![]() The most pronounced ones are in elevated fractions of charged residues, and/or increased amounts of hydrophobic residues in (hyper)thermophilic organisms as compared with mesophilic ones. Indeed, it is well-known that enhanced thermostability is reflected in specific trends in amino acid composition. Various mechanisms of thermostability were discussed in the literature, and many authors pointed to changes in amino acid composition as one of the clearest manifestations of thermal adaptation. Given the limited alphabet of amino acid residues, an apparent way to control protein stability is to properly choose the fractions of different residue types and then to arrange them in sequences that fold into stable and unique native structures at physiological conditions of a given organism. Together these results provide a complete picture of proteomic and genomic determinants of thermophilic adaptation.Īs proteins and nucleic acids must remain in their native conformations at physiologically relevant temperatures, thermal adaptation requires adjustment of interactions within these biopolymers. However, the frequency with which A and G nucleotides appear as nearest neighbors in genome sequences is strongly and independently correlated with OGT as a result of codon bias in corresponding genomes. Resolving the old-standing controversy, we determined that the variation in nucleotide composition (increase of purine load, or A + G content with temperature) is largely a consequence of thermal adaptation of proteins. We discovered that total concentration of seven amino acids in proteomes-IVYWREL-serves as a universal proteomic predictor of OGT in prokaryotes. ![]() Here we performed a comprehensive analysis of amino acid and nucleotide compositional signatures of thermophylic adaptation by exhaustively evaluating all combinations of amino acids and nucleotides as possible determinants of OGT for all prokaryotic organisms with fully sequenced genomes. However, despite significant efforts, the definitive answer of what are the genomic and proteomic compositional determinants of optimal growth temperature (OGT) of prokaryotic organisms remained elusive. Prokaryotes living at extreme environmental temperatures exhibit pronounced signatures in the amino acid composition of their proteins and the nucleotide compositions of their genomes, reflective of adaptation to their thermal environments. Together these results provide a complete picture of how compositions of proteomes and genomes in prokaryotes adjust to the extreme conditions of the environment. On the nucleotide level, the analysis provides an example of how nature utilizes codon bias for evolutionary adaptation to extreme conditions. These findings present a direct link between principles of proteins structure and stability and evolutionary mechanisms of thermophylic adaptation. This adaptation is achieved via codon bias. Further, we found strong and independent correlation between OGT and the frequency with which pairs of A and G nucleotides appear as nearest neighbors in genome sequences. On the other hand, the fraction of A + G in coding DNA is correlated with temperature, to a considerable extent, due to codon patterns of IVYWREL amino acids. We also found that the G + C content in 204 complete genomes does not exhibit a significant correlation with OGT (R = −0.10). The universal set is Ile, Val, Tyr, Trp, Arg, Glu, Leu (IVYWREL), and the correlation coefficient is as high as 0.93. Based on 204 complete proteomes of archaea and bacteria spanning the temperature range from −10 ☌ to 110 ☌, we performed an exhaustive enumeration of all possible sets of amino acids and found a set of amino acids whose total fraction in a proteome is correlated, to a remarkable extent, with the OGT. We present an exhaustive study of the relationship between amino acid composition of proteomes, nucleotide composition of DNA, and optimal growth temperature (OGT) of prokaryotes. However, despite accumulation of anecdotal evidence, an exact and conclusive relationship between the former and the latter has been elusive. There have been considerable attempts in the past to relate phenotypic trait-habitat temperature of organisms-to their genotypes, most importantly compositions of their genomes and proteomes.
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