Disruption of Genes Encoding Putative Zwitterionic Capsular Polysaccharides of Diverse Intestinal Bacteroides Reduces the Induction of Host Anti-Inflammatory Factors.

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.

CANTARE: finding and visualizing network-based multi-omic predictive models.

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.

Gut microbiota from high-risk men who have sex with men drive immune activation in gnotobiotic mice and in vitro HIV infection.

Men who have sex with men (MSM) have differences in immune activation and gut microbiome composition compared with men who have sex with women (MSW), even in the absence of HIV infection. Gut microbiome differences associated with HIV itself when controlling for MSM, as assessed by 16S rRNA sequencing, are relatively subtle. Understanding whether gut microbiome composition impacts immune activation in HIV-negative and HIV-positive MSM has important implications since immune activation has been associated with HIV acquisition risk and disease progression. To investigate the effects of MSM and HIV-associated gut microbiota on immune activation, we transplanted feces from HIV-negative MSW, HIV-negative MSM, and HIV-positive untreated MSM to gnotobiotic mice. Following transplant, 16S rRNA gene sequencing determined that the microbiomes of MSM and MSW maintained distinct compositions in mice and that specific microbial differences between MSM and MSW were replicated. Immunologically, HIV-negative MSM donors had higher frequencies of blood CD38+ HLADR+ and CD103+ T cells and their fecal recipients had higher frequencies of gut CD69+ and CD103+ T cells, compared with HIV-negative MSW donors and recipients, respectively. Significant microbiome differences were not detected between HIV-negative and HIV-positive MSM in this small donor cohort, and immune differences between their recipients were trending but not statistically significant. A larger donor cohort may therefore be needed to detect immune-modulating microbes associated with HIV. To investigate whether our findings in mice could have implications for HIV replication, we infected primary human lamina propria cells stimulated with isolated fecal microbiota, and found that microbiota from MSM stimulated higher frequencies of HIV-infected cells than microbiota from MSW. Finally, we identified several microbes that correlated with immune readouts in both fecal recipients and donors, and with in vitro HIV infection, which suggests a role for gut microbiota in immune activation and potentially HIV acquisition in MSM.

Muc5b is required for airway defence.

Respiratory surfaces are exposed to billions of particulates and pathogens daily. A protective mucus barrier traps and eliminates them through mucociliary clearance (MCC). However, excessive mucus contributes to transient respiratory infections and to the pathogenesis of numerous respiratory diseases. MUC5AC and MUC5B are evolutionarily conserved genes that encode structurally related mucin glycoproteins, the principal macromolecules in airway mucus. Genetic variants are linked to diverse lung diseases, but specific roles for MUC5AC and MUC5B in MCC, and the lasting effects of their inhibition, are unknown. Here we show that mouse Muc5b (but not Muc5ac) is required for MCC, for controlling infections in the airways and middle ear, and for maintaining immune homeostasis in mouse lungs, whereas Muc5ac is dispensable. Muc5b deficiency caused materials to accumulate in upper and lower airways. This defect led to chronic infection by multiple bacterial species, including Staphylococcus aureus, and to inflammation that failed to resolve normally. Apoptotic macrophages accumulated, phagocytosis was impaired, and interleukin-23 (IL-23) production was reduced in Muc5b(-/-) mice. By contrast, in mice that transgenically overexpress Muc5b, macrophage functions improved. Existing dogma defines mucous phenotypes in asthma and chronic obstructive pulmonary disease (COPD) as driven by increased MUC5AC, with MUC5B levels either unaffected or increased in expectorated sputum. However, in many patients, MUC5B production at airway surfaces decreases by as much as 90%. By distinguishing a specific role for Muc5b in MCC, and by determining its impact on bacterial infections and inflammation in mice, our results provide a refined framework for designing targeted therapies to control mucin secretion and restore MCC.

VOLARE: visual analysis of disease-associated microbiome-immune system interplay.

