Deciphering functional redundancy in the human microbiome

Abstract

Although the taxonomic composition of the human microbiome varies tremendously across individuals, its gene composition or functional capacity is highly conserved — implying an ecological property known as functional redundancy. Such functional redundancy has been hypothesized to underlie the stability and resilience of the human microbiome, but this hypothesis has never been quantitatively tested. The origin of functional redundancy is still elusive. Here, we investigate the basis for functional redundancy in the human microbiome by analyzing its genomic content network — a bipartite graph that links microbes to the genes in their genomes. We find that this network exhibits several topological features that favor high functional redundancy. Furthermore, we develop a simple genome evolution model to generate genomic content network, finding that moderate selection pressure and high horizontal gene transfer rate are necessary to generate genomic content networks with key topological features that favor high functional redundancy. Finally, we analyze data from two published studies of fecal microbiota transplantation (FMT), finding that high functional redundancy of the recipient’s pre-FMT microbiota raises barriers to donor microbiota engraftment. This work elucidates the potential ecological and evolutionary processes that create and maintain functional redundancy in the human microbiome and contribute to its resilience.

Evidence of MHC class I and II influencing viral and helminth infection via the microbiome in a non-human primate

“…However, we did not find evidence of an effect of MHC diversity at the taxonomic level. Each metabolic pathway is characterised by a set of bacterial taxa (resulting in functional redundancy [59]), suggesting that the effect of MHCII was only observed in pathway-based analyses due to the cumulative effect of combining multiple taxa. We hypothesize that there is a cost to broad antigen-derived immune responses through high MHCII diversity by negatively impacting functional microbial diversity.…”

A comprehensive approach for microbiota and health monitoring in mouse colonies using metagenomic shotgun sequencing

“…Even though the definition of a "standard" mouse GM was not the goal of the present study, in our experimental setting we have observed that the largest part of SPF and non-SPF GM was made by a relatively small number of bacterial species, probably reflecting a "core" functional role of those species, independent of the housing conditions of the mice. This observation is in line with the decoupling between taxon and function and with the highly preserved functional capacity which are known in different types of microbial systems, host-associated or free-living [76][77][78] In addition to the composition of the microbiota, we used the mNGS data to look for the presence of pathogenic microorganisms. We compared results from metagenomics analyses with those obtained by standard mouse health monitoring performed either using bacterial culture, PCR, serology, or microscopic observation of parasites.…”

CAMAMED: a pipeline for composition-aware mapping-based analysis of metagenomic data

“…The level of annotation in these tools is commonly taxon or gene, while CAMAMED annotates the samples at five levels, including taxon, gene, KO, EC number and reaction. This exclusive feature enables the user to analyze the samples at the functional level, which is reported to be more robust compared to taxonomic or genomic changes ( 30 , 46 ).…”