Tang Vivian W
Full Text Available Abstract Background Zonula occludens, also known as the tight junction, is a specialized cell-cell interaction characterized by membrane "kisses" between epithelial cells. A cytoplasmic plaque of ~100 nm corresponding to a meshwork of densely packed proteins underlies the tight junction membrane domain. Due to its enormous size and difficulties in obtaining a biochemically pure fraction, the molecular composition of the tight junction remains largely unknown. Results A novel biochemical purification protocol has been developed to isolate tight junction protein complexes from cultured human epithelial cells. After identification of proteins by mass spectroscopy and fingerprint analysis, candidate proteins are scored and assessed individually. A simple algorithm has been devised to incorporate transmembrane domains and protein modification sites for scoring membrane proteins. Using this new scoring system, a total of 912 proteins have been identified. These 912 hits are analyzed using a bioinformatics approach to bin the hits in 4 categories: configuration, molecular function, cellular function, and specialized process. Prominent clusters of proteins related to the cytoskeleton, cell adhesion, and vesicular traffic have been identified. Weaker clusters of proteins associated with cell growth, cell migration, translation, and transcription are also found. However, the strongest clusters belong to synaptic proteins and signaling molecules. Localization studies of key components of synaptic transmission have confirmed the presence of both presynaptic and postsynaptic proteins at the tight junction domain. To correlate proteomics data with structure, the tight junction has been examined using electron microscopy. This has revealed many novel structures including end-on cytoskeletal attachments, vesicles fusing/budding at the tight junction membrane domain, secreted substances encased between the tight junction kisses, endocytosis of tight junction
Tambor, V; Kacerovsky, M; Lenco, J; Bhat, G; Menon, R
The presence of microbial invasion of the amniotic cavity (MIAC) and histological chorioamnionitis (HCA) is associated with adverse neonatal outcomes in pregnancies complicated by preterm prelabor rupture of membranes (pPROM). Therefore, there is an urgent need to identify new biomarkers revealing these conditions. The objective of this study is to identify possible biomarkers and their underlying biofunctions in pPROM pregnancies with and without MIAC and HCA. A total of 72 women with pPROM were recruited. Only women with both MIAC and HCA (n = 19) and all women without these complications (n = 19) having the same range of gestational ages at sampling were included in the study. Samples of amniotic fluid were obtained by transabdominal amniocentesis, processed and analyzed using quantitative shotgun proteomics. Ingenuity pathway analysis was used to identify molecular networks that involve altered proteins. Network interaction identified by ingenuity pathway analysis revealed immunological disease and the inflammatory response as the top functions and disease associated with pPROM in the presence of MIAC and HCA. The proteins involved in these pathways were significantly altered between the groups with and without the presence of both MIAC and HCA. Proteins involved included histones H3, H4, H2B, cathelicidin antimicrobial peptide, myeloperoxidase, neutrophil gelatinase-associated lipocalin, matrix metalloproteinase-9, peptidoglycan recognition protein-1 and neutrophil defensin 1, all of which were found to be up-regulated in the presence of MIAC and HCA. Bioinformatic analysis of proteomics data allowed us to project likely biomolecular pathology resulting in pPROM complicated by MIAC and HCA. As inflammation is not a homogeneous phenomenon, we provide evidence for oxidative-stress-associated DNA damage and biomarkers of reactive oxygen species generation as factors associated with inflammation and proteolysis. Copyright © 2012 Elsevier Ltd. All rights reserved.
Xi, W-D; Liu, Y-J; Sun, X-B; Shan, J; Yi, L; Zhang, T-T
RNA-seq data of colon adenocarcinoma (COAD) were analyzed with bioinformatics tools to discover critical genes in the disease. Relevant small molecule drugs, transcription factors (TFs) and microRNAs (miRNAs) were also investigated. RNA-seq data of COAD were downloaded from The Cancer Genome Atlas (TCGA). Differential analysis was performed with package edgeR. False positive discovery (FDR) 1 were set as the cut-offs to screen out differentially expressed genes (DEGs). Gene coexpression network was constructed with package Ebcoexpress. GO enrichment analysis was performed for the DEGs in the gene coexpression network with DAVID. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was also performed for the genes with KOBASS 2.0. Modules were identified with MCODE of Cytoscape. Relevant small molecules drugs were predicted by Connectivity map. Relevant miRNAs and TFs were searched by WebGestalt. A total of 457 DEGs, including 255 up-regulated and 202 down-regulated genes, were identified from 437 COAD and 39 control samples. A gene coexpression network was constructed containing 40 DEGs and 101 edges. The genes were mainly associated with collagen fibril organization, extracellular matrix organization and translation. Two modules were identified from the gene coexpression network, which were implicated in muscle contraction and extracellular matrix organization, respectively. Several critical genes were disclosed, such as MYH11, COL5A2 and ribosomal proteins. Nine relevant small molecule drugs were identified, such as scriptaid and STOCK1N-35874. Accordingly, a total of 17 TFs and 10 miRNAs related to COAD were acquired, such as ETS2, NFAT, AP4, miR-124A, MiR-9, miR-96 and let-7. Several critical genes and relevant drugs, TFs and miRNAs were revealed in COAD. These findings could advance the understanding of the disease and benefit therapy development.
Pinney John W
Full Text Available Abstract Background The neprilysin (M13 family of endopeptidases are zinc-metalloenzymes, the majority of which are type II integral membrane proteins. The best characterised of this family is neprilysin, which has important roles in inactivating signalling peptides involved in modulating neuronal activity, blood pressure and the immune system. Other family members include the endothelin converting enzymes (ECE-1 and ECE-2, which are responsible for the final step in the synthesis of potent vasoconstrictor endothelins. The ECEs, as well as neprilysin, are considered valuable therapeutic targets for treating cardiovascular disease. Other members of the M13 family have not been functionally characterised, but are also likely to have biological roles regulating peptide signalling. The recent sequencing of animal genomes has greatly increased the number of M13 family members in protein databases, information which can be used to reveal evolutionary relationships and to gain insight into conserved biological roles. Results The phylogenetic analysis successfully resolved vertebrate M13 peptidases into seven classes, one of which appears to be specific to mammals, and insect genes into five functional classes and a series of expansions, which may include inactive peptidases. Nematode genes primarily resolved into groups containing no other taxa, bar the two nematode genes associated with Drosophila DmeNEP1 and DmeNEP4. This analysis reconstructed only one relationship between chordate and invertebrate clusters, that of the ECE sub-group and the DmeNEP3 related genes. Analysis of amino acid utilisation in the active site of M13 peptidases reveals a basis for their biochemical properties. A relatively invariant S1' subsite gives the majority of M13 peptidases their strong preference for hydrophobic residues in P1' position. The greater variation in the S2' subsite may be instrumental in determining the specificity of M13 peptidases for their substrates
Full Text Available The tRNA identity elements for some amino acids are distinct between the bacterial and archaeal domains. Searching in recent genomic and metagenomic sequence data, we found some candidate phyla radiation (CPR bacteria with archaeal tRNA identity for Tyr-tRNA and Trp-tRNA synthesis. These bacteria possess genes for tyrosyl-tRNA synthetase (TyrRS and tryptophanyl-tRNA synthetase (TrpRS predicted to be derived from DPANN superphylum archaea, while the cognate tRNATyr and tRNATrp genes reveal bacterial or archaeal origins. We identified a trace of domain fusion and swapping in the archaeal-type TyrRS gene of a bacterial lineage, suggesting that CPR bacteria may have used this mechanism to create diverse proteins. Archaeal-type TrpRS of bacteria and a few TrpRS species of DPANN archaea represent a new phylogenetic clade (named TrpRS-A. The TrpRS-A open reading frames (ORFs are always associated with another ORF (named ORF1 encoding an unknown protein without global sequence identity to any known protein. However, our protein structure prediction identified a putative HIGH-motif and KMSKS-motif as well as many α-helices that are characteristic of class I aminoacyl-tRNA synthetase (aaRS homologs. These results provide another example of the diversity of molecular components that implement the genetic code and provide a clue to the early evolution of life and the genetic code.
Full Text Available The drastic increase in the number of coronaviruses discovered and coronavirus genomes being sequenced have given us an unprecedented opportunity to perform genomics and bioinformatics analysis on this family of viruses. Coronaviruses possess the largest genomes (26.4 to 31.7 kb among all known RNA viruses, with G + C contents varying from 32% to 43%. Variable numbers of small ORFs are present between the various conserved genes (ORF1ab, spike, envelope, membrane and nucleocapsid and downstream to nucleocapsid gene in different coronavirus lineages. Phylogenetically, three genera, Alphacoronavirus, Betacoronavirus and Gammacoronavirus, with Betacoronavirus consisting of subgroups A, B, C and D, exist. A fourth genus, Deltacoronavirus, which includes bulbul coronavirus HKU11, thrush coronavirus HKU12 and munia coronavirus HKU13, is emerging. Molecular clock analysis using various gene loci revealed that the time of most recent common ancestor of human/civet SARS related coronavirus to be 1999-2002, with estimated substitution rate of 4´10-4 to 2´10-2 substitutions per site per year. Recombination in coronaviruses was most notable between different strains of murine hepatitis virus (MHV, between different strains of infectious bronchitis virus, between MHV and bovine coronavirus, between feline coronavirus (FCoV type I and canine coronavirus generating FCoV type II, and between the three genotypes of human coronavirus HKU1 (HCoV-HKU1. Codon usage bias in coronaviruses were observed, with HCoV-HKU1 showing the most extreme bias, and cytosine deamination and selection of CpG suppressed clones are the two major independent biological forces that shape such codon usage bias in coronaviruses.
Baldi, Pierre; Brunak, Søren
, and medicine will be particularly affected by the new results and the increased understanding of life at the molecular level. Bioinformatics is the development and application of computer methods for analysis, interpretation, and prediction, as well as for the design of experiments. It has emerged...
Pedro Manuel Martínez-García
Full Text Available The genome sequence of more than 100 Pseudomonas syringae strains has been sequenced to date; however only few of them have been fully assembled, including P. syringae pv. syringae B728a. Different strains of pv. syringae cause different diseases and have different host specificities; so, UMAF0158 is a P. syringae pv. syringae strain related to B728a but instead of being a bean pathogen it causes apical necrosis of mango trees, and the two strains belong to different phylotypes of pv.syringae and clades of P. syringae. In this study we report the complete sequence and annotation of P. syringae pv. syringae UMAF0158 chromosome and plasmid pPSS158. A comparative analysis with the available sequenced genomes of other 25 P. syringae strains, both closed (the reference genomes DC3000, 1448A and B728a and draft genomes was performed. The 5.8 Mb UMAF0158 chromosome has 59.3% GC content and comprises 5017 predicted protein-coding genes. Bioinformatics analysis revealed the presence of genes potentially implicated in the virulence and epiphytic fitness of this strain. We identified several genetic features, which are absent in B728a, that may explain the ability of UMAF0158 to colonize and infect mango trees: the mangotoxin biosynthetic operon mbo, a gene cluster for cellulose production, two different type III and two type VI secretion systems, and a particular T3SS effector repertoire. A mutant strain defective in the rhizobial-like T3SS Rhc showed no differences compared to wild-type during its interaction with host and non-host plants and worms. Here we report the first complete sequence of the chromosome of a pv. syringae strain pathogenic to a woody plant host. Our data also shed light on the genetic factors that possibly determine the pathogenic and epiphytic lifestyle of UMAF0158. This work provides the basis for further analysis on specific mechanisms that enable this strain to infect woody plants and for the functional analysis of host
Full Text Available The MocR bacterial transcriptional regulators are characterized by an N-terminal domain, 60 residues long on average, possessing the winged-helix-turn-helix (wHTH architecture responsible for DNA recognition and binding, linked to a large C-terminal domain (350 residues on average that is homologous to fold type-I pyridoxal 5′-phosphate (PLP dependent enzymes like aspartate aminotransferase (AAT. These regulators are involved in the expression of genes taking part in several metabolic pathways directly or indirectly connected to PLP chemistry, many of which are still uncharacterized. A bioinformatics analysis is here reported that studied the features of a distinct group of MocR regulators predicted to be functionally linked to a family of homologous genes coding for integral membrane proteins of unknown function. This group occurs mainly in the Actinobacteria and Gammaproteobacteria phyla. An analysis of the multiple sequence alignments of their wHTH and AAT domains suggested the presence of specificity-determining positions (SDPs. Mapping of SDPs onto a homology model of the AAT domain hinted at possible structural/functional roles in effector recognition. Likewise, SDPs in wHTH domain suggested the basis of specificity of Transcription Factor Binding Site recognition. The results reported represent a framework for rational design of experiments and for bioinformatics analysis of other MocR subgroups.
Abu-Jamous, Basel; Nandi, Asoke K
Clustering techniques are increasingly being put to use in the analysis of high-throughput biological datasets. Novel computational techniques to analyse high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. This book details the complete pathway of cluster analysis, from the basics of molecular biology to the generation of biological knowledge. The book also presents the latest clustering methods and clustering validation, thereby offering the reader a comprehensive review o
Evolution has shaped the life forms for billion of years. Domestication is an accelerated process that can be used as a model for evolutionary changes. The aim of this thesis project has been to carry out extensive bioinformatic analyses of whole genome sequencing data to reveal SNPs, InDels and selective sweeps in the chicken, pig and dog genome. Pig genome sequencing revealed loci under selection for elongation of back and increased number of vertebrae, associated with the NR6A1, PLAG1,...
and dhurrin, which have not previously been characterized in blueberries. There are more than 44,500 spider species with distinct habitats and unique characteristics. Spiders are masters of producing silk webs to catch prey and using venom to neutralize. The exploration of the genetics behind these properties...... japonicus (Lotus), Vaccinium corymbosum (blueberry), Stegodyphus mimosarum (spider) and Trifolium occidentale (clover). From a bioinformatics data analysis perspective, my work can be divided into three parts; genome annotation, small RNA, and gene expression analysis. Lotus is a legume of significant...... has just started. We have assembled and annotated the first two spider genomes to facilitate our understanding of spiders at the molecular level. The need for analyzing the large and increasing amount of sequencing data has increased the demand for efficient, user friendly, and broadly applicable...
japonicus (Lotus), Vaccinium corymbosum (blueberry), Stegodyphus mimosarum (spider) and Trifolium occidentale (clover). From a bioinformatics data analysis perspective, my work can be divided into three parts; genome annotation, small RNA, and gene expression analysis. Lotus is a legume of significant...... biology and genetics studies. We present an improved Lotus genome assembly and annotation, a catalog of natural variation based on re-sequencing of 29 accessions, and describe the involvement of small RNAs in the plant-bacteria symbiosis. Blueberries contain anthocyanins, other pigments and various...... polyphenolic compounds, which have been linked to protection against diabetes, cardiovascular disease and age-related cognitive decline. We present the first genome- guided approach in blueberry to identify genes involved in the synthesis of health-protective compounds. Using RNA-Seq data from five stages...
Wang, Xiran; Jiang, Leiyu; Tang, Haoru
GSTF12 has always been known as a key factor of proanthocyanins accumulate in plant testa. Through bioinformatics analysis of the nucleotide and encoded protein sequence of GSTF12, it is more advantageous to the study of genes related to anthocyanin biosynthesis accumulation pathway. Therefore, we chosen GSTF12 gene of 11 kinds species, downloaded their nucleotide and protein sequence from NCBI as the research object, found strawberry GSTF12 gene via bioinformation analyse, constructed phylogenetic tree. At the same time, we analysed the strawberry GSTF12 gene of physical and chemical properties and its protein structure and so on. The phylogenetic tree showed that Strawberry and petunia were closest relative. By the protein prediction, we found that the protein owed one proper signal peptide without obvious transmembrane regions.
In this thesis, I detail my 4-year efforts in developing bioinformatics tools and algorithms to address the growing demands of current proteomics endeavors, covering a range of facets such as large-scale protein expression profiling, charting post-translation modifications as well as
Full Text Available As is well known, soil is a complex ecosystem harboring the most prokaryotic biodiversity on the Earth. In recent years, the advent of high-throughput sequencing techniques has greatly facilitated the progress of soil ecological studies. However, how to effectively understand the underlying biological features of large-scale sequencing data is a new challenge. In the present study, we used 33 publicly available metagenomes from diverse soil sites (i.e. grassland, forest soil, desert, Arctic soil, and mangrove sediment and integrated some state-of-the-art computational tools to explore the phylogenetic and functional characterizations of the microbial communities in soil. Microbial composition and metabolic potential in soils were comprehensively illustrated at the metagenomic level. A spectrum of metagenomic biomarkers containing 46 taxa and 33 metabolic modules were detected to be significantly differential that could be used as indicators to distinguish at least one of five soil communities. The co-occurrence associations between complex microbial compositions and functions were inferred by network-based approaches. Our results together with the established bioinformatic pipelines should provide a foundation for future research into the relation between soil biodiversity and ecosystem function.
Chan, Landon L; Jiang, Peiyong
The discovery of cell-free DNA molecules in plasma has opened up numerous opportunities in noninvasive diagnosis. Cell-free DNA molecules have become increasingly recognized as promising biomarkers for detection and management of many diseases. The advent of next generation sequencing has provided unprecedented opportunities to scrutinize the characteristics of cell-free DNA molecules in plasma in a genome-wide fashion and at single-base resolution. Consequently, clinical applications of circulating cell-free DNA analysis have not only revolutionized noninvasive prenatal diagnosis but also facilitated cancer detection and monitoring toward an era of blood-based personalized medicine. With the remarkably increasing throughput and lowering cost of next generation sequencing, bioinformatics analysis becomes increasingly demanding to understand the large amount of data generated by these sequencing platforms. In this Review, we highlight the major bioinformatics algorithms involved in the analysis of cell-free DNA sequencing data. Firstly, we briefly describe the biological properties of these molecules and provide an overview of the general bioinformatics approach for the analysis of cell-free DNA. Then, we discuss the specific upstream bioinformatics considerations concerning the analysis of sequencing data of circulating cell-free DNA, followed by further detailed elaboration on each key clinical situation in noninvasive prenatal diagnosis and cancer management where downstream bioinformatics analysis is heavily involved. We also discuss bioinformatics analysis as well as clinical applications of the newly developed massively parallel bisulfite sequencing of cell-free DNA. Finally, we offer our perspectives on the future development of bioinformatics in noninvasive diagnosis. Copyright © 2015 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Adachi, Jun; Kumar, Chanchal; Zhang, Yanling
, mitochondria, membrane, and cytosol of 3T3-L1 adipocytes. We identified 3,287 proteins while essentially eliminating false positives, making this one of the largest high confidence proteomes reported to date. Comprehensive bioinformatics analysis revealed that the adipocyte proteome, despite its specialized...
Lue, Jaw-Chyng (Inventor); Fang, Wai-Chi (Inventor)
A system with applications in pattern recognition, or classification, of DNA assay samples. Because DNA reference and sample material in wells of an assay may be caused to fluoresce depending upon dye added to the material, the resulting light may be imaged onto an embodiment comprising an array of photodetectors and an adaptive neural network, with applications to DNA analysis. Other embodiments are described and claimed.
Repin, Rul Aisyah Mat; Mutalib, Sahilah Abdul; Shahimi, Safiyyah; Khalid, Rozida Mohd.; Ayob, Mohd. Khan; Bakar, Mohd. Faizal Abu; Isa, Mohd Noor Mat
In this study, we performed bioinformatics analysis toward genome sequence of Lysinibacillussphaericus (L. sphaericus) to determine gene encoded for gelatinase. L. sphaericus was isolated from soil and gelatinase species-specific bacterium to porcine and bovine gelatin. This bacterium offers the possibility of enzymes production which is specific to both species of meat, respectively. The main focus of this research is to identify the gelatinase encoded gene within the bacteria of L. Sphaericus using bioinformatics analysis of partially sequence genome. From the research study, three candidate gene were identified which was, gelatinase candidate gene 1 (P1), NODE_71_length_93919_cov_158.931839_21 which containing 1563 base pair (bp) in size with 520 amino acids sequence; Secondly, gelatinase candidate gene 2 (P2), NODE_23_length_52851_cov_190.061386_17 which containing 1776 bp in size with 591 amino acids sequence; and Thirdly, gelatinase candidate gene 3 (P3), NODE_106_length_32943_cov_169.147919_8 containing 1701 bp in size with 566 amino acids sequence. Three pairs of oligonucleotide primers were designed and namely as, F1, R1, F2, R2, F3 and R3 were targeted short sequences of cDNA by PCR. The amplicons were reliably results in 1563 bp in size for candidate gene P1 and 1701 bp in size for candidate gene P3. Therefore, the results of bioinformatics analysis of L. Sphaericus resulting in gene encoded gelatinase were identified.
Lin, Sabrina; Fonteno, Shawn; Satish, Shruthi; Bhanu, Bir; Talbot, Prue
Because video data are complex and are comprised of many images, mining information from video material is difficult to do without the aid of computer software. Video bioinformatics is a powerful quantitative approach for extracting spatio-temporal data from video images using computer software to perform dating mining and analysis. In this article, we introduce a video bioinformatics method for quantifying the growth of human embryonic stem cells (hESC) by analyzing time-lapse videos collected in a Nikon BioStation CT incubator equipped with a camera for video imaging. In our experiments, hESC colonies that were attached to Matrigel were filmed for 48 hours in the BioStation CT. To determine the rate of growth of these colonies, recipes were developed using CL-Quant software which enables users to extract various types of data from video images. To accurately evaluate colony growth, three recipes were created. The first segmented the image into the colony and background, the second enhanced the image to define colonies throughout the video sequence accurately, and the third measured the number of pixels in the colony over time. The three recipes were run in sequence on video data collected in a BioStation CT to analyze the rate of growth of individual hESC colonies over 48 hours. To verify the truthfulness of the CL-Quant recipes, the same data were analyzed manually using Adobe Photoshop software. When the data obtained using the CL-Quant recipes and Photoshop were compared, results were virtually identical, indicating the CL-Quant recipes were truthful. The method described here could be applied to any video data to measure growth rates of hESC or other cells that grow in colonies. In addition, other video bioinformatics recipes can be developed in the future for other cell processes such as migration, apoptosis, and cell adhesion. PMID:20495527
Andrew F. Hill
Full Text Available Extracellular vesicles (EVs are the collective term for the various vesicles that are released by cells into the extracellular space. Such vesicles include exosomes and microvesicles, which vary by their size and/or protein and genetic cargo. With the discovery that EVs contain genetic material in the form of RNA (evRNA has come the increased interest in these vesicles for their potential use as sources of disease biomarkers and potential therapeutic agents. Rapid developments in the availability of deep sequencing technologies have enabled the study of EV-related RNA in detail. In October 2012, the International Society for Extracellular Vesicles (ISEV held a workshop on “evRNA analysis and bioinformatics.” Here, we report the conclusions of one of the roundtable discussions where we discussed evRNA analysis technologies and provide some guidelines to researchers in the field to consider when performing such analysis.
Full Text Available Human G-protein coupled receptors (hGPCRs constitute a large and highly pharmaceutically relevant membrane receptor superfamily. About half of the hGPCRs' family members are chemosensory receptors, involved in bitter taste and olfaction, along with a variety of other physiological processes. Hence these receptors constitute promising targets for pharmaceutical intervention. Molecular modeling has been so far the most important tool to get insights on agonist binding and receptor activation. Here we investigate both aspects by bioinformatics-based predictions across all bitter taste and odorant receptors for which site-directed mutagenesis data are available. First, we observe that state-of-the-art homology modeling combined with previously used docking procedures turned out to reproduce only a limited fraction of ligand/receptor interactions inferred by experiments. This is most probably caused by the low sequence identity with available structural templates, which limits the accuracy of the protein model and in particular of the side-chains' orientations. Methods which transcend the limited sampling of the conformational space of docking may improve the predictions. As an example corroborating this, we review here multi-scale simulations from our lab and show that, for the three complexes studied so far, they significantly enhance the predictive power of the computational approach. Second, our bioinformatics analysis provides support to previous claims that several residues, including those at positions 1.50, 2.50, and 7.52, are involved in receptor activation.
Kaczor-Urbanowicz, Karolina Elzbieta; Kim, Yong; Li, Feng; Galeev, Timur; Kitchen, Rob R; Gerstein, Mark; Koyano, Kikuye; Jeong, Sung-Hee; Wang, Xiaoyan; Elashoff, David; Kang, So Young; Kim, Su Mi; Kim, Kyoung; Kim, Sung; Chia, David; Xiao, Xinshu; Rozowsky, Joel; Wong, David T W
Analysis of RNA sequencing (RNA-Seq) data in human saliva is challenging. Lack of standardization and unification of the bioinformatic procedures undermines saliva's diagnostic potential. Thus, it motivated us to perform this study. We applied principal pipelines for bioinformatic analysis of small RNA-Seq data of saliva of 98 healthy Korean volunteers including either direct or indirect mapping of the reads to the human genome using Bowtie1. Analysis of alignments to exogenous genomes by another pipeline revealed that almost all of the reads map to bacterial genomes. Thus, salivary exRNA has fundamental properties that warrant the design of unique additional steps while performing the bioinformatic analysis. Our pipelines can serve as potential guidelines for processing of RNA-Seq data of human saliva. Processing and analysis results of the experimental data generated by the exceRpt (v4.6.3) small RNA-seq pipeline (github.gersteinlab.org/exceRpt) are available from exRNA atlas (exrna-atlas.org). Alignment to exogenous genomes and their quantification results were used in this paper for the analyses of small RNAs of exogenous origin. email@example.com. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: firstname.lastname@example.org
He, Yongqun; Xiang, Zuoshuang
Brucella spp. are Gram-negative, facultative intracellular bacteria that cause brucellosis, one of the commonest zoonotic diseases found worldwide in humans and a variety of animal species. While several animal vaccines are available, there is no effective and safe vaccine for prevention of brucellosis in humans. VIOLIN (http://www.violinet.org) is a web-based vaccine database and analysis system that curates, stores, and analyzes published data of commercialized vaccines, and vaccines in clinical trials or in research. VIOLIN contains information for 454 vaccines or vaccine candidates for 73 pathogens. VIOLIN also contains many bioinformatics tools for vaccine data analysis, data integration, and vaccine target prediction. To demonstrate the applicability of VIOLIN for vaccine research, VIOLIN was used for bioinformatics analysis of existing Brucella vaccines and prediction of new Brucella vaccine targets. VIOLIN contains many literature mining programs (e.g., Vaxmesh) that provide in-depth analysis of Brucella vaccine literature. As a result of manual literature curation, VIOLIN contains information for 38 Brucella vaccines or vaccine candidates, 14 protective Brucella antigens, and 68 host response studies to Brucella vaccines from 97 peer-reviewed articles. These Brucella vaccines are classified in the Vaccine Ontology (VO) system and used for different ontological applications. The web-based VIOLIN vaccine target prediction program Vaxign was used to predict new Brucella vaccine targets. Vaxign identified 14 outer membrane proteins that are conserved in six virulent strains from B. abortus, B. melitensis, and B. suis that are pathogenic in humans. Of the 14 membrane proteins, two proteins (Omp2b and Omp31-1) are not present in B. ovis, a Brucella species that is not pathogenic in humans. Brucella vaccine data stored in VIOLIN were compared and analyzed using the VIOLIN query system. Bioinformatics curation and ontological representation of Brucella vaccines
Background Brucella spp. are Gram-negative, facultative intracellular bacteria that cause brucellosis, one of the commonest zoonotic diseases found worldwide in humans and a variety of animal species. While several animal vaccines are available, there is no effective and safe vaccine for prevention of brucellosis in humans. VIOLIN (http://www.violinet.org) is a web-based vaccine database and analysis system that curates, stores, and analyzes published data of commercialized vaccines, and vaccines in clinical trials or in research. VIOLIN contains information for 454 vaccines or vaccine candidates for 73 pathogens. VIOLIN also contains many bioinformatics tools for vaccine data analysis, data integration, and vaccine target prediction. To demonstrate the applicability of VIOLIN for vaccine research, VIOLIN was used for bioinformatics analysis of existing Brucella vaccines and prediction of new Brucella vaccine targets. Results VIOLIN contains many literature mining programs (e.g., Vaxmesh) that provide in-depth analysis of Brucella vaccine literature. As a result of manual literature curation, VIOLIN contains information for 38 Brucella vaccines or vaccine candidates, 14 protective Brucella antigens, and 68 host response studies to Brucella vaccines from 97 peer-reviewed articles. These Brucella vaccines are classified in the Vaccine Ontology (VO) system and used for different ontological applications. The web-based VIOLIN vaccine target prediction program Vaxign was used to predict new Brucella vaccine targets. Vaxign identified 14 outer membrane proteins that are conserved in six virulent strains from B. abortus, B. melitensis, and B. suis that are pathogenic in humans. Of the 14 membrane proteins, two proteins (Omp2b and Omp31-1) are not present in B. ovis, a Brucella species that is not pathogenic in humans. Brucella vaccine data stored in VIOLIN were compared and analyzed using the VIOLIN query system. Conclusions Bioinformatics curation and ontological
Yalcin, Dicle; Hakguder, Zeynep M; Otu, Hasan H
Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging and omics techniques on single cells. There have been improvements in computational single-cell image analysis in developmental biology regarding feature extraction, segmentation, image enhancement and machine learning, handling limitations of optical resolution to gain new perspectives from the raw microscopy images. Omics approaches, such as transcriptomics, genomics and epigenomics, targeting gene and small RNA expression, single nucleotide and structural variations and methylation and histone modifications, rely heavily on high-throughput sequencing technologies. Although there are well-established bioinformatics methods for analysis of sequence data, there are limited bioinformatics approaches which address experimental design, sample size considerations, amplification bias, normalization, differential expression, coverage, clustering and classification issues, specifically applied at the single-cell level. In this review, we summarize biological and technological advancements, discuss challenges faced in the aforementioned data acquisition and analysis issues and present future prospects for application of single-cell analyses to developmental biology. © The Author 2015. Published by Oxford University Press on behalf of the European
Kumar, Ranjit; Eipers, Peter; Little, Rebecca B; Crowley, Michael; Crossman, David K; Lefkowitz, Elliot J; Morrow, Casey D
Historically, in order to study microbes, it was necessary to grow them in the laboratory. It was clear though that many microbe communities were refractory to study because none of the members could be grown outside of their native habitat. The development of culture-independent methods to study microbiota using high-throughput sequencing of the 16S ribosomal RNA gene variable regions present in all prokaryotic organisms has provided new opportunities to investigate complex microbial communities. In this unit, the process for a microbiome analysis is described. Many of the components required for this process may already exist. A pipeline is described for acquisition of samples from different sites on the human body, isolation of microbial DNA, and DNA sequencing using the Illumina MiSeq sequencing platform. Finally, a new analytical workflow for basic bioinformatics data analysis, QWRAP, is described, which can be used by clinical and basic science investigators. Copyright © 2014 John Wiley & Sons, Inc.
Phosphoenolpyruvate carboxykinase (PEPCK), a critical gluconeogenic enzyme, catalyzes the first committed step in the diversion of tricarboxylic acid cycle intermediates toward gluconeogenesis. According to the relative conservation of homologous gene, a bioinformatics strategy was applied to clone Fusarium ...
Full Text Available Mitogen‐activated protein kinase kinase kinase (MAPKKK is a component of the MAPK cascade pathway that plays an important role in plant growth, development, and response to abiotic stress, the functions of which have been well characterized in several plant species, such as Arabidopsis, rice, and maize. In this study, we performed genome‐wide and systemic bioinformatics analysis of MAPKKK family genes in Medicago truncatula. In total, there were 73 MAPKKK family members identified by search of homologs, and they were classified into three subfamilies, MEKK, ZIK, and RAF. Based on the genomic duplication function, 72 MtMAPKKK genes were located throughout all chromosomes, but they cluster in different chromosomes. Using microarray data and high‐throughput sequencing‐data, we assessed their expression profiles in growth and development processes; these results provided evidence for exploring their important functions in developmental regulation, especially in the nodulation process. Furthermore, we investigated their expression in abiotic stresses by RNA‐seq, which confirmed their critical roles in signal transduction and regulation processes under stress. In summary, our genome‐wide, systemic characterization and expressional analysis of MtMAPKKK genes will provide insights that will be useful for characterizing the molecular functions of these genes in M. truncatula.
May 2, 2011 ... A virus-neutralizing antibody by a virus-specific synthetic peptide. J. Virol. 55(3): 836-839. Geourjon C, Deléage G (1995). SOPMA: significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments. Bioinformatics, 11(6): 681-684. Guex N, Peitsch MC ...
Jun 26, 2013 ... 2Bioinformatics and Biotechnology, DES, FBAS International Islamic University, Islamabad, Pakistan. Accepted 26 April, 2013. The Tp73 ... New discoveries about the control and function of p73 are still in progress and it is ..... modern research for diagnostics and evolutionary history of p73. REFERENCES.
Römer, Michael; Eichner, Johannes; Dräger, Andreas; Wrzodek, Clemens; Wrzodek, Finja; Zell, Andreas
Bioinformatics analysis has become an integral part of research in biology. However, installation and use of scientific software can be difficult and often requires technical expert knowledge. Reasons are dependencies on certain operating systems or required third-party libraries, missing graphical user interfaces and documentation, or nonstandard input and output formats. In order to make bioinformatics software easily accessible to researchers, we here present a web-based platform. The Center for Bioinformatics Tuebingen (ZBIT) Bioinformatics Toolbox provides web-based access to a collection of bioinformatics tools developed for systems biology, protein sequence annotation, and expression data analysis. Currently, the collection encompasses software for conversion and processing of community standards SBML and BioPAX, transcription factor analysis, and analysis of microarray data from transcriptomics and proteomics studies. All tools are hosted on a customized Galaxy instance and run on a dedicated computation cluster. Users only need a web browser and an active internet connection in order to benefit from this service. The web platform is designed to facilitate the usage of the bioinformatics tools for researchers without advanced technical background. Users can combine tools for complex analyses or use predefined, customizable workflows. All results are stored persistently and reproducible. For each tool, we provide documentation, tutorials, and example data to maximize usability. The ZBIT Bioinformatics Toolbox is freely available at https://webservices.cs.uni-tuebingen.de/.
Full Text Available Bioinformatics analysis has become an integral part of research in biology. However, installation and use of scientific software can be difficult and often requires technical expert knowledge. Reasons are dependencies on certain operating systems or required third-party libraries, missing graphical user interfaces and documentation, or nonstandard input and output formats. In order to make bioinformatics software easily accessible to researchers, we here present a web-based platform. The Center for Bioinformatics Tuebingen (ZBIT Bioinformatics Toolbox provides web-based access to a collection of bioinformatics tools developed for systems biology, protein sequence annotation, and expression data analysis. Currently, the collection encompasses software for conversion and processing of community standards SBML and BioPAX, transcription factor analysis, and analysis of microarray data from transcriptomics and proteomics studies. All tools are hosted on a customized Galaxy instance and run on a dedicated computation cluster. Users only need a web browser and an active internet connection in order to benefit from this service. The web platform is designed to facilitate the usage of the bioinformatics tools for researchers without advanced technical background. Users can combine tools for complex analyses or use predefined, customizable workflows. All results are stored persistently and reproducible. For each tool, we provide documentation, tutorials, and example data to maximize usability. The ZBIT Bioinformatics Toolbox is freely available at https://webservices.cs.uni-tuebingen.de/.
Lü, Bing-Jian; Cui, Jing; Xu, Jing; Zhang, Hao; Luo, Min-Jie; Zhu, Yi-Min; Lai, Mao-De
We established a colonic adenoma-normal mucosa suppressive subtraction hybridization (SSH) library in 1999. In this study, we wanted to explore the expression profile of all candidate genes in this library. We developed an EST pipeline which contained two in-house software packages, nucleic acid analytical software and GetUni. The nucleic acid analytical software, an integrator of the universal bioinformatics tools including phred, phd2fasta, cross_match, repeatmasker and blast2.0, can blast sequences of differential clones with the downloaded non-redundant nucleotide (NR) database. GetUni can cluster these NR sequences into Unigene via matching with the downloaded Homo Sapiens UniGene database. Sixty-two candidate genes in A-N library were obtained via the high throughput automatic gene expression bioinformatics pipeline. Gene Ontology online analysis revealed that ribosome genes and immunity-regulating genes were the two most common categories in the KEGG or Biocarta Pathway. We also detected the expression of 2 genes with highest hits, Reg4 and FAM46A, by semi-quantitative RT-PCR. Both genes were up-regulated in 10 or 9 out of 10 adenomas in comparison with the paired normal mucosa, respectively. The candidate genes in A-N library would be of great significance in disclosing the molecular mechanism underlying in colonic adenoma initiation and progression.
Full Text Available Background: Dental caries disease is a dynamic process with a multi-factorial etiology. It is manifested by demineralization of enamel followed by damage spreading into the tooth inner structure. Successful early diagnosis could identify caries-risk and improve dental screening, providing a baseline for evaluating personalized dental treatment and prevention strategies. Methodology:\tSalivary proteome of the whole unstimulated saliva (WUS samples was assessed in caries-free and caries-susceptible individuals of older adolescent age with permanent dentition using a nano-HPLC and MALDI-TOF/TOF mass spectrometry. Results: 554 proteins in the caries-free and 695 proteins in the caries-susceptible group were identified. Assessment using bioinformatics tools and Gene Ontology (GO term enrichment analysis revealed qualitative differences between these two proteomes. Members of the caries-susceptible group exhibited a branch of cytokine binding gene products responsible for the regulation of immune and inflammatory responses to infections. Inspection of molecular functions and biological processes of caries-susceptible saliva samples revealed significant categories predominantly related to the activity of proteolytic peptidases, and the regulation of metabolic and catabolic processes of carbohydrates. Conclusions: Proteomic analysis of the whole saliva revealed information about potential risk factors associated with the development of caries-susceptibility and provides a better understanding of tooth protection mechanisms.
Sánchez-Burgos, Gilma; Ramos-Castañeda, José; Cedillo-Rivera, Roberto; Dumonteil, Eric
We used T cell epitope prediction tools to identify epitopes from Dengue virus polyprotein sequences, and evaluated in vivo and in vitro the immunogenicity and antigenicity of the corresponding synthetic vaccine candidates. Twenty-two epitopes were predicted to have a high affinity for MHC class I (H-2Kd, H-2Dd, H-2Ld alleles) or class II (IAd alleles). These epitopes were conserved between the four virus serotypes, but with no similarity to human and mouse sequences. Thirteen synthetic peptides induced specific antibodies production with or without T cells activation in mice. Three synthetic peptides induced mostly IgG antibodies, and one of these from the E gene induced a neutralizing response. Ten peptides induced a combination of humoral and cellular responses by CD4+ and CD8+ T cells. Twelve peptides were novel B and T cell epitopes. These results indicate that our bioinformatics strategy is a powerful tool for the identification of novel antigens and its application to human HLA may lead to a potent epitope-based vaccine against Dengue virus and many other pathogens. (c) 2010 Elsevier B.V. All rights reserved.
Balqis, Widodo, Lukiati, Betty; Amin, Mohamad
A way to improve the quality of learning in the course of Plant Metabolism in the Department of Biology, State University of Malang, is to develop teaching materials. This research evaluates the needs of bioinformatics-based teaching material in the course Plant Metabolism by the Analyze, Design, Develop, Implement, and Evaluate (ADDIE) development model. Data were collected through questionnaires distributed to the students in the Plant Metabolism course of the Department of Biology, University of Malang, and analysis of the plan of lectures semester (RPS). Learning gains of this course show that it is not yet integrated into the field of bioinformatics. All respondents stated that plant metabolism books do not include bioinformatics and fail to explain the metabolism of a chemical compound of a local plant in Indonesia. Respondents thought that bioinformatics can explain examples and metabolism of a secondary metabolite analysis techniques and discuss potential medicinal compounds from local plants. As many as 65% of the respondents said that the existing metabolism book could not be used to understand secondary metabolism in lectures of plant metabolism. Therefore, the development of teaching materials including plant metabolism-based bioinformatics is important to improve the understanding of the lecture material in plant metabolism.
Shachak, Aviv; Ophir, Ron; Rubin, Eitan
The need to support bioinformatics training has been widely recognized by scientists, industry, and government institutions. However, the discussion of instructional methods for teaching bioinformatics is only beginning. Here we report on a systematic attempt to design two bioinformatics workshops for graduate biology students on the basis of Gagne's Conditions of Learning instructional design theory. This theory, although first published in the early 1970s, is still fundamental in instructional design and instructional technology. First, top-level as well as prerequisite learning objectives for a microarray analysis workshop and a primer design workshop were defined. Then a hierarchy of objectives for each workshop was created. Hands-on tutorials were designed to meet these objectives. Finally, events of learning proposed by Gagne's theory were incorporated into the hands-on tutorials. The resultant manuals were tested on a small number of trainees, revised, and applied in 1-day bioinformatics workshops. Based on this experience and on observations made during the workshops, we conclude that Gagne's Conditions of Learning instructional design theory provides a useful framework for developing bioinformatics training, but may not be optimal as a method for teaching it.
Deka, Ranjit K.; Brautigam, Chad A.; Goldberg, Martin; Schuck, Peter; Tomchick, Diana R.; Norgard, Michael V. (NIH); (UTSMC)
Treponema pallidum, the bacterial agent of syphilis, is predicted to encode one tripartite ATP-independent periplasmic transporter (TRAP-T). TRAP-Ts typically employ a periplasmic substrate-binding protein (SBP) to deliver the cognate ligand to the transmembrane symporter. Herein, we demonstrate that the genes encoding the putative TRAP-T components from T. pallidum, tp0957 (the SBP), and tp0958 (the symporter), are in an operon with an uncharacterized third gene, tp0956. We determined the crystal structure of recombinant Tp0956; the protein is trimeric and perforated by a pore. Part of Tp0956 forms an assembly similar to those of 'tetratricopeptide repeat' (TPR) motifs. The crystal structure of recombinant Tp0957 was also determined; like the SBPs of other TRAP-Ts, there are two lobes separated by a cleft. In these other SBPs, the cleft binds a negatively charged ligand. However, the cleft of Tp0957 has a strikingly hydrophobic chemical composition, indicating that its ligand may be substantially different and likely hydrophobic. Analytical ultracentrifugation of the recombinant versions of Tp0956 and Tp0957 established that these proteins associate avidly. This unprecedented interaction was confirmed for the native molecules using in vivo cross-linking experiments. Finally, bioinformatic analyses suggested that this transporter exemplifies a new subfamily of TPATs (TPR-protein-associated TRAP-Ts) that require the action of a TPR-containing accessory protein for the periplasmic transport of a potentially hydrophobic ligand(s).
Full Text Available Argonaute protein family is the key players in pathways of gene silencing and small regulatory RNAs in different organisms. Argonaute proteins can bind small noncoding RNAs and control protein synthesis, affect messenger RNA stability, and even participate in the production of new forms of small RNAs. The aim of this study was to characterize and perform bioinformatic analysis of Argonaute proteins in 32 plant species that their genome was sequenced. A total of 437 Argonaute genes were identified and were analyzed based on lengths, gene structure, and protein structure. Results showed that Argonaute proteins were highly conserved across plant kingdom. Phylogenic analysis divided plant Argonautes into three classes. Argonaute proteins have three conserved domains PAZ, MID and PIWI. In addition to three conserved domains namely, PAZ, MID, and PIWI, we identified few more domains in AGO of some plant species. Expression profile analysis of Argonaute proteins showed that expression of these genes varies in most of tissues, which means that these proteins are involved in regulation of most pathways of the plant system. Numbers of alternative transcripts of Argonaute genes were highly variable among the plants. A thorough analysis of large number of putative Argonaute genes revealed several interesting aspects associated with this protein and brought novel information with promising usefulness for both basic and biotechnological applications.
Philippe, Florian; Pelloux, Jérôme; Rayon, Catherine
Pectins are plant cell wall polysaccharides that can be acetylated on C2 and/or C3 of galacturonic acid residues. The degree of acetylation of pectin can be modulated by pectin acetylesterase (EC 220.127.116.11, PAE). The function and structure of plant PAEs remain poorly understood and the role of the fine-tuning of pectin acetylation on cell wall properties has not yet been elucidated. In the present study, a bioinformatic approach was used on 72 plant PAEs from 16 species among 611 plant PAEs available in plant genomic databases. An overview of plant PAE proteins, particularly Arabidopsis thaliana PAEs, based on phylogeny analysis, protein motif identification and modeled 3D structure is presented. A phylogenetic tree analysis using protein sequences clustered the plant PAEs into five clades. AtPAEs clustered in four clades in the plant kingdom PAE tree while they formed three clades when a phylogenetic tree was performed only on Arabidopsis proteins, due to isoform AtPAE9. Primitive plants that display a smaller number of PAEs clustered into two clades, while in higher plants, the presence of multiple members of PAE genes indicated a diversification of AtPAEs. 3D homology modeling of AtPAE8 from clade 2 with a human Notum protein showed an α/β hydrolase structure with the hallmark Ser-His-Asp of the active site. A 3D model of AtPAE4 from clade 1 and AtPAE10 from clade 3 showed a similar shape suggesting that the diversification of AtPAEs is unlikely to arise from the shape of the protein. Primary structure prediction analysis of AtPAEs showed a specific motif characteristic of each clade and identified one major group of AtPAEs with a signal peptide and one group without a signal peptide. A multiple sequence alignment of the putative plant PAEs revealed consensus sequences with important putative catalytic residues: Ser, Asp, His and a pectin binding site. Data mining of gene expression profiles of AtPAE revealed that genes from clade 2 including AtPAE7, AtPAE8 and
Kamali, Amir Hossein; Giannoulatou, Eleni; Chen, Tsong Yueh; Charleston, Michael A; McEwan, Alistair L; Ho, Joshua W K
Bioinformatics is the application of computational, mathematical and statistical techniques to solve problems in biology and medicine. Bioinformatics programs developed for computational simulation and large-scale data analysis are widely used in almost all areas of biophysics. The appropriate choice of algorithms and correct implementation of these algorithms are critical for obtaining reliable computational results. Nonetheless, it is often very difficult to systematically test these programs as it is often hard to verify the correctness of the output, and to effectively generate failure-revealing test cases. Software testing is an important process of verification and validation of scientific software, but very few studies have directly dealt with the issues of bioinformatics software testing. In this work, we review important concepts and state-of-the-art methods in the field of software testing. We also discuss recent reports on adapting and implementing software testing methodologies in the bioinformatics field, with specific examples drawn from systems biology and genomic medicine.
Saila Viridiana Cázares-García
Full Text Available The genus Trichoderma includes species of great biotechnological value, both for their mycoparasitic activities and for their ability to produce extracellular hydrolytic enzymes. Although activity of extracellular laccase has previously been reported in Trichoderma spp., the possible number of isoenzymes is still unknown, as are the structural and functional characteristics of both the genes and the putative proteins. In this study, the system of laccases sensu stricto in the Trichoderma species, the genomes of which are publicly available, were analyzed using bioinformatic tools. The intron/exon structure of the genes and the identification of specific motifs in the sequence of amino acids of the proteins generated in silico allow for clear differentiation between extracellular and intracellular enzymes. Phylogenetic analysis suggests that the common ancestor of the genus possessed a functional gene for each one of these enzymes, which is a characteristic preserved in T. atroviride and T. virens. This analysis also reveals that T. harzianum and T. reesei only retained the intracellular activity, whereas T. asperellum added an extracellular isoenzyme acquired through horizontal gene transfer during the mycoparasitic process. The evolutionary analysis shows that in general, extracellular laccases are subjected to purifying selection, and intracellular laccases show neutral evolution. The data provided by the present study will enable the generation of experimental approximations to better understand the physiological role of laccases in the genus Trichoderma and to increase their biotechnological potential.
Cázares-García, Saila Viridiana; Vázquez-Garcidueñas, Soledad; Vázquez-Marrufo, Gerardo
The genus Trichoderma includes species of great biotechnological value, both for their mycoparasitic activities and for their ability to produce extracellular hydrolytic enzymes. Although activity of extracellular laccase has previously been reported in Trichoderma spp., the possible number of isoenzymes is still unknown, as are the structural and functional characteristics of both the genes and the putative proteins. In this study, the system of laccases sensu stricto in the Trichoderma species, the genomes of which are publicly available, were analyzed using bioinformatic tools. The intron/exon structure of the genes and the identification of specific motifs in the sequence of amino acids of the proteins generated in silico allow for clear differentiation between extracellular and intracellular enzymes. Phylogenetic analysis suggests that the common ancestor of the genus possessed a functional gene for each one of these enzymes, which is a characteristic preserved in T. atroviride and T. virens. This analysis also reveals that T. harzianum and T. reesei only retained the intracellular activity, whereas T. asperellum added an extracellular isoenzyme acquired through horizontal gene transfer during the mycoparasitic process. The evolutionary analysis shows that in general, extracellular laccases are subjected to purifying selection, and intracellular laccases show neutral evolution. The data provided by the present study will enable the generation of experimental approximations to better understand the physiological role of laccases in the genus Trichoderma and to increase their biotechnological potential.
Bioinformatic analysis of Rp1 gene causing visual disparity in humans. Sana Zahra and ... mRNA degradation but also results in truncated protein production leading towards visual disparity in humans. Secondary structure of RP1 gene was ..... The comparison clearly supports the fact that missense mutation R677X causes ...
Boomsma, Wouter Krogh; Nielsen, Sofie Vincents; Lindorff-Larsen, Kresten
conduct a bioinformatics analysis to examine >600 human and S. cerevisiae E3 ligases to identify enzymes that are similar to San1 in terms of function and/or mechanism of substrate recognition. An initial sequence-based database search was found to detect candidates primarily based on the homology...
Shao, Jia; Yu, Miao; Jiang, Liang; Wu, Fengliang; Liu, Xiaoguang
The purpose of this study was to detect the differentially expressed genes between ossified herniated discs and herniated discs without ossification. In addition, we sought to identify a few candidate genes and pathways by using bioinformatics analysis. We analyzed 6 samples each of ossified herniated discs (experimental group) and herniated discs without ossification (control group). Purified mRNA and cDNA extracted from the samples were subjected to sequencing. The NOISeq method was used to statistically identify the differentially expressed genes (DEGs) between the 2 groups. An in-depth analysis using bioinformatics tools based on the DEGs was performed using Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and protein-protein interaction network analysis. The top 6 DEGs were verified using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). A total of 132 DEGs was detected. A total of 129 genes in the ossified group were upregulated and 3 genes were found to be downregulated as compared to the control group. The top 3 cellular components in GO ontologies analysis were extracellular matrix components. GO functions were mainly related to the glycoprotein in the cell membrane and extracellular matrix. The GO process was related to completing response to stimulus, immune reflex and defense. The top 5 KEGG enrichment pathways were associated with infection and inflammation. Three of the top 20 DEGs [sclerostin (SOST), WNT inhibitory factor 1 (WIF1) and secreted frizzled related protein 4 (SFRP4)] were related to the inhibition of the Wnt pathway. The ossified discs exhibited a higher expression of the top 6 DEGs [SOST, joining chain of multimeric IgA and IgM (IGJ; also known as JCHAIN), defensin alpha 4 (DEFA4), SFRP4, proteinase 3 (PRTN3) and cathepsin G (CTSG)], with the associated P-values of 0.045, 0.000, 0.008, 0.010, 0.015 and 0.002, respectively, as
Full Text Available Crude extracts of house dust mites are used clinically for diagnosis and immunotherapy of allergic diseases, including bronchial asthma, perennial rhinitis, and atopic dermatitis. However, crude extracts are complexes with non-allergenic antigens and lack effective concentrations of important allergens, resulting in several side effects. Dermatophagoides farinae (Hughes; Acari: Pyroglyphidae is one of the predominant sources of dust mite allergens, which has more than 30 groups of allergen. The cDNA coding for the group 5 allergen of D. farinae from China was cloned, sequenced and expressed. According to alignment using the VECTOR NTI 9.0 software, there were eight mismatched nucleotides in five cDNA clones resulting in seven incompatible amino acid residues, suggesting that the Der f 5 allergen might have sequence polymorphism. Bioinformatics analysis revealed that the matured Der f 5 allergen has a molecular mass of 13604.03 Da, a theoretical pI of 5.43 and is probably hydrophobic and cytoplasmic. Similarities in amino acid sequences between Der f 5 and allergens of other domestic mite species, viz. Der p 5, Blo t 5, Sui m 5, and Lep d 5, were 79, 48, 53, and 37%, respectively. Phylogenetic analysis indicated that Der f 5 and Der p 5 clustered together. Blo t 5 and Ale o 5 also clustered together, although Blomia tropicalis and Aleuroglyphus ovatus belong to different mite families, viz. Echimyopodidae and Acaridae, respectively.
Liu, Zhongyang; Guo, Feifei; Wang, Yong; Li, Chun; Zhang, Xinlei; Li, Honglei; Diao, Lihong; Gu, Jiangyong; Wang, Wei; Li, Dong; He, Fuchu
Traditional Chinese Medicine (TCM), with a history of thousands of years of clinical practice, is gaining more and more attention and application worldwide. And TCM-based new drug development, especially for the treatment of complex diseases is promising. However, owing to the TCM’s diverse ingredients and their complex interaction with human body, it is still quite difficult to uncover its molecular mechanism, which greatly hinders the TCM modernization and internationalization. Here we developed the first online Bioinformatics Analysis Tool for Molecular mechANism of TCM (BATMAN-TCM). Its main functions include 1) TCM ingredients’ target prediction; 2) functional analyses of targets including biological pathway, Gene Ontology functional term and disease enrichment analyses; 3) the visualization of ingredient-target-pathway/disease association network and KEGG biological pathway with highlighted targets; 4) comparison analysis of multiple TCMs. Finally, we applied BATMAN-TCM to Qishen Yiqi dripping Pill (QSYQ) and combined with subsequent experimental validation to reveal the functions of renin-angiotensin system responsible for QSYQ’s cardioprotective effects for the first time. BATMAN-TCM will contribute to the understanding of the “multi-component, multi-target and multi-pathway” combinational therapeutic mechanism of TCM, and provide valuable clues for subsequent experimental validation, accelerating the elucidation of TCM’s molecular mechanism. BATMAN-TCM is available at http://bionet.ncpsb.org/batman-tcm.
Full Text Available Over the past 30 years, genomic and bioinformatic analysis of human adenoviruses has been achieved using a variety of DNA sequencing methods; initially with the use of restriction enzymes and more currently with the use of the GS FLX pyrosequencing technology. Following the conception of DNA sequencing in the 1970s, analysis of adenoviruses has evolved from 100 base pair mRNA fragments to entire genomes. Comparative genomics of adenoviruses made its debut in 1984 when nucleotides and amino acids of coding sequences within the hexon genes of two human adenoviruses (HAdV, HAdV–C2 and HAdV–C5, were compared and analyzed. It was determined that there were three different zones (1-393, 394-1410, 1411-2910 within the hexon gene, of which HAdV–C2 and HAdV–C5 shared zones 1 and 3 with 95% and 89.5% nucleotide identity, respectively. In 1992, HAdV-C5 became the first adenovirus genome to be fully sequenced using the Sanger method. Over the next seven years, whole genome analysis and characterization was completed using bioinformatic tools such as blastn, tblastx, ClustalV and FASTA, in order to determine key proteins in species HAdV-A through HAdV-F. The bioinformatic revolution was initiated with the introduction of a novel species, HAdV-G, that was typed and named by the use of whole genome sequencing and phylogenetics as opposed to traditional serology. HAdV bioinformatics will continue to advance as the latest sequencing technology enables scientists to add to and expand the resource databases. As a result of these advancements, how novel HAdVs are typed has changed. Bioinformatic analysis has become the revolutionary tool that has significantly accelerated the in-depth study of HAdV microevolution through comparative genomics.
Jan 26, 2012 ... JVIRTUAL GEL. GELBANK was available from the NCBI FTP server. This website incorporates only completed genomes and information pertinent to 2-DE. Link is available at www.gelbank.anl.gov. JVirGel is a software for the simulation and analysis of proteomics data (http://www.jvirgel.de/). The Java TM.
Bai, Baoyan; Laiho, Marikki
Small RNAs (size 20-30 nt) of various types have been actively investigated in recent years, and their subcellular compartmentalization and relative concentrations are likely to be of importance to their cellular and physiological functions. Comprehensive data on this subset of the transcriptome can only be obtained by application of high-throughput sequencing, which yields data that are inherently complex and multidimensional, as sequence composition, length, and abundance will all inform to the small RNA function. Subsequent data analysis, hypothesis testing, and presentation/visualization of the results are correspondingly challenging. We have constructed small RNA libraries derived from different cellular compartments, including the nucleolus, and asked whether small RNAs exist in the nucleolus and whether they are distinct from cytoplasmic and nuclear small RNAs, the miRNAs. Here, we present a workflow for analysis of small RNA sequencing data generated by the Ion Torrent PGM sequencer from samples derived from different cellular compartments.
Ilnytskyy, Slava; Bilichak, Andriy
Next-generation sequencing became a method of choice for the investigation of small RNA transcriptomes in plants and animals. Although a technical side of sequencing itself is becoming routine, and experimental costs are affordable, data analysis still remains a challenge, especially for researchers with limited computational experience. Here, we present a detailed description of a computational workflow designed to take raw sequencing reads as input, to obtain small RNA predictions, and to detect the differentially expressed microRNAs as a result. The exact commands and pieces of code are provided and hopefully can be adapted and used by other researchers to facilitate the study of small RNA regulation.
Liu, S Y; Zhang, L; Zhang, Y; Zhen, Y; Wu, Y F
We aimed to identify important genes associated with septic shock and then explore the possibly significant mechanisms of this disease. We downloaded GSE26440 expression data of samples from 98 children with septic shock and 32 normal controls from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in samples from patients with septic shock were analyzed in comparison with those in samples from normal controls using a limma package. Functional enrichment analysis for DEGs was performed using DAVID, and a proteinprotein interaction (PPI) network was constructed. Upstream transcription factors for DEGs were predicted using the CHIPBase database, and a transcriptional regulation network was constructed. A total of 383 significantly DEGs, including 141 downregulated and 242 upregulated genes, were obtained in the sepsis shock group compared with the normal group. The top five nodes in the PPI network were lysine (K)-specific demethylase 6B (KDM6B), histone deacetylase 2 (HDAC2), V-Myc avian myelocytomatosis viral oncogene homolog (MYC), heat-shock protein 90 kDa alpha (cytosolic), class B member 1 (HSP90AB1), and poly (A)-binding protein, cytoplasmic 1 (PABPC1). Nuclear factor kappa-light-chain-enhancer of activated B cells (NFkB) was the transcription factor targeted by most genes, and it regulated the expression of KDM6B, HDAC2, MYC, HSP90AB1, and PABPC1. In conclusion, KDM6B, HDAC2, MYC, HSP90AB1, and PABPC1 may play important roles in the development of septic shock. Furthermore, NFκB may be involved in septic shock by regulating the expression of KDM6B, HDAC2, MYC, HSP90AB1, and PABPC1.
Hu, Hongtao; Yu, Dazhao; Liu, Hong
Small RNAs (sRNAs) are ~20 to 24 nucleotide single-stranded RNAs that play crucial roles in regulation of gene expression. In plants, sRNAs are classified into microRNAs (miRNAs), repeat-associated siRNAs (ra-siRNAs), phased siRNAs (pha-siRNAs), cis and trans natural antisense transcript siRNAs (cis- and trans-nat siRNAs). Pima (Gossypium barbadense L.) is one of the most economically important fiber crops, producing the best and longest spinnable fiber. Although some miRNAs are profiled in Pima, little is known about siRNAs, the largest subclass of plant sRNAs. In order to profile these gene regulators in Pima, a comprehensive analysis of sRNAs was conducted by mining publicly available sRNA data, leading to identification of 678 miRNAs, 3,559,126 ra-siRNAs, 627 pha-siRNAs, 136,600 cis-nat siRNAs and 79,994 trans-nat siRNAs. The 678 miRNAs, belonging to 98 conserved and 402 lineage-specific families, were produced from 2,138 precursors, of which 297 arose from introns, exons, or intron/UTR-exon junctions of protein-coding genes. Ra-siRNAs were produced from various repeat loci, while most (97%) were yielded from retrotransposons, especially LTRs (long terminal repeats). The genes encoding auxin-signaling-related proteins, NBS-LRRs and transcription factors were major sources of pha-siRNAs, while two conserved TAS3 homologs were found as well. Most cis-NATs in Pima overlapped in enclosed and convergent orientations, while a few hybridized in divergent and coincided orientations. Most cis- and trans-nat siRNAs were produced from overlapping regions. Additionally, characteristics of length and the 5’-first nucleotide of each sRNA class were analyzed as well. Results in this study created a valuable molecular resource that would facilitate studies on mechanism of controlling gene expression. PMID:25679373
Zhuang, Qi-Shuai; Zheng, Hao; Gu, Xiao-Dan; Shen, Liang; Ji, Hong-Fang
Alzheimer's disease (AD) represents the major form of dementia in the elderly. In recent years, accumulating evidence indicate that obesity may act as a risk factor for AD, while the genetic link between the two conditions remains unclear. This bioinformatics analysis aimed to detect the genetic link between AD and obesity on single nucleotide polymorphisms (SNPs), gene, and pathway levels based on genome-wide association studies data. A total of 31 SNPs were found to be shared by AD and obes...
Ian B Robertson
Full Text Available Proteins from the LTBP/fibrillin family perform key structural and functional roles in connective tissues. LTBP1 forms the large latent complex with TGFβ and its propeptide LAP, and sequesters the latent growth factor to the extracellular matrix. Bioinformatics studies suggest the main structural features of the LTBP1 C-terminus are conserved through evolution. NMR studies were carried out on three overlapping C-terminal fragments of LTBP1, comprising four domains with characterised homologues, cbEGF14, TB3, EGF3 and cbEGF15, and three regions with no homology to known structures. The NMR data reveal that the four domains adopt canonical folds, but largely lack the interdomain interactions observed with homologous fibrillin domains; the exception is the EGF3-cbEGF15 domain pair which has a well-defined interdomain interface. (15N relaxation studies further demonstrate that the three interdomain regions act as flexible linkers, allowing a wide range of motion between the well-structured domains. This work is consistent with the LTBP1 C-terminus adopting a flexible "knotted rope" structure, which may facilitate cell matrix interactions, and the accessibility to proteases or other factors that could contribute to TGFβ activation.
Full Text Available Background/Aims: Breast cancer is a common cause of cancer mortality throughout the world. The cross-talk between cancer cells and interstitial cells exerts significant effects on neoplasia and tumor development and is modulated in part by chemokines. CXC is one of four chemokine families involved in mediating survival, angiogenesis, and immunosensitization by chemoattracting leukocytes, and it incentivizes tumor cell growth, invasion and metastasis in the tumor microenvironment. However, the differential expression profiles and prognostic values of these chemokines remains to be elucidated. Methods: In this study, we compared transcriptional CXC chemokines and survival data of patients with breast carcinoma (BC using the ONCOMINE dataset, Kaplan-Meier Plotter, TCGA and cBioPortal. Results: We discovered increased mRNA levels for CXCL8/10/11/16/17, whereas mRNA expression of CXCL1/2/3/4/5/6/7/12/14 was lower in BC patients compared to non-tumor tissues. Kaplan-Meier plots revealed that high mRNA levels of CXCL1/2/3/4/5/6/7/12/14 correlate with relapse-free survival (RFS in all types of BC patients. Conversely, high CXCL8/10/11 predicted worse RFS in BC patients. Significantly, high transcription levels of CXCL9/12/13/14 conferred an overall survival (OS advantage in BC patients, while high levels of CXCL8 demonstrated shorter OS in all BC sufferers. Conclusions: Integrative bioinformatics analysis suggests that CXCL8/12/14 are potential suitable targets for precision therapy in BC patients compared to other CXC chemokines.