BACKGROUND: Relationships between specific microbes and proper immune system development, composition, and function have been reported in a number of studies. However, researchers have discovered only a fraction of the likely relationships. "Omic" methodologies such as 16S ribosomal RNA (rRNA) sequencing and time-of-flight mass cytometry (CyTOF) immunophenotyping generate data that support generation of hypotheses, with the potential to identify additional relationships at a level of granularity ripe for further experimentation. Pairwise linear regressions between microbial and host immune features provide one approach for quantifying relationships between "omes", and the differences in these relationships across study cohorts or arms. This approach yields a top table of candidate results. However, the top table alone lacks the detail that domain experts such as microbiologists and immunologists need to vet candidate results for follow-up experiments. RESULTS: To support this vetting, we developed VOLARE (Visualization Of LineAr Regression Elements), a web application that integrates a searchable top table, small in-line graphs illustrating the fitted models, a network summarizing the top table, and on-demand detailed regression plots showing full sample-level detail. We applied VOLARE to three case studies-microbiome:cytokine data from fecal samples in human immunodeficiency virus (HIV), microbiome:cytokine data in inflammatory bowel disease and spondyloarthritis, and microbiome:immune cell data from gut biopsies in HIV. We present both patient-specific phenomena and relationships that differ by disease state. We also analyzed interaction data from system logs to characterize usage scenarios. This log analysis revealed that users frequently generated detailed regression plots, suggesting that this detail aids the vetting of results. CONCLUSIONS: Systematically integrating microbe:immune cell readouts through pairwise linear regressions and presenting the top table in an interactive environment supports the vetting of results for scientific relevance. VOLARE allows domain experts to control the analysis of their results, screening dozens of candidate relationships with ease. This interactive environment transcends the limitations of a static top table.

Multiple-Ascending-Dose Phase 1 Clinical Study of the Safety, Tolerability, and Pharmacokinetics of CRS3123, a Narrow-Spectrum Agent with Minimal Disruption of Normal Gut Microbiota.

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.).

Gut microbiota in adolescents and the association with fatty liver: the EPOCH study.

BACKGROUND: 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. METHODS: 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. RESULTS: Lower alpha diversity was associated with higher HFF (ß=-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. CONCLUSION: 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.

Diversity, stability and resilience of the human gut microbiota.

Trillions of microbes inhabit the human intestine, forming a complex ecological community that influences normal physiology and susceptibility to disease through its collective metabolic activities and host interactions. Understanding the factors that underlie changes in the composition and function of the gut microbiota will aid in the design of therapies that target it. This goal is formidable. The gut microbiota is immensely diverse, varies between individuals and can fluctuate over time - especially during disease and early development. Viewing the microbiota from an ecological perspective could provide insight into how to promote health by targeting this microbial community in clinical treatments.

Human gut microbiome viewed across age and geography.

Gut microbial communities represent one source of human genetic and metabolic diversity. To examine how gut microbiomes differ among human populations, here we characterize bacterial species in fecal samples from 531 individuals, plus the gene content of 110 of them. The cohort encompassed healthy children and adults from the Amazonas of Venezuela, rural Malawi and US metropolitan areas and included mono- and dizygotic twins. Shared features of the functional maturation of the gut microbiome were identified during the first three years of life in all three populations, including age-associated changes in the genes involved in vitamin biosynthesis and metabolism. Pronounced differences in bacterial assemblages and functional gene repertoires were noted between US residents and those in the other two countries. These distinctive features are evident in early infancy as well as adulthood. Our findings underscore the need to consider the microbiome when evaluating human development, nutritional needs, physiological variations and the impact of westernization.

Differences in fecal microbial metabolites and microbiota of children with autism spectrum disorders.

Evidence supporting that gut problems are linked to ASD symptoms has been accumulating both in humans and animal models of ASD. Gut microbes and their metabolites may be linked not only to GI problems but also to ASD behavior symptoms. Despite this high interest, most previous studies have looked mainly at microbial structure, and studies on fecal metabolites are rare in the context of ASD. Thus, we aimed to detect fecal metabolites that may be present at significantly different concentrations between 21 children with ASD and 23 neurotypical children and to investigate its possible link to human gut microbiome. Using 1H-NMR spectroscopy and 16S rRNA gene amplicon sequencing, we examined metabolite profiles and microbial compositions in fecal samples, respectively. Of the 59 metabolites detected, isopropanol concentrations were significantly higher in feces of children with ASD after multiple testing corrections. We also observed similar trends of fecal metabolites to previous studies; children with ASD have higher fecal p-cresol and possibly lower GABA concentrations. In addition, Fisher Discriminant Analysis (FDA) with leave-out-validation suggested that a group of metabolites-caprate, nicotinate, glutamine, thymine, and aspartate-may potentially function as a modest biomarker to separate ASD participants from the neurotypical group (78% sensitivity and 81% specificity). Consistent with our previous Arizona cohort study, we also confirmed lower gut microbial diversity and reduced relative abundances of phylotypes most closely related to Prevotella copri in children with ASD. After multiple testing corrections, we also learned that relative abundances of Feacalibacterium prausnitzii and Haemophilus parainfluenzae were lower in feces of children with ASD. Despite a relatively short list of fecal metabolites, the data in this study support that children with ASD have altered metabolite profiles in feces when compared with neurotypical children and warrant further investigation of metabolites in larger cohorts.

