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Bacterial zwitterionic capsular polysaccharides (ZPS), such as polysaccharide A (PSA) of the intestinal commensal Bacteroides fragilis, have been shown to modulate T cells, including inducing anti-inflammatory IL-10-secreting T regulatory cells (Tregs). We previously used a genomic screen to identify diverse host-associated bacteria with the predicted genetic capacity to produce ZPSs related to PSA of B. fragilis and hypothesized that genetic disruption (KO) of a key functional gene within these operons would reduce the anti-inflammatory activity of these bacteria. We found that ZPS-KO bacteria in two common gut commensals, Bacteroides uniformis and Bacteroides cellulosilyticus, had a reduced ability to induce Tregs and IL-10 in stimulations of human peripheral blood mononuclear cells (PBMCs). Additionally, we found that macrophage stimulated with either wildtype B. fragilis or B. uniformis produced significantly more IL-10 than KOs, indicating a potentially novel function of ZPS of shifting the cytokine response in macrophages to a more anti-inflammatory state. These findings support the hypothesis that these related ZPS may represent a shared strategy to modulate host immune responses.

Funder: National Science Foundation; Id: http://dx.doi.org/10.13039/501100008982, Microbiome studies are often limited by a lack of statistical power due to small sample sizes and a large number of features. This problem is exacerbated in correlative studies of multi-omic datasets. Statistical power can be increased by finding and summarizing modules of correlated observations, which is one dimensionality reduction method. Additionally, modules provide biological insight as correlated groups of microbes can have relationships among themselves. To address these challenges, we developed SCNIC: Sparse Cooccurrence Network Investigation for compositional data. SCNIC is open-source software that can generate correlation networks and detect and summarize modules of highly correlated features. Modules can be formed using either the Louvain Modularity Maximization (LMM) algorithm or a Shared Minimum Distance algorithm (SMD) that we newly describe here and relate to LMM using simulated data. We applied SCNIC to two published datasets and we achieved increased statistical power and identified microbes that not only differed across groups, but also correlated strongly with each other, suggesting shared environmental drivers or cooperative relationships among them. SCNIC provides an easy way to generate correlation networks, identify modules of correlated features and summarize them for downstream statistical analysis. Although SCNIC was designed considering properties of microbiome data, such as compositionality and sparsity, it can be applied to a variety of data types including metabolomics data and used to integrate multiple data types. SCNIC allows for the identification of functional microbial relationships at scale while increasing statistical power through feature reduction.

OBJECTIVE Identifying predictors of weight loss and clinical outcomes may increase understanding of individual variability in weight loss response. We hypothesized that baseline multiomic features, including DNA methylation (DNAme), metabolomics, and gut microbiome, would be predictive of short-term changes in body weight and other clinical outcomes within a comprehensive weight loss intervention. METHODS Healthy adults with overweight or obesity (n = 62, age 18-55 years, BMI 27-45 kg/m2 , 75.8% female) participated in a 1-year behavioral weight loss intervention. To identify baseline omic predictors of changes in clinical outcomes at 3 and 6 months, whole-blood DNAme, plasma metabolites, and gut microbial genera were analyzed. RESULTS A network of multiomic relationships informed predictive models for 10 clinical outcomes (body weight, waist circumference, fat mass, hemoglobin A1c , homeostatic model assessment of insulin resistance, total cholesterol, triglycerides, C-reactive protein, leptin, and ghrelin) that changed significantly (P

Background One goal of multi-omic studies is to identify interpretable predictive models for outcomes of interest, with analytes drawn from multiple omes. Such findings could support refined biological insight and hypothesis generation. However, standard analytical approaches are not designed to be “ome aware.” Thus, some researchers analyze data from one ome at a time, and then combine predictions across omes. Others resort to correlation studies, cataloging pairwise relationships, but lacking an obvious approach for cohesive and interpretable summaries of these catalogs. Methods We present a novel workflow for building predictive regression models from network neighborhoods in multi-omic networks. First, we generate pairwise regression models across all pairs of analytes from all omes, encoding the resulting “top table” of relationships in a network. Then, we build predictive logistic regression models using the analytes in network neighborhoods of interest. We call this method CANTARE (Consolidated Analysis of Network Topology And Regression Elements). Results We applied CANTARE to previously published data from healthy controls and patients with inflammatory bowel disease (IBD) consisting of three omes: gut microbiome, metabolomics, and microbial-derived enzymes. We identified 8 unique predictive models with AUC > 0.90. The number of predictors in these models ranged from 3 to 13. We compare the results of CANTARE to random forests and elastic-net penalized regressions, analyzing AUC, predictions, and predictors. CANTARE AUC values were competitive with those generated by random forests and penalized regressions. The top 3 CANTARE models had a greater dynamic range of predicted probabilities than did random forests and penalized regressions (p-value = 1.35 × 10–5). CANTARE models were significantly more likely to prioritize predictors from multiple omes than were the alternatives (p-value = 0.005). We also showed that predictive models from a network based on pairwise models with an interaction term for IBD have higher AUC than predictive models built from a correlation network (p-value = 0.016). R scripts and a CANTARE User’s Guide are available at https://sourceforge.net/projects/cytomelodics/files/CANTARE/. Conclusion CANTARE offers a flexible approach for building parsimonious, interpretable multi-omic models. These models yield quantitative and directional effect sizes for predictors and support the generation of hypotheses for follow-up investigation.

