Dimitry N. Krementsov

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS), driven by genetic and environmental determinants. The gut microbiome of people with MS (pwMS) is distinct and influences disease through immunomodulatory metabolite production. Circulating metabolites are altered in pwMS, but identifying microbial-metabolic drivers remains challenging. We previously showed that colonization by the gut commensal Limosilactobacillus reuteri exacerbates disease in the experimental autoimmune encephalomyelitis (EAE) model of MS in a tryptophan-dependent manner. Here, we integrated microbiomic and metabolomic data sets from a longitudinal EAE study utilizing high- and low-tryptophan diets in mice colonized with or without L. reuteri . Gut microbiome dynamics, under short- and long-term alterations in tryptophan bioavailability, were affected by diet, microbiome context, or disease. During short-term dietary intervention, L. reuteri colonization exerted a greater impact on microbiome composition than tryptophan bioavailability. With longer dietary exposure and EAE progression, high dietary tryptophan and L. reuteri colonization synergized to elicit profound microbiota changes, including alterations in Lachnospiraceae, Blautia, and Akkermansia . Integration of metabolomic and microbiomic data sets using joint Robust Aitchison PCA revealed clusters of associated metabolites and microbiota enriched for functional pathways, including bile acid and tryptophan metabolism. Metabolites outperformed microbiota in predicting EAE severity, identifying p-cresols and indoles as top disease-associated metabolites. Treatment with p-cresol or 3-indoleglyoxylic acid exacerbated EAE, enhanced proinflammatory T-cell responses, and increased cerebellar pathology. These data demonstrate that dietary responses are shaped by gut microbiome composition and that integrated microbiomic-metabolomic analyses can identify the drivers of disease worsening in MS. IMPORTANCE: Multiple sclerosis (MS) is a multifactorial disease influenced not only by genetics but also by environmental factors, potentially including diet and the composition of the gut microbiome. We show that interactions between diet and commensal gut microbiota profoundly impact the levels of immunomodulatory systemic metabolites, including several that are associated with disease in people with MS (pwMS). Importantly, we demonstrate that individual gut microbiota-produced metabolites are sufficient to worsen disease in a mouse model of MS. Integration of gut microbiome and blood metabolite data sets, combined with subsequent predictive modeling, may bolster biomarker identification and the capacity to predict disease severity in pwMS, as compared to the performance of individual data sets alone. These findings highlight metabolites as key mediators linking diet and the gut microbiota to neuroinflammation. Importantly, this work suggests that targeting microbial metabolites or modifying diet-microbiome interactions may represent new strategies to reduce disease activity in MS and related autoimmune disorders.

Introduction: Multiple sclerosis is autoimmune disease of the central nervous system (CNS) in which myelin-reactive immune attack drives demyelination and subsequent disability. Various studies have documented elevated abundance of the commensal gut bacterium Akkermansia muciniphila (A. muciniphila) in people with multiple sclerosis compared to healthy control subjects, suggesting that its elevated abundance may be a risk factor for the development of CNS autoimmunity. However, A. muciniphila is considered beneficial in various other pathological contexts, and recent studies suggest that A. muciniphila may be paradoxically associated with reduced disability and progression in multiple sclerosis. Moreover, experimental modulation of A. muciniphila levels in experimental autoimmune encephalomyelitis (EAE), an autoimmune model of multiple sclerosis, has generated conflicting results, suggesting that the effects of this microbe on CNS autoimmunity could be context-dependent.Methods: To address this possibility, we generated two distinct microbiome models in C57BL/6J mice, each stably colonized by A. muciniphila or A. muciniphila-free, providing divergent ecological contexts in which A. muciniphila may exert a differential impact. We used EAE, flow cytometry, full-length 16S DNA sequencing, and mass spectrometry to assess the impact of A. muciniphila colonization on neurological outcomes, immune responses, gut microbiome composition, and short-chain fatty acid (SCFA) production, respectively. Dietary intervention was used to assess the functional consequences of differences in gut microbiota metabolic capacity. Results: We found that A. muciniphila colonization increased EAE severity only in a specific microbiome context, in conjunction with increased Th17 responses and CNS-infiltrating immune cells. Profiling of gut microbiome composition revealed that A. muciniphila colonization drove a reduction of Clostridia, key producers of SCFAs, specifically in the microbiome model in which A. muciniphila exacerbates EAE. Inferred metagenomic analyses suggested reduced SCFA production in the presence of A. muciniphila, which was confirmed by mass spectrometry. Consistently, provision of high dietary fiber as a substrate for SCFA production suppressed EAE only in the context of the Clostridia-rich microbiome sensitive to A. muciniphila colonization. Discussion: Taken together, our data suggest that the effect of A. muciniphila on CNS autoimmunity is highly dependent on the overall composition of the gut microbiome and suggest that this microbe may contribute to decreased gut SCFA metabolism in multiple sclerosis.

