Taxonomic-Level Protein Quantification in Metaproteomics Using a Biomass-Constrained Expectation-Maximization Approach.

ABSTRACT: Microbiome communities are found across diverse environments and play critical roles in both ecosystem function and human health. Mass-spectrometry-based metaproteomics provides a powerful means for directly identifying and quantifying microbial proteins. However, its application is hindered by the shared peptide problem, where peptides map to multiple proteins across taxa, complicating taxon-protein quantification. To address this challenge, we extend a previously published modified expectation-maximization algorithm that incorporates taxonomic biomass constraints into the Microorganism Classification and Identification (MiCId) workflow. This enhanced expectation-maximization algorithm is used to quantify taxon-protein pairs derived from clusters of identified taxon-protein pairs, thereby

SUBMITTER: Alves G 

PROVIDER: S-EPMC12879945 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature