Abstract
Production of value-added chemicals in microorganisms is regarded as a viable alternative to chemical synthesis. In the past decade, several engineered pathways producing such chemicals, including plant secondary metabolites in microorganisms have been reported; upscaling their production yields, however, was often challenging. Here, we analyze a modular device designed for sensing malonyl-CoA, a common precursor for both fatty acid and flavonoid biosynthesis. The sensor can be used either for high-throughput pathway screening in synthetic biology applications or for introducing a feedback circuit to regulate production of the desired chemical. Here, we used the sensor to compare the performance of several predicted malonyl-CoA-producing pathways, and validated the utility of malonyl-CoA reductase and malonate-CoA transferase for malonyl-CoA biosynthesis. We generated a second-order dynamic linear model describing the relation of the fluorescence generated by the sensor to the biomass of the host cell representing a filter/amplifier with a gain that correlates with the level of induction. We found the time constants describing filter dynamics to be independent of the level of induction but distinctively clustered for each of the production pathways, indicating the robustness of the sensor. Moreover, by monitoring the effect of the copy-number of the production plasmid on the dose–response curve of the sensor, we managed to coarse-tune the level of pathway expression to maximize malonyl-CoA synthesis. In addition, we provide an example of the sensor’s use in analyzing the effect of inducer or substrate concentrations on production levels. The rational development of models describing sensors, supplemented with the power of high-throughput optimization provide a promising potential for engineering feedback loops regulating enzyme levels to maximize productivity yields of synthetic metabolic pathways.
Highlights
Natural metabolic pathways are highly regulated and can adapt dynamically to changes in the levels of chemicals within and around the cell (Chubukov et al, 2014)
EXPERIMENTAL ASSESSMENT OF MALONYL-CoA SENSING Malonyl-CoA is an important building block from the aspect of metabolic engineering, for it is required for the biosynthesis of fatty acids, polyketides, flavonoids, and other compounds (Fowler et al, 2009; Xu et al, 2011)
Two for malonyl-CoA reductase as well as one for the acetyl-CoA carboxylase complex were expressed together with the complete pinocembrin pathway, and their efficiencies were deduced from the resulting normalized pinocembrin titers
Summary
Natural metabolic pathways are highly regulated and can adapt dynamically to changes in the levels of chemicals within and around the cell (Chubukov et al, 2014). The advantages of using natural sensors such as transcription factors to implement synthetic dynamic regulation in heterologous pathways have been demonstrated in several studies: following pioneering work on lycopene synthesis regulation (Farmer and Liao, 2000), this strategy led recently to higher yields in fatty acid synthesis with the help of fatty acids (Zhang et al, 2012) and malonyl-CoA (Xu et al, 2014; Liu et al, 2015) biosensors Such biosensor-based approaches allow the bacterial factory to artificially monitor its own level of metabolites and to modify expression levels of certain enzymes in order to balance pathway function. In vivo biosensing offers a relevant non-destructive, cost-effective, www.frontiersin.org
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