Compositional descriptors for large scale comparative metagenome analysis

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Metagenomics together with metatranscriptomics provides an essential tool for the investigation of the phylogenetic distribution, the functional potential and the metabolic activity of microbial communities under natural conditions. Currently, rapid progress in sequencing technologies dramatically improves the basis for metagenomic studies. The growing amount and the heterogeneity of sequence material, however, implies a big challenge for bioinformatics. The goal of this project is to realize a bioinformatics framework for comparative metagenome and metatranscriptome analysis which is based on statistical descriptors derived from the protein domain distribution of a sample. These descriptors will be designed to provide a high degree of invariance across different sequencing platforms and a highly informative view on the phylogenetic and functional composition of microbial communities. A probabilistic mixture modelling approach will be utilized to achieve cross-platform comparability of taxonomic and functional descriptors. With the inclusion of an ultra-fast method for identification of protein domains, developed by the applicant, the approach will readily be applicable to metagenomic projects of any size, and the results will even be reproducible by small labs and institutions which do not possess extensive computational facilities. For evaluation of the approach strong collaboration partners from the field of marine microbiology will be involved to test the methodology under real world conditions providing valuable feedback for refinement of the methods.