, indicating that it escapes host immunity by two mechanisms, sequence variability and weak immunogenicity. However, the properties influencing the immunogenicity of regions in an M protein remain poorly understood. Here, we studied the antibody response to different regions of the classical M1 and M5 proteins, in which not only the HVR but also the adjacent fibrinogen-binding B repeat region exhibits extensive sequence divergence. Analysis of antisera from S. pyogenes-infected patients, infected mice, and immunized mice showed that both the HVR and the B repeat region elicited weak antibody responses, while the conserved carboxy-terminal part was immunodominant. Thus, we identified a correlation between sequence variability and weak immunogenicity for M protein regions. A potential explanation for the weak immunogenicity was provided by the demonstration that protease digestion selectively eliminated the HVR-B part from whole M protein-expressing bacteria. These data support a coherent model, in which the entire variable HVR-B part evades antibody attack, not only by sequence variability but also by weak immunogenicity resulting from protease attack. PMID:26175306
JACOP: A simple and robust method for the automated classification of protein sequences with modular architecture

Directory of Open Access Journals (Sweden)

Pagni Marco

2005-08-01

Full Text Available Abstract Background Whole-genome sequencing projects are rapidly producing an enormous number of new sequences. Consequently almost every family of proteins now contains hundreds of members. It has thus become necessary to develop tools, which classify protein sequences automatically and also quickly and reliably. The difficulty of this task is intimately linked to the mechanism by which protein sequences diverge, i.e. by simultaneous residue substitutions, insertions and/or deletions and whole domain reorganisations (duplications/swapping/fusion. Results Here we present a novel approach, which is based on random sampling of sub-sequences (probes out of a set of input sequences. The probes are compared to the input sequences, after a normalisation step; the results are used to partition the input sequences into homogeneous groups of proteins. In addition, this method provides information on diagnostic parts of the proteins. The performance of this method is challenged by two data sets. The first one contains the sequences of prokaryotic lyases that could be arranged as a multiple sequence alignment. The second one contains all proteins from Swiss-Prot Release 36 with at least one Src homology 2 (SH2 domain – a classical example for proteins with modular architecture. Conclusion The outcome of our method is robust, highly reproducible as shown using bootstrap and resampling validation procedures. The results are essentially coherent with the biology. This method depends solely on well-established publicly available software and algorithms.
Sequence charge decoration dictates coil-globule transition in intrinsically disordered proteins.

Science.gov (United States)

Firman, Taylor; Ghosh, Kingshuk

2018-03-28

We present an analytical theory to compute conformations of heteropolymers-applicable to describe disordered proteins-as a function of temperature and charge sequence. The theory describes coil-globule transition for a given protein sequence when temperature is varied and has been benchmarked against the all-atom Monte Carlo simulation (using CAMPARI) of intrinsically disordered proteins (IDPs). In addition, the model quantitatively shows how subtle alterations of charge placement in the primary sequence-while maintaining the same charge composition-can lead to significant changes in conformation, even as drastic as a coil (swelled above a purely random coil) to globule (collapsed below a random coil) and vice versa. The theory provides insights on how to control (enhance or suppress) these changes by tuning the temperature (or solution condition) and charge decoration. As an application, we predict the distribution of conformations (at room temperature) of all naturally occurring IDPs in the DisProt database and notice significant size variation even among IDPs with a similar composition of positive and negative charges. Based on this, we provide a new diagram-of-states delineating the sequence-conformation relation for proteins in the DisProt database. Next, we study the effect of post-translational modification, e.g., phosphorylation, on IDP conformations. Modifications as little as two-site phosphorylation can significantly alter the size of an IDP with everything else being constant (temperature, salt concentration, etc.). However, not all possible modification sites have the same effect on protein conformations; there are certain "hot spots" that can cause maximal change in conformation. The location of these "hot spots" in the parent sequence can readily be identified by using a sequence charge decoration metric originally introduced by Sawle and Ghosh. The ability of our model to predict conformations (both expanded and collapsed states) of IDPs at a high
MODexplorer: an integrated tool for exploring protein sequence, structure and function relationships.

KAUST Repository

Kosinski, Jan; Barbato, Alessandro; Tramontano, Anna

2013-01-01

SUMMARY: MODexplorer is an integrated tool aimed at exploring the sequence, structural and functional diversity in protein families useful in homology modeling and in analyzing protein families in general. It takes as input either the sequence or the structure of a protein and provides alignments with its homologs along with a variety of structural and functional annotations through an interactive interface. The annotations include sequence conservation, similarity scores, ligand-, DNA- and RNA-binding sites, secondary structure, disorder, crystallographic structure resolution and quality scores of models implied by the alignments to the homologs of known structure. MODexplorer can be used to analyze sequence and structural conservation among the structures of similar proteins, to find structures of homologs solved in different conformational state or with different ligands and to transfer functional annotations. Furthermore, if the structure of the query is not known, MODexplorer can be used to select the modeling templates taking all this information into account and to build a comparative model. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://modorama.biocomputing.it/modexplorer. Website implemented in HTML and JavaScript with all major browsers supported. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MODexplorer: an integrated tool for exploring protein sequence, structure and function relationships.

KAUST Repository

Kosinski, Jan

2013-02-08

SUMMARY: MODexplorer is an integrated tool aimed at exploring the sequence, structural and functional diversity in protein families useful in homology modeling and in analyzing protein families in general. It takes as input either the sequence or the structure of a protein and provides alignments with its homologs along with a variety of structural and functional annotations through an interactive interface. The annotations include sequence conservation, similarity scores, ligand-, DNA- and RNA-binding sites, secondary structure, disorder, crystallographic structure resolution and quality scores of models implied by the alignments to the homologs of known structure. MODexplorer can be used to analyze sequence and structural conservation among the structures of similar proteins, to find structures of homologs solved in different conformational state or with different ligands and to transfer functional annotations. Furthermore, if the structure of the query is not known, MODexplorer can be used to select the modeling templates taking all this information into account and to build a comparative model. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://modorama.biocomputing.it/modexplorer. Website implemented in HTML and JavaScript with all major browsers supported. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Application of native signal sequences for recombinant proteins secretion in Pichia pastoris

DEFF Research Database (Denmark)

Borodina, Irina; Do, Duy Duc; Eriksen, Jens C.

Background Methylotrophic yeast Pichia pastoris is widely used for recombinant protein production, largely due to its ability to secrete correctly folded heterologous proteins to the fermentation medium. Secretion is usually achieved by cloning the recombinant gene after a leader sequence, where...... alpha‐mating factor (MF) prepropeptide from Saccharomyces cerevisiae is most commonly used. Our aim was to test whether signal peptides from P. pastoris native secreted proteins could be used to direct secretion of recombinant proteins. Results Eleven native signal peptides from P. pastoris were tested...... by optimization of expression of three different proteins in P. pastoris. Conclusions Native signal peptides from P. pastoris can be used to direct secretion of recombinant proteins. A novel USER‐based P. pastoris system allows easy cloning of protein‐coding gene with the promoter and leader sequence of choice....
Prediction of glutathionylation sites in proteins using minimal sequence information and their experimental validation.

Science.gov (United States)

Pal, Debojyoti; Sharma, Deepak; Kumar, Mukesh; Sandur, Santosh K

2016-09-01

S-glutathionylation of proteins plays an important role in various biological processes and is known to be protective modification during oxidative stress. Since, experimental detection of S-glutathionylation is labor intensive and time consuming, bioinformatics based approach is a viable alternative. Available methods require relatively longer sequence information, which may prevent prediction if sequence information is incomplete. Here, we present a model to predict glutathionylation sites from pentapeptide sequences. It is based upon differential association of amino acids with glutathionylated and non-glutathionylated cysteines from a database of experimentally verified sequences. This data was used to calculate position dependent F-scores, which measure how a particular amino acid at a particular position may affect the likelihood of glutathionylation event. Glutathionylation-score (G-score), indicating propensity of a sequence to undergo glutathionylation, was calculated using position-dependent F-scores for each amino-acid. Cut-off values were used for prediction. Our model returned an accuracy of 58% with Matthew's correlation-coefficient (MCC) value of 0.165. On an independent dataset, our model outperformed the currently available model, in spite of needing much less sequence information. Pentapeptide motifs having high abundance among glutathionylated proteins were identified. A list of potential glutathionylation hotspot sequences were obtained by assigning G-scores and subsequent Protein-BLAST analysis revealed a total of 254 putative glutathionable proteins, a number of which were already known to be glutathionylated. Our model predicted glutathionylation sites in 93.93% of experimentally verified glutathionylated proteins. Outcome of this study may assist in discovering novel glutathionylation sites and finding candidate proteins for glutathionylation.
RSARF: Prediction of residue solvent accessibility from protein sequence using random forest method

KAUST Repository

Ganesan, Pugalenthi; Kandaswamy, Krishna Kumar Umar; Chou -, Kuochen; Vivekanandan, Saravanan; Kolatkar, Prasanna R.

2012-01-01

Prediction of protein structure from its amino acid sequence is still a challenging problem. The complete physicochemical understanding of protein folding is essential for the accurate structure prediction. Knowledge of residue solvent accessibility gives useful insights into protein structure prediction and function prediction. In this work, we propose a random forest method, RSARF, to predict residue accessible surface area from protein sequence information. The training and testing was performed using 120 proteins containing 22006 residues. For each residue, buried and exposed state was computed using five thresholds (0%, 5%, 10%, 25%, and 50%). The prediction accuracy for 0%, 5%, 10%, 25%, and 50% thresholds are 72.9%, 78.25%, 78.12%, 77.57% and 72.07% respectively. Further, comparison of RSARF with other methods using a benchmark dataset containing 20 proteins shows that our approach is useful for prediction of residue solvent accessibility from protein sequence without using structural information. The RSARF program, datasets and supplementary data are available at http://caps.ncbs.res.in/download/pugal/RSARF/. - See more at: http://www.eurekaselect.com/89216/article#sthash.pwVGFUjq.dpuf
Alternative splicing affects the targeting sequence of peroxisome proteins in Arabidopsis.

Science.gov (United States)

An, Chuanjing; Gao, Yuefang; Li, Jinyu; Liu, Xiaomin; Gao, Fuli; Gao, Hongbo

2017-07-01

A systematic analysis of the Arabidopsis genome in combination with localization experiments indicates that alternative splicing affects the peroxisomal targeting sequence of at least 71 genes in Arabidopsis. Peroxisomes are ubiquitous eukaryotic cellular organelles that play a key role in diverse metabolic functions. All peroxisome proteins are encoded by nuclear genes and target to peroxisomes mainly through two types of targeting signals: peroxisomal targeting signal type 1 (PTS1) and PTS2. Alternative splicing (AS) is a process occurring in all eukaryotes by which a single pre-mRNA can generate multiple mRNA variants, often encoding proteins with functional differences. However, the effects of AS on the PTS1 or PTS2 and the targeting of the protein were rarely studied, especially in plants. Here, we systematically analyzed the genome of Arabidopsis, and found that the C-terminal targeting sequence PTS1 of 66 genes and the N-terminal targeting sequence PTS2 of 5 genes are affected by AS. Experimental determination of the targeting of selected protein isoforms further demonstrated that AS at both the 5' and 3' region of a gene can affect the inclusion of PTS2 and PTS1, respectively. This work underscores the importance of AS on the global regulation of peroxisome protein targeting.
Protein sequence annotation in the genome era: the annotation concept of SWISS-PROT+TREMBL.

Science.gov (United States)

Apweiler, R; Gateau, A; Contrino, S; Martin, M J; Junker, V; O'Donovan, C; Lang, F; Mitaritonna, N; Kappus, S; Bairoch, A

1997-01-01

SWISS-PROT is a curated protein sequence database which strives to provide a high level of annotation, a minimal level of redundancy and high level of integration with other databases. Ongoing genome sequencing projects have dramatically increased the number of protein sequences to be incorporated into SWISS-PROT. Since we do not want to dilute the quality standards of SWISS-PROT by incorporating sequences without proper sequence analysis and annotation, we cannot speed up the incorporation of new incoming data indefinitely. However, as we also want to make the sequences available as fast as possible, we introduced TREMBL (TRanslation of EMBL nucleotide sequence database), a supplement to SWISS-PROT. TREMBL consists of computer-annotated entries in SWISS-PROT format derived from the translation of all coding sequences (CDS) in the EMBL nucleotide sequence database, except for CDS already included in SWISS-PROT. While TREMBL is already of immense value, its computer-generated annotation does not match the quality of SWISS-PROTs. The main difference is in the protein functional information attached to sequences. With this in mind, we are dedicating substantial effort to develop and apply computer methods to enhance the functional information attached to TREMBL entries.
Simultaneous and complete genome sequencing of influenza A and B with high coverage by Illumina MiSeq Platform.

Science.gov (United States)

Rutvisuttinunt, Wiriya; Chinnawirotpisan, Piyawan; Simasathien, Sriluck; Shrestha, Sanjaya K; Yoon, In-Kyu; Klungthong, Chonticha; Fernandez, Stefan

2013-11-01

Active global surveillance and characterization of influenza viruses are essential for better preparation against possible pandemic events. Obtaining comprehensive information about the influenza genome can improve our understanding of the evolution of influenza viruses and emergence of new strains, and improve the accuracy when designing preventive vaccines. This study investigated the use of deep sequencing by the next-generation sequencing (NGS) Illumina MiSeq Platform to obtain complete genome sequence information from influenza virus isolates. The influenza virus isolates were cultured from 6 respiratory acute clinical specimens collected in Thailand and Nepal. DNA libraries obtained from each viral isolate were mixed and all were sequenced simultaneously. Total information of 2.6 Gbases was obtained from a 455±14 K/mm2 density with 95.76% (8,571,655/8,950,724 clusters) of the clusters passing quality control (QC) filters. Approximately 93.7% of all sequences from Read1 and 83.5% from Read2 contained high quality sequences that were ≥Q30, a base calling QC score standard. Alignments analysis identified three seasonal influenza A H3N2 strains, one 2009 pandemic influenza A H1N1 strain and two influenza B strains. The nearly entire genomes of all six virus isolates yielded equal or greater than 600-fold sequence coverage depth. MiSeq Platform identified seasonal influenza A H3N2, 2009 pandemic influenza A H1N1and influenza B in the DNA library mixtures efficiently. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.
The European sea bass Dicentrarchus labrax genome puzzle: comparative BAC-mapping and low coverage shotgun sequencing

Directory of Open Access Journals (Sweden)

Volckaert Filip AM

2010-01-01

Full Text Available Abstract Background Food supply from the ocean is constrained by the shortage of domesticated and selected fish. Development of genomic models of economically important fishes should assist with the removal of this bottleneck. European sea bass Dicentrarchus labrax L. (Moronidae, Perciformes, Teleostei is one of the most important fishes in European marine aquaculture; growing genomic resources put it on its way to serve as an economic model. Results End sequencing of a sea bass genomic BAC-library enabled the comparative mapping of the sea bass genome using the three-spined stickleback Gasterosteus aculeatus genome as a reference. BAC-end sequences (102,690 were aligned to the stickleback genome. The number of mappable BACs was improved using a two-fold coverage WGS dataset of sea bass resulting in a comparative BAC-map covering 87% of stickleback chromosomes with 588 BAC-contigs. The minimum size of 83 contigs covering 50% of the reference was 1.2 Mbp; the largest BAC-contig comprised 8.86 Mbp. More than 22,000 BAC-clones aligned with both ends to the reference genome. Intra-chromosomal rearrangements between sea bass and stickleback were identified. Size distributions of mapped BACs were used to calculate that the genome of sea bass may be only 1.3 fold larger than the 460 Mbp stickleback genome. Conclusions The BAC map is used for sequencing single BACs or BAC-pools covering defined genomic entities by second generation sequencing technologies. Together with the WGS dataset it initiates a sea bass genome sequencing project. This will allow the quantification of polymorphisms through resequencing, which is important for selecting highly performing domesticated fish.

Experimental Rugged Fitness Landscape in Protein Sequence Space

OpenAIRE

HAYASHI, Yuuki; 相田, 拓洋; TOYOTA, Hitoshi; 伏見, 譲; URABE, Itaru; YOMO, Tetsuya

2006-01-01

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phag...
A method for partitioning the information contained in a protein sequence between its structure and function.

Science.gov (United States)

Possenti, Andrea; Vendruscolo, Michele; Camilloni, Carlo; Tiana, Guido

2018-05-23

Proteins employ the information stored in the genetic code and translated into their sequences to carry out well-defined functions in the cellular environment. The possibility to encode for such functions is controlled by the balance between the amount of information supplied by the sequence and that left after that the protein has folded into its structure. We study the amount of information necessary to specify the protein structure, providing an estimate that keeps into account the thermodynamic properties of protein folding. We thus show that the information remaining in the protein sequence after encoding for its structure (the 'information gap') is very close to what needed to encode for its function and interactions. Then, by predicting the information gap directly from the protein sequence, we show that it may be possible to use these insights from information theory to discriminate between ordered and disordered proteins, to identify unknown functions, and to optimize artificially-designed protein sequences. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.
Sequence variability is correlated with weak immunogenicity in Streptococcus pyogenes M protein.

Science.gov (United States)

Lannergård, Jonas; Kristensen, Bodil M; Gustafsson, Mattias C U; Persson, Jenny J; Norrby-Teglund, Anna; Stålhammar-Carlemalm, Margaretha; Lindahl, Gunnar

2015-10-01

The M protein of Streptococcus pyogenes, a major bacterial virulence factor, has an amino-terminal hypervariable region (HVR) that is a target for type-specific protective antibodies. Intriguingly, the HVR elicits a weak antibody response, indicating that it escapes host immunity by two mechanisms, sequence variability and weak immunogenicity. However, the properties influencing the immunogenicity of regions in an M protein remain poorly understood. Here, we studied the antibody response to different regions of the classical M1 and M5 proteins, in which not only the HVR but also the adjacent fibrinogen-binding B repeat region exhibits extensive sequence divergence. Analysis of antisera from S. pyogenes-infected patients, infected mice, and immunized mice showed that both the HVR and the B repeat region elicited weak antibody responses, while the conserved carboxy-terminal part was immunodominant. Thus, we identified a correlation between sequence variability and weak immunogenicity for M protein regions. A potential explanation for the weak immunogenicity was provided by the demonstration that protease digestion selectively eliminated the HVR-B part from whole M protein-expressing bacteria. These data support a coherent model, in which the entire variable HVR-B part evades antibody attack, not only by sequence variability but also by weak immunogenicity resulting from protease attack. © 2015 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.
Seeing the trees through the forest : sequence-based homo- and heteromeric protein-protein interaction sites prediction using random forest

NARCIS (Netherlands)

Hou, Qingzhen; De Geest, Paul F.G.; Vranken, Wim F.; Heringa, Jaap; Feenstra, K. Anton

2017-01-01

Motivation: Genome sequencing is producing an ever-increasing amount of associated protein sequences. Few of these sequences have experimentally validated annotations, however, and computational predictions are becoming increasingly successful in producing such annotations. One key challenge remains
Combining protein sequence, structure, and dynamics: A novel approach for functional evolution analysis of PAS domain superfamily.

Science.gov (United States)

Dong, Zheng; Zhou, Hongyu; Tao, Peng

2018-02-01

PAS domains are widespread in archaea, bacteria, and eukaryota, and play important roles in various functions. In this study, we aim to explore functional evolutionary relationship among proteins in the PAS domain superfamily in view of the sequence-structure-dynamics-function relationship. We collected protein sequences and crystal structure data from RCSB Protein Data Bank of the PAS domain superfamily belonging to three biological functions (nucleotide binding, photoreceptor activity, and transferase activity). Protein sequences were aligned and then used to select sequence-conserved residues and build phylogenetic tree. Three-dimensional structure alignment was also applied to obtain structure-conserved residues. The protein dynamics were analyzed using elastic network model (ENM) and validated by molecular dynamics (MD) simulation. The result showed that the proteins with same function could be grouped by sequence similarity, and proteins in different functional groups displayed statistically significant difference in their vibrational patterns. Interestingly, in all three functional groups, conserved amino acid residues identified by sequence and structure conservation analysis generally have a lower fluctuation than other residues. In addition, the fluctuation of conserved residues in each biological function group was strongly correlated with the corresponding biological function. This research suggested a direct connection in which the protein sequences were related to various functions through structural dynamics. This is a new attempt to delineate functional evolution of proteins using the integrated information of sequence, structure, and dynamics. © 2017 The Protein Society.
Analysis of transposable elements in the genome of Asparagus officinalis from high coverage sequence data.

Science.gov (United States)

Li, Shu-Fen; Gao, Wu-Jun; Zhao, Xin-Peng; Dong, Tian-Yu; Deng, Chuan-Liang; Lu, Long-Dou

2014-01-01

Asparagus officinalis is an economically and nutritionally important vegetable crop that is widely cultivated and is used as a model dioecious species to study plant sex determination and sex chromosome evolution. To improve our understanding of its genome composition, especially with respect to transposable elements (TEs), which make up the majority of the genome, we performed Illumina HiSeq2000 sequencing of both male and female asparagus genomes followed by bioinformatics analysis. We generated 17 Gb of sequence (12×coverage) and assembled them into 163,406 scaffolds with a total cumulated length of 400 Mbp, which represent about 30% of asparagus genome. Overall, TEs masked about 53% of the A. officinalis assembly. Majority of the identified TEs belonged to LTR retrotransposons, which constitute about 28% of genomic DNA, with Ty1/copia elements being more diverse and accumulated to higher copy numbers than Ty3/gypsy. Compared with LTR retrotransposons, non-LTR retrotransposons and DNA transposons were relatively rare. In addition, comparison of the abundance of the TE groups between male and female genomes showed that the overall TE composition was highly similar, with only slight differences in the abundance of several TE groups, which is consistent with the relatively recent origin of asparagus sex chromosomes. This study greatly improves our knowledge of the repetitive sequence construction of asparagus, which facilitates the identification of TEs responsible for the early evolution of plant sex chromosomes and is helpful for further studies on this dioecious plant.
Milk protein-gum tragacanth mixed gels: effect of heat-treatment sequence.

Science.gov (United States)

Hatami, Masoud; Nejatian, Mohammad; Mohammadifar, Mohammad Amin; Pourmand, Hanieh

2014-01-30

The aim of this study was to investigate the role of the heat-treatment sequence of biopolymer mixtures as a formulation parameter on the acid-induced gelation of tri-polymeric systems composed of sodium caseinate (Na-caseinate), whey protein concentrate (WPC), and gum tragacanth (GT). This was studied by applying four sequences of heat treatment: (A) co-heating all three biopolymers; (B) heating the milk-protein dispersion and the GT dispersion separately; (C) heating the dispersion containing Na-caseinate and GT together and heating whey protein alone; and (D) co-heating whey protein with GT and heating Na-caseinate alone. According to small-deformation rheological measurements, the strength of the mixed-gel network decreased in the order: C>B>D>A samples. SEM micrographs show that the network of sample C is much more homogenous, coarse and dense than sample A, while the networks of samples B and D are of intermediate density. The heat-treatment sequence of the biopolymer mixtures as a formulation parameter thus offers an opportunity to control the microstructure and rheological properties of mixed gels. Copyright © 2013 Elsevier Ltd. All rights reserved.
Application of Tandem Two-Dimensional Mass Spectrometry for Top-Down Deep Sequencing of Calmodulin.

Science.gov (United States)

Floris, Federico; Chiron, Lionel; Lynch, Alice M; Barrow, Mark P; Delsuc, Marc-André; O'Connor, Peter B

2018-06-04

Two-dimensional mass spectrometry (2DMS) involves simultaneous acquisition of the fragmentation patterns of all the analytes in a mixture by correlating their precursor and fragment ions by modulating precursor ions systematically through a fragmentation zone. Tandem two-dimensional mass spectrometry (MS/2DMS) unites the ultra-high accuracy of Fourier transform ion cyclotron resonance (FT-ICR) MS/MS and the simultaneous data-independent fragmentation of 2DMS to achieve extensive inter-residue fragmentation of entire proteins. 2DMS was recently developed for top-down proteomics (TDP), and applied to the analysis of calmodulin (CaM), reporting a cleavage coverage of about ~23% using infrared multiphoton dissociation (IRMPD) as fragmentation technique. The goal of this work is to expand the utility of top-down protein analysis using MS/2DMS in order to extend the cleavage coverage in top-down proteomics further into the interior regions of the protein. In this case, using MS/2DMS, the cleavage coverage of CaM increased from ~23% to ~42%. Graphical Abstract Two-dimensional mass spectrometry, when applied to primary fragment ions from the source, allows deep-sequencing of the protein calmodulin.
A scalable double-barcode sequencing platform for characterization of dynamic protein-protein interactions.

Science.gov (United States)

Schlecht, Ulrich; Liu, Zhimin; Blundell, Jamie R; St Onge, Robert P; Levy, Sasha F

2017-05-25

Several large-scale efforts have systematically catalogued protein-protein interactions (PPIs) of a cell in a single environment. However, little is known about how the protein interactome changes across environmental perturbations. Current technologies, which assay one PPI at a time, are too low throughput to make it practical to study protein interactome dynamics. Here, we develop a highly parallel protein-protein interaction sequencing (PPiSeq) platform that uses a novel double barcoding system in conjunction with the dihydrofolate reductase protein-fragment complementation assay in Saccharomyces cerevisiae. PPiSeq detects PPIs at a rate that is on par with current assays and, in contrast with current methods, quantitatively scores PPIs with enough accuracy and sensitivity to detect changes across environments. Both PPI scoring and the bulk of strain construction can be performed with cell pools, making the assay scalable and easily reproduced across environments. PPiSeq is therefore a powerful new tool for large-scale investigations of dynamic PPIs.
OPAL: prediction of MoRF regions in intrinsically disordered protein sequences.

Science.gov (United States)

Sharma, Ronesh; Raicar, Gaurav; Tsunoda, Tatsuhiko; Patil, Ashwini; Sharma, Alok

2018-06-01

Intrinsically disordered proteins lack stable 3-dimensional structure and play a crucial role in performing various biological functions. Key to their biological function are the molecular recognition features (MoRFs) located within long disordered regions. Computationally identifying these MoRFs from disordered protein sequences is a challenging task. In this study, we present a new MoRF predictor, OPAL, to identify MoRFs in disordered protein sequences. OPAL utilizes two independent sources of information computed using different component predictors. The scores are processed and combined using common averaging method. The first score is computed using a component MoRF predictor which utilizes composition and sequence similarity of MoRF and non-MoRF regions to detect MoRFs. The second score is calculated using half-sphere exposure (HSE), solvent accessible surface area (ASA) and backbone angle information of the disordered protein sequence, using information from the amino acid properties of flanks surrounding the MoRFs to distinguish MoRF and non-MoRF residues. OPAL is evaluated using test sets that were previously used to evaluate MoRF predictors, MoRFpred, MoRFchibi and MoRFchibi-web. The results demonstrate that OPAL outperforms all the available MoRF predictors and is the most accurate predictor available for MoRF prediction. It is available at http://www.alok-ai-lab.com/tools/opal/. ashwini@hgc.jp or alok.sharma@griffith.edu.au. Supplementary data are available at Bioinformatics online.
Sequence analysis of the genome of carnation (Dianthus caryophyllus L.).

Science.gov (United States)

Yagi, Masafumi; Kosugi, Shunichi; Hirakawa, Hideki; Ohmiya, Akemi; Tanase, Koji; Harada, Taro; Kishimoto, Kyutaro; Nakayama, Masayoshi; Ichimura, Kazuo; Onozaki, Takashi; Yamaguchi, Hiroyasu; Sasaki, Nobuhiro; Miyahara, Taira; Nishizaki, Yuzo; Ozeki, Yoshihiro; Nakamura, Noriko; Suzuki, Takamasa; Tanaka, Yoshikazu; Sato, Shusei; Shirasawa, Kenta; Isobe, Sachiko; Miyamura, Yoshinori; Watanabe, Akiko; Nakayama, Shinobu; Kishida, Yoshie; Kohara, Mitsuyo; Tabata, Satoshi

2014-06-01

The whole-genome sequence of carnation (Dianthus caryophyllus L.) cv. 'Francesco' was determined using a combination of different new-generation multiplex sequencing platforms. The total length of the non-redundant sequences was 568,887,315 bp, consisting of 45,088 scaffolds, which covered 91% of the 622 Mb carnation genome estimated by k-mer analysis. The N50 values of contigs and scaffolds were 16,644 bp and 60,737 bp, respectively, and the longest scaffold was 1,287,144 bp. The average GC content of the contig sequences was 36%. A total of 1050, 13, 92 and 143 genes for tRNAs, rRNAs, snoRNA and miRNA, respectively, were identified in the assembled genomic sequences. For protein-encoding genes, 43 266 complete and partial gene structures excluding those in transposable elements were deduced. Gene coverage was ∼ 98%, as deduced from the coverage of the core eukaryotic genes. Intensive characterization of the assigned carnation genes and comparison with those of other plant species revealed characteristic features of the carnation genome. The results of this study will serve as a valuable resource for fundamental and applied research of carnation, especially for breeding new carnation varieties. Further information on the genomic sequences is available at http://carnation.kazusa.or.jp. © The Author 2013. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.
EST-PAC a web package for EST annotation and protein sequence prediction

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Strahm Yvan

2006-10-01

Full Text Available Abstract With the decreasing cost of DNA sequencing technology and the vast diversity of biological resources, researchers increasingly face the basic challenge of annotating a larger number of expressed sequences tags (EST from a variety of species. This typically consists of a series of repetitive tasks, which should be automated and easy to use. The results of these annotation tasks need to be stored and organized in a consistent way. All these operations should be self-installing, platform independent, easy to customize and amenable to using distributed bioinformatics resources available on the Internet. In order to address these issues, we present EST-PAC a web oriented multi-platform software package for expressed sequences tag (EST annotation. EST-PAC provides a solution for the administration of EST and protein sequence annotations accessible through a web interface. Three aspects of EST annotation are automated: 1 searching local or remote biological databases for sequence similarities using Blast services, 2 predicting protein coding sequence from EST data and, 3 annotating predicted protein sequences with functional domain predictions. In practice, EST-PAC integrates the BLASTALL suite, EST-Scan2 and HMMER in a relational database system accessible through a simple web interface. EST-PAC also takes advantage of the relational database to allow consistent storage, powerful queries of results and, management of the annotation process. The system allows users to customize annotation strategies and provides an open-source data-management environment for research and education in bioinformatics.
Complete genome sequence of Menghai rhabdovirus, a novel mosquito-borne rhabdovirus from China.

Science.gov (United States)

Sun, Qiang; Zhao, Qiumin; An, Xiaoping; Guo, Xiaofang; Zuo, Shuqing; Zhang, Xianglilan; Pei, Guangqian; Liu, Wenli; Cheng, Shi; Wang, Yunfei; Shu, Peng; Mi, Zhiqiang; Huang, Yong; Zhang, Zhiyi; Tong, Yigang; Zhou, Hongning; Zhang, Jiusong

2017-04-01

Menghai rhabdovirus (MRV) was isolated from Aedes albopictus in Menghai county of Yunnan Province, China, in August 2010. Whole-genome sequencing of MRV was performed using an Ion PGM™ Sequencer. We found that MRV is a single-stranded, negative-sense RNA virus. The complete genome of MRV has 10,744 nt, with short inverted repeat termini, encoding five typical rhabdovirus proteins (N, P, M, G, and L) and an additional small hypothetical protein. Nucleotide BLAST analysis using the BLASTn method showed that the genome sequence most similar to that of MRV is that of Arboretum virus (NC_025393.1), with a Max score of 322, query coverage of 14%, and 66% identity. Genomic and phylogenetic analyses both demonstrated that MRV should be considered a member of a novel species of the family Rhabdoviridae.
DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier

KAUST Repository

Kulmanov, Maxat

2017-09-27

Motivation A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. Results We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein–protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations.
Gene identification and protein classification in microbial metagenomic sequence data via incremental clustering

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Li Weizhong

2008-04-01

Full Text Available Abstract Background The identification and study of proteins from metagenomic datasets can shed light on the roles and interactions of the source organisms in their communities. However, metagenomic datasets are characterized by the presence of organisms with varying GC composition, codon usage biases etc., and consequently gene identification is challenging. The vast amount of sequence data also requires faster protein family classification tools. Results We present a computational improvement to a sequence clustering approach that we developed previously to identify and classify protein coding genes in large microbial metagenomic datasets. The clustering approach can be used to identify protein coding genes in prokaryotes, viruses, and intron-less eukaryotes. The computational improvement is based on an incremental clustering method that does not require the expensive all-against-all compute that was required by the original approach, while still preserving the remote homology detection capabilities. We present evaluations of the clustering approach in protein-coding gene identification and classification, and also present the results of updating the protein clusters from our previous work with recent genomic and metagenomic sequences. The clustering results are available via CAMERA, (http://camera.calit2.net. Conclusion The clustering paradigm is shown to be a very useful tool in the analysis of microbial metagenomic data. The incremental clustering method is shown to be much faster than the original approach in identifying genes, grouping sequences into existing protein families, and also identifying novel families that have multiple members in a metagenomic dataset. These clusters provide a basis for further studies of protein families.
Amino acid sequences of ribosomal proteins S11 from Bacillus stearothermophilus and S19 from Halobacterium marismortui. Comparison of the ribosomal protein S11 family.

Science.gov (United States)

Kimura, M; Kimura, J; Hatakeyama, T

1988-11-21

The complete amino acid sequences of ribosomal proteins S11 from the Gram-positive eubacterium Bacillus stearothermophilus and of S19 from the archaebacterium Halobacterium marismortui have been determined. A search for homologous sequences of these proteins revealed that they belong to the ribosomal protein S11 family. Homologous proteins have previously been sequenced from Escherichia coli as well as from chloroplast, yeast and mammalian ribosomes. A pairwise comparison of the amino acid sequences showed that Bacillus protein S11 shares 68% identical residues with S11 from Escherichia coli and a slightly lower homology (52%) with the homologous chloroplast protein. The halophilic protein S19 is more related to the eukaryotic (45-49%) than to the eubacterial counterparts (35%).
Subnanogram proteomics: Impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples

Energy Technology Data Exchange (ETDEWEB)

Zhu, Ying; Zhao, Rui; Piehowski, Paul D.; Moore, Ronald J.; Lim, Sujung; Orphan, Victoria J.; Paša-Tolić, Ljiljana; Qian, Wei-Jun; Smith, Richard D.; Kelly, Ryan T.

2018-04-01

One of the greatest challenges for mass spectrometry (MS)-based proteomics is the limited ability to analyze small samples. Here we investigate the relative contributions of liquid chromatography (LC), MS instrumentation and data analysis methods with the aim of improving proteome coverage for sample sizes ranging from 0.5 ng to 50 ng. We show that the LC separations utilizing 30-µm-i.d. columns increase signal intensity by >3-fold relative to those using 75-µm-i.d. columns, leading to 32% increase in peptide identifications. The Orbitrap Fusion Lumos mass spectrometer significantly boosted both sensitivity and sequencing speed relative to earlier generation Orbitraps (e.g., LTQ-Orbitrap), leading to a ~3× increase in peptide identifications and 1.7× increase in identified protein groups for 2 ng tryptic digests of bacterial lysate. The Match Between Runs algorithm of open-source MaxQuant software further increased proteome coverage by ~ 95% for 0.5 ng samples and by ~42% for 2 ng samples. The present platform is capable of identifying >3000 protein groups from tryptic digestion of cell lysates equivalent to 50 HeLa cells and 100 THP-1 cells (~10 ng total proteins), respectively, and >950 proteins from subnanogram bacterial and archaeal cell lysates. The present ultrasensitive LC-MS platform is expected to enable deep proteome coverage for subnanogram samples, including single mammalian cells.
Efficient use of unlabeled data for protein sequence classification: a comparative study.

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Kuksa, Pavel; Huang, Pai-Hsi; Pavlovic, Vladimir

2009-04-29

Recent studies in computational primary protein sequence analysis have leveraged the power of unlabeled data. For example, predictive models based on string kernels trained on sequences known to belong to particular folds or superfamilies, the so-called labeled data set, can attain significantly improved accuracy if this data is supplemented with protein sequences that lack any class tags-the unlabeled data. In this study, we present a principled and biologically motivated computational framework that more effectively exploits the unlabeled data by only using the sequence regions that are more likely to be biologically relevant for better prediction accuracy. As overly-represented sequences in large uncurated databases may bias the estimation of computational models that rely on unlabeled data, we also propose a method to remove this bias and improve performance of the resulting classifiers. Combined with state-of-the-art string kernels, our proposed computational framework achieves very accurate semi-supervised protein remote fold and homology detection on three large unlabeled databases. It outperforms current state-of-the-art methods and exhibits significant reduction in running time. The unlabeled sequences used under the semi-supervised setting resemble the unpolished gemstones; when used as-is, they may carry unnecessary features and hence compromise the classification accuracy but once cut and polished, they improve the accuracy of the classifiers considerably.
TRDistiller: a rapid filter for enrichment of sequence datasets with proteins containing tandem repeats.

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Richard, François D; Kajava, Andrey V

2014-06-01

The dramatic growth of sequencing data evokes an urgent need to improve bioinformatics tools for large-scale proteome analysis. Over the last two decades, the foremost efforts of computer scientists were devoted to proteins with aperiodic sequences having globular 3D structures. However, a large portion of proteins contain periodic sequences representing arrays of repeats that are directly adjacent to each other (so called tandem repeats or TRs). These proteins frequently fold into elongated fibrous structures carrying different fundamental functions. Algorithms specific to the analysis of these regions are urgently required since the conventional approaches developed for globular domains have had limited success when applied to the TR regions. The protein TRs are frequently not perfect, containing a number of mutations, and some of them cannot be easily identified. To detect such "hidden" repeats several algorithms have been developed. However, the most sensitive among them are time-consuming and, therefore, inappropriate for large scale proteome analysis. To speed up the TR detection we developed a rapid filter that is based on the comparison of composition and order of short strings in the adjacent sequence motifs. Tests show that our filter discards up to 22.5% of proteins which are known to be without TRs while keeping almost all (99.2%) TR-containing sequences. Thus, we are able to decrease the size of the initial sequence dataset enriching it with TR-containing proteins which allows a faster subsequent TR detection by other methods. The program is available upon request. Copyright © 2014 Elsevier Inc. All rights reserved.
Sifting through genomes with iterative-sequence clustering produces a large, phylogenetically diverse protein-family resource.

Science.gov (United States)

Sharpton, Thomas J; Jospin, Guillaume; Wu, Dongying; Langille, Morgan G I; Pollard, Katherine S; Eisen, Jonathan A

2012-10-13

New computational resources are needed to manage the increasing volume of biological data from genome sequencing projects. One fundamental challenge is the ability to maintain a complete and current catalog of protein diversity. We developed a new approach for the identification of protein families that focuses on the rapid discovery of homologous protein sequences. We implemented fully automated and high-throughput procedures to de novo cluster proteins into families based upon global alignment similarity. Our approach employs an iterative clustering strategy in which homologs of known families are sifted out of the search for new families. The resulting reduction in computational complexity enables us to rapidly identify novel protein families found in new genomes and to perform efficient, automated updates that keep pace with genome sequencing. We refer to protein families identified through this approach as "Sifting Families," or SFams. Our analysis of ~10.5 million protein sequences from 2,928 genomes identified 436,360 SFams, many of which are not represented in other protein family databases. We validated the quality of SFam clustering through statistical as well as network topology-based analyses. We describe the rapid identification of SFams and demonstrate how they can be used to annotate genomes and metagenomes. The SFam database catalogs protein-family quality metrics, multiple sequence alignments, hidden Markov models, and phylogenetic trees. Our source code and database are publicly available and will be subject to frequent updates (http://edhar.genomecenter.ucdavis.edu/sifting_families/).

Extreme sequence divergence but conserved ligand-binding specificity in Streptococcus pyogenes M protein.

Directory of Open Access Journals (Sweden)

2006-05-01

Full Text Available Many pathogenic microorganisms evade host immunity through extensive sequence variability in a protein region targeted by protective antibodies. In spite of the sequence variability, a variable region commonly retains an important ligand-binding function, reflected in the presence of a highly conserved sequence motif. Here, we analyze the limits of sequence divergence in a ligand-binding region by characterizing the hypervariable region (HVR of Streptococcus pyogenes M protein. Our studies were focused on HVRs that bind the human complement regulator C4b-binding protein (C4BP, a ligand that confers phagocytosis resistance. A previous comparison of C4BP-binding HVRs identified residue identities that could be part of a binding motif, but the extended analysis reported here shows that no residue identities remain when additional C4BP-binding HVRs are included. Characterization of the HVR in the M22 protein indicated that two relatively conserved Leu residues are essential for C4BP binding, but these residues are probably core residues in a coiled-coil, implying that they do not directly contribute to binding. In contrast, substitution of either of two relatively conserved Glu residues, predicted to be solvent-exposed, had no effect on C4BP binding, although each of these changes had a major effect on the antigenic properties of the HVR. Together, these findings show that HVRs of M proteins have an extraordinary capacity for sequence divergence and antigenic variability while retaining a specific ligand-binding function.
DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier

KAUST Repository

Kulmanov, Maxat; Khan, Mohammed Asif; Hoehndorf, Robert

2017-01-01

A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often
RTA, a candidate G protein-coupled receptor: Cloning, sequencing, and tissue distribution

International Nuclear Information System (INIS)

Ross, P.C.; Figler, R.A.; Corjay, M.H.; Barber, C.M.; Adam, N.; Harcus, D.R.; Lynch, K.R.

1990-01-01

Genomic and cDNA clones, encoding a protein that is a member of the guanine nucleotide-binding regulatory protein (G protein)-coupled receptor superfamily, were isolated by screening rat genomic and thoracic aorta cDNA libraries with an oligonucleotide encoding a highly conserved region of the M 1 muscarinic acetylcholine receptor. Sequence analyses of these clones showed that they encode a 343-amino acid protein (named RTA). The RTA gene is single copy, as demonstrated by restriction mapping and Southern blotting of genomic clones and rat genomic DNA. RTA RNA sequences are relatively abundant throughout the gut, vas deferens, uterus, and aorta but are only barely detectable (on Northern blots) in liver, kidney, lung, and salivary gland. In the rat brain, RTA sequences are markedly abundant in the cerebellum. TRA is most closely related to the mas oncogene (34% identity), which has been suggested to be a forebrain angiotensin receptor. They conclude that RTA is not an angiotensin receptor; to date, they have been unable to identify its ligand
Sequence-specific capture of protein-DNA complexes for mass spectrometric protein identification.

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Cheng-Hsien Wu

Full Text Available The regulation of gene transcription is fundamental to the existence of complex multicellular organisms such as humans. Although it is widely recognized that much of gene regulation is controlled by gene-specific protein-DNA interactions, there presently exists little in the way of tools to identify proteins that interact with the genome at locations of interest. We have developed a novel strategy to address this problem, which we refer to as GENECAPP, for Global ExoNuclease-based Enrichment of Chromatin-Associated Proteins for Proteomics. In this approach, formaldehyde cross-linking is employed to covalently link DNA to its associated proteins; subsequent fragmentation of the DNA, followed by exonuclease digestion, produces a single-stranded region of the DNA that enables sequence-specific hybridization capture of the protein-DNA complex on a solid support. Mass spectrometric (MS analysis of the captured proteins is then used for their identification and/or quantification. We show here the development and optimization of GENECAPP for an in vitro model system, comprised of the murine insulin-like growth factor-binding protein 1 (IGFBP1 promoter region and FoxO1, a member of the forkhead rhabdomyosarcoma (FoxO subfamily of transcription factors, which binds specifically to the IGFBP1 promoter. This novel strategy provides a powerful tool for studies of protein-DNA and protein-protein interactions.
Automated sequence-specific protein NMR assignment using the memetic algorithm MATCH

International Nuclear Information System (INIS)

Volk, Jochen; Herrmann, Torsten; Wuethrich, Kurt

2008-01-01

MATCH (Memetic Algorithm and Combinatorial Optimization Heuristics) is a new memetic algorithm for automated sequence-specific polypeptide backbone NMR assignment of proteins. MATCH employs local optimization for tracing partial sequence-specific assignments within a global, population-based search environment, where the simultaneous application of local and global optimization heuristics guarantees high efficiency and robustness. MATCH thus makes combined use of the two predominant concepts in use for automated NMR assignment of proteins. Dynamic transition and inherent mutation are new techniques that enable automatic adaptation to variable quality of the experimental input data. The concept of dynamic transition is incorporated in all major building blocks of the algorithm, where it enables switching between local and global optimization heuristics at any time during the assignment process. Inherent mutation restricts the intrinsically required randomness of the evolutionary algorithm to those regions of the conformation space that are compatible with the experimental input data. Using intact and artificially deteriorated APSY-NMR input data of proteins, MATCH performed sequence-specific resonance assignment with high efficiency and robustness
Sorting of a HaloTag protein that has only a signal peptide sequence into exocrine secretory granules without protein aggregation.

Science.gov (United States)

Fujita-Yoshigaki, Junko; Matsuki-Fukushima, Miwako; Yokoyama, Megumi; Katsumata-Kato, Osamu

2013-11-15

The mechanism involved in the sorting and accumulation of secretory cargo proteins, such as amylase, into secretory granules of exocrine cells remains to be solved. To clarify that sorting mechanism, we expressed a reporter protein HaloTag fused with partial sequences of salivary amylase protein in primary cultured parotid acinar cells. We found that a HaloTag protein fused with only the signal peptide sequence (Met(1)-Ala(25)) of amylase, termed SS25H, colocalized well with endogenous amylase, which was confirmed by immunofluorescence microscopy. Percoll-density gradient centrifugation of secretory granule fractions shows that the distributions of amylase and SS25H were similar. These results suggest that SS25H is transported to secretory granules and is not discriminated from endogenous amylase by the machinery that functions to remove proteins other than granule cargo from immature granules. Another reporter protein, DsRed2, that has the same signal peptide sequence also colocalized with amylase, suggesting that the sorting to secretory granules is not dependent on a characteristic of the HaloTag protein. Whereas Blue Native PAGE demonstrates that endogenous amylase forms a high-molecular-weight complex, SS25H does not participate in the complex and does not form self-aggregates. Nevertheless, SS25H was released from cells by the addition of a β-adrenergic agonist, isoproterenol, which also induces amylase secretion. These results indicate that addition of the signal peptide sequence, which is necessary for the translocation in the endoplasmic reticulum, is sufficient for the transportation and storage of cargo proteins in secretory granules of exocrine cells.
The N-terminal sequence of ribosomal protein L10 from the archaebacterium Halobacterium marismortui and its relationship to eubacterial protein L6 and other ribosomal proteins.

Science.gov (United States)

Dijk, J; van den Broek, R; Nasiulas, G; Beck, A; Reinhardt, R; Wittmann-Liebold, B

1987-08-01

The amino-terminal sequence of ribosomal protein L10 from Halobacterium marismortui has been determined up to residue 54, using both a liquid- and a gas-phase sequenator. The two sequences are in good agreement. The protein is clearly homologous to protein HcuL10 from the related strain Halobacterium cutirubrum. Furthermore, a weaker but distinct homology to ribosomal protein L6 from Escherichia coli and Bacillus stearothermophilus can be detected. In addition to 7 identical amino acids in the first 36 residues in all four sequences a number of conservative replacements occurs, of mainly hydrophobic amino acids. In this common region the pattern of conserved amino acids suggests the presence of a beta-alpha fold as it occurs in ribosomal proteins L12 and L30. Furthermore, several potential cases of homology to other ribosomal components of the three ur-kingdoms have been found.
Sequence of a cDNA encoding turtle high mobility group 1 protein.

Science.gov (United States)

Zheng, Jifang; Hu, Bi; Wu, Duansheng

2005-07-01

In order to understand sequence information about turtle HMG1 gene, a cDNA encoding HMG1 protein of the Chinese soft-shell turtle (Pelodiscus sinensis) was amplified by RT-PCR from kidney total RNA, and was cloned, sequenced and analyzed. The results revealed that the open reading frame (ORF) of turtle HMG1 cDNA is 606 bp long. The ORF codifies 202 amino acid residues, from which two DNA-binding domains and one polyacidic region are derived. The DNA-binding domains share higher amino acid identity with homologues sequences of chicken (96.5%) and mammalian (74%) than homologues sequence of rainbow trout (67%). The polyacidic region shows 84.6% amino acid homology with the equivalent region of chicken HMG1 cDNA. Turtle HMG1 protein contains 3 Cys residues located at completely conserved positions. Conservation in sequence and structure suggests that the functions of turtle HMG1 cDNA may be highly conserved during evolution. To our knowledge, this is the first report of HMG1 cDNA sequence in any reptilian.
Sifting through genomes with iterative-sequence clustering produces a large, phylogenetically diverse protein-family resource

Directory of Open Access Journals (Sweden)

Sharpton Thomas J

2012-10-01

Full Text Available Abstract Background New computational resources are needed to manage the increasing volume of biological data from genome sequencing projects. One fundamental challenge is the ability to maintain a complete and current catalog of protein diversity. We developed a new approach for the identification of protein families that focuses on the rapid discovery of homologous protein sequences. Results We implemented fully automated and high-throughput procedures to de novo cluster proteins into families based upon global alignment similarity. Our approach employs an iterative clustering strategy in which homologs of known families are sifted out of the search for new families. The resulting reduction in computational complexity enables us to rapidly identify novel protein families found in new genomes and to perform efficient, automated updates that keep pace with genome sequencing. We refer to protein families identified through this approach as “Sifting Families,” or SFams. Our analysis of ~10.5 million protein sequences from 2,928 genomes identified 436,360 SFams, many of which are not represented in other protein family databases. We validated the quality of SFam clustering through statistical as well as network topology–based analyses. Conclusions We describe the rapid identification of SFams and demonstrate how they can be used to annotate genomes and metagenomes. The SFam database catalogs protein-family quality metrics, multiple sequence alignments, hidden Markov models, and phylogenetic trees. Our source code and database are publicly available and will be subject to frequent updates (http://edhar.genomecenter.ucdavis.edu/sifting_families/.
Mass spectrometric protein characterization in proteome analysis using GELoader tip micro-columns packed with various chromatographic material

International Nuclear Information System (INIS)

Larsen, M.R.

2001-01-01

In the early 90'ies mass spectrometry (MS) was introduced as a tool for identifying proteins in protein sequence databases. Since then it has become an integrated tool in protein characterization and is today routinely used to identify proteins separated by gel electrophoresis. A two-tiered mass spectrometric protein identification strategy has recently been proposed. In the first strategy peptide mass maps obtained from the protein of interest are compared with theoretically derived peptide mass maps from proteins in protein sequence databases. If the protein cannot be identified by this strategy, tandem mass spectrometric sequencing is used to generate enough sequence data to identify the protein in protein sequence databases or expressed sequence tag (EST) databases. However, the above strategies primarily identify a protein relatively to the DNA sequence, in which no information about e.g. post-translational modifications (PTMs) is stored. PTMs are known to modify the function, location, solubility and activity of proteins in the cell, and they are therefore very important for understanding living cells. More than 200 different PTMs are known, of which glycosylation, phosphorylation and proteolytic processing are the most common ones. Mass spectrometric analysis of PTMs on gel-separated proteins requires a higher amount of protein than for identification only. In addition, higher sequence coverage from the peptide mass maps or pre-purification of the modified peptides prior to MS analysis, is necessary for detection of putative modified peptides. In this study a multi-tiered strategy, in which GELoader tip micro-columns packed with increasingly more hydrophobic chromatographic material are used in combination with mass spectrometry, is described. The ultimate aim was to gain increased sequence coverage from peptide mixtures derived from gel-separated proteins, in order to locate modified peptides. Graphite powder is described as an alternative to traditional
Facilitating genome navigation : survey sequencing and dense radiation-hybrid gene mapping

NARCIS (Netherlands)

Hitte, C; Madeoy, J; Kirkness, EF; Priat, C; Lorentzen, TD; Senger, F; Thomas, D; Derrien, T; Ramirez, C; Scott, C; Evanno, G; Pullar, B; Cadieu, E; Oza, [No Value; Lourgant, K; Jaffe, DB; Tacher, S; Dreano, S; Berkova, N; Andre, C; Deloukas, P; Fraser, C; Lindblad-Toh, K; Ostrander, EA; Galibert, F

Accurate and comprehensive sequence coverage for large genomes has been restricted to only a few species of specific interest. Lower sequence coverage (survey sequencing) of related species can yield a wealth of information about gene content and putative regulatory elements. But survey sequences
Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

Science.gov (United States)

Currin, Andrew; Swainston, Neil; Day, Philip J.

