Micronutrient Requirements and Sharing Capabilities of the Human Gut Microbiome

Abstract

The human gut microbiome harbors a diverse array of metabolic pathways contributing to its development and homeostasis via a complex web of diet-dependent metabolic interactions within the microbial community and host. Genomics-based reconstruction and predictive modeling of these interactions would provide a framework for diagnostics and treatment of dysbiosis-related syndromes via rational selection of therapeutic prebiotics and dietary nutrients. Of particular interest are micronutrients, such as B-group vitamins, precursors of indispensable metabolic cofactors, that are produced de novo by some gut bacteria (prototrophs) but must be provided exogenously in the diet for many other bacterial species (auxotrophs) as well as for the mammalian host. Cross-feeding of B vitamins between prototrophic and auxotrophic species is expected to strongly contribute to the homeostasis of microbial communities in the distal gut given the efficient absorption of dietary vitamins in the upper gastrointestinal tract. To confidently estimate the balance of microbiome micronutrient biosynthetic capabilities and requirements using available genomic data, we have performed a subsystems-based reconstruction of biogenesis, salvage and uptake for eight B vitamins (B1, B2, B3, B5, B6, B7, B9, and B12) and queuosine (essential factor in tRNA modification) over a reference set of 2,228 bacterial genomes representing 690 cultured species of the human gastrointestinal microbiota. This allowed us to classify the studied organisms with respect to their pathway variants and infer their prototrophic vs. auxotrophic phenotypes. In addition to canonical vitamin pathways, several conserved partial pathways were identified pointing to alternative routes of syntrophic metabolism and expanding a microbial vitamin "menu" by several pathway intermediates (vitamers) such as thiazole, quinolinate, dethiobiotin, pantoate. A cross-species comparison was applied to assess the extent of conservation of vitamin phenotypes at distinct taxonomic levels (from strains to families). The obtained reference collection combined with 16S rRNA gene-based phylogenetic profiles was used to deduce phenotype profiles of the human gut microbiota across in two large cohorts. This analysis provided the first estimate of B-vitamin requirements, production and sharing capabilities in the human gut microbiome establishing predictive phenotype profiling as a new approach to classification of microbiome samples. Future expansion of our reference genomic collection of metabolic phenotypes will allow further improvement in coverage and accuracy of predictive phenotype profiling of the human microbiome.

Keywords: 16S; comparative genomics; gut microbiome; metagenomics; vitamin metabolism.

FIGURE 1

Reconstructed vitamin/cofactor biosynthesis and salvage pathways in HGM genomes. Eight B-vitamins, and queuine (Q) are shown in red boxes. Alternative and universal biosynthetic pathways are marked in blue text and highlighted in colored blocks. Biosynthetic reactions and vitamin/vitamer uptake are depicted by solid black and red dashed lines, respectively. Enzymes are shown by white boxes. The detailed information of enzyme commission (EC) numbers, functional annotations, metabolite abbreviations, and transporter names are provided in Supplementary Figure S1.

FIGURE 2

Distribution of vitamin/vitamer transporters in HGM species. Transporters are grouped by a cofactor (first column) and vitamin/vitamer (second column). Primary active transporters from the ABC or ECF family are shown in dark red, while secondary active transporters/facilitators (e.g., permeases from MFS family) are in blue. The total number of species possessing a specific transporter is shown in bold with relative contribution of corresponding vitamin auxotrophs/prototrophs shown as a pink/green bar.

FIGURE 3

Distribution of vitamin producers among analyzed HGM strains. The phylogenetic tree of HGM genera was obtained from the larger tree constructed by RAxML based on concatenated sequences of ribosomal proteins from the analyzed HGM species. Number of analyzed strains per genus is shown in the inner circle; higher-level taxonomic groups such as orders, classes, and phyla are highlighted inside the tree. Colored bars show average vitamin production phenotypes (prototrophy) of each genus. Empty bars correspond to auxotrophic phenotypes.

FIGURE 4

Inter-and intra-species variability of binary vitamin production phenotypes in HGM genomes. (A) Species with multiple variable vitamin phenotypes. (B) Species with a single variable vitamin phenotype. (C) Genera with variable vitamin phenotypes. (D) Vitamin phenotype variability at various taxonomic levels.

FIGURE 5

Distribution of Community Phenotype Indices for B and Q vitamins in HGM samples from HMP (A) and AGP (B) datasets. CPIs are calculated based on taxonomic assignments before 16S count renormalization.

FIGURE 6

Distribution of ratio of observed and expected probabilities for Vitamin Prototrophy Ranks in HGM samples from HMP (A) and AGP (B) datasets. Distributions are presented on a logarithmic scale.

FIGURE 7

Distribution of relative phenotype abundance for B and Q vitamins in HGM samples from HMP (A) and AGP (B) datasets. Relative phenotype abundances are calculated using PICRUSt based on external traits from BPM for 2,228 reference genomes obtained in this study.