Using PepExplorer to Filter and Organize De Novo Peptide Sequencing Results

PepExplorer aids in the biological interpretation of de novo sequencing results; this is accomplished by assembling a list of homolog proteins obtained by aligning results from widely adopted de novo sequencing tools against a target‐decoy sequence database. Our tool relies on pattern recognition to ensure that the results satisfy a user‐given false‐discovery rate (FDR). For this, it employs a radial basis function neural network that considers the precursor charge states, de novo sequencing scores, the peptide lengths, and alignment scores. PepExplorer is recommended for studies addressing organisms with no genomic sequence available. PepExplorer is integrated into the PatternLab for proteomics environment, which makes available various tools for downstream data analysis, including the resources for quantitative and differential proteomics. © 2015 by John Wiley & Sons, Inc.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152617/1/cpbi1327.pd

Ten Simple Rules for Taking Advantage of Git and GitHub.

Bioinformatics is a broad discipline in which one common denominator is the need to produce and/or use software that can be applied to biological data in different contexts. To enable and ensure the replicability and traceability of scientific claims, it is essential that the scientific publication, the corresponding datasets, and the data analysis are made publicly available [1,2]. All software used for the analysis should be either carefully documented (e.g., for commercial software) or, better yet, openly shared and directly accessible to others [3,4]. The rise of openly available software and source code alongside concomitant collaborative development is facilitated by the existence of several code repository services such as SourceForge, Bitbucket, GitLab, and GitHub, among others. These resources are also essential for collaborative software projects because they enable the organization and sharing of programming tasks between different remote contributors. Here, we introduce the main features of GitHub, a popular web-based platform that offers a free and integrated environment for hosting the source code, documentation, and project-related web content for open-source projects. GitHub also offers paid plans for private repositories (see Box 1) for individuals and businesses as well as free plans including private repositories for research and educational use.Biotechnology and Biological Sciences Research CouncilThis is the final version of the article. It first appeared from Public Library of Science via https://doi.org/10.1371/journal.pcbi.1004947

BioContainers: An open-source and community-driven framework for software standardization

Motivation BioContainers (biocontainers.pro) is an open-source and community-driven framework which provides platform independent executable environments for bioinformatics software. BioContainers allows labs of all sizes to easily install bioinformatics software, maintain multiple versions of the same software and combine tools into powerful analysis pipelines. BioContainers is based on popular open-source projects Docker and rkt frameworks, that allow software to be installed and executed under an isolated and controlled environment. Also, it provides infrastructure and basic guidelines to create, manage and distribute bioinformatics containers with a special focus on omics technologies. These containers can be integrated into more comprehensive bioinformatics pipelines and different architectures (local desktop, cloud environments or HPC clusters). Availability and Implementation The software is freely available at github.com/BioContainers/.publishedVersio

Discovering and linking public omics data sets using the Omics Discovery Index.

Biomedical data are being produced at an unprecedented rate owing to the falling cost of experiments and wider access to genomics, transcriptomics, proteomics and metabolomics platforms1, 2. As a result, public deposition of omics data is on the increase. This presents new challenges, including finding ways to store, organize and access different types of biomedical data stored on different platforms. Here, we present the Omics Discovery Index (OmicsDI; http://www.omicsdi.org), an open-source platform that enables access, discovery and dissemination of omics data sets

Proteogenomic Analysis of Chemo-Refractory High-Grade Serous Ovarian Cancer

To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin-fixed paraffin-embedded and frozen). We identified a 64-protein signature that predicts with high specificity a subset of HGSOCs refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We detected significant association between lack of Ch17 loss of heterozygosity (LOH) and chemo-refractoriness. Based on pathway protein expression, we identified 5 clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities

Caracterização de Genes de Função Desconhecida com Expressão Associada às Formas Infectivas do Trypanosoma cruzi