The complex communities of microbes that constitute the human microbiome are influenced by host and environmental factors. Here, we address how a fundamental aspect of human biology, blood type, contributes to shaping this microscopic ecosystem. Although this question remains largely unexplored, we glean insights from decades of work describing relationships between pathogens and blood type. The bacterial strategies, molecular mechanisms, and host responses that shaped those relationships may parallel those that characterize how blood type and commensals interact. Understanding these nuanced interactions will expand our capacity to analyze and manipulate the human microbiome.

Understanding when and why new species are recruited into microbial communities is a formidable problem with implications for managing microbial systems, for instance by helping us better understand whether a probiotic or pathogen would be expected to colonize a human microbiome. Much theory in microbial temporal dynamics is focused on how phylogenetic relationships between microbes impact the order in which those microbes are recruited; for example species that are closely related may competitively exclude each other. However, several recent human microbiome studies have observed closely-related bacteria being recruited into microbial communities in short succession, suggesting that microbial community assembly is historically contingent, but competitive exclusion of close relatives may not be important. To address this, we developed a mathematical model that describes the order in which new species are detected in microbial communities over time within a phylogenetic framework. We use our model to test three hypothetical assembly modes: underdispersion (species recruitment is more likely if a close relative was previously detected), overdispersion (recruitment is more likely if a close relative has not been previously detected), and the neutral model (recruitment likelihood is not related to phylogenetic relationships among species). We applied our model to longitudinal human microbiome data, and found that for the individuals we analyzed, the human microbiome generally follows the underdispersion (i.e. nepotism) hypothesis. Exceptions were oral communities and the fecal communities of two infants that had undergone heavy antibiotic treatment. None of the data sets we analyzed showed statistically significant phylogenetic overdispersion.

In October of 2020, researchers from around the world met online for the sixth annual International Workshop on Microbiome in HIV Pathogenesis, Prevention, and Treatment. New research was presented on the roles of the microbiome on immune response and HIV transmission and pathogenesis and the potential for alterations in the microbiome to decrease transmission and affect comorbidities. This article presents a summary of the findings reported.

BackgroundUnderstanding the factors that influence microbes’ environmental distributions is important for deter-mining drivers of microbial community composition. These include environmental variables like temperature and pH, and higher-dimensional variables like geographic distance and host species phylogeny. In microbial ecology, “specificity” is often described in the context of symbiotic or host parasitic interactions, but specificity can be more broadly used to describe the extent to which a species occupies a narrower range of an environmental variable than expected by chance. Using a standardization we describe here, Rao’s (1982, 2010) Quadratic Entropy can be conveniently applied to calculate specificity of a feature, such as a species, to many different environmental variables.ResultsWe present our R package specificity for performing the above analyses, and apply it to four real-life microbial data sets to demonstrate its application. We found that many fungi within the leaves of native Hawaiian plants had strong specificity to rainfall and elevation, even though these variables showed minimal importance in a previous analysis of fungal beta-diversity. In Antarctic cryoconite holes, our tool revealed that many bacteria have specificity to co-occurring algal community composition. Similarly, in the human gut microbiome, many bacteria showed specificity to the composition of bile acids. Finally, our analysis of the Earth Microbiome Project data set showed that most bacteria show strong ontological specificity to sample type. Our software performed as expected on synthetic data as well.Conclusionsspecificity is well-suited to analysis of microbiome data, both in synthetic test cases, and across multiple environment types and experimental designs. The analysis and software we present here can reveal patterns in microbial taxa that may not be evident from a community-level perspective. These insights can also be visualized and interactively shared among researchers using specificity’s companion package, specificity.shiny.

Men who have sex with men (MSM), regardless of HIV infection status, have an intestinal microbiome that is compositionally distinct from men who have sex with women (MSW) and women. We recently showed HIV-negative MSM have elevated levels of intestinal CD4+ T cells expressing CCR5, a critical co-receptor for HIV. Whether elevated expression of CCR5 is driven by the altered gut microbiome composition in MSM has not been explored. Here we used in vitro stimulation of gut Lamina Propria Mononuclear Cells (LPMCs) with whole intact microbial cells isolated from stool to demonstrate that fecal bacterial communities (FBCs) from HIV-positive/negative MSM induced higher frequencies of CCR5+ CD4+ T cells compared to FBCs from HIV-negative MSW and women. To identify potential microbial drivers, we related the frequency of CCR5+ CD4+ T cells to the abundance of individual microbial taxa in rectal biopsy of HIV-positive/negative MSM and controls, and Holdemanella biformis was strongly associated with increased frequency of CCR5+ CD4+ T cells. We used in vitro stimulation of gut LPMCs with the type strain of H. biformis, a second strain of H. biformis and an isolate of the closely related Holdemanella porci , cultured from either a HIV-positive or a HIV-negative MSM stool. H. porci elevated the frequency of both CCR5+ CD4+ T cells and the ratio of TNF-α/IL-10 Genomic comparisons of the 3 Holdemanella isolates revealed unique cell wall and capsular components, which may be responsible for their differences in immunogenicity. These findings describe a novel mechanism potentially linking intestinal dysbiosis in MSM to HIV transmission and mucosal pathogenesis.

