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Zawartość zarchiwizowana w dniu 2024-05-27

Uncultivated Microbes In Situ - a Computational Biology Approach to Determine Molecular Capabilities and Ecological Roles

Final Report Summary - UMICIS (Uncultivated Microbes In Situ - a Computational Biology Approach to Determine Molecular Capabilities and Ecological Roles)

The ERC-funded project "UMICIS" (Uncultivated Microbes In Situ), in the lab of Prof. Christian von Mering at University of Zurich, has undertaken a global meta-analysis of published DNA sequence data of microbial communities in their natural environments.
For this project, the lab has re-processed and re-analysed DNA sequencing data from thousands of previously published experiments, for which researchers had sequenced the genomic DNA of Bacteria and Archaea directly from the environment. This type of analysis by-passes the need for the microbes to grow in the laboratory, and hence delivers a uniquely unbiased and comprehensive catalog of microbial identities and their genomic toolkits. The lab has clustered the sequences, identified gene families of interest and tracked these gene families across diverse environments, producing one of the largest annotated collection of environmental sequence datasets worldwide. From the gene families, suitable subsets were identified for a number of important analysis tasks: taxonomic and phylogenetic groupings of microbes into "species" (or rather, "operational taxonomic units"), and functional analysis of microbial communities in human-associated contexts (oral cavity, respiratory tract). The analysis of the sequences has shown that microbes are not distributed randomly across environments, but that most of them have specific habitat preferences (i.e. they occur primarily in specific types of environments, from which they disperse to others). Furthermore, the sorting of environmental microbes into "species" was shown to be non-trivial: a number of previously proposed approaches for this task proved to give inconsistent results when compared to each other. The project also generated sequencing data of its own: from ancient human skeletons (DNA in dental plaque) and from contemporary infections in the lung of Cystic Fibrosis patients. In both cases, functional analysis revealed pathogens, and suggested the extent to which these might be resistant to antibiotics. Overall, the classifications and the insights glanced from the project will be used to better understand the contributions of microbial communities to ecosystem function, biotechnology and human health.