Accurate protein structure modeling using sparse NMR data and homologous structure information.

Science.gov (United States)

Thompson, James M; Sgourakis, Nikolaos G; Liu, Gaohua; Rossi, Paolo; Tang, Yuefeng; Mills, Jeffrey L; Szyperski, Thomas; Montelione, Gaetano T; Baker, David

2012-06-19

While information from homologous structures plays a central role in X-ray structure determination by molecular replacement, such information is rarely used in NMR structure determination because it can be incorrect, both locally and globally, when evolutionary relationships are inferred incorrectly or there has been considerable evolutionary structural divergence. Here we describe a method that allows robust modeling of protein structures of up to 225 residues by combining (1)H(N), (13)C, and (15)N backbone and (13)Cβ chemical shift data, distance restraints derived from homologous structures, and a physically realistic all-atom energy function. Accurate models are distinguished from inaccurate models generated using incorrect sequence alignments by requiring that (i) the all-atom energies of models generated using the restraints are lower than models generated in unrestrained calculations and (ii) the low-energy structures converge to within 2.0 Å backbone rmsd over 75% of the protein. Benchmark calculations on known structures and blind targets show that the method can accurately model protein structures, even with very remote homology information, to a backbone rmsd of 1.2-1.9 Å relative to the conventional determined NMR ensembles and of 0.9-1.6 Å relative to X-ray structures for well-defined regions of the protein structures. This approach facilitates the accurate modeling of protein structures using backbone chemical shift data without need for side-chain resonance assignments and extensive analysis of NOESY cross-peak assignments.

Post-Electrophoretic Identification of Oxidized Proteins

Science.gov (United States)

Conrad, Craig C; Talent, John M; Malakowsky, Christina A

1999-01-01

The oxidative modification of proteins has been shown to play a major role in a number of human diseases. However, the ability to identify specific proteins that are most susceptible to oxidative modifications is difficult. Separation of proteins using polyacrylamide gel electrophoresis (PAGE) offers the analytical potential for the recovery, amino acid sequencing, and identification of thousands of individual proteins from cells and tissues. We have developed a method to allow underivatized proteins to be electroblotted onto PVDF membranes before derivatization and staining. Since both the protein and oxidation proteins are quantifiable, the specific oxidation index of each protein can be determined. The optimal sequence and conditions for the staining process are (a) electrophoresis, (b) electroblotting onto PVDF membranes, (c) derivatization of carbonyls with 2,4-DNP, (d) immunostaining with anti DNP antibody, and (e) protein staining with colloidal gold. PMID:12734585

Identification of one B-cell epitope from NS1 protein of duck Tembusu virus with monoclonal antibodies.

Directory of Open Access Journals (Sweden)

Jinfeng Ti

Full Text Available This study describes the identification of one linear B-cell epitope on TMUV NS1 protein with monoclonal antibody (mAb 3G2 by indirect enzyme-linked immunosorbent assay (ELISA. In this study, NS1 protein was expressed in prokaryotic expression system and purified. One mAb against NS1 protein was generated from Balb/c mice immunized with recombinant protein NS1. A set of 35 partially-overlapping polypeptides covering the entire NS1 protein was expressed with PGEX-6P-1 vector and screened with mAb 3G2. One polypeptide against the mAb was acquired and identified by indirect ELISA and western-blot. To map the epitope accurately, one or two amino acid residues were removed from the carboxy and amino terminal of polypeptide sequentially. A series of truncated oligopeptides were expressed and purified. The minimal determinant of the linear B cell epitope was recognized and identified with mAb 3G2. The accurate linear B-cell epitope was 269DEKEIV274 located in NS1 protein. Furthermore, sequence alignment showed that the epitope was highly conserved and specific among TMUV strains and other flavivirus respectively. The linear B-cell epitope of TMUV NS1 protein could benefit the development of new vaccines and diagnostic assays.

Improved method for rapid and accurate isolation and identification of Streptococcus mutans and Streptococcus sobrinus from human plaque samples.

Science.gov (United States)

Villhauer, Alissa L; Lynch, David J; Drake, David R

2017-08-01

Mutans streptococci (MS), specifically Streptococcus mutans (SM) and Streptococcus sobrinus (SS), are bacterial species frequently targeted for investigation due to their role in the etiology of dental caries. Differentiation of S. mutans and S. sobrinus is an essential part of exploring the role of these organisms in disease progression and the impact of the presence of either/both on a subject's caries experience. Of vital importance to the study of these organisms is an identification protocol that allows us to distinguish between the two species in an easy, accurate, and timely manner. While conducting a 5-year birth cohort study in a Northern Plains American Indian tribe, the need for a more rapid procedure for isolating and identifying high volumes of MS was recognized. We report here on the development of an accurate and rapid method for MS identification. Accuracy, ease of use, and material and time requirements for morphological differentiation on selective agar, biochemical tests, and various combinations of PCR primers were compared. The final protocol included preliminary identification based on colony morphology followed by PCR confirmation of species identification using primers targeting regions of the glucosyltransferase (gtf) genes of SM and SS. This method of isolation and identification was found to be highly accurate, more rapid than the previous methodology used, and easily learned. It resulted in more efficient use of both time and material resources. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification and quantitation of signal molecule-dependent protein phosphorylation

KAUST Repository

Groen, Arnoud J.

2013-09-03

Phosphoproteomics is a fast-growing field that aims at characterizing phosphorylated proteins in a cell or a tissue at a given time. Phosphorylation of proteins is an important regulatory mechanism in many cellular processes. Gel-free phosphoproteome technique involving enrichment of phosphopeptide coupled with mass spectrometry has proven to be invaluable to detect and characterize phosphorylated proteins. In this chapter, a gel-free quantitative approach involving 15N metabolic labelling in combination with phosphopeptide enrichment by titanium dioxide (TiO2) and their identification by MS is described. This workflow can be used to gain insights into the role of signalling molecules such as cyclic nucleotides on regulatory networks through the identification and quantification of responsive phospho(proteins). © Springer Science+Business Media New York 2013.

The SPECIES and ORGANISMS Resources for Fast and Accurate Identification of Taxonomic Names in Text

DEFF Research Database (Denmark)

Pafilis, Evangelos; Pletscher-Frankild, Sune; Fanini, Lucia

2013-01-01

The exponential growth of the biomedical literature is making the need for efficient, accurate text-mining tools increasingly clear. The identification of named biological entities in text is a central and difficult task. We have developed an efficient algorithm and implementation of a dictionary......-based approach to named entity recognition, which we here use to identify names of species and other taxa in text. The tool, SPECIES, is more than an order of magnitude faster and as accurate as existing tools. The precision and recall was assessed both on an existing gold-standard corpus and on a new corpus...

MM-ISMSA: An Ultrafast and Accurate Scoring Function for Protein-Protein Docking.

Science.gov (United States)

Klett, Javier; Núñez-Salgado, Alfonso; Dos Santos, Helena G; Cortés-Cabrera, Álvaro; Perona, Almudena; Gil-Redondo, Rubén; Abia, David; Gago, Federico; Morreale, Antonio

2012-09-11

An ultrafast and accurate scoring function for protein-protein docking is presented. It includes (1) a molecular mechanics (MM) part based on a 12-6 Lennard-Jones potential; (2) an electrostatic component based on an implicit solvent model (ISM) with individual desolvation penalties for each partner in the protein-protein complex plus a hydrogen bonding term; and (3) a surface area (SA) contribution to account for the loss of water contacts upon protein-protein complex formation. The accuracy and performance of the scoring function, termed MM-ISMSA, have been assessed by (1) comparing the total binding energies, the electrostatic term, and its components (charge-charge and individual desolvation energies), as well as the per residue contributions, to results obtained with well-established methods such as APBSA or MM-PB(GB)SA for a set of 1242 decoy protein-protein complexes and (2) testing its ability to recognize the docking solution closest to the experimental structure as that providing the most favorable total binding energy. For this purpose, a test set consisting of 15 protein-protein complexes with known 3D structure mixed with 10 decoys for each complex was used. The correlation between the values afforded by MM-ISMSA and those from the other methods is quite remarkable (r(2) ∼ 0.9), and only 0.2-5.0 s (depending on the number of residues) are spent on a single calculation including an all vs all pairwise energy decomposition. On the other hand, MM-ISMSA correctly identifies the best docking solution as that closest to the experimental structure in 80% of the cases. Finally, MM-ISMSA can process molecular dynamics trajectories and reports the results as averaged values with their standard deviations. MM-ISMSA has been implemented as a plugin to the widely used molecular graphics program PyMOL, although it can also be executed in command-line mode. MM-ISMSA is distributed free of charge to nonprofit organizations.

Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification

DEFF Research Database (Denmark)

Andreatta, Massimo; Karosiene, Edita; Rasmussen, Michael

2015-01-01

with known binding registers, the new method NetMHCIIpan-3.1 significantly outperformed the earlier 3.0 version. We illustrate the impact of accurate binding core identification for the interpretation of T cell cross-reactivity using tetramer double staining with a CMV epitope and its variants mapped...

Seed Storage Proteins as a System for Teaching Protein Identification by Mass Spectrometry in Biochemistry Laboratory

Science.gov (United States)

Wilson, Karl A.; Tan-Wilson, Anna

2013-01-01

Mass spectrometry (MS) has become an important tool in studying biological systems. One application is the identification of proteins and peptides by the matching of peptide and peptide fragment masses to the sequences of proteins in protein sequence databases. Often prior protein separation of complex protein mixtures by 2D-PAGE is needed,…

Identification of Heat Shock Protein families and J-protein types by incorporating Dipeptide Composition into Chou's general PseAAC.

Science.gov (United States)

Ahmad, Saeed; Kabir, Muhammad; Hayat, Maqsood

2015-11-01

Heat Shock Proteins (HSPs) are the substantial ingredients for cell growth and viability, which are found in all living organisms. HSPs manage the process of folding and unfolding of proteins, the quality of newly synthesized proteins and protecting cellular homeostatic processes from environmental stress. On the basis of functionality, HSPs are categorized into six major families namely: (i) HSP20 or sHSP (ii) HSP40 or J-proteins types (iii) HSP60 or GroEL/ES (iv) HSP70 (v) HSP90 and (vi) HSP100. Identification of HSPs family and sub-family through conventional approaches is expensive and laborious. It is therefore, highly desired to establish an automatic, robust and accurate computational method for prediction of HSPs quickly and reliably. Regard, a computational model is developed for the prediction of HSPs family. In this model, protein sequences are formulated using three discrete methods namely: Split Amino Acid Composition, Pseudo Amino Acid Composition, and Dipeptide Composition. Several learning algorithms are utilized to choice the best one for high throughput computational model. Leave one out test is applied to assess the performance of the proposed model. The empirical results showed that support vector machine achieved quite promising results using Dipeptide Composition feature space. The predicted outcomes of proposed model are 90.7% accuracy for HSPs dataset and 97.04% accuracy for J-protein types, which are higher than existing methods in the literature so far. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

PDTD: a web-accessible protein database for drug target identification

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Gao Zhenting

2008-02-01

Full Text Available Abstract Background Target identification is important for modern drug discovery. With the advances in the development of molecular docking, potential binding proteins may be discovered by docking a small molecule to a repository of proteins with three-dimensional (3D structures. To complete this task, a reverse docking program and a drug target database with 3D structures are necessary. To this end, we have developed a web server tool, TarFisDock (Target Fishing Docking http://www.dddc.ac.cn/tarfisdock, which has been used widely by others. Recently, we have constructed a protein target database, Potential Drug Target Database (PDTD, and have integrated PDTD with TarFisDock. This combination aims to assist target identification and validation. Description PDTD is a web-accessible protein database for in silico target identification. It currently contains >1100 protein entries with 3D structures presented in the Protein Data Bank. The data are extracted from the literatures and several online databases such as TTD, DrugBank and Thomson Pharma. The database covers diverse information of >830 known or potential drug targets, including protein and active sites structures in both PDB and mol2 formats, related diseases, biological functions as well as associated regulating (signaling pathways. Each target is categorized by both nosology and biochemical function. PDTD supports keyword search function, such as PDB ID, target name, and disease name. Data set generated by PDTD can be viewed with the plug-in of molecular visualization tools and also can be downloaded freely. Remarkably, PDTD is specially designed for target identification. In conjunction with TarFisDock, PDTD can be used to identify binding proteins for small molecules. The results can be downloaded in the form of mol2 file with the binding pose of the probe compound and a list of potential binding targets according to their ranking scores. Conclusion PDTD serves as a comprehensive and

Large-Scale Off-Target Identification Using Fast and Accurate Dual Regularized One-Class Collaborative Filtering and Its Application to Drug Repurposing.

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Hansaim Lim

2016-10-01

Full Text Available Target-based screening is one of the major approaches in drug discovery. Besides the intended target, unexpected drug off-target interactions often occur, and many of them have not been recognized and characterized. The off-target interactions can be responsible for either therapeutic or side effects. Thus, identifying the genome-wide off-targets of lead compounds or existing drugs will be critical for designing effective and safe drugs, and providing new opportunities for drug repurposing. Although many computational methods have been developed to predict drug-target interactions, they are either less accurate than the one that we are proposing here or computationally too intensive, thereby limiting their capability for large-scale off-target identification. In addition, the performances of most machine learning based algorithms have been mainly evaluated to predict off-target interactions in the same gene family for hundreds of chemicals. It is not clear how these algorithms perform in terms of detecting off-targets across gene families on a proteome scale. Here, we are presenting a fast and accurate off-target prediction method, REMAP, which is based on a dual regularized one-class collaborative filtering algorithm, to explore continuous chemical space, protein space, and their interactome on a large scale. When tested in a reliable, extensive, and cross-gene family benchmark, REMAP outperforms the state-of-the-art methods. Furthermore, REMAP is highly scalable. It can screen a dataset of 200 thousands chemicals against 20 thousands proteins within 2 hours. Using the reconstructed genome-wide target profile as the fingerprint of a chemical compound, we predicted that seven FDA-approved drugs can be repurposed as novel anti-cancer therapies. The anti-cancer activity of six of them is supported by experimental evidences. Thus, REMAP is a valuable addition to the existing in silico toolbox for drug target identification, drug repurposing

Large-Scale Off-Target Identification Using Fast and Accurate Dual Regularized One-Class Collaborative Filtering and Its Application to Drug Repurposing.

Science.gov (United States)

Lim, Hansaim; Poleksic, Aleksandar; Yao, Yuan; Tong, Hanghang; He, Di; Zhuang, Luke; Meng, Patrick; Xie, Lei

2016-10-01

Target-based screening is one of the major approaches in drug discovery. Besides the intended target, unexpected drug off-target interactions often occur, and many of them have not been recognized and characterized. The off-target interactions can be responsible for either therapeutic or side effects. Thus, identifying the genome-wide off-targets of lead compounds or existing drugs will be critical for designing effective and safe drugs, and providing new opportunities for drug repurposing. Although many computational methods have been developed to predict drug-target interactions, they are either less accurate than the one that we are proposing here or computationally too intensive, thereby limiting their capability for large-scale off-target identification. In addition, the performances of most machine learning based algorithms have been mainly evaluated to predict off-target interactions in the same gene family for hundreds of chemicals. It is not clear how these algorithms perform in terms of detecting off-targets across gene families on a proteome scale. Here, we are presenting a fast and accurate off-target prediction method, REMAP, which is based on a dual regularized one-class collaborative filtering algorithm, to explore continuous chemical space, protein space, and their interactome on a large scale. When tested in a reliable, extensive, and cross-gene family benchmark, REMAP outperforms the state-of-the-art methods. Furthermore, REMAP is highly scalable. It can screen a dataset of 200 thousands chemicals against 20 thousands proteins within 2 hours. Using the reconstructed genome-wide target profile as the fingerprint of a chemical compound, we predicted that seven FDA-approved drugs can be repurposed as novel anti-cancer therapies. The anti-cancer activity of six of them is supported by experimental evidences. Thus, REMAP is a valuable addition to the existing in silico toolbox for drug target identification, drug repurposing, phenotypic screening, and

Calculation of accurate small angle X-ray scattering curves from coarse-grained protein models

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Stovgaard Kasper

2010-08-01

Full Text Available Abstract Background Genome sequencing projects have expanded the gap between the amount of known protein sequences and structures. The limitations of current high resolution structure determination methods make it unlikely that this gap will disappear in the near future. Small angle X-ray scattering (SAXS is an established low resolution method for routinely determining the structure of proteins in solution. The purpose of this study is to develop a method for the efficient calculation of accurate SAXS curves from coarse-grained protein models. Such a method can for example be used to construct a likelihood function, which is paramount for structure determination based on statistical inference. Results We present a method for the efficient calculation of accurate SAXS curves based on the Debye formula and a set of scattering form factors for dummy atom representations of amino acids. Such a method avoids the computationally costly iteration over all atoms. We estimated the form factors using generated data from a set of high quality protein structures. No ad hoc scaling or correction factors are applied in the calculation of the curves. Two coarse-grained representations of protein structure were investigated; two scattering bodies per amino acid led to significantly better results than a single scattering body. Conclusion We show that the obtained point estimates allow the calculation of accurate SAXS curves from coarse-grained protein models. The resulting curves are on par with the current state-of-the-art program CRYSOL, which requires full atomic detail. Our method was also comparable to CRYSOL in recognizing native structures among native-like decoys. As a proof-of-concept, we combined the coarse-grained Debye calculation with a previously described probabilistic model of protein structure, TorusDBN. This resulted in a significant improvement in the decoy recognition performance. In conclusion, the presented method shows great promise for

Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity.

Science.gov (United States)

Barkla, Bronwyn J

2016-09-08

Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may contribute to tolerance mechanisms by directly comparing protein abundance under stress conditions between genotypes differing in their stress responses. In this review, a summary is provided of the data accumulated from quantitative proteomic comparisons of crop genotypes/cultivars which present different stress tolerance responses when exposed to various abiotic stress conditions, including drought, salinity, high/low temperature, nutrient deficiency and UV-B irradiation. This field of research aims to identify molecular features that can be developed as biomarkers for crop improvement, however without accurate phenotyping, careful experimental design, statistical robustness and appropriate biomarker validation and verification it will be challenging to deliver what is promised.

Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity

Directory of Open Access Journals (Sweden)

Bronwyn J. Barkla

2016-09-01

Full Text Available Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may contribute to tolerance mechanisms by directly comparing protein abundance under stress conditions between genotypes differing in their stress responses. In this review, a summary is provided of the data accumulated from quantitative proteomic comparisons of crop genotypes/cultivars which present different stress tolerance responses when exposed to various abiotic stress conditions, including drought, salinity, high/low temperature, nutrient deficiency and UV-B irradiation. This field of research aims to identify molecular features that can be developed as biomarkers for crop improvement, however without accurate phenotyping, careful experimental design, statistical robustness and appropriate biomarker validation and verification it will be challenging to deliver what is promised.

Verification of protein biomarker specificity for the identification of biological stains by quadrupole time-of-flight mass spectrometry.

Science.gov (United States)

Legg, Kevin M; Powell, Roger; Reisdorph, Nichole; Reisdorph, Rick; Danielson, Phillip B

2017-03-01

Advances in proteomics technology over the past decade offer forensic serologists a greatly improved opportunity to accurately characterize the tissue source from which a DNA profile has been developed. Such information can provide critical context to evidence and can help to prioritize downstream DNA analyses. Previous proteome studies compiled panels of "candidate biomarkers" specific to each of five body fluids (i.e., peripheral blood, vaginal/menstrual fluid, seminal fluid, urine, and saliva). Here, a multiplex quadrupole time-of-flight mass spectrometry assay has been developed in order to verify the tissue/body fluid specificity the 23 protein biomarkers that comprise these panels and the consistency with which they can be detected across a sample population of 50 humans. Single-source samples of these human body fluids were accurately identified by the detection of one or more high-specificity biomarkers. Recovery of body fluid samples from a variety of substrates did not impede accurate characterization and, of the potential inhibitors assayed, only chewing tobacco juice appeared to preclude the identification of a target body fluid. Using a series of 2-component mixtures of human body fluids, the multiplex assay accurately identified both components in a single-pass. Only in the case of saliva and peripheral blood did matrix effects appear to impede the detection of salivary proteins. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification of outer membrane proteins of Yersinia pestis through biotinylation

NARCIS (Netherlands)

Smither, S.J.; Hill, J.; Baar, B.L.M. van; Hulst, A.G.; Jong, A.L. de; Titball, R.W.

2007-01-01

The outer membrane of Gram-negative bacteria contains proteins that might be good targets for vaccines, antimicrobials or detection systems. The identification of surface located proteins using traditional methods is often difficult. Yersinia pestis, the causative agent of plague, was labelled with

Mass spectrometry allows direct identification of proteins in large genomes

DEFF Research Database (Denmark)

Küster, B; Mortensen, Peter V.; Andersen, Jens S.

2001-01-01

Proteome projects seek to provide systematic functional analysis of the genes uncovered by genome sequencing initiatives. Mass spectrometric protein identification is a key requirement in these studies but to date, database searching tools rely on the availability of protein sequences derived fro...

Use of ribosomal proteins as biomarkers for identification of Flavobacterium psychrophilum by MALDI-TOF mass spectrometry.

Science.gov (United States)

Fernández-Álvarez, Clara; Torres-Corral, Yolanda; Santos, Ysabel

2018-01-06

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS) is a rapid methodology for identification of bacteria that is increasingly used in diagnostic laboratories. This work aimed at evaluating the potential of MALDI-TOF-MS for identification of the main serotypes of Flavobacterium psychrophilum isolated from salmonids, and its discrimination from closely related Flavobacterium spp. A mass spectra library was constructed by analysing 70 F. psychrophilum strains representing the serotypes O1, O2a, O2b and O3, including reference and clinical isolates. Peak mass lists were examined using the Mass-Up software for the detection of potential biomarkers, similarity and cluster analysis. Fourteen species-identifying biomarkers were detected in all the F. psychrophilum isolates tested, moreover, sets of serotype-identifying biomarkers ions were selected. F. psychrophilum-specific biomarkers were identified as ribosomal proteins by matching with protein databases. Furthermore, sequence variation corresponding to amino acid exchanges in several biomarker proteins were tentatively assigned. Closely related Flavobacterium species (F. flevense, F. succinicans, F. columnare, F. branchiophilum and F. johnsoniae) could be differentiated from F. psychrophilum by defining species identifying biomarkers and hierarchical cluster analysis. These results demonstrated that MALDI-TOF spectrometry represents a powerful tool for an accurate identification of the fish pathogen F. psychrophilum as well as for epidemiological studies. The results obtained in this study demonstrated that MALDI-TOF mass spectrometry represents a powerful tool that can be used by diagnostic laboratories for rapid identification of the fish pathogen Flavobacterium psychrophilum and its differentiation from other Flavobacterium-related species. Analysis of mass peak lists revealed the potential of the MALDI-TOF technique to identify epidemiologically important serotypes affecting

Final Progress Report: Isotope Identification Algorithm for Rapid and Accurate Determination of Radioisotopes Feasibility Study

International Nuclear Information System (INIS)

Rawool-Sullivan, Mohini; Bounds, John Alan; Brumby, Steven P.; Prasad, Lakshman; Sullivan, John P.

2012-01-01

This is the final report of the project titled, 'Isotope Identification Algorithm for Rapid and Accurate Determination of Radioisotopes,' PMIS project number LA10-HUMANID-PD03. The goal of the work was to demonstrate principles of emulating a human analysis approach towards the data collected using radiation isotope identification devices (RIIDs). It summarizes work performed over the FY10 time period. The goal of the work was to demonstrate principles of emulating a human analysis approach towards the data collected using radiation isotope identification devices (RIIDs). Human analysts begin analyzing a spectrum based on features in the spectrum - lines and shapes that are present in a given spectrum. The proposed work was to carry out a feasibility study that will pick out all gamma ray peaks and other features such as Compton edges, bremsstrahlung, presence/absence of shielding and presence of neutrons and escape peaks. Ultimately success of this feasibility study will allow us to collectively explain identified features and form a realistic scenario that produced a given spectrum in the future. We wanted to develop and demonstrate machine learning algorithms that will qualitatively enhance the automated identification capabilities of portable radiological sensors that are currently being used in the field.

Identification of protein binding in pictorial art Cuban

International Nuclear Information System (INIS)

Mendoza, Ariadna; Correa, Maurin; Maqueira, Isis

2011-01-01

In this paper were implemented microanalysis methodologies by histochemical analysis, and infrared spectroscopy to determine the nature of the binder in paintings and Gas Chromatography (GC) coupled to Mass Spectrometry (MS) for identification of protein binders of common use in tempera technique with the aim of having these methods as part of the identification of artistic materials in Cuban cultural heritage carried out by Archaeometry Laboratory of Havana city's Historian Cabinet. The methodologies implemented were evaluated using model samples of traditional painting techniques with variable protein binder: yolk, egg white, casein, nut oil and animal glue; ageing for 5 years. The models samples were correctly identified. It was determined the interference of pigments with the presence of nitrogen by histochemical analysis with Amido Black dye. IR spectroscopy technique allowed to differentiate between oily and mixed (oil plus protein) techniques and tempera with yolk. Oily technique was identified in wall paintings of the New San Francisco church (XIX century) and the Obrapia House (XVII century) and the technique of tempera with animal glue in the polychrome of the XVIII century which represents St. John the Evangelist belonging to the San Juan de Letran church

Computational identification of strain-, species- and genus-specific proteins

Directory of Open Access Journals (Sweden)

Thiagarajan Rathi

2005-11-01

Full Text Available Abstract Background The identification of unique proteins at different taxonomic levels has both scientific and practical value. Strain-, species- and genus-specific proteins can provide insight into the criteria that define an organism and its relationship with close relatives. Such proteins can also serve as taxon-specific diagnostic targets. Description A pipeline using a combination of computational and manual analyses of BLAST results was developed to identify strain-, species-, and genus-specific proteins and to catalog the closest sequenced relative for each protein in a proteome. Proteins encoded by a given strain are preliminarily considered to be unique if BLAST, using a comprehensive protein database, fails to retrieve (with an e-value better than 0.001 any protein not encoded by the query strain, species or genus (for strain-, species- and genus-specific proteins respectively, or if BLAST, using the best hit as the query (reverse BLAST, does not retrieve the initial query protein. Results are manually inspected for homology if the initial query is retrieved in the reverse BLAST but is not the best hit. Sequences unlikely to retrieve homologs using the default BLOSUM62 matrix (usually short sequences are re-tested using the PAM30 matrix, thereby increasing the number of retrieved homologs and increasing the stringency of the search for unique proteins. The above protocol was used to examine several food- and water-borne pathogens. We find that the reverse BLAST step filters out about 22% of proteins with homologs that would otherwise be considered unique at the genus and species levels. Analysis of the annotations of unique proteins reveals that many are remnants of prophage proteins, or may be involved in virulence. The data generated from this study can be accessed and further evaluated from the CUPID (Core and Unique Protein Identification system web site (updated semi-annually at http://pir.georgetown.edu/cupid. Conclusion CUPID

Automated protein identification by the combination of MALDI MS and MS/MS spectra from different instruments.

Science.gov (United States)

Levander, Fredrik; James, Peter

2005-01-01

The identification of proteins separated on two-dimensional gels is most commonly performed by trypsin digestion and subsequent matrix-assisted laser desorption ionization (MALDI) with time-of-flight (TOF). Recently, atmospheric pressure (AP) MALDI coupled to an ion trap (IT) has emerged as a convenient method to obtain tandem mass spectra (MS/MS) from samples on MALDI target plates. In the present work, we investigated the feasibility of using the two methodologies in line as a standard method for protein identification. In this setup, the high mass accuracy MALDI-TOF spectra are used to calibrate the peptide precursor masses in the lower mass accuracy AP-MALDI-IT MS/MS spectra. Several software tools were developed to automate the analysis process. Two sets of MALDI samples, consisting of 142 and 421 gel spots, respectively, were analyzed in a highly automated manner. In the first set, the protein identification rate increased from 61% for MALDI-TOF only to 85% for MALDI-TOF combined with AP-MALDI-IT. In the second data set the increase in protein identification rate was from 44% to 58%. AP-MALDI-IT MS/MS spectra were in general less effective than the MALDI-TOF spectra for protein identification, but the combination of the two methods clearly enhanced the confidence in protein identification.

Identification of Essential Proteins Based on a New Combination of Local Interaction Density and Protein Complexes.

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Jiawei Luo

Full Text Available Computational approaches aided by computer science have been used to predict essential proteins and are faster than expensive, time-consuming, laborious experimental approaches. However, the performance of such approaches is still poor, making practical applications of computational approaches difficult in some fields. Hence, the development of more suitable and efficient computing methods is necessary for identification of essential proteins.In this paper, we propose a new method for predicting essential proteins in a protein interaction network, local interaction density combined with protein complexes (LIDC, based on statistical analyses of essential proteins and protein complexes. First, we introduce a new local topological centrality, local interaction density (LID, of the yeast PPI network; second, we discuss a new integration strategy for multiple bioinformatics. The LIDC method was then developed through a combination of LID and protein complex information based on our new integration strategy. The purpose of LIDC is discovery of important features of essential proteins with their neighbors in real protein complexes, thereby improving the efficiency of identification.Experimental results based on three different PPI(protein-protein interaction networks of Saccharomyces cerevisiae and Escherichia coli showed that LIDC outperformed classical topological centrality measures and some recent combinational methods. Moreover, when predicting MIPS datasets, the better improvement of performance obtained by LIDC is over all nine reference methods (i.e., DC, BC, NC, LID, PeC, CoEWC, WDC, ION, and UC.LIDC is more effective for the prediction of essential proteins than other recently developed methods.

Fast and accurate protein substructure searching with simulated annealing and GPUs

Directory of Open Access Journals (Sweden)

Stivala Alex D

2010-09-01

Full Text Available Abstract Background Searching a database of protein structures for matches to a query structure, or occurrences of a structural motif, is an important task in structural biology and bioinformatics. While there are many existing methods for structural similarity searching, faster and more accurate approaches are still required, and few current methods are capable of substructure (motif searching. Results We developed an improved heuristic for tableau-based protein structure and substructure searching using simulated annealing, that is as fast or faster and comparable in accuracy, with some widely used existing methods. Furthermore, we created a parallel implementation on a modern graphics processing unit (GPU. Conclusions The GPU implementation achieves up to 34 times speedup over the CPU implementation of tableau-based structure search with simulated annealing, making it one of the fastest available methods. To the best of our knowledge, this is the first application of a GPU to the protein structural search problem.

Identification of cell wall proteins in the flax (Linum usitatissimum) stem.

Science.gov (United States)

Day, Arnaud; Fénart, Stéphane; Neutelings, Godfrey; Hawkins, Simon; Rolando, Christian; Tokarski, Caroline

2013-03-01

Sequential salt (CaCl2 , LiCl) extractions were used to obtain fractions enriched in cell wall proteins (CWPs) from the stem of 60-day-old flax (Linum usitatissimum) plants. High-resolution FT-ICR MS analysis and the use of recently published genomic data allowed the identification of 11 912 peptides corresponding to a total of 1418 different proteins. Subcellular localization using TargetP, Predotar, and WoLF PSORT led to the identification of 152 putative flax CWPs that were classified into nine different functional classes previously established for Arabidopsis thaliana. Examination of different functional classes revealed the presence of a number of proteins known to be involved in, or potentially involved in cell-wall metabolism in plants. The flax stem cell wall proteome was also compared with transcriptomic data previously obtained on comparable samples. This study represents a major contribution to the identification of CWPs in flax and will lead to a better understanding of cell wall biology in this species. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Performance of VITEK mass spectrometry V3.0 for rapid identification of clinical Aspergillus fumigatus in different culture conditions based on ribosomal proteins

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Zhou L

2017-12-01

Full Text Available Longrong Zhou, Yongquan Chen, Yuanhong Xu Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Anhui, Hefei, People’s Republic of China Abstract: Fast and accurate discrimination of Aspergillus fumigatus is significant, since misidentification may lead to inappropriate clinical therapy. This study assessed VITEK mass spectrometry (MS V3.0 for A. fumigatus identification using extracted fungal ribosomal proteins. A total of 52 isolates preliminarily identified as A. fumigatus by traditional morphological methods were inoculated in three different culture media and cultured at two different temperatures. The specific spectral fingerprints of different culture time points (48, 72, 96, and 120 h were obtained. Of all strains, 88.5% (46/52 were discriminated as A. fumigatus, while the remaining 11.5% (6/52 produced results inconsistent with morphological analysis. Molecular sequencing, as a reference method for species identification, was used to validate the morphological analysis and matrix-assisted laser desorption/ionization time of flight MS. Chi-square tests (Χ2 test, P=0.05 demonstrated that the culture medium and incubation temperature had no effects on identification accuracy; however, identification accuracy of the strains in the 48-h group was lower than that in other groups. In addition, we found that ribosomal proteins extracted from A. fumigatus can be stored in different environments for at least 1 week, with their profiles remaining stable and strain identification results showing no change. This is beneficial for medical institutions with no mass spectrometer at hand. Overall, this study showed the powerful ability of VITEK MS V 3.0 in identifying A. fumigatus. Keywords: VITEK MS V 3.0, Aspergillus fumigatus, identification, ribosomal protein, spectral fingerprints, fungal, matrix assisted laser desorption ionization-time of flight mass spectrometry, MALDI-TOF MS

Efficiency of Database Search for Identification of Mutated and Modified Proteins via Mass Spectrometry

OpenAIRE

Pevzner, Pavel A.; Mulyukov, Zufar; Dancik, Vlado; Tang, Chris L

2001-01-01

Although protein identification by matching tandem mass spectra (MS/MS) against protein databases is a widespread tool in mass spectrometry, the question about reliability of such searches remains open. Absence of rigorous significance scores in MS/MS database search makes it difficult to discard random database hits and may lead to erroneous protein identification, particularly in the case of mutated or post-translationally modified peptides. This problem is especially important for high-thr...

A systematic identification of species-specific protein succinylation sites using joint element features information

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Hasan MM

2017-08-01

Full Text Available Md Mehedi Hasan,1 Mst Shamima Khatun,2 Md Nurul Haque Mollah,2 Cao Yong,3 Dianjing Guo1 1School of Life Sciences and the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, New Territory, Hong Kong, People’s Republic of China; 2Laboratory of Bioinformatics, Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh; 3Department of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen, People’s Republic of China Abstract: Lysine succinylation, an important type of protein posttranslational modification, plays significant roles in many cellular processes. Accurate identification of succinylation sites can facilitate our understanding about the molecular mechanism and potential roles of lysine succinylation. However, even in well-studied systems, a majority of the succinylation sites remain undetected because the traditional experimental approaches to succinylation site identification are often costly, time-consuming, and laborious. In silico approach, on the other hand, is potentially an alternative strategy to predict succinylation substrates. In this paper, a novel computational predictor SuccinSite2.0 was developed for predicting generic and species-specific protein succinylation sites. This predictor takes the composition of profile-based amino acid and orthogonal binary features, which were used to train a random forest classifier. We demonstrated that the proposed SuccinSite2.0 predictor outperformed other currently existing implementations on a complementarily independent dataset. Furthermore, the important features that make visible contributions to species-specific and cross-species-specific prediction of protein succinylation site were analyzed. The proposed predictor is anticipated to be a useful computational resource for lysine succinylation site prediction. The integrated species-specific online tool of SuccinSite2.0 is publicly

CMASA: an accurate algorithm for detecting local protein structural similarity and its application to enzyme catalytic site annotation

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Li Gong-Hua

2010-08-01

Full Text Available Abstract Background The rapid development of structural genomics has resulted in many "unknown function" proteins being deposited in Protein Data Bank (PDB, thus, the functional prediction of these proteins has become a challenge for structural bioinformatics. Several sequence-based and structure-based methods have been developed to predict protein function, but these methods need to be improved further, such as, enhancing the accuracy, sensitivity, and the computational speed. Here, an accurate algorithm, the CMASA (Contact MAtrix based local Structural Alignment algorithm, has been developed to predict unknown functions of proteins based on the local protein structural similarity. This algorithm has been evaluated by building a test set including 164 enzyme families, and also been compared to other methods. Results The evaluation of CMASA shows that the CMASA is highly accurate (0.96, sensitive (0.86, and fast enough to be used in the large-scale functional annotation. Comparing to both sequence-based and global structure-based methods, not only the CMASA can find remote homologous proteins, but also can find the active site convergence. Comparing to other local structure comparison-based methods, the CMASA can obtain the better performance than both FFF (a method using geometry to predict protein function and SPASM (a local structure alignment method; and the CMASA is more sensitive than PINTS and is more accurate than JESS (both are local structure alignment methods. The CMASA was applied to annotate the enzyme catalytic sites of the non-redundant PDB, and at least 166 putative catalytic sites have been suggested, these sites can not be observed by the Catalytic Site Atlas (CSA. Conclusions The CMASA is an accurate algorithm for detecting local protein structural similarity, and it holds several advantages in predicting enzyme active sites. The CMASA can be used in large-scale enzyme active site annotation. The CMASA can be available by the

Sad people are more accurate at expression identification with a smaller own-ethnicity bias than happy people.

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Hills, Peter J; Hill, Dominic M

2017-07-12

Sad individuals perform more accurately at face identity recognition (Hills, Werno, & Lewis, 2011), possibly because they scan more of the face during encoding. During expression identification tasks, sad individuals do not fixate on the eyes as much as happier individuals (Wu, Pu, Allen, & Pauli, 2012). Fixating on features other than the eyes leads to a reduced own-ethnicity bias (Hills & Lewis, 2006). This background indicates that sad individuals would not view the eyes as much as happy individuals and this would result in improved expression recognition and a reduced own-ethnicity bias. This prediction was tested using an expression identification task, with eye tracking. We demonstrate that sad-induced participants show enhanced expression recognition and a reduced own-ethnicity bias than happy-induced participants due to scanning more facial features. We conclude that mood affects eye movements and face encoding by causing a wider sampling strategy and deeper encoding of facial features diagnostic for expression identification.

Neural network and SVM classifiers accurately predict lipid binding proteins, irrespective of sequence homology.

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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.

Pooled protein immunization for identification of cell surface antigens in Streptococcus sanguinis.

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Xiuchun Ge

2010-07-01

Full Text Available Available bacterial genomes provide opportunities for screening vaccines by reverse vaccinology. Efficient identification of surface antigens is required to reduce time and animal cost in this technology. We developed an approach to identify surface antigens rapidly in Streptococcus sanguinis, a common infective endocarditis causative species.We applied bioinformatics for antigen prediction and pooled antigens for immunization. Forty-seven surface-exposed proteins including 28 lipoproteins and 19 cell wall-anchored proteins were chosen based on computer algorithms and comparative genomic analyses. Eight proteins among these candidates and 2 other proteins were pooled together to immunize rabbits. The antiserum reacted strongly with each protein and with S. sanguinis whole cells. Affinity chromatography was used to purify the antibodies to 9 of the antigen pool components. Competitive ELISA and FACS results indicated that these 9 proteins were exposed on S. sanguinis cell surfaces. The purified antibodies had demonstrable opsonic activity.The results indicate that immunization with pooled proteins, in combination with affinity purification, and comprehensive immunological assays may facilitate cell surface antigen identification to combat infectious diseases.

Pooled protein immunization for identification of cell surface antigens in Streptococcus sanguinis.

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Ge, Xiuchun; Kitten, Todd; Munro, Cindy L; Conrad, Daniel H; Xu, Ping

2010-07-26

Available bacterial genomes provide opportunities for screening vaccines by reverse vaccinology. Efficient identification of surface antigens is required to reduce time and animal cost in this technology. We developed an approach to identify surface antigens rapidly in Streptococcus sanguinis, a common infective endocarditis causative species. We applied bioinformatics for antigen prediction and pooled antigens for immunization. Forty-seven surface-exposed proteins including 28 lipoproteins and 19 cell wall-anchored proteins were chosen based on computer algorithms and comparative genomic analyses. Eight proteins among these candidates and 2 other proteins were pooled together to immunize rabbits. The antiserum reacted strongly with each protein and with S. sanguinis whole cells. Affinity chromatography was used to purify the antibodies to 9 of the antigen pool components. Competitive ELISA and FACS results indicated that these 9 proteins were exposed on S. sanguinis cell surfaces. The purified antibodies had demonstrable opsonic activity. The results indicate that immunization with pooled proteins, in combination with affinity purification, and comprehensive immunological assays may facilitate cell surface antigen identification to combat infectious diseases.

Performance of VITEK mass spectrometry V3.0 for rapid identification of clinical Aspergillus fumigatus in different culture conditions based on ribosomal proteins.

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Zhou, Longrong; Chen, Yongquan; Xu, Yuanhong

2017-01-01

Fast and accurate discrimination of Aspergillus fumigatus is significant, since misidentification may lead to inappropriate clinical therapy. This study assessed VITEK mass spectrometry (MS) V3.0 for A. fumigatus identification using extracted fungal ribosomal proteins. A total of 52 isolates preliminarily identified as A. fumigatus by traditional morphological methods were inoculated in three different culture media and cultured at two different temperatures. The specific spectral fingerprints of different culture time points (48, 72, 96, and 120 h) were obtained. Of all strains, 88.5% (46/52) were discriminated as A. fumigatus , while the remaining 11.5% (6/52) produced results inconsistent with morphological analysis. Molecular sequencing, as a reference method for species identification, was used to validate the morphological analysis and matrix-assisted laser desorption/ionization time of flight MS. Chi-square tests ( χ 2 test, P =0.05) demonstrated that the culture medium and incubation temperature had no effects on identification accuracy; however, identification accuracy of the strains in the 48-h group was lower than that in other groups. In addition, we found that ribosomal proteins extracted from A. fumigatus can be stored in different environments for at least 1 week, with their profiles remaining stable and strain identification results showing no change. This is beneficial for medical institutions with no mass spectrometer at hand. Overall, this study showed the powerful ability of VITEK MS V 3.0 in identifying A. fumigatus .

A combinatorial perspective of the protein inference problem.

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Yang, Chao; He, Zengyou; Yu, Weichuan

2013-01-01

In a shotgun proteomics experiment, proteins are the most biologically meaningful output. The success of proteomics studies depends on the ability to accurately and efficiently identify proteins. Many methods have been proposed to facilitate the identification of proteins from peptide identification results. However, the relationship between protein identification and peptide identification has not been thoroughly explained before. In this paper, we devote ourselves to a combinatorial perspective of the protein inference problem. We employ combinatorial mathematics to calculate the conditional protein probabilities (protein probability means the probability that a protein is correctly identified) under three assumptions, which lead to a lower bound, an upper bound, and an empirical estimation of protein probabilities, respectively. The combinatorial perspective enables us to obtain an analytical expression for protein inference. Our method achieves comparable results with ProteinProphet in a more efficient manner in experiments on two data sets of standard protein mixtures and two data sets of real samples. Based on our model, we study the impact of unique peptides and degenerate peptides (degenerate peptides are peptides shared by at least two proteins) on protein probabilities. Meanwhile, we also study the relationship between our model and ProteinProphet. We name our program ProteinInfer. Its Java source code, our supplementary document and experimental results are available at: >http://bioinformatics.ust.hk/proteininfer.

Identification of Arsenic Direct-Binding Proteins in Acute Promyelocytic Leukaemia Cells

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Tao Zhang

2015-11-01

Full Text Available The identification of arsenic direct-binding proteins is essential for determining the mechanism by which arsenic trioxide achieves its chemotherapeutic effects. At least two cysteines close together in the amino acid sequence are crucial to the binding of arsenic and essential to the identification of arsenic-binding proteins. In the present study, arsenic binding proteins were pulled down with streptavidin and identified using a liquid chromatograph-mass spectrometer (LC-MS/MS. More than 40 arsenic-binding proteins were separated, and redox-related proteins, glutathione S-transferase P1 (GSTP1, heat shock 70 kDa protein 9 (HSPA9 and pyruvate kinase M2 (PKM2, were further studied using binding assays in vitro. Notably, PKM2 has a high affinity for arsenic. In contrast to PKM2, GSTP1and HSPA9 did not combine with arsenic directly in vitro. These observations suggest that arsenic-mediated acute promyelocytic leukaemia (APL suppressive effects involve PKM2. In summary, we identified several arsenic binding proteins in APL cells and investigated the therapeutic mechanisms of arsenic trioxide for APL. Further investigation into specific signal pathways by which PKM2 mediates APL developments may lead to a better understanding of arsenic effects on APL.

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.

Protein social behavior makes a stronger signal for partner identification than surface geometry

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Laine, Elodie

2016-01-01

ABSTRACT Cells are interactive living systems where proteins movements, interactions and regulation are substantially free from centralized management. How protein physico‐chemical and geometrical properties determine who interact with whom remains far from fully understood. We show that characterizing how a protein behaves with many potential interactors in a complete cross‐docking study leads to a sharp identification of its cellular/true/native partner(s). We define a sociability index, or S‐index, reflecting whether a protein likes or not to pair with other proteins. Formally, we propose a suitable normalization function that accounts for protein sociability and we combine it with a simple interface‐based (ranking) score to discriminate partners from non‐interactors. We show that sociability is an important factor and that the normalization permits to reach a much higher discriminative power than shape complementarity docking scores. The social effect is also observed with more sophisticated docking algorithms. Docking conformations are evaluated using experimental binding sites. These latter approximate in the best possible way binding sites predictions, which have reached high accuracy in recent years. This makes our analysis helpful for a global understanding of partner identification and for suggesting discriminating strategies. These results contradict previous findings claiming the partner identification problem being solvable solely with geometrical docking. Proteins 2016; 85:137–154. © 2016 Wiley Periodicals, Inc. PMID:27802579

MASS SPECTROMETRIC ANALYSIS FOR THE IDENTIFICATION OF THUNNUS GENUS FOUR SPECIES

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T. Pepe

2011-01-01

Full Text Available An accurate identification of similar fish species is necessary to prevent illegal substitution and is imposed by labeling regulations in UE countries (1. The genus Thunnus comprises many species of different quality and commercial value. The increasing trade of fish preparations of the species included in this genus and the consequent loss of the external anatomical and morphological features enables fraudulent substitutions. This study reports data relating to the proteomic analysis of four tuna species (T. thynnus, T. alalunga, T. albacares, T. obesus. Sarcoplasmic proteins were studied by mono and two dimensional electrophoresis. The most significant proteins for the characterization of the species were analyzed by mass spectrometric techniques. As reported in a previous study (2, an accurate identification of the species seems possible, owing to the polymorphism displayed by the species of the Thunnus genus.

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.

Identification of ATM Protein Kinase Phosphorylation Sites by Mass Spectrometry.

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Graham, Mark E; Lavin, Martin F; Kozlov, Sergei V

2017-01-01

ATM (ataxia-telangiectasia mutated) protein kinase is a key regulator of cellular responses to DNA damage and oxidative stress. DNA damage triggers complex cascade of signaling events leading to numerous posttranslational modification on multitude of proteins. Understanding the regulation of ATM kinase is therefore critical not only for understanding the human genetic disorder ataxia-telangiectasia and potential treatment strategies, but essential for deciphering physiological responses of cells to stress. These responses play an important role in carcinogenesis, neurodegeneration, and aging. We focus here on the identification of DNA damage inducible ATM phosphorylation sites to understand the importance of autophosphorylation in the mechanism of ATM kinase activation. We demonstrate the utility of using immunoprecipitated ATM in quantitative LC-MS/MS workflow with stable isotope dimethyl labeling of ATM peptides for identification of phosphorylation sites.

Verification of Ribosomal Proteins of Aspergillus fumigatus for Use as Biomarkers in MALDI-TOF MS Identification.

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Nakamura, Sayaka; Sato, Hiroaki; Tanaka, Reiko; Yaguchi, Takashi

2016-01-01

We have previously proposed a rapid identification method for bacterial strains based on the profiles of their ribosomal subunit proteins (RSPs), observed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). This method can perform phylogenetic characterization based on the mass of housekeeping RSP biomarkers, ideally calculated from amino acid sequence information registered in public protein databases. With the aim of extending its field of application to medical mycology, this study investigates the actual state of information of RSPs of eukaryotic fungi registered in public protein databases through the characterization of ribosomal protein fractions extracted from genome-sequenced Aspergillus fumigatus strains Af293 and A1163 as a model. In this process, we have found that the public protein databases harbor problems. The RSP names are in confusion, so we have provisionally unified them using the yeast naming system. The most serious problem is that many incorrect sequences are registered in the public protein databases. Surprisingly, more than half of the sequences are incorrect, due chiefly to mis-annotation of exon/intron structures. These errors could be corrected by a combination of in silico inspection by sequence homology analysis and MALDI-TOF MS measurements. We were also able to confirm conserved post-translational modifications in eleven RSPs. After these verifications, the masses of 31 expressed RSPs under 20,000 Da could be accurately confirmed. These RSPs have a potential to be useful biomarkers for identifying clinical isolates of A. fumigatus .

Accurate identification of layer number for few-layer WS2 and WSe2 via spectroscopic study.

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Li, Yuanzheng; Li, Xinshu; Yu, Tong; Yang, Guochun; Chen, Heyu; Zhang, Cen; Feng, Qiushi; Ma, Jiangang; Liu, Weizhen; Xu, Haiyang; Liu, Yichun; Liu, Xinfeng

2018-03-23

Transition metal dichalcogenides (TMDs) with a typical layered structure are highly sensitive to their layer number in optical and electronic properties. Seeking a simple and effective method for layer number identification is very important to low-dimensional TMD samples. Herein, a rapid and accurate layer number identification of few-layer WS 2 and WSe 2 is proposed via locking their photoluminescence (PL) peak-positions. As the layer number of WS 2 /WSe 2 increases, it is found that indirect transition emission is more thickness-sensitive than direct transition emission, and the PL peak-position differences between the indirect and direct transitions can be regarded as fingerprints to identify their layer number. Theoretical calculation confirms that the notable thickness-sensitivity of indirect transition derives from the variations of electron density of states of W atom d-orbitals and chalcogen atom p-orbitals. Besides, the PL peak-position differences between the indirect and direct transitions are almost independent of different insulating substrates. This work not only proposes a new method for layer number identification via PL studies, but also provides a valuable insight into the thickness-dependent optical and electronic properties of W-based TMDs.

Accelerated identification of proteins by mass spectrometry by employing covalent pre-gel staining with Uniblue A.

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Marco A Mata-Gómez

Full Text Available BACKGROUND: The identification of proteins by mass spectrometry is a standard method in biopharmaceutical quality control and biochemical research. Prior to identification by mass spectrometry, proteins are usually pre-separated by electrophoresis. However, current protein staining and de-staining protocols are tedious and time consuming, and therefore prolong the sample preparation time for mass spectrometry. METHODOLOGY AND PRINCIPAL FINDINGS: We developed a 1-minute covalent pre-gel staining protocol for proteins, which does not require de-staining before the mass spectrometry analysis. We investigated the electrophoretic properties of derivatized proteins and peptides and studied their behavior in mass spectrometry. Further, we elucidated the preferred reaction of proteins with Uniblue A and demonstrate the integration of the peptide derivatization into typical informatics tools. CONCLUSIONS AND SIGNIFICANCE: The Uniblue A staining method drastically speeds up the sample preparation for the mass spectrometry based identification of proteins. The application of this chemo-proteomic strategy will be advantageous for routine quality control of proteins and for time-critical tasks in protein analysis.

Enhanced detection method for corneal protein identification using shotgun proteomics

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Schlager John J

2009-06-01

Full Text Available Abstract Background The cornea is a specialized transparent connective tissue responsible for the majority of light refraction and image focus for the retina. There are three main layers of the cornea: the epithelium that is exposed and acts as a protective barrier for the eye, the center stroma consisting of parallel collagen fibrils that refract light, and the endothelium that is responsible for hydration of the cornea from the aqueous humor. Normal cornea is an immunologically privileged tissue devoid of blood vessels, but injury can produce a loss of these conditions causing invasion of other processes that degrade the homeostatic properties resulting in a decrease in the amount of light refracted onto the retina. Determining a measure and drift of phenotypic cornea state from normal to an injured or diseased state requires knowledge of the existing protein signature within the tissue. In the study of corneal proteins, proteomics procedures have typically involved the pulverization of the entire cornea prior to analysis. Separation of the epithelium and endothelium from the core stroma and performing separate shotgun proteomics using liquid chromatography/mass spectrometry results in identification of many more proteins than previously employed methods using complete pulverized cornea. Results Rabbit corneas were purchased, the epithelium and endothelium regions were removed, proteins processed and separately analyzed using liquid chromatography/mass spectrometry. Proteins identified from separate layers were compared against results from complete corneal samples. Protein digests were separated using a six hour liquid chromatographic gradient and ion-trap mass spectrometry used for detection of eluted peptide fractions. The SEQUEST database search results were filtered to allow only proteins with match probabilities of equal or better than 10-3 and peptides with a probability of 10-2 or less with at least two unique peptides isolated within

Proteomics - a novel approach to the identification and characterisation of plasmodesmatal proteins

International Nuclear Information System (INIS)

Faulkner, C.R.; Blackman, L.M.; Lyon, B.R.; Overall, R.L.

2001-01-01

The development of proteomic methods, such as 2-dimensional gel electrophoresis (2-DE), has established a high resolution means of identifying and characterising proteins from a given protein mixture. The biochemical composition of plasmodesmata, the intercellular channels between plant cells, is poorly described despite extensive attempts to identify protemaceous plasmodesmatal components. These attempts have been confounded by the large number of proteins in the cell wall. We have exploited the anatomy of the alga Chara corallina to separate tissues with (nodal cells) and tissues without (internodal cells) plasmodesmata. Proteins specific to the cytoplasmic and wall protein extracts of nodal and internodal tissue were identified by comparison of 2-DE gels of these extracts. In particular, a 95 kDa protein was identified as specific to the nodal cells in both 1-dimensional and 2-dimensional comparisons of cytoplasmic nodal and internodal protein extracts. This protein was analysed by electron spray ionization time of flight tandem mass spectroscopy (ESI-TOF MS/MS) and the sequence obtained showed similarity to plant lipoxygenases. Further proteins of interest were identified in 2-DE resolution of extracts from the nodal cytoplasm, including two 49 kDa proteins and two 46 kDa proteins, and from the nodal cell walls, including a cluster of proteins around 30 kDa. Thus, a proteomic strategy for the identification and characterisation of proteins specific to different cell types in Chara corallina has been developed, with potential application to the identification and characterisation of plasmodesmatal proteins

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.

Are neutral loss and internal product ions useful for top-down protein identification?

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Xiao, Kaijie; Yu, Fan; Fang, Houqin; Xue, Bingbing; Liu, Yan; Li, Yunhui; Tian, Zhixin

2017-05-08

Neutral loss and internal product ions have been found to be significant in both peptide and protein tandem mass spectra and they have been proposed to be included in database search and for protein identification. In addition to common canonical b/y ions in collision-based dissociation or c/z ions in electron-based dissociation, inclusion of neutral loss and internal product ions would certainly make better use of tandem mass spectra data; however, their ultimate utility for protein identification with false discovery rate control remains unclear. Here we report our proteome-level utility benchmarking of neutral loss and internal product ions with tandem mass spectra of intact E. coli proteome. Utility of internal product ions was further evaluated at the protein level using selected tandem mass spectra of individual E. coli proteins. We found that both neutral loss and internal products ions do not have direct utility for protein identification when they were used for scoring of P Score; but they do have indirect utility for provision of more canonical b/y ions when they are included in the database search and overlapping ions between different ion types are resolved. Tandem mass spectrometry has evolved to be a state-of-the-art method for characterization of protein primary structures (including amino acid sequence, post-translational modifications (PTMs) as well as their site location), where full study and utilization tandem mass spectra and product ions are indispensable. This primary structure information is essential for higher order structure and eventual function study of proteins. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification and analysis of multi-protein complexes in placenta.

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Fuqiang Wang

Full Text Available Placental malfunction induces pregnancy disorders which contribute to life-threatening complications for both the mother and the fetus. Identification and characterization of placental multi-protein complexes is an important step to integratedly understand the protein-protein interaction networks in placenta which determine placental function. In this study, blue native/sodium dodecyl sulfate polyacrylamide gel electrophoresis (BN/SDS-PAGE and Liquid chromatography-tandem mass spectrometry (LC-MS/MS were used to screen the multi-protein complexes in placenta. 733 unique proteins and 34 known and novel heterooligomeric multi-protein complexes including mitochondrial respiratory chain complexes, integrin complexes, proteasome complexes, histone complex, and heat shock protein complexes were identified. A novel protein complex, which involves clathrin and small conductance calcium-activated potassium (SK channel protein 2, was identified and validated by antibody based gel shift assay, co-immunoprecipitation and immunofluorescence staining. These results suggest that BN/SDS-PAGE, when integrated with LC-MS/MS, is a very powerful and versatile tool for the investigation of placental protein complexes. This work paves the way for deeper functional characterization of the placental protein complexes associated with pregnancy disorders.

Identification of Tobacco Topping Responsive Proteins in Roots

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Hongxiang eGuo

2016-04-01

Full Text Available Tobacco plant has many responses to topping, such as the increase in ability of nicotine synthesis and secondary growth of roots. Some topping responsive miRNAs and genes had been identified in our previous work, but it is not enough to elaborate mechanism of tobacco response to topping. Here, topping responsive proteins were screened from tobacco roots with two-dimensional electrophoresis. Of these proteins, calretulin (CRT and Auxin-responsive protein IAA9 were related to the secondary growth of roots, LRR disease resistance, heat shock protein 70 and farnesyl pyrophosphate synthase 1（FPPS）were involved in wounding stress response, and F-box protein played an important role in promoting the ability of nicotine synthesis after topping. In addition, there were five tobacco bHLH proteins (NtbHLH, NtMYC1a, NtMYC1b, NtMYC2a and NtMYC2b related to nicotine synthesis. It was suggested that NtMYC2 might be the main positive transcription factor and NtbHLH protein is a negative regulator in the JA-mediating activation of nicotine synthesis after topping. Tobacco topping activates some comprehensive biology processes involving IAA and JA signaling pathway, and the identification of these proteins will be helpful to understand the process of topping response.

Targeted nanodiamonds for identification of subcellular protein assemblies in mammalian cells

Science.gov (United States)

Lake, Michael P.; Bouchard, Louis-S.

