engleski

Translational optimization and functional adaptation across microbial communities

Objectives: Track functional adaptation of genes across microbial communities through codon usage mediated translational optimization of expression. Methods: Computational analysis of translational optimization and codon adaptation in metagenome datasets from 8 distinct environments – marine, whale carcass, farm soil, phosphorous removal sludge, acid mine drainage, human, lean and obese mouse gut microbiomes. We define the metagenome- wide gene expressivity prediction measure that reflects the extent of translational optimization. Results: We show that all microbial species in a metagenome, regardless of their phylogenetic distribution, share similar codon usage bias in genes optimized at the translational level, specifically ribosomal protein genes and genes required for adaptation to specific environments. We have confirmed our findings by examining strains of cosmopolitan bacteria populating various habitats but exhibiting environment- specific codon usage bias and functional adaptation. Selection of expressivity prediction: The human gut metagenome shows high expressivity in genes for energy harvest, corroborated with the recent finding from the corresponding metaproteome. Comparison of the expressivity of genes in the lean human and mouse gut shows similar profiles stressing the importance of environmental conditions, and not phylogenetic distribution or physical location, on functional adaptation. However, the obese mouse gut lacks optimization of energy harvest genes, thus implicating microbial gene expression in development of obesity. Conclusions: We demonstrate that, in respect to codon usage and translational optimization, microbial communities indeed behave as meta-genomes and exhibit constrains to codon usage similar to single bacterial genomes. This enables us to follow functional adaptation of complete microbial communities to diverse environments using only metagenomic sequences.

metagenomics; codon usage; translational optimization

nije evidentirano