A core gut microbiome in obese and lean twins

Abstract

The human distal gut harbours a vast ensemble of microbes (the microbiota) that provide important metabolic capabilities, including the ability to extract energy from otherwise indigestible dietary polysaccharides. Studies of a few unrelated, healthy adults have revealed substantial diversity in their gut communities, as measured by sequencing 16S rRNA genes, yet how this diversity relates to function and to the rest of the genes in the collective genomes of the microbiota (the gut microbiome) remains obscure. Studies of lean and obese mice suggest that the gut microbiota affects energy balance by influencing the efficiency of calorie harvest from the diet, and how this harvested energy is used and stored. Here we characterize the faecal microbial communities of adult female monozygotic and dizygotic twin pairs concordant for leanness or obesity, and their mothers, to address how host genotype, environmental exposure and host adiposity influence the gut microbiome. Analysis of 154 individuals yielded 9,920 near full-length and 1,937,461 partial bacterial 16S rRNA sequences, plus 2.14 gigabases from their microbiomes. The results reveal that the human gut microbiome is shared among family members, but that each person's gut microbial community varies in the specific bacterial lineages present, with a comparable degree of co-variation between adult monozygotic and dizygotic twin pairs. However, there was a wide array of shared microbial genes among sampled individuals, comprising an extensive, identifiable 'core microbiome' at the gene, rather than at the organismal lineage, level. Obesity is associated with phylum-level changes in the microbiota, reduced bacterial diversity and altered representation of bacterial genes and metabolic pathways. These results demonstrate that a diversity of organismal assemblages can nonetheless yield a core microbiome at a functional level, and that deviations from this core are associated with different physiological states (obese compared with lean).

Figures

Figure 1. 16S rRNA gene surveys reveal familial similarity and reduced diversity of the gut microbiota in obese individuals

(A) Average unweighted UniFrac distance (a measure of differences in bacterial community structure) between individuals over time (self), twin-pairs, twins and their mother, and unrelated individuals [1,000 sequences per V2 dataset; Student’s t-test with Monte Carlo; *p<10−5; **p<10−14; ***p<10−41; mean±SEM]. (B) Phylogenetic diversity curves for the microbiota of lean and obese individuals (based on 1 to 10,000 sequences per V6 dataset; mean±95%CI shown).

Figure 2. Metabolic pathway-based clustering and analysis of the human gut microbiome of MZ twins

(A) Clustering of functional profiles based on the relative abundance of KEGG metabolic pathways. All pairwise comparisons were made of the profiles by calculating each R2 value. Sample ID nomenclature: Family number, Twin number or mom, and BMI category (Le=lean, Ov=overweight, Ob=obese; e.g. F1T1Le stands for family 1, twin 1, lean). (B) The relative abundance of Bacteroidetes as a function of the first principal component derived from an analysis of KEGG metabolic profiles. (C) Comparisons of functional similarity between twin pairs, between twins and their mother, and between unrelated individuals. Asterisks indicate significant differences (Student’s t-test with Monte Carlo; p<0.01; mean±SEM).

Figure 3. Comparison of taxonomic and functional variations in the human gut microbiome

(A) Relative abundance of major phyla across 18 fecal microbiomes from MZ twins and their mothers, based on BLASTX comparisons of microbiomes and the NCBI non-redundant database. (B) Relative abundance of COG categories across each sampled gut microbiome.

Figure 4. KEGG categories enriched or depleted in the core versus variable components of the gut microbiome

Sequences from each of the 18 fecal microbiomes were binned into the ‘core’ or ‘variable’ microbiome based on the co-occurrence of KEGG orthologous groups (core groups were found in all 18 microbiomes while variable groups were present in fewer (−5; mean±SEM).

METHODS REFERENCES