2015-01-01

The amino acid sequence of a protein affects both its structure and its function. Thus, the ability to modify the sequence, and hence the structure and activity, of individual proteins in a systematic way, opens up many opportunities, both scientifically and (as we focus on here) for exploitation in biocatalysis. Modern methods of synthetic biology, whereby increasingly large sequences of DNA can be synthesised de novo, allow an unprecedented ability to engineer proteins with novel functions. However, the number of possible proteins is far too large to test individually, so we need means for navigating the ‘search space’ of possible protein sequences efficiently and reliably in order to find desirable activities and other properties. Enzymologists distinguish binding (K d) and catalytic (k cat) steps. In a similar way, judicious strategies have blended design (for binding, specificity and active site modelling) with the more empirical methods of classical directed evolution (DE) for improving k cat (where natural evolution rarely seeks the highest values), especially with regard to residues distant from the active site and where the functional linkages underpinning enzyme dynamics are both unknown and hard to predict. Epistasis (where the ‘best’ amino acid at one site depends on that or those at others) is a notable feature of directed evolution. The aim of this review is to highlight some of the approaches that are being developed to allow us to use directed evolution to improve enzyme properties, often dramatically. We note that directed evolution differs in a number of ways from natural evolution, including in particular the available mechanisms and the likely selection pressures. Thus, we stress the opportunities afforded by techniques that enable one to map sequence to (structure and) activity in silico, as an effective means of modelling and exploring protein landscapes. Because known landscapes may be assessed and reasoned about as a whole
A theoretical justification for single molecule peptide sequencing.

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Jagannath Swaminathan

2015-02-01

Full Text Available The proteomes of cells, tissues, and organisms reflect active cellular processes and change continuously in response to intracellular and extracellular cues. Deep, quantitative profiling of the proteome, especially if combined with mRNA and metabolite measurements, should provide an unprecedented view of cell state, better revealing functions and interactions of cell components. Molecular diagnostics and biomarker discovery should benefit particularly from the accurate quantification of proteomes, since complex diseases like cancer change protein abundances and modifications. Currently, shotgun mass spectrometry is the primary technology for high-throughput protein identification and quantification; while powerful, it lacks high sensitivity and coverage. We draw parallels with next-generation DNA sequencing and propose a strategy, termed fluorosequencing, for sequencing peptides in a complex protein sample at the level of single molecules. In the proposed approach, millions of individual fluorescently labeled peptides are visualized in parallel, monitoring changing patterns of fluorescence intensity as N-terminal amino acids are sequentially removed, and using the resulting fluorescence signatures (fluorosequences to uniquely identify individual peptides. We introduce a theoretical foundation for fluorosequencing and, by using Monte Carlo computer simulations, we explore its feasibility, anticipate the most likely experimental errors, quantify their potential impact, and discuss the broad potential utility offered by a high-throughput peptide sequencing technology.
DNA-binding proteins from marine bacteria expand the known sequence diversity of TALE-like repeats.

Science.gov (United States)

de Lange, Orlando; Wolf, Christina; Thiel, Philipp; Krüger, Jens; Kleusch, Christian; Kohlbacher, Oliver; Lahaye, Thomas

2015-11-16

Transcription Activator-Like Effectors (TALEs) of Xanthomonas bacteria are programmable DNA binding proteins with unprecedented target specificity. Comparative studies into TALE repeat structure and function are hindered by the limited sequence variation among TALE repeats. More sequence-diverse TALE-like proteins are known from Ralstonia solanacearum (RipTALs) and Burkholderia rhizoxinica (Bats), but RipTAL and Bat repeats are conserved with those of TALEs around the DNA-binding residue. We study two novel marine-organism TALE-like proteins (MOrTL1 and MOrTL2), the first to date of non-terrestrial origin. We have assessed their DNA-binding properties and modelled repeat structures. We found that repeats from these proteins mediate sequence specific DNA binding conforming to the TALE code, despite low sequence similarity to TALE repeats, and with novel residues around the BSR. However, MOrTL1 repeats show greater sequence discriminating power than MOrTL2 repeats. Sequence alignments show that there are only three residues conserved between repeats of all TALE-like proteins including the two new additions. This conserved motif could prove useful as an identifier for future TALE-likes. Additionally, comparing MOrTL repeats with those of other TALE-likes suggests a common evolutionary origin for the TALEs, RipTALs and Bats. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
CISAPS: Complex Informational Spectrum for the Analysis of Protein Sequences

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Charalambos Chrysostomou

2015-01-01

Full Text Available Complex informational spectrum analysis for protein sequences (CISAPS and its web-based server are developed and presented. As recent studies show, only the use of the absolute spectrum in the analysis of protein sequences using the informational spectrum analysis is proven to be insufficient. Therefore, CISAPS is developed to consider and provide results in three forms including absolute, real, and imaginary spectrum. Biologically related features to the analysis of influenza A subtypes as presented as a case study in this study can also appear individually either in the real or imaginary spectrum. As the results presented, protein classes can present similarities or differences according to the features extracted from CISAPS web server. These associations are probable to be related with the protein feature that the specific amino acid index represents. In addition, various technical issues such as zero-padding and windowing that may affect the analysis are also addressed. CISAPS uses an expanded list of 611 unique amino acid indices where each one represents a different property to perform the analysis. This web-based server enables researchers with little knowledge of signal processing methods to apply and include complex informational spectrum analysis to their work.
Identification of a novel Plasmopara halstedii elicitor protein combining de novo peptide sequencing algorithms and RACE-PCR

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Madlung Johannes

2010-05-01

Full Text Available Abstract Background Often high-quality MS/MS spectra of tryptic peptides do not match to any database entry because of only partially sequenced genomes and therefore, protein identification requires de novo peptide sequencing. To achieve protein identification of the economically important but still unsequenced plant pathogenic oomycete Plasmopara halstedii, we first evaluated the performance of three different de novo peptide sequencing algorithms applied to a protein digests of standard proteins using a quadrupole TOF (QStar Pulsar i. Results The performance order of the algorithms was PEAKS online > PepNovo > CompNovo. In summary, PEAKS online correctly predicted 45% of measured peptides for a protein test data set. All three de novo peptide sequencing algorithms were used to identify MS/MS spectra of tryptic peptides of an unknown 57 kDa protein of P. halstedii. We found ten de novo sequenced peptides that showed homology to a Phytophthora infestans protein, a closely related organism of P. halstedii. Employing a second complementary approach, verification of peptide prediction and protein identification was performed by creation of degenerate primers for RACE-PCR and led to an ORF of 1,589 bp for a hypothetical phosphoenolpyruvate carboxykinase. Conclusions Our study demonstrated that identification of proteins within minute amounts of sample material improved significantly by combining sensitive LC-MS methods with different de novo peptide sequencing algorithms. In addition, this is the first study that verified protein prediction from MS data by also employing a second complementary approach, in which RACE-PCR led to identification of a novel elicitor protein in P. halstedii.
Top-Down Hydrogen-Deuterium Exchange Analysis of Protein Structures Using Ultraviolet Photodissociation.

Science.gov (United States)

Brodie, Nicholas I; Huguet, Romain; Zhang, Terry; Viner, Rosa; Zabrouskov, Vlad; Pan, Jingxi; Petrotchenko, Evgeniy V; Borchers, Christoph H

2018-03-06

Top-down hydrogen-deuterium exchange (HDX) analysis using electron capture or transfer dissociation Fourier transform mass spectrometry (FTMS) is a powerful method for the analysis of secondary structure of proteins in solution. The resolution of the method is a function of the degree of fragmentation of backbone bonds in the proteins. While fragmentation is usually extensive near the N- and C-termini, electron capture (ECD) or electron transfer dissociation (ETD) fragmentation methods sometimes lack good coverage of certain regions of the protein, most often in the middle of the sequence. Ultraviolet photodissociation (UVPD) is a recently developed fast-fragmentation technique, which provides extensive backbone fragmentation that can be complementary in sequence coverage to the aforementioned electron-based fragmentation techniques. Here, we explore the application of electrospray ionization (ESI)-UVPD FTMS on an Orbitrap Fusion Lumos Tribrid mass spectrometer to top-down HDX analysis of proteins. We have incorporated UVPD-specific fragment-ion types and fragment-ion mixtures into our isotopic envelope fitting software (HDX Match) for the top-down HDX analysis. We have shown that UVPD data is complementary to ETD, thus improving the overall resolution when used as a combined approach.
Prediction of flexible/rigid regions from protein sequences using k-spaced amino acid pairs

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Ruan Jishou

2007-04-01

Full Text Available Abstract Background Traditionally, it is believed that the native structure of a protein corresponds to a global minimum of its free energy. However, with the growing number of known tertiary (3D protein structures, researchers have discovered that some proteins can alter their structures in response to a change in their surroundings or with the help of other proteins or ligands. Such structural shifts play a crucial role with respect to the protein function. To this end, we propose a machine learning method for the prediction of the flexible/rigid regions of proteins (referred to as FlexRP; the method is based on a novel sequence representation and feature selection. Knowledge of the flexible/rigid regions may provide insights into the protein folding process and the 3D structure prediction. Results The flexible/rigid regions were defined based on a dataset, which includes protein sequences that have multiple experimental structures, and which was previously used to study the structural conservation of proteins. Sequences drawn from this dataset were represented based on feature sets that were proposed in prior research, such as PSI-BLAST profiles, composition vector and binary sequence encoding, and a newly proposed representation based on frequencies of k-spaced amino acid pairs. These representations were processed by feature selection to reduce the dimensionality. Several machine learning methods for the prediction of flexible/rigid regions and two recently proposed methods for the prediction of conformational changes and unstructured regions were compared with the proposed method. The FlexRP method, which applies Logistic Regression and collocation-based representation with 95 features, obtained 79.5% accuracy. The two runner-up methods, which apply the same sequence representation and Support Vector Machines (SVM and Naïve Bayes classifiers, obtained 79.2% and 78.4% accuracy, respectively. The remaining considered methods are
Rapid detection and purification of sequence specific DNA binding proteins using magnetic separation

Directory of Open Access Journals (Sweden)

TIJANA SAVIC

2006-02-01

Full Text Available In this paper, a method for the rapid identification and purification of sequence specific DNA binding proteins based on magnetic separation is presented. This method was applied to confirm the binding of the human recombinant USF1 protein to its putative binding site (E-box within the human SOX3 protomer. It has been shown that biotinylated DNA attached to streptavidin magnetic particles specifically binds the USF1 protein in the presence of competitor DNA. It has also been demonstrated that the protein could be successfully eluted from the beads, in high yield and with restored DNA binding activity. The advantage of these procedures is that they could be applied for the identification and purification of any high-affinity sequence-specific DNA binding protein with only minor modifications.
Fast computational methods for predicting protein structure from primary amino acid sequence

Science.gov (United States)

Agarwal, Pratul Kumar [Knoxville, TN

2011-07-19

The present invention provides a method utilizing primary amino acid sequence of a protein, energy minimization, molecular dynamics and protein vibrational modes to predict three-dimensional structure of a protein. The present invention also determines possible intermediates in the protein folding pathway. The present invention has important applications to the design of novel drugs as well as protein engineering. The present invention predicts the three-dimensional structure of a protein independent of size of the protein, overcoming a significant limitation in the prior art.

Analysis of correlations between sites in models of protein sequences

International Nuclear Information System (INIS)

Giraud, B.G.; Lapedes, A.; Liu, L.C.

1998-01-01

A criterion based on conditional probabilities, related to the concept of algorithmic distance, is used to detect correlated mutations at noncontiguous sites on sequences. We apply this criterion to the problem of analyzing correlations between sites in protein sequences; however, the analysis applies generally to networks of interacting sites with discrete states at each site. Elementary models, where explicit results can be derived easily, are introduced. The number of states per site considered ranges from 2, illustrating the relation to familiar classical spin systems, to 20 states, suitable for representing amino acids. Numerical simulations show that the criterion remains valid even when the genetic history of the data samples (e.g., protein sequences), as represented by a phylogenetic tree, introduces nonindependence between samples. Statistical fluctuations due to finite sampling are also investigated and do not invalidate the criterion. A subsidiary result is found: The more homogeneous a population, the more easily its average properties can drift from the properties of its ancestor. copyright 1998 The American Physical Society
Sequence walkers: a graphical method to display how binding proteins interact with DNA or RNA sequences | Center for Cancer Research

Science.gov (United States)

A graphical method is presented for displaying how binding proteins and other macromolecules interact with individual bases of nucleotide sequences. Characters representing the sequence are either oriented normally and placed above a line indicating favorable contact, or upside-down and placed below the line indicating unfavorable contact. The positive or negative height of each letter shows the contribution of that base to the average sequence conservation of the binding site, as represented by a sequence logo.
DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier.

Science.gov (United States)

Kulmanov, Maxat; Khan, Mohammed Asif; Hoehndorf, Robert; Wren, Jonathan

2018-02-15

A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein-protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations. Web server: http://deepgo.bio2vec.net, Source code: https://github.com/bio-ontology-research-group/deepgo. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.
Determining and comparing protein function in Bacterial genome sequences

DEFF Research Database (Denmark)

Vesth, Tammi Camilla

of this class have very little homology to other known genomes making functional annotation based on sequence similarity very difficult. Inspired in part by this analysis, an approach for comparative functional annotation was created based public sequenced genomes, CMGfunc. Functionally related groups......In November 2013, there was around 21.000 different prokaryotic genomes sequenced and publicly available, and the number is growing daily with another 20.000 or more genomes expected to be sequenced and deposited by the end of 2014. An important part of the analysis of this data is the functional...... annotation of genes – the descriptions assigned to genes that describe the likely function of the encoded proteins. This process is limited by several factors, including the definition of a function which can be more or less specific as well as how many genes can actually be assigned a function based...
Biases in Drosophila melanogaster protein trap screens

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Müller Ilka

2009-05-01

Full Text Available Abstract Background The ability to localise or follow endogenous proteins in real time in vivo is of tremendous utility for cell biology or systems biology studies. Protein trap screens utilise the random genomic insertion of a transposon-borne artificial reporter exon (e.g. encoding the green fluorescent protein, GFP into an intron of an endogenous gene to generate a fluorescent fusion protein. Despite recent efforts aimed at achieving comprehensive coverage of the genes encoded in the Drosophila genome, the repertoire of genes that yield protein traps is still small. Results We analysed the collection of available protein trap lines in Drosophila melanogaster and identified potential biases that are likely to restrict genome coverage in protein trap screens. The protein trap screens investigated here primarily used P-element vectors and thus exhibit some of the same positional biases associated with this transposon that are evident from the comprehensive Drosophila Gene Disruption Project. We further found that protein trap target genes usually exhibit broad and persistent expression during embryonic development, which is likely to facilitate better detection. In addition, we investigated the likely influence of the GFP exon on host protein structure and found that protein trap insertions have a significant bias for exon-exon boundaries that encode disordered protein regions. 38.8% of GFP insertions land in disordered protein regions compared with only 23.4% in the case of non-trapping P-element insertions landing in coding sequence introns (p -4. Interestingly, even in cases where protein domains are predicted, protein trap insertions frequently occur in regions encoding surface exposed areas that are likely to be functionally neutral. Considering the various biases observed, we predict that less than one third of intron-containing genes are likely to be amenable to trapping by the existing methods. Conclusion Our analyses suggest that the
FASTERp: A Feature Array Search Tool for Estimating Resemblance of Protein Sequences

Energy Technology Data Exchange (ETDEWEB)

Macklin, Derek; Egan, Rob; Wang, Zhong

2014-03-14

Metagenome sequencing efforts have provided a large pool of billions of genes for identifying enzymes with desirable biochemical traits. However, homology search with billions of genes in a rapidly growing database has become increasingly computationally impractical. Here we present our pilot efforts to develop a novel alignment-free algorithm for homology search. Specifically, we represent individual proteins as feature vectors that denote the presence or absence of short kmers in the protein sequence. Similarity between feature vectors is then computed using the Tanimoto score, a distance metric that can be rapidly computed on bit string representations of feature vectors. Preliminary results indicate good correlation with optimal alignment algorithms (Spearman r of 0.87, ~;;1,000,000 proteins from Pfam), as well as with heuristic algorithms such as BLAST (Spearman r of 0.86, ~;;1,000,000 proteins). Furthermore, a prototype of FASTERp implemented in Python runs approximately four times faster than BLAST on a small scale dataset (~;;1000 proteins). We are optimizing and scaling to improve FASTERp to enable rapid homology searches against billion-protein databases, thereby enabling more comprehensive gene annotation efforts.
muBLASTP: database-indexed protein sequence search on multicore CPUs.

Science.gov (United States)

Zhang, Jing; Misra, Sanchit; Wang, Hao; Feng, Wu-Chun

2016-11-04

The Basic Local Alignment Search Tool (BLAST) is a fundamental program in the life sciences that searches databases for sequences that are most similar to a query sequence. Currently, the BLAST algorithm utilizes a query-indexed approach. Although many approaches suggest that sequence search with a database index can achieve much higher throughput (e.g., BLAT, SSAHA, and CAFE), they cannot deliver the same level of sensitivity as the query-indexed BLAST, i.e., NCBI BLAST, or they can only support nucleotide sequence search, e.g., MegaBLAST. Due to different challenges and characteristics between query indexing and database indexing, the existing techniques for query-indexed search cannot be used into database indexed search. muBLASTP, a novel database-indexed BLAST for protein sequence search, delivers identical hits returned to NCBI BLAST. On Intel Haswell multicore CPUs, for a single query, the single-threaded muBLASTP achieves up to a 4.41-fold speedup for alignment stages, and up to a 1.75-fold end-to-end speedup over single-threaded NCBI BLAST. For a batch of queries, the multithreaded muBLASTP achieves up to a 5.7-fold speedups for alignment stages, and up to a 4.56-fold end-to-end speedup over multithreaded NCBI BLAST. With a newly designed index structure for protein database and associated optimizations in BLASTP algorithm, we re-factored BLASTP algorithm for modern multicore processors that achieves much higher throughput with acceptable memory footprint for the database index.
Isolation and N-terminal sequencing of a novel cadmium-binding protein from Boletus edulis

Science.gov (United States)

Collin-Hansen, C.; Andersen, R. A.; Steinnes, E.

2003-05-01

A Cd-binding protein was isolated from the popular edible mushroom Boletus edulis, which is a hyperaccumulator of both Cd and Hg. Wild-growing samples of B. edulis were collected from soils rich in Cd. Cd radiotracer was added to the crude protein preparation obtained from ethanol precipitation of heat-treated cytosol. Proteins were then further separated in two consecutive steps; gel filtration and anion exchange chromatography. In both steps the Cd radiotracer profile showed only one distinct peak, which corresponded well with the profiles of endogenous Cd obtained by atomic absorption spectrophotometry (AAS). Concentrations of the essential elements Cu and Zn were low in the protein fractions high in Cd. N-terminal sequencing performed on the Cd-binding protein fractions revealed a protein with a novel amino acid sequence, which contained aromatic amino acids as well as proline. Both the N-terminal sequencing and spectrofluorimetric analysis with EDTA and ABD-F (4-aminosulfonyl-7-fluoro-2, 1, 3-benzoxadiazole) failed to detect cysteine in the Cd-binding fractions. These findings conclude that the novel protein does not belong to the metallothionein family. The results suggest a role for the protein in Cd transport and storage, and they are of importance in view of toxicology and food chemistry, but also for environmental protection.
Sequence charge decoration dictates coil-globule transition in intrinsically disordered proteins

Science.gov (United States)

Firman, Taylor; Ghosh, Kingshuk

2018-03-01

We present an analytical theory to compute conformations of heteropolymers—applicable to describe disordered proteins—as a function of temperature and charge sequence. The theory describes coil-globule transition for a given protein sequence when temperature is varied and has been benchmarked against the all-atom Monte Carlo simulation (using CAMPARI) of intrinsically disordered proteins (IDPs). In addition, the model quantitatively shows how subtle alterations of charge placement in the primary sequence—while maintaining the same charge composition—can lead to significant changes in conformation, even as drastic as a coil (swelled above a purely random coil) to globule (collapsed below a random coil) and vice versa. The theory provides insights on how to control (enhance or suppress) these changes by tuning the temperature (or solution condition) and charge decoration. As an application, we predict the distribution of conformations (at room temperature) of all naturally occurring IDPs in the DisProt database and notice significant size variation even among IDPs with a similar composition of positive and negative charges. Based on this, we provide a new diagram-of-states delineating the sequence-conformation relation for proteins in the DisProt database. Next, we study the effect of post-translational modification, e.g., phosphorylation, on IDP conformations. Modifications as little as two-site phosphorylation can significantly alter the size of an IDP with everything else being constant (temperature, salt concentration, etc.). However, not all possible modification sites have the same effect on protein conformations; there are certain "hot spots" that can cause maximal change in conformation. The location of these "hot spots" in the parent sequence can readily be identified by using a sequence charge decoration metric originally introduced by Sawle and Ghosh. The ability of our model to predict conformations (both expanded and collapsed states) of IDPs at
An estimated 5% of new protein structures solved today represent a new Pfam family

International Nuclear Information System (INIS)

Mistry, Jaina; Kloppmann, Edda; Rost, Burkhard; Punta, Marco

2013-01-01

This study uses the Pfam database to show that the sequence redundancy of protein structures deposited in the PDB is increasing. The possible reasons behind this trend are discussed. High-resolution structural knowledge is key to understanding how proteins function at the molecular level. The number of entries in the Protein Data Bank (PDB), the repository of all publicly available protein structures, continues to increase, with more than 8000 structures released in 2012 alone. The authors of this article have studied how structural coverage of the protein-sequence space has changed over time by monitoring the number of Pfam families that acquired their first representative structure each year from 1976 to 2012. Twenty years ago, for every 100 new PDB entries released, an estimated 20 Pfam families acquired their first structure. By 2012, this decreased to only about five families per 100 structures. The reasons behind the slower pace at which previously uncharacterized families are being structurally covered were investigated. It was found that although more than 50% of current Pfam families are still without a structural representative, this set is enriched in families that are small, functionally uncharacterized or rich in problem features such as intrinsically disordered and transmembrane regions. While these are important constraints, the reasons why it may not yet be time to give up the pursuit of a targeted but more comprehensive structural coverage of the protein-sequence space are discussed
Exploring Sequence Characteristics Related to High- Level Production of Secreted Proteins in Aspergillus niger

NARCIS (Netherlands)

Van den Berg, B.A.; Reinders, M.J.T.; Hulsman, M.; Wu, L.; Pel, H.J.; Roubos, J.A.; De Ridder, D.

2012-01-01

Protein sequence features are explored in relation to the production of over-expressed extracellular proteins by fungi. Knowledge on features influencing protein production and secretion could be employed to improve enzyme production levels in industrial bioprocesses via protein engineering. A large
An artificial functional family filter in homolog searching in next-generation sequencing metagenomics.

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Ruofei Du

Full Text Available In functional metagenomics, BLAST homology search is a common method to classify metagenomic reads into protein/domain sequence families such as Clusters of Orthologous Groups of proteins (COGs in order to quantify the abundance of each COG in the community. The resulting functional profile of the community is then used in downstream analysis to correlate the change in abundance to environmental perturbation, clinical variation, and so on. However, the short read length coupled with next-generation sequencing technologies poses a barrier in this approach, essentially because similarity significance cannot be discerned by searching with short reads. Consequently, artificial functional families are produced, in which those with a large number of reads assigned decreases the accuracy of functional profile dramatically. There is no method available to address this problem. We intended to fill this gap in this paper. We revealed that BLAST similarity scores of homologues for short reads from COG protein members coding sequences are distributed differently from the scores of those derived elsewhere. We showed that, by choosing an appropriate score cut-off, we are able to filter out most artificial families and simultaneously to preserve sufficient information in order to build the functional profile. We also showed that, by incorporated application of BLAST and RPS-BLAST, some artificial families with large read counts can be further identified after the score cutoff filtration. Evaluated on three experimental metagenomic datasets with different coverages, we found that the proposed method is robust against read coverage and consistently outperforms the other E-value cutoff methods currently used in literatures.
A tale of three next generation sequencing platforms: comparison of Ion Torrent, Pacific Biosciences and Illumina MiSeq sequencers

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Quail Michael A

2012-07-01

Full Text Available Abstract Background Next generation sequencing (NGS technology has revolutionized genomic and genetic research. The pace of change in this area is rapid with three major new sequencing platforms having been released in 2011: Ion Torrent’s PGM, Pacific Biosciences’ RS and the Illumina MiSeq. Here we compare the results obtained with those platforms to the performance of the Illumina HiSeq, the current market leader. In order to compare these platforms, and get sufficient coverage depth to allow meaningful analysis, we have sequenced a set of 4 microbial genomes with mean GC content ranging from 19.3 to 67.7%. Together, these represent a comprehensive range of genome content. Here we report our analysis of that sequence data in terms of coverage distribution, bias, GC distribution, variant detection and accuracy. Results Sequence generated by Ion Torrent, MiSeq and Pacific Biosciences technologies displays near perfect coverage behaviour on GC-rich, neutral and moderately AT-rich genomes, but a profound bias was observed upon sequencing the extremely AT-rich genome of Plasmodium falciparum on the PGM, resulting in no coverage for approximately 30% of the genome. We analysed the ability to call variants from each platform and found that we could call slightly more variants from Ion Torrent data compared to MiSeq data, but at the expense of a higher false positive rate. Variant calling from Pacific Biosciences data was possible but higher coverage depth was required. Context specific errors were observed in both PGM and MiSeq data, but not in that from the Pacific Biosciences platform. Conclusions All three fast turnaround sequencers evaluated here were able to generate usable sequence. However there are key differences between the quality of that data and the applications it will support.
Revised Mimivirus major capsid protein sequence reveals intron-containing gene structure and extra domain

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Suzan-Monti Marie

2009-05-01

Full Text Available Abstract Background Acanthamoebae polyphaga Mimivirus (APM is the largest known dsDNA virus. The viral particle has a nearly icosahedral structure with an internal capsid shell surrounded with a dense layer of fibrils. A Capsid protein sequence, D13L, was deduced from the APM L425 coding gene and was shown to be the most abundant protein found within the viral particle. However this protein remained poorly characterised until now. A revised protein sequence deposited in a database suggested an additional N-terminal stretch of 142 amino acids missing from the original deduced sequence. This result led us to investigate the L425 gene structure and the biochemical properties of the complete APM major Capsid protein. Results This study describes the full length 3430 bp Capsid coding gene and characterises the 593 amino acids long corresponding Capsid protein 1. The recombinant full length protein allowed the production of a specific monoclonal antibody able to detect the Capsid protein 1 within the viral particle. This protein appeared to be post-translationnally modified by glycosylation and phosphorylation. We proposed a secondary structure prediction of APM Capsid protein 1 compared to the Capsid protein structure of Paramecium Bursaria Chlorella Virus 1, another member of the Nucleo-Cytoplasmic Large DNA virus family. Conclusion The characterisation of the full length L425 Capsid coding gene of Acanthamoebae polyphaga Mimivirus provides new insights into the structure of the main Capsid protein. The production of a full length recombinant protein will be useful for further structural studies.
Interactions of rat repetitive sequence MspI8 with nuclear matrix proteins during spermatogenesis

International Nuclear Information System (INIS)

Rogolinski, J.; Widlak, P.; Rzeszowska-Wolny, J.

1996-01-01

Using the Southwestern blot analysis we have studied the interactions between rat repetitive sequence MspI8 and the nuclear matrix proteins of rats testis cells. Starting from 2 weeks the young to adult animal showed differences in type of testis nuclear matrix proteins recognizing the MspI8 sequence. The same sets of nuclear matrix proteins were detected in some enriched in spermatocytes and spermatids and obtained after fractionation of cells of adult animal by the velocity sedimentation technique. (author). 21 refs, 5 figs
Protein model discrimination using mutational sensitivity derived from deep sequencing.

Science.gov (United States)

Adkar, Bharat V; Tripathi, Arti; Sahoo, Anusmita; Bajaj, Kanika; Goswami, Devrishi; Chakrabarti, Purbani; Swarnkar, Mohit K; Gokhale, Rajesh S; Varadarajan, Raghavan

2012-02-08

A major bottleneck in protein structure prediction is the selection of correct models from a pool of decoys. Relative activities of ∼1,200 individual single-site mutants in a saturation library of the bacterial toxin CcdB were estimated by determining their relative populations using deep sequencing. This phenotypic information was used to define an empirical score for each residue (RankScore), which correlated with the residue depth, and identify active-site residues. Using these correlations, ∼98% of correct models of CcdB (RMSD ≤ 4Å) were identified from a large set of decoys. The model-discrimination methodology was further validated on eleven different monomeric proteins using simulated RankScore values. The methodology is also a rapid, accurate way to obtain relative activities of each mutant in a large pool and derive sequence-structure-function relationships without protein isolation or characterization. It can be applied to any system in which mutational effects can be monitored by a phenotypic readout. Copyright © 2012 Elsevier Ltd. All rights reserved.
Mapping a nucleolar targeting sequence of an RNA binding nucleolar protein, Nop25

International Nuclear Information System (INIS)

Fujiwara, Takashi; Suzuki, Shunji; Kanno, Motoko; Sugiyama, Hironobu; Takahashi, Hisaaki; Tanaka, Junya

2006-01-01

Nop25 is a putative RNA binding nucleolar protein associated with rRNA transcription. The present study was undertaken to determine the mechanism of Nop25 localization in the nucleolus. Deletion experiments of Nop25 amino acid sequence showed Nop25 to contain a nuclear targeting sequence in the N-terminal and a nucleolar targeting sequence in the C-terminal. By expressing derivative peptides from the C-terminal as GFP-fusion proteins in the cells, a lysine and arginine residue-enriched peptide (KRKHPRRAQDSTKKPPSATRTSKTQRRRR) allowed a GFP-fusion protein to be transported and fully retained in the nucleolus. When the peptide was fused with cMyc epitope and expressed in the cells, a cMyc epitope was then detected in the nucleolus. Nop25 did not localize in the nucleolus by deletion of the peptide from Nop25. Furthermore, deletion of a subdomain (KRKHPRRAQ) in the peptide or amino acid substitution of lysine and arginine residues in the subdomain resulted in the loss of Nop25 nucleolar localization. These results suggest that the lysine and arginine residue-enriched peptide is the most prominent nucleolar targeting sequence of Nop25 and that the long stretch of basic residues might play an important role in the nucleolar localization of Nop25. Although Nop25 contained putative SUMOylation, phosphorylation and glycosylation sites, the amino acid substitution in these sites had no effect on the nucleolar localization, thus suggesting that these post-translational modifications did not contribute to the localization of Nop25 in the nucleolus. The treatment of the cells, which expressed a GFP-fusion protein with a nucleolar targeting sequence of Nop25, with RNase A resulted in a complete dislocation of the protein from the nucleolus. These data suggested that the nucleolar targeting sequence might therefore play an important role in the binding of Nop25 to RNA molecules and that the RNA binding of Nop25 might be essential for the nucleolar localization of Nop25
Prediction of Carbohydrate-Binding Proteins from Sequences Using Support Vector Machines

Directory of Open Access Journals (Sweden)

Seizi Someya

2010-01-01

Full Text Available Carbohydrate-binding proteins are proteins that can interact with sugar chains but do not modify them. They are involved in many physiological functions, and we have developed a method for predicting them from their amino acid sequences. Our method is based on support vector machines (SVMs. We first clarified the definition of carbohydrate-binding proteins and then constructed positive and negative datasets with which the SVMs were trained. By applying the leave-one-out test to these datasets, our method delivered 0.92 of the area under the receiver operating characteristic (ROC curve. We also examined two amino acid grouping methods that enable effective learning of sequence patterns and evaluated the performance of these methods. When we applied our method in combination with the homology-based prediction method to the annotated human genome database, H-invDB, we found that the true positive rate of prediction was improved.
Formation of a Multiple Protein Complex on the Adenovirus Packaging Sequence by the IVa2 Protein▿

OpenAIRE

Tyler, Ryan E.; Ewing, Sean G.; Imperiale, Michael J.

2007-01-01

During adenovirus virion assembly, the packaging sequence mediates the encapsidation of the viral genome. This sequence is composed of seven functional units, termed A repeats. Recent evidence suggests that the adenovirus IVa2 protein binds the packaging sequence and is involved in packaging of the genome. Study of the IVa2-packaging sequence interaction has been hindered by difficulty in purifying the protein produced in virus-infected cells or by recombinant techniques. We report the first ...
Discovering approximate-associated sequence patterns for protein-DNA interactions

KAUST Repository

Chan, Tak Ming

2010-12-30

Motivation: The bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) are fundamental protein-DNA interactions in transcriptional regulation. Extensive efforts have been made to better understand the protein-DNA interactions. Recent mining on exact TF-TFBS-associated sequence patterns (rules) has shown great potentials and achieved very promising results. However, exact rules cannot handle variations in real data, resulting in limited informative rules. In this article, we generalize the exact rules to approximate ones for both TFs and TFBSs, which are essential for biological variations. Results: A progressive approach is proposed to address the approximation to alleviate the computational requirements. Firstly, similar TFBSs are grouped from the available TF-TFBS data (TRANSFAC database). Secondly, approximate and highly conserved binding cores are discovered from TF sequences corresponding to each TFBS group. A customized algorithm is developed for the specific objective. We discover the approximate TF-TFBS rules by associating the grouped TFBS consensuses and TF cores. The rules discovered are evaluated by matching (verifying with) the actual protein-DNA binding pairs from Protein Data Bank (PDB) 3D structures. The approximate results exhibit many more verified rules and up to 300% better verification ratios than the exact ones. The customized algorithm achieves over 73% better verification ratios than traditional methods. Approximate rules (64-79%) are shown statistically significant. Detailed variation analysis and conservation verification on NCBI records demonstrate that the approximate rules reveal both the flexible and specific protein-DNA interactions accurately. The approximate TF-TFBS rules discovered show great generalized capability of exploring more informative binding rules. © The Author 2010. Published by Oxford University Press. All rights reserved.

Large-scale analysis of intrinsic disorder flavors and associated functions in the protein sequence universe.

Science.gov (United States)

Necci, Marco; Piovesan, Damiano; Tosatto, Silvio C E

2016-12-01

Intrinsic disorder (ID) in proteins has been extensively described for the last decade; a large-scale classification of ID in proteins is mostly missing. Here, we provide an extensive analysis of ID in the protein universe on the UniProt database derived from sequence-based predictions in MobiDB. Almost half the sequences contain an ID region of at least five residues. About 9% of proteins have a long ID region of over 20 residues which are more abundant in Eukaryotic organisms and most frequently cover less than 20% of the sequence. A small subset of about 67,000 (out of over 80 million) proteins is fully disordered and mostly found in Viruses. Most proteins have only one ID, with short ID evenly distributed along the sequence and long ID overrepresented in the center. The charged residue composition of Das and Pappu was used to classify ID proteins by structural propensities and corresponding functional enrichment. Swollen Coils seem to be used mainly as structural components and in biosynthesis in both Prokaryotes and Eukaryotes. In Bacteria, they are confined in the nucleoid and in Viruses provide DNA binding function. Coils & Hairpins seem to be specialized in ribosome binding and methylation activities. Globules & Tadpoles bind antigens in Eukaryotes but are involved in killing other organisms and cytolysis in Bacteria. The Undefined class is used by Bacteria to bind toxic substances and mediate transport and movement between and within organisms in Viruses. Fully disordered proteins behave similarly, but are enriched for glycine residues and extracellular structures. © 2016 The Protein Society.
Representation of protein-sequence information by amino acid subalphabets

DEFF Research Database (Denmark)

Andersen, C.A.F.; Brunak, Søren

2004-01-01

-sequence information, using machine learning strategies, where the primary goal is the discovery of novel powerful representations for use in AI techniques. In the case of proteins and the 20 different amino acids they typically contain, it is also a secondary goal to discover how the current selection of amino acids...
RStrucFam: a web server to associate structure and cognate RNA for RNA-binding proteins from sequence information.

Science.gov (United States)

Ghosh, Pritha; Mathew, Oommen K; Sowdhamini, Ramanathan

2016-10-07

RNA-binding proteins (RBPs) interact with their cognate RNA(s) to form large biomolecular assemblies. They are versatile in their functionality and are involved in a myriad of processes inside the cell. RBPs with similar structural features and common biological functions are grouped together into families and superfamilies. It will be useful to obtain an early understanding and association of RNA-binding property of sequences of gene products. Here, we report a web server, RStrucFam, to predict the structure, type of cognate RNA(s) and function(s) of proteins, where possible, from mere sequence information. The web server employs Hidden Markov Model scan (hmmscan) to enable association to a back-end database of structural and sequence families. The database (HMMRBP) comprises of 437 HMMs of RBP families of known structure that have been generated using structure-based sequence alignments and 746 sequence-centric RBP family HMMs. The input protein sequence is associated with structural or sequence domain families, if structure or sequence signatures exist. In case of association of the protein with a family of known structures, output features like, multiple structure-based sequence alignment (MSSA) of the query with all others members of that family is provided. Further, cognate RNA partner(s) for that protein, Gene Ontology (GO) annotations, if any and a homology model of the protein can be obtained. The users can also browse through the database for details pertaining to each family, protein or RNA and their related information based on keyword search or RNA motif search. RStrucFam is a web server that exploits structurally conserved features of RBPs, derived from known family members and imprinted in mathematical profiles, to predict putative RBPs from sequence information. Proteins that fail to associate with such structure-centric families are further queried against the sequence-centric RBP family HMMs in the HMMRBP database. Further, all other essential
Coverage analysis of lists of genes involved in heterogeneous ...

Indian Academy of Sciences (India)

The rationale of our study was to specifically evaluate sequence coverage using ... Catherine Badens and Martin Krahn contributed equally to this work. the analysis of ... (Life Technologies) with sequencing data processing using the Torrent ... map4 parameter, which is the default option to balance rapid- ity and maintain a ...
Domain fusion analysis by applying relational algebra to protein sequence and domain databases.

Science.gov (United States)

Truong, Kevin; Ikura, Mitsuhiko

2003-05-06

Domain fusion analysis is a useful method to predict functionally linked proteins that may be involved in direct protein-protein interactions or in the same metabolic or signaling pathway. As separate domain databases like BLOCKS, PROSITE, Pfam, SMART, PRINTS-S, ProDom, TIGRFAMs, and amalgamated domain databases like InterPro continue to grow in size and quality, a computational method to perform domain fusion analysis that leverages on these efforts will become increasingly powerful. This paper proposes a computational method employing relational algebra to find domain fusions in protein sequence databases. The feasibility of this method was illustrated on the SWISS-PROT+TrEMBL sequence database using domain predictions from the Pfam HMM (hidden Markov model) database. We identified 235 and 189 putative functionally linked protein partners in H. sapiens and S. cerevisiae, respectively. From scientific literature, we were able to confirm many of these functional linkages, while the remainder offer testable experimental hypothesis. Results can be viewed at http://calcium.uhnres.utoronto.ca/pi. As the analysis can be computed quickly on any relational database that supports standard SQL (structured query language), it can be dynamically updated along with the sequence and domain databases, thereby improving the quality of predictions over time.
Adaptive GDDA-BLAST: fast and efficient algorithm for protein sequence embedding.

Directory of Open Access Journals (Sweden)

Yoojin Hong

2010-10-01

Full Text Available A major computational challenge in the genomic era is annotating structure/function to the vast quantities of sequence information that is now available. This problem is illustrated by the fact that most proteins lack comprehensive annotations, even when experimental evidence exists. We previously theorized that embedded-alignment profiles (simply "alignment profiles" hereafter provide a quantitative method that is capable of relating the structural and functional properties of proteins, as well as their evolutionary relationships. A key feature of alignment profiles lies in the interoperability of data format (e.g., alignment information, physio-chemical information, genomic information, etc.. Indeed, we have demonstrated that the Position Specific Scoring Matrices (PSSMs are an informative M-dimension that is scored by quantitatively measuring the embedded or unmodified sequence alignments. Moreover, the information obtained from these alignments is informative, and remains so even in the "twilight zone" of sequence similarity (<25% identity. Although our previous embedding strategy was powerful, it suffered from contaminating alignments (embedded AND unmodified and high computational costs. Herein, we describe the logic and algorithmic process for a heuristic embedding strategy named "Adaptive GDDA-BLAST." Adaptive GDDA-BLAST is, on average, up to 19 times faster than, but has similar sensitivity to our previous method. Further, data are provided to demonstrate the benefits of embedded-alignment measurements in terms of detecting structural homology in highly divergent protein sequences and isolating secondary structural elements of transmembrane and ankyrin-repeat domains. Together, these advances allow further exploration of the embedded alignment data space within sufficiently large data sets to eventually induce relevant statistical inferences. We show that sequence embedding could serve as one of the vehicles for measurement of low
Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm

KAUST Repository

Wong, Ka Chun

2011-02-05

Protein-DNA bindings are essential activities. Understanding them forms the basis for further deciphering of biological and genetic systems. In particular, the protein-DNA bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) play a central role in gene transcription. Comprehensive TF-TFBS binding sequence pairs have been found in a recent study. However, they are in one-to-one mappings which cannot fully reflect the many-to-many mappings within the bindings. An evolutionary algorithm is proposed to learn generalized representations (many-to-many mappings) from the TF-TFBS binding sequence pairs (one-to-one mappings). The generalized pairs are shown to be more meaningful than the original TF-TFBS binding sequence pairs. Some representative examples have been analyzed in this study. In particular, it shows that the TF-TFBS binding sequence pairs are not presumably in one-to-one mappings. They can also exhibit many-to-many mappings. The proposed method can help us extract such many-to-many information from the one-to-one TF-TFBS binding sequence pairs found in the previous study, providing further knowledge in understanding the bindings between TFs and TFBSs. © 2011 Springer-Verlag.
Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm

KAUST Repository

Wong, Ka Chun; Peng, Chengbin; Wong, Manhon; Leung, Kwongsak

2011-01-01

Protein-DNA bindings are essential activities. Understanding them forms the basis for further deciphering of biological and genetic systems. In particular, the protein-DNA bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) play a central role in gene transcription. Comprehensive TF-TFBS binding sequence pairs have been found in a recent study. However, they are in one-to-one mappings which cannot fully reflect the many-to-many mappings within the bindings. An evolutionary algorithm is proposed to learn generalized representations (many-to-many mappings) from the TF-TFBS binding sequence pairs (one-to-one mappings). The generalized pairs are shown to be more meaningful than the original TF-TFBS binding sequence pairs. Some representative examples have been analyzed in this study. In particular, it shows that the TF-TFBS binding sequence pairs are not presumably in one-to-one mappings. They can also exhibit many-to-many mappings. The proposed method can help us extract such many-to-many information from the one-to-one TF-TFBS binding sequence pairs found in the previous study, providing further knowledge in understanding the bindings between TFs and TFBSs. © 2011 Springer-Verlag.
SPiCE : A web-based tool for sequence-based protein classification and exploration

NARCIS (Netherlands)

Van den Berg, B.A.; Reinders, M.J.; Roubos, J.A.; De Ridder, D.

2014-01-01

Background Amino acid sequences and features extracted from such sequences have been used to predict many protein properties, such as subcellular localization or solubility, using classifier algorithms. Although software tools are available for both feature extraction and classifier construction,
High-coverage sequencing and annotated assembly of the genome of the Australian dragon lizard Pogona vitticeps.

Science.gov (United States)

Georges, Arthur; Li, Qiye; Lian, Jinmin; O'Meally, Denis; Deakin, Janine; Wang, Zongji; Zhang, Pei; Fujita, Matthew; Patel, Hardip R; Holleley, Clare E; Zhou, Yang; Zhang, Xiuwen; Matsubara, Kazumi; Waters, Paul; Graves, Jennifer A Marshall; Sarre, Stephen D; Zhang, Guojie

2015-01-01

The lizards of the family Agamidae are one of the most prominent elements of the Australian reptile fauna. Here, we present a genomic resource built on the basis of a wild-caught male ZZ central bearded dragon Pogona vitticeps. The genomic sequence for P. vitticeps, generated on the Illumina HiSeq 2000 platform, comprised 317 Gbp (179X raw read depth) from 13 insert libraries ranging from 250 bp to 40 kbp. After filtering for low-quality and duplicated reads, 146 Gbp of data (83X) was available for assembly. Exceptionally high levels of heterozygosity (0.85 % of single nucleotide polymorphisms plus sequence insertions or deletions) complicated assembly; nevertheless, 96.4 % of reads mapped back to the assembled scaffolds, indicating that the assembly included most of the sequenced genome. Length of the assembly was 1.8 Gbp in 545,310 scaffolds (69,852 longer than 300 bp), the longest being 14.68 Mbp. N50 was 2.29 Mbp. Genes were annotated on the basis of de novo prediction, similarity to the green anole Anolis carolinensis, Gallus gallus and Homo sapiens proteins, and P. vitticeps transcriptome sequence assemblies, to yield 19,406 protein-coding genes in the assembly, 63 % of which had intact open reading frames. Our assembly captured 99 % (246 of 248) of core CEGMA genes, with 93 % (231) being complete. The quality of the P. vitticeps assembly is comparable or superior to that of other published squamate genomes, and the annotated P. vitticeps genome can be accessed through a genome browser available at https://genomics.canberra.edu.au.
Rapid detection, classification and accurate alignment of up to a million or more related protein sequences.

Science.gov (United States)

Neuwald, Andrew F

2009-08-01

The patterns of sequence similarity and divergence present within functionally diverse, evolutionarily related proteins contain implicit information about corresponding biochemical similarities and differences. A first step toward accessing such information is to statistically analyze these patterns, which, in turn, requires that one first identify and accurately align a very large set of protein sequences. Ideally, the set should include many distantly related, functionally divergent subgroups. Because it is extremely difficult, if not impossible for fully automated methods to align such sequences correctly, researchers often resort to manual curation based on detailed structural and biochemical information. However, multiply-aligning vast numbers of sequences in this way is clearly impractical. This problem is addressed using Multiply-Aligned Profiles for Global Alignment of Protein Sequences (MAPGAPS). The MAPGAPS program uses a set of multiply-aligned profiles both as a query to detect and classify related sequences and as a template to multiply-align the sequences. It relies on Karlin-Altschul statistics for sensitivity and on PSI-BLAST (and other) heuristics for speed. Using as input a carefully curated multiple-profile alignment for P-loop GTPases, MAPGAPS correctly aligned weakly conserved sequence motifs within 33 distantly related GTPases of known structure. By comparison, the sequence- and structurally based alignment methods hmmalign and PROMALS3D misaligned at least 11 and 23 of these regions, respectively. When applied to a dataset of 65 million protein sequences, MAPGAPS identified, classified and aligned (with comparable accuracy) nearly half a million putative P-loop GTPase sequences. A C++ implementation of MAPGAPS is available at http://mapgaps.igs.umaryland.edu. Supplementary data are available at Bioinformatics online.
The YPLGVG sequence of the Nipah virus matrix protein is required for budding

Directory of Open Access Journals (Sweden)

Yan Lianying

2008-11-01

Full Text Available Abstract Background Nipah virus (NiV is a recently emerged paramyxovirus capable of causing fatal disease in a broad range of mammalian hosts, including humans. Together with Hendra virus (HeV, they comprise the genus Henipavirus in the family Paramyxoviridae. Recombinant expression systems have played a crucial role in studying the cell biology of these Biosafety Level-4 restricted viruses. Henipavirus assembly and budding occurs at the plasma membrane, although the details of this process remain poorly understood. Multivesicular body (MVB proteins have been found to play a role in the budding of several enveloped viruses, including some paramyxoviruses, and the recruitment of MVB proteins by viral proteins possessing late budding domains (L-domains has become an important concept in the viral budding process. Previously we developed a system for producing NiV virus-like particles (VLPs and demonstrated that the matrix (M protein possessed an intrinsic budding ability and played a major role in assembly. Here, we have used this system to further explore the budding process by analyzing elements within the M protein that are critical for particle release. Results Using rationally targeted site-directed mutagenesis we show that a NiV M sequence YPLGVG is required for M budding and that mutation or deletion of the sequence abrogates budding ability. Replacement of the native and overlapping Ebola VP40 L-domains with the NiV sequence failed to rescue VP40 budding; however, it did induce the cellular morphology of extensive filamentous projection consistent with wild-type VP40-expressing cells. Cells expressing wild-type NiV M also displayed this morphology, which was dependent on the YPLGVG sequence, and deletion of the sequence also resulted in nuclear localization of M. Dominant-negative VPS4 proteins had no effect on NiV M budding, suggesting that unlike other viruses such as Ebola, NiV M accomplishes budding independent of MVB cellular proteins
A high-coverage draft genome of the mycalesine butterfly Bicyclus anynana.

Science.gov (United States)

Nowell, Reuben W; Elsworth, Ben; Oostra, Vicencio; Zwaan, Bas J; Wheat, Christopher W; Saastamoinen, Marjo; Saccheri, Ilik J; Van't Hof, Arjen E; Wasik, Bethany R; Connahs, Heidi; Aslam, Muhammad L; Kumar, Sujai; Challis, Richard J; Monteiro, Antónia; Brakefield, Paul M; Blaxter, Mark

2017-07-01

The mycalesine butterfly Bicyclus anynana, the "Squinting bush brown," is a model organism in the study of lepidopteran ecology, development, and evolution. Here, we present a draft genome sequence for B. anynana to serve as a genomics resource for current and future studies of this important model species. Seven libraries with insert sizes ranging from 350 bp to 20 kb were constructed using DNA from an inbred female and sequenced using both Illumina and PacBio technology; 128 Gb of raw Illumina data was filtered to 124 Gb and assembled to a final size of 475 Mb (∼×260 assembly coverage). Contigs were scaffolded using mate-pair, transcriptome, and PacBio data into 10 800 sequences with an N50 of 638 kb (longest scaffold 5 Mb). The genome is comprised of 26% repetitive elements and encodes a total of 22 642 predicted protein-coding genes. Recovery of a BUSCO set of core metazoan genes was almost complete (98%). Overall, these metrics compare well with other recently published lepidopteran genomes. We report a high-quality draft genome sequence for Bicyclus anynana. The genome assembly and annotated gene models are available at LepBase (http://ensembl.lepbase.org/index.html). © The Authors 2017. Published by Oxford University Press.
ORFer--retrieval of protein sequences and open reading frames from GenBank and storage into relational databases or text files.

Science.gov (United States)

Büssow, Konrad; Hoffmann, Steve; Sievert, Volker

2002-12-19

Functional genomics involves the parallel experimentation with large sets of proteins. This requires management of large sets of open reading frames as a prerequisite of the cloning and recombinant expression of these proteins. A Java program was developed for retrieval of protein and nucleic acid sequences and annotations from NCBI GenBank, using the XML sequence format. Annotations retrieved by ORFer include sequence name, organism and also the completeness of the sequence. The program has a graphical user interface, although it can be used in a non-interactive mode. For protein sequences, the program also extracts the open reading frame sequence, if available, and checks its correct translation. ORFer accepts user input in the form of single or lists of GenBank GI identifiers or accession numbers. It can be used to extract complete sets of open reading frames and protein sequences from any kind of GenBank sequence entry, including complete genomes or chromosomes. Sequences are either stored with their features in a relational database or can be exported as text files in Fasta or tabulator delimited format. The ORFer program is freely available at http://www.proteinstrukturfabrik.de/orfer. The ORFer program allows for fast retrieval of DNA sequences, protein sequences and their open reading frames and sequence annotations from GenBank. Furthermore, storage of sequences and features in a relational database is supported. Such a database can supplement a laboratory information system (LIMS) with appropriate sequence information.
Neural network and SVM classifiers accurately predict lipid binding proteins, irrespective of sequence homology.

