Accumulating evidence suggests that the gut microbiota is an important factor in mediating the development of obesity-related metabolic disorders, including type 2 diabetes. Metformin and berberine, two clinically effective drugs for treating diabetes, have recently been shown to exert their actions through modulating the gut microbiota. In this study, we demonstrated that metformin and berberine similarly shifted the overall structure of the gut microbiota in rats. Both drugs showed reverting effects on the high-fat diet-induced structural changes of gut microbiota. The diversity of gut microbiota was significantly reduced by both berberine- and metformin-treatments. Nearest shrunken centroids analysis identified 134 operational taxonomic units (OTUs) responding to the treatments, which showed close associations with the changes of obese phenotypes. Sixty out of the 134 OTUs were decreased by both drugs, while those belonging to putative short-chain fatty acids (SCFA)-producing bacteria, including Allobaculum, Bacteriodes, Blautia, Butyricoccus and Phascolarctobacterium, were markedly increased by both berberine and, to a lesser extent, metformin. Taken together, our findings suggest that berberine and metformin showed similarity in modulating the gut microbiota, including the enrichment of SCFA-producing bacteria and reduction of microbial diversity, which may contribute to their beneficial effects to the host.

Berberine, a major pharmacological component of the Chinese herb Coptis chinensis, which was originally used to treat bacterial diarrhea, has recently been demonstrated to be clinically effective in alleviating type 2 diabetes. In this study, we revealed that berberine effectively prevented the development of obesity and insulin resistance in high-fat diet (HFD)-fed rats, which showed decreased food intake. Increases in the levels of serum lipopolysaccharide-binding protein, monocyte chemoattractant protein-1, and leptin and decrease in the serum level of adiponectin corrected for body fat in HFD-fed rats were also significantly retarded by the co-administration of berberine at 100 mg/kg body weight. Bar-coded pyrosequencing of the V3 region of 16S rRNA genes revealed a significant reduction in the gut microbiota diversity of berberine-treated rats. UniFrac principal coordinates analysis revealed a marked shift of the gut microbiota structure in berberine-treated rats away from that of the controls. Redundancy analysis identified 268 berberine-responding operational taxonomic units (OTUs), most of which were essentially eliminated, whereas a few putative short-chain fatty acid (SCFA)-producing bacteria, including Blautia and Allobaculum, were selectively enriched, along with elevations of fecal SCFA concentrations. Partial least square regression models based on these 268 OTUs were established (Q²>0.6) for predicting the adiposity index, body weight, leptin and adiponectin corrected for body fat, indicating that these discrete phylotypes might have a close association with the host metabolic phenotypes. Taken together, our findings suggest that the prevention of obesity and insulin resistance by berberine in HFD-fed rats is at least partially mediated by structural modulation of the gut microbiota, which may help to alleviate inflammation by reducing the exogenous antigen load in the host and elevating SCFA levels in the intestine.

The gut microbiota is hypothesized to have a critical role in metabolic diseases, including type 2 diabetes (T2D). A traditional Chinese herbal formula, Gegen Qinlian Decoction (GQD), can alleviate T2D. To find out whether GQD modulates the composition of the gut microbiota during T2D treatment, 187 T2D patients were randomly allocated to receive high (HD, n=44), moderate (MD, n=52), low dose GQD (LD, n=50) or the placebo (n=41) for 12 weeks in a double-blinded trial. Patients who received the HD or MD demonstrated significant reductions in adjusted mean changes from baseline of fasting blood glucose (FBG) and glycated hemoglobin (HbA1c) compared with the placebo and LD groups. Pyrosequencing of the V3 regions of 16S rRNA genes revealed a dose-dependent deviation of gut microbiota in response to GQD treatment. This deviation occurred before significant improvement of T2D symptoms was observed. Redundancy analysis identified 47 GQD-enriched species level phylotypes, 17 of which were negatively correlated with FBG and 9 with HbA1c. Real-time quantitative PCR confirmed that GQD significantly enriched Faecalibacterium prausnitzii, which was negatively correlated with FBG, HbA1c and 2-h postprandial blood glucose levels and positively correlated with homeostasis model assessment of β-cell function. Therefore, these data indicate that structural changes of gut microbiota are induced by Chinese herbal formula GQD. Specifically, GQD treatment may enrich the amounts of beneficial bacteria, such as Faecalibacterium spp. In conclusion, changes in the gut microbiota are associated with the anti-diabetic effects of GQD.

The gut microbiome has emerged as an important factor affecting human health and disease. The recent development of –omics approaches, including phylogenetic marker-based microbiome profiling, shotgun metagenomics, metatranscriptomics, metaproteomics, and metabolomics, has enabled efficient characterization of microbial communities. These techniques can provide strain-level taxonomic resolution of the taxa present in microbiomes, assess the potential functions encoded by the microbial community and quantify the metabolic activities occurring within a complex microbiome. The application of these meta-omics approaches to clinical samples has identified microbial species, metabolic pathways, and metabolites that are associated with the development and treatment of human diseases. These findings have further facilitated microbiome-targeted drug discovery and efforts to improve human health management. Recent in vitro and in vivo investigations have uncovered the presence of extensive drug-microbiome interactions. These interactions have also been shown to be important contributors to the disparate patient responses to treatment that are often observed during disease therapy. Therefore, developing techniques or frameworks that enable rapid screening, detailed evaluation, and accurate prediction of drug/host-microbiome interactions is critically important in the modern era of microbiome research and precision medicine. Here we review the current status of meta-omics techniques, including integrative multi-omics approaches, for characterizing the microbiome’s functionality in the context of health and disease. We also summarize and discuss new frameworks for applying meta-omics approaches and microbiome assays to study drug-microbiome interactions. Lastly, we discuss and exemplify strategies for implementing microbiome-based precision medicines using these meta-omics approaches and high throughput microbiome assays.

Alterations in gut microbiota have been implicated in the pathogenesis of inflammatory bowel disease (IBD), however factors that mediate the host–microbiota interactions remain largely unknown. Here we collected mucosal-luminal interface samples from a pediatric IBD inception cohort and characterized both the human and microbiota proteins using metaproteomics. We show that microbial proteins related to oxidative stress responses are upregulated in IBD cases compared to controls. In particular, we demonstrate that the expression of human proteins related to oxidative antimicrobial activities is increased in IBD cases and correlates with the alteration of microbial functions. Additionally, we reveal that many of these human proteins are present and show altered abundance in isolated free extracellular vesicles (EVs). Therefore, our study suggests that the alteration of intestinal EV proteomes is associated with the aberrant host–microbiota interactions in IBD.