Multi-Omic Analysis of the Microbiome and Metabolome in Healthy Subjects Reveals Microbiome-Dependent Relationships Between Diet and Metabolites

Zheng-Zheng Tang, Guanhua Chen, Qilin Hong, Shi Huang, Holly M Smith, Rachana D Shah, Matthew Scholz, Jane F Ferguson, Zheng-Zheng Tang, Guanhua Chen, Qilin Hong, Shi Huang, Holly M Smith, Rachana D Shah, Matthew Scholz, Jane F Ferguson

Abstract

The human microbiome has been associated with health status, and risk of disease development. While the etiology of microbiome-mediated disease remains to be fully elucidated, one mechanism may be through microbial metabolism. Metabolites produced by commensal organisms, including in response to host diet, may affect host metabolic processes, with potentially protective or pathogenic consequences. We conducted multi-omic phenotyping of healthy subjects (N = 136), in order to investigate the interaction between diet, the microbiome, and the metabolome in a cross-sectional sample. We analyzed the nutrient composition of self-reported diet (3-day food records and food frequency questionnaires). We profiled the gut and oral microbiome (16S rRNA) from stool and saliva, and applied metabolomic profiling to plasma and stool samples in a subset of individuals (N = 75). We analyzed these multi-omic data to investigate the relationship between diet, the microbiome, and the gut and circulating metabolome. On a global level, we observed significant relationships, particularly between long-term diet, the gut microbiome and the metabolome. Intake of plant-derived nutrients as well as consumption of artificial sweeteners were associated with significant differences in circulating metabolites, particularly bile acids, which were dependent on gut enterotype, indicating that microbiome composition mediates the effect of diet on host physiology. Our analysis identifies dietary compounds and phytochemicals that may modulate bacterial abundance within the gut and interact with microbiome composition to alter host metabolism.

Keywords: diet; interaction; mediation; metabolome; microbiome; multi-omics analysis.

Figures

FIGURE 1
FIGURE 1
Overview of Study design, subject characteristics, and multi-omic sample availability.
FIGURE 2
FIGURE 2
Overview of global relationships between microbiota, diet, and metabolites. Thick line: distance correlation t-test p-value < 10−5; thin line: distance correlation t-test 10−5< p-value < 10−1.
FIGURE 3
FIGURE 3
Associations between habitual dietary nutrient intake and gut microbiome. Color intensity reflects the magnitude of the association coefficients between dietary variables and taxa.
FIGURE 4
FIGURE 4
Associations between gut microbiome and metabolites in plasma. Color intensity reflects the magnitude of the association coefficients between metabolites and taxa.
FIGURE 5
FIGURE 5
Associations between gut microbiome and metabolites in stool. Color intensity reflects the magnitude of the association coefficients between metabolites and taxa.
FIGURE 6
FIGURE 6
Dietary Fiber has a gut enterotype-dependent association with plasma secondary bile acids including ursodeoxycholate and taurodeoxycholate.
FIGURE 7
FIGURE 7
Plasma Ursodeoxycholate has a gut enterotype-dependent relationship with plasma C-Reactive Protein and BMI, with a positive association in Enterotype 2, and no relationship in Enterotype 1.

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