2017-01-01

Transmission electron microscopy (TEM) can be used to successfully determine the structures of proteins. However, such studies are typically done ex situ after extraction of the protein from the cellular environment. Here we describe an application for nanodiamonds as targeted intensity contrast labels in biological TEM, using the nuclear pore complex (NPC) as a model macroassembly. We demonstrate that delivery of antibody-conjugated nanodiamonds to live mammalian cells using maltotriose-conjugated polypropylenimine dendrimers results in efficient localization of nanodiamonds to the intended cellular target. We further identify signatures of nanodiamonds under TEM that allow for unambiguous identification of individual nanodiamonds from a resin-embedded, OsO4-stained environment. This is the first demonstration of nanodiamonds as labels for nanoscale TEM-based identification of subcellular protein assemblies. These results, combined with the unique fluorescence properties and biocompatibility of nanodiamonds, represent an important step toward the use of nanodiamonds as markers for correlated optical/electron bioimaging. PMID:28636640

Targeted nanodiamonds for identification of subcellular protein assemblies in mammalian cells.

Directory of Open Access Journals (Sweden)

Michael P Lake

Full Text Available Transmission electron microscopy (TEM can be used to successfully determine the structures of proteins. However, such studies are typically done ex situ after extraction of the protein from the cellular environment. Here we describe an application for nanodiamonds as targeted intensity contrast labels in biological TEM, using the nuclear pore complex (NPC as a model macroassembly. We demonstrate that delivery of antibody-conjugated nanodiamonds to live mammalian cells using maltotriose-conjugated polypropylenimine dendrimers results in efficient localization of nanodiamonds to the intended cellular target. We further identify signatures of nanodiamonds under TEM that allow for unambiguous identification of individual nanodiamonds from a resin-embedded, OsO4-stained environment. This is the first demonstration of nanodiamonds as labels for nanoscale TEM-based identification of subcellular protein assemblies. These results, combined with the unique fluorescence properties and biocompatibility of nanodiamonds, represent an important step toward the use of nanodiamonds as markers for correlated optical/electron bioimaging.

Targeted nanodiamonds for identification of subcellular protein assemblies in mammalian cells.

Science.gov (United States)

Lake, Michael P; Bouchard, Louis-S

2017-01-01

Transmission electron microscopy (TEM) can be used to successfully determine the structures of proteins. However, such studies are typically done ex situ after extraction of the protein from the cellular environment. Here we describe an application for nanodiamonds as targeted intensity contrast labels in biological TEM, using the nuclear pore complex (NPC) as a model macroassembly. We demonstrate that delivery of antibody-conjugated nanodiamonds to live mammalian cells using maltotriose-conjugated polypropylenimine dendrimers results in efficient localization of nanodiamonds to the intended cellular target. We further identify signatures of nanodiamonds under TEM that allow for unambiguous identification of individual nanodiamonds from a resin-embedded, OsO4-stained environment. This is the first demonstration of nanodiamonds as labels for nanoscale TEM-based identification of subcellular protein assemblies. These results, combined with the unique fluorescence properties and biocompatibility of nanodiamonds, represent an important step toward the use of nanodiamonds as markers for correlated optical/electron bioimaging.

Identification of proteins from tuberculin purified protein derivative (PPD) by LC-MS/MS.

Science.gov (United States)

Borsuk, Sibele; Newcombe, Jane; Mendum, Tom A; Dellagostin, Odir A; McFadden, Johnjoe

2009-11-01

The tuberculin purified protein derivative (PPD) is a widely used diagnostic antigen for tuberculosis, however it is poorly defined. Most mycobacterial proteins are extensively denatured by the procedure employed in its preparation, which explains previous difficulties in identifying constituents from PPD to characterize their behaviour in B- and T-cell reactions. We here described a proteomics-based characterization of PPD from several different sources by LC-MS/MS, which combines the solute separation power of HPLC, with the detection power of a mass spectrometer. The technique is able to identify proteins from complex mixtures of peptide fragments. A total of 171 different proteins were identified among the four PPD samples (two bovine PPD and two avium PPD) from Brazil and UK. The majority of the proteins were cytoplasmic (77.9%) and involved in intermediary metabolism and respiration (24.25%) but there was a preponderance of proteins involved in lipid metabolism. We identified a group of 21 proteins that are present in both bovine PPD but were not detected in avium PPD preparation. In addition, four proteins found in bovine PPD are absent in Mycobacterium bovis BCG vaccine strain. This study provides a better understanding of the tuberculin PPD components leading to the identification of additional antigens useful as reagents for specific diagnosis of tuberculosis.

Verification of Single-Peptide Protein Identifications by the Application of Complementary Database Search Algorithms

National Research Council Canada - National Science Library

Rohrbough, James G; Breci, Linda; Merchant, Nirav; Miller, Susan; Haynes, Paul A

2005-01-01

.... One such technique, known as the Multi-Dimensional Protein Identification Technique, or MudPIT, involves the use of computer search algorithms that automate the process of identifying proteins...

Leptospiral outer membrane protein microarray, a novel approach to identification of host ligand-binding proteins.

Science.gov (United States)

Pinne, Marija; Matsunaga, James; Haake, David A

2012-11-01

Leptospirosis is a zoonosis with worldwide distribution caused by pathogenic spirochetes belonging to the genus Leptospira. The leptospiral life cycle involves transmission via freshwater and colonization of the renal tubules of their reservoir hosts. Infection requires adherence to cell surfaces and extracellular matrix components of host tissues. These host-pathogen interactions involve outer membrane proteins (OMPs) expressed on the bacterial surface. In this study, we developed an Leptospira interrogans serovar Copenhageni strain Fiocruz L1-130 OMP microarray containing all predicted lipoproteins and transmembrane OMPs. A total of 401 leptospiral genes or their fragments were transcribed and translated in vitro and printed on nitrocellulose-coated glass slides. We investigated the potential of this protein microarray to screen for interactions between leptospiral OMPs and fibronectin (Fn). This approach resulted in the identification of the recently described fibronectin-binding protein, LIC10258 (MFn8, Lsa66), and 14 novel Fn-binding proteins, denoted Microarray Fn-binding proteins (MFns). We confirmed Fn binding of purified recombinant LIC11612 (MFn1), LIC10714 (MFn2), LIC11051 (MFn6), LIC11436 (MFn7), LIC10258 (MFn8, Lsa66), and LIC10537 (MFn9) by far-Western blot assays. Moreover, we obtained specific antibodies to MFn1, MFn7, MFn8 (Lsa66), and MFn9 and demonstrated that MFn1, MFn7, and MFn9 are expressed and surface exposed under in vitro growth conditions. Further, we demonstrated that MFn1, MFn4 (LIC12631, Sph2), and MFn7 enable leptospires to bind fibronectin when expressed in the saprophyte, Leptospira biflexa. Protein microarrays are valuable tools for high-throughput identification of novel host ligand-binding proteins that have the potential to play key roles in the virulence mechanisms of pathogens.

DNA barcode data accurately assign higher spider taxa

Directory of Open Access Journals (Sweden)

Jonathan A. Coddington

2016-07-01

Full Text Available The use of unique DNA sequences as a method for taxonomic identification is no longer fundamentally controversial, even though debate continues on the best markers, methods, and technology to use. Although both existing databanks such as GenBank and BOLD, as well as reference taxonomies, are imperfect, in best case scenarios “barcodes” (whether single or multiple, organelle or nuclear, loci clearly are an increasingly fast and inexpensive method of identification, especially as compared to manual identification of unknowns by increasingly rare expert taxonomists. Because most species on Earth are undescribed, a complete reference database at the species level is impractical in the near term. The question therefore arises whether unidentified species can, using DNA barcodes, be accurately assigned to more inclusive groups such as genera and families—taxonomic ranks of putatively monophyletic groups for which the global inventory is more complete and stable. We used a carefully chosen test library of CO1 sequences from 49 families, 313 genera, and 816 species of spiders to assess the accuracy of genus and family-level assignment. We used BLAST queries of each sequence against the entire library and got the top ten hits. The percent sequence identity was reported from these hits (PIdent, range 75–100%. Accurate assignment of higher taxa (PIdent above which errors totaled less than 5% occurred for genera at PIdent values >95 and families at PIdent values ≥ 91, suggesting these as heuristic thresholds for accurate generic and familial identifications in spiders. Accuracy of identification increases with numbers of species/genus and genera/family in the library; above five genera per family and fifteen species per genus all higher taxon assignments were correct. We propose that using percent sequence identity between conventional barcode sequences may be a feasible and reasonably accurate method to identify animals to family/genus. However

Automated selected reaction monitoring software for accurate label-free protein quantification.

Science.gov (United States)

Teleman, Johan; Karlsson, Christofer; Waldemarson, Sofia; Hansson, Karin; James, Peter; Malmström, Johan; Levander, Fredrik

2012-07-06

Selected reaction monitoring (SRM) is a mass spectrometry method with documented ability to quantify proteins accurately and reproducibly using labeled reference peptides. However, the use of labeled reference peptides becomes impractical if large numbers of peptides are targeted and when high flexibility is desired when selecting peptides. We have developed a label-free quantitative SRM workflow that relies on a new automated algorithm, Anubis, for accurate peak detection. Anubis efficiently removes interfering signals from contaminating peptides to estimate the true signal of the targeted peptides. We evaluated the algorithm on a published multisite data set and achieved results in line with manual data analysis. In complex peptide mixtures from whole proteome digests of Streptococcus pyogenes we achieved a technical variability across the entire proteome abundance range of 6.5-19.2%, which was considerably below the total variation across biological samples. Our results show that the label-free SRM workflow with automated data analysis is feasible for large-scale biological studies, opening up new possibilities for quantitative proteomics and systems biology.

A novel method for accurate needle-tip identification in trans-rectal ultrasound-based high-dose-rate prostate brachytherapy.

Science.gov (United States)

Zheng, Dandan; Todor, Dorin A

2011-01-01

In real-time trans-rectal ultrasound (TRUS)-based high-dose-rate prostate brachytherapy, the accurate identification of needle-tip position is critical for treatment planning and delivery. Currently, needle-tip identification on ultrasound images can be subject to large uncertainty and errors because of ultrasound image quality and imaging artifacts. To address this problem, we developed a method based on physical measurements with simple and practical implementation to improve the accuracy and robustness of needle-tip identification. Our method uses measurements of the residual needle length and an off-line pre-established coordinate transformation factor, to calculate the needle-tip position on the TRUS images. The transformation factor was established through a one-time systematic set of measurements of the probe and template holder positions, applicable to all patients. To compare the accuracy and robustness of the proposed method and the conventional method (ultrasound detection), based on the gold-standard X-ray fluoroscopy, extensive measurements were conducted in water and gel phantoms. In water phantom, our method showed an average tip-detection accuracy of 0.7 mm compared with 1.6 mm of the conventional method. In gel phantom (more realistic and tissue-like), our method maintained its level of accuracy while the uncertainty of the conventional method was 3.4mm on average with maximum values of over 10mm because of imaging artifacts. A novel method based on simple physical measurements was developed to accurately detect the needle-tip position for TRUS-based high-dose-rate prostate brachytherapy. The method demonstrated much improved accuracy and robustness over the conventional method. Copyright © 2011 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Rapid and accurate prediction and scoring of water molecules in protein binding sites.

Directory of Open Access Journals (Sweden)

Gregory A Ross

Full Text Available Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity.

Machine Learning Identification of Protein Properties Useful for Specific Applications

KAUST Repository

Khamis, Abdullah

2016-03-31

Proteins play critical roles in cellular processes of living organisms. It is therefore important to identify and characterize their key properties associated with their functions. Correlating protein’s structural, sequence and physicochemical properties of its amino acids (aa) with protein functions could identify some of the critical factors governing the specific functionality. We point out that not all functions of even well studied proteins are known. This, complemented by the huge increase in the number of newly discovered and predicted proteins, makes challenging the experimental characterization of the whole spectrum of possible protein functions for all proteins of interest. Consequently, the use of computational methods has become more attractive. Here we address two questions. The first one is how to use protein aa sequence and physicochemical properties to characterize a family of proteins. The second one focuses on how to use transcription factor (TF) protein’s domains to enhance accuracy of predicting TF DNA binding sites (TFBSs). To address the first question, we developed a novel method using computational representation of proteins based on characteristics of different protein regions (N-terminal, M-region and C-terminal) and combined these with the properties of protein aa sequences. We show that this description provides important biological insight about characterization of the protein functional groups. Using feature selection techniques, we identified key properties of proteins that allow for very accurate characterization of different protein families. We demonstrated efficiency of our method in application to a number of antimicrobial peptide families. To address the second question we developed another novel method that uses a combination of aa properties of DNA binding domains of TFs and their TFBS properties to develop machine learning models for predicting TFBSs. Feature selection is used to identify the most relevant characteristics

Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning

Directory of Open Access Journals (Sweden)

Tanel Pärnamaa

2017-05-01

Full Text Available High-throughput microscopy of many single cells generates high-dimensional data that are far from straightforward to analyze. One important problem is automatically detecting the cellular compartment where a fluorescently-tagged protein resides, a task relatively simple for an experienced human, but difficult to automate on a computer. Here, we train an 11-layer neural network on data from mapping thousands of yeast proteins, achieving per cell localization classification accuracy of 91%, and per protein accuracy of 99% on held-out images. We confirm that low-level network features correspond to basic image characteristics, while deeper layers separate localization classes. Using this network as a feature calculator, we train standard classifiers that assign proteins to previously unseen compartments after observing only a small number of training examples. Our results are the most accurate subcellular localization classifications to date, and demonstrate the usefulness of deep learning for high-throughput microscopy.

Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning.

Science.gov (United States)

Pärnamaa, Tanel; Parts, Leopold

2017-05-05

High-throughput microscopy of many single cells generates high-dimensional data that are far from straightforward to analyze. One important problem is automatically detecting the cellular compartment where a fluorescently-tagged protein resides, a task relatively simple for an experienced human, but difficult to automate on a computer. Here, we train an 11-layer neural network on data from mapping thousands of yeast proteins, achieving per cell localization classification accuracy of 91%, and per protein accuracy of 99% on held-out images. We confirm that low-level network features correspond to basic image characteristics, while deeper layers separate localization classes. Using this network as a feature calculator, we train standard classifiers that assign proteins to previously unseen compartments after observing only a small number of training examples. Our results are the most accurate subcellular localization classifications to date, and demonstrate the usefulness of deep learning for high-throughput microscopy. Copyright © 2017 Parnamaa and Parts.

Identification of hierarchy of dynamic domains in proteins: comparison of HDWA and HCCP techniques

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Yesylevskyy S. O.

2010-07-01

Full Text Available Aim. There are several techniques for the identification of hierarchy of dynamic domains in proteins. The goal of this work is to compare systematically two recently developed techniques, HCCP and HDWA,on a set of proteins from diverse structural classes. Methods. HDWA and HCCP techniques are used. The HDWA technique is designed to identify hierarchically organized dynamic domains in proteins using the Molecular Dynamics (MD trajectories, while HCCP utilizes the normal modes of simplified elastic network models. Results. It is shown that the dynamic domains found by HDWA are consistent with the domains identified by HCCP and other techniques. At the same time HDWA identifies flexible mobile loops of proteins correctly, which is hard to achieve with other model-based domain identification techniques. Conclusion. HDWA is shown to be a powerful method of analysis of MD trajectories, which can be used in various areas of protein science.

Identification of proteins in the postsynaptic density fraction by mass spectrometry

DEFF Research Database (Denmark)

Walikonis, R S; Jensen, Ole Nørregaard; Mann, M

2000-01-01

Our understanding of the organization of postsynaptic signaling systems at excitatory synapses has been aided by the identification of proteins in the postsynaptic density (PSD) fraction, a subcellular fraction enriched in structures with the morphology of PSDs. In this study, we have completed...... not previously known to be constituents of the PSD fraction and 24 that had previously been associated with the PSD by other methods. The newly identified proteins include the heavy chain of myosin-Va (dilute myosin), a motor protein thought to be involved in vesicle trafficking, and the mammalian homolog...

Identification and accurate quantification of structurally related peptide impurities in synthetic human C-peptide by liquid chromatography-high resolution mass spectrometry.

Science.gov (United States)

Li, Ming; Josephs, Ralf D; Daireaux, Adeline; Choteau, Tiphaine; Westwood, Steven; Wielgosz, Robert I; Li, Hongmei

2018-06-04

Peptides are an increasingly important group of biomarkers and pharmaceuticals. The accurate purity characterization of peptide calibrators is critical for the development of reference measurement systems for laboratory medicine and quality control of pharmaceuticals. The peptides used for these purposes are increasingly produced through peptide synthesis. Various approaches (for example mass balance, amino acid analysis, qNMR, and nitrogen determination) can be applied to accurately value assign the purity of peptide calibrators. However, all purity assessment approaches require a correction for structurally related peptide impurities in order to avoid biases. Liquid chromatography coupled to high resolution mass spectrometry (LC-hrMS) has become the key technique for the identification and accurate quantification of structurally related peptide impurities in intact peptide calibrator materials. In this study, LC-hrMS-based methods were developed and validated in-house for the identification and quantification of structurally related peptide impurities in a synthetic human C-peptide (hCP) material, which served as a study material for an international comparison looking at the competencies of laboratories to perform peptide purity mass fraction assignments. More than 65 impurities were identified, confirmed, and accurately quantified by using LC-hrMS. The total mass fraction of all structurally related peptide impurities in the hCP study material was estimated to be 83.3 mg/g with an associated expanded uncertainty of 3.0 mg/g (k = 2). The calibration hierarchy concept used for the quantification of individual impurities is described in detail. Graphical abstract ᅟ.

Discovering functional interdependence relationship in PPI networks for protein complex identification.

Science.gov (United States)

Lam, Winnie W M; Chan, Keith C C

2012-04-01

Protein molecules interact with each other in protein complexes to perform many vital functions, and different computational techniques have been developed to identify protein complexes in protein-protein interaction (PPI) networks. These techniques are developed to search for subgraphs of high connectivity in PPI networks under the assumption that the proteins in a protein complex are highly interconnected. While these techniques have been shown to be quite effective, it is also possible that the matching rate between the protein complexes they discover and those that are previously determined experimentally be relatively low and the "false-alarm" rate can be relatively high. This is especially the case when the assumption of proteins in protein complexes being more highly interconnected be relatively invalid. To increase the matching rate and reduce the false-alarm rate, we have developed a technique that can work effectively without having to make this assumption. The name of the technique called protein complex identification by discovering functional interdependence (PCIFI) searches for protein complexes in PPI networks by taking into consideration both the functional interdependence relationship between protein molecules and the network topology of the network. The PCIFI works in several steps. The first step is to construct a multiple-function protein network graph by labeling each vertex with one or more of the molecular functions it performs. The second step is to filter out protein interactions between protein pairs that are not functionally interdependent of each other in the statistical sense. The third step is to make use of an information-theoretic measure to determine the strength of the functional interdependence between all remaining interacting protein pairs. Finally, the last step is to try to form protein complexes based on the measure of the strength of functional interdependence and the connectivity between proteins. For performance evaluation

Identification of surface proteins in Enterococcus faecalis V583

Directory of Open Access Journals (Sweden)

Eijsink Vincent GH

2011-03-01

Full Text Available Abstract Background Surface proteins are a key to a deeper understanding of the behaviour of Gram-positive bacteria interacting with the human gastro-intestinal tract. Such proteins contribute to cell wall synthesis and maintenance and are important for interactions between the bacterial cell and the human host. Since they are exposed and may play roles in pathogenicity, surface proteins are interesting targets for drug design. Results Using methods based on proteolytic "shaving" of bacterial cells and subsequent mass spectrometry-based protein identification, we have identified surface-located proteins in Enterococcus faecalis V583. In total 69 unique proteins were identified, few of which have been identified and characterized previously. 33 of these proteins are predicted to be cytoplasmic, whereas the other 36 are predicted to have surface locations (31 or to be secreted (5. Lipid-anchored proteins were the most dominant among the identified surface proteins. The seemingly most abundant surface proteins included a membrane protein with a potentially shedded extracellular sulfatase domain that could act on the sulfate groups in mucin and a lipid-anchored fumarate reductase that could contribute to generation of reactive oxygen species. Conclusions The present proteome analysis gives an experimental impression of the protein landscape on the cell surface of the pathogenic bacterium E. faecalis. The 36 identified secreted (5 and surface (31 proteins included several proteins involved in cell wall synthesis, pheromone-regulated processes, and transport of solutes, as well as proteins with unknown function. These proteins stand out as interesting targets for further investigation of the interaction between E. faecalis and its environment.

Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry

DEFF Research Database (Denmark)

Ho, Yuen; Gruhler, Albrecht; Heilbut, Adrian

2002-01-01

The recent abundance of genome sequence data has brought an urgent need for systematic proteomics to decipher the encoded protein networks that dictate cellular function. To date, generation of large-scale protein-protein interaction maps has relied on the yeast two-hybrid system, which detects...... as a test case, an example of this approach, which we term high-throughput mass spectrometric protein complex identification (HMS-PCI). Beginning with 10% of predicted yeast proteins as baits, we detected 3,617 associated proteins covering 25% of the yeast proteome. Numerous protein complexes were...... identified, including many new interactions in various signalling pathways and in the DNA damage response. Comparison of the HMS-PCI data set with interactions reported in the literature revealed an average threefold higher success rate in detection of known complexes compared with large-scale two...

MP3: a software tool for the prediction of pathogenic proteins in genomic and metagenomic data.

Science.gov (United States)

Gupta, Ankit; Kapil, Rohan; Dhakan, Darshan B; Sharma, Vineet K

2014-01-01

The identification of virulent proteins in any de-novo sequenced genome is useful in estimating its pathogenic ability and understanding the mechanism of pathogenesis. Similarly, the identification of such proteins could be valuable in comparing the metagenome of healthy and diseased individuals and estimating the proportion of pathogenic species. However, the common challenge in both the above tasks is the identification of virulent proteins since a significant proportion of genomic and metagenomic proteins are novel and yet unannotated. The currently available tools which carry out the identification of virulent proteins provide limited accuracy and cannot be used on large datasets. Therefore, we have developed an MP3 standalone tool and web server for the prediction of pathogenic proteins in both genomic and metagenomic datasets. MP3 is developed using an integrated Support Vector Machine (SVM) and Hidden Markov Model (HMM) approach to carry out highly fast, sensitive and accurate prediction of pathogenic proteins. It displayed Sensitivity, Specificity, MCC and accuracy values of 92%, 100%, 0.92 and 96%, respectively, on blind dataset constructed using complete proteins. On the two metagenomic blind datasets (Blind A: 51-100 amino acids and Blind B: 30-50 amino acids), it displayed Sensitivity, Specificity, MCC and accuracy values of 82.39%, 97.86%, 0.80 and 89.32% for Blind A and 71.60%, 94.48%, 0.67 and 81.86% for Blind B, respectively. In addition, the performance of MP3 was validated on selected bacterial genomic and real metagenomic datasets. To our knowledge, MP3 is the only program that specializes in fast and accurate identification of partial pathogenic proteins predicted from short (100-150 bp) metagenomic reads and also performs exceptionally well on complete protein sequences. MP3 is publicly available at http://metagenomics.iiserb.ac.in/mp3/index.php.

Aptamer-conjugated live human immune cell based biosensors for the accurate detection of C-reactive protein

OpenAIRE

Hwang, Jangsun; Seo, Youngmin; Jo, Yeonho; Son, Jaewoo; Choi, Jonghoon

2016-01-01

C-reactive protein (CRP) is a pentameric protein that is present in the bloodstream during inflammatory events, e.g., liver failure, leukemia, and/or bacterial infection. The level of CRP indicates the progress and prognosis of certain diseases; it is therefore necessary to measure CRP levels in the blood accurately. The normal concentration of CRP is reported to be 1?3?mg/L. Inflammatory events increase the level of CRP by up to 500 times; accordingly, CRP is a biomarker of acute inflammator...

Differential identification of Candida species and other yeasts by analysis of [35S]methionine-labeled polypeptide profiles

International Nuclear Information System (INIS)

Shen, H.D.; Choo, K.B.; Tsai, W.C.; Jen, T.M.; Yeh, J.Y.; Han, S.H.

1988-01-01

This paper describes a scheme for differential identification of Candida species and other yeasts based on autoradiographic analysis of protein profiles of [ 35 S]methionine-labeled cellular proteins separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Using ATCC strains as references, protein profile analysis showed that different Candida and other yeast species produced distinctively different patterns. Good agreement in results obtained with this approach and with other conventional systems was observed. Being accurate and reproducible, this approach provides a basis for the development of an alternative method for the identification of yeasts isolated from clinical specimens

Identification of novel direct protein-protein interactions by irradiating living cells with femtosecond UV laser pulses.

Science.gov (United States)

Itri, Francesco; Monti, Daria Maria; Chino, Marco; Vinciguerra, Roberto; Altucci, Carlo; Lombardi, Angela; Piccoli, Renata; Birolo, Leila; Arciello, Angela

2017-10-07

The identification of protein-protein interaction networks in living cells is becoming increasingly fundamental to elucidate main biological processes and to understand disease molecular bases on a system-wide level. We recently described a method (LUCK, Laser UV Cross-linKing) to cross-link interacting protein surfaces in living cells by UV laser irradiation. By using this innovative methodology, that does not require any protein modification or cell engineering, here we demonstrate that, upon UV laser irradiation of HeLa cells, a direct interaction between GAPDH and alpha-enolase was "frozen" by a cross-linking event. We validated the occurrence of this direct interaction by co-immunoprecipitation and Immuno-FRET analyses. This represents a proof of principle of the LUCK capability to reveal direct protein interactions in their physiological environment. Copyright © 2017 Elsevier Inc. All rights reserved.

AFM-based identification of the dynamic properties of globular proteins: simulation study

International Nuclear Information System (INIS)

Kim, Deok Ho; Park, Jung Yul; Kim, Moon K.; Hong, Keum Shik

2008-01-01

Nowadays a mathematical model-based computational approach is getting more attention as an effective tool for understanding the mechanical behaviors of biological systems. To find the mechanical properties of the proteins required to build such a model, this paper investigates a real-time identification method based on an AFM nanomanipulation system. First, an AFM-based bio-characterization system is introduced. Second, a second-order time-varying linear model representing the interaction between an AFM cantilever and globular proteins in a solvent is presented. Finally, we address a real-time estimation method in which the results of AFM experiments are designed to be inputs of the state estimator proposed here. Our attention is restricted to a theoretical feasibility analysis of the proposed methodology. We simply set the mechanical properties of the particular protein such as mass, stiffness, and damping coefficient in the system model prior to running the simulation. Simulation results show very good agreement with the preset properties. We anticipate that the realization of the AFM-based bio-characterization system will also provide an experimental validation of the proposed identification procedure in the future. This methodology can be used to determine a model of protein motion for the purpose of computer simulation and for a real-time modification of protein deformation

Mass spectrometry based approach for identification and characterisation of fluorescent proteins from marine organisms

DEFF Research Database (Denmark)

Wojdyla, Katarzyna Iwona; Rogowska-Wrzesinska, Adelina; Wrzesinski, Krzysztof

2011-01-01

We present here a new analytical strategy for identification and characterisation of fluorescent proteins from marine organisms. By applying basic proteomics tools it is possible to screen large sample collections for fluorescent proteins of desired characteristics prior to gene cloning. Our...

Enhancing Membrane Protein Identification Using a Simplified Centrifugation and Detergent-Based Membrane Extraction Approach.

Science.gov (United States)

Zhou, Yanting; Gao, Jing; Zhu, Hongwen; Xu, Jingjing; He, Han; Gu, Lei; Wang, Hui; Chen, Jie; Ma, Danjun; Zhou, Hu; Zheng, Jing

2018-02-20

Membrane proteins may act as transporters, receptors, enzymes, and adhesion-anchors, accounting for nearly 70% of pharmaceutical drug targets. Difficulties in efficient enrichment, extraction, and solubilization still exist because of their relatively low abundance and poor solubility. A simplified membrane protein extraction approach with advantages of user-friendly sample processing procedures, good repeatability and significant effectiveness was developed in the current research for enhancing enrichment and identification of membrane proteins. This approach combining centrifugation and detergent along with LC-MS/MS successfully identified higher proportion of membrane proteins, integral proteins and transmembrane proteins in membrane fraction (76.6%, 48.1%, and 40.6%) than in total cell lysate (41.6%, 16.4%, and 13.5%), respectively. Moreover, our method tended to capture membrane proteins with high degree of hydrophobicity and number of transmembrane domains as 486 out of 2106 (23.0%) had GRAVY > 0 in membrane fraction, 488 out of 2106 (23.1%) had TMs ≥ 2. It also provided for improved identification of membrane proteins as more than 60.6% of the commonly identified membrane proteins in two cell samples were better identified in membrane fraction with higher sequence coverage. Data are available via ProteomeXchange with identifier PXD008456.

Proteome scale identification, classification and structural analysis of iron-binding proteins in bread wheat.

Science.gov (United States)

Verma, Shailender Kumar; Sharma, Ankita; Sandhu, Padmani; Choudhary, Neha; Sharma, Shailaja; Acharya, Vishal; Akhter, Yusuf

2017-05-01

Bread wheat is one of the major staple foods of worldwide population and iron plays a significant role in growth and development of the plant. In this report, we are presenting the genome wide identification of iron-binding proteins in bread wheat. The wheat genome derived putative proteome was screened for identification of iron-binding sequence motifs. Out of 602 putative iron-binding proteins, 130 were able to produce reliable structural models by homology techniques and further analyzed for the presence of iron-binding structural motifs. The computationally identified proteins appear to bind to ferrous and ferric ions and showed diverse coordination geometries. Glu, His, Asp and Cys amino acid residues were found to be mostly involved in iron binding. We have classified these proteins on the basis of their localization in the different cellular compartments. The identified proteins were further classified into their protein folds, families and functional classes ranging from structure maintenance of cellular components, regulation of gene expression, post translational modification, membrane proteins, enzymes, signaling and storage proteins. This comprehensive report regarding structural iron binding proteome provides useful insights into the diversity of iron binding proteins of wheat plants and further utilized to study their roles in plant growth, development and physiology. Copyright © 2017 Elsevier Inc. All rights reserved.

Identification of Inhibitors of Biological Interactions Involving Intrinsically Disordered Proteins

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Daniela Marasco

2015-04-01

Full Text Available Protein–protein interactions involving disordered partners have unique features and represent prominent targets in drug discovery processes. Intrinsically Disordered Proteins (IDPs are involved in cellular regulation, signaling and control: they bind to multiple partners and these high-specificity/low-affinity interactions play crucial roles in many human diseases. Disordered regions, terminal tails and flexible linkers are particularly abundant in DNA-binding proteins and play crucial roles in the affinity and specificity of DNA recognizing processes. Protein complexes involving IDPs are short-lived and typically involve short amino acid stretches bearing few “hot spots”, thus the identification of molecules able to modulate them can produce important lead compounds: in this scenario peptides and/or peptidomimetics, deriving from structure-based, combinatorial or protein dissection approaches, can play a key role as hit compounds. Here, we propose a panoramic review of the structural features of IDPs and how they regulate molecular recognition mechanisms focusing attention on recently reported drug-design strategies in the field of IDPs.

DisoMCS: Accurately Predicting Protein Intrinsically Disordered Regions Using a Multi-Class Conservative Score Approach.

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Zhiheng Wang

Full Text Available The precise prediction of protein intrinsically disordered regions, which play a crucial role in biological procedures, is a necessary prerequisite to further the understanding of the principles and mechanisms of protein function. Here, we propose a novel predictor, DisoMCS, which is a more accurate predictor of protein intrinsically disordered regions. The DisoMCS bases on an original multi-class conservative score (MCS obtained by sequence-order/disorder alignment. Initially, near-disorder regions are defined on fragments located at both the terminus of an ordered region connecting a disordered region. Then the multi-class conservative score is generated by sequence alignment against a known structure database and represented as order, near-disorder and disorder conservative scores. The MCS of each amino acid has three elements: order, near-disorder and disorder profiles. Finally, the MCS is exploited as features to identify disordered regions in sequences. DisoMCS utilizes a non-redundant data set as the training set, MCS and predicted secondary structure as features, and a conditional random field as the classification algorithm. In predicted near-disorder regions a residue is determined as an order or a disorder according to the optimized decision threshold. DisoMCS was evaluated by cross-validation, large-scale prediction, independent tests and CASP (Critical Assessment of Techniques for Protein Structure Prediction tests. All results confirmed that DisoMCS was very competitive in terms of accuracy of prediction when compared with well-established publicly available disordered region predictors. It also indicated our approach was more accurate when a query has higher homologous with the knowledge database.The DisoMCS is available at http://cal.tongji.edu.cn/disorder/.

Identification of antigenic proteins of setaria cervi by immunoblotting technique

International Nuclear Information System (INIS)

Kaushal, N.A.; Kaushal, D.C.; Ghatak, S.

1987-01-01

Identification and characterization of antigenic proteins of Setaria cervi (bovine filarial parasite) adults and microfilariae was done by immunoblotting technique using hyperimmune rabbit sera against S. cervi and Brugia malayi. The antigens recognized by these sera were detected by using 125 I protein-A followed by autoradiography. Fifteen different antigens were observed to be common between adult and microfilarial stages of the parasite. Some stage specific antigens were also identified. Many antigens of S. cervi adults and microfilariae were also recognized by rabbit anti-B.malayi serum showing the existence of common antigenic determinants between the bovine and human filarial parasites

Identification of Novel Immunogenic Proteins of Neisseria gonorrhoeae by Phage Display.

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Daniel O Connor

Full Text Available Neisseria gonorrhoeae is one of the most prevalent sexually transmitted diseases worldwide with more than 100 million new infections per year. A lack of intense research over the last decades and increasing resistances to the recommended antibiotics call for a better understanding of gonococcal infection, fast diagnostics and therapeutic measures against N. gonorrhoeae. Therefore, the aim of this work was to identify novel immunogenic proteins as a first step to advance those unresolved problems. For the identification of immunogenic proteins, pHORF oligopeptide phage display libraries of the entire N. gonorrhoeae genome were constructed. Several immunogenic oligopeptides were identified using polyclonal rabbit antibodies against N. gonorrhoeae. Corresponding full-length proteins of the identified oligopeptides were expressed and their immunogenic character was verified by ELISA. The immunogenic character of six proteins was identified for the first time. Additional 13 proteins were verified as immunogenic proteins in N. gonorrhoeae.

Processed Meat Protein and Heat-Stable Peptide Marker Identification Using Microwave-Assisted Tryptic Digestion

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Magdalena Montowska

2016-01-01

Full Text Available New approaches to rapid examination of proteins and peptides in complex food matrices are of great interest to the community of food scientists. The aim of the study is to examine the influence of microwave irradiation on the acceleration of enzymatic cleavage and enzymatic digestion of denatured proteins in cooked meat of five species (cattle, horse, pig, chicken and turkey and processed meat products (coarsely minced, smoked, cooked and semi-dried sausages. Severe protein aggregation occurred not only in heated meat under harsh treatment at 190 °C but also in processed meat products. All the protein aggregates were thoroughly hydrolyzed aft er 1 h of trypsin treatment with short exposure times of 40 and 20 s to microwave irradiation at 138 and 303 W. There were much more missed cleavage sites observed in all microwave-assisted digestions. Despite the incompleteness of microwave-assisted digestion, six unique peptide markers were detected, which allowed unambiguous identification of processed meat derived from the examined species. Although the microwave-assisted tryptic digestion can serve as a tool for rapid and high-throughput protein identification, great caution and pre-evaluation of individual samples is recommended in protein quantitation.

Comprehensive Identification of Immunodominant Proteins of Brucella abortus and Brucella melitensis Using Antibodies in the Sera from Naturally Infected Hosts.

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Wareth, Gamal; Eravci, Murat; Weise, Christoph; Roesler, Uwe; Melzer, Falk; Sprague, Lisa D; Neubauer, Heinrich; Murugaiyan, Jayaseelan

2016-04-30

Brucellosis is a debilitating zoonotic disease that affects humans and animals. The diagnosis of brucellosis is challenging, as accurate species level identification is not possible with any of the currently available serology-based diagnostic methods. The present study aimed at identifying Brucella (B.) species-specific proteins from the closely related species B. abortus and B. melitensis using sera collected from naturally infected host species. Unlike earlier reported investigations with either laboratory-grown species or vaccine strains, in the present study, field strains were utilized for analysis. The label-free quantitative proteomic analysis of the naturally isolated strains of these two closely related species revealed 402 differentially expressed proteins, among which 63 and 103 proteins were found exclusively in the whole cell extracts of B. abortus and B. melitensis field strains, respectively. The sera from four different naturally infected host species, i.e., cattle, buffalo, sheep, and goat were applied to identify the immune-binding protein spots present in the whole protein extracts from the isolated B. abortus and B. melitensis field strains and resolved on two-dimensional gel electrophoresis. Comprehensive analysis revealed that 25 proteins of B. abortus and 20 proteins of B. melitensis were distinctly immunoreactive. Dihydrodipicolinate synthase, glyceraldehyde-3-phosphate dehydrogenase and lactate/malate dehydrogenase from B. abortus, amino acid ABC transporter substrate-binding protein from B. melitensis and fumarylacetoacetate hydrolase from both species were reactive with the sera of all the tested naturally infected host species. The identified proteins could be used for the design of serological assays capable of detecting pan-Brucella, B. abortus- and B. melitensis-specific antibodies.

Combining metal oxide affinity chromatography (MOAC and selective mass spectrometry for robust identification of in vivo protein phosphorylation sites

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Weckwerth Wolfram

2005-11-01

Full Text Available Abstract Background Protein phosphorylation is accepted as a major regulatory pathway in plants. More than 1000 protein kinases are predicted in the Arabidopsis proteome, however, only a few studies look systematically for in vivo protein phosphorylation sites. Owing to the low stoichiometry and low abundance of phosphorylated proteins, phosphorylation site identification using mass spectrometry imposes difficulties. Moreover, the often observed poor quality of mass spectra derived from phosphopeptides results frequently in uncertain database hits. Thus, several lines of evidence have to be combined for a precise phosphorylation site identification strategy. Results Here, a strategy is presented that combines enrichment of phosphoproteins using a technique termed metaloxide affinity chromatography (MOAC and selective ion trap mass spectrometry. The complete approach involves (i enrichment of proteins with low phosphorylation stoichiometry out of complex mixtures using MOAC, (ii gel separation and detection of phosphorylation using specific fluorescence staining (confirmation of enrichment, (iii identification of phosphoprotein candidates out of the SDS-PAGE using liquid chromatography coupled to mass spectrometry, and (iv identification of phosphorylation sites of these enriched proteins using automatic detection of H3PO4 neutral loss peaks and data-dependent MS3-fragmentation of the corresponding MS2-fragment. The utility of this approach is demonstrated by the identification of phosphorylation sites in Arabidopsis thaliana seed proteins. Regulatory importance of the identified sites is indicated by conservation of the detected sites in gene families such as ribosomal proteins and sterol dehydrogenases. To demonstrate further the wide applicability of MOAC, phosphoproteins were enriched from Chlamydomonas reinhardtii cell cultures. Conclusion A novel phosphoprotein enrichment procedure MOAC was applied to seed proteins of A. thaliana and to

Rapid identification and typing of Yersinia pestis and other Yersinia species by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry.

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Ayyadurai, Saravanan; Flaudrops, Christophe; Raoult, Didier; Drancourt, Michel

2010-11-12

Accurate identification is necessary to discriminate harmless environmental Yersinia species from the food-borne pathogens Yersinia enterocolitica and Yersinia pseudotuberculosis and from the group A bioterrorism plague agent Yersinia pestis. In order to circumvent the limitations of current phenotypic and PCR-based identification methods, we aimed to assess the usefulness of matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) protein profiling for accurate and rapid identification of Yersinia species. As a first step, we built a database of 39 different Yersinia strains representing 12 different Yersinia species, including 13 Y. pestis isolates representative of the Antiqua, Medievalis and Orientalis biotypes. The organisms were deposited on the MALDI-TOF plate after appropriate ethanol-based inactivation, and a protein profile was obtained within 6 minutes for each of the Yersinia species. When compared with a 3,025-profile database, every Yersinia species yielded a unique protein profile and was unambiguously identified. In the second step of analysis, environmental and clinical isolates of Y. pestis (n = 2) and Y. enterocolitica (n = 11) were compared to the database and correctly identified. In particular, Y. pestis was unambiguously identified at the species level, and MALDI-TOF was able to successfully differentiate the three biotypes. These data indicate that MALDI-TOF can be used as a rapid and accurate first-line method for the identification of Yersinia isolates.

Accurate microRNA target prediction correlates with protein repression levels

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Simossis Victor A

2009-09-01

Full Text Available Abstract Background MicroRNAs are small endogenously expressed non-coding RNA molecules that regulate target gene expression through translation repression or messenger RNA degradation. MicroRNA regulation is performed through pairing of the microRNA to sites in the messenger RNA of protein coding genes. Since experimental identification of miRNA target genes poses difficulties, computational microRNA target prediction is one of the key means in deciphering the role of microRNAs in development and disease. Results DIANA-microT 3.0 is an algorithm for microRNA target prediction which is based on several parameters calculated individually for each microRNA and combines conserved and non-conserved microRNA recognition elements into a final prediction score, which correlates with protein production fold change. Specifically, for each predicted interaction the program reports a signal to noise ratio and a precision score which can be used as an indication of the false positive rate of the prediction. Conclusion Recently, several computational target prediction programs were benchmarked based on a set of microRNA target genes identified by the pSILAC method. In this assessment DIANA-microT 3.0 was found to achieve the highest precision among the most widely used microRNA target prediction programs reaching approximately 66%. The DIANA-microT 3.0 prediction results are available online in a user friendly web server at http://www.microrna.gr/microT

Calculation of accurate small angle X-ray scattering curves from coarse-grained protein models

DEFF Research Database (Denmark)

Stovgaard, Kasper; Andreetta, Christian; Ferkinghoff-Borg, Jesper

2010-01-01

, which is paramount for structure determination based on statistical inference. Results: We present a method for the efficient calculation of accurate SAXS curves based on the Debye formula and a set of scattering form factors for dummy atom representations of amino acids. Such a method avoids......DBN. This resulted in a significant improvement in the decoy recognition performance. In conclusion, the presented method shows great promise for use in statistical inference of protein structures from SAXS data....

Identification Of Protein Vaccine Candidates Using Comprehensive Proteomic Analysis Strategies

Science.gov (United States)

2007-12-01

that fascinating fungus known as Coccidioides. I also want to thank the UA Mass Spectrometry Facility and the UA Proteomics Consortium, especially...W. & N. N. Kav. 2006. The proteome of the phytopathogenic fungus Sclerotinia sclerotiorum. Proteomics 6: 5995-6007. 127. de Godoy, L. M., J. V...IDENTIFICATION OF PROTEIN VACCINE CANDIDATES USING COMPREHENSIVE PROTEOMIC ANALYSIS STRATEGIES by James G. Rohrbough

EpHLA software: a timesaving and accurate tool for improving identification of acceptable mismatches for clinical purposes.

Science.gov (United States)

Filho, Herton Luiz Alves Sales; da Mata Sousa, Luiz Claudio Demes; von Glehn, Cristina de Queiroz Carrascosa; da Silva, Adalberto Socorro; dos Santos Neto, Pedro de Alcântara; do Nascimento, Ferraz; de Castro, Adail Fonseca; do Nascimento, Liliane Machado; Kneib, Carolina; Bianchi Cazarote, Helena; Mayumi Kitamura, Daniele; Torres, Juliane Roberta Dias; da Cruz Lopes, Laiane; Barros, Aryela Loureiro; da Silva Edlin, Evelin Nildiane; de Moura, Fernanda Sá Leal; Watanabe, Janine Midori Figueiredo; do Monte, Semiramis Jamil Hadad

2012-06-01

The HLAMatchmaker algorithm, which allows the identification of “safe” acceptable mismatches (AMMs) for recipients of solid organ and cell allografts, is rarely used in part due to the difficulty in using it in the current Excel format. The automation of this algorithm may universalize its use to benefit the allocation of allografts. Recently, we have developed a new software called EpHLA, which is the first computer program automating the use of the HLAMatchmaker algorithm. Herein, we present the experimental validation of the EpHLA program by showing the time efficiency and the quality of operation. The same results, obtained by a single antigen bead assay with sera from 10 sensitized patients waiting for kidney transplants, were analyzed either by conventional HLAMatchmaker or by automated EpHLA method. Users testing these two methods were asked to record: (i) time required for completion of the analysis (in minutes); (ii) number of eplets obtained for class I and class II HLA molecules; (iii) categorization of eplets as reactive or non-reactive based on the MFI cutoff value; and (iv) determination of AMMs based on eplets' reactivities. We showed that although both methods had similar accuracy, the automated EpHLA method was over 8 times faster in comparison to the conventional HLAMatchmaker method. In particular the EpHLA software was faster and more reliable but equally accurate as the conventional method to define AMMs for allografts. The EpHLA software is an accurate and quick method for the identification of AMMs and thus it may be a very useful tool in the decision-making process of organ allocation for highly sensitized patients as well as in many other applications.

Identification of Phosphorylated Proteins on a Global Scale.

Science.gov (United States)

Iliuk, Anton

2018-05-31

Liquid chromatography (LC) coupled with tandem mass spectrometry (MS/MS) has enabled researchers to analyze complex biological samples with unprecedented depth. It facilitates the identification and quantification of modifications within thousands of proteins in a single large-scale proteomic experiment. Analysis of phosphorylation, one of the most common and important post-translational modifications, has particularly benefited from such progress in the field. Here, detailed protocols are provided for a few well-regarded, common sample preparation methods for an effective phosphoproteomic experiment. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

Working with Proteins in silico: A Review of Online Available Tools for Basic Identification of Proteins

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Caner Yavuz

2017-01-01

Full Text Available Increase in online available bioinformatics tools for protein research creates an important opportunity for scientists to reveal characteristics of the protein of interest by only starting from the predicted or known amino acid sequence without fully depending on experimental approaches. There are many sophisticated tools used for diverse purposes; however, there are not enough reviews covering the tips and tricks in selecting and using the correct tools as the literature mainly state the promotion of the new ones. In this review, with the aim of providing young scientists with no specific experience on protein work a reliable starting point for in silico analysis of the protein of interest, we summarized tools for annotation, identification of motifs and domains, determination isoelectric point, molecular weight, subcellular localization, and post-translational modifications by focusing on the important points to be considered while selecting from online available tools.

Complex mixture analysis of peptides using LC/LC-MS/MS and data-dependent protein identification

International Nuclear Information System (INIS)

Wasinger, V.; Corthals, G.

2001-01-01

The comprehensive identification of proteins within complex solutions by mass-spectrometry largely depends on the sensitivity, resolving power and sampling efficiency of the technology. An integrated orthogonal approach using Strong Cation Exchange-Reverse Phase-MS/MS (SCX-RP-MS/MS) was used to evaluate the data-dependent Collision Induced Dissociation (CID) of yeast peptides. Reverse phase gradient times of 4, 10. 30, 90, and 180 minutes allowed the identification of hundreds of proteins in a nearly automated fashion from nuclear, membrane, and cytosolic distributions. Many proteins from typically difficult to resolve regions of two-dimensional gels, such as >100kDa, > pI 9.0 and Codon Adaptation Index < 0.2, were also identified using this multi-dimensional separation technology. Few low mass proteins (<10kDa) were identified. The impact of scan-range and duty-cycle on CID of peptides will be discussed

Identification and characterization of N-glycosylated proteins using proteomics

DEFF Research Database (Denmark)

Selby, David S; Larsen, Martin R; Calvano, Cosima Damiana

2008-01-01

and analysis of glycoproteins and glycopeptides. Combinations of affinity-enrichment techniques, chemical and biochemical protocols, and advanced mass spectrometry facilitate detailed glycoprotein analysis in proteomics, from fundamental biological studies to biomarker discovery in biomedicine....... is a complex task and is currently achieved by mass spectrometry-based methods that enable identification of glycoproteins and localization, classification, and analysis of individual glycan structures on proteins. In this chapter we briefly introduce a range of analytical technologies for recovery...

A Robust Identification of the Protein Standard Bands in Two-Dimensional Electrophoresis Gel Images

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Serackis Artūras

2017-12-01

Full Text Available The aim of the investigation presented in this paper was to develop a software-based assistant for the protein analysis workflow. The prior characterization of the unknown protein in two-dimensional electrophoresis gel images is performed according to the molecular weight and isoelectric point of each protein spot estimated from the gel image before further sequence analysis by mass spectrometry. The paper presents a method for automatic and robust identification of the protein standard band in a two-dimensional gel image. In addition, the method introduces the identification of the positions of the markers, prepared by using pre-selected proteins with known molecular mass. The robustness of the method was achieved by using special validation rules in the proposed original algorithms. In addition, a self-organizing map-based decision support algorithm is proposed, which takes Gabor coefficients as image features and searches for the differences in preselected vertical image bars. The experimental investigation proved the good performance of the new algorithms included into the proposed method. The detection of the protein standard markers works without modification of algorithm parameters on two-dimensional gel images obtained by using different staining and destaining procedures, which results in different average levels of intensity in the images.

Using context to improve protein domain identification

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Llinás Manuel

2011-03-01

Full Text Available Abstract Background Identifying domains in protein sequences is an important step in protein structural and functional annotation. Existing domain recognition methods typically evaluate each domain prediction independently of the rest. However, the majority of proteins are multidomain, and pairwise domain co-occurrences are highly specific and non-transitive. Results Here, we demonstrate how to exploit domain co-occurrence to boost weak domain predictions that appear in previously observed combinations, while penalizing higher confidence domains if such combinations have never been observed. Our framework, Domain Prediction Using Context (dPUC, incorporates pairwise "context" scores between domains, along with traditional domain scores and thresholds, and improves domain prediction across a variety of organisms from bacteria to protozoa and metazoa. Among the genomes we tested, dPUC is most successful at improving predictions for the poorly-annotated malaria parasite Plasmodium falciparum, for which over 38% of the genome is currently unannotated. Our approach enables high-confidence annotations in this organism and the identification of orthologs to many core machinery proteins conserved in all eukaryotes, including those involved in ribosomal assembly and other RNA processing events, which surprisingly had not been previously known. Conclusions Overall, our results demonstrate that this new context-based approach will provide significant improvements in domain and function prediction, especially for poorly understood genomes for which the need for additional annotations is greatest. Source code for the algorithm is available under a GPL open source license at http://compbio.cs.princeton.edu/dpuc/. Pre-computed results for our test organisms and a web server are also available at that location.

Unveiling protein functions through the dynamics of the interaction network.

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Irene Sendiña-Nadal

Full Text Available Protein interaction networks have become a tool to study biological processes, either for predicting molecular functions or for designing proper new drugs to regulate the main biological interactions. Furthermore, such networks are known to be organized in sub-networks of proteins contributing to the same cellular function. However, the protein function prediction is not accurate and each protein has traditionally been assigned to only one function by the network formalism. By considering the network of the physical interactions between proteins of the yeast together with a manual and single functional classification scheme, we introduce a method able to reveal important information on protein function, at both micro- and macro-scale. In particular, the inspection of the properties of oscillatory dynamics on top of the protein interaction network leads to the identification of misclassification problems in protein function assignments, as well as to unveil correct identification of protein functions. We also demonstrate that our approach can give a network representation of the meta-organization of biological processes by unraveling the interactions between different functional classes.

Exploring the universe of protein structures beyond the Protein Data Bank.

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Cossio, Pilar; Trovato, Antonio; Pietrucci, Fabio; Seno, Flavio; Maritan, Amos; Laio, Alessandro

2010-11-04

It is currently believed that the atlas of existing protein structures is faithfully represented in the Protein Data Bank. However, whether this atlas covers the full universe of all possible protein structures is still a highly debated issue. By using a sophisticated numerical approach, we performed an exhaustive exploration of the conformational space of a 60 amino acid polypeptide chain described with an accurate all-atom interaction potential. We generated a database of around 30,000 compact folds with at least of secondary structure corresponding to local minima of the potential energy. This ensemble plausibly represents the universe of protein folds of similar length; indeed, all the known folds are represented in the set with good accuracy. However, we discover that the known folds form a rather small subset, which cannot be reproduced by choosing random structures in the database. Rather, natural and possible folds differ by the contact order, on average significantly smaller in the former. This suggests the presence of an evolutionary bias, possibly related to kinetic accessibility, towards structures with shorter loops between contacting residues. Beside their conceptual relevance, the new structures open a range of practical applications such as the development of accurate structure prediction strategies, the optimization of force fields, and the identification and design of novel folds.

enDNA-Prot: Identification of DNA-Binding Proteins by Applying Ensemble Learning

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Ruifeng Xu

2014-01-01

Full Text Available DNA-binding proteins are crucial for various cellular processes, such as recognition of specific nucleotide, regulation of transcription, and regulation of gene expression. Developing an effective model for identifying DNA-binding proteins is an urgent research problem. Up to now, many methods have been proposed, but most of them focus on only one classifier and cannot make full use of the large number of negative samples to improve predicting performance. This study proposed a predictor called enDNA-Prot for DNA-binding protein identification by employing the ensemble learning technique. Experiential results showed that enDNA-Prot was comparable with DNA-Prot and outperformed DNAbinder and iDNA-Prot with performance improvement in the range of 3.97–9.52% in ACC and 0.08–0.19 in MCC. Furthermore, when the benchmark dataset was expanded with negative samples, the performance of enDNA-Prot outperformed the three existing methods by 2.83–16.63% in terms of ACC and 0.02–0.16 in terms of MCC. It indicated that enDNA-Prot is an effective method for DNA-binding protein identification and expanding training dataset with negative samples can improve its performance. For the convenience of the vast majority of experimental scientists, we developed a user-friendly web-server for enDNA-Prot which is freely accessible to the public.

Development of a method for the accurate measurement of protein turnover in neoplastic cells grown in culture

International Nuclear Information System (INIS)

Silverman, J.A.

1984-01-01

In this study, it was shown that standard techniques for cell recovery and sample preparation for liquid scintillation counting led to underestimation of the radioactivity present in cell proteins by 20-40%. These techniques involved labeling with 3 He leucine or 14 C leucine, scraping the cells from the dish in a buffer, TCA precipitation of the cell proteins, solubilization in NaOH and counting in a liquid scintillation counter. Hydrolysis of the proteins with HCl or Pronase significantly increased the recovery of the labeled proteins. Also, solubilization in situ with NaOH or hydrolysis in situ with Pronase recovered 5-10% additional labeled proteins. The techniques developed here allow the accurate measurement of radioactivity in cell proteins. In addition, these techniques were used to study protein turnover in rat hepatoma cells grown in culture. These cells regulated their growth rate through changes in the protein synthesis rate as opposed to changes in the protein degradation rate. These data support the hypothesis that neoplastic cells, unlike normal cells, do not regulate proteolysis in growth control; normal cells under similar conditions have been shown to activate lysosomal proteolysis as they reach confluence. The physiologic implications of this observation are discussed

Comprehensive Identification of Immunodominant Proteins of Brucella abortus and Brucella melitensis Using Antibodies in the Sera from Naturally Infected Hosts

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Gamal Wareth

2016-04-01

Full Text Available Brucellosis is a debilitating zoonotic disease that affects humans and animals. The diagnosis of brucellosis is challenging, as accurate species level identification is not possible with any of the currently available serology-based diagnostic methods. The present study aimed at identifying Brucella (B. species-specific proteins from the closely related species B. abortus and B. melitensis using sera collected from naturally infected host species. Unlike earlier reported investigations with either laboratory-grown species or vaccine strains, in the present study, field strains were utilized for analysis. The label-free quantitative proteomic analysis of the naturally isolated strains of these two closely related species revealed 402 differentially expressed proteins, among which 63 and 103 proteins were found exclusively in the whole cell extracts of B. abortus and B. melitensis field strains, respectively. The sera from four different naturally infected host species, i.e., cattle, buffalo, sheep, and goat were applied to identify the immune-binding protein spots present in the whole protein extracts from the isolated B. abortus and B. melitensis field strains and resolved on two-dimensional gel electrophoresis. Comprehensive analysis revealed that 25 proteins of B. abortus and 20 proteins of B. melitensis were distinctly immunoreactive. Dihydrodipicolinate synthase, glyceraldehyde-3-phosphate dehydrogenase and lactate/malate dehydrogenase from B. abortus, amino acid ABC transporter substrate-binding protein from B. melitensis and fumarylacetoacetate hydrolase from both species were reactive with the sera of all the tested naturally infected host species. The identified proteins could be used for the design of serological assays capable of detecting pan-Brucella, B. abortus- and B. melitensis-specific antibodies.

Fast and accurate resonance assignment of small-to-large proteins by combining automated and manual approaches.

Science.gov (United States)

Niklasson, Markus; Ahlner, Alexandra; Andresen, Cecilia; Marsh, Joseph A; Lundström, Patrik

2015-01-01

The process of resonance assignment is fundamental to most NMR studies of protein structure and dynamics. Unfortunately, the manual assignment of residues is tedious and time-consuming, and can represent a significant bottleneck for further characterization. Furthermore, while automated approaches have been developed, they are often limited in their accuracy, particularly for larger proteins. Here, we address this by introducing the software COMPASS, which, by combining automated resonance assignment with manual intervention, is able to achieve accuracy approaching that from manual assignments at greatly accelerated speeds. Moreover, by including the option to compensate for isotope shift effects in deuterated proteins, COMPASS is far more accurate for larger proteins than existing automated methods. COMPASS is an open-source project licensed under GNU General Public License and is available for download from http://www.liu.se/forskning/foass/tidigare-foass/patrik-lundstrom/software?l=en. Source code and binaries for Linux, Mac OS X and Microsoft Windows are available.

Fast and accurate resonance assignment of small-to-large proteins by combining automated and manual approaches.