Science.gov (United States)

Bakhtiarizadeh, Mohammad Reza; Moradi-Shahrbabak, Mohammad; Ebrahimi, Mansour; Ebrahimie, Esmaeil

2014-09-07

Due to the central roles of lipid binding proteins (LBPs) in many biological processes, sequence based identification of LBPs is of great interest. The major challenge is that LBPs are diverse in sequence, structure, and function which results in low accuracy of sequence homology based methods. Therefore, there is a need for developing alternative functional prediction methods irrespective of sequence similarity. To identify LBPs from non-LBPs, the performances of support vector machine (SVM) and neural network were compared in this study. Comprehensive protein features and various techniques were employed to create datasets. Five-fold cross-validation (CV) and independent evaluation (IE) tests were used to assess the validity of the two methods. The results indicated that SVM outperforms neural network. SVM achieved 89.28% (CV) and 89.55% (IE) overall accuracy in identification of LBPs from non-LBPs and 92.06% (CV) and 92.90% (IE) (in average) for classification of different LBPs classes. Increasing the number and the range of extracted protein features as well as optimization of the SVM parameters significantly increased the efficiency of LBPs class prediction in comparison to the only previous report in this field. Altogether, the results showed that the SVM algorithm can be run on broad, computationally calculated protein features and offers a promising tool in detection of LBPs classes. The proposed approach has the potential to integrate and improve the common sequence alignment based methods. Copyright © 2014 Elsevier Ltd. All rights reserved.
An improved classification of G-protein-coupled receptors using sequence-derived features

Directory of Open Access Journals (Sweden)

Peng Zhen-Ling

2010-08-01

Full Text Available Abstract Background G-protein-coupled receptors (GPCRs play a key role in diverse physiological processes and are the targets of almost two-thirds of the marketed drugs. The 3 D structures of GPCRs are largely unavailable; however, a large number of GPCR primary sequences are known. To facilitate the identification and characterization of novel receptors, it is therefore very valuable to develop a computational method to accurately predict GPCRs from the protein primary sequences. Results We propose a new method called PCA-GPCR, to predict GPCRs using a comprehensive set of 1497 sequence-derived features. The principal component analysis is first employed to reduce the dimension of the feature space to 32. Then, the resulting 32-dimensional feature vectors are fed into a simple yet powerful classification algorithm, called intimate sorting, to predict GPCRs at five levels. The prediction at the first level determines whether a protein is a GPCR or a non-GPCR. If it is predicted to be a GPCR, then it will be further predicted into certain family, subfamily, sub-subfamily and subtype by the classifiers at the second, third, fourth, and fifth levels, respectively. To train the classifiers applied at five levels, a non-redundant dataset is carefully constructed, which contains 3178, 1589, 4772, 4924, and 2741 protein sequences at the respective levels. Jackknife tests on this training dataset show that the overall accuracies of PCA-GPCR at five levels (from the first to the fifth can achieve up to 99.5%, 88.8%, 80.47%, 80.3%, and 92.34%, respectively. We further perform predictions on a dataset of 1238 GPCRs at the second level, and on another two datasets of 167 and 566 GPCRs respectively at the fourth level. The overall prediction accuracies of our method are consistently higher than those of the existing methods to be compared. Conclusions The comprehensive set of 1497 features is believed to be capable of capturing information about amino acid
Epitope Sequences in Dengue Virus NS1 Protein Identified by Monoclonal Antibodies

Directory of Open Access Journals (Sweden)

Leticia Barboza Rocha

2017-10-01

Full Text Available Dengue nonstructural protein 1 (NS1 is a multi-functional glycoprotein with essential functions both in viral replication and modulation of host innate immune responses. NS1 has been established as a good surrogate marker for infection. In the present study, we generated four anti-NS1 monoclonal antibodies against recombinant NS1 protein from dengue virus serotype 2 (DENV2, which were used to map three NS1 epitopes. The sequence 193AVHADMGYWIESALNDT209 was recognized by monoclonal antibodies 2H5 and 4H1BC, which also cross-reacted with Zika virus (ZIKV protein. On the other hand, the sequence 25VHTWTEQYKFQPES38 was recognized by mAb 4F6 that did not cross react with ZIKV. Lastly, a previously unidentified DENV2 NS1-specific epitope, represented by the sequence 127ELHNQTFLIDGPETAEC143, is described in the present study after reaction with mAb 4H2, which also did not cross react with ZIKV. The selection and characterization of the epitope, specificity of anti-NS1 mAbs, may contribute to the development of diagnostic tools able to differentiate DENV and ZIKV infections.
Monte Carlo simulation of a statistical mechanical model of multiple protein sequence alignment.

Science.gov (United States)

Kinjo, Akira R

2017-01-01

A grand canonical Monte Carlo (MC) algorithm is presented for studying the lattice gas model (LGM) of multiple protein sequence alignment, which coherently combines long-range interactions and variable-length insertions. MC simulations are used for both parameter optimization of the model and production runs to explore the sequence subspace around a given protein family. In this Note, I describe the details of the MC algorithm as well as some preliminary results of MC simulations with various temperatures and chemical potentials, and compare them with the mean-field approximation. The existence of a two-state transition in the sequence space is suggested for the SH3 domain family, and inappropriateness of the mean-field approximation for the LGM is demonstrated.
A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction

KAUST Repository

Chen, Peng

2015-12-03

Background: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands is important for drug design and protein docking studies. Most of the successful protein-ligand binding predictions were based on known structures. However, structural information is not largely available in practice due to the huge gap between the number of known protein sequences and that of experimentally solved structures
A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction

KAUST Repository

Chen, Peng; Hu, ShanShan; Zhang, Jun; Gao, Xin; Li, Jinyan; Xia, Junfeng; Wang, Bing

2015-01-01

Background: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands is important for drug design and protein docking studies. Most of the successful protein-ligand binding predictions were based on known structures. However, structural information is not largely available in practice due to the huge gap between the number of known protein sequences and that of experimentally solved structures

Protein backbone angle restraints from searching a database for chemical shift and sequence homology

Energy Technology Data Exchange (ETDEWEB)

Cornilescu, Gabriel; Delaglio, Frank; Bax, Ad [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States)

1999-03-15

Chemical shifts of backbone atoms in proteins are exquisitely sensitive to local conformation, and homologous proteins show quite similar patterns of secondary chemical shifts. The inverse of this relation is used to search a database for triplets of adjacent residues with secondary chemical shifts and sequence similarity which provide the best match to the query triplet of interest. The database contains 13C{alpha}, 13C{beta}, 13C', 1H{alpha} and 15N chemical shifts for 20 proteins for which a high resolution X-ray structure is available. The computer program TALOS was developed to search this database for strings of residues with chemical shift and residue type homology. The relative importance of the weighting factors attached to the secondary chemical shifts of the five types of resonances relative to that of sequence similarity was optimized empirically. TALOS yields the 10 triplets which have the closest similarity in secondary chemical shift and amino acid sequence to those of the query sequence. If the central residues in these 10 triplets exhibit similar {phi} and {psi} backbone angles, their averages can reliably be used as angular restraints for the protein whose structure is being studied. Tests carried out for proteins of known structure indicate that the root-mean-square difference (rmsd) between the output of TALOS and the X-ray derived backbone angles is about 15 deg. Approximately 3% of the predictions made by TALOS are found to be in error.
Tertiary alphabet for the observable protein structural universe.

Science.gov (United States)

Mackenzie, Craig O; Zhou, Jianfu; Grigoryan, Gevorg

2016-11-22

Here, we systematically decompose the known protein structural universe into its basic elements, which we dub tertiary structural motifs (TERMs). A TERM is a compact backbone fragment that captures the secondary, tertiary, and quaternary environments around a given residue, comprising one or more disjoint segments (three on average). We seek the set of universal TERMs that capture all structure in the Protein Data Bank (PDB), finding remarkable degeneracy. Only ∼600 TERMs are sufficient to describe 50% of the PDB at sub-Angstrom resolution. However, more rare geometries also exist, and the overall structural coverage grows logarithmically with the number of TERMs. We go on to show that universal TERMs provide an effective mapping between sequence and structure. We demonstrate that TERM-based statistics alone are sufficient to recapitulate close-to-native sequences given either NMR or X-ray backbones. Furthermore, sequence variability predicted from TERM data agrees closely with evolutionary variation. Finally, locations of TERMs in protein chains can be predicted from sequence alone based on sequence signatures emergent from TERM instances in the PDB. For multisegment motifs, this method identifies spatially adjacent fragments that are not contiguous in sequence-a major bottleneck in structure prediction. Although all TERMs recur in diverse proteins, some appear specialized for certain functions, such as interface formation, metal coordination, or even water binding. Structural biology has benefited greatly from previously observed degeneracies in structure. The decomposition of the known structural universe into a finite set of compact TERMs offers exciting opportunities toward better understanding, design, and prediction of protein structure.
Combining sequence-based prediction methods and circular dichroism and infrared spectroscopic data to improve protein secondary structure determinations

Directory of Open Access Journals (Sweden)

Lees Jonathan G

2008-01-01

Full Text Available Abstract Background A number of sequence-based methods exist for protein secondary structure prediction. Protein secondary structures can also be determined experimentally from circular dichroism, and infrared spectroscopic data using empirical analysis methods. It has been proposed that comparable accuracy can be obtained from sequence-based predictions as from these biophysical measurements. Here we have examined the secondary structure determination accuracies of sequence prediction methods with the empirically determined values from the spectroscopic data on datasets of proteins for which both crystal structures and spectroscopic data are available. Results In this study we show that the sequence prediction methods have accuracies nearly comparable to those of spectroscopic methods. However, we also demonstrate that combining the spectroscopic and sequences techniques produces significant overall improvements in secondary structure determinations. In addition, combining the extra information content available from synchrotron radiation circular dichroism data with sequence methods also shows improvements. Conclusion Combining sequence prediction with experimentally determined spectroscopic methods for protein secondary structure content significantly enhances the accuracy of the overall results obtained.
Advanced Whole-Genome Sequencing and Analysis of Fetal Genomes from Amniotic Fluid.

Science.gov (United States)

Mao, Qing; Chin, Robert; Xie, Weiwei; Deng, Yuqing; Zhang, Wenwei; Xu, Huixin; Zhang, Rebecca Yu; Shi, Quan; Peters, Erin E; Gulbahce, Natali; Li, Zhenyu; Chen, Fang; Drmanac, Radoje; Peters, Brock A

2018-04-01

Amniocentesis is a common procedure, the primary purpose of which is to collect cells from the fetus to allow testing for abnormal chromosomes, altered chromosomal copy number, or a small number of genes that have small single- to multibase defects. Here we demonstrate the feasibility of generating an accurate whole-genome sequence of a fetus from either the cellular or cell-free DNA (cfDNA) of an amniotic sample. cfDNA and DNA isolated from the cell pellet of 31 amniocenteses were sequenced to approximately 50× genome coverage by use of the Complete Genomics nanoarray platform. In a subset of the samples, long fragment read libraries were generated from DNA isolated from cells and sequenced to approximately 100× genome coverage. Concordance of variant calls between the 2 DNA sources and with parental libraries was >96%. Two fetal genomes were found to harbor potentially detrimental variants in chromodomain helicase DNA binding protein 8 ( CHD8 ) and LDL receptor-related protein 1 ( LRP1 ), variations of which have been associated with autism spectrum disorder and keratosis pilaris atrophicans, respectively. We also discovered drug sensitivities and carrier information of fetuses for a variety of diseases. We were able to elucidate the complete genome sequence of 31 fetuses from amniotic fluid and demonstrate that the cfDNA or DNA from the cell pellet can be analyzed with little difference in quality. We believe that current technologies could analyze this material in a highly accurate and complete manner and that analyses like these should be considered for addition to current amniocentesis procedures. © 2018 American Association for Clinical Chemistry.
DIALIGN: multiple DNA and protein sequence alignment at BiBiServ.

OpenAIRE

Morgenstern, Burkhard

2004-01-01

DIALIGN is a widely used software tool for multiple DNA and protein sequence alignment. The program combines local and global alignment features and can therefore be applied to sequence data that cannot be correctly aligned by more traditional approaches. DIALIGN is available online through Bielefeld Bioinformatics Server (BiBiServ). The downloadable version of the program offers several new program features. To compare the output of different alignment programs, we developed the program AltA...
Predicted cycloartenol synthase protein from Kandelia obovata and Rhizophora stylosa using online software of Phyre2 and Swiss-model

Science.gov (United States)

Basyuni, M.; Sulistiyono, N.; Wati, R.; Sumardi; Oku, H.; Baba, S.; Sagami, H.

2018-03-01

Cloning of Kandelia obovata KcCAS gene (previously known as Kandelia candel) and Rhizophora stylosa RsCAS have already have been reported and encoded cycloartenol synthases. In this study, the predicted KcCAS and RsCAS protein were analyzed using online software of Phyre2 and Swiss-model. The protein modelling for KcCAS and RsCAS cycloartenol synthases was determined using Pyre2 had similar results with slightly different in sequence identity. By contrast, the Swiss-model for KcCAS slightly had higher sequence identity (47.31%) and Qmean (0.70) compared to RsCAS. No difference of ligands binding site which is considered as modulators for both cycloartenol synthases. The range of predicted protein derived from 91-757 amino acid residues with coverage sequence similarities 0.86, respectively from template model of lanosterol synthase from the human. Homology modelling revealed that 706 residues (93% of the amino acid sequence) had been modelled with 100.0% confidence by the single highest scoring template for both KcCAS and RsCAS using Phyre2. This coverage was more elevated than swiss-model predicted (86%). The present study suggested that both genes are responsible for the genesis of cycloartenol in these mangrove plants.
Oleosome-Associated Protein of the Oleaginous Diatom Fistulifera solaris Contains an Endoplasmic Reticulum-Targeting Signal Sequence

Directory of Open Access Journals (Sweden)

Yoshiaki Maeda

2014-06-01

Full Text Available Microalgae tend to accumulate lipids as an energy storage material in the specific organelle, oleosomes. Current studies have demonstrated that lipids derived from microalgal oleosomes are a promising source of biofuels, while the oleosome formation mechanism has not been fully elucidated. Oleosome-associated proteins have been identified from several microalgae to elucidate the fundamental mechanisms of oleosome formation, although understanding their functions is still in infancy. Recently, we discovered a diatom-oleosome-associated-protein 1 (DOAP1 from the oleaginous diatom, Fistulifera solaris JPCC DA0580. The DOAP1 sequence implied that this protein might be transported into the endoplasmic reticulum (ER due to the signal sequence. To ensure this, we fused the signal sequence to green fluorescence protein. The fusion protein distributed around the chloroplast as like a meshwork membrane structure, indicating the ER localization. This result suggests that DOAP1 could firstly localize at the ER, then move to the oleosomes. This study also demonstrated that the DOAP1 signal sequence allowed recombinant proteins to be specifically expressed in the ER of the oleaginous diatom. It would be a useful technique for engineering the lipid synthesis pathways existing in the ER, and finally controlling the biofuel quality.
Sequence preservation of osteocalcin protein and mitochondrial DNA in bison bones older than 55 ka

Science.gov (United States)

Nielsen-Marsh, Christina M.; Ostrom, Peggy H.; Gandhi, Hasand; Shapiro, Beth; Cooper, Alan; Hauschka, Peter V.; Collins, Matthew J.

2002-12-01

We report the first complete sequences of the protein osteocalcin from small amounts (20 mg) of two bison bone (Bison priscus) dated to older than 55.6 ka and older than 58.9 ka. Osteocalcin was purified using new gravity columns (never exposed to protein) followed by microbore reversed-phase high-performance liquid chromatography. Sequencing of osteocalcin employed two methods of matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS): peptide mass mapping (PMM) and post-source decay (PSD). The PMM shows that ancient and modern bison osteocalcin have the same mass to charge (m/z) distribution, indicating an identical protein sequence and absence of diagenetic products. This was confirmed by PSD of the m/z 2066 tryptic peptide (residues 1 19); the mass spectra from ancient and modern peptides were identical. The 129 mass unit difference in the molecular ion between cow (Bos taurus) and bison is caused by a single amino-acid substitution between the taxa (Trp in cow is replaced by Gly in bison at residue 5). Bison mitochondrial control region DNA sequences were obtained from the older than 55.6 ka fossil. These results suggest that DNA and protein sequences can be used to directly investigate molecular phylogenies over a considerable time period, the absolute limit of which is yet to be determined.
Sequence analysis corresponding to the PPE and PE proteins in ...

Indian Academy of Sciences (India)

Unknown

AB repeats; Mycobacterium tuberculosis genome; PE-PPE domain; PPE, PE proteins; sequence analysis; surface antigens. J. Biosci. | Vol. ... bacterium tuberculosis genomes resulted in the identification of a previously uncharacterized 225 amino acid- ...... Vega Lopez F, Brooks L A, Dockrell H M, De Smet K A,. Thompson ...
Protein sequence analysis by incorporating modified chaos game and physicochemical properties into Chou's general pseudo amino acid composition.

Science.gov (United States)

Xu, Chunrui; Sun, Dandan; Liu, Shenghui; Zhang, Yusen

2016-10-07

In this contribution we introduced a novel graphical method to compare protein sequences. By mapping a protein sequence into 3D space based on codons and physicochemical properties of 20 amino acids, we are able to get a unique P-vector from the 3D curve. This approach is consistent with wobble theory of amino acids. We compute the distance between sequences by their P-vectors to measure similarities/dissimilarities among protein sequences. Finally, we use our method to analyze four datasets and get better results compared with previous approaches. Copyright © 2016 Elsevier Ltd. All rights reserved.
PFP: Automated prediction of gene ontology functional annotations with confidence scores using protein sequence data.

Science.gov (United States)

Hawkins, Troy; Chitale, Meghana; Luban, Stanislav; Kihara, Daisuke

2009-02-15

Protein function prediction is a central problem in bioinformatics, increasing in importance recently due to the rapid accumulation of biological data awaiting interpretation. Sequence data represents the bulk of this new stock and is the obvious target for consideration as input, as newly sequenced organisms often lack any other type of biological characterization. We have previously introduced PFP (Protein Function Prediction) as our sequence-based predictor of Gene Ontology (GO) functional terms. PFP interprets the results of a PSI-BLAST search by extracting and scoring individual functional attributes, searching a wide range of E-value sequence matches, and utilizing conventional data mining techniques to fill in missing information. We have shown it to be effective in predicting both specific and low-resolution functional attributes when sufficient data is unavailable. Here we describe (1) significant improvements to the PFP infrastructure, including the addition of prediction significance and confidence scores, (2) a thorough benchmark of performance and comparisons to other related prediction methods, and (3) applications of PFP predictions to genome-scale data. We applied PFP predictions to uncharacterized protein sequences from 15 organisms. Among these sequences, 60-90% could be annotated with a GO molecular function term at high confidence (>or=80%). We also applied our predictions to the protein-protein interaction network of the Malaria plasmodium (Plasmodium falciparum). High confidence GO biological process predictions (>or=90%) from PFP increased the number of fully enriched interactions in this dataset from 23% of interactions to 94%. Our benchmark comparison shows significant performance improvement of PFP relative to GOtcha, InterProScan, and PSI-BLAST predictions. This is consistent with the performance of PFP as the overall best predictor in both the AFP-SIG '05 and CASP7 function (FN) assessments. PFP is available as a web service at http
Variability of the protein sequences of lcrV between epidemic and atypical rhamnose-positive strains of Yersinia pestis.

Science.gov (United States)

Anisimov, Andrey P; Panfertsev, Evgeniy A; Svetoch, Tat'yana E; Dentovskaya, Svetlana V

2007-01-01

Sequencing of lcrV genes and comparison of the deduced amino acid sequences from ten Y. pestis strains belonging mostly to the group of atypical rhamnose-positive isolates (non-pestis subspecies or pestoides group) showed that the LcrV proteins analyzed could be classified into five sequence types. This classification was based on major amino acid polymorphisms among LcrV proteins in the four "hot points" of the protein sequences. Some additional minor polymorphisms were found throughout these sequence types. The "hot points" corresponded to amino acids 18 (Lys --> Asn), 72 (Lys --> Arg), 273 (Cys --> Ser), and 324-326 (Ser-Gly-Lys --> Arg) in the LcrV sequence of the reference Y. pestis strain CO92. One possible explanation for polymorphism in amino acid sequences of LcrV among different strains is that strain-specific variation resulted from adaptation of the plague pathogen to different rodent and lagomorph hosts.
Accurate and High-Coverage Immune Repertoire Sequencing Reveals Characteristics of Antibody Repertoire Diversification in Young Children with Malaria

Science.gov (United States)

Jiang, Ning

Accurately measuring the immune repertoire sequence composition, diversity, and abundance is important in studying repertoire response in infections, vaccinations, and cancer immunology. Using molecular identifiers (MIDs) to tag mRNA molecules is an effective method in improving the accuracy of immune repertoire sequencing (IR-seq). However, it is still difficult to use IR-seq on small amount of clinical samples to achieve a high coverage of the repertoire diversities. This is especially challenging in studying infections and vaccinations where B cell subpopulations with fewer cells, such as memory B cells or plasmablasts, are often of great interest to study somatic mutation patterns and diversity changes. Here, we describe an approach of IR-seq based on the use of MIDs in combination with a clustering method that can reveal more than 80% of the antibody diversity in a sample and can be applied to as few as 1,000 B cells. We applied this to study the antibody repertoires of young children before and during an acute malaria infection. We discovered unexpectedly high levels of somatic hypermutation (SHM) in infants and revealed characteristics of antibody repertoire development in young children that would have a profound impact on immunization in children.
Low coverage sequencing of three echinoderm genomes: the brittle star Ophionereis fasciata, the sea star Patiriella regularis, and the sea cucumber Australostichopus mollis.

Science.gov (United States)

Long, Kyle A; Nossa, Carlos W; Sewell, Mary A; Putnam, Nicholas H; Ryan, Joseph F

2016-01-01

There are five major extant groups of Echinodermata: Crinoidea (feather stars and sea lillies), Ophiuroidea (brittle stars and basket stars), Asteroidea (sea stars), Echinoidea (sea urchins, sea biscuits, and sand dollars), and Holothuroidea (sea cucumbers). These animals are known for their pentaradial symmetry as adults, unique water vascular system, mutable collagenous tissues, and endoskeletons of high magnesium calcite. To our knowledge, the only echinoderm species with a genome sequence available to date is Strongylocentrotus pupuratus (Echinoidea). The availability of additional echinoderm genome sequences is crucial for understanding the biology of these animals. Here we present assembled draft genomes of the brittle star Ophionereis fasciata, the sea star Patiriella regularis, and the sea cucumber Australostichopus mollis from Illumina sequence data with coverages of 12.5x, 22.5x, and 21.4x, respectively. These data provide a resource for mining gene superfamilies, identifying non-coding RNAs, confirming gene losses, and designing experimental constructs. They will be important comparative resources for future genomic studies in echinoderms.
Visualization of protein sequence features using JavaScript and SVG with pViz.js.

Science.gov (United States)

Mukhyala, Kiran; Masselot, Alexandre

2014-12-01

pViz.js is a visualization library for displaying protein sequence features in a Web browser. By simply providing a sequence and the locations of its features, this lightweight, yet versatile, JavaScript library renders an interactive view of the protein features. Interactive exploration of protein sequence features over the Web is a common need in Bioinformatics. Although many Web sites have developed viewers to display these features, their implementations are usually focused on data from a specific source or use case. Some of these viewers can be adapted to fit other use cases but are not designed to be reusable. pViz makes it easy to display features as boxes aligned to a protein sequence with zooming functionality but also includes predefined renderings for secondary structure and post-translational modifications. The library is designed to further customize this view. We demonstrate such applications of pViz using two examples: a proteomic data visualization tool with an embedded viewer for displaying features on protein structure, and a tool to visualize the results of the variant_effect_predictor tool from Ensembl. pViz.js is a JavaScript library, available on github at https://github.com/Genentech/pviz. This site includes examples and functional applications, installation instructions and usage documentation. A Readme file, which explains how to use pViz with examples, is available as Supplementary Material A. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Implication of the cause of differences in 3D structures of proteins with high sequence identity based on analyses of amino acid sequences and 3D structures.

Science.gov (United States)

Matsuoka, Masanari; Sugita, Masatake; Kikuchi, Takeshi

2014-09-18

Proteins that share a high sequence homology while exhibiting drastically different 3D structures are investigated in this study. Recently, artificial proteins related to the sequences of the GA and IgG binding GB domains of human serum albumin have been designed. These artificial proteins, referred to as GA and GB, share 98% amino acid sequence identity but exhibit different 3D structures, namely, a 3α bundle versus a 4β + α structure. Discriminating between their 3D structures based on their amino acid sequences is a very difficult problem. In the present work, in addition to using bioinformatics techniques, an analysis based on inter-residue average distance statistics is used to address this problem. It was hard to distinguish which structure a given sequence would take only with the results of ordinary analyses like BLAST and conservation analyses. However, in addition to these analyses, with the analysis based on the inter-residue average distance statistics and our sequence tendency analysis, we could infer which part would play an important role in its structural formation. The results suggest possible determinants of the different 3D structures for sequences with high sequence identity. The possibility of discriminating between the 3D structures based on the given sequences is also discussed.
Characteristics of the Lotus japonicus gene repertoire deduced from large-scale expressed sequence tag (EST) analysis.

Science.gov (United States)

Asamizu, Erika; Nakamura, Yasukazu; Sato, Shusei; Tabata, Satoshi

2004-02-01

To perform a comprehensive analysis of genes expressed in a model legume, Lotus japonicus, a total of 74472 3'-end expressed sequence tags (EST) were generated from cDNA libraries produced from six different organs. Clustering of sequences was performed with an identity criterion of 95% for 50 bases, and a total of 20457 non-redundant sequences, 8503 contigs and 11954 singletons were generated. EST sequence coverage was analyzed by using the annotated L. japonicus genomic sequence and 1093 of the 1889 predicted protein-encoding genes (57.9%) were hit by the EST sequence(s). Gene content was compared to several plant species. Among the 8503 contigs, 471 were identified as sequences conserved only in leguminous species and these included several disease resistance-related genes. This suggested that in legumes, these genes may have evolved specifically to resist pathogen attack. The rate of gene sequence divergence was assessed by comparing similarity level and functional category based on the Gene Ontology (GO) annotation of Arabidopsis genes. This revealed that genes encoding ribosomal proteins, as well as those related to translation, photosynthesis, and cellular structure were more abundantly represented in the highly conserved class, and that genes encoding transcription factors and receptor protein kinases were abundantly represented in the less conserved class. To make the sequence information and the cDNA clones available to the research community, a Web database with useful services was created at http://www.kazusa.or.jp/en/plant/lotus/EST/.
Enhancing Protein Disulfide Bond Cleavage by UV Excitation and Electron Capture Dissociation for Top-Down Mass Spectrometry.

Science.gov (United States)

Wongkongkathep, Piriya; Li, Huilin; Zhang, Xing; Loo, Rachel R Ogorzalek; Julian, Ryan R; Loo, Joseph A

2015-11-15

The application of ion pre-activation with 266 nm ultraviolet (UV) laser irradiation combined with electron capture dissociation (ECD) is demonstrated to enhance top-down mass spectrometry sequence coverage of disulfide bond containing proteins. UV-based activation can homolytically cleave a disulfide bond to yield two separated thiol radicals. Activated ECD experiments of insulin and ribonuclease A containing three and four disulfide bonds, respectively, were performed. UV-activation in combination with ECD allowed the three disulfide bonds of insulin to be cleaved and the overall sequence coverage to be increased. For the larger sized ribonuclease A with four disulfide bonds, irradiation from an infrared laser (10.6 µm) to disrupt non-covalent interactions was combined with UV-activation to facilitate the cleavage of up to three disulfide bonds. Preferences for disulfide bond cleavage are dependent on protein structure and sequence. Disulfide bonds can reform if the generated radicals remain in close proximity. By varying the time delay between the UV-activation and the ECD events, it was determined that disulfide bonds reform within 10-100 msec after their UV-homolytic cleavage.
A two-step recognition of signal sequences determines the translocation efficiency of proteins.

Science.gov (United States)

Belin, D; Bost, S; Vassalli, J D; Strub, K

1996-02-01

The cytosolic and secreted, N-glycosylated, forms of plasminogen activator inhibitor-2 (PAI-2) are generated by facultative translocation. To study the molecular events that result in the bi-topological distribution of proteins, we determined in vitro the capacities of several signal sequences to bind the signal recognition particle (SRP) during targeting, and to promote vectorial transport of murine PAI-2 (mPAI-2). Interestingly, the six signal sequences we compared (mPAI-2 and three mutated derivatives thereof, ovalbumin and preprolactin) were found to have the differential activities in the two events. For example, the mPAI-2 signal sequence first binds SRP with moderate efficiency and secondly promotes the vectorial transport of only a fraction of the SRP-bound nascent chains. Our results provide evidence that the translocation efficiency of proteins can be controlled by the recognition of their signal sequences at two steps: during SRP-mediated targeting and during formation of a committed translocation complex. This second recognition may occur at several time points during the insertion/translocation step. In conclusion, signal sequences have a more complex structure than previously anticipated, allowing for multiple and independent interactions with the translocation machinery.
Nucleotide sequence of a cDNA for branched chain acyltransferase with analysis of the deduced protein structure

International Nuclear Information System (INIS)

Hummel, K.B.; Litwer, S.; Bradford, A.P.; Aitken, A.; Danner, D.J.; Yeaman, S.J.

1988-01-01

Nucleotide sequence was determined for a 1.6-kilobase human cDNA putative for the branched chain acyltransferase protein of the branched chain α-ketoacid dehydrogenase complex. Translation of the sequence reveals an open reading frame encoding a 315-amino acid protein of molecular weight 35,759 followed by 560 bases of 3'-untranslated sequence. Three repeats of the polyadenylation signal hexamer ATTAAA are present prior to the polyadenylate tail. Within the open reading frame is a 10-amino acid fragment which matches exactly the amino acid sequence around the lipoate-lysine residue in bovine kidney branched chain acyltransferase, thus confirming the identity of the cDNA. Analysis of the deduced protein structure for the human branched chain acyltransferase revealed an organization into domains similar to that reported for the acyltransferase proteins of the pyruvate and α-ketoglutarate dehydrogenase complexes. This similarity in organization suggests that a more detailed analysis of the proteins will be required to explain the individual substrate and multienzyme complex specificity shown by these acyltransferases

Experimental Rugged Fitness Landscape in Protein Sequence Space

Science.gov (United States)

Hayashi, Yuuki; Aita, Takuyo; Toyota, Hitoshi; Husimi, Yuzuru; Urabe, Itaru; Yomo, Tetsuya

2006-01-01

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12–130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7×104-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18–24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region. PMID:17183728
Experimental rugged fitness landscape in protein sequence space.

Science.gov (United States)

Hayashi, Yuuki; Aita, Takuyo; Toyota, Hitoshi; Husimi, Yuzuru; Urabe, Itaru; Yomo, Tetsuya

2006-12-20

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7x10(4)-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18-24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.
Experimental rugged fitness landscape in protein sequence space.

Directory of Open Access Journals (Sweden)

Yuuki Hayashi

Full Text Available The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7x10(4-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1 the dependence of stationary fitness on library size, which increased gradually, and (2 the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18-24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.
Protein sequences bound to mineral surfaces persist into deep time

DEFF Research Database (Denmark)

Demarchi, Beatrice; Hall, Shaun; Roncal-Herrero, Teresa

2016-01-01

of Laetoli (3.8 Ma) and Olduvai Gorge (1.3 Ma) in Tanzania. By tracking protein diagenesis back in time we find consistent patterns of preservation, demonstrating authenticity of the surviving sequences. Molecular dynamics simulations of struthiocalcin-1 and -2, the dominant proteins within the eggshell......, reveal that distinct domains bind to the mineral surface. It is the domain with the strongest calculated binding energy to the calcite surface that is selectively preserved. Thermal age calculations demonstrate that the Laetoli and Olduvai peptides are 50 times older than any previously authenticated...
Programming molecular self-assembly of intrinsically disordered proteins containing sequences of low complexity

Science.gov (United States)

Simon, Joseph R.; Carroll, Nick J.; Rubinstein, Michael; Chilkoti, Ashutosh; López, Gabriel P.

2017-06-01

Dynamic protein-rich intracellular structures that contain phase-separated intrinsically disordered proteins (IDPs) composed of sequences of low complexity (SLC) have been shown to serve a variety of important cellular functions, which include signalling, compartmentalization and stabilization. However, our understanding of these structures and our ability to synthesize models of them have been limited. We present design rules for IDPs possessing SLCs that phase separate into diverse assemblies within droplet microenvironments. Using theoretical analyses, we interpret the phase behaviour of archetypal IDP sequences and demonstrate the rational design of a vast library of multicomponent protein-rich structures that ranges from uniform nano-, meso- and microscale puncta (distinct protein droplets) to multilayered orthogonally phase-separated granular structures. The ability to predict and program IDP-rich assemblies in this fashion offers new insights into (1) genetic-to-molecular-to-macroscale relationships that encode hierarchical IDP assemblies, (2) design rules of such assemblies in cell biology and (3) molecular-level engineering of self-assembled recombinant IDP-rich materials.
The Ising model for prediction of disordered residues from protein sequence alone

International Nuclear Information System (INIS)

Lobanov, Michail Yu; Galzitskaya, Oxana V

2011-01-01

Intrinsically disordered regions serve as molecular recognition elements, which play an important role in the control of many cellular processes and signaling pathways. It is useful to be able to predict positions of disordered residues and disordered regions in protein chains using protein sequence alone. A new method (IsUnstruct) based on the Ising model for prediction of disordered residues from protein sequence alone has been developed. According to this model, each residue can be in one of two states: ordered or disordered. The model is an approximation of the Ising model in which the interaction term between neighbors has been replaced by a penalty for changing between states (the energy of border). The IsUnstruct has been compared with other available methods and found to perform well. The method correctly finds 77% of disordered residues as well as 87% of ordered residues in the CASP8 database, and 72% of disordered residues as well as 85% of ordered residues in the DisProt database
Molecular Simulations of Sequence-Specific Association of Transmembrane Proteins in Lipid Bilayers

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Doxastakis, Manolis; Prakash, Anupam; Janosi, Lorant

2011-03-01

Association of membrane proteins is central in material and information flow across the cellular membranes. Amino-acid sequence and the membrane environment are two critical factors controlling association, however, quantitative knowledge on such contributions is limited. In this work, we study the dimerization of helices in lipid bilayers using extensive parallel Monte Carlo simulations with recently developed algorithms. The dimerization of Glycophorin A is examined employing a coarse-grain model that retains a level of amino-acid specificity, in three different phospholipid bilayers. Association is driven by a balance of protein-protein and lipid-induced interactions with the latter playing a major role at short separations. Following a different approach, the effect of amino-acid sequence is studied using the four transmembrane domains of the epidermal growth factor receptor family in identical lipid environments. Detailed characterization of dimer formation and estimates of the free energy of association reveal that these helices present significant affinity to self-associate with certain dimers forming non-specific interfaces.
Identification of similar regions of protein structures using integrated sequence and structure analysis tools

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Heiland Randy

2006-03-01

Full Text Available Abstract Background Understanding protein function from its structure is a challenging problem. Sequence based approaches for finding homology have broad use for annotation of both structure and function. 3D structural information of protein domains and their interactions provide a complementary view to structure function relationships to sequence information. We have developed a web site http://www.sblest.org/ and an API of web services that enables users to submit protein structures and identify statistically significant neighbors and the underlying structural environments that make that match using a suite of sequence and structure analysis tools. To do this, we have integrated S-BLEST, PSI-BLAST and HMMer based superfamily predictions to give a unique integrated view to prediction of SCOP superfamilies, EC number, and GO term, as well as identification of the protein structural environments that are associated with that prediction. Additionally, we have extended UCSF Chimera and PyMOL to support our web services, so that users can characterize their own proteins of interest. Results Users are able to submit their own queries or use a structure already in the PDB. Currently the databases that a user can query include the popular structural datasets ASTRAL 40 v1.69, ASTRAL 95 v1.69, CLUSTER50, CLUSTER70 and CLUSTER90 and PDBSELECT25. The results can be downloaded directly from the site and include function prediction, analysis of the most conserved environments and automated annotation of query proteins. These results reflect both the hits found with PSI-BLAST, HMMer and with S-BLEST. We have evaluated how well annotation transfer can be performed on SCOP ID's, Gene Ontology (GO ID's and EC Numbers. The method is very efficient and totally automated, generally taking around fifteen minutes for a 400 residue protein. Conclusion With structural genomics initiatives determining structures with little, if any, functional characterization
Genome-Wide Prediction and Analysis of 3D-Domain Swapped Proteins in the Human Genome from Sequence Information.

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Upadhyay, Atul Kumar; Sowdhamini, Ramanathan

2016-01-01

3D-domain swapping is one of the mechanisms of protein oligomerization and the proteins exhibiting this phenomenon have many biological functions. These proteins, which undergo domain swapping, have acquired much attention owing to their involvement in human diseases, such as conformational diseases, amyloidosis, serpinopathies, proteionopathies etc. Early realisation of proteins in the whole human genome that retain tendency to domain swap will enable many aspects of disease control management. Predictive models were developed by using machine learning approaches with an average accuracy of 78% (85.6% of sensitivity, 87.5% of specificity and an MCC value of 0.72) to predict putative domain swapping in protein sequences. These models were applied to many complete genomes with special emphasis on the human genome. Nearly 44% of the protein sequences in the human genome were predicted positive for domain swapping. Enrichment analysis was performed on the positively predicted sequences from human genome for their domain distribution, disease association and functional importance based on Gene Ontology (GO). Enrichment analysis was also performed to infer a better understanding of the functional importance of these sequences. Finally, we developed hinge region prediction, in the given putative domain swapped sequence, by using important physicochemical properties of amino acids.
Random amino acid mutations and protein misfolding lead to Shannon limit in sequence-structure communication.

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Andreas Martin Lisewski

2008-09-01

Full Text Available The transmission of genomic information from coding sequence to protein structure during protein synthesis is subject to stochastic errors. To analyze transmission limits in the presence of spurious errors, Shannon's noisy channel theorem is applied to a communication channel between amino acid sequences and their structures established from a large-scale statistical analysis of protein atomic coordinates. While Shannon's theorem confirms that in close to native conformations information is transmitted with limited error probability, additional random errors in sequence (amino acid substitutions and in structure (structural defects trigger a decrease in communication capacity toward a Shannon limit at 0.010 bits per amino acid symbol at which communication breaks down. In several controls, simulated error rates above a critical threshold and models of unfolded structures always produce capacities below this limiting value. Thus an essential biological system can be realistically modeled as a digital communication channel that is (a sensitive to random errors and (b restricted by a Shannon error limit. This forms a novel basis for predictions consistent with observed rates of defective ribosomal products during protein synthesis, and with the estimated excess of mutual information in protein contact potentials.
Origin and spread of photosynthesis based upon conserved sequence features in key bacteriochlorophyll biosynthesis proteins.

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Gupta, Radhey S

2012-11-01

The origin of photosynthesis and how this capability has spread to other bacterial phyla remain important unresolved questions. I describe here a number of conserved signature indels (CSIs) in key proteins involved in bacteriochlorophyll (Bchl) biosynthesis that provide important insights in these regards. The proteins BchL and BchX, which are essential for Bchl biosynthesis, are derived by gene duplication in a common ancestor of all phototrophs. More ancient gene duplication gave rise to the BchX-BchL proteins and the NifH protein of the nitrogenase complex. The sequence alignment of NifH-BchX-BchL proteins contain two CSIs that are uniquely shared by all NifH and BchX homologs, but not by any BchL homologs. These CSIs and phylogenetic analysis of NifH-BchX-BchL protein sequences strongly suggest that the BchX homologs are ancestral to BchL and that the Bchl-based anoxygenic photosynthesis originated prior to the chlorophyll (Chl)-based photosynthesis in cyanobacteria. Another CSI in the BchX-BchL sequence alignment that is uniquely shared by all BchX homologs and the BchL sequences from Heliobacteriaceae, but absent in all other BchL homologs, suggests that the BchL homologs from Heliobacteriaceae are primitive in comparison to all other photosynthetic lineages. Several other identified CSIs in the BchN homologs are commonly shared by all proteobacterial homologs and a clade consisting of the marine unicellular Cyanobacteria (Clade C). These CSIs in conjunction with the results of phylogenetic analyses and pair-wise sequence similarity on the BchL, BchN, and BchB proteins, where the homologs from Clade C Cyanobacteria and Proteobacteria exhibited close relationship, provide strong evidence that these two groups have incurred lateral gene transfers. Additionally, phylogenetic analyses and several CSIs in the BchL-N-B proteins that are uniquely shared by all Chlorobi and Chloroflexi homologs provide evidence that the genes for these proteins have also been
Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences

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Ji-Yong An

2016-01-01

Full Text Available We propose a novel computational method known as RVM-LPQ that combines the Relevance Vector Machine (RVM model and Local Phase Quantization (LPQ to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the LPQ feature representation on a Position Specific Scoring Matrix (PSSM, reducing the influence of noise using a Principal Component Analysis (PCA, and using a Relevance Vector Machine (RVM based classifier. We perform 5-fold cross-validation experiments on Yeast and Human datasets, and we achieve very high accuracies of 92.65% and 97.62%, respectively, which is significantly better than previous works. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM classifier on the Yeast dataset. The experimental results demonstrate that our RVM-LPQ method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool for future proteomics research.
Estimating DNA coverage and abundance in metagenomes using a gamma approximation

Energy Technology Data Exchange (ETDEWEB)

Hooper, Sean D; Dalevi, Daniel; Pati, Amrita; Mavromatis, Konstantinos; Ivanova, Natalia N; Kyrpides, Nikos C

2010-01-01

Shotgun sequencing generates large numbers of short DNA reads from either an isolated organism or, in the case of metagenomics projects, from the aggregate genome of a microbial community. These reads are then assembled based on overlapping sequences into larger, contiguous sequences (contigs). The feasibility of assembly and the coverage achieved (reads per nucleotide or distinct sequence of nucleotides) depend on several factors: the number of reads sequenced, the read length and the relative abundances of their source genomes in the microbial community. A low coverage suggests that most of the genomic DNA in the sample has not been sequenced, but it is often difficult to estimate either the extent of the uncaptured diversity or the amount of additional sequencing that would be most efficacious. In this work, we regard a metagenome as a population of DNA fragments (bins), each of which may be covered by one or more reads. We employ a gamma distribution to model this bin population due to its flexibility and ease of use. When a gamma approximation can be found that adequately fits the data, we may estimate the number of bins that were not sequenced and that could potentially be revealed by additional sequencing. We evaluated the performance of this model using simulated metagenomes and demonstrate its applicability on three recent metagenomic datasets.
SigniSite: Identification of residue-level genotype-phenotype correlations in protein multiple sequence alignments

DEFF Research Database (Denmark)

Jessen, Leon Ivar; Hoof, Ilka; Lund, Ole

2013-01-01

Site does not require any pre-definition of subgroups or binary classification. Input is a set of protein sequences where each sequence has an associated real number, quantifying a given phenotype. SigniSite will then identify which amino acid residues are significantly associated with the data set......) using a set of human immunodeficiency virus protease-inhibitor genotype–phenotype data and corresponding resistance mutation scores from the Stanford University HIV Drug Resistance Database, and a data set of protein families with experimentally annotated SDPs. For both data sets, SigniSite was found...
Evolutionary conservation of nuclear and nucleolar targeting sequences in yeast ribosomal protein S6A

International Nuclear Information System (INIS)

Lipsius, Edgar; Walter, Korden; Leicher, Torsten; Phlippen, Wolfgang; Bisotti, Marc-Angelo; Kruppa, Joachim

2005-01-01

Over 1 billion years ago, the animal kingdom diverged from the fungi. Nevertheless, a high sequence homology of 62% exists between human ribosomal protein S6 and S6A of Saccharomyces cerevisiae. To investigate whether this similarity in primary structure is mirrored in corresponding functional protein domains, the nuclear and nucleolar targeting signals were delineated in yeast S6A and compared to the known human S6 signals. The complete sequence of S6A and cDNA fragments was fused to the 5'-end of the LacZ gene, the constructs were transiently expressed in COS cells, and the subcellular localization of the fusion proteins was detected by indirect immunofluorescence. One bipartite and two monopartite nuclear localization signals as well as two nucleolar binding domains were identified in yeast S6A, which are located at homologous regions in human S6 protein. Remarkably, the number, nature, and position of these targeting signals have been conserved, albeit their amino acid sequences have presumably undergone a process of co-evolution with their corresponding rRNAs
Sequencing and De Novo Transcriptome Assembly of Brachypodium sylvaticum (Poaceae

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Samuel E. Fox

2013-03-01

Full Text Available Premise of the study: We report the de novo assembly and characterization of the transcriptomes of Brachypodium sylvaticum (slender false-brome accessions from native populations of Spain and Greece, and an invasive population west of Corvallis, Oregon, USA. Methods and Results: More than 350 million sequence reads from the mRNA libraries prepared from three B. sylvaticum genotypes were assembled into 120,091 (Corvallis, 104,950 (Spain, and 177,682 (Greece transcript contigs. In comparison with the B. distachyon Bd21 reference genome and GenBank protein sequences, we estimate >90% exome coverage for B. sylvaticum. The transcripts were assigned Gene Ontology and InterPro annotations. Brachypodium sylvaticum sequence reads aligned against the Bd21 genome revealed 394,654 single-nucleotide polymorphisms (SNPs and >20,000 simple sequence repeat (SSR DNA sites. Conclusions: To our knowledge, this is the first report of transcriptome sequencing of invasive plant species with a closely related sequenced reference genome. The sequences and identified SNP variant and SSR sites will provide tools for developing novel genetic markers for use in genotyping and characterization of invasive behavior of B. sylvaticum.
BIPS: BIANA Interolog Prediction Server. A tool for protein-protein interaction inference.

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Garcia-Garcia, Javier; Schleker, Sylvia; Klein-Seetharaman, Judith; Oliva, Baldo

2012-07-01

Protein-protein interactions (PPIs) play a crucial role in biology, and high-throughput experiments have greatly increased the coverage of known interactions. Still, identification of complete inter- and intraspecies interactomes is far from being complete. Experimental data can be complemented by the prediction of PPIs within an organism or between two organisms based on the known interactions of the orthologous genes of other organisms (interologs). Here, we present the BIANA (Biologic Interactions and Network Analysis) Interolog Prediction Server (BIPS), which offers a web-based interface to facilitate PPI predictions based on interolog information. BIPS benefits from the capabilities of the framework BIANA to integrate the several PPI-related databases. Additional metadata can be used to improve the reliability of the predicted interactions. Sensitivity and specificity of the server have been calculated using known PPIs from different interactomes using a leave-one-out approach. The specificity is between 72 and 98%, whereas sensitivity varies between 1 and 59%, depending on the sequence identity cut-off used to calculate similarities between sequences. BIPS is freely accessible at http://sbi.imim.es/BIPS.php.
The characterization of twenty sequenced human genomes.

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Kimberly Pelak

2010-09-01

Full Text Available We present the analysis of twenty human genomes to evaluate the prospects for identifying rare functional variants that contribute to a phenotype of interest. We sequenced at high coverage ten "case" genomes from individuals with severe hemophilia A and ten "control" genomes. We summarize the number of genetic variants emerging from a study of this magnitude, and provide a proof of concept for the identification of rare and highly-penetrant functional variants by confirming that the cause of hemophilia A is easily recognizable in this data set. We also show that the number of novel single nucleotide variants (SNVs discovered per genome seems to stabilize at about 144,000 new variants per genome, after the first 15 individuals have been sequenced. Finally, we find that, on average, each genome carries 165 homozygous protein-truncating or stop loss variants in genes representing a diverse set of pathways.
Effect of the sequence data deluge on the performance of methods for detecting protein functional residues.

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Garrido-Martín, Diego; Pazos, Florencio

2018-02-27

The exponential accumulation of new sequences in public databases is expected to improve the performance of all the approaches for predicting protein structural and functional features. Nevertheless, this was never assessed or quantified for some widely used methodologies, such as those aimed at detecting functional sites and functional subfamilies in protein multiple sequence alignments. Using raw protein sequences as only input, these approaches can detect fully conserved positions, as well as those with a family-dependent conservation pattern. Both types of residues are routinely used as predictors of functional sites and, consequently, understanding how the sequence content of the databases affects them is relevant and timely. In this work we evaluate how the growth and change with time in the content of sequence databases affect five sequence-based approaches for detecting functional sites and subfamilies. We do that by recreating historical versions of the multiple sequence alignments that would have been obtained in the past based on the database contents at different time points, covering a period of 20 years. Applying the methods to these historical alignments allows quantifying the temporal variation in their performance. Our results show that the number of families to which these methods can be applied sharply increases with time, while their ability to detect potentially functional residues remains almost constant. These results are informative for the methods' developers and final users, and may have implications in the design of new sequencing initiatives.
RNA2 of grapevine fanleaf virus: sequence analysis and coat protein cistron location.

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Serghini, M A; Fuchs, M; Pinck, M; Reinbolt, J; Walter, B; Pinck, L

1990-07-01

The nucleotide sequence of the genomic RNA2 (3774 nucleotides) of grapevine fanleaf virus strain F13 was determined from overlapping cDNA clones and its genetic organization was deduced. Two rapid and efficient methods were used for cDNA cloning of the 5' region of RNA2. The complete sequence contained only one long open reading frame of 3555 nucleotides (1184 codons, 131K product). The analysis of the N-terminal sequence of purified coat protein (CP) and identification of its C-terminal residue have allowed the CP cistron to be precisely positioned within the polyprotein. The CP produced by proteolytic cleavage at the Arg/Gly site between residues 680 and 681 contains 504 amino acids (Mr 56019) and has hydrophobic properties. The Arg/Gly cleavage site deduced by N-terminal amino acid sequence analysis is the first for a nepovirus coat protein and for plant viruses expressing their genomic RNAs by polyprotein synthesis. Comparison of GFLV RNA2 with M RNA of cowpea mosaic comovirus and with RNA2 of two closely related nepoviruses, tomato black ring virus and Hungarian grapevine chrome mosaic virus, showed strong similarities among the 3' non-coding regions but less similarity among the 5' end non-coding sequences than reported among other nepovirus RNAs.

Structural and sequence analysis of imelysin-like proteins implicated in bacterial iron uptake.

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Qingping Xu

Full Text Available Imelysin-like proteins define a superfamily of bacterial proteins that are likely involved in iron uptake. Members of this superfamily were previously thought to be peptidases and were included in the MEROPS family M75. We determined the first crystal structures of two remotely related, imelysin-like proteins. The Psychrobacter arcticus structure was determined at 2.15 Å resolution and contains the canonical imelysin fold, while higher resolution structures from the gut bacteria Bacteroides ovatus, in two crystal forms (at 1.25 Å and 1.44 Å resolution, have a circularly permuted topology. Both structures are highly similar to each other despite low sequence similarity and circular permutation. The all-helical structure can be divided into two similar four-helix bundle domains. The overall structure and the GxHxxE motif region differ from known HxxE metallopeptidases, suggesting that imelysin-like proteins are not peptidases. A putative functional site is located at the domain interface. We have now organized the known homologous proteins into a superfamily, which can be separated into four families. These families share a similar functional site, but each has family-specific structural and sequence features. These results indicate that imelysin-like proteins have evolved from a common ancestor, and likely have a conserved function.
Properties of Sequence Conservation in Upstream Regulatory and Protein Coding Sequences among Paralogs in Arabidopsis thaliana

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Richardson, Dale N.; Wiehe, Thomas

Whole genome duplication (WGD) has catalyzed the formation of new species, genes with novel functions, altered expression patterns, complexified signaling pathways and has provided organisms a level of genetic robustness. We studied the long-term evolution and interrelationships of 5’ upstream regulatory sequences (URSs), protein coding sequences (CDSs) and expression correlations (EC) of duplicated gene pairs in Arabidopsis. Three distinct methods revealed significant evolutionary conservation between paralogous URSs and were highly correlated with microarray-based expression correlation of the respective gene pairs. Positional information on exact matches between sequences unveiled the contribution of micro-chromosomal rearrangements on expression divergence. A three-way rank analysis of URS similarity, CDS divergence and EC uncovered specific gene functional biases. Transcription factor activity was associated with gene pairs exhibiting conserved URSs and divergent CDSs, whereas a broad array of metabolic enzymes was found to be associated with gene pairs showing diverged URSs but conserved CDSs.
Vaccination coverage and out-of-sequence vaccinations in rural Guinea-Bissau

DEFF Research Database (Denmark)

Hornshøj, Linda; Benn, Christine Stabell; Fernandes, Manuel

2012-01-01

OBJECTIVE: The WHO aims for 90% coverage of the Expanded Program on Immunization (EPI), which in Guinea-Bissau included BCG vaccine at birth, three doses of diphtheria-tetanus-pertussis vaccine (DTP) and oral polio vaccine (OPV) at 6, 10 and 14 weeks and measles vaccine (MV) at 9 months when...
Full-Length Venom Protein cDNA Sequences from Venom-Derived mRNA: Exploring Compositional Variation and Adaptive Multigene Evolution.

