Latent pathway activation and increased pathway capacity enable Escherichia coli adaptation to loss of key metabolic enzymes.

TitleLatent pathway activation and increased pathway capacity enable Escherichia coli adaptation to loss of key metabolic enzymes.
Publication TypeJournal Article
Year of Publication2006
AuthorsFong S, Nanchen A, Palsson BØ, Sauer U
JournalThe Journal of biological chemistry
Volume281
Issue12
Pagination8024-33
PubMed Date2006 Mar 24
ISSN0021-9258
KeywordsAnimals, Bacterial Physiological Phenomena, Bacterial Proteins, Biological Evolution, Carbon, Escherichia coli, Escherichia coli Proteins, Evolution, Molecular, Gas Chromatography-Mass Spectrometry, Gene Deletion, Glycerol, Mass Spectrometry, Mice, Mice, Knockout, Models, Biological, Models, Chemical, Models, Genetic, Mutation, Oligonucleotide Array Sequence Analysis, Phenotype, Protein Biosynthesis, Repressor Proteins, RNA, Messenger, Transcription Factors, Transcription, Genetic
Abstract

The ability of biological systems to adapt to genetic and environmental perturbations is a fundamental but poorly understood process at the molecular level. By quantifying metabolic fluxes and global mRNA abundance, we investigated the genetic and metabolic mechanisms that underlie adaptive evolution of four metabolic gene deletion mutants of Escherichia coli (delta pgi, delta ppc, delta pta, and delta tpi) in parallel evolution experiments of each mutant. The initial response to the gene deletions was flux rerouting through local bypass reactions or normally latent pathways. The principal effect of evolution was improved capacity of already active pathways, whereas new flux distributions were not observed. Combinatorial changes in capacity and pathway activation, however, led to different intracellular flux states that enabled evolution in three of the four parallel cases tested. The molecular bases of the evolved phenotypes were then elucidated by global mRNA transcript analyses. Activation of latent pathways and flux changes in the tricarboxylic acid cycle were found to correlate well with molecular changes at the transcriptional level. Flux alterations in other central metabolic pathways, in contrast, were apparently not connected to changes in the transcriptional network. These results give new insight into the dynamics of the evolutionary process by demonstrating the flexibility of the metabolic network of E. coli to compensate for genetic perturbations and the utility of combining multiple high throughput data sets to differentiate between causal and noncausal mechanistic changes.

Alternate JournalJ. Biol. Chem.
PubMed ID16319065

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