BackgroundIntestinal parasitic infections are among the most common communicable diseases worldwide, particularly in developing countries. Human immunodeficiency virus (HIV) causes dysregulation of the immune system through the depletion of CD4+ T lymphocytes which gives rise to opportunistic infections.MethodologyA cross-sectional study was conducted from January to October 2018. Stool and blood samples were collected from participants aged 1 to 19. Stool samples were analyzed for intestinal parasites. Blood samples were analyzed for HIV and CD4 + T cell counts.ResultsOut of 214 children enrolled, 119 (55.6%) were HIV infected and 95 (44.4%) were HIV non-infected. All infected children were on antiretroviral treatment (ART). The prevalence of intestinal parasites was 20.2% in HIV infected and 15.8% in non-infected children. Among the 119 HIV infected children, 33 (27.7%) of them had a CD4+ T cell count less than 500 cells/mm3, and amongst them 5.9% had CD4+ T cell count less than 200 cells/mm3. Among HIV infected children, Cryptosporidium spp. was frequently detected, 7/119 (5.9%), followed by Giardia lamblia 5/119 (4.2%) then Blastocystis hominis 3/119 (2.5%) and Entamoeba coli 3/119 (2.5%). Participants on ART and prophylactic co-trimoxazole for >10 years had little or no parasite infestation.ConclusionsAlthough ART treatment in combination with prophylactic co-trimoxazole reduces the risk of parasitic infection, 20.2% of HIV infected children harbored intestinal parasites including Cryptosporidium spp. Stool analysis may be routinely carried out in order to treat detected cases of opportunistic parasites and such improve more on the life quality of HIV infected children.

Gut dysbiosis, defined as a maladaptive gut microbial imbalance, has been demonstrated in patients with end-stage liver disease, defined as a contributor to disease progression, and associated clinically with severity of disease and liver-related morbidity and mortality. Despite this well-recognized phenomena in patients with end-stage liver disease, the impact of gut dysbiosis and its rate of recovery following liver transplantation (LT) remains incompletely understood. The mechanisms by which alterations in the gut microbiota impact allograft metabolism and immunity, both directly and indirectly, are multifactorial and reflect the complexity of the gut-liver axis. Importantly, while research has largely focused on quantitative and qualitative changes in gut microbial composition, changes in microbial functionality (in the presence or absence of compositional changes) are of critical importance. Therefore, to translate functional microbiomics into clinical practice, one must understand not only the compositional but also the functional changes associated with gut dysbiosis and its resolution post-LT. In this review, we will summarize critical advances in functional microbiomics in LT recipients as they apply to immune-mediated allograft injury, posttransplant complications, and disease recurrence, while highlighting potential areas for microbial-based therapeutics in LT recipients.

BackgroundWhether human immunodeficiency virus (HIV) infection impacts gut microbial α-diversity is controversial. We reanalyzed raw 16S ribosomal RNA (rRNA) gene sequences and metadata from published studies to examine α-diversity measures between HIV-uninfected (HIV–) and HIV-infected (HIV+) individuals.MethodsWe conducted a systematic review and individual level meta-analysis by searching Embase, Medline, and Scopus for original research studies (inception to 31 December 2017). Included studies reported 16S rRNA gene sequences of fecal samples from HIV+ patients. Raw sequence reads and metadata were obtained from public databases or from study authors. Raw reads were processed through standardized pipelines with use of a high-resolution taxonomic classifier. The χ2 test, paired t tests, and generalized linear mixed models were used to relate α-diversity measures and clinical metadata.ResultsTwenty-two studies were identified with 17 datasets available for analysis, yielding 1032 samples (311 HIV–, 721 HIV+). HIV status was associated with a decrease in measures of α-diversity (P < .001). However, in stratified analysis, HIV status was associated with decreased α-diversity only in women and in men who have sex with women (MSW) but not in men who have sex with men (MSM). In analyses limited to women and MSW, controlling for HIV status, women displayed increased α-diversity compared with MSW.ConclusionsOur study suggests that HIV status, sexual risk category, and gender impact gut microbial community α-diversity. Future studies should consider MSM status in gut microbiome analyses.

