Most of our knowledge about the remarkable microbial diversity on Earth comes from sequencing the 16S rRNA gene. The use of next-generation sequencing methods has increased sample number and sequencing depth, but the read length of the most widely used sequencing platforms today is quite short, requiring the researcher to choose a subset of the gene to sequence (typically 16–33% of the total length). Thus, many bacteria may share the same amplified region, and the resolution of profiling is inherently limited. Platforms that offer ultra-long read lengths, whole genome shotgun sequencing approaches, and computational frameworks formerly suggested by us and by others all allow different ways to circumvent this problem yet suffer various shortcomings. There is a need for a simple and low-cost 16S rRNA gene-based profiling approach that harnesses the short read length to provide a much larger coverage of the gene to allow for high resolution, even in harsh conditions of low bacterial biomass and fragmented DNA. This manuscript suggests Short MUltiple Regions Framework (SMURF), a method to combine sequencing results from different PCR-amplified regions to provide one coherent profiling. The de facto amplicon length is the total length of all amplified regions, thus providing much higher resolution compared to current techniques. Computationally, the method solves a convex optimization problem that allows extremely fast reconstruction and requires only moderate memory. We demonstrate the increase in resolution by in silico simulations and by profiling two mock mixtures and real-world biological samples. Reanalyzing a mock mixture from the Human Microbiome Project achieved about twofold improvement in resolution when combing two independent regions. Using a custom set of six primer pairs spanning about 1200 bp (80%) of the 16S rRNA gene, we were able to achieve ~ 100-fold improvement in resolution compared to a single region, over a mock mixture of common human gut bacterial isolates. Finally, the profiling of a Drosophila melanogaster microbiome using the set of six primer pairs provided a ~ 100-fold increase in resolution and thus enabling efficient downstream analysis. SMURF enables the identification of near full-length 16S rRNA gene sequences in microbial communities, having resolution superior compared to current techniques. It may be applied to standard sample preparation protocols with very little modifications. SMURF also paves the way to high-resolution profiling of low-biomass and fragmented DNA, e.g., in the case of formalin-fixed and paraffin-embedded samples, fossil-derived DNA, or DNA exposed to other degrading conditions. The approach is not restricted to combining amplicons of the 16S rRNA gene and may be applied to any set of amplicons, e.g., in multilocus sequence typing (MLST).

The mammal gut microbiome, which includes host microbes and their respective genes, is now recognized as an essential second genome that provides critical functions to the host. In humans, studies have revealed that lifestyle strongly influences the composition and diversity of the gastrointestinal microbiome. We hypothesized that these trends in humans may be paralleled in mammals subjected to anthropogenic forces such as domestication and captivity, in which diets and natural life histories are often greatly modified. We investigated fecal microbiomes of Przewalski’s horse (PH; Equus ferus przewalskii), the only horses alive today not successfully domesticated by humans, and herded, domestic horse (E. f. caballus) living in adjacent natural grasslands. We discovered PH fecal microbiomes hosted a distinct and more diverse community of bacteria compared to domestic horses, which is likely partly explained by different plant diets as revealed by trnL maker data. Within the PH population, four individuals were born in captivity in European zoos and hosted a strikingly low diversity of fecal microbiota compared to individuals born in natural reserves in France and Mongolia. These results suggest that anthropogenic forces can dramatically reshape equid gastrointestinal microbiomes, which has broader implications for the conservation management of endangered mammals.

Celiac disease is provoked by gluten exposure, but the complete pathogenic process in the duodenum and the loss of tolerance to gluten is not well understood. We aimed to define the core celiac transcriptomic signature and pathologic pathways in pre-treatment formalin-fixed paraffin-embedded (FFPE) duodenum biopsies used for clinical diagnosis. We use mRNAseq to define pre-treatment diagnostic duodenum gene expression in 54 pediatric celiac patients and non-celiac controls, and we validate our key findings in two independent cohorts of 67 adults and pediatric participants that used fresh frozen biopsies. We further define similar and divergent genes and pathways in 177 small bowel Crohn disease patients and controls. We observe a marked suppression of mature epithelial metabolic functions in celiac patients, overlapping substantially with the Crohn disease signature. A marked adaptive immune response was noted for the up-regulated signature including interferon response, alpha-beta, and gamma-delta T-cells that overlapped to some extent with the Crohn disease signature. However, we also identified a celiac disease specific signature linked to increased cell proliferation, nuclear division, and cell cycle activity that was localized primarily to the epithelia as noted by CCNB1 and Ki67 staining. Lastly, we demonstrate the utility of the transcriptomic date to correctly classify disease or healthy states in the discovery and validation cohorts. Our data supplement recently published datasets providing insights into celiac pathogenesis using clinical pathology FFPE samples, and can stimulate new approaches to address this highly prevalent condition.

