Wilmes and Bond proposed the term "metaproteomics" for the large-scale characterization of the entire protein complement of environmental microbiota at a given point in time.
While proteomics is largely a discovery-based approach that is followed by other molecular or analytical techniques to provide a full picture of the subject system, it is not limited to simple cataloging of proteins present in a sample.
With the combined capabilities of "top-down" and "bottom-up" approaches, proteomics can pursue inquiries ranging from quantitation of gene expression between growth conditions (whether nutritional, spatial, temporal, or chemical) to protein structural information.
[13] A similar study done in 2017 by Maier et al. combined metaproteomics with metagenomics and metabolomics to show the effects of resistant starch on the human intestinal microbiome.
Using machine learning, a 2025 study by Yang et al. showed that human and microbial proteins could identify those at high-risk of cardiovascular disease in healthy and heart failure cohorts.
Overall, metaproteomics has gained immense popularity in human intestinal microbiome studies as it has led to important discoveries in the health field.
Bacterial proteins involved are ferredoxin-NADP reductase, acetate kinase, and NADH-quinone oxidoreductase found in the Firmicutes, Proteobacteria, Actinobacteria and Bacteroidetes taxa.
[16] The first quantification method for metaproteomics was reported by Laloo et al. 2018 on an engineered biological reactor enriched for ammonia and nitrite oxidising bacteria.
A 2019 study by Li et al. has demonstrated the use of metaproteomics in observing protein expression of polycyclic aromatic hydrocarbon (PAH) degradation genes.
Pseudomonas Burkholderia, Enterobacter, Lactococcus and Clostridium strains were identified using metagenomic shotgun sequencing, and many bacterial proteins were found to show degradative activity.