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Versatile selective evolutionary pressure using synthetic defect in universal metabolism

Author

Listed:
  • Lara Sellés Vidal

    (Imperial College London
    Imperial College London)

  • James W. Murray

    (Imperial College London)

  • John T. Heap

    (Imperial College London
    Imperial College London
    The University of Nottingham, Biodiscovery Institute, University Park)

Abstract

The non-natural needs of industrial applications often require new or improved enzymes. The structures and properties of enzymes are difficult to predict or design de novo. Instead, semi-rational approaches mimicking evolution entail diversification of parent enzymes followed by evaluation of isolated variants. Artificial selection pressures coupling desired enzyme properties to cell growth could overcome this key bottleneck, but are usually narrow in scope. Here we show diverse enzymes using the ubiquitous cofactors nicotinamide adenine dinucleotide (NAD) or nicotinamide adenine dinucleotide phosphate (NADP) can substitute for defective NAD regeneration, representing a very broadly-applicable artificial selection. Inactivation of Escherichia coli genes required for anaerobic NAD regeneration causes a conditional growth defect. Cells are rescued by foreign enzymes connected to the metabolic network only via NAD or NADP, but only when their substrates are supplied. Using this principle, alcohol dehydrogenase, imine reductase and nitroreductase variants with desired selectivity modifications, and a high-performing isopropanol metabolic pathway, are isolated from libraries of millions of variants in single-round experiments with typical limited information to guide design.

Suggested Citation

  • Lara Sellés Vidal & James W. Murray & John T. Heap, 2021. "Versatile selective evolutionary pressure using synthetic defect in universal metabolism," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-27266-9
    DOI: 10.1038/s41467-021-27266-9
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    References listed on IDEAS

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    1. Kevin M. Esvelt & Jacob C. Carlson & David R. Liu, 2011. "A system for the continuous directed evolution of biomolecules," Nature, Nature, vol. 472(7344), pages 499-503, April.
    2. Ewen Callaway, 2020. "‘It will change everything’: DeepMind’s AI makes gigantic leap in solving protein structures," Nature, Nature, vol. 588(7837), pages 203-204, December.
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    1. Hanyang Dong & Jianji Zhang & Hui Zhang & Yue Han & Congcong Lu & Chen Chen & Xiaoxia Tan & Siyu Wang & Xue Bai & Guijin Zhai & Shanshan Tian & Tao Zhang & Zhongyi Cheng & Enmin Li & Liyan Xu & Kai Zh, 2022. "YiaC and CobB regulate lysine lactylation in Escherichia coli," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    2. Shuke Wu & Chao Xiang & Yi Zhou & Mohammad Saiful Hasan Khan & Weidong Liu & Christian G. Feiler & Ren Wei & Gert Weber & Matthias Höhne & Uwe T. Bornscheuer, 2022. "A growth selection system for the directed evolution of amine-forming or converting enzymes," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    3. Edward King & Sarah Maxel & Yulai Zhang & Karissa C. Kenney & Youtian Cui & Emma Luu & Justin B. Siegel & Gregory A. Weiss & Ray Luo & Han Li, 2022. "Orthogonal glycolytic pathway enables directed evolution of noncanonical cofactor oxidase," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    4. Linyue Zhang & Edward King & William B. Black & Christian M. Heckmann & Allison Wolder & Youtian Cui & Francis Nicklen & Justin B. Siegel & Ray Luo & Caroline E. Paul & Han Li, 2022. "Directed evolution of phosphite dehydrogenase to cycle noncanonical redox cofactors via universal growth selection platform," Nature Communications, Nature, vol. 13(1), pages 1-12, December.

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