The environment, epigenome, and asthma.

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.

Meta-analyses of studies of the human microbiota.

Our body habitat-associated microbial communities are of intense research interest because of their influence on human health. Because many studies of the microbiota are based on the same bacterial 16S ribosomal RNA (rRNA) gene target, they can, in principle, be compared to determine the relative importance of different disease/physiologic/developmental states. However, differences in experimental protocols used may produce variation that outweighs biological differences. By comparing 16S rRNA gene sequences generated from diverse studies of the human microbiota using the QIIME database, we found that variation in composition of the microbiota across different body sites was consistently larger than technical variability across studies. However, samples from different studies of the Western adult fecal microbiota generally clustered by study, and the 16S rRNA target region, DNA extraction technique, and sequencing platform produced systematic biases in observed diversity that could obscure biologically meaningful compositional differences. In contrast, systematic compositional differences in the fecal microbiota that occurred with age and between Western and more agrarian cultures were great enough to outweigh technical variation. Furthermore, individuals with ileal Crohn's disease and in their third trimester of pregnancy often resembled infants from different studies more than controls from the same study, indicating parallel compositional attributes of these distinct developmental/physiological/disease states. Together, these results show that cross-study comparisons of human microbiota are valuable when the studied parameter has a large effect size, but studies of more subtle effects on the human microbiota require carefully selected control populations and standardized protocols.

Striking a Balance with Help from our Little Friends - How the Gut Microbiota Contributes to Immune Homeostasis.

The trillions of microbes that inhabit the human gut (the microbiota) together with the host comprise a complex ecosystem, and like any ecosystem, health relies on stability and balance. Some of the most important members of the human microbiota are those that help maintain this balance via modulation of the host immune system. Gut microbes, through both molecular factors (such as capsular components) and by-products of their metabolism (such as Short Chain Fatty Acids (SCFAs)), can influence both innate and adaptive components of the immune system, in ways that can drive both effector, and regulatory responses. Here we review how commensal microbes can specifically promote a dynamic balance of these immune responses in the mammalian gut.

The UniFrac significance test is sensitive to tree topology.

Long et al. (BMC Bioinformatics 2014, 15(1):278) describe a "discrepancy" in using UniFrac to assess statistical significance of community differences. Specifically, they find that weighted UniFrac results differ between input trees where (a) replicate sequences each have their own tip, or (b) all replicates are assigned to one tip with an associated count. We argue that these are two distinct cases that differ in the probability distribution on which the statistical test is based, because of the differences in tree topology. Further study is needed to understand which randomization procedure best detects different aspects of community dissimilarities.

RNASTAR: an RNA STructural Alignment Repository that provides insight into the evolution of natural and artificial RNAs.

Automated RNA alignment algorithms often fail to recapture the essential conserved sites that are critical for function. To assist in the refinement of these algorithms, we manually curated a set of 148 alignments with a total of 9600 unique sequences, in which each alignment was backed by at least one crystal or NMR structure. These alignments included both naturally and artificially selected molecules. We used principles of isostericity to improve the alignments from an average of 83%-94% isosteric base pairs. We expect that this alignment collection will assist in a wide range of benchmarking efforts and provide new insight into evolutionary principles governing change in RNA structural motifs. The improved alignments have been contributed to the Rfam database.

Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample.

The ongoing revolution in high-throughput sequencing continues to democratize the ability of small groups of investigators to map the microbial component of the biosphere. In particular, the coevolution of new sequencing platforms and new software tools allows data acquisition and analysis on an unprecedented scale. Here we report the next stage in this coevolutionary arms race, using the Illumina GAIIx platform to sequence a diverse array of 25 environmental samples and three known "mock communities" at a depth averaging 3.1 million reads per sample. We demonstrate excellent consistency in taxonomic recovery and recapture diversity patterns that were previously reported on the basis of metaanalysis of many studies from the literature (notably, the saline/nonsaline split in environmental samples and the split between host-associated and free-living communities). We also demonstrate that 2,000 Illumina single-end reads are sufficient to recapture the same relationships among samples that we observe with the full dataset. The results thus open up the possibility of conducting large-scale studies analyzing thousands of samples simultaneously to survey microbial communities at an unprecedented spatial and temporal resolution.

