Transcriptional abundance is not the single force driving the evolution of bacterial proteins

BMC Evolutionary Biology

Feng-Biao Guo¹  Zu-Jun Yang¹  Dan Lin¹  Tao Zhang¹  Wen Wei¹ 

[1] Center of Bioinformatics and Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, 610054 Chengdu, China

关键词: Transcriptional abundance;    Multiple features;    Bacteria;    Evolutionary rates;   

Others  :  1086710
DOI  :  10.1186/1471-2148-13-162

 received in 2013-03-19, accepted in 2013-08-01,  发布年份 2013

【 摘 要 】

Background

Despite rapid progress in understanding the mechanisms that shape the evolution of proteins, the relative importance of various factors remain to be elucidated. In this study, we have assessed the effects of 16 different biological features on the evolutionary rates (ERs) of protein-coding sequences in bacterial genomes.

Results

Our analysis of 18 bacterial species revealed new correlations between ERs and constraining factors. Previous studies have suggested that transcriptional abundance overwhelmingly constrains the evolution of yeast protein sequences. This transcriptional abundance leads to selection against misfolding or misinteractions. In this study we found that there was no single factor in determining the evolution of bacterial proteins. Not only transcriptional abundance (codon adaptation index and expression level), but also protein-protein associations (PPAs), essentiality (ESS), subcellular localization of cytoplasmic membrane (SLM), transmembrane helices (TMH) and hydropathicity score (HS) independently and significantly affected the ERs of bacterial proteins. In some species, PPA and ESS demonstrate higher correlations with ER than transcriptional abundance.

Conclusions

Different forces drive the evolution of protein sequences in yeast and bacteria. In bacteria, the constraints are involved in avoiding a build-up of toxic molecules caused by misfolding/misinteraction (transcriptional abundance), while retaining important functions (ESS, PPA) and maintaining the cell membrane (SLM, TMH and HS). Each of these independently contributes to the variation in protein evolution.

【 授权许可】

   
2013 Wei et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 3.

Figure 3.

Figure 4.

