Most of nature s biodiversity, and many potentially useful metabolic capabilities, remain hidden among the vast numbers of uncharacterized environmental microbes. Because cultivation is still not possible for most of these microbes, cultivation-independent molecular techniques such as polymerase chain reaction (PCR), fluorescent in situ hybridization (FISH), or shotgun DNA sequencing have been used in order to study their function and ecology in their natural habitats. However, none of the above techniques have so far been sufficient for any systematic assignment of molecular functions to distinct microbial lineages. Thus, most of the molecular ecology of natural microbes remains elusive. Here, we propose a computational meta-analysis and synthesis of existing and newly generated molecular sequence data sampled directly from the environment combining DNA sequencing data (metagenomics), and proteome expression data (metaproteomics). This analysis will be coupled to computational modelling of genome content evolution at the community level. We will aim to assess how gene repertoires of microbial communities, and their taxonomic compositions, change across distinct environments, in response to changed conditions, and through time. We plan to address fundamental questions in microbial ecology, including the extent of cooperation among members of the communities, stability of community composition at evolutionary timescales, the importance of lateral gene transfers, the extent of functional adaptation/regulation in situ, and whether gene occurrence and expression patterns are diagnostic of community functions and ecological status.
Field of science
- /natural sciences/biological sciences/ecology
- /medical and health sciences/medical biotechnology/genetic engineering/gene therapy
- /natural sciences/biological sciences/genetics and heredity/genome
- /natural sciences/biological sciences/biochemistry/biomolecules/proteins/proteomics
Call for proposal
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