Chen, Erbao; Qin, Xuan; Peng, Ke; Xu, Xiaojing; Li, Wei; Cheng, Xi; Tang, Cheng; Cui, Yuehong; Wang, Zhiming; Liu, Tianshu
Breast cancer is a common cause of cancer mortality throughout the world. The cross-talk between cancer cells and interstitial cells exerts significant effects on neoplasia and tumor development and is modulated in part by chemokines. CXC is one of four chemokine families involved in mediating survival, angiogenesis, and immunosensitization by chemoattracting leukocytes, and it incentivizes tumor cell growth, invasion and metastasis in the tumor microenvironment. However, the differential expression profiles and prognostic values of these chemokines remains to be elucidated. In this study, we compared transcriptional CXC chemokines and survival data of patients with breast carcinoma (BC) using the ONCOMINE dataset, Kaplan-Meier Plotter, TCGA and cBioPortal. We discovered increased mRNA levels for CXCL8/10/11/16/17, whereas mRNA expression of CXCL1/2/3/4/5/6/7/12/14 was lower in BC patients compared to non-tumor tissues. Kaplan-Meier plots revealed that high mRNA levels of CXCL1/2/3/4/5/6/7/12/14 correlate with relapse-free survival (RFS) in all types of BC patients. Conversely, high CXCL8/10/11 predicted worse RFS in BC patients. Significantly, high transcription levels of CXCL9/12/13/14 conferred an overall survival (OS) advantage in BC patients, while high levels of CXCL8 demonstrated shorter OS in all BC sufferers. Integrative bioinformatics analysis suggests that CXCL8/12/14 are potential suitable targets for precision therapy in BC patients compared to other CXC chemokines. © 2018 The Author(s). Published by S. Karger AG, Basel.
Hamada, Michiaki; Kiryu, Hisanori; Iwasaki, Wataru; Asai, Kiyoshi
In a number of estimation problems in bioinformatics, accuracy measures of the target problem are usually given, and it is important to design estimators that are suitable to those accuracy measures. However, there is often a discrepancy between an employed estimator and a given accuracy measure of the problem. In this study, we introduce a general class of efficient estimators for estimation problems on high-dimensional binary spaces, which represent many fundamental problems in bioinformatics. Theoretical analysis reveals that the proposed estimators generally fit with commonly-used accuracy measures (e.g. sensitivity, PPV, MCC and F-score) as well as it can be computed efficiently in many cases, and cover a wide range of problems in bioinformatics from the viewpoint of the principle of maximum expected accuracy (MEA). It is also shown that some important algorithms in bioinformatics can be interpreted in a unified manner. Not only the concept presented in this paper gives a useful framework to design MEA-based estimators but also it is highly extendable and sheds new light on many problems in bioinformatics. PMID:21365017
Marie, Pauline; Labas, Valérie; Brionne, Aurélien; Harichaux, Grégoire; Hennequet-Antier, Christelle; Nys, Yves; Gautron, Joël
Gallus gallus eggshell is a bioceramic composed of 95% calcium carbonate in calcitic form and 3.5% extracellular organic matrix. The calcification process occurs in the uterine fluid where biomineralization follows a temporal sequence corresponding to the initiation, growth and termination stages of crystal growth. Eggshell texture and its ultrastructure are regulated by organic matrix proteins, which control mineralization process and influence the eggshell biomechanical properties. We performed proteomic qualitative analyses and identified 308 uterine fluid proteins. Quantitative analysis showed differential abundances at the three stages of shell biomineralization for 64 of them. Cluster analysis revealed a first group of proteins related to mineralization and mainly present at the onset of calcification including OVOT, OVAL, OC-17, and two novel calcium binding proteins (EDIL3, MFGE8). A second group of proteins mainly present at the initiation and termination of shell formation was potentially involved in the regulation of the activity of the uterine fluid proteins (e.g. molecular chaperones, folding proteins, proteases and protease inhibitors). OCX21, a protein highly concentrated in the fluid and the shell, belongs to this group. A third group equally represented at all stages of shell mineralization corresponded to antibacterial proteins that could protect the forming egg against microbial invasion. The calcitic avian eggshell protects the developing embryo and, moreover, ensures that the nutritious table egg remains free of pathogens. The eggshell is formed by nucleation upon a fibrous scaffold (the eggshell membranes) followed by an interaction between the growing mineral crystals and the shell organic matrix. This interaction leads to a highly ordered shell microstructure and texture which contribute to its exceptional mechanical properties. Shell mineralization occurs in three distinct phases of calcification (initiation, growth and termination), which
Shachak, Aviv; Ophir, Ron; Rubin, Eitan
The need to support bioinformatics training has been widely recognized by scientists, industry, and government institutions. However, the discussion of instructional methods for teaching bioinformatics is only beginning. Here we report on a systematic attempt to design two bioinformatics workshops for graduate biology students on the basis of…
Full Text Available The ubiquitin-proteasome system targets misfolded proteins for degradation. Since the accumulation of such proteins is potentially harmful for the cell, their prompt removal is important. E3 ubiquitin-protein ligases mediate substrate ubiquitination by bringing together the substrate with an E2 ubiquitin-conjugating enzyme, which transfers ubiquitin to the substrate. For misfolded proteins, substrate recognition is generally delegated to molecular chaperones that subsequently interact with specific E3 ligases. An important exception is San1, a yeast E3 ligase. San1 harbors extensive regions of intrinsic disorder, which provide both conformational flexibility and sites for direct recognition of misfolded targets of vastly different conformations. So far, no mammalian ortholog of San1 is known, nor is it clear whether other E3 ligases utilize disordered regions for substrate recognition. Here, we conduct a bioinformatics analysis to examine >600 human and S. cerevisiae E3 ligases to identify enzymes that are similar to San1 in terms of function and/or mechanism of substrate recognition. An initial sequence-based database search was found to detect candidates primarily based on the homology of their ordered regions, and did not capture the unique disorder patterns that encode the functional mechanism of San1. However, by searching specifically for key features of the San1 sequence, such as long regions of intrinsic disorder embedded with short stretches predicted to be suitable for substrate interaction, we identified several E3 ligases with these characteristics. Our initial analysis revealed that another remarkable trait of San1 is shared with several candidate E3 ligases: long stretches of complete lysine suppression, which in San1 limits auto-ubiquitination. We encode these characteristic features into a San1 similarity-score, and present a set of proteins that are plausible candidates as San1 counterparts in humans. In conclusion, our work
Full Text Available A new bioinformatic methodology was developed founded on the Unsupervised Pattern Cognition Analysis of GRID-based BioGPS descriptors (Global Positioning System in Biological Space. The procedure relies entirely on three-dimensional structure analysis of enzymes and does not stem from sequence or structure alignment. The BioGPS descriptors account for chemical, geometrical and physical-chemical features of enzymes and are able to describe comprehensively the active site of enzymes in terms of "pre-organized environment" able to stabilize the transition state of a given reaction. The efficiency of this new bioinformatic strategy was demonstrated by the consistent clustering of four different Ser hydrolases classes, which are characterized by the same active site organization but able to catalyze different reactions. The method was validated by considering, as a case study, the engineering of amidase activity into the scaffold of a lipase. The BioGPS tool predicted correctly the properties of lipase variants, as demonstrated by the projection of mutants inside the BioGPS "roadmap".
Jimenez-Gutierrez, L. R.; Barrios-Hernández, C. J.; Pedraza-Ferreira, G. R.; Vera-Cala, L.; Martinez-Perez, F.
Recently, bioinformatics has become a new field of science, indispensable in the analysis of millions of nucleic acids sequences, which are currently deposited in international databases (public or private); these databases contain information of genes, RNA, ORF, proteins, intergenic regions, including entire genomes from some species. The analysis of this information requires computer programs; which were renewed in the use of new mathematical methods, and the introduction of the use of artificial intelligence. In addition to the constant creation of supercomputing units trained to withstand the heavy workload of sequence analysis. However, it is still necessary the innovation on platforms that allow genomic analyses, faster and more effectively, with a technological understanding of all biological processes.
William H Thiel
Full Text Available Development of RNA and DNA aptamers for diagnostic and therapeutic applications is a rapidly growing field. Aptamers are identified through iterative rounds of selection in a process termed SELEX (Systematic Evolution of Ligands by EXponential enrichment. High-throughput sequencing (HTS revolutionized the modern SELEX process by identifying millions of aptamer sequences across multiple rounds of aptamer selection. However, these vast aptamer HTS datasets necessitated bioinformatics techniques. Herein, we describe a semiautomated approach to analyze aptamer HTS datasets using the Galaxy Project, a web-based open source collection of bioinformatics tools that were originally developed to analyze genome, exome, and transcriptome HTS data. Using a series of Workflows created in the Galaxy webserver, we demonstrate efficient processing of aptamer HTS data and compilation of a database of unique aptamer sequences. Additional Workflows were created to characterize the abundance and persistence of aptamer sequences within a selection and to filter sequences based on these parameters. A key advantage of this approach is that the online nature of the Galaxy webserver and its graphical interface allow for the analysis of HTS data without the need to compile code or install multiple programs.
Yang, Bo; Cai, Li-Li; Chi, Xiao-Hua; Lu, Xue-Chun; Zhang, Feng; Tuo, Shuai; Zhu, Hong-Li; Liu, Li-Hong; Yan, Jiang-Wei; Tuo, Chao-Wei
Objective of this study was to perform bioinformatics analysis of the characteristics of gene expression profiling regulated by amifostine and predict its novel potential biological function to provide a direction for further exploring pharmacological actions of amifostine and study methods. Amifostine was used as a key word to search internet-based free gene expression database including GEO, affymetrix gene chip database, GenBank, SAGE, GeneCard, InterPro, ProtoNet, UniProt and BLOCKS and the sifted amifostine-regulated gene expression profiling data was subjected to validity testing, gene expression difference analysis and functional clustering and gene annotation. The results showed that only one data of gene expression profiling regulated by amifostine was sifted from GEO database (accession: GSE3212). Through validity testing and gene expression difference analysis, significant difference (p < 0.01) was only found in 2.14% of the whole genome (460/192000). Gene annotation analysis showed that 139 out of 460 genes were known genes, in which 77 genes were up-regulated and 62 genes were down-regulated. 13 out of 139 genes were newly expressed following amifostine treatment of K562 cells, however expression of 5 genes was completely inhibited. Functional clustering displayed that 139 genes were divided into 11 categories and their biological function was involved in hematopoietic and immunologic regulation, apoptosis and cell cycle. It is concluded that bioinformatics method can be applied to analysis of gene expression profiling regulated by amifostine. Amifostine has a regulatory effect on human gene expression profiling and this action is mainly presented in biological processes including hematopoiesis, immunologic regulation, apoptosis and cell cycle and so on. The effect of amifostine on human gene expression need to be further testified in experimental condition.
Khan, Mohammad Ibrahim; Sheel, Chotan
Storage of sequence data is a big concern as the amount of data generated is exponential in nature at several locations. Therefore, there is a need to develop techniques to store data using compression algorithm. Here we describe optimal storage algorithm (OPTSDNA) for storing large amount of DNA sequences of varying length. This paper provides performance analysis of optimal storage algorithm (OPTSDNA) of a distributed bioinformatics computing system for analysis of DNA sequences. OPTSDNA algorithm is used for storing various sizes of DNA sequences into database. DNA sequences of different lengths were stored by using this algorithm. These input DNA sequences are varied in size from very small to very large. Storage size is calculated by this algorithm. Response time is also calculated in this work. The efficiency and performance of the algorithm is high (in size calculation with percentage) when compared with other known with sequential approach.
V. V. Volkomorov
Full Text Available Introduction. Searching for specific and sensitive molecular tumor markers is one of the important tasks of modern oncology. These markers can be used for early tumor diagnosis and prognosis as well as for prediction of therapeutic response, estimation of tumor volume or to assess disease recurrence through monitoring. Gene expression data base mining followed by experimental validation of results obtained is one of the promising approaches for searching of that kind.Objective: to identify several membrane proteins which can be used for serum diagnosis of intestinal type of gastric adenocarcinoma.Materials and methods. We used bioinformatic-driven search using Gene Ontology and The Cancer Genome Atlas (TCGA data to identify mRNA up-regulated in gastric cancer (GC. Then, the expression levels of the mRNAs in 55 pare clinical specimens were investigated using reverse transcription polymerase chain reaction.Results. Comparative analysis of the mRNA levels in normal and tumor tissues using a new bioinformatics algorithm allowed to identify 3 high-copy transcripts (SULF1, PMEPA1 and SPARC, intracellular content of which markedly increased in GC. Expression analysis of these genes in clinical specimens showed significantly higher mRNA levels of PMEPA1 and SPARC in tumor as compared to normal gastric tissue. Interestingly more than twofold increase in expression level of these genes was observed in 75 % of intestinal-type GC. The same results were found only in 25 and 38 % of diffuse-type GC respectively.Conclusions. As a result of original bioinforamtic analysis using TCGA data base two genes (PMEPA1 and SPARC were shown to be significantly upregulated in intestinal-type gastric adenocarcinoma. The findings show the importance of further investigation to clarify the clinical value of their expression level in stomach tumors as well as their role in carcinogenesis.
Malorni, A.; Facchiano, A.
We have developed new bioinformatic tools and strategies, aimed to the identification and characterization of proteins as markers of pathological states, for the analysis of data derived from protein expression profiles obtained by mass spectrometry techniques, for the study of structural and functional properties of the proteins, and for the analysis of data from omics approaches
Full Text Available Abstract Background Modifications of RNA bases have been found in some mRNAs and non-coding RNAs including rRNAs, tRNAs, and snRNAs, where modified bases are important for RNA function. Little is known about RNA base modifications in Arabidopsis thaliana. Results In the current work, we carried out a bioinformatics analysis of RNA base modifications in tRNAs and miRNAs using large numbers of cDNA sequences of small RNAs (sRNAs generated with the 454 technology and the massively parallel signature sequencing (MPSS method. We looked for sRNAs that map to the genome sequence with one-base mismatch (OMM, which indicate candidate modified nucleotides. We obtained 1,187 sites with possible RNA base modifications supported by both 454 and MPSS sequences. Seven hundred and three of these sites were within tRNA loci. Nucleotide substitutions were frequently located in the T arm (substitutions from A to U or G, upstream of the D arm (from G to C, U, or A, and downstream of the D arm (from G to U. The positions of major substitution sites corresponded with the following known RNA base modifications in tRNAs: N1-methyladenosine (m1A, N2-methylguanosine (m2G, and N2-N2-methylguanosine (m22G. Conclusion These results indicate that our bioinformatics method successfully detected modified nucleotides in tRNAs. Using this method, we also found 147 substitution sites in miRNA loci. As with tRNAs, substitutions from A to U or G and from G to C, U, or A were common, suggesting that base modifications might be similar in tRNAs and miRNAs. We suggest that miRNAs contain modified bases and such modifications might be important for miRNA maturation and/or function.
Full Text Available Technological advances in next-generation sequencing-based approaches have greatly impacted the analysis of microbial community composition. In particular, 16S rRNA-based methods have been widely used to analyze the whole set of bacteria present in a target environment. As a consequence, several specific bioinformatic pipelines have been developed to manage these data. MetaGenome Rapid Annotation using Subsystem Technology (MG-RAST and Quantitative Insights Into Microbial Ecology (QIIME are two freely available tools for metagenomic analyses that have been used in a wide range of studies. Here, we report the comparative analysis of the same dataset with both QIIME and MG-RAST in order to evaluate their accuracy in taxonomic assignment and in diversity analysis. We found that taxonomic assignment was more accurate with QIIME which, at family level, assigned a significantly higher number of reads. Thus, QIIME generated a more accurate BIOM file, which in turn improved the diversity analysis output. Finally, although informatics skills are needed to install QIIME, it offers a wide range of metrics that are useful for downstream applications and, not less important, it is not dependent on server times.
Li, Li; Cai, Shengyun; Liu, Shengnan; Feng, Hao; Zhang, Junjie
Ovarian cancer (OC) is a gynecological oncology that has a poor prognosis and high mortality. This study is conducted to identify the key genes implicated in the prognosis of OC by bioinformatic analysis. Gene expression data (including 568 primary OC tissues, 17 recurrent OC tissues, and 8 adjacent normal tissues) and the relevant clinical information of OC patients were downloaded from The Cancer Genome Atlas database. After data preprocessing, cluster analysis was conducted using the ConsensusClusterPlus package in R. Using the limma package in R, differential analysis was performed to identify feature genes. Based on Kaplan-Meier (KM) survival analysis, prognostic seed genes were selected from the feature genes. After key prognostic genes were further screened by cluster analysis and KM survival analysis, they were performed functional enrichment analysis and multivariate survival analysis. Using the survival package in R, cox regression analysis was conducted for the microarray data of GSE17260 to validate the key prognostic genes. A total of 3668 feature genes were obtained, among which 75 genes were identified as prognostic seed genes. Then, 25 key prognostic genes were screened, including AXL, FOS, KLF6, WDR77, DUSP1, GADD45B, and SLIT3. Especially, AXL and SLIT3 were enriched in ovulation cycle. Multivariate survival analysis showed that the key prognostic genes could effectively differentiate the samples and were significantly associated with prognosis. Additionally, GSE17260 confirmed that the key prognostic genes were associated with the prognosis of OC. AXL, FOS, KLF6, WDR77, DUSP1, GADD45B, and SLIT3 might affect the prognosis of OC.
Andrew B. Kinghorn
Full Text Available Aptamers are short nucleic acid sequences capable of specific, high-affinity molecular binding. They are isolated via SELEX (Systematic Evolution of Ligands by Exponential Enrichment, an evolutionary process that involves iterative rounds of selection and amplification before sequencing and aptamer characterization. As aptamers are genetic in nature, bioinformatic approaches have been used to improve both aptamers and their selection. This review will discuss the advancements made in several enclaves of aptamer bioinformatics, including simulation of aptamer selection, fragment-based aptamer design, patterning of libraries, identification of lead aptamers from high-throughput sequencing (HTS data and in silico aptamer optimization.
Dian Eka A. F. Ningrum
Full Text Available This study aims to determine the needs of learning variations on Biotechnology courses using bioinformatics approaches. One example of applied use of bioinformatics in biotechnology course is the analysis of protein profiles carbonic anhydrase II as a potential cause of autism candidate. This research is a qualitative descriptive study consisted of two phases. The first phase of the data obtained from observations of learning, student questionnaires, and questionnaires lecturer. Results from the first phase, namely the need for variations learning in Biotechnology course using bioinformatics. Collecting data on the second stage uses three webserver to predict the target protein and scientific articles. Visualization of proteins using PyMOL software. 3 based webserver which is used, the candidate of target proteins associated with autism is carbonic anhydrase II. The survey results revealed that the protein carbonic anhydrase II as a potential candidate for the cause of autism classified metaloenzim are able to bind with heavy metals. The content of heavy metals in autistic patients high that affect metabolism. This prediction of protein candidate cause autism is applied use to solve the problem in society, so that can achieve the learning outcome in biotechnology course.
Full Text Available The assessment of information transfer in the global economic network helps to understand the current environment and the outlook of an economy. Most approaches on global networks extract information transfer based mainly on a single variable. This paper establishes an entirely new bioinformatics-inspired approach to integrating information transfer derived from multiple variables and develops an international economic network accordingly. In the proposed methodology, we first construct the transfer entropies (TEs between various intra- and inter-country pairs of economic time series variables, test their significances, and then use a weighted sum approach to aggregate information captured in each TE. Through a simulation study, the new method is shown to deliver better information integration compared to existing integration methods in that it can be applied even when intra-country variables are correlated. Empirical investigation with the real world data reveals that Western countries are more influential in the global economic network and that Japan has become less influential following the Asian currency crisis.
Kim, Jinkyu; Kim, Gunn; An, Sungbae; Kwon, Young-Kyun; Yoon, Sungroh
The assessment of information transfer in the global economic network helps to understand the current environment and the outlook of an economy. Most approaches on global networks extract information transfer based mainly on a single variable. This paper establishes an entirely new bioinformatics-inspired approach to integrating information transfer derived from multiple variables and develops an international economic network accordingly. In the proposed methodology, we first construct the transfer entropies (TEs) between various intra- and inter-country pairs of economic time series variables, test their significances, and then use a weighted sum approach to aggregate information captured in each TE. Through a simulation study, the new method is shown to deliver better information integration compared to existing integration methods in that it can be applied even when intra-country variables are correlated. Empirical investigation with the real world data reveals that Western countries are more influential in the global economic network and that Japan has become less influential following the Asian currency crisis.
Feng, Xinyu; Zhou, Xiaojian; Zhou, Shuisen; Wang, Jingwen; Hu, Wei
microRNAs (miRNAs) are small non-coding RNAs widely identified in many mosquitoes. They are reported to play important roles in development, differentiation and innate immunity. However, miRNAs in Anopheles sinensis, one of the Chinese malaria mosquitoes, remain largely unknown. We investigated the global miRNA expression profile of An. sinensis using Illumina Hiseq 2000 sequencing. Meanwhile, we applied a bioinformatic approach to identify potential miRNAs in An. sinensis. The identified miRNA profiles were compared and analyzed by two approaches. The selected miRNAs from the sequencing result and the bioinformatic approach were confirmed with qRT-PCR. Moreover, target prediction, GO annotation and pathway analysis were carried out to understand the role of miRNAs in An. sinensis. We identified 49 conserved miRNAs and 12 novel miRNAs by next-generation high-throughput sequencing technology. In contrast, 43 miRNAs were predicted by the bioinformatic approach, of which two were assigned as novel. Comparative analysis of miRNA profiles by two approaches showed that 21 miRNAs were shared between them. Twelve novel miRNAs did not match any known miRNAs of any organism, indicating that they are possibly species-specific. Forty miRNAs were found in many mosquito species, indicating that these miRNAs are evolutionally conserved and may have critical roles in the process of life. Both the selected known and novel miRNAs (asi-miR-281, asi-miR-184, asi-miR-14, asi-miR-nov5, asi-miR-nov4, asi-miR-9383, and asi-miR-2a) could be detected by quantitative real-time PCR (qRT-PCR) in the sequenced sample, and the expression patterns of these miRNAs measured by qRT-PCR were in concordance with the original miRNA sequencing data. The predicted targets for the known and the novel miRNAs covered many important biological roles and pathways indicating the diversity of miRNA functions. We also found 21 conserved miRNAs and eight counterparts of target immune pathway genes in An. sinensis
Full Text Available Chen Chen,1 Li-Guo Zhang,1 Jian Liu,1 Hui Han,1 Ning Chen,1 An-Liang Yao,1 Shao-San Kang,1 Wei-Xing Gao,1 Hong Shen,2 Long-Jun Zhang,1 Ya-Peng Li,1 Feng-Hong Cao,1 Zhi-Guo Li3 1Department of Urology, North China University of Science and Technology Affiliated Hospital, 2Department of Modern Technology and Education Center, 3Department of Medical Research Center, International Science and Technology Cooperation Base of Geriatric Medicine, North China University of Science and Technology, Tangshan, People’s Republic of China Abstract: We mined the literature for proteomics data to examine the occurrence and metastasis of prostate cancer (PCa through a bioinformatics analysis. We divided the differentially expressed proteins (DEPs into two groups: the group consisting of PCa and benign tissues (P&b and the group presenting both high and low PCa metastatic tendencies (H&L. In the P&b group, we found 320 DEPs, 20 of which were reported more than three times, and DES was the most commonly reported. Among these DEPs, the expression levels of FGG, GSN, SERPINC1, TPM1, and TUBB4B have not yet been correlated with PCa. In the H&L group, we identified 353 DEPs, 13 of which were reported more than three times. Among these DEPs, MDH2 and MYH9 have not yet been correlated with PCa metastasis. We further confirmed that DES was differentially expressed between 30 cancer and 30 benign tissues. In addition, DEPs associated with protein transport, regulation of actin cytoskeleton, and the extracellular matrix (ECM–receptor interaction pathway were prevalent in the H&L group and have not yet been studied in detail in this context. Proteins related to homeostasis, the wound-healing response, focal adhesions, and the complement and coagulation pathways were overrepresented in both groups. Our findings suggest that the repeatedly reported DEPs in the two groups may function as potential biomarkers for detecting PCa and predicting its aggressiveness. Furthermore
Kane, Michael D
The utility of genomic technology and bioinformatic analytical support to provide new and needed insight into the molecular basis of disease, development, and diversity continues to grow as more research model systems and populations are investigated. Yet deriving results that meet a specific set of research objectives requires aligning or coordinating the design of the experiment, the laboratory techniques, and the data analysis. The following paragraphs describe several important interdependent factors that need to be considered to generate high quality data from the microarray platform. These factors include aligning oligonucleotide probe design with the sample labeling strategy if oligonucleotide probes are employed, recognizing that compromises are inherent in different sample procurement methods, normalizing 2-color microarray raw data, and distinguishing the difference between gene clustering and sample clustering. These factors do not represent an exhaustive list of technical variables in microarray-based research, but this list highlights those variables that span both experimental execution and data analysis. Copyright 2001 Wiley-Liss, Inc.
Full Text Available Differential transcription in Ascaris suum was investigated using a genomic-bioinformatic approach. A cDNA archive enriched for molecules in the infective third-stage larva (L3 of A. suum was constructed by suppressive-subtractive hybridization (SSH, and a subset of cDNAs from 3075 clones subjected to microarray analysis using cDNA probes derived from RNA from different developmental stages of A. suum. The cDNAs (n = 498 shown by microarray analysis to be enriched in the L3 were sequenced and subjected to bioinformatic analyses using a semi-automated pipeline (ESTExplorer. Using gene ontology (GO, 235 of these molecules were assigned to 'biological process' (n = 68, 'cellular component' (n = 50, or 'molecular function' (n = 117. Of the 91 clusters assembled, 56 molecules (61.5% had homologues/orthologues in the free-living nematodes Caenorhabditis elegans and C. briggsae and/or other organisms, whereas 35 (38.5% had no significant similarity to any sequences available in current gene databases. Transcripts encoding protein kinases, protein phosphatases (and their precursors, and enolases were abundantly represented in the L3 of A. suum, as were molecules involved in cellular processes, such as ubiquitination and proteasome function, gene transcription, protein-protein interactions, and function. In silico analyses inferred the C. elegans orthologues/homologues (n = 50 to be involved in apoptosis and insulin signaling (2%, ATP synthesis (2%, carbon metabolism (6%, fatty acid biosynthesis (2%, gap junction (2%, glucose metabolism (6%, or porphyrin metabolism (2%, although 34 (68% of them could not be mapped to a specific metabolic pathway. Small numbers of these 50 molecules were predicted to be secreted (10%, anchored (2%, and/or transmembrane (12% proteins. Functionally, 17 (34% of them were predicted to be associated with (non-wild-type RNAi phenotypes in C. elegans, the majority being embryonic lethality (Emb (13 types; 58.8%, larval arrest
Liang, Chengwei; Zhang, Xiaowen; Zou, Jian; Xu, Dong; Su, Feng; Ye, Naihao
miRNAs are a class of non-coding, small RNAs that are approximately 22 nucleotides long and play important roles in the translational level regulation of gene expression by either directly binding or cleaving target mRNAs. The red alga, Porphyra yezoensis is one of the most important marine economic crops worldwide. To date, only a few miRNAs have been identified in green unicellar alga and there is no report about Porphyra miRNAs. To identify miRNAs in Porphyra yezoensis, a small RNA library was constructed. Solexa technology was used to perform high throughput sequencing of the library and subsequent bioinformatics analysis to identify novel miRNAs. Specifically, 180,557,942 reads produced 13,324 unique miRNAs representing 224 conserved miRNA families that have been identified in other plants species. In addition, seven novel putative miRNAs were predicted from a limited number of ESTs. The potential targets of these putative miRNAs were also predicted based on sequence homology search. This study provides a first large scale cloning and characterization of Porphyra miRNAs and their potential targets. These miRNAs belong to 224 conserved miRNA families and 7 miRNAs are novel in Porphyra. These miRNAs add to the growing database of new miRNA and lay the foundation for further understanding of miRNA function in the regulation of Porphyra yezoensis development.
Full Text Available Wingless-type (Wnt signaling proteins participate in various cell developmental processes. A suppressive role of Wnt5a on keratinocyte growth has already been observed. However, the role of other Wnt proteins in proliferation and differentiation of keratinocytes remains unknown. Here, we investigated the effects of the Wnt ligand, Wnt3a, on proliferation and differentiation of keratinocytes. Keratinocytes from normal human skin were cultured and treated with recombinant Wnt3a alone or in combination with the inflammatory cytokine, tumor necrosis factor α (TNFα. Furthermore, using bioinformatics, we analyzed the biochemical parameters, molecular evolution, and protein–protein interaction network for the Wnt family. Application of recombinant Wnt3a showed an anti-proliferative effect on keratinocytes in a dose-dependent manner. After treatment with TNFα, Wnt3a still demonstrated an anti-proliferative effect on human keratinocytes. Exogenous treatment of Wnt3a was unable to alter mRNA expression of differentiation markers of keratinocytes, whereas an altered expression was observed in TNFα-stimulated keratinocytes. In silico phylogenetic, biochemical, and protein–protein interaction analysis showed several close relationships among the family members of the Wnt family. Moreover, a close phylogenetic and biochemical similarity was observed between Wnt3a and Wnt5a. Finally, we proposed a hypothetical mechanism to illustrate how the Wnt3a protein may inhibit the process of proliferation in keratinocytes, which would be useful for future researchers.
Full Text Available Using the reference sequences of pgip genes in GenBank, a fragment of 930 bp covering the open reading frame (ORF of rice Ospgip1 (Oryza sativa polygalacturonase-inhibiting protein 1 was amplified. The prokaryotic expression product of the gene inhibited the growth of Rhizoctonia solani, the causal agent of rice sheath blight, and reduced its polygalacturonase activity. Bioinformatic analysis showed that OsPGIP1 is a hydrophobic protein with a molecular weight of 32.8 kDa and an isoelectric point (pI of 7.26. The protein is mainly located in the cell wall of rice, and its signal peptide cleavage site is located between the 17th and 18th amino acids. There are four cysteines in both the N- and C-termini of the deduced protein, which can form three disulfide bonds (between the 56th and 63rd, the 278th and 298th, and the 300th and 308th amino acids. The protein has a typical leucine-rich repeat (LRR domain, and its secondary structure comprises α-helices, β-sheets and irregular coils. Compared with polygalacturonase-inhibiting proteins (PGIPs from other plants, the 7th LRR is absent in OsPGIP1. The nine LRRs could form a cleft that might associate with proteins from pathogenic fungi, such as polygalacturonase.
Sanchita; Singh, Swati; Sharma, Ashok
Withania somnifera (Ashwagandha) is an affluent storehouse of large number of pharmacologically active secondary metabolites known as withanolides. These secondary metabolites are produced by withanolide biosynthetic pathway. Very less information is available on structural and functional aspects of enzymes involved in withanolides biosynthetic pathways of Withiana somnifera. We therefore performed a bioinformatics analysis to look at functional and structural properties of these important enzymes. The pathway enzymes taken for this study were 3-Hydroxy-3-methylglutaryl coenzyme A reductase, 1-Deoxy-D-xylulose-5-phosphate synthase, 1-Deoxy-D-xylulose-5-phosphate reductase, farnesyl pyrophosphate synthase, squalene synthase, squalene epoxidase, and cycloartenol synthase. The prediction of secondary structure was performed for basic structural information. Three-dimensional structures for these enzymes were predicted. The physico-chemical properties such as pI, AI, GRAVY and instability index were also studied. The current information will provide a platform to know the structural attributes responsible for the function of these protein until experimental structures become available.
Full Text Available Aim of the study : To analyse the expression profile of hepatocellular carcinoma compared with normal liver by using bioinformatics methods. Material and methods : In this study, we analysed the microarray expression data of HCC and adjacent normal liver samples from the Gene Expression Omnibus (GEO database to screen for differentially expressed genes. Then, functional analyses were performed using GenCLiP analysis, Gene Ontology categories, and aberrant pathway identification. In addition, we used the CMap database to identify small molecules that can induce HCC. Results : Overall, 2721 differentially expressed genes (DEGs were identified. We found 180 metastasis-related genes and constructed co-occurrence networks. Several significant pathways, including the transforming growth factor β (TGF-β signalling pathway, were identified as closely related to these DEGs. Some candidate small molecules (such as betahistine were identified that might provide a basis for developing HCC treatments in the future. Conclusions : Although we functionally analysed the differences in the gene expression profiles of HCC and normal liver tissues, our study is essentially preliminary, and it may be premature to apply our results to clinical trials. Further research and experimental testing are required in future studies.
Kesmir, C.; Noort, V. van; Boer, R.J. de; Hogeweg, P.
Intracellular proteins are degraded largely by proteasomes. In cells stimulated with gamma interferon, the active proteasome subunits are replaced by "immuno" subunits that form immunoproteasomes. Phylogenetic analysis of the immunosubunits has revealed that they evolve faster than their
Yu, Xiao-Dan; Jiang, Chao; Huang, Lu-Qi; Qin, Shuang-Shuang; Zeng, Xiang-Mei; Chen, Ping; Yuan, Yuan
To clone SABATH methyltransferase (rLjSABATHMT) gene in Lonicera japonica var. chinensis, and compare the gene expression and intron sequence of SABATH methyltransferase orthologous in L. japonica with L. japonica var. chinensis. It provide a basis for gene regulate the formation of L. japonica floral scents. The cDNA and genome sequences of LjSABATHMT from L. japonica var. chinensis were cloned according to the gene fragments in cDNA library. The LjSABATHMT protein was characterized by bioinformatics analysis. SABATH family phylogenetic tree were built by MEGA 5.0. The transcripted level of SABATHMT orthologous were analyzed in different organs and different flower periods of L. japonica and L. japonica var. chinensis using RT-PCR analysis. Intron sequences of SABATHMT orthologous were also analyzied. The cDNA of LjSABATHMT was 1 251 bp, had a complete coding frame with 365 amino acids. The protein had the conservative SABATHMT domain, and phylogenetic tree showed that it may be a salicylic acid/benzoic acid methyltransferase. Higher expression of SABATH methyltransferase orthologous was found in flower. The intron sequence of L. japonica and L. japonica var. chinensis had rich polymorphism, and two SNP are unique genotype of L. japonica var. chinensis. The motif elements in two orthologous genes were significant differences. The intron difference of SABATH methyltransferase orthologous could be inducing to difference of gene expression between L. japonica and L. japonica var. chinensis. These results will provide important base on regulating active compounds of L. japonica.
When bioinformatics education is considered, several issues are addressed. At the undergraduate level, the main issue revolves around conveying information from two main and different fields: biology and computer science. At the graduate level, the main issue is bridging the gap between biology students and computer science students. However, there is an educational component that is rarely addressed within the context of bioinformatics education: the ethics component. Here, a different perspective is provided on bioinformatics education, and the current status of ethics is analyzed within the existing bioinformatics programs. Analysis of the existing undergraduate and graduate programs, in both Europe and the United States, reveals the minimal attention given to ethics within bioinformatics education. Given that bioinformaticians speedily and effectively shape the biomedical sciences and hence their implications for society, here redesigning of the bioinformatics curricula is suggested in order to integrate the necessary ethics education. Unique ethical problems awaiting bioinformaticians and bioinformatics ethics as a separate field of study are discussed. In addition, a template for an "Ethics in Bioinformatics" course is provided.
Ahmed, M. Z.; Khan, M. A.
Sodium-hydrogen antiporter (NHX) protein regulates the trans-membrane transport of Na+ in higher plants. Vacuolar-NHX is a type of NHX protein located on tonoplast and minimizes the accumulation of Na+ in cytoplasm by compartmentalizing into vacuole especially in salt tolerant plants. In Aeluropus lagopoides, AlaNHX [NCBI: GU199336, Vacuolar-NHX] plays a vital role for efficient Na+ sequestration into the vacuole and helps in plant survival in saline areas. Therefore, sequence analysis, structural analysis and modeling of AlaNHX were performed through bioinformatics tools. Homology of AlaNHX was 99% similar with the Na+/H+ antiporter of Aeluropus littoralis. Sequence of AlaNHX consisted of 2353 bp including 337 bp of un-translated regions (UTR) at 5' and 393 at 3' end. In addition, AlaNHX have an open reading frame (ORF) of 1623 bp which translated into 59.4 KDa protein containing 540 amino acids (Leucine + Serine contributed in 22% of peptide chain). AlaNHX protein consists of 10 transmembrane domains (TMD; 3 primary and 7 secondary protein structural type) and a long (95 amino acids) carboxyl terminal end in cytoplasmic region. In addition, 3, 5, 7 and 8 TMD regions of AlaNHX were highly conserved. Different glycosylation, phosphorylation and myristoylation sites were also found in AlaNHX protein. Three-dimensional (3D) structure analysis revealed that this protein may be classified as stable and of hydrophobic nature containing a significant proportion of alpha helices. In this study, a three-dimensional structure of AlaNHX protein was predicted by using in-silico3D homology modeling technique. This study provides baseline information for understanding the importance of NHX protein structure. (author)
Full Text Available BACKGROUND: miRNAs are a class of non-coding, small RNAs that are approximately 22 nucleotides long and play important roles in the translational level regulation of gene expression by either directly binding or cleaving target mRNAs. The red alga, Porphyra yezoensis is one of the most important marine economic crops worldwide. To date, only a few miRNAs have been identified in green unicellar alga and there is no report about Porphyra miRNAs. METHODOLOGY/PRINCIPAL FINDINGS: To identify miRNAs in Porphyra yezoensis, a small RNA library was constructed. Solexa technology was used to perform high throughput sequencing of the library and subsequent bioinformatics analysis to identify novel miRNAs. Specifically, 180,557,942 reads produced 13,324 unique miRNAs representing 224 conserved miRNA families that have been identified in other plants species. In addition, seven novel putative miRNAs were predicted from a limited number of ESTs. The potential targets of these putative miRNAs were also predicted based on sequence homology search. CONCLUSIONS/SIGNIFICANCE: This study provides a first large scale cloning and characterization of Porphyra miRNAs and their potential targets. These miRNAs belong to 224 conserved miRNA families and 7 miRNAs are novel in Porphyra. These miRNAs add to the growing database of new miRNA and lay the foundation for further understanding of miRNA function in the regulation of Porphyra yezoensis development.
Campbell, Chad E.; Nehm, Ross H.
The growing importance of genomics and bioinformatics methods and paradigms in biology has been accompanied by an explosion of new curricula and pedagogies. An important question to ask about these educational innovations is whether they are having a meaningful impact on students' knowledge, attitudes, or skills. Although assessments are…
Kesmir, Can; van Noort, V.; de Boer, R.J.
not yet been quantified how different the specificity of two forms of the proteasome are. The main question, which still lacks direct evidence, is whether the immunoproteasome generates more MHC ligands. Here we use bioinformatics tools to quantify these differences and show that the immunoproteasome...
Lu, Yang; Wang, Jingchao; Dapeng, Chen; Wu, Di; Cai, Guangyan; Chen, Xiangmei
Dysfunction of renal tubule epithelial cells is associated with renal tubulointerstitial fibrosis. Exploration of the proteomic profiles of senesced tubule epithelial cells is essential to elucidate the mechanism of tubulointerstitium development. Primary human proximal tubule epithelial cells from passage 3 (P3) and passage 6 (P6) were selected for evaluation. EdU and SA-β-galactosidase staining were used to detect cell senescence. p53, p21, and p16 were detected by Western blot analysis. Liquid chromatography mass spectrometry (LC-MS) was used to examine differentially expressed proteins (DEPs) between P6 and P3 cells. The expression of DEPs was examined by Western blot analysis. Bioinformatics analysis was performed by protein-protein interaction and gene ontology analyses. The majority of tubule cells from passage 6 (P6) stained positive for SA-β-galactosidase, whereas passage 3 (P3) cells were negative. Senescence biomarkers, including p53, p21, and p16, were upregulated in P6 cells relative to P3 cells. EdU staining results showed a lower rate of EdU positive cells in P6 cells than in P3 cells. LC-MS was used to examine DEPs between P6 and P3 cells. These DEPs are involved in glycolysis, response to stress, cytoskeleton regulation, oxidative reduction, ATP binding, and oxidative stress. Using Western blot analysis, we validated the down-regulation of AKR1B1, EEF2, EEF1A1, and HSP90 and the up-regulation of VIM in P6 cells seen in the LC-MS data. More importantly, we built the molecular network based on biological functions and protein-protein interactions and found that the DEPs are involved in translation elongation, stress, and glycolysis, and that they are all associated with cytoskeleton regulation, which regulates senescent cell activities such as apoptosis and EMT in tubule epithelial cells. We explored proteomic profile changes in cell culture-induced senescent cells and built senescence-associated molecular networks, which will help to elucidate the
Full Text Available Yubin Kou,1,2* Suya Zhang,3* Xiaoping Chen,2 Sanyuan Hu1 1Department of General Surgery, Qilu Hospital of Shandong University, Jinan, People’s Republic of China; 2Department of General Surgery, 3Department of Neurology, Shuguang Hospital Baoshan Branch, Shanghai, People’s Republic of China *These authors contributed equally to this work Abstract: This study aimed to explore the underlying molecular mechanisms of colorectal cancer (CRC using bioinformatics analysis. Using GSE4107 datasets downloaded from the Gene Expression Omnibus, the differentially expressed genes (DEGs were screened by comparing the RNA expression from the colonic mucosa between 12 CRC patients and ten healthy controls using a paired t-test. The Gene Ontology (GO functional and pathway enrichment analyses of DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID software followed by the construction of a protein–protein interaction (PPI network. In addition, hub gene identification and GO functional and pathway enrichment analyses of the modules were performed. A total of 612 up- and 639 downregulated genes were identified. The upregulated DEGs were mainly involved in the regulation of cell growth, migration, and the MAPK signaling pathway. The downregulated DEGs were significantly associated with oxidative phosphorylation, Alzheimer’s disease, and Parkinson’s disease. Moreover, FOS, FN1, PPP1CC, and CYP2B6 were selected as hub genes in the PPI networks. Two modules (up-A and up-B in the upregulated PPI network and three modules (d-A, d-B, and d-C in the downregulated PPI were identified with the threshold of Molecular Complex Detection (MCODE Molecular Complex Detection (MCODE score ≥4 and nodes ≥6. The genes in module up-A were significantly enriched in neuroactive ligand–receptor interactions and the calcium signaling pathway. The genes in module d-A were enriched in four pathways, including oxidative
Wang, Pengfei; Wang, Yingfang; Duan, Guangcai; Xue, Zerun; Wang, Linlin; Guo, Xiangjiao; Yang, Haiyan; Xi, Yuanlin
This study was aimed to explore the features of clustered regularly interspaced short palindromic repeats (CRISPR) structures in Shigella by using bioinformatics. We used bioinformatics methods, including BLAST, alignment and RNA structure prediction, to analyze the CRISPR structures of Shigella genomes. The results showed that the CRISPRs existed in the four groups of Shigella, and the flanking sequences of upstream CRISPRs could be classified into the same group with those of the downstream. We also found some relatively conserved palindromic motifs in the leader sequences. Repeat sequences had the same group with corresponding flanking sequences, and could be classified into two different types by their RNA secondary structures, which contain "stem" and "ring". Some spacers were found to homologize with part sequences of plasmids or phages. The study indicated that there were correlations between repeat sequences and flanking sequences, and the repeats might act as a kind of recognition mechanism to mediate the interaction between foreign genetic elements and Cas proteins.
Pawełkowicz, Magdalena E.; Skarzyńska, Agnieszka; Posyniak, Kacper; ZiÄ bska, Karolina; PlÄ der, Wojciech; Przybecki, Zbigniew
An important computational challenge is finding the regulatory elements across the promotor region. In this work we present the advantages and disadvantages from the application of different bioinformatics programs for localization of transcription factor binding sites in the upstream region of genes connected with sex determination in cucumber. We use PlantCARE, PlantPAN and SignalScan to find motifs in the promotor regions. The results have been compared and possible function of chosen motifs has been described.
Wang, Yimin; Ye, Fang; Huang, Chanyan; Xue, Faling; Li, Yingyuan; Gao, Shaowei; Qiu, Zeting; Li, Si; Chen, Qinchang; Zhou, Huaqiang; Song, Yiyan; Huang, Wenqi; Tan, Wulin; Wang, Zhongxing
Neuropathic pain is one of the common complications after spinal cord injury (SCI), affecting patients' life quality. The molecular mechanism for neuropathic pain after SCI is still unclear. We aimed to discover potential genes and MicroRNAs(miRNAs) related to neuropathic pain by bioinformatics method. Microarray data of GSE69901 were obtained from Gene Expression Omnibus (GEO) database. Peripheral blood samples from patients with or without neuropathic pain after spinal cord injury (SCI) were collected. 12 samples with neuropathic pain and 13 samples without pain as control were included in the downloaded microarray. Differentially expressed genes (DEGs) between neuropathic pain group and control group were detected using GEO2R online tool. Functional enrichment analysis of DEGs was performed using DAVID database. Protein-protein interaction (PPI) network was constructed from STRING database. MiRNAs targeting these DEGs were obtained from miRNet database. A merged miRNA-DEG network was constructed and analyzed with Cytoscape software. Total 1134 DEGs were identified between patients with or without neuropathic pain(case and control) and 454 biological processes were enriched. We identified 4 targeted miRNAs, including mir-204-5p, mir-519d-3p, mir-20b-5p, mir-6838-5p, which may be the potential biomarker for SCI patients. Protein modification and regulation biological process of central nervous system may be a risk factor of in SCI patients. Certain genes and miRNAs may be potential biomarkers for the prediction of and potential targets for prevention and treatment of neuropathic pain after SCI.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http
Chen, Xiaoling; Chang, Jeffrey T
Bioinformatic analyses are becoming formidably more complex due to the increasing number of steps required to process the data, as well as the proliferation of methods that can be used in each step. To alleviate this difficulty, pipelines are commonly employed. However, pipelines are typically implemented to automate a specific analysis, and thus are difficult to use for exploratory analyses requiring systematic changes to the software or parameters used. To automate the development of pipelines, we have investigated expert systems. We created the Bioinformatics ExperT SYstem (BETSY) that includes a knowledge base where the capabilities of bioinformatics software is explicitly and formally encoded. BETSY is a backwards-chaining rule-based expert system comprised of a data model that can capture the richness of biological data, and an inference engine that reasons on the knowledge base to produce workflows. Currently, the knowledge base is populated with rules to analyze microarray and next generation sequencing data. We evaluated BETSY and found that it could generate workflows that reproduce and go beyond previously published bioinformatics results. Finally, a meta-investigation of the workflows generated from the knowledge base produced a quantitative measure of the technical burden imposed by each step of bioinformatics analyses, revealing the large number of steps devoted to the pre-processing of data. In sum, an expert system approach can facilitate exploratory bioinformatic analysis by automating the development of workflows, a task that requires significant domain expertise. https://github.com/jefftc/changlab. email@example.com. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: firstname.lastname@example.org
Chen, Xiaoling; Chang, Jeffrey T.
Abstract Motivation: Bioinformatic analyses are becoming formidably more complex due to the increasing number of steps required to process the data, as well as the proliferation of methods that can be used in each step. To alleviate this difficulty, pipelines are commonly employed. However, pipelines are typically implemented to automate a specific analysis, and thus are difficult to use for exploratory analyses requiring systematic changes to the software or parameters used. Results: To automate the development of pipelines, we have investigated expert systems. We created the Bioinformatics ExperT SYstem (BETSY) that includes a knowledge base where the capabilities of bioinformatics software is explicitly and formally encoded. BETSY is a backwards-chaining rule-based expert system comprised of a data model that can capture the richness of biological data, and an inference engine that reasons on the knowledge base to produce workflows. Currently, the knowledge base is populated with rules to analyze microarray and next generation sequencing data. We evaluated BETSY and found that it could generate workflows that reproduce and go beyond previously published bioinformatics results. Finally, a meta-investigation of the workflows generated from the knowledge base produced a quantitative measure of the technical burden imposed by each step of bioinformatics analyses, revealing the large number of steps devoted to the pre-processing of data. In sum, an expert system approach can facilitate exploratory bioinformatic analysis by automating the development of workflows, a task that requires significant domain expertise. Availability and Implementation: https://github.com/jefftc/changlab Contact: email@example.com PMID:28052928
Blom, Evert-Jan; Ridder, Anja N.J.A.; Lulko, Andrzej T.; Roerdink, Jos B.T.M.; Kuipers, Oscar P.
We have determined the time-resolved transcriptome of the model gram-positive organism B. subtilis during growth in a batch fermentor on rich medium. DNA microarrays were used to monitor gene transcription using 10-minute intervals at 40 consecutive time points. From the growth curve and analysis of
Farazi, Thalia A; Brown, Miguel; Morozov, Pavel; Ten Hoeve, Jelle J; Ben-Dov, Iddo Z; Hovestadt, Volker; Hafner, Markus; Renwick, Neil; Mihailović, Aleksandra; Wessels, Lodewyk F A; Tuschl, Thomas
The characterization of post-transcriptional gene regulation by small regulatory RNAs of 20-30 nt length, particularly miRNAs and piRNAs, has become a major focus of research in recent years. A prerequisite for the characterization of small RNAs is their identification and quantification across different developmental stages, normal and diseased tissues, as well as model cell lines. Here we present a step-by-step protocol for the bioinformatic analysis of barcoded cDNA libraries for small RNA profiling generated by Illumina sequencing, thereby facilitating miRNA and other small RNA profiling of large sample collections. Copyright © 2012 Elsevier Inc. All rights reserved.
Li, Yan-Hui; Zhang, Gai-Gai
DAF-16, the C. elegans FOXO transcription factor, is an important determinant in aging and longevity. In this work, we manually curated FOXODB http://lyh.pkmu.cn/foxodb/, a database of FOXO direct targets. It now covers 208 genes. Bioinformatics analysis on 109 DAF-16 direct targets in C. elegans found interesting results. (i) DAF-16 and transcription factor PQM-1 co-regulate some targets. (ii) Seventeen targets directly regulate lifespan. (iii) Four targets are involved in lifespan extension induced by dietary restriction. And (iv) DAF-16 direct targets might play global roles in lifespan regulation.
Full Text Available Although RNA-Seq has revolutionized transcript analysis, organellar transcriptomes are rarely assessed even when present in published datasets. Here, we describe the development and application of a rapid and convenient method, ChloroSeq, to delineate qualitative and quantitative features of chloroplast RNA metabolism from strand-specific RNA-Seq datasets, including processing, editing, splicing, and relative transcript abundance. The use of a single experiment to analyze systematically chloroplast transcript maturation and abundance is of particular interest due to frequent pleiotropic effects observed in mutants that affect chloroplast gene expression and/or photosynthesis. To illustrate its utility, ChloroSeq was applied to published RNA-Seq datasets derived from Arabidopsis thaliana grown under control and abiotic stress conditions, where the organellar transcriptome had not been examined. The most appreciable effects were found for heat stress, which induces a global reduction in splicing and editing efficiency, and leads to increased abundance of chloroplast transcripts, including genic, intergenic, and antisense transcripts. Moreover, by concomitantly analyzing nuclear transcripts that encode chloroplast gene expression regulators from the same libraries, we demonstrate the possibility of achieving a holistic understanding of the nucleus-organelle system. ChloroSeq thus represents a unique method for streamlining RNA-Seq data interpretation of the chloroplast transcriptome and its regulators.
Campbell, Chad E.; Nehm, Ross H.
The growing importance of genomics and bioinformatics methods and paradigms in biology has been accompanied by an explosion of new curricula and pedagogies. An important question to ask about these educational innovations is whether they are having a meaningful impact on students’ knowledge, attitudes, or skills. Although assessments are necessary tools for answering this question, their outputs are dependent on their quality. Our study 1) reviews the central importance of reliability and construct validity evidence in the development and evaluation of science assessments and 2) examines the extent to which published assessments in genomics and bioinformatics education (GBE) have been developed using such evidence. We identified 95 GBE articles (out of 226) that contained claims of knowledge increases, affective changes, or skill acquisition. We found that 1) the purpose of most of these studies was to assess summative learning gains associated with curricular change at the undergraduate level, and 2) a minority (quality of evidence derived from these instruments. We end with recommendations for improving assessment quality in GBE. PMID:24006400
Full Text Available Objective(s: The introduction of nucleic acids into cells for therapeutic objectives is significantly hindered by the size and charge of these molecules and therefore requires efficient vectors that assist cellular uptake. For several years great efforts have been devoted to the study of development of recombinant vectors based on biological domains with potential applications in gene therapy. Such vectors have been synthesized in genetically engineered approach, resulting in biomacromolecules with new properties that are not present in nature. Materials and Methods: In this study, we have designed new peptides using homology modeling with the purpose of overcoming the cell barriers for successful gene delivery through Bioinformatics tools. Three different carriers were designed and one of those with better score through Bioinformatics tools was cloned, expressed and its affinity for pDNA was monitored. Results: The resultszz demonstrated that the vector can effectively condense pDNAinto nanoparticles with the average sizes about 100 nm. Conclusion: We hope these peptides can overcome the biological barriers associated with gene transfer, and mediate efficient gene delivery.
Rigbolt, Kristoffer T G; Vanselow, Jens T; Blagoev, Blagoy
-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)(1). The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface...... such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical...... displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics...
Huang, Ming-Der; Huang, Anthony H C
Plant cells contain subcellular lipid droplets with a triacylglycerol matrix enclosed by a layer of phospholipids and the small structural protein oleosin. Oleosins possess a conserved central hydrophobic hairpin of approximately 72 residues penetrating into the lipid droplet matrix and amphipathic amino- and carboxyl (C)-terminal peptides lying on the phospholipid surface. Bioinformatics of 1,000 oleosins of green algae and all plants emphasizing biological implications reveal five oleosin lineages: primitive (in green algae, mosses, and ferns), universal (U; all land plants), and three in specific organs or phylogenetic groups, termed seed low-molecular-weight (SL; seed plants), seed high-molecular-weight (SH; angiosperms), and tapetum (T; Brassicaceae) oleosins. Transition from one lineage to the next is depicted from lineage intermediates at junctions of phylogeny and organ distributions. Within a species, each lineage, except the T oleosin lineage, has one to four genes per haploid genome, only approximately two of which are active. Primitive oleosins already possess all the general characteristics of oleosins. U oleosins have C-terminal sequences as highly conserved as the hairpin sequences; thus, U oleosins including their C-terminal peptide exert indispensable, unknown functions. SL and SH oleosin transcripts in seeds are in an approximately 1:1 ratio, which suggests the occurrence of SL-SH oleosin dimers/multimers. T oleosins in Brassicaceae are encoded by rapidly evolved multitandem genes for alkane storage and transfer. Overall, oleosins have evolved to retain conserved hairpin structures but diversified for unique structures and functions in specific cells and plant families. Also, our studies reveal oleosin in avocado (Persea americana) mesocarp and no acyltransferase/lipase motifs in most oleosins. © 2015 American Society of Plant Biologists. All Rights Reserved.
Jiang, Zhiyun; Ma, Junfen; Wang, Qian; Wu, Fan; Ping, Jiedan; Ming, Liang
Clinically, D-dimer is the only established biomarker for the diagnosis of deep vein thrombosis (DVT). However, low specificity discounts its diagnostic value. Several publications have illustrated the differentially expressed circulating microRNAs (miRNAs) and their potential diagnostic values for DVT patients. Therefore, we systematically evaluated present researches and further performed bioinformatics analysis, to provide new insights into the diagnosis and underlying mechanisms of miRNAs in DVT. Databases PubMed, Web of Science, and Embase were searched from January 2000 to April 2017. Articles on circulating miRNAs expression in DVT were retrieved and reference lists were handpicked. Bioinformatics analysis was conducted for further evaluation. Eventually, the eligibility criteria for inclusion in this study were met by 3 articles, which consisted of 13 specially expressed miRNAs and 149 putative target genes. Two representative KEGG pathways, vascular endothelial growth factor and phosphatidylinositol 3'-kinase (PI3K)-Akt signaling pathway, seemed to participate in the regulatory network of thrombosis. Despite the potential diagnostic value and regulation effect, the results of circulating miRNAs used as biomarkers for DVT are not so encouraging. More in-depth and larger sample investigations are needed to explore the diagnostic and therapeutic values of miRNAs for DVT. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.
Basyuni, M.; Wati, R.
The present study evaluates the bioinformatics methods to analyze twenty-four predicted polyprenol reductase genes from higher plants on GenBank as well as predicted the structure, composition, similarity, subcellular localization, and phylogenetic. The physicochemical properties of plant polyprenol showed diversity among the observed genes. The percentage of the secondary structure of plant polyprenol genes followed the ratio order of α helix > random coil > extended chain structure. The values of chloroplast but not signal peptide were too low, indicated that few chloroplast transit peptide in plant polyprenol reductase genes. The possibility of the potential transit peptide showed variation among the plant polyprenol reductase, suggested the importance of understanding the variety of peptide components of plant polyprenol genes. To clarify this finding, a phylogenetic tree was drawn. The phylogenetic tree shows several branches in the tree, suggested that plant polyprenol reductase genes grouped into divergent clusters in the tree.
Full Text Available Chromatin factors interact with each other in a cell and sequence-specific manner in order to regulate transcription and a wealth of publically available datasets exists describing the genomic locations of these interactions. Our recently published BiSA (Binding Sites Analyser database contains transcription factor binding locations and epigenetic modifications collected from published studies and provides tools to analyse stored and imported data. Using BiSA we investigated the overlapping cis-regulatory role of estrogen receptor alpha (ERα and progesterone receptor (PR in the T-47D breast cancer cell line. We found that ERα binding sites overlap with a subset of PR binding sites. To investigate further, we re-analysed raw data to remove any biases introduced by the use of distinct tools in the original publications. We identified 22,152 PR and 18,560 ERα binding sites (<5% false discovery rate with 4,358 overlapping regions among the two datasets. BiSA statistical analysis revealed a non-significant overall overlap correlation between the two factors, suggesting that ERα and PR are not partner factors and do not require each other for binding to occur. However, Monte Carlo simulation by Binary Interval Search (BITS, Relevant Distance, Absolute Distance, Jaccard and Projection tests by Genometricorr revealed a statistically significant spatial correlation of binding regions on chromosome between the two factors. Motif analysis revealed that the shared binding regions were enriched with binding motifs for ERα, PR and a number of other transcription and pioneer factors. Some of these factors are known to co-locate with ERα and PR binding. Therefore spatially close proximity of ERα binding sites with PR binding sites suggests that ERα and PR, in general function independently at the molecular level, but that their activities converge on a specific subset of transcriptional targets.
Full Text Available Salvia miltiorrhiza is a traditional Chinese medicinal herb used for treating cardiovascular diseases. Depside salt from S. miltiorrhiza (DSSM contains the following active components: magnesium lithospermate B, lithospermic acid, and rosmarinic acid. This study aimed to reveal the mechanisms of action of DSSM. After searching for DSSM-associated genes in GeneCards, Search Tool for Interacting Chemicals, SuperTarget, PubChem, and Comparative Toxicogenomics Database, they were subjected to enrichment analysis using Multifaceted Analysis Tool for Human Transcriptome. A protein-protein interaction (PPI network was visualised; module analysis was conducted using the Cytoscape software. Finally, a transcriptional regulatory network was constructed using the TRRUST database and Cytoscape. Seventy-three DSSM-associated genes were identified. JUN, TNF, NFKB1, and FOS were hub nodes in the PPI network. Modules 1 and 2 were identified from the PPI network, with pathway enrichment analysis, showing that the presence of NFKB1 and BCL2 in module 1 was indicative of a particular association with the NF-κB signalling pathway. JUN, TNF, NFKB1, FOS, and BCL2 exhibited notable interactions among themselves in the PPI network. Several regulatory relationships (such as JUN → TNF/FOS, FOS → NFKB1 and NFKB1 → BCL2/TNF were also found in the regulatory network. Thus, DSSM exerts effects against cardiovascular diseases by targeting JUN, TNF, NFKB1, FOS, and BCL2.
Bioinformatic evaluation of L-arginine catabolic pathways in 24 cyanobacteria and transcriptional analysis of genes encoding enzymes of L-arginine catabolism in the cyanobacterium Synechocystis sp. PCC 6803
Schriek, Sarah; R?ckert, Christian; Staiger, Dorothee; Pistorius, Elfriede K; Michel, Klaus-Peter
Abstract Background So far very limited knowledge exists on L-arginine catabolism in cyanobacteria, although six major L-arginine-degrading pathways have been described for prokaryotes. Thus, we have performed a bioinformatic analysis of possible L-arginine-degrading pathways in cyanobacteria. Further, we chose Synechocystis sp. PCC 6803 for a more detailed bioinformatic analysis and for validation of the bioinformatic predictions on L-arginine catabolism with a transcript analysis. Results W...
Full Text Available Alcohol dehydrogenases (ADH, encoded by multigene family in plants, play a critical role in plant growth, development, adaptation, fruit ripening and aroma production. Thirteen ADH genes were identified in melon genome, including 12 ADHs and one formaldehyde dehydrogenease (FDH, designated CmADH1-12 and CmFDH1, in which CmADH1 and CmADH2 have been isolated in Cantaloupe. ADH genes shared a lower identity with each other at the protein level and had different intron-exon structure at nucleotide level. No typical signal peptides were found in all CmADHs, and CmADH proteins might locate in the cytoplasm. The phylogenetic tree revealed that 13 ADH genes were divided into 3 groups respectively, namely long-, medium- and short-chain ADH subfamily, and CmADH1,3-11, which belongs to the medium-chain ADH subfamily, fell into 6 medium-chain ADH subgroups. CmADH12 may belong to the long-chain ADH subfamily, while CmFDH1 may be a Class III ADH and serve as an ancestral ADH in melon. Expression profiling revealed that CmADH1, CmADH2, CmADH10 and CmFDH1 were moderately or strongly expressed in different vegetative tissues and fruit at medium and late developmental stages, while CmADH8 and CmADH12 were highly expressed in fruit after 20 days. CmADH3 showed preferential expression in young tissues. CmADH4 only had slight expression in root. Promoter analysis revealed several motifs of CmADH genes involved in the gene expression modulated by various hormones, and the response pattern of CmADH genes to ABA, IAA and ethylene were different. These CmADHs were divided into ethylene-sensitive and –insensitive groups, and the functions of CmADHs were discussed.
Good, Benjamin M; Su, Andrew I
Bioinformatics is faced with a variety of problems that require human involvement. Tasks like genome annotation, image analysis, knowledge-base population and protein structure determination all benefit from human input. In some cases, people are needed in vast quantities, whereas in others, we need just a few with rare abilities. Crowdsourcing encompasses an emerging collection of approaches for harnessing such distributed human intelligence. Recently, the bioinformatics community has begun to apply crowdsourcing in a variety of contexts, yet few resources are available that describe how these human-powered systems work and how to use them effectively in scientific domains. Here, we provide a framework for understanding and applying several different types of crowdsourcing. The framework considers two broad classes: systems for solving large-volume 'microtasks' and systems for solving high-difficulty 'megatasks'. Within these classes, we discuss system types, including volunteer labor, games with a purpose, microtask markets and open innovation contests. We illustrate each system type with successful examples in bioinformatics and conclude with a guide for matching problems to crowdsourcing solutions that highlights the positives and negatives of different approaches.
Lucas Antón Pastur-Romay
Full Text Available Over the past decade, Deep Artificial Neural Networks (DNNs have become the state-of-the-art algorithms in Machine Learning (ML, speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs. All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS, Quantitative Structure–Activity Relationship (QSAR research, protein structure prediction and genomics (and other omics data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron–Astrocyte Networks (DANAN could overcome the difficulties in architecture design, learning process and scalability of the current ML methods.