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Modahl, Cassandra M; Mackessy, Stephen P

2016-06-01

Envenomation of humans by snakes is a complex and continuously evolving medical emergency, and treatment is made that much more difficult by the diverse biochemical composition of many venoms. Venomous snakes and their venoms also provide models for the study of molecular evolutionary processes leading to adaptation and genotype-phenotype relationships. To compare venom complexity and protein sequences, venom gland transcriptomes are assembled, which usually requires the sacrifice of snakes for tissue. However, toxin transcripts are also present in venoms, offering the possibility of obtaining cDNA sequences directly from venom. This study provides evidence that unknown full-length venom protein transcripts can be obtained from the venoms of multiple species from all major venomous snake families. These unknown venom protein cDNAs are obtained by the use of primers designed from conserved signal peptide sequences within each venom protein superfamily. This technique was used to assemble a partial venom gland transcriptome for the Middle American Rattlesnake (Crotalus simus tzabcan) by amplifying sequences for phospholipases A2, serine proteases, C-lectins, and metalloproteinases from within venom. Phospholipase A2 sequences were also recovered from the venoms of several rattlesnakes and an elapid snake (Pseudechis porphyriacus), and three-finger toxin sequences were recovered from multiple rear-fanged snake species, demonstrating that the three major clades of advanced snakes (Elapidae, Viperidae, Colubridae) have stable mRNA present in their venoms. These cDNA sequences from venom were then used to explore potential activities derived from protein sequence similarities and evolutionary histories within these large multigene superfamilies. Venom-derived sequences can also be used to aid in characterizing venoms that lack proteomic profiles and identify sequence characteristics indicating specific envenomation profiles. This approach, requiring only venom, provides
Protein domain analysis of genomic sequence data reveals regulation of LRR related domains in plant transpiration in Ficus.

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Lang, Tiange; Yin, Kangquan; Liu, Jinyu; Cao, Kunfang; Cannon, Charles H; Du, Fang K

2014-01-01

Predicting protein domains is essential for understanding a protein's function at the molecular level. However, up till now, there has been no direct and straightforward method for predicting protein domains in species without a reference genome sequence. In this study, we developed a functionality with a set of programs that can predict protein domains directly from genomic sequence data without a reference genome. Using whole genome sequence data, the programming functionality mainly comprised DNA assembly in combination with next-generation sequencing (NGS) assembly methods and traditional methods, peptide prediction and protein domain prediction. The proposed new functionality avoids problems associated with de novo assembly due to micro reads and small single repeats. Furthermore, we applied our functionality for the prediction of leucine rich repeat (LRR) domains in four species of Ficus with no reference genome, based on NGS genomic data. We found that the LRRNT_2 and LRR_8 domains are related to plant transpiration efficiency, as indicated by the stomata index, in the four species of Ficus. The programming functionality established in this study provides new insights for protein domain prediction, which is particularly timely in the current age of NGS data expansion.
On the Power and Limits of Sequence Similarity Based Clustering of Proteins Into Families

DEFF Research Database (Denmark)

Wiwie, Christian; Röttger, Richard

2017-01-01

Over the last decades, we have observed an ongoing tremendous growth of available sequencing data fueled by the advancements in wet-lab technology. The sequencing information is only the beginning of the actual understanding of how organisms survive and prosper. It is, for instance, equally...... important to also unravel the proteomic repertoire of an organism. A classical computational approach for detecting protein families is a sequence-based similarity calculation coupled with a subsequent cluster analysis. In this work we have intensively analyzed various clustering tools on a large scale. We...... used the data to investigate the behavior of the tools' parameters underlining the diversity of the protein families. Furthermore, we trained regression models for predicting the expected performance of a clustering tool for an unknown data set and aimed to also suggest optimal parameters...
Cloning, sequencing, and expression of dnaK-operon proteins from the thermophilic bacterium Thermus thermophilus.

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Osipiuk, J; Joachimiak, A

1997-09-12

We propose that the dnaK operon of Thermus thermophilus HB8 is composed of three functionally linked genes: dnaK, grpE, and dnaJ. The dnaK and dnaJ gene products are most closely related to their cyanobacterial homologs. The DnaK protein sequence places T. thermophilus in the plastid Hsp70 subfamily. In contrast, the grpE translated sequence is most similar to GrpE from Clostridium acetobutylicum, a Gram-positive anaerobic bacterium. A single promoter region, with homology to the Escherichia coli consensus promoter sequences recognized by the sigma70 and sigma32 transcription factors, precedes the postulated operon. This promoter is heat-shock inducible. The dnaK mRNA level increased more than 30 times upon 10 min of heat shock (from 70 degrees C to 85 degrees C). A strong transcription terminating sequence was found between the dnaK and grpE genes. The individual genes were cloned into pET expression vectors and the thermophilic proteins were overproduced at high levels in E. coli and purified to homogeneity. The recombinant T. thermophilus DnaK protein was shown to have a weak ATP-hydrolytic activity, with an optimum at 90 degrees C. The ATPase was stimulated by the presence of GrpE and DnaJ. Another open reading frame, coding for ClpB heat-shock protein, was found downstream of the dnaK operon.
An expressed sequence tag (EST) data mining strategy succeeding in the discovery of new G-protein coupled receptors.

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Wittenberger, T; Schaller, H C; Hellebrand, S

2001-03-30

We have developed a comprehensive expressed sequence tag database search method and used it for the identification of new members of the G-protein coupled receptor superfamily. Our approach proved to be especially useful for the detection of expressed sequence tag sequences that do not encode conserved parts of a protein, making it an ideal tool for the identification of members of divergent protein families or of protein parts without conserved domain structures in the expressed sequence tag database. At least 14 of the expressed sequence tags found with this strategy are promising candidates for new putative G-protein coupled receptors. Here, we describe the sequence and expression analysis of five new members of this receptor superfamily, namely GPR84, GPR86, GPR87, GPR90 and GPR91. We also studied the genomic structure and chromosomal localization of the respective genes applying in silico methods. A cluster of six closely related G-protein coupled receptors was found on the human chromosome 3q24-3q25. It consists of four orphan receptors (GPR86, GPR87, GPR91, and H963), the purinergic receptor P2Y1, and the uridine 5'-diphosphoglucose receptor KIAA0001. It seems likely that these receptors evolved from a common ancestor and therefore might have related ligands. In conclusion, we describe a data mining procedure that proved to be useful for the identification and first characterization of new genes and is well applicable for other gene families. Copyright 2001 Academic Press.
Sequence and conformational preferences at termini of α-helices in membrane proteins: role of the helix environment.

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Shelar, Ashish; Bansal, Manju

2014-12-01

α-Helices are amongst the most common secondary structural elements seen in membrane proteins and are packed in the form of helix bundles. These α-helices encounter varying external environments (hydrophobic, hydrophilic) that may influence the sequence preferences at their N and C-termini. The role of the external environment in stabilization of the helix termini in membrane proteins is still unknown. Here we analyze α-helices in a high-resolution dataset of integral α-helical membrane proteins and establish that their sequence and conformational preferences differ from those in globular proteins. We specifically examine these preferences at the N and C-termini in helices initiating/terminating inside the membrane core as well as in linkers connecting these transmembrane helices. We find that the sequence preferences and structural motifs at capping (Ncap and Ccap) and near-helical (N' and C') positions are influenced by a combination of features including the membrane environment and the innate helix initiation and termination property of residues forming structural motifs. We also find that a large number of helix termini which do not form any particular capping motif are stabilized by formation of hydrogen bonds and hydrophobic interactions contributed from the neighboring helices in the membrane protein. We further validate the sequence preferences obtained from our analysis with data from an ultradeep sequencing study that identifies evolutionarily conserved amino acids in the rat neurotensin receptor. The results from our analysis provide insights for the secondary structure prediction, modeling and design of membrane proteins. © 2014 Wiley Periodicals, Inc.
The Number, Organization, and Size of Polymorphic Membrane Protein Coding Sequences as well as the Most Conserved Pmp Protein Differ within and across Chlamydia Species.

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Van Lent, Sarah; Creasy, Heather Huot; Myers, Garry S A; Vanrompay, Daisy

2016-01-01

Variation is a central trait of the polymorphic membrane protein (Pmp) family. The number of pmp coding sequences differs between Chlamydia species, but it is unknown whether the number of pmp coding sequences is constant within a Chlamydia species. The level of conservation of the Pmp proteins has previously only been determined for Chlamydia trachomatis. As different Pmp proteins might be indispensible for the pathogenesis of different Chlamydia species, this study investigated the conservation of Pmp proteins both within and across C. trachomatis,C. pneumoniae,C. abortus, and C. psittaci. The pmp coding sequences were annotated in 16 C. trachomatis, 6 C. pneumoniae, 2 C. abortus, and 16 C. psittaci genomes. The number and organization of polymorphic membrane coding sequences differed within and across the analyzed Chlamydia species. The length of coding sequences of pmpA,pmpB, and pmpH was conserved among all analyzed genomes, while the length of pmpE/F and pmpG, and remarkably also of the subtype pmpD, differed among the analyzed genomes. PmpD, PmpA, PmpH, and PmpA were the most conserved Pmp in C. trachomatis,C. pneumoniae,C. abortus, and C. psittaci, respectively. PmpB was the most conserved Pmp across the 4 analyzed Chlamydia species. © 2016 S. Karger AG, Basel.
CNNdel: Calling Structural Variations on Low Coverage Data Based on Convolutional Neural Networks

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Jing Wang

2017-01-01

Full Text Available Many structural variations (SVs detection methods have been proposed due to the popularization of next-generation sequencing (NGS. These SV calling methods use different SV-property-dependent features; however, they all suffer from poor accuracy when running on low coverage sequences. The union of results from these tools achieves fairly high sensitivity but still produces low accuracy on low coverage sequence data. That is, these methods contain many false positives. In this paper, we present CNNdel, an approach for calling deletions from paired-end reads. CNNdel gathers SV candidates reported by multiple tools and then extracts features from aligned BAM files at the positions of candidates. With labeled feature-expressed candidates as a training set, CNNdel trains convolutional neural networks (CNNs to distinguish true unlabeled candidates from false ones. Results show that CNNdel works well with NGS reads from 26 low coverage genomes of the 1000 Genomes Project. The paper demonstrates that convolutional neural networks can automatically assign the priority of SV features and reduce the false positives efficaciously.
ProtDCal: A program to compute general-purpose-numerical descriptors for sequences and 3D-structures of proteins.

Science.gov (United States)

Ruiz-Blanco, Yasser B; Paz, Waldo; Green, James; Marrero-Ponce, Yovani

2015-05-16

The exponential growth of protein structural and sequence databases is enabling multifaceted approaches to understanding the long sought sequence-structure-function relationship. Advances in computation now make it possible to apply well-established data mining and pattern recognition techniques to these data to learn models that effectively relate structure and function. However, extracting meaningful numerical descriptors of protein sequence and structure is a key issue that requires an efficient and widely available solution. We here introduce ProtDCal, a new computational software suite capable of generating tens of thousands of features considering both sequence-based and 3D-structural descriptors. We demonstrate, by means of principle component analysis and Shannon entropy tests, how ProtDCal's sequence-based descriptors provide new and more relevant information not encoded by currently available servers for sequence-based protein feature generation. The wide diversity of the 3D-structure-based features generated by ProtDCal is shown to provide additional complementary information and effectively completes its general protein encoding capability. As demonstration of the utility of ProtDCal's features, prediction models of N-linked glycosylation sites are trained and evaluated. Classification performance compares favourably with that of contemporary predictors of N-linked glycosylation sites, in spite of not using domain-specific features as input information. ProtDCal provides a friendly and cross-platform graphical user interface, developed in the Java programming language and is freely available at: http://bioinf.sce.carleton.ca/ProtDCal/ . ProtDCal introduces local and group-based encoding which enhances the diversity of the information captured by the computed features. Furthermore, we have shown that adding structure-based descriptors contributes non-redundant additional information to the features-based characterization of polypeptide systems. This
Translational database selection and multiplexed sequence capture for up front filtering of reliable breast cancer biomarker candidates.

Directory of Open Access Journals (Sweden)

Patrik L Ståhl

Full Text Available Biomarker identification is of utmost importance for the development of novel diagnostics and therapeutics. Here we make use of a translational database selection strategy, utilizing data from the Human Protein Atlas (HPA on differentially expressed protein patterns in healthy and breast cancer tissues as a means to filter out potential biomarkers for underlying genetic causatives of the disease. DNA was isolated from ten breast cancer biopsies, and the protein coding and flanking non-coding genomic regions corresponding to the selected proteins were extracted in a multiplexed format from the samples using a single DNA sequence capture array. Deep sequencing revealed an even enrichment of the multiplexed samples and a great variation of genetic alterations in the tumors of the sampled individuals. Benefiting from the upstream filtering method, the final set of biomarker candidates could be completely verified through bidirectional Sanger sequencing, revealing a 40 percent false positive rate despite high read coverage. Of the variants encountered in translated regions, nine novel non-synonymous variations were identified and verified, two of which were present in more than one of the ten tumor samples.
Exome sequencing and genetic testing for MODY.

Directory of Open Access Journals (Sweden)

Stefan Johansson

Full Text Available Genetic testing for monogenic diabetes is important for patient care. Given the extensive genetic and clinical heterogeneity of diabetes, exome sequencing might provide additional diagnostic potential when standard Sanger sequencing-based diagnostics is inconclusive.The aim of the study was to examine the performance of exome sequencing for a molecular diagnosis of MODY in patients who have undergone conventional diagnostic sequencing of candidate genes with negative results.We performed exome enrichment followed by high-throughput sequencing in nine patients with suspected MODY. They were Sanger sequencing-negative for mutations in the HNF1A, HNF4A, GCK, HNF1B and INS genes. We excluded common, non-coding and synonymous gene variants, and performed in-depth analysis on filtered sequence variants in a pre-defined set of 111 genes implicated in glucose metabolism.On average, we obtained 45 X median coverage of the entire targeted exome and found 199 rare coding variants per individual. We identified 0-4 rare non-synonymous and nonsense variants per individual in our a priori list of 111 candidate genes. Three of the variants were considered pathogenic (in ABCC8, HNF4A and PPARG, respectively, thus exome sequencing led to a genetic diagnosis in at least three of the nine patients. Approximately 91% of known heterozygous SNPs in the target exomes were detected, but we also found low coverage in some key diabetes genes using our current exome sequencing approach. Novel variants in the genes ARAP1, GLIS3, MADD, NOTCH2 and WFS1 need further investigation to reveal their possible role in diabetes.Our results demonstrate that exome sequencing can improve molecular diagnostics of MODY when used as a complement to Sanger sequencing. However, improvements will be needed, especially concerning coverage, before the full potential of exome sequencing can be realized.
Modeling compositional dynamics based on GC and purine contents of protein-coding sequences

KAUST Repository

Zhang, Zhang

2010-11-08

Background: Understanding the compositional dynamics of genomes and their coding sequences is of great significance in gaining clues into molecular evolution and a large number of publically-available genome sequences have allowed us to quantitatively predict deviations of empirical data from their theoretical counterparts. However, the quantification of theoretical compositional variations for a wide diversity of genomes remains a major challenge.Results: To model the compositional dynamics of protein-coding sequences, we propose two simple models that take into account both mutation and selection effects, which act differently at the three codon positions, and use both GC and purine contents as compositional parameters. The two models concern the theoretical composition of nucleotides, codons, and amino acids, with no prerequisite of homologous sequences or their alignments. We evaluated the two models by quantifying theoretical compositions of a large collection of protein-coding sequences (including 46 of Archaea, 686 of Bacteria, and 826 of Eukarya), yielding consistent theoretical compositions across all the collected sequences.Conclusions: We show that the compositions of nucleotides, codons, and amino acids are largely determined by both GC and purine contents and suggest that deviations of the observed from the expected compositions may reflect compositional signatures that arise from a complex interplay between mutation and selection via DNA replication and repair mechanisms.Reviewers: This article was reviewed by Zhaolei Zhang (nominated by Mark Gerstein), Guruprasad Ananda (nominated by Kateryna Makova), and Daniel Haft. 2010 Zhang and Yu; licensee BioMed Central Ltd.
Modeling compositional dynamics based on GC and purine contents of protein-coding sequences

KAUST Repository

Zhang, Zhang; Yu, Jun

2010-01-01

Background: Understanding the compositional dynamics of genomes and their coding sequences is of great significance in gaining clues into molecular evolution and a large number of publically-available genome sequences have allowed us to quantitatively predict deviations of empirical data from their theoretical counterparts. However, the quantification of theoretical compositional variations for a wide diversity of genomes remains a major challenge.Results: To model the compositional dynamics of protein-coding sequences, we propose two simple models that take into account both mutation and selection effects, which act differently at the three codon positions, and use both GC and purine contents as compositional parameters. The two models concern the theoretical composition of nucleotides, codons, and amino acids, with no prerequisite of homologous sequences or their alignments. We evaluated the two models by quantifying theoretical compositions of a large collection of protein-coding sequences (including 46 of Archaea, 686 of Bacteria, and 826 of Eukarya), yielding consistent theoretical compositions across all the collected sequences.Conclusions: We show that the compositions of nucleotides, codons, and amino acids are largely determined by both GC and purine contents and suggest that deviations of the observed from the expected compositions may reflect compositional signatures that arise from a complex interplay between mutation and selection via DNA replication and repair mechanisms.Reviewers: This article was reviewed by Zhaolei Zhang (nominated by Mark Gerstein), Guruprasad Ananda (nominated by Kateryna Makova), and Daniel Haft. 2010 Zhang and Yu; licensee BioMed Central Ltd.
An alignment-free method to find similarity among protein sequences via the general form of Chou's pseudo amino acid composition.

Science.gov (United States)

Gupta, M K; Niyogi, R; Misra, M

2013-01-01

In this paper, we propose a method to create the 60-dimensional feature vector for protein sequences via the general form of pseudo amino acid composition. The construction of the feature vector is based on the contents of amino acids, total distance of each amino acid from the first amino acid in the protein sequence and the distribution of 20 amino acids. The obtained cosine distance metric (also called the similarity matrix) is used to construct the phylogenetic tree by the neighbour joining method. In order to show the applicability of our approach, we tested it on three proteins: 1) ND5 protein sequences from nine species, 2) ND6 protein sequences from eight species, and 3) 50 coronavirus spike proteins. The results are in agreement with known history and the output from the multiple sequence alignment program ClustalW, which is widely used. We have also compared our phylogenetic results with six other recently proposed alignment-free methods. These comparisons show that our proposed method gives a more consistent biological relationship than the others. In addition, the time complexity is linear and space required is less as compared with other alignment-free methods that use graphical representation. It should be noted that the multiple sequence alignment method has exponential time complexity.
The diploid genome sequence of an Asian individual

DEFF Research Database (Denmark)

Wang, Jun; Wang, Wei; Li, Ruiqiang

2008-01-01

Here we present the first diploid genome sequence of an Asian individual. The genome was sequenced to 36-fold average coverage using massively parallel sequencing technology. We aligned the short reads onto the NCBI human reference genome to 99.97% coverage, and guided by the reference genome, we...... used uniquely mapped reads to assemble a high-quality consensus sequence for 92% of the Asian individual's genome. We identified approximately 3 million single-nucleotide polymorphisms (SNPs) inside this region, of which 13.6% were not in the dbSNP database. Genotyping analysis showed that SNP...... identification had high accuracy and consistency, indicating the high sequence quality of this assembly. We also carried out heterozygote phasing and haplotype prediction against HapMap CHB and JPT haplotypes (Chinese and Japanese, respectively), sequence comparison with the two available individual genomes (J...
An intuitive graphical webserver for multiple-choice protein sequence search.

Science.gov (United States)

Banky, Daniel; Szalkai, Balazs; Grolmusz, Vince

2014-04-10

Every day tens of thousands of sequence searches and sequence alignment queries are submitted to webservers. The capitalized word "BLAST" becomes a verb, describing the act of performing sequence search and alignment. However, if one needs to search for sequences that contain, for example, two hydrophobic and three polar residues at five given positions, the query formation on the most frequently used webservers will be difficult. Some servers support the formation of queries with regular expressions, but most of the users are unfamiliar with their syntax. Here we present an intuitive, easily applicable webserver, the Protein Sequence Analysis server, that allows the formation of multiple choice queries by simply drawing the residues to their positions; if more than one residue are drawn to the same position, then they will be nicely stacked on the user interface, indicating the multiple choice at the given position. This computer-game-like interface is natural and intuitive, and the coloring of the residues makes possible to form queries requiring not just certain amino acids in the given positions, but also small nonpolar, negatively charged, hydrophobic, positively charged, or polar ones. The webserver is available at http://psa.pitgroup.org. Copyright © 2014 Elsevier B.V. All rights reserved.
MIToS.jl: mutual information tools for protein sequence analysis in the Julia language

DEFF Research Database (Denmark)

Zea, Diego J.; Anfossi, Diego; Nielsen, Morten

2017-01-01

Motivation: MIToS is an environment for mutual information analysis and a framework for protein multiple sequence alignments (MSAs) and protein structures (PDB) management in Julia language. It integrates sequence and structural information through SIFTS, making Pfam MSAs analysis straightforward....... MIToS streamlines the implementation of any measure calculated from residue contingency tables and its optimization and testing in terms of protein contact prediction. As an example, we implemented and tested a BLOSUM62-based pseudo-count strategy in mutual information analysis. Availability...... and Implementation: The software is totally implemented in Julia and supported for Linux, OS X and Windows. It’s freely available on GitHub under MIT license: http://mitos.leloir.org.ar. Contacts:diegozea@gmail.com or cmb@leloir.org.ar Supplementary information: Supplementary data are available at Bioinformatics...

Prediction of Protein–Protein Interactions by Evidence Combining Methods

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Ji-Wei Chang

2016-11-01

Full Text Available Most cellular functions involve proteins’ features based on their physical interactions with other partner proteins. Sketching a map of protein–protein interactions (PPIs is therefore an important inception step towards understanding the basics of cell functions. Several experimental techniques operating in vivo or in vitro have made significant contributions to screening a large number of protein interaction partners, especially high-throughput experimental methods. However, computational approaches for PPI predication supported by rapid accumulation of data generated from experimental techniques, 3D structure definitions, and genome sequencing have boosted the map sketching of PPIs. In this review, we shed light on in silico PPI prediction methods that integrate evidence from multiple sources, including evolutionary relationship, function annotation, sequence/structure features, network topology and text mining. These methods are developed for integration of multi-dimensional evidence, for designing the strategies to predict novel interactions, and for making the results consistent with the increase of prediction coverage and accuracy.
Implementation of Targeted Next Generation Sequencing in Clinical Diagnostics

DEFF Research Database (Denmark)

Larsen, Martin Jakob; Burton, Mark; Thomassen, Mads

Accurate mutation detection is essential in clinical genetic diagnostics of monogenic hereditary diseases. Targeted next generation sequencing (NGS) provides a promising and cost-effective alternative to Sanger sequencing and MLPA analysis currently used in most diagnostic laboratories. One...... of mutation positive controls previously characterized by Sanger/MLPA analysis. Agilent SureSelect Target-Enrichment kits were used for capturing a set of genes associated with hereditary breast and ovarian cancer syndrome and a compilation of genes involved in multiple rare single gene disorders......, respectively. For diagnostics, the sequencing coverage is essential, wherefore a minimum coverage of 30x per nucleotide in the coding regions was used as our primary quality criterion. For the majority of the included genes, we obtained adequate gene coverage, in which we were able to detect 100% of the known...
Nucleotide sequence of Phaseolus vulgaris L. alcohol dehydrogenase encoding cDNA and three-dimensional structure prediction of the deduced protein.

Science.gov (United States)

Amelia, Kassim; Khor, Chin Yin; Shah, Farida Habib; Bhore, Subhash J

2015-01-01

Common beans (Phaseolus vulgaris L.) are widely consumed as a source of proteins and natural products. However, its yield needs to be increased. In line with the agenda of Phaseomics (an international consortium), work of expressed sequence tags (ESTs) generation from bean pods was initiated. Altogether, 5972 ESTs have been isolated. Alcohol dehydrogenase (AD) encoding gene cDNA was a noticeable transcript among the generated ESTs. This AD is an important enzyme; therefore, to understand more about it this study was undertaken. The objective of this study was to elucidate P. vulgaris L. AD (PvAD) gene cDNA sequence and to predict the three-dimensional (3D) structure of deduced protein. positive and negative strands of the PvAD cDNA clone were sequenced using M13 forward and M13 reverse primers to elucidate the nucleotide sequence. Deduced PvAD cDNA and protein sequence was analyzed for their basic features using online bioinformatics tools. Sequence comparison was carried out using bl2seq program, and tree-view program was used to construct a phylogenetic tree. The secondary structures and 3D structure of PvAD protein were predicted by using the PHYRE automatic fold recognition server. The sequencing results analysis showed that PvAD cDNA is 1294 bp in length. It's open reading frame encodes for a protein that contains 371 amino acids. Deduced protein sequence analysis showed the presence of putative substrate binding, catalytic Zn binding, and NAD binding sites. Results indicate that the predicted 3D structure of PvAD protein is analogous to the experimentally determined crystal structure of s-nitrosoglutathione reductase from an Arabidopsis species. The 1294 bp long PvAD cDNA encodes for 371 amino acid long protein that contains conserved domains required for biological functions of AD. The predicted deduced PvAD protein's 3D structure reflects the analogy with the crystal structure of Arabidopsis thaliana s-nitrosoglutathione reductase. Further study is required
Structural analysis of a set of proteins resulting from a bacterial genomics project.

Science.gov (United States)

Badger, J; Sauder, J M; Adams, J M; Antonysamy, S; Bain, K; Bergseid, M G; Buchanan, S G; Buchanan, M D; Batiyenko, Y; Christopher, J A; Emtage, S; Eroshkina, A; Feil, I; Furlong, E B; Gajiwala, K S; Gao, X; He, D; Hendle, J; Huber, A; Hoda, K; Kearins, P; Kissinger, C; Laubert, B; Lewis, H A; Lin, J; Loomis, K; Lorimer, D; Louie, G; Maletic, M; Marsh, C D; Miller, I; Molinari, J; Muller-Dieckmann, H J; Newman, J M; Noland, B W; Pagarigan, B; Park, F; Peat, T S; Post, K W; Radojicic, S; Ramos, A; Romero, R; Rutter, M E; Sanderson, W E; Schwinn, K D; Tresser, J; Winhoven, J; Wright, T A; Wu, L; Xu, J; Harris, T J R

2005-09-01

The targets of the Structural GenomiX (SGX) bacterial genomics project were proteins conserved in multiple prokaryotic organisms with no obvious sequence homolog in the Protein Data Bank of known structures. The outcome of this work was 80 structures, covering 60 unique sequences and 49 different genes. Experimental phase determination from proteins incorporating Se-Met was carried out for 45 structures with most of the remainder solved by molecular replacement using members of the experimentally phased set as search models. An automated tool was developed to deposit these structures in the Protein Data Bank, along with the associated X-ray diffraction data (including refined experimental phases) and experimentally confirmed sequences. BLAST comparisons of the SGX structures with structures that had appeared in the Protein Data Bank over the intervening 3.5 years since the SGX target list had been compiled identified homologs for 49 of the 60 unique sequences represented by the SGX structures. This result indicates that, for bacterial structures that are relatively easy to express, purify, and crystallize, the structural coverage of gene space is proceeding rapidly. More distant sequence-structure relationships between the SGX and PDB structures were investigated using PDB-BLAST and Combinatorial Extension (CE). Only one structure, SufD, has a truly unique topology compared to all folds in the PDB. Copyright 2005 Wiley-Liss, Inc.
Middle Pleistocene protein sequences from the rhinoceros genus Stephanorhinus and the phylogeny of extant and extinct Middle/Late Pleistocene Rhinocerotidae.

Science.gov (United States)

Welker, Frido; Smith, Geoff M; Hutson, Jarod M; Kindler, Lutz; Garcia-Moreno, Alejandro; Villaluenga, Aritza; Turner, Elaine; Gaudzinski-Windheuser, Sabine

2017-01-01

Ancient protein sequences are increasingly used to elucidate the phylogenetic relationships between extinct and extant mammalian taxa. Here, we apply these recent developments to Middle Pleistocene bone specimens of the rhinoceros genus Stephanorhinus . No biomolecular sequence data is currently available for this genus, leaving phylogenetic hypotheses on its evolutionary relationships to extant and extinct rhinoceroses untested. Furthermore, recent phylogenies based on Rhinocerotidae (partial or complete) mitochondrial DNA sequences differ in the placement of the Sumatran rhinoceros ( Dicerorhinus sumatrensis ). Therefore, studies utilising ancient protein sequences from Middle Pleistocene contexts have the potential to provide further insights into the phylogenetic relationships between extant and extinct species, including Stephanorhinus and Dicerorhinus . ZooMS screening (zooarchaeology by mass spectrometry) was performed on several Late and Middle Pleistocene specimens from the genus Stephanorhinus , subsequently followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) to obtain ancient protein sequences from a Middle Pleistocene Stephanorhinus specimen. We performed parallel analysis on a Late Pleistocene woolly rhinoceros specimen and extant species of rhinoceroses, resulting in the availability of protein sequence data for five extant species and two extinct genera. Phylogenetic analysis additionally included all extant Perissodactyla genera ( Equus , Tapirus ), and was conducted using Bayesian (MrBayes) and maximum-likelihood (RAxML) methods. Various ancient proteins were identified in both the Middle and Late Pleistocene rhinoceros samples. Protein degradation and proteome complexity are consistent with an endogenous origin of the identified proteins. Phylogenetic analysis of informative proteins resolved the Perissodactyla phylogeny in agreement with previous studies in regards to the placement of the families Equidae, Tapiridae, and
Oral treponeme major surface protein: Sequence diversity and distributions within periodontal niches.

Science.gov (United States)

You, M; Chan, Y; Lacap-Bugler, D C; Huo, Y-B; Gao, W; Leung, W K; Watt, R M

2017-12-01

Treponema denticola and other species (phylotypes) of oral spirochetes are widely considered to play important etiological roles in periodontitis and other oral infections. The major surface protein (Msp) of T. denticola is directly implicated in several pathological mechanisms. Here, we have analyzed msp sequence diversity across 68 strains of oral phylogroup 1 and 2 treponemes; including reference strains of T. denticola, Treponema putidum, Treponema medium, 'Treponema vincentii', and 'Treponema sinensis'. All encoded Msp proteins contained highly conserved, taxon-specific signal peptides, and shared a predicted 'three-domain' structure. A clone-based strategy employing 'msp-specific' polymerase chain reaction primers was used to analyze msp gene sequence diversity present in subgingival plaque samples collected from a group of individuals with chronic periodontitis (n=10), vs periodontitis-free controls (n=10). We obtained 626 clinical msp gene sequences, which were assigned to 21 distinct 'clinical msp genotypes' (95% sequence identity cut-off). The most frequently detected clinical msp genotype corresponded to T. denticola ATCC 35405 T , but this was not correlated to disease status. UniFrac and libshuff analysis revealed that individuals with periodontitis and periodontitis-free controls harbored significantly different communities of treponeme clinical msp genotypes (Pdiversity than periodontitis-free controls (Mann-Whitney U-test, Pdiversity of Treponema clinical msp genotypes within their subgingival niches. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
A polyvalent hybrid protein elicits antibodies against the diverse allelic types of block 2 in Plasmodium falciparum merozoite surface protein 1.

Science.gov (United States)

Tetteh, Kevin K A; Conway, David J

2011-10-13

Merozoite surface protein 1 (MSP1) of Plasmodium falciparum has been implicated as an important target of acquired immunity, and candidate components for a vaccine include polymorphic epitopes in the N-terminal polymorphic block 2 region. We designed a polyvalent hybrid recombinant protein incorporating sequences of the three major allelic types of block 2 together with a composite repeat sequence of one of the types and N-terminal flanking T cell epitopes, and compared this with a series of recombinant proteins containing modular sub-components and similarly expressed in Escherichia coli. Immunogenicity of the full polyvalent hybrid protein was tested in both mice and rabbits, and comparative immunogenicity studies of the sub-component modules were performed in mice. The full hybrid protein induced high titre antibodies against each of the major block 2 allelic types expressed as separate recombinant proteins and against a wide range of allelic types naturally expressed by a panel of diverse P. falciparum isolates, while the sub-component modules had partial antigenic coverage as expected. This encourages further development and evaluation of the full MSP1 block 2 polyvalent hybrid protein as a candidate blood-stage component of a malaria vaccine. Copyright © 2011 Elsevier Ltd. All rights reserved.
Amino acid sequences of predicted proteins and their annotation for 95 organism species. - Gclust Server | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Gclust Server Amino acid sequences of predicted proteins and their annotation for 95 organis...m species. Data detail Data name Amino acid sequences of predicted proteins and their annotation for 95 orga...nism species. DOI 10.18908/lsdba.nbdc00464-001 Description of data contents Amino acid sequences of predicted proteins...Database Description Download License Update History of This Database Site Policy | Contact Us Amino acid sequences of predicted prot...eins and their annotation for 95 organism species. - Gclust Server | LSDB Archive ...
Evolutionary rates at codon sites may be used to align sequences and infer protein domain function

Directory of Open Access Journals (Sweden)

Hazelhurst Scott

2010-03-01

Full Text Available Abstract Background Sequence alignments form part of many investigations in molecular biology, including the determination of phylogenetic relationships, the prediction of protein structure and function, and the measurement of evolutionary rates. However, to obtain meaningful results, a significant degree of sequence similarity is required to ensure that the alignments are accurate and the inferences correct. Limitations arise when sequence similarity is low, which is particularly problematic when working with fast-evolving genes, evolutionary distant taxa, genomes with nucleotide biases, and cases of convergent evolution. Results A novel approach was conceptualized to address the "low sequence similarity" alignment problem. We developed an alignment algorithm termed FIRE (Functional Inference using the Rates of Evolution, which aligns sequences using the evolutionary rate at codon sites, as measured by the dN/dS ratio, rather than nucleotide or amino acid residues. FIRE was used to test the hypotheses that evolutionary rates can be used to align sequences and that the alignments may be used to infer protein domain function. Using a range of test data, we found that aligning domains based on evolutionary rates was possible even when sequence similarity was very low (for example, antibody variable regions. Furthermore, the alignment has the potential to infer protein domain function, indicating that domains with similar functions are subject to similar evolutionary constraints. These data suggest that an evolutionary rate-based approach to sequence analysis (particularly when combined with structural data may be used to study cases of convergent evolution or when sequences have very low similarity. However, when aligning homologous gene sets with sequence similarity, FIRE did not perform as well as the best traditional alignment algorithms indicating that the conventional approach of aligning residues as opposed to evolutionary rates remains the
Rapid and Deep Proteomes by Faster Sequencing on a Benchtop Quadrupole Ultra-High-Field Orbitrap Mass Spectrometer

DEFF Research Database (Denmark)

Kelstrup, Christian D; Jersie-Christensen, Rosa R; Batth, Tanveer Singh

2014-01-01

per second or up to 600 new peptides sequenced per gradient minute. We identify 4400 proteins from one microgram of HeLa digest using a one hour gradient, which is an approximately 30% improvement compared to previous instrumentation. In addition, we show very deep proteome coverage can be achieved...... in less than 24 hours of analysis time by offline high pH reversed-phase peptide fractionation from which we identify more than 140,000 unique peptide sequences. This is comparable to state-of-the-art multi-day, multi-enzyme efforts. Finally the acquisition methods are evaluated for single...
Comparative In silico Study of Sex-Determining Region Y (SRY) Protein Sequences Involved in Sex-Determining.

Science.gov (United States)

Vakili Azghandi, Masoume; Nasiri, Mohammadreza; Shamsa, Ali; Jalali, Mohsen; Shariati, Mohammad Mahdi

2016-04-01

The SRY gene (SRY) provides instructions for making a transcription factor called the sex-determining region Y protein. The sex-determining region Y protein causes a fetus to develop as a male. In this study, SRY of 15 spices included of human, chimpanzee, dog, pig, rat, cattle, buffalo, goat, sheep, horse, zebra, frog, urial, dolphin and killer whale were used for determine of bioinformatic differences. Nucleotide sequences of SRY were retrieved from the NCBI databank. Bioinformatic analysis of SRY is done by CLC Main Workbench version 5.5 and ClustalW (http:/www.ebi.ac.uk/clustalw/) and MEGA6 softwares. The multiple sequence alignment results indicated that SRY protein sequences from Orcinus orca (killer whale) and Tursiopsaduncus (dolphin) have least genetic distance of 0.33 in these 15 species and are 99.67% identical at the amino acid level. Homosapiens and Pantroglodytes (chimpanzee) have the next lowest genetic distance of 1.35 and are 98.65% identical at the amino acid level. These findings indicate that the SRY proteins are conserved in the 15 species, and their evolutionary relationships are similar.
Disulfide Linkage Characterization of Disulfide Bond-Containing Proteins and Peptides by Reducing Electrochemistry and Mass Spectrometry

DEFF Research Database (Denmark)

Cramer, Christian N; Haselmann, Kim F; Olsen, Jesper V

2016-01-01

in protein sequencing by tandem MS (MS/MS). Electrochemical (EC) reduction of disulfide bonds has recently been demonstrated to provide efficient reduction efficiencies, significantly enhancing sequence coverages in online coupling with MS characterization. In this study, the potential use of EC disulfide...... link between parent disulfide-linked fragments and free reduced peptides in an LC-EC-MS platform of nonreduced proteolytic protein digestions. Here we report the successful use of EC as a partial reduction approach in mapping of disulfide bonds of intact human insulin (HI) and lysozyme. In addition, we...... established a LC-EC-MS platform advantageous in disulfide characterization of complex and highly disulfide-bonded proteins such as human serum albumin (HSA) by online EC reduction of nonreduced proteolytic digestions....
Sequence of a cloned cDNA encoding human ribosomal protein S11

Energy Technology Data Exchange (ETDEWEB)

Lott, J B; Mackie, G A

1988-02-11

The authors have isolated a cloned cDNA that encodes human ribosomal protein (rp) S11 by screening a human fibroblast cDNA library with a labelled 204 bp DNA fragment encompassing residues 212-416 of pRS11, a rat rp Sll cDNA clone. The human rp S11 cloned cDNA consists of 15 residues of the 5' leader, the entire coding sequence and all 51 residues of the 3' untranslated region. The predicted amino acid sequence of 158 residues is identical to rat rpS11. The nucleotide sequence in the coding region differs, however, from that in rat in the first position in two codons and in the third position in 44 codons.
An Alignment-Free Algorithm in Comparing the Similarity of Protein Sequences Based on Pseudo-Markov Transition Probabilities among Amino Acids.

Science.gov (United States)

Li, Yushuang; Song, Tian; Yang, Jiasheng; Zhang, Yi; Yang, Jialiang

2016-01-01

In this paper, we have proposed a novel alignment-free method for comparing the similarity of protein sequences. We first encode a protein sequence into a 440 dimensional feature vector consisting of a 400 dimensional Pseudo-Markov transition probability vector among the 20 amino acids, a 20 dimensional content ratio vector, and a 20 dimensional position ratio vector of the amino acids in the sequence. By evaluating the Euclidean distances among the representing vectors, we compare the similarity of protein sequences. We then apply this method into the ND5 dataset consisting of the ND5 protein sequences of 9 species, and the F10 and G11 datasets representing two of the xylanases containing glycoside hydrolase families, i.e., families 10 and 11. As a result, our method achieves a correlation coefficient of 0.962 with the canonical protein sequence aligner ClustalW in the ND5 dataset, much higher than those of other 5 popular alignment-free methods. In addition, we successfully separate the xylanases sequences in the F10 family and the G11 family and illustrate that the F10 family is more heat stable than the G11 family, consistent with a few previous studies. Moreover, we prove mathematically an identity equation involving the Pseudo-Markov transition probability vector and the amino acids content ratio vector.
Amyloid fibril formation from sequences of a natural beta-structured fibrous protein, the adenovirus fiber.

Science.gov (United States)

Papanikolopoulou, Katerina; Schoehn, Guy; Forge, Vincent; Forsyth, V Trevor; Riekel, Christian; Hernandez, Jean-François; Ruigrok, Rob W H; Mitraki, Anna

2005-01-28

Amyloid fibrils are fibrous beta-structures that derive from abnormal folding and assembly of peptides and proteins. Despite a wealth of structural studies on amyloids, the nature of the amyloid structure remains elusive; possible connections to natural, beta-structured fibrous motifs have been suggested. In this work we focus on understanding amyloid structure and formation from sequences of a natural, beta-structured fibrous protein. We show that short peptides (25 to 6 amino acids) corresponding to repetitive sequences from the adenovirus fiber shaft have an intrinsic capacity to form amyloid fibrils as judged by electron microscopy, Congo Red binding, infrared spectroscopy, and x-ray fiber diffraction. In the presence of the globular C-terminal domain of the protein that acts as a trimerization motif, the shaft sequences adopt a triple-stranded, beta-fibrous motif. We discuss the possible structure and arrangement of these sequences within the amyloid fibril, as compared with the one adopted within the native structure. A 6-amino acid peptide, corresponding to the last beta-strand of the shaft, was found to be sufficient to form amyloid fibrils. Structural analysis of these amyloid fibrils suggests that perpendicular stacking of beta-strand repeat units is an underlying common feature of amyloid formation.
Predicted Strain Coverage of a New Meningococcal Multicomponent Vaccine (4CMenB in Spain: Analysis of the Differences with Other European Countries.

Directory of Open Access Journals (Sweden)

Raquel Abad

Full Text Available A novel meningococcal multicomponent vaccine, 4CMenB (Bexsero®, has been approved in Europe, Canada, Australia and US. The potential impact of 4CMenB on strain coverage is being estimated by using Meningococcal Antigen Typing System (MATS, an ELISA assay which measures vaccine antigen expression and diversity in each strain. Here we show the genetic characterization and the 4CMenB potential coverage of Spanish invasive strains (collected during one epidemiological year compared to other European countries and discuss the potential reasons for the lower estimate of coverage in Spain.A panel of 300 strains, a representative sample of all serogroup B Neisseria meningitidis notified cases in Spain from 2009 to 2010, was characterized by multilocus sequence typing (MLST and FetA variable region determination. 4CMenB vaccine antigens, PorA, factor H binding protein (fHbp, Neisseria Heparin Binding Antigen (NHBA and Neisserial adhesin A (NadA were molecularly typed by sequencing. PorA coverage was assigned to strain with VR2 = 4. The levels of expression and cross-reactivity of fHbp, NHBA and NadA were analyzed using MATS ELISA.Global estimated strain coverage by MATS was 68.67% (95% CI: 47.77-84.59%, with 51.33%, 15.33% and 2% of strains covered by one, two and three vaccine antigens, respectively. The predicted strain coverage by individual antigens was: 42% NHBA, 36.33% fHbp, 8.33% PorA and 1.33% NadA. Coverage within the most prevalent clonal complexes (cc was 70.37% for cc 269, 30.19% for cc 213 and 95.83% for cc 32.Clonal complexes (cc distribution accounts for variations in strain coverage, so that country-by-country investigations of strain coverage and cc prevalence are important. Because the cc distribution could also vary over time, which in turn could lead to changes in strain coverage, continuous detailed surveillance and monitoring of vaccine antigens expression is needed in those countries where the multicomponent vaccine is introduced
Statistical distributions of optimal global alignment scores of random protein sequences

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Tang Jiaowei

2005-10-01

Full Text Available Abstract Background The inference of homology from statistically significant sequence similarity is a central issue in sequence alignments. So far the statistical distribution function underlying the optimal global alignments has not been completely determined. Results In this study, random and real but unrelated sequences prepared in six different ways were selected as reference datasets to obtain their respective statistical distributions of global alignment scores. All alignments were carried out with the Needleman-Wunsch algorithm and optimal scores were fitted to the Gumbel, normal and gamma distributions respectively. The three-parameter gamma distribution performs the best as the theoretical distribution function of global alignment scores, as it agrees perfectly well with the distribution of alignment scores. The normal distribution also agrees well with the score distribution frequencies when the shape parameter of the gamma distribution is sufficiently large, for this is the scenario when the normal distribution can be viewed as an approximation of the gamma distribution. Conclusion We have shown that the optimal global alignment scores of random protein sequences fit the three-parameter gamma distribution function. This would be useful for the inference of homology between sequences whose relationship is unknown, through the evaluation of gamma distribution significance between sequences.
Fast and simple protein-alignment-guided assembly of orthologous gene families from microbiome sequencing reads.

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Huson, Daniel H; Tappu, Rewati; Bazinet, Adam L; Xie, Chao; Cummings, Michael P; Nieselt, Kay; Williams, Rohan

2017-01-25

Microbiome sequencing projects typically collect tens of millions of short reads per sample. Depending on the goals of the project, the short reads can either be subjected to direct sequence analysis or be assembled into longer contigs. The assembly of whole genomes from metagenomic sequencing reads is a very difficult problem. However, for some questions, only specific genes of interest need to be assembled. This is then a gene-centric assembly where the goal is to assemble reads into contigs for a family of orthologous genes. We present a new method for performing gene-centric assembly, called protein-alignment-guided assembly, and provide an implementation in our metagenome analysis tool MEGAN. Genes are assembled on the fly, based on the alignment of all reads against a protein reference database such as NCBI-nr. Specifically, the user selects a gene family based on a classification such as KEGG and all reads binned to that gene family are assembled. Using published synthetic community metagenome sequencing reads and a set of 41 gene families, we show that the performance of this approach compares favorably with that of full-featured assemblers and that of a recently published HMM-based gene-centric assembler, both in terms of the number of reference genes detected and of the percentage of reference sequence covered. Protein-alignment-guided assembly of orthologous gene families complements whole-metagenome assembly in a new and very useful way.
COCACOLA: binning metagenomic contigs using sequence COmposition, read CoverAge, CO-alignment and paired-end read LinkAge.

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Lu, Yang Young; Chen, Ting; Fuhrman, Jed A; Sun, Fengzhu

2017-03-15

The advent of next-generation sequencing technologies enables researchers to sequence complex microbial communities directly from the environment. Because assembly typically produces only genome fragments, also known as contigs, instead of an entire genome, it is crucial to group them into operational taxonomic units (OTUs) for further taxonomic profiling and down-streaming functional analysis. OTU clustering is also referred to as binning. We present COCACOLA, a general framework automatically bin contigs into OTUs based on sequence composition and coverage across multiple samples. The effectiveness of COCACOLA is demonstrated in both simulated and real datasets in comparison with state-of-art binning approaches such as CONCOCT, GroopM, MaxBin and MetaBAT. The superior performance of COCACOLA relies on two aspects. One is using L 1 distance instead of Euclidean distance for better taxonomic identification during initialization. More importantly, COCACOLA takes advantage of both hard clustering and soft clustering by sparsity regularization. In addition, the COCACOLA framework seamlessly embraces customized knowledge to facilitate binning accuracy. In our study, we have investigated two types of additional knowledge, the co-alignment to reference genomes and linkage of contigs provided by paired-end reads, as well as the ensemble of both. We find that both co-alignment and linkage information further improve binning in the majority of cases. COCACOLA is scalable and faster than CONCOCT, GroopM, MaxBin and MetaBAT. The software is available at https://github.com/younglululu/COCACOLA . fsun@usc.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com
Simple sequence proteins in prokaryotic proteomes

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Ramachandran Srinivasan

2006-06-01

Full Text Available Abstract Background The structural and functional features associated with Simple Sequence Proteins (SSPs are non-globularity, disease states, signaling and post-translational modification. SSPs are also an important source of genetic and possibly phenotypic variation. Analysis of 249 prokaryotic proteomes offers a new opportunity to examine the genomic properties of SSPs. Results SSPs are a minority but they grow with proteome size. This relationship is exhibited across species varying in genomic GC, mutational bias, life style, and pathogenicity. Their proportion in each proteome is strongly influenced by genomic base compositional bias. In most species simple duplications is favoured, but in a few cases such as Mycobacteria, large families of duplications occur. Amino acid preference in SSPs exhibits a trend towards low cost of biosynthesis. In SSPs and in non-SSPs, Alanine, Glycine, Leucine, and Valine are abundant in species widely varying in genomic GC whereas Isoleucine and Lysine are rich only in organisms with low genomic GC. Arginine is abundant in SSPs of two species and in the non-SSPs of Xanthomonas oryzae. Asparagine is abundant only in SSPs of low GC species. Aspartic acid is abundant only in the non-SSPs of Halobacterium sp NRC1. The abundance of Serine in SSPs of 62 species extends over a broader range compared to that of non-SSPs. Threonine(T is abundant only in SSPs of a couple of species. SSPs exhibit preferential association with Cell surface, Cell membrane and Transport functions and a negative association with Metabolism. Mesophiles and Thermophiles display similar ranges in the content of SSPs. Conclusion Although SSPs are a minority, the genomic forces of base compositional bias and duplications influence their growth and pattern in each species. The preferences and abundance of amino acids are governed by low biosynthetic cost, evolutionary age and base composition of codons. Abundance of charged amino acids Arginine

In situ detection of a heat-shock regulatory element binding protein using a soluble short synthetic enhancer sequence

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Harel-Bellan, A; Brini, A T; Farrar, W L [National Cancer Institute, Frederick, MD (USA); Ferris, D K [Program Resources, Inc., Frederick, MD (USA); Robin, P [Institut Gustave Roussy, Villejuif (France)

1989-06-12

In various studies, enhancer binding proteins have been successfully absorbed out by competing sequences inserted into plasmids, resulting in the inhibition of the plasmid expression. Theoretically, such a result could be achieved using synthetic enhancer sequences not inserted into plasmids. In this study, a double stranded DNA sequence corresponding to the human heat shock regulatory element was chemically synthesized. By in vitro retardation assays, the synthetic sequence was shown to bind specifically a protein in extracts from the human T cell line Jurkat. When the synthetic enhancer was electroporated into Jurkat cells, not only the enhancer was shown to remain undegraded into the cells for up to 2 days, but also its was shown to bind intracellularly a protein. The binding was specific and was modulated upon heat shock. Furthermore, the binding protein was shown to be of the expected molecular weight by UV crosslinking. However, when the synthetic enhancer element was co-electroporated with an HSP 70-CAT reporter construct, the expression of the reporter plasmid was consistently enhanced in the presence of the exogenous synthetic enhancer.
A protein-tyrosine phosphatase with sequence similarity to the SH2 domain of the protein-tyrosine kinases.

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Shen, S H; Bastien, L; Posner, B I; Chrétien, P

1991-08-22

The phosphorylation of proteins at tyrosine residues is critical in cellular signal transduction, neoplastic transformation and control of the mitotic cycle. These mechanisms are regulated by the activities of both protein-tyrosine kinases (PTKs) and protein-tyrosine phosphatases (PTPases). As in the PTKs, there are two classes of PTPases: membrane associated, receptor-like enzymes and soluble proteins. Here we report the isolation of a complementary DNA clone encoding a new form of soluble PTPase, PTP1C. The enzyme possesses a large noncatalytic region at the N terminus which unexpectedly contains two adjacent copies of the Src homology region 2 (the SH2 domain) found in various nonreceptor PTKs and other cytoplasmic signalling proteins. As with other SH2 sequences, the SH2 domains of PTP1C formed high-affinity complexes with the activated epidermal growth factor receptor and other phosphotyrosine-containing proteins. These results suggest that the SH2 regions in PTP1C may interact with other cellular components to modulate its own phosphatase activity against interacting substrates. PTPase activity may thus directly link growth factor receptors and other signalling proteins through protein-tyrosine phosphorylation.
Electrophoretic mobility shift assay reveals a novel recognition sequence for Setaria italica NAC protein.

