BackgroundThe role of the microbiota in human health and disease has been increasingly studied, gathering momentum through the use of high-throughput technologies. Further identification of the roles of specific microbes is necessary to better understand the mechanisms involved in diseases related to microbiome perturbations. MethodsHere, we introduce a new microbiome-based group association testing method, optimal microbiome-based association test (OMiAT). OMiAT is a data-driven testing method which takes an optimal test throughout different tests from the sum of powered score tests (SPU) and microbiome regression-based kernel association test (MiRKAT). We illustrate that OMiAT efficiently discovers significant association signals arising from varying microbial abundances and different relative contributions from microbial abundance and phylogenetic information. We also propose a way to apply it to fine-mapping of diverse upper-level taxa at different taxonomic ranks (e.g., phylum, class, order, family, and genus), as well as the entire microbial community, within a newly introduced microbial taxa discovery framework, microbiome comprehensive association mapping (MiCAM).ResultsOur extensive simulations demonstrate that OMiAT is highly robust and powerful compared with other existing methods, while correctly controlling type I error rates. Our real data analyses also confirm that MiCAM is especially efficient for the assessment of upper-level taxa by integrating OMiAT as a group analytic method.ConclusionsOMiAT is attractive in practice due to the high complexity of microbiome data and the unknown true nature of the state. MiCAM also provides a hierarchical association map for numerous microbial taxa and can also be used as a guideline for further investigation on the roles of discovered taxa in human health and disease.Electronic supplementary materialThe online version of this article (doi:10.1186/s40168-017-0262-x) contains supplementary material, which is available to authorized users.

Epitheliotropic intestinal T-cell lymphoma (EITL, also known as type II enteropathy-associated T-cell lymphoma) is an aggressive intestinal disease with poor prognosis and its molecular alterations have not been comprehensively characterized. We aimed to identify actionable easy-to-screen alterations that would allow better diagnostics and/or treatment of this deadly disease. By performing whole-exome sequencing of four EITL tumor-normal pairs, followed by amplicon deep sequencing of 42 tumor samples, frequent alterations of the JAK-STAT and G-protein-coupled receptor (GPCR) signaling pathways were discovered in a large portion of samples. Specifically, STAT5B was mutated in a remarkable 63% of cases, JAK3 in 35% and GNAI2 in 24%, with the majority occurring at known activating hotspots in key functional domains. Moreover, STAT5B locus carried copy-neutral loss of heterozygosity resulting in the duplication of the mutant copy, suggesting the importance of mutant STAT5B dosage for the development of EITL. Dysregulation of the JAK-STAT and GPCR pathways was also supported by gene expression profiling and further verified in patient tumor samples. In vitro overexpression of GNAI2 mutants led to the upregulation of pERK1/2, a member of MEK-ERK pathway. Notably, inhibitors of both JAK-STAT and MEK-ERK pathways effectively reduced viability of patient-derived primary EITL cells, indicating potential therapeutic strategies for this neoplasm with no effective treatment currently available.

The early-life intestinal microbiota plays a key role in shaping host immune system development. We found that a single early-life antibiotic course (1PAT) accelerated type 1 diabetes (T1D) development in male NOD mice. The single course had deep and persistent effects on the intestinal microbiome, leading to altered cecal, hepatic, and serum metabolites. The exposure elicited sex-specific effects on chromatin states in the ileum and liver and perturbed ileal gene expression, altering normal maturational patterns. The global signature changes included specific genes controlling both innate and adaptive immunity. Microbiome analysis revealed four taxa each that potentially protect against or accelerate T1D onset, that were linked in a network model to specific differences in ileal gene expression. This simplified animal model reveals multiple potential pathways to understand pathogenesis by which early-life gut microbiome perturbations alter a global suite of intestinal responses, contributing to the accelerated and enhanced T1D development.

highly effective therapeutic agent to prevent both h-IAPP toxicity and amyloid formation in vivo. These findings highlight RAGE as a therapeutic target for β cell preservation in metabolic disease and provide critical information for the design of inhibitors of h-IAPP/RAGE interactions.

Background: Increasing evidence shows the importance of the commensal microbe Oxalobacter formigenes in regulating host oxalate homeostasis, with effects against calcium oxalate kidney stone formation, and other oxalateassociated pathological conditions. However, limited understanding of O. formigenes in humans poses difficulties for designing targeted experiments to assess its definitive effects and sustainable interventions in clinical settings. We exploited the large-scale dataset from the American Gut Project (AGP) to study O. formigenes colonization in the human gastrointestinal (GI) tract and to explore O. formigenes-associated ecology and the underlying host-microbe relationships. Results: In >8000 AGP samples, we detected two dominant, co-colonizing O. formigenes operational taxonomic units (OTUs) in fecal specimens. Multivariate analysis suggested that O. formigenes abundance was associated with particular host demographic and clinical features, including age, sex, race, geographical location, BMI, and antibiotic history. Furthermore, we found that O. formigenes presence was an indicator of altered host gut microbiota structure, including higher community diversity, global network connectivity, and stronger resilience to simulated disturbances. Conclusions: Through this study, we identified O. formigenes colonizing patterns in the human GI tract, potential underlying host-microbe relationships, and associated microbial community structures. These insights suggest hypotheses to be tested in future experiments. Additionally, we proposed a systematic framework to study any bacterial taxa of interest to computational biologists, using large-scale public data to yield novel biological insights.