The mammalian ovary is the dynamic end-organ of the hypothalamic pituitary ovarian axis. In this coordinated system, ovarian cells undergo continuous cycles of apoptosis, proliferation, and differentiation. These changes parallel fluctuations in ovarian hormones such as estradiol (E2); however, the ovarian immune microenvironment during high-E2 and low-E2 states is not fully understood. We induced a high-E2 state in the mouse ovary by stimulation via gonadotropin treatment. Single-cell RNA sequencing and flow cytometry analysis of ovarian leukocytes revealed abundant mature NK cells, B1 and B2 cells, CD8+ T cells, CD4+ T cells, mature CD4-CD8-T cells, T regulatory cells, and distinct myeloid subsets, including Trem2+ and Apoe+ macrophages. In vivo labeling of circulating cells determined that the vast majority of ovarian leukocytes were tissue-resident. Following gonadotropin treatment, the frequency of NK cells increased two-fold, while B1 cell frequency was reduced by half. Consistently, flow cytometric analysis revealed an increase in mature CD11b+ NK cells following gonadotropin treatment. Gonadotropin treatment also increased cell-cell signaling by myeloid cells at the expense of NK cells. Our findings reveal a diverse resident immune landscape in the ovary that responds robustly to hormonal changes. These findings have implications for a role for immune cells in ovarian physiology and functional dysregulation.

Innate immune cells sense microbial danger signals, resulting in dynamic transcriptional reprogramming and rapid inflammatory responses. If not properly regulated, such responses can be detrimental to the host, as is seen in septic shock. A better understanding of the genetic regulation of responses during endotoxemia could provide potential therapeutic insights. However, the majority of animal model studies have been performed using classic inbred laboratory strains of mice, capturing limited genetic diversity. Here, we compared classic inbred C57BL/6 (B6) mice with wild-derived and genetically divergent PWD/PhJ (PWD) mice using in vivo and in vitro models of endotoxemia. Compared with B6 mice, PWD mice were markedly resistant to bacterial lipopolysaccharide (LPS)-induced endotoxic shock. Using LPS stimulation of bone marrow derived dendritic cells (BMDC) and RNA sequencing, we demonstrate that B6 and PWD BMDCs exhibit partially overlapping yet highly divergent transcriptional responses, with B6 skewed toward stereotypical proinflammatory pathway activation, and PWD engaging regulatory or developmental pathways. To dissect genetic regulation of inflammatory responses by allelic variants, we used BMDCs from a sub-consomic strain carrying a ∼50 Mb PWD-derived portion of chromosome 11 on the B6 background. This identified a subset of cis-regulated and a large number of trans-regulated genes. Bioinformatic analyses identified candidate trans regulators encoded in the chromosome 11 locus as transcription factors Irf1, Ncor1, and Srebf1. Our results demonstrate that natural genetic variation controls host survival and transcriptional reprogramming during endotoxemia, suggesting possibilities for prediction of sepsis risk and/or personalized therapeutic interventions.

Multiple sclerosis (MS) is a complex disease with significant heterogeneity in disease course and progression. Genetic studies have identified numerous loci associated with MS risk, but the genetic basis of disease progression remains elusive. To address this, we leveraged the Collaborative Cross (CC), a genetically diverse mouse strain panel, and experimental autoimmune encephalomyelitis (EAE). The 32 CC strains studied captured a wide spectrum of EAE severity, trajectory, and presentation, including severe-progressive, monophasic, relapsing remitting, and axial rotary–EAE (AR-EAE), accompanied by distinct immunopathology. Sex differences in EAE severity were observed in 6 strains. Quantitative trait locus analysis revealed distinct genetic linkage patterns for different EAE phenotypes, including EAE severity and incidence of AR-EAE. Machine learning–based approaches prioritized candidate genes for loci underlying EAE severity ( Abcc4 and Gpc6 ) and AR-EAE ( Yap1 and Dync2h1 ). This work expands the EAE phenotypic repertoire and identifies potentially novel loci controlling unique EAE phenotypes, supporting the hypothesis that heterogeneity in MS disease course is driven by genetic variation.

