Personalized microbiome-driven effects of non-nutritive sweeteners on human glucose tolerance.

Non-nutritive sweeteners (NNS) are commonly integrated into human diet and presumed to be inert; however, animal studies suggest that they may impact the microbiome and downstream glycemic responses. We causally assessed NNS impacts in humans and their microbiomes in a randomized-controlled trial encompassing 120 healthy adults, administered saccharin, sucralose, aspartame, and stevia sachets for 2 weeks in doses lower than the acceptable daily intake, compared with controls receiving sachet-contained vehicle glucose or no supplement. As groups, each administered NNS distinctly altered stool and oral microbiome and plasma metabolome, whereas saccharin and sucralose significantly impaired glycemic responses. Importantly, gnotobiotic mice conventionalized with microbiomes from multiple top and bottom responders of each of the four NNS-supplemented groups featured glycemic responses largely reflecting those noted in respective human donors, which were preempted by distinct microbial signals, as exemplified by sucralose. Collectively, human NNS consumption may induce person-specific, microbiome-dependent glycemic alterations, necessitating future assessment of clinical implications.

Diet Diurnally Regulates Small Intestinal Microbiome-Epithelial-Immune Homeostasis and Enteritis.

Throughout a 24-h period, the small intestine (SI) is exposed to diurnally varying food- and microbiome-derived antigenic burdens but maintains a strict immune homeostasis, which when perturbed in genetically susceptible individuals, may lead to Crohn disease. Herein, we demonstrate that dietary content and rhythmicity regulate the diurnally shifting SI epithelial cell (SIEC) transcriptional landscape through modulation of the SI microbiome. We exemplify this concept with SIEC major histocompatibility complex (MHC) class II, which is diurnally modulated by distinct mucosal-adherent SI commensals, while supporting downstream diurnal activity of intra-epithelial IL-10+ lymphocytes regulating the SI barrier function. Disruption of this diurnally regulated diet-microbiome-MHC class II-IL-10-epithelial barrier axis by circadian clock disarrangement, alterations in feeding time or content, or epithelial-specific MHC class II depletion leads to an extensive microbial product influx, driving Crohn-like enteritis. Collectively, we highlight nutritional features that modulate SI microbiome, immunity, and barrier function and identify dietary, epithelial, and immune checkpoints along this axis to be potentially exploitable in future Crohn disease interventions.

Personalized Gut Mucosal Colonization Resistance to Empiric Probiotics Is Associated with Unique Host and Microbiome Features.

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.

Post-Antibiotic Gut Mucosal Microbiome Reconstitution Is Impaired by Probiotics and Improved by Autologous FMT.

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.

Gut microbiota modulates weight gain in mice after discontinued smoke exposure.

Cigarette smoking constitutes a leading global cause of morbidity and preventable death1, and most active smokers report a desire or recent attempt to quit2. Smoking-cessation-induced weight gain (SCWG; 4.5 kg reported to be gained on average per 6-12 months, >10 kg year-1 in 13% of those who stopped smoking3) constitutes a major obstacle to smoking abstinence4, even under stable5,6 or restricted7 caloric intake. Here we use a mouse model to demonstrate that smoking and cessation induce a dysbiotic state that is driven by an intestinal influx of cigarette-smoke-related metabolites. Microbiome depletion induced by treatment with antibiotics prevents SCWG. Conversely, fecal microbiome transplantation from mice previously exposed to cigarette smoke into germ-free mice naive to smoke exposure induces excessive weight gain across diets and mouse strains. Metabolically, microbiome-induced SCWG involves a concerted host and microbiome shunting of dietary choline to dimethylglycine driving increased gut energy harvest, coupled with the depletion of a cross-regulated weight-lowering metabolite, N-acetylglycine, and possibly by the effects of other differentially abundant cigarette-smoke-related metabolites. Dimethylglycine and N-acetylglycine may also modulate weight and associated adipose-tissue immunity under non-smoking conditions. Preliminary observations in a small cross-sectional human cohort support these findings, which calls for larger human trials to establish the relevance of this mechanism in active smokers. Collectively, we uncover a microbiome-dependent orchestration of SCWG that may be exploitable to improve smoking-cessation success and to correct metabolic perturbations even in non-smoking settings.

Potential roles of gut microbiome and metabolites in modulating ALS in mice.

Amyotrophic lateral sclerosis (ALS) is a complex neurodegenerative disorder, in which the clinical manifestations may be influenced by genetic and unknown environmental factors. Here we show that ALS-prone Sod1 transgenic (Sod1-Tg) mice have a pre-symptomatic, vivarium-dependent dysbiosis and altered metabolite configuration, coupled with an exacerbated disease under germ-free conditions or after treatment with broad-spectrum antibiotics. We correlate eleven distinct commensal bacteria at our vivarium with the severity of ALS in mice, and by their individual supplementation into antibiotic-treated Sod1-Tg mice we demonstrate that Akkermansia muciniphila (AM) ameliorates whereas Ruminococcus torques and Parabacteroides distasonis exacerbate the symptoms of ALS. Furthermore, Sod1-Tg mice that are administered AM are found to accumulate AM-associated nicotinamide in the central nervous system, and systemic supplementation of nicotinamide improves motor symptoms and gene expression patterns in the spinal cord of Sod1-Tg mice. In humans, we identify distinct microbiome and metabolite configurations-including reduced levels of nicotinamide systemically and in the cerebrospinal fluid-in a small preliminary study that compares patients with ALS with household controls. We suggest that environmentally driven microbiome-brain interactions may modulate ALS in mice, and we call for similar investigations in the human form of the disease.

