Systems biology approach for enhancing limonene yield by re-engineering Escherichia coli

Abstract Limonene is a valuable monoterpene utilised in biofuel, pharmaceutical, material science, food and beverage industries. Recently, microorganisms, such as engineered Escherichia coli, have emerged as potential alternatives for limonene production in the laboratory. However, there are general issues such as low enzyme abundance or activities, and regulatory feedback/forward inhibition resulting in reduced yields. To better understand the underlying metabolism, both mechanistically and dynamically, here we adopted a systems biology approach for cell cultures of engineered E. coli strain K-12 MG1655 producing limonene. Firstly, we generated time-series intra- and extra-cellular targeted metabolomics data and, secondly, developed a dynamic model based on enzyme dynamics to interpret the data. The initial wild-type model tracked native metabolic networks such as the glycolytic, tricarboxylic acid cycle, mixed fermentation, and deoxyxylulose 5-phosphate pathway, as well as the engineered mevalonate pathway. After several iterations of model fitting with experimental profiles, which also included 13C tracer studies, we utilised the finalised model to perform in silico knockouts (KOs) of all enzymes in the model to identify crucial bottleneck(s) for optimal limonene yields. The simulations indicated that the suppression of ALDH/ADH (aldehyde dehydrogenase/alcohol dehydrogenase) and LDH (lactate dehydrogenase), and the enhancement of HK (hexokinase) would increase limonene yields. These results were experimentally confirmed where ALDH-ADH and LDH KOs produced 8- to 11-fold enhancements, while HK overexpression resulted in an 8-fold increase in limonene yield. We believe that our systems biology approach can be extended to study other microbes for re-engineering strains for optimal target compound production.