"Sequence based growth rate prediction in Bacteria and Archaea" - Sara VIEIRA-SILVA et Eduardo P.C. ROCHA
Un séminaire organisé par Genoscope/CEA aura lieu le :
Mardi 28 avril 2009
11 H 00
Salle F. Jacob - RDC - Bât. G1
Titre du séminaire :
"Sequence based growth rate prediction in Bacteria and Archaea"
Bacterial species have evolved a multitude of different strategies to
cope with even the most extreme environments. Although these strategies can be very complex, bacteria have been typically categorized according to their minimal doubling time, which range from less than 10 min to more than 10 days. In stable, toxic or low-resource environments, very fast growth is impossible or selected against. However, where resources are sporadically abundant, high growth rates may be advantageous to compete for nutrient and space, because they allow a quick response to favorable conditions. In bacterial genomes, adaptation to rapid growth leads to selective patterns of gene organization and composition. Bacteria's growth rates heavily depend on their capacity to optimize the transcription and translation machineries. Firstly, the number of genes coding for tRNAs and rRNAs is positively correlated with the growth rate, allowing for very high transcription rates. Secondly, in fast-growing bacteria the genes coding for the translation and transcription machineries are close to the origin of replication. This leads to a replication-associated gene dosage effect at the time of replication. Thirdly, the translation machinery is optimized through the co-evolution of codon usage bias (CUB) and tRNA content: highly expressed genes select for "optimal" codons and even more so in fast growing bacteria.
We are currently working on a dataset of 214 genomes of bacteria and archaea for which published maximal growth rates were available. The number of transcription/translation machinery genes, their position on the chromosome, and indices of CUB were calculated and correlated to the growth rates. CUB indices are the most highly correlated with growth rate. Nonetheless, all of these variables are highly correlated which suggests a common selective pressure. We also found a strong association between deviations from the general patterns and exploitation of extreme habitats.
We then selected the predictor variables that did not require the knowledge of a complete genome and built a growth rate predictor to be used on non-assembled genomes or subsets of genes. Subsequently, we used it to analyze growth rate trends in 3 metagenomic datasets. Our results are coherent with expectations given the stability and richness of these habitats. Our results show that inference of growth phenotypes is possible from genome sequence alone, with obvious consequences for the understanding of bacterial ecology and eventual manipulation. They also suggest that such information can be used to enlighten the most frequent resource exploitation strategies in complex environments.
Présenté par : Sara VIEIRA-SILVA et Eduardo P.C. ROCHA
Atelier de Bioinformatique, Université Pierre et Marie Curie- Paris 6
et Microbial Evolutionary Genomics Group, Institut Pasteur
Invités par Thomas BRULS, Genoscope.