Directory of Open Access Journals (Sweden)

Markus Niklasson

2015-01-01

Full Text Available The process of resonance assignment is fundamental to most NMR studies of protein structure and dynamics. Unfortunately, the manual assignment of residues is tedious and time-consuming, and can represent a significant bottleneck for further characterization. Furthermore, while automated approaches have been developed, they are often limited in their accuracy, particularly for larger proteins. Here, we address this by introducing the software COMPASS, which, by combining automated resonance assignment with manual intervention, is able to achieve accuracy approaching that from manual assignments at greatly accelerated speeds. Moreover, by including the option to compensate for isotope shift effects in deuterated proteins, COMPASS is far more accurate for larger proteins than existing automated methods. COMPASS is an open-source project licensed under GNU General Public License and is available for download from http://www.liu.se/forskning/foass/tidigare-foass/patrik-lundstrom/software?l=en. Source code and binaries for Linux, Mac OS X and Microsoft Windows are available.

Preliminary identification of secreted proteins by Leptospira interrogans serovar Kennewicki strain Pomona Fromm

International Nuclear Information System (INIS)

Ricardi, L.M.P.; Portaro, F.C.; Abreu, P.A.E.; Barbosa, A.S.; Morais, Z.M.; Vasconcellos, S.A.

2012-01-01

Full text: This project aimed to identify secreted proteins by pathogenic Leptospira interrogans serovar Kennewicki strain Pomona Fromm (LPF) by proteomic analyses. The strain LPF, whose virulence was maintained by passages in hamsters, were cultured in EMJH medium. The supernatants were centrifuged, dialyzed and subjected to lyophilization. Protein samples were resolved first by IEF at pH 3 to 10, immobilized pH gradient 13-cm strips. Strips were then processed for the second-dimension separation on SDS-polyacrylamide gels. Proteins from gel spots were subjected to reduction, cysteine-alkylation, and in-gel tryptic digestion, and analyzed by LC/MS/MS spectrometry. Liquid chromatography-based separation followed by automated tandem mass spectrometry was also used to identify secreted proteins. In silico analyses were performed using the PSORTbV.3.0 program and SignalP server. One major obstacle to secretome studies is the difficulty to obtain extracts of secreted proteins without citoplasmatic contamination. In addition, the extraction of low concentration proteins from large volumes of culture media, which are rich in salts, BSA and other compounds, frequently interfere with most proteomics techniques. For these reasons, several experimental approaches were used to optimize the protocol applied. In spite of this fact, our analysis resulted in the identification of 200 proteins with high confidence. Only 5 of 63 secreted proteins predicted by in silico analysis were found. Other classes identified included proteins that possess signal peptide but whose cellular localization prediction is unknown or may have multiple localization sites, and proteins that lack signal peptide and are thus thought to be secreted via non conventional mechanisms or resulting from cytoplasmic contamination by cell lysis. Many of these are hypothetical proteins with no putative conserved domains detected. To our knowledge, this is the first study to identify secreted proteins by

Preliminary identification of secreted proteins by Leptospira interrogans serovar Kennewicki strain Pomona Fromm

Energy Technology Data Exchange (ETDEWEB)

Ricardi, L.M.P.; Portaro, F.C.; Abreu, P.A.E.; Barbosa, A.S. [Instituto Butantan, Sao Paulo, SP (Brazil); Morais, Z.M.; Vasconcellos, S.A. [Universidade de Sao Paulo (USP), SP (Brazil)

2012-07-01

Full text: This project aimed to identify secreted proteins by pathogenic Leptospira interrogans serovar Kennewicki strain Pomona Fromm (LPF) by proteomic analyses. The strain LPF, whose virulence was maintained by passages in hamsters, were cultured in EMJH medium. The supernatants were centrifuged, dialyzed and subjected to lyophilization. Protein samples were resolved first by IEF at pH 3 to 10, immobilized pH gradient 13-cm strips. Strips were then processed for the second-dimension separation on SDS-polyacrylamide gels. Proteins from gel spots were subjected to reduction, cysteine-alkylation, and in-gel tryptic digestion, and analyzed by LC/MS/MS spectrometry. Liquid chromatography-based separation followed by automated tandem mass spectrometry was also used to identify secreted proteins. In silico analyses were performed using the PSORTbV.3.0 program and SignalP server. One major obstacle to secretome studies is the difficulty to obtain extracts of secreted proteins without citoplasmatic contamination. In addition, the extraction of low concentration proteins from large volumes of culture media, which are rich in salts, BSA and other compounds, frequently interfere with most proteomics techniques. For these reasons, several experimental approaches were used to optimize the protocol applied. In spite of this fact, our analysis resulted in the identification of 200 proteins with high confidence. Only 5 of 63 secreted proteins predicted by in silico analysis were found. Other classes identified included proteins that possess signal peptide but whose cellular localization prediction is unknown or may have multiple localization sites, and proteins that lack signal peptide and are thus thought to be secreted via non conventional mechanisms or resulting from cytoplasmic contamination by cell lysis. Many of these are hypothetical proteins with no putative conserved domains detected. To our knowledge, this is the first study to identify secreted proteins by

Effective Identification of Akt Interacting Proteins by Two-Step Chemical Crosslinking, Co-Immunoprecipitation and Mass Spectrometry

Science.gov (United States)

Huang, Bill X.; Kim, Hee-Yong

2013-01-01

Akt is a critical protein for cell survival and known to interact with various proteins. However, Akt binding partners that modulate or regulate Akt activation have not been fully elucidated. Identification of Akt-interacting proteins has been customarily achieved by co-immunoprecipitation combined with western blot and/or MS analysis. An intrinsic problem of the method is loss of interacting proteins during procedures to remove non-specific proteins. Moreover, antibody contamination often interferes with the detection of less abundant proteins. Here, we developed a novel two-step chemical crosslinking strategy to overcome these problems which resulted in a dramatic improvement in identifying Akt interacting partners. Akt antibody was first immobilized on protein A/G beads using disuccinimidyl suberate and allowed to bind to cellular Akt along with its interacting proteins. Subsequently, dithiobis[succinimidylpropionate], a cleavable crosslinker, was introduced to produce stable complexes between Akt and binding partners prior to the SDS-PAGE and nanoLC-MS/MS analysis. This approach enabled identification of ten Akt partners from cell lysates containing as low as 1.5 mg proteins, including two new potential Akt interacting partners. None of these but one protein was detectable without crosslinking procedures. The present method provides a sensitive and effective tool to probe Akt-interacting proteins. This strategy should also prove useful for other protein interactions, particularly those involving less abundant or weakly associating partners. PMID:23613850

Ribosomal subunit protein typing using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) for the identification and discrimination of Aspergillus species.

Science.gov (United States)

Nakamura, Sayaka; Sato, Hiroaki; Tanaka, Reiko; Kusuya, Yoko; Takahashi, Hiroki; Yaguchi, Takashi

2017-04-26

Accurate identification of Aspergillus species is a very important subject. Mass spectral fingerprinting using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is generally employed for the rapid identification of fungal isolates. However, the results are based on simple mass spectral pattern-matching, with no peak assignment and no taxonomic input. We propose here a ribosomal subunit protein (RSP) typing technique using MALDI-TOF MS for the identification and discrimination of Aspergillus species. The results are concluded to be phylogenetic in that they reflect the molecular evolution of housekeeping RSPs. The amino acid sequences of RSPs of genome-sequenced strains of Aspergillus species were first verified and compared to compile a reliable biomarker list for the identification of Aspergillus species. In this process, we revealed that many amino acid sequences of RSPs (about 10-60%, depending on strain) registered in the public protein databases needed to be corrected or newly added. The verified RSPs were allocated to RSP types based on their mass. Peak assignments of RSPs of each sample strain as observed by MALDI-TOF MS were then performed to set RSP type profiles, which were then further processed by means of cluster analysis. The resulting dendrogram based on RSP types showed a relatively good concordance with the tree based on β-tubulin gene sequences. RSP typing was able to further discriminate the strains belonging to Aspergillus section Fumigati. The RSP typing method could be applied to identify Aspergillus species, even for species within section Fumigati. The discrimination power of RSP typing appears to be comparable to conventional β-tubulin gene analysis. This method would therefore be suitable for species identification and discrimination at the strain to species level. Because RSP typing can characterize the strains within section Fumigati, this method has potential as a powerful and reliable tool in

Identification of Differentially Abundant Proteins of Edwardsiella ictaluri during Iron Restriction.

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Pradeep R Dumpala

Full Text Available Edwardsiella ictaluri is a Gram-negative facultative anaerobe intracellular bacterium that causes enteric septicemia in channel catfish. Iron is an essential inorganic nutrient of bacteria and is crucial for bacterial invasion. Reduced availability of iron by the host may cause significant stress for bacterial pathogens and is considered a signal that leads to significant alteration in virulence gene expression. However, the precise effect of iron-restriction on E. ictaluri protein abundance is unknown. The purpose of this study was to identify differentially abundant proteins of E. ictaluri during in vitro iron-restricted conditions. We applied two-dimensional difference in gel electrophoresis (2D-DIGE for determining differentially abundant proteins and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI TOF/TOF MS for protein identification. Gene ontology and pathway-based functional modeling of differentially abundant proteins was also conducted. A total of 50 unique differentially abundant proteins at a minimum of 2-fold (p ≤ 0.05 difference in abundance due to iron-restriction were detected. The numbers of up- and down-regulated proteins were 37 and 13, respectively. We noted several proteins, including EsrB, LamB, MalM, MalE, FdaA, and TonB-dependent heme/hemoglobin receptor family proteins responded to iron restriction in E. ictaluri.

MASCOT HTML and XML parser: an implementation of a novel object model for protein identification data.

Science.gov (United States)

Yang, Chunguang G; Granite, Stephen J; Van Eyk, Jennifer E; Winslow, Raimond L

2006-11-01

Protein identification using MS is an important technique in proteomics as well as a major generator of proteomics data. We have designed the protein identification data object model (PDOM) and developed a parser based on this model to facilitate the analysis and storage of these data. The parser works with HTML or XML files saved or exported from MASCOT MS/MS ions search in peptide summary report or MASCOT PMF search in protein summary report. The program creates PDOM objects, eliminates redundancy in the input file, and has the capability to output any PDOM object to a relational database. This program facilitates additional analysis of MASCOT search results and aids the storage of protein identification information. The implementation is extensible and can serve as a template to develop parsers for other search engines. The parser can be used as a stand-alone application or can be driven by other Java programs. It is currently being used as the front end for a system that loads HTML and XML result files of MASCOT searches into a relational database. The source code is freely available at http://www.ccbm.jhu.edu and the program uses only free and open-source Java libraries.

MFPred: Rapid and accurate prediction of protein-peptide recognition multispecificity using self-consistent mean field theory.

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Aliza B Rubenstein

2017-06-01

Full Text Available Multispecificity-the ability of a single receptor protein molecule to interact with multiple substrates-is a hallmark of molecular recognition at protein-protein and protein-peptide interfaces, including enzyme-substrate complexes. The ability to perform structure-based prediction of multispecificity would aid in the identification of novel enzyme substrates, protein interaction partners, and enable design of novel enzymes targeted towards alternative substrates. The relatively slow speed of current biophysical, structure-based methods limits their use for prediction and, especially, design of multispecificity. Here, we develop a rapid, flexible-backbone self-consistent mean field theory-based technique, MFPred, for multispecificity modeling at protein-peptide interfaces. We benchmark our method by predicting experimentally determined peptide specificity profiles for a range of receptors: protease and kinase enzymes, and protein recognition modules including SH2, SH3, MHC Class I and PDZ domains. We observe robust recapitulation of known specificities for all receptor-peptide complexes, and comparison with other methods shows that MFPred results in equivalent or better prediction accuracy with a ~10-1000-fold decrease in computational expense. We find that modeling bound peptide backbone flexibility is key to the observed accuracy of the method. We used MFPred for predicting with high accuracy the impact of receptor-side mutations on experimentally determined multispecificity of a protease enzyme. Our approach should enable the design of a wide range of altered receptor proteins with programmed multispecificities.

Identification and characterization of RBM44 as a novel intercellular bridge protein.

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Tokuko Iwamori

2011-02-01

Full Text Available Intercellular bridges are evolutionarily conserved structures that connect differentiating germ cells. We previously reported the identification of TEX14 as the first essential intercellular bridge protein, the demonstration that intercellular bridges are required for male fertility, and the finding that intercellular bridges utilize components of the cytokinesis machinery to form. Herein, we report the identification of RNA binding motif protein 44 (RBM44 as a novel germ cell intercellular bridge protein. RBM44 was identified by proteomic analysis after intercellular bridge enrichment using TEX14 as a marker protein. RBM44 is highly conserved between mouse and human and contains an RNA recognition motif of unknown function. RBM44 mRNA is enriched in testis, and immunofluorescence confirms that RBM44 is an intercellular bridge component. However, RBM44 only partially localizes to TEX14-positive intercellular bridges. RBM44 is expressed most highly in pachytene and secondary spermatocytes, but disappears abruptly in spermatids. We discovered that RBM44 interacts with itself and TEX14 using yeast two-hybrid, mammalian two-hybrid, and immunoprecipitation. To define the in vivo function of RBM44, we generated a targeted deletion of Rbm44 in mice. Rbm44 null male mice produce somewhat increased sperm, and show enhanced fertility of unknown etiology. Thus, although RBM44 localizes to intercellular bridges during meiosis, RBM44 is not required for fertility in contrast to TEX14.

Identification of Importin 8 (IPO8 as the most accurate reference gene for the clinicopathological analysis of lung specimens

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Pio Ruben

2008-11-01

Full Text Available Abstract Background The accurate normalization of differentially expressed genes in lung cancer is essential for the identification of novel therapeutic targets and biomarkers by real time RT-PCR and microarrays. Although classical "housekeeping" genes, such as GAPDH, HPRT1, and beta-actin have been widely used in the past, their accuracy as reference genes for lung tissues has not been proven. Results We have conducted a thorough analysis of a panel of 16 candidate reference genes for lung specimens and lung cell lines. Gene expression was measured by quantitative real time RT-PCR and expression stability was analyzed with the softwares GeNorm and NormFinder, mean of |ΔCt| (= |Ct Normal-Ct tumor| ± SEM, and correlation coefficients among genes. Systematic comparison between candidates led us to the identification of a subset of suitable reference genes for clinical samples: IPO8, ACTB, POLR2A, 18S, and PPIA. Further analysis showed that IPO8 had a very low mean of |ΔCt| (0.70 ± 0.09, with no statistically significant differences between normal and malignant samples and with excellent expression stability. Conclusion Our data show that IPO8 is the most accurate reference gene for clinical lung specimens. In addition, we demonstrate that the commonly used genes GAPDH and HPRT1 are inappropriate to normalize data derived from lung biopsies, although they are suitable as reference genes for lung cell lines. We thus propose IPO8 as a novel reference gene for lung cancer samples.

Electrostatics of proteins in dielectric solvent continua. I. An accurate and efficient reaction field description.

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Bauer, Sebastian; Mathias, Gerald; Tavan, Paul

2014-03-14

We present a reaction field (RF) method which accurately solves the Poisson equation for proteins embedded in dielectric solvent continua at a computational effort comparable to that of an electrostatics calculation with polarizable molecular mechanics (MM) force fields. The method combines an approach originally suggested by Egwolf and Tavan [J. Chem. Phys. 118, 2039 (2003)] with concepts generalizing the Born solution [Z. Phys. 1, 45 (1920)] for a solvated ion. First, we derive an exact representation according to which the sources of the RF potential and energy are inducible atomic anti-polarization densities and atomic shielding charge distributions. Modeling these atomic densities by Gaussians leads to an approximate representation. Here, the strengths of the Gaussian shielding charge distributions are directly given in terms of the static partial charges as defined, e.g., by standard MM force fields for the various atom types, whereas the strengths of the Gaussian anti-polarization densities are calculated by a self-consistency iteration. The atomic volumes are also described by Gaussians. To account for covalently overlapping atoms, their effective volumes are calculated by another self-consistency procedure, which guarantees that the dielectric function ε(r) is close to one everywhere inside the protein. The Gaussian widths σ(i) of the atoms i are parameters of the RF approximation. The remarkable accuracy of the method is demonstrated by comparison with Kirkwood's analytical solution for a spherical protein [J. Chem. Phys. 2, 351 (1934)] and with computationally expensive grid-based numerical solutions for simple model systems in dielectric continua including a di-peptide (Ac-Ala-NHMe) as modeled by a standard MM force field. The latter example shows how weakly the RF conformational free energy landscape depends on the parameters σ(i). A summarizing discussion highlights the achievements of the new theory and of its approximate solution particularly by

Electrostatics of proteins in dielectric solvent continua. I. An accurate and efficient reaction field description

Energy Technology Data Exchange (ETDEWEB)

Bauer, Sebastian; Mathias, Gerald; Tavan, Paul, E-mail: paul.tavan@physik.uni-muenchen.de [Lehrstuhl für BioMolekulare Optik, Ludwig–Maximilians Universität München, Oettingenstr. 67, 80538 München (Germany)

2014-03-14

We present a reaction field (RF) method which accurately solves the Poisson equation for proteins embedded in dielectric solvent continua at a computational effort comparable to that of an electrostatics calculation with polarizable molecular mechanics (MM) force fields. The method combines an approach originally suggested by Egwolf and Tavan [J. Chem. Phys. 118, 2039 (2003)] with concepts generalizing the Born solution [Z. Phys. 1, 45 (1920)] for a solvated ion. First, we derive an exact representation according to which the sources of the RF potential and energy are inducible atomic anti-polarization densities and atomic shielding charge distributions. Modeling these atomic densities by Gaussians leads to an approximate representation. Here, the strengths of the Gaussian shielding charge distributions are directly given in terms of the static partial charges as defined, e.g., by standard MM force fields for the various atom types, whereas the strengths of the Gaussian anti-polarization densities are calculated by a self-consistency iteration. The atomic volumes are also described by Gaussians. To account for covalently overlapping atoms, their effective volumes are calculated by another self-consistency procedure, which guarantees that the dielectric function ε(r) is close to one everywhere inside the protein. The Gaussian widths σ{sub i} of the atoms i are parameters of the RF approximation. The remarkable accuracy of the method is demonstrated by comparison with Kirkwood's analytical solution for a spherical protein [J. Chem. Phys. 2, 351 (1934)] and with computationally expensive grid-based numerical solutions for simple model systems in dielectric continua including a di-peptide (Ac-Ala-NHMe) as modeled by a standard MM force field. The latter example shows how weakly the RF conformational free energy landscape depends on the parameters σ{sub i}. A summarizing discussion highlights the achievements of the new theory and of its approximate solution

Identification of NAD interacting residues in proteins

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Raghava Gajendra PS

2010-03-01

Full Text Available Abstract Background Small molecular cofactors or ligands play a crucial role in the proper functioning of cells. Accurate annotation of their target proteins and binding sites is required for the complete understanding of reaction mechanisms. Nicotinamide adenine dinucleotide (NAD+ or NAD is one of the most commonly used organic cofactors in living cells, which plays a critical role in cellular metabolism, storage and regulatory processes. In the past, several NAD binding proteins (NADBP have been reported in the literature, which are responsible for a wide-range of activities in the cell. Attempts have been made to derive a rule for the binding of NAD+ to its target proteins. However, so far an efficient model could not be derived due to the time consuming process of structure determination, and limitations of similarity based approaches. Thus a sequence and non-similarity based method is needed to characterize the NAD binding sites to help in the annotation. In this study attempts have been made to predict NAD binding proteins and their interacting residues (NIRs from amino acid sequence using bioinformatics tools. Results We extracted 1556 proteins chains from 555 NAD binding proteins whose structure is available in Protein Data Bank. Then we removed all redundant protein chains and finally obtained 195 non-redundant NAD binding protein chains, where no two chains have more than 40% sequence identity. In this study all models were developed and evaluated using five-fold cross validation technique on the above dataset of 195 NAD binding proteins. While certain type of residues are preferred (e.g. Gly, Tyr, Thr, His in NAD interaction, residues like Ala, Glu, Leu, Lys are not preferred. A support vector machine (SVM based method has been developed using various window lengths of amino acid sequence for predicting NAD interacting residues and obtained maximum Matthew's correlation coefficient (MCC 0.47 with accuracy 74.13% at window length 17

Multi-Segment Direct Inject nano-ESI-LTQ-FT-ICR-MS/MS For Protein Identification

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Neal Rachel E

2011-07-01

Full Text Available Abstract Reversed phase high performance liquid chromatography (HPLC interfaced to electrospray tandem mass spectrometry (MS/MS is commonly used for the identification of peptides from proteolytically cleaved proteins embedded in a polyacrylamide gel matrix as well as for metabolomics screening. HPLC separations are time consuming (30-60 min average, costly (columns and mobile phase reagents, and carry the risk of column carry over between samples. The use of a chip-based nano-ESI platform (Advion NanoMate based on replaceable nano-tips for sample introduction eliminates sample cross-contamination, provides unchanging sample matrix, and enhances spray stability with attendant increases in reproducibility. Recent papers have established direct infusion nano-ESI-MS/MS utilizing the NanoMate for protein identification of gel spots based on full range MS scans with data dependent MS/MS. In a full range scan, discontinuous ion suppression due to sample matrix can impair identification of putative mass features of interest in both the proteomic and metabolomic workflows. In the current study, an extension of an established direct inject nano-ESI-MS/MS method is described that utilizes the mass filtering capability of an ion-trap for ion packet separation into four narrow mass ranges (50 amu overlap with segment specific dynamic data dependent peak inclusion for MS/MS fragmentation (total acquisition time of 3 minutes. Comparison of this method with a more traditional nanoLC-MS/MS based protocol utilizing solvent/sample stream splitting to achieve nanoflow demonstrated comparable results for protein identification from polyacrylamide gel matrices. The advantages of this method include full automation, lack of cross-contamination, low cost, and high throughput.

Identification of phosphorylation sites in protein kinase A substrates using artificial neural networks and mass spectrometry

DEFF Research Database (Denmark)

Hjerrild, M.; Stensballe, A.; Rasmussen, T.E.

2004-01-01

Protein phosphorylation plays a key role in cell regulation and identification of phosphorylation sites is important for understanding their functional significance. Here, we present an artificial neural network algorithm: NetPhosK (http://www.cbs.dtu.dk/services/NetPhosK/) that predicts protein...

Identification of phosphorylation sites in protein kinase A substrates using artificial neural networks and mass spectrometry

DEFF Research Database (Denmark)

Hjerrild, Majbrit; Stensballe, Allan; Rasmussen, Thomas E

2011-01-01

Protein phosphorylation plays a key role in cell regulation and identification of phosphorylation sites is important for understanding their functional significance. Here, we present an artificial neural network algorithm: NetPhosK (http://www.cbs.dtu.dk/services/NetPhosK/) that predicts protein...

GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula.

Science.gov (United States)

Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling; Wang, Yun

2018-01-01

The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components.

Identification of Pentatricopeptide Repeat Proteins in the Model Organism Dictyostelium discoideum

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Sam Manna

2013-01-01

Full Text Available Pentatricopeptide repeat (PPR proteins are RNA binding proteins with functions in organelle RNA metabolism. They are found in all eukaryotes but have been most extensively studied in plants. We report on the identification of 12 PPR-encoding genes in the genome of the protist Dictyostelium discoideum, with potential homologs in other members of the same lineage and some predicted novel functions for the encoded gene products in protists. For one of the gene products, we show that it localizes to the mitochondria, and we also demonstrate that antisense inhibition of its expression leads to slower growth, a phenotype associated with mitochondrial dysfunction.

Isolation and identification of the human homolog of a new p53-binding protein, Mdmx

NARCIS (Netherlands)

Shvarts, A.; Bazuine, M.; Dekker, P.; Ramos, Y. F.; Steegenga, W. T.; Merckx, G.; van Ham, R. C.; van der Houven van Oordt, W.; van der Eb, A. J.; Jochemsen, A. G.

1997-01-01

We recently reported the identification of a mouse cDNA encoding a new p53-associating protein that we called Mdmx because of its structural similarity to Mdm2, a well-known p53-binding protein. Here we report the isolation of a cDNA encoding the human homolog of Mdmx. The ORF of the cDNA encodes a

Metagenome and Metatranscriptome Analyses Using Protein Family Profiles.

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Cuncong Zhong

2016-07-01

Full Text Available Analyses of metagenome data (MG and metatranscriptome data (MT are often challenged by a paucity of complete reference genome sequences and the uneven/low sequencing depth of the constituent organisms in the microbial community, which respectively limit the power of reference-based alignment and de novo sequence assembly. These limitations make accurate protein family classification and abundance estimation challenging, which in turn hamper downstream analyses such as abundance profiling of metabolic pathways, identification of differentially encoded/expressed genes, and de novo reconstruction of complete gene and protein sequences from the protein family of interest. The profile hidden Markov model (HMM framework enables the construction of very useful probabilistic models for protein families that allow for accurate modeling of position specific matches, insertions, and deletions. We present a novel homology detection algorithm that integrates banded Viterbi algorithm for profile HMM parsing with an iterative simultaneous alignment and assembly computational framework. The algorithm searches a given profile HMM of a protein family against a database of fragmentary MG/MT sequencing data and simultaneously assembles complete or near-complete gene and protein sequences of the protein family. The resulting program, HMM-GRASPx, demonstrates superior performance in aligning and assembling homologs when benchmarked on both simulated marine MG and real human saliva MG datasets. On real supragingival plaque and stool MG datasets that were generated from healthy individuals, HMM-GRASPx accurately estimates the abundances of the antimicrobial resistance (AMR gene families and enables accurate characterization of the resistome profiles of these microbial communities. For real human oral microbiome MT datasets, using the HMM-GRASPx estimated transcript abundances significantly improves detection of differentially expressed (DE genes. Finally, HMM

Exploring the universe of protein structures beyond the Protein Data Bank.

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Pilar Cossio

Full Text Available It is currently believed that the atlas of existing protein structures is faithfully represented in the Protein Data Bank. However, whether this atlas covers the full universe of all possible protein structures is still a highly debated issue. By using a sophisticated numerical approach, we performed an exhaustive exploration of the conformational space of a 60 amino acid polypeptide chain described with an accurate all-atom interaction potential. We generated a database of around 30,000 compact folds with at least of secondary structure corresponding to local minima of the potential energy. This ensemble plausibly represents the universe of protein folds of similar length; indeed, all the known folds are represented in the set with good accuracy. However, we discover that the known folds form a rather small subset, which cannot be reproduced by choosing random structures in the database. Rather, natural and possible folds differ by the contact order, on average significantly smaller in the former. This suggests the presence of an evolutionary bias, possibly related to kinetic accessibility, towards structures with shorter loops between contacting residues. Beside their conceptual relevance, the new structures open a range of practical applications such as the development of accurate structure prediction strategies, the optimization of force fields, and the identification and design of novel folds.

Nucleos: a web server for the identification of nucleotide-binding sites in protein structures.

Science.gov (United States)

Parca, Luca; Ferré, Fabrizio; Ausiello, Gabriele; Helmer-Citterich, Manuela

2013-07-01

Nucleos is a web server for the identification of nucleotide-binding sites in protein structures. Nucleos compares the structure of a query protein against a set of known template 3D binding sites representing nucleotide modules, namely the nucleobase, carbohydrate and phosphate. Structural features, clustering and conservation are used to filter and score the predictions. The predicted nucleotide modules are then joined to build whole nucleotide-binding sites, which are ranked by their score. The server takes as input either the PDB code of the query protein structure or a user-submitted structure in PDB format. The output of Nucleos is composed of ranked lists of predicted nucleotide-binding sites divided by nucleotide type (e.g. ATP-like). For each ranked prediction, Nucleos provides detailed information about the score, the template structure and the structural match for each nucleotide module composing the nucleotide-binding site. The predictions on the query structure and the template-binding sites can be viewed directly on the web through a graphical applet. In 98% of the cases, the modules composing correct predictions belong to proteins with no homology relationship between each other, meaning that the identification of brand-new nucleotide-binding sites is possible using information from non-homologous proteins. Nucleos is available at http://nucleos.bio.uniroma2.it/nucleos/.

A practical guide for the identification of membrane and plasma membrane proteins in human embryonic stem cells and human embryonal carcinoma cells.

Science.gov (United States)

Dormeyer, Wilma; van Hoof, Dennis; Mummery, Christine L; Krijgsveld, Jeroen; Heck, Albert J R

2008-10-01

The identification of (plasma) membrane proteins in cells can provide valuable insights into the regulation of their biological processes. Pluripotent cells such as human embryonic stem cells and embryonal carcinoma cells are capable of unlimited self-renewal and share many of the biological mechanisms that regulate proliferation and differentiation. The comparison of their membrane proteomes will help unravel the biological principles of pluripotency, and the identification of biomarker proteins in their plasma membranes is considered a crucial step to fully exploit pluripotent cells for therapeutic purposes. For these tasks, membrane proteomics is the method of choice, but as indicated by the scarce identification of membrane and plasma membrane proteins in global proteomic surveys it is not an easy task. In this minireview, we first describe the general challenges of membrane proteomics. We then review current sample preparation steps and discuss protocols that we found particularly beneficial for the identification of large numbers of (plasma) membrane proteins in human tumour- and embryo-derived stem cells. Our optimized assembled protocol led to the identification of a large number of membrane proteins. However, as the composition of cells and membranes is highly variable we still recommend adapting the sample preparation protocol for each individual system.

P185-M Protein Identification and Validation of Results in Workflows that Integrate over Various Instruments, Datasets, Search Engines

Science.gov (United States)

Hufnagel, P.; Glandorf, J.; Körting, G.; Jabs, W.; Schweiger-Hufnagel, U.; Hahner, S.; Lubeck, M.; Suckau, D.

2007-01-01

Analysis of complex proteomes often results in long protein lists, but falls short in measuring the validity of identification and quantification results on a greater number of proteins. Biological and technical replicates are mandatory, as is the combination of the MS data from various workflows (gels, 1D-LC, 2D-LC), instruments (TOF/TOF, trap, qTOF or FTMS), and search engines. We describe a database-driven study that combines two workflows, two mass spectrometers, and four search engines with protein identification following a decoy database strategy. The sample was a tryptically digested lysate (10,000 cells) of a human colorectal cancer cell line. Data from two LC-MALDI-TOF/TOF runs and a 2D-LC-ESI-trap run using capillary and nano-LC columns were submitted to the proteomics software platform ProteinScape. The combined MALDI data and the ESI data were searched using Mascot (Matrix Science), Phenyx (GeneBio), ProteinSolver (Bruker and Protagen), and Sequest (Thermo) against a decoy database generated from IPI-human in order to obtain one protein list across all workflows and search engines at a defined maximum false-positive rate of 5%. ProteinScape combined the data to one LC-MALDI and one LC-ESI dataset. The initial separate searches from the two combined datasets generated eight independent peptide lists. These were compiled into an integrated protein list using the ProteinExtractor algorithm. An initial evaluation of the generated data led to the identification of approximately 1200 proteins. Result integration on a peptide level allowed discrimination of protein isoforms that would not have been possible with a mere combination of protein lists.

Stable and accurate methods for identification of water bodies from Landsat series imagery using meta-heuristic algorithms

Science.gov (United States)

Gamshadzaei, Mohammad Hossein; Rahimzadegan, Majid

2017-10-01

Identification of water extents in Landsat images is challenging due to surfaces with similar reflectance to water extents. The objective of this study is to provide stable and accurate methods for identifying water extents in Landsat images based on meta-heuristic algorithms. Then, seven Landsat images were selected from various environmental regions in Iran. Training of the algorithms was performed using 40 water pixels and 40 nonwater pixels in operational land imager images of Chitgar Lake (one of the study regions). Moreover, high-resolution images from Google Earth were digitized to evaluate the results. Two approaches were considered: index-based and artificial intelligence (AI) algorithms. In the first approach, nine common water spectral indices were investigated. AI algorithms were utilized to acquire coefficients of optimal band combinations to extract water extents. Among the AI algorithms, the artificial neural network algorithm and also the ant colony optimization, genetic algorithm, and particle swarm optimization (PSO) meta-heuristic algorithms were implemented. Index-based methods represented different performances in various regions. Among AI methods, PSO had the best performance with average overall accuracy and kappa coefficient of 93% and 98%, respectively. The results indicated the applicability of acquired band combinations to extract accurately and stably water extents in Landsat imagery.

Multidimensional protein fractionation of blood proteins coupled to data-independent nanoLC-MS/MS analysis.

Science.gov (United States)

Levin, Yishai; Jaros, Julian A J; Schwarz, Emanuel; Bahn, Sabine

2010-01-03

In order to exploit human blood as a source of protein disease biomarkers, robust analytical methods are needed to overcome the inherent molecular complexity of this bio-fluid. We present the coupling of label-free SAX chromatography and IMAC to a data-independent nanoLC-MS/MS (nanoLC-MS(E)) platform for analysis of blood plasma and serum proteins. The methods were evaluated using protein standards added at different concentrations to two groups of samples. The results demonstrate that both techniques enable accurate protein quantitation using low sample volumes and a minimal number of fractions. Combining both methods, 883 unique proteins were identified, of which 423 proteins showed high reproducibility. The two approaches resulted in identification of unique molecular signatures with an overlap of approximately 30%, thus providing complimentary information on sub-proteomes. These methods are potentially useful for systems biology, biomarker discovery, and investigation of phosphoproteins in blood. (c) 2009 Elsevier B.V. All rights reserved.

Ribosomal proteins as biomarkers for bacterial identification by mass spectrometry in the clinical microbiology laboratory.

Science.gov (United States)

Suarez, Stéphanie; Ferroni, Agnès; Lotz, Aurélie; Jolley, Keith A; Guérin, Philippe; Leto, Julie; Dauphin, Brunhilde; Jamet, Anne; Maiden, Martin C J; Nassif, Xavier; Armengaud, Jean

2013-09-01

Whole-cell matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is a rapid method for identification of microorganisms that is increasingly used in microbiology laboratories. This identification is based on the comparison of the tested isolate mass spectrum with reference databases. Using Neisseria meningitidis as a model organism, we showed that in one of the available databases, the Andromas database, 10 of the 13 species-specific biomarkers correspond to ribosomal proteins. Remarkably, one biomarker, ribosomal protein L32, was subject to inter-strain variability. The analysis of the ribosomal protein patterns of 100 isolates for which whole genome sequences were available, confirmed the presence of inter-strain variability in the molecular weight of 29 ribosomal proteins, thus establishing a correlation between the sequence type (ST) and/or clonal complex (CC) of each strain and its ribosomal protein pattern. Since the molecular weight of three of the variable ribosomal proteins (L30, L31 and L32) was included in the spectral window observed by MALDI-TOF MS in clinical microbiology, i.e., 3640-12000 m/z, we were able by analyzing the molecular weight of these three ribosomal proteins to classify each strain in one of six subgroups, each of these subgroups corresponding to specific STs and/or CCs. Their detection by MALDI-TOF allows therefore a quick typing of N. meningitidis isolates. © 2013 Elsevier B.V. All rights reserved.

Optimization of the GBMV2 implicit solvent force field for accurate simulation of protein conformational equilibria.

Science.gov (United States)

Lee, Kuo Hao; Chen, Jianhan

2017-06-15

Accurate treatment of solvent environment is critical for reliable simulations of protein conformational equilibria. Implicit treatment of solvation, such as using the generalized Born (GB) class of models arguably provides an optimal balance between computational efficiency and physical accuracy. Yet, GB models are frequently plagued by a tendency to generate overly compact structures. The physical origins of this drawback are relatively well understood, and the key to a balanced implicit solvent protein force field is careful optimization of physical parameters to achieve a sufficient level of cancellation of errors. The latter has been hampered by the difficulty of generating converged conformational ensembles of non-trivial model proteins using the popular replica exchange sampling technique. Here, we leverage improved sampling efficiency of a newly developed multi-scale enhanced sampling technique to re-optimize the generalized-Born with molecular volume (GBMV2) implicit solvent model with the CHARMM36 protein force field. Recursive optimization of key GBMV2 parameters (such as input radii) and protein torsion profiles (via the CMAP torsion cross terms) has led to a more balanced GBMV2 protein force field that recapitulates the structures and stabilities of both helical and β-hairpin model peptides. Importantly, this force field appears to be free of the over-compaction bias, and can generate structural ensembles of several intrinsically disordered proteins of various lengths that seem highly consistent with available experimental data. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Identification of lipopolysaccharide-interacting plasma membrane-type proteins in Arabidopsis thaliana.

Science.gov (United States)

Vilakazi, Cornelius S; Dubery, Ian A; Piater, Lizelle A

2017-02-01

Lipopolysaccharide (LPS) is an amphiphatic bacterial glycoconjugate found on the external membrane of Gram-negative bacteria. This endotoxin is considered as a microbe-associated molecular pattern (MAMP) molecule and has been shown to elicit defense responses in plants. Here, LPS-interacting proteins from Arabidopsis thaliana plasma membrane (PM)-type fractions were captured and identified in order to investigate those involved in LPS perception and linked to triggering of innate immune responses. A novel proteomics-based affinity-capture strategy coupled to liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed for the enrichment and identification of LPS-interacting proteins. As such, LPS isolated from Burkholderia cepacia (LPS B.cep. ) was immobilized on three independent and distinct affinity-based matrices to serve as bait for interacting proteins from A. thaliana leaf and callus tissue. These were resolved by 1D electrophoresis and identified by mass spectrometry. Proteins specifically bound to LPS B.cep. have been implicated in membrane structure (e.g. COBRA-like and tubulin proteins), membrane trafficking and/or transport (e.g. soluble NSF attachment protein receptor (SNARE) proteins, patellin, aquaporin, PM instrinsic proteins (PIP) and H + -ATPase), signal transduction (receptor-like kinases and calcium-dependent protein kinases) as well as defense/stress responses (e.g. hypersensitive-induced response (HIR) proteins, jacalin-like lectin domain-containing protein and myrosinase-binding proteins). The novel affinity-capture strategy for the enrichment of LPS-interacting proteins proved to be effective, especially in the binding of proteins involved in plant defense responses, and can thus be used to elucidate LPS-mediated molecular recognition and disease mechanism(s). Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Rapid and accurate identification of Streptococcus equi subspecies by MALDI-TOF MS

DEFF Research Database (Denmark)

Kudirkiene, Egle; Welker, Martin; Knudsen, Nanna Reumert

2015-01-01

phenotypic and sequence similarity between three subspecies their discrimination remains difficult. In this study, we aimed to design and validate a novel, Superspectra based, MALDI-TOF MS approach for reliable, rapid and cost-effective identification of SEE and SEZ, the most frequent S. equi subspecies.......3±7.5%). This result may be attributed to the highly clonal population structure of SEE, as opposed to the diversity of SEZ seen in horses. Importantly strains with atypical colony appearance both within SEE and SEZ did not affect correct identification of the strains by MALDI-TOF MS. Atypical colony variants...... are often associated with a higher persistence or virulence of S. equi, thus their correct identification using the current method strengthens its potential use in routine clinical diagnostics. In conclusion, reliable identification of S. equi subspecies was achieved by combining a MALDI-TOF MS method...

Efficient identification of critical residues based only on protein structure by network analysis.

Directory of Open Access Journals (Sweden)

Michael P Cusack

2007-05-01

Full Text Available Despite the increasing number of published protein structures, and the fact that each protein's function relies on its three-dimensional structure, there is limited access to automatic programs used for the identification of critical residues from the protein structure, compared with those based on protein sequence. Here we present a new algorithm based on network analysis applied exclusively on protein structures to identify critical residues. Our results show that this method identifies critical residues for protein function with high reliability and improves automatic sequence-based approaches and previous network-based approaches. The reliability of the method depends on the conformational diversity screened for the protein of interest. We have designed a web site to give access to this software at http://bis.ifc.unam.mx/jamming/. In summary, a new method is presented that relates critical residues for protein function with the most traversed residues in networks derived from protein structures. A unique feature of the method is the inclusion of the conformational diversity of proteins in the prediction, thus reproducing a basic feature of the structure/function relationship of proteins.

Proteomic platform for the identification of proteins in olive (Olea europaea) pulp.

Science.gov (United States)

Capriotti, Anna Laura; Cavaliere, Chiara; Foglia, Patrizia; Piovesana, Susy; Samperi, Roberto; Stampachiacchiere, Serena; Laganà, Aldo

2013-10-24

The nutritional and cancer-protective properties of the oil extracted mechanically from the ripe fruits of Olea europaea trees are attracting constantly more attention worldwide. The preparation of high-quality protein samples from plant tissues for proteomic analysis poses many challenging problems. In this study we employed a proteomic platform based on two different extraction methods, SDS and CHAPS based protocols, followed by two precipitation protocols, TCA/acetone and MeOH precipitation, in order to increase the final number of identified proteins. The use of advanced MS techniques in combination with the Swissprot and NCBI Viridiplantae databases and TAIR10 Arabidopsis database allowed us to identify 1265 proteins, of which 22 belong to O. europaea. The application of this proteomic platform for protein extraction and identification will be useful also for other proteomic studies on recalcitrant plant/fruit tissues. Copyright © 2013. Published by Elsevier B.V.

Mass spectrometry applied to the identification of Mycobacterium tuberculosis and biomarker discovery.

Science.gov (United States)

López-Hernández, Y; Patiño-Rodríguez, O; García-Orta, S T; Pinos-Rodríguez, J M

2016-12-01

An adequate and effective tuberculosis (TB) diagnosis system has been identified by the World Health Organization as a priority in the fight against this disease. Over the years, several methods have been developed to identify the bacillus, but bacterial culture remains one of the most affordable methods for most countries. For rapid and accurate identification, however, it is more feasible to implement molecular techniques, taking advantage of the availability of public databases containing protein sequences. Mass spectrometry (MS) has become an interesting technique for the identification of TB. Here, we review some of the most widely employed methods for identifying Mycobacterium tuberculosis and present an update on MS applied for the identification of mycobacterial species. © 2016 The Society for Applied Microbiology.

Identification and characterization of plastid-type proteins from sequence-attributed features using machine learning

Science.gov (United States)

2013-01-01

Background Plastids are an important component of plant cells, being the site of manufacture and storage of chemical compounds used by the cell, and contain pigments such as those used in photosynthesis, starch synthesis/storage, cell color etc. They are essential organelles of the plant cell, also present in algae. Recent advances in genomic technology and sequencing efforts is generating a huge amount of DNA sequence data every day. The predicted proteome of these genomes needs annotation at a faster pace. In view of this, one such annotation need is to develop an automated system that can distinguish between plastid and non-plastid proteins accurately, and further classify plastid-types based on their functionality. We compared the amino acid compositions of plastid proteins with those of non-plastid ones and found significant differences, which were used as a basis to develop various feature-based prediction models using similarity-search and machine learning. Results In this study, we developed separate Support Vector Machine (SVM) trained classifiers for characterizing the plastids in two steps: first distinguishing the plastid vs. non-plastid proteins, and then classifying the identified plastids into their various types based on their function (chloroplast, chromoplast, etioplast, and amyloplast). Five diverse protein features: amino acid composition, dipeptide composition, the pseudo amino acid composition, Nterminal-Center-Cterminal composition and the protein physicochemical properties are used to develop SVM models. Overall, the dipeptide composition-based module shows the best performance with an accuracy of 86.80% and Matthews Correlation Coefficient (MCC) of 0.74 in phase-I and 78.60% with a MCC of 0.44 in phase-II. On independent test data, this model also performs better with an overall accuracy of 76.58% and 74.97% in phase-I and phase-II, respectively. The similarity-based PSI-BLAST module shows very low performance with about 50% prediction

Identification of a nuclear localization signal in the retinitis pigmentosa-mutated RP26 protein, ceramide kinase-like protein

International Nuclear Information System (INIS)

Inagaki, Yuichi; Mitsutake, Susumu; Igarashi, Yasuyuki

2006-01-01

Retinitis pigmentosa (RP) is a genetically heterogeneous disease characterized by degeneration of the retina. A mutation in a new ceramide kinase (CERK) homologous gene, named CERK-like protein (CERKL), was found to cause autosomal recessive retinitis pigmentosa (RP26). Here, we show a point mutation of one of two putative nuclear localization signal (NLS) sequences inhibited the nuclear localization of the protein. Furthermore, the tetra-GFP-tagged NLS, which cannot passively enter the nucleus, was observed not only in the nucleus but also in the nucleolus. Our results provide First evidence of the active nuclear import of CERKL and suggest that the identified NLS might be responsible for nucleolar retention of the protein. As recent studies have shown other RP-related proteins are localized in the nucleus or the nucleolus, our identification of NLS in CERKL suggests that CERKL likely plays important roles for retinal functions in the nucleus and the nucleolus

Identification of ZASP, a novel protein associated to Zona occludens-2

Energy Technology Data Exchange (ETDEWEB)

Lechuga, Susana; Alarcon, Lourdes; Solano, Jesus [Department of Physiology, Biophysics and Neuroscience, Center for Research and Advanced Studies (Cinvestav), Mexico, D.F. 07360 (Mexico); Huerta, Miriam; Lopez-Bayghen, Esther [Department of Genetics and Molecular Biology, Center for Research and Advanced Studies (Cinvestav), Mexico, D.F. 07360 (Mexico); Gonzalez-Mariscal, Lorenza, E-mail: lorenza@fisio.cinvestav.mx [Department of Physiology, Biophysics and Neuroscience, Center for Research and Advanced Studies (Cinvestav), Mexico, D.F. 07360 (Mexico)

2010-11-15

With the aim of discovering new molecular interactions of the tight junction protein ZO-2, a two-hybrid screen was performed on a human kidney cDNA library using as bait the middle segment of ZO-2. Through this assay we identified a 24-kDa novel protein herein named ZASP for ZO-2 associated speckle protein. ZO-2/ZASP interaction further confirmed by pull down and immunoprecipitation experiments, requires the presence of the intact PDZ binding motif SQV of ZASP and the third PDZ domain of ZO-2. ZASP mRNA and protein are present in the kidney and in several epithelial cell lines. Endogenous ZASP is expressed primarily in nuclear speckles in co-localization with splicing factor SC-35. Nocodazole treatment and wash out reveals that ZASP disappears from the nucleus during mitosis in accordance with speckle disassembly during metaphase. ZASP amino acid sequence exhibits a canonical nuclear exportation signal and in agreement the protein exits the nucleus through a process mediated by exportin/CRM1. ZASP over-expression blocks the inhibitory activity of ZO-2 on cyclin D1 gene transcription and protein expression. The identification of ZASP helps to unfold the complex nuclear molecular arrays that form on ZO-2 scaffolds.

Identification of ZASP, a novel protein associated to Zona occludens-2.

Science.gov (United States)

Lechuga, Susana; Alarcón, Lourdes; Solano, Jesús; Huerta, Miriam; Lopez-Bayghen, Esther; González-Mariscal, Lorenza

2010-11-15

With the aim of discovering new molecular interactions of the tight junction protein ZO-2, a two-hybrid screen was performed on a human kidney cDNA library using as bait the middle segment of ZO-2. Through this assay we identified a 24-kDa novel protein herein named ZASP for ZO-2 associated speckle protein. ZO-2/ZASP interaction further confirmed by pull down and immunoprecipitation experiments, requires the presence of the intact PDZ binding motif SQV of ZASP and the third PDZ domain of ZO-2. ZASP mRNA and protein are present in the kidney and in several epithelial cell lines. Endogenous ZASP is expressed primarily in nuclear speckles in co-localization with splicing factor SC-35. Nocodazole treatment and wash out reveals that ZASP disappears from the nucleus during mitosis in accordance with speckle disassembly during metaphase. ZASP amino acid sequence exhibits a canonical nuclear exportation signal and in agreement the protein exits the nucleus through a process mediated by exportin/CRM1. ZASP over-expression blocks the inhibitory activity of ZO-2 on cyclin D1 gene transcription and protein expression. The identification of ZASP helps to unfold the complex nuclear molecular arrays that form on ZO-2 scaffolds. Copyright © 2010 Elsevier Inc. All rights reserved.

Identification of ZASP, a novel protein associated to Zona occludens-2

International Nuclear Information System (INIS)

Lechuga, Susana; Alarcon, Lourdes; Solano, Jesus; Huerta, Miriam; Lopez-Bayghen, Esther; Gonzalez-Mariscal, Lorenza

2010-01-01

With the aim of discovering new molecular interactions of the tight junction protein ZO-2, a two-hybrid screen was performed on a human kidney cDNA library using as bait the middle segment of ZO-2. Through this assay we identified a 24-kDa novel protein herein named ZASP for ZO-2 associated speckle protein. ZO-2/ZASP interaction further confirmed by pull down and immunoprecipitation experiments, requires the presence of the intact PDZ binding motif SQV of ZASP and the third PDZ domain of ZO-2. ZASP mRNA and protein are present in the kidney and in several epithelial cell lines. Endogenous ZASP is expressed primarily in nuclear speckles in co-localization with splicing factor SC-35. Nocodazole treatment and wash out reveals that ZASP disappears from the nucleus during mitosis in accordance with speckle disassembly during metaphase. ZASP amino acid sequence exhibits a canonical nuclear exportation signal and in agreement the protein exits the nucleus through a process mediated by exportin/CRM1. ZASP over-expression blocks the inhibitory activity of ZO-2 on cyclin D1 gene transcription and protein expression. The identification of ZASP helps to unfold the complex nuclear molecular arrays that form on ZO-2 scaffolds.

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry for fast and accurate identification of clinically relevant Aspergillus species.

Science.gov (United States)

Alanio, A; Beretti, J-L; Dauphin, B; Mellado, E; Quesne, G; Lacroix, C; Amara, A; Berche, P; Nassif, X; Bougnoux, M-E

2011-05-01

New Aspergillus species have recently been described with the use of multilocus sequencing in refractory cases of invasive aspergillosis. The classical phenotypic identification methods routinely used in clinical laboratories failed to identify them adequately. Some of these Aspergillus species have specific patterns of susceptibility to antifungal agents, and misidentification may lead to inappropriate therapy. We developed a matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS)-based strategy to adequately identify Aspergillus species to the species level. A database including the reference spectra of 28 clinically relevant species from seven Aspergillus sections (five common and 23 unusual species) was engineered. The profiles of young and mature colonies were analysed for each reference strain, and species-specific spectral fingerprints were identified. The performance of the database was then tested on 124 clinical and 16 environmental isolates previously characterized by partial sequencing of the β-tubulin and calmodulin genes. One hundred and thirty-eight isolates of 140 (98.6%) were correctly identified. Two atypical isolates could not be identified, but no isolate was misidentified (specificity: 100%). The database, including species-specific spectral fingerprints of young and mature colonies of the reference strains, allowed identification regardless of the maturity of the clinical isolate. These results indicate that MALDI-TOF MS is a powerful tool for rapid and accurate identification of both common and unusual species of Aspergillus. It can give better results than morphological identification in clinical laboratories. © 2010 The Authors. Clinical Microbiology and Infection © 2010 European Society of Clinical Microbiology and Infectious Diseases.

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.

Identification of a putative protein-profile associating with tamoxifen therapy-resistance in breast cancer

NARCIS (Netherlands)

A. Umar (Arzu); J.W.M. Martens (John); J.A. Foekens (John); L. Paša-Tolić (Ljiljana); H. Kang; A.M. Timmermans (Mieke); M.P. Look (Maxime); M.E. Meijer van Gelder (Marion); N. Jaitly (Navdeep); M.A. den Bakker (Michael)

2009-01-01

textabstractTamoxifen-resistance is a major cause of death in patients with recurrent breast cancer. Current clinical parameters can correctly predict therapy response in only half of the treated patients. Identification of proteins that associate with tamoxifen-resistance is a first step towards

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.

Identification of a 5-protein biomarker molecular signature for predicting Alzheimer's disease.

Directory of Open Access Journals (Sweden)

Martín Gómez Ravetti

Full Text Available BACKGROUND: Alzheimer's disease (AD is a progressive brain disease with a huge cost to human lives. The impact of the disease is also a growing concern for the governments of developing countries, in particular due to the increasingly high number of elderly citizens at risk. Alzheimer's is the most common form of dementia, a common term for memory loss and other cognitive impairments. There is no current cure for AD, but there are drug and non-drug based approaches for its treatment. In general the drug-treatments are directed at slowing the progression of symptoms. They have proved to be effective in a large group of patients but success is directly correlated with identifying the disease carriers at its early stages. This justifies the need for timely and accurate forms of diagnosis via molecular means. We report here a 5-protein biomarker molecular signature that achieves, on average, a 96% total accuracy in predicting clinical AD. The signature is composed of the abundances of IL-1alpha, IL-3, EGF, TNF-alpha and G-CSF. METHODOLOGY/PRINCIPAL FINDINGS: Our results are based on a recent molecular dataset that has attracted worldwide attention. Our paper illustrates that improved results can be obtained with the abundance of only five proteins. Our methodology consisted of the application of an integrative data analysis method. This four step process included: a abundance quantization, b feature selection, c literature analysis, d selection of a classifier algorithm which is independent of the feature selection process. These steps were performed without using any sample of the test datasets. For the first two steps, we used the application of Fayyad and Irani's discretization algorithm for selection and quantization, which in turn creates an instance of the (alpha-beta-k-Feature Set problem; a numerical solution of this problem led to the selection of only 10 proteins. CONCLUSIONS/SIGNIFICANCE: the previous study has provided an extremely

Bottom–up protein identifications from microliter quantities of individual human tear samples. Important steps towards clinical relevance.

Directory of Open Access Journals (Sweden)

Peter Raus

2015-12-01

With 375 confidently identified proteins in the healthy adult tear, the obtained results are comprehensive and in large agreement with previously published observations on pooled samples of multiple patients. We conclude that, to a limited extent, bottom–up tear protein identifications from individual patients may have clinical relevance.

Identification of Newly Synthesized Proteins by Echinococcus granulosus Protoscoleces upon Induction of Strobilation.

Directory of Open Access Journals (Sweden)

João Antonio Debarba

2015-09-01

Full Text Available The proteins responsible for the key molecular events leading to the structural changes between the developmental stages of Echinococcus granulosus remain unknown. In this work, azidohomoalanine (AHA-specific labeling was used to identify proteins expressed by E. granulosus protoscoleces (PSCs upon the induction of strobilar development.The in vitro incorporation of AHA with different tags into newly synthesized proteins (NSPs by PSCs was analyzed using SDS-PAGE and confocal microscopy. The LC-MS/MS analysis of AHA-labeled NSPs by PSCs undergoing strobilation allowed for the identification of 365 proteins, of which 75 were differentially expressed in comparison between the presence or absence of strobilation stimuli and 51 were expressed exclusively in either condition. These proteins were mainly involved in metabolic, regulatory and signaling processes.After the controlled-labeling of proteins during the induction of strobilar development, we identified modifications in protein expression. The changes in the metabolism and the activation of control and signaling pathways may be important for the correct parasite development and be target for further studies.

Decision peptide-driven: a free software tool for accurate protein quantification using gel electrophoresis and matrix assisted laser desorption ionization time of flight mass spectrometry.

Science.gov (United States)

Santos, Hugo M; Reboiro-Jato, Miguel; Glez-Peña, Daniel; Nunes-Miranda, J D; Fdez-Riverola, Florentino; Carvallo, R; Capelo, J L

2010-09-15

The decision peptide-driven tool implements a software application for assisting the user in a protocol for accurate protein quantification based on the following steps: (1) protein separation through gel electrophoresis; (2) in-gel protein digestion; (3) direct and inverse (18)O-labeling and (4) matrix assisted laser desorption ionization time of flight mass spectrometry, MALDI analysis. The DPD software compares the MALDI results of the direct and inverse (18)O-labeling experiments and quickly identifies those peptides with paralleled loses in different sets of a typical proteomic workflow. Those peptides are used for subsequent accurate protein quantification. The interpretation of the MALDI data from direct and inverse labeling experiments is time-consuming requiring a significant amount of time to do all comparisons manually. The DPD software shortens and simplifies the searching of the peptides that must be used for quantification from a week to just some minutes. To do so, it takes as input several MALDI spectra and aids the researcher in an automatic mode (i) to compare data from direct and inverse (18)O-labeling experiments, calculating the corresponding ratios to determine those peptides with paralleled losses throughout different sets of experiments; and (ii) allow to use those peptides as internal standards for subsequent accurate protein quantification using (18)O-labeling. In this work the DPD software is presented and explained with the quantification of protein carbonic anhydrase. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Accurate prediction of stability changes in protein mutants by combining machine learning with structure based computational mutagenesis.

Science.gov (United States)

Masso, Majid; Vaisman, Iosif I

2008-09-15

Accurate predictive models for the impact of single amino acid substitutions on protein stability provide insight into protein structure and function. Such models are also valuable for the design and engineering of new proteins. Previously described methods have utilized properties of protein sequence or structure to predict the free energy change of mutants due to thermal (DeltaDeltaG) and denaturant (DeltaDeltaG(H2O)) denaturations, as well as mutant thermal stability (DeltaT(m)), through the application of either computational energy-based approaches or machine learning techniques. However, accuracy associated with applying these methods separately is frequently far from optimal. We detail a computational mutagenesis technique based on a four-body, knowledge-based, statistical contact potential. For any mutation due to a single amino acid replacement in a protein, the method provides an empirical normalized measure of the ensuing environmental perturbation occurring at every residue position. A feature vector is generated for the mutant by considering perturbations at the mutated position and it's ordered six nearest neighbors in the 3-dimensional (3D) protein structure. These predictors of stability change are evaluated by applying machine learning tools to large training sets of mutants derived from diverse proteins that have been experimentally studied and described. Predictive models based on our combined approach are either comparable to, or in many cases significantly outperform, previously published results. A web server with supporting documentation is available at http://proteins.gmu.edu/automute.

Proteogenomic Analysis Greatly Expands the Identification of Proteins Related to Reproduction in the Apogamous Fern Dryopteris affinis ssp. affinis.