【 参考文献 】

• [1]Hirsh AE, Fraser HB: Protein dispensability and rate of evolution. Nature 2001, 411(6841):1046-1049.
• [2]Pal C, Papp B, Hurst LD: Genomic function: rate of evolution and gene dispensability. Nature 2003, 421(6922):496-497. discussion 497–498
• [3]Fraser HB, Hirsh AE, Steinmetz LM, Scharfe C, Feldman MW: Evolutionary rate in the protein interaction network. Science 2002, 296(5568):750-752.
• [4]Jordan IK, Rogozin IB, Wolf YI, Koonin EV: Essential genes are more evolutionarily conserved than are nonessential genes in bacteria. Genome Res 2002, 12(6):962-968.
• [5]Yang J, Gu Z, Li WH: Rate of protein evolution versus fitness effect of gene deletion. Mol Biol Evol 2003, 20(5):772-774.
• [6]Hahn MW, Kern AD: Comparative genomics of centrality and essentiality in three eukaryotic protein-interaction networks. Mol Biol Evol 2005, 22(4):803-806.
• [7]Drummond DA, Wilke CO: Mistranslation-induced protein misfolding as a dominant constraint on coding-sequence evolution. Cell 2008, 134(2):341-352.
• [8]Liao BY, Weng MP, Zhang J: Impact of extracellularity on the evolutionary rate of mammalian proteins. Genome Biol Evol 2010, 2:39-43.
• [9]Chang TY, Liao BY: Flagellated algae protein evolution suggests the prevalence of lineage-specific rules governing evolutionary rates of eukaryotic proteins. Genome Biol Evol 2013, 5(5):913-922.
• [10]Nogueira T, Touchon M, Rocha EP: Rapid evolution of the sequences and gene repertoires of secreted proteins in bacteria. PLoS One 2012, 7(11):e49403.
• [11]Wilson AC, Carlson SS, White TJ: Biochemical evolution. Annu Rev Biochem 1977, 46:573-639.
• [12]Rocha EP, Danchin A: An analysis of determinants of amino acids substitution rates in bacterial proteins. Mol Biol Evol 2004, 21(1):108-116.
• [13]Drummond DA, Raval A, Wilke CO: A single determinant dominates the rate of yeast protein evolution. Mol Biol Evol 2006, 23(2):327-337.
• [14]Pal C, Papp B, Hurst LD: Highly expressed genes in yeast evolve slowly. Genetics 2001, 158(2):927-931.
• [15]Krylov DM, Wolf YI, Rogozin IB, Koonin EV: Gene loss, protein sequence divergence, gene dispensability, expression level, and interactivity are correlated in eukaryotic evolution. Genome Res 2003, 13(10):2229-2235.
• [16]Subramanian S, Kumar S: Gene expression intensity shapes evolutionary rates of the proteins encoded by the vertebrate genome. Genetics 2004, 168(1):373-381.
• [17]Lemos B, Bettencourt BR, Meiklejohn CD, Hartl DL: Evolution of proteins and gene expression levels are coupled in Drosophila and are independently associated with mRNA abundance, protein length, and number of protein-protein interactions. Mol Biol Evol 2005, 22(5):1345-1354.
• [18]Popescu CE, Borza T, Bielawski JP, Lee RW: Evolutionary rates and expression level in Chlamydomonas. Genetics 2006, 172(3):1567-1576.
• [19]Ingvarsson PK: Gene expression and protein length influence codon usage and rates of sequence evolution in Populus tremula. Mol Biol Evol 2007, 24(3):836-844.
• [20]Sharp PM, Li WH: The codon Adaptation Index–a measure of directional synonymous codon usage bias, and its potential applications. Nucleic Acids Res 1987, 15(3):1281-1295.
• [21]Wall DP, Hirsh AE, Fraser HB, Kumm J, Giaever G, Eisen MB, Feldman MW: Functional genomic analysis of the rates of protein evolution. Proc Natl Acad Sci U S A 2005, 102(15):5483-5488.
• [22]Zhang J, He X: Significant impact of protein dispensability on the instantaneous rate of protein evolution. Mol Biol Evol 2005, 22(4):1147-1155.
• [23]Yang JR, Liao BY, Zhuang SM, Zhang J: Protein misinteraction avoidance causes highly expressed proteins to evolve slowly. Proc Natl Acad Sci U S A 2012, 109(14):E831-E840.
• [24]Plotkin JB, Fraser HB: Assessing the determinants of evolutionary rates in the presence of noise. Mol Biol Evol 2007, 24(5):1113-1121.
• [25]Wolf MY, Wolf YI, Koonin EV: Comparable contributions of structural-functional constraints and expression level to the rate of protein sequence evolution. Biol Direct 2008, 3:40. BioMed Central Full Text
• [26]Park C, Chen X, Yang JR, Zhang J: Differential requirements for mRNA folding partially explain why highly expressed proteins evolve slowly. Proc Natl Acad Sci U S A 2013, 110(8):E678-E686.
