Revealing Protein-Level Functional Redundancy in the Human Gut Microbiome using Ultra-deep Metaproteomics

Abstract

Functional redundancy is a key property of ecosystems and represents the fact that phylogenetically unrelated taxa can play similar functional roles within an ecosystem. The redundancy of potential functions of human microbiome has been recently quantified using metagenomics data. Yet, the redundancy of functions which are actually expressed within the human microbiome remains largely unexplored. Here, we quantify the protein-level functional redundancy in the human gut microbiome using metaproteomics and network approaches. In particular, our ultra-deep metaproteomics approach revealed high protein-level functional redundancy and high nestedness in proteomic content networks - bipartite graphs that connect taxa with their expressed functions. We further examined multiple metaproteomics datasets and showed that various environmental factors, including individuality, biogeography, xenobiotics, and disease, significantly altered the protein-level functional redundancy. Finally, by projecting the bipartite proteomic content networks into unipartite weighted genus networks, functional hub genera across individual microbiomes were discovered, suggesting that there may be a universal principle of functional organization in microbiome assembly.

Comprehensive Assessment of Functional Effects of Commonly Used Sugar Substitute Sweeteners on Ex Vivo Human Gut Microbiome

“…PLS-DA was performed in MetaboAnalyst 5.0 ( 52 ), and discriminative proteins with VIP scores of >2 were selected. The taxonomic sources of the discriminative proteins were obtained by the method described in a previous study ( 53 ). Briefly, among all of the peptides contained in the discriminative protein, the taxonomic source of the peptide with the most detailed taxonomic information was regarded as the taxonomic source of the protein.…”

Pairing Metagenomics and Metaproteomics to Characterize Ecological Niches and Metabolic Essentiality of gut microbiomes

“…Similar fold changes of ABC-type transporters were observed for metaproteomic measurements 12 hours, and 24 hours later (Supplemental Figs. [14][15], while the fold changes 1 hour later are still fairly small (Supplemental Fig. 13).…”

“…Here we focused on the genus level and annotated the identified proteins from metagenomics and metaproteomics data via the COGs (Clusters of Orthologous genes) database 35,36 . We constructed the GCN and PCN for all the samples following the same procedure as reported in a previous study 14 , and took the intersected COGs between the two networks. In the main text, we focus on the analysis and discussion of subject HM454, and similar findings from the other three subjects are shown in Supplementary Figs.…”

“…For the ultra-deep metaproteomic dataset, the genus-COG version of GCN and PCN tables were directly obtained from the previous work 14 . In addition, here we generated a genus-KEGG version of GCN and PCN for each individual microbiome using a similar method.…”

“…Does the behavior of selective expression of microbial proteins differ between metabolic function (e.g., essential for microbial growth metabolism) and ecological function (e.g., claiming resources as a niche)? To address this question, in this work we developed a computational method to perform paired metagenomic and metaproteomic [25][26][27][28]14 data analysis and revealed whether a protein is essential for microbial metabolism or relevant for occupying ecological niches. In particular, we used the metagenomic data to construct the Gene Content Network (GCN) ---a bipartite graph that connects microbial taxa to their genes (Fig.…”