In metagenomics the microbial genomes are studied directly in their natural habitats, which obviates the need of isolation and cultivation of individual species. In this study, we will use metagenomics techniques in the analysis of microbiota from the human gut. Crohn's disease is a chronic inflammatory disease of the digestive tract affecting about a million individuals worldwide. The incidence of Crohn's disease has increased during the past decades, however, the cause of the disease remains unknown. The amount of data created by this study is immense and effective computational approaches are needed for analysis. Especially the function prediction of novel proteins is of great importance, since sequences without molecular function annotation are of limited use to us. Automated phylogenomics is one of the most promising ways of having consistent reliable protein annotations that is applicable on a large scale and particularly for metagenomics information. SIFTER, a prototype tool for automated phylogenomic protein function prediction, has been shown to annotate ten times more proteins on tested protein families compared with the traditional method, BLAST. In this study, unique aspects of the metabolic and signaling capacities of microbiota from the inflamed gut of Crohn's patients versus undiseased tissue will be analyzed, with an ultimate long-term goal of understanding how microbial communities contribute to Crohn's disease and how treatment may be improved. To reach this goal, the SIFTER protein function prediction method will be refined to work on metagenomic data. SIFTER will then be applied to analyze sequences sampled from diseased and healthy intestinal tissue. The work of this proposal will be performed in two very high-quality host organizations in Berkeley, USA and in Cambridge, UK. Furthermore, the successful completion of the proposed project would significantly increase the European competitiveness in the fields of metagenomics and phylogenomics.
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