Previous experimental research has found that metabolomics can be used to monitor the impact of host diet on gut microbiota functionality. These data suggest that focusing on gut microbiota functionality may allow for a better characterization of the gut microbiota and its interaction with the host than only studying its composition.

A new study, led by Dr. Tim Spector and Dr. Cristina Menni from the Department of Twin Research and Genetic Epidemiology at King’s College London (United Kingdom), has found that the fecal metabolome may provide a complementary functional approach to gut microbial communities’ metabolism and interaction with host genetics and diet.

The researchers analyzed 786 individuals, predominantly female (93.4%), with an average age of 65.2 and an average body mass index (BMI) of 26.1 from the population-based twin study TwinsUK. Genetic results were also replicated in an independent set of 230 individuals (98.3% female) from the TwinsUK study, aged 66.9 with an average BMI of 27.2.

The metabolic profiling of the participants’ fecal samples measured a total of 1,116 metabolites. Among them, 570 metabolites were detected in at least 80% of all samples and 345 metabolites were detected in fewer than 80% but in more than 20% of all samples. It is worth mentioning that of the whole pool of measured fecal metabolites, 647 were unique to fecal samples, which highlights how the fecal metabolome may provide information that complements that of blood metabolomics.

The researchers found 102 statistically significant associations between visceral-fat mass—a measure of abdominal obesity—and fecal metabolites, which explained 28.4% of the observed total variance in visceral fat. Visceral-fat-associated metabolites included amino acids, fatty acids, nucleotides, sugars and vitamins. The abundance of some bacterial families previously associated with lower visceral-fat mass were strongly associated with a lower abundance of amino acids. These findings suggest that amino acid availability might be involved in the role of microbial metabolites in mediating the relationship between the fecal microbiome and adiposity, and deserves deeper study of the complex host-microbe interactions. On the other hand, only 8 metabolites were associated with BMI. These results suggest an influence of gut microbiota metabolites on abdominal adiposity, which is in line with previous results from the same research group. And when exploring associations between fecal metabolome and age, the researchers found that some metabolites distinguished the oldest (>75 years, n = 79) and youngest (<56 years, n = 80) deciles among the participants.

Host genetics had a modest influence on the fecal metabolome (heritability of 17.9%). One replicated locus at the NAT2 gene, which is involved in caffeine and several elements of xenobiotic metabolism, was associated with fecal metabolic features, showing that fecal metabolites may mediate the crosstalk between host genetics and xenobiotic metabolism.

Regarding the extent to which the fecal metabolome reflects the gut microbiome metabolic function, gut microbial composition explained 67.7% of the observed variance of 710 metabolites. Specifically, xenobiotics showed the strongest associations with microbial composition. As for the influence of the fecal metabolome on gut microbial taxa, 264 metabolites were associated with microbes at the operational taxonomic level, and the remainder were also associated with broader taxonomic groupings. By using a complex statistical model, the researchers also found up to 2,553 independent associations between metabolites, microbes and connecting metabolites and microbes.

In conclusion, the fecal metabolome may partially reflect gut microbiome composition. These results open up the role of the fecal metabolome as an emerging biomarker for exploring the metabolism of gut microbial communities and its interaction with host genetics and diet.

 

Reference:

Zierer J, Jackson MA, Kastenmüller G, et al. The fecal metabolome as a functional readout of the gut microbiome. Nat Genet. 2018; doi: 10.1038/s41588-018-0135-7.