MEGAN Community Edition - Interactive Exploration and Analysis of Large-Scale Microbiome Sequencing Data.

There is increasing interest in employing shotgun sequencing, rather than amplicon sequencing, to analyze microbiome samples. Typical projects may involve hundreds of samples and billions of sequencing reads. The comparison of such samples against a protein reference database generates billions of alignments and the analysis of such data is computationally challenging. To address this, we have substantially rewritten and extended our widely-used microbiome analysis tool MEGAN so as to facilitate the interactive analysis of the taxonomic and functional content of very large microbiome datasets. Other new features include a functional classifier called InterPro2GO, gene-centric read assembly, principal coordinate analysis of taxonomy and function, and support for metadata. The new program is called MEGAN Community Edition (CE) and is open source. By integrating MEGAN CE with our high-throughput DNA-to-protein alignment tool DIAMOND and by providing a new program MeganServer that allows access to metagenome analysis files hosted on a server, we provide a straightforward, yet powerful and complete pipeline for the analysis of metagenome shotgun sequences. We illustrate how to perform a full-scale computational analysis of a metagenomic sequencing project, involving 12 samples and 800 million reads, in less than three days on a single server. All source code is available here: https://github.com/danielhuson/megan-ce.

Endotoxicity of lipopolysaccharide as a determinant of T-cell-mediated colitis induction in mice.

BACKGROUND & AIMS: The intestinal microbiota is an important determinant of the mucosal response. In patients with inflammatory bowel diseases, the mucosal immune system has inappropriate interactions with the intestinal microbiota. We investigated how the composition of the intestinal microbiota affects its endotoxicity and development of colitis in mice. METHODS: Germ-free C57BL/6J-Rag(1tm1Mom) (Rag1(-/-)) mice were colonized with 2 different types of complex intestinal microbiota. Colitis was induced in Rag1(-/-) mice by transfer of CD4(+)CD62L(+) T cells from C57BL/6J mice. Colonic tissues were collected and used for histologic analysis and cell isolation. Activation of lamina propria dendritic cells and T cells was analyzed by flow cytometry. RESULTS: After transfer of CD4(+)CD62L(+) T cells, mice with intestinal Endo(lo) microbiota (a low proportion of Enterobacteriaceae, high proportion of Bacteroidetes, and low endotoxicity) maintained mucosal immune homeostasis, and mice with highly endotoxic Endo(hi) microbiota (a high proportion of Enterobacteriaceae and low proportion of Bacteroidetes) developed colitis. To determine whether the effects of Endo(hi) microbiota were related to the higher endotoxic activity of lipopolysaccharide (LPS), we compared LPS from Enterobacteriaceae with that of Bacteroidetes. Administration of Escherichia coli JM83 (wild-type LPS) to the mice exacerbated colitis, and Escherichia coli JM83 + htrBPG (mutated LPS, with lower endotoxicity, similar to that of Bacteroidetes) prevented development of colitis after transfer of the T cells to mice. CONCLUSIONS: The endotoxicity of LPS produced by the intestinal microbiota is a determinant of whether mice develop colitis after transfer of CD4(+)CD62L(+) T cells. This finding might aid the design of novel biologics or probiotics to treat inflammatory bowel disease.

The Patient as Genomic Data Manager - Evaluation of the PROMISE App.

PROMISE (Personal Medical Safe) was a German research project which aimed to provide the responsibility of genomic data to the patient via a mobile app. The patient should accept or decline study requests to use his/her genomic data via the app. In the evaluation of the app the experiences with mobile health as well as the opinion on being the genomic data manager were measured. Furthermore, the test patients were asked about their opinion and their concerns on the PROMISE app. Most of the 19 test patients were aware of the high sensibility of genomic data and thought that the PROMISE app was a suitable solution. The largest part found it good that they were the responsible data owner. However, several participants also found it important to have a permanent contact person when it comes to questions on inquiries or the app.

TLR signaling-induced CD103-expressing cells protect against intestinal inflammation.

BACKGROUND: Toll-like receptor (TLR) expression in patients with inflammatory bowel disease is increased when compared with healthy controls. However, the impact of TLR signaling during inflammatory bowel disease is not fully understood. METHODS: In this study, we used a murine model of acute phase inflammation in bone marrow chimeric mice to investigate in which cell type TLR2/4 signal induction is important in preventing intestinal inflammation and how intestinal dendritic cells are influenced. Mice were either fed with wild-type bacteria, able to initiate the TLR2/4 signaling cascade, or with mutant strains with impaired signal induction capacity. RESULTS: The induction of the TLR2/4 signal cascade in epithelial cells resulted in inflammation in bone marrow chimeric mice, whereas induction in hematopoietic cells had an opposed function. Furthermore, feeding of wild-type bacteria prevented disease; however, differing signal induction of bacteria had no effect on lamina propria dendritic cell activation. In contrast, functional TLR2/4 signals resulted in increased frequencies of CD103-expressing lamina propria and mesenteric lymph node dendritic cells, which were able to ameliorate disease. CONCLUSIONS: The TLR-mediated amelioration of disease, the increase in CD103-expressing cells, and the beneficial function of TLR signal induction in hematopoietic cells indicate that the increased expression of TLRs in patients with inflammatory bowel disease might result in counterregulation of the host and serve in preventing disease.