Pastur-Romay, Lucas Antón; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana Belén
Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL) and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs). All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS), Quantitative Structure-Activity Relationship (QSAR) research, protein structure prediction and genomics (and other omics) data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron-Astrocyte Networks (DANAN) could overcome the difficulties in architecture design, learning process and scalability of the current ML methods.
Pastur-Romay, Lucas Antón; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana Belén
Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL) and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs). All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS), Quantitative Structure–Activity Relationship (QSAR) research, protein structure prediction and genomics (and other omics) data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron–Astrocyte Networks (DANAN) could overcome the difficulties in architecture design, learning process and scalability of the current ML methods. PMID:27529225
Wang, Fen; Ye, Bin
Cyst echinococcosis caused by the matacestodal larvae of Echinococcus granulosus (Eg), is a chronic, worldwide, and severe zoonotic parasitosis. The treatment of cyst echinococcosis is still difficult since surgery cannot fit the needs of all patients, and drugs can lead to serious adverse events as well as resistance. The screen of target proteins interacted with new anti-hydatidosis drugs is urgently needed to meet the prevailing challenges. Here, we analyzed the sequences and structure properties, and constructed a phylogenetic tree by bioinformatics methods. The MIP family signature and Protein kinase C phosphorylation sites were predicted in all nine EgAQPs. α-helix and random coil were the main secondary structures of EgAQPs. The numbers of transmembrane regions were three to six, which indicated that EgAQPs contained multiple hydrophobic regions. A neighbor-joining tree indicated that EgAQPs were divided into two branches, seven EgAQPs formed a clade with AQP1 from human, a "strict" aquaporins, other two EgAQPs formed a clade with AQP9 from human, an aquaglyceroporins. Unfortunately, homology modeling of EgAQPs was aborted. These results provide a foundation for understanding and researches of the biological function of E. granulosus.
Basyuni, M.; Wati, R.
This study described the bioinformatics methods to analyze seven oxidosqualene cyclase (OSC) genes from mangrove plants on DDBJ/EMBL/GenBank as well as predicted the structure, composition, similarity, subcellular localization and phylogenetic. The physical and chemical properties of seven mangrove OSC showed variation among the genes. The percentage of the secondary structure of seven mangrove OSC genes followed the order of a helix > random coil > extended chain structure. The values of chloroplast or signal peptide were too low, indicated that no chloroplast transit peptide or signal peptide of secretion pathway in mangrove OSC genes. The target peptide value of mitochondria varied from 0.163 to 0.430, indicated it was possible to exist. These results suggested the importance of understanding the diversity and functional of properties of the different amino acids in mangrove OSC genes. To clarify the relationship among the mangrove OSC gene, a phylogenetic tree was constructed. The phylogenetic tree shows that there are three clusters, Kandelia KcMS join with Bruguiera BgLUS, Rhizophora RsM1 was close to Bruguiera BgbAS, and Rhizophora RcCAS join with Kandelia KcCAS. The present study, therefore, supported the previous results that plant OSC genes form distinct clusters in the tree.
Xiao, Jing; Lu, Fu-Ping; Li, Yu; Li, Jin-Ting
In order to exploit new genetic resources, Pectate lyase(PEL) gene was amplified by PCR using the genome DNA from an alkaline Bacillus subtilis521. The PCR product was inserted into pET22b(+) vector. The recombinant plasmids were cloned in E.coli DH5α and then expressed in E.coli BL21. When cultured in the optimized medium, the positive clones E.coli BL21(pET22b(+)pel)showed intracellular pectate lyase activity of 90.0 U/mL. It was indicated that we had obtained the correct PEL gene. The pel has an open reading frame of 1263 nucleotides and codes for a product of 420 amino acids with a calculated molecular mass of 45.5 kD. Based on computer assisted analysis, a signal peptides and two conserved domains were revealed. The sequence analysis for PEL showed that it shares 26-82% homology with other strains in GenBank. In addition, the advanced structure of PEL were also predicted and analysed. This study will help to the experimental design of PEL fermentation and production purification and enzyme evolution.
Full Text Available Fungal laccases have been used in various fields ranging from processes in wood and paper industries to environmental applications. Although a few bacterial laccases have been characterized in recent years, prokaryotes have largely been neglected as a source of novel enzymes, in part due to the lack of knowledge about the diversity and distribution of laccases within Bacteria. In this work genes for laccase-like enzymes were searched for in over 2,200 complete and draft bacterial genomes and four metagenomic datasets, using the custom profile Hidden Markov Models for two- and three-domain laccases. More than 1,200 putative genes for laccase-like enzymes were retrieved from chromosomes and plasmids of diverse bacteria. In 76% of the genes, signal peptides were predicted, indicating that these bacterial laccases may be exported from the cytoplasm, which contrasts with the current belief. Moreover, several examples of putatively horizontally transferred bacterial laccase genes were described. Many metagenomic sequences encoding fragments of laccase-like enzymes could not be phylogenetically assigned, indicating considerable novelty. Laccase-like genes were also found in anaerobic bacteria, autotrophs and alkaliphiles, thus opening new hypotheses regarding their ecological functions. Bacteria identified as carrying laccase genes represent potential sources for future biotechnological applications.
Le Large, Tessa Y. S.; Mato Prado, Mireia; Krell, Jonathan; Bijlsma, Maarten F.; Meijer, Laura L.; Kazemier, Geert; Frampton, Adam E.; Giovannetti, Elisa
Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease characterized by a dense desmoplastic reaction surrounding malignant epithelial cells. Interaction between the epithelial and stromal compartments is suggested to enhance its aggressive nature. Indeed, therapies targeting the stroma, as
Felsani, Armando; Gudmundsson, Bjarki; Nanni, Simona; Brini, Elena; Moles, Anna; Thormar, Hans Guttormur; Estibeiro, Peter; Gaetano, Carlo; Capogrossi, Maurizio; Farsetti, Antonella; Jonsson, Jon Johannes; Guffanti, Alessandro
Different ChIP-Seq protocols may have a significant impact on the final outcome in terms of quality, number and distribution of called peaks. Sample DNA undergoes a long procedure before the final sequencing step, and damaged DNA can result in excessive mismatches in the alignment with reference genome. In this letter, we present the effect of well-defined modifications (timing of formaldehyde crosslink reversal, brand of the sonicator) of standard ChIP-Seq protocol on parallel samples derived from the same cell line correlating the initial DNA quality control metrics to the final bioinformatics analysis results. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please email: firstname.lastname@example.org.
Suwanchaichinda, C.; Brattsten, L. B.
Abstract The cytochrome P450 monooxygenase (P450) enzyme system is a major mechanism of xenobiotic biotransformation. The nicotinamide adenine dinucleotide phosphate (NADPH)-cytochrome P450 reductase (CPR) is required for transfer of electrons from NADPH to P450. One CPR gene was identified in the genome of the malaria-transmitting mosquito Anopheles stephensi Liston (Diptera: Culicidae). The gene encodes a polypeptide containing highly conserved flavin mononucleotide-, flavin adenine dinucleotide-, and NADPH-binding domains, a unique characteristic of the reductase. Phylogenetic analysis revealed that the A. stephensi and other known mosquito CPRs belong to a monophyletic group distinctly separated from other insects in the same order, Diptera. Amino acid residues of CPRs involved in binding of P450 and cytochrome c are conserved between A. stephensi and the Norway rat Rattus norvegicus Berkenhout (Rodentia: Muridae). However, gene structure particularly within the coding region is evidently different between the two organisms. Such difference might arise during the evolution process as also seen in the difference of P450 families and isoforms found in these organisms. CPR in the mosquito A. stephensi is expected to be active and serve as an essential component of the P450 system. PMID:25368081
Kesika, Periyanaina; Balamurugan, Krishnaswamy
Shigella boydii causes bacillary dysentery or shigellosis and generates a significant burden in the developing nations. S. boydii-mediated infection assays were performed at both physiological and molecular levels using Caenorhabditis elegans as a host. Continuous exposure of worms to S. boydii showed a reduced life span indicating the pathogenicity of Shigella. Quantitative Real-Time PCR analysis was performed to analyze the expression and regulation of host specific candidate-antimicrobial genes (clec-60, clec-87, lys-7), which were expressed significantly during early infection, but weakened during the latter hours. Increased mortality of mutant RB1285 by S. boydii and Shigella flexneri indicated the role of lys-7 during Shigella infection. Protein-protein interactions (PPIs) database was used to analyze the interaction of immune proteins in both C. elegans and humans. In addition, the expression and regulation were revealed about immune genes (clec-61, clec-62, clec-63, F54D5.3 and ZK1320.2), which encode several intermediate immune protein partners (CLEC-61, CLEC-62, CLEC-63, F54D5.3, ZK1320.2, W03D2.6 and THN-2) that interact with LYS-7 and CLEC-60 and were found to play a role in C. elegans immune defense against S. boydii infections. Similarly, the immune genes that are specific to the human defense system, which encode IGHV4-39, A2M, LTF, and CD79A, were predicted to be expressed with LYZ and MBL2, thus indicating their regulation during Shigella infections. Our results using the lowest eukaryotic model system and human database indicated that the major players involved in immunity-related processes appear to be common in cases of Shigella sp. mediated immune responses. This article is part of a Special Issue entitled: Computational Methods for Protein Interaction and Structural Prediction. Copyright © 2012 Elsevier B.V. All rights reserved.
Remarkable advances in next-generation sequencing (NGS) technologies, bioinformatics algorithms, and computational technologies have significantly accelerated genomic research. However, complicated NGS data analysis still remains as a major bottleneck. RNA-seq, as one of the major area in the NGS fi...
van Kampen, Antoine H C; Moerland, Perry D
Systems medicine promotes a range of approaches and strategies to study human health and disease at a systems level with the aim of improving the overall well-being of (healthy) individuals, and preventing, diagnosing, or curing disease. In this chapter we discuss how bioinformatics critically contributes to systems medicine. First, we explain the role of bioinformatics in the management and analysis of data. In particular we show the importance of publicly available biological and clinical repositories to support systems medicine studies. Second, we discuss how the integration and analysis of multiple types of omics data through integrative bioinformatics may facilitate the determination of more predictive and robust disease signatures, lead to a better understanding of (patho)physiological molecular mechanisms, and facilitate personalized medicine. Third, we focus on network analysis and discuss how gene networks can be constructed from omics data and how these networks can be decomposed into smaller modules. We discuss how the resulting modules can be used to generate experimentally testable hypotheses, provide insight into disease mechanisms, and lead to predictive models. Throughout, we provide several examples demonstrating how bioinformatics contributes to systems medicine and discuss future challenges in bioinformatics that need to be addressed to enable the advancement of systems medicine.
Full Text Available Flow cytometry bioinformatics is the application of bioinformatics to flow cytometry data, which involves storing, retrieving, organizing, and analyzing flow cytometry data using extensive computational resources and tools. Flow cytometry bioinformatics requires extensive use of and contributes to the development of techniques from computational statistics and machine learning. Flow cytometry and related methods allow the quantification of multiple independent biomarkers on large numbers of single cells. The rapid growth in the multidimensionality and throughput of flow cytometry data, particularly in the 2000s, has led to the creation of a variety of computational analysis methods, data standards, and public databases for the sharing of results. Computational methods exist to assist in the preprocessing of flow cytometry data, identifying cell populations within it, matching those cell populations across samples, and performing diagnosis and discovery using the results of previous steps. For preprocessing, this includes compensating for spectral overlap, transforming data onto scales conducive to visualization and analysis, assessing data for quality, and normalizing data across samples and experiments. For population identification, tools are available to aid traditional manual identification of populations in two-dimensional scatter plots (gating, to use dimensionality reduction to aid gating, and to find populations automatically in higher dimensional space in a variety of ways. It is also possible to characterize data in more comprehensive ways, such as the density-guided binary space partitioning technique known as probability binning, or by combinatorial gating. Finally, diagnosis using flow cytometry data can be aided by supervised learning techniques, and discovery of new cell types of biological importance by high-throughput statistical methods, as part of pipelines incorporating all of the aforementioned methods. Open standards, data
Goodacre, Norman; Aljanahi, Aisha; Nandakumar, Subhiksha; Mikailov, Mike; Khan, Arifa S
Detection of distantly related viruses by high-throughput sequencing (HTS) is bioinformatically challenging because of the lack of a public database containing all viral sequences, without abundant nonviral sequences, which can extend runtime and obscure viral hits. Our reference viral database (RVDB) includes all viral, virus-related, and virus-like nucleotide sequences (excluding bacterial viruses), regardless of length, and with overall reduced cellular sequences. Semantic selection criteria (SEM-I) were used to select viral sequences from GenBank, resulting in a first-generation viral database (VDB). This database was manually and computationally reviewed, resulting in refined, semantic selection criteria (SEM-R), which were applied to a new download of updated GenBank sequences to create a second-generation VDB. Viral entries in the latter were clustered at 98% by CD-HIT-EST to reduce redundancy while retaining high viral sequence diversity. The viral identity of the clustered representative sequences (creps) was confirmed by BLAST searches in NCBI databases and HMMER searches in PFAM and DFAM databases. The resulting RVDB contained a broad representation of viral families, sequence diversity, and a reduced cellular content; it includes full-length and partial sequences and endogenous nonretroviral elements, endogenous retroviruses, and retrotransposons. Testing of RVDBv10.2, with an in-house HTS transcriptomic data set indicated a significantly faster run for virus detection than interrogating the entirety of the NCBI nonredundant nucleotide database, which contains all viral sequences but also nonviral sequences. RVDB is publically available for facilitating HTS analysis, particularly for novel virus detection. It is meant to be updated on a regular basis to include new viral sequences added to GenBank. IMPORTANCE To facilitate bioinformatics analysis of high-throughput sequencing (HTS) data for the detection of both known and novel viruses, we have
Gong, Qimei; Jiang, Hongwei; Wang, Jinming; Ling, Junqi
To investigate the differential expression profile and bioinformatic analysis of microRNA (miRNA) in human dental pulp cells (DPC) during endothelial differentiation. DPC were cultured in endothelial induction medium (50 µg/L vascular endothelial growth factor, 10 µg/L basic fibroblast growth factor and 2% fetal calf serum) for 7 days. Meanwhile non-induced DPC were used as control.Quantitative real-time PCR (qRT-PCR) was applied to detect vascular endothelial marker genes [CD31, von Willebrand factor (vWF) and vascular endothelial-cadherin (VE-cadherin)] and in vitro tube formation on matrigel was used to analyze the angiogenic ability of differentiated cells. And then miRNA expression profiles of DPC were examined using miRNA microarray and then the differentially expressed miRNA were validated by qRT-PCR. Furthermore, bioinformatic analysis was employed to predict the target genes of miRNA and to analyze the possible biological functions and signaling pathways that were involved in DPC after induction. The relative mRNA level of CD31, vWF and VE-cadherin in the control group were (3.48 ± 0.22) ×10(-4), (3.13 ± 0.31) ×10(-4) and (39.60 ± 2.36) ×10(-4), and (19.57 ± 2.20) ×10(-4), (48.13 ± 0.54) ×10(-4) and (228.00 ± 8.89) ×10(-4) in the induced group. The expressions of CD31, vWF and VE-cadherin were increased significantly in endothelial induced DPC compared to the control group (P functions, such as the regulation of transcription, cell motion, blood vessel morphogenesis, angiogenesis and cytoskeletal protein, and signaling pathways including the mitogen-activated protein kinase (MAPK) and the Wnt signaling pathway. The differential miRNA expression identified in this study may be involved in governing DPC endothelial differentiation, thus contributing to the future research on regulatory mechanisms in dental pulp angiogenesis.
Pan, Hai-Tao; Ding, Hai-Gang; Fang, Min; Yu, Bin; Cheng, Yi; Tan, Ya-Jing; Fu, Qi-Qin; Lu, Bo; Cai, Hong-Guang; Jin, Xin; Xia, Xian-Qing; Zhang, Tao
Recurrent miscarriage (RM) affects 5% of women, it has an adverse emotional impact on women. Because of the complexities of early development, the mechanism of recurrent miscarriage is still unclear. We hypothesized that abnormal placenta leads to early recurrent miscarriage (ERM). The aim of this study was to identify ERM associated factors in human placenta villous tissue using proteomics. Investigation of these differences in protein expression in parallel profiling is essential to understand the comprehensive pathophysiological mechanism underlying recurrent miscarriage (RM). To gain more insight into mechanisms of recurrent miscarriage (RM), a comparative proteome profile of the human placenta villous tissue in normal and RM pregnancies was analyzed using iTRAQ technology and bioinformatics analysis used by Ingenuity Pathway Analysis (IPA) software. In this study, we employed an iTRAQ based proteomics analysis of four placental villous tissues from patients with early recurrent miscarriage (ERM) and four from normal pregnant women. Finally, we identified 2805 proteins and 79,998 peptides between patients with RM and normal matched group. Further analysis identified 314 differentially expressed proteins in placental villous tissue (≥1.3-fold, Student's t-test, p embryo. Furthermore, network analysis show that Angiotensinogen (AGT), MAPK14 and Prothrombin (F2) are core factors in early embryonic development. We used another 8 independent samples (4 cases and 4 controls) to cross validation of the proteomic data. This study has identified several proteins that are associated with early development, these results may supply new insight into mechanisms behind recurrent miscarriage. Copyright © 2017 Elsevier Ltd. All rights reserved.
Myster, Steven H; Wang, Fei; Cavallo, Robert; Christian, Whitney; Bhotika, Seema; Anderson, Charles T; Peifer, Mark
Genomic sequences provide powerful new tools in genetic analysis, making it possible to combine classical genetics with genomics to characterize the genes in a particular chromosome region. These approaches have been applied successfully to the euchromatin, but analysis of the heterochromatin has lagged somewhat behind. We describe a combined genetic and bioinformatics approach to the base of the right arm of the Drosophila melanogaster second chromosome, at the boundary between pericentric h...
Chen, Xiwen; Cheng, Anchun; Wang, Mingshu; Xiang, Jun
In this study, the predicted information about structures and functions of VP23 encoded by the newly identified DEV UL18 gene through bioinformatics softwares and tools. The DEV UL18 was predicted to encode a polypeptide with 322 amino acids, termed VP23, with a putative molecular mass of 35.250 kDa and a predicted isoelectric point (PI) of 8.37, no signal peptide and transmembrane domain in the polypeptide. The prediction of subcellular localization showed that the DEV-VP23 located at endoplasmic reticulum with 33.3%, mitochondrial with 22.2%, extracellular, including cell wall with 11.1%, vesicles of secretory system with 11.1%, Golgi with 11.1%, and plasma membrane with 11.1%. The acid sequence of analysis showed that the potential antigenic epitopes are situated in 45-47, 53-60, 102-105, 173-180, 185-189, 260-265, 267-271, and 292-299 amino acids. All the consequences inevitably provide some insights for further research about the DEV-VP23 and also provide a fundament for further study on the the new type clinical diagnosis of DEV and can be used for the development of new DEV vaccine.
Full Text Available Huang-Lian-Jie-Du-Tang (HLJDT is a classic TCM formula to clear “heat” and “poison” that exhibits antirheumatic activity. Here we investigated the therapeutic mechanisms of HLJDT at protein network level using bioinformatics approach. It was found that HLJDT shares 5 target proteins with 3 types of anti-RA drugs, and several pathways in immune system and bone formation are significantly regulated by HLJDT’s components, suggesting the therapeutic effect of HLJDT on RA. By defining an antirheumatic effect score to quantitatively measure the therapeutic effect, we found that the score of each HLJDT’s component is very low, while the whole HLJDT achieves a much higher effect score, suggesting a synergistic effect of HLJDT achieved by its multiple components acting on multiple targets. At last, topological analysis on the RA-associated PPI network was conducted to illustrate key roles of HLJDT’s target proteins on this network. Integrating our findings with TCM theory suggests that HLJDT targets on hub nodes and main pathway in the Hot ZENG network, and thus it could be applied as adjuvant treatment for Hot-ZENG-related RA. This study may facilitate our understanding of antirheumatic effect of HLJDT and it may suggest new approach for the study of TCM pharmacology.
Gao, Hongyu; Hawkins, Troy; Jasti, Aparna; Chen, Yu-Hsiang; Mockaitis, Keithanne; Dinauer, Mary; Cornetta, Kenneth
Integration of viral vectors into a host genome is associated with insertional mutagenesis and subjects in clinical gene therapy trials must be monitored for this adverse event. Several PCR based methods such as ligase-mediated (LM) PCR, linear-amplification-mediated (LAM) PCR and non-restrictive (nr) LAM PCR were developed to identify sites of vector integration. Coupling the power of next-generation sequencing technologies with various PCR approaches will provide a comprehensive and genome-wide profiling of insertion sites and increase throughput. In this bioinformatics study, we aimed to develop and apply quality metrics to viral insertion data obtained using next-generation sequencing. We developed five simple metrics for assessing next-generation sequencing data from different PCR products and showed how the metrics can be used to objectively compare runs performed with the same methodology as well as data generated using different PCR techniques. The results will help researchers troubleshoot complex methodologies, understand the quality of sequencing data, and provide a starting point for developing standardization of vector insertion site data analysis.
Daga, Aditi; Ansari, Afzal; Pandya, Medha; Shah, Krupa; Patel, Shanaya; Rawal, Rakesh; Umrania, Valentina
Recurrent non-random chromosomal translocations are hallmark characteristics of leukemogenesis, and however, molecular mechanisms underlying these rearrangements are less explored. The fundamental question is, why and how chromosomes break and reunite so precisely in the genome. Meticulous understanding of mechanism leading to chromosomal rearrangement can be achieved by characterizing breakpoints. To address this hypothesis, a novel multi-parametric computational approach for characterization of major leukemic translocations within and around breakpoint region was performed. To best of our knowledge, this bioinformatic analysis is unique in finding the presence of segmental duplications (SDs) flanking breakpoints of all major leukemic translocation. Breakpoint islands (BpIs) were analyzed for stress-induced duplex destabilization (SIDD) sites along with other complex genomic architecture and physicochemical properties. Our study distinctly emphasizes on the probable correlative role of SDs, SIDD sites and various genomic features in the occurrence of breakpoints. Further, it also highlights potential features which may be playing a crucial role in causing double-strand breaks, leading to translocation.
Zhu, Zheng; Qi, Yuhua; Fan, Huan; Cui, Lunbiao; Shi, Zhiyang
Hand, foot, and mouth disease (HFMD), mainly caused by coxsackievirus A16 (CVA16) and enterovirus 71 (EV71) infections, remains a serious public health issue with thousands of newly diagnostic cases each year since 2008 in China. The mechanisms underlying viral infection, however, are elusive to date. In the present study, we systematically investigated the host cellular microRNA (miRNA) expression patterns in response to CVA16 and EV71 infections. Through microarray examination, 27 miRNAs (15 upregulated and 12 downregulated) were found to be coassociated with the replication process of two viruses, while the expression levels of 15 and 5 miRNAs were significantly changed in CVA16- and EV71-infected cells, respectively. A great number of target genes of 27 common differentially expressed miRNAs were predicted by combined use of two computational target prediction algorithms, TargetScan and MiRanda. Comprehensive bioinformatic analysis of target genes in GO categories and KEGG pathways indicated the involvement of diverse biological functions and signaling pathways during viral infection. These results provide an overview of the roles of miRNAs in virus-host interaction, which will contribute to further understanding of HFMD pathological mechanisms.
Full Text Available Nudix enzymes are a superfamily with a conserved common reaction mechanism that provides the capacity for the hydrolysis of a broad spectrum of metabolites. We used hidden Markov models based on Nudix sequences from the PFAM and PROSITE databases to identify Nudix hydrolases encoded by the Arabidopsis genome. 25 Nudix hydrolases were identified and classified into 11 individual families by pairwise sequence alignments. Intron phases were strikingly conserved in each family. Phylogenetic analysis showed that all multimember families formed monophyletic clusters. Conserved familial sequence motifs were identified with the MEME motif analysis algorithm. One motif (motif 4 was found in three diverse families. All proteins containing motif 4 demonstrated a degree of preference for substrates containing an ADP moiety. We conclude that HMM model-based genome scanning and MEME motif analysis, respectively, can significantly improve the identification and assignment of function of new members of this mechanistically-diverse protein superfamily.
Chen, Wenzheng; Liu, Qingfeng; Lv, Yunxia; Xu, Debin; Chen, Wanzhi; Yu, Jichun
Papillary thyroid carcinoma (PTC) is the most common malignancy in thyroid tissue, and the number of patients with PTC has been increasing in recent years. Discovering the mechanism of PTC genesis and progression and finding new potential diagnostic biomarkers/therapeutic target genes of PTC are of great significance. In this work, the datasets GSE3467 and GSE3678 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified with the limma package in R. GO function and KEGG pathway enrichment were conducted with DAVID tool. The interaction network of the DEGs and other genes was performed with Cytoscape plugin BisoGenet, while clustering analysis was performed with Cytoscape plugin ClusterOne. A total of 1800 overlapped DEGs were detected in two datasets. Enrichment analysis of the DEGs found that the top three enriched GO terms in three ontologies and four significantly enriched KEGG pathways were mainly concerned with intercellular junction and extracellular matrix components. Interaction network analysis found that transcription factor hepatocyte nuclear factor 4, alpha (HNF4A) and DEG JUN had higher connection degrees. Clustering analysis indicated that two function modules, in which JUN was playing a central role, were highly relevant to PTC genesis and progression. JUN may be used as a specific diagnostic biomarker/therapeutic molecular target of PTC. However, further experiments are still needed to confirm our results.
Rawana N. Alkhalili
Full Text Available A thermophilic bacterial strain, Geobacillus sp. ZGt-1, isolated from Zara hot spring in Jordan, was capable of inhibiting the growth of the thermophilic G. stearothermophilus and the mesophilic Bacillus subtilis and Salmonella typhimurium on a solid cultivation medium. Antibacterial activity was not observed when ZGt-1 was cultivated in a liquid medium; however, immobilization of the cells in agar beads that were subjected to sequential batch cultivation in the liquid medium at 60 °C showed increasing antibacterial activity up to 14 cycles. The antibacterial activity was lost on protease treatment of the culture supernatant. Concentration of the protein fraction by ammonium sulphate precipitation followed by denaturing polyacrylamide gel electrophoresis separation and analysis of the gel for antibacterial activity against G. stearothermophilus showed a distinct inhibition zone in 15–20 kDa range, suggesting that the active molecule(s are resistant to denaturation by SDS. Mass spectrometric analysis of the protein bands around the active region resulted in identification of 22 proteins with molecular weight in the range of interest, three of which were new and are here proposed as potential antimicrobial protein candidates by in silico analysis of their amino acid sequences. Mass spectrometric analysis also indicated the presence of partial sequences of antimicrobial enzymes, amidase and dd-carboxypeptidase.
Full Text Available RNA expression analysis was performed on the corpus luteum tissue at five time points after prostaglandin F2 alpha treatment of midcycle cows using an Affymetrix Bovine Gene v1 Array. The normalized linear microarray data was uploaded to the NCBI GEO repository (GSE94069. Subsequent statistical analysis determined differentially expressed transcripts ± 1.5-fold change from saline control with P ≤ 0.05. Gene ontology of differentially expressed transcripts was annotated by DAVID and Panther. Physiological characteristics of the study animals are presented in a figure. Bioinformatic analysis by Ingenuity Pathway Analysis was curated, compiled, and presented in tables. A dataset comparison with similar microarray analyses was performed and bioinformatics analysis by Ingenuity Pathway Analysis, DAVID, Panther, and String of differentially expressed genes from each dataset as well as the differentially expressed genes common to all three datasets were curated, compiled, and presented in tables. Finally, a table comparing four bioinformatics tools’ predictions of functions associated with genes common to all three datasets is presented. These data have been further analyzed and interpreted in the companion article “Early transcriptome responses of the bovine mid-cycle corpus luteum to prostaglandin F2 alpha includes cytokine signaling” .
Ko, GunHwan; Kim, Pan-Gyu; Yoon, Jongcheol; Han, Gukhee; Park, Seong-Jin; Song, Wangho; Lee, Byungwook
While next-generation sequencing (NGS) costs have fallen in recent years, the cost and complexity of computation remain substantial obstacles to the use of NGS in bio-medical care and genomic research. The rapidly increasing amounts of data available from the new high-throughput methods have made data processing infeasible without automated pipelines. The integration of data and analytic resources into workflow systems provides a solution to the problem by simplifying the task of data analysis. To address this challenge, we developed a cloud-based workflow management system, Closha, to provide fast and cost-effective analysis of massive genomic data. We implemented complex workflows making optimal use of high-performance computing clusters. Closha allows users to create multi-step analyses using drag and drop functionality and to modify the parameters of pipeline tools. Users can also import the Galaxy pipelines into Closha. Closha is a hybrid system that enables users to use both analysis programs providing traditional tools and MapReduce-based big data analysis programs simultaneously in a single pipeline. Thus, the execution of analytics algorithms can be parallelized, speeding up the whole process. We also developed a high-speed data transmission solution, KoDS, to transmit a large amount of data at a fast rate. KoDS has a file transfer speed of up to 10 times that of normal FTP and HTTP. The computer hardware for Closha is 660 CPU cores and 800 TB of disk storage, enabling 500 jobs to run at the same time. Closha is a scalable, cost-effective, and publicly available web service for large-scale genomic data analysis. Closha supports the reliable and highly scalable execution of sequencing analysis workflows in a fully automated manner. Closha provides a user-friendly interface to all genomic scientists to try to derive accurate results from NGS platform data. The Closha cloud server is freely available for use from http://closha.kobic.re.kr/ .
Paparini, A; Santoni, D; Romano Spica, V
Sequence-based approaches to prokaryotic systematics and typing represent a modern and promising strategy in epidemiology and environmental microbiology. GenEnv, a database-driven system for bacterial typing, was developed in order to provide user friendly tools for supporting biomolecular analysis of bacteria. The family Vibrionaceae represents a heterogeneous taxon of aquatic microrganisms, harbouring a plethora of genomes currently analyzed by different molecular techniques. Under the query "Vibrio", GenEnv retrieved 256 organisms, included in a total number of 19 families. Overall, 548 sequences, comprising 16S rRNA (n=402), rpoB (n=1), gyrB (n=145) were available. In addition, GenEnv system allowed primer design, homology analysis and restriction maps, for immediate applications to the study of Vibrionaceae.
D'Souza, Mark; Sulakhe, Dinanath; Wang, Sheng; Xie, Bing; Hashemifar, Somaye; Taylor, Andrew; Dubchak, Inna; Conrad Gilliam, T; Maltsev, Natalia
Recent technological advances in genomics allow the production of biological data at unprecedented tera- and petabyte scales. Efficient mining of these vast and complex datasets for the needs of biomedical research critically depends on a seamless integration of the clinical, genomic, and experimental information with prior knowledge about genotype-phenotype relationships. Such experimental data accumulated in publicly available databases should be accessible to a variety of algorithms and analytical pipelines that drive computational analysis and data mining.We present an integrated computational platform Lynx (Sulakhe et al., Nucleic Acids Res 44:D882-D887, 2016) ( http://lynx.cri.uchicago.edu ), a web-based database and knowledge extraction engine. It provides advanced search capabilities and a variety of algorithms for enrichment analysis and network-based gene prioritization. It gives public access to the Lynx integrated knowledge base (LynxKB) and its analytical tools via user-friendly web services and interfaces. The Lynx service-oriented architecture supports annotation and analysis of high-throughput experimental data. Lynx tools assist the user in extracting meaningful knowledge from LynxKB and experimental data, and in the generation of weighted hypotheses regarding the genes and molecular mechanisms contributing to human phenotypes or conditions of interest. The goal of this integrated platform is to support the end-to-end analytical needs of various translational projects.
Full Text Available Background. Coronary artery atherosclerosis is a chronic inflammatory disease. This study aimed to identify the key changes of gene expression between early and advanced carotid atherosclerotic plaque in human. Methods. Gene expression dataset GSE28829 was downloaded from Gene Expression Omnibus (GEO, including 16 advanced and 13 early stage atherosclerotic plaque samples from human carotid. Differentially expressed genes (DEGs were analyzed. Results. 42,450 genes were obtained from the dataset. Top 100 up- and downregulated DEGs were listed. Functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG identification were performed. The result of functional and pathway enrichment analysis indicted that the immune system process played a critical role in the progression of carotid atherosclerotic plaque. Protein-protein interaction (PPI networks were performed either. Top 10 hub genes were identified from PPI network and top 6 modules were inferred. These genes were mainly involved in chemokine signaling pathway, cell cycle, B cell receptor signaling pathway, focal adhesion, and regulation of actin cytoskeleton. Conclusion. The present study indicated that analysis of DEGs would make a deeper understanding of the molecular mechanisms of atherosclerosis development and they might be used as molecular targets and diagnostic biomarkers for the treatment of atherosclerosis.
Hao, Ling; Leng, Jun; Xiao, Ruijing; Kingsley, Tembo; Li, Xinran; Tu, Zhenbo; Yang, Xiangyong; Deng, Xinzhou; Xiong, Meng; Xiong, Jie; Zhang, Qiuping
Tripartite motif containing 28 (TRIM28) is a transcriptional regulator acting as an essential corepressor for Krüppel-associated box zinc finger domain-containing proteins in multiple tissue and cell types. An increasing number of studies have investigated the function of TRIM28; however, its prognostic value in breast cancer (BC) remains unclear. In the present study, the expression of TRIM28 was identified to be significantly higher in cancerous compared with healthy tissue samples. Furthermore, it was demonstrated that TRIM28 expression was significantly correlated with several clinicopathological characteristics of patients with BC, such as p53 mutation, tumor recurrence and Elston grade of the tumor. In addition, a protein-protein interaction network was created to illustrate the interactions of TRIM28 with other proteins. The prognostic value of TRIM28 in patients with BC was investigated using the Kaplan-Meier Plotter database, which revealed that high expression of TRIM28 is a predictor of poor prognosis in patients with BC. In conclusion, the results of the present study indicate that TRIM28 provides a survival advantage to patients with BC and is a novel prognostic biomarker, in addition to being a therapeutic target for the treatment of BC.
Rasmussen Carol A
Full Text Available Abstract Background The nonhuman primate model of glaucomatous optic neuropathy most faithfully reproduces the human disease. We used high-density oligonucleotide arrays to investigate whole genome transcriptional changes occurring at the optic nerve head during primate experimental glaucoma. Results Laser scarification of the trabecular meshwork of cynomolgus macaques produced elevated intraocular pressure that was monitored over time and led to varying degrees of damage in different samples. The macaques were examined clinically before enucleation and the myelinated optic nerves were processed post-mortem to determine the degree of neuronal loss. Global gene expression was examined in dissected optic nerve heads with Affymetrix GeneChip microarrays. We validated a subset of differentially expressed genes using qRT-PCR, immunohistochemistry, and immuno-enriched astrocytes from healthy and glaucomatous human donors. These genes have previously defined roles in axonal outgrowth, immune response, cell motility, neuroprotection, and extracellular matrix remodeling. Conclusion Our findings show that glaucoma is associated with increased expression of genes that mediate axonal outgrowth, immune response, cell motility, neuroprotection, and ECM remodeling. These studies also reveal that, as glaucoma progresses, retinal ganglion cell axons may make a regenerative attempt to restore lost nerve cell contact.
Bioinformatic evaluation of L-arginine catabolic pathways in 24 cyanobacteria and transcriptional analysis of genes encoding enzymes of L-arginine catabolism in the cyanobacterium Synechocystis sp. PCC 6803
Pistorius Elfriede K
Full Text Available Abstract Background So far very limited knowledge exists on L-arginine catabolism in cyanobacteria, although six major L-arginine-degrading pathways have been described for prokaryotes. Thus, we have performed a bioinformatic analysis of possible L-arginine-degrading pathways in cyanobacteria. Further, we chose Synechocystis sp. PCC 6803 for a more detailed bioinformatic analysis and for validation of the bioinformatic predictions on L-arginine catabolism with a transcript analysis. Results We have evaluated 24 cyanobacterial genomes of freshwater or marine strains for the presence of putative L-arginine-degrading enzymes. We identified an L-arginine decarboxylase pathway in all 24 strains. In addition, cyanobacteria have one or two further pathways representing either an arginase pathway or L-arginine deiminase pathway or an L-arginine oxidase/dehydrogenase pathway. An L-arginine amidinotransferase pathway as a major L-arginine-degrading pathway is not likely but can not be entirely excluded. A rather unusual finding was that the cyanobacterial L-arginine deiminases are substantially larger than the enzymes in non-photosynthetic bacteria and that they are membrane-bound. A more detailed bioinformatic analysis of Synechocystis sp. PCC 6803 revealed that three different L-arginine-degrading pathways may in principle be functional in this cyanobacterium. These are (i an L-arginine decarboxylase pathway, (ii an L-arginine deiminase pathway, and (iii an L-arginine oxidase/dehydrogenase pathway. A transcript analysis of cells grown either with nitrate or L-arginine as sole N-source and with an illumination of 50 μmol photons m-2 s-1 showed that the transcripts for the first enzyme(s of all three pathways were present, but that the transcript levels for the L-arginine deiminase and the L-arginine oxidase/dehydrogenase were substantially higher than that of the three isoenzymes of L-arginine decarboxylase. Conclusion The evaluation of 24
Maloney, Mark; Parker, Jeffrey; LeBlanc, Mark; Woodard, Craig T.; Glackin, Mary; Hanrahan, Michael
Recent advances involving high-throughput techniques for data generation and analysis have made familiarity with basic bioinformatics concepts and programs a necessity in the biological sciences. Undergraduate students increasingly need training in methods related to finding and retrieving information stored in vast databases. The rapid rise of…
Vesth, Tammi Camilla; Rasmussen, Jane Lind Nybo; Theobald, Sebastian
with the Joint Genome Institute. The Aspergillus Mine is not intended as a genomic data sharing service but instead focuses on creating an environment where the results of bioinformatic analysis is made available for inspection. The data and code is public upon request and figures can be obtained directly from...
Full Text Available Toll-like receptors (TLRs play important role in the innate immune system. TLR15 is reported to have a unique role in defense against pathogens, but its structural and evolution characterizations are still poorly understood. In this study, we identified 57 completed TLR15 genes from avian and reptilian genomes. TLR15 clustered into an individual clade and was closely related to family 1 on the phylogenetic tree. Unlike the TLRs in family 1 with the broken asparagine ladders in the middle, TLR15 ectodomain had an intact asparagine ladder that is critical to maintain the overall shape of ectodomain. The conservation analysis found that TLR15 ectodomain had a highly evolutionarily conserved region on the convex surface of LRR11 module, which is probably involved in TLR15 activation process. Furthermore, the protein–protein docking analysis indicated that TLR15 TIR domains have the potential to form homodimers, the predicted interaction interface of TIR dimer was formed mainly by residues from the BB-loops and αC-helixes. Although TLR15 mainly underwent purifying selection, we detected 27 sites under positive selection for TLR15, 24 of which are located on its ectodomain. Our observations suggest the structural features of TLR15 which may be relevant to its function, but which requires further experimental validation.
Shan, Si; Tu, Jun; Nie, Peng; Yan, Xiaojun
Objective: To study the molecular mechanism of Rheum officinale in the treatment of Jaundice by building molecular networks and comparing canonical pathways. Methods: Target proteins of Rheum officinale and related genes of Jaundice were searched from Pubchem and Gene databases online respectively. Molecular networks and canonical pathways comparison analyses were performed by Ingenuity Pathway Analysis (IPA). Results: The molecular networks of Rheum officinale and Jaundice were complex and multifunctional. The 40 target proteins of Rheum officinale and 33 Homo sapiens genes of Jaundice were found in databases. There were 19 common pathways both related networks. Rheum officinale could regulate endothelial differentiation, Interleukin-1B (IL-1B) and Tumor Necrosis Factor (TNF) in these pathways. Conclusions: Rheum officinale treat Jaundice by regulating many effective nodes of Apoptotic pathway and cellular immunity related pathways.
Ma, Min; Luo, Shulin; Zhou, Wei; Lu, Liangyu; Cai, Junfeng; Yuan, Feng; Yin, Feng
The aim of this study was to gain a better understanding of the molecular mechanisms and identify more critical genes associated with the pathogenesis of postmenopausal osteoporosis (PMOP). Microarray data of GSE13850 were download from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified either in B cells from postmenopausal female nonsmokers with high bone mineral density (BMD) compared with those with low BMD (defined as DEG1 group) or in B cells from postmenopausal female smokers with high BMD compared with postmenopausal female nonsmokers with high BMD (defined as DEG2 group). Gene ontology and immune-related functional enrichment analysis of DEGs were performed. Additionally, the protein-protein interaction network of all DEGs was constructed and subnetworks of the hub genes were extracted. A total of 51 DEGs were identified in the DEG1 group, including 30 up- and 21 downregulated genes. Besides, 86 DEGs were identified in the DEG2 group, of which 46 were upregulated and 40 were downregulated. Immune enrichment analysis showed DEGs were mainly enriched in functions of CD molecules and chemokines and receptor, and the upregulated gene interleukin 4 receptor (IL-4R) was significantly enriched. Moreover, guanine nucleotide-binding protein G (GNAI2), filamin A alpha (FLNA), and transforming growth factor-β1 (TGFB1) were hub proteins in the protein-protein interaction network. IL-4R, GNAI2, FLNA, and TGFB1 may be potential target genes associated with the pathogenesis of PMOP. In particular, FLNA, and TGFB1 may be affected by smoking, a risk factor of PMOP. Copyright © 2017. Published by Elsevier B.V.
Linghu, Dandan; Guo, Lili; Zhao, Yinghua; Liu, Zhiming; Zhao, Mingwei; Huang, Lvzhen; Li, Xiaoxin
To analyze proteins in the tissue of pterygia, and to investigate their potential roles in pterygia, using the comparative proteomic technique of Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) coupled with offline 2DLC-MS/MS, Western-bolt. The tissue of pterygia and healthy conjunctiva was collected from 10 pterygia patients (6 females, 4 males; average age was 52 years old; average course of disease was 6 years) in our hospital from September, 2015 to March, 2016. iTRAQ was used to analyze proteins in the patients' pterygia and healthy conjunctiva. Proteins with a fold change of >2. 0 or proteins were subjected to subsequent gene ontology analysis using the DAVID database. Then we confirmed the targeted proteins with western-blot. 156 proteins that expressed differently between the pterygia and healthy conjunctiva were identified using iTRAQ analysis. Of these proteins, 18 were down-regulated, and 138 were up-regulated. On the basis of biological processes in gene ontology, the identified proteins were mainly involved in cellular process, metabolic process, developmental process, location, cellular component organization, Among these proteins, matrix Metalloproteinase 10 (MMP-10) and CD34 may have potential roles in the pathogenesis of pterygia. Then we confirmed with Western-bolt that MMP-10 and CD34 were up-regulated in pterygia. This study is the first to identify 156 proteins associated with pterygia with iTRAQ technology. Data in our study will aid in providing a better understanding of pterygia. © 2017 The Authors. PROTEOMICS - Clinical Applications published by WILEY-VCH Verlag GmbH & Co. KGaA.
Ai, L; Xu, M J; Chen, M X; Zhang, Y N; Chen, S H; Guo, J; Cai, Y C; Zhou, X N; Zhu, X Q; Chen, J X
The beef tapeworm Taenia saginata infects human beings with symptoms ranging from nausea, abdominal discomfort to digestive disturbances and intestinal blockage. In the present study, microRNA (miRNA) expressing profile in adult T. saginata was analyzed using Solexa deep sequencing and bioinformatics analysis. A total of 15.8 million reads was obtained by Solexa sequencing, and 13.3 million clean reads (1.73 million unique sequences) was obtained after removing reads smaller than 18 nt. Ten conserved miRNAs corresponding to 607,382 reads were found when matching the reads against known miRNAs of Schistosoma japonicum in miRBase database. The miR-71 had the most abundant expression in T. saginata, followed by miR-219-5p, but some other common miRNAs such as let-7, miR-40, and miR-103 were not identified in T. saginata. Nucleotide bias analysis found that the known miRNAs showed high bias and the uracil was the dominant nucleotide, particularly at the first and 11th positions which were almost at the beginning and middle of conserved miRNAs. One novel miRNA (Tsa-miR-001) corresponding to ten precursors was identified and confirmed by stem-loop RT-PCR. To our knowledge, this is the first report of miRNA profiles in T. saginata, which will contribute to better understanding of the complex biology of this zoonotic trematode. The reported data of T. saginata miRNAs should provide valuable references for miRNA studies of closed related zoonotic Taenia cestodes such as Taenia solium and Taenia asiatica.
Full Text Available Molecular imaging has moved to the forefront of drug development and biomedical research. The identification of appropriate imaging targets has become the touchstone for the accurate diagnosis and prognosis of human cancer. Particularly, cell surface- or membrane-bound proteins are attractive imaging targets for their aberrant expression, easily accessible location, and unique biochemical functions in tumor cells. Previously, we published a literature mining of potential targets for our in-house enzyme-mediated cancer imaging and therapy technology. Here we present a simple and integrated bioinformatics analysis approach that assembles a public cancer microarray database with a pathway knowledge base for ascertaining and prioritizing upregulated genes encoding cell surface- or membrane-bound proteins, which could serve imaging targets. As examples, we obtained lists of potential hits for six common and lethal human tumors in the prostate, breast, lung, colon, ovary, and pancreas. As control tests, a number of well-known cancer imaging targets were detected and confirmed by our study. Further, by consulting gene-disease and protein-disease databases, we suggest a number of significantly upregulated genes as promising imaging targets, including cell surface-associated mucin-1, prostate-specific membrane antigen, hepsin, urokinase plasminogen activator receptor, and folate receptors. By integrating pathway analysis, we are able to organize and map “focused” interaction networks derived from significantly dysregulated entity pairs to reflect important cellular functions in disease processes. We provide herein an example of identifying a tumor cell growth and proliferation subnetwork for prostate cancer. This systematic mining approach can be broadly applied to identify imaging or therapeutic targets for other human diseases.
Platt, Michael; Howell, Sara; Sachdeva, Ricky; Dumont, Charles
Clinical allergy cross-reactivity that is seen with related inhalant allergens or between unrelated inhalant allergens and foods in oral allergy syndrome (OAS) remains poorly understood. The goal of this study is to determine whether clinical cross-reactivity can be identified from primary protein sequences in allergy epitopes and food proteins. High-throughput analysis was performed by assembling all known allergy epitopes within the Immune Epitope Database (IEDB; http://www.iedb.org) for 5 common species from 5 inhalant allergen subclasses and comparing their protein sequences to each other, as well as to sequences of intact proteins from known cross-reactive foods in the European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI) protein database (http://www.uniprot.org) that have been implicated in OAS. Computational methods were employed to allow for exact matching, gaps, and similar amino acids using multiple algorithms. A phylogenetic tree was created to determine evolutionary relationships between cross-reactive epitopes in OAS. Twenty-three common inhalant allergens had 4429 unique epitopes; the 19 foods implicated in OAS had 9497 protein sequences. The Basic Local Alignment Search Tool (BLAST) algorithm identified interclass and intraclass sequence similarities for the 5 inhalant allergy classes with high similarity for mites, grasses, and trees. Analysis of OAS proteins identified 104 matches to inhalant allergy epitopes that are known to cross-react. The phylogenetic tree displayed relationships that mostly followed organism phylogeny. Use of primary protein sequences was successful in explaining clinical allergy cross-reactivity. Clinical correlation is needed for use of these epitopes as diagnostic or therapeutic entities for patients with cross-reactive allergic disease. © 2014 ARS-AAOA, LLC.
Full Text Available Background: Reduced salivation is considered a major clinical feature of most but not all cases of primary Sjögren's syndrome (pSS. Reduced saliva flow may lead to changes in the salivary microbiota. These changes have mainly been studied with culture that typically recovers only 65% of the bacteria present. Objective: This study was to use high throughput sequencing, covering both cultivated and not-yet-cultivated bacteria, to assess the bacterial microbiota of whole saliva in pSS patients with normal salivation. Methods: Bacteria of whole unstimulated saliva from nine pSS patients with normal salivation flow and from nine healthy controls were examined by high throughput sequencing of the hypervariable region V1V2 of 16S rRNA using the 454 GS Junior system. Raw sequence reads were subjected to a species-level, reference-based taxonomy assignment pipeline specially designed for studying the human oral microbial community. Each of the sequence reads was BLASTN-searched against a database consisting of reference sequences representing 1,156 oral and 12,013 non-oral species. Unassigned reads were then screened for high-quality non-chimeras and subjected to de novo species-level operational taxonomy unit (OTU calling for potential novel species. Downstream analyses, including alpha and beta diversities, were analyzed using the Quantitative Insights into Microbial Ecology (QIIME pipeline. To reveal significant differences between the microbiota of control saliva and Sjögren's saliva, a statistical method introduced in Metastats www.metastats.cbcb.umd.edu was used. Results: Saliva of pSS patients with normal salivation had a significantly higher frequency of Firmicutes compared with controls (p=0.004. Two other major phyla, Synergistetes and Spirochaetes, were significantly depleted in pSS (p=0.001 for both. In addition, we saw a nearly 17% decrease in the number of genera in pSS (25 vs. 30. While Prevotella was almost equally abundant in both
Full Text Available Guang-Yu Wang,1,* Ling Li,2,* Bo Liu,1 Xiao Han,1 Chun-Hua Wang,1 Ji-Wen Wang3 1Department of Neurosurgery, 2Department of Pediatrics, Qilu Children’s Hospital of Shandong University, Jinan, Shandong, 3Department of Neurology, Shanghai Children’s Medical Center, Shanghai Jiaotong University School of Medicine, Pudong New District, Shanghai, People’s Republic of China *These authors contributed equally to this work Purpose: This study aimed to explore significant genes and pathways involved in the pathogenesis of supratentorial primitive neuroectodermal tumor (sPNET. Materials and methods: Gene expression profile of GSE14295 was downloaded from publicly available Gene Expression Omnibus (GEO database. Differentially expressed genes (DEGs were screened out in primary sPNET samples compared with normal fetal and adult brain reference samples (sPNET vs fetal brain and sPNET vs adult brain. Pathway enrichment analysis of these DEGs was conducted, followed by protein–protein interaction (PPI network construction and significant module selection. Additionally, transcription factors (TFs regulating the common DEGs in the two comparison groups were identified, and the regulatory network was constructed. Results: In total, 526 DEGs (99 up- and 427 downregulated in sPNET vs fetal brain and 815 DEGs (200 up- and 615 downregulated in sPNET vs adult brain were identified. DEGs in sPNET vs fetal brain and sPNET vs adult brain were associated with calcium signaling pathway, cell cycle, and p53 signaling pathway. CDK1, CDC20, BUB1B, and BUB1 were hub nodes in the PPI networks of DEGs in sPNET vs fetal brain and sPNET vs adult brain. Significant modules were extracted from the PPI networks. In addition, 64 upregulated and 200 downregulated overlapping DEGs were identified in both sPNET vs fetal brain and sPNET vs adult brain. The genes involved in the regulatory network upon overlapping DEGs and the TFs were correlated with calcium signaling pathway
Full Text Available The molecular mechanisms and genetic risk factors underlying Alzheimer's disease (AD pathogenesis are only partly understood. To identify new factors, which may contribute to AD, different approaches are taken including proteomics, genetics, and functional genomics. Here, we used a bioinformatics approach and found that distinct AD-related genes share modules of transcription factor binding sites, suggesting a transcriptional coregulation. To detect additional coregulated genes, which may potentially contribute to AD, we established a new bioinformatics workflow with known multivariate methods like support vector machines, biclustering, and predicted transcription factor binding site modules by using in silico analysis and over 400 expression arrays from human and mouse. Two significant modules are composed of three transcription factor families: CTCF, SP1F, and EGRF/ZBPF, which are conserved between human and mouse APP promoter sequences. The specific combination of in silico promoter and multivariate analysis can identify regulation mechanisms of genes involved in multifactorial diseases.
Miguel E Rentería
Full Text Available The insulin receptor (IR, the insulin-like growth factor 1 receptor (IGF1R and the insulin receptor-related receptor (IRR are covalently-linked homodimers made up of several structural domains. The molecular mechanism of ligand binding to the ectodomain of these receptors and the resulting activation of their tyrosine kinase domain is still not well understood. We have carried out an amino acid residue conservation analysis in order to reconstruct the phylogeny of the IR Family. We have confirmed the location of ligand binding site 1 of the IGF1R and IR. Importantly, we have also predicted the likely location of the insulin binding site 2 on the surface of the fibronectin type III domains of the IR. An evolutionary conserved surface on the second leucine-rich domain that may interact with the ligand could not be detected. We suggest a possible mechanical trigger of the activation of the IR that involves a slight 'twist' rotation of the last two fibronectin type III domains in order to face the likely location of insulin. Finally, a strong selective pressure was found amongst the IRR orthologous sequences, suggesting that this orphan receptor has a yet unknown physiological role which may be conserved from amphibians to mammals.
Magis, Andrew T; Funk, Cory C; Price, Nathan D
The process of converting raw RNA sequencing data to interpretable results can be circuitous and time consuming, requiring multiple steps. We present an RNA-seq mapping algorithm that streamlines this process. Our algorithm utilizes a hash table approach to leverage the availability and power of high memory machines. SNAPR, which can be run on a single library or thousands of libraries, can take compressed or uncompressed FASTQ and BAM files as inputs, and can output a sorted BAM file, individual read counts, gene fusions and identify exogenous RNA species in a single step. SNAPR also does native Phred score filtering of reads. SNAPR is also well suited for future sequencing platforms that generate longer reads. Using SNAPR, we show how we can analyze data from hundreds of TCGA samples in a matter of hours, while identifying gene fusions and viral events at the same time. With the references genome and transcriptome undergoing periodic updates, and the need for uniform parameters when integrating multiple data sets, there is great need for a streamlined process for RNA-seq analysis. We demonstrate how SNAPR does this efficiently and accurately, with the high-throughput capacity needed to do high-volume analyses.
Full Text Available Trypanosoma brucei is a protozoan parasite of major of interest in discovering new genes for drug targets. This parasite alternates its life cycle between the mammal host(s (bloodstream form and the insect vector (procyclic form, with two divergent glucose metabolism amenable to in vitro culture. While the metabolic network of the bloodstream forms has been well characterized, the flux distribution between the different branches of the glucose metabolic network in the procyclic form has not been addressed so far. We present a computational analysis (called Metaboflux that exploits the metabolic topology of the procyclic form, and allows the incorporation of multipurpose experimental data to increase the biological relevance of the model. The alternatives resulting from the structural complexity of networks are formulated as an optimization problem solved by a metaheuristic where experimental data are modeled in a multiobjective function. Our results show that the current metabolic model is in agreement with experimental data and confirms the observed high metabolic flexibility of glucose metabolism. In addition, Metaboflux offers a rational explanation for the high flexibility in the ratio between final products from glucose metabolism, thsat is, flux redistribution through the malic enzyme steps.
Bhagwan N. Rekadwad
Full Text Available A total of five highly related strains of an unidentified marine bacterium were analyzed through their short genome sequences (AM260709–AM260713. Genome-to-Genome Distance (GGDC showed high similarity to Pseudoalteromonas haloplanktis (X67024. The generated unique Quick Response (QR codes indicated no identity to other microbial species or gene sequences. Chaos Game Representation (CGR showed the number of bases concentrated in the area. Guanine residues were highest in number followed by cytosine. Frequency of Chaos Game Representation (FCGR indicated that CC and GG blocks have higher frequency in the sequence from the evaluated marine bacterium strains. Maximum GC content for the marine bacterium strains ranged 53-54%. The use of QR codes, CGR, FCGR, and GC dataset helped in identifying and interpreting short genome sequences from specific isolates. A phylogenetic tree was constructed with the bootstrap test (1000 replicates using MEGA6 software. Principal Component Analysis (PCA was carried out using EMBL-EBI MUSCLE program. Thus, generated genomic data are of great assistance for hierarchical classification in Bacterial Systematics which combined with phenotypic features represents a basic procedure for a polyphasic approach on unambiguous bacterial isolate taxonomic classification.
Guo, Wenbin; Yuan, Huwei; Gao, Liuxiao; Guo, Haipeng; Qiu, Lingling; Xu, Dongbin; Yan, Daoliang; Zheng, Bingsong
PILS is a key auxin efflux carrier protein in the auxin signal transduction. A CcPILS gene related to hickory (Carya carthayensis) grafting process was obtained by RACE techniques. The full length of CcPILS gene was1541bp contained a 1263bp length open reading flame (ORF). The CcPILS encoded 294 amino acids with molecular weight of 46 kDa, PI 5.38 and localized at endoplasmic reticulum membrane. The gene contained a central hydrophilic loop separating two hydrophobic domains of about five transmembrane regions each. The gene of CcPILS belonged to Clade III sub-family of PILS and its sequence had high homology with Arabidopsis. Real Time RT-PCR analysis showed that the gene expressions were weakly induced in bud, inflorescence, fruit, leaf and stem, while strongly in root. The expression levels were strongly induced and reached a peak at the third day of grafting in scion and rootstock of hickory, which were 1.45 and 3.45 times higher, respectively, compared to that of control. The results indicated that CcPILS may be involved in regulating the expression of genes related to auxin signal transduction during hickory graft process.
Full Text Available Chinese hamster ovary (CHO cell lines represent the most commonly used mammalian expression system for the production of therapeutic proteins. In this context, detailed knowledge of the CHO cell transcriptome might help to improve biotechnological processes conducted by specific cell lines. Nevertheless, very few assembled cDNA sequences of CHO cells were publicly released until recently, which puts a severe limitation on biotechnological research. Two extended annotation systems and web-based tools, one for browsing eukaryotic genomes (GenDBE and one for viewing eukaryotic transcriptomes (SAMS, were established as the first step towards a publicly usable CHO cell genome/transcriptome analysis platform. This is complemented by the development of a new strategy to assemble the ca. 100 million reads, sequenced from a broad range of diverse transcripts, to a high quality CHO cell transcript set. The cDNA libraries were constructed from different CHO cell lines grown under various culture conditions and sequenced using Roche/454 and Illumina sequencing technologies in addition to sequencing reads from a previous study. Two pipelines to extend and improve the CHO cell line transcripts were established. First, de novo assemblies were carried out with the Trinity and Oases assemblers, using varying k-mer sizes. The resulting contigs were screened for potential CDS using ESTScan. Redundant contigs were filtered out using cd-hit-est. The remaining CDS contigs were re-assembled with CAP3. Second, a reference-based assembly with the TopHat/Cufflinks pipeline was performed, using the recently published draft genome sequence of CHO-K1 as reference. Additionally, the de novo contigs were mapped to the reference genome using GMAP and merged with the Cufflinks assembly using the cuffmerge software. With this approach 28,874 transcripts located on 16,492 gene loci could be assembled. Combining the results of both approaches, 65,561 transcripts were identified
Fuller, Jonathan C; Khoueiry, Pierre; Dinkel, Holger; Forslund, Kristoffer; Stamatakis, Alexandros; Barry, Joseph; Budd, Aidan; Soldatos, Theodoros G; Linssen, Katja; Rajput, Abdul Mateen
The third Heidelberg Unseminars in Bioinformatics (HUB) was held on 18th October 2012, at Heidelberg University, Germany. HUB brought together around 40 bioinformaticians from academia and industry to discuss the 'Biggest Challenges in Bioinformatics' in a 'World Café' style event.
Fuller, Jonathan C; Khoueiry, Pierre; Dinkel, Holger; Forslund, Kristoffer; Stamatakis, Alexandros; Barry, Joseph; Budd, Aidan; Soldatos, Theodoros G; Linssen, Katja; Rajput, Abdul Mateen
The third Heidelberg Unseminars in Bioinformatics (HUB) was held in October at Heidelberg University in Germany. HUB brought together around 40 bioinformaticians from academia and industry to discuss the ‘Biggest Challenges in Bioinformatics' in a ‘World Café' style event.
Full Text Available Patients with systemic lupus erythematosus (SLE and Sjögren's syndrome (SS display increased levels of type I IFN-induced genes. Plasmacytoid dendritic cells (PDCs are natural interferon producing cells and considered to be a primary source of IFN-α in these two diseases. Differential expression patterns of type I IFN inducible transcripts can be found in different immune cell subsets and in patients with both active and inactive autoimmune disease. A type I IFN gene signature generally consists of three groups of IFN-induced genes - those regulated in response to virus-induced type I IFN, those regulated by the IFN-induced mitogen-activated protein kinase/extracellular-regulated kinase (MAPK/ERK pathway, and those by the IFN-induced phosphoinositide-3 kinase (PI-3K pathway. These three groups of type I IFN-regulated genes control important cellular processes such as apoptosis, survival, adhesion, and chemotaxis, that when dysregulated, contribute to autoimmunity. With the recent generation of large datasets in the public domain from next-generation sequencing and DNA microarray experiments, one can perform detailed analyses of cell type-specific gene signatures as well as identify distinct transcription factors that differentially regulate these gene signatures. We have performed bioinformatics analysis of data in the public domain and experimental data from our lab to gain insight into the regulation of type I IFN gene expression. We have found that the genetic landscape of the IFNA and IFNB genes are occupied by transcription factors, such as insulators CTCF and cohesin, that negatively regulate transcription, as well as IRF5 and IRF7, that positively and distinctly regulate IFNA subtypes. A detailed understanding of the factors controlling type I IFN gene transcription will significantly aid in the identification and development of new therapeutic strategies targeting the IFN pathway in autoimmune disease.
Gary J. Olsen
Nesbo, Boucher and Doolittle (2001) used phylogenetic trees of four taxa to assess whether euryarchaeal genes share a common history. They have suggested that of the 521 genes examined, each of the three possible tree topologies relating the four taxa was supported essentially equal numbers of times. They suggest that this might be the result of numerous horizontal gene transfer events, essentially randomizing the relationships between gene histories (as inferred in the 521 gene trees) and organismal relationships (which would be a single underlying tree). Motivated by the fact that the order in which sequences are added to a multiple sequence alignment influences the alignment, and ultimately inferred tree, they were interested in the extent to which the variations among inferred trees might be due to variations in the alignment order. This bears directly on their efforts to evaluate and improve upon methods of multiple sequence alignment. They set out to analyze the influence of alignment order on the tree inferred for 43 genes shared among these same 4 taxa. Because alignments produced by CLUSTALW are directed by a rooted guide tree (the denderogram), there are 15 possible alignment orders of 4 taxa. For each gene they tested all 15 alignment orders, and as a 16th option, allowed CLUSTALW to generate its own guide tree. If we supply all 15 possible rooted guide trees, they expected that at least one of them should be as good at CLUSTAL's own guide tree, but most of the time they differed (sometimes being better than CLUSTAL's default tree and sometimes being worse). The difference seems to be that the user-supplied tree is not given meaningful branch lengths, which effect the assumed probability of amino acid changes. They examined the practicality of modifying CLUSTALW to improve its treatment of user-supplied guide trees. This work became ever increasing bogged down in finding and repairing minor bugs in the CLUSTALW code. This effort was put on hold as we feel that our other proposed approaches will ultimately be better.
