Asymmetric relationships between proteins shape genome evolution

BackgroundThe relationships between proteins are often asymmetric: one protein (A) depends for its function on another protein (B), but the second protein does not depend on the first. In metabolic networks there are multiple pathways that converge into one central pathway. The enzymes in the converging pathways depend on the enzymes in the central pathway, but the enzymes in the latter do not depend on any specific enzyme in the converging pathways. Asymmetric relations are analogous to the “if->then” logical relation where A implies B, but B does not imply A (A->B).ResultsWe show that the majority of relationships between enzymes in metabolic flux models of metabolism in Escherichia coli and Saccharomyces cerevisiae are asymmetric. We show furthermore that these asymmetric relationships are reflected in the expression of the genes encoding those enzymes, the effect of gene knockouts and the evolution of genomes. From the asymmetric relative dependency, one would expect that the gene that is relatively independent (B) can occur without the other dependent gene (A), but not the reverse. Indeed, when only one gene of an A->B pair is expressed, is essential, is present in a genome after an evolutionary gain or loss, it tends to be the independent gene (B). This bias is strongest for genes encoding proteins whose asymmetric relationship is evolutionarily conserved.ConclusionsThe asymmetric relations between proteins that arise from the system properties of metabolic networks affect gene expression, the relative effect of gene knockouts and genome evolution in a predictable manner.

[1]  Christian von Mering,et al.  STRING 7—recent developments in the integration and prediction of protein interactions , 2006, Nucleic Acids Res..

[2]  Balázs Papp,et al.  Evaluation of predicted network modules in yeast metabolism using NMR-based metabolite profiling. , 2007, Genome research.

[3]  Robert P. St.Onge,et al.  The Chemical Genomic Portrait of Yeast: Uncovering a Phenotype for All Genes , 2008, Science.

[4]  M. Primig,et al.  Novel Response to Microtubule Perturbation in Meiosis , 2005, Molecular and Cellular Biology.

[5]  Dennis B. Troup,et al.  NCBI GEO: mining tens of millions of expression profiles—database and tools update , 2006, Nucleic Acids Res..

[6]  G. Church,et al.  Expression dynamics of a cellular metabolic network , 2005, Molecular systems biology.

[7]  Elizabeth Yohannes,et al.  Oxygen limitation modulates pH regulation of catabolism and hydrogenases, multidrug transporters, and envelope composition in Escherichia coli K-12 , 2006, BMC Microbiology.

[8]  Juha-Pekka Pitkänen,et al.  Excess Mannose Limits the Growth of Phosphomannose Isomerase PMI40 Deletion Strain of Saccharomyces cerevisiae*[boxs] , 2004, Journal of Biological Chemistry.

[9]  J. W. Campbell,et al.  Experimental Determination and System Level Analysis of Essential Genes in Escherichia coli MG1655 , 2003, Journal of bacteriology.

[10]  B. Palsson,et al.  Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110 , 1994, Applied and environmental microbiology.

[11]  H. Schellhorn,et al.  RpoS regulation of gene expression during exponential growth of Escherichia coli K12 , 2008, Molecular Genetics and Genomics.

[12]  Naren Ramakrishnan,et al.  Transcriptional Response of Saccharomyces cerevisiae to Desiccation and Rehydration , 2005, Applied and Environmental Microbiology.

[13]  J. Collins,et al.  Large-Scale Mapping and Validation of Escherichia coli Transcriptional Regulation from a Compendium of Expression Profiles , 2007, PLoS biology.

[14]  Dmitrij Frishman,et al.  MIPS: analysis and annotation of proteins from whole genomes in 2005 , 2005, Nucleic Acids Res..

[15]  D. Eisenberg,et al.  Detecting protein function and protein-protein interactions from genome sequences. , 1999, Science.

[16]  Jun Li,et al.  luxS-Dependent Gene Regulation in Escherichia coli K-12 Revealed by Genomic Expression Profiling , 2005, Journal of bacteriology.

[17]  U. Sauer,et al.  Metabolic functions of duplicate genes in Saccharomyces cerevisiae. , 2005, Genome research.

