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The rapid development of multiplexed imaging technologies has enabled the spatial cartography of various healthy and tumor tissues. However, the lack of adequate statistical models has hampered the use of multiplexed imaging to efficiently compare tissue composition across sample groups, for instance between healthy and tumor tissue samples. Here, we developed two statistical models that accurately describe the distribution of cell counts observed in a given field of view in an imaging experiment. The parameters of these distributions are directly linked to the field of view size and also to properties of the studied cell type such as cellular density and spatial aggregation. Using these models, we identified statistical tests that have improved statistical power for differential abundance testing of tissue composition compared to the commonly used rank-based test. Our analysis revealed that spatial aggregation is the main determinant of statistical power and that to have sufficient power to detect differences in cell counts when cells are highly aggregated may require sampling of hundreds of fields of view. To overcome this challenge, we provide a new stratified sampling strategy that might significantly reduce the number of required samples.

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; US, 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 confounded by an increased pre-treatment tumor burden and systemic inflammation in high-risk antibiotics-pre-treated patients. 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 uncovered between pre-CAR-T-infusion Bifidobacterium longum and microbiome-encoded peptidoglycan biosynthesis, and CAR-T treatment-associated 6-months 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 associating with pre-infusion peripheral T cell levels in these patients. Collectively, we uncover conserved microbiome features across clinical and geographical variations, which may enable cross-cohort microbiome-based predictions of outcomes in CAR-T cell immunotherapy.

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.

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.

Summary 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.

IL-6 signaling via its receptor (IL-6R) and co-receptor (gp130) performs multiple roles in regulating metabolic homeostasis. However, gp130 is also expressed systemically in a soluble form (sgp130), which limits soluble IL-6 receptor (sIL-6R)-mediated signaling – also called trans-signaling. Here we find that transgenic peripheral sgp130-mediated trans-signaling blockade induces mature-onset obesity, while differentially affecting age-dependent behavioral determinants of energy expenditure. In youth, trans-signaling blockade increases feeding associated with reduced leptin sensitivity but increases energy expenditure to maintain metabolic balance. In aging, reduced physical activity predisposes mice to adiposity, adipose tissue macrophage recruitment, hepatosteatosis, hyperglycemia, and insulin resistance. Mechanistically, trans-signaling blockade reduces hepatic Stat3 phosphorylation and suppresses PPARα, associated with miR-21 upregulation, while pharmacological activation of PPARα prevents obesity and hepatosteatosis, and rescues insulin sensitivity. Together these experiments reveal a role for peripheral IL-6 trans-signaling in metabolic homeostasis and provide clinical significance to elevated sgp130 levels found in some obese and diabetic patients.

Cigarette smoking constitutes a leading global cause of morbidity and preventable death

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.

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.

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.

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.

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.