Full Text Available Simultaneous nitrate-N, phosphate and COD removal was evaluated from synthetic waste water using mixed microbial consortia in an anoxic environment under various initial carbon load (ICL in a batch scale reactor system. Within 6 hours of incubation, enriched DNPAOs (Denitrifying Polyphosphate Accumulating Microorganisms were able to remove maximum COD (87% at 2 g/L of ICL whereas maximum nitrate-N (97% and phosphate (87% removal along with PHB accumulation (49 mg/L was achieved at 8 g/L of ICL. Exhaustion of nitrate-N, beyond 6 hours of incubation, had a detrimental effect on COD and phosphate removal rate. Fresh supply of nitrate-N to the reaction medium, beyond 6 hours, helped revive the removal rates of both COD and phosphate. Therefore, it was apparent that in spite of a high carbon load, maximum COD and nutrient removal can be maintained, with adequate nitrate-N availability. Denitrifying condition in the medium was evident from an increasing pH trend. PHB accumulation by the mixed culture was directly proportional to ICL; however the time taken for accumulation at higher ICL was more. Unlike conventional EBPR, PHB depletion did not support phosphate accumulation in this case. The unique aspect of all the batch studies were PHB accumulation was observed along with phosphate uptake and nitrate reduction under anoxic conditions. Bioinformatics analysis followed by pyrosequencing of the mixed culture DNA from the seed sludge revealed the dominance of denitrifying population, such as Corynebacterium, Rhodocyclus and Paraccocus (Alphaproteobacteria and Betaproteobacteria. Rarefaction curve indicated complete bacterial population and corresponding number of OTUs through sequence analysis. Chao1 and Shannon index (H' was used to study the diversity of sampling. "UCI95" and "LCI95" indicated 95% confidence level of upper and lower values of Chao1 for each distance. Values of Chao1 index supported the results of rarefaction curve.
Dai, Lin; Gao, Xin; Guo, Yan; Xiao, Jingfa; Zhang, Zhang
As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics. This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.
Full Text Available Abstract As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS, Software as a Service (SaaS, Platform as a Service (PaaS, and Infrastructure as a Service (IaaS, and present our perspectives on the adoption of cloud computing in bioinformatics. Reviewers This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.
Abstract As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics. Reviewers This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor. PMID:23190475
As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics.This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor. 2012 Dai et al.; licensee BioMed Central Ltd.
Monosomic analysis reveals duplicated chromosomal segments in maize genome. MAHESH C. YADAV1,2∗, J. K. S. ... cated chromosomal segments in maize genome. Materials and methods. Development and .... each in chromosomes 2 and 7, while 10 other pairs of du- plicate loci had one copy in chromosome 3 and the ...
Genomics analysis of genes expressed reveals differential responses to low chronic nitrogen stress in maize. ... Most induced clones were largely involved in various metabolism processes including physiological process, organelle regulation of biological process, nutrient reservoir activity, transcription regulator activity and ...
Full Text Available The immensely popular fields of cancer research and bioinformatics overlap in many different areas, e.g. large data repositories that allow for users to analyze data from many experiments (data handling, databases, pattern mining, microarray data analysis, and interpretation of proteomics data. There are many newly available resources in these areas that may be unfamiliar to most cancer researchers wanting to incorporate bioinformatics tools and analyses into their work, and also to bioinformaticians looking for real data to develop and test algorithms. This review reveals the interdependence of cancer research and bioinformatics, and highlight the most appropriate and useful resources available to cancer researchers. These include not only public databases, but general and specific bioinformatics tools which can be useful to the cancer researcher. The primary foci are function and structure prediction tools of protein genes. The result is a useful reference to cancer researchers and bioinformaticians studying cancer alike.
Deshmukh, Atul S; Cox, Juergen; Jensen, Lars Juhl
the secretome of lipid-induced insulin-resistant skeletal muscle cells. Our workflow identified 1073 putative secreted proteins including 32 growth factors, 25 cytokines, and 29 metalloproteinases. In addition to previously reported proteins, we report hundreds of novel ones. Intriguingly, ∼40% of the secreted......-resistant conditions. Our study demonstrates an efficient combined experimental and bioinformatics workflow to identify putative secreted proteins from insulin-resistant skeletal muscle cells, which could easily be adapted to other cellular models....
Researchers take on challenges and opportunities to mine "Big Data" for answers to complex biological questions. Learn how bioinformatics uses advanced computing, mathematics, and technological platforms to store, manage, analyze, and understand data.
Spengler, Sylvia J.
There is a well-known story about the blind man examining the elephant: the part of the elephant examined determines his perception of the whole beast. Perhaps bioinformatics--the shotgun marriage between biology and mathematics, computer science, and engineering--is like an elephant that occupies a large chair in the scientific living room. Given the demand for and shortage of researchers with the computer skills to handle large volumes of biological data, where exactly does the bioinformatics elephant sit? There are probably many biologists who feel that a major product of this bioinformatics elephant is large piles of waste material. If you have tried to plow through Web sites and software packages in search of a specific tool for analyzing and collating large amounts of research data, you may well feel the same way. But there has been progress with major initiatives to develop more computing power, educate biologists about computers, increase funding, and set standards. For our purposes, bioinformatics is not simply a biologically inclined rehash of information theory (1) nor is it a hodgepodge of computer science techniques for building, updating, and accessing biological data. Rather bioinformatics incorporates both of these capabilities into a broad interdisciplinary science that involves both conceptual and practical tools for the understanding, generation, processing, and propagation of biological information. As such, bioinformatics is the sine qua non of 21st-century biology. Analyzing gene expression using cDNA microarrays immobilized on slides or other solid supports (gene chips) is set to revolutionize biology and medicine and, in so doing, generate vast quantities of data that have to be accurately interpreted (Fig. 1). As discussed at a meeting a few months ago (Microarray Algorithms and Statistical Analysis: Methods and Standards; Tahoe City, California; 9-12 November 1999), experiments with cDNA arrays must be subjected to quality control
Min, Seonwoo; Lee, Byunghan; Yoon, Sungroh
In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-the-art performance in various fields. Accordingly, application of deep learning in bioinformatics to gain insight from data has been emphasized in both academia and industry. Here, we review deep learning in bioinformatics, presenting examples of current research. To provide a useful and comprehensive perspective, we categorize research both by the bioinformatics domain (i.e. omics, biomedical imaging, biomedical signal processing) and deep learning architecture (i.e. deep neural networks, convolutional neural networks, recurrent neural networks, emergent architectures) and present brief descriptions of each study. Additionally, we discuss theoretical and practical issues of deep learning in bioinformatics and suggest future research directions. We believe that this review will provide valuable insights and serve as a starting point for researchers to apply deep learning approaches in their bioinformatics studies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: email@example.com.
Semenov, Mikhail; Zhuravleva, Anna; Semenov, Vyacheslav; Yevdokimov, Ilya; Larionova, Alla
Recent climate scenarios predict not only continued global warming but also an increased frequency and intensity of extreme climatic events such as strong changes in temperature and precipitation regimes. Microorganisms are well known to be more sensitive to changes in environmental conditions than to other soil chemical and physical parameters. In this study, we determined the shifts in soil microbial community structure as well as indicative taxa in soils under three moisture regimes using high-throughput Illumina sequencing and range of bioinformatics approaches for the assessment of sequence data. Incubation experiments were performed in soil-filled (Greyic Phaeozems Albic) rhizoboxes with maize and without plants. Three contrasting moisture regimes were being simulated: 1) optimal wetting (OW), a watering 2-3 times per week to maintain soil moisture of 20-25% by weight; 2) periodic wetting (PW), with alternating periods of wetting and drought; and 3) constant insufficient wetting (IW), while soil moisture of 12% by weight was permanently maintained. Sampled fresh soils were homogenized, and the total DNA of three replicates was extracted using the FastDNA® SPIN kit for Soil. DNA replicates were combined in a pooled sample and the DNA was used for PCR with specific primers for the 16S V3 and V4 regions. In order to compare variability between different samples and replicates within a single sample, some DNA replicates treated separately. The products were purified and submitted to Illumina MiSeq sequencing. Sequence data were evaluated by alpha-diversity (Chao1 and Shannon H' diversity indexes), beta-diversity (UniFrac and Bray-Curtis dissimilarity), heatmap, tagcloud, and plot-bar analyses using the MiSeq Reporter Metagenomics Workflow and R packages (phyloseq, vegan, tagcloud). Shannon index varied in a rather narrow range (4.4-4.9) with the lowest values for microbial communities under PW treatment. Chao1 index varied from 385 to 480, being a more flexible
Pallen, Mark J
Microbial bioinformatics in 2020 will remain a vibrant, creative discipline, adding value to the ever-growing flood of new sequence data, while embracing novel technologies and fresh approaches. Databases and search strategies will struggle to cope and manual curation will not be sustainable during the scale-up to the million-microbial-genome era. Microbial taxonomy will have to adapt to a situation in which most microorganisms are discovered and characterised through the analysis of sequences. Genome sequencing will become a routine approach in clinical and research laboratories, with fresh demands for interpretable user-friendly outputs. The "internet of things" will penetrate healthcare systems, so that even a piece of hospital plumbing might have its own IP address that can be integrated with pathogen genome sequences. Microbiome mania will continue, but the tide will turn from molecular barcoding towards metagenomics. Crowd-sourced analyses will collide with cloud computing, but eternal vigilance will be the price of preventing the misinterpretation and overselling of microbial sequence data. Output from hand-held sequencers will be analysed on mobile devices. Open-source training materials will address the need for the development of a skilled labour force. As we boldly go into the third decade of the twenty-first century, microbial sequence space will remain the final frontier! © 2016 The Author. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.
Schweighofer, Karl; Pohorille, Andrew
Building on an existing prototype, we have fielded a facility with bioinformatics technologies that will help NASA meet its unique requirements for biological research. This facility consists of a cluster of computers capable of performing computationally intensive tasks, software tools, databases and knowledge management systems. Novel computational technologies for analyzing and integrating new biological data and already existing knowledge have been developed. With continued development and support, the facility will fulfill strategic NASA s bioinformatics needs in astrobiology and space exploration. . As a demonstration of these capabilities, we will present a detailed analysis of how spaceflight factors impact gene expression in the liver and kidney for mice flown aboard shuttle flight STS-108. We have found that many genes involved in signal transduction, cell cycle, and development respond to changes in microgravity, but that most metabolic pathways appear unchanged.
Vymětal, Jiří; Slabý, I.; Spahr, A.; Vondrášek, Jiří; Lyngstadaas, S. P.
Roč. 116, č. 2 (2008), s. 124-134 ISSN 0909-8836 R&D Projects: GA ČR GA203/05/0009; GA ČR GA203/06/1727; GA MŠk LC512 Grant - others:EU(XE) QLK3-CT-2001-00090 Institutional research plan: CEZ:AV0Z40550506 Keywords : ameloblastin * bioinformatic modelling * calcium * intrinsically unstructured protein Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 1.957, year: 2008
Olsen, Lars Rønn; Campos, Benito; Barnkob, Mike Stein
cancer immunotherapies has yet to be fulfilled. The insufficient efficacy of existing treatments can be attributed to a number of biological and technical issues. In this review, we detail the current limitations of immunotherapy target selection and design, and review computational methods to streamline...... therapy target discovery in a bioinformatics analysis pipeline. We describe specialized bioinformatics tools and databases for three main bottlenecks in immunotherapy target discovery: the cataloging of potentially antigenic proteins, the identification of potential HLA binders, and the selection epitopes...
Full Text Available The assessment of genetically modified (GM crops for regulatory approval currently requires a detailed molecular characterization of the DNA sequence and integrity of the transgene locus. In addition, molecular characterization is a critical component of event selection and advancement during product development. Typically, molecular characterization has relied on Southern blot analysis to establish locus and copy number along with targeted sequencing of polymerase chain reaction products spanning any inserted DNA to complete the characterization process. Here we describe the use of next generation (NexGen sequencing and junction sequence analysis bioinformatics in a new method for achieving full molecular characterization of a GM event without the need for Southern blot analysis. In this study, we examine a typical GM soybean [ (L. Merr.] line and demonstrate that this new method provides molecular characterization equivalent to the current Southern blot-based method. We also examine an event containing in vivo DNA rearrangement of multiple transfer DNA inserts to demonstrate that the new method is effective at identifying complex cases. Next generation sequencing and bioinformatics offers certain advantages over current approaches, most notably the simplicity, efficiency, and consistency of the method, and provides a viable alternative for efficiently and robustly achieving molecular characterization of GM crops.
Wang, Chen; Han, Jian; Liu, Chonghuai; Kibet, Korir Nicholas; Kayesh, Emrul; Shangguan, Lingfei; Li, Xiaoying; Fang, Jinggui
MicroRNA (miRNA) is a class of functional non-coding small RNA with 19-25 nucleotides in length while Amur grape (Vitis amurensis Rupr.) is an important wild fruit crop with the strongest cold resistance among the Vitis species, is used as an excellent breeding parent for grapevine, and has elicited growing interest in wine production. To date, there is a relatively large number of grapevine miRNAs (vv-miRNAs) from cultivated grapevine varieties such as Vitis vinifera L. and hybrids of V. vinifera and V. labrusca, but there is no report on miRNAs from Vitis amurensis Rupr, a wild grapevine species. A small RNA library from Amur grape was constructed and Solexa technology used to perform deep sequencing of the library followed by subsequent bioinformatics analysis to identify new miRNAs. In total, 126 conserved miRNAs belonging to 27 miRNA families were identified, and 34 known but non-conserved miRNAs were also found. Significantly, 72 new potential Amur grape-specific miRNAs were discovered. The sequences of these new potential va-miRNAs were further validated through miR-RACE, and accumulation of 18 new va-miRNAs in seven tissues of grapevines confirmed by real time RT-PCR (qRT-PCR) analysis. The expression levels of va-miRNAs in flowers and berries were found to be basically consistent in identity to those from deep sequenced sRNAs libraries of combined corresponding tissues. We also describe the conservation and variation of va-miRNAs using miR-SNPs and miR-LDs during plant evolution based on comparison of orthologous sequences, and further reveal that the number and sites of miR-SNP in diverse miRNA families exhibit distinct divergence. Finally, 346 target genes for the new miRNAs were predicted and they include a number of Amur grape stress tolerance genes and many genes regulating anthocyanin synthesis and sugar metabolism. Deep sequencing of short RNAs from Amur grape flowers and berries identified 72 new potential miRNAs and 34 known but non-conserved mi
Full Text Available Abstract Background MicroRNA (miRNA is a class of functional non-coding small RNA with 19-25 nucleotides in length while Amur grape (Vitis amurensis Rupr. is an important wild fruit crop with the strongest cold resistance among the Vitis species, is used as an excellent breeding parent for grapevine, and has elicited growing interest in wine production. To date, there is a relatively large number of grapevine miRNAs (vv-miRNAs from cultivated grapevine varieties such as Vitis vinifera L. and hybrids of V. vinifera and V. labrusca, but there is no report on miRNAs from Vitis amurensis Rupr, a wild grapevine species. Results A small RNA library from Amur grape was constructed and Solexa technology used to perform deep sequencing of the library followed by subsequent bioinformatics analysis to identify new miRNAs. In total, 126 conserved miRNAs belonging to 27 miRNA families were identified, and 34 known but non-conserved miRNAs were also found. Significantly, 72 new potential Amur grape-specific miRNAs were discovered. The sequences of these new potential va-miRNAs were further validated through miR-RACE, and accumulation of 18 new va-miRNAs in seven tissues of grapevines confirmed by real time RT-PCR (qRT-PCR analysis. The expression levels of va-miRNAs in flowers and berries were found to be basically consistent in identity to those from deep sequenced sRNAs libraries of combined corresponding tissues. We also describe the conservation and variation of va-miRNAs using miR-SNPs and miR-LDs during plant evolution based on comparison of orthologous sequences, and further reveal that the number and sites of miR-SNP in diverse miRNA families exhibit distinct divergence. Finally, 346 target genes for the new miRNAs were predicted and they include a number of Amur grape stress tolerance genes and many genes regulating anthocyanin synthesis and sugar metabolism. Conclusions Deep sequencing of short RNAs from Amur grape flowers and berries identified 72
Mihalas, George I; Tudor, Anca; Paralescu, Sorin; Andor, Minodora; Stoicu-Tivadar, Lacramioara
The paper refers to our methodology and experience in establishing the content of the course in bioinformatics introduced to the school of "Information Systems in Healthcare" (SIIS), master level. The syllabi of both lectures and laboratory works are presented and discussed.
Suplatov, Dmitry; Kirilin, Eugeny; Arbatsky, Mikhail; Takhaveev, Vakil; Svedas, Vytas
The new web-server pocketZebra implements the power of bioinformatics and geometry-based structural approaches to identify and rank subfamily-specific binding sites in proteins by functional significance, and select particular positions in the structure that determine selective accommodation of ligands. A new scoring function has been developed to annotate binding sites by the presence of the subfamily-specific positions in diverse protein families. pocketZebra web-server has multiple input modes to meet the needs of users with different experience in bioinformatics. The server provides on-site visualization of the results as well as off-line version of the output in annotated text format and as PyMol sessions ready for structural analysis. pocketZebra can be used to study structure-function relationship and regulation in large protein superfamilies, classify functionally important binding sites and annotate proteins with unknown function. The server can be used to engineer ligand-binding sites and allosteric regulation of enzymes, or implemented in a drug discovery process to search for potential molecular targets and novel selective inhibitors/effectors. The server, documentation and examples are freely available at http://biokinet.belozersky.msu.ru/pocketzebra and there are no login requirements. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
Zhao, Xiaolu; Leon, Ileana R; Bak, Steffen
. In skeletal muscle, mitochondrial dysfunction is linked to insulin resistance in humans with obesity and type 2 diabetes. We performed a phosphoproteomic study of functional mitochondria isolated from human muscle biopsies with the aim to obtain a comprehensive overview of mitochondrial phosphoproteins....... Future comparative phosphoproteome analysis of mitochondria from healthy and diseased individuals will provide insights into the role of abnormal phosphorylation in pathologies, such as type 2 diabetes....... in insulin resistance. We also assigned phosphorylation sites in mitochondrial proteins involved in amino acid degradation, importers and transporters, calcium homeostasis, and apoptosis. Bioinformatics analysis of kinase motifs revealed that many of these mitochondrial phosphoproteins are substrates...
Mulder, Nicola J; Adebiyi, Ezekiel; Adebiyi, Marion; Adeyemi, Seun; Ahmed, Azza; Ahmed, Rehab; Akanle, Bola; Alibi, Mohamed; Armstrong, Don L; Aron, Shaun; Ashano, Efejiro; Baichoo, Shakuntala; Benkahla, Alia; Brown, David K; Chimusa, Emile R; Fadlelmola, Faisal M; Falola, Dare; Fatumo, Segun; Ghedira, Kais; Ghouila, Amel; Hazelhurst, Scott; Isewon, Itunuoluwa; Jung, Segun; Kassim, Samar Kamal; Kayondo, Jonathan K; Mbiyavanga, Mamana; Meintjes, Ayton; Mohammed, Somia; Mosaku, Abayomi; Moussa, Ahmed; Muhammd, Mustafa; Mungloo-Dilmohamud, Zahra; Nashiru, Oyekanmi; Odia, Trust; Okafor, Adaobi; Oladipo, Olaleye; Osamor, Victor; Oyelade, Jellili; Sadki, Khalid; Salifu, Samson Pandam; Soyemi, Jumoke; Panji, Sumir; Radouani, Fouzia; Souiai, Oussama; Tastan Bishop, Özlem
Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet's role has evolved in response to changing needs from the consortium and the African bioinformatics community. H3ABioNet set out to develop core bioinformatics infrastructure and capacity for genomics research in various aspects of data collection, transfer, storage, and analysis. Various resources have been developed to address genomic data management and analysis needs of H3Africa researchers and other scientific communities on the continent. NetMap was developed and used to build an accurate picture of network performance within Africa and between Africa and the rest of the world, and Globus Online has been rolled out to facilitate data transfer. A participant recruitment database was developed to monitor participant enrollment, and data is being harmonized through the use of ontologies and controlled vocabularies. The standardized metadata will be integrated to provide a search facility for H3Africa data and biospecimens. Because H3Africa projects are generating large-scale genomic data, facilities for analysis and interpretation are critical. H3ABioNet is implementing several data analysis platforms that provide a large range of bioinformatics tools or workflows, such as Galaxy, the Job Management System, and eBiokits. A set of reproducible, portable, and cloud-scalable pipelines to support the multiple H3Africa data types are also being developed and dockerized to enable execution on multiple computing infrastructures. In addition, new tools have been developed for analysis of the uniquely divergent African data and for
Gelbart, Hadas; Ben-Dor, Shifra; Yarden, Anat
Despite the central place held by bioinformatics in modern life sciences and related areas, it has only recently been integrated to a limited extent into high-school teaching and learning programs. Here we describe the assessment of a learning environment entitled ‘Bioinformatics in the Service of Biotechnology’. Students’ learning outcomes and attitudes toward the bioinformatics learning environment were measured by analyzing their answers to questions embedded within the activities, questionnaires, interviews and observations. Students’ difficulties and knowledge acquisition were characterized based on four categories: the required domain-specific knowledge (declarative, procedural, strategic or situational), the scientific field that each question stems from (biology, bioinformatics or their combination), the associated cognitive-process dimension (remember, understand, apply, analyze, evaluate, create) and the type of question (open-ended or multiple choice). Analysis of students’ cognitive outcomes revealed learning gains in bioinformatics and related scientific fields, as well as appropriation of the bioinformatics approach as part of the students’ scientific ‘toolbox’. For students, questions stemming from the ‘old world’ biology field and requiring declarative or strategic knowledge were harder to deal with. This stands in contrast to their teachers’ prediction. Analysis of students’ affective outcomes revealed positive attitudes toward bioinformatics and the learning environment, as well as their perception of the teacher’s role. Insights from this analysis yielded implications and recommendations for curriculum design, classroom enactment, teacher education and research. For example, we recommend teaching bioinformatics in an integrative and comprehensive manner, through an inquiry process, and linking it to the wider science curriculum. PMID:26801769
Full Text Available The IGF family is essential for normal embryonic and postnatal development and plays important roles in the immune system, myogenesis, bone metabolism and other physiological functions, which makes the study of its structure and biological characteristics important. Tianzhu white yak (Bos grunniens domesticated under alpine hypoxia environments, is well adapted to survive and grow against severe hypoxia and cold temperatures for extended periods. In this study, a full coding sequence of the IGF2 gene of Tianzhu white yak was amplified by reverse transcription PCR and rapid-amplification of cDNA ends (RACE for the first time. The cDNA sequence revealed an open reading frame of 450 nucleotides, encoding a protein with 179 amino acids. Its expression in different tissues was also studied by Real time PCR. Phylogenetic tree analysis indicated that yak IGF2 was similar to Bos taurus, and 3D structure showed high similarity with the human IGF2. The putative full CDS of yak IGF2 was amplified by PCR in five tissues, and cDNA sequence analysis showed high homology to bovine IGF2. Moreover the super secondary structure prediction showed a similar 3D structure with human IGF2. Its conservation in sequence and structure has facilitated research on IGF2 and its physiological function in yak.
Full Text Available Background & Objective: Single nucleotide polymorphisms are the cause of genetic variation to living organisms. Single nucleotide polymorphisms alter residues in the protein sequence. In this investigation, the relationship between prion protein gene polymorphisms and its relevance to pathogenicity was studied. Material & Method: Amino acid sequence of the main isoform from the human prion protein gene (PRNP was extracted from UniProt database and evaluated by FoldAmyloid and AmylPred servers. All non-synonymous single nucleotide polymorphisms (nsSNPs from SNP database (dbSNP were further analyzed by bioinformatics servers including SIFT, PolyPhen-2, I-Mutant-3.0, PANTHER, SNPs & GO, PHD-SNP, Meta-SNP, and MutPred to determine the most damaging nsSNPs. Results: The results of the first structure analyses by FoldAmyloid and AmylPerd servers implied that regions including 5-15, 174-178, 180-184, 211-217, and 240-252 were the most sensitive parts of the protein sequence to amyloidosis. Screening all nsSNPs of the main protein isoform using bioinformatic servers revealed that substitution of Aspartic acid with Valine at position 178 (ID code: rs11538766 was the most deleterious nsSNP in the protein structure. Conclusion: Substitution of the Aspartic acid with Valine at position 178 (D178V was the most pathogenic mutation in the human prion protein gene. Analyses from the MutPred server also showed that beta-sheets’ increment in the secondary structure was the main reason behind the molecular mechanism of the prion protein aggregation.
Johnson, Kathy A.
For the purpose of this paper, bioinformatics is defined as the application of computer technology to the management of biological information. It can be thought of as the science of developing computer databases and algorithms to facilitate and expedite biological research. This is a crosscutting capability that supports nearly all human health areas ranging from computational modeling, to pharmacodynamics research projects, to decision support systems within autonomous medical care. Bioinformatics serves to increase the efficiency and effectiveness of the life sciences research program. It provides data, information, and knowledge capture which further supports management of the bioastronautics research roadmap - identifying gaps that still remain and enabling the determination of which risks have been addressed.
Colombo Elisa A
Full Text Available Abstract Background Poikiloderma with Neutropenia (PN is a rare autosomal recessive genodermatosis caused by C16orf57 mutations. To date 17 mutations have been identified in 31 PN patients. Results We characterize six PN patients expanding the clinical phenotype of the syndrome and the mutational repertoire of the gene. We detect the two novel C16orf57 mutations, c.232C>T and c.265+2T>G, as well as the already reported c.179delC, c.531delA and c.693+1G>T mutations. cDNA analysis evidences the presence of aberrant transcripts, and bioinformatic prediction of C16orf57 protein structure gauges the mutations effects on the folded protein chain. Computational analysis of the C16orf57 protein shows two conserved H-X-S/T-X tetrapeptide motifs marking the active site of a two-fold pseudosymmetric structure recalling the 2H phosphoesterase superfamily. Based on this model C16orf57 is likely a 2H-active site enzyme functioning in RNA processing, as a presumptive RNA ligase. According to bioinformatic prediction, all known C16orf57 mutations, including the novel mutations herein described, impair the protein structure by either removing one or both tetrapeptide motifs or by destroying the symmetry of the native folding. Finally, we analyse the geographical distribution of the recurrent mutations that depicts clusters featuring a founder effect. Conclusions In cohorts of patients clinically affected by genodermatoses with overlapping symptoms, the molecular screening of C16orf57 gene seems the proper way to address the correct diagnosis of PN, enabling the syndrome-specific oncosurveillance. The bioinformatic prediction of the C16orf57 protein structure denotes a very basic enzymatic function consistent with a housekeeping function. Detection of aberrant transcripts, also in cells from PN patients carrying early truncated mutations, suggests they might be translatable. Tissue-specific sensitivity to the lack of functionally correct protein accounts for the
Wei, Dongqing; Zhao, Tangzhen; Dai, Hao
This text examines in detail mathematical and physical modeling, computational methods and systems for obtaining and analyzing biological structures, using pioneering research cases as examples. As such, it emphasizes programming and problem-solving skills. It provides information on structure bioinformatics at various levels, with individual chapters covering introductory to advanced aspects, from fundamental methods and guidelines on acquiring and analyzing genomics and proteomics sequences, the structures of protein, DNA and RNA, to the basics of physical simulations and methods for conform
Burr, Tom L [Los Alamos National Laboratory
Genetic data is often used to infer evolutionary relationships among a collection of viruses, bacteria, animal or plant species, or other operational taxonomic units (OTU). A phylogenetic tree depicts such relationships and provides a visual representation of the estimated branching order of the OTUs. Tree estimation is unique for several reasons, including: the types of data used to represent each OTU; the use ofprobabilistic nucleotide substitution models; the inference goals involving both tree topology and branch length, and the huge number of possible trees for a given sample of a very modest number of OTUs, which implies that fmding the best tree(s) to describe the genetic data for each OTU is computationally demanding. Bioinformatics is too large a field to review here. We focus on that aspect of bioinformatics that includes study of similarities in genetic data from multiple OTUs. Although research questions are diverse, a common underlying challenge is to estimate the evolutionary history of the OTUs. Therefore, this paper reviews the role of phylogenetic tree estimation in bioinformatics, available methods and software, and identifies areas for additional research and development.
Full Text Available BACKGROUND: Colorectal cancer (CRC is with approximately 1 million cases the third most common cancer worldwide. Extensive research is ongoing to decipher the underlying genetic patterns with the hope to improve early cancer diagnosis and treatment. In this direction, the recent progress in next generation sequencing technologies has revolutionized the field of cancer genomics. However, one caveat of these studies remains the large amount of genetic variations identified and their interpretation. METHODOLOGY/PRINCIPAL FINDINGS: Here we present the first work on whole exome NGS of primary colon cancers. We performed 454 whole exome pyrosequencing of tumor as well as adjacent not affected normal colonic tissue from microsatellite stable (MSS and microsatellite instable (MSI colon cancer patients and identified more than 50,000 small nucleotide variations for each tissue. According to predictions based on MSS and MSI pathomechanisms we identified eight times more somatic non-synonymous variations in MSI cancers than in MSS and we were able to reproduce the result in four additional CRCs. Our bioinformatics filtering approach narrowed down the rate of most significant mutations to 359 for MSI and 45 for MSS CRCs with predicted altered protein functions. In both CRCs, MSI and MSS, we found somatic mutations in the intracellular kinase domain of bone morphogenetic protein receptor 1A, BMPR1A, a gene where so far germline mutations are associated with juvenile polyposis syndrome, and show that the mutations functionally impair the protein function. CONCLUSIONS/SIGNIFICANCE: We conclude that with deep sequencing of tumor exomes one may be able to predict the microsatellite status of CRC and in addition identify potentially clinically relevant mutations.
Zhang, J; Feuk, L; Duggan, G E; Khaja, R; Scherer, S W
The discovery of an abundance of copy number variants (CNVs; gains and losses of DNA sequences >1 kb) and other structural variants in the human genome is influencing the way research and diagnostic analyses are being designed and interpreted. As such, comprehensive databases with the most relevant information will be critical to fully understand the results and have impact in a diverse range of disciplines ranging from molecular biology to clinical genetics. Here, we describe the development of bioinformatics resources to facilitate these studies. The Database of Genomic Variants (http://projects.tcag.ca/variation/) is a comprehensive catalogue of structural variation in the human genome. The database currently contains 1,267 regions reported to contain copy number variation or inversions in apparently healthy human cases. We describe the current contents of the database and how it can serve as a resource for interpretation of array comparative genomic hybridization (array CGH) and other DNA copy imbalance data. We also present the structure of the database, which was built using a new data modeling methodology termed Cross-Referenced Tables (XRT). This is a generic and easy-to-use platform, which is strong in handling textual data and complex relationships. Web-based presentation tools have been built allowing publication of XRT data to the web immediately along with rapid sharing of files with other databases and genome browsers. We also describe a novel tool named eFISH (electronic fluorescence in situ hybridization) (http://projects.tcag.ca/efish/), a BLAST-based program that was developed to facilitate the choice of appropriate clones for FISH and CGH experiments, as well as interpretation of results in which genomic DNA probes are used in hybridization-based experiments. Copyright (c) 2006 S. Karger AG, Basel.
Full Text Available BACKGROUND: A comprehensive network-based understanding of molecular pathways abnormally altered in glioblastoma multiforme (GBM is essential for developing effective therapeutic approaches for this deadly disease. METHODOLOGY/PRINCIPAL FINDINGS: Applying a next generation sequencing technology, massively parallel signature sequencing (MPSS, we identified a total of 4535 genes that are differentially expressed between normal brain and GBM tissue. The expression changes of three up-regulated genes, CHI3L1, CHI3L2, and FOXM1, and two down-regulated genes, neurogranin and L1CAM, were confirmed by quantitative PCR. Pathway analysis revealed that TGF- beta pathway related genes were significantly up-regulated in GBM tumor samples. An integrative pathway analysis of the TGF beta signaling network identified two alternative TGF-beta signaling pathways mediated by SOX4 (sex determining region Y-box 4 and TGFBI (Transforming growth factor beta induced. Quantitative RT-PCR and immunohistochemistry staining demonstrated that SOX4 and TGFBI expression is elevated in GBM tissues compared with normal brain tissues at both the RNA and protein levels. In vitro functional studies confirmed that TGFBI and SOX4 expression is increased by TGF-beta stimulation and decreased by a specific inhibitor of TGF-beta receptor 1 kinase. CONCLUSIONS/SIGNIFICANCE: Our MPSS database for GBM and normal brain tissues provides a useful resource for the scientific community. The identification of non-SMAD mediated TGF-beta signaling pathways acting through SOX4 and TGFBI (GENE ID:7045 in GBM indicates that these alternative pathways should be considered, in addition to the canonical SMAD mediated pathway, in the development of new therapeutic strategies targeting TGF-beta signaling in GBM. Finally, the construction of an extended TGF-beta signaling network with overlaid gene expression changes between GBM and normal brain extends our understanding of the biology of GBM.
Lin, Biaoyang; Madan, Anup; Yoon, Jae-Geun; Fang, Xuefeng; Yan, Xiaowei; Kim, Taek-Kyun; Hwang, Daehee; Hood, Leroy; Foltz, Gregory
A comprehensive network-based understanding of molecular pathways abnormally altered in glioblastoma multiforme (GBM) is essential for developing effective therapeutic approaches for this deadly disease. Applying a next generation sequencing technology, massively parallel signature sequencing (MPSS), we identified a total of 4535 genes that are differentially expressed between normal brain and GBM tissue. The expression changes of three up-regulated genes, CHI3L1, CHI3L2, and FOXM1, and two down-regulated genes, neurogranin and L1CAM, were confirmed by quantitative PCR. Pathway analysis revealed that TGF- beta pathway related genes were significantly up-regulated in GBM tumor samples. An integrative pathway analysis of the TGF beta signaling network identified two alternative TGF-beta signaling pathways mediated by SOX4 (sex determining region Y-box 4) and TGFBI (Transforming growth factor beta induced). Quantitative RT-PCR and immunohistochemistry staining demonstrated that SOX4 and TGFBI expression is elevated in GBM tissues compared with normal brain tissues at both the RNA and protein levels. In vitro functional studies confirmed that TGFBI and SOX4 expression is increased by TGF-beta stimulation and decreased by a specific inhibitor of TGF-beta receptor 1 kinase. Our MPSS database for GBM and normal brain tissues provides a useful resource for the scientific community. The identification of non-SMAD mediated TGF-beta signaling pathways acting through SOX4 and TGFBI (GENE ID:7045) in GBM indicates that these alternative pathways should be considered, in addition to the canonical SMAD mediated pathway, in the development of new therapeutic strategies targeting TGF-beta signaling in GBM. Finally, the construction of an extended TGF-beta signaling network with overlaid gene expression changes between GBM and normal brain extends our understanding of the biology of GBM.
Kim, Y Y; Hwang, J; Kim, H-S; Kwon, H J; Kim, S; Lee, J H; Lee, J H
Mesiodens is the most common type of supernumerary tooth which includes a population prevalence of 0.15%-1.9%. Alongside evidence that the condition is heritable, mutations in single genes have been reported in few human supernumerary tooth cases. Gene sequencing methods in tradition way are time-consuming and labor-intensive, whereas next-generation sequencing and bioinformatics are cost-effective for large samples and target sizes. We describe the application of a targeted next-generation sequencing (NGS) and bioinformatics approach to samples from 17 mesiodens patients. Subjects were diagnosed on the basis of panoramic radiograph. A total of 101 candidate genes which were captured custom genes were sequenced on the Illumina HiSeq 2500. Multistep bioinformatics processing was performed including variant identification, base calling, and in silico analysis of putative disease-causing variants. Targeted capture identified 88 non-synonymous, rare, exonic variants involving 42 of the 101 candidate genes. Moreover, we investigated gene co-occurrence relationships between the genomic alterations and identified 88 significant relationships among 18 most recurrent driver alterations. Our search for co-occurring genetic alterations revealed that such alterations interact cooperatively to drive mesiodens. We discovered a gene co-occurrence network in mesiodens patients with functionally enriched gene groups in the sonic hedgehog (SHH), bone morphogenetic proteins (BMP), and wingless integrated (WNT) signaling pathways. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd. All rights reserved.
Ren, Juanjuan; Zhao, Guoqing; Sun, Xiujia; Liu, Hongmei; Jiang, Ping; Chen, Jun; Wu, Zhiguo; Peng, Daihui; Fang, Yiru; Zhang, Chen
It is important to differentiate between bipolar disorder (BD) and major depressive disorder (MDD) in the first depressive episode because of the potential treatment implications. Previous studies have mainly focused on the different clinical features or pathological biomarkers to distinguish these two diseases; however, a better understanding of the proteomics profiling of BD may help aid future therapeutic strategies. Here, we applied isobaric tags for relative and absolute quantification (iTRAQ) technology combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify differentially expressed proteins between MDD and bipolar depression (BP). In total, 30 MDD, 30 BP and 30 healthy subjects were included. Proteins from depleted plasma samples were digested into peptides, individually labeled with iTRAQ reagents, combined and subjected to LC-MS/MS and further bioinformatics analyses. Our results showed that 9 proteins were significantly altered between MDD and BP. Briefly, B2RAN2, B4E1B2, APOA1, ENG, SBSN and QSOX2 were up-regulated, whereas ORM1, MRC2 and SLPI were down-regulated. Most identified proteins were related to the immune system. The bioinformatics analysis showed that B2RAN2 (highly similar to vanin-1) was involved in the significantly enriched KEGG pathways "pantothenate and CoA biosynthesis" (P=0.009). B2RAN2 and ENG may play important roles in depression. They may serve as candidate biomarkers for distinguishing MDD and BP. Further validation and investigation are required to illuminate the roles of B2RAN2 and ENG in MDD and BP. The current study provided a potential and novel biomarker panel that may, in turn, aid the diagnosis of BD. Copyright © 2017 Elsevier Ltd. All rights reserved.
Wei, Yahong; Fu, Jing; Wu, Jianying; Jia, Xinmiao; Zhou, Yunheng; Li, Cuidan; Dong, Mengxing; Wang, Shanshan; Zhang, Ju; Chen, Fei
Polyvinyl alcohol (PVA) is used widely in industry, and associated environmental pollution is a serious problem. Herein, we report a novel, efficient PVA degrader, Stenotrophomonas rhizophila QL-P4, isolated from fallen leaves from a virgin forest in the Qinling Mountains. The complete genome was obtained using single-molecule real-time (SMRT) technology and corrected using Illumina sequencing. Bioinformatics analysis revealed eight PVA/vinyl alcohol oligomer (OVA)-degrading genes. Of these, seven genes were predicted to be involved in the classic intracellular PVA/OVA degradation pathway, and one (BAY15_3292) was identified as a novel PVA oxidase. Five PVA/OVA-degrading enzymes were purified and characterized. One of these, BAY15_1712, a PVA dehydrogenase (PVADH), displayed high catalytic efficiency toward PVA and OVA substrate. All reported PVADHs only have PVA-degrading ability. Most importantly, we discovered a novel PVA oxidase (BAY15_3292) that exhibited higher PVA-degrading efficiency than the reported PVADHs. Further investigation indicated that BAY15_3292 plays a crucial role in PVA degradation in S. rhizophila QL-P4. Knocking out BAY15_3292 resulted in a significant decline in PVA-degrading activity in S. rhizophila QL-P4. Interestingly, we found that BAY15_3292 possesses exocrine activity, which distinguishes it from classic PVADHs. Transparent circle experiments further proved that BAY15_3292 greatly affects extracellular PVA degradation in S. rhizophila QL-P4. The exocrine characteristics of BAY15_3292 facilitate its potential application to PVA bioremediation. In addition, we report three new efficient secondary alcohol dehydrogenases (SADHs) with OVA-degrading ability in S. rhizophila QL-P4; in contrast, only one OVA-degrading SADH was reported previously. IMPORTANCE With the widespread application of PVA in industry, PVA-related environmental pollution is an increasingly serious issue. Because PVA is difficult to degrade, it accumulates in aquatic
Yu, Guangchuang; Wang, Li-Gen; Meng, Xiao-Hua; He, Qing-Yu
Recent advances in high-throughput technologies dramatically increase biological data generation. However, many research groups lack computing facilities and specialists. This is an obstacle that remains to be addressed. Here, we present a Linux distribution, LXtoo, to provide a flexible computing platform for bioinformatics analysis. Unlike most of the existing live Linux distributions for bioinformatics limiting their usage to sequence analysis and protein structure prediction, LXtoo incorporates a comprehensive collection of bioinformatics software, including data mining tools for microarray and proteomics, protein-protein interaction analysis, and computationally complex tasks like molecular dynamics. Moreover, most of the programs have been configured and optimized for high performance computing. LXtoo aims to provide well-supported computing environment tailored for bioinformatics research, reducing duplication of efforts in building computing infrastructure. LXtoo is distributed as a Live DVD and freely available at http://bioinformatics.jnu.edu.cn/LXtoo.
Revisiting Francisella tularensis subsp. holarctica, Causative Agent of Tularemia in Germany With Bioinformatics: New Insights in Genome Structure, DNA Methylation and Comparative Phylogenetic Analysis
Full Text Available Francisella (F. tularensis is a highly virulent, Gram-negative bacterial pathogen and the causative agent of the zoonotic disease tularemia. Here, we generated, analyzed and characterized a high quality circular genome sequence of the F. tularensis subsp. holarctica strain 12T0050 that caused fatal tularemia in a hare. Besides the genomic structure, we focused on the analysis of oriC, unique to the Francisella genus and regulating replication in and outside hosts and the first report on genomic DNA methylation of a Francisella strain. The high quality genome was used to establish and evaluate a diagnostic whole genome sequencing pipeline. A genotyping strategy for F. tularensis was developed using various bioinformatics tools for genotyping. Additionally, whole genome sequences of F. tularensis subsp. holarctica isolates isolated in the years 2008–2015 in Germany were generated. A phylogenetic analysis allowed to determine the genetic relatedness of these isolates and confirmed the highly conserved nature of F. tularensis subsp. holarctica.
d'Acierno, Antonio; Facchiano, Angelo; Marabotti, Anna
We describe the GALT-Prot database and its related web-based application that have been developed to collect information about the structural and functional effects of mutations on the human enzyme galactose-1-phosphate uridyltransferase (GALT) involved in the genetic disease named galactosemia type I. Besides a list of missense mutations at gene and protein sequence levels, GALT-Prot reports the analysis results of mutant GALT structures. In addition to the structural information about the wild-type enzyme, the database also includes structures of over 100 single point mutants simulated by means of a computational procedure, and the analysis to each mutant was made with several bioinformatics programs in order to investigate the effect of the mutations. The web-based interface allows querying of the database, and several links are also provided in order to guarantee a high integration with other resources already present on the web. Moreover, the architecture of the database and the web application is flexible and can be easily adapted to store data related to other proteins with point mutations. GALT-Prot is freely available at http://bioinformatica.isa.cnr.it/GALT/.
Chavez, Juan D; Schweppe, Devin K; Eng, Jimmy K; Zheng, Chunxiang; Taipale, Alex; Zhang, Yiyi; Takara, Kohji; Bruce, James E
Chemoresistance is a common mode of therapy failure for many cancers. Tumours develop resistance to chemotherapeutics through a variety of mechanisms, with proteins serving pivotal roles. Changes in protein conformations and interactions affect the cellular response to environmental conditions contributing to the development of new phenotypes. The ability to understand how protein interaction networks adapt to yield new function or alter phenotype is limited by the inability to determine structural and protein interaction changes on a proteomic scale. Here, chemical crosslinking and mass spectrometry were employed to quantify changes in protein structures and interactions in multidrug-resistant human carcinoma cells. Quantitative analysis of the largest crosslinking-derived, protein interaction network comprising 1,391 crosslinked peptides allows for 'edgotype' analysis in a cell model of chemoresistance. We detect consistent changes to protein interactions and structures, including those involving cytokeratins, topoisomerase-2-alpha, and post-translationally modified histones, which correlate with a chemoresistant phenotype.
Emergent Computation is concerned with recent applications of Mathematical Linguistics or Automata Theory. This subject has a primary focus upon "Bioinformatics" (the Genome and arising interest in the Proteome), but the closing chapter also examines applications in Biology, Medicine, Anthropology, etc. The book is composed of an organized examination of DNA, RNA, and the assembly of amino acids into proteins. Rather than examine these areas from a purely mathematical viewpoint (that excludes much of the biochemical reality), the author uses scientific papers written mostly by biochemists based upon their laboratory observations. Thus while DNA may exist in its double stranded form, triple stranded forms are not excluded. Similarly, while bases exist in Watson-Crick complements, mismatched bases and abasic pairs are not excluded, nor are Hoogsteen bonds. Just as there are four bases naturally found in DNA, the existence of additional bases is not ignored, nor amino acids in addition to the usual complement of...
Cantacessi, C; Campbell, B E; Jex, A R; Young, N D; Hall, R S; Ranganathan, S; Gasser, R B
The advent and integration of high-throughput '-omics' technologies (e.g. genomics, transcriptomics, proteomics, metabolomics, glycomics and lipidomics) are revolutionizing the way biology is done, allowing the systems biology of organisms to be explored. These technologies are now providing unique opportunities for global, molecular investigations of parasites. For example, studies of a transcriptome (all transcripts in an organism, tissue or cell) have become instrumental in providing insights into aspects of gene expression, regulation and function in a parasite, which is a major step to understanding its biology. The purpose of this article was to review recent applications of next-generation sequencing technologies and bioinformatic tools to large-scale investigations of the transcriptomes of parasitic nematodes of socio-economic significance (particularly key species of the order Strongylida) and to indicate the prospects and implications of these explorations for developing novel methods of parasite intervention. © 2011 Blackwell Publishing Ltd.
Tolvanen, Martti; Vihinen, Mauno
Distance learning as a computer-aided concept allows students to take courses from anywhere at any time. In bioinformatics, computers are needed to collect, store, process, and analyze massive amounts of biological and biomedical data. We have applied the concept of distance learning in virtual bioinformatics to provide university course material…
Kortsarts, Yana; Morris, Robert W.; Utell, Janine M.
Bioinformatics is a relatively new interdisciplinary field that integrates computer science, mathematics, biology, and information technology to manage, analyze, and understand biological, biochemical and biophysical information. We present our experience in teaching an interdisciplinary course, Introduction to Bioinformatics, which was developed…
Domínguez, César; Heras, Jónathan; Mata, Eloy; Pascual, Vico; Vázquez-Garcidueñas, Maria Soledad; Vázquez-Marrufo, Gerardo
The manual transformation of DNA fingerprints of dominant markers into the input of tools for population genetics analysis is a time-consuming and error-prone task; especially when the researcher deals with a large number of samples. In addition, when the researcher needs to use several tools for population genetics analysis, the situation worsens due to the incompatibility of data-formats across tools. The goal of this work consists in automating, from banding patterns of gel images, the input-generation for the great diversity of tools devoted to population genetics analysis. After a thorough analysis of tools for population genetics analysis with dominant markers, and tools for working with phylogenetic trees; we have detected the input requirements of those systems. In the case of programs devoted to phylogenetic trees, the Newick and Nexus formats are widely employed; whereas, each population genetics analysis tool uses its own specific format. In order to handle such a diversity of formats in the latter case, we have developed a new XML format, called PopXML, that takes into account the variety of information required by each population genetics analysis tool. Moreover, the acquired knowledge has been incorporated into the pipeline of the GelJ system - a tool for analysing DNA fingerprint gel images - to reach our automatisation goal. We have implemented, in the GelJ system, a pipeline that automatically generates, from gel banding patterns, the input of tools for population genetics analysis and phylogenetic trees. Such a pipeline has been employed to successfully generate, from thousands of banding patterns, the input of 29 population genetics analysis tools and 32 tools for managing phylogenetic trees. GelJ has become the first tool that fills the gap between gel image processing software and population genetics analysis with dominant markers, phylogenetic reconstruction, and tree editing software. This has been achieved by automating the process of
Jin, Yuan; Goodman, Richard E; Tetteh, Afua O; Lu, Mei; Tripathi, Leena
Banana Xanthomonas wilt (BXW) disease threatens banana production and food security throughout East Africa. Natural resistance is lacking among common cultivars. Genetically modified (GM) bananas resistant to BXW disease were developed by inserting the hypersensitive response-assisting protein (Hrap) or/and the plant ferredoxin-like protein (Pflp) gene(s) from sweet pepper (Capsicum annuum). Several of these GM banana events showed 100% resistance to BXW disease under field conditions in Uganda. The current study evaluated the potential allergenicity and toxicity of the expressed proteins HRAP and PFLP based on evaluation of published information on the history of safe use of the natural source of the proteins as well as established bioinformatics sequence comparison methods to known allergens (www.AllergenOnline.org and NCBI Protein) and toxins (NCBI Protein). The results did not identify potential risks of allergy and toxicity to either HRAP or PFLP proteins expressed in the GM bananas that might suggest potential health risks to humans. We recognize that additional tests including stability of these proteins in pepsin assay, nutrient analysis and possibly an acute rodent toxicity assay may be required by national regulatory authorities. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Bryzgunova, O. E.; Lekchnov, E. A.; Zaripov, M. M.; Yurchenko, Yu. B.; Yarmoschuk, S. V.; Pashkovskaya, O. A.; Rykova, E. Yu.; Zheravin, A. A.; Laktionov, P. P.
Presence of tumor-derived cell-free miRNA in biological fluids as well as simplicity and robustness of cell-free miRNA quantification makes them suitable markers for cancer diagnostics. Based on previously published data demonstrating diagnostic potentialities of miR-205 in blood and miR-19b as well as miR-125b in urine of prostate cancer patients, bioinformatics analysis was carried out to follow their involvement in prostate cancer development and select additional miRNA-markers for prostate cancer diagnostics. Studied miRNAs are involved in different signaling pathways and regulate a number of genes involved in cancer development. Five of their targets (CCND1, BRAF, CCNE1, CCNE2, RAF1), according to the STRING database, act as part of the same signaling pathway. RAF1 is regulated by miR-19b and miR-125b, and it was shown to be involved in prostate cancer development by DIANA and STRING databases. Thus, other microRNAs regulating RAF1 expression such as miR-16, -195, -497, and -7 (suggested by DIANA, TargetScan, MiRTarBase and miRDB databases) can potentially be regarded as prostate cancer markers.
The suppression subtractive hybridization (SSH) approach, a PCR based approach which amplifies differentially expressed cDNAs (complementary DNAs), while simultaneously suppressing amplification of common cDNAs, was employed to identify immuneinducible genes in insects. This technique has been used as a suitable tool for experimental identification of novel genes in eukaryotes as well as prokaryotes; whose genomes have been sequenced, or the species whose genomes have yet to be sequenced. In this article, I have proposed a method for in silico functional characterization of immune-inducible genes from insects. Apart from immune-inducible genes from insects, this method can be applied for the analysis of genes from other species, starting from bacteria to plants and animals. This article is provided with a background of SSH-based method taking specific examples from innate immune-inducible genes in insects, and subsequently a bioinformatics pipeline is proposed for functional characterization of newly sequenced genes. The proposed workflow presented here, can also be applied for any newly sequenced species generated from Next Generation Sequencing (NGS) platforms.
Mefford, Megan E; Kunstman, Kevin; Wolinsky, Steven M; Gabuzda, Dana
Macrophages express low levels of the CD4 receptor compared to T-cells. Macrophage-tropic HIV strains replicating in brain of untreated patients with HIV-associated dementia (HAD) express Envs that are adapted to overcome this restriction through mechanisms that are poorly understood. Here, bioinformatic analysis of env sequence datasets together with functional studies identified polymorphisms in the β3 strand of the HIV gp120 bridging sheet that increase M-tropism. D197, which results in loss of an N-glycan located near the HIV Env trimer apex, was detected in brain in some HAD patients, while position 200 was estimated to be under positive selection. D197 and T/V200 increased fusion and infection of cells expressing low CD4 by enhancing gp120 binding to CCR5. These results identify polymorphisms in the HIV gp120 bridging sheet that overcome the restriction to macrophage infection imposed by low CD4 through enhanced gp120-CCR5 interactions, thereby promoting infection of brain and other macrophage-rich tissues. Copyright © 2015 Elsevier Inc. All rights reserved.
Skarzyńska, Agnieszka; Pawełkowicz, Magdalena; PlÄ der, Wojciech; Przybecki, Zbigniew
Real-time quantitative polymerase chain reaction is consider as the most reliable method for gene expression studies. However, the expression of target gene could be misinterpreted due to improper normalization. Therefore, the crucial step for analysing of qPCR data is selection of suitable reference genes, which should be validated experimentally. In order to choice the gene with stable expression in the designed experiment, we performed reference gene expression analysis. In this study genes described in the literature and novel genes predicted as control genes, based on the in silico analysis of transcriptome data were used. Analysis with geNorm and NormFinder algorithms allow to create the ranking of candidate genes and indicate the best reference for flower morphogenesis study. According to the results, genes CACS and CYCL were characterised the most stable expression, but the least suitable genes were TUA and EF.
Brown, William M
Epigenetics is the study of processes--beyond DNA sequence alteration--producing heritable characteristics. For example, DNA methylation modifies gene expression without altering the nucleotide sequence. A well-studied DNA methylation-based phenomenon is genomic imprinting (ie, genotype-independent parent-of-origin effects). We aimed to elucidate: (1) the effect of exercise on DNA methylation and (2) the role of imprinted genes in skeletal muscle gene networks (ie, gene group functional profiling analyses). Gene ontology (ie, gene product elucidation)/meta-analysis. 26 skeletal muscle and 86 imprinted genes were subjected to g:Profiler ontology analysis. Meta-analysis assessed exercise-associated DNA methylation change. g:Profiler found four muscle gene networks with imprinted loci. Meta-analysis identified 16 articles (387 genes/1580 individuals) associated with exercise. Age, method, sample size, sex and tissue variation could elevate effect size bias. Only skeletal muscle gene networks including imprinted genes were reported. Exercise-associated effect sizes were calculated by gene. Age, method, sample size, sex and tissue variation were moderators. Six imprinted loci (RB1, MEG3, UBE3A, PLAGL1, SGCE, INS) were important for muscle gene networks, while meta-analysis uncovered five exercise-associated imprinted loci (KCNQ1, MEG3, GRB10, L3MBTL1, PLAGL1). DNA methylation decreased with exercise (60% of loci). Exercise-associated DNA methylation change was stronger among older people (ie, age accounted for 30% of the variation). Among older people, genes exhibiting DNA methylation decreases were part of a microRNA-regulated gene network functioning to suppress cancer. Imprinted genes were identified in skeletal muscle gene networks and exercise-associated DNA methylation change. Exercise-associated DNA methylation modification could rewind the 'epigenetic clock' as we age. CRD42014009800. Published by the BMJ Publishing Group Limited. For permission to use (where
Ueno, Saneyoshi; Le Provost, Grégoire; Léger, Valérie; Klopp, Christophe; Noirot, Céline; Frigerio, Jean-Marc; Salin, Franck; Salse, Jérôme; Abrouk, Michael; Murat, Florent; Brendel, Oliver; Derory, Jérémy; Abadie, Pierre; Léger, Patrick; Cabane, Cyril; Barré, Aurélien; de Daruvar, Antoine; Couloux, Arnaud; Wincker, Patrick; Reviron, Marie-Pierre; Kremer, Antoine; Plomion, Christophe
The Fagaceae family comprises about 1,000 woody species worldwide. About half belong to the Quercus family. These oaks are often a source of raw material for biomass wood and fiber. Pedunculate and sessile oaks, are among the most important deciduous forest tree species in Europe. Despite their ecological and economical importance, very few genomic resources have yet been generated for these species. Here, we describe the development of an EST catalogue that will support ecosystem genomics studies, where geneticists, ecophysiologists, molecular biologists and ecologists join their efforts for understanding, monitoring and predicting functional genetic diversity. We generated 145,827 sequence reads from 20 cDNA libraries using the Sanger method. Unexploitable chromatograms and quality checking lead us to eliminate 19,941 sequences. Finally a total of 125,925 ESTs were retained from 111,361 cDNA clones. Pyrosequencing was also conducted for 14 libraries, generating 1,948,579 reads, from which 370,566 sequences (19.0%) were eliminated, resulting in 1,578,192 sequences. Following clustering and assembly using TGICL pipeline, 1,704,117 EST sequences collapsed into 69,154 tentative contigs and 153,517 singletons, providing 222,671 non-redundant sequences (including alternative transcripts). We also assembled the sequences using MIRA and PartiGene software and compared the three unigene sets. Gene ontology annotation was then assigned to 29,303 unigene elements. Blast search against the SWISS-PROT database revealed putative homologs for 32,810 (14.7%) unigene elements, but more extensive search with Pfam, Refseq_protein, Refseq_RNA and eight gene indices revealed homology for 67.4% of them. The EST catalogue was examined for putative homologs of candidate genes involved in bud phenology, cuticle formation, phenylpropanoids biosynthesis and cell wall formation. Our results suggest a good coverage of genes involved in these traits. Comparative orthologous sequences (COS
Full Text Available Abstract Background The Fagaceae family comprises about 1,000 woody species worldwide. About half belong to the Quercus family. These oaks are often a source of raw material for biomass wood and fiber. Pedunculate and sessile oaks, are among the most important deciduous forest tree species in Europe. Despite their ecological and economical importance, very few genomic resources have yet been generated for these species. Here, we describe the development of an EST catalogue that will support ecosystem genomics studies, where geneticists, ecophysiologists, molecular biologists and ecologists join their efforts for understanding, monitoring and predicting functional genetic diversity. Results We generated 145,827 sequence reads from 20 cDNA libraries using the Sanger method. Unexploitable chromatograms and quality checking lead us to eliminate 19,941 sequences. Finally a total of 125,925 ESTs were retained from 111,361 cDNA clones. Pyrosequencing was also conducted for 14 libraries, generating 1,948,579 reads, from which 370,566 sequences (19.0% were eliminated, resulting in 1,578,192 sequences. Following clustering and assembly using TGICL pipeline, 1,704,117 EST sequences collapsed into 69,154 tentative contigs and 153,517 singletons, providing 222,671 non-redundant sequences (including alternative transcripts. We also assembled the sequences using MIRA and PartiGene software and compared the three unigene sets. Gene ontology annotation was then assigned to 29,303 unigene elements. Blast search against the SWISS-PROT database revealed putative homologs for 32,810 (14.7% unigene elements, but more extensive search with Pfam, Refseq_protein, Refseq_RNA and eight gene indices revealed homology for 67.4% of them. The EST catalogue was examined for putative homologs of candidate genes involved in bud phenology, cuticle formation, phenylpropanoids biosynthesis and cell wall formation. Our results suggest a good coverage of genes involved in these
Hu, Hejing; Zhang, Yannan; Shi, Yanfeng; Feng, Lin; Duan, Junchao; Sun, Zhiwei
With rapid development of nanotechnology and growing environmental pollution, the combined toxic effects of SiNPs and pollutants of heavy metals like lead have received global attentions. The aim of this study was to explore the cardiovascular effects of the co-exposure of SiNPs and lead acetate (PbAc) in zebrafish using microarray and bioinformatics analysis. Although there was no other obvious cardiovascular malformation except bleeding phenotype, bradycardia, angiogenesis inhibition and declined cardiac output in zebrafish co-exposed of SiNPs and PbAc at NOAEL level, significant changes were observed in mRNA and microRNA (miRNA) expression patterns. STC-GO analysis indicated that the co-exposure might have more toxic effects on cardiovascular system than that exposure alone. Key differentially expressed genes were discerned out based on the Dynamic-gene-network, including stxbp1a, ndfip2, celf4 and gsk3b. Furthermore, several miRNAs obtained from the miRNA-Gene-Network might play crucial roles in cardiovascular disease, such as dre-miR-93, dre-miR-34a, dre-miR-181c, dre-miR-7145, dre-miR-730, dre-miR-129-5p, dre-miR-19d, dre-miR-218b, dre-miR-221. Besides, the analysis of miRNA-pathway-network indicated that the zebrafish were stimulated by the co-exposure of SiNPs and PbAc, which might cause the disturbance of calcium homeostasis and endoplasmic reticulum stress. As a result, cardiac muscle contraction might be deteriorated. In general, our data provide abundant fundamental research clues to the combined toxicity of environmental pollutants and further in-depth verifications are needed. Copyright © 2017 Elsevier Ltd. All rights reserved.
Rath, Ethan C; Pitman, Stephanie; Cho, Kyu Hong; Bai, Yongsheng
Small noncoding regulatory RNAs (sRNAs) are post-transcriptional regulators, regulating mRNAs, proteins, and DNA in bacteria. One class of sRNAs, trans-acting sRNAs, are the most abundant sRNAs transcribed from the intergenic regions (IGRs) of the bacterial genome. In Streptococcus pyogenes, a common and potentially deadly pathogen, many sRNAs have been identified, but only a few have been studied. The goal of this study is to identify trans-acting sRNAs that can be substrates of RNase III. The endoribonuclease RNase III cleaves double stranded RNAs, which can be formed during the interaction between an sRNA and target mRNAs. For this study, we created an RNase III null mutant of Streptococcus pyogenes and its RNA sequencing (RNA-Seq) data were analyzed and compared to that of the wild-type. First, we developed a custom script that can detect intergenic regions of the S. pyogenes genome. A differential expression analysis with Cufflinks and Stringtie was then performed to identify the intergenic regions whose expression was influenced by the RNase III gene deletion. This analysis yielded 12 differentially expressed regions with >|2| fold change and p ≤ 0.05. Using Artemis and Bamview genome viewers, these regions were visually verified leaving 6 putative sRNAs. This study not only expanded our knowledge on novel sRNAs but would also give us new insight into sRNA degradation.
Field, Helen I; Fenyö, David; Beavis, Ronald C
RADARS, a rapid, automated, data archiving and retrieval software system for high-throughput proteomic mass spectral data processing and storage, is described. The majority of mass spectrometer data files are compatible with RADARS, for consistent processing. The system automatically takes unprocessed data files, identifies proteins via in silico database searching, then stores the processed data and search results in a relational database suitable for customized reporting. The system is robust, used in 24/7 operation, accessible to multiple users of an intranet through a web browser, may be monitored by Virtual Private Network, and is secure. RADARS is scalable for use on one or many computers, and is suited to multiple processor systems. It can incorporate any local database in FASTA format, and can search protein and DNA databases online. A key feature is a suite of visualisation tools (many available gratis), allowing facile manipulation of spectra, by hand annotation, reanalysis, and access to all procedures. We also described the use of Sonar MS/MS, a novel, rapid search engine requiring 40 MB RAM per process for searches against a genomic or EST database translated in all six reading frames. RADARS reduces the cost of analysis by its efficient algorithms: Sonar MS/MS can identifiy proteins without accurate knowledge of the parent ion mass and without protein tags. Statistical scoring methods provide close-to-expert accuracy and brings robust data analysis to the non-expert user.
Full Text Available Abstract Background The inhalation of allergens by allergic asthmatics results in the early asthmatic response (EAR, which is characterized by acute airway obstruction beginning within a few minutes. The EAR is the earliest indicator of the pathological progression of allergic asthma. Because the molecular mechanism underlying the EAR is not fully defined, this study will contribute to a better understanding of asthma. Methods In order to gain insight into the molecular basis of the EAR, we examined changes in protein expression patterns in the lung tissue of asthmatic rats during the EAR using 2-DE/MS-based proteomic techniques. Bioinformatic analysis of the proteomic data was then performed using PPI Spider and KEGG Spider to investigate the underlying molecular mechanism. Results In total, 44 differentially expressed protein spots were detected in the 2-DE gels. Of these 44 protein spots, 42 corresponded to 36 unique proteins successfully identified using mass spectrometry. During subsequent bioinformatic analysis, the gene ontology classification, the protein-protein interaction networking and the biological pathway exploration demonstrated that the identified proteins were mainly involved in glycolysis, calcium binding and mitochondrial activity. Using western blot and semi-quantitative RT-PCR, we confirmed the changes in expression of five selected proteins, which further supports our proteomic and bioinformatic analyses. Conclusions Our results reveal that the allergen-induced EAR in asthmatic rats is associated with glycolysis, calcium binding and mitochondrial activity, which could establish a functional network in which calcium binding may play a central role in promoting the progression of asthma.