Science.gov (United States)

Grossmann, Jonas; Fernández, Helena; Chaubey, Pururawa M; Valdés, Ana E; Gagliardini, Valeria; Cañal, María J; Russo, Giancarlo; Grossniklaus, Ueli

2017-01-01

Performing proteomic studies on non-model organisms with little or no genomic information is still difficult. However, many specific processes and biochemical pathways occur only in species that are poorly characterized at the genomic level. For example, many plants can reproduce both sexually and asexually, the first one allowing the generation of new genotypes and the latter their fixation. Thus, both modes of reproduction are of great agronomic value. However, the molecular basis of asexual reproduction is not well understood in any plant. In ferns, it combines the production of unreduced spores (diplospory) and the formation of sporophytes from somatic cells (apogamy). To set the basis to study these processes, we performed transcriptomics by next-generation sequencing (NGS) and shotgun proteomics by tandem mass spectrometry in the apogamous fern D. affinis ssp. affinis . For protein identification we used the public viridiplantae database (VPDB) to identify orthologous proteins from other plant species and new transcriptomics data to generate a "species-specific transcriptome database" (SSTDB). In total 1,397 protein clusters with 5,865 unique peptide sequences were identified (13 decoy proteins out of 1,410, protFDR 0.93% on protein cluster level). We show that using the SSTDB for protein identification increases the number of identified peptides almost four times compared to using only the publically available VPDB. We identified homologs of proteins involved in reproduction of higher plants, including proteins with a potential role in apogamy. With the increasing availability of genomic data from non-model species, similar proteogenomics approaches will improve the sensitivity in protein identification for species only distantly related to models.

Efficient and accurate Greedy Search Methods for mining functional modules in protein interaction networks.

Science.gov (United States)

He, Jieyue; Li, Chaojun; Ye, Baoliu; Zhong, Wei

2012-06-25

Most computational algorithms mainly focus on detecting highly connected subgraphs in PPI networks as protein complexes but ignore their inherent organization. Furthermore, many of these algorithms are computationally expensive. However, recent analysis indicates that experimentally detected protein complexes generally contain Core/attachment structures. In this paper, a Greedy Search Method based on Core-Attachment structure (GSM-CA) is proposed. The GSM-CA method detects densely connected regions in large protein-protein interaction networks based on the edge weight and two criteria for determining core nodes and attachment nodes. The GSM-CA method improves the prediction accuracy compared to other similar module detection approaches, however it is computationally expensive. Many module detection approaches are based on the traditional hierarchical methods, which is also computationally inefficient because the hierarchical tree structure produced by these approaches cannot provide adequate information to identify whether a network belongs to a module structure or not. In order to speed up the computational process, the Greedy Search Method based on Fast Clustering (GSM-FC) is proposed in this work. The edge weight based GSM-FC method uses a greedy procedure to traverse all edges just once to separate the network into the suitable set of modules. The proposed methods are applied to the protein interaction network of S. cerevisiae. Experimental results indicate that many significant functional modules are detected, most of which match the known complexes. Results also demonstrate that the GSM-FC algorithm is faster and more accurate as compared to other competing algorithms. Based on the new edge weight definition, the proposed algorithm takes advantages of the greedy search procedure to separate the network into the suitable set of modules. Experimental analysis shows that the identified modules are statistically significant. The algorithm can reduce the

A Proof of Concept to Bridge the Gap between Mass Spectrometry Imaging, Protein Identification and Relative Quantitation: MSI~LC-MS/MS-LF

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Laëtitia Théron

2016-10-01

Full Text Available Mass spectrometry imaging (MSI is a powerful tool to visualize the spatial distribution of molecules on a tissue section. The main limitation of MALDI-MSI of proteins is the lack of direct identification. Therefore, this study focuses on a MSI~LC-MS/MS-LF workflow to link the results from MALDI-MSI with potential peak identification and label-free quantitation, using only one tissue section. At first, we studied the impact of matrix deposition and laser ablation on protein extraction from the tissue section. Then, we did a back-correlation of the m/z of the proteins detected by MALDI-MSI to those identified by label-free quantitation. This allowed us to compare the label-free quantitation of proteins obtained in LC-MS/MS with the peak intensities observed in MALDI-MSI. We managed to link identification to nine peaks observed by MALDI-MSI. The results showed that the MSI~LC-MS/MS-LF workflow (i allowed us to study a representative muscle proteome compared to a classical bottom-up workflow; and (ii was sparsely impacted by matrix deposition and laser ablation. This workflow, performed as a proof-of-concept, suggests that a single tissue section can be used to perform MALDI-MSI and protein extraction, identification, and relative quantitation.

Exploring the relationship between sequence similarity and accurate phylogenetic trees.

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Cantarel, Brandi L; Morrison, Hilary G; Pearson, William

2006-11-01

We have characterized the relationship between accurate phylogenetic reconstruction and sequence similarity, testing whether high levels of sequence similarity can consistently produce accurate evolutionary trees. We generated protein families with known phylogenies using a modified version of the PAML/EVOLVER program that produces insertions and deletions as well as substitutions. Protein families were evolved over a range of 100-400 point accepted mutations; at these distances 63% of the families shared significant sequence similarity. Protein families were evolved using balanced and unbalanced trees, with ancient or recent radiations. In families sharing statistically significant similarity, about 60% of multiple sequence alignments were 95% identical to true alignments. To compare recovered topologies with true topologies, we used a score that reflects the fraction of clades that were correctly clustered. As expected, the accuracy of the phylogenies was greatest in the least divergent families. About 88% of phylogenies clustered over 80% of clades in families that shared significant sequence similarity, using Bayesian, parsimony, distance, and maximum likelihood methods. However, for protein families with short ancient branches (ancient radiation), only 30% of the most divergent (but statistically significant) families produced accurate phylogenies, and only about 70% of the second most highly conserved families, with median expectation values better than 10(-60), produced accurate trees. These values represent upper bounds on expected tree accuracy for sequences with a simple divergence history; proteins from 700 Giardia families, with a similar range of sequence similarities but considerably more gaps, produced much less accurate trees. For our simulated insertions and deletions, correct multiple sequence alignments did not perform much better than those produced by T-COFFEE, and including sequences with expressed sequence tag-like sequencing errors did not

Accurate, safe, and rapid method of intraoperative tumor identification for totally laparoscopic distal gastrectomy: injection of mixed fluid of sodium hyaluronate and patent blue.

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Nakagawa, Masatoshi; Ehara, Kazuhisa; Ueno, Masaki; Tanaka, Tsuyoshi; Kaida, Sachiko; Udagawa, Harushi

2014-04-01

In totally laparoscopic distal gastrectomy, determining the resection line with safe proximal margins is often difficult, particularly for tumors located in a relatively upper area. This is because, in contrast to open surgery, identifying lesions by palpating or opening the stomach is essentially impossible. This study introduces a useful method of tumor identification that is accurate, safe, and rapid. On the operation day, after inducing general anesthesia, a mixture of sodium hyaluronate and patent blue is injected into the submucosal layer of the proximal margin. When resecting stomach, all marker spots should be on the resected side. In all cases, the proximal margin is examined histologically by using frozen sections during the operation. From October 2009 to September 2011, a prospective study that evaluated this method was performed. A total of 34 patients who underwent totally laparoscopic distal gastrectomy were enrolled in this study. Approximately 5 min was required to complete the procedure. Proximal margins were negative in all cases, and the mean ± standard deviation length of the proximal margin was 23.5 ± 12.8 mm. No side effects, such as allergy, were encountered. As a method of tumor identification for totally laparoscopic distal gastrectomy, this procedure appears accurate, safe, and rapid.

A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information.

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Yi, Hai-Cheng; You, Zhu-Hong; Huang, De-Shuang; Li, Xiao; Jiang, Tong-Hai; Li, Li-Ping

2018-06-01

The interactions between non-coding RNAs (ncRNAs) and proteins play an important role in many biological processes, and their biological functions are primarily achieved by binding with a variety of proteins. High-throughput biological techniques are used to identify protein molecules bound with specific ncRNA, but they are usually expensive and time consuming. Deep learning provides a powerful solution to computationally predict RNA-protein interactions. In this work, we propose the RPI-SAN model by using the deep-learning stacked auto-encoder network to mine the hidden high-level features from RNA and protein sequences and feed them into a random forest (RF) model to predict ncRNA binding proteins. Stacked assembling is further used to improve the accuracy of the proposed method. Four benchmark datasets, including RPI2241, RPI488, RPI1807, and NPInter v2.0, were employed for the unbiased evaluation of five established prediction tools: RPI-Pred, IPMiner, RPISeq-RF, lncPro, and RPI-SAN. The experimental results show that our RPI-SAN model achieves much better performance than other methods, with accuracies of 90.77%, 89.7%, 96.1%, and 99.33%, respectively. It is anticipated that RPI-SAN can be used as an effective computational tool for future biomedical researches and can accurately predict the potential ncRNA-protein interacted pairs, which provides reliable guidance for biological research. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Accurate spectroscopic characterization of oxirane: A valuable route to its identification in Titan's atmosphere and the assignment of unidentified infrared bands

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Puzzarini, Cristina [Dipartimento di Chimica " Giacomo Ciamician," Università di Bologna, Via Selmi 2, I-40126 Bologna (Italy); Biczysko, Malgorzata; Bloino, Julien; Barone, Vincenzo, E-mail: cristina.puzzarini@unibo.it [Scuola Normale Superiore, Piazza dei Cavalieri 7, I-56126 Pisa (Italy)

2014-04-20

In an effort to provide an accurate spectroscopic characterization of oxirane, state-of-the-art computational methods and approaches have been employed to determine highly accurate fundamental vibrational frequencies and rotational parameters. Available experimental data were used to assess the reliability of our computations, and an accuracy on average of 10 cm{sup –1} for fundamental transitions as well as overtones and combination bands has been pointed out. Moving to rotational spectroscopy, relative discrepancies of 0.1%, 2%-3%, and 3%-4% were observed for rotational, quartic, and sextic centrifugal-distortion constants, respectively. We are therefore confident that the highly accurate spectroscopic data provided herein can be useful for identification of oxirane in Titan's atmosphere and the assignment of unidentified infrared bands. Since oxirane was already observed in the interstellar medium and some astronomical objects are characterized by very high D/H ratios, we also considered the accurate determination of the spectroscopic parameters for the mono-deuterated species, oxirane-d1. For the latter, an empirical scaling procedure allowed us to improve our computed data and to provide predictions for rotational transitions with a relative accuracy of about 0.02% (i.e., an uncertainty of about 40 MHz for a transition lying at 200 GHz).

A comparative proteomics method for multiple samples based on a 18O-reference strategy and a quantitation and identification-decoupled strategy.

Science.gov (United States)

Wang, Hongbin; Zhang, Yongqian; Gui, Shuqi; Zhang, Yong; Lu, Fuping; Deng, Yulin

2017-08-15

Comparisons across large numbers of samples are frequently necessary in quantitative proteomics. Many quantitative methods used in proteomics are based on stable isotope labeling, but most of these are only useful for comparing two samples. For up to eight samples, the iTRAQ labeling technique can be used. For greater numbers of samples, the label-free method has been used, but this method was criticized for low reproducibility and accuracy. An ingenious strategy has been introduced, comparing each sample against a 18 O-labeled reference sample that was created by pooling equal amounts of all samples. However, it is necessary to use proportion-known protein mixtures to investigate and evaluate this new strategy. Another problem for comparative proteomics of multiple samples is the poor coincidence and reproducibility in protein identification results across samples. In present study, a method combining 18 O-reference strategy and a quantitation and identification-decoupled strategy was investigated with proportion-known protein mixtures. The results obviously demonstrated that the 18 O-reference strategy had greater accuracy and reliability than other previously used comparison methods based on transferring comparison or label-free strategies. By the decoupling strategy, the quantification data acquired by LC-MS and the identification data acquired by LC-MS/MS are matched and correlated to identify differential expressed proteins, according to retention time and accurate mass. This strategy made protein identification possible for all samples using a single pooled sample, and therefore gave a good reproducibility in protein identification across multiple samples, and allowed for optimizing peptide identification separately so as to identify more proteins. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification and quantification of major maillard cross-links in human serum albumin and lens protein. Evidence for glucosepane as the dominant compound.

Science.gov (United States)

Biemel, Klaus M; Friedl, D Alexander; Lederer, Markus O

2002-07-12

Glycation reactions leading to protein modifications (advanced glycation end products) contribute to various pathologies associated with the general aging process and long term complications of diabetes. However, only few relevant compounds have so far been detected in vivo. We now report on the first unequivocal identification of the lysine-arginine cross-links glucosepane 5, DOGDIC 6, MODIC 7, and GODIC 8 in human material. For their accurate quantification by coupled liquid chromatography-electrospray ionization mass spectrometry, (13)C-labeled reference compounds were synthesized independently. Compounds 5-8 are formed via the alpha-dicarbonyl compounds N(6)-(2,3-dihydroxy-5,6-dioxohexyl)-l-lysinate (1a,b), 3-deoxyglucosone (), methylglyoxal (), and glyoxal (), respectively. The protein-bound dideoxyosone 1a,b seems to be of prime significance for cross-linking because it presumably is not detoxified by mammalian enzymes as readily as 2-4. Hence, the follow-up product glucosepane 5 was found to be the dominant compound. Up to 42.3 pmol of 5/mg of protein was identified in human serum albumin of diabetics; the level of 5 correlates markedly with the glycated hemoglobin HbA(1c). In the water-insoluble fraction of lens proteins from normoglycemics, concentration of 5 ranges between 132.3 and 241.7 pmol/mg. The advanced glycoxidation end product GODIC 8 is elevated significantly in brunescent lenses, indicating enhanced oxidative stress in this material. Compounds 5-8 thus appear predestined as markers for pathophysiological processes.

Accurate Quantification of Cardiovascular Biomarkers in Serum Using Protein Standard Absolute Quantification (PSAQ™) and Selected Reaction Monitoring*

Science.gov (United States)

Huillet, Céline; Adrait, Annie; Lebert, Dorothée; Picard, Guillaume; Trauchessec, Mathieu; Louwagie, Mathilde; Dupuis, Alain; Hittinger, Luc; Ghaleh, Bijan; Le Corvoisier, Philippe; Jaquinod, Michel; Garin, Jérôme; Bruley, Christophe; Brun, Virginie

2012-01-01

Development of new biomarkers needs to be significantly accelerated to improve diagnostic, prognostic, and toxicity monitoring as well as therapeutic follow-up. Biomarker evaluation is the main bottleneck in this development process. Selected Reaction Monitoring (SRM) combined with stable isotope dilution has emerged as a promising option to speed this step, particularly because of its multiplexing capacities. However, analytical variabilities because of upstream sample handling or incomplete trypsin digestion still need to be resolved. In 2007, we developed the PSAQ™ method (Protein Standard Absolute Quantification), which uses full-length isotope-labeled protein standards to quantify target proteins. In the present study we used clinically validated cardiovascular biomarkers (LDH-B, CKMB, myoglobin, and troponin I) to demonstrate that the combination of PSAQ and SRM (PSAQ-SRM) allows highly accurate biomarker quantification in serum samples. A multiplex PSAQ-SRM assay was used to quantify these biomarkers in clinical samples from myocardial infarction patients. Good correlation between PSAQ-SRM and ELISA assay results was found and demonstrated the consistency between these analytical approaches. Thus, PSAQ-SRM has the capacity to improve both accuracy and reproducibility in protein analysis. This will be a major contribution to efficient biomarker development strategies. PMID:22080464

Establishment of a protein frequency library and its application in the reliable identification of specific protein interaction partners.

Science.gov (United States)

Boulon, Séverine; Ahmad, Yasmeen; Trinkle-Mulcahy, Laura; Verheggen, Céline; Cobley, Andy; Gregor, Peter; Bertrand, Edouard; Whitehorn, Mark; Lamond, Angus I

2010-05-01

The reliable identification of protein interaction partners and how such interactions change in response to physiological or pathological perturbations is a key goal in most areas of cell biology. Stable isotope labeling with amino acids in cell culture (SILAC)-based mass spectrometry has been shown to provide a powerful strategy for characterizing protein complexes and identifying specific interactions. Here, we show how SILAC can be combined with computational methods drawn from the business intelligence field for multidimensional data analysis to improve the discrimination between specific and nonspecific protein associations and to analyze dynamic protein complexes. A strategy is shown for developing a protein frequency library (PFL) that improves on previous use of static "bead proteomes." The PFL annotates the frequency of detection in co-immunoprecipitation and pulldown experiments for all proteins in the human proteome. It can provide a flexible and objective filter for discriminating between contaminants and specifically bound proteins and can be used to normalize data values and facilitate comparisons between data obtained in separate experiments. The PFL is a dynamic tool that can be filtered for specific experimental parameters to generate a customized library. It will be continuously updated as data from each new experiment are added to the library, thereby progressively enhancing its utility. The application of the PFL to pulldown experiments is especially helpful in identifying either lower abundance or less tightly bound specific components of protein complexes that are otherwise lost among the large, nonspecific background.

Systematic analysis of protein turnover in primary cells.

Science.gov (United States)

Mathieson, Toby; Franken, Holger; Kosinski, Jan; Kurzawa, Nils; Zinn, Nico; Sweetman, Gavain; Poeckel, Daniel; Ratnu, Vikram S; Schramm, Maike; Becher, Isabelle; Steidel, Michael; Noh, Kyung-Min; Bergamini, Giovanna; Beck, Martin; Bantscheff, Marcus; Savitski, Mikhail M

2018-02-15

A better understanding of proteostasis in health and disease requires robust methods to determine protein half-lives. Here we improve the precision and accuracy of peptide ion intensity-based quantification, enabling more accurate protein turnover determination in non-dividing cells by dynamic SILAC-based proteomics. This approach allows exact determination of protein half-lives ranging from 10 to >1000 h. We identified 4000-6000 proteins in several non-dividing cell types, corresponding to 9699 unique protein identifications over the entire data set. We observed similar protein half-lives in B-cells, natural killer cells and monocytes, whereas hepatocytes and mouse embryonic neurons show substantial differences. Our data set extends and statistically validates the previous observation that subunits of protein complexes tend to have coherent turnover. Moreover, analysis of different proteasome and nuclear pore complex assemblies suggests that their turnover rate is architecture dependent. These results illustrate that our approach allows investigating protein turnover and its implications in various cell types.

Binomial probability distribution model-based protein identification algorithm for tandem mass spectrometry utilizing peak intensity information.

Science.gov (United States)

Xiao, Chuan-Le; Chen, Xiao-Zhou; Du, Yang-Li; Sun, Xuesong; Zhang, Gong; He, Qing-Yu

2013-01-04

Mass spectrometry has become one of the most important technologies in proteomic analysis. Tandem mass spectrometry (LC-MS/MS) is a major tool for the analysis of peptide mixtures from protein samples. The key step of MS data processing is the identification of peptides from experimental spectra by searching public sequence databases. Although a number of algorithms to identify peptides from MS/MS data have been already proposed, e.g. Sequest, OMSSA, X!Tandem, Mascot, etc., they are mainly based on statistical models considering only peak-matches between experimental and theoretical spectra, but not peak intensity information. Moreover, different algorithms gave different results from the same MS data, implying their probable incompleteness and questionable reproducibility. We developed a novel peptide identification algorithm, ProVerB, based on a binomial probability distribution model of protein tandem mass spectrometry combined with a new scoring function, making full use of peak intensity information and, thus, enhancing the ability of identification. Compared with Mascot, Sequest, and SQID, ProVerB identified significantly more peptides from LC-MS/MS data sets than the current algorithms at 1% False Discovery Rate (FDR) and provided more confident peptide identifications. ProVerB is also compatible with various platforms and experimental data sets, showing its robustness and versatility. The open-source program ProVerB is available at http://bioinformatics.jnu.edu.cn/software/proverb/ .

An approach to large scale identification of non-obvious structural similarities between proteins

Science.gov (United States)

Cherkasov, Artem; Jones, Steven JM

2004-01-01

Background A new sequence independent bioinformatics approach allowing genome-wide search for proteins with similar three dimensional structures has been developed. By utilizing the numerical output of the sequence threading it establishes putative non-obvious structural similarities between proteins. When applied to the testing set of proteins with known three dimensional structures the developed approach was able to recognize structurally similar proteins with high accuracy. Results The method has been developed to identify pathogenic proteins with low sequence identity and high structural similarity to host analogues. Such protein structure relationships would be hypothesized to arise through convergent evolution or through ancient horizontal gene transfer events, now undetectable using current sequence alignment techniques. The pathogen proteins, which could mimic or interfere with host activities, would represent candidate virulence factors. The developed approach utilizes the numerical outputs from the sequence-structure threading. It identifies the potential structural similarity between a pair of proteins by correlating the threading scores of the corresponding two primary sequences against the library of the standard folds. This approach allowed up to 64% sensitivity and 99.9% specificity in distinguishing protein pairs with high structural similarity. Conclusion Preliminary results obtained by comparison of the genomes of Homo sapiens and several strains of Chlamydia trachomatis have demonstrated the potential usefulness of the method in the identification of bacterial proteins with known or potential roles in virulence. PMID:15147578

An approach to large scale identification of non-obvious structural similarities between proteins

Directory of Open Access Journals (Sweden)

Cherkasov Artem

2004-05-01

Full Text Available Abstract Background A new sequence independent bioinformatics approach allowing genome-wide search for proteins with similar three dimensional structures has been developed. By utilizing the numerical output of the sequence threading it establishes putative non-obvious structural similarities between proteins. When applied to the testing set of proteins with known three dimensional structures the developed approach was able to recognize structurally similar proteins with high accuracy. Results The method has been developed to identify pathogenic proteins with low sequence identity and high structural similarity to host analogues. Such protein structure relationships would be hypothesized to arise through convergent evolution or through ancient horizontal gene transfer events, now undetectable using current sequence alignment techniques. The pathogen proteins, which could mimic or interfere with host activities, would represent candidate virulence factors. The developed approach utilizes the numerical outputs from the sequence-structure threading. It identifies the potential structural similarity between a pair of proteins by correlating the threading scores of the corresponding two primary sequences against the library of the standard folds. This approach allowed up to 64% sensitivity and 99.9% specificity in distinguishing protein pairs with high structural similarity. Conclusion Preliminary results obtained by comparison of the genomes of Homo sapiens and several strains of Chlamydia trachomatis have demonstrated the potential usefulness of the method in the identification of bacterial proteins with known or potential roles in virulence.

Fast and accurate non-sequential protein structure alignment using a new asymmetric linear sum assignment heuristic.

Science.gov (United States)

Brown, Peter; Pullan, Wayne; Yang, Yuedong; Zhou, Yaoqi

2016-02-01

The three dimensional tertiary structure of a protein at near atomic level resolution provides insight alluding to its function and evolution. As protein structure decides its functionality, similarity in structure usually implies similarity in function. As such, structure alignment techniques are often useful in the classifications of protein function. Given the rapidly growing rate of new, experimentally determined structures being made available from repositories such as the Protein Data Bank, fast and accurate computational structure comparison tools are required. This paper presents SPalignNS, a non-sequential protein structure alignment tool using a novel asymmetrical greedy search technique. The performance of SPalignNS was evaluated against existing sequential and non-sequential structure alignment methods by performing trials with commonly used datasets. These benchmark datasets used to gauge alignment accuracy include (i) 9538 pairwise alignments implied by the HOMSTRAD database of homologous proteins; (ii) a subset of 64 difficult alignments from set (i) that have low structure similarity; (iii) 199 pairwise alignments of proteins with similar structure but different topology; and (iv) a subset of 20 pairwise alignments from the RIPC set. SPalignNS is shown to achieve greater alignment accuracy (lower or comparable root-mean squared distance with increased structure overlap coverage) for all datasets, and the highest agreement with reference alignments from the challenging dataset (iv) above, when compared with both sequentially constrained alignments and other non-sequential alignments. SPalignNS was implemented in C++. The source code, binary executable, and a web server version is freely available at: http://sparks-lab.org yaoqi.zhou@griffith.edu.au. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Rapid identification of fluorochrome modification sites in proteins by LC ESI-Q-TOF mass spectrometry.

Science.gov (United States)

Manikwar, Prakash; Zimmerman, Tahl; Blanco, Francisco J; Williams, Todd D; Siahaan, Teruna J

2011-07-20

Conjugation of either a fluorescent dye or a drug molecule to the ε-amino groups of lysine residues of proteins has many applications in biology and medicine. However, this type of conjugation produces a heterogeneous population of protein conjugates. Because conjugation of fluorochrome or drug molecule to a protein may have deleterious effects on protein function, the identification of conjugation sites is necessary. Unfortunately, the identification process can be time-consuming and laborious; therefore, there is a need to develop a rapid and reliable way to determine the conjugation sites of the fluorescent label or drug molecule. In this study, the sites of conjugation of fluorescein-5'-isothiocyanate and rhodamine-B-isothiocyanate to free amino groups on the insert-domain (I-domain) protein derived from the α-subunit of lymphocyte function-associated antigen-1 (LFA-1) were determined by electrospray ionization quadrupole time-of-flight mass spectrometry (ESI-Q-TOF MS) along with peptide mapping using trypsin digestion. A reporter fragment of the fluorochrome moiety that is generated in the collision cell of the Q-TOF without explicit MS/MS precursor selection was used to identify the conjugation site. Selected ion plots of the reporter ion readily mark modified peptides in chromatograms of the complex digest. Interrogation of theses spectra reveals a neutral loss/precursor pair that identifies the modified peptide. The results show that one to seven fluorescein molecules or one to four rhodamine molecules were attached to the lysine residue(s) of the I-domain protein. No modifications were found in the metal ion-dependent adhesion site (MIDAS), which is an important binding region of the I-domain.

Serum protein profile at remission can accurately assess therapeutic outcomes and survival for serous ovarian cancer.

Directory of Open Access Journals (Sweden)

Jinhua Wang

Full Text Available BACKGROUND: Biomarkers play critical roles in early detection, diagnosis and monitoring of therapeutic outcome and recurrence of cancer. Previous biomarker research on ovarian cancer (OC has mostly focused on the discovery and validation of diagnostic biomarkers. The primary purpose of this study is to identify serum biomarkers for prognosis and therapeutic outcomes of ovarian cancer. EXPERIMENTAL DESIGN: Forty serum proteins were analyzed in 70 serum samples from healthy controls (HC and 101 serum samples from serous OC patients at three different disease phases: post diagnosis (PD, remission (RM and recurrence (RC. The utility of serum proteins as OC biomarkers was evaluated using a variety of statistical methods including survival analysis. RESULTS: Ten serum proteins (PDGF-AB/BB, PDGF-AA, CRP, sFas, CA125, SAA, sTNFRII, sIL-6R, IGFBP6 and MDC have individually good area-under-the-curve (AUC values (AUC = 0.69-0.86 and more than 10 three-marker combinations have excellent AUC values (0.91-0.93 in distinguishing active cancer samples (PD & RC from HC. The mean serum protein levels for RM samples are usually intermediate between HC and OC patients with active cancer (PD & RC. Most importantly, five proteins (sICAM1, RANTES, sgp130, sTNFR-II and sVCAM1 measured at remission can classify, individually and in combination, serous OC patients into two subsets with significantly different overall survival (best HR = 17, p<10(-3. CONCLUSION: We identified five serum proteins which, when measured at remission, can accurately predict the overall survival of serous OC patients, suggesting that they may be useful for monitoring the therapeutic outcomes for ovarian cancer.

Top-Down and Bottom-Up Identification of Proteins by Liquid Extraction Surface Analysis Mass Spectrometry of Healthy and Diseased Human Liver Tissue

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Sarsby, Joscelyn; Martin, Nicholas J.; Lalor, Patricia F.; Bunch, Josephine; Cooper, Helen J.

2014-09-01

Liquid extraction surface analysis mass spectrometry (LESA MS) has the potential to become a useful tool in the spatially-resolved profiling of proteins in substrates. Here, the approach has been applied to the analysis of thin tissue sections from human liver. The aim was to determine whether LESA MS was a suitable approach for the detection of protein biomarkers of nonalcoholic liver disease (nonalcoholic steatohepatitis, NASH), with a view to the eventual development of LESA MS for imaging NASH pathology. Two approaches were considered. In the first, endogenous proteins were extracted from liver tissue sections by LESA, subjected to automated trypsin digestion, and the resulting peptide mixture was analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS) (bottom-up approach). In the second (top-down approach), endogenous proteins were extracted by LESA, and analyzed intact. Selected protein ions were subjected to collision-induced dissociation (CID) and/or electron transfer dissociation (ETD) mass spectrometry. The bottom-up approach resulted in the identification of over 500 proteins; however identification of key protein biomarkers, liver fatty acid binding protein (FABP1), and its variant (Thr→Ala, position 94), was unreliable and irreproducible. Top-down LESA MS analysis of healthy and diseased liver tissue revealed peaks corresponding to multiple (~15-25) proteins. MS/MS of four of these proteins identified them as FABP1, its variant, α-hemoglobin, and 10 kDa heat shock protein. The reliable identification of FABP1 and its variant by top-down LESA MS suggests that the approach may be suitable for imaging NASH pathology in sections from liver biopsies.

Analysis of Proteins, Protein Complexes, and Organellar Proteomes Using Sheathless Capillary Zone Electrophoresis - Native Mass Spectrometry

Science.gov (United States)

Belov, Arseniy M.; Viner, Rosa; Santos, Marcia R.; Horn, David M.; Bern, Marshall; Karger, Barry L.; Ivanov, Alexander R.

2017-12-01

Native mass spectrometry (MS) is a rapidly advancing field in the analysis of proteins, protein complexes, and macromolecular species of various types. The majority of native MS experiments reported to-date has been conducted using direct infusion of purified analytes into a mass spectrometer. In this study, capillary zone electrophoresis (CZE) was coupled online to Orbitrap mass spectrometers using a commercial sheathless interface to enable high-performance separation, identification, and structural characterization of limited amounts of purified proteins and protein complexes, the latter with preserved non-covalent associations under native conditions. The performance of both bare-fused silica and polyacrylamide-coated capillaries was assessed using mixtures of protein standards known to form non-covalent protein-protein and protein-ligand complexes. High-efficiency separation of native complexes is demonstrated using both capillary types, while the polyacrylamide neutral-coated capillary showed better reproducibility and higher efficiency for more complex samples. The platform was then evaluated for the determination of monoclonal antibody aggregation and for analysis of proteomes of limited complexity using a ribosomal isolate from E. coli. Native CZE-MS, using accurate single stage and tandem-MS measurements, enabled identification of proteoforms and non-covalent complexes at femtomole levels. This study demonstrates that native CZE-MS can serve as an orthogonal and complementary technique to conventional native MS methodologies with the advantages of low sample consumption, minimal sample processing and losses, and high throughput and sensitivity. This study presents a novel platform for analysis of ribosomes and other macromolecular complexes and organelles, with the potential for discovery of novel structural features defining cellular phenotypes (e.g., specialized ribosomes). [Figure not available: see fulltext.

Identification of a tripartite import signal in the Ewing Sarcoma protein (EWS)

International Nuclear Information System (INIS)

Shaw, Debra J.; Morse, Robert; Todd, Adrian G.; Eggleton, Paul; Lorson, Christian L.; Young, Philip J.

2009-01-01

The Ewing Sarcoma (EWS) protein is a ubiquitously expressed RNA processing factor that localises predominantly to the nucleus. However, the mechanism through which EWS enters the nucleus remains unclear, with differing reports identifying three separate import signals within the EWS protein. Here we have utilized a panel of truncated EWS proteins to clarify the reported nuclear localisation signals. We describe three C-terminal domains that are important for efficient EWS nuclear localization: (1) the third RGG-motif; (2) the last 10 amino acids (known as the PY-import motif); and (3) the zinc-finger motif. Although these three domains are involved in nuclear import, they are not independently capable of driving the efficient import of a GFP-moiety. However, collectively they form a complex tripartite signal that efficiently drives GFP-import into the nucleus. This study helps clarify the EWS import signal, and the identification of the involvement of both the RGG- and zinc-finger motifs has wide reaching implications.

Identification of a tripartite import signal in the Ewing Sarcoma protein (EWS)

Energy Technology Data Exchange (ETDEWEB)

Shaw, Debra J.; Morse, Robert; Todd, Adrian G. [Clinical Neurobiology, IBCS, Peninsula College of Medicine and Dentistry, Exeter EX1 2LU (United Kingdom); Eggleton, Paul [Inflammation and Musculoskeletal Disease, IBCS, Peninsula College of Medicine and Dentistry, Exeter EX1 2LU (United Kingdom); MRC Immunochemistry Unit, University of Oxford, Oxford OX1 3QU (United Kingdom); Lorson, Christian L. [Department of Veterinary Pathobiology, Bond Life Sciences Center, 1201 Rollins Road, University of Missouri, Columbia, MO 65211 (United States); Young, Philip J., E-mail: philip.young@pms.ac.uk [Clinical Neurobiology, IBCS, Peninsula College of Medicine and Dentistry, Exeter EX1 2LU (United Kingdom)

2009-12-25

The Ewing Sarcoma (EWS) protein is a ubiquitously expressed RNA processing factor that localises predominantly to the nucleus. However, the mechanism through which EWS enters the nucleus remains unclear, with differing reports identifying three separate import signals within the EWS protein. Here we have utilized a panel of truncated EWS proteins to clarify the reported nuclear localisation signals. We describe three C-terminal domains that are important for efficient EWS nuclear localization: (1) the third RGG-motif; (2) the last 10 amino acids (known as the PY-import motif); and (3) the zinc-finger motif. Although these three domains are involved in nuclear import, they are not independently capable of driving the efficient import of a GFP-moiety. However, collectively they form a complex tripartite signal that efficiently drives GFP-import into the nucleus. This study helps clarify the EWS import signal, and the identification of the involvement of both the RGG- and zinc-finger motifs has wide reaching implications.

Identification of novel type 1 diabetes candidate genes by integrating genome-wide association data, protein-protein interactions, and human pancreatic islet gene expression

DEFF Research Database (Denmark)

Bergholdt, Regine; Brorsson, Caroline; Palleja, Albert

2012-01-01

Genome-wide association studies (GWAS) have heralded a new era in susceptibility locus discovery in complex diseases. For type 1 diabetes, >40 susceptibility loci have been discovered. However, GWAS do not inevitably lead to identification of the gene or genes in a given locus associated with dis......-cells. Our results provide novel insight to the mechanisms behind type 1 diabetes pathogenesis and, thus, may provide the basis for the design of novel treatment strategies.......Genome-wide association studies (GWAS) have heralded a new era in susceptibility locus discovery in complex diseases. For type 1 diabetes, >40 susceptibility loci have been discovered. However, GWAS do not inevitably lead to identification of the gene or genes in a given locus associated...... with disease, and they do not typically inform the broader context in which the disease genes operate. Here, we integrated type 1 diabetes GWAS data with protein-protein interactions to construct biological networks of relevance for disease. A total of 17 networks were identified. To prioritize...

Identification of a multi-protein reductive dehalogenase complex in Dehalococcoides mccartyi strain CBDB1 suggests a protein-dependent respiratory electron transport chain obviating quinone involvement

DEFF Research Database (Denmark)

Kublik, Anja; Deobald, Darja; Hartwig, Stefanie

2016-01-01

electrophoresis (BN-PAGE), gel filtration and ultrafiltration an active dehalogenating protein complex with a molecular mass of 250–270 kDa was identified. The active subunit of reductive dehalogenase (RdhA) colocalised with a complex iron-sulfur molybdoenzyme (CISM) subunit (CbdbA195) and an iron-sulfur cluster...... of the dehalogenating complex prior to membrane solubilisation. Taken together, the identification of the respiratory dehalogenase protein complex and the absence of indications for quinone participation in the respiration suggest a quinone-independent protein-based respiratory electron transfer chain in D. mccartyi....

Identification of compounds with binding affinity to proteins via magnetization transfer from bulk water

International Nuclear Information System (INIS)

Dalvit, Claudio; Pevarello, Paolo; Tato, Marco; Veronesi, Marina; Vulpetti, Anna; Sundstroem, Michael

2000-01-01

A powerful screening by NMR methodology (WaterLOGSY), based on transfer of magnetization from bulk water, for the identification of compounds that interact with target biomolecules (proteins, RNA and DNA fragments) is described. The method exploits efficiently the large reservoir of H 2 O magnetization. The high sensitivity of the technique reduces the amount of biomolecule and ligands needed for the screening, which constitutes an important requirement for high throughput screening by NMR of large libraries of compounds. Application of the method to a compound mixture against the cyclin-dependent kinase 2 (cdk2) protein is presented

Chromatin Immunoprecipitation Assay for the Identification of Arabidopsis Protein-DNA Interactions In Vivo.

Science.gov (United States)

Komar, Dorota N; Mouriz, Alfonso; Jarillo, José A; Piñeiro, Manuel

2016-01-14

Intricate gene regulatory networks orchestrate biological processes and developmental transitions in plants. Selective transcriptional activation and silencing of genes mediate the response of plants to environmental signals and developmental cues. Therefore, insights into the mechanisms that control plant gene expression are essential to gain a deep understanding of how biological processes are regulated in plants. The chromatin immunoprecipitation (ChIP) technique described here is a procedure to identify the DNA-binding sites of proteins in genes or genomic regions of the model species Arabidopsis thaliana. The interactions with DNA of proteins of interest such as transcription factors, chromatin proteins or posttranslationally modified versions of histones can be efficiently analyzed with the ChIP protocol. This method is based on the fixation of protein-DNA interactions in vivo, random fragmentation of chromatin, immunoprecipitation of protein-DNA complexes with specific antibodies, and quantification of the DNA associated with the protein of interest by PCR techniques. The use of this methodology in Arabidopsis has contributed significantly to unveil transcriptional regulatory mechanisms that control a variety of plant biological processes. This approach allowed the identification of the binding sites of the Arabidopsis chromatin protein EBS to regulatory regions of the master gene of flowering FT. The impact of this protein in the accumulation of particular histone marks in the genomic region of FT was also revealed through ChIP analysis.

Decision tree for accurate infection timing in individuals newly diagnosed with HIV-1 infection.

Science.gov (United States)

Verhofstede, Chris; Fransen, Katrien; Van Den Heuvel, Annelies; Van Laethem, Kristel; Ruelle, Jean; Vancutsem, Ellen; Stoffels, Karolien; Van den Wijngaert, Sigi; Delforge, Marie-Luce; Vaira, Dolores; Hebberecht, Laura; Schauvliege, Marlies; Mortier, Virginie; Dauwe, Kenny; Callens, Steven

2017-11-29

There is today no gold standard method to accurately define the time passed since infection at HIV diagnosis. Infection timing and incidence measurement is however essential to better monitor the dynamics of local epidemics and the effect of prevention initiatives. Three methods for infection timing were evaluated using 237 serial samples from documented seroconversions and 566 cross sectional samples from newly diagnosed patients: identification of antibodies against the HIV p31 protein in INNO-LIA, SediaTM BED CEIA and SediaTM LAg-Avidity EIA. A multi-assay decision tree for infection timing was developed. Clear differences in recency window between BED CEIA, LAg-Avidity EIA and p31 antibody presence were observed with a switch from recent to long term infection a median of 169.5, 108.0 and 64.5 days after collection of the pre-seroconversion sample respectively. BED showed high reliability for identification of long term infections while LAg-Avidity is highly accurate for identification of recent infections. Using BED as initial assay to identify the long term infections and LAg-Avidity as a confirmatory assay for those classified as recent infection by BED, explores the strengths of both while reduces the workload. The short recency window of p31 antibodies allows to discriminate very early from early infections based on this marker. BED recent infection results not confirmed by LAg-Avidity are considered to reflect a period more distant from the infection time. False recency predictions in this group can be minimized by elimination of patients with a CD4 count of less than 100 cells/mm3 or without no p31 antibodies. For 566 cross sectional sample the outcome of the decision tree confirmed the infection timing based on the results of all 3 markers but reduced the overall cost from 13.2 USD to 5.2 USD per sample. A step-wise multi assay decision tree allows accurate timing of the HIV infection at diagnosis at affordable effort and cost and can be an important

Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity

OpenAIRE

Barkla, Bronwyn J.

2016-01-01

Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may cont...

High throughput and accurate serum proteome profiling by integrated sample preparation technology and single-run data independent mass spectrometry analysis.

Science.gov (United States)

Lin, Lin; Zheng, Jiaxin; Yu, Quan; Chen, Wendong; Xing, Jinchun; Chen, Chenxi; Tian, Ruijun

2018-03-01

Mass spectrometry (MS)-based serum proteome analysis is extremely challenging due to its high complexity and dynamic range of protein abundances. Developing high throughput and accurate serum proteomic profiling approach capable of analyzing large cohorts is urgently needed for biomarker discovery. Herein, we report a streamlined workflow for fast and accurate proteomic profiling from 1μL of blood serum. The workflow combined an integrated technique for highly sensitive and reproducible sample preparation and a new data-independent acquisition (DIA)-based MS method. Comparing with standard data dependent acquisition (DDA) approach, the optimized DIA method doubled the number of detected peptides and proteins with better reproducibility. Without protein immunodepletion and prefractionation, the single-run DIA analysis enables quantitative profiling of over 300 proteins with 50min gradient time. The quantified proteins span more than five orders of magnitude of abundance range and contain over 50 FDA-approved disease markers. The workflow allowed us to analyze 20 serum samples per day, with about 358 protein groups per sample being identified. A proof-of-concept study on renal cell carcinoma (RCC) serum samples confirmed the feasibility of the workflow for large scale serum proteomic profiling and disease-related biomarker discovery. Blood serum or plasma is the predominant specimen for clinical proteomic studies while the analysis is extremely challenging for its high complexity. Many efforts had been made in the past for serum proteomics for maximizing protein identifications, whereas few have been concerned with throughput and reproducibility. Here, we establish a rapid, robust and high reproducible DIA-based workflow for streamlined serum proteomic profiling from 1μL serum. The workflow doesn't need protein depletion and pre-fractionation, while still being able to detect disease-relevant proteins accurately. The workflow is promising in clinical application

The Identification and Validation of Novel Small Proteins in Pseudomonas Putida KT-2440

DEFF Research Database (Denmark)

Yang, Xiaochen; Long, Katherine

2014-01-01

and activities and may lead to the discovery of novel antimicrobial agents. Our project focuses on the identification, validation and characterization of novel s-­‐proteins in the bacterium Pseudomonas putida KT-­2440. As there is virtually no information on s-­‐proteins in pseudomonads, the first step......, total protein samples are prepared, fractionated, and analyzed with mass spectrometry (MS/MS). The MS/MS data are compared to a custom database containing >80000 putative sORF sequences to identify candidates for validation. A total of 56 and 22 putative sORFs were obtained from MS/MS data...... and bioinformatics prediction, respectively, where there is no overlap between the putative sORFs obtained from the two approaches. The sequences encoding the putative sORFs will be integrated onto the Tn7 site on the chromosome as well as on a plasmid expression vector for validation....

An accurate and efficient identification of children with psychosocial problems by means of computerized adaptive testing

Directory of Open Access Journals (Sweden)

Reijneveld Symen A

2011-08-01

Full Text Available Abstract Background Questionnaires used by health services to identify children with psychosocial problems are often rather short. The psychometric properties of such short questionnaires are mostly less than needed for an accurate distinction between children with and without problems. We aimed to assess whether a short Computerized Adaptive Test (CAT can overcome the weaknesses of short written questionnaires when identifying children with psychosocial problems. Method We used a Dutch national data set obtained from parents of children invited for a routine health examination by Preventive Child Healthcare with 205 items on behavioral and emotional problems (n = 2,041, response 84%. In a random subsample we determined which items met the requirements of an Item Response Theory (IRT model to a sufficient degree. Using those items, item parameters necessary for a CAT were calculated and a cut-off point was defined. In the remaining subsample we determined the validity and efficiency of a Computerized Adaptive Test using simulation techniques, with current treatment status and a clinical score on the Total Problem Scale (TPS of the Child Behavior Checklist as criteria. Results Out of 205 items available 190 sufficiently met the criteria of the underlying IRT model. For 90% of the children a score above or below cut-off point could be determined with 95% accuracy. The mean number of items needed to achieve this was 12. Sensitivity and specificity with the TPS as a criterion were 0.89 and 0.91, respectively. Conclusion An IRT-based CAT is a very promising option for the identification of psychosocial problems in children, as it can lead to an efficient, yet high-quality identification. The results of our simulation study need to be replicated in a real-life administration of this CAT.

Computational Identification of Protein Pupylation Sites by Using Profile-Based Composition of k-Spaced Amino Acid Pairs.

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Md Mehedi Hasan

Full Text Available Prokaryotic proteins are regulated by pupylation, a type of post-translational modification that contributes to cellular function in bacterial organisms. In pupylation process, the prokaryotic ubiquitin-like protein (Pup tagging is functionally analogous to ubiquitination in order to tag target proteins for proteasomal degradation. To date, several experimental methods have been developed to identify pupylated proteins and their pupylation sites, but these experimental methods are generally laborious and costly. Therefore, computational methods that can accurately predict potential pupylation sites based on protein sequence information are highly desirable. In this paper, a novel predictor termed as pbPUP has been developed for accurate prediction of pupylation sites. In particular, a sophisticated sequence encoding scheme [i.e. the profile-based composition of k-spaced amino acid pairs (pbCKSAAP] is used to represent the sequence patterns and evolutionary information of the sequence fragments surrounding pupylation sites. Then, a Support Vector Machine (SVM classifier is trained using the pbCKSAAP encoding scheme. The final pbPUP predictor achieves an AUC value of 0.849 in 10-fold cross-validation tests and outperforms other existing predictors on a comprehensive independent test dataset. The proposed method is anticipated to be a helpful computational resource for the prediction of pupylation sites. The web server and curated datasets in this study are freely available at http://protein.cau.edu.cn/pbPUP/.

Identification and quantification of major bovine milk proteins by liquid chromatography.

Science.gov (United States)

Bordin, G; Cordeiro Raposo, F; de la Calle, B; Rodriguez, A R

2001-08-31

In the field of food quality, bovine milk products are of particular interest due to the social and economic importance of the dairy products market. However, the risk of fraudulent manipulation is high in this area, for instance, replacing milk powder by whey is very interesting from an economic point of view. Therefore, there is a need to have suitable analytical methods available for the determination of all milk components, which is currently not the case, especially for the main proteins. The detection of potential manipulations requires then a clear analytical characterisation of each type of bovine milk, what constitutes the goal of this work. The separation of the major milk proteinic components has been carried out by ion-pair reversed-phase HPLC with photodiode array detection, using a C4 column. The overall optimisation has been achieved using a statistical experimental design procedure. The identification of each protein was ascertained using retention times, peak area ratios and second derivative UV spectra. Quantification was based on calibration curves drawn using purified proteins. Major sources of uncertainty were identified and the full uncertainty budget was established. The procedure was initially developed using the skimmed milk powder certified reference material CRM 063R and then applied to various types of commercial milks as well as to raw milk. The method is able to separate and quantify the seven major proteins (K-casein, alphas2-casein, alphas1-casein, beta-casein, alpha-lactalbumin, beta-lactoglobulin B and beta-lactoglobulin A) in one run and also to provide precise determinations of the total protein concentration. These are important results towards the further development of a reference method for major proteins in milk. In addition, the use of a certified material reference is suggested in order to make comparisons of method performances possible.

Identification of herpesvirus proteins that contribute to G1/S arrest.

Science.gov (United States)

Paladino, Patrick; Marcon, Edyta; Greenblatt, Jack; Frappier, Lori

2014-04-01

Lytic infection by herpesviruses induces cell cycle arrest at the G1/S transition. This appears to be a function of multiple herpesvirus proteins, but only a minority of herpesvirus proteins have been examined for cell cycle effects. To gain a more comprehensive understanding of the viral proteins that contribute to G1/S arrest, we screened a library of over 200 proteins from herpes simplex virus type 1, human cytomegalovirus, and Epstein-Barr virus (EBV) for effects on the G1/S interface, using HeLa fluorescent, ubiquitination-based cell cycle indicator (Fucci) cells in which G1/S can be detected colorimetrically. Proteins from each virus were identified that induce accumulation of G1/S cells, predominantly tegument, early, and capsid proteins. The identification of several capsid proteins in this screen suggests that incoming viral capsids may function to modulate cellular processes. The cell cycle effects of selected EBV proteins were further verified and examined for effects on p53 and p21 as regulators of the G1/S transition. Two EBV replication proteins (BORF2 and BMRF1) were found to induce p53 but not p21, while a previously uncharacterized tegument protein (BGLF2) was found to induce p21 protein levels in a p53-independent manner. Proteomic analyses of BGLF2-interacting proteins identified interactions with the NIMA-related protein kinase (NEK9) and GEM-interacting protein (GMIP). Silencing of either NEK9 or GMIP induced p21 without affecting p53 and abrogated the ability of BGLF2 to further induce p21. Collectively, these results suggest multiple viral proteins contribute to G1/S arrest, including BGLF2, which induces p21 levels likely by interfering with the functions of NEK9 and GMIP. Most people are infected with multiple herpesviruses, whose proteins alter the infected cells in several ways. During lytic infection, the viral proteins block cell proliferation just before the cellular DNA replicates. We used a novel screening method to identify proteins

Identification and modification of dynamical regions in proteins for alteration of enzyme catalytic effect

Science.gov (United States)

Agarwal, Pratul K.

2013-04-09

A method for analysis, control, and manipulation for improvement of the chemical reaction rate of a protein-mediated reaction is provided. Enzymes, which typically comprise protein molecules, are very efficient catalysts that enhance chemical reaction rates by many orders of magnitude. Enzymes are widely used for a number of functions in chemical, biochemical, pharmaceutical, and other purposes. The method identifies key protein vibration modes that control the chemical reaction rate of the protein-mediated reaction, providing identification of the factors that enable the enzymes to achieve the high rate of reaction enhancement. By controlling these factors, the function of enzymes may be modulated, i.e., the activity can either be increased for faster enzyme reaction or it can be decreased when a slower enzyme is desired. This method provides an inexpensive and efficient solution by utilizing computer simulations, in combination with available experimental data, to build suitable models and investigate the enzyme activity.

Proteomic identification of early salicylate- and flg22-responsive redox-sensitive proteins in Arabidopsis

KAUST Repository

Liu, Peng

2015-02-27

Accumulation of reactive oxygen species (ROS) is one of the early defense responses against pathogen infection in plants. The mechanism about the initial and direct regulation of the defense signaling pathway by ROS remains elusive. Perturbation of cellular redox homeostasis by ROS is believed to alter functions of redox-sensitive proteins through their oxidative modifications. Here we report an OxiTRAQ-based proteomic study in identifying proteins whose cysteines underwent oxidative modifications in Arabidopsis cells during the early response to salicylate or flg22, two defense pathway elicitors that are known to disturb cellular redox homeostasis. Among the salicylate- and/or flg22-responsive redox-sensitive proteins are those involved in transcriptional regulation, chromatin remodeling, RNA processing, post-translational modifications, and nucleocytoplasmic shuttling. The identification of the salicylate-/flg22-responsive redox-sensitive proteins provides a foundation from which further study can be conducted toward understanding biological significance of their oxidative modifications during the plant defense response.

Accurate determination of interfacial protein secondary structure by combining interfacial-sensitive amide I and amide III spectral signals.

Science.gov (United States)

Ye, Shuji; Li, Hongchun; Yang, Weilai; Luo, Yi

2014-01-29

Accurate determination of protein structures at the interface is essential to understand the nature of interfacial protein interactions, but it can only be done with a few, very limited experimental methods. Here, we demonstrate for the first time that sum frequency generation vibrational spectroscopy can unambiguously differentiate the interfacial protein secondary structures by combining surface-sensitive amide I and amide III spectral signals. This combination offers a powerful tool to directly distinguish random-coil (disordered) and α-helical structures in proteins. From a systematic study on the interactions between several antimicrobial peptides (including LKα14, mastoparan X, cecropin P1, melittin, and pardaxin) and lipid bilayers, it is found that the spectral profiles of the random-coil and α-helical structures are well separated in the amide III spectra, appearing below and above 1260 cm(-1), respectively. For the peptides with a straight backbone chain, the strength ratio for the peaks of the random-coil and α-helical structures shows a distinct linear relationship with the fraction of the disordered structure deduced from independent NMR experiments reported in the literature. It is revealed that increasing the fraction of negatively charged lipids can induce a conformational change of pardaxin from random-coil to α-helical structures. This experimental protocol can be employed for determining the interfacial protein secondary structures and dynamics in situ and in real time without extraneous labels.

Detection of protein-protein interactions by ribosome display and protein in situ immobilisation.

Science.gov (United States)

He, Mingyue; Liu, Hong; Turner, Martin; Taussig, Michael J

2009-12-31

We describe a method for identification of protein-protein interactions by combining two cell-free protein technologies, namely ribosome display and protein in situ immobilisation. The method requires only PCR fragments as the starting material, the target proteins being made through cell-free protein synthesis, either associated with their encoding mRNA as ribosome complexes or immobilised on a solid surface. The use of ribosome complexes allows identification of interacting protein partners from their attached coding mRNA. To demonstrate the procedures, we have employed the lymphocyte signalling proteins Vav1 and Grb2 and confirmed the interaction between Grb2 and the N-terminal SH3 domain of Vav1. The method has promise for library screening of pairwise protein interactions, down to the analytical level of individual domain or motif mapping.

Proteomic Identification of Altered Cerebral Proteins in the Complex Regional Pain Syndrome Animal Model

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Francis Sahngun Nahm

2014-01-01

Full Text Available Background. Complex regional pain syndrome (CRPS is a rare but debilitating pain disorder. Although the exact pathophysiology of CRPS is not fully understood, central and peripheral mechanisms might be involved in the development of this disorder. To reveal the central mechanism of CRPS, we conducted a proteomic analysis of rat cerebrum using the chronic postischemia pain (CPIP model, a novel experimental model of CRPS. Materials and Methods. After generating the CPIP animal model, we performed a proteomic analysis of the rat cerebrum using a multidimensional protein identification technology, and screened the proteins differentially expressed between the CPIP and control groups. Results. A total of 155 proteins were differentially expressed between the CPIP and control groups: 125 increased and 30 decreased; expressions of proteins related to cell signaling, synaptic plasticity, regulation of cell proliferation, and cytoskeletal formation were increased in the CPIP group. However, proenkephalin A, cereblon, and neuroserpin were decreased in CPIP group. Conclusion. Altered expression of cerebral proteins in the CPIP model indicates cerebral involvement in the pathogenesis of CRPS. Further study is required to elucidate the roles of these proteins in the development and maintenance of CRPS.

Proteomic identification of altered cerebral proteins in the complex regional pain syndrome animal model.

Science.gov (United States)

Nahm, Francis Sahngun; Park, Zee-Yong; Nahm, Sang-Soep; Kim, Yong Chul; Lee, Pyung Bok

2014-01-01

Complex regional pain syndrome (CRPS) is a rare but debilitating pain disorder. Although the exact pathophysiology of CRPS is not fully understood, central and peripheral mechanisms might be involved in the development of this disorder. To reveal the central mechanism of CRPS, we conducted a proteomic analysis of rat cerebrum using the chronic postischemia pain (CPIP) model, a novel experimental model of CRPS. After generating the CPIP animal model, we performed a proteomic analysis of the rat cerebrum using a multidimensional protein identification technology, and screened the proteins differentially expressed between the CPIP and control groups. Results. A total of 155 proteins were differentially expressed between the CPIP and control groups: 125 increased and 30 decreased; expressions of proteins related to cell signaling, synaptic plasticity, regulation of cell proliferation, and cytoskeletal formation were increased in the CPIP group. However, proenkephalin A, cereblon, and neuroserpin were decreased in CPIP group. Altered expression of cerebral proteins in the CPIP model indicates cerebral involvement in the pathogenesis of CRPS. Further study is required to elucidate the roles of these proteins in the development and maintenance of CRPS.

Novel Accurate Bacterial Discrimination by MALDI-Time-of-Flight MS Based on Ribosomal Proteins Coding in S10-spc-alpha Operon at Strain Level S10-GERMS

Science.gov (United States)

Tamura, Hiroto; Hotta, Yudai; Sato, Hiroaki

2013-08-01

Matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is one of the most widely used mass-based approaches for bacterial identification and classification because of the simple sample preparation and extremely rapid analysis within a few minutes. To establish the accurate MALDI-TOF MS bacterial discrimination method at strain level, the ribosomal subunit proteins coded in the S 10-spc-alpha operon, which encodes half of the ribosomal subunit protein and is highly conserved in eubacterial genomes, were selected as reliable biomarkers. This method, named the S10-GERMS method, revealed that the strains of genus Pseudomonas were successfully identified and discriminated at species and strain levels, respectively; therefore, the S10-GERMS method was further applied to discriminate the pathovar of P. syringae. The eight selected biomarkers (L24, L30, S10, S12, S14, S16, S17, and S19) suggested the rapid discrimination of P. syringae at the strain (pathovar) level. The S10-GERMS method appears to be a powerful tool for rapid and reliable bacterial discrimination and successful phylogenetic characterization. In this article, an overview of the utilization of results from the S10-GERMS method is presented, highlighting the characterization of the Lactobacillus casei group and discrimination of the bacteria of genera Bacillus and Sphingopyxis despite only two and one base difference in the 16S rRNA gene sequence, respectively.

Identification of southern radio sources

International Nuclear Information System (INIS)

Savage, A.; Bolton, J.G.; Wright, A.E.

1977-01-01

Identifications are suggested for 53 radio sources from the southern zones of the Parkes 2700-MHz survey, 32 with galaxies, 11 with suggested QSOs and 10 with confirmed QSOs. The identifications were made from the ESO quick blue survey plates, the SRC IIIa-J deep survey plates and the Palomar Sky Survey prints. Accurate optical positions have been measured for four of the new identifications and for two previously suggested identifications. A further nine previously suggested QSO identifications have also been confirmed by two-colour photography or spectroscopy. (author)

Identification of salivary mucin MUC7 binding proteins from Streptococcus gordonii

Directory of Open Access Journals (Sweden)

Thornton David J

2009-08-01

Full Text Available Abstract Background The salivary mucin MUC7 (previously known as MG2 can adhere to various strains of streptococci that are primary colonizers and predominant microorganisms of the oral cavity. Although there is a growing interest in interaction between oral pathogens and salivary mucins, studies reporting the specific binding sites on the bacteria are rather limited. Identification and characterization of the specific interacting proteins on the bacterial cell surface, termed adhesins, are crucial to further understand host-pathogen interactions. Results We demonstrate here, using purified MUC7 to overlay blots of SDS-extracts of Streptococcus gordonii cell surface proteins, 4 MUC7-binding bands, with apparent molecular masses of 62, 78, 84 and 133 kDa from the Streptococcus gordonii strain, PK488. Putative adhesins were identified by in-gel digestion and subsequent nanoLC-tandem mass spectrometry analysis of resultant peptides. The 62 kDa and 84 kDa bands were identified as elongation factor (EF Tu and EF-G respectively. The 78 kDa band was a hppA gene product; the 74 kDa oligopeptide-binding lipoprotein. The 133 kDa band contained two proteins; alpha enolase and DNA-directed RNA polymerase, beta' subunit. Some of these proteins, for example alpha enolase are expected to be intracellular, however, flow cytometric analysis confirmed its location on the bacterial surface. Conclusion Our data demonstrated that S. gordonii expressed a number of putative MUC7 recognizing proteins and these contribute to MUC7 mucin binding of this streptococcal strain.