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Puranik, Swati; Kumar, Karunesh; Srivastava, Prem S; Prasad, Manoj

2011-10-01

The NAC (NAM/ATAF1,2/CUC2) proteins are among the largest family of plant transcription factors. Its members have been associated with diverse plant processes and intricately regulate the expression of several genes. Inspite of this immense progress, knowledge of their DNA-binding properties are still limited. In our recent publication,1 we reported isolation of a membrane-associated NAC domain protein from Setaria italica (SiNAC). Transactivation analysis revealed that it was a functionally active transcription factor as it could stimulate expression of reporter genes in vivo. Truncations of the transmembrane region of the protein lead to its nuclear localization. Here we describe expression and purification of SiNAC DNA-binding domain. We further report identification of a novel DNA-binding site, [C/G][A/T][T/A][G/C]TC[C/G][A/T][C/G][G/C] for SiNAC by electrophoretic mobility shift assay. The SiNAC-GST protein could bind to the NAC recognition sequence in vitro as well as to sequences where some bases had been reshuffled. The results presented here contribute to our understanding of the DNA-binding specificity of SiNAC protein.
GenProBiS: web server for mapping of sequence variants to protein binding sites.

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Konc, Janez; Skrlj, Blaz; Erzen, Nika; Kunej, Tanja; Janezic, Dusanka

2017-07-03

Discovery of potentially deleterious sequence variants is important and has wide implications for research and generation of new hypotheses in human and veterinary medicine, and drug discovery. The GenProBiS web server maps sequence variants to protein structures from the Protein Data Bank (PDB), and further to protein-protein, protein-nucleic acid, protein-compound, and protein-metal ion binding sites. The concept of a protein-compound binding site is understood in the broadest sense, which includes glycosylation and other post-translational modification sites. Binding sites were defined by local structural comparisons of whole protein structures using the Protein Binding Sites (ProBiS) algorithm and transposition of ligands from the similar binding sites found to the query protein using the ProBiS-ligands approach with new improvements introduced in GenProBiS. Binding site surfaces were generated as three-dimensional grids encompassing the space occupied by predicted ligands. The server allows intuitive visual exploration of comprehensively mapped variants, such as human somatic mis-sense mutations related to cancer and non-synonymous single nucleotide polymorphisms from 21 species, within the predicted binding sites regions for about 80 000 PDB protein structures using fast WebGL graphics. The GenProBiS web server is open and free to all users at http://genprobis.insilab.org. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
Simplifying complex sequence information: a PCP-consensus protein binds antibodies against all four Dengue serotypes.

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Bowen, David M; Lewis, Jessica A; Lu, Wenzhe; Schein, Catherine H

2012-09-14

Designing proteins that reflect the natural variability of a pathogen is essential for developing novel vaccines and drugs. Flaviviruses, including Dengue (DENV) and West Nile (WNV), evolve rapidly and can "escape" neutralizing monoclonal antibodies by mutation. Designing antigens that represent many distinct strains is important for DENV, where infection with a strain from one of the four serotypes may lead to severe hemorrhagic disease on subsequent infection with a strain from another serotype. Here, a DENV physicochemical property (PCP)-consensus sequence was derived from 671 unique sequences from the Flavitrack database. PCP-consensus proteins for domain 3 of the envelope protein (EdomIII) were expressed from synthetic genes in Escherichia coli. The ability of the purified consensus proteins to bind polyclonal antibodies generated in response to infection with strains from each of the four DENV serotypes was determined. The initial consensus protein bound antibodies from DENV-1-3 in ELISA and Western blot assays. This sequence was altered in 3 steps to incorporate regions of maximum variability, identified as significant changes in the PCPs, characteristic of DENV-4 strains. The final protein was recognized by antibodies against all four serotypes. Two amino acids essential for efficient binding to all DENV antibodies are part of a discontinuous epitope previously defined for a neutralizing monoclonal antibody. The PCP-consensus method can significantly reduce the number of experiments required to define a multivalent antigen, which is particularly important when dealing with pathogens that must be tested at higher biosafety levels. Copyright © 2012 Elsevier Ltd. All rights reserved.
A branch-heterogeneous model of protein evolution for efficient inference of ancestral sequences.

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Groussin, M; Boussau, B; Gouy, M

2013-07-01

Most models of nucleotide or amino acid substitution used in phylogenetic studies assume that the evolutionary process has been homogeneous across lineages and that composition of nucleotides or amino acids has remained the same throughout the tree. These oversimplified assumptions are refuted by the observation that compositional variability characterizes extant biological sequences. Branch-heterogeneous models of protein evolution that account for compositional variability have been developed, but are not yet in common use because of the large number of parameters required, leading to high computational costs and potential overparameterization. Here, we present a new branch-nonhomogeneous and nonstationary model of protein evolution that captures more accurately the high complexity of sequence evolution. This model, henceforth called Correspondence and likelihood analysis (COaLA), makes use of a correspondence analysis to reduce the number of parameters to be optimized through maximum likelihood, focusing on most of the compositional variation observed in the data. The model was thoroughly tested on both simulated and biological data sets to show its high performance in terms of data fitting and CPU time. COaLA efficiently estimates ancestral amino acid frequencies and sequences, making it relevant for studies aiming at reconstructing and resurrecting ancestral amino acid sequences. Finally, we applied COaLA on a concatenate of universal amino acid sequences to confirm previous results obtained with a nonhomogeneous Bayesian model regarding the early pattern of adaptation to optimal growth temperature, supporting the mesophilic nature of the Last Universal Common Ancestor.
UFO: a web server for ultra-fast functional profiling of whole genome protein sequences.

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Meinicke, Peter

2009-09-02

Functional profiling is a key technique to characterize and compare the functional potential of entire genomes. The estimation of profiles according to an assignment of sequences to functional categories is a computationally expensive task because it requires the comparison of all protein sequences from a genome with a usually large database of annotated sequences or sequence families. Based on machine learning techniques for Pfam domain detection, the UFO web server for ultra-fast functional profiling allows researchers to process large protein sequence collections instantaneously. Besides the frequencies of Pfam and GO categories, the user also obtains the sequence specific assignments to Pfam domain families. In addition, a comparison with existing genomes provides dissimilarity scores with respect to 821 reference proteomes. Considering the underlying UFO domain detection, the results on 206 test genomes indicate a high sensitivity of the approach. In comparison with current state-of-the-art HMMs, the runtime measurements show a considerable speed up in the range of four orders of magnitude. For an average size prokaryotic genome, the computation of a functional profile together with its comparison typically requires about 10 seconds of processing time. For the first time the UFO web server makes it possible to get a quick overview on the functional inventory of newly sequenced organisms. The genome scale comparison with a large number of precomputed profiles allows a first guess about functionally related organisms. The service is freely available and does not require user registration or specification of a valid email address.
UFO: a web server for ultra-fast functional profiling of whole genome protein sequences

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Meinicke Peter

2009-09-01

Full Text Available Abstract Background Functional profiling is a key technique to characterize and compare the functional potential of entire genomes. The estimation of profiles according to an assignment of sequences to functional categories is a computationally expensive task because it requires the comparison of all protein sequences from a genome with a usually large database of annotated sequences or sequence families. Description Based on machine learning techniques for Pfam domain detection, the UFO web server for ultra-fast functional profiling allows researchers to process large protein sequence collections instantaneously. Besides the frequencies of Pfam and GO categories, the user also obtains the sequence specific assignments to Pfam domain families. In addition, a comparison with existing genomes provides dissimilarity scores with respect to 821 reference proteomes. Considering the underlying UFO domain detection, the results on 206 test genomes indicate a high sensitivity of the approach. In comparison with current state-of-the-art HMMs, the runtime measurements show a considerable speed up in the range of four orders of magnitude. For an average size prokaryotic genome, the computation of a functional profile together with its comparison typically requires about 10 seconds of processing time. Conclusion For the first time the UFO web server makes it possible to get a quick overview on the functional inventory of newly sequenced organisms. The genome scale comparison with a large number of precomputed profiles allows a first guess about functionally related organisms. The service is freely available and does not require user registration or specification of a valid email address.
A kingdom-specific protein domain HMM library for improved annotation of fungal genomes

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Oliver Stephen G

2007-04-01

Full Text Available Abstract Background Pfam is a general-purpose database of protein domain alignments and profile Hidden Markov Models (HMMs, which is very popular for the annotation of sequence data produced by genome sequencing projects. Pfam provides models that are often very general in terms of the taxa that they cover and it has previously been suggested that such general models may lack some of the specificity or selectivity that would be provided by kingdom-specific models. Results Here we present a general approach to create domain libraries of HMMs for sub-taxa of a kingdom. Taking fungal species as an example, we construct a domain library of HMMs (called Fungal Pfam or FPfam using sequences from 30 genomes, consisting of 24 species from the ascomycetes group and two basidiomycetes, Ustilago maydis, a fungal pathogen of maize, and the white rot fungus Phanerochaete chrysosporium. In addition, we include the Microsporidion Encephalitozoon cuniculi, an obligate intracellular parasite, and two non-fungal species, the oomycetes Phytophthora sojae and Phytophthora ramorum, both plant pathogens. We evaluate the performance in terms of coverage against the original 30 genomes used in training FPfam and against five more recently sequenced fungal genomes that can be considered as an independent test set. We show that kingdom-specific models such as FPfam can find instances of both novel and well characterized domains, increases overall coverage and detects more domains per sequence with typically higher bitscores than Pfam for the same domain families. An evaluation of the effect of changing E-values on the coverage shows that the performance of FPfam is consistent over the range of E-values applied. Conclusion Kingdom-specific models are shown to provide improved coverage. However, as the models become more specific, some sequences found by Pfam may be missed by the models in FPfam and some of the families represented in the test set are not present in FPfam
Cluster based on sequence comparison of homologous proteins of 95 organism species - Gclust Server | LSDB Archive [Life Science Database Archive metadata

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Full Text Available List Contact us Gclust Server Cluster based on sequence comparison of homologous proteins of 95 organism spe...cies Data detail Data name Cluster based on sequence comparison of homologous proteins of 95 organism specie...istory of This Database Site Policy | Contact Us Cluster based on sequence compariso
Accessible surface area of proteins from purely sequence information and the importance of global features

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Faraggi, Eshel; Zhou, Yaoqi; Kloczkowski, Andrzej

2014-03-01

We present a new approach for predicting the accessible surface area of proteins. The novelty of this approach lies in not using residue mutation profiles generated by multiple sequence alignments as descriptive inputs. Rather, sequential window information and the global monomer and dimer compositions of the chain are used. We find that much of the lost accuracy due to the elimination of evolutionary information is recouped by the use of global features. Furthermore, this new predictor produces similar results for proteins with or without sequence homologs deposited in the Protein Data Bank, and hence shows generalizability. Finally, these predictions are obtained in a small fraction (1/1000) of the time required to run mutation profile based prediction. All these factors indicate the possible usability of this work in de-novo protein structure prediction and in de-novo protein design using iterative searches. Funded in part by the financial support of the National Institutes of Health through Grants R01GM072014 and R01GM073095, and the National Science Foundation through Grant NSF MCB 1071785.
The complete chloroplast genome sequence of Helwingia himalaica (Helwingiaceae, Aquifoliales) and a chloroplast phylogenomic analysis of the Campanulidae.

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Yao, Xin; Liu, Ying-Ying; Tan, Yun-Hong; Song, Yu; Corlett, Richard T

2016-01-01

Complete chloroplast genome sequences have been very useful for understanding phylogenetic relationships in angiosperms at the family level and above, but there are currently large gaps in coverage. We report the chloroplast genome for Helwingia himalaica , the first in the distinctive family Helwingiaceae and only the second genus to be sequenced in the order Aquifoliales. We then combine this with 36 published sequences in the large (c. 35,000 species) subclass Campanulidae in order to investigate relationships at the order and family levels. The Helwingia genome consists of 158,362 bp containing a pair of inverted repeat (IR) regions of 25,996 bp separated by a large single-copy (LSC) region and a small single-copy (SSC) region which are 87,810 and 18,560 bp, respectively. There are 142 known genes, including 94 protein-coding genes, eight ribosomal RNA genes, and 40 tRNA genes. The topology of the phylogenetic relationships between Apiales, Asterales, and Dipsacales differed between analyses based on complete genome sequences and on 36 shared protein-coding genes, showing that further studies of campanulid phylogeny are needed.
Complete amino acid sequences of the ribosomal proteins L25, L29 and L31 from the archaebacterium Halobacterium marismortui.

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Hatakeyama, T; Kimura, M

1988-03-15

Ribosomal proteins were extracted from 50S ribosomal subunits of the archaebacterium Halobacterium marismortui by decreasing the concentration of Mg2+ and K+, and the proteins were separated and purified by ion-exchange column chromatography on DEAE-cellulose. Ten proteins were purified to homogeneity and three of these proteins were subjected to sequence analysis. The complete amino acid sequences of the ribosomal proteins L25, L29 and L31 were established by analyses of the peptides obtained by enzymatic digestion with trypsin, Staphylococcus aureus protease, chymotrypsin and lysylendopeptidase. Proteins L25, L29 and L31 consist of 84, 115 and 95 amino acid residues with the molecular masses of 9472 Da, 12293 Da and 10418 Da respectively. A comparison of their sequences with those of other large-ribosomal-subunit proteins from other organisms revealed that protein L25 from H. marismortui is homologous to protein L23 from Escherichia coli (34.6%), Bacillus stearothermophilus (41.8%), and tobacco chloroplasts (16.3%) as well as to protein L25 from yeast (38.0%). Proteins L29 and L31 do not appear to be homologous to any other ribosomal proteins whose structures are so far known.
Direct comparisons of Illumina vs. Roche 454 sequencing technologies on the same microbial community DNA sample.

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Luo, Chengwei; Tsementzi, Despina; Kyrpides, Nikos; Read, Timothy; Konstantinidis, Konstantinos T

2012-01-01

Next-generation sequencing (NGS) is commonly used in metagenomic studies of complex microbial communities but whether or not different NGS platforms recover the same diversity from a sample and their assembled sequences are of comparable quality remain unclear. We compared the two most frequently used platforms, the Roche 454 FLX Titanium and the Illumina Genome Analyzer (GA) II, on the same DNA sample obtained from a complex freshwater planktonic community. Despite the substantial differences in read length and sequencing protocols, the platforms provided a comparable view of the community sampled. For instance, derived assemblies overlapped in ~90% of their total sequences and in situ abundances of genes and genotypes (estimated based on sequence coverage) correlated highly between the two platforms (R(2)>0.9). Evaluation of base-call error, frameshift frequency, and contig length suggested that Illumina offered equivalent, if not better, assemblies than Roche 454. The results from metagenomic samples were further validated against DNA samples of eighteen isolate genomes, which showed a range of genome sizes and G+C% content. We also provide quantitative estimates of the errors in gene and contig sequences assembled from datasets characterized by different levels of complexity and G+C% content. For instance, we noted that homopolymer-associated, single-base errors affected ~1% of the protein sequences recovered in Illumina contigs of 10× coverage and 50% G+C; this frequency increased to ~3% when non-homopolymer errors were also considered. Collectively, our results should serve as a useful practical guide for choosing proper sampling strategies and data possessing protocols for future metagenomic studies.
Length and sequence dependence in the association of Huntingtin protein with lipid membranes

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Jawahery, Sudi; Nagarajan, Anu; Matysiak, Silvina

2013-03-01

There is a fundamental gap in our understanding of how aggregates of mutant Huntingtin protein (htt) with overextended polyglutamine (polyQ) sequences gain the toxic properties that cause Huntington's disease (HD). Experimental studies have shown that the most important step associated with toxicity is the binding of mutant htt aggregates to lipid membranes. Studies have also shown that flanking amino acid sequences around the polyQ sequence directly affect interactions with the lipid bilayer, and that polyQ sequences of greater than 35 glutamine repeats in htt are a characteristic of HD. The key steps that determine how flanking sequences and polyQ length affect the structure of lipid bilayers remain unknown. In this study, we use atomistic molecular dynamics simulations to study the interactions between lipid membranes of varying compositions and polyQ peptides of varying lengths and flanking sequences. We find that overextended polyQ interactions do cause deformation in model membranes, and that the flanking sequences do play a role in intensifying this deformation by altering the shape of the affected regions.
DomPep--a general method for predicting modular domain-mediated protein-protein interactions.

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Lei Li

Full Text Available Protein-protein interactions (PPIs are frequently mediated by the binding of a modular domain in one protein to a short, linear peptide motif in its partner. The advent of proteomic methods such as peptide and protein arrays has led to the accumulation of a wealth of interaction data for modular interaction domains. Although several computational programs have been developed to predict modular domain-mediated PPI events, they are often restricted to a given domain type. We describe DomPep, a method that can potentially be used to predict PPIs mediated by any modular domains. DomPep combines proteomic data with sequence information to achieve high accuracy and high coverage in PPI prediction. Proteomic binding data were employed to determine a simple yet novel parameter Ligand-Binding Similarity which, in turn, is used to calibrate Domain Sequence Identity and Position-Weighted-Matrix distance, two parameters that are used in constructing prediction models. Moreover, DomPep can be used to predict PPIs for both domains with experimental binding data and those without. Using the PDZ and SH2 domain families as test cases, we show that DomPep can predict PPIs with accuracies superior to existing methods. To evaluate DomPep as a discovery tool, we deployed DomPep to identify interactions mediated by three human PDZ domains. Subsequent in-solution binding assays validated the high accuracy of DomPep in predicting authentic PPIs at the proteome scale. Because DomPep makes use of only interaction data and the primary sequence of a domain, it can be readily expanded to include other types of modular domains.
Comparative In silico Study of Sex-Determining Region Y (SRY Protein Sequences Involved in Sex-Determining

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Masoume Vakili Azghandi

2016-05-01

Full Text Available Background: The SRY gene (SRY provides instructions for making a transcription factor called the sex-determining region Y protein. The sex-determining region Y protein causes a fetus to develop as a male. In this study, SRY of 15 spices included of human, chimpanzee, dog, pig, rat, cattle, buffalo, goat, sheep, horse, zebra, frog, urial, dolphin and killer whale were used for determine of bioinformatic differences. Methods: Nucleotide sequences of SRY were retrieved from the NCBI databank. Bioinformatic analysis of SRY is done by CLC Main Workbench version 5.5 and ClustalW (http:/www.ebi.ac.uk/clustalw/ and MEGA6 softwares. Results: The multiple sequence alignment results indicated that SRY protein sequences from Orcinus orca (killer whale and Tursiopsaduncus (dolphin have least genetic distance of 0.33 in these 15 species and are 99.67% identical at the amino acid level. Homosapiens and Pantroglodytes (chimpanzee have the next lowest genetic distance of 1.35 and are 98.65% identical at the amino acid level. Conclusion: These findings indicate that the SRY proteins are conserved in the 15 species, and their evolutionary relationships are similar.
Transposon fingerprinting using low coverage whole genome shotgun sequencing in cacao (Theobroma cacao L.) and related species.

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Sveinsson, Saemundur; Gill, Navdeep; Kane, Nolan C; Cronk, Quentin

2013-07-24

Transposable elements (TEs) and other repetitive elements are a large and dynamically evolving part of eukaryotic genomes, especially in plants where they can account for a significant proportion of genome size. Their dynamic nature gives them the potential for use in identifying and characterizing crop germplasm. However, their repetitive nature makes them challenging to study using conventional methods of molecular biology. Next generation sequencing and new computational tools have greatly facilitated the investigation of TE variation within species and among closely related species. (i) We generated low-coverage Illumina whole genome shotgun sequencing reads for multiple individuals of cacao (Theobroma cacao) and related species. These reads were analysed using both an alignment/mapping approach and a de novo (graph based clustering) approach. (ii) A standard set of ultra-conserved orthologous sequences (UCOS) standardized TE data between samples and provided phylogenetic information on the relatedness of samples. (iii) The mapping approach proved highly effective within the reference species but underestimated TE abundance in interspecific comparisons relative to the de novo methods. (iv) Individual T. cacao accessions have unique patterns of TE abundance indicating that the TE composition of the genome is evolving actively within this species. (v) LTR/Gypsy elements are the most abundant, comprising c.10% of the genome. (vi) Within T. cacao the retroelement families show an order of magnitude greater sequence variability than the DNA transposon families. (vii) Theobroma grandiflorum has a similar TE composition to T. cacao, but the related genus Herrania is rather different, with LTRs making up a lower proportion of the genome, perhaps because of a massive presence (c. 20%) of distinctive low complexity satellite-like repeats in this genome. (i) Short read alignment/mapping to reference TE contigs provides a simple and effective method of investigating
Two low coverage bird genomes and a comparison of reference-guided versus de novo genome assemblies.

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Card, Daren C; Schield, Drew R; Reyes-Velasco, Jacobo; Fujita, Matthew K; Andrew, Audra L; Oyler-McCance, Sara J; Fike, Jennifer A; Tomback, Diana F; Ruggiero, Robert P; Castoe, Todd A

2014-01-01

As a greater number and diversity of high-quality vertebrate reference genomes become available, it is increasingly feasible to use these references to guide new draft assemblies for related species. Reference-guided assembly approaches may substantially increase the contiguity and completeness of a new genome using only low levels of genome coverage that might otherwise be insufficient for de novo genome assembly. We used low-coverage (∼3.5-5.5x) Illumina paired-end sequencing to assemble draft genomes of two bird species (the Gunnison Sage-Grouse, Centrocercus minimus, and the Clark's Nutcracker, Nucifraga columbiana). We used these data to estimate de novo genome assemblies and reference-guided assemblies, and compared the information content and completeness of these assemblies by comparing CEGMA gene set representation, repeat element content, simple sequence repeat content, and GC isochore structure among assemblies. Our results demonstrate that even lower-coverage genome sequencing projects are capable of producing informative and useful genomic resources, particularly through the use of reference-guided assemblies.
Two low coverage bird genomes and a comparison of reference-guided versus de novo genome assemblies

Science.gov (United States)

Card, Daren C.; Schield, Drew R.; Reyes-Velasco, Jacobo; Fujita, Matthre K.; Andrew, Audra L.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Tomback, Diana F.; Ruggiero, Robert P.; Castoe, Todd A.

2014-01-01

As a greater number and diversity of high-quality vertebrate reference genomes become available, it is increasingly feasible to use these references to guide new draft assemblies for related species. Reference-guided assembly approaches may substantially increase the contiguity and completeness of a new genome using only low levels of genome coverage that might otherwise be insufficient for de novo genome assembly. We used low-coverage (~3.5–5.5x) Illumina paired-end sequencing to assemble draft genomes of two bird species (the Gunnison Sage-Grouse, Centrocercus minimus, and the Clark's Nutcracker, Nucifraga columbiana). We used these data to estimate de novo genome assemblies and reference-guided assemblies, and compared the information content and completeness of these assemblies by comparing CEGMA gene set representation, repeat element content, simple sequence repeat content, and GC isochore structure among assemblies. Our results demonstrate that even lower-coverage genome sequencing projects are capable of producing informative and useful genomic resources, particularly through the use of reference-guided assemblies.

C-terminal sequences of hsp70 and hsp90 as non-specific anchors for tetratricopeptide repeat (TPR) proteins.

Science.gov (United States)

Ramsey, Andrew J; Russell, Lance C; Chinkers, Michael

2009-10-12

Steroid-hormone-receptor maturation is a multi-step process that involves several TPR (tetratricopeptide repeat) proteins that bind to the maturation complex via the C-termini of hsp70 (heat-shock protein 70) and hsp90 (heat-shock protein 90). We produced a random T7 peptide library to investigate the roles played by the C-termini of the two heat-shock proteins in the TPR-hsp interactions. Surprisingly, phages with the MEEVD sequence, found at the C-terminus of hsp90, were not recovered from our biopanning experiments. However, two groups of phages were isolated that bound relatively tightly to HsPP5 (Homo sapiens protein phosphatase 5) TPR. Multiple copies of phages with a C-terminal sequence of LFG were isolated. These phages bound specifically to the TPR domain of HsPP5, although mutation studies produced no evidence that they bound to the domain's hsp90-binding groove. However, the most abundant family obtained in the initial screen had an aspartate residue at the C-terminus. Two members of this family with a C-terminal sequence of VD appeared to bind with approximately the same affinity as the hsp90 C-12 control. A second generation pseudo-random phage library produced a large number of phages with an LD C-terminus. These sequences acted as hsp70 analogues and had relatively low affinities for hsp90-specific TPR domains. Unfortunately, we failed to identify residues near hsp90's C-terminus that impart binding specificity to individual hsp90-TPR interactions. The results suggest that the C-terminal sequences of hsp70 and hsp90 act primarily as non-specific anchors for TPR proteins.
A two-step recognition of signal sequences determines the translocation efficiency of proteins.

OpenAIRE

Belin, D; Bost, S; Vassalli, J D; Strub, K

1996-01-01

The cytosolic and secreted, N-glycosylated, forms of plasminogen activator inhibitor-2 (PAI-2) are generated by facultative translocation. To study the molecular events that result in the bi-topological distribution of proteins, we determined in vitro the capacities of several signal sequences to bind the signal recognition particle (SRP) during targeting, and to promote vectorial transport of murine PAI-2 (mPAI-2). Interestingly, the six signal sequences we compared (mPAI-2 and three mutated...
Hidden Markov model-derived structural alphabet for proteins: the learning of protein local shapes captures sequence specificity.

Science.gov (United States)

Camproux, A C; Tufféry, P

2005-08-05

Understanding and predicting protein structures depend on the complexity and the accuracy of the models used to represent them. We have recently set up a Hidden Markov Model to optimally compress protein three-dimensional conformations into a one-dimensional series of letters of a structural alphabet. Such a model learns simultaneously the shape of representative structural letters describing the local conformation and the logic of their connections, i.e. the transition matrix between the letters. Here, we move one step further and report some evidence that such a model of protein local architecture also captures some accurate amino acid features. All the letters have specific and distinct amino acid distributions. Moreover, we show that words of amino acids can have significant propensities for some letters. Perspectives point towards the prediction of the series of letters describing the structure of a protein from its amino acid sequence.
The two capsid proteins of maize rayado fino virus contain common peptide sequences.

Science.gov (United States)

Falk, B W; Tsai, J H

1986-01-01

Virions of maize rayado fino virus (MRFV) were purified and two major capsid proteins (ca. Mr 29,000 and 22,000) were resolved by SDS-PAGE. When the two major capsid proteins were isolated from gels and compared by one-dimensional peptide mapping after digestion with Staphylococcus aureus V-8 protease, indistinguishable peptide maps were obtained, suggesting that these two proteins contain common peptide sequences. Some preparations also showed minor protein components that were intermediate between the Mr 22,000 and Mr 29,000 capsid proteins. One of the minor proteins, ca. Mr 27,000, gave a peptide map indistinguishable from the major capsid proteins. In vitro ageing of partially purified preparations or virion treatment with proteolytic enzymes failed to show conversion of the Mr 29,000 protein to a Mr 22,000. Protease inhibitors added to the buffers used for virion purification did not affect the apparent 1:3 ratio of 29,000 to 22,000 proteins in the purified preparations.
Recombinant Protein Truncation Strategy for Inducing Bactericidal Antibodies to the Macrophage Infectivity Potentiator Protein of Neisseria meningitidis and Circumventing Potential Cross-Reactivity with Human FK506-Binding Proteins

Science.gov (United States)

Bielecka, Magdalena K.; Devos, Nathalie; Gilbert, Mélanie; Hung, Miao-Chiu; Weynants, Vincent; Heckels, John E.

2014-01-01

A recombinant macrophage infectivity potentiator (rMIP) protein of Neisseria meningitidis induces significant serum bactericidal antibody production in mice and is a candidate meningococcal vaccine antigen. However, bioinformatics analysis of MIP showed some amino acid sequence similarity to human FK506-binding proteins (FKBPs) in residues 166 to 252 located in the globular domain of the protein. To circumvent the potential concern over generating antibodies that could recognize human proteins, we immunized mice with recombinant truncated type I rMIP proteins that lacked the globular domain and the signal leader peptide (LP) signal sequence (amino acids 1 to 22) and contained the His purification tag at either the N or C terminus (C-term). The immunogenicity of truncated rMIP proteins was compared to that of full (i.e., full-length) rMIP proteins (containing the globular domain) with either an N- or C-terminal His tag and with or without the LP sequence. By comparing the functional murine antibody responses to these various constructs, we determined that C-term His truncated rMIP (−LP) delivered in liposomes induced high levels of antibodies that bound to the surface of wild-type but not Δmip mutant meningococci and showed bactericidal activity against homologous type I MIP (median titers of 128 to 256) and heterologous type II and III (median titers of 256 to 512) strains, thereby providing at least 82% serogroup B strain coverage. In contrast, in constructs lacking the LP, placement of the His tag at the N terminus appeared to abrogate bactericidal activity. The strategy used in this study would obviate any potential concerns regarding the use of MIP antigens for inclusion in bacterial vaccines. PMID:25452551
Recombinant protein truncation strategy for inducing bactericidal antibodies to the macrophage infectivity potentiator protein of Neisseria meningitidis and circumventing potential cross-reactivity with human FK506-binding proteins.

Science.gov (United States)

Bielecka, Magdalena K; Devos, Nathalie; Gilbert, Mélanie; Hung, Miao-Chiu; Weynants, Vincent; Heckels, John E; Christodoulides, Myron

2015-02-01

A recombinant macrophage infectivity potentiator (rMIP) protein of Neisseria meningitidis induces significant serum bactericidal antibody production in mice and is a candidate meningococcal vaccine antigen. However, bioinformatics analysis of MIP showed some amino acid sequence similarity to human FK506-binding proteins (FKBPs) in residues 166 to 252 located in the globular domain of the protein. To circumvent the potential concern over generating antibodies that could recognize human proteins, we immunized mice with recombinant truncated type I rMIP proteins that lacked the globular domain and the signal leader peptide (LP) signal sequence (amino acids 1 to 22) and contained the His purification tag at either the N or C terminus (C-term). The immunogenicity of truncated rMIP proteins was compared to that of full (i.e., full-length) rMIP proteins (containing the globular domain) with either an N- or C-terminal His tag and with or without the LP sequence. By comparing the functional murine antibody responses to these various constructs, we determined that C-term His truncated rMIP (-LP) delivered in liposomes induced high levels of antibodies that bound to the surface of wild-type but not Δmip mutant meningococci and showed bactericidal activity against homologous type I MIP (median titers of 128 to 256) and heterologous type II and III (median titers of 256 to 512) strains, thereby providing at least 82% serogroup B strain coverage. In contrast, in constructs lacking the LP, placement of the His tag at the N terminus appeared to abrogate bactericidal activity. The strategy used in this study would obviate any potential concerns regarding the use of MIP antigens for inclusion in bacterial vaccines. Copyright © 2015, American Society for Microbiology. All Rights Reserved.
Highly multiplexed targeted DNA sequencing from single nuclei.

Science.gov (United States)

Leung, Marco L; Wang, Yong; Kim, Charissa; Gao, Ruli; Jiang, Jerry; Sei, Emi; Navin, Nicholas E

2016-02-01

Single-cell DNA sequencing methods are challenged by poor physical coverage, high technical error rates and low throughput. To address these issues, we developed a single-cell DNA sequencing protocol that combines flow-sorting of single nuclei, time-limited multiple-displacement amplification (MDA), low-input library preparation, DNA barcoding, targeted capture and next-generation sequencing (NGS). This approach represents a major improvement over our previous single nucleus sequencing (SNS) Nature Protocols paper in terms of generating higher-coverage data (>90%), thereby enabling the detection of genome-wide variants in single mammalian cells at base-pair resolution. Furthermore, by pooling 48-96 single-cell libraries together for targeted capture, this approach can be used to sequence many single-cell libraries in parallel in a single reaction. This protocol greatly reduces the cost of single-cell DNA sequencing, and it can be completed in 5-6 d by advanced users. This single-cell DNA sequencing protocol has broad applications for studying rare cells and complex populations in diverse fields of biological research and medicine.
Prediction of host - pathogen protein interactions between Mycobacterium tuberculosis and Homo sapiens using sequence motifs.

Science.gov (United States)

Huo, Tong; Liu, Wei; Guo, Yu; Yang, Cheng; Lin, Jianping; Rao, Zihe

2015-03-26

Emergence of multiple drug resistant strains of M. tuberculosis (MDR-TB) threatens to derail global efforts aimed at reigning in the pathogen. Co-infections of M. tuberculosis with HIV are difficult to treat. To counter these new challenges, it is essential to study the interactions between M. tuberculosis and the host to learn how these bacteria cause disease. We report a systematic flow to predict the host pathogen interactions (HPIs) between M. tuberculosis and Homo sapiens based on sequence motifs. First, protein sequences were used as initial input for identifying the HPIs by 'interolog' method. HPIs were further filtered by prediction of domain-domain interactions (DDIs). Functional annotations of protein and publicly available experimental results were applied to filter the remaining HPIs. Using such a strategy, 118 pairs of HPIs were identified, which involve 43 proteins from M. tuberculosis and 48 proteins from Homo sapiens. A biological interaction network between M. tuberculosis and Homo sapiens was then constructed using the predicted inter- and intra-species interactions based on the 118 pairs of HPIs. Finally, a web accessible database named PATH (Protein interactions of M. tuberculosis and Human) was constructed to store these predicted interactions and proteins. This interaction network will facilitate the research on host-pathogen protein-protein interactions, and may throw light on how M. tuberculosis interacts with its host.
Structural protein descriptors in 1-dimension and their sequence-based predictions.

Science.gov (United States)

Kurgan, Lukasz; Disfani, Fatemeh Miri

2011-09-01

The last few decades observed an increasing interest in development and application of 1-dimensional (1D) descriptors of protein structure. These descriptors project 3D structural features onto 1D strings of residue-wise structural assignments. They cover a wide-range of structural aspects including conformation of the backbone, burying depth/solvent exposure and flexibility of residues, and inter-chain residue-residue contacts. We perform first-of-its-kind comprehensive comparative review of the existing 1D structural descriptors. We define, review and categorize ten structural descriptors and we also describe, summarize and contrast over eighty computational models that are used to predict these descriptors from the protein sequences. We show that the majority of the recent sequence-based predictors utilize machine learning models, with the most popular being neural networks, support vector machines, hidden Markov models, and support vector and linear regressions. These methods provide high-throughput predictions and most of them are accessible to a non-expert user via web servers and/or stand-alone software packages. We empirically evaluate several recent sequence-based predictors of secondary structure, disorder, and solvent accessibility descriptors using a benchmark set based on CASP8 targets. Our analysis shows that the secondary structure can be predicted with over 80% accuracy and segment overlap (SOV), disorder with over 0.9 AUC, 0.6 Matthews Correlation Coefficient (MCC), and 75% SOV, and relative solvent accessibility with PCC of 0.7 and MCC of 0.6 (0.86 when homology is used). We demonstrate that the secondary structure predicted from sequence without the use of homology modeling is as good as the structure extracted from the 3D folds predicted by top-performing template-based methods.
High-Throughput Next-Generation Sequencing of Polioviruses

Science.gov (United States)

Montmayeur, Anna M.; Schmidt, Alexander; Zhao, Kun; Magaña, Laura; Iber, Jane; Castro, Christina J.; Chen, Qi; Henderson, Elizabeth; Ramos, Edward; Shaw, Jing; Tatusov, Roman L.; Dybdahl-Sissoko, Naomi; Endegue-Zanga, Marie Claire; Adeniji, Johnson A.; Oberste, M. Steven; Burns, Cara C.

2016-01-01

ABSTRACT The poliovirus (PV) is currently targeted for worldwide eradication and containment. Sanger-based sequencing of the viral protein 1 (VP1) capsid region is currently the standard method for PV surveillance. However, the whole-genome sequence is sometimes needed for higher resolution global surveillance. In this study, we optimized whole-genome sequencing protocols for poliovirus isolates and FTA cards using next-generation sequencing (NGS), aiming for high sequence coverage, efficiency, and throughput. We found that DNase treatment of poliovirus RNA followed by random reverse transcription (RT), amplification, and the use of the Nextera XT DNA library preparation kit produced significantly better results than other preparations. The average viral reads per total reads, a measurement of efficiency, was as high as 84.2% ± 15.6%. PV genomes covering >99 to 100% of the reference length were obtained and validated with Sanger sequencing. A total of 52 PV genomes were generated, multiplexing as many as 64 samples in a single Illumina MiSeq run. This high-throughput, sequence-independent NGS approach facilitated the detection of a diverse range of PVs, especially for those in vaccine-derived polioviruses (VDPV), circulating VDPV, or immunodeficiency-related VDPV. In contrast to results from previous studies on other viruses, our results showed that filtration and nuclease treatment did not discernibly increase the sequencing efficiency of PV isolates. However, DNase treatment after nucleic acid extraction to remove host DNA significantly improved the sequencing results. This NGS method has been successfully implemented to generate PV genomes for molecular epidemiology of the most recent PV isolates. Additionally, the ability to obtain full PV genomes from FTA cards will aid in facilitating global poliovirus surveillance. PMID:27927929
Using structural knowledge in the protein data bank to inform the search for potential host-microbe protein interactions in sequence space: application to Mycobacterium tuberculosis.

Science.gov (United States)

Mahajan, Gaurang; Mande, Shekhar C

2017-04-04

A comprehensive map of the human-M. tuberculosis (MTB) protein interactome would help fill the gaps in our understanding of the disease, and computational prediction can aid and complement experimental studies towards this end. Several sequence-based in silico approaches tap the existing data on experimentally validated protein-protein interactions (PPIs); these PPIs serve as templates from which novel interactions between pathogen and host are inferred. Such comparative approaches typically make use of local sequence alignment, which, in the absence of structural details about the interfaces mediating the template interactions, could lead to incorrect inferences, particularly when multi-domain proteins are involved. We propose leveraging the domain-domain interaction (DDI) information in PDB complexes to score and prioritize candidate PPIs between host and pathogen proteomes based on targeted sequence-level comparisons. Our method picks out a small set of human-MTB protein pairs as candidates for physical interactions, and the use of functional meta-data suggests that some of them could contribute to the in vivo molecular cross-talk between pathogen and host that regulates the course of the infection. Further, we present numerical data for Pfam domain families that highlights interaction specificity on the domain level. Not every instance of a pair of domains, for which interaction evidence has been found in a few instances (i.e. structures), is likely to functionally interact. Our sorting approach scores candidates according to how "distant" they are in sequence space from known examples of DDIs (templates). Thus, it provides a natural way to deal with the heterogeneity in domain-level interactions. Our method represents a more informed application of local alignment to the sequence-based search for potential human-microbial interactions that uses available PPI data as a prior. Our approach is somewhat limited in its sensitivity by the restricted size and
Insights into Protein Sequence and Structure-Derived Features Mediating 3D Domain Swapping Mechanism using Support Vector Machine Based Approach

Directory of Open Access Journals (Sweden)

Khader Shameer

2010-06-01

Full Text Available 3-dimensional domain swapping is a mechanism where two or more protein molecules form higher order oligomers by exchanging identical or similar subunits. Recently, this phenomenon has received much attention in the context of prions and neuro-degenerative diseases, due to its role in the functional regulation, formation of higher oligomers, protein misfolding, aggregation etc. While 3-dimensional domain swap mechanism can be detected from three-dimensional structures, it remains a formidable challenge to derive common sequence or structural patterns from proteins involved in swapping. We have developed a SVM-based classifier to predict domain swapping events using a set of features derived from sequence and structural data. The SVM classifier was trained on features derived from 150 proteins reported to be involved in 3D domain swapping and 150 proteins not known to be involved in swapped conformation or related to proteins involved in swapping phenomenon. The testing was performed using 63 proteins from the positive dataset and 63 proteins from the negative dataset. We obtained 76.33% accuracy from training and 73.81% accuracy from testing. Due to high diversity in the sequence, structure and functions of proteins involved in domain swapping, availability of such an algorithm to predict swapping events from sequence and structure-derived features will be an initial step towards identification of more putative proteins that may be involved in swapping or proteins involved in deposition disease. Further, the top features emerging in our feature selection method may be analysed further to understand their roles in the mechanism of domain swapping.
RCK: accurate and efficient inference of sequence- and structure-based protein-RNA binding models from RNAcompete data.

Science.gov (United States)

Orenstein, Yaron; Wang, Yuhao; Berger, Bonnie

2016-06-15

Protein-RNA interactions, which play vital roles in many processes, are mediated through both RNA sequence and structure. CLIP-based methods, which measure protein-RNA binding in vivo, suffer from experimental noise and systematic biases, whereas in vitro experiments capture a clearer signal of protein RNA-binding. Among them, RNAcompete provides binding affinities of a specific protein to more than 240 000 unstructured RNA probes in one experiment. The computational challenge is to infer RNA structure- and sequence-based binding models from these data. The state-of-the-art in sequence models, Deepbind, does not model structural preferences. RNAcontext models both sequence and structure preferences, but is outperformed by GraphProt. Unfortunately, GraphProt cannot detect structural preferences from RNAcompete data due to the unstructured nature of the data, as noted by its developers, nor can it be tractably run on the full RNACompete dataset. We develop RCK, an efficient, scalable algorithm that infers both sequence and structure preferences based on a new k-mer based model. Remarkably, even though RNAcompete data is designed to be unstructured, RCK can still learn structural preferences from it. RCK significantly outperforms both RNAcontext and Deepbind in in vitro binding prediction for 244 RNAcompete experiments. Moreover, RCK is also faster and uses less memory, which enables scalability. While currently on par with existing methods in in vivo binding prediction on a small scale test, we demonstrate that RCK will increasingly benefit from experimentally measured RNA structure profiles as compared to computationally predicted ones. By running RCK on the entire RNAcompete dataset, we generate and provide as a resource a set of protein-RNA structure-based models on an unprecedented scale. Software and models are freely available at http://rck.csail.mit.edu/ bab@mit.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by
Creation and structure determination of an artificial protein with three complete sequence repeats

Energy Technology Data Exchange (ETDEWEB)

Adachi, Motoyasu, E-mail: adachi.motoyasu@jaea.go.jp; Shimizu, Rumi; Kuroki, Ryota [Japan Atomic Energy Agency, Shirakatashirane 2-4, Nakagun Tokaimura, Ibaraki 319-1195 (Japan); Blaber, Michael [Japan Atomic Energy Agency, Shirakatashirane 2-4, Nakagun Tokaimura, Ibaraki 319-1195 (Japan); Florida State University, Tallahassee, FL 32306-4300 (United States)

2013-11-01

An artificial protein with three complete sequence repeats was created and the structure was determined by X-ray crystallography. The structure showed threefold symmetry even though there is an amino- and carboxy-terminal. The artificial protein with threefold symmetry may be useful as a scaffold to capture small materials with C3 symmetry. Symfoil-4P is a de novo protein exhibiting the threefold symmetrical β-trefoil fold designed based on the human acidic fibroblast growth factor. First three asparagine–glycine sequences of Symfoil-4P are replaced with glutamine–glycine (Symfoil-QG) or serine–glycine (Symfoil-SG) sequences protecting from deamidation, and His-Symfoil-II was prepared by introducing a protease digestion site into Symfoil-QG so that Symfoil-II has three complete repeats after removal of the N-terminal histidine tag. The Symfoil-QG and SG and His-Symfoil-II proteins were expressed in Eschericha coli as soluble protein, and purified by nickel affinity chromatography. Symfoil-II was further purified by anion-exchange chromatography after removing the HisTag by proteolysis. Both Symfoil-QG and Symfoil-II were crystallized in 0.1 M Tris-HCl buffer (pH 7.0) containing 1.8 M ammonium sulfate as precipitant at 293 K; several crystal forms were observed for Symfoil-QG and II. The maximum diffraction of Symfoil-QG and II crystals were 1.5 and 1.1 Å resolution, respectively. The Symfoil-II without histidine tag diffracted better than Symfoil-QG with N-terminal histidine tag. Although the crystal packing of Symfoil-II is slightly different from Symfoil-QG and other crystals of Symfoil derivatives having the N-terminal histidine tag, the refined crystal structure of Symfoil-II showed pseudo-threefold symmetry as expected from other Symfoils. Since the removal of the unstructured N-terminal histidine tag did not affect the threefold structure of Symfoil, the improvement of diffraction quality of Symfoil-II may be caused by molecular characteristics of
Large scale identification and categorization of protein sequences using structured logistic regression

DEFF Research Database (Denmark)

Pedersen, Bjørn Panella; Ifrim, Georgiana; Liboriussen, Poul

2014-01-01

Abstract Background Structured Logistic Regression (SLR) is a newly developed machine learning tool first proposed in the context of text categorization. Current availability of extensive protein sequence databases calls for an automated method to reliably classify sequences and SLR seems well...... problem. Results Using SLR, we have built classifiers to identify and automatically categorize P-type ATPases into one of 11 pre-defined classes. The SLR-classifiers are compared to a Hidden Markov Model approach and shown to be highly accurate and scalable. Representing the bulk of currently known...... for further biochemical characterization and structural analysis....
Nucleotide sequence of the coat protein gene of the Skierniewice isolate of plum pox virus (PPV)

International Nuclear Information System (INIS)

Wypijewski, K.; Musial, W.; Augustyniak, J.; Malinowski, T.

1994-01-01

The coat protein (CP) gene of the Skierniewice isolate of plum pox virus (PPV-S) has been amplified using the reverse transcription - polymerase chain reaction (RT-PCR), cloned and sequenced. The nucleotide sequence of the gene and the deduced amino-acid sequences of PPV-S CP were compared with those of other PPV strains. The nucleotide sequence showed very high homology to most of the published sequences. The motif: Asp-Ala-Gly (DAG), important for the aphid transmissibility, was present in the amino-acid sequence. Our isolate did not react in ELISA with monoclonal antibodies MAb06 supposed to be specific for PPV-D. (author). 32 refs, 1 fig., 2 tabs
Protein-Protein Interactions Prediction Using a Novel Local Conjoint Triad Descriptor of Amino Acid Sequences

Directory of Open Access Journals (Sweden)

Jun Wang

2017-11-01

Full Text Available Protein-protein interactions (PPIs play crucial roles in almost all cellular processes. Although a large amount of PPIs have been verified by high-throughput techniques in the past decades, currently known PPIs pairs are still far from complete. Furthermore, the wet-lab experiments based techniques for detecting PPIs are time-consuming and expensive. Hence, it is urgent and essential to develop automatic computational methods to efficiently and accurately predict PPIs. In this paper, a sequence-based approach called DNN-LCTD is developed by combining deep neural networks (DNNs and a novel local conjoint triad description (LCTD feature representation. LCTD incorporates the advantage of local description and conjoint triad, thus, it is capable to account for the interactions between residues in both continuous and discontinuous regions of amino acid sequences. DNNs can not only learn suitable features from the data by themselves, but also learn and discover hierarchical representations of data. When performing on the PPIs data of Saccharomyces cerevisiae, DNN-LCTD achieves superior performance with accuracy as 93.12%, precision as 93.75%, sensitivity as 93.83%, area under the receiver operating characteristic curve (AUC as 97.92%, and it only needs 718 s. These results indicate DNN-LCTD is very promising for predicting PPIs. DNN-LCTD can be a useful supplementary tool for future proteomics study.
PuLSE: Quality control and quantification of peptide sequences explored by phage display libraries.

Science.gov (United States)

Shave, Steven; Mann, Stefan; Koszela, Joanna; Kerr, Alastair; Auer, Manfred

2018-01-01

The design of highly diverse phage display libraries is based on assumption that DNA bases are incorporated at similar rates within the randomized sequence. As library complexity increases and expected copy numbers of unique sequences decrease, the exploration of library space becomes sparser and the presence of truly random sequences becomes critical. We present the program PuLSE (Phage Library Sequence Evaluation) as a tool for assessing randomness and therefore diversity of phage display libraries. PuLSE runs on a collection of sequence reads in the fastq file format and generates tables profiling the library in terms of unique DNA sequence counts and positions, translated peptide sequences, and normalized 'expected' occurrences from base to residue codon frequencies. The output allows at-a-glance quantitative quality control of a phage library in terms of sequence coverage both at the DNA base and translated protein residue level, which has been missing from toolsets and literature. The open source program PuLSE is available in two formats, a C++ source code package for compilation and integration into existing bioinformatics pipelines and precompiled binaries for ease of use.
Sequence analysis of the L protein of the Ebola 2014 outbreak: Insight into conserved regions and mutations.

Science.gov (United States)

Ayub, Gohar; Waheed, Yasir

2016-06-01

The 2014 Ebola outbreak was one of the largest that have occurred; it started in Guinea and spread to Nigeria, Liberia and Sierra Leone. Phylogenetic analysis of the current virus species indicated that this outbreak is the result of a divergent lineage of the Zaire ebolavirus. The L protein of Ebola virus (EBOV) is the catalytic subunit of the RNA‑dependent RNA polymerase complex, which, with VP35, is key for the replication and transcription of viral RNA. Earlier sequence analysis demonstrated that the L protein of all non‑segmented negative‑sense (NNS) RNA viruses consists of six domains containing conserved functional motifs. The aim of the present study was to analyze the presence of these motifs in 2014 EBOV isolates, highlight their function and how they may contribute to the overall pathogenicity of the isolates. For this purpose, 81 2014 EBOV L protein sequences were aligned with 475 other NNS RNA viruses, including Paramyxoviridae and Rhabdoviridae viruses. Phylogenetic analysis of all EBOV outbreak L protein sequences was also performed. Analysis of the amino acid substitutions in the 2014 EBOV outbreak was conducted using sequence analysis. The alignment demonstrated the presence of previously conserved motifs in the 2014 EBOV isolates and novel residues. Notably, all the mutations identified in the 2014 EBOV isolates were tolerant, they were pathogenic with certain examples occurring within previously determined functional conserved motifs, possibly altering viral pathogenicity, replication and virulence. The phylogenetic analysis demonstrated that all sequences with the exception of the 2014 EBOV sequences were clustered together. The 2014 EBOV outbreak has acquired a great number of mutations, which may explain the reasons behind this unprecedented outbreak. Certain residues critical to the function of the polymerase remain conserved and may be targets for the development of antiviral therapeutic agents.
Hydrophobic cluster analysis of G protein-coupled receptors: a powerful tool to derive structural and functional information from 2D-representation of protein sequences

NARCIS (Netherlands)

Lentes, K.U.; Mathieu, E.; Bischoff, Rainer; Rasmussen, U.B.; Pavirani, A.

1993-01-01

Current methods for comparative analyses of protein sequences are 1D-alignments of amino acid sequences based on the maximization of amino acid identity (homology) and the prediction of secondary structure elements. This method has a major drawback once the amino acid identity drops below 20-25%,

Deep whole-genome sequencing of 90 Han Chinese genomes.