Tatjana P Kristensen
Full Text Available The hexameric MCM complex is the catalytic core of the replicative helicase in eukaryotic and archaeal cells. Here we describe the first in vivo analysis of archaeal MCM protein structure and function relationships using the genetically tractable haloarchaeon Haloferax volcanii as a model system. Hfx. volcanii encodes a single MCM protein that is part of the previously identified core group of haloarchaeal MCM proteins. Three structural features of the N-terminal domain of the Hfx. volcanii MCM protein were targeted for mutagenesis: the β7-β8 and β9-β10 β-hairpin loops and putative zinc binding domain. Five strains carrying single point mutations in the β7-β8 β-hairpin loop were constructed, none of which displayed impaired cell growth under normal conditions or when treated with the DNA damaging agent mitomycin C. However, short sequence deletions within the β7-β8 β-hairpin were not tolerated and neither was replacement of the highly conserved residue glutamate 187 with alanine. Six strains carrying paired alanine substitutions within the β9-β10 β-hairpin loop were constructed, leading to the conclusion that no individual amino acid within that hairpin loop is absolutely required for MCM function, although one of the mutant strains displays greatly enhanced sensitivity to mitomycin C. Deletions of two or four amino acids from the β9-β10 β-hairpin were tolerated but mutants carrying larger deletions were inviable. Similarly, it was not possible to construct mutants in which any of the conserved zinc binding cysteines was replaced with alanine, underlining the likely importance of zinc binding for MCM function. The results of these studies demonstrate the feasibility of using Hfx. volcanii as a model system for reverse genetic analysis of archaeal MCM protein function and provide important confirmation of the in vivo importance of conserved structural features identified by previous bioinformatic, biochemical and structural
Full Text Available MicroRNAs (miRNAs are key post-transcriptional regulators that affect protein translation by targeting mRNAs. Their role in disease etiology and toxicity are well recognized. Given the rapid advancement of next-generation sequencing techniques, miRNA profiling has been increasingly conducted with RNA-seq, namely miRNA-seq. Analysis of miRNA-seq data requires several steps: (1 mapping the reads to miRBase, (2 considering mismatches during the hairpin alignment (windowing, and (3 counting the reads (quantification. The choice made in each step with respect to the parameter settings could affect miRNA quantification, differentially expressed miRNAs (DEMs detection and novel miRNA identification. Furthermore, these parameters do not act in isolation and their joint effects impact miRNA-seq results and interpretation. In toxicogenomics, the variation associated with parameter setting should not overpower the treatment effect (such as the dose/time-dependent effect. In this study, four commonly used miRNA-seq analysis tools (i.e., miRDeep2, miRExpress, miRNAkey, sRNAbench were comparatively evaluated with a standard toxicogenomics study design. We tested 30 different parameter settings on miRNA-seq data generated from thioacetamide-treated rat liver samples for three dose levels across four time points, followed by four normalization options. Because both miRExpress and miRNAkey yielded larger variation than that of the treatment effects across multiple parameter settings, our analyses mainly focused on the side-by-side comparison between miRDeep2 and sRNAbench. While the number of miRNAs detected by miRDeep2 was almost the subset of those detected by sRNAbench, the number of DEMs identified by both tools was comparable under the same parameter settings and normalization method. Change in the number of nucleotides out of the mature sequence in the hairpin alignment (window option yielded the largest variation for miRNA quantification and DEMs
Puig-Butille, Joan Anton; Gimenez-Xavier, Pol; Visconti, Alessia; Nsengimana, Jérémie; Garcia-García, Francisco; Tell-Marti, Gemma; Escamez, Maria José; Newton-Bishop, Julia; Bataille, Veronique; Del Río, Marcela; Dopazo, Joaquín; Falchi, Mario; Puig, Susana
The MC1R gene plays a crucial role in pigmentation synthesis. Loss-of-function MC1R variants, which impair protein function, are associated with red hair color (RHC) phenotype and increased skin cancer risk. Cultured cutaneous cells bearing loss-of-function MC1R variants show a distinct gene expression profile compared to wild-type MC1R cultured cutaneous cells. We analysed the gene signature associated with RHC co-cultured melanocytes and keratinocytes by Protein-Protein interaction (PPI) network analysis to identify genes related with non-functional MC1R variants. From two detected networks, we selected 23 nodes as hub genes based on topological parameters. Differential expression of hub genes was then evaluated in healthy skin biopsies from RHC and black hair color (BHC) individuals. We also compared gene expression in melanoma tumors from individuals with RHC versus BHC. Gene expression in normal skin from RHC cutaneous cells showed dysregulation in 8 out of 23 hub genes (CLN3, ATG10, WIPI2, SNX2, GABARAPL2, YWHA, PCNA and GBAS). Hub genes did not differ between melanoma tumors in RHC versus BHC individuals. The study suggests that healthy skin cells from RHC individuals present a constitutive genomic deregulation associated with the red hair phenotype and identify novel genes involved in melanocyte biology.
Full Text Available The glycosylphosphatidylinositol (GPI moiety is one of the ways by which many cell surface proteins, such as Gal/GalNAc lectin and proteophosphoglycans (PPGs attach to the surface of Entamoeba histolytica, the agent of human amoebiasis. It is believed that these GPI-anchored molecules are involved in parasite adhesion to cells, mucus and the extracellular matrix. We identified an E. histolytica homolog of PIG-M, which is a mannosyltransferase required for synthesis of GPI. The sequence and structural analysis led to the conclusion that EhPIG-M1 is composed of one signal peptide and 11 transmembrane domains with two large intra luminal loops, one of which contains the DXD motif, involved in the enzymatic catalysis and conserved in most glycosyltransferases. Expressing a fragment of the EhPIG-M1 encoding gene in antisense orientation generated parasite lines diminished in EhPIG-M1 levels; these lines displayed reduced GPI production, were highly sensitive to complement and were dramatically inhibited for amoebic abscess formation. The data suggest a role for GPI surface anchored molecules in the survival of E. histolytica during pathogenesis.
Full Text Available Stargardt disease (STGD is the most common hereditary macular degeneration in juveniles, with loss of central vision occurring in the first or second decade of life. The aim of this study is to identify the genetic defects in 33 probands with Stargardt disease. Clinical data and genomic DNA were collected from 33 probands from unrelated families with STGD. Variants in coding genes were initially screened by whole exome sequencing. Candidate variants were selected from all known genes associated with hereditary retinal dystrophy and then confirmed by Sanger sequencing. Putative pathogenic variants were further validated in available family members and controls. Potential pathogenic mutations were identified in 19 of the 33 probands (57.6%. These mutations were all present in ABCA4, but not in the other four STGD-associated genes or in genes responsible for other retinal dystrophies. Of the 19 probands, ABCA4 mutations were homozygous in one proband and compound heterozygous in 18 probands, involving 28 variants (13 novel and 15 known. Analysis of normal controls and available family members in 12 of the 19 families further support the pathogenicity of these variants. Clinical manifestation of all probands met the diagnostic criteria of STGD. This study provides an overview of a genetic basis for STGD in Chinese patients. Mutations in ABCA4 are the most common cause of STGD in this cohort. Genetic defects in approximately 42.4% of STGD patients await identification in future studies.
Mishima, Hiroyuki; Sasaki, Kensaku; Tanaka, Masahiro; Tatebe, Osamu; Yoshiura, Koh-Ichiro
In bioinformatics projects, scientific workflow systems are widely used to manage computational procedures. Full-featured workflow systems have been proposed to fulfil the demand for workflow management. However, such systems tend to be over-weighted for actual bioinformatics practices. We realize that quick deployment of cutting-edge software implementing advanced algorithms and data formats, and continuous adaptation to changes in computational resources and the environment are often prioritized in scientific workflow management. These features have a greater affinity with the agile software development method through iterative development phases after trial and error.Here, we show the application of a scientific workflow system Pwrake to bioinformatics workflows. Pwrake is a parallel workflow extension of Ruby's standard build tool Rake, the flexibility of which has been demonstrated in the astronomy domain. Therefore, we hypothesize that Pwrake also has advantages in actual bioinformatics workflows. We implemented the Pwrake workflows to process next generation sequencing data using the Genomic Analysis Toolkit (GATK) and Dindel. GATK and Dindel workflows are typical examples of sequential and parallel workflows, respectively. We found that in practice, actual scientific workflow development iterates over two phases, the workflow definition phase and the parameter adjustment phase. We introduced separate workflow definitions to help focus on each of the two developmental phases, as well as helper methods to simplify the descriptions. This approach increased iterative development efficiency. Moreover, we implemented combined workflows to demonstrate modularity of the GATK and Dindel workflows. Pwrake enables agile management of scientific workflows in the bioinformatics domain. The internal domain specific language design built on Ruby gives the flexibility of rakefiles for writing scientific workflows. Furthermore, readability and maintainability of rakefiles
Background In bioinformatics projects, scientific workflow systems are widely used to manage computational procedures. Full-featured workflow systems have been proposed to fulfil the demand for workflow management. However, such systems tend to be over-weighted for actual bioinformatics practices. We realize that quick deployment of cutting-edge software implementing advanced algorithms and data formats, and continuous adaptation to changes in computational resources and the environment are often prioritized in scientific workflow management. These features have a greater affinity with the agile software development method through iterative development phases after trial and error. Here, we show the application of a scientific workflow system Pwrake to bioinformatics workflows. Pwrake is a parallel workflow extension of Ruby's standard build tool Rake, the flexibility of which has been demonstrated in the astronomy domain. Therefore, we hypothesize that Pwrake also has advantages in actual bioinformatics workflows. Findings We implemented the Pwrake workflows to process next generation sequencing data using the Genomic Analysis Toolkit (GATK) and Dindel. GATK and Dindel workflows are typical examples of sequential and parallel workflows, respectively. We found that in practice, actual scientific workflow development iterates over two phases, the workflow definition phase and the parameter adjustment phase. We introduced separate workflow definitions to help focus on each of the two developmental phases, as well as helper methods to simplify the descriptions. This approach increased iterative development efficiency. Moreover, we implemented combined workflows to demonstrate modularity of the GATK and Dindel workflows. Conclusions Pwrake enables agile management of scientific workflows in the bioinformatics domain. The internal domain specific language design built on Ruby gives the flexibility of rakefiles for writing scientific workflows. Furthermore, readability
Lawlor, Brendan; Walsh, Paul
There is a lack of software engineering skills in bioinformatic contexts. We discuss the consequences of this lack, examine existing explanations and remedies to the problem, point out their shortcomings, and propose alternatives. Previous analyses of the problem have tended to treat the use of software in scientific contexts as categorically different from the general application of software engineering in commercial settings. In contrast, we describe bioinformatic software engineering as a specialization of general software engineering, and examine how it should be practiced. Specifically, we highlight the difference between programming and software engineering, list elements of the latter and present the results of a survey of bioinformatic practitioners which quantifies the extent to which those elements are employed in bioinformatics. We propose that the ideal way to bring engineering values into research projects is to bring engineers themselves. We identify the role of Bioinformatic Engineer and describe how such a role would work within bioinformatic research teams. We conclude by recommending an educational emphasis on cross-training software engineers into life sciences, and propose research on Domain Specific Languages to facilitate collaboration between engineers and bioinformaticians.
Bruhn, Russel Elton; Burton, Philip John
Data interchange bioinformatics databases will, in the future, most likely take place using extensible markup language (XML). The document structure will be described by an XML Schema rather than a document type definition (DTD). To ensure flexibility, the XML Schema must incorporate aspects of Object-Oriented Modeling. This impinges on the choice of the data model, which, in turn, is based on the organization of bioinformatics data by biologists. Thus, there is a need for the general bioinformatics community to be aware of the design issues relating to XML Schema. This paper, which is aimed at a general bioinformatics audience, uses examples to describe the differences between a DTD and an XML Schema and indicates how Unified Modeling Language diagrams may be used to incorporate Object-Oriented Modeling in the design of schema.
Mefford, Megan E.; Kunstman, Kevin; Wolinsky, Steven M.; Gabuzda, Dana
Macrophages express low levels of the CD4 receptor compared to T-cells. Macrophage-tropic HIV strains replicating in brain of untreated patients with HIV-associated dementia (HAD) express Envs that are adapted to overcome this restriction through mechanisms that are poorly understood. Here, bioinformatic analysis of env sequence datasets together with functional studies identified polymorphisms in the β3 strand of the HIV gp120 bridging sheet that increase M-tropism. D197, which results in loss of an N-glycan located near the HIV Env trimer apex, was detected in brain in some HAD patients, while position 200 was estimated to be under positive selection. D197 and T/V200 increased fusion and infection of cells expressing low CD4 by enhancing gp120 binding to CCR5. These results identify polymorphisms in the HIV gp120 bridging sheet that overcome the restriction to macrophage infection imposed by low CD4 through enhanced gp120–CCR5 interactions, thereby promoting infection of brain and other macrophage-rich tissues. - Highlights: • We analyze HIV Env sequences and identify amino acids in beta 3 of the gp120 bridging sheet that enhance macrophage tropism. • These amino acids at positions 197 and 200 are present in brain of some patients with HIV-associated dementia. • D197 results in loss of a glycan near the HIV Env trimer apex, which may increase exposure of V3. • These variants may promote infection of macrophages in the brain by enhancing gp120–CCR5 interactions
Full Text Available Abstract Background Severe acute respiratory syndrome (SARS is an emerging infectious disease caused by the novel coronavirus SARS-CoV. The T cell epitopes of the SARS CoV spike protein are well known, but no systematic evaluation of the functional and structural roles of each residue has been reported for these antigenic epitopes. Analysis of the functional importance of side-chains by mutational study may exaggerate the effect by imposing a structural disturbance or an unusual steric, electrostatic or hydrophobic interaction. Results We demonstrated that N50 could induce significant IFN-gamma response from SARS-CoV S DNA immunized mice splenocytes by the means of ELISA, ELISPOT and FACS. Moreover, S366-374 was predicted to be an optimal epitope by bioinformatics tools: ANN, SMM, ARB and BIMAS, and confirmed by IFN-gamma response induced by a series of S358-374-derived peptides. Furthermore, each of S366-374 was replaced by alanine (A, lysine (K or aspartic acid (D, respectively. ANN was used to estimate the binding affinity of single S366-374 mutants to H-2 Kd. Y367 and L374 were predicated to possess the most important role in peptide binding. Additionally, these one residue mutated peptides were synthesized, and IFN-gamma production induced by G368, V369, A371, T372 and K373 mutated S366-374 were decreased obviously. Conclusions We demonstrated that S366-374 is an optimal H-2 Kd CTL epitope in the SARS CoV S protein. Moreover, Y367, S370, and L374 are anchors in the epitope, while C366, G368, V369, A371, T372, and K373 may directly interact with TCR on the surface of CD8-T cells.
Mefford, Megan E., E-mail: firstname.lastname@example.org [Department of Cancer Immunology and AIDS, Dana-Farber Cancer Institute, Boston, MA (United States); Kunstman, Kevin, E-mail: email@example.com [Northwestern University Medical School, Chicago, IL (United States); Wolinsky, Steven M., E-mail: firstname.lastname@example.org [Northwestern University Medical School, Chicago, IL (United States); Gabuzda, Dana, E-mail: email@example.com [Department of Cancer Immunology and AIDS, Dana-Farber Cancer Institute, Boston, MA (United States); Department of Neurology (Microbiology and Immunobiology), Harvard Medical School, Boston, MA (United States)
Macrophages express low levels of the CD4 receptor compared to T-cells. Macrophage-tropic HIV strains replicating in brain of untreated patients with HIV-associated dementia (HAD) express Envs that are adapted to overcome this restriction through mechanisms that are poorly understood. Here, bioinformatic analysis of env sequence datasets together with functional studies identified polymorphisms in the β3 strand of the HIV gp120 bridging sheet that increase M-tropism. D197, which results in loss of an N-glycan located near the HIV Env trimer apex, was detected in brain in some HAD patients, while position 200 was estimated to be under positive selection. D197 and T/V200 increased fusion and infection of cells expressing low CD4 by enhancing gp120 binding to CCR5. These results identify polymorphisms in the HIV gp120 bridging sheet that overcome the restriction to macrophage infection imposed by low CD4 through enhanced gp120–CCR5 interactions, thereby promoting infection of brain and other macrophage-rich tissues. - Highlights: • We analyze HIV Env sequences and identify amino acids in beta 3 of the gp120 bridging sheet that enhance macrophage tropism. • These amino acids at positions 197 and 200 are present in brain of some patients with HIV-associated dementia. • D197 results in loss of a glycan near the HIV Env trimer apex, which may increase exposure of V3. • These variants may promote infection of macrophages in the brain by enhancing gp120–CCR5 interactions.
de Jong, Anne; van Heel, Auke J.; Kuipers, Oscar P.
Bioinformatic tools can greatly improve the efficiency of bacteriocin screening efforts by limiting the amount of strains. Different classes of bacteriocins can be detected in genomes by looking at different features. Finding small bacteriocins can be especially challenging due to low homology and because small open reading frames (ORFs) are often omitted from annotations. In this chapter, several bioinformatic tools/strategies to identify bacteriocins in genomes are discussed.
Magana, Alejandra J.; Taleyarkhan, Manaz; Alvarado, Daniela Rivera; Kane, Michael; Springer, John; Clase, Kari
Bioinformatics education can be broadly defined as the teaching and learning of the use of computer and information technology, along with mathematical and statistical analysis for gathering, storing, analyzing, interpreting, and integrating data to solve biological problems. The recent surge of genomics, proteomics, and structural biology in the…
Full Text Available Abstract Background: The v-erbA oncogene, carried by the Avian Erythroblastosis Virus, derives from the c-erbAα proto-oncogene that encodes the nuclear receptor for triiodothyronine (T3R. v-ErbA transforms erythroid progenitors in vitro by blocking their differentiation, supposedly by interference with T3R and RAR (Retinoic Acid Receptor. However, v-ErbA target genes involved in its transforming activity still remain to be identified. Results: By using Serial Analysis of Gene Expression (SAGE, we identified 110 genes deregulated by v-ErbA and potentially implicated in the transformation process. Bioinformatic analysis of promoter sequence and transcriptional assays point out a potential role of c-Myb in the v-ErbA effect. Furthermore, grouping of newly identified target genes by function revealed both expected (chromatin/transcription and unexpected (protein metabolism functions potentially deregulated by v-ErbA. We then focused our study on 15 of the new v-ErbA target genes and demonstrated by real time PCR that in majority their expression was activated neither by T3, nor RA, nor during differentiation. This was unexpected based upon the previously known role of v-ErbA. Conclusion: This paper suggests the involvement of a wealth of new unanticipated mechanisms of v-ErbA action.
Fang, Wai-Chi; Lue, Jaw-Chyng
A system comprising very-large-scale integrated (VLSI) circuits is being developed as a means of bioinformatics-oriented analysis and recognition of patterns of fluorescence generated in a microarray in an advanced, highly miniaturized, portable genetic-expression-assay instrument. Such an instrument implements an on-chip combination of polymerase chain reactions and electrochemical transduction for amplification and detection of deoxyribonucleic acid (DNA).
Background MicroRNAs (miRNAs) are noncoding RNAs that direct post-transcriptional regulation of protein coding genes. Recent studies have shown miRNAs are important for controlling many biological processes, including nervous system development, and are highly conserved across species. Given their importance, computational tools are necessary for analysis, interpretation and integration of high-throughput (HTP) miRNA data in an increasing number of model species. The Bioinformatics Resource Manager (BRM) v2.3 is a software environment for data management, mining, integration and functional annotation of HTP biological data. In this study, we report recent updates to BRM for miRNA data analysis and cross-species comparisons across datasets. Results BRM v2.3 has the capability to query predicted miRNA targets from multiple databases, retrieve potential regulatory miRNAs for known genes, integrate experimentally derived miRNA and mRNA datasets, perform ortholog mapping across species, and retrieve annotation and cross-reference identifiers for an expanded number of species. Here we use BRM to show that developmental exposure of zebrafish to 30 uM nicotine from 6–48 hours post fertilization (hpf) results in behavioral hyperactivity in larval zebrafish and alteration of putative miRNA gene targets in whole embryos at developmental stages that encompass early neurogenesis. We show typical workflows for using BRM to integrate experimental zebrafish miRNA and mRNA microarray datasets with example retrievals for zebrafish, including pathway annotation and mapping to human ortholog. Functional analysis of differentially regulated (p<0.05) gene targets in BRM indicates that nicotine exposure disrupts genes involved in neurogenesis, possibly through misregulation of nicotine-sensitive miRNAs. Conclusions BRM provides the ability to mine complex data for identification of candidate miRNAs or pathways that drive phenotypic outcome and, therefore, is a useful hypothesis
Tilton Susan C
Full Text Available Abstract Background MicroRNAs (miRNAs are noncoding RNAs that direct post-transcriptional regulation of protein coding genes. Recent studies have shown miRNAs are important for controlling many biological processes, including nervous system development, and are highly conserved across species. Given their importance, computational tools are necessary for analysis, interpretation and integration of high-throughput (HTP miRNA data in an increasing number of model species. The Bioinformatics Resource Manager (BRM v2.3 is a software environment for data management, mining, integration and functional annotation of HTP biological data. In this study, we report recent updates to BRM for miRNA data analysis and cross-species comparisons across datasets. Results BRM v2.3 has the capability to query predicted miRNA targets from multiple databases, retrieve potential regulatory miRNAs for known genes, integrate experimentally derived miRNA and mRNA datasets, perform ortholog mapping across species, and retrieve annotation and cross-reference identifiers for an expanded number of species. Here we use BRM to show that developmental exposure of zebrafish to 30 uM nicotine from 6–48 hours post fertilization (hpf results in behavioral hyperactivity in larval zebrafish and alteration of putative miRNA gene targets in whole embryos at developmental stages that encompass early neurogenesis. We show typical workflows for using BRM to integrate experimental zebrafish miRNA and mRNA microarray datasets with example retrievals for zebrafish, including pathway annotation and mapping to human ortholog. Functional analysis of differentially regulated (p Conclusions BRM provides the ability to mine complex data for identification of candidate miRNAs or pathways that drive phenotypic outcome and, therefore, is a useful hypothesis generation tool for systems biology. The miRNA workflow in BRM allows for efficient processing of multiple miRNA and mRNA datasets in a single
Fu, Zhiyan; Lin, Jing
The rapidly increasing number of characterized allergens has created huge demands for advanced information storage, retrieval, and analysis. Bioinformatics and machine learning approaches provide useful tools for the study of allergens and epitopes prediction, which greatly complement traditional laboratory techniques. The specific applications mainly include identification of B- and T-cell epitopes, and assessment of allergenicity and cross-reactivity. In order to facilitate the work of clinical and basic researchers who are not familiar with bioinformatics, we review in this chapter the most important databases, bioinformatic tools, and methods with relevance to the study of allergens.
Mount, David W
... at www.bioinformaticsonline.org: 1. Open the home page of the site. 2. Follow the registration procedure that begins on that page. 3. When prompted, enter the unique access code that is printed on the inside front cover of this book. 4. When prompted, enter your E-mail address as your user name and a password of your choice. 5. Complete the registration procedu...
Leung, Anthony K L; Andersen, Jens S; Mann, Matthias
The nucleolus is a plurifunctional, nuclear organelle, which is responsible for ribosome biogenesis and many other functions in eukaryotes, including RNA processing, viral replication and tumour suppression. Our knowledge of the human nucleolar proteome has been expanded dramatically by the two r...
Greene, Anna C.; Giffin, Kristine A.; Greene, Casey S.
Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs. PMID:25829469
Strabala, Timothy J; Phillips, Lorelle; West, Mark; Stanbra, Lisa
found in conifers and they exhibit at least as much sequence diversity in these species as they do in other plant species. Only one CLE peptide sequence has been 100% conserved between gymnosperms and angiosperms over 300 million years of evolutionary history, the CLE41/44-TDIF peptide and its likely conifer orthologues. The preferential expression of these vascular development-regulating genes in phloem in conifers, as they are in dicot species, suggests close parallels in the regulation of secondary growth and wood formation in gymnosperm and dicot plants. Based on our bioinformatic analysis, we predict a novel mechanism of regulation of the expression of several conifer CLEL peptides, via alternative splicing resulting in the selection of alternative C-terminal exons encoding separate CLEL peptides.
Full Text Available Abstract Background We have reported arginine-sensitive regulation of LAT1 amino acid transporter (SLC 7A5 in normal rodent hepatic cells with loss of arginine sensitivity and high level constitutive expression in tumor cells. We hypothesized that liver cell gene expression is highly sensitive to alterations in the amino acid microenvironment and that tumor cells may differ substantially in gene sets sensitive to amino acid availability. To assess the potential number and classes of hepatic genes sensitive to arginine availability at the RNA level and compare these between normal and tumor cells, we used an Affymetrix microarray approach, a paired in vitro model of normal rat hepatic cells and a tumorigenic derivative with triplicate independent replicates. Cells were exposed to arginine-deficient or control conditions for 18 hours in medium formulated to maintain differentiated function. Results Initial two-way analysis with a p-value of 0.05 identified 1419 genes in normal cells versus 2175 in tumor cells whose expression was altered in arginine-deficient conditions relative to controls, representing 9–14% of the rat genome. More stringent bioinformatic analysis with 9-way comparisons and a minimum of 2-fold variation narrowed this set to 56 arginine-responsive genes in normal liver cells and 162 in tumor cells. Approximately half the arginine-responsive genes in normal cells overlap with those in tumor cells. Of these, the majority was increased in expression and included multiple growth, survival, and stress-related genes. GADD45, TA1/LAT1, and caspases 11 and 12 were among this group. Previously known amino acid regulated genes were among the pool in both cell types. Available cDNA probes allowed independent validation of microarray data for multiple genes. Among genes downregulated under arginine-deficient conditions were multiple genes involved in cholesterol and fatty acid metabolism. Expression of low-density lipoprotein receptor was
Full Text Available The human microbiome has received much attention because many studies have reported that the human gut microbiome is associated with several diseases. The very large datasets that are produced by these kinds of studies means that bioinformatics approaches are crucial for their analysis. Here, we systematically reviewed bioinformatics tools that are commonly used in microbiome research, including a typical pipeline and software for sequence alignment, abundance profiling, enterotype determination, taxonomic diversity, identifying differentially abundant species/genes, gene cataloging, and functional analyses. We also summarized the algorithms and methods used to define metagenomic species and co-abundance gene groups to expand our understanding of unclassified and poorly understood gut microbes that are undocumented in the current genome databases. Additionally, we examined the methods used to identify metagenomic biomarkers based on the gut microbiome, which might help to expand the knowledge and approaches for disease detection and monitoring.
Hande, Sneha; Goswami, Kalyan; Sharma, Richa; Bhoj, Priyanka; Jena, Lingaraj; Reddy, Maryada Venkata Rami
Lymphatic filariasis, commonly called elephantiasis, poses a burden of estimated level of 5.09 million disability adjusted life year. Limitations of its sole drug, diethylcarbamazine (DEC) drive exploration of effective filarial target. A few plant extracts having polyphenolic ingredients and some synthetic compounds possess potential dihydrofolate reductase (DHFR) inhibitory effect. Here, we postulated a plausible link between folates and polyphenolics based on their common precursor in shikimate metabolism. Considering its implication in structural resemblance based antagonism, we have attempted to validate parasitic DHFR protein as a target. The bioinformatics approach, in the absence of crystal structure of the proposed target, used to authenticate and for virtual docking with suitable tested compounds, showed remarkably lower thermodynamic parameters as opposed to the positive control. A comparative docking analysis between human and Brugia malayi DHFR also showed effective binding parameters with lower inhibition constants of these ligands with parasitic target, but not with human counterpart highlighting safety and efficacy. This study suggests that DHFR could be a valid drug target for lymphatic filariasis, and further reveal that bioinformatics may be an effective tool in reverse pharmacological approach for drug design.
Ranganathan, Shoba; Hsu, Wen-Lian; Yang, Ueng-Cheng; Tan, Tin Wee
The 2008 annual conference of the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation set up in 1998, was organized as the 7th International Conference on Bioinformatics (InCoB), jointly with the Bioinformatics and Systems Biology in Taiwan (BIT 2008) Conference, Oct. 20?23, 2008 at Taipei, Taiwan. Besides bringing together scientists from the field of bioinformatics in this region, InCoB is actively involving researchers from the area of systems biology,...
Li, Yuan; Jin, Feng; Chao, Qing; Wang, Bai-Chen
Wood is the most important natural source of energy and also provides fuel and fiber. Considering the significant role of wood, it is critical to understand how wood is formed. Integration of knowledge about wood development at the cellular and molecular levels will allow more comprehensive understanding of this complex process. In the present study, we used a comparative proteomic approach to investigate the differences in protein profiles between primary and secondary growth in young poplar stems using tandem mass tag (TMT)-labeling. More than 10,816 proteins were identified, and, among these, 3106 proteins were differentially expressed during primary to secondary growth. Proteomic data were validated using a combination of histochemical staining, enzyme activity assays, and quantitative real-time PCR. Bioinformatics analysis revealed that these differentially expressed proteins are related to various metabolic pathways, mainly including signaling, phytohormones, cell cycle, cell wall, secondary metabolism, carbohydrate and energy metabolism, and protein metabolism as well as redox and stress pathways. This large proteomics dataset will be valuable for uncovering the molecular changes occurring during the transition from primary to secondary growth. Further, it provides new and accurate information for tree breeding to modify wood properties. Copyright © 2017 Elsevier GmbH. All rights reserved.
Wooller, Sarah K; Benstead-Hume, Graeme; Chen, Xiangrong; Ali, Yusuf; Pearl, Frances M G
Bioinformatics approaches are becoming ever more essential in translational drug discovery both in academia and within the pharmaceutical industry. Computational exploitation of the increasing volumes of data generated during all phases of drug discovery is enabling key challenges of the process to be addressed. Here, we highlight some of the areas in which bioinformatics resources and methods are being developed to support the drug discovery pipeline. These include the creation of large data warehouses, bioinformatics algorithms to analyse 'big data' that identify novel drug targets and/or biomarkers, programs to assess the tractability of targets, and prediction of repositioning opportunities that use licensed drugs to treat additional indications. © 2017 The Author(s).
Zhang, Zhang; Cheung, Kei-Hoi; Townsend, Jeffrey P
Enabling deft data integration from numerous, voluminous and heterogeneous data sources is a major bioinformatic challenge. Several approaches have been proposed to address this challenge, including data warehousing and federated databasing. Yet despite the rise of these approaches, integration of data from multiple sources remains problematic and toilsome. These two approaches follow a user-to-computer communication model for data exchange, and do not facilitate a broader concept of data sharing or collaboration among users. In this report, we discuss the potential of Web 2.0 technologies to transcend this model and enhance bioinformatics research. We propose a Web 2.0-based Scientific Social Community (SSC) model for the implementation of these technologies. By establishing a social, collective and collaborative platform for data creation, sharing and integration, we promote a web services-based pipeline featuring web services for computer-to-computer data exchange as users add value. This pipeline aims to simplify data integration and creation, to realize automatic analysis, and to facilitate reuse and sharing of data. SSC can foster collaboration and harness collective intelligence to create and discover new knowledge. In addition to its research potential, we also describe its potential role as an e-learning platform in education. We discuss lessons from information technology, predict the next generation of Web (Web 3.0), and describe its potential impact on the future of bioinformatics studies.
Christopher L Williams
Full Text Available Objective: Within the information technology (IT industry, best practices and standards are constantly evolving and being refined. In contrast, computer technology utilized within the healthcare industry often evolves at a glacial pace, with reduced opportunities for justified innovation. Although the use of timely technology refreshes within an enterprise′s overall technology stack can be costly, thoughtful adoption of select technologies with a demonstrated return on investment can be very effective in increasing productivity and at the same time, reducing the burden of maintenance often associated with older and legacy systems. In this brief technical communication, we introduce the concept of microservices as applied to the ecosystem of data analysis pipelines. Microservice architecture is a framework for dividing complex systems into easily managed parts. Each individual service is limited in functional scope, thereby conferring a higher measure of functional isolation and reliability to the collective solution. Moreover, maintenance challenges are greatly simplified by virtue of the reduced architectural complexity of each constitutive module. This fact notwithstanding, rendered overall solutions utilizing a microservices-based approach provide equal or greater levels of functionality as compared to conventional programming approaches. Bioinformatics, with its ever-increasing demand for performance and new testing algorithms, is the perfect use-case for such a solution. Moreover, if promulgated within the greater development community as an open-source solution, such an approach holds potential to be transformative to current bioinformatics software development. Context: Bioinformatics relies on nimble IT framework which can adapt to changing requirements. Aims: To present a well-established software design and deployment strategy as a solution for current challenges within bioinformatics Conclusions: Use of the microservices framework
Vecsey, Christopher G; Peixoto, Lucia; Choi, Jennifer H K; Wimmer, Mathieu; Jaganath, Devan; Hernandez, Pepe J; Blackwell, Jennifer; Meda, Karuna; Park, Alan J; Hannenhalli, Sridhar; Abel, Ted
Sleep deprivation is a common problem of considerable health and economic impact in today's society. Sleep loss is associated with deleterious effects on cognitive functions such as memory and has a high comorbidity with many neurodegenerative and neuropsychiatric disorders. Therefore, it is crucial to understand the molecular basis of the effect of sleep deprivation in the brain. In this study, we combined genome-wide and traditional molecular biological approaches to determine the cellular and molecular impacts of sleep deprivation in the mouse hippocampus, a brain area crucial for many forms of memory. Microarray analysis examining the effects of 5 h of sleep deprivation on gene expression in the mouse hippocampus found 533 genes with altered expression. Bioinformatic analysis revealed that a prominent effect of sleep deprivation was to downregulate translation, potentially mediated through components of the insulin signaling pathway such as the mammalian target of rapamycin (mTOR), a key regulator of protein synthesis. Consistent with this analysis, sleep deprivation reduced levels of total and phosphorylated mTOR, and levels returned to baseline after 2.5 h of recovery sleep. Our findings represent the first genome-wide analysis of the effects of sleep deprivation on the mouse hippocampus, and they suggest that the detrimental effects of sleep deprivation may be mediated by reductions in protein synthesis via downregulation of mTOR. Because protein synthesis and mTOR activation are required for long-term memory formation, our study improves our understanding of the molecular mechanisms underlying the memory impairments induced by sleep deprivation.
Weber, Tilmann; Kim, Hyun Uk
. In this context, this review gives a summary of tools and databases that currently are available to mine, identify and characterize natural product biosynthesis pathways and their producers based on ‘omics data. A web portal called Secondary Metabolite Bioinformatics Portal (SMBP at http......://www.secondarymetabolites.org) is introduced to provide a one-stop catalog and links to these bioinformatics resources. In addition, an outlook is presented how the existing tools and those to be developed will influence synthetic biology approaches in the natural products field....
Lue, Jaw-Chyng L.; Fang, Wai-Chi
A microsystem architecture for real-time, on-site, robust bioinformatic patterns recognition and analysis has been proposed. This system is compatible with on-chip DNA analysis means such as polymerase chain reaction (PCR)amplification. A corresponding novel artificial neural network (ANN) learning algorithm using new sigmoid-logarithmic transfer function based on error backpropagation (EBP) algorithm is invented. Our results show the trained new ANN can recognize low fluorescence patterns better than the conventional sigmoidal ANN does. A differential logarithmic imaging chip is designed for calculating logarithm of relative intensities of fluorescence signals. The single-rail logarithmic circuit and a prototype ANN chip are designed, fabricated and characterized.
van Kampen, Antoine H. C.; Moerland, Perry D.
Systems medicine promotes a range of approaches and strategies to study human health and disease at a systems level with the aim of improving the overall well-being of (healthy) individuals, and preventing, diagnosing, or curing disease. In this chapter we discuss how bioinformatics critically
This book chapter describes the current Big Data problem in Bioinformatics and the resulting issues with performing reproducible computational research. The core of the chapter provides guidelines and summaries of current tools/techniques that a noncomputational researcher would need to learn to pe...
Vaez Barzani, Ahmad
In this thesis we present an overview of bioinformatics-based approaches for genomic association mapping, with emphasis on human quantitative traits and their contribution to complex diseases. We aim to provide a comprehensive walk-through of the classic steps of genomic association mapping
Hassanien, Aboul Ella; Al-Shammari, Eiman Tamah; Ghali, Neveen I
Computational intelligence (CI) is a well-established paradigm with current systems having many of the characteristics of biological computers and capable of performing a variety of tasks that are difficult to do using conventional techniques. It is a methodology involving adaptive mechanisms and/or an ability to learn that facilitate intelligent behavior in complex and changing environments, such that the system is perceived to possess one or more attributes of reason, such as generalization, discovery, association and abstraction. The objective of this article is to present to the CI and bioinformatics research communities some of the state-of-the-art in CI applications to bioinformatics and motivate research in new trend-setting directions. In this article, we present an overview of the CI techniques in bioinformatics. We will show how CI techniques including neural networks, restricted Boltzmann machine, deep belief network, fuzzy logic, rough sets, evolutionary algorithms (EA), genetic algorithms (GA), swarm intelligence, artificial immune systems and support vector machines, could be successfully employed to tackle various problems such as gene expression clustering and classification, protein sequence classification, gene selection, DNA fragment assembly, multiple sequence alignment, and protein function prediction and its structure. We discuss some representative methods to provide inspiring examples to illustrate how CI can be utilized to address these problems and how bioinformatics data can be characterized by CI. Challenges to be addressed and future directions of research are also presented and an extensive bibliography is included. Copyright © 2013 Elsevier Ltd. All rights reserved.
Full Text Available Abstract Background Recent advances in experimental and computational technologies have fueled the development of many sophisticated bioinformatics programs. The correctness of such programs is crucial as incorrectly computed results may lead to wrong biological conclusion or misguide downstream experimentation. Common software testing procedures involve executing the target program with a set of test inputs and then verifying the correctness of the test outputs. However, due to the complexity of many bioinformatics programs, it is often difficult to verify the correctness of the test outputs. Therefore our ability to perform systematic software testing is greatly hindered. Results We propose to use a novel software testing technique, metamorphic testing (MT, to test a range of bioinformatics programs. Instead of requiring a mechanism to verify whether an individual test output is correct, the MT technique verifies whether a pair of test outputs conform to a set of domain specific properties, called metamorphic relations (MRs, thus greatly increases the number and variety of test cases that can be applied. To demonstrate how MT is used in practice, we applied MT to test two open-source bioinformatics programs, namely GNLab and SeqMap. In particular we show that MT is simple to implement, and is effective in detecting faults in a real-life program and some artificially fault-seeded programs. Further, we discuss how MT can be applied to test programs from various domains of bioinformatics. Conclusion This paper describes the application of a simple, effective and automated technique to systematically test a range of bioinformatics programs. We show how MT can be implemented in practice through two real-life case studies. Since many bioinformatics programs, particularly those for large scale simulation and data analysis, are hard to test systematically, their developers may benefit from using MT as part of the testing strategy. Therefore our work
Krawetz, Stephen A
..., requires an unprecedented level of development to collect, manage and mine the data for interesting associations. To begin to understand this information we now rely on statistical analysis to aid in our selection of the fruit from the tree. However, this often takes us on a journey into a new field for which we are not yet prepared. Samuel Joh...
"The overall aim of "EURASIP Journal on Bioinformatics and Systems Biology" is to publish research results related to signal processing and bioinformatics theories and techniques relevant to a wide...
CERN. Geneva; Deutsch, Sam; Michielin, Olivier; Thomas, Arthur; Descombes, Patrick
Extracting the fundamental genomic sequence from the DNA From Genome to Sequence : Biology in the early 21st century has been radically transformed by the availability of the full genome sequences of an ever increasing number of life forms, from bacteria to major crop plants and to humans. The lecture will concentrate on the computational challenges associated with the production, storage and analysis of genome sequence data, with an emphasis on mammalian genomes. The quality and usability of genome sequences is increasingly conditioned by the careful integration of strategies for data collection and computational analysis, from the construction of maps and libraries to the assembly of raw data into sequence contigs and chromosome-sized scaffolds. Once the sequence is assembled, a major challenge is the mapping of biologically relevant information onto this sequence: promoters, introns and exons of protein-encoding genes, regulatory elements, functional RNAs, pseudogenes, transposons, etc. The methodological ...
Full Text Available The redox-regulated transcription factor SoxR is conserved in diverse bacteria, but emerging studies suggest that this protein plays distinct physiological roles in different bacteria. SoxR regulates a global oxidative stress response (involving > 100 genes against exogenous redox-cycling drugs in Escherichia coli and related enterics. In the antibiotic producers Streptomyces coelicolor and Pseudomonas aeruginosa, however, SoxR regulates a smaller number of genes that encode membrane transporters and proteins with homology to antibiotic-tailoring enzymes. In both S. coelicolor and P. aeruginosa, SoxR-regulated genes are expressed in stationary phase during the production of endogenously-produced redox-active antibiotics. These observations suggest that SoxR evolved to sense endogenous secondary metabolites and activate machinery to process and transport them in antibiotic-producing bacteria. Previous bioinformatics analysis that searched the genome for SoxR-binding sites in putative promoters defined a five-gene SoxR regulon in S. coelicolor including an ABC transporter, two oxidoreductases, a monooxygenase and an epimerase/dehydratase. Since this in silico screen may have missed potential SoxR-targets, we conducted a whole genome transcriptome comparison of wild type S. coelicolor and a soxR-deficient mutant in stationary phase using RNA-Seq. Our analysis revealed a sixth SoxR-regulated gene in S. coelicolor that encodes a putative quinone oxidoreductase. Knowledge of the full complement of genes regulated by SoxR will facilitate studies to elucidate the function of this regulatory molecule in antibiotic producers.
Biochemical, Transcriptional, and Bioinformatic Analysis of Lipid Droplets from Seeds of Date Palm (Phoenix dactylifera L.) and Their Use as Potent Sequestration Agents against the Toxic Pollutant, 2,3,7,8-Tetrachlorinated Dibenzo-p-Dioxin.
Hanano, Abdulsamie; Almousally, Ibrahem; Shaban, Mouhnad; Rahman, Farzana; Blee, Elizabeth; Murphy, Denis J
Contamination of aquatic environments with dioxins, the most toxic group of persistent organic pollutants (POPs), is a major ecological issue. Dioxins are highly lipophilic and bioaccumulate in fatty tissues of marine organisms used for seafood where they constitute a potential risk for human health. Lipid droplets (LDs) purified from date palm, Phoenix dactylifera, seeds were characterized and their capacity to extract dioxins from aquatic systems was assessed. The bioaffinity of date palm LDs toward 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), the most toxic congener of dioxins was determined. Fractioned LDs were spheroidal with mean diameters of 2.5 µm, enclosing an oil-rich core of 392.5 mg mL(-1). Isolated LDs did not aggregate and/or coalesce unless placed in acidic media and were strongly associated with three major groups of polypeptides of relative mass 32-37, 20-24, and 16-18 kDa. These masses correspond to the LD-associated proteins, oleosins, caleosins, and steroleosins, respectively. Efficient partitioning of TCDD into LDs occurred with a coefficient of log K LB/w,TCDD = 7.528 ± 0.024; it was optimal at neutral pH and was dependent on the presence of the oil-rich core, but was independent of the presence of LD-associated proteins. Bioinformatic analysis of the date palm genome revealed nine oleosin-like, five caleosin-like, and five steroleosin-like sequences, with predicted structures having putative lipid-binding domains that match their LD stabilizing roles and use as bio-based encapsulation systems. Transcriptomic analysis of date palm seedlings exposed to TCDD showed strong up-regulation of several caleosin and steroleosin genes, consistent with increased LD formation. The results suggest that the plant LDs could be used in ecological remediation strategies to remove POPs from aquatic environments. Recent reports suggest that several fungal and algal species also use LDs to sequester both external and internally derived hydrophobic toxins, which
Feenstra, K. Anton; Abeln, Sanne
While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims to give an introduction into Structural Bioinformatics, which
Gront, Dominik; Kolinski, Andrzej
In this Note we present a new software library for structural bioinformatics. The library contains programs, computing sequence- and profile-based alignments and a variety of structural calculations with user-friendly handling of various data formats. The software organization is very flexible. Algorithms are written in Java language and may be used by Java programs. Moreover the modules can be accessed from Jython (Python scripting language implemented in Java) scripts. Finally, the new version of BioShell delivers several utility programs that can do typical bioinformatics task from a command-line level. Availability The software is available for download free of charge from its website: http://bioshell.chem.uw.edu.pl. This website provides also numerous examples, code snippets and API documentation.
Loving, Cathleen C.; Cobern, William W.
This paper analyzes how Thomas Kuhn's writings are used by others, especially science education researchers. Previous research in citation analysis is used to frame questions related to who cites Kuhn, in what manner and why. Research questions first focus on the variety of disciplines invoking Kuhn and to what extent Structure of Scientific Revolutions (SSR) is cited. The Web of Science database provides material from 1982 for this analysis. The science education literature is analyzed using back issues from 1985 of the Journal of Research in Science Teaching and Science Education. An article analysis reveals trends in terms of what Kuhnian ideas are most frequently invoked. Results indicate a wide array of disciplines from beekeeping to law cite Kuhn - especially generic citations to SSR. The science education journal analysis reveals pervasive use of the term paradigm, although use is quite varied. The two areas of research in science education most impacted by Kuhn appear to be conceptual change theory and constructivist epistemologies. Additional uses of Kuhn are discussed. The degree to which Kuhn is invoked in ways supporting the theoretical framework of citation analysis, whether his work is misappropriated, and the impact of Kuhn are discussed.
Full Text Available WSSV is one of the most dangerous pathogens in shrimp aquaculture. However, the molecular mechanism of how WSSV interacts with shrimp is still not very clear. In the present study, bioinformatic approaches were used to predict interactions between proteins from WSSV and shrimp. The genome data of WSSV (NC_003225.1 and the constructed transcriptome data of F. chinensis were used to screen potentially interacting proteins by searching in protein interaction databases, including STRING, Reactome, and DIP. Forty-four pairs of proteins were suggested to have interactions between WSSV and the shrimp. Gene ontology analysis revealed that 6 pairs of these interacting proteins were classified into “extracellular region” or “receptor complex” GO-terms. KEGG pathway analysis showed that they were involved in the “ECM-receptor interaction pathway.” In the 6 pairs of interacting proteins, an envelope protein called “collagen-like protein” (WSSV-CLP encoded by an early virus gene “wsv001” in WSSV interacted with 6 deduced proteins from the shrimp, including three integrin alpha (ITGA, two integrin beta (ITGB, and one syndecan (SDC. Sequence analysis on WSSV-CLP, ITGA, ITGB, and SDC revealed that they possessed the sequence features for protein-protein interactions. This study might provide new insights into the interaction mechanisms between WSSV and shrimp.
An, Mengting; Zhang, Fengbo; Zhu, Yuejie; Zhao, Xiao; Ding, Jianbing
Cystic echinococcosis, as a zoonosis, seriously endangers humans and animals, so early diagnosis of this disease is particularly important. Therefore, this study is to predict B-cell epitopes of EgAgB1 and EgAgB3 proteins by bioinformatics software. B-cell epitopes of EgAgB1 and EgAgB3 proteins are predicted using DNAStar and IEDB software. The results suggest that there are two potential B-cell epitopes in EgAgB1, which located in the 8-15 and 31-37 amino acid residue segments. And two potential B-cell epitopes in EgAgB2, located in the 20∼27 and 47∼53 amino acid residue segments. This study predicted the B-cell epitopes of EgAgB1 and EgAgB3 proteins, which laid the foundation for the early diagnosis of Cystic echinococcosis.
Wren, Jonathan D
To analyze the relative proportion of bioinformatics papers and their non-bioinformatics counterparts in the top 20 most cited papers annually for the past two decades. When defining bioinformatics papers as encompassing both those that provide software for data analysis or methods underlying data analysis software, we find that over the past two decades, more than a third (34%) of the most cited papers in science were bioinformatics papers, which is approximately a 31-fold enrichment relative to the total number of bioinformatics papers published. More than half of the most cited papers during this span were bioinformatics papers. Yet, the average 5-year JIF of top 20 bioinformatics papers was 7.7, whereas the average JIF for top 20 non-bioinformatics papers was 25.8, significantly higher (P bioinformatics journals tended to have higher Gini coefficients, suggesting that development of novel bioinformatics resources may be somewhat 'hit or miss'. That is, relative to other fields, bioinformatics produces some programs that are extremely widely adopted and cited, yet there are fewer of intermediate success. firstname.lastname@example.org Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: email@example.com.
Hettne, K.M.; Kleinjans, J.; Stierum, R.H.; Boorsma, A.; Kors, J.A.
This chapter concerns the application of bioinformatics methods to the analysis of toxicogenomics data. The chapter starts with an introduction covering how bioinformatics has been applied in toxicogenomics data analysis, and continues with a description of the foundations of a specific
Buschhardt, Tasja; Bahl, Martin Iain; Hansen, Tina Beck
monitored during aerobic chill-storage (4 °C and 7 °C) and temperature abuse (12 °C and 16 °C) for 96 hours, by culture-based methods and 16S rRNA gene sequencing. Bacterial genera that dominated during prolonged temperature abuse were Acinetobacter, Serratia and Pseudomonas, whereas chill-stored meat...... was dominated by Pseudomonas only. We also showed that the initial community affects subsequent changes during storage. The results suggest that principal coordinate analysis of beta diversity could be a useful tool to reveal temperature abused meat. Sequence data and culturing data revealed a strong positive......Violations of temperature regulations in the meat chain may affect meat safety. Methods are lacking to estimate whether meat has been subjected to temperature abuse. Exposure to too high temperatures may lead to systematic changes in the diverse bacterial communities of fresh meat. We investigated...
Buschhardt, Tasja; Bahl, Martin Iain; Hansen, Tina Beck
Violations of temperature regulations in the meat chain may affect meat safety. Methods are lacking to estimate whether meat has been subjected to temperature abuse. Exposure to too high temperatures may lead to systematic changes in the diverse bacterial communities of fresh meat. We investigated...... monitored during aerobic chill-storage (4 °C and 7 °C) and temperature abuse (12 °C and 16 °C) for 96 hours, by culture-based methods and 16S rRNA gene sequencing. Bacterial genera that dominated during prolonged temperature abuse were Acinetobacter, Serratia and Pseudomonas, whereas chill-stored meat...... was dominated by Pseudomonas only. We also showed that the initial community affects subsequent changes during storage. The results suggest that principal coordinate analysis of beta diversity could be a useful tool to reveal temperature abused meat. Sequence data and culturing data revealed a strong positive...
Full Text Available To gain insight on the impart of high-grain diets on liver metabolism in ruminants, we employed a comparative proteomic approach to investigate the proteome-wide effects of diet in lactating dairy goats by conducting a proteomic analysis of the liver extracts of 10 lactating goats fed either a control diet or a high-grain diet. More than 500 protein spots were detected per condition by two-dimensional electrophoresis (2-DE. In total, 52 differentially expressed spots (≥2.0-fold changed were excised and analyzed using MALDI TOF/TOF. Fifty-one protein spots were successfully identified. Of these, 29 proteins were upregulated, while 22 were downregulated in the high-grain fed vs. control animals. Differential expressions of proteins including alpha enolase, elongation factor 2, calreticulin, cytochrome b5, apolipoprotein A-I, catalase, was verified by mRNA analysis and/or Western blotting. Database searches combined with Gene Ontology (GO analysis and KEGG pathway analysis revealed that the high-grain diet resulted in altered expression of proteins related to amino acids metabolism. These results suggest new candidate proteins that may contribute to a better understanding of the signaling pathways and mechanisms that mediate liver adaptation to high-grain diet.
Yukinawa, N; Ishii, S; Takenouchi, T; Oba, S
Multi-class classification is one of the fundamental tasks in bioinformatics and typically arises in cancer diagnosis studies by gene expression profiling. This article reviews two recent approaches to multi-class classification by combining multiple binary classifiers, which are formulated based on a unified framework of error-correcting output coding (ECOC). The first approach is to construct a multi-class classifier in which each binary classifier to be aggregated has a weight value to be optimally tuned based on the observed data. In the second approach, misclassification of each binary classifier is formulated as a bit inversion error with a probabilistic model by making an analogy to the context of information transmission theory. Experimental studies using various real-world datasets including cancer classification problems reveal that both of the new methods are superior or comparable to other multi-class classification methods
Schneider, Maria V; Walter, Peter; Blatter, Marie-Claude; Watson, James; Brazas, Michelle D; Rother, Kristian; Budd, Aidan; Via, Allegra; van Gelder, Celia W G; Jacob, Joachim; Fernandes, Pedro; Nyrönen, Tommi H; De Las Rivas, Javier; Blicher, Thomas; Jimenez, Rafael C; Loveland, Jane; McDowall, Jennifer; Jones, Phil; Vaughan, Brendan W; Lopez, Rodrigo; Attwood, Teresa K; Brooksbank, Catherine
Funding bodies are increasingly recognizing the need to provide graduates and researchers with access to short intensive courses in a variety of disciplines, in order both to improve the general skills base and to provide solid foundations on which researchers may build their careers. In response to the development of 'high-throughput biology', the need for training in the field of bioinformatics, in particular, is seeing a resurgence: it has been defined as a key priority by many Institutions and research programmes and is now an important component of many grant proposals. Nevertheless, when it comes to planning and preparing to meet such training needs, tension arises between the reward structures that predominate in the scientific community which compel individuals to publish or perish, and the time that must be devoted to the design, delivery and maintenance of high-quality training materials. Conversely, there is much relevant teaching material and training expertise available worldwide that, were it properly organized, could be exploited by anyone who needs to provide training or needs to set up a new course. To do this, however, the materials would have to be centralized in a database and clearly tagged in relation to target audiences, learning objectives, etc. Ideally, they would also be peer reviewed, and easily and efficiently accessible for downloading. Here, we present the Bioinformatics Training Network (BTN), a new enterprise that has been initiated to address these needs and review it, respectively, to similar initiatives and collections.
The automatic classification of GPCRs by bioinformatics methodology can provide functional information for new GPCRs in the whole 'GPCR proteome' and this information is important for the development of novel drugs. Since GPCR proteome is classified hierarchically, general ways for GPCR function prediction are based on hierarchical classification. Various computational tools have been developed to predict GPCR functions; those tools use not simple sequence searches but more powerful methods, such as alignment-free methods, statistical model methods, and machine learning methods used in protein sequence analysis, based on learning datasets. The first stage of hierarchical function prediction involves the discrimination of GPCRs from non-GPCRs and the second stage involves the classification of the predicted GPCR candidates into family, subfamily, and sub-subfamily levels. Then, further classification is performed according to their protein-protein interaction type: binding G-protein type, oligomerized partner type, etc. Those methods have achieved predictive accuracies of around 90 %. Finally, I described the future subject of research of the bioinformatics technique about functional prediction of GPCR.
Ben Ayed, Rayda; Ben Hassen, Hanen; Ennouri, Karim; Rebai, Ahmed
The genetic diversity of 22 olive tree cultivars (Olea europaea L.) sampled from different Mediterranean countries was assessed using 5 SNP markers (FAD2.1; FAD2.3; CALC; SOD and ANTHO3) located in four different genes. The genotyping analysis of the 22 cultivars with 5 SNP loci revealed 11 alleles (average 2.2 per allele). The dendrogram based on cultivar genotypes revealed three clusters consistent with the cultivars classification. Besides, the results obtained with the five SNPs were compared to those obtained with the SSR markers using bioinformatic analyses and by computing a cophenetic correlation coefficient, indicating the usefulness of the UPGMA method for clustering plant genotypes. Based on principal coordinate analysis using a similarity matrix, the first two coordinates, revealed 54.94 % of the total variance. This work provides a more comprehensive explanation of the diversity available in Tunisia olive cultivars, and an important contribution for olive breeding and olive oil authenticity.
Zou, Quan; Li, Xu-Bin; Jiang, Wen-Rui; Lin, Zi-Yu; Li, Gui-Lin; Chen, Ke
Bioinformatics is challenged by the fact that traditional analysis tools have difficulty in processing large-scale data from high-throughput sequencing. The open source Apache Hadoop project, which adopts the MapReduce framework and a distributed file system, has recently given bioinformatics researchers an opportunity to achieve scalable, efficient and reliable computing performance on Linux clusters and on cloud computing services. In this article, we present MapReduce frame-based applications that can be employed in the next-generation sequencing and other biological domains. In addition, we discuss the challenges faced by this field as well as the future works on parallel computing in bioinformatics. © The Author 2013. Published by Oxford University Press. For Permissions, please email: firstname.lastname@example.org.
Attwood, Teresa K; Atwood, Teresa K; Bongcam-Rudloff, Erik; Brazas, Michelle E; Corpas, Manuel; Gaudet, Pascale; Lewitter, Fran; Mulder, Nicola; Palagi, Patricia M; Schneider, Maria Victoria; van Gelder, Celia W G
In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy--paradoxically, many are actually closing "niche" bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all.
Full Text Available Background and Aim: The ability to predict antigenic sites on proteins is of major importance for medication. The aim of this study was to predict the antigenic sites on Agglutin in Like Sequence (ALS1 and Hyphal Wall Protein Sequences (HWP1 in Candida albicans isolated of vaginal infections using Physico-Chemical Profiles server. Materials and Methods: 7 isolates were obtained from women with vaginal infection which were collected from various medical centers of Tehran in 2011 and 2012. At the first,DNA was extracted by Phenol-Chloroform method. Multiplex PCR was performed by using specific primers. In order to do bioinformatic studies, the genes were sequenced and then translated. Antigenic sites of protein sequences were identified by Physico-Chemical Profiles program. Results: The results showed that the presence of two genes als1 and hwp1 in isolates. In ALS1 and HWP1, respectively 2 and 1 antigenic site with the most antigenicity were identified. Conclusions: According to previous studies, Serine and Threonine phosphorylation is an important mechanism in pathogenesis of ALS1 and HWP1 proteins. Results in this study showed that serine and threonine are the most amino acids in the antigenic sites with high antigenicity property.
Thomas K Karikari
Full Text Available Until recently, bioinformatics, an important discipline in the biological sciences, was largely limited to countries with advanced scientific resources. Nonetheless, several developing countries have lately been making progress in bioinformatics training and applications. In Africa, leading countries in the discipline include South Africa, Nigeria, and Kenya. However, one country that is less known when it comes to bioinformatics is Ghana. Here, I provide a first description of the development of bioinformatics activities in Ghana and how these activities contribute to the overall development of the discipline in Africa. Over the past decade, scientists in Ghana have been involved in publications incorporating bioinformatics analyses, aimed at addressing research questions in biomedical science and agriculture. Scarce research funding and inadequate training opportunities are some of the challenges that need to be addressed for Ghanaian scientists to continue developing their expertise in bioinformatics.
Karikari, Thomas K
Until recently, bioinformatics, an important discipline in the biological sciences, was largely limited to countries with advanced scientific resources. Nonetheless, several developing countries have lately been making progress in bioinformatics training and applications. In Africa, leading countries in the discipline include South Africa, Nigeria, and Kenya. However, one country that is less known when it comes to bioinformatics is Ghana. Here, I provide a first description of the development of bioinformatics activities in Ghana and how these activities contribute to the overall development of the discipline in Africa. Over the past decade, scientists in Ghana have been involved in publications incorporating bioinformatics analyses, aimed at addressing research questions in biomedical science and agriculture. Scarce research funding and inadequate training opportunities are some of the challenges that need to be addressed for Ghanaian scientists to continue developing their expertise in bioinformatics.
An introductory bioinformatics laboratory experiment focused on protein analysis has been developed that is suitable for undergraduate students in introductory biochemistry courses. The laboratory experiment is designed to be potentially used as a "stand-alone" activity in which students are introduced to basic bioinformatics tools and…
Oakley, Mark T; Barthel, Daniel; Bykov, Yuri; Garibaldi, Jonathan M; Burke, Edmund K; Krasnogor, Natalio; Hirst, Jonathan D
Optimisation problems pervade structural bioinformatics. In this review, we describe recent work addressing a selection of bioinformatics challenges. We begin with a discussion of research into protein structure comparison, and highlight the utility of Kolmogorov complexity as a measure of structural similarity. We then turn to research into de novo protein structure prediction, in which structures are generated from first principles. In this endeavour, there is a compromise between the detail of the model and the extent to which the conformational space of the protein can be sampled. We discuss some developments in this area, including off-lattice structure prediction using the great deluge algorithm. One strategy to reduce the size of the search space is to restrict the protein chain to sites on a regular lattice. In this context, we highlight the use of memetic algorithms, which combine genetic algorithms with local optimisation, to the study of simple protein models on the two-dimensional square lattice and the face-centred cubic lattice.
Kang, K-L; Lee, S-W; Ahn, Y-S; Kim, S-H; Kang, Y-G
Analyzing responses of human periodontal ligament cells to mechanical stress and mechanotransduction is important for understanding periodontal tissue physiology and remodeling. It has been shown that the cellular response to mechanical stress can vary according to the type and duration of force and to extracellular attachment conditions. This study investigated the gene-expression profile of human periodontal ligament cells cultured in two-dimension (2D) and three-dimension (3D) conditions after application of compressive stress for 2 and 48 h. Human primary periodontal ligament cells were obtained from premolars extracted for orthodontic purposes. Cells were cultured in a conventional 2D culture dish or in 3D collagen gel and compressive stress was applied for 2 and 48 h. Control cells were cultured under identical conditions but without the application of compressive stress. After the application of compressive stress, total RNA was extracted and a cDNA microarray was performed. Microarray data were analyzed using statistical methods, including david and gene set enrichment analysis to identify significant signaling pathways. Real-time PCR was performed for five mRNAs in order to confirm the cDNA microarray results. The cDNA microarray analysis revealed that after application of compressive stress for 2 h, 191 and 553 genes showed changes in their expression levels in 2D and 3D cultured cells, respectively. After application of compressive stress for 48 h, 280 and 519 genes showed changes in their expression levels in 2D and 3D cultured cells, respectively. Euclidean clustering method was used to demonstrate the gene-expression kinetics. Analysis of the results showed that several signaling pathways, including the MAPK pathway and the focal adhesion kinase pathway are relevant to the compressive force-induced cellular response. 2D and 3D cultured cells showed significantly different gene-expression profiles, suggesting that cellular attachment to extracellular
Hao, Ling; Du, Boyu; Xi, Xueyan
Lung cancer is the leading cause of cancer-associated mortality worldwide and its prognosis is poor. Few effective biomarkers for non-small cell lung cancer (NSCLC) have been translated into the clinical practice aiming to assist in the treatment plan design and prognosis evaluation. The aim of the present study was to identify novel potential prognostic biomarkers for NSCLC. Tripartite motif 59 (TRIM59) was identified from a microarray dataset of matched-samples and was verified as an aberrantly upregulated gene in NSCLC tissue. The expression level of TRIM59 in NSCLC subtypes was observed to be significantly increased in large cell lung carcinoma and squamous cell carcinoma as compared with that in adenocarcinoma. Its expression correlated with several clinicopathological features, including gender, smoking habits, and unfavorable tumor node and pathological stages. Notably, TRIM59 demonstrated a negative correlation with survival time and its overexpression indicated a poor prognosis in NSCLC. Furthermore, univariate and multivariate Cox's regression analyses indicated that TRIM59 was an independent prognostic factor in tumor tissue as compared with age, gender, tumor stage, node stage, and metastasis. Gene set enrichment analysis and protein-protein interaction network construction revealed that TRIM59 was associated with oncogenic mammalian target of rapamycin (MTOR) and eukaryotic initiation factor 4E (EIF4E) signaling through ubiquitin C binding. In conclusion, it was revealed that TRIM59 is a novel prognostic biomarker modulating oncogenic MTOR and EIF4E signaling pathways in NSCLC. These findings provided a novel insight into the clinical application of TRIM59. Therefore, TRIM59 may serve as an independent predictor for prognosis and a potential therapeutic target for NSCLC.