Accurate, rapid identification of dislocation lines in coherent diffractive imaging via a min-max optimization formulation

Energy Technology Data Exchange (ETDEWEB)

Ulvestad, A. [Materials Science Division, Argonne National Laboratory, Lemont, IL 60439, USA; Menickelly, M. [Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL 60439, USA; Wild, S. M. [Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL 60439, USA

2018-01-01

Defects such as dislocations impact materials properties and their response during external stimuli. Imaging these defects in their native operating conditions to establish the structure-function relationship and, ultimately, to improve performance via defect engineering has remained a considerable challenge for both electron-based and x-ray-based imaging techniques. While Bragg coherent x-ray diffractive imaging (BCDI) is successful in many cases, nuances in identifying the dislocations has left manual identification as the preferred method. Derivative-based methods are also used, but they can be inaccurate and are computationally inefficient. Here we demonstrate a derivative-free method that is both more accurate and more computationally efficient than either derivative-or human-based methods for identifying 3D dislocation lines in nanocrystal images produced by BCDI. We formulate the problem as a min-max optimization problem and show exceptional accuracy for experimental images. We demonstrate a 227x speedup for a typical experimental dataset with higher accuracy over current methods. We discuss the possibility of using this algorithm as part of a sparsity-based phase retrieval process. We also provide MATLAB code for use by other researchers.

Identification of active pocket and protein druggability within envelope glycoprotein GP2 from Ebola virus

Directory of Open Access Journals (Sweden)

Beuy Joob

2014-12-01

Full Text Available The drug searching for combating the present outbreak of Ebola virus infection is the urgent activity at present. Finding the new effective drug at present must base on the molecular analysis of the pathogenic virus. The in-depth analysis of the viral protein to find the binding site, active pocket is needed. Here, the authors analyzed the envelope glycoprotein GP2 from Ebola virus. Identification of active pocket and protein druggability within envelope glycoprotein GP2 from Ebola virus was done. According to this assessment, 7 active pockets with varied druggability could be identified.

Diversity and subcellular distribution of archaeal secreted proteins

Directory of Open Access Journals (Sweden)

Mechthild ePohlschroder

2012-07-01

Full Text Available Secreted proteins make up a significant percentage of a prokaryotic proteome and play critical roles in important cellular processes such as polymer degradation, nutrient uptake, signal transduction, cell wall biosynthesis and motility. The majority of archaeal proteins are believed to be secreted either in an unfolded conformation via the universally conserved Sec pathway or in a folded conformation via the Twin arginine transport (Tat pathway. Extensive in vivo and in silico analyses of N-terminal signal peptides that target proteins to these pathways have led to the development of computational tools that not only predict Sec and Tat substrates with high accuracy but also provide information about signal peptide processing and targeting. Predictions therefore include indications as to whether a substrate is a soluble secreted protein, a membrane or cell-wall anchored protein, or a surface structure subunit, and whether it is targeted for post-translational modification such as glycosylation or the addition of a lipid. The use of these in silico tools, in combination with biochemical and genetic analyses of transport pathways and their substrates, has resulted in improved predictions of the subcellular localization of archaeal secreted proteins, allowing for a more accurate annotation of archaeal proteomes, and has led to the identification of potential adaptations to extreme environments, as well as archaeal kingdom-specific pathways. A more comprehensive understanding of the transport pathways and post-translational modifications of secreted archaeal proteins will also generate invaluable insights that will facilitate the identification of commercially valuable archaeal enzymes and the development of heterologous systems in which to efficiently express them.

Diversity and subcellular distribution of archaeal secreted proteins.

Science.gov (United States)

Szabo, Zalan; Pohlschroder, Mechthild

2012-01-01

Secreted proteins make up a significant percentage of a prokaryotic proteome and play critical roles in important cellular processes such as polymer degradation, nutrient uptake, signal transduction, cell wall biosynthesis, and motility. The majority of archaeal proteins are believed to be secreted either in an unfolded conformation via the universally conserved Sec pathway or in a folded conformation via the Twin arginine transport (Tat) pathway. Extensive in vivo and in silico analyses of N-terminal signal peptides that target proteins to these pathways have led to the development of computational tools that not only predict Sec and Tat substrates with high accuracy but also provide information about signal peptide processing and targeting. Predictions therefore include indications as to whether a substrate is a soluble secreted protein, a membrane or cell wall anchored protein, or a surface structure subunit, and whether it is targeted for post-translational modification such as glycosylation or the addition of a lipid. The use of these in silico tools, in combination with biochemical and genetic analyses of transport pathways and their substrates, has resulted in improved predictions of the subcellular localization of archaeal secreted proteins, allowing for a more accurate annotation of archaeal proteomes, and has led to the identification of potential adaptations to extreme environments, as well as phyla-specific pathways among the archaea. A more comprehensive understanding of the transport pathways used and post-translational modifications of secreted archaeal proteins will also facilitate the identification and heterologous expression of commercially valuable archaeal enzymes.

Subpathway-GM: identification of metabolic subpathways via joint power of interesting genes and metabolites and their topologies within pathways.

Science.gov (United States)

Li, Chunquan; Han, Junwei; Yao, Qianlan; Zou, Chendan; Xu, Yanjun; Zhang, Chunlong; Shang, Desi; Zhou, Lingyun; Zou, Chaoxia; Sun, Zeguo; Li, Jing; Zhang, Yunpeng; Yang, Haixiu; Gao, Xu; Li, Xia

2013-05-01

Various 'omics' technologies, including microarrays and gas chromatography mass spectrometry, can be used to identify hundreds of interesting genes, proteins and metabolites, such as differential genes, proteins and metabolites associated with diseases. Identifying metabolic pathways has become an invaluable aid to understanding the genes and metabolites associated with studying conditions. However, the classical methods used to identify pathways fail to accurately consider joint power of interesting gene/metabolite and the key regions impacted by them within metabolic pathways. In this study, we propose a powerful analytical method referred to as Subpathway-GM for the identification of metabolic subpathways. This provides a more accurate level of pathway analysis by integrating information from genes and metabolites, and their positions and cascade regions within the given pathway. We analyzed two colorectal cancer and one metastatic prostate cancer data sets and demonstrated that Subpathway-GM was able to identify disease-relevant subpathways whose corresponding entire pathways might be ignored using classical entire pathway identification methods. Further analysis indicated that the power of a joint genes/metabolites and subpathway strategy based on their topologies may play a key role in reliably recalling disease-relevant subpathways and finding novel subpathways.

Enhancing bioactive peptide release and identification using targeted enzymatic hydrolysis of milk proteins.

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Nongonierma, Alice B; FitzGerald, Richard J

2018-06-01

Milk proteins have been extensively studied for their ability to yield a range of bioactive peptides following enzymatic hydrolysis/digestion. However, many hurdles still exist regarding the widespread utilization of milk protein-derived bioactive peptides as health enhancing agents for humans. These mostly arise from the fact that most milk protein-derived bioactive peptides are not highly potent. In addition, they may be degraded during gastrointestinal digestion and/or have a low intestinal permeability. The targeted release of bioactive peptides during the enzymatic hydrolysis of milk proteins may allow the generation of particularly potent bioactive hydrolysates and peptides. Therefore, the development of milk protein hydrolysates capable of improving human health requires, in the first instance, optimized targeted release of specific bioactive peptides. The targeted hydrolysis of milk proteins has been aided by a range of in silico tools. These include peptide cutters and predictive modeling linking bioactivity to peptide structure [i.e., molecular docking, quantitative structure activity relationship (QSAR)], or hydrolysis parameters [design of experiments (DOE)]. Different targeted enzymatic release strategies employed during the generation of milk protein hydrolysates are reviewed herein and their limitations are outlined. In addition, specific examples are provided to demonstrate how in silico tools may help in the identification and discovery of potent milk protein-derived peptides. It is anticipated that the development of novel strategies employing a range of in silico tools may help in the generation of milk protein hydrolysates containing potent and bioavailable peptides, which in turn may be used to validate their health promoting effects in humans. Graphical abstract The targeted enzymatic hydrolysis of milk proteins may allow the generation of highly potent and bioavailable bioactive peptides.

Identification of immunogenic proteins and evaluation of four recombinant proteins as potential vaccine antigens from Vibrio anguillarum in flounder (Paralichthys olivaceus).

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Xing, Jing; Xu, Hongsen; Wang, Yang; Tang, Xiaoqian; Sheng, Xiuzhen; Zhan, Wenbin

2017-05-31

Vibrio anguillarum is a severe bacterial pathogen that can infect a wide range of fish species. Identification of immunogenic proteins and development of vaccine are essential for disease prevention. In this study, immunogenic proteins were screened and identified from V. anguillarum, and then protective efficacy of the immunogenic proteins was evaluated. Immunogenic proteins in V. anguillarum whole cell were detected by Western blotting (WB) using immunized flounder (Paralichthys olivaceus) serum, and then identified by Mass spectrometry (MS). The recombinant proteins of four identified immunogenic proteins were produced and immunized to fish, and then percentages of surface membrane immunoglobulin-positive (sIg+) cells in peripheral blood lymphocytes (PBL), total antibodies, antibodies against V. anguillarum, antibodies against recombinant proteins and relative percent survival (RPS) were measured, respectively. The results showed that five immunogenic proteins, VAA, Groel, OmpU, PteF and SpK, were identified; their recombinant proteins, rOmpU, rGroel, rSpK and rVAA, could induce the proliferation of sIg+ cells in PBL and production of total antibodies, antibodies against V. anguillarum and antibodies against the recombinant proteins; their protection against V. anguillarum showed 64.86%, 72.97%, 21.62% and 78.38% RPS, respectively. The results revealed that the immunoproteomic technique using fish anti-V. anguillarum serum provided an efficient way to screen the immunogenic protein for vaccine antigen. Moreover, the rVAA, rGroel and rOmpU had potential to be vaccine candidates against V. anguillarum infection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Signal peptide discrimination and cleavage site identification using SVM and NN.

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Kazemian, H B; Yusuf, S A; White, K

2014-02-01

About 15% of all proteins in a genome contain a signal peptide (SP) sequence, at the N-terminus, that targets the protein to intracellular secretory pathways. Once the protein is targeted correctly in the cell, the SP is cleaved, releasing the mature protein. Accurate prediction of the presence of these short amino-acid SP chains is crucial for modelling the topology of membrane proteins, since SP sequences can be confused with transmembrane domains due to similar composition of hydrophobic amino acids. This paper presents a cascaded Support Vector Machine (SVM)-Neural Network (NN) classification methodology for SP discrimination and cleavage site identification. The proposed method utilises a dual phase classification approach using SVM as a primary classifier to discriminate SP sequences from Non-SP. The methodology further employs NNs to predict the most suitable cleavage site candidates. In phase one, a SVM classification utilises hydrophobic propensities as a primary feature vector extraction using symmetric sliding window amino-acid sequence analysis for discrimination of SP and Non-SP. In phase two, a NN classification uses asymmetric sliding window sequence analysis for prediction of cleavage site identification. The proposed SVM-NN method was tested using Uni-Prot non-redundant datasets of eukaryotic and prokaryotic proteins with SP and Non-SP N-termini. Computer simulation results demonstrate an overall accuracy of 0.90 for SP and Non-SP discrimination based on Matthews Correlation Coefficient (MCC) tests using SVM. For SP cleavage site prediction, the overall accuracy is 91.5% based on cross-validation tests using the novel SVM-NN model. © 2013 Published by Elsevier Ltd.

Matrix-assisted laser desorption/ionization coupled with quadrupole/orthogonal acceleration time-of-flight mass spectrometry for protein discovery, identification, and structural analysis.

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Baldwin, M A; Medzihradszky, K F; Lock, C M; Fisher, B; Settineri, T A; Burlingame, A L

2001-04-15

The design and operation of a novel UV-MALDI ionization source on a commercial QqoaTOF mass spectrometer (Applied Biosystem/MDS Sciex QSTAR Pulsar) is described. Samples are loaded on a 96-well target plate, the movement of which is under software control and can be readily automated. Unlike conventional high-energy MALDI-TOF, the ions are produced with low energies (5-10 eV) in a region of relatively low vacuum (8 mTorr). Thus, they are cooled by extensive low-energy collisions before selection in the quadrupole mass analyzer (Q1), potentially giving a quasi-continuous ion beam ideally suited to the oaTOF used for mass analysis of the fragment ions, although ion yields from individual laser shots may vary widely. Ion dissociation is induced by collisions with argon in an rf-only quadrupole cell, giving typical low-energy CID spectra for protonated peptide ions. Ions separated in the oaTOF are registered by a four-anode detector and time-to-digital converter and accumulated in "bins" that are 625 ps wide. Peak shapes depend upon the number of ion counts in adjacent bins. As expected, the accuracy of mass measurement is shown to be dependent upon the number of ions recorded for a particular peak. With internal calibration, mass accuracy better than 10 ppm is attainable for peaks that contain sufficient ions to give well-defined Gaussian profiles. By virtue of its high resolution, capability for accurate mass measurements, and sensitivity in the low-femotomole range, this instrument is ideally suited to protein identification for proteomic applications by generation of peptide tags, manual sequence interpretation, identification of modifications such as phosphorylation, and protein structural elucidation. Unlike the multiply charged ions typical of electrospray ionization, the singly charged MALDI-generated peptide ions show a linear dependence of optimal collision energy upon molecular mass, which is advantageous for automated operation. It is shown that the novel

A peptide affinity column for the identification of integrin alpha IIb-binding proteins.

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Daxecker, Heide; Raab, Markus; Bernard, Elise; Devocelle, Marc; Treumann, Achim; Moran, Niamh

2008-03-01

To understand the regulation of integrin alpha(IIb)beta(3), a critical platelet adhesion molecule, we have developed a peptide affinity chromatography method using the known integrin regulatory motif, LAMWKVGFFKR. Using standard Fmoc chemistry, this peptide was synthesized onto a Toyopearl AF-Amino-650 M resin on a 6-aminohexanoic acid (Ahx) linker. Peptide density was controlled by acetylation of 83% of the Ahx amino groups. Four recombinant human proteins (CIB1, PP1, ICln and RN181), previously identified as binding to this integrin regulatory motif, were specifically retained by the column containing the integrin peptide but not by a column presenting an irrelevant peptide. Hemoglobin, creatine kinase, bovine serum albumin, fibrinogen and alpha-tubulin failed to bind under the chosen conditions. Immunodetection methods confirmed the binding of endogenous platelet proteins, including CIB1, PP1, ICln RN181, AUP-1 and beta3-integrin, from a detergent-free platelet lysate. Thus, we describe a reproducible method that facilitates the reliable extraction of specific integrin-binding proteins from complex biological matrices. This methodology may enable the sensitive and specific identification of proteins that interact with linear, membrane-proximal peptide motifs such as the integrin regulatory motif LAMWKVGFFKR.

ChIP-seq Accurately Predicts Tissue-Specific Activity of Enhancers

Energy Technology Data Exchange (ETDEWEB)

Visel, Axel; Blow, Matthew J.; Li, Zirong; Zhang, Tao; Akiyama, Jennifer A.; Holt, Amy; Plajzer-Frick, Ingrid; Shoukry, Malak; Wright, Crystal; Chen, Feng; Afzal, Veena; Ren, Bing; Rubin, Edward M.; Pennacchio, Len A.

2009-02-01

A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover since they are scattered amongst the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here, we performed chromatin immunoprecipitation with the enhancer-associated protein p300, followed by massively-parallel sequencing, to map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain, and limb tissue. We tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases revealed reproducible enhancer activity in those tissues predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities and suggest that such datasets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale.

Identification of Potential Plants Producing Tannin-protein Complex for a-amylase as Botanical Pesticide

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Asriyah Firdausi

2013-05-01

Full Text Available Research  on  the  development  of  botanical  pesticides  should  be developed  through  new  methods,  such  as  by  inhibiting the  activity  of  digestive enzymes  by  secondary  metabolites.  The  aim  of  this  study  was  to  identify some  of  potential  plants  as  a  source  of  tannin-protein  complexes  to  inhibitthe  activity  of  - amylase.  The  study  of  identification  of  potential  plants producing  the  active  ingredient  tannin-protein  complex  was  divided  into  three stages,  1  identification  of  potential  plants  producing  tannin,  2  isolation  of tannin-protein  complexes,  and  3  in  vitro  test  of  tannin-protein  complexes effect  of  the  -amylase activity.  Some  of  the observed  plants  were  sidaguri  leaf (Sida rhombifolia, melinjo leaf (Gnetum gnemon, gamal leaf (Gliricidia sepium,lamtoro  leaf  (Leucaena  leucocephala ,  betel  nut  (Areca  catechu ,  and  crude gambier  (Uncaria  gambir a s  a  source of  tannins  and  melinjo  seed was  used  asprotein  source.  Betel  nut  and  melinjo  seed  were  the  best  source  of  tannin-protein  complex,  tannin  content  1.77  mg  TAE/mL  with  antioxidant  activity  of  90%,the  ability  to  inhibit  the  activity  of  -amylase by  95%  with  IC 50  values  of 10 mg/mL.Key words: Tannin, protein, -amylase, botanical pesticides,Areca catechu, Gnetum gnemon.

Serum protein identification and quantification of the corona of 5, 15 and 80 nm gold nanoparticles

International Nuclear Information System (INIS)

Schäffler, Martin; Semmler-Behnke, Manuela; Takenaka, Shinji; Wenk, Alexander; Schleh, Carsten; Johnston, Blair D; Kreyling, Wolfgang G; Sarioglu, Hakan; Hauck, Stefanie M

2013-01-01

When nanoparticles (NP) enter the body they come into contact with body fluids containing proteins which can adsorb to their surface. These proteins may influence the NP interactions with the biological vicinity, eventually determining their biological fate inside the body. Adsorption of the most abundantly binding proteins was studied after an in vitro 24 hr incubation of monodisperse, negatively charged 5, 15 and 80 nm gold spheres (AuNP) in mouse serum by a two-step analysis: proteomic protein identification and quantitative protein biochemistry. The adsorbed proteins were separated from non-adsorbed proteins by centrifugation and gel electrophoresis and identified using a MALDI-TOF-MS-Proteomics-Analyzer. Quantitative analysis of proteins in gel bands by protein densitometry, required the focus on predominantly binding serum proteins. Numerous proteins adsorbed to the AuNP depending on their size, e.g. apolipoproteins or complement C3. The qualitative and quantitative amount of adsorbed proteins differed between 5, 15 and 80 nm AuNP. Band intensities of adsorbed proteins decreased with increasing AuNP sizes based not only on their mass but also on their surface area. Summarizing, the AuNP surface is covered with serum proteins containing transport and immune related proteins among others. Hence, protein binding depends on the size, surface area and curvature of the AuNP. (paper)

On plate graphite supported sample processing for simultaneous lipid and protein identification by matrix assisted laser desorption ionization mass spectrometry.

Science.gov (United States)

Calvano, Cosima Damiana; van der Werf, Inez Dorothé; Sabbatini, Luigia; Palmisano, Francesco

2015-05-01

The simultaneous identification of lipids and proteins by matrix assisted laser desorption ionization-mass spectrometry (MALDI-MS) after direct on-plate processing of micro-samples supported on colloidal graphite is demonstrated. Taking advantages of large surface area and thermal conductivity, graphite provided an ideal substrate for on-plate proteolysis and lipid extraction. Indeed proteins could be efficiently digested on-plate within 15 min, providing sequence coverages comparable to those obtained by conventional in-solution overnight digestion. Interestingly, detection of hydrophilic phosphorylated peptides could be easily achieved without any further enrichment step. Furthermore, lipids could be simultaneously extracted/identified without any additional treatment/processing step as demonstrated for model complex samples such as milk and egg. The present approach is simple, efficient, of large applicability and offers great promise for protein and lipid identification in very small samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Maximizing Selective Cleavages at Aspartic Acid and Proline Residues for the Identification of Intact Proteins

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Foreman, David J.; Dziekonski, Eric T.; McLuckey, Scott A.

2018-04-01

A new approach for the identification of intact proteins has been developed that relies on the generation of relatively few abundant products from specific cleavage sites. This strategy is intended to complement standard approaches that seek to generate many fragments relatively non-selectively. Specifically, this strategy seeks to maximize selective cleavage at aspartic acid and proline residues via collisional activation of precursor ions formed via electrospray ionization (ESI) under denaturing conditions. A statistical analysis of the SWISS-PROT database was used to predict the number of arginine residues for a given intact protein mass and predict a m/z range where the protein carries a similar charge to the number of arginine residues thereby enhancing cleavage at aspartic acid residues by limiting proton mobility. Cleavage at aspartic acid residues is predicted to be most favorable in the m/z range of 1500-2500, a range higher than that normally generated by ESI at low pH. Gas-phase proton transfer ion/ion reactions are therefore used for precursor ion concentration from relatively high charge states followed by ion isolation and subsequent generation of precursor ions within the optimal m/z range via a second proton transfer reaction step. It is shown that the majority of product ion abundance is concentrated into cleavages C-terminal to aspartic acid residues and N-terminal to proline residues for ions generated by this process. Implementation of a scoring system that weights both ion fragment type and ion fragment area demonstrated identification of standard proteins, ranging in mass from 8.5 to 29.0 kDa. [Figure not available: see fulltext.

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.

Applications of MALDI-TOF MS in Microbiological identification

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Soner Yilmaz

2014-10-01

Full Text Available MALDI-TOF MS (Matriks assisted laser desorption ionization time of flight mass spectrometry is a new metohod for identification of microorganisms nowadays. This method is based revealing of microorganisms protein profile with ionization of protein structure and these ionized mass pass through the electrical field. Profiles which were obtained from microorganisms compare with database of system thus identification is made by this way. Ribosomal proteins are used in identification which are less affected by enviromental conditions. Fresh culture should preferably use in MALDI-TOF MS identification. Ribosomal proteins can be deteriorate in old cultures. The correct identification rates are changing between 84,1% to 95,2% in routine bacterial isolates. The correct identification rates in yeasts are changing between 85% to 100%. It makes identification in positive blood culture bottles without the need of subculture, also makes identification on urine samples without the need of culture which has greater than 105 microorganisms in a microliter. When it compared with conventional and molecular identification methods, it is more effective on per sample costs and elapsed time on working [TAF Prev Med Bull 2014; 13(5.000: 421-426

Identification, characterization and antigenicity of the Plasmodium vivax rhoptry neck protein 1 (PvRON1

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Patarroyo Manuel E

2011-10-01

Full Text Available Abstract Background Plasmodium vivax malaria remains a major health problem in tropical and sub-tropical regions worldwide. Several rhoptry proteins which are important for interaction with and/or invasion of red blood cells, such as PfRONs, Pf92, Pf38, Pf12 and Pf34, have been described during the last few years and are being considered as potential anti-malarial vaccine candidates. This study describes the identification and characterization of the P. vivax rhoptry neck protein 1 (PvRON1 and examine its antigenicity in natural P. vivax infections. Methods The PvRON1 encoding gene, which is homologous to that encoding the P. falciparum apical sushi protein (ASP according to the plasmoDB database, was selected as our study target. The pvron1 gene transcription was evaluated by RT-PCR using RNA obtained from the P. vivax VCG-1 strain. Two peptides derived from the deduced P. vivax Sal-I PvRON1 sequence were synthesized and inoculated in rabbits for obtaining anti-PvRON1 antibodies which were used to confirm the protein expression in VCG-1 strain schizonts along with its association with detergent-resistant microdomains (DRMs by Western blot, and its localization by immunofluorescence assays. The antigenicity of the PvRON1 protein was assessed using human sera from individuals previously exposed to P. vivax malaria by ELISA. Results In the P. vivax VCG-1 strain, RON1 is a 764 amino acid-long protein. In silico analysis has revealed that PvRON1 shares essential characteristics with different antigens involved in invasion, such as the presence of a secretory signal, a GPI-anchor sequence and a putative sushi domain. The PvRON1 protein is expressed in parasite's schizont stage, localized in rhoptry necks and it is associated with DRMs. Recombinant protein recognition by human sera indicates that this antigen can trigger an immune response during a natural infection with P. vivax. Conclusions This study shows the identification and characterization of

Evaluation of mass spectrometric data using principal component analysis for determination of the effects of organic lakes on protein binder identification.

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Hrdlickova Kuckova, Stepanka; Rambouskova, Gabriela; Hynek, Radovan; Cejnar, Pavel; Oltrogge, Doris; Fuchs, Robert

2015-11-01

Matrix-assisted laser desorption/ionisation-time of flight (MALDI-TOF) mass spectrometry is commonly used for the identification of proteinaceous binders and their mixtures in artworks. The determination of protein binders is based on a comparison between the m/z values of tryptic peptides in the unknown sample and a reference one (egg, casein, animal glues etc.), but this method has greater potential to study changes due to ageing and the influence of organic/inorganic components on protein identification. However, it is necessary to then carry out statistical evaluation on the obtained data. Before now, it has been complicated to routinely convert the mass spectrometric data into a statistical programme, to extract and match the appropriate peaks. Only several 'homemade' computer programmes without user-friendly interfaces are available for these purposes. In this paper, we would like to present our completely new, publically available, non-commercial software, ms-alone and multiMS-toolbox, for principal component analyses of MALDI-TOF MS data for R software, and their application to the study of the influence of heterogeneous matrices (organic lakes) for protein identification. Using this new software, we determined the main factors that influence the protein analyses of artificially aged model mixtures of organic lakes and fish glue, prepared according to historical recipes that were used for book illumination, using MALDI-TOF peptide mass mapping. Copyright © 2015 John Wiley & Sons, Ltd.

Identification of southern radio sources

International Nuclear Information System (INIS)

Savage, A.; Bolton, J.G.; Wright, A.E.

1976-01-01

Identifications are suggested for 36 radio sources from the southern zones of the Parkes 2700 MHz survey, 28 with galaxies, six with confirmed and two with suggested quasi-stellar objects. The identifications were made from the ESO quick blue survey plates, the SRC IIIa-J deep survey plates and the Palomar sky survey prints. Accurate optical positions have also been measured for nine of the objects and for five previously suggested identifications. (author)

Proteomic Investigation of Falciparum and Vivax Malaria for Identification of Surrogate Protein Markers

Science.gov (United States)

Ray, Sandipan; Renu, Durairaj; Srivastava, Rajneesh; Gollapalli, Kishore; Taur, Santosh; Jhaveri, Tulip; Dhali, Snigdha; Chennareddy, Srinivasarao; Potla, Ankit; Dikshit, Jyoti Bajpai; Srikanth, Rapole; Gogtay, Nithya; Thatte, Urmila; Patankar, Swati; Srivastava, Sanjeeva

2012-01-01

This study was conducted to analyze alterations in the human serum proteome as a consequence of infection by malaria parasites Plasmodium falciparum and P. vivax to obtain mechanistic insights about disease pathogenesis, host immune response, and identification of potential protein markers. Serum samples from patients diagnosed with falciparum malaria (FM) (n = 20), vivax malaria (VM) (n = 17) and healthy controls (HC) (n = 20) were investigated using multiple proteomic techniques and results were validated by employing immunoassay-based approaches. Specificity of the identified malaria related serum markers was evaluated by means of analysis of leptospirosis as a febrile control (FC). Compared to HC, 30 and 31 differentially expressed and statistically significant (p<0.05) serum proteins were identified in FM and VM respectively, and almost half (46.2%) of these proteins were commonly modulated due to both of the plasmodial infections. 13 proteins were found to be differentially expressed in FM compared to VM. Functional pathway analysis involving the identified proteins revealed the modulation of different vital physiological pathways, including acute phase response signaling, chemokine and cytokine signaling, complement cascades and blood coagulation in malaria. A panel of identified proteins consists of six candidates; serum amyloid A, hemopexin, apolipoprotein E, haptoglobin, retinol-binding protein and apolipoprotein A-I was used to build statistical sample class prediction models. By employing PLS-DA and other classification methods the clinical phenotypic classes (FM, VM, FC and HC) were predicted with over 95% prediction accuracy. Individual performance of three classifier proteins; haptoglobin, apolipoprotein A-I and retinol-binding protein in diagnosis of malaria was analyzed using receiver operating characteristic (ROC) curves. The discrimination of FM, VM, FC and HC groups on the basis of differentially expressed serum proteins demonstrates

Proteomic investigation of falciparum and vivax malaria for identification of surrogate protein markers.

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Sandipan Ray

Full Text Available This study was conducted to analyze alterations in the human serum proteome as a consequence of infection by malaria parasites Plasmodium falciparum and P. vivax to obtain mechanistic insights about disease pathogenesis, host immune response, and identification of potential protein markers. Serum samples from patients diagnosed with falciparum malaria (FM (n = 20, vivax malaria (VM (n = 17 and healthy controls (HC (n = 20 were investigated using multiple proteomic techniques and results were validated by employing immunoassay-based approaches. Specificity of the identified malaria related serum markers was evaluated by means of analysis of leptospirosis as a febrile control (FC. Compared to HC, 30 and 31 differentially expressed and statistically significant (p<0.05 serum proteins were identified in FM and VM respectively, and almost half (46.2% of these proteins were commonly modulated due to both of the plasmodial infections. 13 proteins were found to be differentially expressed in FM compared to VM. Functional pathway analysis involving the identified proteins revealed the modulation of different vital physiological pathways, including acute phase response signaling, chemokine and cytokine signaling, complement cascades and blood coagulation in malaria. A panel of identified proteins consists of six candidates; serum amyloid A, hemopexin, apolipoprotein E, haptoglobin, retinol-binding protein and apolipoprotein A-I was used to build statistical sample class prediction models. By employing PLS-DA and other classification methods the clinical phenotypic classes (FM, VM, FC and HC were predicted with over 95% prediction accuracy. Individual performance of three classifier proteins; haptoglobin, apolipoprotein A-I and retinol-binding protein in diagnosis of malaria was analyzed using receiver operating characteristic (ROC curves. The discrimination of FM, VM, FC and HC groups on the basis of differentially expressed serum proteins demonstrates

Isotope coded protein labeling coupled immunoprecipitation (ICPL-IP): a novel approach for quantitative protein complex analysis from native tissue.

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Vogt, Andreas; Fuerholzner, Bettina; Kinkl, Norbert; Boldt, Karsten; Ueffing, Marius

2013-05-01

High confidence definition of protein interactions is an important objective toward the understanding of biological systems. Isotope labeling in combination with affinity-based isolation of protein complexes has increased in accuracy and reproducibility, yet, larger organisms--including humans--are hardly accessible to metabolic labeling and thus, a major limitation has been its restriction to small animals, cell lines, and yeast. As composition as well as the stoichiometry of protein complexes can significantly differ in primary tissues, there is a great demand for methods capable to combine the selectivity of affinity-based isolation as well as the accuracy and reproducibility of isotope-based labeling with its application toward analysis of protein interactions from intact tissue. Toward this goal, we combined isotope coded protein labeling (ICPL)(1) with immunoprecipitation (IP) and quantitative mass spectrometry (MS). ICPL-IP allows sensitive and accurate analysis of protein interactions from primary tissue. We applied ICPL-IP to immuno-isolate protein complexes from bovine retinal tissue. Protein complexes of immunoprecipitated β-tubulin, a highly abundant protein with known interactors as well as the lowly expressed small GTPase RhoA were analyzed. The results of both analyses demonstrate sensitive and selective identification of known as well as new protein interactions by our method.

Isotope Coded Protein Labeling Coupled Immunoprecipitation (ICPL-IP): A Novel Approach for Quantitative Protein Complex Analysis From Native Tissue*

Science.gov (United States)

Vogt, Andreas; Fuerholzner, Bettina; Kinkl, Norbert; Boldt, Karsten; Ueffing, Marius

2013-01-01

High confidence definition of protein interactions is an important objective toward the understanding of biological systems. Isotope labeling in combination with affinity-based isolation of protein complexes has increased in accuracy and reproducibility, yet, larger organisms—including humans—are hardly accessible to metabolic labeling and thus, a major limitation has been its restriction to small animals, cell lines, and yeast. As composition as well as the stoichiometry of protein complexes can significantly differ in primary tissues, there is a great demand for methods capable to combine the selectivity of affinity-based isolation as well as the accuracy and reproducibility of isotope-based labeling with its application toward analysis of protein interactions from intact tissue. Toward this goal, we combined isotope coded protein labeling (ICPL)1 with immunoprecipitation (IP) and quantitative mass spectrometry (MS). ICPL-IP allows sensitive and accurate analysis of protein interactions from primary tissue. We applied ICPL-IP to immuno-isolate protein complexes from bovine retinal tissue. Protein complexes of immunoprecipitated β-tubulin, a highly abundant protein with known interactors as well as the lowly expressed small GTPase RhoA were analyzed. The results of both analyses demonstrate sensitive and selective identification of known as well as new protein interactions by our method. PMID:23268931

Purification, identification and preliminary crystallographic studies of Pru du amandin, an allergenic protein from Prunus dulcis

International Nuclear Information System (INIS)

Gaur, Vineet; Sethi, Dhruv K.; Salunke, Dinakar M.

2007-01-01

The purification, identification, crystallization and preliminary crystallographic studies of an allergy-related protein, Pru du amandin, from P. dulcis nuts are reported. Food allergies appear to be one of the foremost causes of hypersensitivity reactions. Nut allergies account for most food allergies and are often permanent. The 360 kDa hexameric protein Pru du amandin, a known allergen, was purified from almonds (Prunus dulcis) by ammonium sulfate fractionation and ion-exchange chromatography. The protein was identified by a BLAST homology search against the nonredundant sequence database. Pru du amandin belongs to the 11S legumin family of seed storage proteins characterized by the presence of a cupin motif. Crystals were obtained by the hanging-drop vapour-diffusion method. The crystals belong to space group P4 1 (or P4 3 ), with unit-cell parameters a = b = 150.7, c = 164.9 Å

Large-scale proteomic identification of S100 proteins in breast cancer tissues

International Nuclear Information System (INIS)

Cancemi, Patrizia; Di Cara, Gianluca; Albanese, Nadia Ninfa; Costantini, Francesca; Marabeti, Maria Rita; Musso, Rosa; Lupo, Carmelo; Roz, Elena; Pucci-Minafra, Ida

2010-01-01

Attempts to reduce morbidity and mortality in breast cancer is based on efforts to identify novel biomarkers to support prognosis and therapeutic choices. The present study has focussed on S100 proteins as a potentially promising group of markers in cancer development and progression. One reason of interest in this family of proteins is because the majority of the S100 genes are clustered on a region of human chromosome 1q21 that is prone to genomic rearrangements. Moreover, there is increasing evidence that S100 proteins are often up-regulated in many cancers, including breast, and this is frequently associated with tumour progression. Samples of breast cancer tissues were obtained during surgical intervention, according to the bioethical recommendations, and cryo-preserved until used. Tissue extracts were submitted to proteomic preparations for 2D-IPG. Protein identification was performed by N-terminal sequencing and/or peptide mass finger printing. The majority of the detected S100 proteins were absent, or present at very low levels, in the non-tumoral tissues adjacent to the primary tumor. This finding strengthens the role of S100 proteins as putative biomarkers. The proteomic screening of 100 cryo-preserved breast cancer tissues showed that some proteins were ubiquitously expressed in almost all patients while others appeared more sporadic. Most, if not all, of the detected S100 members appeared reciprocally correlated. Finally, from the perspective of biomarkers establishment, a promising finding was the observation that patients which developed distant metastases after a three year follow-up showed a general tendency of higher S100 protein expression, compared to the disease-free group. This article reports for the first time the comparative proteomic screening of several S100 protein members among a large group of breast cancer patients. The results obtained strongly support the hypothesis that a significant deregulation of multiple S100 protein members is

Microorganism Identification Based On MALDI-TOF-MS Fingerprints

Science.gov (United States)

Elssner, Thomas; Kostrzewa, Markus; Maier, Thomas; Kruppa, Gary

Advances in MALDI-TOF mass spectrometry have enabled the ­development of a rapid, accurate and specific method for the identification of bacteria directly from colonies picked from culture plates, which we have named the MALDI Biotyper. The picked colonies are placed on a target plate, a drop of matrix solution is added, and a pattern of protein molecular weights and intensities, "the protein fingerprint" of the bacteria, is produced by the MALDI-TOF mass spectrometer. The obtained protein mass fingerprint representing a molecular signature of the microorganism is then matched against a database containing a library of previously measured protein mass fingerprints, and scores for the match to every library entry are produced. An ID is obtained if a score is returned over a pre-set threshold. The sensitivity of the techniques is such that only approximately 104 bacterial cells are needed, meaning that an overnight culture is sufficient, and the results are obtained in minutes after culture. The improvement in time to result over biochemical methods, and the capability to perform a non-targeted identification of bacteria and spores, potentially makes this method suitable for use in the detect-to-treat timeframe in a bioterrorism event. In the case of white-powder samples, the infectious spore is present in sufficient quantity in the powder so that the MALDI Biotyper result can be obtained directly from the white powder, without the need for culture. While spores produce very different patterns from the vegetative colonies of the corresponding bacteria, this problem is overcome by simply including protein fingerprints of the spores in the library. Results on spores can be returned within minutes, making the method suitable for use in the "detect-to-protect" timeframe.

Molecular cloning of the gene for the human placental GTP-binding protein Gp (G25K): Identification of this GTP-binding protein as the human homolog of the yeast cell-division-cycle protein CDC42

International Nuclear Information System (INIS)

Shinjo, K.; Koland, J.G.; Hart, M.J.; Narasimhan, V.; Cerione, R.A.; Johnson, D.I.; Evans, T.

1990-01-01

The authors have isolated cDNA clones from a human placental library that code for a low molecular weight GTP-binding protein originally designated G p (also called G25K). This identification is based on comparisons with the available peptide sequences for the purified human G p protein and the use of two highly specific anti-peptide antibodies. The predicted amino acid sequence of the protein is very similar to those of various members of the ras superfamily of low molecular weight GTP-binding proteins, including the N-, Ki-, and Ha-ras proteins (30-35% identical), the rho proteins and the rac proteins. The highest degree of sequence identity (80%) is found with the Saccharomyces cerevisiae cell division-cycle protein CDC42. The human placental gene, which they designate CDC42Hs, complements the cdc42-1 mutation in S. cerevisiae, which suggests that this GTP-binding protein is the human homolog of the yeast protein

Identification of membrane-associated proteins with pathogenic potential expressed by Corynebacterium pseudotuberculosis grown in animal serum.

Science.gov (United States)

Raynal, José Tadeu; Bastos, Bruno Lopes; Vilas-Boas, Priscilla Carolinne Bagano; Sousa, Thiago de Jesus; Costa-Silva, Marcos; de Sá, Maria da Conceição Aquino; Portela, Ricardo Wagner; Moura-Costa, Lília Ferreira; Azevedo, Vasco; Meyer, Roberto

2018-01-25

Previous works defining antigens that might be used as vaccine targets against Corynebacterium pseudotuberculosis, which is the causative agent of sheep and goat caseous lymphadenitis, have focused on secreted proteins produced in a chemically defined culture media. Considering that such antigens might not reflect the repertoire of proteins expressed during infection conditions, this experiment aimed to investigate the membrane-associated proteins with pathogenic potential expressed by C. pseudotuberculosis grown directly in animal serum. Its membrane-associated proteins have been extracted using an organic solvent enrichment methodology, followed by LC-MS/MS and bioinformatics analysis for protein identification and classification. The results revealed 22 membrane-associated proteins characterized as potentially pathogenic. An interaction network analysis indicated that the four potentially pathogenic proteins ciuA, fagA, OppA4 and OppCD were biologically connected within two distinct network pathways, which were both associated with the ABC Transporters KEGG pathway. These results suggest that C. pseudotuberculosis pathogenesis might be associated with the transport and uptake of nutrients; other seven identified potentially pathogenic membrane proteins also suggest that pathogenesis might involve events of bacterial resistance and adhesion. The proteins herein reported potentially reflect part of the protein repertoire expressed during real infection conditions and might be tested as vaccine antigens.

Identification of Tyrosine Phosphorylated Proteins by SH2 Domain Affinity Purification and Mass Spectrometry.

Science.gov (United States)

Buhs, Sophia; Gerull, Helwe; Nollau, Peter

2017-01-01

Phosphotyrosine signaling plays a major role in the control of many important biological functions such as cell proliferation and apoptosis. Deciphering of phosphotyrosine-dependent signaling is therefore of great interest paving the way for the understanding of physiological and pathological processes of signal transduction. On the basis of the specific binding of SH2 domains to phosphotyrosine residues, we here present an experimental workflow for affinity purification and subsequent identification of tyrosine phosphorylated proteins by mass spectrometry. In combination with SH2 profiling, a broadly applicable platform for the characterization of phosphotyrosine profiles in cell extracts, our pull down strategy enables researchers by now to identify proteins in signaling cascades which are differentially phosphorylated and selectively recognized by distinct SH2 domains.

Molecular identification of polydorid polychaetes (Annelida ...

African Journals Online (AJOL)

The early detection and correct identification of polydorid polychaete species is essential as they are often encountered as invasive alien pests in aquaculture facilities or the intertidal where they may modify the ecosystem. Accurate identification is, however, often hampered by high levels of morphological similarity among ...

DNA Methylation as a Biomarker for Body Fluid Identification

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Rania Gomaa

2017-12-01

Full Text Available Currently, available identification techniques for forensic samples are either enzyme or protein based, which can be subjected to degradation, thus limiting its storage potentials. Epigenetic changes arising due to DNA methylation and histone acetylation can be used for body fluid identification. Markers DACT1, USP49, ZC3H12D, FGF7, cg23521140, cg17610929, chromosome 4 (25287119–25287254, chromosome 11 (72085678–72085798, 57171095–57171236, 1493401–1493538, and chromosome 19 (47395505–47395651 are currently being used for semen identification. Markers cg26107890, cg20691722, cg01774894 and cg14991487 are used to differentiate saliva and vaginal secretions from other body fluids. However, such markers show overlapping methylation pattern. This review article aimed to highlight the feasibility of using DNA methylation of certain genetic markers in body fluid identification and its implications for forensic investigations. The reviewed articles have employed molecular genetics techniques such as Bisulfite sequencing PCR (BSP, methylation specific PCR (MSP, Pyrosequencing, Combined Bisulfite Restriction Analysis (COBRA, Methylation-sensitive Single Nucleotide Primer Extension (SNuPE, and Multiplex SNaPshot Microarray. Bioinformatics software such as MATLAB and BiQ Analyzer has been used. Biological fluids have different methylation patterns and thus, this difference can be used to identify the nature of the biological fluid found at the crime scene. Using DNA methylation to identify the body fluids gives accurate results without consumption of the trace evidence and requires a minute amount of DNA for analysis. Recent studies have incorporated next-generation sequencing aiming to find out more reliable markers that can differentiate between different body fluids. Nonetheless, new DNA methylation markers are yet to be discovered to accurately differentiate between saliva and vaginal secretions with high confidence. Epigenetic changes are

Investigation and identification of functional post-translational modification sites associated with drug binding and protein-protein interactions.

Science.gov (United States)

Su, Min-Gang; Weng, Julia Tzu-Ya; Hsu, Justin Bo-Kai; Huang, Kai-Yao; Chi, Yu-Hsiang; Lee, Tzong-Yi

2017-12-21

tools for exploring the structural characteristics of PTMs, is presented. In addition, all tertiary structures of PTM sites on proteins can be visualized using the JSmol program. Resolving the function of PTM sites is important for understanding the role that proteins play in biological mechanisms. Our work attempted to delineate the structural correlation between PTM sites and PPI or drug-target binding. CurxPTM could help scientists narrow the scope of their PTM research and enhance the efficiency of PTM identification in the face of big proteome data. CruxPTM is now available at http://csb.cse.yzu.edu.tw/CruxPTM/ .

Identification of an exported heat shock protein 70 in Plasmodium falciparum

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Grover Manish

2013-01-01

Full Text Available Host cell remodelling is a hallmark of malaria pathogenesis. It involves protein folding, unfolding and trafficking events and thus participation of chaperones such as Hsp70s and Hsp40s is well speculated. Until recently, only Hsp40s were thought to be the sole representative of the parasite chaperones in the exportome. However, based on the re-annotated Plasmodium falciparum genome sequence, a putative candidate for exported Hsp70 has been reported, which otherwise was known to be a pseudogene. We raised a specific antiserum against a C-terminal peptide uniquely present in PfHsp70-x. Immunoblotting and immunofluorescence-based approaches in combination with sub-cellular fractionation by saponin and streptolysin-O have been taken to determine the expression and localization of PfHsp70-x in infected erythrocyte. The re-annotated sequence of PfHsp70-x reveals it to be a functional protein with an endoplasmic reticulum signal peptide. It gets maximally expressed at the schizont stage of intra-erythrocytic life cycle. Majority of the protein localizes to the parasitophorous vacuole and some of it gets exported to the erythrocyte compartment where it associates with Maurer’s clefts. The identification of an exported parasite Hsp70 chaperone presents us with the fact that the parasite has evolved customized chaperones which might be playing crucial roles in aspects of trafficking and host cell remodelling.

Nuclear Magnetic Resonance Spectroscopy-Based Identification of Yeast.

Science.gov (United States)

Himmelreich, Uwe; Sorrell, Tania C; Daniel, Heide-Marie

2017-01-01

Rapid and robust high-throughput identification of environmental, industrial, or clinical yeast isolates is important whenever relatively large numbers of samples need to be processed in a cost-efficient way. Nuclear magnetic resonance (NMR) spectroscopy generates complex data based on metabolite profiles, chemical composition and possibly on medium consumption, which can not only be used for the assessment of metabolic pathways but also for accurate identification of yeast down to the subspecies level. Initial results on NMR based yeast identification where comparable with conventional and DNA-based identification. Potential advantages of NMR spectroscopy in mycological laboratories include not only accurate identification but also the potential of automated sample delivery, automated analysis using computer-based methods, rapid turnaround time, high throughput, and low running costs.We describe here the sample preparation, data acquisition and analysis for NMR-based yeast identification. In addition, a roadmap for the development of classification strategies is given that will result in the acquisition of a database and analysis algorithms for yeast identification in different environments.

Combining structural modeling with ensemble machine learning to accurately predict protein fold stability and binding affinity effects upon mutation.

Directory of Open Access Journals (Sweden)

Niklas Berliner

Full Text Available Advances in sequencing have led to a rapid accumulation of mutations, some of which are associated with diseases. However, to draw mechanistic conclusions, a biochemical understanding of these mutations is necessary. For coding mutations, accurate prediction of significant changes in either the stability of proteins or their affinity to their binding partners is required. Traditional methods have used semi-empirical force fields, while newer methods employ machine learning of sequence and structural features. Here, we show how combining both of these approaches leads to a marked boost in accuracy. We introduce ELASPIC, a novel ensemble machine learning approach that is able to predict stability effects upon mutation in both, domain cores and domain-domain interfaces. We combine semi-empirical energy terms, sequence conservation, and a wide variety of molecular details with a Stochastic Gradient Boosting of Decision Trees (SGB-DT algorithm. The accuracy of our predictions surpasses existing methods by a considerable margin, achieving correlation coefficients of 0.77 for stability, and 0.75 for affinity predictions. Notably, we integrated homology modeling to enable proteome-wide prediction and show that accurate prediction on modeled structures is possible. Lastly, ELASPIC showed significant differences between various types of disease-associated mutations, as well as between disease and common neutral mutations. Unlike pure sequence-based prediction methods that try to predict phenotypic effects of mutations, our predictions unravel the molecular details governing the protein instability, and help us better understand the molecular causes of diseases.

Identification of α(1,6)fucosylated proteins differentially expressed in human colorectal cancer

International Nuclear Information System (INIS)

Muinelo-Romay, Laura; Villar-Portela, Susana; Cuevas, Elisa; Gil-Martín, Emilio; Fernández-Briera, Almudena

2011-01-01

A universal hallmark of cancer cells is the change in their glycosylation phenotype. One of the most frequent alterations in the normal glycosylation pattern observed during carcinogenesis is the enhancement of α(1,6)linked fucose residues of glycoproteins, due to the up-regulation of the α(1,6)fucosyltransferase activity. Our previous results demonstrated the specific alteration of this enzyme activity and expression in colorectal cancer, suggesting its implication in tumour development and progression. In the current work we combined a LCA-affinity chromatography with SDS-PAGE and mass spectrometry in order to identify α(1,6)fucosylated proteins differentially expressed in colorectal cancer. This strategy allowed the identification of a group of α(1,6)fucosylated proteins candidates to be involved in CRC malignancy. The majority of the identified proteins take part in cell signaling and interaction processes as well as in modulation of the immunological response. Likewise, we confirmed the increased expression of GRP94 in colorectal cancer tissue and the significant down-regulation of the IgGFcBP expression in tumour cells. All these results validate the importance of core-fucosylated proteins profile analysis to understand the mechanisms which promote cancer onset and progression and to discover new tumour markers or therapeutic targets

Separation and identification of Musa acuminate Colla (banana) leaf proteins by two-dimensional gel electrophoresis and mass spectrometry.

Science.gov (United States)

Lu, Y; Qi, Y X; Zhang, H; Zhang, H Q; Pu, J J; Xie, Y X

2013-12-19

To establish a proteomic reference map of Musa acuminate Colla (banana) leaf, we separated and identified leaf proteins using two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and mass spectrometry (MS). Tryptic digests of 44 spots were subjected to peptide mass fingerprinting (PMF) by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS. Three spots that were not identified by MALDI-TOF MS analysis were identified by searching against the NCBInr, SwissProt, and expressed sequence tag (EST) databases. We identified 41 unique proteins. The majority of the identified leaf proteins were found to be involved in energy metabolism. The results indicate that 2D-PAGE is a sensitive and powerful technique for the separation and identification of Musa leaf proteins. A summary of the identified proteins and their putative functions is discussed.

Purification, identification and preliminary crystallographic studies of Pru du amandin, an allergenic protein from Prunus dulcis

Energy Technology Data Exchange (ETDEWEB)

Gaur, Vineet; Sethi, Dhruv K.; Salunke, Dinakar M., E-mail: dinakar@nii.res.in [National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110 067 (India)

2008-01-01

The purification, identification, crystallization and preliminary crystallographic studies of an allergy-related protein, Pru du amandin, from P. dulcis nuts are reported. Food allergies appear to be one of the foremost causes of hypersensitivity reactions. Nut allergies account for most food allergies and are often permanent. The 360 kDa hexameric protein Pru du amandin, a known allergen, was purified from almonds (Prunus dulcis) by ammonium sulfate fractionation and ion-exchange chromatography. The protein was identified by a BLAST homology search against the nonredundant sequence database. Pru du amandin belongs to the 11S legumin family of seed storage proteins characterized by the presence of a cupin motif. Crystals were obtained by the hanging-drop vapour-diffusion method. The crystals belong to space group P4{sub 1} (or P4{sub 3}), with unit-cell parameters a = b = 150.7, c = 164.9 Å.

Experimental strategies for the identification and characterization of adhesive proteins in animals: a review

Science.gov (United States)

Hennebert, Elise; Maldonado, Barbara; Ladurner, Peter; Flammang, Patrick; Santos, Romana

2015-01-01

Adhesive secretions occur in both aquatic and terrestrial animals, in which they perform diverse functions. Biological adhesives can therefore be remarkably complex and involve a large range of components with different functions and interactions. However, being mainly protein based, biological adhesives can be characterized by classical molecular methods. This review compiles experimental strategies that were successfully used to identify, characterize and obtain the full-length sequence of adhesive proteins from nine biological models: echinoderms, barnacles, tubeworms, mussels, sticklebacks, slugs, velvet worms, spiders and ticks. A brief description and practical examples are given for a variety of tools used to study adhesive molecules at different levels from genes to secreted proteins. In most studies, proteins, extracted from secreted materials or from adhesive organs, are analysed for the presence of post-translational modifications and submitted to peptide sequencing. The peptide sequences are then used directly for a BLAST search in genomic or transcriptomic databases, or to design degenerate primers to perform RT-PCR, both allowing the recovery of the sequence of the cDNA coding for the investigated protein. These sequences can then be used for functional validation and recombinant production. In recent years, the dual proteomic and transcriptomic approach has emerged as the best way leading to the identification of novel adhesive proteins and retrieval of their complete sequences. PMID:25657842

Comprehensive identification of protein substrates of the Dot/Icm type IV transporter of Legionella pneumophila.

Directory of Open Access Journals (Sweden)

Wenhan Zhu

2011-03-01

Full Text Available A large number of proteins transferred by the Legionella pneumophila Dot/Icm system have been identified by various strategies. With no exceptions, these strategies are based on one or more characteristics associated with the tested proteins. Given the high level of diversity exhibited by the identified proteins, it is possible that some substrates have been missed in these screenings. In this study, we took a systematic method to survey the L. pneumophila genome by testing hypothetical orfs larger than 300 base pairs for Dot/Icm-dependent translocation. 798 of the 832 analyzed orfs were successfully fused to the carboxyl end of β-lactamase. The transfer of the fusions into mammalian cells was determined using the β-lactamase reporter substrate CCF4-AM. These efforts led to the identification of 164 proteins positive in translocation. Among these, 70 proteins are novel substrates of the Dot/Icm system. These results brought the total number of experimentally confirmed Dot/Icm substrates to 275. Sequence analysis of the C-termini of these identified proteins revealed that Lpg2844, which contains few features known to be important for Dot/Icm-dependent protein transfer can be translocated at a high efficiency. Thus, our efforts have identified a large number of novel substrates of the Dot/Icm system and have revealed the diverse features recognizable by this protein transporter.

Computational Prediction of Human Salivary Proteins from Blood Circulation and Application to Diagnostic Biomarker Identification

Science.gov (United States)

Wang, Jiaxin; Liang, Yanchun; Wang, Yan; Cui, Juan; Liu, Ming; Du, Wei; Xu, Ying

2013-01-01

Proteins can move from blood circulation into salivary glands through active transportation, passive diffusion or ultrafiltration, some of which are then released into saliva and hence can potentially serve as biomarkers for diseases if accurately identified. We present a novel computational method for predicting salivary proteins that come from circulation. The basis for the prediction is a set of physiochemical and sequence features we found to be discerning between human proteins known to be movable from circulation to saliva and proteins deemed to be not in saliva. A classifier was trained based on these features using a support-vector machine to predict protein secretion into saliva. The classifier achieved 88.56% average recall and 90.76% average precision in 10-fold cross-validation on the training data, indicating that the selected features are informative. Considering the possibility that our negative training data may not be highly reliable (i.e., proteins predicted to be not in saliva), we have also trained a ranking method, aiming to rank the known salivary proteins from circulation as the highest among the proteins in the general background, based on the same features. This prediction capability can be used to predict potential biomarker proteins for specific human diseases when coupled with the information of differentially expressed proteins in diseased versus healthy control tissues and a prediction capability for blood-secretory proteins. Using such integrated information, we predicted 31 candidate biomarker proteins in saliva for breast cancer. PMID:24324552

A coevolution analysis for identifying protein-protein interactions by Fourier transform

Science.gov (United States)

Yin, Changchuan; Yau, Stephen S. -T.

2017-01-01

Protein-protein interactions (PPIs) play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA); however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40). The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI). PMID:28430779

A coevolution analysis for identifying protein-protein interactions by Fourier transform.

Directory of Open Access Journals (Sweden)

Changchuan Yin

Full Text Available Protein-protein interactions (PPIs play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA; however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40. The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI.

Protein Correlation Profiles Identify Lipid Droplet Proteins with High Confidence*

Science.gov (United States)

Krahmer, Natalie; Hilger, Maximiliane; Kory, Nora; Wilfling, Florian; Stoehr, Gabriele; Mann, Matthias; Farese, Robert V.; Walther, Tobias C.

2013-01-01

Lipid droplets (LDs) are important organelles in energy metabolism and lipid storage. Their cores are composed of neutral lipids that form a hydrophobic phase and are surrounded by a phospholipid monolayer that harbors specific proteins. Most well-established LD proteins perform important functions, particularly in cellular lipid metabolism. Morphological studies show LDs in close proximity to and interacting with membrane-bound cellular organelles, including the endoplasmic reticulum, mitochondria, peroxisomes, and endosomes. Because of these close associations, it is difficult to purify LDs to homogeneity. Consequently, the confident identification of bona fide LD proteins via proteomics has been challenging. Here, we report a methodology for LD protein identification based on mass spectrometry and protein correlation profiles. Using LD purification and quantitative, high-resolution mass spectrometry, we identified LD proteins by correlating their purification profiles to those of known LD proteins. Application of the protein correlation profile strategy to LDs isolated from Drosophila S2 cells led to the identification of 111 LD proteins in a cellular LD fraction in which 1481 proteins were detected. LD localization was confirmed in a subset of identified proteins via microscopy of the expressed proteins, thereby validating the approach. Among the identified LD proteins were both well-characterized LD proteins and proteins not previously known to be localized to LDs. Our method provides a high-confidence LD proteome of Drosophila cells and a novel approach that can be applied to identify LD proteins of other cell types and tissues. PMID:23319140

Discerning cultural identification from a thinly sliced behavioral sample.

Science.gov (United States)

Hamamura, Takeshi; Li, Liman Man Wai

2012-12-01

This research examined whether individual differences in cultural identification can be discerned at zero acquaintance. This issue was examined in Hong Kong, where the idiosyncrasy of cultural identification is a salient social-psychological issue. The participants were able to perceive accurately the targets' identification with Western culture from a video clip and from a still image. Findings also indicated that a stereotype of Western cultural identity (i.e., extraversion and particular hairstyle) facilitated these perceptions. Specifically, (a) the participants with a stronger stereotype were more accurate in perceiving Western cultural identification, (b) the targets who were experimentally manipulated to appear extraverted were rated as more strongly identifying with Western culture, and (c) the participants relatively unfamiliar with these stereotypes did not correctly perceive Western cultural identification. Implications of these findings on research on multiculturalism are also discussed.

