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[An evolving and flourishing metabolic engineering].

Zhifeng Liu, Yong Wang

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Abstract

In 1990s, Bailey and Stephanopoulos put forward the concept of classic metabolic engineering, aiming to use DNA recombination technology to rewire metabolic network to achieve improved cell performance and increased target products. In the last 30 years since the birth of metabolic engineering, life science have flourished, and new disciplines such as genomics, systems biology and synthetic biology have emerged, injecting new connotations and vitality into the development of metabolic engineering. Classic metabolic engineering research has entered into an unprecedented stage of systems metabolic engineering. The application of synthetic biology tools and strategies, such as omics technology, genomic-scale metabolic model, parts assembly, circuits design, dynamic control, genome editing and many others, have greatly improved the design, build, and rewiring capabilities of complex metabolism. The intervention of machine learning and the combination of evolutionary engineering and metabolic engineering will further promote the development of systems metabolic engineering. This paper analyzes the development of metabolic engineering in the past 30 years and summarizes the novel theories, techniques, strategies, and applications of metabolic engineering that have emerged over the past 30 years.

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What this paper is about

In 1990s, Bailey and Stephanopoulos put forward the concept of classic metabolic engineering, aiming to use DNA recombination technology to rewire metabolic network to achieve improved cell performance and increased target products. In the last 30 years since the birth of metabolic engineering, life science have flourished, and new disciplines such as genomics, systems biology and synthetic biology have emerged, injecting new connotations and vitality into the development of metabolic engineering. Classic metabolic engineering research has entered into an unprecedented stage of systems metabolic engineering. The application of synthetic biology tools and strategies, such as omics technology, genomic-scale metabolic model, parts assembly, circuits design, dynamic control, genome editing and many others, have greatly improved the design, build, and rewiring capabilities of complex metabolism. The intervention of machine learning and the combination of evolutionary engineering and metabolic engineering will further promote the development of systems metabolic engineering. This paper analyzes the development of metabolic engineering in the past 30 years and summarizes the novel theories, techniques, strategies, and applications of metabolic engineering that have emerged over the past 30 years.

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Available abstract

In 1990s, Bailey and Stephanopoulos put forward the concept of classic metabolic engineering, aiming to use DNA recombination technology to rewire metabolic network to achieve improved cell performance and increased target products. In the last 30 years since the birth of metabolic engineering, life science have flourished, and new disciplines such as genomics, systems biology and synthetic biology have emerged, injecting new connotations and vitality into the development of metabolic engineering. Classic metabolic engineering research has entered into an unprecedented stage of systems metabolic engineering. The application of synthetic biology tools and strategies, such as omics technology, genomic-scale metabolic model, parts assembly, circuits design, dynamic control, genome editing and many others, have greatly improved the design, build, and rewiring capabilities of complex metabolism. The intervention of machine learning and the combination of evolutionary engineering and metabolic engineering will further promote the development of systems metabolic engineering. This paper analyzes the development of metabolic engineering in the past 30 years and summarizes the novel theories, techniques, strategies, and applications of metabolic engineering that have emerged over the past 30 years.

Key concepts: Metabolic engineering, Flourishing, Synthetic biology, Systems biology, Metabolic network, Genome engineering, Metabolic flux analysis, Computer science

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