Background: Gut microbial alteration is implicated in inflammatory bowel disease but is noted in other diseases. Systematic comparison to define similarities and specificities is hampered since most studies focus on a single disease. Results: We develop a pipeline to compare between disease cohorts starting from the raw V4 16S amplicon sequence variants. Including 12,838 subjects, from 59 disease cohorts, we demonstrate a predominant shared signature across diseases, indicating a common bacterial response to different diseases. We show that classifiers trained on one disease cohort predict relatively well other diseases due to this shared signal, and hence, caution should be taken when using such classifiers in real-world scenarios, where diseases are intermixed. Based on this common signature across a large array of diseases, we develop a universal dysbiosis index that successfully differentiates between cases and controls across various diseases and can be used for prioritizing fecal donors and samples with lower disease probability. Finally, we identify a set of IBD-specific bacteria, which can direct mechanistic studies and design of IBD-specific microbial interventions. Conclusions: A robust non-specific general response of the gut microbiome is detected in a large array of diseases. Disease classifiers may confuse between different diseases due to this shared microbial response. Our universal dysbiosis index can be used as a tool to prioritize fecal samples and donors. Finally, the IBD-specific taxa may indicate a more direct association to gut inflammation and disease pathogenesis, and those can be further used as biomarkers and as future targets for interventions.

Crohn disease (CD) burden has increased with globalization/urbanization, and the rapid rise is attributed to environmental changes rather than genetic drift. The Study Of Urban and Rural CD Evolution (SOURCE, n = 380) has considered diet-omics domains simultaneously to detect complex interactions and identify potential beneficial and pathogenic factors linked with rural-urban transition and CD. We characterize exposures, diet, ileal transcriptomics, metabolomics, and microbiome in newly diagnosed CD patients and controls in rural and urban China and Israel. We show that time spent by rural residents in urban environments is linked with changes in gut microbial composition and metabolomics, which mirror those seen in CD. Ileal transcriptomics highlights personal metabolic and immune gene expression modules, that are directly linked to potential protective dietary exposures (coffee, manganese, vitamin D), fecal metabolites, and the microbiome. Bacteria-associated metabolites are primarily linked with host immune modules, whereas diet-linked metabolites are associated with host epithelial metabolic functions.

Ulcerative colitis (UC), Crohn’s disease (CD), and celiac disease are prevalent intestinal inflammatory disorders with nonsatisfactory therapeutic interventions. Analyzing patient data-driven cohorts can highlight disease pathways and new targets for interventions. Long noncoding RNAs (lncRNAs) are attractive candidates, since they are readily targetable by RNA therapeutics, show relative cell-specific expression, and play key cellular functions. Uniformly analyzing gut mucosal transcriptomics from 696 subjects, we have highlighted lncRNA expression along the gastrointestinal (GI) tract, demonstrating that, in control samples, lncRNAs have a more location-specific expression in comparison with protein-coding genes. We defined dysregulation of lncRNAs in treatment-naive UC, CD, and celiac diseases using independent test and validation cohorts. Using the Predicting Response to Standardized Pediatric Colitis Therapy (PROTECT) inception UC cohort, we defined and prioritized lncRNA linked with UC severity and prospective outcomes, and we highlighted lncRNAs linked with gut microbes previously implicated in mucosal homeostasis. HNF1A-AS1 lncRNA was reduced in all 3 conditions and was further reduced in more severe UC form. Similarly, the reduction of HNF1A-AS1 ortholog in mice gut epithelia showed higher sensitivity to dextran sodium sulfate–induced colitis, which was coupled with alteration in the gut microbial community. These analyses highlight prioritized dysregulated lncRNAs that can guide future preclinical studies for testing them as potential targets.