[18]  D. Eisenberg,et al.  Use of Logic Relationships to Decipher Protein Network Organization , 2004, Science.

[19]  R. Kornberg,et al.  Ubiquitin ligase activity of TFIIH and the transcriptional response to DNA damage. , 2005, Molecular cell.

[20]  J. Pronk,et al.  When transcriptome meets metabolome: fast cellular responses of yeast to sudden relief of glucose limitation , 2006, Molecular systems biology.

[21]  Erwin G. Zoetendal,et al.  The BaeSR Two-Component Regulatory System Mediates Resistance to Condensed Tannins in Escherichia coli , 2007, Applied and Environmental Microbiology.

[22]  L. Kruglyak,et al.  Simultaneous genotyping, gene-expression measurement, and detection of allele-specific expression with oligonucleotide arrays. , 2005, Genome research.

[23]  Arul Jayaraman,et al.  Indole is an inter-species biofilm signal mediated by SdiA , 2007, BMC Microbiology.

[24]  D. Shore,et al.  Growth-regulated recruitment of the essential yeast ribosomal protein gene activator Ifh1 , 2004, Nature.

[25]  C. Schilling,et al.  Flux coupling analysis of genome-scale metabolic network reconstructions. , 2004, Genome research.

[26]  P. Bork,et al.  Measuring genome evolution. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[27]  D. Swofford PAUP*: Phylogenetic analysis using parsimony (*and other methods), Version 4.0b10 , 2002 .

[28]  C. Pál,et al.  Adaptive evolution of bacterial metabolic networks by horizontal gene transfer , 2005, Nature Genetics.

[29]  B. Palsson,et al.  An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR) , 2003, Genome Biology.

[30]  M. Radmacher,et al.  pH Regulates Genes for Flagellar Motility, Catabolism, and Oxidative Stress in Escherichia coli K-12 , 2005, Journal of bacteriology.

[31]  Markus J. Herrgård,et al.  Integrating high-throughput and computational data elucidates bacterial networks , 2004, Nature.

[32]  C. Lawrence,et al.  Contribution of the Histone H3 and H4 Amino Termini to Gcn4p- and Gcn5p-mediated Transcription in Yeast* , 2006, Journal of Biological Chemistry.

[33]  Cailin Yu,et al.  Genome-Wide Analysis of the Relationship between Transcriptional Regulation by Rpd3p and the Histone H3 and H4 Amino Termini in Budding Yeast , 2004, Molecular and Cellular Biology.

[34]  Scott J. Hultgren,et al.  Functional Genomic Studies of Uropathogenic Escherichia coli and Host Urothelial Cells when Intracellular Bacterial Communities Are Assembled* , 2007, Journal of Biological Chemistry.

[35]  B. Snel,et al.  Genomes in flux: the evolution of archaeal and proteobacterial gene content. , 2002, Genome research.

[36]  Mark Pagel,et al.  Predicting Functional Gene Links from Phylogenetic-Statistical Analyses of Whole Genomes , 2005, 2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05).

[37]  M. Fenner Genome sequence of Thermofilum pendens reveals an exceptional loss of biosynthetic pathways without genome reduction , 2008 .

[38]  B. Snel,et al.  Systematic discovery of analogous enzymes in thiamin biosynthesis , 2003, Nature Biotechnology.

[39]  Bas Teusink,et al.  Co-Regulation of Metabolic Genes Is Better Explained by Flux Coupling Than by Network Distance , 2008, PLoS Comput. Biol..

[40]  T. Wood,et al.  Structure and function of the Escherichia coli protein YmgB: a protein critical for biofilm formation and acid-resistance. , 2007, Journal of molecular biology.

[41]  L. Parfrey,et al.  Genome-wide analysis of transcriptional dependence and probable target sites for Abf1 and Rap1 in Saccharomyces cerevisiae , 2006, Nucleic acids research.

[42]  B. Yandell,et al.  Impact of Nonsense-Mediated mRNA Decay on the Global Expression Profile of Budding Yeast , 2006, PLoS genetics.