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Metabolic network analysis of the causes and evolution of enzyme dispensability in yeast


Under laboratory conditions 80% of yeast genes seem not to be essential for viability1. This raises the question of what the mechanistic basis for dispensability is, and whether it is the result of selection for buffering or an incidental side product. Here we analyse these issues using an in silico flux model2,3,4,5 of the yeast metabolic network. The model correctly predicts the knockout fitness effects in 88% of the genes studied4 and in vivo fluxes. Dispensable genes might be important, but under conditions not yet examined in the laboratory. Our model indicates that this is the dominant explanation for apparent dispensability, accounting for 37–68% of dispensable genes, whereas 15–28% of them are compensated by a duplicate, and only 4–17% are buffered by metabolic network flux reorganization. For over one-half of those not important under nutrient-rich conditions, we can predict conditions when they will be important. As expected, such condition-specific genes have a more restricted phylogenetic distribution. Gene duplicates catalysing the same reaction are not more common for indispensable reactions, suggesting that the reason for their retention is not to provide compensation. Instead their presence is better explained by selection for high enzymatic flux.

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Figure 1: Number of experimentally verified essential and non-essential genes in different categories.
Figure 2: The proportion of genes predicted to have non-zero flux and to be essential under different growth conditions.
Figure 3: Relationship between phylogenetic distribution and condition specificity.


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We thank J. Förster and B. Palsson for discussions and providing information on the yeast flux balance model. We also thank J. Glasner for providing growth data on the E. coli wild-type strain. B.P. and C.P. were supported by the Hungarian National Research Grant Foundation (OTKA).

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Correspondence to Laurence D. Hurst.

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Supplementary Information

Contains: Table S1a. Comparison of experimentally estimated flux values with predicted ones under four growth conditions; Table S1b. The model predicts presence or absence of fluxes with 91-95% success in central carbon metabolism; Table S2a. In silico flux values of selected metabolic reactions; Table S2b. Average in silico flux values of major metabolic units; Table S3. Comparison of predicted and measured gene dispensability on rich medium with glucose (YPD); Table S4. Causes of metabolic gene dispensability; Table S5. What explains failure of compensation by a duplicate? Figure S1. The extent of flux reorganisation correlates with predicted fitness effect of the knock-out; Table S6. No association between importance of reactions and presence of isoenzymes; Table S7. Reactions catalysed by isoenzymes have larger fluxes than those catalysed by solo copy enzymes; Figure S2. Distribution of environmental specificity of fitness defects of Escherichia coli mutant strains; Figure S3. Phylogenetic distribution of E. coli genes correlates with environmental specificity of mutant phenotypes; Table S8. Calculation of phylogenetic distribution of E. coli genes; Equation S1. Biomass equation used for metabolic simulations; Figure S4. Distribution of predicted growth rates for knock-out strains; References. (DOC 165 kb)

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Papp, B., Pál, C. & Hurst, L. Metabolic network analysis of the causes and evolution of enzyme dispensability in yeast. Nature 429, 661–664 (2004).

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