Dimensionality reduction of longitudinal 'omics data using modern tensor factorizations.

Longitudinal 'omics analytical methods are extensively used in the evolving field of precision medicine, by enabling 'big data' recording and high-resolution interpretation of complex datasets, driven by individual variations in response to perturbations such as disease pathogenesis, medical treatment or changes in lifestyle. However, inherent technical limitations in biomedical studies often result in the generation of feature-rich and sample-limited datasets. Analyzing such data using conventional modalities often proves to be challenging since the repeated, high-dimensional measurements overload the outlook with inconsequential variations that must be filtered from the data in order to find the true, biologically relevant signal. Tensor methods for the analysis and meaningful representation of multiway data may prove useful to the biological research community by their advertised ability to tackle this challenge. In this study, we present tcam-a new unsupervised tensor factorization method for the analysis of multiway data. Building on top of cutting-edge developments in the field of tensor-tensor algebra, we characterize the unique mathematical properties of our method, namely, 1) preservation of geometric and statistical traits of the data, which enable uncovering information beyond the inter-individual variation that often takes over the focus, especially in human studies. 2) Natural and straightforward out-of-sample extension, making tcam amenable for integration in machine learning workflows. A series of re-analyses of real-world, human experimental datasets showcase these theoretical properties, while providing empirical confirmation of tcam's utility in the analysis of longitudinal 'omics data.

A non-antibiotic-disrupted gut microbiome is associated with clinical responses to CD19-CAR-T cell cancer immunotherapy.

Increasing evidence suggests that the gut microbiome may modulate the efficacy of cancer immunotherapy. In a B cell lymphoma patient cohort from five centers in Germany and the United States (Germany, n = 66; United States, n = 106; total, n = 172), we demonstrate that wide-spectrum antibiotics treatment ('high-risk antibiotics') prior to CD19-targeted chimeric antigen receptor (CAR)-T cell therapy is associated with adverse outcomes, but this effect is likely to be confounded by an increased pretreatment tumor burden and systemic inflammation in patients pretreated with high-risk antibiotics. To resolve this confounding effect and gain insights into antibiotics-masked microbiome signals impacting CAR-T efficacy, we focused on the high-risk antibiotics non-exposed patient population. Indeed, in these patients, significant correlations were noted between pre-CAR-T infusion Bifidobacterium longum and microbiome-encoded peptidoglycan biosynthesis, and CAR-T treatment-associated 6-month survival or lymphoma progression. Furthermore, predictive pre-CAR-T treatment microbiome-based machine learning algorithms trained on the high-risk antibiotics non-exposed German cohort and validated by the respective US cohort robustly segregated long-term responders from non-responders. Bacteroides, Ruminococcus, Eubacterium and Akkermansia were most important in determining CAR-T responsiveness, with Akkermansia also being associated with pre-infusion peripheral T cell levels in these patients. Collectively, we identify conserved microbiome features across clinical and geographical variations, which may enable cross-cohort microbiome-based predictions of outcomes in CAR-T cell immunotherapy.

Machine learning in clinical decision making.

Machine learning is increasingly integrated into clinical practice, with applications ranging from pre-clinical data processing, bedside diagnosis assistance, patient stratification, treatment decision making, and early warning as part of primary and secondary prevention. However, a multitude of technological, medical, and ethical considerations are critical in machine-learning utilization, including the necessity for careful validation of machine-learning-based technologies in real-life contexts, unbiased evaluation of benefits and risks, and avoidance of technological over-dependence and associated loss of clinical, ethical, and social-related decision-making capacities. Other challenges include the need for careful benchmarking and external validations, dissemination of end-user knowledge from computational experts to field users, and responsible code and data sharing, enabling transparent assessment of pipelines. In this review, we highlight key promises and achievements in integration of machine-learning platforms into clinical medicine while highlighting limitations, pitfalls, and challenges toward enhanced integration of learning systems into the medical realm.

Vaginal microbiome transplantation in women with intractable bacterial vaginosis.

We report the results of a first exploratory study testing the use of vaginal microbiome transplantation (VMT) from healthy donors as a therapeutic alternative for patients suffering from symptomatic, intractable and recurrent bacterial vaginosis (ClinicalTrials.gov NCT02236429 ). In our case series, five patients were treated, and in four of them VMT was associated with full long-term remission until the end of follow-up at 5-21 months after VMT, defined as marked improvement of symptoms, Amsel criteria, microscopic vaginal fluid appearance and reconstitution of a Lactobacillus-dominated vaginal microbiome. One patient presented with incomplete remission in clinical and laboratory features. No adverse effects were observed in any of the five women. Notably, remission in three patients necessitated repeated VMT, including a donor change in one patient, to elicit a long-standing clinical response. The therapeutic efficacy of VMT in women with intractable and recurrent bacterial vaginosis should be further determined in randomized, placebo-controlled clinical trials.