The Dictyostelium discoideum cellulose synthase: Structure/function analysis and identification of interacting proteins

Energy Technology Data Exchange (ETDEWEB)

Richard L. Blanton

2004-02-19

OAK-B135 The major accomplishments of this project were: (1) the initial characterization of dcsA, the gene for the putative catalytic subunit of cellulose synthase in the cellular slime mold Dictyostelium discoideum; (2) the detection of a developmentally regulated event (unidentified, but perhaps a protein modification or association with a protein partner) that is required for cellulose synthase activity (i.e., the dcsA product is necessary, but not sufficient for cellulose synthesis); (3) the continued exploration of the developmental context of cellulose synthesis and DcsA; (4) the isolation of a GFP-DcsA-expressing strain (work in progress); and (5) the identification of Dictyostelium homologues for plant genes whose products play roles in cellulose biosynthesis. Although our progress was slow and many of our results negative, we did develop a number of promising avenues of investigation that can serve as the foundation for future projects.

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....

High-throughput peptide mass fingerprinting and protein macroarray analysis using chemical printing strategies

International Nuclear Information System (INIS)

Sloane, A.J.; Duff, J.L.; Hopwood, F.G.; Wilson, N.L.; Smith, P.E.; Hill, C.J.; Packer, N.H.; Williams, K.L.; Gooley, A.A.; Cole, R.A.; Cooley, P.W.; Wallace, D.B.

2001-01-01

We describe a 'chemical printer' that uses piezoelectric pulsing for rapid and accurate microdispensing of picolitre volumes of fluid for proteomic analysis of 'protein macroarrays'. Unlike positive transfer and pin transfer systems, our printer dispenses fluid in a non-contact process that ensures that the fluid source cannot be contaminated by substrate during a printing event. We demonstrate automated delivery of enzyme and matrix solutions for on-membrane protein digestion and subsequent peptide mass fingerprinting (pmf) analysis directly from the membrane surface using matrix-assisted laser-desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). This approach bypasses the more commonly used multi-step procedures, thereby permitting a more rapid procedure for protein identification. We also highlight the advantage of printing different chemistries onto an individual protein spot for multiple microscale analyses. This ability is particularly useful when detailed characterisation of rare and valuable sample is required. Using a combination of PNGase F and trypsin we have mapped sites of N-glycosylation using on-membrane digestion strategies. We also demonstrate the ability to print multiple serum samples in a micro-ELISA format and rapidly screen a protein macroarray of human blood plasma for pathogen-derived antigens. We anticipate that the 'chemical printer' will be a major component of proteomic platforms for high-throughput protein identification and characterisation with widespread applications in biomedical and diagnostic discovery

Comparison of identification methods for oral asaccharolytic Eubacterium species.

Science.gov (United States)

Wade, W G; Slayne, M A; Aldred, M J

1990-12-01

Thirty one strains of oral, asaccharolytic Eubacterium spp. and the type strains of E. brachy, E. nodatum and E. timidum were subjected to three identification techniques--protein-profile analysis, determination of metabolic end-products, and the API ATB32A identification kit. Five clusters were obtained from numerical analysis of protein profiles and excellent correlations were seen with the other two methods. Protein profiles alone allowed unequivocal identification.

A Multifaceted Study of Scedosporium boydii Cell Wall Changes during Germination and Identification of GPI-Anchored Proteins

Science.gov (United States)

Ghamrawi, Sarah; Gastebois, Amandine; Zykwinska, Agata; Vandeputte, Patrick; Marot, Agnès; Mabilleau, Guillaume; Cuenot, Stéphane; Bouchara, Jean-Philippe

2015-01-01

Scedosporium boydii is a pathogenic filamentous fungus that causes a wide range of human infections, notably respiratory infections in patients with cystic fibrosis. The development of new therapeutic strategies targeting S. boydii necessitates a better understanding of the physiology of this fungus and the identification of new molecular targets. In this work, we studied the conidium-to-germ tube transition using a variety of techniques including scanning and transmission electron microscopy, atomic force microscopy, two-phase partitioning, microelectrophoresis and cationized ferritin labeling, chemical force spectroscopy, lectin labeling, and nanoLC-MS/MS for cell wall GPI-anchored protein analysis. We demonstrated that the cell wall undergoes structural changes with germination accompanied with a lower hydrophobicity, electrostatic charge and binding capacity to cationized ferritin. Changes during germination also included a higher accessibility of some cell wall polysaccharides to lectins and less CH3/CH3 interactions (hydrophobic adhesion forces mainly due to glycoproteins). We also extracted and identified 20 GPI-anchored proteins from the cell wall of S. boydii, among which one was detected only in the conidial wall extract and 12 only in the mycelial wall extract. The identified sequences belonged to protein families involved in virulence in other fungi like Gelp/Gasp, Crhp, Bglp/Bgtp families and a superoxide dismutase. These results highlighted the cell wall remodeling during germination in S. boydii with the identification of a substantial number of cell wall GPI-anchored conidial or hyphal specific proteins, which provides a basis to investigate the role of these molecules in the host-pathogen interaction and fungal virulence. PMID:26038837

Matrix-assisted laser desorption/ionization-time of flight mass spectrometry: protocol standardization and database expansion for rapid identification of clinically important molds.

Science.gov (United States)

Paul, Saikat; Singh, Pankaj; Rudramurthy, Shivaprakash M; Chakrabarti, Arunaloke; Ghosh, Anup K

2017-12-01

To standardize the matrix-assisted laser desorption ionization-time of flight mass spectrometry protocols and expansion of existing Bruker Biotyper database for mold identification. Four different sample preparation methods (protocol A, B, C and D) were evaluated. On analyzing each protein extraction method, reliable identification and best log scores were achieved through protocol D. The same protocol was used to identify 153 clinical isolates. Of these 153, 123 (80.3%) were accurately identified by using existing database and remaining 30 (19.7%) were not identified due to unavailability in database. On inclusion of missing main spectrum profile in existing database, all 153 isolates were identified. Matrix-assisted laser desorption ionization-time of flight mass spectrometry can be used for routine identification of clinically important molds.

Importance of molecular diagnosis in the accurate diagnosis of ...

Indian Academy of Sciences (India)

1Department of Health and Environmental Sciences, Kyoto University Graduate School of Medicine, Yoshida Konoecho, ... of molecular diagnosis in the accurate diagnosis of systemic carnitine deficiency. .... 'affecting protein function' by SIFT.

Stealth proteins: in silico identification of a novel protein family rendering bacterial pathogens invisible to host immune defense.

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Peter Sperisen

2005-11-01

Full Text Available There are a variety of bacterial defense strategies to survive in a hostile environment. Generation of extracellular polysaccharides has proved to be a simple but effective strategy against the host's innate immune system. A comparative genomics approach led us to identify a new protein family termed Stealth, most likely involved in the synthesis of extracellular polysaccharides. This protein family is characterized by a series of domains conserved across phylogeny from bacteria to eukaryotes. In bacteria, Stealth (previously characterized as SacB, XcbA, or WefC is encoded by subsets of strains mainly colonizing multicellular organisms, with evidence for a protective effect against the host innate immune defense. More specifically, integrating all the available information about Stealth proteins in bacteria, we propose that Stealth is a D-hexose-1-phosphoryl transferase involved in the synthesis of polysaccharides. In the animal kingdom, Stealth is strongly conserved across evolution from social amoebas to simple and complex multicellular organisms, such as Dictyostelium discoideum, hydra, and human. Based on the occurrence of Stealth in most Eukaryotes and a subset of Prokaryotes together with its potential role in extracellular polysaccharide synthesis, we propose that metazoan Stealth functions to regulate the innate immune system. Moreover, there is good reason to speculate that the acquisition and spread of Stealth could be responsible for future epidemic outbreaks of infectious diseases caused by a large variety of eubacterial pathogens. Our in silico identification of a homologous protein in the human host will help to elucidate the causes of Stealth-dependent virulence. At a more basic level, the characterization of the molecular and cellular function of Stealth proteins may shed light on fundamental mechanisms of innate immune defense against microbial invasion.

Stealth Proteins: In Silico Identification of a Novel Protein Family Rendering Bacterial Pathogens Invisible to Host Immune Defense.

Directory of Open Access Journals (Sweden)

2005-11-01

Full Text Available There are a variety of bacterial defense strategies to survive in a hostile environment. Generation of extracellular polysaccharides has proved to be a simple but effective strategy against the host's innate immune system. A comparative genomics approach led us to identify a new protein family termed Stealth, most likely involved in the synthesis of extracellular polysaccharides. This protein family is characterized by a series of domains conserved across phylogeny from bacteria to eukaryotes. In bacteria, Stealth (previously characterized as SacB, XcbA, or WefC is encoded by subsets of strains mainly colonizing multicellular organisms, with evidence for a protective effect against the host innate immune defense. More specifically, integrating all the available information about Stealth proteins in bacteria, we propose that Stealth is a D-hexose-1-phosphoryl transferase involved in the synthesis of polysaccharides. In the animal kingdom, Stealth is strongly conserved across evolution from social amoebas to simple and complex multicellular organisms, such as Dictyostelium discoideum, hydra, and human. Based on the occurrence of Stealth in most Eukaryotes and a subset of Prokaryotes together with its potential role in extracellular polysaccharide synthesis, we propose that metazoan Stealth functions to regulate the innate immune system. Moreover, there is good reason to speculate that the acquisition and spread of Stealth could be responsible for future epidemic outbreaks of infectious diseases caused by a large variety of eubacterial pathogens. Our in silico identification of a homologous protein in the human host will help to elucidate the causes of Stealth-dependent virulence. At a more basic level, the characterization of the molecular and cellular function of Stealth proteins may shed light on fundamental mechanisms of innate immune defense against microbial invasion.

Identification of TOEFAZ1-interacting proteins reveals key regulators of Trypanosoma brucei cytokinesis.

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Hilton, Nicholas A; Sladewski, Thomas E; Perry, Jenna A; Pataki, Zemplen; Sinclair-Davis, Amy N; Muniz, Richard S; Tran, Holly L; Wurster, Jenna I; Seo, Jiwon; de Graffenried, Christopher L

2018-05-21

The protist parasite Trypanosoma brucei is an obligate extracellular pathogen that retains its highly-polarized morphology during cell division and has evolved a novel cytokinetic process independent of non-muscle myosin II. The polo-like kinase homolog TbPLK is essential for transmission of cell polarity during division and for cytokinesis. We previously identified a putative TbPLK substrate named Tip of the Extending FAZ 1 (TOEFAZ1) as an essential kinetoplastid-specific component of the T. brucei cytokinetic machinery. We performed a proximity-dependent biotinylation (BioID) screen using TOEFAZ1 as a means to identify additional proteins that are involved in cytokinesis. Using quantitative proteomic methods, we identified nearly 500 TOEFAZ1-proximal proteins and characterized 59 in further detail. Among the candidates, we identified an essential putative phosphatase that regulates the expression level and localization of both TOEFAZ1 and TbPLK, a previously uncharacterized protein that is necessary for the assembly of a new cell posterior, and a microtubule plus-end directed orphan kinesin that is required for completing cleavage furrow ingression. The identification of these proteins provides new insight into T. brucei cytokinesis and establishes TOEFAZ1 as a key component of this essential and uniquely-configured process in kinetoplastids. This article is protected by copyright. All rights reserved. © 2018 John Wiley & Sons Ltd.

Biotic stress protein markers of Aquilaria sp. for gaharu species identification in Malaysia

International Nuclear Information System (INIS)

Azhar Mohamad; Abdul Rahim Harun

2012-01-01

Gaharu trees (Aquilaria) is in danger of extinction in the wild due to illegal logging. Its resin (Gaharu) is used for the production of highly valued incense throughout Asia. In Aquilaria sp. systemic induction of defense genes in response to mechanical wounding in nature is regulated by an 18-amino-acid peptide signal protein called systemin. This protein is produced in response to the natural stress at the vicinity of the wound and is also influenced by its genetic background. As the protein can be differentiated by its locality, the protein expressed is also found to be significantly different which, in turn, can be used for identification of this plant species. In this work, A. malaccensis and A. hirta were evaluated based on the targeted genes related to systemin. Targeted gene refers to specific sequence in genomic DNA. Sequence mining from public databases is part of the crucial process in getting the specific genes. The sequences will go through alignment step to identify conserved region prior to primer design. The primers were used in Polymerase Chain Reaction (PCR) techniques to amplify the conserved regions. It was found that both samples can be differentiated. This would be useful for plant breeders, trader and planter in ensuring authentic planting materials. This paper will describe the use of targeted genes primers as markers in identifying the Aquilaria species. (author)

Identification of Secretory Proteins in Mycobacterium tuberculosis Using Pseudo Amino Acid Composition

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Huan Yang

2016-01-01

Full Text Available Tuberculosis is killing millions of lives every year and on the blacklist of the most appalling public health problems. Recent findings suggest that secretory protein of Mycobacterium tuberculosis may serve the purpose of developing specific vaccines and drugs due to their antigenicity. Responding to global infectious disease, we focused on the identification of secretory proteins in Mycobacterium tuberculosis. A novel method called MycoSec was designed by incorporating g-gap dipeptide compositions into pseudo amino acid composition. Analysis of variance-based technique was applied in the process of feature selection and a total of 374 optimal features were obtained and used for constructing the final predicting model. In the jackknife test, MycoSec yielded a good performance with the area under the receiver operating characteristic curve of 0.93, demonstrating that the proposed system is powerful and robust. For user’s convenience, the web server MycoSec was established and an obliging manual on how to use it was provided for getting around any trouble unnecessary.

Identification of small peptides arising from hydrolysis of meat proteins in dry fermented sausages.

Science.gov (United States)

López, Constanza M; Bru, Elena; Vignolo, Graciela M; Fadda, Silvina G

2015-06-01

In this study, proteolysis and low molecular weight (LMW) peptides (<3kDa) from commercial Argentinean fermented sausages were characterized by applying a peptidomic approach. Protein profiles and peptides obtained by Tricine-SDS-PAGE and RP-HPLC-MS, respectively, allowed distinguishing two different types of fermented sausages, although no specific biomarkers relating to commercial brands or quality were recognized. From electrophoresis, α-actin, myoglobin, creatine kinase M-type and L-lactate dehydrogenase were degraded at different intensities. In addition, a partial characterization of fermented sausage peptidome through the identification of 36 peptides, in the range of 1000-2100 Da, arising from sarcoplasmic (28) and myofibrillar (8) proteins was achieved. These peptides had been originated from α-actin, myoglobin, and creatine kinase M-type, but also from the hydrolysis of other proteins not previously reported. Although muscle enzymes exerted a major role on peptidogenesis, microbial contribution cannot be excluded as it was postulated herein. This work represents a first peptidomic approach for fermented sausages, thereby providing a baseline to define key peptides acting as potential biomarkers. Copyright © 2015 Elsevier Ltd. All rights reserved.

Identification of S-glutathionylation sites in species-specific proteins by incorporating five sequence-derived features into the general pseudo-amino acid composition.

Science.gov (United States)

Zhao, Xiaowei; Ning, Qiao; Ai, Meiyue; Chai, Haiting; Yang, Guifu

2016-06-07

As a selective and reversible protein post-translational modification, S-glutathionylation generates mixed disulfides between glutathione (GSH) and cysteine residues, and plays an important role in regulating protein activity, stability, and redox regulation. To fully understand S-glutathionylation mechanisms, identification of substrates and specific S-Glutathionylated sites is crucial. Experimental identification of S-glutathionylated sites is labor-intensive and time consuming, so establishing an effective computational method is much desirable due to their convenient and fast speed. Therefore, in this study, a new bioinformatics tool named SSGlu (Species-Specific identification of Protein S-glutathionylation Sites) was developed to identify species-specific protein S-glutathionylated sites, utilizing support vector machines that combine multiple sequence-derived features with a two-step feature selection. By 5-fold cross validation, the performance of SSGlu was measured with an AUC of 0.8105 and 0.8041 for Homo sapiens and Mus musculus, respectively. Additionally, SSGlu was compared with the existing methods, and the higher MCC and AUC of SSGlu demonstrated that SSGlu was very promising to predict S-glutathionylated sites. Furthermore, a site-specific analysis showed that S-glutathionylation intimately correlated with the features derived from its surrounding sites. The conclusions derived from this study might help to understand more of the S-glutathionylation mechanism and guide the related experimental validation. For public access, SSGlu is freely accessible at http://59.73.198.144:8080/SSGlu/. Copyright © 2016 Elsevier Ltd. All rights reserved.

Protein identification from two-dimensional gel electrophoresis analysis of Klebsiella pneumoniae by combined use of mass spectrometry data and raw genome sequences

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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.

Identification of liver protein targets modified by tienilic acid metabolites using a two-dimensional Western blot-mass spectrometry approach

Science.gov (United States)

Methogo, Ruth Menque; Dansette, Patrick M.; Klarskov, Klaus

2007-12-01

A combined approach based on two-dimensional electrophoresis-immuno-blotting and nanoliquid chromatography coupled on-line with electrospray ionization mass spectrometry (nLC-MS/MS) was used to identify proteins modified by a reactive intermediate of tienilic acid (TA). Liver homogenates from rats exposed to TA were fractionated using ultra centrifugation; four fractions were obtained and subjected to 2D electrophoresis. Following transfer to PVDF membranes, modified proteins were visualized after India ink staining, using an anti-serum raised against TA and ECL detection. Immuno-reactive spots were localized on the PVDF membrane by superposition of the ECL image, protein spots of interest were excised, digested on the membrane with trypsin followed by nLC-MS/MS analysis and protein identification. A total of 15 proteins were identified as likely targets modified by a TA reactive metabolite. These include selenium binding protein 2, senescence marker protein SMP-30, adenosine kinase, Acy1 protein, adenosylhomocysteinase, capping protein (actin filament), protein disulfide isomerase, fumarylacetoacetase, arginase chain A, ketohexokinase, proteasome endopeptidase complex, triosephosphate isomerase, superoxide dismutase, dna-type molecular chaperone hsc73 and malate dehydrogenase.

Bacillus anthracis secretome time course under host-simulated conditions and identification of immunogenic proteins

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Whittington Jessica

2007-07-01

accumulation may be relevant in elucidation of the progression of pathogenicity, identification of therapeutics and diagnostic markers, and vaccine development. This study also adds to the continuously growing list of identified Bacillus anthracis secretome proteins.

Affinity purification combined with mass spectrometry to identify herpes simplex virus protein-protein interactions.

Science.gov (United States)

Meckes, David G

2014-01-01

The identification and characterization of herpes simplex virus protein interaction complexes are fundamental to understanding the molecular mechanisms governing the replication and pathogenesis of the virus. Recent advances in affinity-based methods, mass spectrometry configurations, and bioinformatics tools have greatly increased the quantity and quality of protein-protein interaction datasets. In this chapter, detailed and reliable methods that can easily be implemented are presented for the identification of protein-protein interactions using cryogenic cell lysis, affinity purification, trypsin digestion, and mass spectrometry.

Identification of Protein Complexes from Tandem Affinity Purification/Mass Spectrometry Data via Biased Random Walk.

Science.gov (United States)

Cai, Bingjing; Wang, Haiying; Zheng, Huiru; Wang, Hui

2015-01-01

Systematic identification of protein complexes from protein-protein interaction networks (PPIs) is an important application of data mining in life science. Over the past decades, various new clustering techniques have been developed based on modelling PPIs as binary relations. Non-binary information of co-complex relations (prey/bait) in PPIs data derived from tandem affinity purification/mass spectrometry (TAP-MS) experiments has been unfairly disregarded. In this paper, we propose a Biased Random Walk based algorithm for detecting protein complexes from TAP-MS data, resulting in the random walk with restarting baits (RWRB). RWRB is developed based on Random walk with restart. The main contribution of RWRB is the incorporation of co-complex relations in TAP-MS PPI networks into the clustering process, by implementing a new restarting strategy during the process of random walk. Through experimentation on un-weighted and weighted TAP-MS data sets, we validated biological significance of our results by mapping them to manually curated complexes. Results showed that, by incorporating non-binary, co-membership information, significant improvement has been achieved in terms of both statistical measurements and biological relevance. Better accuracy demonstrates that the proposed method outperformed several state-of-the-art clustering algorithms for the detection of protein complexes in TAP-MS data.

Evaluation of matrix-assisted laser desorption/ionization time of flight mass spectrometry for the identification of ceratopogonid and culicid larvae.

Science.gov (United States)

Steinmann, I C; Pflüger, V; Schaffner, F; Mathis, A; Kaufmann, C

2013-03-01

Matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) was evaluated for the rapid identification of ceratopogonid larvae. Optimal sample preparation as evaluated with laboratory-reared biting midges Culicoides nubeculosus was the homogenization of gut-less larvae in 10% formic acid, and analysis of 0.2 mg/ml crude protein homogenate mixed with SA matrix at a ratio of 1:1.5. Using 5 larvae each of 4 ceratopogonid species (C. nubeculosus, C. obsoletus, C. decor, and Dasyhelea sp.) and of 2 culicid species (Aedes aegypti, Ae. japonicus), biomarker mass sets between 27 and 33 masses were determined. In a validation study, 67 larvae belonging to the target species were correctly identified by automated database-based identification (91%) or manual full comparison (9%). Four specimens of non-target species did not yield identification. As anticipated for holometabolous insects, the biomarker mass sets of adults cannot be used for the identification of larvae, and vice versa, because they share only very few similar masses as shown for C. nubeculosus, C. obsoletus, and Ae. japonicus. Thus, protein profiling by MALDI-TOF as a quick, inexpensive and accurate alternative tool is applicable to identify insect larvae of vector species collected in the field.

Investigation of the utility of selective methyl protonation for determination of membrane protein structures

International Nuclear Information System (INIS)

Shih, Steve C. C.; Stoica, Ileana; Goto, Natalie K.

2008-01-01

Polytopic α-helical membrane proteins present one of the final frontiers for protein structural biology, with significant challenges causing severe under-representation in the protein structure databank. However, with the advent of hardware and methodology geared to the study of large molecular weight complexes, solution NMR is being increasingly considered as a tool for structural studies of these types of membrane proteins. One method that has the potential to facilitate these studies utilizes uniformly deuterated samples with protons reintroduced at one or two methyl groups of leucine, valine and isoleucine. In this work we demonstrate that in spite of the increased proportion of these amino acids in membrane proteins, the quality of structures that can be obtained from this strategy is similar to that obtained for all α-helical water soluble proteins. This is partly attributed to the observation that NOEs between residues within the transmembrane helix did not have an impact on structure quality. Instead the most important factors controlling structure accuracy were the strength of dihedral angle restraints imposed and the number of unique inter-helical pairs of residues constrained by NOEs. Overall these results suggest that the most accurate structures will arise from accurate identification of helical segments and utilization of inter-helical distance restraints from various sources to maximize the distribution of long-range restraints

Optimizing scoring function of protein-nucleic acid interactions with both affinity and specificity.

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Zhiqiang Yan

Full Text Available Protein-nucleic acid (protein-DNA and protein-RNA recognition is fundamental to the regulation of gene expression. Determination of the structures of the protein-nucleic acid recognition and insight into their interactions at molecular level are vital to understanding the regulation function. Recently, quantitative computational approach has been becoming an alternative of experimental technique for predicting the structures and interactions of biomolecular recognition. However, the progress of protein-nucleic acid structure prediction, especially protein-RNA, is far behind that of the protein-ligand and protein-protein structure predictions due to the lack of reliable and accurate scoring function for quantifying the protein-nucleic acid interactions. In this work, we developed an accurate scoring function (named as SPA-PN, SPecificity and Affinity of the Protein-Nucleic acid interactions for protein-nucleic acid interactions by incorporating both the specificity and affinity into the optimization strategy. Specificity and affinity are two requirements of highly efficient and specific biomolecular recognition. Previous quantitative descriptions of the biomolecular interactions considered the affinity, but often ignored the specificity owing to the challenge of specificity quantification. We applied our concept of intrinsic specificity to connect the conventional specificity, which circumvents the challenge of specificity quantification. In addition to the affinity optimization, we incorporated the quantified intrinsic specificity into the optimization strategy of SPA-PN. The testing results and comparisons with other scoring functions validated that SPA-PN performs well on both the prediction of binding affinity and identification of native conformation. In terms of its performance, SPA-PN can be widely used to predict the protein-nucleic acid structures and quantify their interactions.

Proteomic tools for environmental microbiology--a roadmap from sample preparation to protein identification and quantification.

Science.gov (United States)

Wöhlbrand, Lars; Trautwein, Kathleen; Rabus, Ralf

2013-10-01

The steadily increasing amount of (meta-)genomic sequence information of diverse organisms and habitats has a strong impact on research in microbial physiology and ecology. In-depth functional understanding of metabolic processes and overall physiological adaptation to environmental changes, however, requires application of proteomics, as the context specific proteome constitutes the true functional output of a cell. Considering the enormous structural and functional diversity of proteins, only rational combinations of various analytical approaches allow a holistic view on the overall state of the cell. Within the past decade, proteomic methods became increasingly accessible to microbiologists mainly due to the robustness of analytical methods (e.g. 2DE), and affordability of mass spectrometers and their relative ease of use. This review provides an overview on the complex portfolio of state-of-the-art proteomics and highlights the basic principles of key methods, ranging from sample preparation of laboratory or environmental samples, via protein/peptide separation (gel-based or gel-free) and different types of mass spectrometric protein/peptide analyses, to protein identification and abundance determination. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A novel strategy for global mapping of O-GlcNAc proteins and peptides using selective enzymatic deglycosylation, HILIC enrichment and mass spectrometry identification.

Science.gov (United States)

Shen, Bingquan; Zhang, Wanjun; Shi, Zhaomei; Tian, Fang; Deng, Yulin; Sun, Changqing; Wang, Guangshun; Qin, Weijie; Qian, Xiaohong

2017-07-01

O-GlcNAcylation is a kind of dynamic O-linked glycosylation of nucleocytoplasmic and mitochondrial proteins. It serves as a major nutrient sensor to regulate numerous biological processes including transcriptional regulation, cell metabolism, cellular signaling, and protein degradation. Dysregulation of cellular O-GlcNAcylated levels contributes to the etiologies of many diseases such as diabetes, neurodegenerative disease and cancer. However, deeper insight into the biological mechanism of O-GlcNAcylation is hampered by its extremely low stoichiometry and the lack of efficient enrichment approaches for large-scale identification by mass spectrometry. Herein, we developed a novel strategy for the global identification of O-GlcNAc proteins and peptides using selective enzymatic deglycosylation, HILIC enrichment and mass spectrometry analysis. Standard O-GlcNAc peptides can be efficiently enriched even in the presence of 500-fold more abundant non-O-GlcNAc peptides and identified by mass spectrometry with a low nanogram detection sensitivity. This strategy successfully achieved the first large-scale enrichment and characterization of O-GlcNAc proteins and peptides in human urine. A total of 474 O-GlcNAc peptides corresponding to 457 O-GlcNAc proteins were identified by mass spectrometry analysis, which is at least three times more than that obtained by commonly used enrichment methods. A large number of unreported O-GlcNAc proteins related to cell cycle, biological regulation, metabolic and developmental process were found in our data. The above results demonstrated that this novel strategy is highly efficient in the global enrichment and identification of O-GlcNAc peptides. These data provide new insights into the biological function of O-GlcNAcylation in human urine, which is correlated with the physiological states and pathological changes of human body and therefore indicate the potential of this strategy for biomarker discovery from human urine. Copyright �

Identification of Increased Amounts of Eppin Protein Complex Components in Sperm Cells of Diabetic and Obese Individuals by Difference Gel Electrophoresis*

Science.gov (United States)

Paasch, Uwe; Heidenreich, Falk; Pursche, Theresia; Kuhlisch, Eberhard; Kettner, Karina; Grunewald, Sonja; Kratzsch, Jürgen; Dittmar, Gunnar; Glander, Hans-Jürgen; Hoflack, Bernard; Kriegel, Thomas M.

2011-01-01

Metabolic disorders like diabetes mellitus and obesity may compromise the fertility of men and women. To unveil disease-associated proteomic changes potentially affecting male fertility, the proteomes of sperm cells from type-1 diabetic, type-2 diabetic, non-diabetic obese and clinically healthy individuals were comparatively analyzed by difference gel electrophoresis. The adaptation of a general protein extraction procedure to the solubilization of proteins from sperm cells allowed for the resolution of 3187 fluorescent spots in the difference gel electrophoresis image of the master gel, which contained the entirety of solubilized sperm proteins. Comparison of the pathological and reference proteomes by applying an average abundance ratio setting of 1.6 and a p ≤ 0.05 criterion resulted in the identification of 79 fluorescent spots containing proteins that were present at significantly changed levels in the sperm cells. Biometric evaluation of the fluorescence data followed by mass spectrometric protein identification revealed altered levels of 12, 71, and 13 protein species in the proteomes of the type-1 diabetic, type-2 diabetic, and non-diabetic obese patients, respectively, with considerably enhanced amounts of the same set of one molecular form of semenogelin-1, one form of clusterin, and two forms of lactotransferrin in each group of pathologic samples. Remarkably, β-galactosidase-1-like protein was the only protein that was detected at decreased levels in all three pathologic situations. The former three proteins are part of the eppin (epididymal proteinase inhibitor) protein complex, which is thought to fulfill fertilization-related functions, such as ejaculate sperm protection, motility regulation and gain of competence for acrosome reaction, whereas the putative role of the latter protein to function as a glycosyl hydrolase during sperm maturation remains to be explored at the protein/enzyme level. The strikingly similar differences detected in the

Cell-Free Expression and In Situ Immobilization of Parasite Proteins from Clonorchis sinensis for Rapid Identification of Antigenic Candidates.

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Christy Catherine

Full Text Available Progress towards genetic sequencing of human parasites has provided the groundwork for a post-genomic approach to develop novel antigens for the diagnosis and treatment of parasite infections. To fully utilize the genomic data, however, high-throughput methodologies are required for functional analysis of the proteins encoded in the genomic sequences. In this study, we investigated cell-free expression and in situ immobilization of parasite proteins as a novel platform for the discovery of antigenic proteins. PCR-amplified parasite DNA was immobilized on microbeads that were also functionalized to capture synthesized proteins. When the microbeads were incubated in a reaction mixture for cell-free synthesis, proteins expressed from the microbead-immobilized DNA were instantly immobilized on the same microbeads, providing a physical linkage between the genetic information and encoded proteins. This approach of in situ expression and isolation enables streamlined recovery and analysis of cell-free synthesized proteins and also allows facile identification of the genes coding antigenic proteins through direct PCR of the microbead-bound DNA.

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

Putative drug and vaccine target protein identification using comparative genomic analysis of KEGG annotated metabolic pathways of Mycoplasma hyopneumoniae.

Science.gov (United States)

Damte, Dereje; Suh, Joo-Won; Lee, Seung-Jin; Yohannes, Sileshi Belew; Hossain, Md Akil; Park, Seung-Chun

2013-07-01

In the present study, a computational comparative and subtractive genomic/proteomic analysis aimed at the identification of putative therapeutic target and vaccine candidate proteins from Kyoto Encyclopedia of Genes and Genomes (KEGG) annotated metabolic pathways of Mycoplasma hyopneumoniae was performed for drug design and vaccine production pipelines against M.hyopneumoniae. The employed comparative genomic and metabolic pathway analysis with a predefined computational systemic workflow extracted a total of 41 annotated metabolic pathways from KEGG among which five were unique to M. hyopneumoniae. A total of 234 proteins were identified to be involved in these metabolic pathways. Although 125 non homologous and predicted essential proteins were found from the total that could serve as potential drug targets and vaccine candidates, additional prioritizing parameters characterize 21 proteins as vaccine candidate while druggability of each of the identified proteins evaluated by the DrugBank database prioritized 42 proteins suitable for drug targets. Copyright © 2013 Elsevier Inc. All rights reserved.

Identification of Host Defense-Related Proteins Using Label-Free Quantitative Proteomic Analysis of Milk Whey from Cows with Staphylococcus aureus Subclinical Mastitis

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Shaimaa Abdelmegid

2017-12-01

Full Text Available Staphylococcus aureus is the most common contagious pathogen associated with bovine subclinical mastitis. Current diagnosis of S. aureus mastitis is based on bacteriological culture of milk samples and somatic cell counts, which lack either sensitivity or specificity. Identification of milk proteins that contribute to host defense and their variable responses to pathogenic stimuli would enable the characterization of putative biomarkers of subclinical mastitis. To accomplish this, milk whey samples from healthy and mastitic dairy cows were analyzed using a label-free quantitative proteomics approach. In total, 90 proteins were identified, of which 25 showed significant differential abundance between healthy and mastitic samples. In silico functional analyses indicated the involvement of the differentially abundant proteins in biological mechanisms and signaling pathways related to host defense including pathogen-recognition, direct antimicrobial function, and the acute-phase response. This proteomics and bioinformatics analysis not only facilitates the identification of putative biomarkers of S. aureus subclinical mastitis but also recapitulates previous findings demonstrating the abundance of host defense proteins in intramammary infection. All mass spectrometry data are available via ProteomeXchange with identifier PXD007516.

Efficient Isolation and Quantitative Proteomic Analysis of Cancer Cell Plasma Membrane Proteins for Identification of Metastasis-Associated Cell Surface Markers

DEFF Research Database (Denmark)

Lund, Rikke; Leth-Larsen, Rikke; Jensen, Ole N

2009-01-01

Cell surface membrane proteins are involved in central processes such as cell signaling, cell-cell interactions, ion and solute transport, and they seem to play a pivotal role in several steps of the metastatic process of cancer cells. The low abundance and hydrophobic nature of cell surface...... membrane proteins complicate their purification and identification by MS. We used two isogenic cell lines with opposite metastatic capabilities in nude mice to optimize cell surface membrane protein purification and to identify potential novel markers of metastatic cancer. The cell surface membrane...... proteins were isolated by centrifugation/ultracentrifugation steps, followed by membrane separation using a Percoll/sucrose density gradient. The gradient fractions containing the cell surface membrane proteins were identified by enzymatic assays. Stable isotope labeling of the proteome of the metastatic...

Decreasing the amount of trypsin in in-gel digestion leads to diminished chemical noise and improved protein identifications.

Science.gov (United States)

Hu, Mo; Liu, Yanhua; Yu, Kaiwen; Liu, Xiaoyun

2014-09-23

Pre-fractionation by gel electrophoresis is often combined with liquid chromatography-mass spectrometry (LC-MS) for large-scale profiling of complex protein samples. An essential component of this widely applied proteomic platform is in-gel protein digestion. In nearly two decades of practicing this approach, an extremely high level of trypsin has been utilized due to the consideration of slow enzyme diffusion into the gel matrix. Here we report that trypsin autolysis products contribute to the bulk of chemical noise in in-gel digestion and remarkably we found evidence that the amount of trypsin can be slashed by an order of magnitude with comparable digestion performance. By revising perhaps the most critical element of this decade-old digestion protocol, the proteomics community relying on gel separation prior to LC-MS analysis will benefit instantly from much lowered cost due to enzyme expenditure. More importantly, substantially reduced chemical noise (i.e., trypsin self-cleavage products) as a result of less enzyme usage translates into more protein identifications when limited amounts of samples are the interest of interrogation. In-gel digestion is one of the most widely used methods in proteomics. An exceedingly high level of trypsin has been utilized due to the consideration of slow enzyme diffusion into the gel matrix. This requirement has been faithfully kept in nearly two decades of practicing this approach. Here we report that trypsin concentration can be slashed by at least an order of magnitude while still providing comparable digestion performance. Thus the proteomics community relying on gel separation prior to LC-MS analysis will benefit instantly from much lowered enzyme cost. More importantly, substantially reduced chemical noise (i.e., trypsin autolysis products) due to less enzyme usage translates into ~30% more protein identifications when limited amounts of protein samples are analyzed. Copyright © 2014 Elsevier B.V. All rights reserved.

Disease candidate gene identification and prioritization using protein interaction networks

Directory of Open Access Journals (Sweden)

Aronow Bruce J

2009-02-01

Full Text Available Abstract Background Although most of the current disease candidate gene identification and prioritization methods depend on functional annotations, the coverage of the gene functional annotations is a limiting factor. In the current study, we describe a candidate gene prioritization method that is entirely based on protein-protein interaction network (PPIN analyses. Results For the first time, extended versions of the PageRank and HITS algorithms, and the K-Step Markov method are applied to prioritize disease candidate genes in a training-test schema. Using a list of known disease-related genes from our earlier study as a training set ("seeds", and the rest of the known genes as a test list, we perform large-scale cross validation to rank the candidate genes and also evaluate and compare the performance of our approach. Under appropriate settings – for example, a back probability of 0.3 for PageRank with Priors and HITS with Priors, and step size 6 for K-Step Markov method – the three methods achieved a comparable AUC value, suggesting a similar performance. Conclusion Even though network-based methods are generally not as effective as integrated functional annotation-based methods for disease candidate gene prioritization, in a one-to-one comparison, PPIN-based candidate gene prioritization performs better than all other gene features or annotations. Additionally, we demonstrate that methods used for studying both social and Web networks can be successfully used for disease candidate gene prioritization.

Evaluation of a simple protein extraction method for species identification of clinically relevant staphylococci by matrix-assisted laser desorption ionization-time of flight mass spectrometry.

Science.gov (United States)

Matsuda, Naoto; Matsuda, Mari; Notake, Shigeyuki; Yokokawa, Hirohide; Kawamura, Yoshiaki; Hiramatsu, Keiichi; Kikuchi, Ken

2012-12-01

In clinical microbiology, bacterial identification is labor-intensive and time-consuming. A solution for this problem is the use of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). In this study, we evaluated a modified protein extraction method of identification performed on target plates (on-plate extraction method) with MALDI-TOF (Bruker Microflex LT with Biotyper version 3.0) and compared it to 2 previously described methods: the direct colony method and a standard protein extraction method (standard extraction method). We evaluated the species of 273 clinical strains and 14 reference strains of staphylococci. All isolates were characterized using the superoxide dismutase A sequence as a reference. For the species identification, the on-plate, standard extraction, and direct colony methods identified 257 isolates (89.5%), 232 isolates (80.8%), and 173 isolates (60.2%), respectively, with statistically significant differences among the three methods (P extraction method is at least as good as standard extraction in identification rate and has the advantage of a shorter processing time.

Identification of Protein Pupylation Sites Using Bi-Profile Bayes Feature Extraction and Ensemble Learning

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Xiaowei Zhao

2013-01-01

Full Text Available Pupylation, one of the most important posttranslational modifications of proteins, typically takes place when prokaryotic ubiquitin-like protein (Pup is attached to specific lysine residues on a target protein. Identification of pupylation substrates and their corresponding sites will facilitate the understanding of the molecular mechanism of pupylation. Comparing with the labor-intensive and time-consuming experiment approaches, computational prediction of pupylation sites is much desirable for their convenience and fast speed. In this study, a new bioinformatics tool named EnsemblePup was developed that used an ensemble of support vector machine classifiers to predict pupylation sites. The highlight of EnsemblePup was to utilize the Bi-profile Bayes feature extraction as the encoding scheme. The performance of EnsemblePup was measured with a sensitivity of 79.49%, a specificity of 82.35%, an accuracy of 85.43%, and a Matthews correlation coefficient of 0.617 using the 5-fold cross validation on the training dataset. When compared with other existing methods on a benchmark dataset, the EnsemblePup provided better predictive performance, with a sensitivity of 80.00%, a specificity of 83.33%, an accuracy of 82.00%, and a Matthews correlation coefficient of 0.629. The experimental results suggested that EnsemblePup presented here might be useful to identify and annotate potential pupylation sites in proteins of interest. A web server for predicting pupylation sites was developed.

Computational identification of binding energy hot spots in protein-RNA complexes using an ensemble approach.

Science.gov (United States)

Pan, Yuliang; Wang, Zixiang; Zhan, Weihua; Deng, Lei

2018-05-01

Identifying RNA-binding residues, especially energetically favored hot spots, can provide valuable clues for understanding the mechanisms and functional importance of protein-RNA interactions. Yet, limited availability of experimentally recognized energy hot spots in protein-RNA crystal structures leads to the difficulties in developing empirical identification approaches. Computational prediction of RNA-binding hot spot residues is still in its infant stage. Here, we describe a computational method, PrabHot (Prediction of protein-RNA binding hot spots), that can effectively detect hot spot residues on protein-RNA binding interfaces using an ensemble of conceptually different machine learning classifiers. Residue interaction network features and new solvent exposure characteristics are combined together and selected for classification with the Boruta algorithm. In particular, two new reference datasets (benchmark and independent) have been generated containing 107 hot spots from 47 known protein-RNA complex structures. In 10-fold cross-validation on the training dataset, PrabHot achieves promising performances with an AUC score of 0.86 and a sensitivity of 0.78, which are significantly better than that of the pioneer RNA-binding hot spot prediction method HotSPRing. We also demonstrate the capability of our proposed method on the independent test dataset and gain a competitive advantage as a result. The PrabHot webserver is freely available at http://denglab.org/PrabHot/. leideng@csu.edu.cn. Supplementary data are available at Bioinformatics online.

On System Identification of Wind Turbines

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Perisic, Nevena; Pedersen, B.J.

Recently several methods have been proposed for the system identification of wind turbines which can be considered as a linear time-varying system due to the operating conditions. For the identification of linear wind turbine models, either black-box or grey-box identification can be used....... The operational model analysis (OMA) methodology can provide accurate estimates of the natural frequencies, damping ratios and mode shapes of the systems as long as the measurements have a low noise to signal ratio. However, in order to take information about the wind turbine into account a grey...

A Proteomic Approach for the Identification of Up-Regulated Proteins Involved in the Metabolic Process of the Leiomyoma.

Science.gov (United States)

Ura, Blendi; Scrimin, Federica; Arrigoni, Giorgio; Franchin, Cinzia; Monasta, Lorenzo; Ricci, Giuseppe

2016-04-09

Uterine leiomyoma is the most common benign smooth muscle cell tumor of the uterus. Proteomics is a powerful tool for the analysis of complex mixtures of proteins. In our study, we focused on proteins that were upregulated in the leiomyoma compared to the myometrium. Paired samples of eight leiomyomas and adjacent myometrium were obtained and submitted to two-dimensional gel electrophoresis (2-DE) and mass spectrometry for protein identification and to Western blotting for 2-DE data validation. The comparison between the patterns revealed 24 significantly upregulated (p leiomyoma and not with the normal myometrium. The overexpression of seven proteins involved in the metabolic processes of the leiomyoma was further validated by Western blotting and 2D Western blotting. Four of these proteins have never been associated with the leiomyoma before. The 2-DE approach coupled with mass spectrometry, which is among the methods of choice for comparative proteomic studies, identified a number of proteins overexpressed in the leiomyoma and involved in several biological processes, including metabolic processes. A better understanding of the mechanism underlying the overexpression of these proteins may be important for therapeutic purposes.

Substructure identification for shear structures: cross-power spectral density method

International Nuclear Information System (INIS)

Zhang, Dongyu; Johnson, Erik A

2012-01-01

In this paper, a substructure identification method for shear structures is proposed. A shear structure is divided into many small substructures; utilizing the dynamic equilibrium of a one-floor substructure, an inductive identification problem is formulated, using the cross-power spectral densities between structural floor accelerations and a reference response, to estimate the parameters of that one story. Repeating this procedure, all story parameters of the shear structure are identified from top to bottom recursively. An identification error analysis is performed for the proposed substructure method, revealing how uncertain factors (e.g. measurement noise) in the identification process affect the identification accuracy. According to the error analysis, a smart reference selection rule is designed to choose the optimal reference response that further enhances the identification accuracy. Moreover, based on the identification error analysis, explicit formulae are developed to calculate the variances of the parameter identification errors. A ten-story shear structure is used to illustrate the effectiveness of the proposed substructure method. The simulation results show that the method, combined with the reference selection rule, can very accurately identify structural parameters despite large measurement noise. Furthermore, the proposed formulae provide good predictions for the variances of the parameter identification errors, which are vital for providing accurate warnings of structural damage. (paper)

Identification of Surface Protein Biomarkers of Listeria monocytogenes via Bioinformatics and Antibody-Based Protein Detection Tools

Science.gov (United States)

Zhang, Cathy X. Y.; Brooks, Brian W.; Huang, Hongsheng; Pagotto, Franco

2016-01-01

ABSTRACT The Gram-positive bacterium Listeria monocytogenes causes a significant percentage of the fatalities among foodborne illnesses in humans. Surface proteins specifically expressed in a wide range of L. monocytogenes serotypes under selective enrichment culture conditions could serve as potential biomarkers for detection and isolation of this pathogen via antibody-based methods. Our study aimed to identify such biomarkers. Interrogation of the L. monocytogenes serotype 4b strain F2365 genome identified 130 putative or known surface proteins. The homologues of four surface proteins, LMOf2365_0578, LMOf2365_0581, LMOf2365_0639, and LMOf2365_2117, were assessed as biomarkers due to the presence of conserved regions among strains of L. monocytogenes which are variable among other Listeria species. Rabbit polyclonal antibodies against the four recombinant proteins revealed the expression of only LMOf2365_0639 on the surface of serotype 4b strain LI0521 cells despite PCR detection of mRNA transcripts for all four proteins in the organism. Three of 35 monoclonal antibodies (MAbs) to LMOf2365_0639, MAbs M3643, M3644, and M3651, specifically recognized 42 (91.3%) of 46 L. monocytogenes lineage I and II isolates grown in nonselective brain heart infusion medium. While M3644 and M3651 reacted with 14 to 15 (82.4 to 88.2%) of 17 L. monocytogenes lineage I and II isolates, M3643 reacted with 22 (91.7%) of 24 lineage I, II, and III isolates grown in selective enrichment media (UVM1, modified Fraser, Palcam, and UVM2 media). The three MAbs exhibited only weak reactivities (the optical densities at 414 nm were close to the cutoff value) to some other Listeria species grown in selective enrichment media. Collectively, the data indicate the potential of LMOf2365_0639 as a surface biomarker of L. monocytogenes, with the aid of specific MAbs, for pathogen detection, identification, and isolation in clinical, environmental, and food samples. IMPORTANCE L. monocytogenes is

pMD-Membrane: A Method for Ligand Binding Site Identification in Membrane-Bound Proteins.

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Priyanka Prakash

2015-10-01

Full Text Available Probe-based or mixed solvent molecular dynamics simulation is a useful approach for the identification and characterization of druggable sites in drug targets. However, thus far the method has been applied only to soluble proteins. A major reason for this is the potential effect of the probe molecules on membrane structure. We have developed a technique to overcome this limitation that entails modification of force field parameters to reduce a few pairwise non-bonded interactions between selected atoms of the probe molecules and bilayer lipids. We used the resulting technique, termed pMD-membrane, to identify allosteric ligand binding sites on the G12D and G13D oncogenic mutants of the K-Ras protein bound to a negatively charged lipid bilayer. In addition, we show that differences in probe occupancy can be used to quantify changes in the accessibility of druggable sites due to conformational changes induced by membrane binding or mutation.

Prioritizing disease candidate proteins in cardiomyopathy-specific protein-protein interaction networks based on "guilt by association" analysis.

Directory of Open Access Journals (Sweden)

Wan Li

Full Text Available The cardiomyopathies are a group of heart muscle diseases which can be inherited (familial. Identifying potential disease-related proteins is important to understand mechanisms of cardiomyopathies. Experimental identification of cardiomyophthies is costly and labour-intensive. In contrast, bioinformatics approach has a competitive advantage over experimental method. Based on "guilt by association" analysis, we prioritized candidate proteins involving in human cardiomyopathies. We first built weighted human cardiomyopathy-specific protein-protein interaction networks for three subtypes of cardiomyopathies using the known disease proteins from Online Mendelian Inheritance in Man as seeds. We then developed a method in prioritizing disease candidate proteins to rank candidate proteins in the network based on "guilt by association" analysis. It was found that most candidate proteins with high scores shared disease-related pathways with disease seed proteins. These top ranked candidate proteins were related with the corresponding disease subtypes, and were potential disease-related proteins. Cross-validation and comparison with other methods indicated that our approach could be used for the identification of potentially novel disease proteins, which may provide insights into cardiomyopathy-related mechanisms in a more comprehensive and integrated way.

Identification of Open Stomata1-Interacting Proteins Reveals Interactions with Sucrose Non-fermenting1-Related Protein Kinases2 and with Type 2A Protein Phosphatases That Function in Abscisic Acid Responses1[OPEN

Science.gov (United States)

Waadt, Rainer; Manalansan, Bianca; Rauniyar, Navin; Munemasa, Shintaro; Booker, Matthew A.; Brandt, Benjamin; Waadt, Christian; Nusinow, Dmitri A.; Kay, Steve A.; Kunz, Hans-Henning; Schumacher, Karin; DeLong, Alison; Yates, John R.; Schroeder, Julian I.

2015-01-01

The plant hormone abscisic acid (ABA) controls growth and development and regulates plant water status through an established signaling pathway. In the presence of ABA, pyrabactin resistance/regulatory component of ABA receptor proteins inhibit type 2C protein phosphatases (PP2Cs). This, in turn, enables the activation of Sucrose Nonfermenting1-Related Protein Kinases2 (SnRK2). Open Stomata1 (OST1)/SnRK2.6/SRK2E is a major SnRK2-type protein kinase responsible for mediating ABA responses. Arabidopsis (Arabidopsis thaliana) expressing an epitope-tagged OST1 in the recessive ost1-3 mutant background was used for the copurification and identification of OST1-interacting proteins after osmotic stress and ABA treatments. These analyses, which were confirmed using bimolecular fluorescence complementation and coimmunoprecipitation, unexpectedly revealed homo- and heteromerization of OST1 with SnRK2.2, SnRK2.3, OST1, and SnRK2.8. Furthermore, several OST1-complexed proteins were identified as type 2A protein phosphatase (PP2A) subunits and as proteins involved in lipid and galactolipid metabolism. More detailed analyses suggested an interaction network between ABA-activated SnRK2-type protein kinases and several PP2A-type protein phosphatase regulatory subunits. pp2a double mutants exhibited a reduced sensitivity to ABA during seed germination and stomatal closure and an enhanced ABA sensitivity in root growth regulation. These analyses add PP2A-type protein phosphatases as another class of protein phosphatases to the interaction network of SnRK2-type protein kinases. PMID:26175513

Rapid and Accurate Molecular Identification of the Emerging Multidrug-Resistant Pathogen Candida auris.

Science.gov (United States)

Kordalewska, Milena; Zhao, Yanan; Lockhart, Shawn R; Chowdhary, Anuradha; Berrio, Indira; Perlin, David S

2017-08-01

Candida auris is an emerging multidrug-resistant fungal pathogen causing nosocomial and invasive infections associated with high mortality. C. auris is commonly misidentified as several different yeast species by commercially available phenotypic identification platforms. Thus, there is an urgent need for a reliable diagnostic method. In this paper, we present fast, robust, easy-to-perform and interpret PCR and real-time PCR assays to identify C. auris and related species: Candida duobushaemulonii , Candida haemulonii , and Candida lusitaniae Targeting rDNA region nucleotide sequences, primers specific for C. auris only or C. auris and related species were designed. A panel of 140 clinical fungal isolates was used in both PCR and real-time PCR assays followed by electrophoresis or melting temperature analysis, respectively. The identification results from the assays were 100% concordant with DNA sequencing results. These molecular assays overcome the deficiencies of existing phenotypic tests to identify C. auris and related species. Copyright © 2017 Kordalewska et al.

MAGGIE Component 1: Identification and Purification of Native and Recombinant Multiprotein Complexes and Modified Proteins from Pyrococcus furiosus

Energy Technology Data Exchange (ETDEWEB)

Adams, Michael W. [University of Georgia; W. W. Adams, Michael

2014-01-07

Virtualy all cellular processes are carried out by dynamic molecular assemblies or multiprotein complexes (PCs), the composition of which is largely unknown. Structural genomics efforts have demonstrated that less than 25% of the genes in a given prokaryotic genome will yield stable, soluble proteins when expressed using a one-ORF-at-a-time approach. We proposed that much of the remaining 75% of the genes encode proteins that are part of multiprotein complexes or are modified post-translationally, for example, with metals. The problem is that PCs and metalloproteins (MPs) cannot be accurately predicted on a genome-wide scale. The only solution to this dilemma is to experimentally determine PCs and MPs in biomass of a model organism and to develop analytical tools that can then be applied to the biomass of any other organism. In other words, organisms themselves must be analyzed to identify their PCs and MPs: “native proteomes” must be determined. This information can then be utilized to design multiple ORF expression systems to produce recombinant forms of PCs and MPs. Moreover, the information and utility of this approach can be enhanced by using a hyperthermophile, one that grows optimally at 100°C, as a model organism. By analyzing the native proteome at close to 100 °C below the optimum growth temperature, we will trap reversible and dynamic complexes, thereby enabling their identification, purification, and subsequent characterization. The model organism for the current study is Pyrococcus furiosus, a hyperthermophilic archaeon that grows optimally at 100°C. It is grown up to 600-liter scale and kg quantities of biomass are available. In this project we identified native PCs and MPs using P. furiosus biomass (with MS/MS analyses to identify proteins by component 4). In addition, we provided samples of abundant native PCs and MPs for structural characterization (using SAXS by component 5). We also designed and evaluated generic bioinformatics and

Identification of membrane proteins by tandem mass spectrometry of protein ions

Science.gov (United States)

Carroll, Joe; Altman, Matthew C.; Fearnley, Ian M.; Walker, John E.

2007-01-01

The most common way of identifying proteins in proteomic analyses is to use short segments of sequence (“tags”) determined by mass spectrometric analysis of proteolytic fragments. The approach is effective with globular proteins and with membrane proteins with significant polar segments between membrane-spanning α-helices, but it is ineffective with other hydrophobic proteins where protease cleavage sites are either infrequent or absent. By developing methods to purify hydrophobic proteins in organic solvents and by fragmenting ions of these proteins by collision induced dissociation with argon, we have shown that partial sequences of many membrane proteins can be deduced easily by manual inspection. The spectra from small proteolipids (1–4 transmembrane α-helices) are dominated usually by fragment ions arising from internal amide cleavages, from which internal sequences can be obtained, whereas the spectra from larger membrane proteins (5–18 transmembrane α-helices) often contain fragment ions from N- and/or C-terminal parts yielding sequences in those regions. With these techniques, we have, for example, identified an abundant protein of unknown function from inner membranes of mitochondria that to our knowledge has escaped detection in proteomic studies, and we have produced sequences from 10 of 13 proteins encoded in mitochondrial DNA. They include the ND6 subunit of complex I, the last of its 45 subunits to be analyzed. The procedures have the potential to be developed further, for example by using newly introduced methods for protein ion dissociation to induce fragmentation of internal regions of large membrane proteins, which may remain partially folded in the gas phase. PMID:17720804

Retrival experience as an accurate indicator of person identification in line-ups

Directory of Open Access Journals (Sweden)

María José Contreras

2011-07-01

Full Text Available Responses in eyewitness identification of a person in a line-up may be based on two types of recovery experiences, remember and know experiences. Remember responses involve eyewitness identification of the target person as an episodic memory task, because it implies retrieving information about the target person in the place and at the time of the event. Know responses, in contrast, engage recognition based on familiarity or perceptual facilitation, that is, as a semantic memory task. To explore the relation between retrieval experiences and recognition accuracy, 86 participants took part in a recognition task with two conditions: one with an interpolated target absent line-up and the other only with the target present line-up. Accuracy of recognition and retrieval experience was measured. The results showed that, having previously participated in a target-absent line-up, increased omissions, while the number of hits decreased. Furthermore, participants’ know responses were associated to false recognition, whilst remember responses were associated to hits in recognition. Thus, asking eyewitnesses to inform about the kind of retrieval experience in which they based their recognition responses, may serve as a reliable indicator of accuracy in recognition. Future studies are needed to investigate whether this is also the case in natural settings.

[Study on the Identification of Geographical Indication Wuchang Rice Based on the Content of Inorganic Elements].

Science.gov (United States)

Li, Yong-le; Zheng, Yan-jie; Tang, Lu; Su, Zhi-yi; Xiong, Cen

2016-03-01

Wuchang rice is a geographical indication product in China. Due to its high quality and low production, the phenome- non of fake is more and more serious. An effective identification method of Wuchang rice is urgent needed, for the maintenance of its brand image and interest of consumers. Base on the content of inorganic elements which are analyzed by ICP-AES and ICP-MS in rice, the identification model of Wuchang rice is studied combining with principal component analysis (PCA), Fisher discrimination and artificial neural network (ANN) in this paper. The effect on the identification of samples is poor through PCA, while the samples from Wuchang area and other areas can be identified accurately through Fisher discrimination and ANN. The average accurate identification ratio of training and verification set through Fisher discrimination is 93.5%, while the average accurate identification ratio through ANN is 96.4%. The ability to identify of ANN is better than Fisher discrimination. Wuchang rice can be identified accurately through the result of this research which provides a technology for the protection of geographical indications of this product.

CPAD, Curated Protein Aggregation Database: A Repository of Manually Curated Experimental Data on Protein and Peptide Aggregation.