Poor metabolic health, characterized by insulin resistance and dyslipidemia, is higher in people living with HIV and has been linked with inflammation, antiretroviral therapy (ART) drugs, and ART-associated lipodystrophy (LD). Metabolic disease is associated with gut microbiome composition outside the context of HIV but has not been deeply explored in HIV infection or in high-risk men who have sex with men (HR-MSM), who have a highly altered gut microbiome composition. Furthermore, the contribution of increased bacterial translocation and associated systemic inflammation that has been described in HIV-positive and HR-MSM individuals has not been explored. We used a multiomic approach to explore relationships between impaired metabolic health, defined using fasting blood markers, gut microbes, immune phenotypes, and diet. Our cohort included ART-treated HIV-positive MSM with or without LD, untreated HIV-positive MSM, and HR-MSM. For HIV-positive MSM on ART, we further explored associations with the plasma metabolome. We found that elevated plasma lipopolysaccharide binding protein (LBP) was the most important predictor of impaired metabolic health and network analysis showed that LBP formed a hub joining correlated microbial and immune predictors of metabolic disease. Taken together, our results suggest the role of inflammatory processes linked with bacterial translocation and interaction with the gut microbiome in metabolic disease among HIV-positive and -negative MSM. IMPORTANCE The gut microbiome in people living with HIV (PLWH) is of interest since chronic infection often results in long-term comorbidities. Metabolic disease is prevalent in PLWH even in well-controlled infection and has been linked with the gut microbiome in previous studies, but little attention has been given to PLWH. Furthermore, integrated analyses that consider gut microbiome, together with diet, systemic immune activation, metabolites, and demographics, have been lacking. In a systems-level analysis of predictors of metabolic disease in PLWH and men who are at high risk of acquiring HIV, we found that increased lipopolysaccharide-binding protein, an inflammatory marker indicative of compromised intestinal barrier function, was associated with worse metabolic health. We also found impaired metabolic health associated with specific dietary components, gut microbes, and host and microbial metabolites. This study lays the framework for mechanistic studies aimed at targeting the microbiome to prevent or treat metabolic endotoxemia in HIV-infected individuals.

Research relating gut microbiome composition to autism spectrum disorders (ASD) has produced inconsistent results, indicative of the disorder’s complexity and the need for more sophisticated experimental designs. We address this need by (i) comparing gut microbiome composition between individuals with ASD and neurotypical controls in Arizona and Colorado using standardized DNA extraction and sequencing methods at both locations and (ii) longitudinally evaluating the gut microbiome’s relationship to autism behavioral severity, diet, and gastrointestinal symptoms. Gut microbiome composition differed between individuals in Arizona and individuals in Colorado, and gastrointestinal symptoms were significantly higher in ASD individuals than in neurotypical individuals in Arizona but not in Colorado. Gut microbiome composition was significantly associated with ASD while controlling for study-site location but not when controlling for gastrointestinal symptoms. This suggests that non-ASD-related study site differences in gut microbiome composition and different degrees of gastrointestinal symptoms involvement with ASD between sites may contribute to inconsistent results in the literature regarding the association between gut microbiome composition and ASD. In the longitudinal analysis, we found that difference in levels of lethargy/social withdrawal measured in individuals at different time points correlated with the degree of change in gut microbiome composition and that a worsening of inappropriate speech between time points was associated with decreased gut microbiome diversity. This relationship between changes in the gut microbiome composition within individuals and ASD behavioral severity metrics indicates that longitudinal study designs may be useful for exploring microbial drivers of ASD severity when substantial variability exists in baseline microbiome compositions across individuals and geographical regions. IMPORTANCE Autism spectrum disorder (ASD) is a brain developmental disorder with varying behavioral symptom severity both across individuals and within individuals over time. There have been promising but also inconsistent literature results regarding how the gut microbiota (microbiome) may be involved. We found that the gut microbiome in individuals with ASD is affected by study-site location as well as gastrointestinal symptom severity. When we sampled some individuals with ASD at several different time points, we found that some behaviors, such as lethargy/social withdrawal and inappropriate speech, changed along with changes in the gut microbiota composition. This is the first study to relate severity of behavior symptoms to gut microbiome composition within individuals over time and suggests a dynamic relationship between ASD-associated symptoms and gut microbes. Longitudinal study designs as well as collaborative efforts across multiple centers are needed to fully characterize the relationship between ASD and gut microbes.

Multiple factors, such as immune disruption, prophylactic co-trimoxazole, and antiretroviral therapy, may influence the structure and function of the gut microbiome of children infected with HIV from birth. In order to understand whether HIV infection altered gut microbiome and to relate changes in microbiome structure and function to immune status, virological response and pediatric ART regimens, we characterized the gut microbiome of 87 HIV-infected and 82 non-exposed HIV-negative children from Yaounde, a cosmopolitan city in Cameroon. We found that children living with HIV had significantly lower alpha diversity in their gut microbiome and altered beta diversity that may not be related to CD4+ T cell count or viral load. There was an increased level of Akkermansia and Faecalibacterium genera and decreased level of Escherichia and other Gamma proteobacteria in children infected with HIV, among other differences. We noted an effect of ethnicity/geography on observed gut microbiome composition and that children on ritonavir-boosted protease inhibitor (PI/r)-based ART had gut microbiome composition that diverged more from HIV-negative controls compared to those on non-nucleoside reverse-transcriptase inhibitors-based ART. Further studies investigating the role of this altered gut microbiome in increased disease susceptibility are warranted for individuals who acquired HIV via mother-to-child transmission.

