ArticleMolecular & cellular proteomics : MCP2019
metaQuantome: An Integrated, Quantitative Metaproteomics Approach Reveals Connections Between Taxonomy and Protein Function in Complex Microbiomes.
Article in Molecular & cellular proteomics : MCP, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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
22 citing papers in PubMed.
- Taxonomic-Level Protein Quantification in Metaproteomics Using a Biomass-Constrained Expectation-Maximization Approach.Journal of the American Society for Mass Spectrometry · 2026Article
- Biological Function Assignment across Taxonomic Levels in Mass-Spectrometry-Based Metaproteomics via a Modified Expectation Maximization Algorithm.Journal of proteome research · 2025Article
- Integrative systems biology approaches for analyzing microbiome dysbiosis and species interactions.Briefings in bioinformatics · 2025Review
- The microbiologist's guide to metaproteomics.iMeta · 2025Review
- Article
- Metaproteomics-informed stoichiometric modeling reveals the responses of wetland microbial communities to oxygen and sulfate exposure.NPJ biofilms and microbiomes · 2024Article
- Multiomics data integration, limitations, and prospects to reveal the metabolic activity of the coral holobiont.FEMS microbiology ecology · 2024Review
- The Association of Biomolecular Resource Facilities Proteome Informatics Research Group Study on Metaproteomics (iPRG-2020).Journal of biomolecular techniques : JBT · 2023Article
- Integrative meta-omics in Galaxy and beyond.Environmental microbiome · 2023Article
- Meta4P: A User-Friendly Tool to Parse Label-Free Quantitative Metaproteomic Data and Taxonomic/Functional Annotations.Journal of proteome research · 2023Article
- The community ecology perspective of omics data.Microbiome · 2022Article
- Novel Bioinformatics Strategies Driving Dynamic Metaproteomic Studies.Methods in molecular biology (Clifton, N.J.) · 2022Article
- In-Depth Metaproteomics Analysis of Oral Microbiome for Lung Cancer.Research (Washington, D.C.) · 2022Article
- Review
- Five key aspects of metaproteomics as a tool to understand functional interactions in host-associated microbiomes.PLoS pathogens · 2021Article
- Synergies of Systems Biology and Synthetic Biology in Human Microbiome Studies.Frontiers in microbiology · 2021Review
- Microbiota and Ocular Diseases.Frontiers in cellular and infection microbiology · 2021Review
- ASaiM-MT: a validated and optimized ASaiM workflow for metatranscriptomics analysis within Galaxy framework.F1000Research · 2021Article
- Precursor Intensity-Based Label-Free Quantification Software Tools for Proteomic and Multi-Omic Analysis within the Galaxy Platform.Proteomes · 2020Article
- The Human Oral Microbiome in Health and Disease: From Sequences to Ecosystems.Microorganisms · 2020Review
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Microbiome research offers promising insights into the impact of microorganisms on biological systems. Metaproteomics, the study of microbial proteins at the community level, integrates genomic, transcriptomic, and proteomic data to determine the taxonomic and functional state of a microbiome. However, standard metaproteomics software is subject to several limitations, commonly supporting only spectral counts, emphasizing exploratory analysis rather than hypothesis testing and rarely offering the ability to analyze the interaction of function and taxonomy - that is, which taxa are responsible for different processes.Here we present metaQuantome, a novel, multifaceted software suite that analyzes the state of a microbiome by leveraging complex taxonomic and functional hierarchies to summarize peptide-level quantitative information, emphasizing label-free intensity-based methods. For experiments with multiple experimental conditions, metaQuantome offers differential abundance analysis, principal components analysis, and clustered heat map visualizations, as well as exploratory analysis for a single sample or experimental condition. We benchmark metaQuantome analysis against standard methods, using two previously published datasets: (1) an artificially assembled microbial community dataset (taxonomy benchmarking) and (2) a dataset with a range of recombinant human proteins spiked into an
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Registered trials
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