engleski

Codon usage at the level of microbial communities

I will present the computational analysis of genomic data from microbial community sequencing projects in terms of synonymous codon usage (CU). The main hypothesis is that microbial communities behave as meta-genomes, with concerted evolution and selection for similar codon usage patterns across the entire ecological niche. We have demonstrated that codon usage patterns are non-random in each metagenome data-set and that there is a pronounced and statistically significant bias in use of synonymous codons across each metagenome, moreover that different metagenomes show different CU bias. We have further explored the effect of microbial genomes optimizing codon usage for translational efficiency (by selecting for synonymous codons that match the tRNA abundance and contribute to mRNA stability) in order to predict the expressivity of functionally characterized genes and to rank the gene functions according to their predicted expressivity within the entire metagenome. This revealed the existence of metagenome-wide optimization for lifestyle-specific genes (e.g. Sargasso sea metagenome shows optimization for amino acid transport across the membrane while the whale carcass metagenome selects for energy conversion functions). Finally, we have demonstrated that metagenomes contain functional categories with highly conserved CU patterns (i.e. high CU bias) and we have determined that genes in these functional categories may be candidates for horizontal gene transfer.

microbial ecosystem; metagenomics; high-throughput genomics; computational biology

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