Poor metabolic health, characterized by insulin resistance and dyslipidemia, is higher in people living with HIV (PLWH) and has been linked with inflammation, anti-retroviral therapy (ART) drugs, and ART-associated lipodystrophy (LD). Metabolic disease is associated with gut microbiome composition outside the context of HIV but has not been deeply explored in HIV infection nor in high-risk men who have sex with men (HR-MSM), who have a highly altered gut microbiome composition. Furthermore, the contribution of increased bacterial translocation and associated systemic inflammation that has been described in HIV-positive and HR-MSM individuals has not been explored. We used a multi-omic approach to explore relationships between gut microbes, immune phenotypes, diet, and metabolic health across ART-treated PLWH with and without LD; untreated PLWH; and HR-MSM. For PLWH on ART, we further explored associations with the plasma metabolome. Sixty-nine measures of diet, gut microbes, inflammation, and demographics were associated with impaired metabolic health defined using fasting blood markers including lipids, glucose and hormones. We found microbiome-associated metabolites associated with metabolic disease including the microbially produced metabolites, dehydroalanine and bacteriohopane-32,33,34,35-tetrol. Our central result was that elevated plasma lipopolysaccharide binding protein (LBP) was the most important predictor of metabolic disease in PLWH and HR-MSM, with network analysis of predictors showing that LBP formed a hub joining correlated microbial and immune predictors of metabolic disease. Our results suggest the role of inflammatory processes linked with bacterial translocation (measured by LBP) and interaction with dietary components and the gut microbiome in metabolic disease among PLWH and HR-MSM. Importance StatementThe role of the gut microbiome in the health of HIV infected individuals is of interest because current therapies, while effective at controlling disease, still result in long term comorbidities. Metabolic disease is prevalent in HIV-infected individuals even in well-controlled infection. Metabolic disease has been linked with the gut microbiome in previous studies but little attention has been given to HIV infected populations. Furthermore, integrated analyses that consider gut microbiome composition together with data on diet, systemic immune activation, metabolites and demographic data have been lacking. By conducting a systems level analysis of predictors of metabolic disease in people living with HIV and men who are at high risk of acquiring HIV, we found that increased LBP, an inflammatory marker indicative of compromised intestinal barrier function, was associated with worse metabolic health. We also found this relationship to be associated with dietary, microbial, and metabolic factors suggesting a systemic gut microbiome influence on the presence of increased inflammatory markers which, in turn, influences the risk of metabolic disease. This work lays the framework for mechanistic studies aimed at targeting the microbiome and diet to prevent or treat metabolic endotoxemia in HIV-infected individuals.

Although the COVID-19 pandemic is caused by a single virus, the rest of the human microbiome appears to be involved in the disease and could influence vaccine responses while offering opportunities for microbiome-directed therapeutics. The newly formed Microbiome Centers Consortium (MCC) surveyed its membership and identified four ways to leverage the strengths and experience of microbiome centers in the response to the COVID-19 pandemic., Although the COVID-19 pandemic is caused by a single virus, the rest of the human microbiome appears to be involved in the disease and could influence vaccine responses while offering opportunities for microbiome-directed therapeutics. The newly formed Microbiome Centers Consortium (MCC) surveyed its membership and identified four ways to leverage the strengths and experience of microbiome centers in the response to the COVID-19 pandemic. To meet these needs, the MCC will provide a platform to coordinate clinical and environmental research, assist with practical obstacles, and help communicate the connections between the microbiome and COVID-19. We ask that microbiome researchers join us in these efforts to address the ongoing pandemic.

BackgroundMicrobiome studies are often limited by a lack of statistical power due to small sample sizes and a large number of features. This problem is exacerbated in correlative studies of multi-omic datasets. Statistical power can be increased by finding and summarizing modules of correlated observations, which is one dimensionality reduction method. Additionally, modules provide biological insight as correlated groups of microbes can have relationships among themselves.ResultsTo address these challenges, we developed SCNIC: Sparse Cooccurrence Network Investigation for compositional data. SCNIC is open-source software that can generate correlation networks and detect and summarize modules of highly correlated features. Modules can be formed using either the Louvain Modularity Maximization (LMM) algorithm or a Shared Minimum Distance algorithm (SMD) that we newly describe here and relate to LMM using simulated data. We applied SCNIC to two published datasets and we achieved increased statistical power and identified microbes that not only differed across groups, but also correlated strongly with each other, suggesting shared environmental drivers or cooperative relationships among them.ConclusionsSCNIC provides an easy way to generate correlation networks, identify modules of correlated features and summarize them for downstream statistical analysis. Although SCNIC was designed considering properties of microbiome data, such as compositionality and sparsity, it can be applied to a variety of data types including metabolomics data and used to integrate multiple data types. SCNIC allows for the identification of functional microbial relationships at scale while increasing statistical power through feature reduction.