Science.gov (United States)

Lan, Tianming; Lin, Haoxiang; Zhu, Wenjuan; Laurent, Tellier Christian Asker Melchior; Yang, Mengcheng; Liu, Xin; Wang, Jun; Wang, Jian; Yang, Huanming; Xu, Xun; Guo, Xiaosen

2017-09-01

Next-generation sequencing provides a high-resolution insight into human genetic information. However, the focus of previous studies has primarily been on low-coverage data due to the high cost of sequencing. Although the 1000 Genomes Project and the Haplotype Reference Consortium have both provided powerful reference panels for imputation, low-frequency and novel variants remain difficult to discover and call with accuracy on the basis of low-coverage data. Deep sequencing provides an optimal solution for the problem of these low-frequency and novel variants. Although whole-exome sequencing is also a viable choice for exome regions, it cannot account for noncoding regions, sometimes resulting in the absence of important, causal variants. For Han Chinese populations, the majority of variants have been discovered based upon low-coverage data from the 1000 Genomes Project. However, high-coverage, whole-genome sequencing data are limited for any population, and a large amount of low-frequency, population-specific variants remain uncharacterized. We have performed whole-genome sequencing at a high depth (∼×80) of 90 unrelated individuals of Chinese ancestry, collected from the 1000 Genomes Project samples, including 45 Northern Han Chinese and 45 Southern Han Chinese samples. Eighty-three of these 90 have been sequenced by the 1000 Genomes Project. We have identified 12 568 804 single nucleotide polymorphisms, 2 074 210 short InDels, and 26 142 structural variations from these 90 samples. Compared to the Han Chinese data from the 1000 Genomes Project, we have found 7 000 629 novel variants with low frequency (defined as minor allele frequency genome. Compared to the 1000 Genomes Project, these Han Chinese deep sequencing data enhance the characterization of a large number of low-frequency, novel variants. This will be a valuable resource for promoting Chinese genetics research and medical development. Additionally, it will provide a valuable supplement to the 1000
Protein identification from two-dimensional gel electrophoresis analysis of Klebsiella pneumoniae by combined use of mass spectrometry data and raw genome sequences

Directory of Open Access Journals (Sweden)

Zeng An-Ping

2003-12-01

Full Text Available Abstract Separation of proteins by two-dimensional gel electrophoresis (2-DE coupled with identification of proteins through peptide mass fingerprinting (PMF by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS is the widely used technique for proteomic analysis. This approach relies, however, on the presence of the proteins studied in public-accessible protein databases or the availability of annotated genome sequences of an organism. In this work, we investigated the reliability of using raw genome sequences for identifying proteins by PMF without the need of additional information such as amino acid sequences. The method is demonstrated for proteomic analysis of Klebsiella pneumoniae grown anaerobically on glycerol. For 197 spots excised from 2-DE gels and submitted for mass spectrometric analysis 164 spots were clearly identified as 122 individual proteins. 95% of the 164 spots can be successfully identified merely by using peptide mass fingerprints and a strain-specific protein database (ProtKpn constructed from the raw genome sequences of K. pneumoniae. Cross-species protein searching in the public databases mainly resulted in the identification of 57% of the 66 high expressed protein spots in comparison to 97% by using the ProtKpn database. 10 dha regulon related proteins that are essential for the initial enzymatic steps of anaerobic glycerol metabolism were successfully identified using the ProtKpn database, whereas none of them could be identified by cross-species searching. In conclusion, the use of strain-specific protein database constructed from raw genome sequences makes it possible to reliably identify most of the proteins from 2-DE analysis simply through peptide mass fingerprinting.
High dimensional and high resolution pulse sequences for backbone resonance assignment of intrinsically disordered proteins

Energy Technology Data Exchange (ETDEWEB)

Zawadzka-Kazimierczuk, Anna; Kozminski, Wiktor, E-mail: kozmin@chem.uw.edu.pl [University of Warsaw, Faculty of Chemistry (Poland); Sanderova, Hana; Krasny, Libor [Institute of Microbiology, Academy of Sciences of the Czech Republic, Laboratory of Molecular Genetics of Bacteria, Department of Bacteriology (Czech Republic)

2012-04-15

Four novel 5D (HACA(N)CONH, HNCOCACB, (HACA)CON(CA)CONH, (H)NCO(NCA)CONH), and one 6D ((H)NCO(N)CACONH) NMR pulse sequences are proposed. The new experiments employ non-uniform sampling that enables achieving high resolution in indirectly detected dimensions. The experiments facilitate resonance assignment of intrinsically disordered proteins. The novel pulse sequences were successfully tested using {delta} subunit (20 kDa) of Bacillus subtilis RNA polymerase that has an 81-amino acid disordered part containing various repetitive sequences.
Genomic Enzymology: Web Tools for Leveraging Protein Family Sequence-Function Space and Genome Context to Discover Novel Functions.

Science.gov (United States)

Gerlt, John A

2017-08-22

The exponentially increasing number of protein and nucleic acid sequences provides opportunities to discover novel enzymes, metabolic pathways, and metabolites/natural products, thereby adding to our knowledge of biochemistry and biology. The challenge has evolved from generating sequence information to mining the databases to integrating and leveraging the available information, i.e., the availability of "genomic enzymology" web tools. Web tools that allow identification of biosynthetic gene clusters are widely used by the natural products/synthetic biology community, thereby facilitating the discovery of novel natural products and the enzymes responsible for their biosynthesis. However, many novel enzymes with interesting mechanisms participate in uncharacterized small-molecule metabolic pathways; their discovery and functional characterization also can be accomplished by leveraging information in protein and nucleic acid databases. This Perspective focuses on two genomic enzymology web tools that assist the discovery novel metabolic pathways: (1) Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST) for generating sequence similarity networks to visualize and analyze sequence-function space in protein families and (2) Enzyme Function Initiative-Genome Neighborhood Tool (EFI-GNT) for generating genome neighborhood networks to visualize and analyze the genome context in microbial and fungal genomes. Both tools have been adapted to other applications to facilitate target selection for enzyme discovery and functional characterization. As the natural products community has demonstrated, the enzymology community needs to embrace the essential role of web tools that allow the protein and genome sequence databases to be leveraged for novel insights into enzymological problems.
Complete characterization of posttranslational modification sites in the bovine milk protein PP3 by tandem mass spectrometry with electron capture dissociation as the last stage

DEFF Research Database (Denmark)

Kjeldsen, Frank; Haselmann, Kim F; Budnik, Bogdan A

2003-01-01

the PTM site. Chromatographic peak analysis continues until full sequence coverage is obtained, after which the molecular mass is reconstructed and compared with the measured value. An agreement indicates that the PTM characterization was complete. This procedure applied to the bovine milk PP3 protein...
Nucleotide sequence analysis of the Legionella micdadei mip gene, encoding a 30-kilodalton analog of the Legionella pneumophila Mip protein

DEFF Research Database (Denmark)

Bangsborg, Jette Marie; Cianciotto, N P; Hindersson, P

1991-01-01

After the demonstration of analogs of the Legionella pneumophila macrophage infectivity potentiator (Mip) protein in other Legionella species, the Legionella micdadei mip gene was cloned and expressed in Escherichia coli. DNA sequence analysis of the L. micdadei mip gene contained in the plasmid p...... homology with the mip-like genes of several Legionella species. Furthermore, amino acid sequence comparisons revealed significant homology to two eukaryotic proteins with isomerase activity (FK506-binding proteins)....
ReRep: Computational detection of repetitive sequences in genome survey sequences (GSS

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Alves-Ferreira Marcelo

2008-09-01

Full Text Available Abstract Background Genome survey sequences (GSS offer a preliminary global view of a genome since, unlike ESTs, they cover coding as well as non-coding DNA and include repetitive regions of the genome. A more precise estimation of the nature, quantity and variability of repetitive sequences very early in a genome sequencing project is of considerable importance, as such data strongly influence the estimation of genome coverage, library quality and progress in scaffold construction. Also, the elimination of repetitive sequences from the initial assembly process is important to avoid errors and unnecessary complexity. Repetitive sequences are also of interest in a variety of other studies, for instance as molecular markers. Results We designed and implemented a straightforward pipeline called ReRep, which combines bioinformatics tools for identifying repetitive structures in a GSS dataset. In a case study, we first applied the pipeline to a set of 970 GSSs, sequenced in our laboratory from the human pathogen Leishmania braziliensis, the causative agent of leishmaniosis, an important public health problem in Brazil. We also verified the applicability of ReRep to new sequencing technologies using a set of 454-reads of an Escheria coli. The behaviour of several parameters in the algorithm is evaluated and suggestions are made for tuning of the analysis. Conclusion The ReRep approach for identification of repetitive elements in GSS datasets proved to be straightforward and efficient. Several potential repetitive sequences were found in a L. braziliensis GSS dataset generated in our laboratory, and further validated by the analysis of a more complete genomic dataset from the EMBL and Sanger Centre databases. ReRep also identified most of the E. coli K12 repeats prior to assembly in an example dataset obtained by automated sequencing using 454 technology. The parameters controlling the algorithm behaved consistently and may be tuned to the properties
Nucleotide sequence of a human cDNA encoding a ras-related protein (rap1B)

Energy Technology Data Exchange (ETDEWEB)

Pizon, V; Lerosey, I; Chardin, P; Tavitian, A [INSERM, Paris (France)

1988-08-11

The authors have previously characterized two human ras-related genes rap1 and rap2. Using the rap1 clone as probe they isolated and sequenced a new rap cDNA encoding the 184aa rap1B protein. The rap1B protein is 95% identical to rap1 and shares several properties with the ras protein suggesting that it could bind GTP/GDP and have a membrane location. As for rap1, the structural characteristics of rap1B suggest that the rap and ras proteins might interact on the same effector.
Direct comparisons of Illumina vs. Roche 454 sequencing technologies on the same microbial community DNA sample.

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Chengwei Luo

Full Text Available Next-generation sequencing (NGS is commonly used in metagenomic studies of complex microbial communities but whether or not different NGS platforms recover the same diversity from a sample and their assembled sequences are of comparable quality remain unclear. We compared the two most frequently used platforms, the Roche 454 FLX Titanium and the Illumina Genome Analyzer (GA II, on the same DNA sample obtained from a complex freshwater planktonic community. Despite the substantial differences in read length and sequencing protocols, the platforms provided a comparable view of the community sampled. For instance, derived assemblies overlapped in ~90% of their total sequences and in situ abundances of genes and genotypes (estimated based on sequence coverage correlated highly between the two platforms (R(2>0.9. Evaluation of base-call error, frameshift frequency, and contig length suggested that Illumina offered equivalent, if not better, assemblies than Roche 454. The results from metagenomic samples were further validated against DNA samples of eighteen isolate genomes, which showed a range of genome sizes and G+C% content. We also provide quantitative estimates of the errors in gene and contig sequences assembled from datasets characterized by different levels of complexity and G+C% content. For instance, we noted that homopolymer-associated, single-base errors affected ~1% of the protein sequences recovered in Illumina contigs of 10× coverage and 50% G+C; this frequency increased to ~3% when non-homopolymer errors were also considered. Collectively, our results should serve as a useful practical guide for choosing proper sampling strategies and data possessing protocols for future metagenomic studies.
High Performance Protein Sequence Database Scanning on the Cell Broadband Engine

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Adrianto Wirawan

2009-01-01

Full Text Available The enormous growth of biological sequence databases has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing rapidly as well. The recent emergence of low cost parallel multicore accelerator technologies has made it possible to reduce execution times of many bioinformatics applications. In this paper, we demonstrate how the Cell Broadband Engine can be used as a computational platform to accelerate two approaches for protein sequence database scanning: exhaustive and heuristic. We present efficient parallelization techniques for two representative algorithms: the dynamic programming based Smith–Waterman algorithm and the popular BLASTP heuristic. Their implementation on a Playstation®3 leads to significant runtime savings compared to corresponding sequential implementations.
A structural study for the optimisation of functional motifs encoded in protein sequences

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Helmer-Citterich Manuela

2004-04-01

Full Text Available Abstract Background A large number of PROSITE patterns select false positives and/or miss known true positives. It is possible that – at least in some cases – the weak specificity and/or sensitivity of a pattern is due to the fact that one, or maybe more, functional and/or structural key residues are not represented in the pattern. Multiple sequence alignments are commonly used to build functional sequence patterns. If residues structurally conserved in proteins sharing a function cannot be aligned in a multiple sequence alignment, they are likely to be missed in a standard pattern construction procedure. Results Here we present a new procedure aimed at improving the sensitivity and/ or specificity of poorly-performing patterns. The procedure can be summarised as follows: 1. residues structurally conserved in different proteins, that are true positives for a pattern, are identified by means of a computational technique and by visual inspection. 2. the sequence positions of the structurally conserved residues falling outside the pattern are used to build extended sequence patterns. 3. the extended patterns are optimised on the SWISS-PROT database for their sensitivity and specificity. The method was applied to eight PROSITE patterns. Whenever structurally conserved residues are found in the surface region close to the pattern (seven out of eight cases, the addition of information inferred from structural analysis is shown to improve pattern selectivity and in some cases selectivity and sensitivity as well. In some of the cases considered the procedure allowed the identification of functionally interesting residues, whose biological role is also discussed. Conclusion Our method can be applied to any type of functional motif or pattern (not only PROSITE ones which is not able to select all and only the true positive hits and for which at least two true positive structures are available. The computational technique for the identification of
Elucidation of the outer membrane proteome of Salmonella enterica serovar Typhimurium utilising a lipid-based protein immobilization technique

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Appleton Hazel

2010-02-01

Full Text Available Abstract Background Salmonella enterica serovar Typhimurium (S. Typhimurium is a major cause of human gastroenteritis worldwide. The outer membrane proteins expressed by S. Typhimurium mediate the process of adhesion and internalisation within the intestinal epithelium of the host thus influencing the progression of disease. Since the outer membrane proteins are surface-exposed, they provide attractive targets for the development of improved antimicrobial agents and vaccines. Various techniques have been developed for their characterisation, but issues such as carryover of cytosolic proteins still remain a problem. In this study we attempted to characterise the surface proteome of S. Typhimurium using Lipid-based Protein Immobilisation technology in the form of LPI™ FlowCells. No detergents are required and no sample clean up is needed prior to downstream analysis. The immobilised proteins can be digested with proteases in multiple steps to increase sequence coverage, and the peptides eluted can be characterised directly by liquid chromatography - tandem mass spectrometry (LC-MS/MS and identified from mass spectral database searches. Results In this study, 54 outer membrane proteins, were identified with two or more peptide hits using a multi-step digest approach. Out of these 28 were lipoproteins, nine were involved in transport and three with enzyme activity These included the transporters BtuB which is responsible for the uptake of vitamin B12, LamB which is involved in the uptake of maltose and maltodextrins and LolB which is involved in the incorporation of lipoproteins in the outer membrane. Other proteins identified included the enzymes MltC which may play a role in cell elongation and division and NlpD which is involved in catabolic processes in cell wall formation as well as proteins involved in virulence such as Lpp1, Lpp2 and OmpX. Conclusion Using a multi-step digest approach the LPI™ technique enables the incorporation of a
Signatures of pleiotropy, economy and convergent evolution in a domain-resolved map of human-virus protein-protein interaction networks.

Science.gov (United States)

Garamszegi, Sara; Franzosa, Eric A; Xia, Yu

2013-01-01

A central challenge in host-pathogen systems biology is the elucidation of general, systems-level principles that distinguish host-pathogen interactions from within-host interactions. Current analyses of host-pathogen and within-host protein-protein interaction networks are largely limited by their resolution, treating proteins as nodes and interactions as edges. Here, we construct a domain-resolved map of human-virus and within-human protein-protein interaction networks by annotating protein interactions with high-coverage, high-accuracy, domain-centric interaction mechanisms: (1) domain-domain interactions, in which a domain in one protein binds to a domain in a second protein, and (2) domain-motif interactions, in which a domain in one protein binds to a short, linear peptide motif in a second protein. Analysis of these domain-resolved networks reveals, for the first time, significant mechanistic differences between virus-human and within-human interactions at the resolution of single domains. While human proteins tend to compete with each other for domain binding sites by means of sequence similarity, viral proteins tend to compete with human proteins for domain binding sites in the absence of sequence similarity. Independent of their previously established preference for targeting human protein hubs, viral proteins also preferentially target human proteins containing linear motif-binding domains. Compared to human proteins, viral proteins participate in more domain-motif interactions, target more unique linear motif-binding domains per residue, and contain more unique linear motifs per residue. Together, these results suggest that viruses surmount genome size constraints by convergently evolving multiple short linear motifs in order to effectively mimic, hijack, and manipulate complex host processes for their survival. Our domain-resolved analyses reveal unique signatures of pleiotropy, economy, and convergent evolution in viral-host interactions that are
RNAcontext: a new method for learning the sequence and structure binding preferences of RNA-binding proteins.

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Hilal Kazan

2010-07-01

Full Text Available Metazoan genomes encode hundreds of RNA-binding proteins (RBPs. These proteins regulate post-transcriptional gene expression and have critical roles in numerous cellular processes including mRNA splicing, export, stability and translation. Despite their ubiquity and importance, the binding preferences for most RBPs are not well characterized. In vitro and in vivo studies, using affinity selection-based approaches, have successfully identified RNA sequence associated with specific RBPs; however, it is difficult to infer RBP sequence and structural preferences without specifically designed motif finding methods. In this study, we introduce a new motif-finding method, RNAcontext, designed to elucidate RBP-specific sequence and structural preferences with greater accuracy than existing approaches. We evaluated RNAcontext on recently published in vitro and in vivo RNA affinity selected data and demonstrate that RNAcontext identifies known binding preferences for several control proteins including HuR, PTB, and Vts1p and predicts new RNA structure preferences for SF2/ASF, RBM4, FUSIP1 and SLM2. The predicted preferences for SF2/ASF are consistent with its recently reported in vivo binding sites. RNAcontext is an accurate and efficient motif finding method ideally suited for using large-scale RNA-binding affinity datasets to determine the relative binding preferences of RBPs for a wide range of RNA sequences and structures.
Purification and sequencing of radish seed calmodulin antagonists phosphorylated by calcium-dependent protein kinase.

Science.gov (United States)

Polya, G M; Chandra, S; Condron, R

1993-02-01

A family of radish (Raphanus sativus) calmodulin antagonists (RCAs) was purified from seeds by extraction, centrifugation, batch-wise elution from carboxymethyl-cellulose, and high performance liquid chromatography (HPLC) on an SP5PW cation-exchange column. This RCA fraction was further resolved into three calmodulin antagonist polypeptides (RCA1, RCA2, and RCA3) by denaturation in the presence of guanidinium HCl and mercaptoethanol and subsequent reverse-phase HPLC on a C8 column eluted with an acetonitrile gradient in the presence of 0.1% trifluoroacetic acid. The RCA preparation, RCA1, RCA2, RCA3, and other radish seed proteins are phosphorylated by wheat embryo Ca(2+)-dependent protein kinase (CDPK). The RCA preparation contains other CDPK substrates in addition to RCA1, RCA2, and RCA3. The RCA preparation, RCA1, RCA2, and RCA3 inhibit chicken gizzard calmodulin-dependent myosin light chain kinase assayed with a myosin-light chain-based synthetic peptide substrate (fifty percent inhibitory concentrations of RCA2 and RCA3 are about 7 and 2 microM, respectively). N-terminal sequencing by sequential Edman degradation of RCA1, RCA2, and RCA3 revealed sequences having a high homology with the small subunit of the storage protein napin from Brassica napus and with related proteins. The deduced amino acid sequences of RCA1, RCA2, RCA3, and RCA3' (a subform of RCA3) have agreement with average molecular masses from electrospray mass spectrometry of 4537, 4543, 4532, and 4560 kD, respectively. The only sites for serine phosphorylation are near or at the C termini and hence adjacent to the sites of proteolytic precursor cleavage.
Actin and ubiquitin protein sequences support a cercozoan/foraminiferan ancestry for the plasmodiophorid plant pathogens.

Science.gov (United States)

Archibald, John M; Keeling, Patrick J

2004-01-01

The plasmodiophorids are a group of eukaryotic intracellular parasites that cause disease in a variety of economically significant crops. Plasmodiophorids have traditionally been considered fungi but have more recently been suggested to be members of the Cercozoa, a morphologically diverse group of amoeboid, flagellate, and amoeboflagellate protists. The recognition that Cercozoa constitute a monophyletic lineage has come from phylogenetic analyses of small subunit ribosomal RNA genes. Protein sequence data have suggested that the closest relatives of Cercozoa are the Foraminifera. To further test a cercozoan origin for the plasmodiophorids, we isolated actin genes from Plasmodiophora brassicae, Sorosphaera veronicae, and Spongospora subterranea, and polyubiquitin gene fragments from P. brassicae and S. subterranea. We also isolated actin genes from the chlorarachniophyte Lotharella globosa. In protein phylogenies of actin, the plasmodiophorid sequences consistently branch with Cercozoa and Foraminifera, and weakly branch as the sister group to the foraminiferans. The plasmodiophorid polyubiquitin sequences contain a single amino acid residue insertion at the functionally important processing point between ubiquitin monomers, the same place in which an otherwise unique insertion exists in the cercozoan and foraminiferan proteins. Taken together, these results indicate that plasmodiophorids are indeed related to Cercozoa and Foraminifera, although the relationships amongst these groups remain unresolved.
Spike protein assembly into the coronavirion: exploring the limits of its sequence requirements

International Nuclear Information System (INIS)

Bosch, Berend Jan; Haan, Cornelis A.M. de; Smits, Saskia L.; Rottier, Peter J.M.

2005-01-01

The coronavirus spike (S) protein, required for receptor binding and membrane fusion, is incorporated into the assembling virion by interactions with the viral membrane (M) protein. Earlier we showed that the ectodomain of the S protein is not involved in this process. Here we further defined the requirements of the S protein for virion incorporation. We show that the cytoplasmic domain, not the transmembrane domain, determines the association with the M protein and suffices to effect the incorporation into viral particles of chimeric spikes as well as of foreign viral glycoproteins. The essential sequence was mapped to the membrane-proximal region of the cytoplasmic domain, which is also known to be of critical importance for the fusion function of the S protein. Consistently, only short C-terminal truncations of the S protein were tolerated when introduced into the virus by targeted recombination. The important role of the about 38-residues cytoplasmic domain in the assembly of and membrane fusion by this approximately 1300 amino acids long protein is discussed
Cloning and sequencing of the cDNA encoding a core protein of the paired helical filament of Alzheimer's disease: Identification as the microtubule-associated protein tau

International Nuclear Information System (INIS)

Goedert, M.; Wischik, C.M.; Crowther, R.A.; Walker, J.E.; Klug, A.

1988-01-01

Screening of cDNA libraries prepared from the frontal cortex of an Alzheimer's disease patient and from fetal human brain has led to isolation of the cDNA for a core protein of the paired helical filament of Alzheimer's disease. The partial amino acid sequence of this core protein was used to design synthetic oligonucleotide probes. The cDNA encodes a protein of 352 amino acids that contains a characteristic amino acid repeat in its carboxyl-terminal half. This protein is highly homologous to the sequence of the mouse microtubule-associated protein tau and thus constitutes the human equivalent of mouse tau. RNA blot analysis indicates the presence of two major transcripts, 6 and 2 kilobases long, with a wide distribution in normal human brain. Tau protein mRNAs were found in normal amounts in the frontal cortex from patients with Alzheimer's disease. The proof that at least part of tau protein forms a component of the paired helical filament core opens the way to understanding the mode of formation of paired helical filaments and thus, ultimately, the pathogenesis of Alzheimer's disease
The master two-dimensional gel database of human AMA cell proteins: towards linking protein and genome sequence and mapping information (update 1991)

DEFF Research Database (Denmark)

Celis, J E; Leffers, H; Rasmussen, H H

1991-01-01

autoantigens" and "cDNAs". For convenience we have included an alphabetical list of all known proteins recorded in this database. In the long run, the main goal of this database is to link protein and DNA sequencing and mapping information (Human Genome Program) and to provide an integrated picture......The master two-dimensional gel database of human AMA cells currently lists 3801 cellular and secreted proteins, of which 371 cellular polypeptides (306 IEF; 65 NEPHGE) were added to the master images during the last 10 months. These include: (i) very basic and acidic proteins that do not focus...
Improved protein extraction and protein identification from archival formalin-fixed paraffin-embedded human aortas.

Science.gov (United States)

Fu, Zongming; Yan, Kun; Rosenberg, Avraham; Jin, Zhicheng; Crain, Barbara; Athas, Grace; Heide, Richard S Vander; Howard, Timothy; Everett, Allen D; Herrington, David; Van Eyk, Jennifer E

2013-04-01

Evaluate combination of heat and elevated pressure to enhance protein extraction and quality of formalin-fixed (FF), and FF paraffin-embedded (FFPE) aorta for proteomics. Proteins were extracted from fresh frozen aorta at room temperature (RT). FF and FFPE aortas (3 months and 15 years) were extracted at RT, heat alone, or a combination of heat and high pressure. Protein yields were compared, and digested peptides from the extracts were analyzed with MS. Combined heat and elevated pressure increased protein yield from human FF or FFPE aorta compared to matched tissues with heat alone (1.5-fold) or at RT (8.3-fold), resulting in more proteins identified and with more sequence coverage. The length of storage did adversely affect the quality of proteins from FF tissue. For long-term storage, aorta was preserved better with FFPE than FF alone. Periostin and MGF-E8 were demonstrated suitable for MRM assays from FFPE aorta. Combination of heat and high pressure is an effective method to extract proteins from FFPE aorta for downstream proteomics. This method opens the possibility for use of archival and often rare FFPE aortas and possibly other tissues available to proteomics for biomarker discovery and quantification. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Classification of Dutch and German avian reoviruses by sequencing the sigma-C protein.

NARCIS (Netherlands)

Kant, A.; Balk, F.R.M.; Born, L.; Roozelaar, van D.; Heijmans, J.; Gielkens, A.; Huurne, ter A.A.H.M.

2003-01-01

We have amplified, cloned and sequenced (part of) the open reading frame of the S1 segment encoding the ¿ C protein of avian reoviruses isolated from chickens with different disease conditions in Germany and The Netherlands during 1980 up to 2000. These avian reoviruses were analysed
Detection of genomic variation by selection of a 9 mb DNA region and high throughput sequencing.

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Sergey I Nikolaev

Full Text Available Detection of the rare polymorphisms and causative mutations of genetic diseases in a targeted genomic area has become a major goal in order to understand genomic and phenotypic variability. We have interrogated repeat-masked regions of 8.9 Mb on human chromosomes 21 (7.8 Mb and 7 (1.1 Mb from an individual from the International HapMap Project (NA12872. We have optimized a method of genomic selection for high throughput sequencing. Microarray-based selection and sequencing resulted in 260-fold enrichment, with 41% of reads mapping to the target region. 83% of SNPs in the targeted region had at least 4-fold sequence coverage and 54% at least 15-fold. When assaying HapMap SNPs in NA12872, our sequence genotypes are 91.3% concordant in regions with coverage > or = 4-fold, and 97.9% concordant in regions with coverage > or = 15-fold. About 81% of the SNPs recovered with both thresholds are listed in dbSNP. We observed that regions with low sequence coverage occur in close proximity to low-complexity DNA. Validation experiments using Sanger sequencing were performed for 46 SNPs with 15-20 fold coverage, with a confirmation rate of 96%, suggesting that DNA selection provides an accurate and cost-effective method for identifying rare genomic variants.
Analyses of the Sequence and Structural Properties Corresponding to Pentapeptide and Large Palindromes in Proteins.

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Settu Sridhar

Full Text Available The analyses of 3967 representative proteins selected from the Protein Data Bank revealed the presence of 2803 pentapeptide and large palindrome sequences with known secondary structure conformation. These represent 2014 unique palindrome sequences. 60% palindromes are not associated with any regular secondary structure and 28% are in helix conformation, 11% in strand conformation and 1% in the coil conformation. The average solvent accessibility values are in the range between 0-155.28 Å2 suggesting that the palindromes in proteins can be either buried, exposed to the solvent or share an intermittent property. The number of residue neighborhood contacts defined by interactions ≤ 3.2 Ǻ is in the range between 0-29 residues. Palindromes of the same length in helix, strand and coil conformation are associated with different amino acid residue preferences at the individual positions. Nearly, 20% palindromes interact with catalytic/active site residues, ligand or metal ions in proteins and may therefore be important for function in the corresponding protein. The average hydrophobicity values for the pentapeptide and large palindromes range between -4.3 to +4.32 and the number of palindromes is almost equally distributed between the negative and positive hydrophobicity values. The palindromes represent 107 different protein families and the hydrolases, transferases, oxidoreductases and lyases contain relatively large number of palindromes.
Chameleon sequences in neurodegenerative diseases.

Science.gov (United States)

Bahramali, Golnaz; Goliaei, Bahram; Minuchehr, Zarrin; Salari, Ali

2016-03-25

Chameleon sequences can adopt either alpha helix sheet or a coil conformation. Defining chameleon sequences in PDB (Protein Data Bank) may yield to an insight on defining peptides and proteins responsible in neurodegeneration. In this research, we benefitted from the large PDB and performed a sequence analysis on Chameleons, where we developed an algorithm to extract peptide segments with identical sequences, but different structures. In order to find new chameleon sequences, we extracted a set of 8315 non-redundant protein sequences from the PDB with an identity less than 25%. Our data was classified to "helix to strand (HE)", "helix to coil (HC)" and "strand to coil (CE)" alterations. We also analyzed the occurrence of singlet and doublet amino acids and the solvent accessibility in the chameleon sequences; we then sorted out the proteins with the most number of chameleon sequences and named them Chameleon Flexible Proteins (CFPs) in our dataset. Our data revealed that Gly, Val, Ile, Tyr and Phe, are the major amino acids in Chameleons. We also found that there are proteins such as Insulin Degrading Enzyme IDE and GTP-binding nuclear protein Ran (RAN) with the most number of chameleons (640 and 405 respectively). These proteins have known roles in neurodegenerative diseases. Therefore it can be inferred that other CFP's can serve as key proteins in neurodegeneration, and a study on them can shed light on curing and preventing neurodegenerative diseases. Copyright © 2016 Elsevier Inc. All rights reserved.
Chameleon sequences in neurodegenerative diseases

International Nuclear Information System (INIS)

Bahramali, Golnaz; Goliaei, Bahram; Minuchehr, Zarrin; Salari, Ali

2016-01-01

Chameleon sequences can adopt either alpha helix sheet or a coil conformation. Defining chameleon sequences in PDB (Protein Data Bank) may yield to an insight on defining peptides and proteins responsible in neurodegeneration. In this research, we benefitted from the large PDB and performed a sequence analysis on Chameleons, where we developed an algorithm to extract peptide segments with identical sequences, but different structures. In order to find new chameleon sequences, we extracted a set of 8315 non-redundant protein sequences from the PDB with an identity less than 25%. Our data was classified to “helix to strand (HE)”, “helix to coil (HC)” and “strand to coil (CE)” alterations. We also analyzed the occurrence of singlet and doublet amino acids and the solvent accessibility in the chameleon sequences; we then sorted out the proteins with the most number of chameleon sequences and named them Chameleon Flexible Proteins (CFPs) in our dataset. Our data revealed that Gly, Val, Ile, Tyr and Phe, are the major amino acids in Chameleons. We also found that there are proteins such as Insulin Degrading Enzyme IDE and GTP-binding nuclear protein Ran (RAN) with the most number of chameleons (640 and 405 respectively). These proteins have known roles in neurodegenerative diseases. Therefore it can be inferred that other CFP's can serve as key proteins in neurodegeneration, and a study on them can shed light on curing and preventing neurodegenerative diseases.
Chameleon sequences in neurodegenerative diseases

Energy Technology Data Exchange (ETDEWEB)

Bahramali, Golnaz [Institute of Biochemistry and Biophysics, University of Tehran, Tehran (Iran, Islamic Republic of); Goliaei, Bahram, E-mail: goliaei@ut.ac.ir [Institute of Biochemistry and Biophysics, University of Tehran, Tehran (Iran, Islamic Republic of); Minuchehr, Zarrin, E-mail: minuchehr@nigeb.ac.ir [Department of Systems Biotechnology, National Institute of Genetic Engineering and Biotechnology, (NIGEB), Tehran (Iran, Islamic Republic of); Salari, Ali [Department of Systems Biotechnology, National Institute of Genetic Engineering and Biotechnology, (NIGEB), Tehran (Iran, Islamic Republic of)

2016-03-25

Chameleon sequences can adopt either alpha helix sheet or a coil conformation. Defining chameleon sequences in PDB (Protein Data Bank) may yield to an insight on defining peptides and proteins responsible in neurodegeneration. In this research, we benefitted from the large PDB and performed a sequence analysis on Chameleons, where we developed an algorithm to extract peptide segments with identical sequences, but different structures. In order to find new chameleon sequences, we extracted a set of 8315 non-redundant protein sequences from the PDB with an identity less than 25%. Our data was classified to “helix to strand (HE)”, “helix to coil (HC)” and “strand to coil (CE)” alterations. We also analyzed the occurrence of singlet and doublet amino acids and the solvent accessibility in the chameleon sequences; we then sorted out the proteins with the most number of chameleon sequences and named them Chameleon Flexible Proteins (CFPs) in our dataset. Our data revealed that Gly, Val, Ile, Tyr and Phe, are the major amino acids in Chameleons. We also found that there are proteins such as Insulin Degrading Enzyme IDE and GTP-binding nuclear protein Ran (RAN) with the most number of chameleons (640 and 405 respectively). These proteins have known roles in neurodegenerative diseases. Therefore it can be inferred that other CFP's can serve as key proteins in neurodegeneration, and a study on them can shed light on curing and preventing neurodegenerative diseases.
Measles seroprevalence, outbreaks, and vaccine coverage in Rwanda.

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Seruyange, Eric; Gahutu, Jean-Bosco; Mambo Muvunyi, Claude; Uwimana, Zena G; Gatera, Maurice; Twagirumugabe, Theogene; Katare, Swaibu; Karenzi, Ben; Bergström, Tomas

2016-01-01

Measles outbreaks are reported after insufficient vaccine coverage, especially in countries recovering from natural disaster or conflict. We compared seroprevalence to measles in blood donors in Rwanda and Sweden and explored distribution of active cases of measles and vaccine coverage in Rwanda. 516 Rwandan and 215 Swedish blood donors were assayed for measles-specific immunoglobulin G (IgG) by enzyme-linked immunosorbent assay (ELISA). Data on vaccine coverage and acute cases in Rwanda from 1980 to 2014 were collected, and IgM on serum samples and polymerase chain reaction (PCR) on nasopharyngeal (NPH) swabs from suspected measles cases during 2010-2011 were analysed. The seroprevalence of measles IgG was significantly higher in Swedish blood donors (92.6%; 95% CI: 89.1-96.1%) compared to Rwandan subjects (71.5%; 95% CI: 67.6-75.4%) and more pronounced Rwanda, with the exception of an outbreak in 1995 following the 1994 genocide. 76/544 serum samples were IgM positive and 21/31 NPH swabs were PCR positive for measles, determined by sequencing to be of genotype B3. Measles seroprevalence was lower in Rwandan blood donors compared to Swedish subjects. Despite this, the number of reported measles cases in Rwanda rapidly decreased during the study period, concomitant with increased vaccine coverage. Taken together, the circulation of measles was limited in Rwanda and vaccine coverage was favourable, but seroprevalence and IgG levels were low especially in younger age groups.
The complete chloroplast genome sequence of Helwingia himalaica (Helwingiaceae, Aquifoliales and a chloroplast phylogenomic analysis of the Campanulidae

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Xin Yao

2016-11-01

Full Text Available Complete chloroplast genome sequences have been very useful for understanding phylogenetic relationships in angiosperms at the family level and above, but there are currently large gaps in coverage. We report the chloroplast genome for Helwingia himalaica, the first in the distinctive family Helwingiaceae and only the second genus to be sequenced in the order Aquifoliales. We then combine this with 36 published sequences in the large (c. 35,000 species subclass Campanulidae in order to investigate relationships at the order and family levels. The Helwingia genome consists of 158,362 bp containing a pair of inverted repeat (IR regions of 25,996 bp separated by a large single-copy (LSC region and a small single-copy (SSC region which are 87,810 and 18,560 bp, respectively. There are 142 known genes, including 94 protein-coding genes, eight ribosomal RNA genes, and 40 tRNA genes. The topology of the phylogenetic relationships between Apiales, Asterales, and Dipsacales differed between analyses based on complete genome sequences and on 36 shared protein-coding genes, showing that further studies of campanulid phylogeny are needed.
Preparative Protein Production from Inclusion Bodies and Crystallization: A Seven-Week Biochemistry Sequence

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Peterson, Megan J.; Snyder, W. Kalani; Westerman, Shelley; McFarland, Benjamin J.

2011-01-01

We describe how to produce and purify proteins from E. coli inclusion bodies by adapting versatile, preparative-scale techniques to the undergraduate laboratory schedule. This seven-week sequence of experiments fits into an annual cycle of research activity in biochemistry courses. Recombinant proteins are expressed as inclusion bodies, which are collected, washed, then solubilized in urea. Stepwise dialysis to dilute urea over the course of a week produces refolded protein. Column chromatography is used to purify protein into fractions, which are then analyzed with gel electrophoresis and concentration assays. Students culminate the project by designing crystallization trials in sitting-drop trays. Student evaluation of the experience has been positive, listing 5–12 new techniques learned, which are transferrable to graduate research in academia and industry. PMID:21691428
A curated gluten protein sequence database to support development of proteomics methods for determination of gluten in gluten-free foods.

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Bromilow, Sophie; Gethings, Lee A; Buckley, Mike; Bromley, Mike; Shewry, Peter R; Langridge, James I; Clare Mills, E N

2017-06-23

The unique physiochemical properties of wheat gluten enable a diverse range of food products to be manufactured. However, gluten triggers coeliac disease, a condition which is treated using a gluten-free diet. Analytical methods are required to confirm if foods are gluten-free, but current immunoassay-based methods can unreliable and proteomic methods offer an alternative but require comprehensive and well annotated sequence databases which are lacking for gluten. A manually a curated database (GluPro V1.0) of gluten proteins, comprising 630 discrete unique full length protein sequences has been compiled. It is representative of the different types of gliadin and glutenin components found in gluten. An in silico comparison of their coeliac toxicity was undertaken by analysing the distribution of coeliac toxic motifs. This demonstrated that whilst the α-gliadin proteins contained more toxic motifs, these were distributed across all gluten protein sub-types. Comparison of annotations observed using a discovery proteomics dataset acquired using ion mobility MS/MS showed that more reliable identifications were obtained using the GluPro V1.0 database compared to the complete reviewed Viridiplantae database. This highlights the value of a curated sequence database specifically designed to support the proteomic workflows and the development of methods to detect and quantify gluten. We have constructed the first manually curated open-source wheat gluten protein sequence database (GluPro V1.0) in a FASTA format to support the application of proteomic methods for gluten protein detection and quantification. We have also analysed the manually verified sequences to give the first comprehensive overview of the distribution of sequences able to elicit a reaction in coeliac disease, the prevalent form of gluten intolerance. Provision of this database will improve the reliability of gluten protein identification by proteomic analysis, and aid the development of targeted mass
WebScipio: An online tool for the determination of gene structures using protein sequences

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Waack Stephan

2008-09-01

Full Text Available Abstract Background Obtaining the gene structure for a given protein encoding gene is an important step in many analyses. A software suited for this task should be readily accessible, accurate, easy to handle and should provide the user with a coherent representation of the most probable gene structure. It should be rigorous enough to optimise features on the level of single bases and at the same time flexible enough to allow for cross-species searches. Results WebScipio, a web interface to the Scipio software, allows a user to obtain the corresponding coding sequence structure of a here given a query protein sequence that belongs to an already assembled eukaryotic genome. The resulting gene structure is presented in various human readable formats like a schematic representation, and a detailed alignment of the query and the target sequence highlighting any discrepancies. WebScipio can also be used to identify and characterise the gene structures of homologs in related organisms. In addition, it offers a web service for integration with other programs. Conclusion WebScipio is a tool that allows users to get a high-quality gene structure prediction from a protein query. It offers more than 250 eukaryotic genomes that can be searched and produces predictions that are close to what can be achieved by manual annotation, for in-species and cross-species searches alike. WebScipio is freely accessible at http://www.webscipio.org.
Complete genome sequence of Klebsiella pneumoniae J1, a protein-based microbial flocculant-producing bacterium.

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Pang, Changlong; Li, Ang; Cui, Di; Yang, Jixian; Ma, Fang; Guo, Haijuan

2016-02-20

Klebsiella pneumoniae J1 is a Gram-negative strain, which belongs to a protein-based microbial flocculant-producing bacterium. However, little genetic information is known about this species. Here we carried out a whole-genome sequence analysis of this strain and report the complete genome sequence of this organism and its genetic basis for carbohydrate metabolism, capsule biosynthesis and transport system. Copyright © 2016 Elsevier B.V. All rights reserved.
A stochastic context free grammar based framework for analysis of protein sequences

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Nebel Jean-Christophe

2009-10-01

Full Text Available Abstract Background In the last decade, there have been many applications of formal language theory in bioinformatics such as RNA structure prediction and detection of patterns in DNA. However, in the field of proteomics, the size of the protein alphabet and the complexity of relationship between amino acids have mainly limited the application of formal language theory to the production of grammars whose expressive power is not higher than stochastic regular grammars. However, these grammars, like other state of the art methods, cannot cover any higher-order dependencies such as nested and crossing relationships that are common in proteins. In order to overcome some of these limitations, we propose a Stochastic Context Free Grammar based framework for the analysis of protein sequences where grammars are induced using a genetic algorithm. Results This framework was implemented in a system aiming at the production of binding site descriptors. These descriptors not only allow detection of protein regions that are involved in these sites, but also provide insight in their structure. Grammars were induced using quantitative properties of amino acids to deal with the size of the protein alphabet. Moreover, we imposed some structural constraints on grammars to reduce the extent of the rule search space. Finally, grammars based on different properties were combined to convey as much information as possible. Evaluation was performed on sites of various sizes and complexity described either by PROSITE patterns, domain profiles or a set of patterns. Results show the produced binding site descriptors are human-readable and, hence, highlight biologically meaningful features. Moreover, they achieve good accuracy in both annotation and detection. In addition, findings suggest that, unlike current state-of-the-art methods, our system may be particularly suited to deal with patterns shared by non-homologous proteins. Conclusion A new Stochastic Context Free
High depth, whole-genome sequencing of cholera isolates from Haiti and the Dominican Republic.

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Sealfon, Rachel; Gire, Stephen; Ellis, Crystal; Calderwood, Stephen; Qadri, Firdausi; Hensley, Lisa; Kellis, Manolis; Ryan, Edward T; LaRocque, Regina C; Harris, Jason B; Sabeti, Pardis C

2012-09-11

Whole-genome sequencing is an important tool for understanding microbial evolution and identifying the emergence of functionally important variants over the course of epidemics. In October 2010, a severe cholera epidemic began in Haiti, with additional cases identified in the neighboring Dominican Republic. We used whole-genome approaches to sequence four Vibrio cholerae isolates from Haiti and the Dominican Republic and three additional V. cholerae isolates to a high depth of coverage (>2000x); four of the seven isolates were previously sequenced. Using these sequence data, we examined the effect of depth of coverage and sequencing platform on genome assembly and identification of sequence variants. We found that 50x coverage is sufficient to construct a whole-genome assembly and to accurately call most variants from 100 base pair paired-end sequencing reads. Phylogenetic analysis between the newly sequenced and thirty-three previously sequenced V. cholerae isolates indicates that the Haitian and Dominican Republic isolates are closest to strains from South Asia. The Haitian and Dominican Republic isolates form a tight cluster, with only four variants unique to individual isolates. These variants are located in the CTX region, the SXT region, and the core genome. Of the 126 mutations identified that separate the Haiti-Dominican Republic cluster from the V. cholerae reference strain (N16961), 73 are non-synonymous changes, and a number of these changes cluster in specific genes and pathways. Sequence variant analyses of V. cholerae isolates, including multiple isolates from the Haitian outbreak, identify coverage-specific and technology-specific effects on variant detection, and provide insight into genomic change and functional evolution during an epidemic.
High depth, whole-genome sequencing of cholera isolates from Haiti and the Dominican Republic

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Sealfon Rachel

2012-09-01

Full Text Available Abstract Background Whole-genome sequencing is an important tool for understanding microbial evolution and identifying the emergence of functionally important variants over the course of epidemics. In October 2010, a severe cholera epidemic began in Haiti, with additional cases identified in the neighboring Dominican Republic. We used whole-genome approaches to sequence four Vibrio cholerae isolates from Haiti and the Dominican Republic and three additional V. cholerae isolates to a high depth of coverage (>2000x; four of the seven isolates were previously sequenced. Results Using these sequence data, we examined the effect of depth of coverage and sequencing platform on genome assembly and identification of sequence variants. We found that 50x coverage is sufficient to construct a whole-genome assembly and to accurately call most variants from 100 base pair paired-end sequencing reads. Phylogenetic analysis between the newly sequenced and thirty-three previously sequenced V. cholerae isolates indicates that the Haitian and Dominican Republic isolates are closest to strains from South Asia. The Haitian and Dominican Republic isolates form a tight cluster, with only four variants unique to individual isolates. These variants are located in the CTX region, the SXT region, and the core genome. Of the 126 mutations identified that separate the Haiti-Dominican Republic cluster from the V. cholerae reference strain (N16961, 73 are non-synonymous changes, and a number of these changes cluster in specific genes and pathways. Conclusions Sequence variant analyses of V. cholerae isolates, including multiple isolates from the Haitian outbreak, identify coverage-specific and technology-specific effects on variant detection, and provide insight into genomic change and functional evolution during an epidemic.
An efficient, versatile and scalable pattern growth approach to mine frequent patterns in unaligned protein sequences.

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Ye, Kai; Kosters, Walter A; Ijzerman, Adriaan P

2007-03-15

Pattern discovery in protein sequences is often based on multiple sequence alignments (MSA). The procedure can be computationally intensive and often requires manual adjustment, which may be particularly difficult for a set of deviating sequences. In contrast, two algorithms, PRATT2 (http//www.ebi.ac.uk/pratt/) and TEIRESIAS (http://cbcsrv.watson.ibm.com/) are used to directly identify frequent patterns from unaligned biological sequences without an attempt to align them. Here we propose a new algorithm with more efficiency and more functionality than both PRATT2 and TEIRESIAS, and discuss some of its applications to G protein-coupled receptors, a protein family of important drug targets. In this study, we designed and implemented six algorithms to mine three different pattern types from either one or two datasets using a pattern growth approach. We compared our approach to PRATT2 and TEIRESIAS in efficiency, completeness and the diversity of pattern types. Compared to PRATT2, our approach is faster, capable of processing large datasets and able to identify the so-called type III patterns. Our approach is comparable to TEIRESIAS in the discovery of the so-called type I patterns but has additional functionality such as mining the so-called type II and type III patterns and finding discriminating patterns between two datasets. The source code for pattern growth algorithms and their pseudo-code are available at http://www.liacs.nl/home/kosters/pg/.
Prediction of membrane transport proteins and their substrate specificities using primary sequence information.

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Nitish K Mishra

Full Text Available Membrane transport proteins (transporters move hydrophilic substrates across hydrophobic membranes and play vital roles in most cellular functions. Transporters represent a diverse group of proteins that differ in topology, energy coupling mechanism, and substrate specificity as well as sequence similarity. Among the functional annotations of transporters, information about their transporting substrates is especially important. The experimental identification and characterization of transporters is currently costly and time-consuming. The development of robust bioinformatics-based methods for the prediction of membrane transport proteins and their substrate specificities is therefore an important and urgent task.Support vector machine (SVM-based computational models, which comprehensively utilize integrative protein sequence features such as amino acid composition, dipeptide composition, physico-chemical composition, biochemical composition, and position-specific scoring matrices (PSSM, were developed to predict the substrate specificity of seven transporter classes: amino acid, anion, cation, electron, protein/mRNA, sugar, and other transporters. An additional model to differentiate transporters from non-transporters was also developed. Among the developed models, the biochemical composition and PSSM hybrid model outperformed other models and achieved an overall average prediction accuracy of 76.69% with a Mathews correlation coefficient (MCC of 0.49 and a receiver operating characteristic area under the curve (AUC of 0.833 on our main dataset. This model also achieved an overall average prediction accuracy of 78.88% and MCC of 0.41 on an independent dataset.Our analyses suggest that evolutionary information (i.e., the PSSM and the AAIndex are key features for the substrate specificity prediction of transport proteins. In comparison, similarity-based methods such as BLAST, PSI-BLAST, and hidden Markov models do not provide accurate predictions
Sequence-engineered mRNA Without Chemical Nucleoside Modifications Enables an Effective Protein Therapy in Large Animals

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Thess, Andreas; Grund, Stefanie; Mui, Barbara L; Hope, Michael J; Baumhof, Patrick; Fotin-Mleczek, Mariola; Schlake, Thomas

2015-01-01

Being a transient carrier of genetic information, mRNA could be a versatile, flexible, and safe means for protein therapies. While recent findings highlight the enormous therapeutic potential of mRNA, evidence that mRNA-based protein therapies are feasible beyond small animals such as mice is still lacking. Previous studies imply that mRNA therapeutics require chemical nucleoside modifications to obtain sufficient protein expression and avoid activation of the innate immune system. Here we show that chemically unmodified mRNA can achieve those goals as well by applying sequence-engineered molecules. Using erythropoietin (EPO) driven production of red blood cells as the biological model, engineered Epo mRNA elicited meaningful physiological responses from mice to nonhuman primates. Even in pigs of about 20 kg in weight, a single adequate dose of engineered mRNA encapsulated in lipid nanoparticles (LNPs) induced high systemic Epo levels and strong physiological effects. Our results demonstrate that sequence-engineered mRNA has the potential to revolutionize human protein therapies. PMID:26050989
Amino acid sequences mediating vascular cell adhesion molecule 1 binding to integrin alpha 4: homologous DSP sequence found for JC polyoma VP1 coat protein

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Michael Andrew Meyer

2013-07-01

Full Text Available The JC polyoma viral coat protein VP1 was analyzed for amino acid sequences homologies to the IDSP sequence which mediates binding of VLA-4 (integrin alpha 4 to vascular cell adhesion molecule 1. Although the full sequence was not found, a DSP sequence was located near the critical arginine residue linked to infectivity of the virus and binding to sialic acid containing molecules such as integrins (3. For the JC polyoma virus, a DSP sequence was found at residues 70, 71 and 72 with homology also noted for the mouse polyoma virus and SV40 virus. Three dimensional modeling of the VP1 molecule suggests that the DSP loop has an accessible site for interaction from the external side of the assembled viral capsid pentamer.
Eukaryote-wide sequence analysis of mitochondrial β-barrel outer membrane proteins

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Fujita Naoya

2011-01-01

Full Text Available Abstract Background The outer membranes of mitochondria are thought to be homologous to the outer membranes of Gram negative bacteria, which contain 100's of distinct families of β-barrel membrane proteins (BOMPs often forming channels for transport of nutrients or drugs. However, only four families of mitochondrial BOMPs (MBOMPs have been confirmed to date. Although estimates as high as 100 have been made in the past, the number of yet undiscovered MBOMPs is an open question. Fortunately, the recent discovery of a membrane integration signal (the β-signal for MBOMPs gave us an opportunity to look for undiscovered MBOMPs. Results We present the results of a comprehensive survey of eukaryotic protein sequences intended to identify new MBOMPs. Our search employs recent results on β-signals as well as structural information and a novel BOMP predictor trained on both bacterial and mitochondrial BOMPs. Our principal finding is circumstantial evidence suggesting that few MBOMPs remain to be discovered, if one assumes that, like known MBOMPs, novel MBOMPs will be monomeric and β-signal dependent. In addition to this, our analysis of MBOMP homologs reveals some exceptions to the current model of the β-signal, but confirms its consistent presence in the C-terminal region of MBOMP proteins. We also report a β-signal independent search for MBOMPs against the yeast and Arabidopsis proteomes. We find no good candidates MBOMPs in yeast but the Arabidopsis results are less conclusive. Conclusions Our results suggest there are no remaining MBOMPs left to discover in yeast; and if one assumes all MBOMPs are β-signal dependent, few MBOMP families remain undiscovered in any sequenced organism.

Sequencing of chloroplast genome using whole cellular DNA and Solexa sequencing technology

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Jian eWu

2012-11-01

Full Text Available Sequencing of the chloroplast genome using traditional sequencing methods has been difficult because of its size (>120 kb and the complicated procedures required to prepare templates. To explore the feasibility of sequencing the chloroplast genome using DNA extracted from whole cells and Solexa sequencing technology, we sequenced whole cellular DNA isolated from leaves of three Brassica rapa accessions with one lane per accession. In total, 246 Mb, 362Mb, 361 Mb sequence data were generated for the three accessions Chiifu-401-42, Z16 and FT, respectively. Microreads were assembled by reference-guided assembly using the cpDNA sequences of B. rapa, Arabidopsis thaliana, and Nicotiana tabacum. We achieved coverage of more than 99.96% of the cp genome in the three tested accessions using the B. rapa sequence as the reference. When A. thaliana or N. tabacum sequences were used as references, 99.7–99.8% or 95.5–99.7% of the B. rapa chloroplast genome was covered, respectively. These results demonstrated that sequencing of whole cellular DNA isolated from young leaves using the Illumina Genome Analyzer is an efficient method for high-throughput sequencing of chloroplast genome.
Structural analysis of a repetitive protein sequence motif in strepsirrhine primate amelogenin.