Pan-genome of the dominant human gut-associated archaeon, Methanobrevibacter smithii, studied in twins.

The human gut microbiota harbors three main groups of H(2)-consuming microbes: methanogens including the dominant archaeon, Methanobrevibacter smithii, a polyphyletic group of acetogens, and sulfate-reducing bacteria. Defining their roles in the gut is important for understanding how hydrogen metabolism affects the efficiency of fermentation of dietary components. We quantified methanogens in fecal samples from 40 healthy adult female monozygotic (MZ) and 28 dizygotic (DZ) twin pairs, analyzed bacterial 16S rRNA datasets generated from their fecal samples to identify taxa that co-occur with methanogens, sequenced the genomes of 20 M. smithii strains isolated from families of MZ and DZ twins, and performed RNA-Seq of a subset of strains to identify their responses to varied formate concentrations. The concordance rate for methanogen carriage was significantly higher for MZ versus DZ twin pairs. Co-occurrence analysis revealed 22 bacterial species-level taxa positively correlated with methanogens: all but two were members of the Clostridiales, with several being, or related to, known hydrogen-producing and -consuming bacteria. The M. smithii pan-genome contains 987 genes conserved in all strains, and 1,860 variably represented genes. Strains from MZ and DZ twin pairs had a similar degree of shared genes and SNPs, and were significantly more similar than strains isolated from mothers or members of other families. The 101 adhesin-like proteins (ALPs) in the pan-genome (45 ± 6 per strain) exhibit strain-specific differences in expression and responsiveness to formate. We hypothesize that M. smithii strains use their different repertoires of ALPs to create diversity in their metabolic niches, by allowing them to establish syntrophic relationships with bacterial partners with differing metabolic capabilities and patterns of co-occurrence.

Integrating biological knowledge for mechanistic inference in the host-associated microbiome.

Advances in high-throughput technologies have enhanced our ability to describe microbial communities as they relate to human health and disease. Alongside the growth in sequencing data has come an influx of resources that synthesize knowledge surrounding microbial traits, functions, and metabolic potential with knowledge of how they may impact host pathways to influence disease phenotypes. These knowledge bases can enable the development of mechanistic explanations that may underlie correlations detected between microbial communities and disease. In this review, we survey existing resources and methodologies for the computational integration of broad classes of microbial and host knowledge. We evaluate these knowledge bases in their access methods, content, and source characteristics. We discuss challenges of the creation and utilization of knowledge bases including inconsistency of nomenclature assignment of taxa and metabolites across sources, whether the biological entities represented are rooted in ontologies or taxonomies, and how the structure and accessibility limit the diversity of applications and user types. We make this information available in a code and data repository at: https://github.com/lozuponelab/knowledge-source-mappings. Addressing these challenges will allow for the development of more effective tools for drawing from abundant knowledge to find new insights into microbial mechanisms in disease by fostering a systematic and unbiased exploration of existing information.

SCNIC: Sparse correlation network investigation for compositional data.

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.

Environmental and ecological factors that shape the gut bacterial communities of fish: a meta-analysis.

Symbiotic bacteria often help their hosts acquire nutrients from their diet, showing trends of co-evolution and independent acquisition by hosts from the same trophic levels. While these trends hint at important roles for biotic factors, the effects of the abiotic environment on symbiotic community composition remain comparably understudied. In this investigation, we examined the influence of abiotic and biotic factors on the gut bacterial communities of fish from different taxa, trophic levels and habitats. Phylogenetic and statistical analyses of 25 16S rRNA libraries revealed that salinity, trophic level and possibly host phylogeny shape the composition of fish gut bacteria. When analysed alongside bacterial communities from other environments, fish gut communities typically clustered with gut communities from mammals and insects. Similar consideration of individual phylotypes (vs. communities) revealed evolutionary ties between fish gut microbes and symbionts of animals, as many of the bacteria from the guts of herbivorous fish were closely related to those from mammals. Our results indicate that fish harbour more specialized gut communities than previously recognized. They also highlight a trend of convergent acquisition of similar bacterial communities by fish and mammals, raising the possibility that fish were the first to evolve symbioses resembling those found among extant gut fermenting mammals.