While much of the research concerning factors associated with responses to immunotherapies focuses on the contributions of conventional peptide-specific T cells, the role of unconventional T cells, such as mucosalassociated invariant T (MAIT) cells, in human melanoma remains largely unknown. MAIT cells are innate-like T cells expressing a semi-invariant T cell receptor restricted to the non-classical MHC class I molecule MR1 presenting vitamin metabolites derived from bacteria. In this prospective clinical study, we sought to characterize MAIT cells in melanoma patients and determine their association with clinical outcomes. We identified tumor-infiltrating MAIT cells in melanomas across metastatic sites and found that the number of circulating MAIT cells is reduced in melanoma patients. However, circulating MAIT cell frequency is restored by anti-PD1 treatment in responding patients, correlating with treatment responses in which patients with high frequencies of MAIT cells exhibited improved overall survival. These data provide evidence for leveraging MAIT cells and their functions as novel targets for future therapies.

Bacterial hemagglutination of red blood cells (RBCs) is mediated by interactions between bacterial cell components and RBC envelope glycans that vary across individuals by ABO blood type. ABO glycans are also expressed on intestinal epithelial cells and in most individuals secreted into the intestinal mucosa, indicating that hemagglutination by bacteria may be informative about bacteria-host interactions in the intestine. Bacteroides fragilis, a prominent member of the human gut microbiota, can hemagglutinate RBCs by an unknown mechanism. Using a novel technology for quantifying bacterial hemagglutination, genetic knockout strains of B. fragilis and blocking antiserums, we demonstrate that the capsular polysaccharides of B. fragilis, polysaccharide B (PSB), and PSC are both strong hemagglutinins. Furthermore, the capacity of B. fragilis to hemagglutinate was much stronger in individuals with Type O blood compared to Types A and B, an adaptation that could impact the capacity of B. fragilis to colonize and thrive in the host.Importance StatementThis study found that the human pathobiont, B. fragilis, hemagglutinates human red blood cells using specific capsular polysaccharides (PSB and PSC) which are known to be important for interacting with and influencing host immune responses. Because the factors found on red blood cells are also abundantly expressed on other tissues and in the mucous, the ability to hemagglutinate sheds light on interactions between bacteria and host throughout the body. Intriguingly, the strength of hemagglutination varied based on the ABO blood type of the host, a finding which could have implications for understanding if an individual’s blood type may influence interactions with B. fragilis and its potential as a pathogen versus a commensal.

Gut microbiome characteristics associated with HIV infection are of intense research interest but a deep understanding has been challenged by confounding factors across studied populations. Notably, a Prevotella-rich microbiome described in HIV-infected populations is now understood to be common in men who have sex with men (MSM) regardless of HIV status, but driving factors and potential health implications are unknown.Here, we further define the MSM-associated gut microbiome and describe compositional differences between the fecal microbiomes of Prevotella-rich MSM and non-MSM that may underlie observed pro-inflammatory properties. Furthermore, we show relatively subtle gut microbiome changes in HIV infection in MSM and women that include an increase in potential pathogens that is ameliorated with antiretroviral therapy (ART). Lastly, using a longitudinal cohort, we describe microbiome changes that happen after ART initiation.This study provides an in-depth characterization of microbiome differences that occur in a US population infected with HIV and demonstrates the degree to which these differences may be driven by lifestyle factors, ART, and HIV infection itself. Understanding microbiome compositions that occur with sexual behaviors that are high risk for acquiring HIV and untreated and ART-treated HIV infection will guide the investigation of immune and metabolic functional implications to ultimately target the microbiome therapeutically.

Dysbiosis, an imbalance in microbial communities, is linked with disease when this imbalance disturbs microbiota functions essential for maintaining health or introduces processes that promote disease. Dysbiosis in disease is predicted when microbiota differ compositionally from a healthy control population, but only truly defined when these differences are mechanistically related to adverse phenotypes. For the human gut microbiota, dysbiosis varies across diseases. One common manifestation is replacement of the complex community of anaerobes typical of the healthy adult gut microbiome with a community of lower overall microbial diversity and increased facultative anaerobes. Here we review diseases in which low-diversity dysbiosis has been observed and mechanistically linked with disease, with a particular focus on liver disease, inflammatory bowel disease, and Clostridium difficile infection.