Science.gov (United States)

Thangakani, A Mary; Nagarajan, R; Kumar, Sandeep; Sakthivel, R; Velmurugan, D; Gromiha, M Michael

2016-01-01

Accurate distinction between peptide sequences that can form amyloid-fibrils or amorphous β-aggregates, identification of potential aggregation prone regions in proteins, and prediction of change in aggregation rate of a protein upon mutation(s) are critical to research on protein misfolding diseases, such as Alzheimer's and Parkinson's, as well as biotechnological production of protein based therapeutics. We have developed a Curated Protein Aggregation Database (CPAD), which has collected results from experimental studies performed by scientific community aimed at understanding protein/peptide aggregation. CPAD contains more than 2300 experimentally observed aggregation rates upon mutations in known amyloidogenic proteins. Each entry includes numerical values for the following parameters: change in rate of aggregation as measured by fluorescence intensity or turbidity, name and source of the protein, Uniprot and Protein Data Bank codes, single point as well as multiple mutations, and literature citation. The data in CPAD has been supplemented with five different types of additional information: (i) Amyloid fibril forming hexa-peptides, (ii) Amorphous β-aggregating hexa-peptides, (iii) Amyloid fibril forming peptides of different lengths, (iv) Amyloid fibril forming hexa-peptides whose crystal structures are available in the Protein Data Bank (PDB) and (v) Experimentally validated aggregation prone regions found in amyloidogenic proteins. Furthermore, CPAD is linked to other related databases and resources, such as Uniprot, Protein Data Bank, PUBMED, GAP, TANGO, WALTZ etc. We have set up a web interface with different search and display options so that users have the ability to get the data in multiple ways. CPAD is freely available at http://www.iitm.ac.in/bioinfo/CPAD/. The potential applications of CPAD have also been discussed.

Identification of a key structural element for protein folding within beta-hairpin turns.

Science.gov (United States)

Kim, Jaewon; Brych, Stephen R; Lee, Jihun; Logan, Timothy M; Blaber, Michael

2003-05-09

Specific residues in a polypeptide may be key contributors to the stability and foldability of the unique native structure. Identification and prediction of such residues is, therefore, an important area of investigation in solving the protein folding problem. Atypical main-chain conformations can help identify strains within a folded protein, and by inference, positions where unique amino acids may have a naturally high frequency of occurrence due to favorable contributions to stability and folding. Non-Gly residues located near the left-handed alpha-helical region (L-alpha) of the Ramachandran plot are a potential indicator of structural strain. Although many investigators have studied mutations at such positions, no consistent energetic or kinetic contributions to stability or folding have been elucidated. Here we report a study of the effects of Gly, Ala and Asn substitutions found within the L-alpha region at a characteristic position in defined beta-hairpin turns within human acidic fibroblast growth factor, and demonstrate consistent effects upon stability and folding kinetics. The thermodynamic and kinetic data are compared to available data for similar mutations in other proteins, with excellent agreement. The results have identified that Gly at the i+3 position within a subset of beta-hairpin turns is a key contributor towards increasing the rate of folding to the native state of the polypeptide while leaving the rate of unfolding largely unchanged.

Biosynthetically directed fractional 13C labeling facilitates identification of Phe and Tyr aromatic signals in proteins

International Nuclear Information System (INIS)

Jacob, Jaison; Louis, John M.; Nesheiwat, Issa; Torchia, Dennis A.

2002-01-01

Analysis of 2D [ 13 C, 1 H]-HSQC spectra of biosynthetic fractionally 13 C labeled proteins is a reliable, straightforward means to obtain stereospecific assignments of Val and Leu methyl sites in proteins. Herein we show that the same fractionally labeled protein sample facilitates observation and identification of Phe and Tyr aromatic signals. This is the case, in part, because the fractional 13 C labeling yields aromatic rings in which some of the 13 C- 13 C J-couplings, present in uniformly labeled samples, are absent. Also, the number of homonuclear J-coupling partners differs for the δ-, ε- and ζ-carbons. This enabled us to vary their signal intensities in distinctly different ways by appropriately setting the 13 C constant-time period in 2D [ 13 C, 1 H]-HSQC spectra. We illustrate the application of this approach to an 18 kDa protein, c-VIAF, a modulator of apoptosis. In addition, we show that cancellation of the aromatic 13 C CSA and 13 C- 1 H dipolar interactions can be fruitfully utilized in the case of the fractionally labeled sample to obtain high resolution 13 C constant-time spectra with good sensitivity

ContaMiner and ContaBase: a webserver and database for early identification of unwantedly crystallized protein contaminants

Science.gov (United States)

Hungler, Arnaud; Momin, Afaque; Diederichs, Kay; Arold, Stefan, T.

2016-01-01

Solving the phase problem in protein X-ray crystallography relies heavily on the identity of the crystallized protein, especially when molecular replacement (MR) methods are used. Yet, it is not uncommon that a contaminant crystallizes instead of the protein of interest. Such contaminants may be proteins from the expression host organism, protein fusion tags or proteins added during the purification steps. Many contaminants co-purify easily, crystallize and give good diffraction data. Identification of contaminant crystals may take time, since the presence of the contaminant is unexpected and its identity unknown. A webserver (ContaMiner) and a contaminant database (ContaBase) have been established, to allow fast MR-based screening of crystallographic data against currently 62 known contaminants. The web-based ContaMiner (available at http://strube.cbrc.kaust.edu.sa/contaminer/) currently produces results in 5 min to 4 h. The program is also available in a github repository and can be installed locally. ContaMiner enables screening of novel crystals at synchrotron beamlines, and it would be valuable as a routine safety check for ‘crystallization and preliminary X-ray analysis’ publications. Thus, in addition to potentially saving X-ray crystallographers much time and effort, ContaMiner might considerably lower the risk of publishing erroneous data. PMID:27980519

SPRED: A machine learning approach for the identification of classical and non-classical secretory proteins in mammalian genomes

Energy Technology Data Exchange (ETDEWEB)

Kandaswamy, Krishna Kumar [Institute for Neuro- and Bioinformatics, University of Luebeck, 23538 Luebeck (Germany); Graduate School for Computing in Medicine and Life Sciences, University of Luebeck, 23538 Luebeck (Germany); Pugalenthi, Ganesan [School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798 (Singapore); Hartmann, Enno; Kalies, Kai-Uwe [Centre for Structural and Cell Biology in Medicine, Institute of Biology, University of Luebeck, 23538 Luebeck (Germany); Moeller, Steffen [Institute for Neuro- and Bioinformatics, University of Luebeck, 23538 Luebeck (Germany); Suganthan, P.N. [School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798 (Singapore); Martinetz, Thomas, E-mail: martinetz@inb.uni-luebeck.de [Institute for Neuro- and Bioinformatics, University of Luebeck, 23538 Luebeck (Germany)

2010-01-15

Eukaryotic protein secretion generally occurs via the classical secretory pathway that traverses the ER and Golgi apparatus. Secreted proteins usually contain a signal sequence with all the essential information required to target them for secretion. However, some proteins like fibroblast growth factors (FGF-1, FGF-2), interleukins (IL-1 alpha, IL-1 beta), galectins and thioredoxin are exported by an alternative pathway. This is known as leaderless or non-classical secretion and works without a signal sequence. Most computational methods for the identification of secretory proteins use the signal peptide as indicator and are therefore not able to identify substrates of non-classical secretion. In this work, we report a random forest method, SPRED, to identify secretory proteins from protein sequences irrespective of N-terminal signal peptides, thus allowing also correct classification of non-classical secretory proteins. Training was performed on a dataset containing 600 extracellular proteins and 600 cytoplasmic and/or nuclear proteins. The algorithm was tested on 180 extracellular proteins and 1380 cytoplasmic and/or nuclear proteins. We obtained 85.92% accuracy from training and 82.18% accuracy from testing. Since SPRED does not use N-terminal signals, it can detect non-classical secreted proteins by filtering those secreted proteins with an N-terminal signal by using SignalP. SPRED predicted 15 out of 19 experimentally verified non-classical secretory proteins. By scanning the entire human proteome we identified 566 protein sequences potentially undergoing non-classical secretion. The dataset and standalone version of the SPRED software is available at (http://www.inb.uni-luebeck.de/tools-demos/spred/spred).

SPRED: A machine learning approach for the identification of classical and non-classical secretory proteins in mammalian genomes

International Nuclear Information System (INIS)

Kandaswamy, Krishna Kumar; Pugalenthi, Ganesan; Hartmann, Enno; Kalies, Kai-Uwe; Moeller, Steffen; Suganthan, P.N.; Martinetz, Thomas

2010-01-01

Eukaryotic protein secretion generally occurs via the classical secretory pathway that traverses the ER and Golgi apparatus. Secreted proteins usually contain a signal sequence with all the essential information required to target them for secretion. However, some proteins like fibroblast growth factors (FGF-1, FGF-2), interleukins (IL-1 alpha, IL-1 beta), galectins and thioredoxin are exported by an alternative pathway. This is known as leaderless or non-classical secretion and works without a signal sequence. Most computational methods for the identification of secretory proteins use the signal peptide as indicator and are therefore not able to identify substrates of non-classical secretion. In this work, we report a random forest method, SPRED, to identify secretory proteins from protein sequences irrespective of N-terminal signal peptides, thus allowing also correct classification of non-classical secretory proteins. Training was performed on a dataset containing 600 extracellular proteins and 600 cytoplasmic and/or nuclear proteins. The algorithm was tested on 180 extracellular proteins and 1380 cytoplasmic and/or nuclear proteins. We obtained 85.92% accuracy from training and 82.18% accuracy from testing. Since SPRED does not use N-terminal signals, it can detect non-classical secreted proteins by filtering those secreted proteins with an N-terminal signal by using SignalP. SPRED predicted 15 out of 19 experimentally verified non-classical secretory proteins. By scanning the entire human proteome we identified 566 protein sequences potentially undergoing non-classical secretion. The dataset and standalone version of the SPRED software is available at (http://www.inb.uni-luebeck.de/tools-demos/spred/spred).

Identification and quantification of protein S-nitrosation by nitrite in the mouse heart during ischemia.

Science.gov (United States)

Chouchani, Edward T; James, Andrew M; Methner, Carmen; Pell, Victoria R; Prime, Tracy A; Erickson, Brian K; Forkink, Marleen; Lau, Gigi Y; Bright, Thomas P; Menger, Katja E; Fearnley, Ian M; Krieg, Thomas; Murphy, Michael P

2017-09-01

Nitrate (NO 3 - ) and nitrite (NO 2 - ) are known to be cardioprotective and to alter energy metabolism in vivo NO 3 - action results from its conversion to NO 2 - by salivary bacteria, but the mechanism(s) by which NO 2 - affects metabolism remains obscure. NO 2 - may act by S -nitrosating protein thiols, thereby altering protein activity. But how this occurs, and the functional importance of S -nitrosation sites across the mammalian proteome, remain largely uncharacterized. Here we analyzed protein thiols within mouse hearts in vivo using quantitative proteomics to determine S -nitrosation site occupancy. We extended the thiol-redox proteomic technique, isotope-coded affinity tag labeling, to quantify the extent of NO 2 - -dependent S -nitrosation of proteins thiols in vivo Using this approach, called SNOxICAT ( S -nitrosothiol redox isotope-coded affinity tag), we found that exposure to NO 2 - under normoxic conditions or exposure to ischemia alone results in minimal S -nitrosation of protein thiols. However, exposure to NO 2 - in conjunction with ischemia led to extensive S -nitrosation of protein thiols across all cellular compartments. Several mitochondrial protein thiols exposed to the mitochondrial matrix were selectively S -nitrosated under these conditions, potentially contributing to the beneficial effects of NO 2 - on mitochondrial metabolism. The permeability of the mitochondrial inner membrane to HNO 2 , but not to NO 2 - , combined with the lack of S -nitrosation during anoxia alone or by NO 2 - during normoxia places constraints on how S -nitrosation occurs in vivo and on its mechanisms of cardioprotection and modulation of energy metabolism. Quantifying S -nitrosated protein thiols now allows determination of modified cysteines across the proteome and identification of those most likely responsible for the functional consequences of NO 2 - exposure. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Maternal serum protein profile and immune response protein subunits as markers for non-invasive prenatal diagnosis of trisomy 21, 18, and 13

KAUST Repository

Narasimhan, Kothandaraman

2013-02-01

Objectives: To use proteomics to identify and characterize proteins in maternal serum from patients at high-risk for fetal trisomy 21, trisomy 18, and trisomy 13 on the basis of ultrasound and maternal serum triple tests. Methods: We performed a comprehensive proteomic analysis on 23 trisomy cases and 85 normal cases during the early second trimester of pregnancy. Protein profiling along with conventional sodium dodecyl sulfate polyacrylamide gel electrophoresis/Tandem mass spectrometry analysis was carried out to characterize proteins associated with each trisomy condition and later validated using Western blot. Results: Protein profiling approach using surface enhanced laser desorption/ionization time-of-flight mass (SELDI-TOF/MS) spectrometry resulted in the identification of 37 unique hydrophobic proteomic features for three trisomy conditions. Using sodium dodecyl sulfate polyacrylamide gel electrophoresis followed by Matrix Assisted Laser Desorption Ionization - Time of Flight/Time of Flight (MALDI-TOF/TOF) and western blot, glyco proteins such as alpha-1-antitrypsin, apolipoprotein E, apolipoprotein H, and serum carrier protein transthyretin were identified as potential maternal serum markers for fetal trisomy condition. The identified proteins showed differential expression at the subunit level. Conclusions: Maternal serum protein profiling using proteomics may allow non-invasive diagnostic testing for the most common trisomies and may complement ultrasound-based methods to more accurately determine pregnancies with fetal aneuploidies. © 2013 John Wiley & Sons, Ltd.

Protein identification and quantification from riverbank grape, Vitis riparia: Comparing SDS-PAGE and FASP-GPF techniques for shotgun proteomic analysis.

Science.gov (United States)

George, Iniga S; Fennell, Anne Y; Haynes, Paul A

2015-09-01

Protein sample preparation optimisation is critical for establishing reproducible high throughput proteomic analysis. In this study, two different fractionation sample preparation techniques (in-gel digestion and in-solution digestion) for shotgun proteomics were used to quantitatively compare proteins identified in Vitis riparia leaf samples. The total number of proteins and peptides identified were compared between filter aided sample preparation (FASP) coupled with gas phase fractionation (GPF) and SDS-PAGE methods. There was a 24% increase in the total number of reproducibly identified proteins when FASP-GPF was used. FASP-GPF is more reproducible, less expensive and a better method than SDS-PAGE for shotgun proteomics of grapevine samples as it significantly increases protein identification across biological replicates. Total peptide and protein information from the two fractionation techniques is available in PRIDE with the identifier PXD001399 (http://proteomecentral.proteomexchange.org/dataset/PXD001399). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of an enzyme-linked-immunosorbent-assay technique for accurate identification of poorly preserved silks unearthed in ancient tombs.

Science.gov (United States)

Zheng, Qin; Wu, Xiaofeng; Zheng, Hailing; Zhou, Yang

2015-05-01

We report the preparation of a specific fibroin antibody and its use for the identification of unearthed ancient silk relics. Based on the 12-amino-acid repeat sequence "GAGAGSGAGAGS", which is found in fibroin of the silkworm Bombyx mori, a specific antibody against fibroin was prepared in rabbits through peptide synthesis and carrier-protein coupling. This antibody was highly specific for fibroin found in silk. Using this antibody we have successfully identified four silk samples from different time periods. Our results reveal, for the first time, a method capable of detecting silk from a few milligrams of archaeological fabric that has been buried for thousands of years, confirming that the ancient practice of wearing silk products while praying for rebirth dated back to at least 400 BCE. This method also complements current approaches in silk detection, especially for the characterization of poorly preserved silks, promoting the investigation of silk origins and of ancient clothing cultures.

LocateP: Genome-scale subcellular-location predictor for bacterial proteins

Directory of Open Access Journals (Sweden)

Zhou Miaomiao

2008-03-01

Full Text Available Abstract Background In the past decades, various protein subcellular-location (SCL predictors have been developed. Most of these predictors, like TMHMM 2.0, SignalP 3.0, PrediSi and Phobius, aim at the identification of one or a few SCLs, whereas others such as CELLO and Psortb.v.2.0 aim at a broader classification. Although these tools and pipelines can achieve a high precision in the accurate prediction of signal peptides and transmembrane helices, they have a much lower accuracy when other sequence characteristics are concerned. For instance, it proved notoriously difficult to identify the fate of proteins carrying a putative type I signal peptidase (SPIase cleavage site, as many of those proteins are retained in the cell membrane as N-terminally anchored membrane proteins. Moreover, most of the SCL classifiers are based on the classification of the Swiss-Prot database and consequently inherited the inconsistency of that SCL classification. As accurate and detailed SCL prediction on a genome scale is highly desired by experimental researchers, we decided to construct a new SCL prediction pipeline: LocateP. Results LocateP combines many of the existing high-precision SCL identifiers with our own newly developed identifiers for specific SCLs. The LocateP pipeline was designed such that it mimics protein targeting and secretion processes. It distinguishes 7 different SCLs within Gram-positive bacteria: intracellular, multi-transmembrane, N-terminally membrane anchored, C-terminally membrane anchored, lipid-anchored, LPxTG-type cell-wall anchored, and secreted/released proteins. Moreover, it distinguishes pathways for Sec- or Tat-dependent secretion and alternative secretion of bacteriocin-like proteins. The pipeline was tested on data sets extracted from literature, including experimental proteomics studies. The tests showed that LocateP performs as well as, or even slightly better than other SCL predictors for some locations and outperforms

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.

The Search Engine for Multi-Proteoform Complexes: An Online Tool for the Identification and Stoichiometry Determination of Protein Complexes.

Science.gov (United States)

Skinner, Owen S; Schachner, Luis F; Kelleher, Neil L

2016-12-08

Recent advances in top-down mass spectrometry using native electrospray now enable the analysis of intact protein complexes with relatively small sample amounts in an untargeted mode. Here, we describe how to characterize both homo- and heteropolymeric complexes with high molecular specificity using input data produced by tandem mass spectrometry of whole protein assemblies. The tool described is a "search engine for multi-proteoform complexes," (SEMPC) and is available for free online. The output is a list of candidate multi-proteoform complexes and scoring metrics, which are used to define a distinct set of one or more unique protein subunits, their overall stoichiometry in the intact complex, and their pre- and post-translational modifications. Thus, we present an approach for the identification and characterization of intact protein complexes from native mass spectrometry data. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Proteome analysis of barley seeds: Identification of major proteins from two-dimensional gels (pl 4-7)

DEFF Research Database (Denmark)

Østergaard, O.; Finnie, Christine; Laugesen, S.

2004-01-01

inhibitors), and proteins related to desiccation and oxidative stress. Sixty-four of the identifications were made using expressed sequence tags (ESTs). Numerous spots in the 2-D gel pattern changed during germination (micromalting) and an intensely stained area which contained large amounts of the serpin......Germination of monocotyledonous plants involves activation and de novo synthesis of enzymes that degrade cell walls and starch and mobilize stored endosperm reserves for embryo growth. Two-dimensional (2-D) gel electrophoresis and mass spectrometry were applied to identify major water...

Vulnerability Identification Errors in Security Risk Assessments

OpenAIRE

Taubenberger, Stefan

2014-01-01

At present, companies rely on information technology systems to achieve their business objectives, making them vulnerable to cybersecurity threats. Information security risk assessments help organisations to identify their risks and vulnerabilities. An accurate identification of risks and vulnerabilities is a challenge, because the input data is uncertain. So-called ’vulnerability identification errors‘ can occur if false positive vulnerabilities are identified, or if vulnerabilities remain u...

The human interactome knowledge base (hint-kb): An integrative human protein interaction database enriched with predicted protein–protein interaction scores using a novel hybrid technique

KAUST Repository

Theofilatos, Konstantinos A.

2013-07-12

Proteins are the functional components of many cellular processes and the identification of their physical protein–protein interactions (PPIs) is an area of mature academic research. Various databases have been developed containing information about experimentally and computationally detected human PPIs as well as their corresponding annotation data. However, these databases contain many false positive interactions, are partial and only a few of them incorporate data from various sources. To overcome these limitations, we have developed HINT-KB (http://biotools.ceid.upatras.gr/hint-kb/), a knowledge base that integrates data from various sources, provides a user-friendly interface for their retrieval, cal-culatesasetoffeaturesofinterest and computesaconfidence score for every candidate protein interaction. This confidence score is essential for filtering the false positive interactions which are present in existing databases, predicting new protein interactions and measuring the frequency of each true protein interaction. For this reason, a novel machine learning hybrid methodology, called (Evolutionary Kalman Mathematical Modelling—EvoKalMaModel), was used to achieve an accurate and interpretable scoring methodology. The experimental results indicated that the proposed scoring scheme outperforms existing computational methods for the prediction of PPIs.

Eyewitness Identification Accuracy and Response Latency: The Unruly 10-12-Second Rule

Science.gov (United States)

Weber, Nathan; Brewer, Neil; Wells, Gary L.; Semmler, Carolyn; Keast, Amber

2004-01-01

Data are reported from 3,213 research eyewitnesses confirming that accurate eyewitness identifications from lineups are made faster than are inaccurate identifications. However, consistent with predictions from the recognition and search literatures, the authors did not find support for the "10-12-s rule" in which lineup identifications faster…

Accurate and sensitive quantification of protein-DNA binding affinity.

Science.gov (United States)

Rastogi, Chaitanya; Rube, H Tomas; Kribelbauer, Judith F; Crocker, Justin; Loker, Ryan E; Martini, Gabriella D; Laptenko, Oleg; Freed-Pastor, William A; Prives, Carol; Stern, David L; Mann, Richard S; Bussemaker, Harmen J

2018-04-17

Transcription factors (TFs) control gene expression by binding to genomic DNA in a sequence-specific manner. Mutations in TF binding sites are increasingly found to be associated with human disease, yet we currently lack robust methods to predict these sites. Here, we developed a versatile maximum likelihood framework named No Read Left Behind (NRLB) that infers a biophysical model of protein-DNA recognition across the full affinity range from a library of in vitro selected DNA binding sites. NRLB predicts human Max homodimer binding in near-perfect agreement with existing low-throughput measurements. It can capture the specificity of the p53 tetramer and distinguish multiple binding modes within a single sample. Additionally, we confirm that newly identified low-affinity enhancer binding sites are functional in vivo, and that their contribution to gene expression matches their predicted affinity. Our results establish a powerful paradigm for identifying protein binding sites and interpreting gene regulatory sequences in eukaryotic genomes. Copyright © 2018 the Author(s). Published by PNAS.

Identification of similar regions of protein structures using integrated sequence and structure analysis tools

Directory of Open Access Journals (Sweden)

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

Identification of southern radio sources

International Nuclear Information System (INIS)

Savage, A.

1976-01-01

Identifications are suggested for 32 radio sources from the southern zones of the Parkes 2700 MHz survey, 18 with galaxies, one with a confirmed and 12 with possible quasistellar objects, and one with a supernova remnant in the Large Magellanic Cloud. The identifications were made from the ESO IIa-O quick blue survey plates, the SRC IIIa-J deep survey plates and the Palomar sky survey prints. Accurate optical positions have also been measured for 10 of the objects and for five previously suggested QSOs. (author)

Identification of the hemoglobin scavenger receptor/CD163 as a natural soluble protein in plasma

DEFF Research Database (Denmark)

Møller, Holger Jon; Peterslund, Niels Anker; Graversen, Jonas Heilskov

2002-01-01

enabled identification of a soluble plasma form of HbSR (sHbSR) having an electrophoretic mobility equal to that of recombinant HbSR consisting of the extracellular domain (scavenger receptor cysteine-rich 1-9). A sandwich enzyme-linked immunosorbent assay was established and used to measure the s...... a level of sHbSR above the range of healthy persons. Patients with myelomonocytic leukemias and pneumonia/sepsis exhibited the highest levels (up to 67.3 mg/L). In conclusion, sHbSR is an abundant plasma protein potentially valuable in monitoring patients with infections and myelomonocytic leukemia....

iTRAQ-Based Identification of Proteins Related to Muscle Growth in the Pacific Abalone, Haliotis discus hannai

Directory of Open Access Journals (Sweden)

Jianfang Huang

2017-10-01

Full Text Available The abalone Haliotis discus hannai is an important aquaculture species that is grown for human consumption. However, little is known of the genetic mechanisms governing muscle growth in this species, particularly with respect to proteomics. The isobaric tag for relative and absolute quantitation (iTRAQ method allows for sensitive and accurate protein quantification. Our study was the first to use iTRAQ-based quantitative proteomics to investigate muscle growth regulation in H. discus hannai. Among the 1904 proteins identified from six samples, 125 proteins were differentially expressed in large specimens of H. discus hannai as compared to small specimens. In the large specimens, 47 proteins were upregulated and 78 were downregulated. Many of the significant Kyoto Encyclopedia of Genes and Genomes (KEGG pathways, including these differentially expressed proteins, were closely related to muscle growth, including apoptosis, thyroid hormone signaling, regulation of the actin cytoskeleton, and viral myocarditis (p < 0.05. Our quantitative real-time polymerase chain reaction (qRT-PCR analyses suggested that the alterations in expression levels observed in the differentially expressed proteins were consistent with the alterations observed in the encoding mRNAs, indicating the repeatability of our proteomic approach. Our findings contribute to the knowledge of the molecular mechanisms of muscle growth in H. discus hannai.

A practical guide for the identification of membrane and plasma membrane proteins in human embryonic stem cells and human embryonal carcinoma cells.

NARCIS (Netherlands)

Dormeyer, W.; van Hoof, D.; Mummery, C.L.; Krijgsveld, J.; Heck, A.

2008-01-01

The identification of (plasma) membrane proteins in cells can provide valuable insights into the regulation of their biological processes. Pluripotent cells such as human embryonic stem cells and embryonal carcinoma cells are capable of unlimited self-renewal and share many of the biological

MZDASoft: a software architecture that enables large-scale comparison of protein expression levels over multiple samples based on liquid chromatography/tandem mass spectrometry.

Science.gov (United States)

Ghanat Bari, Mehrab; Ramirez, Nelson; Wang, Zhiwei; Zhang, Jianqiu Michelle

2015-10-15

Without accurate peak linking/alignment, only the expression levels of a small percentage of proteins can be compared across multiple samples in Liquid Chromatography/Mass Spectrometry/Tandem Mass Spectrometry (LC/MS/MS) due to the selective nature of tandem MS peptide identification. This greatly hampers biomedical research that aims at finding biomarkers for disease diagnosis, treatment, and the understanding of disease mechanisms. A recent algorithm, PeakLink, has allowed the accurate linking of LC/MS peaks without tandem MS identifications to their corresponding ones with identifications across multiple samples collected from different instruments, tissues and labs, which greatly enhanced the ability of comparing proteins. However, PeakLink cannot be implemented practically for large numbers of samples based on existing software architectures, because it requires access to peak elution profiles from multiple LC/MS/MS samples simultaneously. We propose a new architecture based on parallel processing, which extracts LC/MS peak features, and saves them in database files to enable the implementation of PeakLink for multiple samples. The software has been deployed in High-Performance Computing (HPC) environments. The core part of the software, MZDASoft Parallel Peak Extractor (PPE), can be downloaded with a user and developer's guide, and it can be run on HPC centers directly. The quantification applications, MZDASoft TandemQuant and MZDASoft PeakLink, are written in Matlab, which are compiled with a Matlab runtime compiler. A sample script that incorporates all necessary processing steps of MZDASoft for LC/MS/MS quantification in a parallel processing environment is available. The project webpage is http://compgenomics.utsa.edu/zgroup/MZDASoft. The proposed architecture enables the implementation of PeakLink for multiple samples. Significantly more (100%-500%) proteins can be compared over multiple samples with better quantification accuracy in test cases. MZDASoft

Autoimmunity to Tropomyosin-Specific Peptides Induced by Mycobacterium leprae in Leprosy Patients: Identification of Mimicking Proteins.

Science.gov (United States)

Singh, Itu; Yadav, Asha Ram; Mohanty, Keshar Kunja; Katoch, Kiran; Sharma, Prashant; Pathak, Vinay Kumar; Bisht, Deepa; Gupta, Umesh D; Sengupta, Utpal

2018-01-01

It has been shown earlier that there is a rise in the levels of autoantibodies and T cell response to cytoskeletal proteins in leprosy. Our group recently demonstrated a rise in both T and B cell responses to keratin and myelin basic protein in all types of leprosy patients and their associations in type 1 reaction (T1R) group of leprosy. In this study, we investigated the association of levels of autoantibodies and lymphoproliferation against myosin in leprosy patients across the spectrum and tried to find out the mimicking proteins or epitopes between host protein and protein/s of Mycobacterium leprae . One hundred and sixty-nine leprosy patients and 55 healthy controls (HC) were enrolled in the present study. Levels of anti-myosin antibodies and T-cell responses against myosin were measured by ELISA and lymphoproliferation assay, respectively. Using 2-D gel electrophoresis, western blot and MALDI-TOF/TOF antibody-reactive spots were identified. Three-dimensional structure of mimicking proteins was modeled by online server. B cell epitopes of the proteins were predicted by BCPREDS server 1.0 followed by identification of mimicking epitopes. Mice of inbred BALB/c strain were hyperimmunized with M. leprae soluble antigen (MLSA) and splenocytes and lymph node cells of these animals were adoptively transferred to naïve mice. Highest level of anti-myosin antibodies was noted in sera of T1R leprosy patients. We observed significantly higher levels of lymphoproliferative response ( p  leprae . We found four mimicking epitopes between these sequences. These data suggest that these mimicking proteins tropomyosin and ATP-dependent Clp protease ATP-binding subunit of M. leprae or more precisely mimicking epitopes (four B cell epitopes) might be responsible for extensive tissue damage during type1 reaction in leprosy.

PSI/TM-Coffee: a web server for fast and accurate multiple sequence alignments of regular and transmembrane proteins using homology extension on reduced databases.

Science.gov (United States)

Floden, Evan W; Tommaso, Paolo D; Chatzou, Maria; Magis, Cedrik; Notredame, Cedric; Chang, Jia-Ming

2016-07-08

The PSI/TM-Coffee web server performs multiple sequence alignment (MSA) of proteins by combining homology extension with a consistency based alignment approach. Homology extension is performed with Position Specific Iterative (PSI) BLAST searches against a choice of redundant and non-redundant databases. The main novelty of this server is to allow databases of reduced complexity to rapidly perform homology extension. This server also gives the possibility to use transmembrane proteins (TMPs) reference databases to allow even faster homology extension on this important category of proteins. Aside from an MSA, the server also outputs topological prediction of TMPs using the HMMTOP algorithm. Previous benchmarking of the method has shown this approach outperforms the most accurate alignment methods such as MSAProbs, Kalign, PROMALS, MAFFT, ProbCons and PRALINE™. The web server is available at http://tcoffee.crg.cat/tmcoffee. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identification of T1D susceptibility genes within the MHC region by combining protein interaction networks and SNP genotyping data

DEFF Research Database (Denmark)

Brorsson, C.; Hansen, Niclas Tue; Hansen, Kasper Lage

2009-01-01

genes. We have developed a novel method that combines single nucleotide polymorphism (SNP) genotyping data with protein-protein interaction (ppi) networks to identify disease-associated network modules enriched for proteins encoded from the MHC region. Approximately 2500 SNPs located in the 4 Mb MHC......To develop novel methods for identifying new genes that contribute to the risk of developing type 1 diabetes within the Major Histocompatibility Complex (MHC) region on chromosome 6, independently of the known linkage disequilibrium (LD) between human leucocyte antigen (HLA)-DRB1, -DQA1, -DQB1...... region were analysed in 1000 affected offspring trios generated by the Type 1 Diabetes Genetics Consortium (T1DGC). The most associated SNP in each gene was chosen and genes were mapped to ppi networks for identification of interaction partners. The association testing and resulting interacting protein...

Identification of protein tyrosine phosphatase 1B and casein as substrates for 124-v-Mos

Directory of Open Access Journals (Sweden)

Stabel Silvia

2002-04-01

Full Text Available Abstract Background The mos proto-oncogene encodes a cytoplasmic serine/threonine-specific protein kinase with crucial function during meiotic cell division in vertebrates. Based on oncogenic amino acid substitutions the viral derivative, 124-v-Mos, displays constitutive protein kinase activity and functions independent of unknown upstream effectors of mos protein kinase. We have utilized this property of 124-v-Mos and screened for novel mos substrates in immunocomplex kinase assays in vitro. Results We generated recombinant 124-v-Mos using the baculovirus expression system in Spodoptera frugiperda cells and demonstrated constitutive kinase activity by the ability of 124-v-Mos to auto-phosphorylate and to phosphorylate vimentin, a known substrate of c-Mos. Using this approach we analyzed a panel of acidic and basic substrates in immunocomplex protein kinase assays and identified novel in vitro substrates for 124-v-Mos, the protein tyrosine phosphatase 1B (PTP1B, alpha-casein and beta-casein. We controlled mos-specific phosphorylation of PTP1B and casein in comparative assays using a synthetic kinase-inactive 124-v-Mos mutant and further, tryptic digests of mos-phosphorylated beta-casein identified a phosphopeptide specifically targeted by wild-type 124-v-Mos. Two-dimensional phosphoamino acid analyses showed that 124-v-mos targets serine and threonine residues for phosphorylation in casein at a 1:1 ratio but auto-phosphorylation occurs predominantly on serine residues. Conclusion The mos substrates identified in this study represent a basis to approach the identification of the mos-consensus phosphorylation motif, important for the development of specific inhibitors of the Mos protein kinase.

Protein identification by peptide mass fingerprinting

DEFF Research Database (Denmark)

Hjernø, Karin

2007-01-01

  Peptide mass fingerprinting is an effective way of identifying, e.g., gel-separated proteins, by matching experimentally obtained peptide mass data against large databases. However, several factors are known to influence the quality of the resulting matches, such as proteins contaminating the s...

Detecting protein-protein interactions in the intact cell of Bacillus subtilis (ATCC 6633).

Science.gov (United States)

Winters, Michael S; Day, R A

2003-07-01

The salt bridge, paired group-specific reagent cyanogen (ethanedinitrile; C(2)N(2)) converts naturally occurring pairs of functional groups into covalently linked products. Cyanogen readily permeates cell walls and membranes. When the paired groups are shared between associated proteins, isolation of the covalently linked proteins allows their identity to be assigned. Examination of organisms of known genome sequence permits identification of the linked proteins by mass spectrometric techniques applied to peptides derived from them. The cyanogen-linked proteins were isolated by polyacrylamide gel electrophoresis. Digestion of the isolated proteins with proteases of known specificity afforded sets of peptides that could be analyzed by mass spectrometry. These data were compared with those derived theoretically from the Swiss Protein Database by computer-based comparisons (Protein Prospector; http://prospector.ucsf.edu). Identification of associated proteins in the ribosome of Bacillus subtilis strain ATCC 6633 showed that there is an association homology with the association patterns of the ribosomal proteins of Haloarcula marismortui and Thermus thermophilus. In addition, other proteins involved in protein biosynthesis were shown to be associated with ribosomal proteins.

Identification of unknown protein complex members by radiolocalization and analysis of low-abundance complexes resolved using native polyacrylamide gel electrophoresis.

Science.gov (United States)

Bose, Mahuya; Adams, Brian P; Whittal, Randy M; Bose, Himangshu S

2008-02-01

Identification of unknown binding partners of a protein of interest can be a difficult process. Current strategies to determine protein binding partners result in a high amount of false-positives, requiring use of several different methods to confirm the accuracy of the apparent association. We have developed and utilized a method that is reliable and easily substantiated. Complexes are isolated from cell extract after exposure to the radiolabeled protein of interest, followed by resolution on a native polyacrylamide gel. Native conformations are preserved, allowing the complex members to maintain associations. By radiolabeling the protein of interest, the complex can be easily identified at detection levels below the threshold of Serva Blue, Coomassie, and silver stains. The visualized radioactive band is analyzed by MS to identify binding partners, which can be subsequently verified by antibody shift and immunoprecipitation of the complex. By using this method we have successfully identified binding partners of two proteins that reside in different locations of a cellular organelle.

Identification of StARD3 as a Lutein-binding Protein in the Macula of the Primate Retina†

Science.gov (United States)

Li, Binxing; Vachali, Preejith; Frederick, Jeanne M.; Bernstein, Paul S.

2011-01-01

Lutein, zeaxanthin and their metabolites are the xanthophyll carotenoids that form the macular pigment of the human retina. Epidemiological evidence suggests that high levels of these carotenoids in the diet, serum and macula are associated with decreased risk of age-related macular degeneration (AMD), and the AREDS2 study is prospectively testing this hypothesis. Understanding the biochemical mechanisms underlying the selective uptakes of lutein and zeaxanthin into the human macula may provide important insights into the physiology of the human macula in health and disease. GSTP1 is the macular zeaxanthin-binding protein, but the identity of the human macular lutein-binding protein has remained elusive. Prior identification of the silkworm lutein-binding protein (CBP) as a member of the steroidogenic acute regulatory domain (StARD) protein family, and selective labeling of monkey photoreceptor inner segments by anti-CBP antibody provided an important clue toward identifying the primate retina lutein-binding protein. Homology of CBP to all 15 human StARD proteins was analyzed using database searches, western blotting and immunohistochemistry, and we here provide evidence to identify StARD3 (also known as MLN64) as a human retinal lutein-binding protein. Further, recombinant StARD3 selectively binds lutein with high affinity (KD = 0.45 micromolar) when assessed by surface plasmon resonance (SPR) binding assays. Our results demonstrate previously unrecognized, specific interactions of StARD3 with lutein and provide novel avenues to explore its roles in human macular physiology and disease. PMID:21322544

Identification of RNAIII-binding proteins in Staphylococcus aureus using tethered RNAs and streptavidin aptamers based pull-down assay.

Science.gov (United States)

Zhang, Xu; Zhu, Qing; Tian, Tian; Zhao, Changlong; Zang, Jianye; Xue, Ting; Sun, Baolin

2015-05-15

It has been widely recognized that small RNAs (sRNAs) play important roles in physiology and virulence control in bacteria. In Staphylococcus aureus, many sRNAs have been identified and some of them have been functionally studied. Since it is difficult to identify RNA-binding proteins (RBPs), very little has been known about the RBPs in S. aureus, especially those associated with sRNAs. Here we adopted a tRNA scaffold streptavidin aptamer based pull-down assay to identify RBPs in S. aureus. The tethered RNA was successfully captured by the streptavidin magnetic beads, and proteins binding to RNAIII were isolated and analyzed by mass spectrometry. We have identified 81 proteins, and expressed heterologously 9 of them in Escherichia coli. The binding ability of the recombinant proteins with RNAIII was further analyzed by electrophoresis mobility shift assay, and the result indicates that proteins CshA, RNase J2, Era, Hu, WalR, Pyk, and FtsZ can bind to RNAIII. This study suggests that some proteins can bind to RNA III in S. aureus, and may be involved in RNA III function. And tRSA based pull-down assay is an effective method to search for RBPs in bacteria, which should facilitate the identification and functional study of RBPs in diverse bacterial species.

Purification and Identification of Membrane Proteins from Urinary Extracellular Vesicles using Triton X-114 Phase Partitioning.

Science.gov (United States)

Hu, Shuiwang; Musante, Luca; Tataruch, Dorota; Xu, Xiaomeng; Kretz, Oliver; Henry, Michael; Meleady, Paula; Luo, Haihua; Zou, Hequn; Jiang, Yong; Holthofer, Harry

2018-01-05

Urinary extracellular vesicles (uEVs) have become a promising source for biomarkers accurately reflecting biochemical changes in kidney and urogenital diseases. Characteristically, uEVs are rich in membrane proteins associated with several cellular functions like adhesion, transport, and signaling. Hence, membrane proteins of uEVs should represent an exciting protein class with unique biological properties. In this study, we utilized uEVs to optimize the Triton X-114 detergent partitioning protocol targeted for membrane proteins and proceeded to their subsequent characterization while eliminating effects of Tamm-Horsfall protein, the most abundant interfering protein in urine. This is the first report aiming to enrich and characterize the integral transmembrane proteins present in human urinary vesicles. First, uEVs were enriched using a "hydrostatic filtration dialysis'' appliance, and then the enriched uEVs and lysates were verified by transmission electron microscopy. After using Triton X-114 phase partitioning, we generated an insoluble pellet fraction and aqueous phase (AP) and detergent phase (DP) fractions and analyzed them with LC-MS/MS. Both in- and off-gel protein digestion methods were used to reveal an increased number of membrane proteins of uEVs. After comparing with the identified proteins without phase separation as in our earlier publication, 199 different proteins were detected in DP. Prediction of transmembrane domains (TMDs) from these protein fractions showed that DP had more TMDs than other groups. The analyses of hydrophobicity revealed that the GRAVY score of DP was much higher than those of the other fractions. Furthermore, the analysis of proteins with lipid anchor revealed that DP proteins had more lipid anchors than other fractions. Additionally, KEGG pathway analysis showed that the DP proteins detected participate in endocytosis and signaling, which is consistent with the expected biological functions of membrane proteins. Finally

Elevated pressure improves the extraction and identification of proteins recovered from formalin-fixed, paraffin-embedded tissue surrogates.

Directory of Open Access Journals (Sweden)

Carol B Fowler

2010-12-01

Full Text Available Proteomic studies of formalin-fixed paraffin-embedded (FFPE tissues are frustrated by the inability to extract proteins from archival tissue in a form suitable for analysis by 2-D gel electrophoresis or mass spectrometry. This inability arises from the difficulty of reversing formaldehyde-induced protein adducts and cross-links within FFPE tissues. We previously reported the use of elevated hydrostatic pressure as a method for efficient protein recovery from a hen egg-white lysozyme tissue surrogate, a model system developed to study formalin fixation and histochemical processing.In this study, we demonstrate the utility of elevated hydrostatic pressure as a method for efficient protein recovery from FFPE mouse liver tissue and a complex multi-protein FFPE tissue surrogate comprised of hen egg-white lysozyme, bovine carbonic anhydrase, bovine ribonuclease A, bovine serum albumin, and equine myoglobin (55∶15∶15∶10∶5 wt%. Mass spectrometry of the FFPE tissue surrogates retrieved under elevated pressure showed that both the low and high-abundance proteins were identified with sequence coverage comparable to that of the surrogate mixture prior to formaldehyde treatment. In contrast, non-pressure-extracted tissue surrogate samples yielded few positive and many false peptide identifications. Studies with soluble formalin-treated bovine ribonuclease A demonstrated that pressure modestly inhibited the rate of reversal (hydrolysis of formaldehyde-induced protein cross-links. Dynamic light scattering studies suggest that elevated hydrostatic pressure and heat facilitate the recovery of proteins free of formaldehyde adducts and cross-links by promoting protein unfolding and hydration with a concomitant reduction in the average size of the protein aggregates.These studies demonstrate that elevated hydrostatic pressure treatment is a promising approach for improving the recovery of proteins from FFPE tissues in a form suitable for proteomic analysis.

Elevated Pressure Improves the Extraction and Identification of Proteins Recovered from Formalin-Fixed, Paraffin-Embedded Tissue Surrogates

Science.gov (United States)

Fowler, Carol B.; Chesnick, Ingrid E.; Moore, Cedric D.; O'Leary, Timothy J.; Mason, Jeffrey T.

2010-01-01

Background Proteomic studies of formalin-fixed paraffin-embedded (FFPE) tissues are frustrated by the inability to extract proteins from archival tissue in a form suitable for analysis by 2-D gel electrophoresis or mass spectrometry. This inability arises from the difficulty of reversing formaldehyde-induced protein adducts and cross-links within FFPE tissues. We previously reported the use of elevated hydrostatic pressure as a method for efficient protein recovery from a hen egg-white lysozyme tissue surrogate, a model system developed to study formalin fixation and histochemical processing. Principal Findings In this study, we demonstrate the utility of elevated hydrostatic pressure as a method for efficient protein recovery from FFPE mouse liver tissue and a complex multi-protein FFPE tissue surrogate comprised of hen egg-white lysozyme, bovine carbonic anhydrase, bovine ribonuclease A, bovine serum albumin, and equine myoglobin (55∶15∶15∶10∶5 wt%). Mass spectrometry of the FFPE tissue surrogates retrieved under elevated pressure showed that both the low and high-abundance proteins were identified with sequence coverage comparable to that of the surrogate mixture prior to formaldehyde treatment. In contrast, non-pressure-extracted tissue surrogate samples yielded few positive and many false peptide identifications. Studies with soluble formalin-treated bovine ribonuclease A demonstrated that pressure modestly inhibited the rate of reversal (hydrolysis) of formaldehyde-induced protein cross-links. Dynamic light scattering studies suggest that elevated hydrostatic pressure and heat facilitate the recovery of proteins free of formaldehyde adducts and cross-links by promoting protein unfolding and hydration with a concomitant reduction in the average size of the protein aggregates. Conclusions These studies demonstrate that elevated hydrostatic pressure treatment is a promising approach for improving the recovery of proteins from FFPE tissues in a form

On-line signal trend identification

International Nuclear Information System (INIS)

Tambouratzis, T.; Antonopoulos-Domis, M.

2004-01-01

An artificial neural network, based on the self-organizing map, is proposed for on-line signal trend identification. Trends are categorized at each incoming signal as steady-state, increasing and decreasing, while they are further classified according to characteristics such signal shape and rate of change. Tests with model-generated signals illustrate the ability of the self-organizing map to accurately and reliably perform on-line trend identification in terms of both detection and classification. The proposed methodology has been found robust to the presence of white noise

A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces

NARCIS (Netherlands)

Melo, Rita; Fieldhouse, Robert; Melo, André; Correia, João D G; Cordeiro, Maria Natália D S; Gümüş, Zeynep H; Costa, Joaquim; Bonvin, Alexandre M J J; de Sousa Moreira, Irina

2016-01-01

Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS) in protein-protein interfaces from their native complex structure compared to previous published Machine Learning (ML) techniques. Our model

Identification of proteins similar to AvrE type III effector proteins from ...

African Journals Online (AJOL)

Type III effector proteins are injected into host cells through type III secretion systems. Some effectors are similar to host proteins to promote pathogenicity, while others lead to the activation of disease resistance. We used partial least squares alignment-free bioinformatics methods to identify proteins similar to AvrE proteins ...

Proteomics: Protein Identification Using Online Databases

Science.gov (United States)

Eurich, Chris; Fields, Peter A.; Rice, Elizabeth

2012-01-01

Proteomics is an emerging area of systems biology that allows simultaneous study of thousands of proteins expressed in cells, tissues, or whole organisms. We have developed this activity to enable high school or college students to explore proteomic databases using mass spectrometry data files generated from yeast proteins in a college laboratory…

Sequence Based Prediction of Antioxidant Proteins Using a Classifier Selection Strategy.

Directory of Open Access Journals (Sweden)

Lina Zhang

Full Text Available Antioxidant proteins perform significant functions in maintaining oxidation/antioxidation balance and have potential therapies for some diseases. Accurate identification of antioxidant proteins could contribute to revealing physiological processes of oxidation/antioxidation balance and developing novel antioxidation-based drugs. In this study, an ensemble method is presented to predict antioxidant proteins with hybrid features, incorporating SSI (Secondary Structure Information, PSSM (Position Specific Scoring Matrix, RSA (Relative Solvent Accessibility, and CTD (Composition, Transition, Distribution. The prediction results of the ensemble predictor are determined by an average of prediction results of multiple base classifiers. Based on a classifier selection strategy, we obtain an optimal ensemble classifier composed of RF (Random Forest, SMO (Sequential Minimal Optimization, NNA (Nearest Neighbor Algorithm, and J48 with an accuracy of 0.925. A Relief combined with IFS (Incremental Feature Selection method is adopted to obtain optimal features from hybrid features. With the optimal features, the ensemble method achieves improved performance with a sensitivity of 0.95, a specificity of 0.93, an accuracy of 0.94, and an MCC (Matthew's Correlation Coefficient of 0.880, far better than the existing method. To evaluate the prediction performance objectively, the proposed method is compared with existing methods on the same independent testing dataset. Encouragingly, our method performs better than previous studies. In addition, our method achieves more balanced performance with a sensitivity of 0.878 and a specificity of 0.860. These results suggest that the proposed ensemble method can be a potential candidate for antioxidant protein prediction. For public access, we develop a user-friendly web server for antioxidant protein identification that is freely accessible at http://antioxidant.weka.cc.

Identification of FUSE-binding proteins as interacting partners of TIA proteins

International Nuclear Information System (INIS)

Rothe, Francoise; Gueydan, Cyril; Bellefroid, Eric; Huez, Georges; Kruys, Veronique

2006-01-01

TIA-1 and TIAR are closely related RNA-binding proteins involved in several mechanisms of RNA metabolism, including alternative hnRNA splicing and mRNA translation regulation. In particular, TIA-1 represses tumor necrosis factor (TNF) mRNA translation by binding to the AU-rich element (ARE) present in the mRNA 3' untranslated region. Here, we demonstrate that TIA proteins interact with FUSE-binding proteins (FBPs) and that fbp genes are co-expressed with tia genes during Xenopus embryogenesis. FBPs participate in various steps of RNA processing and degradation. In Cos cells, FBPs co-localize with TIA proteins in the nucleus and migrate into TIA-enriched cytoplasmic granules upon oxidative stress. Overexpression of FBP2-KH3 RNA-binding domain fused to EGFP induces the specific sequestration of TIA proteins in cytoplasmic foci, thereby precluding their nuclear accumulation. In cytosolic RAW 264.7 macrophage extracts, FBPs are found associated in EMSA to the TIA-1/TNF-ARE complex. Together, our results indicate that TIA and FBP proteins may thus be relevant biological involved in common events of RNA metabolism occurring both in the nucleus and the cytoplasm

A unique charge-coupled device/xenon arc lamp based imaging system for the accurate detection and quantitation of multicolour fluorescence.

Science.gov (United States)

Spibey, C A; Jackson, P; Herick, K

2001-03-01

In recent years the use of fluorescent dyes in biological applications has dramatically increased. The continual improvement in the capabilities of these fluorescent dyes demands increasingly sensitive detection systems that provide accurate quantitation over a wide linear dynamic range. In the field of proteomics, the detection, quantitation and identification of very low abundance proteins are of extreme importance in understanding cellular processes. Therefore, the instrumentation used to acquire an image of such samples, for spot picking and identification by mass spectrometry, must be sensitive enough to be able, not only, to maximise the sensitivity and dynamic range of the staining dyes but, as importantly, adapt to the ever changing portfolio of fluorescent dyes as they become available. Just as the available fluorescent probes are improving and evolving so are the users application requirements. Therefore, the instrumentation chosen must be flexible to address and adapt to those changing needs. As a result, a highly competitive market for the supply and production of such dyes and the instrumentation for their detection and quantitation have emerged. The instrumentation currently available is based on either laser/photomultiplier tube (PMT) scanning or lamp/charge-coupled device (CCD) based mechanisms. This review briefly discusses the advantages and disadvantages of both System types for fluorescence imaging, gives a technical overview of CCD technology and describes in detail a unique xenon/are lamp CCD based instrument, from PerkinElmer Life Sciences. The Wallac-1442 ARTHUR is unique in its ability to scan both large areas at high resolution and give accurate selectable excitation over the whole of the UV/visible range. It operates by filtering both the excitation and emission wavelengths, providing optimal and accurate measurement and quantitation of virtually any available dye and allows excellent spectral resolution between different fluorophores

A method for investigating protein-protein interactions related to Salmonella typhimurium pathogenesis

Energy Technology Data Exchange (ETDEWEB)

Chowdhury, Saiful M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Shi, Liang [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Yoon, Hyunjin [Dartmouth College, Hanover, NH (United States); Ansong, Charles [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Rommereim, Leah M. [Dartmouth College, Hanover, NH (United States); Norbeck, Angela D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Auberry, Kenneth J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Moore, R. J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Adkins, Joshua N. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Heffron, Fred [Oregon Health and Science Univ., Portland, OR (United States); Smith, Richard D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2009-02-10

We successfully modified an existing method to investigate protein-protein interactions in the pathogenic bacterium Salmonella typhimurium (STM). This method includes i) addition of a histidine-biotin-histidine tag to the bait proteins via recombinant DNA techniques; ii) in vivo cross-linking with formaldehyde; iii) tandem affinity purification of bait proteins under fully denaturing conditions; and iv) identification of the proteins cross-linked to the bait proteins by liquid-chromatography in conjunction with tandem mass-spectrometry. In vivo cross-linking stabilized protein interactions permitted the subsequent two-step purification step conducted under denaturing conditions. The two-step purification greatly reduced nonspecific binding of non-cross-linked proteins to bait proteins. Two different negative controls were employed to reduce false-positive identification. In an initial demonstration of this approach, we tagged three selected STM proteins- HimD, PduB and PhoP- with known binding partners that ranged from stable (e.g., HimD) to transient (i.e., PhoP). Distinct sets of interacting proteins were identified with each bait protein, including the known binding partners such as HimA for HimD, as well as anticipated and unexpected binding partners. Our results suggest that novel protein-protein interactions may be critical to pathogenesis by Salmonella typhimurium. .

Identification of novel components in microProtein signalling

DEFF Research Database (Denmark)

Rodrigues, Vandasue Lily

characterization of smaller proteins. Using a computational approach, we identified putative microProteins that could target a diverse variety of protein classes. Using a synthetic microProtein approach, we demonstrate that miPs can target a diverse variety of target proteins, which makes them of interest...

A rapid and accurate method for determining protein content in dairy products based on asynchronous-injection alternating merging zone flow-injection spectrophotometry.

Science.gov (United States)

Liang, Qin-Qin; Li, Yong-Sheng

2013-12-01

An accurate and rapid method and a system to determine protein content using asynchronous-injection alternating merging zone flow-injection spectrophotometry based on reaction between coomassie brilliant blue G250 (CBBG) and protein was established. Main merit of our approach is that it can avoid interferences of other nitric-compounds in samples, such as melamine and urea. Optimized conditions are as follows: Concentrations of CBBG, polyvinyl alcohol (PVA), NaCl and HCl are 150 mg/l, 30 mg/l, 0.1 mol/l and 1.0% (v/v), respectively; volumes of the sample and reagent are 150 μl and 30 μl, respectively; length of a reaction coil is 200 cm; total flow rate is 2.65 ml/min. The linear range of the method is 0.5-15 mg/l (BSA), its detection limit is 0.05 mg/l, relative standard deviation is less than 1.87% (n=11), and analytical speed is 60 samples per hour. Copyright © 2013 Elsevier Ltd. All rights reserved.

Live Cell Genomics: RNA Exon-Specific RNA-Binding Protein Isolation.

Science.gov (United States)

Bell, Thomas J; Eberwine, James

2015-01-01

RNA-binding proteins (RBPs) are essential regulatory proteins that control all modes of RNA processing and regulation. New experimental approaches to isolate these indispensable proteins under in vivo conditions are needed to advance the field of RBP biology. Historically, in vitro biochemical approaches to isolate RBP complexes have been useful and productive, but biological relevance of the identified RBP complexes can be imprecise or erroneous. Here we review an inventive experimental to isolate RBPs under the in vivo conditions. The method is called peptide nucleic acid (PNA)-assisted identification of RBP (PAIR) technology and it uses cell-penetrating peptides (CPPs) to deliver photo-activatible RBP-capture molecule to the cytoplasm of the live cells. The PAIR methodology provides two significant advantages over the most commonly used approaches: (1) it overcomes the in vitro limitation of standard biochemical approaches and (2) the PAIR RBP-capture molecule is highly selective and adaptable which allows investigators to isolate exon-specific RBP complexes. Most importantly, the in vivo capture conditions and selectivity of the RBP-capture molecule yield biologically accurate and relevant RBP data.

Identification of proteins similar to AvrE type III effector proteins from ...

African Journals Online (AJOL)

Stephen Opiyo

GSE22274), and AraCyc databases, we highlighted 16 protein candidates from Arabidopsidis genome .... projection method similar to principal component analysis (PCA) .... RIN4 RIN4 (RPM1 INTERACTING PROTEIN 4); protein binding.

Optimization of Search Engines and Postprocessing Approaches to Maximize Peptide and Protein Identification for High-Resolution Mass Data.

Science.gov (United States)

Tu, Chengjian; Sheng, Quanhu; Li, Jun; Ma, Danjun; Shen, Xiaomeng; Wang, Xue; Shyr, Yu; Yi, Zhengping; Qu, Jun

2015-11-06

The two key steps for analyzing proteomic data generated by high-resolution MS are database searching and postprocessing. While the two steps are interrelated, studies on their combinatory effects and the optimization of these procedures have not been adequately conducted. Here, we investigated the performance of three popular search engines (SEQUEST, Mascot, and MS Amanda) in conjunction with five filtering approaches, including respective score-based filtering, a group-based approach, local false discovery rate (LFDR), PeptideProphet, and Percolator. A total of eight data sets from various proteomes (e.g., E. coli, yeast, and human) produced by various instruments with high-accuracy survey scan (MS1) and high- or low-accuracy fragment ion scan (MS2) (LTQ-Orbitrap, Orbitrap-Velos, Orbitrap-Elite, Q-Exactive, Orbitrap-Fusion, and Q-TOF) were analyzed. It was found combinations involving Percolator achieved markedly more peptide and protein identifications at the same FDR level than the other 12 combinations for all data sets. Among these, combinations of SEQUEST-Percolator and MS Amanda-Percolator provided slightly better performances for data sets with low-accuracy MS2 (ion trap or IT) and high accuracy MS2 (Orbitrap or TOF), respectively, than did other methods. For approaches without Percolator, SEQUEST-group performs the best for data sets with MS2 produced by collision-induced dissociation (CID) and IT analysis; Mascot-LFDR gives more identifications for data sets generated by higher-energy collisional dissociation (HCD) and analyzed in Orbitrap (HCD-OT) and in Orbitrap Fusion (HCD-IT); MS Amanda-Group excels for the Q-TOF data set and the Orbitrap Velos HCD-OT data set. Therefore, if Percolator was not used, a specific combination should be applied for each type of data set. Moreover, a higher percentage of multiple-peptide proteins and lower variation of protein spectral counts were observed when analyzing technical replicates using Percolator

Identification of new binding partners of the chemosensory signalling protein Gγ13 expressed in taste and olfactory sensory cells.

