Loading
Alpha-cyanobacteria are the most abundant and ubiquitous photosynthetic prokaryotes in both marine and freshwater ecosystems. This ecological success as well as the numerous available strains, genomes and metagenomes make them highly pertinent models in microbial ecology, which can be studied at all organization scales from genes to ecosystems. Yet, their long evolutionary history, similar morphologies, high phenotypic plasticity and high degree of functional variation among closely related lineages, have so far made it difficult to classify them in a rigorous and consensual way, while a reliable systematics for this group is critical to unravel the links between phylogenetic diversification, differential functional capacities and colonization of specific environmental niches. Although several standardized classifications based on comparative genomics have recently been proposed for the whole Bacteria domain or more restricted phylogenetic groups, they all have largely ignored the wealth of experimental and in situ data available on alpha-cyanobacteria and therefore appear inappropriate to tackle these questions in this ecologically important group. In this context, the main objectives of the TaxCy project will be to : i) propose an integrative formulation of the species concept for alpha-cyanobacteria by combining the existent and newly generated data on phenotypes, genotypes and habitat, with a particular focus on both marine and freshwater uncultivated taxa that have been largely overlooked so far, ii) determine how the different genotypes differentiate functionally and ecologically from their close (intra-species variability) and more distant relatives (inter-species variability) and iii) describe and model environmental and metabolic niches to decipher the importance of particular reactions and pathways in the survival of the different species in their specific niches. In practice, starting from an initial set of candidate species selected by pre-screening the ca. 500 alpha-cyanobacteria strains of the Roscoff Culture Collection (RCC), the delineation of valid species will be done using an iterative, multi-step approach combining comparative physiology, comparative genomics and metagenomic analyses in order to identify strains that share a number of phenotypic, genotypic, functional and ecological characteristics, which differentiate them from all other species. To fill diversity gaps, the initial set of candidate species will be complemented by targeting specific aquatic environments for isolating new strains that will then be characterized using the same protocol. Each validated species will then be formally described according to the bacteriological code and type strains will be made axenic and deposited in the RCC and other collections. Based on this rigorous and reasoned taxonomy, complemented by the development, update or expansion of large, manually-curated open-access databases for inter-comparison of marker genes (CyanoMarks), genomes (Cyanorak) and traits (CyanoTraits), we will then i) unveil the functional specificities of each species potentially involved in their adaptation to these niches and ii) use the latest developments in genome-scale metabolic modeling to build realistic metabolic and ecological niche models for alpha-cyanobacteria species and higher taxonomic ranks. This will allow us not only to describe, but also predict their realized environmental niches, based on their within-species metabolic capacities as well as to assess the importance of specific metabolic pathways and/or of specific genomic regions on metabolic niches. The TaxCy project will therefore provide novel insights into the relationships between systematics, function and niche partitioning for key members of aquatic ecosystems and should give us a better appraisal of the ecosystemic services potentially offered by alpha-picocyanobacteria.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=anr_________::ded79e93b9709e185aed166cb7f0e413&type=result"></script>');
-->
</script>