Amino acid usage is asymmetrically biased in AT- and GC-rich microbial genomes

PLoS One. 2013 Jul 26;8(7):e69878. doi: 10.1371/journal.pone.0069878. Print 2013.

Abstract

Introduction: Genomic base composition ranges from less than 25% AT to more than 85% AT in prokaryotes. Since only a small fraction of prokaryotic genomes is not protein coding even a minor change in genomic base composition will induce profound protein changes. We examined how amino acid and codon frequencies were distributed in over 2000 microbial genomes and how these distributions were affected by base compositional changes. In addition, we wanted to know how genome-wide amino acid usage was biased in the different genomes and how changes to base composition and mutations affected this bias. To carry this out, we used a Generalized Additive Mixed-effects Model (GAMM) to explore non-linear associations and strong data dependences in closely related microbes; principal component analysis (PCA) was used to examine genomic amino acid- and codon frequencies, while the concept of relative entropy was used to analyze genomic mutation rates.

Results: We found that genomic amino acid frequencies carried a stronger phylogenetic signal than codon frequencies, but that this signal was weak compared to that of genomic %AT. Further, in contrast to codon usage bias (CUB), amino acid usage bias (AAUB) was differently distributed in AT- and GC-rich genomes in the sense that AT-rich genomes did not prefer specific amino acids over others to the same extent as GC-rich genomes. AAUB was also associated with relative entropy; genomes with low AAUB contained more random mutations as a consequence of relaxed purifying selection than genomes with higher AAUB.

Conclusion: Genomic base composition has a substantial effect on both amino acid- and codon frequencies in bacterial genomes. While phylogeny influenced amino acid usage more in GC-rich genomes, AT-content was driving amino acid usage in AT-rich genomes. We found the GAMM model to be an excellent tool to analyze the genomic data used in this study.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Amino Acids / genetics*
  • Base Composition / genetics*
  • Bias
  • Codon / genetics
  • Entropy
  • Genome, Microbial / genetics*
  • Models, Genetic
  • Mutation / genetics
  • Principal Component Analysis
  • Prokaryotic Cells / metabolism
  • Regression Analysis

Substances

  • Amino Acids
  • Codon

Grant support

Jon Bohlin, Ola Brynildsrud and Eystein Skjerve were all funded by the Department of Food Safety, Norwegian School of Veterinary Science. Tammi Vesth and David Ussery were founded by Centre for Biological Sequence Analysis, Technical University of Denmark. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.