Advanced Science (Mar 2024)

Co‐Cultivated Enzyme Constraint Metabolic Network Model for Rational Guidance in Constructing Synthetic Consortia to Achieve Optimal Pathway Allocation Prediction

  • Boyuan Xue,
  • Yu Liu,
  • Chen Yang,
  • Hao Liu,
  • Qianqian Yuan,
  • Shaojie Wang,
  • Haijia Su

DOI
https://doi.org/10.1002/advs.202306662
Journal volume & issue
Vol. 11, no. 9
pp. n/a – n/a

Abstract

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Abstract Synthetic consortia have emerged as a promising biosynthetic platform that offers new opportunities for biosynthesis. Genome‐scale metabolic network models (GEMs) with complex constraints are extensively utilized to guide the synthesis in monocultures. However, few methods are currently available to guide the rational construction of synthetic consortia for predicting the optimal allocation strategy of synthetic pathways aimed at enhancing product synthesis. A standardized method to construct the co‐cultivated Enzyme Constraint metabolic network model (CulECpy) is proposed, which integrates enzyme constraints and modular interaction scale constraints based on the research concept of “independent + global”. This method is applied to construct several synthetic consortia models, which encompassed different target products, strains, synthetic pathways, and compositional structures. Analyzing the model, the optimal pathway allocation and initial inoculum ratio that enhance the synthesis of target products by synthetic consortia are predicted and verified. When comparing with the constructed co‐culture synthesis system, the normalized root mean square error of all optimal theoretical yield simulations is found to be less than or equal to 0.25. The analyses and verifications demonstrate that the method CulECpy can guide the rational construction of synthetic consortia systems to facilitate biochemical synthesis.

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