Graña, Osvaldo; López-Fernández, Hugo; Fdez-Riverola, Florentino; González Pisano, David; Glez-Peña, Daniel
High-throughput sequencing of bisulfite-converted DNA is a technique used to measure DNA methylation levels. Although a considerable number of computational pipelines have been developed to analyze such data, none of them tackles all the peculiarities of the analysis together, revealing limitations that can force the user to manually perform additional steps needed for a complete processing of the data. This article presents bicycle, an integrated, flexible analysis pipeline for bisulfite sequencing data. Bicycle analyzes whole genome bisulfite sequencing data, targeted bisulfite sequencing data and hydroxymethylation data. To show how bicycle overtakes other available pipelines, we compared them on a defined number of features that are summarized in a table. We also tested bicycle with both simulated and real datasets, to show its level of performance, and compared it to different state-of-the-art methylation analysis pipelines. Bicycle is publicly available under GNU LGPL v3.0 license at http://www.sing-group.org/bicycle. Users can also download a customized Ubuntu LiveCD including bicycle and other bisulfite sequencing data pipelines compared here. In addition, a docker image with bicycle and its dependencies, which allows a straightforward use of bicycle in any platform (e.g. Linux, OS X or Windows), is also available. email@example.com or firstname.lastname@example.org. Supplementary data are available at Bioinformatics online.
Lima, Andre O. S.; Garces, Sergio P. S.
Bioinformatics is one of the fastest growing scientific areas over the last decade. It focuses on the use of informatics tools for the organization and analysis of biological data. An example of their importance is the availability nowadays of dozens of software programs for genomic and proteomic studies. Thus, there is a growing field (private…
Ranganathan, Shoba; Hsu, Wen-Lian; Yang, Ueng-Cheng; Tan, Tin Wee
The 2008 annual conference of the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation set up in 1998, was organized as the 7th International Conference on Bioinformatics (InCoB), jointly with the Bioinformatics and Systems Biology in Taiwan (BIT 2008) Conference, Oct. 20-23, 2008 at Taipei, Taiwan. Besides bringing together scientists from the field of bioinformatics in this region, InCoB is actively involving researchers from the area of systems biology, to facilitate greater synergy between these two groups. Marking the 10th Anniversary of APBioNet, this InCoB 2008 meeting followed on from a series of successful annual events in Bangkok (Thailand), Penang (Malaysia), Auckland (New Zealand), Busan (South Korea), New Delhi (India) and Hong Kong. Additionally, tutorials and the Workshop on Education in Bioinformatics and Computational Biology (WEBCB) immediately prior to the 20th Federation of Asian and Oceanian Biochemists and Molecular Biologists (FAOBMB) Taipei Conference provided ample opportunity for inducting mainstream biochemists and molecular biologists from the region into a greater level of awareness of the importance of bioinformatics in their craft. In this editorial, we provide a brief overview of the peer-reviewed manuscripts accepted for publication herein, grouped into thematic areas. As the regional research expertise in bioinformatics matures, the papers fall into thematic areas, illustrating the specific contributions made by APBioNet to global bioinformatics efforts.
Gao, Jia-Min; Huang, Lin-Zhen; Huang, Zhi-Guang; He, Rong-Quan
The clinicopathological value and exploration of the potential molecular mechanism of microRNA-183-5p (miR-183-5p) have been investigated in various cancers; however, to the best of the author's knowledge, no similar research has been reported for bladder cancer. In the present study, it was revealed that the expression level of miR-183-5p was notably increased in bladder cancer tissues compared with adjacent non-cancerous tissues (P=0.001) and was markedly increased in the tissue samples of papillary, pathological T stage (T0-T2) and pathological stage (I-II) compared with tissue samples of their counterparts (P=0.05), according to data from The Cancer Genome Atlas. Receiver operating characteristic analysis revealed the robust diagnostic value of miR-183-5p for distinguishing bladder cancer from non-cancerous bladder tissues (area under curve=0.948; 95% confidence interval: 0.919-0.977). Amplification and deep deletion of miR-183-5p were indicated by cBioPortal, accounting for 1% (4/412) of bladder cancer cases. Data from YM500v3 demonstrated that compared with other cancers, bladder cancer exhibited high expression levels of miR-183-5p, and miR-183-5p expression in primary solid tumors was much higher compared with solid normal tissues. A meta-analysis indicated that miR-183-5p was more highly expressed in bladder cancer samples compared with normal counterparts. A total of 88 potential target genes of miR-183-5p were identified, 13 of which were discerned as hub genes by protein-protein interaction. The epithelial-to-mesenchymal transition pathway was the most significantly enriched pathway by FunRich (P=0.0001). In summary, miR-183-5p may participate in the tumorigenesis and development of bladder cancer via certain signaling pathways, particularly the epithelial-to-mesenchymal transition pathway. However, the exact molecular mechanism of miR-183-5p in bladder cancer must be validated by in vitro and in vivo experiments.
Schneider, Maria V.; Walter, Peter; Blatter, Marie-Claude
Funding bodies are increasingly recognizing the need to provide graduates and researchers with access to short intensive courses in a variety of disciplines, in order both to improve the general skills base and to provide solid foundations on which researchers may build their careers. In response...... to the development of ‘high-throughput biology’, the need for training in the field of bioinformatics, in particular, is seeing a resurgence: it has been defined as a key priority by many Institutions and research programmes and is now an important component of many grant proposals. Nevertheless, when it comes...... to planning and preparing to meet such training needs, tension arises between the reward structures that predominate in the scientific community which compel individuals to publish or perish, and the time that must be devoted to the design, delivery and maintenance of high-quality training materials...
Heba F Alzan
Full Text Available Apicomplexa tick-borne hemoparasites, including Babesia bovis, Babesia microti, and Theileria equi are responsible for bovine and human babesiosis and equine theileriosis, respectively. These parasites of vast medical, epidemiological, and economic impact have complex life cycles in their vertebrate and tick hosts. Large gaps in knowledge concerning the mechanisms used by these parasites for gene regulation remain. Regulatory genes coding for DNA binding proteins such as members of the Api-AP2, HMG, and Myb families are known to play crucial roles as transcription factors. Although the repertoire of Api-AP2 has been defined and a HMG gene was previously identified in the B. bovis genome, these regulatory genes have not been described in detail in B. microti and T. equi. In this study, comparative bioinformatics was used to: (i identify and map genes encoding for these transcription factors among three parasites' genomes; (ii identify a previously unreported HMG gene in B. microti; (iii define a repertoire of eight conserved Myb genes; and (iv identify AP2 correlates among B. bovis and the better-studied Plasmodium parasites. Searching the available transcriptome of B. bovis defined patterns of transcription of these three gene families in B. bovis erythrocyte stage parasites. Sequence comparisons show conservation of functional domains and general architecture in the AP2, Myb, and HMG proteins, which may be significant for the regulation of common critical parasite life cycle transitions in B. bovis, B. microti, and T. equi. A detailed understanding of the role of gene families encoding DNA binding proteins will provide new tools for unraveling regulatory mechanisms involved in B. bovis, B. microti, and T. equi life cycles and environmental adaptive responses and potentially contributes to the development of novel convergent strategies for improved control of babesiosis and equine piroplasmosis.
Linda E. Kippner
Full Text Available Single-cell analysis has the potential to provide us with a host of new knowledge about biological systems, but it comes with the challenge of correctly interpreting the biological information. While emerging techniques have made it possible to measure inter-cellular variability at the transcriptome level, no consensus yet exists on the most appropriate method of data analysis of such single cell data. Methods for analysis of transcriptional data at the population level are well established but are not well suited to single cell analysis due to their dependence on population averages. In order to address this question, we have systematically tested combinations of methods for primary data analysis on single cell transcription data generated from two types of primary immune cells, neutrophils and T lymphocytes. Cells were obtained from healthy individuals, and single cell transcript expression data was obtained by a combination of single cell sorting and nanoscale quantitative real time PCR (qRT-PCR for markers of cell type, intracellular signaling, and immune functionality. Gene expression analysis was focused on hierarchical clustering to determine the existence of cellular subgroups within the populations. Nine combinations of criteria for data exclusion and normalization were tested and evaluated. Bimodality in gene expression indicated the presence of cellular subgroups which were also revealed by data clustering. We observed evidence for two clearly defined cellular subtypes in the neutrophil populations and at least two in the T lymphocyte populations. When normalizing the data by different methods, we observed varying outcomes with corresponding interpretations of the biological characteristics of the cell populations. Normalization of the data by linear standardization taking into account technical effects such as plate effects, resulted in interpretations that most closely matched biological expectations. Single cell transcription
Kilaparty, Surya P; Singh, Awantika; Baltosser, William H; Ali, Nawab
Multiple inositol polyphosphate phosphatase 1 (Minpp1) in higher organisms dephosphorylates InsP6, the most abundant inositol phosphate. It also dephosphorylates less phosphorylated InsP5 and InsP4 and more phosphorylated InsP7 or InsP8. Minpp1 is classified as a member of the histidine acid phosphatase super family of proteins with functional resemblance to phytases found in lower organisms. This study took a bioinformatics approach to explore the extent of evolutionary diversification in Minpp1 structure and function in order to understand its physiological relevance in higher organisms. The human Minpp1 amino acid (AA) sequence was BLAST searched against available national protein databases. Phylogenetic analysis revealed that Minpp1 was widely distributed from lower to higher organisms. Further, we have identified that there exist four isoforms of Minpp1. Multiple computational tools were used to identify key functional motifs and their conservation among various species. Analyses showed that certain motifs predominant in higher organisms were absent in lower organisms. Variation in AA sequences within motifs was also analyzed. We found that there is diversification of key motifs and thus their functions present in Minpp1 from lower organisms to higher organisms. Another interesting result of this analysis was the presence of a glucose-1-phosphate interaction site in Minpp1; the functional significance of which has yet to be determined experimentally. The overall findings of our study point to an evolutionary adaptability of Minpp1 functions from lower to higher life forms.
Ikegami, Keisuke; Yoshimura, Takashi
Animals utilize photoperiodic changes as a calendar to regulate seasonal reproduction. Birds have highly sophisticated photoperiodic mechanisms and functional genomics analysis in quail uncovered the signal transduction pathway regulating avian seasonal reproduction. Birds detect light with deep brain photoreceptors. Long day (LD) stimulus induces secretion of thyroid-stimulating hormone (TSH) from the pars tuberalis (PT) of the pituitary gland. PT-derived TSH locally activates thyroid hormone (TH) in the hypothalamus, which induces gonadotropin-releasing hormone (GnRH) and hence gonadotropin secretion. However, during winter, low temperatures increase serum TH for adaptive thermogenesis, which accelerates germ cell apoptosis by activating the genes involved in metamorphosis. Therefore, TH has a dual role in the regulation of seasonal reproduction. Studies using TSH receptor knockout mice confirmed the involvement of PT-derived TSH in mammalian seasonal reproduction. In addition, studies in mice revealed that the tissue-specific glycosylation of TSH diversifies its function in the circulation to avoid crosstalk. In contrast to birds and mammals, one of the molecular machineries necessary for the seasonal reproduction of fish are localized in the saccus vasculosus from the photoreceptor to the neuroendocrine output. Thus, comparative analysis is a powerful tool to uncover the universality and diversity of fundamental properties in various organisms. Copyright © 2015 Elsevier Inc. All rights reserved.
Full Text Available The purpose of this paper is to present a general view of the current applications of fuzzy logic in medicine and bioinformatics. We particularly review the medical literature using fuzzy logic. We then recall the geometrical interpretation of fuzzy sets as points in a fuzzy hypercube and present two concrete illustrations in medicine (drug addictions and in bioinformatics (comparison of genomes.
Bioinformatics is a scientific discipline that applies computer science and information technology to help understand biological processes. The NIH provides a list of free online bioinformatics tutorials, either generated by the NIH Library or other institutes, which includes introductory lectures and "how to" videos on using various tools.
This article describes a new approach to teaching bioinformatics using "Arabidopsis" genetic sequences. Several open-ended and inquiry-based laboratory exercises have been designed to help students grasp key concepts and gain practical skills in bioinformatics, using "Arabidopsis" leucine-rich repeat receptor-like kinase (LRR…
Heyer, Laurie J.
This article describes the sequence alignment problem in bioinformatics. Through examples, we formulate sequence alignment as an optimization problem and show how to compute the optimal alignment with dynamic programming. The examples and sample exercises have been used by the author in a specialized course in bioinformatics, but could be adapted…
Structural bioinformatics is concerned with the molecular structure of biomacromolecules on a genomic scale, using computational methods. Classic problems in structural bioinformatics include the prediction of protein and RNA structure from sequence, the design of artificial proteins or enzymes, and the automated analysis and comparison of biomacromolecules in atomic detail. The determination of macromolecular structure from experimental data (for example coming from nuclear magnetic resonance, X-ray crystallography or small angle X-ray scattering) has close ties with the field of structural bioinformatics. Recently, probabilistic models and machine learning methods based on Bayesian principles are providing efficient and rigorous solutions to challenging problems that were long regarded as intractable. In this review, I will highlight some important recent developments in the prediction, analysis and experimental determination of macromolecular structure that are based on such methods. These developments include generative models of protein structure, the estimation of the parameters of energy functions that are used in structure prediction, the superposition of macromolecules and structure determination methods that are based on inference. Although this review is not exhaustive, I believe the selected topics give a good impression of the exciting new, probabilistic road the field of structural bioinformatics is taking.
Harris, Nomi L; Cock, Peter J A; Chapman, Brad; Fields, Christopher J; Hokamp, Karsten; Lapp, Hilmar; Muñoz-Torres, Monica; Wiencko, Heather
Message from the ISCB: The Bioinformatics Open Source Conference (BOSC) is a yearly meeting organized by the Open Bioinformatics Foundation (OBF), a non-profit group dedicated to promoting the practice and philosophy of Open Source software development and Open Science within the biological research community. BOSC has been run since 2000 as a two-day Special Interest Group (SIG) before the annual ISMB conference. The 17th annual BOSC ( http://www.open-bio.org/wiki/BOSC_2016) took place in Orlando, Florida in July 2016. As in previous years, the conference was preceded by a two-day collaborative coding event open to the bioinformatics community. The conference brought together nearly 100 bioinformatics researchers, developers and users of open source software to interact and share ideas about standards, bioinformatics software development, and open and reproducible science.
Chakraborty, Chiranjib; George Priya Doss, C; Zhu, Hailong; Agoramoorthy, Govindasamy
Hong Kong's bioinformatics sector is attaining new heights in combination with its economic boom and the predominance of the working-age group in its population. Factors such as a knowledge-based and free-market economy have contributed towards a prominent position on the world map of bioinformatics. In this review, we have considered the educational measures, landmark research activities and the achievements of bioinformatics companies and the role of the Hong Kong government in the establishment of bioinformatics as strength. However, several hurdles remain. New government policies will assist computational biologists to overcome these hurdles and further raise the profile of the field. There is a high expectation that bioinformatics in Hong Kong will be a promising area for the next generation.
Full Text Available Voltage-gated calcium channels (VGCCs are well documented to play roles in cell proliferation, migration, and apoptosis; however, whether VGCCs regulate the onset and progression of cancer is still under investigation. The VGCC family consists of five members, which are L-type, N-type, T-type, R-type and P/Q type. To date, no holistic approach has been used to screen VGCC family genes in different types of cancer. We analyzed the transcript expression of VGCCs in clinical cancer tissue samples by accessing ONCOMINE (www.oncomine.org, a web-based microarray database, to perform a systematic analysis. Every member of the VGCCs was examined across 21 different types of cancer by comparing mRNA expression in cancer to that in normal tissue. A previous study showed that altered expression of mRNA in cancer tissue may play an oncogenic role and promote tumor development; therefore, in the present findings, we focus only on the overexpression of VGCCs in different types of cancer. This bioinformatics analysis revealed that different subtypes of VGCCs (CACNA1C, CACNA1D, CACNA1B, CACNA1G, and CACNA1I are implicated in the development and progression of diverse types of cancer and show dramatic up-regulation in breast cancer. CACNA1F only showed high expression in testis cancer, whereas CACNA1A, CACNA1C, and CACNA1D were highly expressed in most types of cancer. The current analysis revealed that specific VGCCs likely play essential roles in specific types of cancer. Collectively, we identified several VGCC targets and classified them according to different cancer subtypes for prospective studies on the underlying carcinogenic mechanisms. The present findings suggest that VGCCs are possible targets for prospective investigation in cancer treatment.
Wang, Chih-Yang; Lai, Ming-Derg; Phan, Nam Nhut; Sun, Zhengda; Lin, Yen-Chang
Voltage-gated calcium channels (VGCCs) are well documented to play roles in cell proliferation, migration, and apoptosis; however, whether VGCCs regulate the onset and progression of cancer is still under investigation. The VGCC family consists of five members, which are L-type, N-type, T-type, R-type and P/Q type. To date, no holistic approach has been used to screen VGCC family genes in different types of cancer. We analyzed the transcript expression of VGCCs in clinical cancer tissue samples by accessing ONCOMINE (www.oncomine.org), a web-based microarray database, to perform a systematic analysis. Every member of the VGCCs was examined across 21 different types of cancer by comparing mRNA expression in cancer to that in normal tissue. A previous study showed that altered expression of mRNA in cancer tissue may play an oncogenic role and promote tumor development; therefore, in the present findings, we focus only on the overexpression of VGCCs in different types of cancer. This bioinformatics analysis revealed that different subtypes of VGCCs (CACNA1C, CACNA1D, CACNA1B, CACNA1G, and CACNA1I) are implicated in the development and progression of diverse types of cancer and show dramatic up-regulation in breast cancer. CACNA1F only showed high expression in testis cancer, whereas CACNA1A, CACNA1C, and CACNA1D were highly expressed in most types of cancer. The current analysis revealed that specific VGCCs likely play essential roles in specific types of cancer. Collectively, we identified several VGCC targets and classified them according to different cancer subtypes for prospective studies on the underlying carcinogenic mechanisms. The present findings suggest that VGCCs are possible targets for prospective investigation in cancer treatment. PMID:26147197
Cohen Kadosh, Roi; Gevers, Wim; Notebaert, Wim
Automatic processing of irrelevant stimulus dimensions has been demonstrated in a variety of tasks. Previous studies have shown that conflict between relevant and irrelevant dimensions can be reduced when a feature of the irrelevant dimension is repeated. The specific level at which the automatic process is suppressed (e.g., perceptual repetition, response repetition), however, is less understood. In the current experiment we used the numerical Stroop paradigm, in which the processing of irrelevant numerical values of 2 digits interferes with the processing of their physical size, to pinpoint the precise level of the suppression. Using a sequential analysis, we dissociated perceptual repetition from response repetition of the relevant and irrelevant dimension. Our analyses of reaction times, error rates, and diffusion modeling revealed that the congruity effect is significantly reduced or even absent when the response sequence of the irrelevant dimension, rather than the numerical value or the physical size, is repeated. These results suggest that automatic activation of the irrelevant dimension is suppressed at the response level. The current results shed light on the level of interaction between numerical magnitude and physical size as well as the effect of variability of responses and stimuli on automatic processing. (c) 2011 APA, all rights reserved.
Rocha, Miguel; Fdez-Riverola, Florentino; Paz, Juan
This proceedings presents recent practical applications of Computational Biology and Bioinformatics. It contains the proceedings of the 9th International Conference on Practical Applications of Computational Biology & Bioinformatics held at University of Salamanca, Spain, at June 3rd-5th, 2015. The International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB) is an annual international meeting dedicated to emerging and challenging applied research in Bioinformatics and Computational Biology. Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis o...
Tian, Yunhong; Tian, Yunming; Luo, Xiaojun; Zhou, Tao; Huang, Zuoping; Liu, Ying; Qiu, Yihan; Hou, Bing; Sun, Dan; Deng, Hongyu; Qian, Shen; Yao, Kaitai
MicroRNAs (miRNAs) are a new class of endogenous regulators of a broad range of physiological processes, which act by regulating gene expression post-transcriptionally. The brassica vegetable, broccoli (Brassica oleracea var. italica), is very popular with a wide range of consumers, but environmental stresses such as salinity are a problem worldwide in restricting its growth and yield. Little is known about the role of miRNAs in the response of broccoli to salt stress. In this study, broccoli subjected to salt stress and broccoli grown under control conditions were analyzed by high-throughput sequencing. Differential miRNA expression was confirmed by real-time reverse transcription polymerase chain reaction (RT-PCR). The prediction of miRNA targets was undertaken using the Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology (KO) database and Gene Ontology (GO)-enrichment analyses. Two libraries of small (or short) RNAs (sRNAs) were constructed and sequenced by high-throughput Solexa sequencing. A total of 24,511,963 and 21,034,728 clean reads, representing 9,861,236 (40.23%) and 8,574,665 (40.76%) unique reads, were obtained for control and salt-stressed broccoli, respectively. Furthermore, 42 putative known and 39 putative candidate miRNAs that were differentially expressed between control and salt-stressed broccoli were revealed by their read counts and confirmed by the use of stem-loop real-time RT-PCR. Amongst these, the putative conserved miRNAs, miR393 and miR855, and two putative candidate miRNAs, miR3 and miR34, were the most strongly down-regulated when broccoli was salt-stressed, whereas the putative conserved miRNA, miR396a, and the putative candidate miRNA, miR37, were the most up-regulated. Finally, analysis of the predicted gene targets of miRNAs using the GO and KO databases indicated that a range of metabolic and other cellular functions known to be associated with salt stress were up-regulated in broccoli treated with salt. A comprehensive
Ditty, Jayna L.; Kvaal, Christopher A.; Goodner, Brad; Freyermuth, Sharyn K.; Bailey, Cheryl; Britton, Robert A.; Gordon, Stuart G.; Heinhorst, Sabine; Reed, Kelynne; Xu, Zhaohui; Sanders-Lorenz, Erin R.; Axen, Seth; Kim, Edwin; Johns, Mitrick; Scott, Kathleen; Kerfeld, Cheryl A.
into courses or independent research projects requires infrastructure for organizing and assessing student work. Here, we present a new platform for faculty to keep current with the rapidly changing field of bioinformatics, the Integrated Microbial Genomes Annotation Collaboration Toolkit (IMG-ACT). It was developed by instructors from both research-intensive and predominately undergraduate institutions in collaboration with the Department of Energy-Joint Genome Institute (DOE-JGI) as a means to innovate and update undergraduate education and faculty development. The IMG-ACT program provides a cadre of tools, including access to a clearinghouse of genome sequences, bioinformatics databases, data storage, instructor course management, and student notebooks for organizing the results of their bioinformatic investigations. In the process, IMG-ACT makes it feasible to provide undergraduate research opportunities to a greater number and diversity of students, in contrast to the traditional mentor-to-student apprenticeship model for undergraduate research, which can be too expensive and time-consuming to provide for every undergraduate. The IMG-ACT serves as the hub for the network of faculty and students that use the system for microbial genome analysis. Open access of the IMG-ACT infrastructure to participating schools ensures that all types of higher education institutions can utilize it. With the infrastructure in place, faculty can focus their efforts on the pedagogy of bioinformatics, involvement of students in research, and use of this tool for their own research agenda. What the original faculty members of the IMG-ACT development team present here is an overview of how the IMG-ACT program has affected our development in terms of teaching and research with the hopes that it will inspire more faculty to get involved.
Full Text Available Although the beneficial effects of acupuncture in asthma treatment have been well documented, little is known regarding the biological basis of this treatment. Changes in the lung proteome of acupuncture-treated rats with asthma onset were comparatively analyzed using a two-dimensional gel electrophoresis (2DE and mass-spectrometry- (MS- based proteomic approach. Acupuncture on specific acupuncture points appeared to improve respiratory function and reduce the total number of leukocytes and eosinophils in bronchoalveolar lavage fluid in OVA-induced asthma onset. Image analysis of 2DE gels revealed 32 differentially expressed acupuncture-specific protein spots in asthma onset; 30 of which were successfully identified as 28 unique proteins using LC-MS/MS. Bioinformatic analyses indicated that these altered proteins are most likely involved in inflammation-related biological functions, and the functional associations of these proteins result in an inflammation signaling pathway. Acupuncture regulates the pathway at different levels by regulating several key nodal proteins, including downregulating of proinflammatory proteins (e.g., S100A8, RAGE, and S100A11 and upregulating of anti-inflammatory proteins (e.g., CC10, ANXA5, and sRAGE. These deregulated inflammation-related proteins may mediate, at least in part, the antiasthmatic effect of acupuncture. Further functional investigation of these acupuncture-specific effector proteins could identify new drug candidates for the prophylaxis and treatment of asthma.
Cazals, Frédéric; Dreyfus, Tom
Software in structural bioinformatics has mainly been application driven. To favor practitioners seeking off-the-shelf applications, but also developers seeking advanced building blocks to develop novel applications, we undertook the design of the Structural Bioinformatics Library ( SBL , http://sbl.inria.fr ), a generic C ++/python cross-platform software library targeting complex problems in structural bioinformatics. Its tenet is based on a modular design offering a rich and versatile framework allowing the development of novel applications requiring well specified complex operations, without compromising robustness and performances. The SBL involves four software components (1-4 thereafter). For end-users, the SBL provides ready to use, state-of-the-art (1) applications to handle molecular models defined by unions of balls, to deal with molecular flexibility, to model macro-molecular assemblies. These applications can also be combined to tackle integrated analysis problems. For developers, the SBL provides a broad C ++ toolbox with modular design, involving core (2) algorithms , (3) biophysical models and (4) modules , the latter being especially suited to develop novel applications. The SBL comes with a thorough documentation consisting of user and reference manuals, and a bugzilla platform to handle community feedback. The SBL is available from http://sbl.inria.fr. Frederic.Cazals@inria.fr. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: email@example.com
Suplatov, Dmitry; Voevodin, Vladimir; Švedas, Vytas
The ability of proteins and enzymes to maintain a functionally active conformation under adverse environmental conditions is an important feature of biocatalysts, vaccines, and biopharmaceutical proteins. From an evolutionary perspective, robust stability of proteins improves their biological fitness and allows for further optimization. Viewed from an industrial perspective, enzyme stability is crucial for the practical application of enzymes under the required reaction conditions. In this review, we analyze bioinformatic-driven strategies that are used to predict structural changes that can be applied to wild type proteins in order to produce more stable variants. The most commonly employed techniques can be classified into stochastic approaches, empirical or systematic rational design strategies, and design of chimeric proteins. We conclude that bioinformatic analysis can be efficiently used to study large protein superfamilies systematically as well as to predict particular structural changes which increase enzyme stability. Evolution has created a diversity of protein properties that are encoded in genomic sequences and structural data. Bioinformatics has the power to uncover this evolutionary code and provide a reproducible selection of hotspots - key residues to be mutated in order to produce more stable and functionally diverse proteins and enzymes. Further development of systematic bioinformatic procedures is needed to organize and analyze sequences and structures of proteins within large superfamilies and to link them to function, as well as to provide knowledge-based predictions for experimental evaluation. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Deepti D. Deobagkar
Full Text Available Bioinformatics software and visualisation tools have been a key factor in the rapid and phenomenal advances in genomics, proteomics, medicine, drug discovery, systems approaches and in fact in every area of new development. Indian scientists have also made a mark in a few specific areas. India has an advantage of an early start and extensive and organised network in the Bioinformatics education and research with substantial inputs from the Indian government. India has a strong hold in computation and IT and has a pool of bright and young talent with demographic dividend along with experienced and excellent mentors and researchers. Although small in number and scale, Bioinformatics Industry also has a presence and is making its mark in India. There are a number of high throughput and extremely useful resources available which are critical in biological data analysis and interpretation. This has made a paradigm shift in the way research can be carried out and discoveries can be made in any area of biological, biochemical and chemical research. This article summarises the current status and contributions from India in the development of software and web servers for Bioinformatics applications.
Full Text Available BACKGROUND: The leatherback turtle (Dermochelys coriacea has undergone a dramatic decline over the last 25 years, and this is believed to be primarily the result of mortality associated with fisheries bycatch followed by egg and nesting female harvest. Atlantic leatherback turtles undertake long migrations across ocean basins from subtropical and tropical nesting beaches to productive frontal areas. Migration between two nesting seasons can last 2 or 3 years, a time period termed the remigration interval (RI. Recent satellite transmitter data revealed that Atlantic leatherbacks follow two major dispersion patterns after nesting season, through the North Gulf Stream area or more eastward across the North Equatorial Current. However, information on the whole RI is lacking, precluding the accurate identification of feeding areas where conservation measures may need to be applied. METHODOLOGY/PRINCIPAL FINDINGS: Using stable isotopes as dietary tracers we determined the characteristics of feeding grounds of leatherback females nesting in French Guiana. During migration, 3-year RI females differed from 2-year RI females in their isotope values, implying differences in their choice of feeding habitats (offshore vs. more coastal and foraging latitude (North Atlantic vs. West African coasts, respectively. Egg-yolk and blood isotope values are correlated in nesting females, indicating that egg analysis is a useful tool for assessing isotope values in these turtles, including adults when not available. CONCLUSIONS/SIGNIFICANCE: Our results complement previous data on turtle movements during the first year following the nesting season, integrating the diet consumed during the year before nesting. We suggest that the French Guiana leatherback population segregates into two distinct isotopic groupings, and highlight the urgent need to determine the feeding habitats of the turtle in the Atlantic in order to protect this species from incidental take by
Full Text Available Yellowstone National Park is home to one of the only plains bison populations that have continuously existed on their present landscape since prehistoric times without evidence of domestic cattle introgression. Previous studies characterized the relatively high levels of nuclear genetic diversity in these bison, but little is known about their mitochondrial haplotype diversity. This study assessed mitochondrial genomes from 25 randomly selected Yellowstone bison and found 10 different mitochondrial haplotypes with a haplotype diversity of 0.78 (± 0.06. Spatial analysis of these mitochondrial DNA (mtDNA haplotypes did not detect geographic population subdivision (FST = -0.06, p = 0.76. However, we identified two independent and historically important lineages in Yellowstone bison by combining data from 65 bison (defined by 120 polymorphic sites from across North America representing a total of 30 different mitochondrial DNA haplotypes. Mitochondrial DNA haplotypes from one of the Yellowstone lineages represent descendants of the 22 indigenous bison remaining in central Yellowstone in 1902. The other mitochondrial DNA lineage represents descendants of the 18 females introduced from northern Montana in 1902 to supplement the indigenous bison population and develop a new breeding herd in the northern region of the park. Comparing modern and historical mitochondrial DNA diversity in Yellowstone bison helps uncover a historical context of park restoration efforts during the early 1900s, provides evidence against a hypothesized mitochondrial disease in bison, and reveals the signature of recent hybridization between American plains bison (Bison bison bison and Canadian wood bison (B. b. athabascae. Our study demonstrates how mitochondrial DNA can be applied to delineate the history of wildlife species and inform future conservation actions.
Fan, Jing; Ye, Jiangbin; Kamphorst, Jurre J.; Shlomi, Tomer; Thompson, Craig B.; Rabinowitz, Joshua D.
ATP is the dominant energy source in animals for mechanical and electrical work (for example, muscle contraction or neuronal firing). For chemical work, there is an equally important role for NADPH, which powers redox defence and reductive biosynthesis. The most direct route to produce NADPH from glucose is the oxidative pentose phosphate pathway, with malic enzyme sometimes also important. Although the relative contribution of glycolysis and oxidative phosphorylation to ATP production has been extensively analysed, similar analysis of NADPH metabolism has been lacking. Here we demonstrate the ability to directly track, by liquid chromatography-mass spectrometry, the passage of deuterium from labelled substrates into NADPH, and combine this approach with carbon labelling and mathematical modelling to measure NADPH fluxes. In proliferating cells, the largest contributor to cytosolic NADPH is the oxidative pentose phosphate pathway. Surprisingly, a nearly comparable contribution comes from serine-driven one-carbon metabolism, in which oxidation of methylene tetrahydrofolate to 10-formyl-tetrahydrofolate is coupled to reduction of NADP+ to NADPH. Moreover, tracing of mitochondrial one-carbon metabolism revealed complete oxidation of 10-formyl-tetrahydrofolate to make NADPH. As folate metabolism has not previously been considered an NADPH producer, confirmation of its functional significance was undertaken through knockdown of methylenetetrahydrofolate dehydrogenase (MTHFD) genes. Depletion of either the cytosolic or mitochondrial MTHFD isozyme resulted in decreased cellular NADPH/NADP+ and reduced/oxidized glutathione ratios (GSH/GSSG) and increased cell sensitivity to oxidative stress. Thus, although the importance of folate metabolism for proliferating cells has been long recognized and attributed to its function of producing one-carbon units for nucleic acid synthesis, another crucial function of this pathway is generating reducing power.
Fatumo, Segun A.; Adoga, Moses P.; Ojo, Opeolu O.; Oluwagbemi, Olugbenga; Adeoye, Tolulope; Ewejobi, Itunuoluwa; Adebiyi, Marion; Adebiyi, Ezekiel; Bewaji, Clement; Nashiru, Oyekanmi
Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries. PMID:24763310
Segun A Fatumo
Full Text Available Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries.
Fatumo, Segun A; Adoga, Moses P; Ojo, Opeolu O; Oluwagbemi, Olugbenga; Adeoye, Tolulope; Ewejobi, Itunuoluwa; Adebiyi, Marion; Adebiyi, Ezekiel; Bewaji, Clement; Nashiru, Oyekanmi
Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries.
This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty models with structural dispersion, just to mention two examples. The contributors include distinguished international statisticians such as Philip Hougaard, John Hinde, Il Do Ha, Roger Payne and Alessandra Durio, among others, as well as promising newcomers. Some of the contributions have come from researchers working in the BIO-SI research programme on Biostatistics and Bioinformatics, centred on the Universities of Limerick and Galway in Ireland and fu...
Zhou, Shuigeng; Liao, Ruiqi; Guan, Jihong
In the past decades, with the rapid development of high-throughput technologies, biology research has generated an unprecedented amount of data. In order to store and process such a great amount of data, cloud computing and MapReduce were applied to many fields of bioinformatics. In this paper, we first introduce the basic concepts of cloud computing and MapReduce, and their applications in bioinformatics. We then highlight some problems challenging the applications of cloud computing and MapReduce to bioinformatics. Finally, we give a brief guideline for using cloud computing in biology research.
Audoux, Jérôme; Salson, Mikaël; Grosset, Christophe F; Beaumeunier, Sacha; Holder, Jean-Marc; Commes, Thérèse; Philippe, Nicolas
The evolution of next-generation sequencing (NGS) technologies has led to increased focus on RNA-Seq. Many bioinformatic tools have been developed for RNA-Seq analysis, each with unique performance characteristics and configuration parameters. Users face an increasingly complex task in understanding which bioinformatic tools are best for their specific needs and how they should be configured. In order to provide some answers to these questions, we investigate the performance of leading bioinformatic tools designed for RNA-Seq analysis and propose a methodology for systematic evaluation and comparison of performance to help users make well informed choices. To evaluate RNA-Seq pipelines, we developed a suite of two benchmarking tools. SimCT generates simulated datasets that get as close as possible to specific real biological conditions accompanied by the list of genomic incidents and mutations that have been inserted. BenchCT then compares the output of any bioinformatics pipeline that has been run against a SimCT dataset with the simulated genomic and transcriptional variations it contains to give an accurate performance evaluation in addressing specific biological question. We used these tools to simulate a real-world genomic medicine question s involving the comparison of healthy and cancerous cells. Results revealed that performance in addressing a particular biological context varied significantly depending on the choice of tools and settings used. We also found that by combining the output of certain pipelines, substantial performance improvements could be achieved. Our research emphasizes the importance of selecting and configuring bioinformatic tools for the specific biological question being investigated to obtain optimal results. Pipeline designers, developers and users should include benchmarking in the context of their biological question as part of their design and quality control process. Our SimBA suite of benchmarking tools provides a reliable basis
Stringer-Calvert David WJ
Full Text Available Abstract Background This article addresses the problem of interoperation of heterogeneous bioinformatics databases. Results We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. Conclusion BioWarehouse embodies significant progress on the
Rezig, Slim; Sakhri, Saber
Salmonellas are the main responsible agent for the frequent food-borne gastrointestinal diseases. Their detection using classical methods are laborious and their results take a lot of time to be revealed. In this context, we tried to set up a revealing technique of the invA virulence gene, found in the majority of Salmonella species. After amplification with PCR using specific primers created and verified by bioinformatics programs, two couples of primers were set up and they appeared to be very specific and sensitive for the detection of invA gene. (Author)
Pathak, Ashish; Chauhan, Ashvini; Blom, Jochen; Indest, Karl J; Jung, Carina M; Stothard, Paul; Bera, Gopal; Green, Stefan J; Ogram, Andrew
The genome of Rhodococcus opacus strain M213, isolated from a fuel-oil contaminated soil, was sequenced and annotated which revealed a genome size of 9,194,165 bp encoding 8680 putative genes and a G+C content of 66.72%. Among the protein coding genes, 71.77% were annotated as clusters of orthologous groups of proteins (COGs); 55% of the COGs were present as paralog clusters. Pulsed field gel electrophoresis (PFGE) analysis of M213 revealed the presence of three different sized replicons- a circular chromosome and two megaplasmids (pNUO1 and pNUO2) estimated to be of 750Kb 350Kb in size, respectively. Conversely, using an alternative approach of optical mapping, the plasmid replicons appeared as a circular ~1.2 Mb megaplasmid and a linear, ~0.7 Mb megaplasmid. Genome-wide comparative analysis of M213 with a cohort of sequenced Rhodococcus species revealed low syntenic affiliation with other R. opacus species including strains B4 and PD630. Conversely, a closer affiliation of M213, at the functional (COG) level, was observed with the catabolically versatile R. jostii strain RHA1 and other Rhodococcii such as R. wratislaviensis strain IFP 2016, R. imtechensis strain RKJ300, Rhodococcus sp. strain JVH1, and Rhodococcus sp. strain DK17, respectively. An in-depth, genome-wide comparison between these functional relatives revealed 971 unique genes in M213 representing 11% of its total genome; many associating with catabolic functions. Of major interest was the identification of as many as 154 genomic islands (GEIs), many with duplicated catabolic genes, in particular for PAHs; a trait that was confirmed by PCR-based identification of naphthalene dioxygenase (NDO) as a representative gene, across PFGE-resolved replicons of strain M213. Interestingly, several plasmid/GEI-encoded genes, that likely participate in degrading naphthalene (NAP) via a peculiar pathway, were also identified in strain M213 using a combination of bioinformatics, metabolic analysis and gene
Melero, Juan L; Andrades, Sergi; Arola, Lluís; Romeu, Antoni
Psoriasis is an immune-mediated, inflammatory and hyperproliferative disease of the skin and joints. The cause of psoriasis is still unknown. The fundamental feature of the disease is the hyperproliferation of keratinocytes and the recruitment of cells from the immune system in the region of the affected skin, which leads to deregulation of many well-known gene expressions. Based on data mining and bioinformatic scripting, here we show a new dimension of the effect of psoriasis at the genomic level. Using our own pipeline of scripts in Perl and MySql and based on the freely available NCBI Gene Expression Omnibus (GEO) database: DataSet Record GDS4602 (Series GSE13355), we explore the extent of the effect of psoriasis on gene expression in the affected tissue. We give greater insight into the effects of psoriasis on the up-regulation of some genes in the cell cycle (CCNB1, CCNA2, CCNE2, CDK1) or the dynamin system (GBPs, MXs, MFN1), as well as the down-regulation of typical antioxidant genes (catalase, CAT; superoxide dismutases, SOD1-3; and glutathione reductase, GSR). We also provide a complete list of the human genes and how they respond in a state of psoriasis. Our results show that psoriasis affects all chromosomes and many biological functions. If we further consider the stable and mitotically inheritable character of the psoriasis phenotype, and the influence of environmental factors, then it seems that psoriasis has an epigenetic origin. This fit well with the strong hereditary character of the disease as well as its complex genetic background. Copyright © 2017 Japanese Society for Investigative Dermatology. Published by Elsevier B.V. All rights reserved.
Vetrivel, Umashankar; Pilla, Kalabharath
Historically, live linux distributions for Bioinformatics have paved way for portability of Bioinformatics workbench in a platform independent manner. Moreover, most of the existing live Linux distributions limit their usage to sequence analysis and basic molecular visualization programs and are devoid of data persistence. Hence, open discovery - a live linux distribution has been developed with the capability to perform complex tasks like molecular modeling, docking and molecular dynamics in a swift manner. Furthermore, it is also equipped with complete sequence analysis environment and is capable of running windows executable programs in Linux environment. Open discovery portrays the advanced customizable configuration of fedora, with data persistency accessible via USB drive or DVD. The Open Discovery is distributed free under Academic Free License (AFL) and can be downloaded from http://www.OpenDiscovery.org.in.
López, Vivian F.; Aguilar, Ramiro; Alonso, Luis; Moreno, María N.; Corchado, Juan M.
In this paper we describe both theoretical and practical results of a novel data mining process that combines hybrid techniques of association analysis and classical sequentiation algorithms of genomics to generate grammatical structures of a specific language. We used an application of a compilers generator system that allows the development of a practical application within the area of grammarware, where the concepts of the language analysis are applied to other disciplines, such as Bioinformatic. The tool allows the complexity of the obtained grammar to be measured automatically from textual data. A technique of incremental discovery of sequential patterns is presented to obtain simplified production rules, and compacted with bioinformatics criteria to make up a grammar.
RNA expression analysis was performed on the corpus luteum tissue at five time points after prostaglandin F2 alpha treatment of midcycle cows using an Affymetrix Bovine Gene v1 Array. The normalized linear microarray data was uploaded to the NCBI GEO repository (GSE94069). Subsequent statistical ana...
Full Text Available The present study depicted the role of silicon in limiting the hyperhydricity in shoot cultures of carnation through proteomic analysis. Four-week-old healthy shoot cultures of carnation “Purple Beauty” were sub-cultured on Murashige and Skoog medium followed with four treatments, viz. control (–Si/–Hyperhydricity, hyperhydric with no silicon treatment (–Si/+Hyperhydricity, hyperhydric with silicon treatment (+Si/+Hyperhydricity, and only silicon treated with no hyperhydricity (+Si/–Hyperhydricity. Comparing to control morphological features of hyperhydric carnations showed significantly fragile, bushy and lustrous leaf nature, while Si supply restored these effects. Proteomic investigation revealed that approximately seventy protein spots were differentially expressed under Si and/or hyperhydric treatments and were either up- or downregulated in abundance depending on their functions. Most of the identified protein spots were related to stress responses, photosynthesis, and signal transduction. Proteomic results were further confirmed through immunoblots by selecting specific proteins such as superoxide dismutase (SOD, ascorbate peroxidase (APX, catalase (CAT, PsaA, and PsbA. Moreover, protein–protein interaction was also performed on differentially expressed protein spots using specific bioinformatic tools. In addition, stress markers were analyzed by histochemical localization of hydrogen peroxide (H2O2 and singlet oxygen (O21–. In addition, the ultrastructure of chloroplasts in hyperhydric leaves significantly resulted in inefficiency of thylakoid lamella with the loss of grana but were recovered in silicon supplemented leaves. The proteomic study together with physiological analysis indicated that Si has a substantial role in upholding the hyperhydricity in in vitro grown carnation shoot cultures.
Zhang, Ming; Lv, Dongwen; Ge, Pei; Bian, Yanwei; Chen, Guanxing; Zhu, Gengrui; Li, Xiaohui; Yan, Yueming
Drought is a major form of abiotic stress that significantly affects plant growth and development. In this study, we performed the first phosphoproteome analysis of seedling leaves from two bread wheat cultivars (Hanxuan 10 and Ningchun 47) subjected to drought stress. As a result, a total of 191 and 251 unique phosphopeptides, representing 173 and 227 phosphoproteins in two cultivars, respectively, were identified as being significant changes in phosphorylation level (SCPL) under drought stress. Through the comparison of SCPL phosphoproteins between two cultivars, 31 common SCPL phosphoproteins were found in both cultivars. Function analysis showed that the SCPL phosphoproteins in the two cultivars are mainly involved in three biological processes: RNA transcription/processing, stress/detoxification/defense, and signal transduction. Further analyses revealed that some SCPL phosphoproteins may play key roles in signal transduction and the signaling cascade under drought stress. Furthermore, some phosphoproteins related to drought tolerance and osmotic regulation exhibited significant phosphorylation changes. This study used a series of bioinformatics tools to profile the phosphorylation status of wheat seedling leaves under drought stress with greater accuracy. Drought is of the most studied abiotic stresses, because it severely restricts the development and yield of plants. In this study, large numbers of stress-related phosphoproteins are identified from the two bread wheat cultivars. These phosphoproteins contribute to signal transduction, osmotic regulation and ROS scavenging under water stress. This work provides a detailed insight into the mechanisms of drought response and defense in bread wheat from the perspective of phosphoproteomics, and identifies some important drought-tolerant candidates for further transgenosis study and incorporation into the breeding of resistant cultivars. Copyright © 2014 Elsevier B.V. All rights reserved.
Muneer, Sowbiya; Wei, Hao; Park, Yoo Gyeong; Jeong, Hai Kyoung; Jeong, Byoung Ryong
The present study depicted the role of silicon in limiting the hyperhydricity in shoot cultures of carnation through proteomic analysis. Four-week-old healthy shoot cultures of carnation "Purple Beauty" were sub-cultured on Murashige and Skoog medium followed with four treatments, viz. control (-Si/-Hyperhydricity), hyperhydric with no silicon treatment (-Si/+Hyperhydricity), hyperhydric with silicon treatment (+Si/+Hyperhydricity), and only silicon treated with no hyperhydricity (+Si/-Hyperhydricity). Comparing to control morphological features of hyperhydric carnations showed significantly fragile, bushy and lustrous leaf nature, while Si supply restored these effects. Proteomic investigation revealed that approximately seventy protein spots were differentially expressed under Si and/or hyperhydric treatments and were either up- or downregulated in abundance depending on their functions. Most of the identified protein spots were related to stress responses, photosynthesis, and signal transduction. Proteomic results were further confirmed through immunoblots by selecting specific proteins such as superoxide dismutase (SOD), ascorbate peroxidase (APX), catalase (CAT), PsaA, and PsbA. Moreover, protein-protein interaction was also performed on differentially expressed protein spots using specific bioinformatic tools. In addition, stress markers were analyzed by histochemical localization of hydrogen peroxide (H₂O₂) and singlet oxygen (O₂ 1- ). In addition, the ultrastructure of chloroplasts in hyperhydric leaves significantly resulted in inefficiency of thylakoid lamella with the loss of grana but were recovered in silicon supplemented leaves. The proteomic study together with physiological analysis indicated that Si has a substantial role in upholding the hyperhydricity in in vitro grown carnation shoot cultures.
Keerthikumar, Shivakumar; Gangoda, Lahiru; Gho, Yong Song; Mathivanan, Suresh
Extracellular vesicles (EVs) are a class of membranous vesicles that are released by multiple cell types into the extracellular environment. This unique class of extracellular organelles which play pivotal role in intercellular communication are conserved across prokaryotes and eukaryotes. Depending upon the cell origin and the functional state, the molecular cargo including proteins, lipids, and RNA within the EVs are modulated. Owing to this, EVs are considered as a subrepertoire of the host cell and are rich reservoirs of disease biomarkers. In addition, the availability of EVs in multiple bodily fluids including blood has created significant interest in biomarker and signaling research. With the advancement in high-throughput techniques, multiple EV studies have embarked on profiling the molecular cargo. To benefit the scientific community, existing free Web-based resources including ExoCarta, EVpedia, and Vesiclepedia catalog multiple datasets. These resources aid in elucidating molecular mechanism and pathophysiology underlying different disease conditions from which EVs are isolated. Here, the existing bioinformatics tools to perform integrated analysis to identify key functional components in the EV datasets are discussed.
Whereas a vast amount of new information on bioinformatics is made available to the public through patents, only a small set of patents are cited in academic papers. A detailed analysis of registered bioinformatics patents, using the existing patent search system, can provide valuable information links between science and technology. However, it is extremely difficult to select keywords to capture bioinformatics patents, reflecting the convergence of several underlying technologies. No single word or even several words are sufficient to identify such patents. The analysis of patent subclasses can provide valuable information. In this paper, I did a preliminary study of the current status of bioinformatics patents and their International Patent Classification (IPC) groups registered in the Korea Intellectual Property Rights Information Service (KIPRIS) database.
Cristancho, Marco; Isaza, Gustavo; Pinzón, Andrés; Rodríguez, Juan
This volume compiles accepted contributions for the 2nd Edition of the Colombian Computational Biology and Bioinformatics Congress CCBCOL, after a rigorous review process in which 54 papers were accepted for publication from 119 submitted contributions. Bioinformatics and Computational Biology are areas of knowledge that have emerged due to advances that have taken place in the Biological Sciences and its integration with Information Sciences. The expansion of projects involving the study of genomes has led the way in the production of vast amounts of sequence data which needs to be organized, analyzed and stored to understand phenomena associated with living organisms related to their evolution, behavior in different ecosystems, and the development of applications that can be derived from this analysis. .
Košir, Alexandra Bogožalec; Arulandhu, Alfred J; Voorhuijzen, Marleen M; Xiao, Hongmei; Hagelaar, Rico; Staats, Martijn; Costessi, Adalberto; Žel, Jana; Kok, Esther J; Dijk, Jeroen P van
The majority of feed products in industrialised countries contains materials derived from genetically modified organisms (GMOs). In parallel, the number of reports of unauthorised GMOs (UGMOs) is gradually increasing. There is a lack of specific detection methods for UGMOs, due to the absence of detailed sequence information and reference materials. In this research, an adapted genome walking approach was developed, called ALF: Amplification of Linearly-enriched Fragments. Coupling of ALF to NGS aims for simultaneous detection and identification of all GMOs, including UGMOs, in one sample, in a single analysis. The ALF approach was assessed on a mixture made of DNA extracts from four reference materials, in an uneven distribution, mimicking a real life situation. The complete insert and genomic flanking regions were known for three of the included GMO events, while for MON15985 only partial sequence information was available. Combined with a known organisation of elements, this GMO served as a model for a UGMO. We successfully identified sequences matching with this organisation of elements serving as proof of principle for ALF as new UGMO detection strategy. Additionally, this study provides a first outline of an automated, web-based analysis pipeline for identification of UGMOs containing known GM elements.
Brazas, Michelle D.; Ouellette, B. F. Francis
With the advent of YouTube channels in bioinformatics, open platforms for problem solving in bioinformatics, active web forums in computing analyses and online resources for learning to code or use a bioinformatics tool, the more traditional continuing education bioinformatics training programs have had to adapt. Bioinformatics training programs that solely rely on traditional didactic methods are being superseded by these newer resources. Yet such face-to-face instruction is still invaluable...
Evdokim Kovach; Alexey Alekhin; Eduardo Pareja Tobes; Raquel Tobes; Eduardo Pareja; Marina Manrique
Nowadays it is widely accepted that the bioinformatics data analysis is a real bottleneck in many research activities related to life sciences. High-throughput technologies like Next Generation Sequencing (NGS) have completely reshaped the biology and bioinformatics landscape. Undoubtedly NGS has allowed important progress in many life-sciences related fields but has also presented interesting challenges in terms of computation capabilities and algorithms. Many kinds of tasks related with NGS...
Butt, Davin; Roger, Andrew J; Blouin, Christian
Background An increasing number of bioinformatics methods are considering the phylogenetic relationships between biological sequences. Implementing new methodologies using the maximum likelihood phylogenetic framework can be a time consuming task. Results The bioinformatics library libcov is a collection of C++ classes that provides a high and low-level interface to maximum likelihood phylogenetics, sequence analysis and a data structure for structural biological methods. libcov can be used ...
Valerie A Walshe
Full Text Available Predictive models of peptide-Major Histocompatibility Complex (MHC binding affinity are important components of modern computational immunovaccinology. Here, we describe the development and deployment of a reliable peptide-binding prediction method for a previously poorly-characterized human MHC class I allele, HLA-Cw*0102.Using an in-house, flow cytometry-based MHC stabilization assay we generated novel peptide binding data, from which we derived a precise two-dimensional quantitative structure-activity relationship (2D-QSAR binding model. This allowed us to explore the peptide specificity of HLA-Cw*0102 molecule in detail. We used this model to design peptides optimized for HLA-Cw*0102-binding. Experimental analysis showed these peptides to have high binding affinities for the HLA-Cw*0102 molecule. As a functional validation of our approach, we also predicted HLA-Cw*0102-binding peptides within the HIV-1 genome, identifying a set of potent binding peptides. The most affine of these binding peptides was subsequently determined to be an epitope recognized in a subset of HLA-Cw*0102-positive individuals chronically infected with HIV-1.A functionally-validated in silico-in vitro approach to the reliable and efficient prediction of peptide binding to a previously uncharacterized human MHC allele HLA-Cw*0102 was developed. This technique is generally applicable to all T cell epitope identification problems in immunology and vaccinology.
Structural Bioinformatics and Protein Docking Analysis of the Molecular Chaperone-Kinase Interactions: Towards Allosteric Inhibition of Protein Kinases by Targeting the Hsp90-Cdc37 Chaperone Machinery
Full Text Available A fundamental role of the Hsp90-Cdc37 chaperone system in mediating maturation of protein kinase clients and supporting kinase functional activity is essential for the integrity and viability of signaling pathways involved in cell cycle control and organism development. Despite significant advances in understanding structure and function of molecular chaperones, the molecular mechanisms and guiding principles of kinase recruitment to the chaperone system are lacking quantitative characterization. Structural and thermodynamic characterization of Hsp90-Cdc37 binding with protein kinase clients by modern experimental techniques is highly challenging, owing to a transient nature of chaperone-mediated interactions. In this work, we used experimentally-guided protein docking to probe the allosteric nature of the Hsp90-Cdc37 binding with the cyclin-dependent kinase 4 (Cdk4 kinase clients. The results of docking simulations suggest that the kinase recognition and recruitment to the chaperone system may be primarily determined by Cdc37 targeting of the N-terminal kinase lobe. The interactions of Hsp90 with the C-terminal kinase lobe may provide additional “molecular brakes” that can lock (or unlock kinase from the system during client loading (release stages. The results of this study support a central role of the Cdc37 chaperone in recognition and recruitment of the kinase clients. Structural analysis may have useful implications in developing strategies for allosteric inhibition of protein kinases by targeting the Hsp90-Cdc37 chaperone machinery.
Brandes, E.; McNunn, G. S.; Schulte, L. A.; Bonner, I. J.; Muth, D. J.; Babcock, B. A.; Sharma, B.; Heaton, E. A.
Public agencies and private enterprises increasingly desire to achieve ecosystem service outcomes in agricultural systems, but are limited by perceived conflicts between economic and ecosystem service goals and a lack of tools enabling effective operational management. Here we use Iowa—an agriculturally homogeneous state representative of the Maize Belt—to demonstrate an economic rationale for cropland diversification at the subfield scale. We used a novel computational framework that integrates disparate but publicly available data to map ˜3.3 million unique potential management polygons (9.3 Mha) and reveal subfield opportunities to increase overall field profitability. We analyzed subfield profitability for maize/soybean fields during 2010-2013—four of the most profitable years in recent history—and projected results for 2015. While cropland operating at a loss of US 250 ha-1 or more was negligible between 2010 and 2013 at 18 000-190 000 ha (<2% of row-crop land), the extent of highly unprofitable land increased to 2.5 Mha, or 27% of row-crop land, in the 2015 projection. Aggregation of these areas to the township level revealed ‘hotspots’ for potential management change in Western, Central, and Northeast Iowa. In these least profitable areas, incorporating conservation management that breaks even (e.g., planting low-input perennials), into low-yielding portions of fields could increase overall cropland profitability by 80%. This approach is applicable to the broader region and differs substantially from the status quo of ‘top-down’ land management for conservation by harnessing private interest to align profitability with the production of ecosystem services.
c Indian Academy of Sciences. RESEARCH NOTE. A genetic analysis of segregation ... 2College of Life Science, Northeast Forest University, Harbin 150040, People's Republic of China. [Cai J., Zhang X., Wang B., Yan M., Qi Y. and Kong L. ... elite agronomic traits (Zhang et al. 2011). However, there is still no report about ...
Kevin J. McGuire; Christian E. Torgersen; Gene E. Likens; Donald C. Buso; Winsor H. Lowe; Scott W. Bailey
By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in...
Withers Dominic J
Full Text Available Abstract Background Obesity causes insulin resistance in target tissues - skeletal muscle, adipose tissue, liver and the brain. Insulin resistance predisposes to type-2 diabetes (T2D and cardiovascular disease (CVD. Adipose tissue inflammation is an essential characteristic of obesity and insulin resistance. Neuronatin (Nnat expression has been found to be altered in a number of conditions related to inflammatory or metabolic disturbance, but its physiological roles and regulatory mechanisms in adipose tissue, brain, pancreatic islets and other tissues are not understood. Results We identified transcription factor binding sites (TFBS conserved in the Nnat promoter, and transcription factors (TF abundantly expressed in adipose tissue. These include transcription factors concerned with the control of: adipogenesis (Pparγ, Klf15, Irf1, Creb1, Egr2, Gata3; lipogenesis (Mlxipl, Srebp1c; inflammation (Jun, Stat3; insulin signalling and diabetes susceptibility (Foxo1, Tcf7l2. We also identified NeuroD1 the only documented TF that controls Nnat expression. We identified KEGG pathways significantly associated with Nnat expression, including positive correlations with inflammation and negative correlations with metabolic pathways (most prominently oxidative phosphorylation, glycolysis and gluconeogenesis, pyruvate metabolism and protein turnover. 27 genes, including; Gstt1 and Sod3, concerned with oxidative stress; Sncg and Cxcl9 concerned with inflammation; Ebf1, Lgals12 and Fzd4 involved in adipogenesis; whose expression co-varies with Nnat were identified, and conserved transcription factor binding sites identified on their promoters. Functional networks relating to each of these genes were identified. Conclusions Our analysis shows that Nnat is an acute diet-responsive gene in white adipose tissue and hypothalamus; it may play an important role in metabolism, adipogenesis, and resolution of oxidative stress and inflammation in response to dietary
Li, Xinzhong; Thomason, Peter A; Withers, Dominic J; Scott, James
Obesity causes insulin resistance in target tissues - skeletal muscle, adipose tissue, liver and the brain. Insulin resistance predisposes to type-2 diabetes (T2D) and cardiovascular disease (CVD). Adipose tissue inflammation is an essential characteristic of obesity and insulin resistance. Neuronatin (Nnat) expression has been found to be altered in a number of conditions related to inflammatory or metabolic disturbance, but its physiological roles and regulatory mechanisms in adipose tissue, brain, pancreatic islets and other tissues are not understood. We identified transcription factor binding sites (TFBS) conserved in the Nnat promoter, and transcription factors (TF) abundantly expressed in adipose tissue. These include transcription factors concerned with the control of: adipogenesis (Pparγ, Klf15, Irf1, Creb1, Egr2, Gata3); lipogenesis (Mlxipl, Srebp1c); inflammation (Jun, Stat3); insulin signalling and diabetes susceptibility (Foxo1, Tcf7l2). We also identified NeuroD1 the only documented TF that controls Nnat expression. We identified KEGG pathways significantly associated with Nnat expression, including positive correlations with inflammation and negative correlations with metabolic pathways (most prominently oxidative phosphorylation, glycolysis and gluconeogenesis, pyruvate metabolism) and protein turnover. 27 genes, including; Gstt1 and Sod3, concerned with oxidative stress; Sncg and Cxcl9 concerned with inflammation; Ebf1, Lgals12 and Fzd4 involved in adipogenesis; whose expression co-varies with Nnat were identified, and conserved transcription factor binding sites identified on their promoters. Functional networks relating to each of these genes were identified. Our analysis shows that Nnat is an acute diet-responsive gene in white adipose tissue and hypothalamus; it may play an important role in metabolism, adipogenesis, and resolution of oxidative stress and inflammation in response to dietary excess.
Full Text Available This study was designed to investigate at the molecular level how a transgenic version of rice “Nipponbare” obtained a drought-resistant phenotype. Using multi-omics sequencing data, we compared wild-type rice (WT and a transgenic version (erf71 that had obtained a drought-resistant phenotype by overexpressing OsERF71, a member of the AP2/ERF transcription factor (TF family. A comprehensive bioinformatics analysis pipeline, including TF networks and a cascade tree, was developed for the analysis of multi-omics data. The results of the analysis showed that the presence of OsERF71 at the source of the network controlled global gene expression levels in a specific manner to make erf71 survive longer than WT. Our analysis of the time-series transcriptome data suggests that erf71 diverted more energy to survival-critical mechanisms related to translation, oxidative response, and DNA replication, while further suppressing energy-consuming mechanisms, such as photosynthesis. To support this hypothesis further, we measured the net photosynthesis level under physiological conditions, which confirmed the further suppression of photosynthesis in erf71. In summary, our work presents a comprehensive snapshot of transcriptional modification in transgenic rice and shows how this induced the plants to acquire a drought-resistant phenotype.
Disasters events are perfect examples of compound events. Disaster risk lies at the intersection of several independent components such as hazard, exposure and vulnerability. Understanding the weight of each component requires extensive standardisation. Here, I show how footprints of past disastrous events were generated using GIS modelling techniques and used for extracting population and economic exposures based on distribution models. Using past event losses, it was possible to identify and quantify a wide range of socio-politico-economic drivers associated with human vulnerability. The analysis was applied to about nine thousand individual past disastrous events covering earthquakes, floods and tropical cyclones. Using a multiple regression analysis on these individual events it was possible to quantify each risk component and assess how vulnerability is influenced by various hazard intensities. The results show that hazard intensity, exposure, poverty, governance as well as other underlying factors (e.g. remoteness) can explain the magnitude of past disasters. Analysis was also performed to highlight the role of future trends in population and climate change and how this may impacts exposure to tropical cyclones in the future. GIS models combined with statistical multiple regression analysis provided a powerful methodology to identify, quantify and model disaster risk taking into account its various components. The same methodology can be applied to various types of risk at local to global scale. This method was applied and developed for the Global Risk Analysis of the Global Assessment Report on Disaster Risk Reduction (GAR). It was first applied on mortality risk in GAR 2009 and GAR 2011. New models ranging from global assets exposure and global flood hazard models were also recently developed to improve the resolution of the risk analysis and applied through CAPRA software to provide probabilistic economic risk assessments such as Average Annual Losses (AAL
Ray, Ann; Kinch, Lisa N; de Souza Santos, Marcela; Grishin, Nick V; Orth, Kim; Salomon, Dor
Members of the genus Vibrio include many pathogens of humans and marine animals that share genetic information via horizontal gene transfer. Hence, the Vibrio pan-genome carries the potential to establish new pathogenic strains by sharing virulence determinants, many of which have yet to be characterized. Here, we investigated the virulence properties of Vibrio proteolyticus, a Gram-negative marine bacterium previously identified as part of the Vibrio consortium isolated from diseased corals. We found that V. proteolyticus causes actin cytoskeleton rearrangements followed by cell lysis in HeLa cells in a contact-independent manner. In search of the responsible virulence factor involved, we determined the V. proteolyticus secretome. This proteomics approach revealed various putative virulence factors, including active type VI secretion systems and effectors with virulence toxin domains; however, these type VI secretion systems were not responsible for the observed cytotoxic effects. Further examination of the V. proteolyticus secretome led us to hypothesize and subsequently demonstrate that a secreted hemolysin, belonging to a previously uncharacterized clan of the leukocidin superfamily, was the toxin responsible for the V. proteolyticus-mediated cytotoxicity in both HeLa cells and macrophages. Clearly, there remains an armory of yet-to-be-discovered virulence factors in the Vibrio pan-genome that will undoubtedly provide a wealth of knowledge on how a pathogen can manipulate host cells. The pan-genome of the genus Vibrio is a potential reservoir of unidentified toxins that can provide insight into how members of this genus have successfully risen as emerging pathogens worldwide. We focused on Vibrio proteolyticus, a marine bacterium that was previously implicated in virulence toward marine animals, and characterized its interaction with eukaryotic cells. We found that this bacterium causes actin cytoskeleton rearrangements and leads to cell death. Using a
Schoos, Ann-Marie M.; Chawes, Bo L.; Melen, Erik
BACKGROUND: Assessment of sensitization at a single time point during childhood provides limited clinical information. We hypothesized that sensitization develops as specific patterns with respect to age at debut, development over time, and involved allergens and that such patterns might be more...... biologically and clinically relevant. OBJECTIVE: We sought to explore latent patterns of sensitization during the first 6 years of life and investigate whether such patterns associate with the development of asthma, rhinitis, and eczema. METHODS: We investigated 398 children from the at-risk Copenhagen...... Prospective Studies on Asthma in Childhood 2000 (COPSAC2000) birth cohort with specific IgE against 13 common food and inhalant allergens at the ages of ½, 1½, 4, and 6 years. An unsupervised cluster analysis for 3-dimensional data (nonnegative sparse parallel factor analysis) was used to extract latent...