Directory of Open Access Journals (Sweden)

Zhenhui eLiu

2012-06-01

Full Text Available Tastant detection in the oral cavity involves selective receptors localized at the apical extremity of a subset of specialized taste bud cells called taste receptor cells (TRCs. The identification of the genes coding for the taste receptors involved in this process have greatly improved our understanding of the molecular mechanisms underlying detection. However, how these receptors signal in TRCs, and whether the components of the signaling cascades interact with each other or are organized in complexes is mostly unexplored. Here we report on the identification of three new binding partners for the mouse G protein gamma 13 subunit (Gγ13, a component of the bitter taste receptors signalling cascade. For two of these Gγ13 associated proteins, namely GOPC and MPDZ, we describe the expression in taste bud cells for the first time. Furthermore, we demonstrate by means of a yeast two-hybrid interaction assay that the C terminal PDZ binding motif of Gγ13 interacts with selected PDZ domains in these proteins. In the case of the PDZ domain-containing protein zona occludens-1 (ZO-1, a major component of the tight junction defining the boundary between the apical and baso-lateral region of TRCs, we identified the first PDZ domain as the site of strong interaction with Gγ13. This association was further confirmed by co-immunoprecipitation experiments in HEK 293 cells. In addition, we present immunohistological data supporting partial co-localization of GOPC, MPDZ or ZO-1 and Gγ13 in taste buds cells. Finally, we extend this observation to olfactory sensory neurons, another type of chemosensory cells known to express both ZO-1 and Gγ13. Taken together our results implicate these new interaction partners in the sub-cellular distribution of Gγ13 in olfactory and gustatory primary sensory cells.

Rapid and accurate identification by real-time PCR of biotoxin-producing dinoflagellates from the family gymnodiniaceae.

Science.gov (United States)

Smith, Kirsty F; de Salas, Miguel; Adamson, Janet; Rhodes, Lesley L

2014-03-07

The identification of toxin-producing dinoflagellates for monitoring programmes and bio-compound discovery requires considerable taxonomic expertise. It can also be difficult to morphologically differentiate toxic and non-toxic species or strains. Various molecular methods have been used for dinoflagellate identification and detection, and this study describes the development of eight real-time polymerase chain reaction (PCR) assays targeting the large subunit ribosomal RNA (LSU rRNA) gene of species from the genera Gymnodinium, Karenia, Karlodinium, and Takayama. Assays proved to be highly specific and sensitive, and the assay for G. catenatum was further developed for quantification in response to a bloom in Manukau Harbour, New Zealand. The assay estimated cell densities from environmental samples as low as 0.07 cells per PCR reaction, which equated to three cells per litre. This assay not only enabled conclusive species identification but also detected the presence of cells below the limit of detection for light microscopy. This study demonstrates the usefulness of real-time PCR as a sensitive and rapid molecular technique for the detection and quantification of micro-algae from environmental samples.

The rapid identification for the unaware radioactive material

International Nuclear Information System (INIS)

Jin Yuren; Cheng Zhiwei; Xu Hui; Wang Jiang; Han Xiaoyuan; Long Bin

2010-01-01

The unaware radioactive material(URM) appeared in the society may induce serious deterministic effect, even result in havoc and instability of the society. The rapid and accurate identification for URM is the premise for its reasonable treatment. In this paper, an identification procedure for URM was developed and which was successfully implemented in the identification of an URM. The In-situ HPGe gamma spectrometry etc was employed for the rapid preliminary identification, and the laboratory HPGe gamma spectrometry and ICP-MS as well as the density measurement were used for its final identification. One unaware radioactive material was assayed, and the results indicate that it is a kind of high pure depleted uranium metal with the 235 U/ 238 U atomic ratio of 0.454%. (authors)

Quantitation and Identification of Intact Major Milk Proteins for High-Throughput LC-ESI-Q-TOF MS Analyses.

Directory of Open Access Journals (Sweden)

Delphine Vincent

Full Text Available Cow's milk is an important source of proteins in human nutrition. On average, cow's milk contains 3.5% protein. The most abundant proteins in bovine milk are caseins and some of the whey proteins, namely beta-lactoglobulin, alpha-lactalbumin, and serum albumin. A number of allelic variants and post-translationally modified forms of these proteins have been identified. Their occurrence varies with breed, individuality, stage of lactation, and health and nutritional status of the animal. It is therefore essential to have reliable methods of detection and quantitation of these proteins. Traditionally, major milk proteins are quantified using liquid chromatography (LC and ultra violet detection method. However, as these protein variants co-elute to some degree, another dimension of separation is beneficial to accurately measure their amounts. Mass spectrometry (MS offers such a tool. In this study, we tested several RP-HPLC and MS parameters to optimise the analysis of intact bovine proteins from milk. From our tests, we developed an optimum method that includes a 20-28-40% phase B gradient with 0.02% TFA in both mobile phases, at 0.2 mL/min flow rate, using 75°C for the C8 column temperature, scanning every 3 sec over a 600-3000 m/z window. The optimisations were performed using external standards commercially purchased for which ionisation efficiency, linearity of calibration, LOD, LOQ, sensitivity, selectivity, precision, reproducibility, and mass accuracy were demonstrated. From the MS analysis, we can use extracted ion chromatograms (EICs of specific ion series of known proteins and integrate peaks at defined retention time (RT window for quantitation purposes. This optimum quantitative method was successfully applied to two bulk milk samples from different breeds, Holstein-Friesian and Jersey, to assess differences in protein variant levels.

Identification of ultramodified proteins using top-down spectra

Energy Technology Data Exchange (ETDEWEB)

Liu, Xiaowen; Hengel, Shawna M.; Wu, Si; Tolic, Nikola; Pasa-Tolic, Ljiljana; Pevzner, Pavel A.

2013-04-10

Post-translational modifications (PTMs) play an important role in various biological processes through changing protein structure and function. Some ultramodified proteins (like histones) have multiple PTMs forming PTM patterns that define the functionality of a protein. While bottom-up mass spectrometry (MS) has been successful in identifying individual PTMs within short peptides, it is unable to identify PTM patterns spread along entire proteins in a coordinated fashion. In contrast, top-down MS analyzes intact proteins and reveals PTM patterns along the entire proteins. However, while recent advances in instrumentation have made top-down MS accessible to many laboratories, most computational tools for top-down MS focus on proteins with few PTMs and are unable to identify complex PTM patterns. We propose a new algorithm, MS-Align-E, that identifies both expected and unexpected PTMs in ultramodified proteins. We demonstrate that MS-Align-E identifies many protein forms of histone H4 and benchmark it against the currently accepted software tools.

Identification of children with reading difficulties: Cheap can be adequate

DEFF Research Database (Denmark)

Poulsen, Mads; Nielsen, Anne-Mette Veber

Classification of reading difficulties: Cheap screening can be accurate Purpose: Three factors are important for identification of students in need of remedial instruction: accuracy, timeliness, and cost. The identification has to be accurate to be of any use, the identification has to be timely......, inexpensive testing. The present study investigated the classification accuracy of three screening models varying in timeliness and cost. Method: We compared the ROC statistics of three logistic models for predicting end of Grade 2 reading difficulties in a sample of 164 students: 1) an early, comprehensive...... model using a battery of Grade 0 tests, including phoneme awareness, rapid naming, and paired associate learning, 2) a late, comprehensive model adding reading measures from January of Grade 1, and 3) a late, inexpensive model using only group-administered reading measures from January of Grade 1...

Rapid identification of ascomycetous yeasts from clinical specimens by a molecular method based on flow cytometry and comparison with identifications from phenotypic assays.

Science.gov (United States)

Page, Brent T; Shields, Christine E; Merz, William G; Kurtzman, Cletus P

2006-09-01

This study was designed to compare the identification of ascomycetous yeasts recovered from clinical specimens by using phenotypic assays (PA) and a molecular flow cytometric (FC) method. Large-subunit rRNA domains 1 and 2 (D1/D2) gene sequence analysis was also performed and served as the reference for correct strain identification. A panel of 88 clinical isolates was tested that included representatives of nine commonly encountered species and six infrequently encountered species. The PA included germ tube production, fermentation of seven carbohydrates, morphology on corn meal agar, urease and phenoloxidase activities, and carbohydrate assimilation tests when needed. The FC method (Luminex) employed species-specific oligonucleotides attached to polystyrene beads, which were hybridized with D1/D2 amplicons from the unidentified isolates. The PA identified 81 of 88 strains correctly but misidentified 4 of Candida dubliniensis, 1 of C. bovina, 1 of C. palmioleophila, and 1 of C. bracarensis. The FC method correctly identified 79 of 88 strains and did not misidentify any isolate but did not identify nine isolates because oligonucleotide probes were not available in the current library. The FC assay takes approximately 5 h, whereas the PA takes from 2 h to 5 days for identification. In conclusion, PA did well with the commonly encountered species, was not accurate for uncommon species, and takes significantly longer than the FC method. These data strongly support the potential of FC technology for rapid and accurate identification of medically important yeasts. With the introduction of new antifungals, rapid, accurate identification of pathogenic yeasts is more important than ever for guiding antifungal chemotherapy.

Correction for phylogeny, small number of observations and data redundancy improves the identification of coevolving amino acid pairs using mutual information

DEFF Research Database (Denmark)

Buslje, C.M.; Santos, J.; Delfino, J.M.

2009-01-01

Motivation: Mutual information (MI) theory is often applied to predict positional correlations in a multiple sequence alignment (MSA) to make possible the analysis of those positions structurally or functionally important in a given fold or protein family. Accurate identification of coevolving......-weighting techniques to reduce sequence redundancy and low-count corrections to account for small number of observations in limited size sequence families, can significantly improve the predictability of MI. The evaluation is made on large sets of both in silico-generated alignments as well as on biological sequence...

Identification of Ina proteins from Fusarium acuminatum

Science.gov (United States)

Scheel, Jan Frederik; Kunert, Anna Theresa; Pöschl, Ulrich; Fröhlich-Nowoisky, Janine

2015-04-01

Freezing of water above -36° C is based on ice nucleation activity (INA) mediated by ice nucleators (IN) which can be of various origins. Beside mineral IN, biological particles are a potentially important source of atmospheric IN. The best-known biological IN are common plant-associated bacteria. The IN activity of these bacteria is induced by a surface protein on the outer cell membrane, which is fully characterized. In contrast, much less is known about the nature of fungal IN. The fungal genus Fusarium is widely spread throughout the earth. It belongs to the Ascomycota and is one of the most severe fungal pathogens. It can affect a variety of organisms from plants to animals including humans. INA of Fusarium was already described about 30 years ago and INA of Fusarium as well as other fungal genera is assumed to be mediated by proteins or at least to contain a proteinaceous compound. Although many efforts were made the precise INA machinery of Fusarium and other fungal species including the proteins and their corresponding genes remain unidentified. In this study preparations from living fungal samples of F. acuminatum were fractionated by liquid chromatography and IN active fractions were identified by freezing assays. SDS-page and de novo sequencing by mass spectrometry were used to identify the primary structure of the protein. Preliminary results show that the INA protein of F. acuminatum is contained in the early size exclusion chromatography fractions indicating a high molecular size. Moreover we could identify a single protein band from IN active fractions at 130-145 kDa corresponding to sizes of IN proteins from bacterial species. To our knowledge this is for the first time an isolation of a single protein from in vivo samples, which can be assigned as IN active from Fusarium.

SPERM HY-LITER™ for the identification of spermatozoa from sexual assault evidence

DEFF Research Database (Denmark)

Westring, Christian Gustav; Wiuf, Morten; Nielsen, S Jock

2014-01-01

Accurate microscopic identification of human spermatozoa is important in sexual assault cases. We have compared the results of examinations with (1) a fluorescent microscopy method, SPERM HY-LITER™, and (2) Baecchi's method for identification of human spermatozoa. In 35 artificial, forensic type...

Accurate and Reliable Prediction of the Binding Affinities of Macrocycles to Their Protein Targets.

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Yu, Haoyu S; Deng, Yuqing; Wu, Yujie; Sindhikara, Dan; Rask, Amy R; Kimura, Takayuki; Abel, Robert; Wang, Lingle

2017-12-12

Macrocycles have been emerging as a very important drug class in the past few decades largely due to their expanded chemical diversity benefiting from advances in synthetic methods. Macrocyclization has been recognized as an effective way to restrict the conformational space of acyclic small molecule inhibitors with the hope of improving potency, selectivity, and metabolic stability. Because of their relatively larger size as compared to typical small molecule drugs and the complexity of the structures, efficient sampling of the accessible macrocycle conformational space and accurate prediction of their binding affinities to their target protein receptors poses a great challenge of central importance in computational macrocycle drug design. In this article, we present a novel method for relative binding free energy calculations between macrocycles with different ring sizes and between the macrocycles and their corresponding acyclic counterparts. We have applied the method to seven pharmaceutically interesting data sets taken from recent drug discovery projects including 33 macrocyclic ligands covering a diverse chemical space. The predicted binding free energies are in good agreement with experimental data with an overall root-mean-square error (RMSE) of 0.94 kcal/mol. This is to our knowledge the first time where the free energy of the macrocyclization of linear molecules has been directly calculated with rigorous physics-based free energy calculation methods, and we anticipate the outstanding accuracy demonstrated here across a broad range of target classes may have significant implications for macrocycle drug discovery.

Proteomic analysis of processing by-products from canned and fresh tuna: identification of potentially functional food proteins.

Science.gov (United States)

Sanmartín, Esther; Arboleya, Juan Carlos; Iloro, Ibon; Escuredo, Kepa; Elortza, Felix; Moreno, F Javier

2012-09-15

Proteomic approaches have been used to identify the main proteins present in processing by-products generated by the canning tuna-industry, as well as in by-products derived from filleting of skeletal red muscle of fresh tuna. Following fractionation by using an ammonium sulphate precipitation method, three proteins (tropomyosin, haemoglobin and the stress-shock protein ubiquitin) were identified in the highly heterogeneous and heat-treated material discarded by the canning-industry. Additionally, this fractionation method was successful to obtain tropomyosin of high purity from the heterogeneous starting material. By-products from skeletal red muscle of fresh tuna were efficiently fractionated to sarcoplasmic and myofibrillar fractions, prior to the identification based mainly on the combined searching of the peptide mass fingerprint (MALDI-TOF) and peptide fragment fingerprinting (MALDI LIFT-TOF/TOF) spectra of fifteen bands separated by 1D SDS-PAGE. Thus, the sarcoplasmic fraction contained myoglobin and several enzymes that are essential for efficient energy production, whereas the myofibrillar fraction had important contractile proteins, such as actin, tropomyosin, myosin or an isoform of the enzyme creatine kinase. Application of proteomic technologies has revealed new knowledge on the composition of important by-products from tuna species, enabling a better evaluation of their potential applications. Copyright © 2012 Elsevier Ltd. All rights reserved.

Identification of structural protein-protein interactions of herpes simplex virus type 1.

Science.gov (United States)

Lee, Jin H; Vittone, Valerio; Diefenbach, Eve; Cunningham, Anthony L; Diefenbach, Russell J

2008-09-01

In this study we have defined protein-protein interactions between the structural proteins of herpes simplex virus type 1 (HSV-1) using a LexA yeast two-hybrid system. The majority of the capsid, tegument and envelope proteins of HSV-1 were screened in a matrix approach. A total of 40 binary interactions were detected including 9 out of 10 previously identified tegument-tegument interactions (Vittone, V., Diefenbach, E., Triffett, D., Douglas, M.W., Cunningham, A.L., and Diefenbach, R.J., 2005. Determination of interactions between tegument proteins of herpes simplex virus type 1. J. Virol. 79, 9566-9571). A total of 12 interactions involving the capsid protein pUL35 (VP26) and 11 interactions involving the tegument protein pUL46 (VP11/12) were identified. The most significant novel interactions detected in this study, which are likely to play a role in viral assembly, include pUL35-pUL37 (capsid-tegument), pUL46-pUL37 (tegument-tegument) and pUL49 (VP22)-pUS9 (tegument-envelope). This information will provide further insights into the pathways of HSV-1 assembly and the identified interactions are potential targets for new antiviral drugs.

Transduction proteins of olfactory receptor cells: identification of guanine nucleotide binding proteins and protein kinase C

International Nuclear Information System (INIS)

Anholt, R.R.H.; Mumby, S.M.; Stoffers, D.A.; Girard, P.R.; Kuo, J.F.; Snyder, S.H.

1987-01-01

The authors have analyzed guanine nucleotide binding proteins (G-proteins) in the olfactory epithelium of Rana catesbeiana using subunit-specific antisera. The olfactory epithelium contained the α subunits of three G-proteins, migrating on polyacrylamide gels in SDS with apparent molecular weights of 45,000, 42,000, and 40,000, corresponding to G/sub s/, G/sub i/, and G/sub o/, respectively. A single β subunit with an apparent molecular weight of 36,000 was detected. An antiserum against the α subunit of retinal transducin failed to detect immunoreactive proteins in olfactory cilia detached from the epithelium. The olfactory cilia appeared to be enriched in immunoreactive G/sub sα/ relative to G/sub ichemical bond/ and G/sub ochemical bond/ when compared to membranes prepared from the olfactory epithelium after detachment of the cilia. Bound antibody was detected by autoradiography after incubation with [ 125 I]protein. Immunohistochemical studies using an antiserum against the β subunit of G-proteins revealed intense staining of the ciliary surface of the olfactory epithelium and of the axon bundles in the lamina propria. In contrast, an antiserum against a common sequence of the α subunits preferentially stained the cell membranes of the olfactory receptor cells and the acinar cells of Bowman's glands and the deep submucosal glands. In addition to G-proteins, they have identified protein kinase C in olfactory cilia via a protein kinase C specific antiserum and via phorbol ester binding. However, in contrast to the G-proteins, protein kinase C occurred also in cilia isolated from respiratory epithelium

Fragment-based quantum mechanical calculation of protein-protein binding affinities.

Science.gov (United States)

Wang, Yaqian; Liu, Jinfeng; Li, Jinjin; He, Xiao

2018-04-29

The electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method has been successfully utilized for efficient linear-scaling quantum mechanical (QM) calculation of protein energies. In this work, we applied the EE-GMFCC method for calculation of binding affinity of Endonuclease colicin-immunity protein complex. The binding free energy changes between the wild-type and mutants of the complex calculated by EE-GMFCC are in good agreement with experimental results. The correlation coefficient (R) between the predicted binding energy changes and experimental values is 0.906 at the B3LYP/6-31G*-D level, based on the snapshot whose binding affinity is closest to the average result from the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) calculation. The inclusion of the QM effects is important for accurate prediction of protein-protein binding affinities. Moreover, the self-consistent calculation of PB solvation energy is required for accurate calculations of protein-protein binding free energies. This study demonstrates that the EE-GMFCC method is capable of providing reliable prediction of relative binding affinities for protein-protein complexes. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

BMRF-Net: a software tool for identification of protein interaction subnetworks by a bagging Markov random field-based method.

Science.gov (United States)

Shi, Xu; Barnes, Robert O; Chen, Li; Shajahan-Haq, Ayesha N; Hilakivi-Clarke, Leena; Clarke, Robert; Wang, Yue; Xuan, Jianhua

2015-07-15

Identification of protein interaction subnetworks is an important step to help us understand complex molecular mechanisms in cancer. In this paper, we develop a BMRF-Net package, implemented in Java and C++, to identify protein interaction subnetworks based on a bagging Markov random field (BMRF) framework. By integrating gene expression data and protein-protein interaction data, this software tool can be used to identify biologically meaningful subnetworks. A user friendly graphic user interface is developed as a Cytoscape plugin for the BMRF-Net software to deal with the input/output interface. The detailed structure of the identified networks can be visualized in Cytoscape conveniently. The BMRF-Net package has been applied to breast cancer data to identify significant subnetworks related to breast cancer recurrence. The BMRF-Net package is available at http://sourceforge.net/projects/bmrfcjava/. The package is tested under Ubuntu 12.04 (64-bit), Java 7, glibc 2.15 and Cytoscape 3.1.0. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Accurate identification of RNA editing sites from primitive sequence with deep neural networks.

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Ouyang, Zhangyi; Liu, Feng; Zhao, Chenghui; Ren, Chao; An, Gaole; Mei, Chuan; Bo, Xiaochen; Shu, Wenjie

2018-04-16

RNA editing is a post-transcriptional RNA sequence alteration. Current methods have identified editing sites and facilitated research but require sufficient genomic annotations and prior-knowledge-based filtering steps, resulting in a cumbersome, time-consuming identification process. Moreover, these methods have limited generalizability and applicability in species with insufficient genomic annotations or in conditions of limited prior knowledge. We developed DeepRed, a deep learning-based method that identifies RNA editing from primitive RNA sequences without prior-knowledge-based filtering steps or genomic annotations. DeepRed achieved 98.1% and 97.9% area under the curve (AUC) in training and test sets, respectively. We further validated DeepRed using experimentally verified U87 cell RNA-seq data, achieving 97.9% positive predictive value (PPV). We demonstrated that DeepRed offers better prediction accuracy and computational efficiency than current methods with large-scale, mass RNA-seq data. We used DeepRed to assess the impact of multiple factors on editing identification with RNA-seq data from the Association of Biomolecular Resource Facilities and Sequencing Quality Control projects. We explored developmental RNA editing pattern changes during human early embryogenesis and evolutionary patterns in Drosophila species and the primate lineage using DeepRed. Our work illustrates DeepRed's state-of-the-art performance; it may decipher the hidden principles behind RNA editing, making editing detection convenient and effective.

A genome-wide analysis of the flax (Linum usitatissimum L.) dirigent protein family: from gene identification and evolution to differential regulation.

Energy Technology Data Exchange (ETDEWEB)

Corbin, Cyrielle; Drouet, Samantha; Markulin, Lucija; Auguin, Daniel; Laine, Eric; Davin, Laurence B.; Cort, John R.; Lewis, Norman G.; Hano, Christophe

2018-04-30

Identification of DIR encoding genes in flax genome. Analysis of phylogeny, gene/protein structures and evolution. Identification of new conserved motifs linked to biochemical functions. Investigation of spatio-temporal gene expression and response to stress. Dirigent proteins (DIRs) were discovered during 8-8' lignan biosynthesis studies, through identification of stereoselective coupling to afford either (+)- or (-)-pinoresinols from E-coniferyl alcohol. DIRs are also involved or potentially involved in terpenoid, allyl/propenyl phenol lignan, pterocarpan and lignin biosynthesis. DIRs have very large multigene families in different vascular plants including flax, with most still of unknown function. DIR studies typically focus on a small subset of genes and identification of biochemical/physiological functions. Herein, a genome-wide analysis and characterization of the predicted flax DIR 44-membered multigene family was performed, this species being a rich natural grain source of 8-8' linked secoisolariciresinol-derived lignan oligomers. All predicted DIR sequences, including their promoters, were analyzed together with their public gene expression datasets. Expression patterns of selected DIRs were examined using qPCR, as well as through clustering analysis of DIR gene expression. These analyses further implicated roles for specific DIRs in (-)-pinoresinol formation in seed-coats, as well as (+)-pinoresinol in vegetative organs and/or specific responses to stress. Phylogeny and gene expression analysis segregated flax DIRs into six distinct clusters with new cluster-specific motifs identified. We propose that these findings can serve as a foundation to further systematically determine functions of DIRs, i.e. other than those already known in lignan biosynthesis in flax and other species. Given the differential expression profiles and inducibility of the flax DIR family, we provisionally propose that some DIR genes of unknown function could be involved

A genome-wide analysis of the flax (Linum usitatissimum L.) dirigent protein family: from gene identification and evolution to differential regulation.

Science.gov (United States)

Corbin, Cyrielle; Drouet, Samantha; Markulin, Lucija; Auguin, Daniel; Lainé, Éric; Davin, Laurence B; Cort, John R; Lewis, Norman G; Hano, Christophe

2018-05-01

Identification of DIR encoding genes in flax genome. Analysis of phylogeny, gene/protein structures and evolution. Identification of new conserved motifs linked to biochemical functions. Investigation of spatio-temporal gene expression and response to stress. Dirigent proteins (DIRs) were discovered during 8-8' lignan biosynthesis studies, through identification of stereoselective coupling to afford either (+)- or (-)-pinoresinols from E-coniferyl alcohol. DIRs are also involved or potentially involved in terpenoid, allyl/propenyl phenol lignan, pterocarpan and lignin biosynthesis. DIRs have very large multigene families in different vascular plants including flax, with most still of unknown function. DIR studies typically focus on a small subset of genes and identification of biochemical/physiological functions. Herein, a genome-wide analysis and characterization of the predicted flax DIR 44-membered multigene family was performed, this species being a rich natural grain source of 8-8' linked secoisolariciresinol-derived lignan oligomers. All predicted DIR sequences, including their promoters, were analyzed together with their public gene expression datasets. Expression patterns of selected DIRs were examined using qPCR, as well as through clustering analysis of DIR gene expression. These analyses further implicated roles for specific DIRs in (-)-pinoresinol formation in seed-coats, as well as (+)-pinoresinol in vegetative organs and/or specific responses to stress. Phylogeny and gene expression analysis segregated flax DIRs into six distinct clusters with new cluster-specific motifs identified. We propose that these findings can serve as a foundation to further systematically determine functions of DIRs, i.e. other than those already known in lignan biosynthesis in flax and other species. Given the differential expression profiles and inducibility of the flax DIR family, we provisionally propose that some DIR genes of unknown function could be involved in

A novel multidimensional protein identification technology approach combining protein size exclusion prefractionation, peptide zwitterion-ion hydrophilic interaction chromatography, and nano-ultraperformance RP chromatography/nESI-MS2 for the in-depth analysis of the serum proteome and phosphoproteome: application to clinical sera derived from humans with benign prostate hyperplasia.

Science.gov (United States)

Garbis, Spiros D; Roumeliotis, Theodoros I; Tyritzis, Stavros I; Zorpas, Kostas M; Pavlakis, Kitty; Constantinides, Constantinos A

2011-02-01

The current proof-of-principle study was aimed toward development of a novel multidimensional protein identification technology (MudPIT) approach for the in-depth proteome analysis of human serum derived from patients with benign prostate hyperplasia (BPH) using rational chromatographic design principles. This study constituted an extension of our published work relating to the identification and relative quantification of potential clinical biomarkers in BPH and prostate cancer (PCa) tissue specimens. The proposed MudPIT approach encompassed the use of three distinct yet complementary liquid chromatographic chemistries. High-pressure size-exclusion chromatography (SEC) was used for the prefractionation of serum proteins followed by their dialysis exchange and solution phase trypsin proteolysis. The tryptic peptides were then subjected to offline zwitterion-ion hydrophilic interaction chromatography (ZIC-HILIC) fractionation followed by their online analysis with reversed-phase nano-ultraperformance chromatography (RP-nUPLC) hyphenated to nanoelectrospray ionization-tandem mass spectrometry using an ion trap mass analyzer. For the spectral processing, the sequential use of the SpectrumMill, Scaffold, and InsPecT software tools was applied for the tryptic peptide product ion MS(2) spectral processing, false discovery rate (FDR) assessment, validation, and protein identification. This milestone serum analysis study allowed the confident identification of over 1955 proteins (p ≤ 0.05; FDR ≤ 5%) with a broad spectrum of biological and physicochemical properties including secreted, tissue-specific proteins spanning approximately 12 orders of magnitude as they occur in their native abundance levels in the serum matrix. Also encompassed in this proteome was the confident identification of 375 phosphoproteins (p ≤ 0.05; FDR ≤ 5%) with potential importance to cancer biology. To demonstrate the performance characteristics of this novel MudPIT approach, a comparison

Rapid and Accurate Identification by Real-Time PCR of Biotoxin-Producing Dinoflagellates from the Family Gymnodiniaceae

Directory of Open Access Journals (Sweden)

Kirsty F. Smith

2014-03-01

Full Text Available The identification of toxin-producing dinoflagellates for monitoring programmes and bio-compound discovery requires considerable taxonomic expertise. It can also be difficult to morphologically differentiate toxic and non-toxic species or strains. Various molecular methods have been used for dinoflagellate identification and detection, and this study describes the development of eight real-time polymerase chain reaction (PCR assays targeting the large subunit ribosomal RNA (LSU rRNA gene of species from the genera Gymnodinium, Karenia, Karlodinium, and Takayama. Assays proved to be highly specific and sensitive, and the assay for G. catenatum was further developed for quantification in response to a bloom in Manukau Harbour, New Zealand. The assay estimated cell densities from environmental samples as low as 0.07 cells per PCR reaction, which equated to three cells per litre. This assay not only enabled conclusive species identification but also detected the presence of cells below the limit of detection for light microscopy. This study demonstrates the usefulness of real-time PCR as a sensitive and rapid molecular technique for the detection and quantification of micro-algae from environmental samples.

Are current atomistic force fields accurate enough to study proteins in crowded environments?

Directory of Open Access Journals (Sweden)

Drazen Petrov

2014-05-01

Full Text Available The high concentration of macromolecules in the crowded cellular interior influences different thermodynamic and kinetic properties of proteins, including their structural stabilities, intermolecular binding affinities and enzymatic rates. Moreover, various structural biology methods, such as NMR or different spectroscopies, typically involve samples with relatively high protein concentration. Due to large sampling requirements, however, the accuracy of classical molecular dynamics (MD simulations in capturing protein behavior at high concentration still remains largely untested. Here, we use explicit-solvent MD simulations and a total of 6.4 µs of simulated time to study wild-type (folded and oxidatively damaged (unfolded forms of villin headpiece at 6 mM and 9.2 mM protein concentration. We first perform an exhaustive set of simulations with multiple protein molecules in the simulation box using GROMOS 45a3 and 54a7 force fields together with different types of electrostatics treatment and solution ionic strengths. Surprisingly, the two villin headpiece variants exhibit similar aggregation behavior, despite the fact that their estimated aggregation propensities markedly differ. Importantly, regardless of the simulation protocol applied, wild-type villin headpiece consistently aggregates even under conditions at which it is experimentally known to be soluble. We demonstrate that aggregation is accompanied by a large decrease in the total potential energy, with not only hydrophobic, but also polar residues and backbone contributing substantially. The same effect is directly observed for two other major atomistic force fields (AMBER99SB-ILDN and CHARMM22-CMAP as well as indirectly shown for additional two (AMBER94, OPLS-AAL, and is possibly due to a general overestimation of the potential energy of protein-protein interactions at the expense of water-water and water-protein interactions. Overall, our results suggest that current MD force fields

CYP450 phenotyping and accurate mass identification of metabolites of the 8-aminoquinoline, anti-malarial drug primaquine

Directory of Open Access Journals (Sweden)

Pybus Brandon S

2012-08-01

Full Text Available Abstract Background The 8-aminoquinoline (8AQ drug primaquine (PQ is currently the only approved drug effective against the persistent liver stage of the hypnozoite forming strains Plasmodium vivax and Plasmodium ovale as well as Stage V gametocytes of Plasmodium falciparum. To date, several groups have investigated the toxicity observed in the 8AQ class, however, exact mechanisms and/or metabolic species responsible for PQ’s haemotoxic and anti-malarial properties are not fully understood. Methods In the present study, the metabolism of PQ was evaluated using in vitro recombinant metabolic enzymes from the cytochrome P450 (CYP and mono-amine oxidase (MAO families. Based on this information, metabolite identification experiments were performed using nominal and accurate mass measurements. Results Relative activity factor (RAF-weighted intrinsic clearance values show the relative role of each enzyme to be MAO-A, 2C19, 3A4, and 2D6, with 76.1, 17.0, 5.2, and 1.7% contributions to PQ metabolism, respectively. CYP 2D6 was shown to produce at least six different oxidative metabolites along with demethylations, while MAO-A products derived from the PQ aldehyde, a pre-cursor to carboxy PQ. CYPs 2C19 and 3A4 produced only trace levels of hydroxylated species. Conclusions As a result of this work, CYP 2D6 and MAO-A have been implicated as the key enzymes associated with PQ metabolism, and metabolites previously identified as potentially playing a role in efficacy and haemolytic toxicity have been attributed to production via CYP 2D6 mediated pathways.

An analytical platform for mass spectrometry-based identification and chemical analysis of RNA in ribonucleoprotein complexes.

Science.gov (United States)

Taoka, Masato; Yamauchi, Yoshio; Nobe, Yuko; Masaki, Shunpei; Nakayama, Hiroshi; Ishikawa, Hideaki; Takahashi, Nobuhiro; Isobe, Toshiaki

2009-11-01

We describe here a mass spectrometry (MS)-based analytical platform of RNA, which combines direct nano-flow reversed-phase liquid chromatography (RPLC) on a spray tip column and a high-resolution LTQ-Orbitrap mass spectrometer. Operating RPLC under a very low flow rate with volatile solvents and MS in the negative mode, we could estimate highly accurate mass values sufficient to predict the nucleotide composition of a approximately 21-nucleotide small interfering RNA, detect post-transcriptional modifications in yeast tRNA, and perform collision-induced dissociation/tandem MS-based structural analysis of nucleolytic fragments of RNA at a sub-femtomole level. Importantly, the method allowed the identification and chemical analysis of small RNAs in ribonucleoprotein (RNP) complex, such as the pre-spliceosomal RNP complex, which was pulled down from cultured cells with a tagged protein cofactor as bait. We have recently developed a unique genome-oriented database search engine, Ariadne, which allows tandem MS-based identification of RNAs in biological samples. Thus, the method presented here has broad potential for automated analysis of RNA; it complements conventional molecular biology-based techniques and is particularly suited for simultaneous analysis of the composition, structure, interaction, and dynamics of RNA and protein components in various cellular RNP complexes.

Proteomic identification of S-nitrosylated Golgi proteins: new insights into endothelial cell regulation by eNOS-derived NO.

Directory of Open Access Journals (Sweden)

Panjamaporn Sangwung

Full Text Available Endothelial nitric oxide synthase (eNOS is primarily localized on the Golgi apparatus and plasma membrane caveolae in endothelial cells. Previously, we demonstrated that protein S-nitrosylation occurs preferentially where eNOS is localized. Thus, in endothelial cells, Golgi proteins are likely to be targets for S-nitrosylation. The aim of this study was to identify S-nitrosylated Golgi proteins and attribute their S-nitrosylation to eNOS-derived nitric oxide in endothelial cells.Golgi membranes were isolated from rat livers. S-nitrosylated Golgi proteins were determined by a modified biotin-switch assay coupled with mass spectrometry that allows the identification of the S-nitrosylated cysteine residue. The biotin switch assay followed by Western blot or immunoprecipitation using an S-nitrosocysteine antibody was also employed to validate S-nitrosylated proteins in endothelial cell lysates.Seventy-eight potential S-nitrosylated proteins and their target cysteine residues for S-nitrosylation were identified; 9 of them were Golgi-resident or Golgi/endoplasmic reticulum (ER-associated proteins. Among these 9 proteins, S-nitrosylation of EMMPRIN and Golgi phosphoprotein 3 (GOLPH3 was verified in endothelial cells. Furthermore, S-nitrosylation of these proteins was found at the basal levels and increased in response to eNOS stimulation by the calcium ionophore A23187. Immunofluorescence microscopy and immunoprecipitation showed that EMMPRIN and GOLPH3 are co-localized with eNOS at the Golgi apparatus in endothelial cells. S-nitrosylation of EMMPRIN was notably increased in the aorta of cirrhotic rats.Our data suggest that the selective S-nitrosylation of EMMPRIN and GOLPH3 at the Golgi apparatus in endothelial cells results from the physical proximity to eNOS-derived nitric oxide.

Signal trend identification with fuzzy methods

International Nuclear Information System (INIS)

Reifman, J.; Tsoukalas, L. H.; Wang, X.; Wei, T. Y. C.

1999-01-01

A fuzzy-logic-based methodology for on-line signal trend identification is introduced. Although signal trend identification is complicated by the presence of noise, fuzzy logic can help capture important features of on-line signals and classify incoming power plant signals into increasing, decreasing and steady-state trend categories. In order to verify the methodology, a code named PROTREN is developed and tested using plant data. The results indicate that the code is capable of detecting transients accurately, identifying trends reliably, and not misinterpreting a steady-state signal as a transient one

Properties of Protein Drug Target Classes

Science.gov (United States)

Bull, Simon C.; Doig, Andrew J.

2015-01-01

Accurate identification of drug targets is a crucial part of any drug development program. We mined the human proteome to discover properties of proteins that may be important in determining their suitability for pharmaceutical modulation. Data was gathered concerning each protein’s sequence, post-translational modifications, secondary structure, germline variants, expression profile and drug target status. The data was then analysed to determine features for which the target and non-target proteins had significantly different values. This analysis was repeated for subsets of the proteome consisting of all G-protein coupled receptors, ion channels, kinases and proteases, as well as proteins that are implicated in cancer. Machine learning was used to quantify the proteins in each dataset in terms of their potential to serve as a drug target. This was accomplished by first inducing a random forest that could distinguish between its targets and non-targets, and then using the random forest to quantify the drug target likeness of the non-targets. The properties that can best differentiate targets from non-targets were primarily those that are directly related to a protein’s sequence (e.g. secondary structure). Germline variants, expression levels and interactions between proteins had minimal discriminative power. Overall, the best indicators of drug target likeness were found to be the proteins’ hydrophobicities, in vivo half-lives, propensity for being membrane bound and the fraction of non-polar amino acids in their sequences. In terms of predicting potential targets, datasets of proteases, ion channels and cancer proteins were able to induce random forests that were highly capable of distinguishing between targets and non-targets. The non-target proteins predicted to be targets by these random forests comprise the set of the most suitable potential future drug targets, and should therefore be prioritised when building a drug development programme. PMID

Rapid identification of moulds and arthroconidial yeasts from positive blood cultures by MALDI-TOF mass spectrometry.

Science.gov (United States)

de Almeida, João N; Sztajnbok, Jaques; da Silva, Afonso Rafael; Vieira, Vinicius Adriano; Galastri, Anne Layze; Bissoli, Leandro; Litvinov, Nadia; Del Negro, Gilda Maria Barbaro; Motta, Adriana Lopes; Rossi, Flávia; Benard, Gil

2016-11-01

Moulds and arthroconidial yeasts are potential life-threatening agents of fungemia in immunocompromised patients. Fast and accurate identification (ID) of these pathogens hastens initiation of targeted antifungal therapy, thereby improving the patients' prognosis. We describe a new strategy that enabled the identification of moulds and arthroconidial yeasts directly from positive blood cultures by MALDI-TOF mass spectrometry (MS). Positive blood cultures (BCs) with Gram staining showing hyphae and/or arthroconidia were prospectively selected and submitted to an in-house protein extraction protocol. Mass spectra were obtained by Vitek MS™ system, and identifications were carried out with in the research use only (RUO) mode with an extended database (SARAMIS™ [v.4.12] plus in-house database). Fusarium solani, Fusarium verticillioides, Exophiala dermatitidis, Saprochaete clavata, and Trichosporon asahii had correct species ID by MALDI-TOF MS analysis of positive BCs. All cases were related to critically ill patients with high mortality fungemia and direct ID from positive BCs was helpful for rapid administration of targeted antifungal therapy. © The Author 2016. Published by Oxford University Press on behalf of The International Society for Human and Animal Mycology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Quantum-Chemical Electron Densities of Proteins and of Selected Protein Sites from Subsystem Density Functional Theory

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Kiewisch, K.; Jacob, C.R.; Visscher, L.

2013-01-01

The ability to calculate accurate electron densities of full proteins or of selected sites in proteins is a prerequisite for a fully quantum-mechanical calculation of protein-protein and protein-ligand interaction energies. Quantum-chemical subsystem methods capable of treating proteins and other

Proteomic identification of rhythmic proteins in rice seedlings.

Science.gov (United States)

Hwang, Heeyoun; Cho, Man-Ho; Hahn, Bum-Soo; Lim, Hyemin; Kwon, Yong-Kook; Hahn, Tae-Ryong; Bhoo, Seong Hee

2011-04-01

Many aspects of plant metabolism that are involved in plant growth and development are influenced by light-regulated diurnal rhythms as well as endogenous clock-regulated circadian rhythms. To identify the rhythmic proteins in rice, periodically grown (12h light/12h dark cycle) seedlings were harvested for three days at six-hour intervals. Continuous dark-adapted plants were also harvested for two days. Among approximately 3000 reproducible protein spots on each gel, proteomic analysis ascertained 354 spots (~12%) as light-regulated rhythmic proteins, in which 53 spots showed prolonged rhythm under continuous dark conditions. Of these 354 ascertained rhythmic protein spots, 74 diurnal spots and 10 prolonged rhythmic spots under continuous dark were identified by MALDI-TOF MS analysis. The rhythmic proteins were functionally classified into photosynthesis, central metabolism, protein synthesis, nitrogen metabolism, stress resistance, signal transduction and unknown. Comparative analysis of our proteomic data with the public microarray database (the Plant DIURNAL Project) and RT-PCR analysis of rhythmic proteins showed differences in rhythmic expression phases between mRNA and protein, suggesting that the clock-regulated proteins in rice are modulated by not only transcriptional but also post-transcriptional, translational, and/or post-translational processes. 2011 Elsevier B.V. All rights reserved.

Identification of transcriptional signals in Encephalitozoon cuniculi widespread among Microsporidia phylum: support for accurate structural genome annotation

Directory of Open Access Journals (Sweden)

Wincker Patrick

2009-12-01

Full Text Available Abstract Background Microsporidia are obligate intracellular eukaryotic parasites with genomes ranging in size from 2.3 Mbp to more than 20 Mbp. The extremely small (2.9 Mbp and highly compact (~1 gene/kb genome of the human parasite Encephalitozoon cuniculi has been fully sequenced. The aim of this study was to characterize noncoding motifs that could be involved in regulation of gene expression in E. cuniculi and to show whether these motifs are conserved among the phylum Microsporidia. Results To identify such signals, 5' and 3'RACE-PCR experiments were performed on different E. cuniculi mRNAs. This analysis confirmed that transcription overrun occurs in E. cuniculi and may result from stochastic recognition of the AAUAAA polyadenylation signal. Such experiments also showed highly reduced 5'UTR's (E. cuniculi genes presented a CCC-like motif immediately upstream from the coding start. To characterize other signals involved in differential transcriptional regulation, we then focused our attention on the gene family coding for ribosomal proteins. An AAATTT-like signal was identified upstream from the CCC-like motif. In rare cases the cytosine triplet was shown to be substituted by a GGG-like motif. Comparative genomic studies confirmed that these different signals are also located upstream from genes encoding ribosomal proteins in other microsporidian species including Antonospora locustae, Enterocytozoon bieneusi, Anncaliia algerae (syn. Brachiola algerae and Nosema ceranae. Based on these results a systematic analysis of the ~2000 E. cuniculi coding DNA sequences was then performed and brings to highlight that 364 translation initiation codons (18.29% of total CDSs had been badly predicted. Conclusion We identified various signals involved in the maturation of E. cuniculi mRNAs. Presence of such signals, in phylogenetically distant microsporidian species, suggests that a common regulatory mechanism exists among the microsporidia. Furthermore

Soft Biometrics; Human Identification Using Comparative Descriptions.

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Reid, Daniel A; Nixon, Mark S; Stevenage, Sarah V

2014-06-01

Soft biometrics are a new form of biometric identification which use physical or behavioral traits that can be naturally described by humans. Unlike other biometric approaches, this allows identification based solely on verbal descriptions, bridging the semantic gap between biometrics and human description. To permit soft biometric identification the description must be accurate, yet conventional human descriptions comprising of absolute labels and estimations are often unreliable. A novel method of obtaining human descriptions will be introduced which utilizes comparative categorical labels to describe differences between subjects. This innovative approach has been shown to address many problems associated with absolute categorical labels-most critically, the descriptions contain more objective information and have increased discriminatory capabilities. Relative measurements of the subjects' traits can be inferred from comparative human descriptions using the Elo rating system. The resulting soft biometric signatures have been demonstrated to be robust and allow accurate recognition of subjects. Relative measurements can also be obtained from other forms of human representation. This is demonstrated using a support vector machine to determine relative measurements from gait biometric signatures-allowing retrieval of subjects from video footage by using human comparisons, bridging the semantic gap.

Identification, characterization, and synthesis of peptide epitopes and a recombinant six-epitope protein for Trichomonas vaginalis serodiagnosis

Directory of Open Access Journals (Sweden)

Alderete JF

2013-08-01

Full Text Available J F Alderete, Calvin J NeaceSchool of Molecular Biosciences, College of Veterinary Medicine, Washington State University, Pullman, WA, USAAbstract: There is a need for a rapid, accurate serodiagnostic test useful for both women and men infected by Trichomonas vaginalis, which causes the number one sexually transmitted infection (STI. Women and men exposed to T. vaginalis make serum antibody to fructose-1,6-bisphosphate aldolase (ALD, α-enolase (ENO, and glyceraldehyde-3-phosphate dehydrogenase (GAP. We identified, by epitope mapping, the common and distinct epitopes of each protein detected by the sera of women patients with trichomonosis and by the sera of men highly seropositive to the immunogenic protein α-actinin (positive control sera. We analyzed the amino acid sequences to determine the extent of identity of the epitopes of each protein with other proteins in the databanks. This approach identified epitopes unique to T. vaginalis, indicating these peptide-epitopes as possible targets for a serodiagnostic test. Individual or combinations of 15-mer peptide epitopes with low to no identity with other proteins were reactive with positive control sera from both women and men but were unreactive with negative control sera. These analyses permitted the synthesis of a recombinant His6 fusion protein of 111 amino acids with an Mr of ~13.4 kDa, which consisted of 15-mer peptides of two distinct epitopes each for ALD, ENO, and GAP. This recombinant protein was purified by affinity chromatography. This composite protein was detected by enzyme-linked immunosorbent assay (ELISA, dot blots, and immunoblots, using positive control sera from women and men. These data indicate that it is possible to identify epitopes and that either singly, in combination, or as a composite protein represent targets for a point-of-care serodiagnostic test for T. vaginalis.Keywords: diagnostics, point-of-care, targets, trichomonosis

Identification of multiply charged proteins and amino acid clusters by liquid nitrogen assisted spray ionization mass spectrometry.

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Kumar Kailasa, Suresh; Hasan, Nazim; Wu, Hui-Fen

2012-08-15

The development of liquid nitrogen assisted spray ionization mass spectrometry (LNASI MS) for the analysis of multiply charged proteins (insulin, ubiquitin, cytochrome c, α-lactalbumin, myoglobin and BSA), peptides (glutathione, HW6, angiotensin-II and valinomycin) and amino acid (arginine) clusters is described. The charged droplets are formed by liquid nitrogen assisted sample spray through a stainless steel nebulizer and transported into mass analyzer for the identification of multiply charged protein ions. The effects of acids and modifier volumes for the efficient ionization of the above analytes in LNASI MS were carefully investigated. Multiply charged proteins and amino acid clusters were effectively identified by LNASI MS. The present approach can effectively detect the multiply charged states of cytochrome c at 400 nM. A comparison between LNASI and ESI, CSI, SSI and V-EASI methods on instrumental conditions, applied temperature and observed charge states for the multiply charged proteins, shows that the LNASI method produces the good quality spectra of amino acid clusters at ambient conditions without applied any electric field and heat. To date, we believe that the LNASI method is the most simple, low cost and provided an alternative paradigm for production of multiply charged ions by LNASI MS, just as ESI-like ions yet no need for applying any electrical field and it could be operated at low temperature for generation of highly charged protein/peptide ions. Copyright © 2012 Elsevier B.V. All rights reserved.

Embodied memory allows accurate and stable perception of hidden objects despite orientation change.

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Pan, Jing Samantha; Bingham, Ned; Bingham, Geoffrey P

2017-07-01

Rotating a scene in a frontoparallel plane (rolling) yields a change in orientation of constituent images. When using only information provided by static images to perceive a scene after orientation change, identification performance typically decreases (Rock & Heimer, 1957). However, rolling generates optic flow information that relates the discrete, static images (before and after the change) and forms an embodied memory that aids recognition. The embodied memory hypothesis predicts that upon detecting a continuous spatial transformation of image structure, or in other words, seeing the continuous rolling process and objects undergoing rolling observers should accurately perceive objects during and after motion. Thus, in this case, orientation change should not affect performance. We tested this hypothesis in three experiments and found that (a) using combined optic flow and image structure, participants identified locations of previously perceived but currently occluded targets with great accuracy and stability (Experiment 1); (b) using combined optic flow and image structure information, participants identified hidden targets equally well with or without 30° orientation changes (Experiment 2); and (c) when the rolling was unseen, identification of hidden targets after orientation change became worse (Experiment 3). Furthermore, when rolling was unseen, although target identification was better when participants were told about the orientation change than when they were not told, performance was still worse than when there was no orientation change. Therefore, combined optic flow and image structure information, not mere knowledge about the rolling, enables accurate and stable perception despite orientation change. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Leptospira borgpetersenii hybrid leucine-rich repeat protein: Cloning and expression, immunogenic identification and molecular docking evaluation.

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Sritrakul, Tepyuda; Nitipan, Supachai; Wajjwalku, Worawidh; La-Ard, Anchalee; Suphatpahirapol, Chattip; Petkarnjanapong, Wimol; Ongphiphadhanakul, Boonsong; Prapong, Siriwan

2017-11-01

Leptospirosis is an important zoonotic disease, and the major outbreak of this disease in Thailand in 1999 was due largely to the Leptospira borgpetersenii serovar Sejroe. Identification of the leucine-rich repeat (LRR) LBJ_2271 protein containing immunogenic epitopes and the discovery of the LBJ_2271 ortholog in Leptospira serovar Sejroe, KU_Sej_R21_2271, led to further studies of the antigenic immune properties of KU_Sej_LRR_2271. The recombinant hybrid (rh) protein was created and expressed from a hybrid PCR fragment of KU_Sej_R21_2271 fused with DNA encoding the LBJ_2271 signal sequence for targeting protein as a membrane-anchoring protein. The fusion DNA was cloned into pET160/GW/D-TOPO® to form the pET160_hKU_R21_2271 plasmid. The plasmid was used to express the rhKU_Sej_LRR_2271 protein in Escherichia coli BL21 Star™ (DE3). The expressed protein was immunologically detected by Western blotting and immunoreactivity detection with hyperimmune sera, T cell epitope prediction by HLA allele and epitope peptide binding affinity, and potential T cell reactivity analysis. The immunogenic epitopes of the protein were evaluated and verified by HLA allele and epitope peptide complex structure molecular docking. Among fourteen best allele epitopes of this protein, binding affinity values of 12 allele epitopes remained unchanged compared to LBJ_2271. Two epitopes for alleles HLA-A0202 and -A0301 had higher IC 50 values, while T cell reactivity values of these peptides were better than values from LBJ_2271 epitopes. Eight of twelve epitope peptides had positive T-cell reactivity scores. Although the molecular docking of two epitopes, 3FPLLKEFLV11/47FPLLKEFLV55 and 50KLSTVPEGV58, into an HLA-A0202 model revealed a good fit in the docked structures, 50KLSTVPEGV58 and 94KLSTVPEEV102 are still considered as the proteins' best epitopes for allele HLA-A0202. The results of this study showed that rhKU_Sej_LRR_2271 protein contained natural immunological properties that should

DiffSLC: A graph centrality method to detect essential proteins of a protein-protein interaction network.

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Mistry, Divya; Wise, Roger P; Dickerson, Julie A

2017-01-01

Identification of central genes and proteins in biomolecular networks provides credible candidates for pathway analysis, functional analysis, and essentiality prediction. The DiffSLC centrality measure predicts central and essential genes and proteins using a protein-protein interaction network. Network centrality measures prioritize nodes and edges based on their importance to the network topology. These measures helped identify critical genes and proteins in biomolecular networks. The proposed centrality measure, DiffSLC, combines the number of interactions of a protein and the gene coexpression values of genes from which those proteins were translated, as a weighting factor to bias the identification of essential proteins in a protein interaction network. Potentially essential proteins with low node degree are promoted through eigenvector centrality. Thus, the gene coexpression values are used in conjunction with the eigenvector of the network's adjacency matrix and edge clustering coefficient to improve essentiality prediction. The outcome of this prediction is shown using three variations: (1) inclusion or exclusion of gene co-expression data, (2) impact of different coexpression measures, and (3) impact of different gene expression data sets. For a total of seven networks, DiffSLC is compared to other centrality measures using Saccharomyces cerevisiae protein interaction networks and gene expression data. Comparisons are also performed for the top ranked proteins against the known essential genes from the Saccharomyces Gene Deletion Project, which show that DiffSLC detects more essential proteins and has a higher area under the ROC curve than other compared methods. This makes DiffSLC a stronger alternative to other centrality methods for detecting essential genes using a protein-protein interaction network that obeys centrality-lethality principle. DiffSLC is implemented using the igraph package in R, and networkx package in Python. The python package can be

Facial expressions of emotion (KDEF): identification under different display-duration conditions.

Science.gov (United States)

Calvo, Manuel G; Lundqvist, Daniel

2008-02-01

Participants judged which of seven facial expressions (neutrality, happiness, anger, sadness, surprise, fear, and disgust) were displayed by a set of 280 faces corresponding to 20 female and 20 male models of the Karolinska Directed Emotional Faces database (Lundqvist, Flykt, & Ohman, 1998). Each face was presented under free-viewing conditions (to 63 participants) and also for 25, 50, 100, 250, and 500 msec (to 160 participants), to examine identification thresholds. Measures of identification accuracy, types of errors, and reaction times were obtained for each expression. In general, happy faces were identified more accurately, earlier, and faster than other faces, whereas judgments of fearful faces were the least accurate, the latest, and the slowest. Norms for each face and expression regarding level of identification accuracy, errors, and reaction times may be downloaded from www.psychonomic.org/archive/.

Supporting child witnesses during identification lineups: Exploring the effectiveness of registered intermediaries.

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Wilcock, Rachel; Crane, Laura; Hobson, Zoe; Nash, Gilly; Kirke-Smith, Mimi; Henry, Lucy A

2018-01-01

Performance at identification lineup was assessed in eighty-five 6- to 11-year-old typically developing children. Children viewed a live staged event involving 2 male actors, and were asked to identify the perpetrators from 2 separate lineups (one perpetrator-present lineup and one perpetrator-absent lineup). Half the children took part in lineups adapted by a registered intermediary (an impartial, trained professional who facilitates understanding and communication between vulnerable witnesses and members of the justice system), and half took part in "best-practice" lineups, according to the current guidance for eyewitness identification in England and Wales. Children receiving assistance from a registered intermediary (relative to children who received best-practice lineups) were more accurate in their identifications for perpetrator-present lineups, and there was some evidence that they were also more accurate for perpetrator-absent lineups. This provides the first empirical evidence for the effectiveness of registered intermediary support during identification lineups.

Template-based protein-protein docking exploiting pairwise interfacial residue restraints

NARCIS (Netherlands)

Xue, Li C; Garcia Lopes Maia Rodrigues, João; Dobbs, Drena; Honavar, Vasant; Bonvin, Alexandre M J J

2016-01-01

Although many advanced and sophisticatedab initioapproaches for modeling protein-protein complexes have been proposed in past decades, template-based modeling (TBM) remains the most accurate and widely used approach, given a reliable template is available. However, there are many different ways to

Knowledge of damage identification about tensegrities via flexibility disassembly

Science.gov (United States)

Jiang, Ge; Feng, Xiaodong; Du, Shigui

2017-12-01

Tensegrity structures composing of continuous cables and discrete struts are under tension and compression, respectively. In order to determine the damage extents of tensegrity structures, a new method for tensegrity structural damage identification is presented based on flexibility disassembly. To decompose a tensegrity structural flexibility matrix into the matrix represention of the connectivity between degress-of-freedoms and the diagonal matrix comprising of magnitude informations. Step 1: Calculate perturbation flexibility; Step 2: Compute the flexibility connectivity matrix and perturbation flexibility parameters; Step 3: Calculate the perturbation stiffness parameters. The efficiency of the proposed method is demonstrated by a numeical example comprising of 12 cables and 4 struts with pretensioned. Accurate identification of local damage depends on the availability of good measured data, an accurate and reasonable algorithm.

Direct identification of bacteria from charcoal-containing blood culture bottles using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry.

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Wüppenhorst, N; Consoir, C; Lörch, D; Schneider, C

2012-10-01

Several protocols for direct matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) from positive blood cultures are currently used to speed up the diagnostic process of bacteraemia. Identification rates are high and results are accurate for the BACTEC™ system and for charcoal-free bottles. Only a few studies have evaluated protocols for charcoal-containing BacT/ALERT bottles reaching substantially lower identification rates. We established a new protocol for sample preparation from aerobic and anaerobic positive charcoal-containing BacT/ALERT blood culture bottles and measured the protein profiles (n = 167). Then, we integrated this protocol in the routine workflow of our laboratory (n = 212). During the establishment of our protocol, 74.3 % of bacteria were correctly identified to the species level, in 23.4 %, no result and in 2.4 %, a false identification were obtained. Reliable criteria for correct species identification were a score value ≥1.400 and a best match on rank 1-3 of the same species. Identification rates during routine workflow were 77.8 % for correct identification, 20.8 % for not identified samples and 1.4 % for discordant identification. In conclusion, our results indicate that MALDI-TOF MS is possible, even from charcoal-containing blood cultures. Reliable criteria for correct species identification are a score value ≥1.400 and a best match on rank 1-3 of a single species.

Ligand identification using electron-density map correlations

International Nuclear Information System (INIS)

Terwilliger, Thomas C.; Adams, Paul D.; Moriarty, Nigel W.; Cohn, Judith D.

2007-01-01

An automated ligand-fitting procedure is applied to (F o − F c )exp(iϕ c ) difference density for 200 commonly found ligands from macromolecular structures in the Protein Data Bank to identify ligands from density maps. A procedure for the identification of ligands bound in crystal structures of macromolecules is described. Two characteristics of the density corresponding to a ligand are used in the identification procedure. One is the correlation of the ligand density with each of a set of test ligands after optimization of the fit of that ligand to the density. The other is the correlation of a fingerprint of the density with the fingerprint of model density for each possible ligand. The fingerprints consist of an ordered list of correlations of each the test ligands with the density. The two characteristics are scored using a Z-score approach in which the correlations are normalized to the mean and standard deviation of correlations found for a variety of mismatched ligand-density pairs, so that the Z scores are related to the probability of observing a particular value of the correlation by chance. The procedure was tested with a set of 200 of the most commonly found ligands in the Protein Data Bank, collectively representing 57% of all ligands in the Protein Data Bank. Using a combination of these two characteristics of ligand density, ranked lists of ligand identifications were made for representative (F o − F c )exp(iϕ c ) difference density from entries in the Protein Data Bank. In 48% of the 200 cases, the correct ligand was at the top of the ranked list of ligands. This approach may be useful in identification of unknown ligands in new macromolecular structures as well as in the identification of which ligands in a mixture have bound to a macromolecule