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      Protein and DNA Sequence Determinants of Thermophilic Adaptation

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          Abstract

          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. However, despite accumulation of anecdotal evidence, an exact and conclusive relationship between the former and the latter has been elusive. 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. Based on 204 complete proteomes of archaea and bacteria spanning the temperature range from −10 °C to 110 °C, 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. The universal set is Ile, Val, Tyr, Trp, Arg, Glu, Leu (IVYWREL), and the correlation coefficient is as high as 0.93. We also found that the G + C content in 204 complete genomes does not exhibit a significant correlation with OGT (R = −0.10). 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. 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. This adaptation is achieved via codon bias. These findings present a direct link between principles of proteins structure and stability and evolutionary mechanisms of thermophylic adaptation. On the nucleotide level, the analysis provides an example of how nature utilizes codon bias for evolutionary adaptation to extreme conditions. Together these results provide a complete picture of how compositions of proteomes and genomes in prokaryotes adjust to the extreme conditions of the environment.

          Author Summary

          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. 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. 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. We discovered that total concentration of seven amino acids in proteomes—IVYWREL—serves as a universal proteomic predictor of OGT in prokaryotes. 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. 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. Together these results provide a complete picture of proteomic and genomic determinants of thermophilic adaptation.

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          Most cited references37

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          Base-stacking and base-pairing contributions into thermal stability of the DNA double helix

          Two factors are mainly responsible for the stability of the DNA double helix: base pairing between complementary strands and stacking between adjacent bases. By studying DNA molecules with solitary nicks and gaps we measure temperature and salt dependence of the stacking free energy of the DNA double helix. For the first time, DNA stacking parameters are obtained directly (without extrapolation) for temperatures from below room temperature to close to melting temperature. We also obtain DNA stacking parameters for different salt concentrations ranging from 15 to 100 mM Na+. From stacking parameters of individual contacts, we calculate base-stacking contribution to the stability of A•T- and G•C-containing DNA polymers. We find that temperature and salt dependences of the stacking term fully determine the temperature and the salt dependence of DNA stability parameters. For all temperatures and salt concentrations employed in present study, base-stacking is the main stabilizing factor in the DNA double helix. A•T pairing is always destabilizing and G•C pairing contributes almost no stabilization. Base-stacking interaction dominates not only in the duplex overall stability but also significantly contributes into the dependence of the duplex stability on its sequence.
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            Partition of tRNA synthetases into two classes based on mutually exclusive sets of sequence motifs.

            The aminoacyl-transfer RNA synthetases (aaRS) catalyse the attachment of an amino acid to its cognate transfer RNA molecule in a highly specific two-step reaction. These proteins differ widely in size and oligomeric state, and have limited sequence homology. Out of the 18 known aaRS, only 9 referred to as class I synthetases (GlnRS, TyrRS, MetRS, GluRS, ArgRS, ValRS, IleRS, LeuRS, TrpRS), display two short common consensus sequences ('HIGH' and 'KMSKS') which indicate, as observed in three crystal structures, the presence of a structural domain (the Rossman fold) that binds ATP. We report here the sequence of Escherichia coli ProRS, a dimer of relative molecular mass 127,402, which is homologous to both ThrRS and SerRS. These three latter aaRS share three new sequence motifs with AspRS, AsnRS, LysRS, HisRS and the beta subunit of PheRS. These three motifs (motifs 1, 2 and 3), in a search through the entire data bank, proved to be specific for this set of aaRS (referred to as class II). Class II may also contain AlaRS and GlyRS, because these sequences have a typical motif 3. Surprisingly, this partition of aaRS in two classes is found to be strongly correlated on the functional level with the acylation occurring either on the 2' OH (class I) or 3' OH (class II) of the ribose of the last nucleotide of tRNA.
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              Proteins with selected sequences fold into unique native conformation.

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                pcbi
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                1553-734X
                1553-7358
                January 2007
                12 January 2007
                30 November 2006
                : 3
                : 1
                : e5
                Affiliations
                [1]Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America
                University of California San Diego, United States of America
                Author notes
                * To whom correspondence should be addressed. E-mail: eugene@ 123456belok.harvard.edu
                Article
                06-PLCB-RA-0266R2 plcb-03-01-06
                10.1371/journal.pcbi.0030005
                1769408
                17222055
                d3e31737-a7ea-4afc-b127-ef497cab50f4
                Copyright: © 2007 Zeldovich et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 5 July 2006
                : 29 November 2006
                Page count
                Pages: 11
                Categories
                Research Article
                Computational Biology
                Computational Biology
                Evolutionary Biology
                Molecular Biology
                Prokaryotes
                Custom metadata
                Zeldovich KB, Berezovsky IN, Shakhnovich EI (2007) Protein and DNA Sequence Determinants of Thermophilic Adaptation. PLoS Comput Biol 3(1): e5. doi: 10.1371/journal.pcbi.0030005

                Quantitative & Systems biology
                Quantitative & Systems biology

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