Elevated postprandial blood glucose levels constitute a global epidemic and a major risk factor for prediabetes and type II diabetes, but existing dietary methods for controlling them have limited efficacy. Here, we continuously monitored week-long glucose levels in an 800-person cohort, measured responses to 46,898 meals, and found high variability in the response to identical meals, suggesting that universal dietary recommendations may have limited utility. We devised a machine-learning algorithm that integrates blood parameters, dietary habits, anthropometrics, physical activity, and gut microbiota measured in this cohort and showed that it accurately predicts personalized postprandial glycemic response to real-life meals. We validated these predictions in an independent 100-person cohort. Finally, a blinded randomized controlled dietary intervention based on this algorithm resulted in significantly lower postprandial responses and consistent alterations to gut microbiota configuration. Together, our results suggest that personalized diets may successfully modify elevated postprandial blood glucose and its metabolic consequences. VIDEO ABSTRACT.

Transcription factors (TFs) bind in a combinatorial fashion to specify the on-and-off states of genes; the ensemble of these binding events forms a regulatory network, constituting the wiring diagram for a cell. To examine the principles of the human transcriptional regulatory network, we determined the genomic binding information of 119 TFs in 458 ChIP-Seq experiments. We found the combinatorial, co-association of TFs to be highly context specific: distinct combinations of factors bind at specific genomic locations. In particular, there are significant differences in the binding proximal and distal to genes. We organized all the TF binding into a hierarchy and integrated it with other genomic information (e.g. miRNA regulation), forming a dense meta-network. Factors at different levels have different properties: for instance, top-level TFs more strongly influence expression and middle-level ones co-regulate targets to mitigate information-flow bottlenecks. Moreover, these co-regulations give rise to many enriched network motifs -- e.g. noise-buffering feed-forward loops. Finally, more connected network components are under stronger selection and exhibit a greater degree of allele-specific activity (i.e., differential binding to the two parental alleles). The regulatory information obtained in this study will be crucial for interpreting personal genome sequences and understanding basic principles of human biology and disease.

Non-caloric artificial sweeteners (NAS) are among the most widely used food additives worldwide, regularly consumed by lean and obese individuals alike. NAS consumption is considered safe and beneficial owing to their low caloric content, yet supporting scientific data remain sparse and controversial. Here we demonstrate that consumption of commonly used NAS formulations drives the development of glucose intolerance through induction of compositional and functional alterations to the intestinal microbiota. These NAS-mediated deleterious metabolic effects are abrogated by antibiotic treatment, and are fully transferrable to germ-free mice upon faecal transplantation of microbiota configurations from NAS-consuming mice, or of microbiota anaerobically incubated in the presence of NAS. We identify NAS-altered microbial metabolic pathways that are linked to host susceptibility to metabolic disease, and demonstrate similar NAS-induced dysbiosis and glucose intolerance in healthy human subjects. Collectively, our results link NAS consumption, dysbiosis and metabolic abnormalities, thereby calling for a reassessment of massive NAS usage.

All domains of life feature diverse molecular clock machineries that synchronize physiological processes to diurnal environmental fluctuations. However, no mechanisms are known to cross-regulate prokaryotic and eukaryotic circadian rhythms in multikingdom ecosystems. Here, we show that the intestinal microbiota, in both mice and humans, exhibits diurnal oscillations that are influenced by feeding rhythms, leading to time-specific compositional and functional profiles over the course of a day. Ablation of host molecular clock components or induction of jet lag leads to aberrant microbiota diurnal fluctuations and dysbiosis, driven by impaired feeding rhythmicity. Consequently, jet-lag-induced dysbiosis in both mice and humans promotes glucose intolerance and obesity that are transferrable to germ-free mice upon fecal transplantation. Together, these findings provide evidence of coordinated metaorganism diurnal rhythmicity and offer a microbiome-dependent mechanism for common metabolic disturbances in humans with aberrant circadian rhythms, such as those documented in shift workers and frequent flyers.

