Genomics-Based Reconstruction and Predictive Profiling of Amino Acid Biosynthesis in the Human Gut Microbiome

Abstract

The human gut microbiota (HGM) have an impact on host health and disease. Amino acids are building blocks of proteins and peptides, also serving as precursors of many essential metabolites including nucleotides, cofactors, etc. Many HGM community members are unable to synthesize some amino acids (auxotrophs), while other members possess complete biosynthetic pathways for these nutrients (prototrophs). Metabolite exchange between auxotrophs and prototrophs affects microbial community structure. Previous studies of amino acid biosynthetic phenotypes were limited to model species or narrow taxonomic groups of bacteria. We analyzed over 2800 genomes representing 823 cultured HGM species with the aim to reconstruct biosynthetic pathways for proteinogenic amino acids. The genome context analysis of incomplete pathway variants allowed us to identify new potential enzyme variants in amino acid biosynthetic pathways. We further classified the studied organisms with respect to their pathway variants and inferred their prototrophic vs. auxotrophic phenotypes. A cross-species comparison was applied to assess the extent of conservation of the assigned phenotypes at distinct taxonomic levels. The obtained reference collection of binary metabolic phenotypes was used for predictive metabolic profiling of HGM samples from several large metagenomic datasets. The established approach for metabolic phenotype profiling will be useful for prediction of overall metabolic properties, interactions, and responses of HGM microbiomes as a function of dietary variations, dysbiosis and other perturbations.

Keywords: amino acid metabolism; human gut microbiome; metabolic reconstruction; metagenomics; non-orthologous displacements; phenotype.

Figure 1

Reconstructed amino acid biosynthesis pathways in HGM genomes. Biosynthetic enzymes are shown in black using solid black arrows. Amino acid uptake transporters are shown in red using dashed red arrows.

Figure 2

Genomic context of new non-orthologous enzymes in amino acid biosynthetic pathways. The Venn diagrams show co-occurrence of 4 different variants of N-acetylglutamate synthase ArgA (A), and phosphoserine phosphatase SerB (B). Gene co-localization is shown for selected genomes only (C).

Figure 3

(A) Distribution of amino acids producers among analyzed HGM strains. Colored bars show the average amino acid prototrophy of each genus; empty bars represent auxotrophy. The phylogenetic tree of HGM genera was obtained using concatenated ribosomal proteins as previously described [25]. Number of analyzed strains per genus is shown in the inner circle. (B) Distribution of the amino acid producers at the phylum level. The number of analyzed genomes in each phylum is shown.

Figure 4

Distribution of Community Phenotype Indices (CPIs) for amino acid biosynthesis pathways in HGM samples. Samples from the AGP, UKT, and Hadza datasets are shown in blue, red, and green, respectively.

Figure 5

Mutual dependence of median rCPI and rPAD values for each amino acid synthesis phenotype in three HGM datasets.

Figure 6

Distribution of metagenomic abundances for amino acid biosynthetic pathways in HGM samples from IBD dataset. Pathway abundances were calculated as a sum of TMM-normalized counts for two selected signature genes in each biosynthetic pathway (see Table S8).