Recent evidence supports that the gut microbiota may be involved in the pathophysiology of non-alcoholic fatty liver disease (NAFLD), and may also offer avenues for treatment or prevention. We investigated the associations among gut microbiota, diet, and hepatic fat fraction (HFF) in 107 adolescents. Magnetic resonance imaging (MRI) was used to assess HFF, and 16S rRNA gene sequencing was performed on collected fecal samples. Dietary intake was assessed using Food Frequency Questionnaires. We examined the association between gut microbiota alpha diversity and HFF, and assessed the predictive accuracy for HFF of (1) taxonomic composition, (2) dietary intake, (3) demographic and comorbid conditions, and (4) the combination of these. Lower alpha diversity was associated with higher HFF (β=−0.19, 95% confidence interval (CI) −0.36, −0.02). The selected taxa explained 17.7% (95% CI: 16.0–19.4%) of the variation in HFF. The combination of two of these taxa, Bilophila and Paraprevotella, with dietary intake of monounsaturated fatty acids and BMI z-scores explained 32.0% (95% CI: 30.3–33.6%) of the variation in HFF. The gut microbiota is associated with HFF in adolescents and may be useful to help identify youth who would be amenable to gut microbiota-based interventions.

The inflammatory properties of the enteric microbiota of Human Immunodeficiency Virus (HIV)-infected individuals are of considerable interest because of strong evidence that bacterial translocation contributes to chronic immune activation and disease progression. Altered enteric microbiota composition occurs with HIV infection but whether altered microbiota composition or increased intestinal permeability alone drives peripheral immune activation is controversial. To comprehensively assess the inflammatory properties of HIV-associated enteric microbiota and relate these to systemic immune activation, we developed methods to purify whole fecal bacterial communities (FBCs) from stool for use in in vitro immune stimulation assays with human cells. We show that the enteric microbiota of untreated HIV-infected subjects induce significantly higher levels of activated monocytes and T cells compared to seronegative subjects. FBCs from anti-retroviral therapy (ART)-treated HIV-infected individuals induced intermediate T cell activation, indicating an only partial correction of adaptive immune cell activation capacity of the microbiome with ART. In vitro activation levels correlated with activation levels and viral load in blood and were particularly high in individuals harboring specific gram-positive opportunistic pathogens. Blockade experiments implicated Tumor Necrosis Factor (TNF)-α and Toll-Like Receptor-2 (TLR2), which recognizes peptidoglycan, as strong mediators of T cell activation; This may contradict a previous focus on lipopolysaccharide as a primary mediator of chronic immune activation. These data support that increased inflammatory properties of the enteric microbiota and not increased permeability alone drives chronic inflammation in HIV., Highlights • The fecal microbiomes of HIV positive subjects induce higher levels of activated monocytes and T cells in vitro. • Levels of induced activation in vitro correlate with activation levels and viral load in the blood. • HIV-associated microbiome immune activation is linked to the pathways involving the inflammatory cytokine TNF-α, and TLR-2. Chronic immune activation is a hallmark of HIV infection. Although many studies defined gut microbiome dysbiosis with HIV, we have little understanding of whether a pro-inflammatory microbiome underlies systemic immune activation. Here, we show that fecal microbiomes of individuals with HIV induce higher levels of activated monocytes and T cells in vitro, and these levels correlate with activation levels and viral load in blood. We also link this to the inflammatory cytokine TNF-α, TLR2 (which recognizes peptidoglycan), and specific gram-positive opportunistic bacteria. This work heralds toward a deep understanding of mechanisms by which the HIV-associated gut microbiome composition drives disease.

Growing evidence suggests that host-microbiota interactions influence GvHD risk following allogeneic hematopoietic stem cell transplant. However, little is known about the influence of the transplant recipient's pre-conditioning microbiota nor the influence of the transplant donor's microbiota. Our study examines associations between acute gastrointestinal GvHD (agGvHD) and 16S rRNA fecal bacterial profiles in a prospective cohort of N=57 recipients before preparative conditioning, as well as N=22 of their paired HLA-matched sibling donors. On average, recipients had lower fecal bacterial diversity (P=0.0002) and different phylogenetic membership (UniFrac P=0.001) than the healthy transplant donors. Recipients with lower phylogenetic diversity had higher overall mortality rates (hazard ratio=0.37, P=0.008), but no statistically significant difference in agGvHD risk. In contrast, high bacterial donor diversity was associated with decreased agGvHD risk (odds ratio=0.12, P=0.038). Further investigation is warranted as to whether selection of hematopoietic stem cell transplant donors with high gut microbiota diversity and/or other specific compositional attributes may reduce agGvHD incidence, and by what mechanisms.

Asthma prevalence has been on the increase, especially in North America compared with other continents. However, the prevalence of asthma differs worldwide, and in many countries the prevalence is stable or decreasing. This highlights the influence of environmental exposures, such as allergens, air pollution, and the environmental microbiome, on disease etiology and pathogenesis. The epigenome might provide the unifying mechanism that translates the influence of environmental exposures to changes in gene expression, respiratory epithelial function, and immune cell skewing that are hallmarks of asthma. In this review we will introduce the concept of the environmental epigenome in asthmatic patients, summarize previous publications of relevance to this field, and discuss future directions.

