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포스터 발표 : 미생물공학

Reduced-genome Escherichia coli Undergoes Adaptive Evolution to A chieve the Optimal Growth on a Laboratory Timescale

초록

영어

Synthetic biology aims to redesign biological systems with desirable properties to provide the foundation for the biosynthesis of metabolites and proteins of commercial interest. In this regard, Escherichia coli is one of the best industrial microbes. In an effort to supply only the necessary genes for full functionality, and therefore reduce the complexity of the metabolic and regulatory networks, large blocks of nonessential genes have been deleted1,2. However, removal of the nonessential genes resulted in reduction of the growth rate of the reduced-genome E. coli (MS56) on M9 minimal medium. To achieve a growth rate equivalent to that of wild-type E. coli K-12 MG1655, the reduced-genome MS56 strain was subjected to adaptive evolution on glucose M9 medium for 62 days. Along with achievement of the equivalent growth, the evolved E. coli strain (eJY62) exhibited unique physiological behaviors compared to the parental MS56 strain under the conditions, suggesting that the adaptive evolution resulted in significant metabolic and regulatory perturbations. To investigate the ability of the reduced-genome MS56 strain to overcome the reduction of growth rate, we monitored the acquisition and fixation of mutations that conveyed a selective growth advantage during adaptation to the M9 minimal medium by whole-genome resequencing. We identified 16 different mutations in the parental MS56 strain and evaluated the contributions of individual mutations to the reduced growth rate in M9 minimal medium. Several mutations identified from the eJY62 clones were responsible for the improved fitness of growth rates and the unique physiological properties. These results demonstrate that the E. coli can adapt to the genome reduction with several mutations, resulting in equivalent growth rate compared to the wild-type strain. This comprehensive genetic information on the reduction of microbial genome will provide the foundation for designing and rewriting an artificial genome.

저자정보

  • Jayoung KIM Department of Biological Sciences ,Korea Advanced Institute of Science and Technology, Daejeon
  • Yoseb SONG Department of Biological Sciences and KAIST Institute for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon.
  • Mikyoung LEE Department of Biological Sciences and KAIST Institute for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon.
  • Youngeun YEON Department of Biological Sciences and KAIST Institute for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon.
  • Sooin LEE Department of Biological Sciences and KAIST Institute for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon.
  • Sun Chang KIM Department of Biological Sciences and KAIST Institute for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon.
  • Byung-Kwan CHO Department of Biological Sciences and KAIST Institute for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon.

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