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Graph-based and constraint-based heterologous metabolic pathway design methods and application / 生物工程学报
Chinese Journal of Biotechnology ; (12): 1390-1407, 2022.
Article in Chinese | WPRIM | ID: wpr-927788
ABSTRACT
It is among the goals in metabolic engineering to construct microbial cell factories producing high-yield and high value-added target products, and an important solution is to design efficient synthetic pathway for the target products. However, due to the difference in metabolic capacity among microbial chassises, the available substrate and the yielded products are limited. Therefore, it is urgent to design related metabolic pathways to improve the production capacity. Existing metabolic engineering approaches to designing heterologous pathways are mainly based on biological experience, which are inefficient. Moreover, the yielded results are in no way comprehensive. However, systems biology provides new methods for heterologous pathway design, particularly the graph-based and constraint-based methods. Based on the databases containing rich metabolism information, they search for and uncover possible metabolic pathways with designated strategy (graph-based method) or algorithm (constraint-based method) and then screen out the optimal pathway to guide the modification of strains. In this paper, we reviewed the databases and algorithms for pathway design, and the applications in metabolic engineering and discussed the strengths and weaknesses of existing algorithms in practical application, hoping to provide a reference for the selection of optimal methods for the design of product synthesis pathway.
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Full text: Available Index: WPRIM (Western Pacific) Main subject: Algorithms / Systems Biology / Metabolic Networks and Pathways / Biosynthetic Pathways / Metabolic Engineering Language: Chinese Journal: Chinese Journal of Biotechnology Year: 2022 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Algorithms / Systems Biology / Metabolic Networks and Pathways / Biosynthetic Pathways / Metabolic Engineering Language: Chinese Journal: Chinese Journal of Biotechnology Year: 2022 Type: Article