Submitted by Anderson Silva ([email protected]) on 2013-11-04T12:15:31Z No. of bitstreams: 1 Dissertação Mestrado Felipe Leprevost.pdf: 8130365 bytes, checksum: 2af7aa9ac89832c8e4c552a4d889c5e9 (MD5)Made available in DSpace on 2013-11-04T12:15:31Z (GMT). No. of bitstreams: 1 Dissertação Mestrado Felipe Leprevost.pdf: 8130365 bytes, checksum: 2af7aa9ac89832c8e4c552a4d889c5e9 (MD5) Previous issue date: 2009Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Rio de Janeiro, RJ, BrasilAtualmente novas abordagens e metodologias de pesquisa nos permitem iniciar projetos de caracterização de um conjunto de proteínas de um determinado organismo em escalas superiores aos realizados há algum tempo. Novas tecnologias para seqüenciamento, clonagem e expressão protéica permitem a geração de uma quantidade grande de novas informações numa fração de tempo relativamente curta. Organismos como o Trypanosoma cruzi, que possuem praticamente metade de seu genoma sem função conhecida, necessitam que estudos sejam realizados para que se consiga atribuir às proteínas de função desconhecida características funcionais. Em um esforço para se conhecer melhor os genes de função desconhecida deste parasita, um grupo de 10 genes foi selecionado com base na sua expressão diferencial durante a metaciclogênese, consistindo de genes anotados como ‘proteína hipotética’ em banco de dados públicos, com domínio identificado pelo banco de famílias protéicas PFAM e com ortólogos em outros organismos. Os 10 genes selecionados foram amplificados e clonados na plataforma de clonagem Gateway e as proteínas recombinantes foram expressas em Escherichia coli. Dos 10 genes destinados à expressão protéica, 8 expressaram proteínas insolúveis as quais foram utilizadas para obtenção de soro policlonal. Os soros obtidos foram utilizados em ensaios de Western Blot para averiguação da expressão protéica ao longo da metaciclogênese do parasita e ensaios de localização celular por microscopia ótica e eletrônica. Foram realizados também ensaios de transfecção em T. cruzi para a expressão das proteínas fusionadas com GFP, visando à determinação da localização celular, utilizando um vetor compatível com a plataforma Gateway, e foram realizados ensaios de imunoprecipitação para todas as 8 proteínas expressas. Os resultados obtidos no presente trabalho auxiliam na atribuição de informações experimentais a genes e proteínas anotados como ‘proteína hipotética de função desconhecida’ e avaliam a possibilidade de implementação de um estudo sistemático com este para uma aplicação em média/larga escalaRecent research approaches and methodologies allow us to develop projects for the characterization of proteins of a given organism in scales greater than possible some time ago. New technologies for sequencing, cloning and protein expression allow the generation of large amounts of new information in relatively short time. Organisms such as Trypanosoma cruzi, which have nearly half of its genome with no known function, require studies to assign functions to proteins of unknown function. In an effort to characterize the genes of unknown function of this parasite, a group of 10 genes was selected based on their differential expression during metacyclogenesis. The genes were annotated as 'hypothetical protein' in public databases, with domains identified in the PFAM database and with orthologs in other organisms. The 10 selected genes were amplified and cloned in Gateway cloning platform and the recombinant proteins were expressed in Escherichia coli. Eight of the 10 genes expressed insoluble proteins which were used to obtain polyclonal serum. The sera were used in Western Blot analysis to verify protein expression throughout the parasite metacyclogenesis as well as cellular localization by optical and electron microscopy. To determine cellular localization, transfection experiments were conducted in T. cruzi for the expression of proteins fused with GFP using a vector compatible with the Gateway platform. Immunoprecipitation assays were also performed for the 8 expressed proteins. The results obtained in this work uncover experimental information of genes annotated as 'hypothetical protein of unknown function' and assess the possibility of implementing a systematic approach with this methodology in medium to large scal

Nesvilab/philosopher: Philosopher 4.1.1

Added Changed Fixed Fixed an issue with the ion mobility column not showing in empty PSM tables. Fixed an issue where high-scoring peptides mapping to complicated razor cases where not showing in the reports

Differences in Extracellular Vesicle Protein Cargo Are Dependent on Head and Neck Squamous Cell Carcinoma Cell of Origin and Human Papillomavirus Status

To identify potential extracellular vesicle (EV) biomarkers in head and neck squamous cell carcinoma (HNSCC), we evaluated EV protein cargo and whole cell lysates (WCL) from HPV-positive and -negative HNSCC cell lines, as well as normal oral keratinocytes and HPV16-transformed cells. EVs were isolated from serum-depleted, conditioned cell culture media by polyethylene glycol (PEG) precipitation/ultracentrifugation. EV and WCL preparations were analyzed by LC-MS/MS. Candidate proteins detected at significantly higher levels in EV compared with WCL, or compared with EV from normal oral keratinocytes, were identified and confirmed by Wes Simple Western protein analysis. Our findings suggest that these proteins may be potential HNSCC EV markers as proteins that may be (1) selectively included in EV cargo for export from the cell as a strategy for metastasis, tumor cell survival, or modification of tumor microenvironment, or (2) representative of originating cell composition, which may be developed for diagnostic or prognostic use in clinical liquid biopsy applications. This work demonstrates that our method can be used to reliably detect EV proteins from HNSCC, normal keratinocyte, and transformed cell lines. Furthermore, this work has identified HNSCC EV protein candidates for continued evaluation, specifically tenascin-C, HLA-A, E-cadherin, EGFR, EPHA2, and cytokeratin 19

Enhancing multiplexed cysteine chemoproteomics by uniting FragPipe with solid-phase compatible dialkoxydiphenylsilane reagents

The human proteome harbors tens of thousands of ligandable or potentially druggable cysteine residues. Consequently, pinpointing the optimal covalent molecule for each cysteine residue represents an exciting means to close the druggability gap, namely the ~96% of human proteins not yet targeted by an FDA approved drug. Realizing the full therapeutic potential of the cysteineome will require comprehensive proteome-wide cysteine-compound structure activity relationship (SAR) analysis. While mass spectrometry-based chemoproteomic platforms have made significant inroads into this challenge, achieving comprehensive cysteine-SAR necessitates technical innovation in two key areas: (1) streamlined sample preparation workflows and (2) high throughput and high coverage data acquisition. Here we report the silane-based Cleavable Linkers for Isotopically labeled Proteomics (sCLIP) method. sCLIP streamlines sample preparation with unparalleled early-stage isobaric labeling and sample pooling, allowing for high coverage and increased sample throughput via customized low cost 6-plex sample multiplexing. The sCLIP method is distinguished by its unprecedented click-assembled isobaric tags, in which the reporter group is encoded in the sCLIP capture reagent and balancer in the pan cysteine-reactive probe. When paired with a custom FragPipe data analysis workflow and applied to cysteine-reactive fragment screens, sCLIP proteomics revealed established and unprecedented cysteine-ligand pairs, including the discovery that the mitochondrial uncoupling agent FCCP acts as a covalent-reversible cysteine-reactive electrophile