Objective
The history of life is a subject that attracts the interest from both researchers and the society in general - it is in the human nature to wonder about our own history. Our only sources of information about microbial evolution reside in genomic data and geological records. Major advances in sequencing techniques are overwhelming databases with rich and novel insights into microbial taxonomic diversity, in particular about new uncultured lineages. Through metagenomics we now know that they are there but we still do not understand what they are doing.The key to that understanding is not genomics, it is physiology.Our main impediment to understand environmental microbial life is our lack of insights into the physiology of newly discovered lineages, how they harness and conserve energy.While phylogenetic trees based on universal genes can be generated for thousands of lineages at a time, they do not represent the genome as a whole and, most importantly, due to lateral gene transfer, branching patterns in the tree of life have never correlated well with key physiological traits.The goal of this proposal, whose focus is physiology, is to better understand how microbes harness energy from available environmental sources, how they learned to use new ones, and how this process unfolded during microbial evolution.This will involve i) large-scale comparative phylogenetic analysis of genes involved in and genomically associated with physiology combined with ii) experimental data, using as evolutionary constraints geochemical records of available environmental energy sources.With a top-down approach this work will successively eliminate among extant biological traits ones that cannot be ancient, constraining the physiological space of older microbial solutions.This proposal will lead to testable predictions regarding the order of events in evolutionary bioenergetic transitions, the focus on biological energy harnessing will narrow the gap between geochemistry and microbiology.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesearth and related environmental sciencesgeochemistry
- humanitieshistory and archaeologyhistory
- medical and health sciencesbasic medicinephysiology
- natural sciencesbiological sciencesgeneticsgenomes
- natural sciencesbiological sciencesmicrobiology
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Funding Scheme
ERC-STG - Starting GrantHost institution
1010 Wien
Austria