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Stochasticity in protein levels drives colinearity of gene order in metabolic operons of Escherichia coli.

ABSTRACT: In bacterial genomes, gene order is not random. This is most evident when looking at operons, these often encoding enzymes involved in the same metabolic pathway or proteins from the same complex. Is gene order within operons nonrandom, however, and if so why? We examine this issue using metabolic operons as a case study. Using the metabolic network of Escherichia coli, we define the temporal order of reactions. We find a pronounced trend for genes to appear in operons in the same order as they are needed in metabolism (colinearity). This is paradoxical as, at steady state, enzymes abundance should be independent of order within the operon. We consider three extensions of the steady-state model that could potentially account for colinearity: (1) increased productivity associated with higher expression levels of the most 5' genes, (2) a faster metabolic processing immediately after up-regulation, and (3) metabolic stalling owing to stochastic protein loss. We establish the validity of these hypotheses by employing deterministic and stochastic models of enzyme kinetics. The stochastic stalling hypothesis correctly and uniquely predicts that colinearity is more pronounced both for lowly expressed operons and for genes that are not physically adjacent. The alternative models fail to find any support. These results support the view that stochasticity is a pervasive problem to a cell and that gene order evolution can be driven by the selective consequences of fluctuations in protein levels.

SUBMITTER: Kovacs K

PROVIDER: S-EPMC2684527 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature

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Stochasticity in protein levels drives colinearity of gene order in metabolic operons of Escherichia coli.

Kovács Károly K Hurst Laurence D LD Papp Balázs B

PLoS biology 20090526 5

In bacterial genomes, gene order is not random. This is most evident when looking at operons, these often encoding enzymes involved in the same metabolic pathway or proteins from the same complex. Is gene order within operons nonrandom, however, and if so why? We examine this issue using metabolic operons as a case study. Using the metabolic network of Escherichia coli, we define the temporal order of reactions. We find a pronounced trend for genes to appear in operons in the same order as they ...[more]

PMID: 19492041

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Project description:Metabolic networks are characterized by multiple redundant reactions that do not have a clear biological function. The redundancies in the metabolic networks are implicated in adaptation to random mutations and survival under different environmental conditions. Reactions that are not active under wild-type growth conditions, but get transiently activated after a mutation event such as gene deletion are known as latent reactions. Characterization of multiple-gene knockout mutants can identify the physiological roles of latent reactions. In this study, we characterized double-gene deletion mutants of E. coli with the aim of investigating the sub-optimal physiology of the mutants and the possible roles of latent reactions. Specifically, we investigated the effects of the deletion of the glyoxylate-shunt gene aceA (encoding a latent reaction enzyme, isocitrate lyase) on the growth characteristics of the mutant E. coli ?pgi. The deletion of aceA reduced the growth rate of E. coli ?pgi, indicating that the activation of the glyoxylate shunt plays an important role in adaptation of the mutant E. coli ?pgi when no other latent reactions are concurrently inactivated. We also investigated the effect of the order of the gene deletions on the growth rates and substrate uptake rates of the double-gene deletion mutants. The results indicate that the order in which genes are deleted determines the phenotype of the mutants during the sub-optimal growth phase. To elucidate the mechanism behind the difference between the observed phenotypes, we carried out transcriptomic analysis and constraint-based modeling of the mutants. Transcriptomic analysis showed differential expression of the gene aceK (encoding the protein isocitrate dehydrogenase kinase) involved in controlling the isocitrate flux through the TCA cycle and the glyoxylate shunt. Higher acetate production in the E. coli ?aceA1 ?pgi2 mutant was consistent with the increased aceK expression, which limits the TCA cycle flux and causes acetate production via overflow metabolism.

Dataset Information

Stochasticity in protein levels drives colinearity of gene order in metabolic operons of Escherichia coli.

Publications

Stochasticity in protein levels drives colinearity of gene order in metabolic operons of Escherichia coli.

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