Predicting the adaptive evolution of Thermoanaerobacterium saccharolyticum

Pornkamol Unrean, Friedrich Srienc

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

A fully evolved metabolic network can be described as a weighted sum of elementary modes where the usage probabilities of modes are distributed according to the Boltzmann distribution law (. Srienc and Unrean, 2010). An organism presumably achieves the fully evolved state through adaptive changes in the kinetics of rate-controlling enzymes. Metabolic control analysis identifies reactions catalyzed by such enzymes. Comparison of the experimentally determined metabolic flux distributions of Thermoanaerobacterium saccharolyticum AS411 with the predicted flux distribution of a fully evolved metabolic network identified phosphoglucose isomerase (PGI) as the enzyme with the greatest flux control, the rate-controlling enzyme. The analysis predicts that an increased activity of PGI would enable the metabolic network to approach the fully evolved state and result in a faster specific growth rate. The prediction was confirmed by experimental results that showed an increased specific activity of PGI in a culture of strain AS411 that adaptively evolved over 280 generations. Sequencing of the gene confirmed the occurrence of a group of mutations clustered in the subunit binding domain of the dimeric enzyme. The results indicate that the evolutionary path is predictable as the strain AS411 adapted toward the fully evolved state by increasing the PGI activity. This experimental finding confirms that enzymes with predicted highest metabolic flux control are the targets of adaptive metabolic pathway evolution.

Original languageEnglish (US)
Pages (from-to)259-266
Number of pages8
JournalJournal of Biotechnology
Volume158
Issue number4
DOIs
StatePublished - Apr 30 2012

Bibliographical note

Funding Information:
We thank the National Institutes of Health (NIH) Grant No. GM077529 , Mascoma Corp. and IREE for support, and the Minnesota Supercomputing Institute (MSI) for using their resources. We also thank D. Bond for helping with the anaerobic cultivation and P. Daoutidis for helpful discussions.

Keywords

  • Adaptive evolution
  • Elementary modes
  • Metabolic pathway analysis

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