Mouton, Stijn; Willems, Maxime; Back, Patricia; Braeckman, Bart; Borgonie, Gaetan
Abstract Free-living flatworms ("Turbellaria") are appropriate model organisms to gain better insight into the role of stem cells in ageing and rejuvenation. Ageing research in flatworms is, however, still scarce. This is partly due to culture difficulties and the lack of a complete set of demographic data, including parameters such as median lifespan and age-specific mortality rate. In this paper, we report on the first flatworm survival analysis. We used the species Macrostomum lignano, whi...
Full Text Available Members of the genus Vibrio include many pathogens of humans and marine animals that share genetic information via horizontal gene transfer. Hence, the Vibrio pan-genome carries the potential to establish new pathogenic strains by sharing virulence determinants, many of which have yet to be characterized. Here, we investigated the virulence properties of Vibrio proteolyticus, a Gram-negative marine bacterium previously identified as part of the Vibrio consortium isolated from diseased corals. We found that V. proteolyticus causes actin cytoskeleton rearrangements followed by cell lysis in HeLa cells in a contact-independent manner. In search of the responsible virulence factor involved, we determined the V. proteolyticus secretome. This proteomics approach revealed various putative virulence factors, including active type VI secretion systems and effectors with virulence toxin domains; however, these type VI secretion systems were not responsible for the observed cytotoxic effects. Further examination of the V. proteolyticus secretome led us to hypothesize and subsequently demonstrate that a secreted hemolysin, belonging to a previously uncharacterized clan of the leukocidin superfamily, was the toxin responsible for the V. proteolyticus-mediated cytotoxicity in both HeLa cells and macrophages. Clearly, there remains an armory of yet-to-be-discovered virulence factors in the Vibrio pan-genome that will undoubtedly provide a wealth of knowledge on how a pathogen can manipulate host cells.
Hua, Qingzhu; Zhou, Qianjun; Gan, Susheng; Wu, Jingyu; Chen, Canbin; Li, Jiaqiang; Ye, Yaoxiong; Zhao, Jietang; Hu, Guibing; Qin, Yonghua
Red dragon fruit or red pitaya ( Hylocereus polyrhizus ) is the only edible fruit that contains betalains. The color of betalains ranges from red and violet to yellow in plants. Betalains may also serve as an important component of health-promoting and disease-preventing functional food. Currently, the biosynthetic and regulatory pathways for betalain production remain to be fully deciphered. In this study, isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomic analyses were used to reveal the molecular mechanism of betalain biosynthesis in H. polyrhizus fruits at white and red pulp stages, respectively. A total of 1946 proteins were identified as the differentially expressed between the two samples, and 936 of them were significantly highly expressed at the red pulp stage of H. polyrhizus . RNA-seq and iTRAQ analyses showed that some transcripts and proteins were positively correlated; they belonged to "phenylpropanoid biosynthesis", "tyrosine metabolism", "flavonoid biosynthesis", "ascorbate and aldarate metabolism", "betalains biosynthesis" and "anthocyanin biosynthesis". In betalains biosynthesis pathway, several proteins/enzymes such as polyphenol oxidase, CYP76AD3 and 4,5-dihydroxy-phenylalanine (DOPA) dioxygenase extradiol-like protein were identified. The present study provides a new insight into the molecular mechanism of the betalain biosynthesis at the posttranscriptional level.
Full Text Available Red dragon fruit or red pitaya (Hylocereus polyrhizus is the only edible fruit that contains betalains. The color of betalains ranges from red and violet to yellow in plants. Betalains may also serve as an important component of health-promoting and disease-preventing functional food. Currently, the biosynthetic and regulatory pathways for betalain production remain to be fully deciphered. In this study, isobaric tags for relative and absolute quantitation (iTRAQ-based proteomic analyses were used to reveal the molecular mechanism of betalain biosynthesis in H. polyrhizus fruits at white and red pulp stages, respectively. A total of 1946 proteins were identified as the differentially expressed between the two samples, and 936 of them were significantly highly expressed at the red pulp stage of H. polyrhizus. RNA-seq and iTRAQ analyses showed that some transcripts and proteins were positively correlated; they belonged to “phenylpropanoid biosynthesis”, “tyrosine metabolism”, “flavonoid biosynthesis”, “ascorbate and aldarate metabolism”, “betalains biosynthesis” and “anthocyanin biosynthesis”. In betalains biosynthesis pathway, several proteins/enzymes such as polyphenol oxidase, CYP76AD3 and 4,5-dihydroxy-phenylalanine (DOPA dioxygenase extradiol-like protein were identified. The present study provides a new insight into the molecular mechanism of the betalain biosynthesis at the posttranscriptional level.
Sirintrapun, S Joseph; Zehir, Ahmet; Syed, Aijazuddin; Gao, JianJiong; Schultz, Nikolaus; Cheng, Donavan T
Translational bioinformatics and clinical research (biomedical) informatics are the primary domains related to informatics activities that support translational research. Translational bioinformatics focuses on computational techniques in genetics, molecular biology, and systems biology. Clinical research (biomedical) informatics involves the use of informatics in discovery and management of new knowledge relating to health and disease. This article details 3 projects that are hybrid applications of translational bioinformatics and clinical research (biomedical) informatics: The Cancer Genome Atlas, the cBioPortal for Cancer Genomics, and the Memorial Sloan Kettering Cancer Center clinical variants and results database, all designed to facilitate insights into cancer biology and clinical/therapeutic correlations. Copyright © 2015 Elsevier Inc. All rights reserved.
Díaz-Del-Pino, Sergio; Falgueras, Juan; Perez-Wohlfeil, Esteban; Trelles, Oswaldo
Nearly 10 years have passed since the first mobile apps appeared. Given the fact that bioinformatics is a web-based world and that mobile devices are endowed with web-browsers, it seemed natural that bioinformatics would transit from personal computers to mobile devices but nothing could be further from the truth. The transition demands new paradigms, designs and novel implementations. Throughout an in-depth analysis of requirements of existing bioinformatics applications we designed and deployed an easy-to-use web-based lightweight mobile client. Such client is able to browse, select, compose automatically interface parameters, invoke services and monitor the execution of Web Services using the service's metadata stored in catalogs or repositories. mORCA is available at http://bitlab-es.com/morca/app as a web-app. It is also available in the App store by Apple and Play Store by Google. The software will be available for at least 2 years. firstname.lastname@example.org. Source code, final web-app, training material and documentation is available at http://bitlab-es.com/morca. © The Author(s) 2017. Published by Oxford University Press.
Bencharit, Sompop; Border, Michael B; Edelmann, Alex; Byrd, Warren C
The 3rd International Conference on Proteomics & Bioinformatics (Proteomics 2013) Philadelphia, PA, USA, 15-17 July 2013 The Third International Conference on Proteomics & Bioinformatics (Proteomics 2013) was sponsored by the OMICS group and was organized in order to strengthen the future of proteomics science by bringing together professionals, researchers and scholars from leading universities across the globe. The main topics of this conference included the integration of novel platforms in data analysis, the use of a systems biology approach, different novel mass spectrometry platforms and biomarker discovery methods. The conference was divided into proteomic methods and research interests. Among these two categories, interactions between methods in proteomics and bioinformatics, as well as other research methodologies, were discussed. Exceptional topics from the keynote forum, oral presentations and the poster session have been highlighted. The topics range from new techniques for analyzing proteomics data, to new models designed to help better understand genetic variations to the differences in the salivary proteomes of HIV-infected patients.
Teresa K Attwood
Full Text Available In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy--paradoxically, many are actually closing "niche" bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all.
The mountains of data thrusting from the new landscape of modern high-throughput biology are irrevocably changing biomedical research and creating a near-insatiable demand for training in data management and manipulation and data mining and analysis. Among life scientists, from clinicians to environmental researchers, a common theme is the need not just to use, and gain familiarity with, bioinformatics tools and resources but also to understand their underlying fundamental theoretical and practical concepts. Providing bioinformatics training to empower life scientists to handle and analyse their data efficiently, and progress their research, is a challenge across the globe. Delivering good training goes beyond traditional lectures and resource-centric demos, using interactivity, problem-solving exercises and cooperative learning to substantially enhance training quality and learning outcomes. In this context, this article discusses various pragmatic criteria for identifying training needs and learning objectives, for selecting suitable trainees and trainers, for developing and maintaining training skills and evaluating training quality. Adherence to these criteria may help not only to guide course organizers and trainers on the path towards bioinformatics training excellence but, importantly, also to improve the training experience for life scientists.
Atwood, Teresa K.; Bongcam-Rudloff, Erik; Brazas, Michelle E.; Corpas, Manuel; Gaudet, Pascale; Lewitter, Fran; Mulder, Nicola; Palagi, Patricia M.; Schneider, Maria Victoria; van Gelder, Celia W. G.
In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy—paradoxically, many are actually closing “niche” bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all. PMID:25856076
Singh, Gautam B
This book offers comprehensive coverage of all the core topics of bioinformatics, and includes practical examples completed using the MATLAB bioinformatics toolbox™. It is primarily intended as a textbook for engineering and computer science students attending advanced undergraduate and graduate courses in bioinformatics and computational biology. The book develops bioinformatics concepts from the ground up, starting with an introductory chapter on molecular biology and genetics. This chapter will enable physical science students to fully understand and appreciate the ultimate goals of applying the principles of information technology to challenges in biological data management, sequence analysis, and systems biology. The first part of the book also includes a survey of existing biological databases, tools that have become essential in today’s biotechnology research. The second part of the book covers methodologies for retrieving biological information, including fundamental algorithms for sequence compar...
BASIC QUALIFICATIONS To be considered for this position, you must minimally meet the knowledge, skills, and abilities listed below: Bachelor’s degree in life science/bioinformatics/math/physics/computer related field from an accredited college or university according to the Council for Higher Education Accreditation (CHEA). (Additional qualifying experience may be substituted for the required education). Foreign degrees must be evaluated for U.S. equivalency. In addition to the educational requirements, a minimum of five (5) years of progressively responsible relevant experience. Must be able to obtain and maintain a security clearance. PREFERRED QUALIFICATIONS Candidates with these desired skills will be given preferential consideration: A Masters’ or PhD degree in any quantitative science is preferred. Commitment to solving biological problems and communicating these solutions. Ability to multi-task across projects. Experience in submitting data sets to public repositories. Management of large genomic data sets including integration with data available from public sources. Prior customer-facing role. Record of scientific achievements including journal publications and conference presentations. Expected Competencies: Deep understanding of and experience in processing high throughput biomedical data: data cleaning, normalization, analysis, interpretation and visualization. Ability to understand and analyze data from complex experimental designs. Proficiency in at least two of the following programming languages: Perl, Python, R, Java and C/C++. Experience in at least two of the following areas: metagenomics, ChIPSeq, RNASeq, ExomeSeq, DHS-Seq, microarray analysis. Familiarity with public databases: NCBI, Ensembl, TCGA, cBioPortal, Broad FireHose. Knowledge of working in a cluster environment.
Wang, Pengfei; Zhang, Bing; Duan, Guangcai; Wang, Yingfang; Hong, Lijuan; Wang, Linlin; Guo, Xiangjiao; Xi, Yuanlin; Yang, Haiyan
Clustered regularly interspaced short palindromic repeats (CRISPR) are inheritable genetic elements of a variety of archaea and bacteria and indicative of the bacterial ecological adaptation, conferring acquired immunity against invading foreign nucleic acids. Shigella is an important pathogen for anthroponosis. This study aimed to analyze the features of Shigella CRISPR structure and classify the spacers through bioinformatics approach. Among 107 Shigella, 434 CRISPR structure loci were identified with two to seven loci in different strains. CRISPR-Q1, CRISPR-Q4 and CRISPR-Q5 were widely distributed in Shigella strains. Comparison of the first and last repeats of CRISPR1, CRISPR2 and CRISPR3 revealed several base variants and different stem-loop structures. A total of 259 cas genes were found among these 107 Shigella strains. The cas gene deletions were discovered in 88 strains. However, there is one strain that does not contain cas gene. Intact clusters of cas genes were found in 19 strains. From comprehensive analysis of sequence signature and BLAST and CRISPRTarget score, the 708 spacers were classified into three subtypes: Type I, Type II and Type III. Of them, Type I spacer referred to those linked with one gene segment, Type II spacer linked with two or more different gene segments, and Type III spacer undefined. This study examined the diversity of CRISPR/cas system in Shigella strains, demonstrated the main features of CRISPR structure and spacer classification, which provided critical information for elucidation of the mechanisms of spacer formation and exploration of the role the spacers play in the function of the CRISPR/cas system.
Zhu, Z-Q; Tang, J-S; Cao, X-J
Ankylosing spondylitis (AS) is a chronic, inflammatory arthritis and autoimmune disease. The main symptom of AS is inflammatory spinal pain; with time, some patients develop ankylosis and spinal immobility. We aim to find cure available for ankylosing spondylitis. We used the GSE11886 series to identify potential genes that related to AS to construct a regulation network. In the network, some of TFs and target genes have been proved related with AS in previous study, such as NFKB1, STAT1, STAT4, TNFSF10, IL2RA, and IL2RB. We also found some new TFs (Franscription Factors) and target genes response to AS, such as BXDC5, and EGFR. Further analysis indicated some significant pathways are associated with AS, including antigen processing and presentation and cytokine-cytokine receptor interaction, etc.; although not significant, there was evident that they play an important role in AS progression, such as apoptosis and systemic lupus erythematosus. Therefore, it is demonstrated that transcriptome network analysis is useful in identification of the candidate genes in AS.
Pawełkowicz, Magdalena; Osipowski, Paweł; Wojcieszek, Michał; Kowalczuk, Cezary; PlÄ der, Wojciech; Przybecki, Zbigniew
Three cDNA clones were used to screen cucumber genome in order to find genes and proteins. Functional annotation reveals that they are correlated with ubiquitination pathways. Various bioinformatics tools were used to screen and check protein sequences features such as: the presence of specific domains, transmembrane regions, cleavage site and cellular placement. The computational analysis for promotor region shows many binding sites for transcription factors, which could regulate the expression of genes. In order to check gene expression levels in developing flower buds of monoecious (B10) and gynoecious (2gg) cucumber lines, the real - time PCR technique was applied. The expression was checked for the whole buds and only for the 3rd and 4th whorls of bud when generative organ are form which were obtained by Laser Capture Microdissection (LCM) technique.
Schoos, Ann-Marie M; Chawes, Bo L; Melén, Erik; Bergström, Anna; Kull, Inger; Wickman, Magnus; Bønnelykke, Klaus; Bisgaard, Hans; Rasmussen, Morten A
Assessment of sensitization at a single time point during childhood provides limited clinical information. We hypothesized that sensitization develops as specific patterns with respect to age at debut, development over time, and involved allergens and that such patterns might be more biologically and clinically relevant. We sought to explore latent patterns of sensitization during the first 6 years of life and investigate whether such patterns associate with the development of asthma, rhinitis, and eczema. We investigated 398 children from the at-risk Copenhagen Prospective Studies on Asthma in Childhood 2000 (COPSAC 2000 ) birth cohort with specific IgE against 13 common food and inhalant allergens at the ages of ½, 1½, 4, and 6 years. An unsupervised cluster analysis for 3-dimensional data (nonnegative sparse parallel factor analysis) was used to extract latent patterns explicitly characterizing temporal development of sensitization while clustering allergens and children. Subsequently, these patterns were investigated in relation to asthma, rhinitis, and eczema. Verification was sought in an independent unselected birth cohort (BAMSE) constituting 3051 children with specific IgE against the same allergens at 4 and 8 years of age. The nonnegative sparse parallel factor analysis indicated a complex latent structure involving 7 age- and allergen-specific patterns in the COPSAC 2000 birth cohort data: (1) dog/cat/horse, (2) timothy grass/birch, (3) molds, (4) house dust mites, (5) peanut/wheat flour/mugwort, (6) peanut/soybean, and (7) egg/milk/wheat flour. Asthma was solely associated with pattern 1 (odds ratio [OR], 3.3; 95% CI, 1.5-7.2), rhinitis with patterns 1 to 4 and 6 (OR, 2.2-4.3), and eczema with patterns 1 to 3 and 5 to 7 (OR, 1.6-2.5). All 7 patterns were verified in the independent BAMSE cohort (R 2 > 0.89). This study suggests the presence of specific sensitization patterns in early childhood differentially associated with development of
Rebholz-Schuhman, Dietrich; Cameron, Graham; Clark, Dominic; van Mulligen, Erik; Coatrieux, Jean-Louis; Del Hoyo Barbolla, Eva; Martin-Sanchez, Fernando; Milanesi, Luciano; Porro, Ivan; Beltrame, Francesco; Tollis, Ioannis; Van der Lei, Johan
Background The SYMBIOmatics Specific Support Action (SSA) is "an information gathering and dissemination activity" that seeks "to identify synergies between the bioinformatics and the medical informatics" domain to improve collaborative progress between both domains (ref. to ). As part of the project experts in both research fields will be identified and approached through a survey. To provide input to the survey, the scientific literature was analysed to extract topics relevant to both medical informatics and bioinformatics. Results This paper presents results of a systematic analysis of the scientific literature from medical informatics research and bioinformatics research. In the analysis pairs of words (bigrams) from the leading bioinformatics and medical informatics journals have been used as indication of existing and emerging technologies and topics over the period 2000–2005 ("recent") and 1990–1990 ("past"). We identified emerging topics that were equally important to bioinformatics and medical informatics in recent years such as microarray experiments, ontologies, open source, text mining and support vector machines. Emerging topics that evolved only in bioinformatics were system biology, protein interaction networks and statistical methods for microarray analyses, whereas emerging topics in medical informatics were grid technology and tissue microarrays. Conclusion We conclude that although both fields have their own specific domains of interest, they share common technological developments that tend to be initiated by new developments in biotechnology and computer science. PMID:17430562
Warren, Wesley C; Hillier, LaDeana W; Marshall Graves, Jennifer A; Birney, Ewan; Ponting, Chris P; Grützner, Frank; Belov, Katherine; Miller, Webb; Clarke, Laura; Chinwalla, Asif T; Yang, Shiaw-Pyng; Heger, Andreas; Locke, Devin P; Miethke, Pat; Waters, Paul D; Veyrunes, Frédéric; Fulton, Lucinda; Fulton, Bob; Graves, Tina; Wallis, John; Puente, Xose S; López-Otín, Carlos; Ordóñez, Gonzalo R; Eichler, Evan E; Chen, Lin; Cheng, Ze; Deakin, Janine E; Alsop, Amber; Thompson, Katherine; Kirby, Patrick; Papenfuss, Anthony T; Wakefield, Matthew J; Olender, Tsviya; Lancet, Doron; Huttley, Gavin A; Smit, Arian F A; Pask, Andrew; Temple-Smith, Peter; Batzer, Mark A; Walker, Jerilyn A; Konkel, Miriam K; Harris, Robert S; Whittington, Camilla M; Wong, Emily S W; Gemmell, Neil J; Buschiazzo, Emmanuel; Vargas Jentzsch, Iris M; Merkel, Angelika; Schmitz, Juergen; Zemann, Anja; Churakov, Gennady; Kriegs, Jan Ole; Brosius, Juergen; Murchison, Elizabeth P; Sachidanandam, Ravi; Smith, Carly; Hannon, Gregory J; Tsend-Ayush, Enkhjargal; McMillan, Daniel; Attenborough, Rosalind; Rens, Willem; Ferguson-Smith, Malcolm; Lefèvre, Christophe M; Sharp, Julie A; Nicholas, Kevin R; Ray, David A; Kube, Michael; Reinhardt, Richard; Pringle, Thomas H; Taylor, James; Jones, Russell C; Nixon, Brett; Dacheux, Jean-Louis; Niwa, Hitoshi; Sekita, Yoko; Huang, Xiaoqiu; Stark, Alexander; Kheradpour, Pouya; Kellis, Manolis; Flicek, Paul; Chen, Yuan; Webber, Caleb; Hardison, Ross; Nelson, Joanne; Hallsworth-Pepin, Kym; Delehaunty, Kim; Markovic, Chris; Minx, Pat; Feng, Yucheng; Kremitzki, Colin; Mitreva, Makedonka; Glasscock, Jarret; Wylie, Todd; Wohldmann, Patricia; Thiru, Prathapan; Nhan, Michael N; Pohl, Craig S; Smith, Scott M; Hou, Shunfeng; Nefedov, Mikhail; de Jong, Pieter J; Renfree, Marilyn B; Mardis, Elaine R; Wilson, Richard K
We present a draft genome sequence of the platypus, Ornithorhynchus anatinus. This monotreme exhibits a fascinating combination of reptilian and mammalian characters. For example, platypuses have a coat of fur adapted to an aquatic lifestyle; platypus females lactate, yet lay eggs; and males are equipped with venom similar to that of reptiles. Analysis of the first monotreme genome aligned these features with genetic innovations. We find that reptile and platypus venom proteins have been co-opted independently from the same gene families; milk protein genes are conserved despite platypuses laying eggs; and immune gene family expansions are directly related to platypus biology. Expansions of protein, non-protein-coding RNA and microRNA families, as well as repeat elements, are identified. Sequencing of this genome now provides a valuable resource for deep mammalian comparative analyses, as well as for monotreme biology and conservation.
Warren, Wesley C.; Hillier, LaDeana W.; Marshall Graves, Jennifer A.; Birney, Ewan; Ponting, Chris P.; Grützner, Frank; Belov, Katherine; Miller, Webb; Clarke, Laura; Chinwalla, Asif T.; Yang, Shiaw-Pyng; Heger, Andreas; Locke, Devin P.; Miethke, Pat; Waters, Paul D.; Veyrunes, Frédéric; Fulton, Lucinda; Fulton, Bob; Graves, Tina; Wallis, John; Puente, Xose S.; López-Otín, Carlos; Ordóñez, Gonzalo R.; Eichler, Evan E.; Chen, Lin; Cheng, Ze; Deakin, Janine E.; Alsop, Amber; Thompson, Katherine; Kirby, Patrick; Papenfuss, Anthony T.; Wakefield, Matthew J.; Olender, Tsviya; Lancet, Doron; Huttley, Gavin A.; Smit, Arian F. A.; Pask, Andrew; Temple-Smith, Peter; Batzer, Mark A.; Walker, Jerilyn A.; Konkel, Miriam K.; Harris, Robert S.; Whittington, Camilla M.; Wong, Emily S. W.; Gemmell, Neil J.; Buschiazzo, Emmanuel; Vargas Jentzsch, Iris M.; Merkel, Angelika; Schmitz, Juergen; Zemann, Anja; Churakov, Gennady; Kriegs, Jan Ole; Brosius, Juergen; Murchison, Elizabeth P.; Sachidanandam, Ravi; Smith, Carly; Hannon, Gregory J.; Tsend-Ayush, Enkhjargal; McMillan, Daniel; Attenborough, Rosalind; Rens, Willem; Ferguson-Smith, Malcolm; Lefèvre, Christophe M.; Sharp, Julie A.; Nicholas, Kevin R.; Ray, David A.; Kube, Michael; Reinhardt, Richard; Pringle, Thomas H.; Taylor, James; Jones, Russell C.; Nixon, Brett; Dacheux, Jean-Louis; Niwa, Hitoshi; Sekita, Yoko; Huang, Xiaoqiu; Stark, Alexander; Kheradpour, Pouya; Kellis, Manolis; Flicek, Paul; Chen, Yuan; Webber, Caleb; Hardison, Ross; Nelson, Joanne; Hallsworth-Pepin, Kym; Delehaunty, Kim; Markovic, Chris; Minx, Pat; Feng, Yucheng; Kremitzki, Colin; Mitreva, Makedonka; Glasscock, Jarret; Wylie, Todd; Wohldmann, Patricia; Thiru, Prathapan; Nhan, Michael N.; Pohl, Craig S.; Smith, Scott M.; Hou, Shunfeng; Renfree, Marilyn B.; Mardis, Elaine R.; Wilson, Richard K.
We present a draft genome sequence of the platypus, Ornithorhynchus anatinus. This monotreme exhibits a fascinating combination of reptilian and mammalian characters. For example, platypuses have a coat of fur adapted to an aquatic lifestyle; platypus females lactate, yet lay eggs; and males are equipped with venom similar to that of reptiles. Analysis of the first monotreme genome aligned these features with genetic innovations. We find that reptile and platypus venom proteins have been co-opted independently from the same gene families; milk protein genes are conserved despite platypuses laying eggs; and immune gene family expansions are directly related to platypus biology. Expansions of protein, non-protein-coding RNA and microRNA families, as well as repeat elements, are identified. Sequencing of this genome now provides a valuable resource for deep mammalian comparative analyses, as well as for monotreme biology and conservation. PMID:18464734
Kjærsgård, Inger Vibeke Holst; Nørrelykke, M.R.; Jessen, Flemming
Multivariate data analysis has been combined with proteomics to enhance the recovery of information from 2-DE of cod muscle proteins during different storage conditions. Proteins were extracted according to 11 different storage conditions and samples were resolved by 2-DE. Data generated by 2-DE...... was subjected to principal component analysis (PCA) and discriminant partial least squares regression (DPLSR). Applying PCA to 2-DE data revealed the samples to form groups according to frozen storage time, whereas differences due to different storage temperatures or chilled storage in modified atmosphere...... light chain 1, 2 and 3, triose-phosphate isomerase, glyceraldehyde-3-phosphate dehydrogenase, aldolase A and two ?-actin fragments, and a nuclease diphosphate kinase B fragment to change in concentration, during frozen storage. Application of proteomics, multivariate data analysis and MS/MS to analyse...
Arockiaraj, Jesu; Chaurasia, Mukesh Kumar; Kumaresan, Venkatesh; Palanisamy, Rajesh; Harikrishnan, Ramasamy; Pasupuleti, Mukesh; Kasi, Marimuthu
Mannose-binding lectin (MBL), an antimicrobial protein, is an important component of innate immune system which recognizes repetitive sugar groups on the surface of bacteria and viruses leading to activation of the complement system. In this study, we reported a complete molecular characterization of cDNA encoded for MBL from freshwater prawn Macrobrachium rosenbergii (Mr). Two short peptides (MrMBL-N20: (20)AWNTYDYMKREHSLVKPYQG(39) and MrMBL-C16: (307)GGLFYVKHKEQQRKRF(322)) were synthesized from the MrMBL polypeptide. The purity of the MrMBL-N20 (89%) and MrMBL-C16 (93%) peptides were confirmed by MS analysis (MALDI-ToF). The purified peptides were used for further antimicrobial characterization including minimum inhibitory concentration (MIC) assay, kinetics of bactericidal efficiency and analysis of hemolytic capacity. The peptides exhibited antimicrobial activity towards all the Gram-negative bacteria taken for analysis, whereas they showed the activity towards only a few selected Gram-positive bacteria. MrMBL-C16 peptides produced the highest inhibition towards both the Gram-negative and Gram-positive bacteria compared to the MrMBL-N20. Both peptides do not produce any inhibition against Bacillus sps. The kinetics of bactericidal efficiency showed that the peptides drastically reduced the number of surviving bacterial colonies after 24 h incubation. The results of hemolytic activity showed that both peptides produced strong activity at higher concentration. However, MrMBL-C16 peptide produced the highest activity compared to the MrMBL-N20 peptide. Overall, the results indicated that the peptides can be used as bactericidal agents. The MrMBL protein sequence was characterized using various bioinformatics tools including phylogenetic analysis and structure prediction. We also reported the MrMBL gene expression pattern upon viral and bacterial infection in M. rosenbergii gills. It could be concluded that the prawn MBL may be one of the important molecule which
Ribonucleïnezuur (RNA) vervult twee verschillende rollen binnen een cel. Enerzijds heeft het molecuul de functie om informatie op te slaan (net zoals desoxyribonucleïnezuur (DNA)), anderzijds dient het als katalysator (op een manier zoals ook eiwit deze rol vervult). Bovendien kan RNA optreden als
David P Hall
Full Text Available Acute mountain sickness (AMS is a common problem among visitors at high altitude, and may progress to life-threatening pulmonary and cerebral oedema in a minority of cases. International consensus defines AMS as a constellation of subjective, non-specific symptoms. Specifically, headache, sleep disturbance, fatigue and dizziness are given equal diagnostic weighting. Different pathophysiological mechanisms are now thought to underlie headache and sleep disturbance during acute exposure to high altitude. Hence, these symptoms may not belong together as a single syndrome. Using a novel visual analogue scale (VAS, we sought to undertake a systematic exploration of the symptomatology of AMS using an unbiased, data-driven approach originally designed for analysis of gene expression. Symptom scores were collected from 292 subjects during 1110 subject-days at altitudes between 3650 m and 5200 m on Apex expeditions to Bolivia and Kilimanjaro. Three distinct patterns of symptoms were consistently identified. Although fatigue is a ubiquitous finding, sleep disturbance and headache are each commonly reported without the other. The commonest pattern of symptoms was sleep disturbance and fatigue, with little or no headache. In subjects reporting severe headache, 40% did not report sleep disturbance. Sleep disturbance correlates poorly with other symptoms of AMS (Mean Spearman correlation 0.25. These results challenge the accepted paradigm that AMS is a single disease process and describe at least two distinct syndromes following acute ascent to high altitude. This approach to analysing symptom patterns has potential utility in other clinical syndromes.
Fiziev, Petko; Akdemir, Kadir C; Miller, John P; Keung, Emily Z; Samant, Neha S; Sharma, Sneha; Natale, Christopher A; Terranova, Christopher J; Maitituoheti, Mayinuer; Amin, Samirkumar B; Martinez-Ledesma, Emmanuel; Dhamdhere, Mayura; Axelrad, Jacob B; Shah, Amiksha; Cheng, Christine S; Mahadeshwar, Harshad; Seth, Sahil; Barton, Michelle C; Protopopov, Alexei; Tsai, Kenneth Y; Davies, Michael A; Garcia, Benjamin A; Amit, Ido; Chin, Lynda; Ernst, Jason; Rai, Kunal
The extent and nature of epigenomic changes associated with melanoma progression is poorly understood. Through systematic epigenomic profiling of 35 epigenetic modifications and transcriptomic analysis, we define chromatin state changes associated with melanomagenesis by using a cell phenotypic model of non-tumorigenic and tumorigenic states. Computation of specific chromatin state transitions showed loss of histone acetylations and H3K4me2/3 on regulatory regions proximal to specific cancer-regulatory genes in important melanoma-driving cell signaling pathways. Importantly, such acetylation changes were also observed between benign nevi and malignant melanoma human tissues. Intriguingly, only a small fraction of chromatin state transitions correlated with expected changes in gene expression patterns. Restoration of acetylation levels on deacetylated loci by histone deacetylase (HDAC) inhibitors selectively blocked excessive proliferation in tumorigenic cells and human melanoma cells, suggesting functional roles of observed chromatin state transitions in driving hyperproliferative phenotype. Through these results, we define functionally relevant chromatin states associated with melanoma progression. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.
Hoenigsberg H. F.
Full Text Available The above refer to experiments present a new method which permits the study of philogenesis in the genus Drosophila. There are several types of results: a close kinship among the various geographical races of D. melanogaster in the neo-tropics coincides with their spectrophotometric similarities; b the interspecific differences are also identified with the photometric analysis; c finally there are optical density affinities among the various species which belong to the same taxonomic groups. Acknowledgment. The authors want to express their gratitude to Professor Everet of the physico-chemical laboratory of the National University for the use of his Beckman DU spectrophotometer and for his generous advice. This research is supported by the American Agricultural Research Service grant F. G. Co 107. For technical assistance we are indebted to Miss B. I. Cortés and to Mr. L. Castro.
Emami, Kaveh; Morris, Nicholas J; Cockell, Simon J; Golebiowska, Gabriela; Shu, Qing-Yao; Gatehouse, Angharad M R
The seed proteome of a low phytic acid (lpa) rice line (Os-lpa-XS110-1), developed as a novel food source, was compared to that of its parental line, Xiushui 110 (XS-110). Analysis by surfaced enhanced laser desorption ionization-time-of-flight mass spectrometry (SELDI-TOF MS) and two-dimensional gel electrophoresis (2-DE) allowed the detection of a potential low molecular weight biomarker and identification of 23 differentially expressed proteins that include stress-related proteins, storage proteins, and potential allergens. Bioinformatic analyses revealed that triose phosphate isomerase (TPI) and fructose bisphosphatealdolase (FBA), two major differentially expressed proteins, are involved in myo-inositol metabolism. Accumulation of globulin was also significantly decreased in the lpa line. This study demonstrates the potential of proteomic and bioinformatic profiling techniques for safety assessment of novel foods. Furthermore, these techniques provide powerful tools for studying functional genomics due to the possibility of identifying genes related to the mutated traits.
McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.
By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.
Braeckman Bart P
Full Text Available Abstract Free-living flatworms ("Turbellaria" are appropriate model organisms to gain better insight into the role of stem cells in ageing and rejuvenation. Ageing research in flatworms is, however, still scarce. This is partly due to culture difficulties and the lack of a complete set of demographic data, including parameters such as median lifespan and age-specific mortality rate. In this paper, we report on the first flatworm survival analysis. We used the species Macrostomum lignano, which is an emerging model for studying the reciprocal influence between stem cells, ageing and rejuvenation. This species has a median lifespan of 205 ± 13 days (average ± standard deviation [SD] and a 90th percentile lifespan of 373 ± 32 days. The maximum lifespan, however, is more than 745 days, and the average survival curve is characterised by a long tail because a small number of individuals lives twice as long as 90% of the population. Similar to earlier observations in a wide range of animals, in M. lignano the age-specific mortality rate increases exponentially, but levels off at the oldest ages. To compare the senescence of M. lignano with that of other ageing models, we determined the mortality rate doubling time, which is 0.20 ± 0.02 years. As a result, we can conclude that M. lignano shows gradual senescence at a rate similar to the vertebrate ageing models Rattus norvegicus and Mus musculus. We argue that M. lignano is a suitable model for ageing and rejuvenation research, and especially for the role of stem cells in these processes, due to its accessible stem cell system and regeneration capacity, and the possibility of combining stem cell studies with demographic analyses.
Mouton, Stijn; Willems, Maxime; Back, Patricia; Braeckman, Bart P; Borgonie, Gaetan
Free-living flatworms ("Turbellaria") are appropriate model organisms to gain better insight into the role of stem cells in ageing and rejuvenation. Ageing research in flatworms is, however, still scarce. This is partly due to culture difficulties and the lack of a complete set of demographic data, including parameters such as median lifespan and age-specific mortality rate. In this paper, we report on the first flatworm survival analysis. We used the species Macrostomum lignano, which is an emerging model for studying the reciprocal influence between stem cells, ageing and rejuvenation. This species has a median lifespan of 205 +/- 13 days (average +/- standard deviation [SD]) and a 90th percentile lifespan of 373 +/- 32 days. The maximum lifespan, however, is more than 745 days, and the average survival curve is characterised by a long tail because a small number of individuals lives twice as long as 90% of the population. Similar to earlier observations in a wide range of animals, in M. lignano the age-specific mortality rate increases exponentially, but levels off at the oldest ages. To compare the senescence of M. lignano with that of other ageing models, we determined the mortality rate doubling time, which is 0.20 +/- 0.02 years. As a result, we can conclude that M. lignano shows gradual senescence at a rate similar to the vertebrate ageing models Rattus norvegicus and Mus musculus. We argue that M. lignano is a suitable model for ageing and rejuvenation research, and especially for the role of stem cells in these processes, due to its accessible stem cell system and regeneration capacity, and the possibility of combining stem cell studies with demographic analyses.
Dimitrieva, Slavica; Bucher, Philipp
Genomic context analysis, also known as phylogenetic profiling, is widely used to infer functional interactions between proteins but rarely applied to non-coding cis-regulatory DNA elements. We were wondering whether this approach could provide insights about utlraconserved non-coding elements (UCNEs). These elements are organized as large clusters, so-called gene regulatory blocks (GRBs) around key developmental genes. Their molecular functions and the reasons for their high degree of conservation remain enigmatic. In a special setting of genomic context analysis, we analyzed the fate of GRBs after a whole-genome duplication event in five fish genomes. We found that in most cases all UCNEs were retained together as a single block, whereas the corresponding target genes were often retained in two copies, one completely devoid of UCNEs. This 'winner-takes-all' pattern suggests that UCNEs of a GRB function in a highly cooperative manner. We propose that the multitude of interactions between UCNEs is the reason for their extreme sequence conservation. Supplementary data are available at Bioinformatics online and at http://ccg.vital-it.ch/ucne/
The thesis focuses on two bioinformatics research topics: the development of tools for an efficient and reliable identification of single nucleotides polymorphisms (SNPs) and polymorphic simple sequence repeats (SSRs) from expressed sequence tags (ESTs) (Chapter 2, 3 and 4), and the subsequent
Biological databases are having a growth spurt. Much of this results from research in genetics and biodiversity, coupled with fast-paced developments in information technology. The revolution in bioinformatics, defined by Sugden and Pennisi (2000) as the "tools and techniques for...
An integrative bioinformatics pipeline for the genomewide identification of novel porcine microRNA genes. Wei Fang, Na Zhou, Dengyun Li, Zhigang Chen, Pengfei Jiang and Deli Zhang. J. Genet. 92,587 593. Figure 1. Primary sequence of the predicted SSc-mir-2053 precursor and locations of some terms in the secondary ...
Lelieveld, S.H.; Veltman, J.A.; Gilissen, C.F.
With the widespread adoption of next generation sequencing technologies by the genetics community and the rapid decrease in costs per base, exome sequencing has become a standard within the repertoire of genetic experiments for both research and diagnostics. Although bioinformatics now offers
Dec 6, 2013 ... The majority of miRNAs in pig (Sus scrofa), an impor- tant domestic animal, remain unknown. From this perspec- tive, we attempted the genomewide identification of novel porcine miRNAs. Here, we propose a novel integrative bioinformatics pipeline to identify conservative and non- conservative novel ...
Thus, there is the need for appropriate strategies of introducing the basic components of this emerging scientific field to part of the African populace through the development of an online distance education learning tool. This study involved the design of a bioinformatics online distance educative tool an implementation of ...
reaction (PCR), oligo hybridization and DNA sequencing. Proper primer design is actually one of the most important factors/steps in successful DNA sequencing. Various bioinformatics programs are available for selection of primer pairs from a template sequence. The plethora programs for PCR primer design reflects the.
Computational workflows in bioinformatics are becoming increasingly important in the achievement of scientific advances. These workflows typically require the integrated use of multiple, distributed data sources and analytic tools. The BioExtract Server (http://bioextract.org) is a distributed servi...
Kelley, Scott; Alger, Christianna; Deutschman, Douglas
The importance of Bioinformatics tools and methodology in modern biological research underscores the need for robust and effective courses at the college level. This paper describes such a course designed on the principles of cooperative learning based on a computer software industry production model called "Extreme Programming" (EP).…
Nielsen, Henrik; Sperotto, Maria Maddalena
)-based bioinformatics approach. The ANN was trained to recognize feature-based patterns in proteins that are considered to be associated with lipid rafts. The trained ANN was then used to predict protein raftophilicity. We found that, in the case of α-helical membrane proteins, their hydrophobic length does not affect...
Ondrej, Vladan; Dvorak, Petr
Bioinformatics, biological databases, and the worldwide use of computers have accelerated biological research in many fields, such as evolutionary biology. Here, we describe a primer of nucleotide sequence management and the construction of a phylogenetic tree with two examples; the two selected are from completely different groups of organisms:…
In recent years, new bioinformatics technologies, such as gene expression microarray, genome-wide association study, proteomics, and metabolomics, have been widely used to simultaneously identify a huge number of human genomic/genetic biomarkers, generate a tremendously large amount of data, and dramatically increase the knowledge on human…
Boyle, John A.
Bioinformatics has emerged as an important research tool in recent years. The ability to mine large databases for relevant information has become increasingly central to many different aspects of biochemistry and molecular biology. It is important that undergraduates be introduced to the available information and methodologies. We present a…
... on molecular biology, especially D N A sequence analysis and protein structure prediction. These two issues are also central to this book. Other application areas covered here are: interpretation of spectroscopic data and discovery of structure-function relationships in D N A and proteins. Figure 1 depicts the interdependence of computer science,...
Bansal Arvind K
Full Text Available Abstract The revolutionary growth in the computation speed and memory storage capability has fueled a new era in the analysis of biological data. Hundreds of microbial genomes and many eukaryotic genomes including a cleaner draft of human genome have been sequenced raising the expectation of better control of microorganisms. The goals are as lofty as the development of rational drugs and antimicrobial agents, development of new enhanced bacterial strains for bioremediation and pollution control, development of better and easy to administer vaccines, the development of protein biomarkers for various bacterial diseases, and better understanding of host-bacteria interaction to prevent bacterial infections. In the last decade the development of many new bioinformatics techniques and integrated databases has facilitated the realization of these goals. Current research in bioinformatics can be classified into: (i genomics – sequencing and comparative study of genomes to identify gene and genome functionality, (ii proteomics – identification and characterization of protein related properties and reconstruction of metabolic and regulatory pathways, (iii cell visualization and simulation to study and model cell behavior, and (iv application to the development of drugs and anti-microbial agents. In this article, we will focus on the techniques and their limitations in genomics and proteomics. Bioinformatics research can be classified under three major approaches: (1 analysis based upon the available experimental wet-lab data, (2 the use of mathematical modeling to derive new information, and (3 an integrated approach that integrates search techniques with mathematical modeling. The major impact of bioinformatics research has been to automate the genome sequencing, automated development of integrated genomics and proteomics databases, automated genome comparisons to identify the genome function, automated derivation of metabolic pathways, gene
Brazas, Michelle D; Ouellette, B F Francis
With the advent of YouTube channels in bioinformatics, open platforms for problem solving in bioinformatics, active web forums in computing analyses and online resources for learning to code or use a bioinformatics tool, the more traditional continuing education bioinformatics training programs have had to adapt. Bioinformatics training programs that solely rely on traditional didactic methods are being superseded by these newer resources. Yet such face-to-face instruction is still invaluable in the learning continuum. Bioinformatics.ca, which hosts the Canadian Bioinformatics Workshops, has blended more traditional learning styles with current online and social learning styles. Here we share our growing experiences over the past 12 years and look toward what the future holds for bioinformatics training programs.
Hiew, Hong Liang; Bellgard, Matthew
Life Science research faces the constant challenge of how to effectively handle an ever-growing body of bioinformatics software and online resources. The users and developers of bioinformatics resources have a diverse set of competing demands on how these resources need to be developed and organised. Unfortunately, there does not exist an adequate community-wide framework to integrate such competing demands. The problems that arise from this include unstructured standards development, the emergence of tools that do not meet specific needs of researchers, and often times a communications gap between those who use the tools and those who supply them. This paper presents an overview of the different functions and needs of bioinformatics stakeholders to determine what may be required in a community-wide framework. A Bioinformatics Reference Model is proposed as a basis for such a framework. The reference model outlines the functional relationship between research usage and technical aspects of bioinformatics resources. It separates important functions into multiple structured layers, clarifies how they relate to each other, and highlights the gaps that need to be addressed for progress towards a diverse, manageable, and sustainable body of resources. The relevance of this reference model to the bioscience research community, and its implications in progress for organising our bioinformatics resources, are discussed.
Ma, Yanyan; Yang, Mingkun; Lin, Xiaohuang; Liu, Xin; Huang, Hui; Ge, Feng
As a recently validated reversible post translational modification, lysine malonylation regulates diverse cellular processes from bacteria to mammals, but its existence and function in photosynthetic organisms remain unknown. Cyanobacteria are the most ancient group of photosynthetic prokaryotes and contribute about 50% of the total primary production on Earth. Previously, we reported the lysine acetylome in the model cyanobacterium Synechocystis sp. PCC 6803 (Synechocystis). Here we performed the first proteomic survey of lysine malonylation in Synechocystis using highly accurate tandem mass spectrometry in combination with affinity purification. We identified 598 lysine malonylation sites on 339 proteins with high confidence in total. A bioinformatic analysis suggested that these malonylated proteins may play various functions and were distributed in diverse subcellular compartments. Among them, many malonylated proteins were involved in cellular metabolism. The functional significance of lysine malonylation in the metabolic enzyme activity of phosphoglycerate kinase (PGK) was determined by site-specific mutagenesis and biochemical studies. Interestingly, 27 proteins involved in photosynthesis were found to be malonylated for the first time, suggesting that lysine malonylation may be involved in photosynthesis. Thus our results provide the first lysine malonylome in a photosynthetic organism and suggest a previously unexplored role of lysine malonylation in the regulation of metabolic processes and photosynthesis in Synechocystis as well as in other photosynthetic organisms.
Accardi, Luigi; Freudenberg, Wolfgang; Ohya, Masanori
The QP-DYN algorithms / L. Accardi, M. Regoli and M. Ohya -- Study of transcriptional regulatory network based on Cis module database / S. Akasaka ... [et al.] -- On Lie group-Lie algebra correspondences of unitary groups in finite von Neumann algebras / H. Ando, I. Ojima and Y. Matsuzawa -- On a general form of time operators of a Hamiltonian with purely discrete spectrum / A. Arai -- Quantum uncertainty and decision-making in game theory / M. Asano ... [et al.] -- New types of quantum entropies and additive information capacities / V. P. Belavkin -- Non-Markovian dynamics of quantum systems / D. Chruscinski and A. Kossakowski -- Self-collapses of quantum systems and brain activities / K.-H. Fichtner ... [et al.] -- Statistical analysis of random number generators / L. Accardi and M. Gabler -- Entangled effects of two consecutive pairs in residues and its use in alignment / T. Ham, K. Sato and M. Ohya -- The passage from digital to analogue in white noise analysis and applications / T. Hida -- Remarks on the degree of entanglement / D. Chruscinski ... [et al.] -- A completely discrete particle model derived from a stochastic partial differential equation by point systems / K.-H. Fichtner, K. Inoue and M. Ohya -- On quantum algorithm for exptime problem / S. Iriyama and M. Ohya -- On sufficient algebraic conditions for identification of quantum states / A. Jamiolkowski -- Concurrence and its estimations by entanglement witnesses / J. Jurkowski -- Classical wave model of quantum-like processing in brain / A. Khrennikov -- Entanglement mapping vs. quantum conditional probability operator / D. Chruscinski ... [et al.] -- Constructing multipartite entanglement witnesses / M. Michalski -- On Kadison-Schwarz property of quantum quadratic operators on M[symbol](C) / F. Mukhamedov and A. Abduganiev -- On phase transitions in quantum Markov chains on Cayley Tree / L. Accardi, F. Mukhamedov and M. Saburov -- Space(-time) emergence as symmetry breaking effect / I. Ojima
The aim of this review is to discuss the importance of bioinformatics and emphasize the need to acquire bioinformatics training and skills so as to maximize its potentials for improved delivery of animal health. In this review, bioinformatics is introduced, challenges to effective animal disease diagnosis, prevention and control, ...
Poe, D.; Venkatraman, N.; Hansen, C.; Singh, G.
There is an increasing need for an effective method of teaching bioinformatics. Increased progress and availability of computer-based tools for educating students have led to the implementation of a computer-based system for teaching bioinformatics as described in this paper. Bioinformatics is a recent, hybrid field of study combining elements of…
Schönbach, Christian; Verma, Chandra; Bond, Peter J; Ranganathan, Shoba
The International Conference on Bioinformatics (InCoB) has been publishing peer-reviewed conference papers in BMC Bioinformatics since 2006. Of the 44 articles accepted for publication in supplement issues of BMC Bioinformatics, BMC Genomics, BMC Medical Genomics and BMC Systems Biology, 24 articles with a bioinformatics or systems biology focus are reviewed in this editorial. InCoB2017 is scheduled to be held in Shenzen, China, September 20-22, 2017.
Grisham, William; Schottler, Natalie A; Valli-Marill, Joanne; Beck, Lisa; Beatty, Jackson
This completely computer-based module's purpose is to introduce students to bioinformatics resources. We present an easy-to-adopt module that weaves together several important bioinformatic tools so students can grasp how these tools are used in answering research questions. Students integrate information gathered from websites dealing with anatomy (Mouse Brain Library), quantitative trait locus analysis (WebQTL from GeneNetwork), bioinformatics and gene expression analyses (University of California, Santa Cruz Genome Browser, National Center for Biotechnology Information's Entrez Gene, and the Allen Brain Atlas), and information resources (PubMed). Instructors can use these various websites in concert to teach genetics from the phenotypic level to the molecular level, aspects of neuroanatomy and histology, statistics, quantitative trait locus analysis, and molecular biology (including in situ hybridization and microarray analysis), and to introduce bioinformatic resources. Students use these resources to discover 1) the region(s) of chromosome(s) influencing the phenotypic trait, 2) a list of candidate genes-narrowed by expression data, 3) the in situ pattern of a given gene in the region of interest, 4) the nucleotide sequence of the candidate gene, and 5) articles describing the gene. Teaching materials such as a detailed student/instructor's manual, PowerPoints, sample exams, and links to free Web resources can be found at http://mdcune.psych.ucla.edu/modules/bioinformatics.
Zhou, Sun; Ji, Guoli; Liu, Xiaolin; Li, Pei; Moler, James; Karro, John E; Liang, Chun
Expressed Sequence Tag (EST) sequences are widely used in applications such as genome annotation, gene discovery and gene expression studies. However, some of GenBank dbEST sequences have proven to be "unclean". Identification of cDNA termini/ends and their structures in raw ESTs not only facilitates data quality control and accurate delineation of transcription ends, but also furthers our understanding of the potential sources of data abnormalities/errors present in the wet-lab procedures for cDNA library construction. After analyzing a total of 309,976 raw Pinus taeda ESTs, we uncovered many distinct variations of cDNA termini, some of which prove to be good indicators of wet-lab artifacts, and characterized each raw EST by its cDNA terminus structure patterns. In contrast to the expected patterns, many ESTs displayed complex and/or abnormal patterns that represent potential wet-lab errors such as: a failure of one or both of the restriction enzymes to cut the plasmid vector; a failure of the restriction enzymes to cut the vector at the correct positions; the insertion of two cDNA inserts into a single vector; the insertion of multiple and/or concatenated adapters/linkers; the presence of 3'-end terminal structures in designated 5'-end sequences or vice versa; and so on. With a close examination of these artifacts, many problematic ESTs that have been deposited into public databases by conventional bioinformatics pipelines or tools could be cleaned or filtered by our methodology. We developed a software tool for Abnormality Filtering and Sequence Trimming for ESTs (AFST, http://code.google.com/p/afst/) using a pattern analysis approach. To compare AFST with other pipelines that submitted ESTs into dbEST, we reprocessed 230,783 Pinus taeda and 38,709 Arachis hypogaea GenBank ESTs. We found 7.4% of Pinus taeda and 29.2% of Arachis hypogaea GenBank ESTs are "unclean" or abnormal, all of which could be cleaned or filtered by AFST. cDNA terminal pattern analysis, as
Full Text Available Abstract Background Expressed Sequence Tag (EST sequences are widely used in applications such as genome annotation, gene discovery and gene expression studies. However, some of GenBank dbEST sequences have proven to be “unclean”. Identification of cDNA termini/ends and their structures in raw ESTs not only facilitates data quality control and accurate delineation of transcription ends, but also furthers our understanding of the potential sources of data abnormalities/errors present in the wet-lab procedures for cDNA library construction. Results After analyzing a total of 309,976 raw Pinus taeda ESTs, we uncovered many distinct variations of cDNA termini, some of which prove to be good indicators of wet-lab artifacts, and characterized each raw EST by its cDNA terminus structure patterns. In contrast to the expected patterns, many ESTs displayed complex and/or abnormal patterns that represent potential wet-lab errors such as: a failure of one or both of the restriction enzymes to cut the plasmid vector; a failure of the restriction enzymes to cut the vector at the correct positions; the insertion of two cDNA inserts into a single vector; the insertion of multiple and/or concatenated adapters/linkers; the presence of 3′-end terminal structures in designated 5′-end sequences or vice versa; and so on. With a close examination of these artifacts, many problematic ESTs that have been deposited into public databases by conventional bioinformatics pipelines or tools could be cleaned or filtered by our methodology. We developed a software tool for Abnormality Filtering and Sequence Trimming for ESTs (AFST, http://code.google.com/p/afst/ using a pattern analysis approach. To compare AFST with other pipelines that submitted ESTs into dbEST, we reprocessed 230,783 Pinus taeda and 38,709 Arachis hypogaea GenBank ESTs. We found 7.4% of Pinus taeda and 29.2% of Arachis hypogaea GenBank ESTs are “unclean” or abnormal, all of which could be cleaned
Gorodkin, Jan; Hofacker, Ivo L.; Ruzzo, Walter L.
RNA bioinformatics and computational RNA biology have emerged from implementing methods for predicting the secondary structure of single sequences. The field has evolved to exploit multiple sequences to take evolutionary information into account, such as compensating (and structure preserving) base...... changes. These methods have been developed further and applied for computational screens of genomic sequence. Furthermore, a number of additional directions have emerged. These include methods to search for RNA 3D structure, RNA-RNA interactions, and design of interfering RNAs (RNAi) as well as methods...... for interactions between RNA and proteins.Here, we introduce the basic concepts of predicting RNA secondary structure relevant to the further analyses of RNA sequences. We also provide pointers to methods addressing various aspects of RNA bioinformatics and computational RNA biology....
Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter
Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly
Full Text Available PURPOSE: Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. METHODS: This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. RESULTS: The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. CONCLUSIONS: The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets
Hildebrandt, Anna Katharina; Stöckel, Daniel; Fischer, Nina M; de la Garza, Luis; Krüger, Jens; Nickels, Stefan; Röttig, Marc; Schärfe, Charlotta; Schumann, Marcel; Thiel, Philipp; Lenhof, Hans-Peter; Kohlbacher, Oliver; Hildebrandt, Andreas
Web-based workflow systems have gained considerable momentum in sequence-oriented bioinformatics. In structural bioinformatics, however, such systems are still relatively rare; while commercial stand-alone workflow applications are common in the pharmaceutical industry, academic researchers often still rely on command-line scripting to glue individual tools together. In this work, we address the problem of building a web-based system for workflows in structural bioinformatics. For the underlying molecular modelling engine, we opted for the BALL framework because of its extensive and well-tested functionality in the field of structural bioinformatics. The large number of molecular data structures and algorithms implemented in BALL allows for elegant and sophisticated development of new approaches in the field. We hence connected the versatile BALL library and its visualization and editing front end BALLView with the Galaxy workflow framework. The result, which we call ballaxy, enables the user to simply and intuitively create sophisticated pipelines for applications in structure-based computational biology, integrated into a standard tool for molecular modelling. ballaxy consists of three parts: some minor modifications to the Galaxy system, a collection of tools and an integration into the BALL framework and the BALLView application for molecular modelling. Modifications to Galaxy will be submitted to the Galaxy project, and the BALL and BALLView integrations will be integrated in the next major BALL release. After acceptance of the modifications into the Galaxy project, we will publish all ballaxy tools via the Galaxy toolshed. In the meantime, all three components are available from http://www.ball-project.org/ballaxy. Also, docker images for ballaxy are available at https://registry.hub.docker.com/u/anhi/ballaxy/dockerfile/. ballaxy is licensed under the terms of the GPL. © The Author 2014. Published by Oxford University Press. All rights reserved. For
Liu, Yao-Yuan; Harbison, SallyAnn
Short tandem repeats, single nucleotide polymorphisms, and whole mitochondrial analyses are three classes of markers which will play an important role in the future of forensic DNA typing. The arrival of massively parallel sequencing platforms in forensic science reveals new information such as insights into the complexity and variability of the markers that were previously unseen, along with amounts of data too immense for analyses by manual means. Along with the sequencing chemistries employed, bioinformatic methods are required to process and interpret this new and extensive data. As more is learnt about the use of these new technologies for forensic applications, development and standardization of efficient, favourable tools for each stage of data processing is being carried out, and faster, more accurate methods that improve on the original approaches have been developed. As forensic laboratories search for the optimal pipeline of tools, sequencer manufacturers have incorporated pipelines into sequencer software to make analyses convenient. This review explores the current state of bioinformatic methods and tools used for the analyses of forensic markers sequenced on the massively parallel sequencing (MPS) platforms currently most widely used. Copyright © 2017 Elsevier B.V. All rights reserved.
Full Text Available Our previous study demonstrated that human KIAA0100 gene was a novel acute monocytic leukemia-associated antigen (MLAA gene. But the functional characterization of human KIAA0100 gene has remained unknown to date. Here, firstly, bioinformatic prediction of human KIAA0100 gene was carried out using online softwares; Secondly, Human KIAA0100 gene expression was downregulated by the clustered regularly interspaced short palindromic repeats (CRISPR/CRISPR-associated (Cas 9 system in U937 cells. Cell proliferation and apoptosis were next evaluated in KIAA0100-knockdown U937 cells. The bioinformatic prediction showed that human KIAA0100 gene was located on 17q11.2, and human KIAA0100 protein was located in the secretory pathway. Besides, human KIAA0100 protein contained a signalpeptide, a transmembrane region, three types of secondary structures (alpha helix, extended strand, and random coil , and four domains from mitochondrial protein 27 (FMP27. The observation on functional characterization of human KIAA0100 gene revealed that its downregulation inhibited cell proliferation, and promoted cell apoptosis in U937 cells. To summarize, these results suggest human KIAA0100 gene possibly comes within mitochondrial genome; moreover, it is a novel anti-apoptotic factor related to carcinogenesis or progression in acute monocytic leukemia, and may be a potential target for immunotherapy against acute monocytic leukemia.
Hugh P Shanahan
Full Text Available We discuss the applicability of the Microsoft cloud computing platform, Azure, for bioinformatics. We focus on the usability of the resource rather than its performance. We provide an example of how R can be used on Azure to analyse a large amount of microarray expression data deposited at the public database ArrayExpress. We provide a walk through to demonstrate explicitly how Azure can be used to perform these analyses in Appendix S1 and we offer a comparison with a local computation. We note that the use of the Platform as a Service (PaaS offering of Azure can represent a steep learning curve for bioinformatics developers who will usually have a Linux and scripting language background. On the other hand, the presence of an additional set of libraries makes it easier to deploy software in a parallel (scalable fashion and explicitly manage such a production run with only a few hundred lines of code, most of which can be incorporated from a template. We propose that this environment is best suited for running stable bioinformatics software by users not involved with its development.
Shanahan, Hugh P; Owen, Anne M; Harrison, Andrew P
We discuss the applicability of the Microsoft cloud computing platform, Azure, for bioinformatics. We focus on the usability of the resource rather than its performance. We provide an example of how R can be used on Azure to analyse a large amount of microarray expression data deposited at the public database ArrayExpress. We provide a walk through to demonstrate explicitly how Azure can be used to perform these analyses in Appendix S1 and we offer a comparison with a local computation. We note that the use of the Platform as a Service (PaaS) offering of Azure can represent a steep learning curve for bioinformatics developers who will usually have a Linux and scripting language background. On the other hand, the presence of an additional set of libraries makes it easier to deploy software in a parallel (scalable) fashion and explicitly manage such a production run with only a few hundred lines of code, most of which can be incorporated from a template. We propose that this environment is best suited for running stable bioinformatics software by users not involved with its development.
Cohen, K Bretonnel; Hunter, Lawrence E
Text mining for translational bioinformatics is a new field with tremendous research potential. It is a subfield of biomedical natural language processing that concerns itself directly with the problem of relating basic biomedical research to clinical practice, and vice versa. Applications of text mining fall both into the category of T1 translational research-translating basic science results into new interventions-and T2 translational research, or translational research for public health. Potential use cases include better phenotyping of research subjects, and pharmacogenomic research. A variety of methods for evaluating text mining applications exist, including corpora, structured test suites, and post hoc judging. Two basic principles of linguistic structure are relevant for building text mining applications. One is that linguistic structure consists of multiple levels. The other is that every level of linguistic structure is characterized by ambiguity. There are two basic approaches to text mining: rule-based, also known as knowledge-based; and machine-learning-based, also known as statistical. Many systems are hybrids of the two approaches. Shared tasks have had a strong effect on the direction of the field. Like all translational bioinformatics software, text mining software for translational bioinformatics can be considered health-critical and should be subject to the strictest standards of quality assurance and software testing.
Schneider, Maria Victoria; Watson, James; Attwood, Teresa; Rother, Kristian; Budd, Aidan; McDowall, Jennifer; Via, Allegra; Fernandes, Pedro; Nyronen, Tommy; Blicher, Thomas; Jones, Phil; Blatter, Marie-Claude; De Las Rivas, Javier; Judge, David Phillip; van der Gool, Wouter; Brooksbank, Cath
As bioinformatics becomes increasingly central to research in the molecular life sciences, the need to train non-bioinformaticians to make the most of bioinformatics resources is growing. Here, we review the key challenges and pitfalls to providing effective training for users of bioinformatics services, and discuss successful training strategies shared by a diverse set of bioinformatics trainers. We also identify steps that trainers in bioinformatics could take together to advance the state of the art in current training practices. The ideas presented in this article derive from the first Trainer Networking Session held under the auspices of the EU-funded SLING Integrating Activity, which took place in November 2009.
Schneider, M.V.; Watson, J.; Attwood, T.
As bioinformatics becomes increasingly central to research in the molecular life sciences, the need to train non-bioinformaticians to make the most of bioinformatics resources is growing. Here, we review the key challenges and pitfalls to providing effective training for users of bioinformatics...... services, and discuss successful training strategies shared by a diverse set of bioinformatics trainers. We also identify steps that trainers in bioinformatics could take together to advance the state of the art in current training practices. The ideas presented in this article derive from the first...