• [27]Zur H, Tuller T: Strong association between mRNA folding strength and protein abundance in S. cerevisiae. EMBO Rep 2012, 13(3):272-277.
• [28]Lafay B, Atherton JC, Sharp PM: Absence of translationally selected synonymous codon usage bias in Helicobacter pylori. Microbiology 2000, 146(Pt 4):851-860.
• [29]Vieira-Silva S, Rocha EP: The systemic imprint of growth and its uses in ecological (meta) genomics. PLoS Genet 2010, 6(1):e1000808.
• [30]Plotkin JB, Kudla G: Synonymous but not the same: the causes and consequences of codon bias. Nat Rev Genet 2011, 12(1):32-42.
• [31]Naya H, Romero H, Carels N, Zavala A, Musto H: Translational selection shapes codon usage in the GC-rich genome of Chlamydomonas reinhardtii. FEBS Lett 2001, 501(2–3):127-130.
• [32]Voges D, Watzele M, Nemetz C, Wizemann S, Buchberger B: Analyzing and enhancing mRNA translational efficiency in an Escherichia coli in vitro expression system. Biochem Biophys Res Commun 2004, 318(2):601-614.
• [33]Kudla G, Murray AW, Tollervey D, Plotkin JB: Coding-sequence determinants of gene expression in Escherichia coli. Science 2009, 324(5924):255-258.
• [34]Gu W, Zhou T, Wilke CO: A universal trend of reduced mRNA stability near the translation-initiation site in prokaryotes and eukaryotes. PLoS Comput Biol 2010, 6(2):e1000664.
• [35]Hershberg R, Petrov DA: General rules for optimal codon choice. PLoS Genet 2009, 5(7):e1000556.
• [36]Mirkin EV, Mirkin SM: Mechanisms of transcription-replication collisions in bacteria. Mol Cell Biol 2005, 25(3):888-895.
• [37]Pomerantz RT, O’Donnell M: What happens when replication and transcription complexes collide? Cell Cycle 2010, 9(13):2537-2543.
• [38]Kim N, Jinks-Robertson S: Transcription as a source of genome instability. Nat Rev Genet 2012, 13(3):204-214.
• [39]Theis FJ, Latif N, Wong P, Frishman D: Complex principal component and correlation structure of 16 yeast genomic variables. Mol Biol Evol 2011, 28(9):2501-2512.
• [40]Liao BY, Scott NM, Zhang J: Impacts of gene essentiality, expression pattern, and gene compactness on the evolutionary rate of mammalian proteins. Mol Biol Evol 2006, 23(11):2072-2080.
• [41]Zhang J, Maslov S, Shakhnovich EI: Constraints imposed by non-functional protein-protein interactions on gene expression and proteome size. Mol Syst Biol 2008, 4:210.
• [42]Zhang R, Lin Y: DEG 5.0, a database of essential genes in both prokaryotes and eukaryotes. Nucleic Acids Res 2009, 37(Database issue):D455-D458.
• [43]Thompson JD, Higgins DG, Gibson TJ: CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 1994, 22(22):4673-4680.
• [44]Yang Z: PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol 2007, 24(8):1586-1591.
• [45]Garcia-Vallve S, Guzman E, Montero MA, Romeu A: HGT-DB: a database of putative horizontally transferred genes in prokaryotic complete genomes. Nucleic Acids Res 2003, 31(1):187-189.
• [46]Podell S, Gaasterland T: DarkHorse: a method for genome-wide prediction of horizontal gene transfer. Genome Biol 2007, 8(2):R16. BioMed Central Full Text
• [47]Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, Marshall KA, Phillippy KH, Sherman PM, Holko M, et al.: NCBI GEO: archive for functional genomics data sets–update. Nucleic Acids Res 2013, 41(D1):D991-D995.
• [48]Lorenz R, Bernhart SH, Honer Zu Siederdissen C, Tafer H, Flamm C, Stadler PF, Hofacker IL: ViennaRNA Package 2.0. Algorithms Mol Biol 2011, 6:26. BioMed Central Full Text
• [49]Szklarczyk D, Franceschini A, Kuhn M, Simonovic M, Roth A, Minguez P, Doerks T, Stark M, Muller J, Bork P, et al.: The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored. Nucleic Acids Res 2011, 39(Database issue):D561-D568.
• [50]Yu NY, Wagner JR, Laird MR, Melli G, Rey S, Lo R, Dao P, Sahinalp SC, Ester M, Foster LJ, et al.: PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes. Bioinformatics 2010, 26(13):1608-1615.
• [51]Gao F, Luo H, Zhang CT: DoriC 5.0: an updated database of oriC regions in both bacterial and archaeal genomes. Nucleic Acids Res 2013, 41(Database issue):D90-D93.