Short-chain fatty acids (SCFAs), produced by the gut microbiota, are thought to exert an anti-inflammatory effect on the host immune system. The levels of SCFAs and abundance of the microbiota that produce them are depleted in multiple sclerosis (MS), an autoimmune disease of the central nervous system (CNS). The mechanisms leading to this depletion are unknown. Using experimental autoimmune encephalomyelitis (EAE) as a model for MS, we have previously shown that gut microbiomes divergent in their abundance of specific commensal Lactobacillaceae, Limosilactobacillus reuteri (L. reuteri) and Ligilactobacillus murinus (L. murinus), differentially impact CNS autoimmunity. To determine the underlying mechanisms, we employed colonization by L. reuteri and L. murinus in disparate gut microbiome configurations in vivo and in vitro, profiling their impact on gut microbiome composition and metabolism, coupled with modulation of dietary fiber in the EAE model. We show that stable colonization by L. reuteri, but not L. murinus, exacerbates EAE, in conjunction with a significant remodeling of gut microbiome composition, depleting SCFA-producing microbiota, including Lachnospiraceae, Prevotellaceae, and Bifidobacterium, with a net decrease in bacterial metabolic pathways involved in butyrate production. In a minimal microbiome culture model in vitro, L. reuteri directly inhibited SCFA-producer growth and depleted butyrate. Genomic analysis of L. reuteri isolates revealed an enrichment in bacteriocins with known antimicrobial activity against SCFA-producing microbiota. Functionally, provision of excess dietary fiber, as the prebiotic substrate for SCFA production, elevated SCFA levels and abrogated the ability of L. reuteri to exacerbate EAE. Our data highlight a potential mechanism for reduced SCFAs and their producers in MS through depletion by other members of the gut microbiome, demonstrating that interactions between microbiota can impact CNS autoimmunity in a diet-dependent manner. These data suggest that therapeutic restoration of SCFA levels in MS may require not only dietary intervention, but also modulation of the gut microbiome.

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system and a leading cause of neurological disability in young adults. Clinical presentation and disease course are highly heterogeneous. Typically, disease progression occurs over time and is characterized by the gradual accumulation of disability. The risk of developing MS is driven by complex interactions between genetic and environmental factors, including the gut microbiome. How the commensal gut microbiota impacts disease severity and progression over time remains unknown. In a longitudinal study, disability status and associated clinical features in 58 MS patients were tracked over 4.2 ± 0.98 years, and the baseline fecal gut microbiome was characterized via 16S amplicon sequencing. Progressor status, defined as patients with an increase in Expanded Disability Status Scale (EDSS), were correlated with features of the gut microbiome to determine candidate microbiota associated with risk of MS disease progression. We found no overt differences in microbial community diversity and overall structure between MS patients exhibiting disease progression and non-progressors. However, a total of 41 bacterial species were associated with worsening disease, including a marked depletion in Akkermansia, Lachnospiraceae, and Oscillospiraceae, with an expansion of Alloprevotella, Prevotella-9, and Rhodospirillales. Analysis of the metabolic potential of the inferred metagenome from taxa associated with progression revealed enrichment in oxidative stress-inducing aerobic respiration at the expense of microbial vitamin K₂ production (linked to Akkermansia), and a depletion in SCFA metabolism (linked to Oscillospiraceae). Further, as a proof of principle, statistical modeling demonstrated that microbiota composition and clinical features were sufficient to predict disease progression. Additionally, we found that constipation, a frequent gastrointestinal comorbidity among MS patients, exhibited a divergent microbial signature compared with progressor status. These results demonstrate a proof of principle for the utility of the gut microbiome for predicting disease progression in MS in a small well-defined cohort. Further, analysis of the inferred metagenome suggested that oxidative stress, vitamin K₂, and SCFAs are associated with progression, warranting future functional validation and mechanistic study.

