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Asymmetric relationships between metabolic reactions shape genome evolution Philip R. Kensche*, Richard A. Notebaart*, Martijn A. Huynen , Bas E. Dutilh *authors contributed equally C B m i Center for Molecular and Biomolecular Informatics Radboud University Nijmegen Medical Center Nijmegen Center for Molecular Life Sciences The Netherlands Results Summary Often, dependency relations between proteins are asymmetric: one protein (A) depends for its function on another, second protein (B), but that second protein does not depend on the first. Stoichiometric modelling of complete metabolisms suggests that most of the reaction pairs with coupled fluxes are asymmetrically rather than symmetrically coupled: 82% in S. cerevisiae and 67% in E. coli. This asymmetry in the coupling of fluxes is reflected in the expression of the catalyzing enzymes, the impact of their gene’s knock-outs and the evolution of gene content. Figure 1 reaction A is active also reaction B carries a flux. Conversely, B can be than the random expectation (two-sided, onesample Wilcoxon test; McNemar test). S. cerevisiae E. coli E. coli and S. cerevisiae 0.0 0.2 0.4 ). B | Analysis outline. As activity of reaction A is not necessary for reaction B, A could be considered “dispensable”. Various other genomic data can be interpreted in terms of dispensability: “dispensable” genes are not expressed in a condition, do not affect growth when knocked-out or are absent from a species’ genome. flux-coupling analysis | growth/ expression essentiality directional coupling A→B 1.0 Strength of asymmetry is independent of network distance. essentiality expression growth occurrence B phylogenetic occurrence dispensability profiles avg. asymmetry Figure 2 0.8 A Figure 5 A 0.6 average asymmetry active without A because of alternative converging or diverging fluxes ( essentiality expression growth occurrence losses gains contingent gain A maintenance Asymmetry in various genomic All asymmetry values are significantly larger | Examples of asymmetric relations between reactions. Nodes represent metabolites, edges reactions. For a reaction pair A→B, if | Figure 4 data sets is consistent with model predictions. gains losses contingent gain A maintenance 1.0 0.5 S. cerevisiae 0.0 Figure 6 3 4 5 6 7 E. coli 1 2 8 9+ 1 2 3 network distance 4 5 6 7 8 | The asymmetric relationship [ThrB → Asd] conserved 9+ between E. coli and S. cerevisiae is reflected in their phylogenetic asymmetry measure f01=n01/(n01+n10) distributions: thrB is almost never present in a genome without asd because ThrB’s activity depends on Asd, but not vice versa. Aspartate semialdehyde dehydrogenase (Asd) Is there asymmetry? H0: fAB:=f01=0.5 Figure 3 Homoserine kinase (ThrB) Threonine synthesis | Four measures of asymmetry extracted from the parsimony reconstruction of ancestral gene content (STRING database & PAUP). The type of change across branches that is more expected in asymmetric pairs A→B is denoted in pink. E.g. “contingent gain A”: If A’s function depends on Lysine synthesis Methionine synthesis B, then A should be gained if B is already present but not if B is absent. asd #gain 00 #loss 11 10 01 10 #contingent gain A 00 01 01 10 11 #maintenance 10 01 10 01 thrB present absent present absent 184 1 129 59 Thermophilum pendens Crenarcheote that feeds on peptides Conclusions Genomic data contain not only information about whether proteins interact but also about the characteristics of the interaction. Asymmetric patterns could be used to predict characteristics of known and new functional relations. Contact [email protected]