Amino acid variation in cellular processes in 108 bacterial proteomes

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

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.

Comparative analysis of essential genes and nonessential genes in Escherichia coli K12

Genes can be classified as essential or nonessential based on their indispensability for a living organism. Previous researches have suggested that essential genes evolve more slowly than nonessential genes and the impact of gene dispensability on a gene's evolutionary rate is not as strong as expected. However, findings have not been consistent and evidence is controversial regarding the relationship between the gene indispensability and the rate of gene evolution. Understanding how different classes of genes evolve is essential for a full understanding of evolutionary biology, and may have medical relevance in the design of new antibacterial agents. We therefore performed an investigation into the properties of essential and nonessential genes. Analysis of evolutionary conservation, protein length distribution and amino acid usage between essential and nonessential genes in Escherichia coli K12 demonstrated that essential genes are relatively preserved throughout the bacterial kingdom when compared to nonessential genes. Furthermore, results show that essential genes, compared to nonessential genes, have a significantly higher proportion of large (>534 amino acids) and small proteins (<139 amino acids) relative to medium-sized proteins. The pattern of amino acids usage shows a similar trend for essential and nonessential genes, although some notable exceptions are observed. These findings help to clarify our understanding of the evolutionary mechanisms of essential and nonessential genes, relevant to the study of mutagenesis and possibly allowing prediction of gene properties in other poorly understood organisms.

Static light scattering study of complex formation between protein and neutral water-soluble polymer

Complex formation of poly(N-isopropylacrylamide) (PNIPA) having a weight-average molecular weight of 1,720,000g/mol with human serum albumin (HSA), ovalbumin (OVA) and lysozyme (LYZ) was studied in an aqueous medium containing 0.01 M NaCl and adjusted to pH 3. The polymer-protein mixtures at different molar ratios (r(m)) were examined by static light scattering (SLS). The analysis of SLS data using our own approach [Kokufuta et al., Langmuir 15 (1999) 940; Biomacromolecules 4 (2003) 728] showed that the molecular weight of each resulting complex is smaller than that of the interpolymer complex composed of two polymer chains plus one protein. This indicates the formation of an intrapolymer complex in all the polymer-protein systems studied. Thus, at each r(m) we calculated the number of bound proteins per polymer, the value of which was OVA>HSA>LYZ in order. These results were compared with the hydropathy profiles of each protein which are a good tool for obtaining an information about distribution of hydrophobic and hydrophilic segments in a protein. It has become apparent that the hydrophobic interaction between polymer and protein plays an important role in the intrapolymer complex formation.