Multiple sclerosis (MS) is a complex disease with significant heterogeneity in disease course and progression. Genetic studies have identified numerous loci associated with MS risk, but the genetic basis of disease progression remains elusive. To address this, we leveraged the Collaborative Cross (CC), a genetically diverse mouse strain panel, and experimental autoimmune encephalomyelitis (EAE). The thirty-two CC strains studied captured a wide spectrum of EAE severity, trajectory, and presentation, including severe-progressive, monophasic, relapsing remitting, and axial rotary (AR)-EAE, accompanied by distinct immunopathology. Sex differences in EAE severity were observed in six strains. Quantitative trait locus analysis revealed distinct genetic linkage patterns for different EAE phenotypes, including EAE severity and incidence of AR-EAE. Machine learning-based approaches prioritized candidate genes for loci underlying EAE severity ( Abcc4 and Gpc6 ) and AR-EAE ( Yap1 and Dync2h1 ). This work expands the EAE phenotypic repertoire and identifies novel loci controlling unique EAE phenotypes, supporting the hypothesis that heterogeneity in MS disease course is driven by genetic variation. Summary: The genetic basis of disease heterogeneity in multiple sclerosis (MS) remains elusive. We leveraged the Collaborative Cross to expand the phenotypic repertoire of the experimental autoimmune encephalomyelitis (EAE) model of MS and identify loci controlling EAE severity, trajectory, and presentation.

Summary: Multiple sclerosis (MS) is an autoimmune disease of the central nervous system, affecting nearly 2 million people worldwide. The etiology of MS is multifactorial: Approximately 30% of the MS risk is genetic, which implies that the remaining ~70% is environmental, with a number of factors proposed. One recently implicated risk factor for MS is the composition of the gut microbiome. Numerous case–control studies have identified changes in gut microbiota composition of people with MS (pwMS) compared with healthy control individuals, and more recent studies in animal models have begun to identify the causative microbes and underlying mechanisms. Here, we review some of these mechanisms, with a specific focus on the role of host genetic variation, dietary inputs, and gut microbial metabolism, with a particular emphasis on short‐chain fatty acid and tryptophan metabolism. We put forward a model where, in an individual genetically susceptible to MS, the gut microbiota and diet can synergize as potent environmental modifiers of disease risk and possibly progression, with diet‐dependent gut microbial metabolites serving as a key mechanism. We also propose that specific microbial taxa may have divergent effects in individuals carrying distinct variants of MS risk alleles or other polymorphisms, as a consequence of host gene‐by‐gut microbiota interactions. Finally, we also propose that the effects of specific microbial taxa, especially those that exert their effects through metabolites, are highly dependent on the host dietary intake. What emerges is a complex multifaceted interaction that has been challenging to disentangle in human studies, contributing to the divergence of findings across heterogeneous cohorts with differing geography, dietary preferences, and genetics. Nonetheless, this provides a complex and individualized, yet tractable, model of how the gut microbiota regulate susceptibility to MS, and potentially progression of this disease. Thus, we conclude that prophylactic or therapeutic modulation of the gut microbiome to prevent or treat MS will require a careful and personalized consideration of host genetics, baseline gut microbiota composition, and dietary inputs.

Obesity is a global health problem characterized by excessive fat accumulation, driven by adipogenesis and lipid accumulation. Long non‐coding RNAs (lncRNAs) have recently been implicated in regulating adipogenesis and adipose tissue function. Mouse lncRNA U90926 was previously identified as a repressor of in vitro adipogenesis in 3T3‐L1 preadipocytes. Consequently, we hypothesized that, in vivo, U90926 may repress adipogenesis, and hence its deletion would increase weight gain and adiposity. We tested the hypothesis by applying U90926‐deficient (U9‐KO) mice to a high‐throughput phenotyping pipeline. Compared with WT, U9‐KO mice showed no major differences across a wide range of behavioral, neurological, and other physiological parameters. In mice fed a standard diet, we have found no differences in obesity‐related phenotypes, including weight gain, fat mass, and plasma concentrations of glucose, insulin, triglycerides, and free fatty acids, in U9‐KO mice compared to WT. U90926 deficiency lacked a major effect on white adipose tissue morphology and gene expression profile. Furthermore, in mice fed a high‐fat diet, we found increased expression of U90926 in adipose tissue stromal vascular cell fraction, yet observed no effect of U90926 deficiency on weight gain, fat mass, adipogenesis marker expression, and immune cell infiltration into the adipose tissue. These data suggest that the U90926 lacks an essential role in obesity‐related phenotypes and adipose tissue biology in vivo.