Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pcbi.0030005
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dc.titleProtein and DNA sequence determinants of thermophilic adaptation
dc.contributor.authorZeldovich K.B.
dc.contributor.authorBerezovsky I.N.
dc.contributor.authorShakhnovich E.I.
dc.date.accessioned2019-11-08T06:40:14Z
dc.date.available2019-11-08T06:40:14Z
dc.date.issued2007
dc.identifier.citationZeldovich K.B., Berezovsky I.N., Shakhnovich E.I. (2007). Protein and DNA sequence determinants of thermophilic adaptation. PLoS Computational Biology 3 (1) : 62-72. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pcbi.0030005
dc.identifier.issn1553734X
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/161871
dc.description.abstractThere 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. ? 2007 Zeldovich et al.
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceUnpaywall 20191101
dc.subjectarginine
dc.subjectglutamine
dc.subjectisoleucine
dc.subjectleucine
dc.subjectmembrane protein
dc.subjectproteome
dc.subjecttyrosine
dc.subjectvaline
dc.subjectbacterial protein
dc.subjectDNA
dc.subjectproteome
dc.subjectarticle
dc.subjectcontrolled study
dc.subjectDNA determination
dc.subjectDNA sequence
dc.subjectgenome analysis
dc.subjectnonhuman
dc.subjectprokaryote
dc.subjectprotein analysis
dc.subjectprotein folding
dc.subjecttemperature acclimatization
dc.subjectthermophile
dc.subjectadaptation
dc.subjectamino acid sequence
dc.subjectarchaeon
dc.subjectchemistry
dc.subjectchromosome map
dc.subjectDNA sequence
dc.subjectgenetics
dc.subjectmolecular evolution
dc.subjectmolecular genetics
dc.subjectnucleotide sequence
dc.subjectsequence analysis
dc.subjectsequence homology
dc.subjecttemperature
dc.subjectProkaryota
dc.subjectAdaptation, Physiological
dc.subjectAmino Acid Sequence
dc.subjectArchaea
dc.subjectBacterial Proteins
dc.subjectChromosome Mapping
dc.subjectConserved Sequence
dc.subjectDNA
dc.subjectEvolution, Molecular
dc.subjectMolecular Sequence Data
dc.subjectProteome
dc.subjectSequence Analysis, DNA
dc.subjectSequence Analysis, Protein
dc.subjectSequence Homology
dc.subjectTemperature
dc.typeArticle
dc.contributor.departmentBIOLOGICAL SCIENCES
dc.description.doi10.1371/journal.pcbi.0030005
dc.description.sourcetitlePLoS Computational Biology
dc.description.volume3
dc.description.issue1
dc.description.page62-72
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