He, Yue-E; Qiu, Hui-Xian; Jiang, Jian-Bing; Wu, Rong-Zhou; Xiang, Ru-Lian; Zhang, Yuan-Hai
The aim of the present study was to identify key genes that may be involved in the pathogenesis of Tetralogy of Fallot (TOF) using bioinformatics methods. The GSE26125 microarray dataset, which includes cardiovascular tissue samples derived from 16 children with TOF and five healthy age-matched control infants, was downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed between TOF and control samples to identify differentially expressed genes (DEGs) using Student's t-test, and the R/limma package, with a log2 fold-change of >2 and a false discovery rate of <0.01 set as thresholds. The biological functions of DEGs were analyzed using the ToppGene database. The ReactomeFIViz application was used to construct functional interaction (FI) networks, and the genes in each module were subjected to pathway enrichment analysis. The iRegulon plugin was used to identify transcription factors predicted to regulate the DEGs in the FI network, and the gene-transcription factor pairs were then visualized using Cytoscape software. A total of 878 DEGs were identified, including 848 upregulated genes and 30 downregulated genes. The gene FI network contained seven function modules, which were all comprised of upregulated genes. Genes enriched in Module 1 were enriched in the following three neurological disorder-associated signaling pathways: Parkinson's disease, Alzheimer's disease and Huntington's disease. Genes in Modules 0, 3 and 5 were dominantly enriched in pathways associated with ribosomes and protein translation. The Xbox binding protein 1 transcription factor was demonstrated to be involved in the regulation of genes encoding the subunits of cytoplasmic and mitochondrial ribosomes, as well as genes involved in neurodegenerative disorders. Therefore, dysfunction of genes involved in signaling pathways associated with neurodegenerative disorders, ribosome function and protein translation may contribute to the pathogenesis of TOF
Zhao, Wei; Liu, Zhongjie; Yu, Xujiao; Lai, Luying; Li, Haobo; Liu, Zipeng; Li, Le; Jiang, Shan; Xia, Zhengyuan; Xu, Shi-yuan
Bupivacaine, a commonly used local anesthetic, has potential neurotoxicity through diverse signaling pathways. However, the key mechanism of bupivacaine-induced neurotoxicity remains unclear. Cultured human SH-SY5Y neuroblastoma cells were treated (bupivacaine) or untreated (control) with bupivacaine for 24 h. Compared to the control group, bupivacaine significantly increased cyto-inhibition, cellular reactive oxygen species, DNA damage, mitochondrial injury, apoptosis (increased TUNEL-positive cells, cleaved caspase 3, and Bcl-2/Bax), and activated autophagy (enhanced LC3II/LC3I ratio). To explore changes in protein expression and intercommunication among the pathways involved in bupivacaine-induced neurotoxicity, an 8-plex iTRAQ proteomic technique and bioinformatics analysis were performed. Compared to the control group, 241 differentially expressed proteins were identified, of which, 145 were up-regulated and 96 were down-regulated. Bioinformatics analysis of the cross-talk between the significant proteins with altered expression in bupivacaine-induced neurotoxicity indicated that phosphatidyl-3-kinase (PI3K) was the most frequently targeted protein in each of the interactions. We further confirmed these results by determining the downstream targets of the identified signaling pathways (PI3K, Akt, FoxO1, Erk, and JNK). In conclusion, our study demonstrated that PI3K may play a central role in contacting and regulating the signaling pathways that contribute to bupivacaine-induced neurotoxicity. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Rideout, Jai Ram; Chase, John H; Bolyen, Evan; Ackermann, Gail; González, Antonio; Knight, Rob; Caporaso, J Gregory
Bioinformatics software often requires human-generated tabular text files as input and has specific requirements for how those data are formatted. Users frequently manage these data in spreadsheet programs, which is convenient for researchers who are compiling the requisite information because the spreadsheet programs can easily be used on different platforms including laptops and tablets, and because they provide a familiar interface. It is increasingly common for many different researchers to be involved in compiling these data, including study coordinators, clinicians, lab technicians and bioinformaticians. As a result, many research groups are shifting toward using cloud-based spreadsheet programs, such as Google Sheets, which support the concurrent editing of a single spreadsheet by different users working on different platforms. Most of the researchers who enter data are not familiar with the formatting requirements of the bioinformatics programs that will be used, so validating and correcting file formats is often a bottleneck prior to beginning bioinformatics analysis. We present Keemei, a Google Sheets Add-on, for validating tabular files used in bioinformatics analyses. Keemei is available free of charge from Google's Chrome Web Store. Keemei can be installed and run on any web browser supported by Google Sheets. Keemei currently supports the validation of two widely used tabular bioinformatics formats, the Quantitative Insights into Microbial Ecology (QIIME) sample metadata mapping file format and the Spatially Referenced Genetic Data (SRGD) format, but is designed to easily support the addition of others. Keemei will save researchers time and frustration by providing a convenient interface for tabular bioinformatics file format validation. By allowing everyone involved with data entry for a project to easily validate their data, it will reduce the validation and formatting bottlenecks that are commonly encountered when human-generated data files are
Full Text Available ColE1 plasmids are important vehicles for the spread of antibiotic resistance in the Enterobacteriaceae and Pasteurellaceae families of bacteria. Their monitoring is essential, as they harbor important resistant determinants in humans, animals and the environment. In this work, we have analyzed ColE1 replicons using bioinformatic and experimental approaches. First, we carried out a computational study examining the structure of different ColE1 plasmids deposited in databases. Bioinformatic analysis of these ColE1 replicons revealed a mosaic genetic structure consisting of a host-adapted conserved region responsible for the housekeeping functions of the plasmid, and a variable region encoding a wide variety of genes, including multiple antibiotic resistance determinants. From this exhaustive computational analysis we developed a new PCR-based technique, targeting a specific sequence in the conserved region, for the screening, capture and sequencing of these small plasmids, either specific for Enterobacteriaceae or specific for Pasteurellaceae. To validate this PCR-based system, we tested various collections of isolates from both bacterial families, finding that ColE1 replicons were not only highly prevalent in antibiotic-resistant isolates, but also present in susceptible bacteria. In Pasteurellaceae, ColE1 plasmids carried almost exclusively antibiotic resistance genes. In Enterobacteriaceae, these plasmids encoded a large range of traits, including not only antibiotic resistance determinants, but also a wide variety of genes, showing the huge genetic plasticity of these small replicons. Finally, we also used a metagenomic approach in order to validate this technique, performing this PCR system using total DNA extractions from fecal samples from poultry, turkeys, pigs and humans. Using Illumina sequencing of the PCR products we identified a great diversity of genes encoded by ColE1 replicons, including different antibiotic resistance
Taylor, Ronald C.
Bioinformatics researchers are increasingly confronted with analysis of ultra large-scale data sets, a problem that will only increase at an alarming rate in coming years. Recent developments in open source software, that is, the Hadoop project and associated software, provide a foundation for scaling to petabyte scale data warehouses on Linux clusters, providing fault-tolerant parallelized analysis on such data using a programming style named MapReduce. An overview is given of the current usage within the bioinformatics community of Hadoop, a top-level Apache Software Foundation project, and of associated open source software projects. The concepts behind Hadoop and the associated HBase project are defined, and current bioinformatics software that employ Hadoop is described. The focus is on next-generation sequencing, as the leading application area to date.
Goto, Naohisa; Prins, Pjotr; Nakao, Mitsuteru; Bonnal, Raoul; Aerts, Jan; Katayama, Toshiaki
The BioRuby software toolkit contains a comprehensive set of free development tools and libraries for bioinformatics and molecular biology, written in the Ruby programming language. BioRuby has components for sequence analysis, pathway analysis, protein modelling and phylogenetic analysis; it supports many widely used data formats and provides easy access to databases, external programs and public web services, including BLAST, KEGG, GenBank, MEDLINE and GO. BioRuby comes with a tutorial, documentation and an interactive environment, which can be used in the shell, and in the web browser. BioRuby is free and open source software, made available under the Ruby license. BioRuby runs on all platforms that support Ruby, including Linux, Mac OS X and Windows. And, with JRuby, BioRuby runs on the Java Virtual Machine. The source code is available from http://www.bioruby.org/. email@example.com
Halim, Adnan; Carlsson, Michael C; Mathiesen, Caroline Benedicte K
characterization by bottom-up analysis. In addition, top-down mass spectrometry is utilized for targeted analysis of individual proteins, revealing hitherto unknown PTMs of HDM allergens. We demonstrate the presence of lysine-linked polyhexose glycans and asparagine-linked N-acetylhexosamine glycans on HDM...
Mulder, Nicola J.; Adebiyi, Ezekiel; Alami, Raouf; Benkahla, Alia; Brandful, James; Doumbia, Seydou; Everett, Dean; Fadlelmola, Faisal M.; Gaboun, Fatima; Gaseitsiwe, Simani; Ghazal, Hassan; Hazelhurst, Scott; Hide, Winston; Ibrahimi, Azeddine; Jaufeerally Fakim, Yasmina; Jongeneel, C. Victor; Joubert, Fourie; Kassim, Samar; Kayondo, Jonathan; Kumuthini, Judit; Lyantagaye, Sylvester; Makani, Julie; Mansour Alzohairy, Ahmed; Masiga, Daniel; Moussa, Ahmed; Nash, Oyekanmi; Ouwe Missi Oukem-Boyer, Odile; Owusu-Dabo, Ellis; Panji, Sumir; Patterton, Hugh; Radouani, Fouzia; Sadki, Khalid; Seghrouchni, Fouad; Tastan Bishop, Özlem; Tiffin, Nicki; Ulenga, Nzovu
The application of genomics technologies to medicine and biomedical research is increasing in popularity, made possible by new high-throughput genotyping and sequencing technologies and improved data analysis capabilities. Some of the greatest genetic diversity among humans, animals, plants, and microbiota occurs in Africa, yet genomic research outputs from the continent are limited. The Human Heredity and Health in Africa (H3Africa) initiative was established to drive the development of genomic research for human health in Africa, and through recognition of the critical role of bioinformatics in this process, spurred the establishment of H3ABioNet, a pan-African bioinformatics network for H3Africa. The limitations in bioinformatics capacity on the continent have been a major contributory factor to the lack of notable outputs in high-throughput biology research. Although pockets of high-quality bioinformatics teams have existed previously, the majority of research institutions lack experienced faculty who can train and supervise bioinformatics students. H3ABioNet aims to address this dire need, specifically in the area of human genetics and genomics, but knock-on effects are ensuring this extends to other areas of bioinformatics. Here, we describe the emergence of genomics research and the development of bioinformatics in Africa through H3ABioNet. PMID:26627985
Müller, Boje; Groscurth, Sira; Menzel, Matthias; Rüping, Boris A.; Twyman, Richard M.; Prüfer, Dirk; Noll, Gundula A.
Background and Aims Forisomes are specialized structural phloem proteins that mediate sieve element occlusion after wounding exclusively in papilionoid legumes, but most studies of forisome structure and function have focused on the Old World clade rather than the early lineages. A comprehensive phylogenetic, molecular, structural and functional analysis of forisomes from species covering a broad spectrum of the papilionoid legumes was therefore carried out, including the first analysis of Dipteryx panamensis forisomes, representing the earliest branch of the Papilionoideae lineage. The aim was to study the molecular, structural and functional conservation among forisomes from different tribes and to establish the roles of individual forisome subunits. Methods Sequence analysis and bioinformatics were combined with structural and functional analysis of native forisomes and artificial forisome-like protein bodies, the latter produced by expressing forisome genes from different legumes in a heterologous background. The structure of these bodies was analysed using a combination of confocal laser scanning microscopy (CLSM), scanning electron microscopy (SEM) and transmission electron microscopy (TEM), and the function of individual subunits was examined by combinatorial expression, micromanipulation and light microscopy. Key Results Dipteryx panamensis native forisomes and homomeric protein bodies assembled from the single sieve element occlusion by forisome (SEO-F) subunit identified in this species were structurally and functionally similar to forisomes from the Old World clade. In contrast, homomeric protein bodies assembled from individual SEO-F subunits from Old World species yielded artificial forisomes differing in proportion to their native counterparts, suggesting that multiple SEO-F proteins are required for forisome assembly in these plants. Structural differences between Medicago truncatula native forisomes, homomeric protein bodies and heteromeric bodies
Liu, Lin; Tang, Lin; Dong, Wen; Yao, Shaowen; Zhou, Wei
With the rapid accumulation of biological datasets, machine learning methods designed to automate data analysis are urgently needed. In recent years, so-called topic models that originated from the field of natural language processing have been receiving much attention in bioinformatics because of their interpretability. Our aim was to review the application and development of topic models for bioinformatics. This paper starts with the description of a topic model, with a focus on the understanding of topic modeling. A general outline is provided on how to build an application in a topic model and how to develop a topic model. Meanwhile, the literature on application of topic models to biological data was searched and analyzed in depth. According to the types of models and the analogy between the concept of document-topic-word and a biological object (as well as the tasks of a topic model), we categorized the related studies and provided an outlook on the use of topic models for the development of bioinformatics applications. Topic modeling is a useful method (in contrast to the traditional means of data reduction in bioinformatics) and enhances researchers' ability to interpret biological information. Nevertheless, due to the lack of topic models optimized for specific biological data, the studies on topic modeling in biological data still have a long and challenging road ahead. We believe that topic models are a promising method for various applications in bioinformatics research.
Reproducibility in Data Analysis research has long been a significant concern, particularly in the areas of Bioinformatics and Computational Biology. Towards the aim of developing reproducible and reusable processes, Data Analysis management tools can help giving structure and coherence to complex data flows. Nonetheless, improved software quality comes at the cost of additional design and planning effort, which may become impractical in rapidly changing development environments. I propose that an adjustment of focus from processes to data in the management of Bioinformatic pipelines may help improving reproducibility with minimal impact on preexisting development practices. In this paper I introduce the repo R package for bioinformatic analysis management. The tool supports a data-centered philosophy that aims at improving analysis reproducibility and reusability with minimal design overhead. The core of repo lies in its support for easy data storage, retrieval, distribution and annotation. In repo the data analysis flow is derived a posteriori from dependency annotations. The repo package constitutes an unobtrusive data and flow management extension of the R statistical language. Its adoption, together with good development practices, can help improving data analysis management, sharing and reproducibility, especially in the fields of Bioinformatics and Computational Biology.
Fan, Ben; Li, Yu-Long; Li, Lei; Peng, Xiao-Jun; Bu, Chen; Wu, Xiao-Qin; Borriss, Rainer
Using the combination of affinity enrichment and high-resolution LC-MS/MS analysis, we performed a large-scale lysine malonylation analysis in the model representative of Gram-positive plant growth-promoting rhizobacteria (PGPR), Bacillus amyloliquefaciens FZB42. Altogether, 809 malonyllysine sites in 382 proteins were identified. The bioinformatic analysis revealed that lysine malonylation occurs on the proteins involved in a variety of biological functions including central carbon metabolism, fatty acid biosynthesis and metabolism, NAD(P) binding and translation machinery. A group of proteins known to be implicated in rhizobacterium-plant interaction were also malonylated; especially, the enzymes responsible for antibiotic production including polyketide synthases (PKSs) and nonribosomal peptide synthases (NRPSs) were highly malonylated. Furthermore, our analysis showed malonylation occurred on proteins structure with higher surface accessibility and appeared to be conserved in many bacteria but not in archaea. The results provide us valuable insights into the potential roles of lysine malonylation in governing bacterial metabolism and cellular processes. Although in mammalian cells some important findings have been discovered that protein malonylation is related to basic metabolism and chronic disease, few studies have been performed on prokaryotic malonylome. In this study, we determined the malonylation profiles of Bacillus amyloliquefaciens FZB42, a model organism of Gram-positive plant growth-promoting rhizobacteria. FZB42 is known for the extensive investigations on its strong ability of producing antimicrobial polyketides and its potent activities of stimulating plant growth. Our analysis shows that malonylation is highly related to the polyketide synthases and the proteins involved bacterial interactions with plants. The results not only provide one of the first malonylomes for exploring the biochemical nature of bacterial proteins, but also shed light on
Karimzadeh, Mehran; Hoffman, Michael M
Investing in documenting your bioinformatics software well can increase its impact and save your time. To maximize the effectiveness of your documentation, we suggest following a few guidelines we propose here. We recommend providing multiple avenues for users to use your research software, including a navigable HTML interface with a quick start, useful help messages with detailed explanation and thorough examples for each feature of your software. By following these guidelines, you can assure that your hard work maximally benefits yourself and others. © The Author 2017. Published by Oxford University Press.
The general audience for these lectures is mainly physicists, computer scientists, engineers or the general public wanting to know more about what’s going on in the biosciences. What’s bioinformatics and why is all this fuss being made about it ? What’s this revolution triggered by the human genome project ? Are there any results yet ? What are the problems ? What new avenues of research have been opened up ? What about the technology ? These new developments will be compared with what happened at CERN earlier in its evolution, and it is hoped that the similiraties and contrasts will stimulate new curiosity and provoke new thoughts.
Handl, Julia; Kell, Douglas B; Knowles, Joshua
This paper reviews the application of multiobjective optimization in the fields of bioinformatics and computational biology. A survey of existing work, organized by application area, forms the main body of the review, following an introduction to the key concepts in multiobjective optimization. An original contribution of the review is the identification of five distinct "contexts," giving rise to multiple objectives: These are used to explain the reasons behind the use of multiobjective optimization in each application area and also to point the way to potential future uses of the technique.
Full Text Available Allergies and/or food intolerances are a growing problem of the modern world. Diffi culties associated with the correct diagnosis of food allergies result in the need to classify the factors causing allergies and allergens themselves. Therefore, internet databases and other bioinformatic tools play a special role in deepening knowledge of biologically-important compounds. Internet repositories, as a source of information on different chemical compounds, including those related to allergy and intolerance, are increasingly being used by scientists. Bioinformatic methods play a signifi cant role in biological and medical sciences, and their importance in food science is increasing. This study aimed at presenting selected databases and tools of bioinformatic analysis useful in research on food allergies, allergens (11 databases, epitopes (7 databases, and haptens (2 databases. It also presents examples of the application of computer methods in studies related to allergies.
Accardi, L.; Freudenberg, Wolfgang; Ohya, Masanori
/ H. Kamimura -- Massive collection of full-length complementary DNA clones and microarray analyses: keys to rice transcriptome analysis / S. Kikuchi -- Changes of influenza A(H5) viruses by means of entropic chaos degree / K. Sato and M. Ohya -- Basics of genome sequence analysis in bioinformatics - its fundamental ideas and problems / T. Suzuki and S. Miyazaki -- A basic introduction to gene expression studies using microarray expression data analysis / D. Wanke and J. Kilian -- Integrating biological perspectives: a quantum leap for microarray expression analysis / D. Wanke ... [et al.].
Taylor, Ronald C
Bioinformatics researchers are now confronted with analysis of ultra large-scale data sets, a problem that will only increase at an alarming rate in coming years. Recent developments in open source software, that is, the Hadoop project and associated software, provide a foundation for scaling to petabyte scale data warehouses on Linux clusters, providing fault-tolerant parallelized analysis on such data using a programming style named MapReduce. An overview is given of the current usage within the bioinformatics community of Hadoop, a top-level Apache Software Foundation project, and of associated open source software projects. The concepts behind Hadoop and the associated HBase project are defined, and current bioinformatics software that employ Hadoop is described. The focus is on next-generation sequencing, as the leading application area to date. Hadoop and the MapReduce programming paradigm already have a substantial base in the bioinformatics community, especially in the field of next-generation sequencing analysis, and such use is increasing. This is due to the cost-effectiveness of Hadoop-based analysis on commodity Linux clusters, and in the cloud via data upload to cloud vendors who have implemented Hadoop/HBase; and due to the effectiveness and ease-of-use of the MapReduce method in parallelization of many data analysis algorithms.
With the development of the Internet and the growth of online resources, bioinformatics training for wet-lab biologists became necessary as a part of their education. This article describes a one-semester course 'Applied Bioinformatics Course' (ABC, http://abc.cbi.pku.edu.cn/) that the author has been teaching to biological graduate students at the Peking University and the Chinese Academy of Agricultural Sciences for the past 13 years. ABC is a hands-on practical course to teach students to use online bioinformatics resources to solve biological problems related to their ongoing research projects in molecular biology. With a brief introduction to the background of the course, detailed information about the teaching strategies of the course are outlined in the 'How to teach' section. The contents of the course are briefly described in the 'What to teach' section with some real examples. The author wishes to share his teaching experiences and the online teaching materials with colleagues working in bioinformatics education both in local and international universities. © The Author 2013. Published by Oxford University Press.
Katayama, T.; Arakawa, K.; Nakao, M.; Prins, J.C.P.
Web services have become a key technology for bioinformatics, since life science databases are globally decentralized and the exponential increase in the amount of available data demands for efficient systems without the need to transfer entire databases for every step of an analysis. However,
van der Pouw Kraan, T. C. T. M.; van der Laan, A. M.; Piek, J. J.; Horrevoets, A. J. G.
In this review we compare expression studies on monocyte subsets as an example to show the integrated possibilities of molecular databases and bioinformatic analysis tools. Monocytes have been recognized as cells with great plasticity and differentiation potential that play a pivotal role in
Alyuruk, Hakan; Cavas, Levent
Genomics and proteomics projects have produced a huge amount of raw biological data including DNA and protein sequences. Although these data have been stored in data banks, their evaluation is strictly dependent on bioinformatics tools. These tools have been developed by multidisciplinary experts for fast and robust analysis of biological data.…
Oct 10, 2006 ... Bioinformatics has delivered great contributions to genome and genomics research, without which the world-wide success of this and other global ('omics') approaches would not have been possible. More recently, it has developed further towards the analysis of different kinds of networks thus laying the ...
Full Text Available Wheat seed development is an important physiological process of seed maturation and directly affects wheat yield and quality. In this study, we performed dynamic transcriptome microarray analysis of an elite Chinese bread wheat cultivar (Jimai 20 during grain development using the GeneChip Wheat Genome Array. Grain morphology and scanning electron microscope observations showed that the period of 11–15 days post-anthesis (DPA was a key stage for the synthesis and accumulation of seed starch. Genome-wide transcriptional profiling and significance analysis of microarrays revealed that the period from 11 to 15 DPA was more important than the 15–20 DPA stage for the synthesis and accumulation of nutritive reserves. Series test of cluster analysis of differential genes revealed five statistically significant gene expression profiles. Gene ontology annotation and enrichment analysis gave further information about differentially expressed genes, and MapMan analysis revealed expression changes within functional groups during seed development. Metabolic pathway network analysis showed that major and minor metabolic pathways regulate one another to ensure regular seed development and nutritive reserve accumulation. We performed gene co-expression network analysis to identify genes that play vital roles in seed development and identified several key genes involved in important metabolic pathways. The transcriptional expression of eight key genes involved in starch and protein synthesis and stress defense was further validated by qRT-PCR. Our results provide new insight into the molecular mechanisms of wheat seed development and the determinants of yield and quality.
Yue Sheng; Wei Zhao; Ying Song; Zhigang Li; Majing Luo; Quan Lei; Hanhua Cheng; Rongjia Zhou
A variety of mechanisms are engaged in sex determination in vertebrates. The teleost fish swamp eel undergoes sex reversal naturally and is an ideal model for vertebrate sexual development. However, the importance of proteome-wide scanning for gonad reversal was not previously determined. We report a 2-D electrophoresis analysis of three gonad types of proteomes during sex reversal. MS/MS analysis revealed a group of differentially expressed proteins during ovary to ovotestis to testis transf...
Applied bioinformatics skills are becoming ever more indispensable for biologists, yet incorporation of these skills into the undergraduate biology curriculum is lagging behind, in part due to a lack of instructors willing and able to teach basic bioinformatics in classes that don't specifically focus on quantitative skill development, such as statistics or computer sciences. To help undergraduate course instructors who themselves did not learn bioinformatics as part of their own education and are hesitant to plunge into teaching big data analysis, a module was developed that is written in plain-enough language, using publicly available computing tools and data, to allow novice instructors to teach next-generation sequence analysis to upper-level undergraduate students. To determine if the module allowed students to develop a better understanding of and appreciation for applied bioinformatics, various tools were developed and employed to assess the impact of the module. This article describes both the module and its assessment. Students found the activity valuable for their education and, in focus group discussions, emphasized that they saw a need for more and earlier instruction of big data analysis as part of the undergraduate biology curriculum.
Li, Shengjie; Shen, Li; Sun, Lianjie; Xu, Jiao; Jin, Ping; Chen, Liming; Ma, Fei
Drosophila have served as a model for research on innate immunity for decades. However, knowledge of the post-transcriptional regulation of immune gene expression by microRNAs (miRNAs) remains rudimentary. In the present study, using small RNA-seq and bioinformatics analysis, we identified 67 differentially expressed miRNAs in Drosophila infected with Escherichia coli compared to injured flies at three time-points. Furthermore, we found that 21 of these miRNAs were potentially involved in the regulation of Imd pathway-related genes. Strikingly, based on UAS-miRNAs line screening and Dual-luciferase assay, we identified that miR-9a and miR-981 could both negatively regulate Drosophila antibacterial defenses and decrease the level of the antibacterial peptide, Diptericin. Taken together, these data support the involvement of miRNAs in the regulation of the Drosophila Imd pathway. Copyright © 2017 Elsevier Ltd. All rights reserved.
Kevin Barnett; Carol Miller; Tyron J. Venn
A goal of fire management in wilderness is to allow fire to play its natural ecological role without intervention. Unfortunately, most unplanned ignitions in wilderness are suppressed, in part because of the risk they might pose to values outside of the wilderness. We capitalize on recent advances in fire risk analysis to demonstrate a risk-based approach for revealing...
Full Text Available Abstract Background HIV-1 Nef protein contributes to pathogenesis via multiple functions that include enhancement of viral replication and infectivity, alteration of intracellular trafficking, and modulation of cellular signaling pathways. Nef stimulates formation of tunneling nanotubes and virological synapses, and is transferred to bystander cells via these intercellular contacts and secreted microvesicles. Nef associates with and activates Pak2, a kinase that regulates T-cell signaling and actin cytoskeleton dynamics, but how Nef promotes nanotube formation is unknown. Results To identify Nef binding partners involved in Pak2-association dependent Nef functions, we employed tandem mass spectrometry analysis of Nef immunocomplexes from Jurkat cells expressing wild-type Nef or Nef mutants defective for the ability to associate with Pak2 (F85L, F89H, H191F and A72P, A75P in NL4-3. We report that wild-type, but not mutant Nef, was associated with 5 components of the exocyst complex (EXOC1, EXOC2, EXOC3, EXOC4, and EXOC6, an octameric complex that tethers vesicles at the plasma membrane, regulates polarized exocytosis, and recruits membranes and proteins required for nanotube formation. Additionally, Pak2 kinase was associated exclusively with wild-type Nef. Association of EXOC1, EXOC2, EXOC3, and EXOC4 with wild-type, but not mutant Nef, was verified by co-immunoprecipitation assays in Jurkat cells. Furthermore, shRNA-mediated depletion of EXOC2 in Jurkat cells abrogated Nef-mediated enhancement of nanotube formation. Using bioinformatic tools, we visualized protein interaction networks that reveal functional linkages between Nef, the exocyst complex, and the cellular endocytic and exocytic trafficking machinery. Conclusions Exocyst complex proteins are likely a key effector of Nef-mediated enhancement of nanotube formation, and possibly microvesicle secretion. Linkages revealed between Nef and the exocyst complex suggest a new paradigm of
Ashoori, Maryam; Burns, Catherine M.; d'Entremont, Barbara; Momtahan, Kathryn
Cognitive work analysis (CWA) as an analytical approach for examining complex sociotechnical systems has shown success in modelling the work of single operators. The CWA approach incorporates social and team interactions, but a more explicit analysis of team aspects can reveal more information for systems design. In this paper, Team CWA is explored to understand teamwork within a birthing unit at a hospital. Team CWA models are derived from theories and models of teamworkand leverage the existing CWA approaches to analyse team interactions. Team CWA is explained and contrasted with prior approaches to CWA. Team CWA does not replace CWA, but supplements traditional CWA to more easily reveal team information. As a result, Team CWA may be a useful approach to enhance CWA in complex environments where effective teamwork is required. Practitioner Summary: This paper looks at ways of analysing cognitive work in healthcare teams. Team Cognitive Work Analysis, when used to supplement traditional Cognitive Work Analysis, revealed more team information than traditional Cognitive Work Analysis. Team Cognitive Work Analysis should be considered when studying teams PMID:24837514
Ashoori, Maryam; Burns, Catherine M; d'Entremont, Barbara; Momtahan, Kathryn
Cognitive work analysis (CWA) as an analytical approach for examining complex sociotechnical systems has shown success in modelling the work of single operators. The CWA approach incorporates social and team interactions, but a more explicit analysis of team aspects can reveal more information for systems design. In this paper, Team CWA is explored to understand teamwork within a birthing unit at a hospital. Team CWA models are derived from theories and models of teamwork and leverage the existing CWA approaches to analyse team interactions. Team CWA is explained and contrasted with prior approaches to CWA. Team CWA does not replace CWA, but supplements traditional CWA to more easily reveal team information. As a result, Team CWA may be a useful approach to enhance CWA in complex environments where effective teamwork is required. This paper looks at ways of analysing cognitive work in healthcare teams. Team Cognitive Work Analysis, when used to supplement traditional Cognitive Work Analysis, revealed more team information than traditional Cognitive Work Analysis. Team Cognitive Work Analysis should be considered when studying teams.
Zhou, Yinhua; Datta, Saheli; Salter, Charlotte
The governments of China, India, and the United Kingdom are unanimous in their belief that bioinformatics should supply the link between basic life sciences research and its translation into health benefits for the population and the economy. Yet at the same time, as ambitious states vying for position in the future global bioeconomy they differ considerably in the strategies adopted in pursuit of this goal. At the heart of these differences lies the interaction between epistemic change within the scientific community itself and the apparatus of the state. Drawing on desk-based research and thirty-two interviews with scientists and policy makers in the three countries, this article analyzes the politics that shape this interaction. From this analysis emerges an understanding of the variable capacities of different kinds of states and political systems to work with science in harnessing the potential of new epistemic territories in global life sciences innovation. PMID:27546935
Scheuermann, Richard H; Sinkovits, Robert S; Schenkelberg, Theodore; Koff, Wayne C
Biomedical research has become a data intensive science in which high throughput experimentation is producing comprehensive data about biological systems at an ever-increasing pace. The Human Vaccines Project is a new public-private partnership, with the goal of accelerating development of improved vaccines and immunotherapies for global infectious diseases and cancers by decoding the human immune system. To achieve its mission, the Project is developing a Bioinformatics Hub as an open-source, multidisciplinary effort with the overarching goal of providing an enabling infrastructure to support the data processing, analysis and knowledge extraction procedures required to translate high throughput, high complexity human immunology research data into biomedical knowledge, to determine the core principles driving specific and durable protective immune responses.
Tucker, Allan; Duplisea, Daniel
There has been a huge effort in the advancement of analytical techniques for molecular biological data over the past decade. This has led to many novel algorithms that are specialized to deal with data associated with biological phenomena, such as gene expression and protein interactions. In contrast, ecological data analysis has remained focused to some degree on off-the-shelf statistical techniques though this is starting to change with the adoption of state-of-the-art methods, where few assumptions can be made about the data and a more explorative approach is required, for example, through the use of Bayesian networks. In this paper, some novel bioinformatics tools for microarray data are discussed along with their ‘crossover potential’ with an application to fisheries data. In particular, a focus is made on the development of models that identify functionally equivalent species in different fish communities with the aim of predicting functional collapse. PMID:22144390
Chen, X; Xie, Z H; Lv, Y X; Tang, Q P; Zhang, H; Zhang, J Y; Wu, B; Jiang, W H
Proteomics tools can be used to identify the differentially expressed proteins related to allergic rhinitis (AR). However, the large numbers of proteins related to AR have not yet been explored using an advanced quantitative proteomics approach, known as isobaric tags for relative and absolute quantitation (iTRAQ). To identify differentially expressed proteins in persistent AR patients and to explore the regulatory signalling pathways involving the identified proteins. Forty-five persistent AR patients and 20 healthy controls were recruited for this study. iTRAQ was used to identify the proteins that were differentially expressed between these two groups, and a bioinformatics analysis was then conducted to identify the signalling pathways associated with the identified proteins. Immunofluorescence labelling was performed to detect alpha-2-macroglobulin (A2M), STAT3, p-STAT3 and IL17 in the nasal mucosa. A total of 133 differentially expressed proteins were identified. We then determined the top 10 regulatory pathways associated with these proteins and found that the blood coagulation pathway had the most significant association. A2M, a protein involved in the blood coagulation pathway, was found to be differentially expressed in the serum of AR patients. The bioinformatics analysis indicated that STAT3 is an upstream transcription factor that might regulate A2M expression. An immunofluorescence study further confirmed that STAT3 and A2M are co-localized in nasal mucosa cells. Additionally, A2M, STAT3, p-STAT3, and IL17 are elevated in AR patients. The expressional level of A2M is positively related to IL17 and the symptom of the congestion in AR subjects. The blood coagulation pathway may be a key regulatory network pathway contributing to the allergic inflammatory response in AR patients. A2M, which is regulated by STAT3, may be an important protein in the pathogenesis of allergic rhinitis in AR patients. © 2016 John Wiley & Sons Ltd.
Surangi W. Punyasena
Full Text Available Recent advances in microscopy, imaging, and data analyses have permitted both the greater application of quantitative methods and the collection of large data sets that can be used to investigate plant morphology. This special issue, the first for Applications in Plant Sciences, presents a collection of papers highlighting recent methods in the quantitative study of plant form. These emerging biometric and bioinformatic approaches to plant sciences are critical for better understanding how morphology relates to ecology, physiology, genotype, and evolutionary and phylogenetic history. From microscopic pollen grains and charcoal particles, to macroscopic leaves and whole root systems, the methods presented include automated classification and identification, geometric morphometrics, and skeleton networks, as well as tests of the limits of human assessment. All demonstrate a clear need for these computational and morphometric approaches in order to increase the consistency, objectivity, and throughput of plant morphological studies.
ACADEMIC TRAINING LECTURE SERIES 27, 28 February 1, 2, 3 March 2006 from 11:00 to 12:00 - Auditorium, bldg. 500 Decoding the Genome A special series of 5 lectures on: Recent extraordinary advances in the life sciences arising through new detection technologies and bioinformatics The past five years have seen an extraordinary change in the information and tools available in the life sciences. The sequencing of the human genome, the discovery that we possess far fewer genes than foreseen, the measurement of the tiny changes in the genomes that differentiate us, the sequencing of the genomes of many pathogens that lead to diseases such as malaria are all examples of completely new information that is now available in the quest for improved healthcare. New tools have allowed similar strides in the discovery of the associated protein structures, providing invaluable information for those searching for new drugs. New DNA microarray chips permit simultaneous measurement of the state of expression of tens...
J. Köster (Johannes)
textabstractWe present Rust-Bio, the first general purpose bioinformatics library for the innovative Rust programming language. Rust-Bio leverages the unique combination of speed, memory safety and high-level syntax offered by Rust to provide a fast and safe set of bioinformatics algorithms and data
The main bottleneck in advancing genomics in present times is the lack of expertise in using bioinformatics tools and approaches for data mining in raw DNA sequences generated by modern high throughput technologies such as next generation sequencing. Although bioinformatics has been making major progress and ...
Nomi L Harris
Full Text Available The Bioinformatics Open Source Conference (BOSC is organized by the Open Bioinformatics Foundation (OBF, a nonprofit group dedicated to promoting the practice and philosophy of open source software development and open science within the biological research community. Since its inception in 2000, BOSC has provided bioinformatics developers with a forum for communicating the results of their latest efforts to the wider research community. BOSC offers a focused environment for developers and users to interact and share ideas about standards; software development practices; practical techniques for solving bioinformatics problems; and approaches that promote open science and sharing of data, results, and software. BOSC is run as a two-day special interest group (SIG before the annual Intelligent Systems in Molecular Biology (ISMB conference. BOSC 2015 took place in Dublin, Ireland, and was attended by over 125 people, about half of whom were first-time attendees. Session topics included "Data Science;" "Standards and Interoperability;" "Open Science and Reproducibility;" "Translational Bioinformatics;" "Visualization;" and "Bioinformatics Open Source Project Updates". In addition to two keynote talks and dozens of shorter talks chosen from submitted abstracts, BOSC 2015 included a panel, titled "Open Source, Open Door: Increasing Diversity in the Bioinformatics Open Source Community," that provided an opportunity for open discussion about ways to increase the diversity of participants in BOSC in particular, and in open source bioinformatics in general. The complete program of BOSC 2015 is available online at http://www.open-bio.org/wiki/BOSC_2015_Schedule.
Life sciences research and development has opened up new challenges and opportunities for bioinformatics. The contribution of bioinformatics advances made possible the mapping of the entire human genome and genomes of many other organisms in just over a decade. These discoveries, along with current efforts to ...
Harris, Nomi L; Cock, Peter J A; Lapp, Hilmar; Chapman, Brad; Davey, Rob; Fields, Christopher; Hokamp, Karsten; Munoz-Torres, Monica
The Bioinformatics Open Source Conference (BOSC) is organized by the Open Bioinformatics Foundation (OBF), a nonprofit group dedicated to promoting the practice and philosophy of open source software development and open science within the biological research community. Since its inception in 2000, BOSC has provided bioinformatics developers with a forum for communicating the results of their latest efforts to the wider research community. BOSC offers a focused environment for developers and users to interact and share ideas about standards; software development practices; practical techniques for solving bioinformatics problems; and approaches that promote open science and sharing of data, results, and software. BOSC is run as a two-day special interest group (SIG) before the annual Intelligent Systems in Molecular Biology (ISMB) conference. BOSC 2015 took place in Dublin, Ireland, and was attended by over 125 people, about half of whom were first-time attendees. Session topics included "Data Science;" "Standards and Interoperability;" "Open Science and Reproducibility;" "Translational Bioinformatics;" "Visualization;" and "Bioinformatics Open Source Project Updates". In addition to two keynote talks and dozens of shorter talks chosen from submitted abstracts, BOSC 2015 included a panel, titled "Open Source, Open Door: Increasing Diversity in the Bioinformatics Open Source Community," that provided an opportunity for open discussion about ways to increase the diversity of participants in BOSC in particular, and in open source bioinformatics in general. The complete program of BOSC 2015 is available online at http://www.open-bio.org/wiki/BOSC_2015_Schedule.
Buttigieg, Pier Luigi
Using live presentation to communicate the interdisciplinary and abstract content of bioinformatics to its educationally diverse studentship is a sizeable challenge. This review collects a number of perspectives on multimedia presentation, visual communication and pedagogy. The aim is to encourage educators to reflect on the great potential of live presentation in facilitating bioinformatics education.
Bioinformatics has advanced the course of research and future veterinary vaccines development because it has provided new tools for identification of vaccine targets from sequenced biological data of organisms. In Nigeria, there is lack of bioinformatics training in the universities, expect for short training courses in which ...
Howard, David R.; Miskowski, Jennifer A.; Grunwald, Sandra K.; Abler, Michael L.
At the University of Wisconsin-La Crosse, we have undertaken a program to integrate the study of bioinformatics across the undergraduate life science curricula. Our efforts have included incorporating bioinformatics exercises into courses in the biology, microbiology, and chemistry departments, as well as coordinating the efforts of faculty within…
Probabilistic topic models have been developed for applications in various domains such as text mining, information retrieval and computer vision and bioinformatics domain. In this thesis, we focus on developing novel probabilistic topic models for image mining and bioinformatics studies. Specifically, a probabilistic topic-connection (PTC) model…
Ramlo, Susan E.; McConnell, David; Duan, Zhong-Hui; Moore, Francisco B.
Faculty at a Midwestern metropolitan public university recently developed a course on bioinformatics that emphasized collaboration and inquiry. Bioinformatics, essentially the application of computational tools to biological data, is inherently interdisciplinary. Thus part of the challenge of creating this course was serving the needs and…
Shi, Lizhen [Florida State Univ., Tallahassee, FL (United States); Wang, Zhong [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Yu, Weikuan [Florida State Univ., Tallahassee, FL (United States); Meng, Xiandong [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
The combination of the Hadoop MapReduce programming model and cloud computing allows biological scientists to analyze next-generation sequencing (NGS) data in a timely and cost-effective manner. Cloud computing platforms remove the burden of IT facility procurement and management from end users and provide ease of access to Hadoop clusters. However, biological scientists are still expected to choose appropriate Hadoop parameters for running their jobs. More importantly, the available Hadoop tuning guidelines are either obsolete or too general to capture the particular characteristics of bioinformatics applications. In this paper, we aim to minimize the cloud computing cost spent on bioinformatics data analysis by optimizing the extracted significant Hadoop parameters. When using MapReduce-based bioinformatics tools in the cloud, the default settings often lead to resource underutilization and wasteful expenses. We choose k-mer counting, a representative application used in a large number of NGS data analysis tools, as our study case. Experimental results show that, with the fine-tuned parameters, we achieve a total of 4× speedup compared with the original performance (using the default settings). Finally, this paper presents an exemplary case for tuning MapReduce-based bioinformatics applications in the cloud, and documents the key parameters that could lead to significant performance benefits.
Magalhães, Wagner C S; Rodrigues, Maíra R; Silva, Donnys; Soares-Souza, Giordano; Iannini, Márcia L; Cerqueira, Gustavo C; Faria-Campos, Alessandra C; Tarazona-Santos, Eduardo
Large-scale genomics initiatives such as the HapMap project and the 1000-genomes rely on powerful bioinformatics support to assist data production and analysis. Contrastingly, few bioinformatics platforms oriented to smaller research groups exist to store, handle, share, and integrate data from different sources, as well as to assist these scientists to perform their analyses efficiently. We developed such a bioinformatics platform, DIVERGENOME, to assist population genetics and genetic epidemiology studies performed by small- to medium-sized research groups. The platform is composed of two integrated components, a relational database (DIVERGENOMEdb), and a set of tools to convert data formats as required by popular software in population genetics and genetic epidemiology (DIVERGENOMEtools). In DIVERGENOMEdb, information on genotypes, polymorphism, laboratory protocols, individuals, populations, and phenotypes is organized in projects. These can be queried according to permissions. Here, we validated DIVERGENOME through a use case regarding the analysis of SLC2A4 genetic diversity in human populations. DIVERGENOME, with its intuitive Web interface and automatic data loading capability, facilitates its use by individuals without bioinformatics background, allowing complex queries to be easily interrogated and straightforward data format conversions (not available in similar platforms). DIVERGENOME is open source, freely available, and can be accessed online (pggenetica.icb.ufmg.br/divergenome) or hosted locally. © 2012 Wiley Periodicals, Inc.
Full Text Available This paper is on data analysis strategy in a complex, multidimensional, and dynamic domain. The focus is on the use of data mining techniques to explore the importance of multivariate structures; using climate variables which influences climate change. Techniques involved in data mining exercise vary according to the data structures. The multivariate analysis strategy considered here involved choosing an appropriate tool to analyze a process. Factor analysis is introduced into data mining technique in order to reveal the influencing impacts of factors involved as well as solving for multicolinearity effect among the variables. The temporal nature and multidimensionality of the target variables is revealed in the model using multidimensional regression estimates. The strategy of integrating the method of several statistical techniques, using climate variables in Nigeria was employed. R2 of 0.518 was obtained from the ordinary least square regression analysis carried out and the test was not significant at 5% level of significance. However, factor analysis regression strategy gave a good fit with R2 of 0.811 and the test was significant at 5% level of significance. Based on this study, model building should go beyond the usual confirmatory data analysis (CDA, rather it should be complemented with exploratory data analysis (EDA in order to achieve a desired result.
Brooksbank, Cath; Morgan, Sarah L.; Rosenwald, Anne; Warnow, Tandy; Welch, Lonnie
Bioinformatics is recognized as part of the essential knowledge base of numerous career paths in biomedical research and healthcare. However, there is little agreement in the field over what that knowledge entails or how best to provide it. These disagreements are compounded by the wide range of populations in need of bioinformatics training, with divergent prior backgrounds and intended application areas. The Curriculum Task Force of the International Society of Computational Biology (ISCB) Education Committee has sought to provide a framework for training needs and curricula in terms of a set of bioinformatics core competencies that cut across many user personas and training programs. The initial competencies developed based on surveys of employers and training programs have since been refined through a multiyear process of community engagement. This report describes the current status of the competencies and presents a series of use cases illustrating how they are being applied in diverse training contexts. These use cases are intended to demonstrate how others can make use of the competencies and engage in the process of their continuing refinement and application. The report concludes with a consideration of remaining challenges and future plans. PMID:29390004
Chen, Yadong; Chang, Yaqing; Wang, Xiuli; Qiu, Xuemei; Liu, Yang
Strongylocentrotus intermedius is an important marine species in north China and Japan. Recent years, diseases are threating the sea urchin aquaculture industry seriously. To provide a genetic resource for S. intermedius as well as overview the immune-related genes of S. intermedius, we performed transcriptome sequencing of three cDNA libraries representing three tissues, coelomocytes, gut and peristomial membrane respectively. In total 138,421 contigs were assembled from all sequencing data. 96,764 contigs were annotated according to bioinformatics databases, including NT, nr, Swiss-Prot, KEGG, COG. 49,336 Contigs were annotated as CDS. In this study, we obtained 24,778 gene families from S. intermedius transcriptome. The gene expression analysis revealed that more genes were expressed in gut, more high expression level genes in coelomocytes when compared with other tissues. Specific expressed contigs in coelomocytes, gut, and peristomial membrane were 546, 1136, and 1012 respectively. Pathway analysis suggested 25, 17 and 36 potential specifically pathways may specific progressed in peristomial membrane, gut and coelomocytes respectively. Similarities and differences between S. intermedius and other echinoderms were analyzed. S. intermedius was more homology to Strongylocentrotus purpuratus than others sea urchin. Of 24,778 genes, 1074 genes are immune-related, immune genes were expressed with a higher level in coelomocytes than other tissues. Complement system may be the most important immune system in sea urchin. We also identified 2438 SSRs and 16,236 SNPs for S. intermedius. These results provide a transcriptome resource and foundation to study molecular mechanisms of sea urchin immune system. Copyright © 2015 Elsevier Ltd. All rights reserved.
Background Teaching bioinformatics at universities is complicated by typical computer classroom settings. As well as running software locally and online, students should gain experience of systems administration. For a future career in biology or bioinformatics, the installation of software is a useful skill. We propose that this may be taught by running the course on GNU/Linux running on inexpensive Raspberry Pi computer hardware, for which students may be granted full administrator access. Results We release 4273π, an operating system image for Raspberry Pi based on Raspbian Linux. This includes minor customisations for classroom use and includes our Open Access bioinformatics course, 4273π Bioinformatics for Biologists. This is based on the final-year undergraduate module BL4273, run on Raspberry Pi computers at the University of St Andrews, Semester 1, academic year 2012–2013. Conclusions 4273π is a means to teach bioinformatics, including systems administration tasks, to undergraduates at low cost. PMID:23937194
Barker, Daniel; Ferrier, David Ek; Holland, Peter Wh; Mitchell, John Bo; Plaisier, Heleen; Ritchie, Michael G; Smart, Steven D
Teaching bioinformatics at universities is complicated by typical computer classroom settings. As well as running software locally and online, students should gain experience of systems administration. For a future career in biology or bioinformatics, the installation of software is a useful skill. We propose that this may be taught by running the course on GNU/Linux running on inexpensive Raspberry Pi computer hardware, for which students may be granted full administrator access. We release 4273π, an operating system image for Raspberry Pi based on Raspbian Linux. This includes minor customisations for classroom use and includes our Open Access bioinformatics course, 4273π Bioinformatics for Biologists. This is based on the final-year undergraduate module BL4273, run on Raspberry Pi computers at the University of St Andrews, Semester 1, academic year 2012-2013. 4273π is a means to teach bioinformatics, including systems administration tasks, to undergraduates at low cost.
Roellig, Daniela; Tan-Cabugao, Johanna; Esaian, Sevan; Bronner, Marianne E
The 'neural plate border' of vertebrate embryos contains precursors of neural crest and placode cells, both defining vertebrate characteristics. How these lineages segregate from neural and epidermal fates has been a matter of debate. We address this by performing a fine-scale quantitative temporal analysis of transcription factor expression in the neural plate border of chick embryos. The results reveal significant overlap of transcription factors characteristic of multiple lineages in individual border cells from gastrula through neurula stages. Cell fate analysis using a Sox2 (neural) enhancer reveals that cells that are initially Sox2+ cells can contribute not only to neural tube but also to neural crest and epidermis. Moreover, modulating levels of Sox2 or Pax7 alters the apportionment of neural tube versus neural crest fates. Our results resolve a long-standing question and suggest that many individual border cells maintain ability to contribute to multiple ectodermal lineages until or beyond neural tube closure.
Zhao, Zhongtao; Liu, Huiquan; Wang, Chenfang; Xu, Jin-Rong
Fungi produce a variety of carbohydrate activity enzymes (CAZymes) for the degradation of plant polysaccharide materials to facilitate infection and/or gain nutrition. Identifying and comparing CAZymes from fungi with different nutritional modes or infection mechanisms may provide information for better understanding of their life styles and infection models. To date, over hundreds of fungal genomes are publicly available. However, a systematic comparative analysis of fungal CAZymes across the entire fungal kingdom has not been reported. In this study, we systemically identified glycoside hydrolases (GHs), polysaccharide lyases (PLs), carbohydrate esterases (CEs), and glycosyltransferases (GTs) as well as carbohydrate-binding modules (CBMs) in the predicted proteomes of 103 representative fungi from Ascomycota, Basidiomycota, Chytridiomycota, and Zygomycota. Comparative analysis of these CAZymes that play major roles in plant polysaccharide degradation revealed that fungi exhibit tremendous diversity in the number and variety of CAZymes. Among them, some families of GHs and CEs are the most prevalent CAZymes that are distributed in all of the fungi analyzed. Importantly, cellulases of some GH families are present in fungi that are not known to have cellulose-degrading ability. In addition, our results also showed that in general, plant pathogenic fungi have the highest number of CAZymes. Biotrophic fungi tend to have fewer CAZymes than necrotrophic and hemibiotrophic fungi. Pathogens of dicots often contain more pectinases than fungi infecting monocots. Interestingly, besides yeasts, many saprophytic fungi that are highly active in degrading plant biomass contain fewer CAZymes than plant pathogenic fungi. Furthermore, analysis of the gene expression profile of the wheat scab fungus Fusarium graminearum revealed that most of the CAZyme genes related to cell wall degradation were up-regulated during plant infection. Phylogenetic analysis also revealed a complex
d'Aspremont-Lynden, Claude; Dos Santos Ferreira, Rodolphe
We use a comprehensive model of strategic household behaviour in which the spouses' expenditure on each public good is decomposed into autonomous spending and coordinated spending à la Lindahl. We obtain a continuum of semi-cooperative regimes parameterized by the relative weights put on autonomous spending, by each spouse and for each public good, nesting full cooperative and non-cooperative regimes as limit cases. Testing is approached through revealed preference analysis, by looking for ra...
Background Fungi produce a variety of carbohydrate activity enzymes (CAZymes) for the degradation of plant polysaccharide materials to facilitate infection and/or gain nutrition. Identifying and comparing CAZymes from fungi with different nutritional modes or infection mechanisms may provide information for better understanding of their life styles and infection models. To date, over hundreds of fungal genomes are publicly available. However, a systematic comparative analysis of fungal CAZymes across the entire fungal kingdom has not been reported. Results In this study, we systemically identified glycoside hydrolases (GHs), polysaccharide lyases (PLs), carbohydrate esterases (CEs), and glycosyltransferases (GTs) as well as carbohydrate-binding modules (CBMs) in the predicted proteomes of 103 representative fungi from Ascomycota, Basidiomycota, Chytridiomycota, and Zygomycota. Comparative analysis of these CAZymes that play major roles in plant polysaccharide degradation revealed that fungi exhibit tremendous diversity in the number and variety of CAZymes. Among them, some families of GHs and CEs are the most prevalent CAZymes that are distributed in all of the fungi analyzed. Importantly, cellulases of some GH families are present in fungi that are not known to have cellulose-degrading ability. In addition, our results also showed that in general, plant pathogenic fungi have the highest number of CAZymes. Biotrophic fungi tend to have fewer CAZymes than necrotrophic and hemibiotrophic fungi. Pathogens of dicots often contain more pectinases than fungi infecting monocots. Interestingly, besides yeasts, many saprophytic fungi that are highly active in degrading plant biomass contain fewer CAZymes than plant pathogenic fungi. Furthermore, analysis of the gene expression profile of the wheat scab fungus Fusarium graminearum revealed that most of the CAZyme genes related to cell wall degradation were up-regulated during plant infection. Phylogenetic analysis also
M?ller, Sebastian; Balaz, Miroslav; Stefanicka, Patrik; Varga, Lukas; Amri, Ez-Zoubir; Ukropec, Jozef; Wollscheid, Bernd; Wolfrum, Christian
Human brown adipose tissue (BAT) has become an attractive target to combat the current epidemical spread of obesity and its associated co-morbidities. Currently, information on its functional role is primarily derived from rodent studies. Here, we present the first comparative proteotype analysis of primary human brown adipose tissue versus adjacent white adipose tissue, which reveals significant quantitative differences in protein abundances and in turn differential functional capabilities. ...
Brejnrod, Asker Daniel
two conditions. The purpose is to assess the false discovery rate, recovery of truly differential abundant bacteria and the impact of beta diversity exploration strategies commonly used in microbiome research. We assess these differences by simulation and by making biological assumptions about...... of various molecular methods to build hypotheses about the impact of a copper contaminated soil. The introduction is a broad introduction to the field of microbiome research with a focus on the technologies that enable these discoveries and how some of the broader issues have related to this thesis...... 1 ,“Large-scale benchmarking reveals false discoveries and count transformation sensitivity in 16S rRNA gene amplicon data analysis methods used in microbiome studies”, benchmarked the performance of a variety of popular statistical methods for discovering differentially abundant bacteria . between...
Manyam, Ganiraju; Payton, Michelle A.; Roth, Jack A.; Abruzzo, Lynne V.; Coombes, Kevin R.
With the proliferation of high-throughput technologies, genome-level data analysis has become common in molecular biology. Bioinformaticians are developing extensive resources to annotate and mine biological features from high-throughput data. The underlying database management systems for most bioinformatics software are based on a relational model. Modern non-relational databases offer an alternative that has flexibility, scalability, and a non-rigid design schema. Moreover, with an accelerated development pace, non-relational databases like CouchDB can be ideal tools to construct bioinformatics utilities. We describe CouchDB by presenting three new bioinformatics resources: (a) geneSmash, which collates data from bioinformatics resources and provides automated gene-centric annotations, (b) drugBase, a database of drug-target interactions with a web interface powered by geneSmash, and (c) HapMap-CN, which provides a web interface to query copy number variations from three SNP-chip HapMap datasets. In addition to the web sites, all three systems can be accessed programmatically via web services. PMID:22609849
Guingab-Cagmat, J.D.; Cagmat, E.B.; Hayes, R.L.; Anagli, J.
Traumatic brain injury (TBI) is a major medical crisis without any FDA-approved pharmacological therapies that have been demonstrated to improve functional outcomes. It has been argued that discovery of disease-relevant biomarkers might help to guide successful clinical trials for TBI. Major advances in mass spectrometry (MS) have revolutionized the field of proteomic biomarker discovery and facilitated the identification of several candidate markers that are being further evaluated for their efficacy as TBI biomarkers. However, several hurdles have to be overcome even during the discovery phase which is only the first step in the long process of biomarker development. The high-throughput nature of MS-based proteomic experiments generates a massive amount of mass spectral data presenting great challenges in downstream interpretation. Currently, different bioinformatics platforms are available for functional analysis and data mining of MS-generated proteomic data. These tools provide a way to convert data sets to biologically interpretable results and functional outcomes. A strategy that has promise in advancing biomarker development involves the triad of proteomics, bioinformatics, and systems biology. In this review, a brief overview of how bioinformatics and systems biology tools analyze, transform, and interpret complex MS datasets into biologically relevant results is discussed. In addition, challenges and limitations of proteomics, bioinformatics, and systems biology in TBI biomarker discovery are presented. A brief survey of researches that utilized these three overlapping disciplines in TBI biomarker discovery is also presented. Finally, examples of TBI biomarkers and their applications are discussed. PMID:23750150
Attwood, Teresa K; Blackford, Sarah; Brazas, Michelle D; Davies, Angela; Schneider, Maria Victoria
Bioinformatics is now intrinsic to life science research, but the past decade has witnessed a continuing deficiency in this essential expertise. Basic data stewardship is still taught relatively rarely in life science education programmes, creating a chasm between theory and practice, and fuelling demand for bioinformatics training across all educational levels and career roles. Concerned by this, surveys have been conducted in recent years to monitor bioinformatics and computational training needs worldwide. This article briefly reviews the principal findings of a number of these studies. We see that there is still a strong appetite for short courses to improve expertise and confidence in data analysis and interpretation; strikingly, however, the most urgent appeal is for bioinformatics to be woven into the fabric of life science degree programmes. Satisfying the relentless training needs of current and future generations of life scientists will require a concerted response from stakeholders across the globe, who need to deliver sustainable solutions capable of both transforming education curricula and cultivating a new cadre of trainer scientists. © The Author 2017. Published by Oxford University Press.
Caroline H. Johnson
Full Text Available Abstract Background Cancer cells that enter the metastatic cascade require traits that allow them to survive within the circulation and colonize distant organ sites. As disseminating cancer cells adapt to their changing microenvironments, they also modify their metabolism and metabolite production. Methods A mouse xenograft model of spontaneous tumor metastasis was used to determine the metabolic rewiring that occurs between primary cancers and their metastases. An “autonomous” mass spectrometry-based untargeted metabolomic workflow with integrative metabolic pathway analysis revealed a number of differentially regulated metabolites in primary mammary fat pad (MFP tumors compared to microdissected paired lung metastases. The study was further extended to analyze metabolites in paired normal tissues which determined the potential influence of metabolites from the microenvironment. Results Metabolomic analysis revealed that multiple metabolites were increased in metastases, including cholesterol sulfate and phospholipids (phosphatidylglycerols and phosphatidylethanolamine. Metabolite analysis of normal lung tissue in the mouse model also revealed increased levels of these metabolites compared to tissues from normal MFP and primary MFP tumors, indicating potential extracellular uptake by cancer cells in lung metastases. These results indicate a potential functional importance of cholesterol sulfate and phospholipids in propagating metastasis. In addition, metabolites involved in DNA/RNA synthesis and the TCA cycle were decreased in lung metastases compared to primary MFP tumors. Conclusions Using an integrated metabolomic workflow, this study identified a link between cholesterol sulfate and phospholipids, metabolic characteristics of the metastatic niche, and the capacity of tumor cells to colonize distant sites.
Hernández-de-Diego, Rafael; de Villiers, Etienne P; Klingström, Tomas; Gourlé, Hadrien; Conesa, Ana; Bongcam-Rudloff, Erik
Bioinformatics skills have become essential for many research areas; however, the availability of qualified researchers is usually lower than the demand and training to increase the number of able bioinformaticians is an important task for the bioinformatics community. When conducting training or hands-on tutorials, the lack of control over the analysis tools and repositories often results in undesirable situations during training, as unavailable online tools or version conflicts may delay, complicate, or even prevent the successful completion of a training event. The eBioKit is a stand-alone educational platform that hosts numerous tools and databases for bioinformatics research and allows training to take place in a controlled environment. A key advantage of the eBioKit over other existing teaching solutions is that all the required software and databases are locally installed on the system, significantly reducing the dependence on the internet. Furthermore, the architecture of the eBioKit has demonstrated itself to be an excellent balance between portability and performance, not only making the eBioKit an exceptional educational tool but also providing small research groups with a platform to incorporate bioinformatics analysis in their research. As a result, the eBioKit has formed an integral part of training and research performed by a wide variety of universities and organizations such as the Pan African Bioinformatics Network (H3ABioNet) as part of the initiative Human Heredity and Health in Africa (H3Africa), the Southern Africa Network for Biosciences (SAnBio) initiative, the Biosciences eastern and central Africa (BecA) hub, and the International Glossina Genome Initiative.
Agarwal, Krishna; Prasad, Dilip K
This paper presents eigen-analysis of image stack of blinking fluorophores to identify the components that enable super-resolved imaging of blinking fluorophores. Eigen-analysis reveals that the contributions of spatial distribution of fluorophores and their temporal photon emission characteristics can be completely separated. While cross-emitter cross-pixel information of spatial distribution that permits super-resolution is encoded in two matrices, temporal statistics weigh the contribution of these matrices to the measured data. The properties and conditions of exploitation of these matrices are investigated. Con-temporary super-resolution imaging methods that use blinking for super-resolution are studied in the context of the presented analysis. Besides providing insight into the capabilities and limitations of existing super-resolution methods, the analysis shall help in designing better super-resolution techniques that directly exploit these matrices.
Brazas, Michelle D; Ouellette, B F Francis
Bioinformatics.ca has been hosting continuing education programs in introductory and advanced bioinformatics topics in Canada since 1999 and has trained more than 2,000 participants to date. These workshops have been adapted over the years to keep pace with advances in both science and technology as well as the changing landscape in available learning modalities and the bioinformatics training needs of our audience. Post-workshop surveys have been a mandatory component of each workshop and are used to ensure appropriate adjustments are made to workshops to maximize learning. However, neither bioinformatics.ca nor others offering similar training programs have explored the long-term impact of bioinformatics continuing education training. Bioinformatics.ca recently initiated a look back on the impact its workshops have had on the career trajectories, research outcomes, publications, and collaborations of its participants. Using an anonymous online survey, bioinformatics.ca analyzed responses from those surveyed and discovered its workshops have had a positive impact on collaborations, research, publications, and career progression.
Wang, Yijun; Lu, Wenjie; Deng, Dexiang
Diverse bioinformatic resources have been developed for plant transcription factor (TF) research. This review presents the bioinformatic resources and methodologies for the elucidation of plant TF-mediated biological events. Such information is helpful to dissect the transcriptional regulatory systems in the three reference plants Arabidopsis , rice, and maize and translation to other plants. Transcription factors (TFs) orchestrate diverse biological programs by the modulation of spatiotemporal patterns of gene expression via binding cis-regulatory elements. Advanced sequencing platforms accompanied by emerging bioinformatic tools revolutionize the scope and extent of TF research. The system-level integration of bioinformatic resources is beneficial to the decoding of TF-involved networks. Herein, we first briefly introduce general and specialized databases for TF research in three reference plants Arabidopsis, rice, and maize. Then, as proof of concept, we identified and characterized heat shock transcription factor (HSF) members through the TF databases. Finally, we present how the integration of bioinformatic resources at -omics layers can aid the dissection of TF-mediated pathways. We also suggest ways forward to improve the bioinformatic resources of plant TFs. Leveraging these bioinformatic resources and methodologies opens new avenues for the elucidation of transcriptional regulatory systems in the three model systems and translation to other plants.
Full Text Available ABSTRACT:The traditional methods for mining foods for bioactive peptides are tedious and long. Similar to the drug industry, the length of time to identify and deliver a commercial health ingredient that reduces disease symptoms can take anything between 5 to 10 years. Reducing this time and effort is crucial in order to create new commercially viable products with clear and important health benefits. In the past few years, bioinformatics, the science that brings together fast computational biology, and efficient genome mining, is appearing as the long awaited solution to this problem. By quickly mining food genomes for characteristics of certain food therapeutic ingredients, researchers can potentially find new ones in a matter of a few weeks. Yet, surprisingly, very little success has been achieved so far using bioinformatics in mining for food bioactives.The absence of food specific bioinformatic mining tools, the slow integration of both experimental mining and bioinformatics, and the important difference between different experimental platforms are some of the reasons for the slow progress of bioinformatics in the field of functional food and more specifically in bioactive peptide discovery.In this paper I discuss some methods that could be easily translated, using a rational peptide bioinformatics design, to food bioactive peptide mining. I highlight the need for an integrated food peptide database. I also discuss how to better integrate experimental work with bioinformatics in order to improve the mining of food for bioactive peptides, therefore achieving a higher success rates.
Xin, Qi-Lin; Deng, Cheng-Lin; Chen, Xi; Wang, Jun; Wang, Shao-Bo; Wang, Wei; Deng, Fei;