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
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 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.
The Tübiom project is a community-based project aimed at constructing a large, representative reference database of human gut microbiome profiles. The goal is to collect 10 000 profiles, along with detailed metadata on each participants health and lifestyle. All samples will be processed using identical sequencing and analysis protocols to ensure comparability. The project has four technical components: sequencing, sequence analysis, data storage and visualization. The project website http://www.tuebiom.de allows interested people to learn about the project, order a sampling kit and fill-in the metadata questionnaire. Once a sample as been submitted and processed, a participant can explore the taxonomic profile of their gut microbiome and compare it to the typical profile of different comparison groups.This community-based project also hopes to engage participants in science-propagation, spread knowledge about the gut microbiome and the importance of this area of research. Here we provide a brief introduction to the Tübiom project and describe the bioinformatics framework that we have developed for it.
The Tübiom project is a community-based project aimed at constructing a large, representative reference database of human gut microbiome profiles. The goal is to collect 10 000 profiles, along with detailed metadata on each participants health and lifestyle. All samples will be processed using identical sequencing and analysis protocols to ensure comparability. The project has four technical components: sequencing, sequence analysis, data storage and visualization. The project website http://www.tuebiom.de allows interested people to learn about the project, order a sampling kit and fill-in the metadata questionnaire. Once a sample as been submitted and processed, a participant can explore the taxonomic profile of their gut microbiome and compare it to the typical profile of different comparison groups.This community-based project also hopes to engage participants in science-propagation, spread knowledge about the gut microbiome and the importance of this area of research. Here we provide a brief introduction to the Tübiom project and describe the bioinformatics framework that we have developed for it.
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