A microbial signature for Crohn's disease.

OBJECTIVE: A decade of microbiome studies has linked IBD to an alteration in the gut microbial community of genetically predisposed subjects. However, existing profiles of gut microbiome dysbiosis in adult IBD patients are inconsistent among published studies, and did not allow the identification of microbial signatures for CD and UC. Here, we aimed to compare the faecal microbiome of CD with patients having UC and with non-IBD subjects in a longitudinal study. DESIGN: We analysed a cohort of 2045 non-IBD and IBD faecal samples from four countries (Spain, Belgium, the UK and Germany), applied a 16S rRNA sequencing approach and analysed a total dataset of 115 million sequences. RESULTS: In the Spanish cohort, dysbiosis was found significantly greater in patients with CD than with UC, as shown by a more reduced diversity, a less stable microbial community and eight microbial groups were proposed as a specific microbial signature for CD. Tested against the whole cohort, the signature achieved an overall sensitivity of 80% and a specificity of 94%, 94%, 89% and 91% for the detection of CD versus healthy controls, patients with anorexia, IBS and UC, respectively. CONCLUSIONS: Although UC and CD share many epidemiologic, immunologic, therapeutic and clinical features, our results showed that they are two distinct subtypes of IBD at the microbiome level. For the first time, we are proposing microbiomarkers to discriminate between CD and non-CD independently of geographical regions.

Altered host-gut microbes symbiosis in severely malnourished anorexia nervosa (AN) patients undergoing enteral nutrition: An explicative factor of functional intestinal disorders?

BACKGROUND: Functional intestinal disorders (FIDs) are frequently observed in patients with anorexia nervosa (AN). Relationship between FIDs and a potential gut microbiota dysbiosis has been poorly explored. OBJECTIVE: We aimed to determine an association between FIDs severity and dysbiosis of the intestinal microbiota in a severely malnourished patient population with AN undergoing enteral nutrition. DESIGN: Faecal microbiota of AN (DSM IVr criteria) female inpatients were collected and compared to healthy controls based on 16S rRNA profiling. The severity of FIDs was evaluated in patients and healthy controls using Francis Score. RESULTS: Thirty-three patients (BMI: 11,7 ± 1,5; Age: 32 ± 12) and 22 healthy controls (BMI: 21 ± 2; age: 36 ± 12) were included. A marked dysbiosis was identified in AN patients compared to healthy controls (p = 0.03). Some potentially pathogenic bacterial genera (Klebsiella, Salmonella) were more abundant in AN patients whereas, other bacterial symbionts (Eubacterium and Roseburia) involved in immune balance were significantly less abundant in patients than controls. Severity of FIDs was strongly correlated with several microbial genera (r = -0.581 for an unknown genus belonging to Peptostreptococcaceae family; r = 0.392 for Dialister, r = 0.444 for Robinsoniella and r = 0.488 for Enterococcus). Other associations between dysbiosis, clinical and biological characteristics were identified including severity of undernutrition (BMI). CONCLUSION: Observed gut microbiota dysbiosis in malnourished patients with anorexia nervosa is correlated with the severity of FIDs and other metabolic disturbances, which strongly suggests an altered host-microbe symbiosis.

MetaTrans: an open-source pipeline for metatranscriptomics.

To date, meta-omic approaches use high-throughput sequencing technologies, which produce a huge amount of data, thus challenging modern computers. Here we present MetaTrans, an efficient open-source pipeline to analyze the structure and functions of active microbial communities using the power of multi-threading computers. The pipeline is designed to perform two types of RNA-Seq analyses: taxonomic and gene expression. It performs quality-control assessment, rRNA removal, maps reads against functional databases and also handles differential gene expression analysis. Its efficacy was validated by analyzing data from synthetic mock communities, data from a previous study and data generated from twelve human fecal samples. Compared to an existing web application server, MetaTrans shows more efficiency in terms of runtime (around 2 hours per million of transcripts) and presents adapted tools to compare gene expression levels. It has been tested with a human gut microbiome database but also proposes an option to use a general database in order to analyze other ecosystems. For the installation and use of the pipeline, we provide a detailed guide at the following website (www.metatrans.org).