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Dynamic metabolic control: towards precision engineering of metabolism

Abstract

Advances in metabolic engineering have led to the synthesis of a wide variety of valuable chemicals in microorganisms. The key to commercializing these processes is the improvement of titer, productivity, yield, and robustness. Traditional approaches to enhancing production use the “push–pull-block” strategy that modulates enzyme expression under static control. However, strains are often optimized for specific laboratory set-up and are sensitive to environmental fluctuations. Exposure to sub-optimal growth conditions during large-scale fermentation often reduces their production capacity. Moreover, static control of engineered pathways may imbalance cofactors or cause the accumulation of toxic intermediates, which imposes burden on the host and results in decreased production. To overcome these problems, the last decade has witnessed the emergence of a new technology that uses synthetic regulation to control heterologous pathways dynamically, in ways akin to regulatory networks found in nature. Here, we review natural metabolic control strategies and recent developments in how they inspire the engineering of dynamically regulated pathways. We further discuss the challenges of designing and engineering dynamic control and highlight how model-based design can provide a powerful formalism to engineer dynamic control circuits, which together with the tools of synthetic biology, can work to enhance microbial production.

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Acknowledgements

This work was funded by the Human Frontier Science Program through a Young Investigator Grant awarded to D. O. and F. Z. (Grant no. RGY0076-2015) and the US National Science Foundation (MCB1453147) to F. Z.

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Correspondence to Diego A. Oyarzún or Fuzhong Zhang.

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Liu, D., Mannan, A.A., Han, Y. et al. Dynamic metabolic control: towards precision engineering of metabolism. J Ind Microbiol Biotechnol 45, 535–543 (2018). https://doi.org/10.1007/s10295-018-2013-9

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Keywords

  • Dynamic metabolic control
  • Genetic circuits
  • Biosensors
  • Synthetic biology
  • Model-based design