Clostridioides difficile infection (CDI) is the leading cause of hospital-acquired diarrhea, and emerging evidence has linked dietary components with CDI pathogenesis, suggesting that dietary modulation may be an effective strategy for prevention. Here, we show that mice fed a high-fat/low-fiber "Western-type" diet (WD) had dramatically increased mortality in a murine model of antibiotic-induced CDI compared to a low-fat/low-fiber (LF/LF) diet and standard mouse chow controls. We found that the WD had a pro- C. difficile bile acid composition that was driven in part by higher levels of primary bile acids that are produced to digest fat, and a lower level of secondary bile acids that are produced by the gut microbiome. This lack of secondary bile acids was associated with a greater disturbance to the gut microbiome with antibiotics in both the WD and LF/LF diet compared to mouse chow. Mice fed the WD also had the highest level of toxin TcdA just prior to the onset of mortality, but not of TcdB or increased inflammation. These findings indicate that dietary intervention to decrease fat may complement previously proposed dietary intervention strategies to prevent CDI in high-risk individuals.

Clostridioides difficile infection (CDI), is the leading cause of hospital-acquired diarrhea and emerging evidence has linked dietary components with CDI pathogenesis, suggesting that dietary modulation may be an effective strategy for prevention. Here, we show that mice fed a high-fat/low-fiber “Western type” diet (WD) had dramatically increased mortality in a murine model of antibiotic-induced CDI compared to a low-fat/low-fiber (LF/LF) diet and standard mouse chow controls. We found that the WD had a pro- C. difficile bile acid composition that was driven in part by higher levels of primary bile acids that are produced to digest fat, and a lower level of secondary bile acids that are produced by the gut microbiome. This lack of secondary bile acids was associated with a greater disturbance to the gut microbiome with antibiotics in both the WD and LF/LF diet compared to mouse chow. Mice fed the WD also had the highest level of toxin TcdA just prior to the onset of mortality, but not of TcdB or increased inflammation. These findings indicate that dietary intervention to decrease fat may complement previously proposed dietary intervention strategies to prevent CDI in high-risk individuals.One Sentence SummaryA high-fat/low-fiber Western type diet promoted mortality in a mouse model of antibiotic-induced C. difficile infection compared to a low-fat/low-fiber diet and chow diet, suggesting that lower dietary fat may be an effective strategy for preventing C. difficile pathology.

Background Untargeted metabolomics of host-associated samples has yielded insights into mechanisms by which microbes modulate health. However, data interpretation is challenged by the complexity of origins of the small molecules measured, which can come from the host, microbes that live within the host, or from other exposures such as diet or the environment. Results We address this challenge through development of AMON: Annotation of Metabolite Origins via Networks. AMON is an open-source bioinformatics application that can be used to annotate which compounds in the metabolome could have been produced by bacteria present or the host, to evaluate pathway enrichment of host verses microbial metabolites, and to visualize which compounds may have been produced by host versus microbial enzymes in KEGG pathway maps. Conclusions AMON empowers researchers to predict origins of metabolites via genomic information and to visualize potential host:microbe interplay. Additionally, the evaluation of enrichment of pathway metabolites of host versus microbial origin gives insight into the metabolic functionality that a microbial community adds to a host:microbe system. Through integrated analysis of microbiome and metabolome data, mechanistic relationships between microbial communities and host phenotypes can be better understood.

CRS3123 is a novel small molecule that potently inhibits methionyl-tRNA synthetase of Clostridioides difficile, inhibiting C. difficile toxin production and spore formation. CRS3123 has been evaluated in a multiple-ascending-dose placebo-controlled phase 1 trial., CRS3123 is a novel small molecule that potently inhibits methionyl-tRNA synthetase of Clostridioides difficile, inhibiting C. difficile toxin production and spore formation. CRS3123 has been evaluated in a multiple-ascending-dose placebo-controlled phase 1 trial. Thirty healthy subjects, ages 18 to 45 years, were randomized into three cohorts of 10 subjects each, receiving either 200, 400, or 600 mg of CRS3123 (8 subjects per cohort) or placebo (2 subjects per cohort) by oral administration twice daily for 10 days. CRS3123 was generally safe and well tolerated, with no serious adverse events (SAEs) or severe treatment-emergent adverse events (TEAEs) reported. All subjects completed their assigned treatment and follow-up visits, and there were no trends in systemic, vital sign, or laboratory TEAEs. There were no QTcF interval changes or any clinically significant changes in other electrocardiogram (ECG) intervals or morphology. CRS3123 showed limited but detectable systemic uptake; although absorption increased with increasing dose, the increase was less than dose proportional. Importantly, the bulk of the oral dose was not absorbed, and fecal concentrations were substantially above the MIC90 value of 1 μg/ml at all dosages tested. Subjects receiving either of the two lower doses of CRS3123 exhibited minimal disruption of normal gut microbiota after 10 days of twice-daily dosing. CRS3123 was inactive against important commensal anaerobes, including Bacteroides, bifidobacteria, and commensal clostridia. Microbiome data showed favorable differentiation compared to other CDI therapeutics. These results support further development of CRS3123 as an oral agent for the treatment of CDI. (This study has been registered at Clinicaltrials.gov under identifier NCT02106338.)