ArticleNature protocols2020
A complete and flexible workflow for metaproteomics data analysis based on MetaProteomeAnalyzer and Prophane.
Article in Nature protocols, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
48 citing papers in PubMed, 92 citations in OpenAlex.
- ProteoRift Protocols: A Deep Learning Filtering Workflow for Peptide Identification in Mass Spectrometry Data.Methods in molecular biology (Clifton, N.J.) · 2027Article
- The need for standardization and improved open (meta)data practices in metaproteomics.Microbiome · 2026Article
- Biomolecular profiling for noninvasive health monitoring.Nature biotechnology · 2026Review
- End-to-end deep attention-based multitask pipeline for predicting uncertainty-quantified peptide properties from mass spectrometry data.Scientific reports · 2026Article
- Innovative Systems Biology in Baijiu Fermentation: Unveiling Omics Landscapes and Microbial Synergy.Foods (Basel, Switzerland) · 2026Review
- Polyunsaturated aldehydes induce distinct proteomic responses in two diatom-associated bacterial communities.Frontiers in microbiology · 2026Article
- Microbial Omics.Progress in molecular and subcellular biology · 2026Review
- Mesaconic acid as a key metabolite with anti-inflammatory and anti-aging properties produced by Lactobacillus plantarum 124 from centenarian gut microbiota.NPJ biofilms and microbiomes · 2025Article
- Biological Function Assignment across Taxonomic Levels in Mass-Spectrometry-Based Metaproteomics via a Modified Expectation Maximization Algorithm.Journal of proteome research · 2025Article
- The microbiologist's guide to metaproteomics.iMeta · 2025Review
- Metaproteomics in the One Health framework for unraveling microbial effectors in microbiomes.Microbiome · 2025Review
- MicrobiomeStatPlots: Microbiome statistics plotting gallery for meta-omics and bioinformatics.iMeta · 2025Article
- Biodegradation of synthetic organic pollutants: principles, progress, problems, and perspectives.FEMS microbiology reviews · 2025Review
- Quantitative analysis of proteomic changes in two monoclonal suspension MDCK cell lines infected with human influenza A virus (H1N1).PloS one · 2025Article
- metaExpertPro: A Computational Workflow for Metaproteomics Spectral Library Construction and Data-Independent Acquisition Mass Spectrometry Data Analysis.Molecular & cellular proteomics : MCP · 2024Article
- Article
- Soil Metaproteomics for Microbial Community Profiling: Methodologies and Challenges.Current microbiology · 2024Review
- The microbiome of the lichen Lobaria pulmonaria varies according to climate on a subcontinental scale.Environmental microbiology reports · 2024Article
- Marine particle microbiomes during a spring diatom bloom contain active sulfate-reducing bacteria.FEMS microbiology ecology · 2024Article
- Article
Corrections and comments
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Authors and funding
9 authors at 7 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metaproteomics, the study of the collective protein composition of multi-organism systems, provides deep insights into the biodiversity of microbial communities and the complex functional interplay between microbes and their hosts or environment. Thus, metaproteomics has become an indispensable tool in various fields such as microbiology and related medical applications. The computational challenges in the analysis of corresponding datasets differ from those of pure-culture proteomics, e.g., due to the higher complexity of the samples and the larger reference databases demanding specific computing pipelines. Corresponding data analyses usually consist of numerous manual steps that must be closely synchronized. With MetaProteomeAnalyzer and Prophane, we have established two open-source software solutions specifically developed and optimized for metaproteomics. Among other features, peptide-spectrum matching is improved by combining different search engines and, compared to similar tools, metaproteome annotation benefits from the most comprehensive set of available databases (such as NCBI, UniProt, EggNOG, PFAM, and CAZy). The workflow described in this protocol combines both tools and leads the user through the entire data analysis process, including protein database creation, database search, protein grouping and annotation, and results visualization. To the best of our knowledge, this protocol presents the most comprehensive, detailed and flexible guide to metaproteomics data analysis to date. While beginners are provided with robust, easy-to-use, state-of-the-art data analysis in a reasonable time (a few hours, depending on, among other factors, the protein database size and the number of identified peptides and inferred proteins), advanced users benefit from the flexibility and adaptability of the workflow.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.