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Rodrigo S Lacruz

2011-03-01

Full Text Available Strepsirrhines are members of a primate suborder that has a distinctive set of features associated with the development of the dentition. Amelogenin (AMEL, the better known of the enamel matrix proteins, forms 90% of the secreted organic matrix during amelogenesis. Although AMEL has been sequenced in numerous mammalian lineages, the only reported strepsirrhine AMEL sequences are those of the ring-tailed lemur and galago, which contain a set of additional proline-rich tandem repeats absent in all other primates species analyzed to date, but present in some non-primate mammals. Here, we first determined that these repeats are present in AMEL from three additional lemur species and thus are likely to be widespread throughout this group. To evaluate the functional relevance of these repeats in strepsirrhines, we engineered a mutated murine amelogenin sequence containing a similar proline-rich sequence to that of Lemur catta. In the monomeric form, the MQP insertions had no influence on the secondary structure or refolding properties, whereas in the assembled form, the insertions increased the hydrodynamic radii. We speculate that increased AMEL nanosphere size may influence enamel formation in strepsirrhine primates.
An effective approach for annotation of protein families with low sequence similarity and conserved motifs: identifying GDSL hydrolases across the plant kingdom.

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Vujaklija, Ivan; Bielen, Ana; Paradžik, Tina; Biđin, Siniša; Goldstein, Pavle; Vujaklija, Dušica

2016-02-18

The massive accumulation of protein sequences arising from the rapid development of high-throughput sequencing, coupled with automatic annotation, results in high levels of incorrect annotations. In this study, we describe an approach to decrease annotation errors of protein families characterized by low overall sequence similarity. The GDSL lipolytic family comprises proteins with multifunctional properties and high potential for pharmaceutical and industrial applications. The number of proteins assigned to this family has increased rapidly over the last few years. In particular, the natural abundance of GDSL enzymes reported recently in plants indicates that they could be a good source of novel GDSL enzymes. We noticed that a significant proportion of annotated sequences lack specific GDSL motif(s) or catalytic residue(s). Here, we applied motif-based sequence analyses to identify enzymes possessing conserved GDSL motifs in selected proteomes across the plant kingdom. Motif-based HMM scanning (Viterbi decoding-VD and posterior decoding-PD) and the here described PD/VD protocol were successfully applied on 12 selected plant proteomes to identify sequences with GDSL motifs. A significant number of identified GDSL sequences were novel. Moreover, our scanning approach successfully detected protein sequences lacking at least one of the essential motifs (171/820) annotated by Pfam profile search (PfamA) as GDSL. Based on these analyses we provide a curated list of GDSL enzymes from the selected plants. CLANS clustering and phylogenetic analysis helped us to gain a better insight into the evolutionary relationship of all identified GDSL sequences. Three novel GDSL subfamilies as well as unreported variations in GDSL motifs were discovered in this study. In addition, analyses of selected proteomes showed a remarkable expansion of GDSL enzymes in the lycophyte, Selaginella moellendorffii. Finally, we provide a general motif-HMM scanner which is easily accessible through
A bumpy ride on the diagnostic bench of massive parallel sequencing, the case of the mitochondrial genome.

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Kim Vancampenhout

Full Text Available The advent of massive parallel sequencing (MPS has revolutionized the field of human molecular genetics, including the diagnostic study of mitochondrial (mt DNA dysfunction. The analysis of the complete mitochondrial genome using MPS platforms is now common and will soon outrun conventional sequencing. However, the development of a robust and reliable protocol is rather challenging. A previous pilot study for the re-sequencing of human mtDNA revealed an uneven coverage, affecting predominantly part of the plus strand. In an attempt to address this problem, we undertook a comparative study of standard and modified protocols for the Ion Torrent PGM system. We could not improve strand representation by altering the recommended shearing methodology of the standard workflow or omitting the DNA polymerase amplification step from the library construction process. However, we were able to associate coverage bias of the plus strand with a specific sequence motif. Additionally, we compared coverage and variant calling across technologies. The same samples were also sequenced on a MiSeq device which showed that coverage and heteroplasmic variant calling were much improved.
Refining the Results of a Classical SELEX Experiment by Expanding the Sequence Data Set of an Aptamer Pool Selected for Protein A

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Regina Stoltenburg

2018-02-01

Full Text Available New, as yet undiscovered aptamers for Protein A were identified by applying next generation sequencing (NGS to a previously selected aptamer pool. This pool was obtained in a classical SELEX (Systematic Evolution of Ligands by EXponential enrichment experiment using the FluMag-SELEX procedure followed by cloning and Sanger sequencing. PA#2/8 was identified as the only Protein A-binding aptamer from the Sanger sequence pool, and was shown to be able to bind intact cells of Staphylococcus aureus. In this study, we show the extension of the SELEX results by re-sequencing of the same aptamer pool using a medium throughput NGS approach and data analysis. Both data pools were compared. They confirm the selection of a highly complex and heterogeneous oligonucleotide pool and show consistently a high content of orphans as well as a similar relative frequency of certain sequence groups. But in contrast to the Sanger data pool, the NGS pool was clearly dominated by one sequence group containing the known Protein A-binding aptamer PA#2/8 as the most frequent sequence in this group. In addition, we found two new sequence groups in the NGS pool represented by PA-C10 and PA-C8, respectively, which also have high specificity for Protein A. Comparative affinity studies reveal differences between the aptamers and confirm that PA#2/8 remains the most potent sequence within the selected aptamer pool reaching affinities in the low nanomolar range of KD = 20 ± 1 nM.
Refining the Results of a Classical SELEX Experiment by Expanding the Sequence Data Set of an Aptamer Pool Selected for Protein A.

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Stoltenburg, Regina; Strehlitz, Beate

2018-02-24

New, as yet undiscovered aptamers for Protein A were identified by applying next generation sequencing (NGS) to a previously selected aptamer pool. This pool was obtained in a classical SELEX (Systematic Evolution of Ligands by EXponential enrichment) experiment using the FluMag-SELEX procedure followed by cloning and Sanger sequencing. PA#2/8 was identified as the only Protein A-binding aptamer from the Sanger sequence pool, and was shown to be able to bind intact cells of Staphylococcus aureus . In this study, we show the extension of the SELEX results by re-sequencing of the same aptamer pool using a medium throughput NGS approach and data analysis. Both data pools were compared. They confirm the selection of a highly complex and heterogeneous oligonucleotide pool and show consistently a high content of orphans as well as a similar relative frequency of certain sequence groups. But in contrast to the Sanger data pool, the NGS pool was clearly dominated by one sequence group containing the known Protein A-binding aptamer PA#2/8 as the most frequent sequence in this group. In addition, we found two new sequence groups in the NGS pool represented by PA-C10 and PA-C8, respectively, which also have high specificity for Protein A. Comparative affinity studies reveal differences between the aptamers and confirm that PA#2/8 remains the most potent sequence within the selected aptamer pool reaching affinities in the low nanomolar range of K D = 20 ± 1 nM.
Less is More: Membrane Protein Digestion Beyond Urea–Trypsin Solution for Next-level Proteomics*

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Zhang, Xi

2015-01-01

The goal of next-level bottom-up membrane proteomics is protein function investigation, via high-coverage high-throughput peptide-centric quantitation of expression, modifications and dynamic structures at systems scale. Yet efficient digestion of mammalian membrane proteins presents a daunting barrier, and prevalent day-long urea–trypsin in-solution digestion proved insufficient to reach this goal. Many efforts contributed incremental advances over past years, but involved protein denaturation that disconnected measurement from functional states. Beyond denaturation, the recent discovery of structure/proteomics omni-compatible detergent n-dodecyl-β-d-maltopyranoside, combined with pepsin and PNGase F columns, enabled breakthroughs in membrane protein digestion: a 2010 DDM-low-TCEP (DLT) method for H/D-exchange (HDX) using human G protein-coupled receptor, and a 2015 flow/detergent-facilitated protease and de-PTM digestions (FDD) for integrative deep sequencing and quantitation using full-length human ion channel complex. Distinguishing protein solubilization from denaturation, protease digestion reliability from theoretical specificity, and reduction from alkylation, these methods shifted day(s)-long paradigms into minutes, and afforded fully automatable (HDX)-protein-peptide-(tandem mass tag)-HPLC pipelines to instantly measure functional proteins at deep coverage, high peptide reproducibility, low artifacts and minimal leakage. Promoting—not destroying—structures and activities harnessed membrane proteins for the next-level streamlined functional proteomics. This review analyzes recent advances in membrane protein digestion methods and highlights critical discoveries for future proteomics. PMID:26081834
Less is More: Membrane Protein Digestion Beyond Urea-Trypsin Solution for Next-level Proteomics.

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Zhang, Xi

2015-09-01

The goal of next-level bottom-up membrane proteomics is protein function investigation, via high-coverage high-throughput peptide-centric quantitation of expression, modifications and dynamic structures at systems scale. Yet efficient digestion of mammalian membrane proteins presents a daunting barrier, and prevalent day-long urea-trypsin in-solution digestion proved insufficient to reach this goal. Many efforts contributed incremental advances over past years, but involved protein denaturation that disconnected measurement from functional states. Beyond denaturation, the recent discovery of structure/proteomics omni-compatible detergent n-dodecyl-β-d-maltopyranoside, combined with pepsin and PNGase F columns, enabled breakthroughs in membrane protein digestion: a 2010 DDM-low-TCEP (DLT) method for H/D-exchange (HDX) using human G protein-coupled receptor, and a 2015 flow/detergent-facilitated protease and de-PTM digestions (FDD) for integrative deep sequencing and quantitation using full-length human ion channel complex. Distinguishing protein solubilization from denaturation, protease digestion reliability from theoretical specificity, and reduction from alkylation, these methods shifted day(s)-long paradigms into minutes, and afforded fully automatable (HDX)-protein-peptide-(tandem mass tag)-HPLC pipelines to instantly measure functional proteins at deep coverage, high peptide reproducibility, low artifacts and minimal leakage. Promoting-not destroying-structures and activities harnessed membrane proteins for the next-level streamlined functional proteomics. This review analyzes recent advances in membrane protein digestion methods and highlights critical discoveries for future proteomics. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.
Sequence, structure and function relationships in flaviviruses as assessed by evolutive aspects of its conserved non-structural protein domains.

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da Fonseca, Néli José; Lima Afonso, Marcelo Querino; Pedersolli, Natan Gonçalves; de Oliveira, Lucas Carrijo; Andrade, Dhiego Souto; Bleicher, Lucas

2017-10-28

Flaviviruses are responsible for serious diseases such as dengue, yellow fever, and zika fever. Their genomes encode a polyprotein which, after cleavage, results in three structural and seven non-structural proteins. Homologous proteins can be studied by conservation and coevolution analysis as detected in multiple sequence alignments, usually reporting positions which are strictly necessary for the structure and/or function of all members in a protein family or which are involved in a specific sub-class feature requiring the coevolution of residue sets. This study provides a complete conservation and coevolution analysis on all flaviviruses non-structural proteins, with results mapped on all well-annotated available sequences. A literature review on the residues found in the analysis enabled us to compile available information on their roles and distribution among different flaviviruses. Also, we provide the mapping of conserved and coevolved residues for all sequences currently in SwissProt as a supplementary material, so that particularities in different viruses can be easily analyzed. Copyright © 2017 Elsevier Inc. All rights reserved.
Top-Down-Assisted Bottom-Up Method for Homologous Protein Sequencing: Hemoglobin from 33 Bird Species

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Song, Yang; Laskay, Ünige A.; Vilcins, Inger-Marie E.; Barbour, Alan G.; Wysocki, Vicki H.

2015-11-01

Ticks are vectors for disease transmission because they are indiscriminant in their feeding on multiple vertebrate hosts, transmitting pathogens between their hosts. Identifying the hosts on which ticks have fed is important for disease prevention and intervention. We have previously shown that hemoglobin (Hb) remnants from a host on which a tick fed can be used to reveal the host's identity. For the present research, blood was collected from 33 bird species that are common in the U.S. as hosts for ticks but that have unknown Hb sequences. A top-down-assisted bottom-up mass spectrometry approach with a customized searching database, based on variability in known bird hemoglobin sequences, has been devised to facilitate fast and complete sequencing of hemoglobin from birds with unknown sequences. These hemoglobin sequences will be added to a hemoglobin database and used for tick host identification. The general approach has the potential to sequence any set of homologous proteins completely in a rapid manner.
Combination of Multiple Spectral Libraries Improves the Current Search Methods Used to Identify Missing Proteins in the Chromosome-Centric Human Proteome Project.

Science.gov (United States)

Cho, Jin-Young; Lee, Hyoung-Joo; Jeong, Seul-Ki; Kim, Kwang-Youl; Kwon, Kyung-Hoon; Yoo, Jong Shin; Omenn, Gilbert S; Baker, Mark S; Hancock, William S; Paik, Young-Ki

2015-12-04

Approximately 2.9 billion long base-pair human reference genome sequences are known to encode some 20 000 representative proteins. However, 3000 proteins, that is, ~15% of all proteins, have no or very weak proteomic evidence and are still missing. Missing proteins may be present in rare samples in very low abundance or be only temporarily expressed, causing problems in their detection and protein profiling. In particular, some technical limitations cause missing proteins to remain unassigned. For example, current mass spectrometry techniques have high limits and error rates for the detection of complex biological samples. An insufficient proteome coverage in a reference sequence database and spectral library also raises major issues. Thus, the development of a better strategy that results in greater sensitivity and accuracy in the search for missing proteins is necessary. To this end, we used a new strategy, which combines a reference spectral library search and a simulated spectral library search, to identify missing proteins. We built the human iRefSPL, which contains the original human reference spectral library and additional peptide sequence-spectrum match entries from other species. We also constructed the human simSPL, which contains the simulated spectra of 173 907 human tryptic peptides determined by MassAnalyzer (version 2.3.1). To prove the enhanced analytical performance of the combination of the human iRefSPL and simSPL methods for the identification of missing proteins, we attempted to reanalyze the placental tissue data set (PXD000754). The data from each experiment were analyzed using PeptideProphet, and the results were combined using iProphet. For the quality control, we applied the class-specific false-discovery rate filtering method. All of the results were filtered at a false-discovery rate of libraries, iRefSPL and simSPL, were designed to ensure no overlap of the proteome coverage. They were shown to be complementary to spectral library
Draft genome sequencing of giardia intestinalis assemblage B isolate GS: is human giardiasis caused by two different species?

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Oscar Franzén

2009-08-01

Full Text Available Giardia intestinalis is a major cause of diarrheal disease worldwide and two major Giardia genotypes, assemblages A and B, infect humans. The genome of assemblage A parasite WB was recently sequenced, and the structurally compact 11.7 Mbp genome contains simplified basic cellular machineries and metabolism. We here performed 454 sequencing to 16x coverage of the assemblage B isolate GS, the only Giardia isolate successfully used to experimentally infect animals and humans. The two genomes show 77% nucleotide and 78% amino-acid identity in protein coding regions. Comparative analysis identified 28 unique GS and 3 unique WB protein coding genes, and the variable surface protein (VSP repertoires of the two isolates are completely different. The promoters of several enzymes involved in the synthesis of the cyst-wall lack binding sites for encystation-specific transcription factors in GS. Several synteny-breaks were detected and verified. The tetraploid GS genome shows higher levels of overall allelic sequence polymorphism (0.5 versus <0.01% in WB. The genomic differences between WB and GS may explain some of the observed biological and clinical differences between the two isolates, and it suggests that assemblage A and B Giardia can be two different species.
eMatchSite: sequence order-independent structure alignments of ligand binding pockets in protein models.

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Michal Brylinski

2014-09-01

Full Text Available Detecting similarities between ligand binding sites in the absence of global homology between target proteins has been recognized as one of the critical components of modern drug discovery. Local binding site alignments can be constructed using sequence order-independent techniques, however, to achieve a high accuracy, many current algorithms for binding site comparison require high-quality experimental protein structures, preferably in the bound conformational state. This, in turn, complicates proteome scale applications, where only various quality structure models are available for the majority of gene products. To improve the state-of-the-art, we developed eMatchSite, a new method for constructing sequence order-independent alignments of ligand binding sites in protein models. Large-scale benchmarking calculations using adenine-binding pockets in crystal structures demonstrate that eMatchSite generates accurate alignments for almost three times more protein pairs than SOIPPA. More importantly, eMatchSite offers a high tolerance to structural distortions in ligand binding regions in protein models. For example, the percentage of correctly aligned pairs of adenine-binding sites in weakly homologous protein models is only 4-9% lower than those aligned using crystal structures. This represents a significant improvement over other algorithms, e.g. the performance of eMatchSite in recognizing similar binding sites is 6% and 13% higher than that of SiteEngine using high- and moderate-quality protein models, respectively. Constructing biologically correct alignments using predicted ligand binding sites in protein models opens up the possibility to investigate drug-protein interaction networks for complete proteomes with prospective systems-level applications in polypharmacology and rational drug repositioning. eMatchSite is freely available to the academic community as a web-server and a stand-alone software distribution at http://www.brylinski.org/ematchsite.
Amino acid sequence analysis of the annexin super-gene family of proteins.

Science.gov (United States)

Barton, G J; Newman, R H; Freemont, P S; Crumpton, M J

1991-06-15

The annexins are a widespread family of calcium-dependent membrane-binding proteins. No common function has been identified for the family and, until recently, no crystallographic data existed for an annexin. In this paper we draw together 22 available annexin sequences consisting of 88 similar repeat units, and apply the techniques of multiple sequence alignment, pattern matching, secondary structure prediction and conservation analysis to the characterisation of the molecules. The analysis clearly shows that the repeats cluster into four distinct families and that greatest variation occurs within the repeat 3 units. Multiple alignment of the 88 repeats shows amino acids with conserved physicochemical properties at 22 positions, with only Gly at position 23 being absolutely conserved in all repeats. Secondary structure prediction techniques identify five conserved helices in each repeat unit and patterns of conserved hydrophobic amino acids are consistent with one face of a helix packing against the protein core in predicted helices a, c, d, e. Helix b is generally hydrophobic in all repeats, but contains a striking pattern of repeat-specific residue conservation at position 31, with Arg in repeats 4 and Glu in repeats 2, but unconserved amino acids in repeats 1 and 3. This suggests repeats 2 and 4 may interact via a buried saltbridge. The loop between predicted helices a and b of repeat 3 shows features distinct from the equivalent loop in repeats 1, 2 and 4, suggesting an important structural and/or functional role for this region. No compelling evidence emerges from this study for uteroglobin and the annexins sharing similar tertiary structures, or for uteroglobin representing a derivative of a primordial one-repeat structure that underwent duplication to give the present day annexins. The analyses performed in this paper are re-evaluated in the Appendix, in the light of the recently published X-ray structure for human annexin V. The structure confirms most of
Diversity of extracellular proteins during the transition from the ‘proto-apicomplexan’ alveolates to the apicomplexan obligate parasites

KAUST Repository

Templeton, Thomas J.; Pain, Arnab

2015-01-01

The recent completion of high-coverage draft genome sequences for several alveolate protozoans – namely, the chromerids, Chromera velia and Vitrella brassicaformis ; the perkinsid Perkinsus marinus ; the apicomplexan, Gregarina niphandrodes , as well as high coverage transcriptome sequence information for several colpodellids, allows for new genome-scale comparisons across a rich landscape of apicomplexans and other alveolates. Genome annotations can now be used to help interpret fine ultrastructure and cell biology, and guide new studies to describe a variety of alveolate life strategies, such as symbiosis or free living, predation, and obligate intracellular parasitism, as well to provide foundations to dissect the evolutionary transitions between these niches. This review focuses on the attempt to identify extracellular proteins which might mediate the physical interface of cell–cell interactions within the above life strategies, aided by annotation of the repertoires of predicted surface and secreted proteins encoded within alveolate genomes. In particular, we discuss what descriptions of the predicted extracellular proteomes reveal regarding a hypothetical last common ancestor of a pre-apicomplexan alveolate – guided by ultrastructure, life strategies and phylogenetic relationships – in an attempt to understand the evolution of obligate parasitism in apicomplexans.
Diversity of extracellular proteins during the transition from the ‘proto-apicomplexan’ alveolates to the apicomplexan obligate parasites

KAUST Repository

Templeton, Thomas J.

2015-11-20

The recent completion of high-coverage draft genome sequences for several alveolate protozoans – namely, the chromerids, Chromera velia and Vitrella brassicaformis ; the perkinsid Perkinsus marinus ; the apicomplexan, Gregarina niphandrodes , as well as high coverage transcriptome sequence information for several colpodellids, allows for new genome-scale comparisons across a rich landscape of apicomplexans and other alveolates. Genome annotations can now be used to help interpret fine ultrastructure and cell biology, and guide new studies to describe a variety of alveolate life strategies, such as symbiosis or free living, predation, and obligate intracellular parasitism, as well to provide foundations to dissect the evolutionary transitions between these niches. This review focuses on the attempt to identify extracellular proteins which might mediate the physical interface of cell–cell interactions within the above life strategies, aided by annotation of the repertoires of predicted surface and secreted proteins encoded within alveolate genomes. In particular, we discuss what descriptions of the predicted extracellular proteomes reveal regarding a hypothetical last common ancestor of a pre-apicomplexan alveolate – guided by ultrastructure, life strategies and phylogenetic relationships – in an attempt to understand the evolution of obligate parasitism in apicomplexans.
Label-Free Quantitative Analysis of Mitochondrial Proteomes Using the Multienzyme Digestion-Filter Aided Sample Preparation (MED-FASP) and "Total Protein Approach".

Science.gov (United States)

Wiśniewski, Jacek R

2017-01-01

Determination of proteome composition and measuring of changes in protein titers provide important information with a substantial value for studying mitochondria.This chapter describes a workflow for the quantitative analysis of mitochondrial proteome with a focus on sample preparation and quantitative analysis of the data. The workflow involves the multienzyme digestion-filter aided sample preparation (MED-FASP) protocol enabling efficient extraction of proteins and high rate of protein-to-peptide conversion. Consecutive protein digestion with Lys C and trypsin enables generation of peptide fractions with minimal overlap, largely increases the number of identified proteins, and extends their sequence coverage. Abundances of proteins identified by multiple peptides can be assessed by the "Total Protein Approach."
Comment on "Protein sequences from mastodon and Tyrannosaurus rex revealed by mass spectrometry".

Science.gov (United States)

Pevzner, Pavel A; Kim, Sangtae; Ng, Julio

2008-08-22

Asara et al. (Reports, 13 April 2007, p. 280) reported sequencing of Tyrannosaurus rex proteins and used them to establish the evolutionary relationships between birds and dinosaurs. We argue that the reported T. rex peptides may represent statistical artifacts and call for complete data release to enable experimental and computational verification of their findings.
Nucleotide sequence of the gene coding for human factor VII, a vitamin K-dependent protein participating in blood coagulation

International Nuclear Information System (INIS)

O'Hara, P.J.; Grant, F.J.; Haldeman, B.A.; Gray, C.L.; Insley, M.Y.; Hagen, F.S.; Murray, M.J.

1987-01-01

Activated factor VII (factor VIIa) is a vitamin K-dependent plasma serine protease that participates in a cascade of reactions leading to the coagulation of blood. Two overlapping genomic clones containing sequences encoding human factor VII were isolated and characterized. The complete sequence of the gene was determined and found to span about 12.8 kilobases. The mRNA for factor VII as demonstrated by cDNA cloning is polyadenylylated at multiple sites but contains only one AAUAAA poly(A) signal sequence. The mRNA can undergo alternative splicing, forming one transcript containing eight segments as exons and another with an additional exon that encodes a larger prepro leader sequence. The latter transcript has no known counterpart in the other vitamin K-dependent proteins. The positions of the introns with respect to the amino acid sequence encoded by the eight essential exons of factor VII are the same as those present in factor IX, factor X, protein C, and the first three exons of prothrombin. These exons code for domains generally conserved among members of this gene family. The comparable introns in these genes, however, are dissimilar with respect to size and sequence, with the exception of intron C in factor VII and protein C. The gene for factor VII also contains five regions made up of tandem repeats of oligonucleotide monomer elements. More than a quarter of the intron sequences and more than a third of the 3' untranslated portion of the mRNA transcript consist of these minisatellite tandem repeats
Pleiotropy constrains the evolution of protein but not regulatory sequences in a transcription regulatory network influencing complex social behaviours

Directory of Open Access Journals (Sweden)

Daria eMolodtsova

2014-12-01

Full Text Available It is increasingly apparent that genes and networks that influence complex behaviour are evolutionary conserved, which is paradoxical considering that behaviour is labile over evolutionary timescales. How does adaptive change in behaviour arise if behaviour is controlled by conserved, pleiotropic, and likely evolutionary constrained genes? Pleiotropy and connectedness are known to constrain the general rate of protein evolution, prompting some to suggest that the evolution of complex traits, including behaviour, is fuelled by regulatory sequence evolution. However, we seldom have data on the strength of selection on mutations in coding and regulatory sequences, and this hinders our ability to study how pleiotropy influences coding and regulatory sequence evolution. Here we use population genomics to estimate the strength of selection on coding and regulatory mutations for a transcriptional regulatory network that influences complex behaviour of honey bees. We found that replacement mutations in highly connected transcription factors and target genes experience significantly stronger negative selection relative to weakly connected transcription factors and targets. Adaptively evolving proteins were significantly more likely to reside at the periphery of the regulatory network, while proteins with signs of negative selection were near the core of the network. Interestingly, connectedness and network structure had minimal influence on the strength of selection on putative regulatory sequences for both transcription factors and their targets. Our study indicates that adaptive evolution of complex behaviour can arise because of positive selection on protein-coding mutations in peripheral genes, and on regulatory sequence mutations in both transcription factors and their targets throughout the network.

[Complete genome sequencing and sequence analysis of BCG Tice].

Science.gov (United States)

Wang, Zhiming; Pan, Yuanlong; Wu, Jun; Zhu, Baoli

2012-10-04

The objective of this study is to obtain the complete genome sequence of Bacillus Calmette-Guerin Tice (BCG Tice), in order to provide more information about the molecular biology of BCG Tice and design more reasonable vaccines to prevent tuberculosis. We assembled the data from high-throughput sequencing with SOAPdenovo software, with many contigs and scaffolds obtained. There are many sequence gaps and physical gaps remained as a result of regional low coverage and low quality. We designed primers at the end of contigs and performed PCR amplification in order to link these contigs and scaffolds. With various enzymes to perform PCR amplification, adjustment of PCR reaction conditions, and combined with clone construction to sequence, all the gaps were finished. We obtained the complete genome sequence of BCG Tice and submitted it to GenBank of National Center for Biotechnology Information (NCBI). The genome of BCG Tice is 4334064 base pairs in length, with GC content 65.65%. The problems and strategies during the finishing step of BCG Tice sequencing are illuminated here, with the hope of affording some experience to those who are involved in the finishing step of genome sequencing. The microarray data were verified by our results.
Comparison of whole genome amplification techniques for human single cell exome sequencing.

Science.gov (United States)

Borgström, Erik; Paterlini, Marta; Mold, Jeff E; Frisen, Jonas; Lundeberg, Joakim

2017-01-01

Whole genome amplification (WGA) is currently a prerequisite for single cell whole genome or exome sequencing. Depending on the method used the rate of artifact formation, allelic dropout and sequence coverage over the genome may differ significantly. The largest difference between the evaluated protocols was observed when analyzing the target coverage and read depth distribution. These differences also had impact on the downstream variant calling. Conclusively, the products from the AMPLI1 and MALBAC kits were shown to be most similar to the bulk samples and are therefore recommended for WGA of single cells. In this study four commercial kits for WGA (AMPLI1, MALBAC, Repli-G and PicoPlex) were used to amplify human single cells. The WGA products were exome sequenced together with non-amplified bulk samples from the same source. The resulting data was evaluated in terms of genomic coverage, allelic dropout and SNP calling.
High throughput sequencing and proteomics to identify immunogenic proteins of a new pathogen: the dirty genome approach.

Science.gov (United States)

Greub, Gilbert; Kebbi-Beghdadi, Carole; Bertelli, Claire; Collyn, François; Riederer, Beat M; Yersin, Camille; Croxatto, Antony; Raoult, Didier

2009-12-23

With the availability of new generation sequencing technologies, bacterial genome projects have undergone a major boost. Still, chromosome completion needs a costly and time-consuming gap closure, especially when containing highly repetitive elements. However, incomplete genome data may be sufficiently informative to derive the pursued information. For emerging pathogens, i.e. newly identified pathogens, lack of release of genome data during gap closure stage is clearly medically counterproductive. We thus investigated the feasibility of a dirty genome approach, i.e. the release of unfinished genome sequences to develop serological diagnostic tools. We showed that almost the whole genome sequence of the emerging pathogen Parachlamydia acanthamoebae was retrieved even with relatively short reads from Genome Sequencer 20 and Solexa. The bacterial proteome was analyzed to select immunogenic proteins, which were then expressed and used to elaborate the first steps of an ELISA. This work constitutes the proof of principle for a dirty genome approach, i.e. the use of unfinished genome sequences of pathogenic bacteria, coupled with proteomics to rapidly identify new immunogenic proteins useful to develop in the future specific diagnostic tests such as ELISA, immunohistochemistry and direct antigen detection. Although applied here to an emerging pathogen, this combined dirty genome sequencing/proteomic approach may be used for any pathogen for which better diagnostics are needed. These genome sequences may also be very useful to develop DNA based diagnostic tests. All these diagnostic tools will allow further evaluations of the pathogenic potential of this obligate intracellular bacterium.
Automation of C-terminal sequence analysis of 2D-PAGE separated proteins

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P.P. Moerman

2014-06-01

Full Text Available Experimental assignment of the protein termini remains essential to define the functional protein structure. Here, we report on the improvement of a proteomic C-terminal sequence analysis method. The approach aims to discriminate the C-terminal peptide in a CNBr-digest where Met-Xxx peptide bonds are cleaved in internal peptides ending at a homoserine lactone (hsl-derivative. pH-dependent partial opening of the lactone ring results in the formation of doublets for all internal peptides. C-terminal peptides are distinguished as singlet peaks by MALDI-TOF MS and MS/MS is then used for their identification. We present a fully automated protocol established on a robotic liquid-handling station.
A Targeted Enrichment Strategy for Massively Parallel Sequencing of Angiosperm Plastid Genomes

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Gregory W. Stull

2013-02-01

Full Text Available Premise of the study: We explored a targeted enrichment strategy to facilitate rapid and low-cost next-generation sequencing (NGS of numerous complete plastid genomes from across the phylogenetic breadth of angiosperms. Methods and Results: A custom RNA probe set including the complete sequences of 22 previously sequenced eudicot plastomes was designed to facilitate hybridization-based targeted enrichment of eudicot plastid genomes. Using this probe set and an Agilent SureSelect targeted enrichment kit, we conducted an enrichment experiment including 24 angiosperms (22 eudicots, two monocots, which were subsequently sequenced on a single lane of the Illumina GAIIx with single-end, 100-bp reads. This approach yielded nearly complete to complete plastid genomes with exceptionally high coverage (mean coverage: 717×, even for the two monocots. Conclusions: Our enrichment experiment was highly successful even though many aspects of the capture process employed were suboptimal. Hence, significant improvements to this methodology are feasible. With this general approach and probe set, it should be possible to sequence more than 300 essentially complete plastid genomes in a single Illumina GAIIx lane (achieving 50× mean coverage. However, given the complications of pooling numerous samples for multiplex sequencing and the limited number of barcodes (e.g., 96 available in commercial kits, we recommend 96 samples as a current practical maximum for multiplex plastome sequencing. This high-throughput approach should facilitate large-scale plastid genome sequencing at any level of phylogenetic diversity in angiosperms.
Medicare Coverage Database

Data.gov (United States)

U.S. Department of Health & Human Services — The Medicare Coverage Database (MCD) contains all National Coverage Determinations (NCDs) and Local Coverage Determinations (LCDs), local articles, and proposed NCD...
SVM-PB-Pred: SVM based protein block prediction method using sequence profiles and secondary structures.

Science.gov (United States)

Suresh, V; Parthasarathy, S

2014-01-01

We developed a support vector machine based web server called SVM-PB-Pred, to predict the Protein Block for any given amino acid sequence. The input features of SVM-PB-Pred include i) sequence profiles (PSSM) and ii) actual secondary structures (SS) from DSSP method or predicted secondary structures from NPS@ and GOR4 methods. There were three combined input features PSSM+SS(DSSP), PSSM+SS(NPS@) and PSSM+SS(GOR4) used to test and train the SVM models. Similarly, four datasets RS90, DB433, LI1264 and SP1577 were used to develop the SVM models. These four SVM models developed were tested using three different benchmarking tests namely; (i) self consistency, (ii) seven fold cross validation test and (iii) independent case test. The maximum possible prediction accuracy of ~70% was observed in self consistency test for the SVM models of both LI1264 and SP1577 datasets, where PSSM+SS(DSSP) input features was used to test. The prediction accuracies were reduced to ~53% for PSSM+SS(NPS@) and ~43% for PSSM+SS(GOR4) in independent case test, for the SVM models of above two same datasets. Using our method, it is possible to predict the protein block letters for any query protein sequence with ~53% accuracy, when the SP1577 dataset and predicted secondary structure from NPS@ server were used. The SVM-PB-Pred server can be freely accessed through http://bioinfo.bdu.ac.in/~svmpbpred.
Transduplication resulted in the incorporation of two protein-coding sequences into the Turmoil-1 transposable element of C. elegans

Directory of Open Access Journals (Sweden)

Pupko Tal

2008-10-01

Full Text Available Abstract Transposable elements may acquire unrelated gene fragments into their sequences in a process called transduplication. Transduplication of protein-coding genes is common in plants, but is unknown of in animals. Here, we report that the Turmoil-1 transposable element in C. elegans has incorporated two protein-coding sequences into its inverted terminal repeat (ITR sequences. The ITRs of Turmoil-1 contain a conserved RNA recognition motif (RRM that originated from the rsp-2 gene and a fragment from the protein-coding region of the cpg-3 gene. We further report that an open reading frame specific to C. elegans may have been created as a result of a Turmoil-1 insertion. Mutations at the 5' splice site of this open reading frame may have reactivated the transduplicated RRM motif. Reviewers This article was reviewed by Dan Graur and William Martin. For the full reviews, please go to the Reviewers' Reports section.
HP-Lattice QSAR for dynein proteins: experimental proteomics (2D-electrophoresis, mass spectrometry) and theoretic study of a Leishmania infantum sequence.

Science.gov (United States)

Dea-Ayuela, María Auxiliadora; Pérez-Castillo, Yunierkis; Meneses-Marcel, Alfredo; Ubeira, Florencio M; Bolas-Fernández, Francisco; Chou, Kuo-Chen; González-Díaz, Humberto

2008-08-15

The toxicity and inefficacy of actual organic drugs against Leishmaniosis justify research projects to find new molecular targets in Leishmania species including Leishmania infantum (L. infantum) and Leishmaniamajor (L. major), both important pathogens. In this sense, quantitative structure-activity relationship (QSAR) methods, which are very useful in Bioorganic and Medicinal Chemistry to discover small-sized drugs, may help to identify not only new drugs but also new drug targets, if we apply them to proteins. Dyneins are important proteins of these parasites governing fundamental processes such as cilia and flagella motion, nuclear migration, organization of the mitotic splinde, and chromosome separation during mitosis. However, despite the interest for them as potential drug targets, so far there has been no report whatsoever on dyneins with QSAR techniques. To the best of our knowledge, we report here the first QSAR for dynein proteins. We used as input the Spectral Moments of a Markov matrix associated to the HP-Lattice Network of the protein sequence. The data contain 411 protein sequences of different species selected by ClustalX to develop a QSAR that correctly discriminates on average between 92.75% and 92.51% of dyneins and other proteins in four different train and cross-validation datasets. We also report a combined experimental and theoretic study of a new dynein sequence in order to illustrate the utility of the model to search for potential drug targets with a practical example. First, we carried out a 2D-electrophoresis analysis of L. infantum biological samples. Next, we excised from 2D-E gels one spot of interest belonging to an unknown protein or protein fragment in the region Mdata base with the highest similarity score to the MS of the protein isolated from L. infantum. We used the QSAR model to predict the new sequence as dynein with probability of 99.99% without relying upon alignment. In order to confirm the previous function annotation we
Quantification of massively parallel sequencing libraries - a comparative study of eight methods

DEFF Research Database (Denmark)

Hussing, Christian; Kampmann, Marie-Louise; Mogensen, Helle Smidt

2018-01-01

Quantification of massively parallel sequencing libraries is important for acquisition of monoclonal beads or clusters prior to clonal amplification and to avoid large variations in library coverage when multiple samples are included in one sequencing analysis. No gold standard for quantification...... estimates followed by Qubit and electrophoresis-based instruments (Bioanalyzer, TapeStation, GX Touch, and Fragment Analyzer), while SYBR Green and TaqMan based qPCR assays gave the lowest estimates. qPCR gave more accurate predictions of sequencing coverage than Qubit and TapeStation did. Costs, time......-consumption, workflow simplicity, and ability to quantify multiple samples are discussed. Technical specifications, advantages, and disadvantages of the various methods are pointed out....
Sequence Variation in Rhoptry Neck Protein 10 Gene among Toxoplasma gondii Isolates from Different Hosts and Geographical Locations

Directory of Open Access Journals (Sweden)

Yu ZHAO

2017-09-01

Full Text Available Background: Toxoplasma gondii, as a eukaryotic parasite of the phylum Apicomplexa, can infect almost all the warm-blooded animals and humans, causing toxoplasmosis. Rhoptry neck proteins (RONs play a key role in the invasion process of T. gondii and are potential vaccine candidate molecules against toxoplasmosis.Methods: The present study examined sequence variation in the rhoptry neck protein 10 (TgRON10 gene among 10 T. gondii isolates from different hosts and geographical locations from Lanzhou province during 2014, and compared with the corresponding sequences of strains ME49 and VEG obtained from the ToxoDB database, using polymerase chain reaction (PCR amplification, sequence analysis, and phylogenetic reconstruction by Bayesian inference (BI and maximum parsimony (MP. Results: Analysis of all the 12 TgRON10 genomic and cDNA sequences revealed 7 exons and 6 introns in the TgRON10 gDNA. The complete genomic sequence of the TgRON10 gene ranged from 4759 bp to 4763 bp, and sequence variation was 0-0.6% among the 12 T. gondii isolates, indicating a low sequence variation in TgRON10 gene. Phylogenetic analysis of TgRON10 sequences showed that the cluster of the 12 T. gondii isolates was not completely consistent with their respective genotypes.Conclusion: TgRON10 gene is not a suitable genetic marker for the differentiation of T. gondii isolates from different hosts and geographical locations, but may represent a potential vaccine candidate against toxoplasmosis, worth further studies.
Sequence Variation in Rhoptry Neck Protein 10 Gene among Toxoplasma gondii Isolates from Different Hosts and Geographical Locations.

Science.gov (United States)

Zhao, Yu; Zhou, Donghui; Chen, Jia; Sun, Xiaolin

2017-01-01

Toxoplasma gondii, as a eukaryotic parasite of the phylum Apicomplexa, can infect almost all the warm-blooded animals and humans, causing toxoplasmosis. Rhoptry neck proteins (RONs) play a key role in the invasion process of T. gondii and are potential vaccine candidate molecules against toxoplasmosis. The present study examined sequence variation in the rhoptry neck protein 10 (TgRON10) gene among 10 T. gondii isolates from different hosts and geographical locations from Lanzhou province during 2014, and compared with the corresponding sequences of strains ME49 and VEG obtained from the ToxoDB database, using polymerase chain reaction (PCR) amplification, sequence analysis, and phylogenetic reconstruction by Bayesian inference (BI) and maximum parsimony (MP). Analysis of all the 12 TgRON10 genomic and cDNA sequences revealed 7 exons and 6 introns in the TgRON10 gDNA. The complete genomic sequence of the TgRON10 gene ranged from 4759 bp to 4763 bp, and sequence variation was 0-0.6% among the 12 T. gondii isolates, indicating a low sequence variation in TgRON10 gene. Phylogenetic analysis of TgRON10 sequences showed that the cluster of the 12 T. gondii isolates was not completely consistent with their respective genotypes. TgRON10 gene is not a suitable genetic marker for the differentiation of T. gondii isolates from different hosts and geographical locations, but may represent a potential vaccine candidate against toxoplasmosis, worth further studies.
Characterization of bud emergence 46 (BEM46) protein: Sequence, structural, phylogenetic and subcellular localization analyses

International Nuclear Information System (INIS)

Kumar, Abhishek; Kollath-Leiß, Krisztina; Kempken, Frank

2013-01-01

Highlights: •All eukaryotes have at least a single copy of a bem46 ortholog. •The catalytic triad of BEM46 is illustrated using sequence and structural analysis. •We identified indels in the conserved domain of BEM46 protein. •Localization studies of BEM46 protein were carried out using GFP-fusion tagging. -- Abstract: The bud emergence 46 (BEM46) protein from Neurospora crassa belongs to the α/β-hydrolase superfamily. Recently, we have reported that the BEM46 protein is localized in the perinuclear ER and also forms spots close by the plasma membrane. The protein appears to be required for cell type-specific polarity formation in N. crassa. Furthermore, initial studies suggested that the BEM46 amino acid sequence is conserved in eukaryotes and is considered to be one of the widespread conserved “known unknown” eukaryotic genes. This warrants for a comprehensive phylogenetic analysis of this superfamily to unravel origin and molecular evolution of these genes in different eukaryotes. Herein, we observe that all eukaryotes have at least a single copy of a bem46 ortholog. Upon scanning of these proteins in various genomes, we find that there are expansions leading into several paralogs in vertebrates. Usingcomparative genomic analyses, we identified insertion/deletions (indels) in the conserved domain of BEM46 protein, which allow to differentiate fungal classes such as ascomycetes from basidiomycetes. We also find that exonic indels are able to differentiate BEM46 homologs of different eukaryotic lineage. Furthermore, we unravel that BEM46 protein from N. crassa possess a novel endoplasmic-retention signal (PEKK) using GFP-fusion tagging experiments. We propose that three residues namely a serine 188S, a histidine 292H and an aspartic acid 262D are most critical residues, forming a catalytic triad in BEM46 protein from N. crassa. We carried out a comprehensive study on bem46 genes from a molecular evolution perspective with combination of functional
Characterization of bud emergence 46 (BEM46) protein: Sequence, structural, phylogenetic and subcellular localization analyses

Energy Technology Data Exchange (ETDEWEB)

Kumar, Abhishek; Kollath-Leiß, Krisztina; Kempken, Frank, E-mail: fkempken@bot.uni-kiel.de

2013-08-30

Highlights: •All eukaryotes have at least a single copy of a bem46 ortholog. •The catalytic triad of BEM46 is illustrated using sequence and structural analysis. •We identified indels in the conserved domain of BEM46 protein. •Localization studies of BEM46 protein were carried out using GFP-fusion tagging. -- Abstract: The bud emergence 46 (BEM46) protein from Neurospora crassa belongs to the α/β-hydrolase superfamily. Recently, we have reported that the BEM46 protein is localized in the perinuclear ER and also forms spots close by the plasma membrane. The protein appears to be required for cell type-specific polarity formation in N. crassa. Furthermore, initial studies suggested that the BEM46 amino acid sequence is conserved in eukaryotes and is considered to be one of the widespread conserved “known unknown” eukaryotic genes. This warrants for a comprehensive phylogenetic analysis of this superfamily to unravel origin and molecular evolution of these genes in different eukaryotes. Herein, we observe that all eukaryotes have at least a single copy of a bem46 ortholog. Upon scanning of these proteins in various genomes, we find that there are expansions leading into several paralogs in vertebrates. Usingcomparative genomic analyses, we identified insertion/deletions (indels) in the conserved domain of BEM46 protein, which allow to differentiate fungal classes such as ascomycetes from basidiomycetes. We also find that exonic indels are able to differentiate BEM46 homologs of different eukaryotic lineage. Furthermore, we unravel that BEM46 protein from N. crassa possess a novel endoplasmic-retention signal (PEKK) using GFP-fusion tagging experiments. We propose that three residues namely a serine 188S, a histidine 292H and an aspartic acid 262D are most critical residues, forming a catalytic triad in BEM46 protein from N. crassa. We carried out a comprehensive study on bem46 genes from a molecular evolution perspective with combination of functional
Analysis of quality raw data of second generation sequencers with Quality Assessment Software.

Science.gov (United States)

Ramos, Rommel Tj; Carneiro, Adriana R; Baumbach, Jan; Azevedo, Vasco; Schneider, Maria Pc; Silva, Artur

2011-04-18

Second generation technologies have advantages over Sanger; however, they have resulted in new challenges for the genome construction process, especially because of the small size of the reads, despite the high degree of coverage. Independent of the program chosen for the construction process, DNA sequences are superimposed, based on identity, to extend the reads, generating contigs; mismatches indicate a lack of homology and are not included. This process improves our confidence in the sequences that are generated. We developed Quality Assessment Software, with which one can review graphs showing the distribution of quality values from the sequencing reads. This software allow us to adopt more stringent quality standards for sequence data, based on quality-graph analysis and estimated coverage after applying the quality filter, providing acceptable sequence coverage for genome construction from short reads. Quality filtering is a fundamental step in the process of constructing genomes, as it reduces the frequency of incorrect alignments that are caused by measuring errors, which can occur during the construction process due to the size of the reads, provoking misassemblies. Application of quality filters to sequence data, using the software Quality Assessment, along with graphing analyses, provided greater precision in the definition of cutoff parameters, which increased the accuracy of genome construction.
Mass spectrometry compatible surfactant for optimized in-gel protein digestion.

Science.gov (United States)

Saveliev, Sergei V; Woodroofe, Carolyn C; Sabat, Grzegorz; Adams, Christopher M; Klaubert, Dieter; Wood, Keith; Urh, Marjeta

2013-01-15

Identification of proteins resolved by SDS-PAGE depends on robust in-gel protein digestion and efficient peptide extraction, requirements that are often difficult to achieve. A lengthy and laborious procedure is an additional challenge of protein identification in gel. We show here that with the use of the mass spectrometry compatible surfactant sodium 3-((1-(furan-2-yl)undecyloxy)carbonylamino)propane-1-sulfonate, the challenges of in-gel protein digestion are effectively addressed. Peptide quantitation based on stable isotope labeling showed that the surfactant induced 1.5-2 fold increase in peptide recovery. Consequently, protein sequence coverage was increased by 20-30%, on average, and the number of identified proteins saw a substantial boost. The surfactant also accelerated the digestion process. Maximal in-gel digestion was achieved in as little as one hour, depending on incubation temperature, and peptides were readily recovered from gel eliminating the need for postdigestion extraction. This study shows that the surfactant provides an efficient means of improving protein identification in gel and streamlining the in-gel digestion procedure requiring no extra handling steps or special equipment.
Refining the Results of a Classical SELEX Experiment by Expanding the Sequence Data Set of an Aptamer Pool Selected for Protein A

OpenAIRE

Regina Stoltenburg; Beate Strehlitz

2018-01-01

New, as yet undiscovered aptamers for Protein A were identified by applying next generation sequencing (NGS) to a previously selected aptamer pool. This pool was obtained in a classical SELEX (Systematic Evolution of Ligands by EXponential enrichment) experiment using the FluMag-SELEX procedure followed by cloning and Sanger sequencing. PA#2/8 was identified as the only Protein A-binding aptamer from the Sanger sequence pool, and was shown to be able to bind intact cells of Staphylococcus aur...
Signatures of pleiotropy, economy and convergent evolution in a domain-resolved map of human-virus protein-protein interaction networks.

Directory of Open Access Journals (Sweden)

Sara Garamszegi

Full Text Available A central challenge in host-pathogen systems biology is the elucidation of general, systems-level principles that distinguish host-pathogen interactions from within-host interactions. Current analyses of host-pathogen and within-host protein-protein interaction networks are largely limited by their resolution, treating proteins as nodes and interactions as edges. Here, we construct a domain-resolved map of human-virus and within-human protein-protein interaction networks by annotating protein interactions with high-coverage, high-accuracy, domain-centric interaction mechanisms: (1 domain-domain interactions, in which a domain in one protein binds to a domain in a second protein, and (2 domain-motif interactions, in which a domain in one protein binds to a short, linear peptide motif in a second protein. Analysis of these domain-resolved networks reveals, for the first time, significant mechanistic differences between virus-human and within-human interactions at the resolution of single domains. While human proteins tend to compete with each other for domain binding sites by means of sequence similarity, viral proteins tend to compete with human proteins for domain binding sites in the absence of sequence similarity. Independent of their previously established preference for targeting human protein hubs, viral proteins also preferentially target human proteins containing linear motif-binding domains. Compared to human proteins, viral proteins participate in more domain-motif interactions, target more unique linear motif-binding domains per residue, and contain more unique linear motifs per residue. Together, these results suggest that viruses surmount genome size constraints by convergently evolving multiple short linear motifs in order to effectively mimic, hijack, and manipulate complex host processes for their survival. Our domain-resolved analyses reveal unique signatures of pleiotropy, economy, and convergent evolution in viral
Enhancing Protein Disulfide Bond Cleavage by UV Excitation and Electron Capture Dissociation for Top-Down Mass Spectrometry

OpenAIRE

Wongkongkathep, Piriya; Li, Huilin; Zhang, Xing; Loo, Rachel R. Ogorzalek; Julian, Ryan R.; Loo, Joseph A.

2015-01-01

The application of ion pre-activation with 266 nm ultraviolet (UV) laser irradiation combined with electron capture dissociation (ECD) is demonstrated to enhance top-down mass spectrometry sequence coverage of disulfide bond containing proteins. UV-based activation can homolytically cleave a disulfide bond to yield two separated thiol radicals. Activated ECD experiments of insulin and ribonuclease A containing three and four disulfide bonds, respectively, were performed. UV-activation in comb...
Trypsin immobilization in ordered porous polymer membranes for effective protein digestion

International Nuclear Information System (INIS)

Qiao, Juan; Kim, Jin Yong; Wang, Yuan Yuan; Qi, Li; Wang, Fu Yi; Moon, Myeong Hee

2016-01-01

Fast and effective protein digestion is a vital process for mass spectrometry (MS) based protein analysis. This study introduces a porous polymer membrane enzyme reactor (PPMER) coupled to nanoflow liquid chromatography-tandem MS (nLC-ESI-MS/MS) for on-line digestion and analysis of proteins. Poly (styrene-co-maleic anhydride) (PS-co-MAn) was fabricated by the breath figure method to make a porous polymer membrane in which the MAn group was covalently bound to enzyme. Based on this strategy, microscale PPMER (μPPMER) was constructed for on-line connection with the nLC-ESI-MS/MS system. Its capability for enzymatic digestion with bovine serum albumin (BSA) was evaluated with varied digestion periods. The on-line proteolysis of BSA and subsequent analysis with μPPMER-nLC-ESI-MS/MS revealed that peptide sequence coverage increased from 10.3% (digestion time 10 min) to 89.1% (digestion time 30 min). μPPMER can efficiently digest proteins due to the microscopic confinement effect, showing its potential application in fast protein identification and protease immobilization. Applications of on-line digestion using μPPMER with human plasma and urinary proteome samples showed that the developed on-line method yielded equivalent or better performance in protein coverage and identified more membrane proteins than the in-solution method. This may be due to easy accommodation of hydrophobic membrane proteins within membrane pores. - Highlights: • A porous polymer membrane enzyme reactor was developed. • Breath figure method was used for the fabrication of porous polymer membrane. • The enzyme reactor was coupled to nLC-ESI-MS/MS for proteins on-line digestion.

