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20 results for “metaproteomics”
Metaproteomic Analysis of Sarracenia Purpurea Pitcher Fluid at Harvard Forest 2012-2017
Aquatic ecosystem enrichment can lead to distinct and irreversible changes to undesirable states. Understanding changes in active microbial community function and composition following organic-matter loading in enriched ecosystems can help identify biomarkers of such state changes. In a field experiment, we enriched replicate aquatic ecosystems in the pitchers of the northern pitcher plant, Sarracenia purpurea. Shotgun metaproteomics using a custom metagenomic database identified proteins, molecular pathways, and contributing microbial taxa that differentiated control ecosystems from those that were enriched. The number of microbial taxa contributing to protein expression was comparable between treatments; however, taxonomic evenness was higher in controls. Functionally active bacterial composition differed significantly among treatments and was more divergent in control pitchers than enriched pitchers. Aerobic and facultative anaerobic bacteria contributed most to identified proteins in control and enriched ecosystems, respectively. The molecular pathways and contributing taxa in enriched pitcher ecosystems were similar to those found in larger enriched aquatic ecosystems and are consistent with microbial processes occurring at the base of detrital food webs. Detectable differences between protein profiles of enriched and control ecosystems suggest that a time series of environmental proteomics data may identify protein biomarkers of impending state changes to enriched states.
Metagenomic and metaproteomic insights into bacterial communities in leaf-cutter ant fungus gardens
<p>The submitted protein sequences were compiled from two of our previous studies, 1) 'Metagenomic and metaproteomic insights into bacterial communities in leaf-cutter ant fungus gardens' (doi.org/10.1038/ismej.2012.10) and 2) 'Leucoagaricus gongylophorus Produces Diverse Enzymes for the Degradation of Recalcitrant Plant Polymers in Leaf-Cutter Ant Fungus Gardens' (doi.org/10.1128/AEM.03833-12).</p>
Disseminating metaproteomic informatics capabilities and knowledge using the Galaxy-P framework
<p>Data for the "<strong>Disseminating metaproteomic informatics capabilities and knowledge using the Galaxy-P framework</strong>" paper and training.</p>
Metaproteomics reveals age-specific alterations of gut microbiome in hamsters with SARS-CoV-2 infection
<p><span>The gut microbiome's pivotal role in health and disease is well-established. SARS-CoV-2 infection often causes gastrointestinal symptoms and is associated with changes of the microbiome in both human and animal studies. While hamsters serve as important animal models for coronavirus research, there exists a notable void in functional characterization of their microbiomes with metaproteomics. In this study, we present a workflow for analyzing the hamster gut microbiome, including a metagenomics-derived hamster gut microbial protein database and a data-independent acquisition metaproteomics method. Using this workflow, we identified 32419 protein groups from the fecal microbiomes of young and old hamsters infected with SARS-CoV-2 . We showed age-specific changes in the expressions of microbiome functions and host proteins associated with microbiomes, providing further functional insight into the dysbiosis and aberrant cross-talks between the microbiome and host in SARS-CoV-2 infection. Altogether this study established and demonstrated the capability of metaproteomics for the study of hamster microbiomes.<span> </span></span></p>
MetaPep: A core peptide database for faster human gut metaproteomics database searches
<p>Metaproteomics has increasingly been applied to study functional changes in the human gut microbiome. And peptide identification is an important step in metaproteomics research. However, the large search space in metaproteomics studies causes significant challenges for peptide identification. Here, we constructed MetaPep, a core peptide database (including both collections of peptide sequences and tandem MS spectra) greatly accelerating the peptide identifications. Raw files from fifteen metaproteomics projects were re-analyzed and the identified peptide-spectrum matches (PSMs) were used to construct the MetaPep database. The constructed MetaPep database achieved rapid and accurate identification of peptides for human gut metaproteomics.</p>
Freshwater viral metagenome assembled genomes (vMAGs) used for vContact2 analysis in publication Genome-resolved metaproteomics decodes the microbial and viral contributions to coupled carbon and nitrogen cycling in river sediments
<p>This dataset contains all freshwater viruses that were mined from publicly available data in an effort to provide biogeographical context to viral communities identified from the Columbia River. These two files include data from:</p> <p>1) East River, CO (PRJNA579838)</p> <p>2) A previous study from the Columbia River, WA (PRJNA375338)</p> <p>3) Prairie Potholes, ND (PRJNA365086)</p> <p>4) Amazon River (PRJNA237344)</p> <p> </p> <p>Manuscript title Genome-resolved metaproteomics decodes the microbial and viral contributions to coupled carbon and nitrogen cycling in river sediments</p>
Data-Independent Acquisition Mass Spectrometry as a Tool for Metaproteomics: Interlaboratory Comparison Using a Model Microbiome
