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[An evolving and flourishing metabolic engineering].

Zhifeng Liu1,2, Yong Wang1

  • 1CAS Center for Excellence in Molecular Plant Sciences, Key Laboratory of Synthetic Biology, Chinese Academy of Sciences, Shanghai 200032, China.

Sheng Wu Gong Cheng Xue Bao = Chinese Journal of Biotechnology
|June 4, 2021
PubMed
Summary
This summary is machine-generated.

Metabolic engineering has evolved over 30 years from classic DNA recombination to systems metabolic engineering. New tools from synthetic biology and machine learning enhance cell performance and product yields.

Keywords:
dynamic controlevolution engineeringmachine learningmetabolic engineering

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Area of Science:

  • Biotechnology
  • Synthetic Biology
  • Metabolic Engineering

Background:

  • Metabolic engineering, conceptualized in the 1990s, utilized DNA recombination to optimize cellular functions and product generation.
  • The field has significantly advanced due to breakthroughs in genomics, systems biology, and synthetic biology.

Purpose of the Study:

  • To analyze the 30-year evolution of metabolic engineering.
  • To summarize emerging theories, techniques, strategies, and applications in the field.

Main Methods:

  • Review of classic metabolic engineering principles.
  • Integration of systems biology approaches.
  • Application of synthetic biology tools (omics, metabolic models, genome editing).
  • Incorporation of machine learning and evolutionary engineering.

Main Results:

  • Transition from classic to systems metabolic engineering.
  • Enhanced capabilities in designing, building, and rewiring complex metabolic networks.
  • Significant improvements in cell performance and target product yields.

Conclusions:

  • Metabolic engineering has entered a new era driven by interdisciplinary advancements.
  • Future development will be propelled by machine learning and evolutionary engineering integration.
  • The field continues to expand its scope and applications in life sciences.