The importance of gut microbiota in human health and pathophysiology is undisputable. Despite the abundance of metagenomics data, the functional dynamics of gut microbiota in human health and disease remain elusive. Urolithin A (UroA), a major microbial metabolite derived from polyphenolics of berries and pomegranate fruits displays anti-inflammatory, anti-oxidative, and anti-ageing activities. Here, we show that UroA and its potent synthetic analogue (UAS03) significantly enhance gut barrier function and inhibit unwarranted inflammation. We demonstrate that UroA and UAS03 exert their barrier functions through activation of aryl hydrocarbon receptor (AhR)- nuclear factor erythroid 2–related factor 2 (Nrf2)-dependent pathways to upregulate epithelial tight junction proteins. Importantly, treatment with these compounds attenuated colitis in pre-clinical models by remedying barrier dysfunction in addition to anti-inflammatory activities. Cumulatively, the results highlight how microbial metabolites provide two-pronged beneficial activities at gut epithelium by enhancing barrier functions and reducing inflammation to protect from colonic diseases.

Objective: Diets rich in fermentable fibres provide an array of health benefits; however, many patients with IBD report poor tolerance to fermentable fibre-rich foods. Intervention studies with dietary fibres in murine models of colonic inflammation have yielded conflicting results on whether fibres ameliorate or exacerbate IBD. Herein, we examined how replacing the insoluble fibre, cellulose, with the fermentable fibres, inulin or pectin, impacted murine colitis resulting from immune dysregulation via inhibition of interleukin (IL)-10 signalling and/or innate immune deficiency (Tlr5KO). Design: Mice were fed with diet containing either cellulose, inulin or pectin and subjected to weekly injections of an IL-10 receptor (αIL-10R) neutralising antibody. Colitis development was examined by serological, biochemical, histological and immunological parameters. Results: Inulin potentiated the severity of αIL10R-induced colitis, while pectin ameliorated the disease. Such exacerbation of colitis following inulin feeding was associated with enrichment of butyrate-producing bacteria and elevated levels of caecal butyrate. Blockade of butyrate production by either metronidazole or hops β-acids ameliorated colitis severity in inulin-fed mice, whereas augmenting caecal butyrate via tributyrin increased colitis severity in cellulose containing diet-fed mice. Elevated butyrate levels were associated with increased IL-1β activity, while inhibition of the NOD-like receptor protein 3 by genetic, pharmacologic or dietary means markedly reduced colitis. Conclusion: These results not only support the notion that fermentable fibres have the potential to ameliorate colitis but also caution that, in some contexts, prebiotic fibres can lead to gut dysbiosis and surfeit colonic butyrate that might exacerbate IBD.

Dietary salt reduction and exercise are lifestyle modifications for salt-sensitive hypertensives. While exercise has prominent metabolic effects, salt has an adverse effect on metabolic syndrome, of which hypertension is a hallmark. We hypothesized that dietary salt impacts metabolism in a salt-sensitive model of hypertension. An untargeted metabolomic approach demonstrates lower circulating levels of the ketone body, beta-hydroxybutyrate (βOHB), in high salt-fed hypertensive rats. Despite the high salt intake, specific rescue of βOHB levels by nutritional supplementation of its precursor, 1,3-butanediol, attenuates hypertension and protects kidney function. This beneficial effect of βOHB was likely independent of gut-microbiotal and Th17-mediated effects of salt and instead facilitated by βOHB inhibiting the renal Nlrp3 inflammasome. The juxtaposed effects of dietary salt and exercise on salt-sensitive hypertension, which decrease and increase βOHB respectively, indicate that nutritional supplementation of a precursor of βOHB provides a similar benefit to salt-sensitive hypertension as exercise.

Cardiovascular disease (CVD) is the number one leading cause for human mortality. Besides genetics and environmental factors, in recent years, gut microbiota has emerged as a new factor influencing CVD. Although cause-effect relationships are not clearly established, the reported associations between alterations in gut microbiota and CVD are prominent. Therefore, we hypothesized that machine learning (ML) could be used for gut microbiome–based diagnostic screening of CVD. To test our hypothesis, fecal 16S ribosomal RNA sequencing data of 478 CVD and 473 non-CVD human subjects collected through the American Gut Project were analyzed using 5 supervised ML algorithms including random forest, support vector machine, decision tree, elastic net, and neural networks. Thirty-nine differential bacterial taxa were identified between the CVD and non-CVD groups. ML modeling using these taxonomic features achieved a testing area under the receiver operating characteristic curve (0.0, perfect antidiscrimination; 0.5, random guessing; 1.0, perfect discrimination) of ≈0.58 (random forest and neural networks). Next, the ML models were trained with the top 500 high-variance features of operational taxonomic units, instead of bacterial taxa, and an improved testing area under the receiver operating characteristic curves of ≈0.65 (random forest) was achieved. Further, by limiting the selection to only the top 25 highly contributing operational taxonomic unit features, the area under the receiver operating characteristic curves was further significantly enhanced to ≈0.70. Overall, our study is the first to identify dysbiosis of gut microbiota in CVD patients as a group and apply this knowledge to develop a gut microbiome–based ML approach for diagnostic screening of CVD.

Our study demonstrates the promising potential of artificial intelligence via supervised machine learning modeling for predictive diagnostics of different types of inflammatory bowel diseases using fecal gut microbiome data.