Empiric probiotics are commonly consumed by healthy individuals as means of life quality improvement and disease prevention. However, evidence of probiotic gut mucosal colonization efficacy remains sparse and controversial. We metagenomically characterized the murine and human mucosal-associated gastrointestinal microbiome and found it to only partially correlate with stool microbiome. A sequential invasive multi-omics measurement at baseline and during consumption of an 11-strain probiotic combination or placebo demonstrated that probiotics remain viable upon gastrointestinal passage. In colonized, but not germ-free mice, probiotics encountered a marked mucosal colonization resistance. In contrast, humans featured person-, region- and strain-specific mucosal colonization patterns, hallmarked by predictive baseline host and microbiome features, but indistinguishable by probiotics presence in stool. Consequently, probiotics induced a transient, individualized impact on mucosal community structure and gut transcriptome. Collectively, empiric probiotics supplementation may be limited in universally and persistently impacting the gut mucosa, meriting development of new personalized probiotic approaches.

Host-microbiome co-evolution drives homeostasis and disease susceptibility, yet regulatory principles governing the integrated intestinal host-commensal microenvironment remain obscure. While inflammasome signaling participates in these interactions, its activators and microbiome-modulating mechanisms are unknown. Here, we demonstrate that the microbiota-associated metabolites taurine, histamine, and spermine shape the host-microbiome interface by co-modulating NLRP6 inflammasome signaling, epithelial IL-18 secretion, and downstream anti-microbial peptide (AMP) profiles. Distortion of this balanced AMP landscape by inflammasome deficiency drives dysbiosis development. Upon fecal transfer, colitis-inducing microbiota hijacks this microenvironment-orchestrating machinery through metabolite-mediated inflammasome suppression, leading to distorted AMP balance favoring its preferential colonization. Restoration of the metabolite-inflammasome-AMP axis reinstates a normal microbiota and ameliorates colitis. Together, we identify microbial modulators of the NLRP6 inflammasome and highlight mechanisms by which microbiome-host interactions cooperatively drive microbial community stability through metabolite-mediated innate immune modulation. Therefore, targeted ‘postbiotic’ metabolomic intervention may restore a normal microenvironment, as treatment or prevention of dysbiosis-driven diseases.

Probiotics are widely prescribed for prevention of antibiotics-associated dysbiosis and related adverse effects. However, probiotic impact on post-antibiotic reconstitution of the gut mucosal host-microbiome niche remains elusive. We invasively examined the effects of multi-strain probiotics or autologous fecal microbiome transplantation (aFMT) on post-antibiotic reconstitution of the murine and human mucosal microbiome niche. Contrary to homeostasis, antibiotic perturbation enhanced probiotics colonization in the human mucosa but only mildly improved colonization in mice. Compared to spontaneous post-antibiotic recovery, probiotics induced a markedly delayed and persistently incomplete indigenous stool/mucosal microbiome reconstitution and host transcriptome recovery toward homeostatic configuration, while aFMT induced a rapid and near-complete recovery within days of administration. In vitro, Lactobacillus-secreted soluble factors contributed to probiotics-induced microbiome inhibition. Collectively, potential post-antibiotic probiotic benefits may be offset by a compromised gut mucosal recovery, highlighting a need of developing aFMT or personalized probiotic approaches achieving mucosal protection without compromising microbiome recolonization in the antibiotics-perturbed host.

The human intestinal microbiome is a microbial ecosystem that expresses as many as 100 times more genes than the human host, thereby constituting an important component of the human holobiome, which contributes to multiple health and disease processes. As most commensal species are difficult or impossible to culture, genomic characterization of microbiome composition and function, under various environmental conditions, comprises a central tool in understanding its roles in health and disease. The first decade of microbiome research was mainly characterized by usage of DNA sequencing-based 16S rDNA and shotgun metagenome sequencing, allowing for the elucidation of microbial composition and genome structure. Technological advances in RNA-seq have recently provided us with an ability to gain insight into the genes that are actively expressed in complex bacterial communities, enabling the elucidation of the functional changes that dictate the microbiome functions at given contexts, its interactions with the host, and functional alterations that accompany the conversion of a healthy microbiome toward a disease-driving configuration. Here, we highlight some of the key metatranscriptomics strategies that are implemented to determine microbiota gene expression and its regulation and discuss the advantages and potential challenges associated with these approaches.