<p>Mass spectrometry (MS)-based metaproteomics is used to identify and quantify proteins in microbiome samples, with the frequently used methodology being Data-Dependent Acquisition mass spectrometry (DDA-MS). However, DDA-MS is limited in its ability to reproducibly identify and quantify lower abundant peptides and proteins. To address DDA-MS deficiencies, proteomics researchers have started using Data-Independent Acquisition Mass Spectrometry (DIA-MS) for reproducible detection and quantification of peptides and proteins. We sought to evaluate the reproducibility and accuracy of DIA-MS metaproteomic measurements relative to DDA-MS metaproteomic measurements using a mock community of known taxonomic composition. Artificial microbial communities of known composition were analyzed independently in three laboratories using DDA- and DIA-MS acquisition methods. DIA-MS yielded more protein and peptide identifications than DDA-MS in each laboratory. In addition, the protein and peptide identifications were more reproducible in all laboratories and provided an accurate quantification of proteins and taxonomic groups in the samples. We also identified some limitations of current DIA tools when applied to metaproteomic data highlighting specific needs to further improve DIA tools to enable analysis of metaproteomic datasets from complex microbiomes. Ultimately, DIA-MS represents a promising data collection strategy for MS-based metaproteomics due to its large number of detected proteins and peptides, reproducibility, deep sequencing capabilities, and accurate quantitation.</p>
Metaproteomics analysis of SARS-CoV-2-infected patient samples reveals presence of potential co-infecting microorganisms
<p>Supplemental data for SARS-CoV-2 patient sample metaproteomics analysis</p>
Clinical Metaproteomics-discovery-input-files-iwc
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Clinical Metaproteomics-database-generation-input-files-iwc
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Assembly-mapped metaproteomics gene annotations from Columbia River hyporheic sediments
<p>Annotations for the full set of genes that recruited unique peptides from the Columbia River hyporheic zone sediments manuscript.</p>
Interactive heatmaps for metagenome assembled genome (MAG) metagenomic potential and metaproteomic peptide recruitment
<p>Interactive heatmaps for supplementary figure 1 and supplementary figure 4 from publication to be submitted titled "<strong>Microbial genome-resolved metaproteomic analyses frame intertwined carbon and nitrogen cycles in river hyporheic sediments". </strong></p>
Clinical Metaproteomics Database generation
<p>Generation of a Large Database using 16S rRNA or literature survey-defined microorganisms and then reducing the size of the database to make it compact for search algorithms.</p>
PRObing The Efficacy of Commercial Stage Storage Buffers and Evaluating Gut Metaproteome Variability Between Individuals
ClinicalTrials.gov study NCT06423508. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Metaproteomics reveals metabolic transitions between healthy and diseased stony coral Mussismilia braziliensis
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MePPi: A complete and flexible workflow for metaproteomics data analyses
<p>Data for an examplary metaproteomics data analysis with the <a href="https://github.com/compomics/meta-proteome-analyzer">MetaProteomeAnalyzer</a> (MPA) and <a href="https://gitlab.com/s.fuchs/prophane/">Prophane</a> software tools. Data is from the PRIDE dataset <a href="https://www.ebi.ac.uk/pride/archive/projects/PXD010550/">PXD010550</a>.</p> <p>Files include:</p> <ul> <li>protein databases (FASTA) : <ol> <li>UniProt Swiss-Prot: <a href="https://zenodo.org/record/3727600/files/UniprotSwP-2020_03.fasta">UniprotSwP-2020_03.fasta</a></li> <li>Metagenome (+ Swiss-Prot): <a href="https://zenodo.org/record/3727600/files/MG_BG__UPSP-sp_2020_03.fasta">MG_BG__UPSP.fasta</a></li> </ol> </li> <li>MS Datasets (MGF): <ol> <li>FASP digest: <a href="https://zenodo.org/record/3727600/files/FASP_BGP_A.mgf">FASP_BGP_A.mgf</a></li> <li>In-gel digest: <a href="https://zenodo.org/record/3727600/files/InGel_BGP_A.mgf">InGel_BGP_A.mgf</a></li> </ol> </li> <li>Example results for a single experiment analysis (Sample A, based on: MS data: FASP digest, FASTA: UniProt Swiss-Prot): <ul> <li>MPA results: <a href="https://zenodo.org/record/3727600/files/mpa_result-sample_a-fdr_0.05-single_exp.csv">mpa_result-sample_a-fdr_0.05-single_exp.csv</a></li> <li>Prophane results: <a href="https://zenodo.org/record/3727600/files/prophane_result-sample_a.zip">prophane_result-sample_a.zip</a></li> </ul> </li> <li>Example results for a multi-experiment analysis (Sample B, based on: MS data: FASP + in-gel digest, FASTA: Metagenome): <ul> <li>MPA results: <a href="https://zenodo.org/record/3727600/files/mpa_result-sample_b-fdr_0.01-multi_exp.csv">mpa_result-sample_b-fdr_0.01-multi_exp.csv</a></li> <li>Prophane results: <a href="https://zenodo.org/record/3727600/files/prophane_result-sample_b.zip">prophane_result-sample_b.zip</a></li> </ul> </li> <li><a href="https://zenodo.org/record/3727600/files/mpa_ressources_incl_swissprot_03-2020.zip">MPA data dump</a> including preprocessed UniProt Swiss-Prot FASTA (optionally used by <a href="https://anaconda.org/bioconda/mpa-server">conda mpa-server package</a>)</li> </ul>
Survey of metaproteomics software tools for functional microbiome analysis
<p>The dataset contains files used as input for running functional tools, and it also contains the output files generated by them. These output files were then used for data analysis to comparing them.</p>
Metaproteomics tutorial (training data)
<p><strong>Metaproteomics</strong> uses MS/MS data and matches it to peptide sequences.</p> <p>In the training available at https://galaxyproject.github.io/training-material//topics/proteomics/tutorials/metaproteomics/tutorial.html, we introduce the bioinformatics methods to analyze metaproteomics data.</p>
Quantitative metaproteomics and activity-based protein profiling of patient fecal microbiomes identifies host and microbial serine-type endopeptidase activity associated with ulcerative colitis
<p>Supplemental files associated with patient ulcerative colitis metaproteomics study including protein fasta files, protein group (CD-HIT cluster) files, label free quantification output, de novo-database peptide comparison output tables, ComPIL database search output PSM files, 16S amplicon sequencing data, and Interproscan annotations.</p>
Metagenomic, metatranscriptomic and metaproteomic study of enrichment culture of M. oxyfera (denitrifying methanotroph)
GEO Series GSE18535. Candidatus Methylomirabilis oxygeniifera. 1 samples. Type: Expression profiling by high throughput sequencing.
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