Peptide abundance correlations in metaproteomics enhance taxonomic and functional analysis of the human gut microbiome

Abstract Mass spectrometry (MS)-based proteomics is widely used for quantitative protein profiling and protein interaction studies. However, most current research focuses on single-species proteomics, while protein interactions within complex microbiomes, composed of hundreds of bacterial species, r...

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Main Authors: Zhongzhi Sun, Zhibin Ning, Qing Wu, Leyuan Li, Andrew C. Doxey, Daniel Figeys
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:npj Biofilms and Microbiomes
Online Access:https://doi.org/10.1038/s41522-025-00801-y
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author Zhongzhi Sun
Zhibin Ning
Qing Wu
Leyuan Li
Andrew C. Doxey
Daniel Figeys
author_facet Zhongzhi Sun
Zhibin Ning
Qing Wu
Leyuan Li
Andrew C. Doxey
Daniel Figeys
author_sort Zhongzhi Sun
collection DOAJ
description Abstract Mass spectrometry (MS)-based proteomics is widely used for quantitative protein profiling and protein interaction studies. However, most current research focuses on single-species proteomics, while protein interactions within complex microbiomes, composed of hundreds of bacterial species, remain largely unexplored. In this study, we analyzed peptide abundance correlations within a metaproteomics dataset derived from in vitro cultured human gut microbiomes subjected to various drug treatments. Our analysis revealed that peptides from the same protein or taxon exhibited correlated abundance changes. By using t-SNE for visualization, we generated a peptide correlation map in which peptides from the same taxon formed distinct clusters. Furthermore, peptide abundance correlations enabled genome-level taxonomic assignments for a greater number of peptides. For instance, 1880 (48.9%) of the 3845 peptides initially assigned only to the family Bacteroidaceae could now be assigned to a specific genome. In species representative genome subsets, peptide correlation networks based on taxon-normalized peptide abundance (TNPA) linked functionally related peptides and provided insights into uncharacterized proteins. Altogether, our study demonstrates that analyzing peptide abundance correlations enhances both taxonomic and functional analyses in human gut metaproteomics research.
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spelling doaj-art-23d2c333d8704a8dba7d510b929bd5702025-08-24T11:10:41ZengNature Portfolionpj Biofilms and Microbiomes2055-50082025-08-0111111510.1038/s41522-025-00801-yPeptide abundance correlations in metaproteomics enhance taxonomic and functional analysis of the human gut microbiomeZhongzhi Sun0Zhibin Ning1Qing Wu2Leyuan Li3Andrew C. Doxey4Daniel Figeys5School of Pharmaceutical Sciences, Ottawa Institute of Systems Biology, and Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of OttawaSchool of Pharmaceutical Sciences, Ottawa Institute of Systems Biology, and Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of OttawaSchool of Pharmaceutical Sciences, Ottawa Institute of Systems Biology, and Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of OttawaState Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of LifeomicsDepartment of Biology and Waterloo Centre for Microbial Research, University of WaterlooSchool of Pharmaceutical Sciences, Ottawa Institute of Systems Biology, and Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of OttawaAbstract Mass spectrometry (MS)-based proteomics is widely used for quantitative protein profiling and protein interaction studies. However, most current research focuses on single-species proteomics, while protein interactions within complex microbiomes, composed of hundreds of bacterial species, remain largely unexplored. In this study, we analyzed peptide abundance correlations within a metaproteomics dataset derived from in vitro cultured human gut microbiomes subjected to various drug treatments. Our analysis revealed that peptides from the same protein or taxon exhibited correlated abundance changes. By using t-SNE for visualization, we generated a peptide correlation map in which peptides from the same taxon formed distinct clusters. Furthermore, peptide abundance correlations enabled genome-level taxonomic assignments for a greater number of peptides. For instance, 1880 (48.9%) of the 3845 peptides initially assigned only to the family Bacteroidaceae could now be assigned to a specific genome. In species representative genome subsets, peptide correlation networks based on taxon-normalized peptide abundance (TNPA) linked functionally related peptides and provided insights into uncharacterized proteins. Altogether, our study demonstrates that analyzing peptide abundance correlations enhances both taxonomic and functional analyses in human gut metaproteomics research.https://doi.org/10.1038/s41522-025-00801-y
spellingShingle Zhongzhi Sun
Zhibin Ning
Qing Wu
Leyuan Li
Andrew C. Doxey
Daniel Figeys
Peptide abundance correlations in metaproteomics enhance taxonomic and functional analysis of the human gut microbiome
npj Biofilms and Microbiomes
title Peptide abundance correlations in metaproteomics enhance taxonomic and functional analysis of the human gut microbiome
title_full Peptide abundance correlations in metaproteomics enhance taxonomic and functional analysis of the human gut microbiome
title_fullStr Peptide abundance correlations in metaproteomics enhance taxonomic and functional analysis of the human gut microbiome
title_full_unstemmed Peptide abundance correlations in metaproteomics enhance taxonomic and functional analysis of the human gut microbiome
title_short Peptide abundance correlations in metaproteomics enhance taxonomic and functional analysis of the human gut microbiome
title_sort peptide abundance correlations in metaproteomics enhance taxonomic and functional analysis of the human gut microbiome
url https://doi.org/10.1038/s41522-025-00801-y
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