Trypsin immobilization in ordered porous polymer membranes for effective protein digestion

Energy Technology Data Exchange (ETDEWEB)

Qiao, Juan [Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, No. 2 Zhongguancun Beiyijie, Beijing 100190 (China); Kim, Jin Yong [Department of Chemistry, Yonsei University, 50 Yonsei-ro, Seoul 120-749 (Korea, Republic of); Wang, Yuan Yuan [Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, No. 2 Zhongguancun Beiyijie, Beijing 100190 (China); Qi, Li, E-mail: qili@iccas.ac.cn [Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, No. 2 Zhongguancun Beiyijie, Beijing 100190 (China); Wang, Fu Yi [Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, No. 2 Zhongguancun Beiyijie, Beijing 100190 (China); Moon, Myeong Hee, E-mail: mhmoon@yonsei.ac.kr [Department of Chemistry, Yonsei University, 50 Yonsei-ro, Seoul 120-749 (Korea, Republic of)

2016-02-04

Fast and effective protein digestion is a vital process for mass spectrometry (MS) based protein analysis. This study introduces a porous polymer membrane enzyme reactor (PPMER) coupled to nanoflow liquid chromatography-tandem MS (nLC-ESI-MS/MS) for on-line digestion and analysis of proteins. Poly (styrene-co-maleic anhydride) (PS-co-MAn) was fabricated by the breath figure method to make a porous polymer membrane in which the MAn group was covalently bound to enzyme. Based on this strategy, microscale PPMER (μPPMER) was constructed for on-line connection with the nLC-ESI-MS/MS system. Its capability for enzymatic digestion with bovine serum albumin (BSA) was evaluated with varied digestion periods. The on-line proteolysis of BSA and subsequent analysis with μPPMER-nLC-ESI-MS/MS revealed that peptide sequence coverage increased from 10.3% (digestion time 10 min) to 89.1% (digestion time 30 min). μPPMER can efficiently digest proteins due to the microscopic confinement effect, showing its potential application in fast protein identification and protease immobilization. Applications of on-line digestion using μPPMER with human plasma and urinary proteome samples showed that the developed on-line method yielded equivalent or better performance in protein coverage and identified more membrane proteins than the in-solution method. This may be due to easy accommodation of hydrophobic membrane proteins within membrane pores. - Highlights: • A porous polymer membrane enzyme reactor was developed. • Breath figure method was used for the fabrication of porous polymer membrane. • The enzyme reactor was coupled to nLC-ESI-MS/MS for proteins on-line digestion.
Integrating genomic information with protein sequence and 3D atomic level structure at the RCSB protein data bank.

Science.gov (United States)

Prlic, Andreas; Kalro, Tara; Bhattacharya, Roshni; Christie, Cole; Burley, Stephen K; Rose, Peter W

2016-12-15

The Protein Data Bank (PDB) now contains more than 120,000 three-dimensional (3D) structures of biological macromolecules. To allow an interpretation of how PDB data relates to other publicly available annotations, we developed a novel data integration platform that maps 3D structural information across various datasets. This integration bridges from the human genome across protein sequence to 3D structure space. We developed novel software solutions for data management and visualization, while incorporating new libraries for web-based visualization using SVG graphics. The new views are available from http://www.rcsb.org and software is available from https://github.com/rcsb/. andreas.prlic@rcsb.orgSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.
A dimer of the lymphoid protein RAG1 recognizes the recombination signal sequence and the complex stably incorporates the high mobility group protein HMG2.

Science.gov (United States)

Rodgers, K K; Villey, I J; Ptaszek, L; Corbett, E; Schatz, D G; Coleman, J E

1999-07-15

RAG1 and RAG2 are the two lymphoid-specific proteins required for the cleavage of DNA sequences known as the recombination signal sequences (RSSs) flanking V, D or J regions of the antigen-binding genes. Previous studies have shown that RAG1 alone is capable of binding to the RSS, whereas RAG2 only binds as a RAG1/RAG2 complex. We have expressed recombinant core RAG1 (amino acids 384-1008) in Escherichia coli and demonstrated catalytic activity when combined with RAG2. This protein was then used to determine its oligomeric forms and the dissociation constant of binding to the RSS. Electrophoretic mobility shift assays show that up to three oligomeric complexes of core RAG1 form with a single RSS. Core RAG1 was found to exist as a dimer both when free in solution and as the minimal species bound to the RSS. Competition assays show that RAG1 recognizes both the conserved nonamer and heptamer sequences of the RSS. Zinc analysis shows the core to contain two zinc ions. The purified RAG1 protein overexpressed in E.coli exhibited the expected cleavage activity when combined with RAG2 purified from transfected 293T cells. The high mobility group protein HMG2 is stably incorporated into the recombinant RAG1/RSS complex and can increase the affinity of RAG1 for the RSS in the absence of RAG2.
Computational analysis of sequence selection mechanisms.

Science.gov (United States)

Meyerguz, Leonid; Grasso, Catherine; Kleinberg, Jon; Elber, Ron

2004-04-01

Mechanisms leading to gene variations are responsible for the diversity of species and are important components of the theory of evolution. One constraint on gene evolution is that of protein foldability; the three-dimensional shapes of proteins must be thermodynamically stable. We explore the impact of this constraint and calculate properties of foldable sequences using 3660 structures from the Protein Data Bank. We seek a selection function that receives sequences as input, and outputs survival probability based on sequence fitness to structure. We compute the number of sequences that match a particular protein structure with energy lower than the native sequence, the density of the number of sequences, the entropy, and the "selection" temperature. The mechanism of structure selection for sequences longer than 200 amino acids is approximately universal. For shorter sequences, it is not. We speculate on concrete evolutionary mechanisms that show this behavior.
Conservation in gene encoding Mycobacterium tuberculosis antigen Rv2660 and a high predicted population coverage of H56 multistage vaccine in South Africa.

Science.gov (United States)

Perez-Martinez, Angy P; Ong, Edison; Zhang, Lixin; Marrs, Carl F; He, Yongqun; Yang, Zhenhua

2017-11-01

H56/AERAS-456+IC31 (H56), composed of two early secretion proteins, Ag85B and ESAT-6, and a latency associated protein, Rv2660, and the IC31 Intercell adjuvant, is a new fusion subunit vaccine candidate designed to induce immunity against both new infection and reactivation of latent tuberculosis infection. Efficacy of subunit vaccines may be affected by the diversity of vaccine antigens among clinical strains and the extent of recognition by the diverse HLA molecules in the recipient population. Although a previous study showed the conservative nature of Ag85B- and ESAT-6-encoding genes, genetic diversity of Rv2660c that encodes RV2660 is largely unknown. The population coverage of H56 as a whole yet remains to be assessed. The present study was conducted to address these important knowledge gaps. DNA sequence analysis of Rv2660c found no variation among 83 of the 84 investigated clinical strains belonging to four genetic lineages. H56 was predicted to have as high as 99.6% population coverage in the South Africa population using the Immune Epitope Database (IEDB) Population Coverage Tool. Further comparison of H56 population coverage between South African Blacks and Caucasians based on the phenotypic frequencies of binding MHC Class I and Class II supertype alleles found that all of the nine MHC-I and six of eight MHC-II human leukocyte antigen (HLA) supertype alleles analyzed were significantly differentially expressed between the two subpopulations. This finding suggests the presence of race-specific functional binding motifs of MHC-I and MHC-II HLA alleles, which, in turn, highlights the importance of including diverse populations in vaccine clinical evaluation. In conclusion, H56 vaccine is predicted to have a promising population coverage in South Africa; this study demonstrates the utility of integrating comparative genomics and bioinformatics in bridging animal and clinical studies of novel TB vaccines. Copyright © 2017 Elsevier B.V. All rights reserved.
A protein with amino acid sequence homology to bovine insulin is present in the legume Vigna unguiculata (cowpea

Directory of Open Access Journals (Sweden)

Venâncio T.M.

2003-01-01

Full Text Available Since the discovery of bovine insulin in plants, much effort has been devoted to the characterization of these proteins and elucidation of their functions. We report here the isolation of a protein with similar molecular mass and same amino acid sequence to bovine insulin from developing fruits of cowpea (Vigna unguiculata genotype Epace 10. Insulin was measured by ELISA using an anti-human insulin antibody and was detected both in empty pods and seed coats but not in the embryo. The highest concentrations (about 0.5 ng/µg of protein of the protein were detected in seed coats at 16 and 18 days after pollination, and the values were 1.6 to 4.0 times higher than those found for isolated pods tested on any day. N-terminal amino acid sequencing of insulin was performed on the protein purified by C4-HPLC. The significance of the presence of insulin in these plant tissues is not fully understood but we speculate that it may be involved in the transport of carbohydrate to the fruit.
Dinoflagellate phylogeny as inferred from heat shock protein 90 and ribosomal gene sequences.

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Mona Hoppenrath

2010-10-01

Full Text Available Interrelationships among dinoflagellates in molecular phylogenies are largely unresolved, especially in the deepest branches. Ribosomal DNA (rDNA sequences provide phylogenetic signals only at the tips of the dinoflagellate tree. Two reasons for the poor resolution of deep dinoflagellate relationships using rDNA sequences are (1 most sites are relatively conserved and (2 there are different evolutionary rates among sites in different lineages. Therefore, alternative molecular markers are required to address the deeper phylogenetic relationships among dinoflagellates. Preliminary evidence indicates that the heat shock protein 90 gene (Hsp90 will provide an informative marker, mainly because this gene is relatively long and appears to have relatively uniform rates of evolution in different lineages.We more than doubled the previous dataset of Hsp90 sequences from dinoflagellates by generating additional sequences from 17 different species, representing seven different orders. In order to concatenate the Hsp90 data with rDNA sequences, we supplemented the Hsp90 sequences with three new SSU rDNA sequences and five new LSU rDNA sequences. The new Hsp90 sequences were generated, in part, from four additional heterotrophic dinoflagellates and the type species for six different genera. Molecular phylogenetic analyses resulted in a paraphyletic assemblage near the base of the dinoflagellate tree consisting of only athecate species. However, Noctiluca was never part of this assemblage and branched in a position that was nested within other lineages of dinokaryotes. The phylogenetic trees inferred from Hsp90 sequences were consistent with trees inferred from rDNA sequences in that the backbone of the dinoflagellate clade was largely unresolved.The sequence conservation in both Hsp90 and rDNA sequences and the poor resolution of the deepest nodes suggests that dinoflagellates reflect an explosive radiation in morphological diversity in their recent
High throughput sequencing and proteomics to identify immunogenic proteins of a new pathogen: the dirty genome approach.

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Gilbert Greub

Full Text Available BACKGROUND: With the availability of new generation sequencing technologies, bacterial genome projects have undergone a major boost. Still, chromosome completion needs a costly and time-consuming gap closure, especially when containing highly repetitive elements. However, incomplete genome data may be sufficiently informative to derive the pursued information. For emerging pathogens, i.e. newly identified pathogens, lack of release of genome data during gap closure stage is clearly medically counterproductive. METHODS/PRINCIPAL FINDINGS: We thus investigated the feasibility of a dirty genome approach, i.e. the release of unfinished genome sequences to develop serological diagnostic tools. We showed that almost the whole genome sequence of the emerging pathogen Parachlamydia acanthamoebae was retrieved even with relatively short reads from Genome Sequencer 20 and Solexa. The bacterial proteome was analyzed to select immunogenic proteins, which were then expressed and used to elaborate the first steps of an ELISA. CONCLUSIONS/SIGNIFICANCE: This work constitutes the proof of principle for a dirty genome approach, i.e. the use of unfinished genome sequences of pathogenic bacteria, coupled with proteomics to rapidly identify new immunogenic proteins useful to develop in the future specific diagnostic tests such as ELISA, immunohistochemistry and direct antigen detection. Although applied here to an emerging pathogen, this combined dirty genome sequencing/proteomic approach may be used for any pathogen for which better diagnostics are needed. These genome sequences may also be very useful to develop DNA based diagnostic tests. All these diagnostic tools will allow further evaluations of the pathogenic potential of this obligate intracellular bacterium.
Yeast prions and human prion-like proteins: sequence features and prediction methods.

Science.gov (United States)

Cascarina, Sean M; Ross, Eric D

2014-06-01

Prions are self-propagating infectious protein isoforms. A growing number of prions have been identified in yeast, each resulting from the conversion of soluble proteins into an insoluble amyloid form. These yeast prions have served as a powerful model system for studying the causes and consequences of prion aggregation. Remarkably, a number of human proteins containing prion-like domains, defined as domains with compositional similarity to yeast prion domains, have recently been linked to various human degenerative diseases, including amyotrophic lateral sclerosis. This suggests that the lessons learned from yeast prions may help in understanding these human diseases. In this review, we examine what has been learned about the amino acid sequence basis for prion aggregation in yeast, and how this information has been used to develop methods to predict aggregation propensity. We then discuss how this information is being applied to understand human disease, and the challenges involved in applying yeast prediction methods to higher organisms.
Comparison of Enzymes / Non-Enzymes Proteins Classification Models Based on 3D, Composition, Sequences and Topological Indices

OpenAIRE

Munteanu, Cristian Robert

2014-01-01

Comparison of Enzymes / Non-Enzymes Proteins Classification Models Based on 3D, Composition, Sequences and Topological Indices, German Conference on Bioinformatics (GCB), Potsdam, Germany (September, 2007)
Characterization of upstream sequences of the LIM2 gene that bind developmentally regulated and lens-specific proteins

Institute of Scientific and Technical Information of China (English)

HSU Heng; Robert L. CHURCH

2004-01-01

During lens development, lens epithelial cells differentiate into fiber cells. To date, four major lens fiber cell intrinsic membrane proteins (MIP) ranging in size from 70 kD to 19 kD have been characterized. The second most abundant lens fiber cell intrinsic membrane protein is MP19. This protein probably is involved with lens cell communication and relates with cataractogenesis. The aim of this research is to characterize upstream sequences of the MP19 (also called LIM2) gene that bind developmentally regulated and lens-specific proteins. We have used the gel mobility assays and corresponding competition experiments to identify and characterize cis elements within approximately 500 bases of LIM2 upstream sequences. Our studies locate the positions of some cis elements, including a "CA" repeat, a methylation Hha I island, an FnuD II site, an Ap1 and an Ap2 consensus sequences, and identify some specific cis elements which relate to lens-specific transcription of LIM2. Our experiments also preliminarily identify trans factors which bind to specific cis elements of the LIM2 promoter and/or regulate transcription of LIM2. We conclude that developmental regulation and coordination of the MP 19 gene in ocular lens fiber cells is controlled by the presence of specific cis elements that bind regulatory trans factors that affect LIM2 gene expression. DNA methylation is one mechanism of controlling LIM2 gene expression during lens development.
RT-PCR and sequence analysis of the full-length fusion protein of Canine Distemper Virus from domestic dogs.

Science.gov (United States)

Romanutti, Carina; Gallo Calderón, Marina; Keller, Leticia; Mattion, Nora; La Torre, José

2016-02-01

During 2007-2014, 84 out of 236 (35.6%) samples from domestic dogs submitted to our laboratory for diagnostic purposes were positive for Canine Distemper Virus (CDV), as analyzed by RT-PCR amplification of a fragment of the nucleoprotein gene. Fifty-nine of them (70.2%) were from dogs that had been vaccinated against CDV. The full-length gene encoding the Fusion (F) protein of fifteen isolates was sequenced and compared with that of those of other CDVs, including wild-type and vaccine strains. Phylogenetic analysis using the F gene full-length sequences grouped all the Argentinean CDV strains in the SA2 clade. Sequence identity with the Onderstepoort vaccine strain was 89.0-90.6%, and the highest divergence was found in the 135 amino acids corresponding to the F protein signal-peptide, Fsp (64.4-66.7% identity). In contrast, this region was highly conserved among the local strains (94.1-100% identity). One extra putative N-glycosylation site was identified in the F gene of CDV Argentinean strains with respect to the vaccine strain. The present report is the first to analyze full-length F protein sequences of CDV strains circulating in Argentina, and contributes to the knowledge of molecular epidemiology of CDV, which may help in understanding future disease outbreaks. Copyright © 2015 Elsevier B.V. All rights reserved.
Mason: a JavaScript web site widget for visualizing and comparing annotated features in nucleotide or protein sequences.

Science.gov (United States)

Jaschob, Daniel; Davis, Trisha N; Riffle, Michael

2015-03-07

Sequence feature annotations (e.g., protein domain boundaries, binding sites, and secondary structure predictions) are an essential part of biological research. Annotations are widely used by scientists during research and experimental design, and are frequently the result of biological studies. A generalized and simple means of disseminating and visualizing these data via the web would be of value to the research community. Mason is a web site widget designed to visualize and compare annotated features of one or more nucleotide or protein sequence. Annotated features may be of virtually any type, ranging from annotating transcription binding sites or exons and introns in DNA to secondary structure or domain boundaries in proteins. Mason is simple to use and easy to integrate into web sites. Mason has a highly dynamic and configurable interface supporting multiple sets of annotations per sequence, overlapping regions, customization of interface and user-driven events (e.g., clicks and text to appear for tooltips). It is written purely in JavaScript and SVG, requiring no 3(rd) party plugins or browser customization. Mason is a solution for dissemination of sequence annotation data on the web. It is highly flexible, customizable, simple to use, and is designed to be easily integrated into web sites. Mason is open source and freely available at https://github.com/yeastrc/mason.
An AU-rich element in the 3{prime} untranslated region of the spinach chloroplast petD gene participates in sequence-specific RNA-protein complex formation

Energy Technology Data Exchange (ETDEWEB)

Chen, Qiuyun; Adams, C.C.; Usack, L. [Cornell Univ., Ithaca, NY (United States)] [and others

1995-04-01

In chloroplasts, the 3{prime} untranslated regions of most mRNAs contain a stem-loop-forming inverted repeat (IR) sequence that is required for mRNA stability and correct 3{prime}-end formation. The IR regions of several mRNAs are also known to bind chloroplast proteins, as judged from in vitro gel mobility shift and UV cross-linking assays, and these RNA-protein interactions may be involved in the regulation of chloroplast mRNA processing and/or stability. Here we describe in detail the RNA and protein components that are involved in 3{prime} IR-containing RNA (3{prime} IR-RNA)-protein complex formation for the spinach chloroplast petD gene, which encodes subunit IV of the cytochrome b{sub 6}/f complex. We show that the complex contains 55-, 41-, and 29-kDa RNA-binding proteins (ribonucleoproteins [RNPs]). These proteins together protect a 90-nucleotide segment of RNA from RNase T{sub 1} digestion; this RNA contains the IR and downstream flanking sequences. Competition experiments using 3{prime} IR-RNAs from the psbA or rbcL gene demonstrate that the RNPs have a strong specificity for the petD sequence. Site-directed mutagenesis was carried out to define the RNA sequence elements required for complex formation. These studies identified an 8-nucleotide AU-rich sequence downstream of the IR; mutations within this sequence had moderate to severe effects on RNA-protein complex formation. Although other similar sequences are present in the petD 3{prime} untranslated region, only a single copy, which we have termed box II, appears to be essential for in vivo protein binding. In addition, the IR itself is necessary for optimal complex formation. These two sequence elements together with an RNP complex may direct correct 3{prime}-end processing and/or influence the stability of petD mRNA in chloroplasts. 48 refs., 9 figs., 2 tabs.
The Occurrence of Sequences Identical with Epitopes from the Allergen Pen a 1.0102 Among Food and Non-Food Proteins

Directory of Open Access Journals (Sweden)

Minkiewicz Piotr

2015-03-01

Full Text Available The presence of common epitopes among tropomyosins of invertebrates, including arthropods, e.g. edible ones, may help to explain the molecular basis of cross-reactivity between allergens. The work presented is the first survey concerning global distribution of epitopes from Pen a 1.0102 in universal proteome. In the group of known tropomyosin epitopes, the fragment with the sequence ESKIVELEEEL was found in the sequence of channel catfish (Ictalurus punctatus tropomyosin. To date, this is the first result suggesting the presence of a complete sequential epitope interacting with gE in vertebrate tropomyosin. Another fragment with the sequence VAALNRRIQL, a major part of the epitope, was found in 11 fish, 8 amphibians, 3 birds, 19 mammalians and 4 human tropomyosin sequences. Identical epitopes are common in sequences of invertebrate tropomyosins, including food and non-food allergens annotated in the Allergome database. The rare pentapeptide with the DEERM sequence occurs in proteins not sharing homology with tropomyosins. Pathogenic microorganisms are the most abundant category of organisms synthesizing such proteins.
Identification of DNA-binding protein target sequences by physical effective energy functions: free energy analysis of lambda repressor-DNA complexes.

Directory of Open Access Journals (Sweden)

Caselle Michele

2007-09-01

Full Text Available Abstract Background Specific binding of proteins to DNA is one of the most common ways gene expression is controlled. Although general rules for the DNA-protein recognition can be derived, the ambiguous and complex nature of this mechanism precludes a simple recognition code, therefore the prediction of DNA target sequences is not straightforward. DNA-protein interactions can be studied using computational methods which can complement the current experimental methods and offer some advantages. In the present work we use physical effective potentials to evaluate the DNA-protein binding affinities for the λ repressor-DNA complex for which structural and thermodynamic experimental data are available. Results The binding free energy of two molecules can be expressed as the sum of an intermolecular energy (evaluated using a molecular mechanics forcefield, a solvation free energy term and an entropic term. Different solvation models are used including distance dependent dielectric constants, solvent accessible surface tension models and the Generalized Born model. The effect of conformational sampling by Molecular Dynamics simulations on the computed binding energy is assessed; results show that this effect is in general negative and the reproducibility of the experimental values decreases with the increase of simulation time considered. The free energy of binding for non-specific complexes, estimated using the best energetic model, agrees with earlier theoretical suggestions. As a results of these analyses, we propose a protocol for the prediction of DNA-binding target sequences. The possibility of searching regulatory elements within the bacteriophage λ genome using this protocol is explored. Our analysis shows good prediction capabilities, even in absence of any thermodynamic data and information on the naturally recognized sequence. Conclusion This study supports the conclusion that physics-based methods can offer a completely complementary
Sequence variation of koala retrovirus transmembrane protein p15E among koalas from different geographic regions

Science.gov (United States)

Ishida, Yasuko; McCallister, Chelsea; Nikolaidis, Nikolas; Tsangaras, Kyriakos; Helgen, Kristofer M.; Greenwood, Alex D.; Roca, Alfred L.

2014-01-01

The koala retrovirus (KoRV), which is transitioning from an exogenous to an endogenous form, has been associated with high mortality in koalas. For other retroviruses, the envelope protein p15E has been considered a candidate for vaccine development. We therefore examined proviral sequence variation of KoRV p15E in a captive Queensland and three wild southern Australian koalas. We generated 163 sequences with intact open reading frames, which grouped into 39 distinct haplotypes. Sixteen distinct haplotypes comprising 139 of the sequences (85%) coded for the same polypeptide. Among the remaining 23 haplotypes, 22 were detected only once among the sequences, and each had 1 or 2 non-synonymous differences from the majority sequence. Several analyses suggested that p15E was under purifying selection. Important epitopes and domains were highly conserved across the p15E sequences and in previously reported exogenous KoRVs. Overall, these results support the potential use of p15E for KoRV vaccine development. PMID:25462343
Metabolic fingerprinting of high-fat plasma samples processed by centrifugation- and filtration-based protein precipitation delineates significant differences in metabolite information coverage.

Science.gov (United States)

Barri, Thaer; Holmer-Jensen, Jens; Hermansen, Kjeld; Dragsted, Lars O

2012-03-09

Metabolomics and metabolic fingerprinting are being extensively employed for improved understanding of biological changes induced by endogenous or exogenous factors. Blood serum or plasma samples are often employed for metabolomics studies. Plasma protein precipitation (PPP) is currently performed in most laboratories before LC-MS analysis. However, the impact of fat content in plasma samples on metabolite coverage has not previously been investigated. Here, we have studied whether PPP procedures influence coverage of plasma metabolites from high-fat plasma samples. An optimized UPLC-QTOF/MS metabolic fingerprinting approach and multivariate modeling (PCA and OPLS-DA) were utilized for finding characteristic metabolite changes induced by two PPP procedures; centrifugation and filtration. We used 12-h fasting samples and postprandial samples collected at 2h after a standardized high-fat protein-rich meal in obese non-diabetic subjects recruited in a dietary intervention. The two PPP procedures as well as external and internal standards (ISs) were used to track errors in response normalization and quantification. Remarkably and sometimes uniquely, the fPPP, but not the cPPP approach, recovered not only high molecular weight (HMW) lipophilic metabolites, but also small molecular weight (SMW) relatively polar metabolites. Characteristic SMW markers of postprandial samples were aromatic and branched-chain amino acids that were elevated (p<0.001) as a consequence of the protein challenge. In contrast, some HMW lipophilic species, e.g. acylcarnitines, were moderately lower (p<0.001) in postprandial samples. LysoPCs were largely unaffected. In conclusion, the fPPP procedure is recommended for processing high-fat plasma samples in metabolomics studies. While method improvements presented here were clear, use of several ISs revealed substantial challenges to untargeted metabolomics due to large and variable matrix effects. Copyright © 2012 Elsevier B.V. All rights reserved.
Sequence Identification, Recombinant Production, and Analysis of the Self-Assembly of Egg Stalk Silk Proteins from Lacewing Chrysoperla carnea.

Science.gov (United States)

Neuenfeldt, Martin; Scheibel, Thomas

2017-06-13

Egg stalk silks of the common green lacewing Chrysoperla carnea likely comprise at least three different silk proteins. Based on the natural spinning process, it was hypothesized that these proteins self-assemble without shear stress, as adult lacewings do not use a spinneret. To examine this, the first sequence identification and determination of the gene expression profile of several silk proteins and various transcript variants thereof was conducted, and then the three major proteins were recombinantly produced in Escherichia coli encoded by their native complementary DNA (cDNA) sequences. Circular dichroism measurements indicated that the silk proteins in aqueous solutions had a mainly intrinsically disordered structure. The largest silk protein, which we named ChryC1, exhibited a lower critical solution temperature (LCST) behavior and self-assembled into fibers or film morphologies, depending on the conditions used. The second silk protein, ChryC2, self-assembled into nanofibrils and subsequently formed hydrogels. Circular dichroism and Fourier transform infrared spectroscopy confirmed conformational changes of both proteins into beta sheet rich structures upon assembly. ChryC3 did not self-assemble into any morphology under the tested conditions. Thereby, through this work, it could be shown that recombinant lacewing silk proteins can be produced and further used for studying the fiber formation of lacewing egg stalks.
Protein backbone chemical shifts predicted from searching a database for torsion angle and sequence homology

International Nuclear Information System (INIS)

Shen Yang; Bax, Ad

2007-01-01

Chemical shifts of nuclei in or attached to a protein backbone are exquisitely sensitive to their local environment. A computer program, SPARTA, is described that uses this correlation with local structure to predict protein backbone chemical shifts, given an input three-dimensional structure, by searching a newly generated database for triplets of adjacent residues that provide the best match in φ/ψ/χ 1 torsion angles and sequence similarity to the query triplet of interest. The database contains 15 N, 1 H N , 1 H α , 13 C α , 13 C β and 13 C' chemical shifts for 200 proteins for which a high resolution X-ray (≤2.4 A) structure is available. The relative importance of the weighting factors for the φ/ψ/χ 1 angles and sequence similarity was optimized empirically. The weighted, average secondary shifts of the central residues in the 20 best-matching triplets, after inclusion of nearest neighbor, ring current, and hydrogen bonding effects, are used to predict chemical shifts for the protein of known structure. Validation shows good agreement between the SPARTA-predicted and experimental shifts, with standard deviations of 2.52, 0.51, 0.27, 0.98, 1.07 and 1.08 ppm for 15 N, 1 H N , 1 H α , 13 C α , 13 C β and 13 C', respectively, including outliers

A Case Study into Microbial Genome Assembly Gap Sequences and Finishing Strategies.

Science.gov (United States)

Utturkar, Sagar M; Klingeman, Dawn M; Hurt, Richard A; Brown, Steven D

2017-01-01

This study characterized regions of DNA which remained unassembled by either PacBio and Illumina sequencing technologies for seven bacterial genomes. Two genomes were manually finished using bioinformatics and PCR/Sanger sequencing approaches and regions not assembled by automated software were analyzed. Gaps present within Illumina assemblies mostly correspond to repetitive DNA regions such as multiple rRNA operon sequences. PacBio gap sequences were evaluated for several properties such as GC content, read coverage, gap length, ability to form strong secondary structures, and corresponding annotations. Our hypothesis that strong secondary DNA structures blocked DNA polymerases and contributed to gap sequences was not accepted. PacBio assemblies had few limitations overall and gaps were explained as cumulative effect of lower than average sequence coverage and repetitive sequences at contig termini. An important aspect of the present study is the compilation of biological features that interfered with assembly and included active transposons, multiple plasmid sequences, phage DNA integration, and large sequence duplication. Our targeted genome finishing approach and systematic evaluation of the unassembled DNA will be useful for others looking to close, finish, and polish microbial genome sequences.
Resolution of a protein sequence ambiguity by X-ray crystallographic and mass spectrometric methods

International Nuclear Information System (INIS)

Keefe, L.J.; Lattman, E.E.; Wolkow, C.; Woods, A.; Chevrier, M.; Cotter, R.J.

1992-01-01

Ambiguities in amino acid sequences are a potential problem in X-ray crystallographic studies of proteins. Amino acid side chains often cannot be reliably identified from the electron density. Many protein crystal structures that are now being solved are simple variants of a known wild-type structure. Thus, cloning artifacts or other untoward events can readily lead to cases in which the proposed sequence is not correct. An example is presented showing that mass spectrometry provides an excellent tool for analyzing suspected errors. The X-ray crystal structure of an insertion mutant of Staphylococcal nuclease has been solved to 1.67 A resolution and refined to a crystallographic R value of 0.170. A single residue has been inserted in the C-terminal α helix. The inserted amino acid was believed to be an alanine residue, but the final electron density maps strongly indicated that a glycine had been inserted instead. To confirm the observations from the X-ray data, matrix-assisted laser desorption mass spectrometry was employed to verify the glycine insertion. This mass spectrometric technique has sufficient mass accuracy to detect the methyl group that distinguishes glycine from alanine and can be extended to the more common situation in which crystallographic measurements suggest a problem with the sequence, but cannot pinpoint its location or nature. (orig.)
Resolution of a protein sequence ambiguity by X-ray crystallographic and mass spectrometric methods

Energy Technology Data Exchange (ETDEWEB)

Keefe, L.J.; Lattman, E.E. (Dept. of Biophysics and Biophysical Chemistry, Johns Hopkins Univ. School of Medicine, Baltimore, MD (United States)); Wolkow, C.; Woods, A.; Chevrier, M.; Cotter, R.J. (Middle Atlantic Mass Spectrometry Lab., Johns Hopkins Univ. School of Medicine, Baltimore, MD (United States))

1992-04-01

Ambiguities in amino acid sequences are a potential problem in X-ray crystallographic studies of proteins. Amino acid side chains often cannot be reliably identified from the electron density. Many protein crystal structures that are now being solved are simple variants of a known wild-type structure. Thus, cloning artifacts or other untoward events can readily lead to cases in which the proposed sequence is not correct. An example is presented showing that mass spectrometry provides an excellent tool for analyzing suspected errors. The X-ray crystal structure of an insertion mutant of Staphylococcal nuclease has been solved to 1.67 A resolution and refined to a crystallographic R value of 0.170. A single residue has been inserted in the C-terminal {alpha} helix. The inserted amino acid was believed to be an alanine residue, but the final electron density maps strongly indicated that a glycine had been inserted instead. To confirm the observations from the X-ray data, matrix-assisted laser desorption mass spectrometry was employed to verify the glycine insertion. This mass spectrometric technique has sufficient mass accuracy to detect the methyl group that distinguishes glycine from alanine and can be extended to the more common situation in which crystallographic measurements suggest a problem with the sequence, but cannot pinpoint its location or nature. (orig.).
Exome sequencing for prenatal diagnosis of fetuses with sonographic abnormalities.

Science.gov (United States)

Drury, Suzanne; Williams, Hywel; Trump, Natalie; Boustred, Christopher; Lench, Nicholas; Scott, Richard H; Chitty, Lyn S

2015-10-01

In the absence of aneuploidy or other pathogenic cytogenetic abnormality, fetuses with increased nuchal translucency (NT ≥ 3.5 mm) and/or other sonographic abnormalities have a greater incidence of genetic syndromes, but defining the underlying pathology can be challenging. Here, we investigate the value of whole exome sequencing in fetuses with sonographic abnormalities but normal microarray analysis. Whole exome sequencing was performed on DNA extracted from chorionic villi or amniocytes in 24 fetuses with unexplained ultrasound findings. In the first 14 cases sequencing was initially performed on fetal DNA only. For the remaining 10, the trio of fetus, mother and father was sequenced simultaneously. In 21% (5/24) cases, exome sequencing provided definitive diagnoses (Milroy disease, hypophosphatasia, achondrogenesis type 2, Freeman-Sheldon syndrome and Baraitser-Winter Syndrome). In a further case, a plausible diagnosis of orofaciodigital syndrome type 6 was made. In two others, a single mutation in an autosomal recessive gene was identified, but incomplete sequencing coverage precluded exclusion of the presence of a second mutation. Whole exome sequencing improves prenatal diagnosis in euploid fetuses with abnormal ultrasound scans. In order to expedite interpretation of results, trio sequencing should be employed, but interpretation can still be compromised by incomplete coverage of relevant genes. © 2015 John Wiley & Sons, Ltd.
Amino acid sequences of the ribosomal proteins HL30 and HmaL5 from the archaebacterium Halobacterium marismortui.

Science.gov (United States)

Hatakeyama, T; Hatakeyama, T

1990-07-06

The complete amino acid sequences of the ribosomal proteins HL30 and HmaL5 from the archaebacterium Halobacterium marismortui were determined. Protein HL30 was found to be acetylated at its N-terminal amino acid and shows homology to the eukaryotic ribosomal proteins YL34 from yeast and RL31 from rat. Protein HmaL5 was homologous to the protein L5 from Escherichia coli and Bacillus stearothermophilus as well as to YL16 from yeast. HmaL5 shows more similarities to its eukaryotic counterpart than to eubacterial ones.
Quantitative assessment of in-solution digestion efficiency identifies optimal protocols for unbiased protein analysis

DEFF Research Database (Denmark)

Leon, Ileana R; Schwämmle, Veit; Jensen, Ole N

2013-01-01

a combination of qualitative and quantitative LC-MS/MS methods and statistical data analysis. In contrast to previous studies we employed both standard qualitative as well as data-independent quantitative workflows to systematically assess trypsin digestion efficiency and bias using mitochondrial protein...... conditions (buffer, RapiGest, deoxycholate, urea), and two methods for removal of detergents prior to analysis of peptides (acid precipitation or phase separation with ethyl acetate). Our data-independent quantitative LC-MS/MS workflow quantified over 3700 distinct peptides with 96% completeness between all...... protocols and replicates, with an average 40% protein sequence coverage and an average of 11 peptides identified per protein. Systematic quantitative and statistical analysis of physicochemical parameters demonstrated that deoxycholate-assisted in-solution digestion combined with phase transfer allows...
Exploring the potential of second-generation sequencing in diverse biological contexts

DEFF Research Database (Denmark)

Fordyce, Sarah Louise

Second generation sequencing (SGS) has revolutionized the study of DNA, allowing massive parallel sequencing of nucleic acids with unprecedented depths of coverage. The research undertaken in this thesis occurred in parallel with the increased accessibility of SGS platforms for routine genetic...
Evaluating imputation algorithms for low-depth genotyping-by-sequencing (GBS) data

Science.gov (United States)

Well-powered genomic studies require genome-wide marker coverage across many individuals. For non-model species with few genomic resources, high-throughput sequencing (HTS) methods, such as Genotyping-By-Sequencing (GBS), offer an inexpensive alternative to array-based genotyping. Although affordabl...
Comparison of cDNA-derived protein sequences of the human fibronectin and vitronectin receptor α-subunits and platelet glycoprotein IIb

International Nuclear Information System (INIS)

Fitzgerald, L.A.; Poncz, M.; Steiner, B.; Rall, S.C. Jr.; Bennett, J.S.; Phillips, D.R.

1987-01-01

The fibronectin receptor (FnR), the vitronectin receptor (VnR), and the platelet membrane glycoprotein (GP) IIb-IIIa complex are members of a family of cell adhesion receptors, which consist of noncovalently associated α- and β-subunits. The present study was designed to compare the cDNA-derived protein sequences of the α-subunits of human FnR, VnR, and platelet GP IIb. cDNA clones for the α-subunit of the FnR (FnR/sub α/) were obtained from a human umbilical vein endothelial (HUVE) cell library by using an oligonucleotide probe designed from a peptide sequence of platelet GP IIb. cDNA clones for platelet GP IIb were isolated from a cDNA expression library of human erythroleukemia cells by using antibodies. cDNA clones of the VnR α-subunit (VnR/sub α/) were obtained from the HUVE cell library by using an oligonucleotide probe from the partial cDNA sequence for the VnR/sub α/. Translation of these sequences showed that the FNR/sub α/, the VnR/sub α/, and GP IIb are composed of disulfide-linked large (858-871 amino acids) and small (137-158 amino acids) chains that are posttranslationally processed from a single mRNA. A single hydrophobic segment located near the carboxyl terminus of each small chain appears to be a transmembrane domain. The large chains appear to be entirely extracellular, and each contains four repeated putative Ca 2+ -binding domains of about 30 amino acids that have sequence similarities to other Ca 2+ -binding proteins. The identity among the protein sequences of the three receptor α-subunits ranges from 36.1% to 44.5%, with the Ca 2+ -binding domains having the greatest homology. These proteins apparently evolved by a process of gene duplication
Increasing the Structural Coverage of Tuberculosis Drug Targets

Science.gov (United States)

Baugh, Loren; Phan, Isabelle; Begley, Darren W.; Clifton, Matthew C.; Armour, Brianna; Dranow, David M.; Taylor, Brandy M.; Muruthi, Marvin M.; Abendroth, Jan; Fairman, James W.; Fox, David; Dieterich, Shellie H.; Staker, Bart L.; Gardberg, Anna S.; Choi, Ryan; Hewitt, Stephen N.; Napuli, Alberto J.; Myers, Janette; Barrett, Lynn K.; Zhang, Yang; Ferrell, Micah; Mundt, Elizabeth; Thompkins, Katie; Tran, Ngoc; Lyons-Abbott, Sally; Abramov, Ariel; Sekar, Aarthi; Serbzhinskiy, Dmitri; Lorimer, Don; Buchko, Garry W.; Stacy, Robin; Stewart, Lance J.; Edwards, Thomas E.; Van Voorhis, Wesley C.; Myler, Peter J.

2015-01-01

High-resolution three-dimensional structures of essential Mycobacterium tuberculosis (Mtb) proteins provide templates for TB drug design, but are available for only a small fraction of the Mtb proteome. Here we evaluate an intra-genus “homolog-rescue” strategy to increase the structural information available for TB drug discovery by using mycobacterial homologs with conserved active sites. Of 179 potential TB drug targets selected for x-ray structure determination, only 16 yielded a crystal structure. By adding 1675 homologs from nine other mycobacterial species to the pipeline, structures representing an additional 52 otherwise intractable targets were solved. To determine whether these homolog structures would be useful surrogates in TB drug design, we compared the active sites of 106 pairs of Mtb and non-TB mycobacterial (NTM) enzyme homologs with experimentally determined structures, using three metrics of active site similarity, including superposition of continuous pharmacophoric property distributions. Pair-wise structural comparisons revealed that 19/22 pairs with >55% overall sequence identity had active site Cα RMSD 85% side chain identity, and ≥80% PSAPF (similarity based on pharmacophoric properties) indicating highly conserved active site shape and chemistry. Applying these results to the 52 NTM structures described above, 41 shared >55% sequence identity with the Mtb target, thus increasing the effective structural coverage of the 179 Mtb targets over three-fold (from 9% to 32%). The utility of these structures in TB drug design can be tested by designing inhibitors using the homolog structure and assaying the cognate Mtb enzyme; a promising test case, Mtb cytidylate kinase, is described. The homolog-rescue strategy evaluated here for TB is also generalizable to drug targets for other diseases. PMID:25613812
Electrochemistry-assisted top-down characterization of disulfide-containing proteins.

Science.gov (United States)

Zhang, Yun; Cui, Weidong; Zhang, Hao; Dewald, Howard D; Chen, Hao

2012-04-17

Covalent disulfide bond linkage in a protein represents an important challenge for mass spectrometry (MS)-based top-down protein structure analysis as it reduces the backbone cleavage efficiency for MS/MS dissociation. This study presents a strategy for solving this critical issue via integrating electrochemistry (EC) online with a top-down MS approach. In this approach, proteins undergo electrolytic reduction in an electrochemical cell to break disulfide bonds and then undergo online ionization into gaseous ions for analysis by electron-capture dissociation (ECD) and collision-induced dissociation (CID). The electrochemical reduction of proteins allows one to remove disulfide bond constraints and also leads to increased charge numbers of the resulting protein ions. As a result, sequence coverage was significantly enhanced, as exemplified by β-lactoglobulin A (24 vs 75 backbone cleavages before and after electrolytic reduction, respectively) and lysozyme (5 vs 66 backbone cleavages before and after electrolytic reduction, respectively). This methodology is fast and does not need chemical reductants, which would have an important impact in high-throughput proteomics research.
ASAP: Amplification, sequencing & annotation of plastomes

Directory of Open Access Journals (Sweden)

Folta Kevin M

2005-12-01

Full Text Available Abstract Background Availability of DNA sequence information is vital for pursuing structural, functional and comparative genomics studies in plastids. Traditionally, the first step in mining the valuable information within a chloroplast genome requires sequencing a chloroplast plasmid library or BAC clones. These activities involve complicated preparatory procedures like chloroplast DNA isolation or identification of the appropriate BAC clones to be sequenced. Rolling circle amplification (RCA is being used currently to amplify the chloroplast genome from purified chloroplast DNA and the resulting products are sheared and cloned prior to sequencing. Herein we present a universal high-throughput, rapid PCR-based technique to amplify, sequence and assemble plastid genome sequence from diverse species in a short time and at reasonable cost from total plant DNA, using the large inverted repeat region from strawberry and peach as proof of concept. The method exploits the highly conserved coding regions or intergenic regions of plastid genes. Using an informatics approach, chloroplast DNA sequence information from 5 available eudicot plastomes was aligned to identify the most conserved regions. Cognate primer pairs were then designed to generate ~1 – 1.2 kb overlapping amplicons from the inverted repeat region in 14 diverse genera. Results 100% coverage of the inverted repeat region was obtained from Arabidopsis, tobacco, orange, strawberry, peach, lettuce, tomato and Amaranthus. Over 80% coverage was obtained from distant species, including Ginkgo, loblolly pine and Equisetum. Sequence from the inverted repeat region of strawberry and peach plastome was obtained, annotated and analyzed. Additionally, a polymorphic region identified from gel electrophoresis was sequenced from tomato and Amaranthus. Sequence analysis revealed large deletions in these species relative to tobacco plastome thus exhibiting the utility of this method for structural and
Influence of the Amino Acid Sequence on Protein-Mineral Interactions in Soil

Science.gov (United States)

Chacon, S. S.; Reardon, P. N.; Purvine, S.; Lipton, M. S.; Washton, N.; Kleber, M.

2017-12-01

The intimate associations between protein and mineral surfaces have profound impacts on nutrient cycling in soil. Proteins are an important source of organic C and N, and a subset of proteins, extracellular enzymes (EE), can catalyze the depolymerization of soil organic matter (SOM). Our goal was to determine how variation in the amino acid sequence could influence a protein's susceptibility to become chemically altered by mineral surfaces to infer the fate of adsorbed EE function in soil. We hypothesized that (1) addition of charged amino acids would enhance the adsorption onto oppositely charged mineral surfaces (2) addition of aromatic amino acids would increase adsorption onto zero charged surfaces (3) Increase adsorption of modified proteins would enhance their susceptibility to alterations by redox active minerals. To test these hypotheses, we generated three engineered proxies of a model protein Gb1 (IEP 4.0, 6.2 kDA) by inserting either negatively charged, positively charged or aromatic amino acids in the second loop. These modified proteins were allowed to interact with functionally different mineral surfaces (goethite, montmorillonite, kaolinite and birnessite) at pH 5 and 7. We used LC-MS/MS and solution-state Heteronuclear Single Quantum Coherence Spectroscopy NMR to observe modifications on engineered proteins as a consequence to mineral interactions. Preliminary results indicate that addition of any amino acids to a protein increase its susceptibility to fragmentation and oxidation by redox active mineral surfaces, and alter adsorption to the other mineral surfaces. This suggest that not all mineral surfaces in soil may act as sorbents for EEs and chemical modification of their structure should also be considered as an explanation for decrease in EE activity. Fragmentation of proteins by minerals can bypass the need to produce proteases, but microbial acquisition of other nutrients that require enzymes such as cellulases, ligninases or phosphatases
Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection

Directory of Open Access Journals (Sweden)

Xin Ma

2015-01-01

Full Text Available The prediction of RNA-binding proteins is one of the most challenging problems in computation biology. Although some studies have investigated this problem, the accuracy of prediction is still not sufficient. In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR method, followed by incremental feature selection (IFS. We incorporated features of conjoint triad features and three novel features: binding propensity (BP, nonbinding propensity (NBP, and evolutionary information combined with physicochemical properties (EIPP. The results showed that these novel features have important roles in improving the performance of the predictor. Using the mRMR-IFS method, our predictor achieved the best performance (86.62% accuracy and 0.737 Matthews correlation coefficient. High prediction accuracy and successful prediction performance suggested that our method can be a useful approach to identify RNA-binding proteins from sequence information.
Sequencing and analysis of an Irish human genome.

LENUS (Irish Health Repository)

Tong, Pin

2010-01-01

Recent studies generating complete human sequences from Asian, African and European subgroups have revealed population-specific variation and disease susceptibility loci. Here, choosing a DNA sample from a population of interest due to its relative geographical isolation and genetic impact on further populations, we extend the above studies through the generation of 11-fold coverage of the first Irish human genome sequence.
Genomic sequencing: assessing the health care system, policy, and big-data implications.

Science.gov (United States)

Phillips, Kathryn A; Trosman, Julia R; Kelley, Robin K; Pletcher, Mark J; Douglas, Michael P; Weldon, Christine B

2014-07-01

New genomic sequencing technologies enable the high-speed analysis of multiple genes simultaneously, including all of those in a person's genome. Sequencing is a prominent example of a "big data" technology because of the massive amount of information it produces and its complexity, diversity, and timeliness. Our objective in this article is to provide a policy primer on sequencing and illustrate how it can affect health care system and policy issues. Toward this end, we developed an easily applied classification of sequencing based on inputs, methods, and outputs. We used it to examine the implications of sequencing for three health care system and policy issues: making care more patient-centered, developing coverage and reimbursement policies, and assessing economic value. We conclude that sequencing has great promise but that policy challenges include how to optimize patient engagement as well as privacy, develop coverage policies that distinguish research from clinical uses and account for bioinformatics costs, and determine the economic value of sequencing through complex economic models that take into account multiple findings and downstream costs. Project HOPE—The People-to-People Health Foundation, Inc.
Recognition of secretory proteins in Escherichia coli requires signals in addition to the signal sequence and slow folding

Directory of Open Access Journals (Sweden)

Flower Ann M

2002-11-01

Full Text Available Abstract Background The Sec-dependent protein export apparatus of Escherichia coli is very efficient at correctly identifying proteins to be exported from the cytoplasm. Even bacterial strains that carry prl mutations, which allow export of signal sequence-defective precursors, accurately differentiate between cytoplasmic and mutant secretory proteins. It was proposed previously that the basis for this precise discrimination is the slow folding rate of secretory proteins, resulting in binding by the secretory chaperone, SecB, and subsequent targeting to translocase. Based on this proposal, we hypothesized that a cytoplasmic protein containing a mutation that slows its rate of folding would be recognized by SecB and therefore targeted to the Sec pathway. In a Prl suppressor strain the mutant protein would be exported to the periplasm due to loss of ability to reject non-secretory proteins from the pathway. Results In the current work, we tested this hypothesis using a mutant form of λ repressor that folds slowly. No export of the mutant protein was observed, even in a prl strain. We then examined binding of the mutant λ repressor to SecB. We did not observe interaction by either of two assays, indicating that slow folding is not sufficient for SecB binding and targeting to translocase. Conclusions These results strongly suggest that to be targeted to the export pathway, secretory proteins contain signals in addition to the canonical signal sequence and the rate of folding.
Divide and conquer: enriching environmental sequencing data.

Directory of Open Access Journals (Sweden)

Anne Bergeron

2007-09-01

Full Text Available In environmental sequencing projects, a mix of DNA from a whole microbial community is fragmented and sequenced, with one of the possible goals being to reconstruct partial or complete genomes of members of the community. In communities with high diversity of species, a significant proportion of the sequences do not overlap any other fragment in the sample. This problem will arise not only in situations with a relatively even distribution of many species, but also when the community in a particular environment is routinely dominated by the same few species. In the former case, no genomes may be assembled at all, while in the latter case a few dominant species in an environment will always be sequenced at high coverage to the detriment of coverage of the greater number of sparse species.Here we show that, with the same global sequencing effort, separating the species into two or more sub-communities prior to sequencing can yield a much higher proportion of sequences that can be assembled. We first use the Lander-Waterman model to show that, if the expected percentage of singleton sequences is higher than 25%, then, under the uniform distribution hypothesis, splitting the community is always a wise choice. We then construct simulated microbial communities to show that the results hold for highly non-uniform distributions. We also show that, for the distributions considered in the experiments, it is possible to estimate quite accurately the relative diversity of the two sub-communities.Given the fact that several methods exist to split microbial communities based on physical properties such as size, density, surface biochemistry, or optical properties, we strongly suggest that groups involved in environmental sequencing, and expecting high diversity, consider splitting their communities in order to maximize the information content of their sequencing effort.
Deep coverage of the beer proteome.

Science.gov (United States)

Grochalová, Martina; Konečná, Hana; Stejskal, Karel; Potěšil, David; Fridrichová, Danuše; Srbová, Eva; Ornerová, Kateřina; Zdráhal, Zbyněk

2017-06-06

We adopted an approach based on peptide immobilized pH gradient-isoelectric focusing (IPG-IEF) separation, coupled with LC-MS/MS, in order to maximize coverage of the beer proteome. A lager beer brewed using traditional Czech technology was degassed, desalted and digested. Tryptic peptides were separated by isoelectric focusing on an immobilized pH gradient strip and, after separation, the gel strip was divided into seven equally sized parts. Peptides extracted from gel fractions were analyzed by LC-MS/MS. This approach resulted in a three-fold increase in the number of proteins identified (over 1700) when compared to analysis of unfractionated beer processed by a filter-aided sample preparation (FASP). Over 1900 protein groups (PGs) in total were identified by both approaches. The study significantly extends knowledge about the beer proteome and demonstrates its complexity. Detailed knowledge of the protein content, especially gluten proteins, will enhance the evaluation of potential health risks related to beer consumption (coeliac disease) and will contribute to improving beer quality. Copyright © 2017 Elsevier B.V. All rights reserved.
2-Aminobenzamide and 2-Aminobenzoic Acid as New MALDI Matrices Inducing Radical Mediated In-Source Decay of Peptides and Proteins

Science.gov (United States)

Smargiasso, Nicolas; Quinton, Loic; de Pauw, Edwin

2012-03-01

One of the mechanisms leading to MALDI in-source decay (MALDI ISD) is the transfer of hydrogen radicals to analytes upon laser irradiation. Analytes such as peptides or proteins may undergo ISD and this method can therefore be exploited for top-down sequencing. When performed on peptides, radical-induced ISD results in production of c- and z-ions, as also found in ETD and ECD activation. Here, we describe two new compounds which, when used as MALDI matrices, are able to efficiently induce ISD of peptides and proteins: 2-aminobenzamide and 2-aminobenzoic acid. In-source reduction of the disulfide bridge containing peptide Calcitonin further confirmed the radicalar mechanism of the ISD process. ISD of peptides led, in addition to c- and z-ions, to the generation of a-, x-, and y-ions both in positive and in negative ion modes. Finally, good sequence coverage was obtained for the sequencing of myoglobin (17 kDa protein), confirming the effectiveness of both 2-aminobenzamide and 2-aminobenzoic acid as MALDI ISD matrices.

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