A Computational Metabolic Model for Engineered Production of Resveratrol in Escherichia coli

Although engineered microbial production of natural compounds provides a promising alternative method to plant production and extraction, the process can be inefficient and ineffective in terms of time and cost. To render microbial systems profitable and viable, the process must be optimized to produce as much product as possible. To this end, this work illustrates the construction of a new probabilistic computational model to simulate the microbial production of a well-known cardioprotective molecule, resveratrol, and the implementation of the model to enhance the yield of the product in Escherichia coli. This model identified stilbene synthase as the limiting enzyme and informed the effects on changes in concentration and source of this enzyme. These parameters, when employed in a laboratory system, were able to improve the titer from 62.472 mg/L to 172.799 mg/L, demonstrating the model's ability to produce a useful simulation of a dynamic microbial resveratrol production system.

Automated summary

A new probabilistic computational model was constructed to optimize the microbial production of resveratrol in Escherichia coli. By identifying the limiting enzyme and informing the effects of changes in enzyme concentration and source, the model successfully increased the yield of resveratrol in the laboratory system.