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Type I modular polyketide synthases (PKSs) are polymerases that utilize acyl-CoAs as substrates. Each polyketide elongation reaction is catalyzed by a set of protein domains called a module. Each module usually contains an acyltransferase (AT) domain, which determines the specific acyl-CoA incorporated into each condensation reaction. Although a successful exchange of individual AT domains can lead to the biosynthesis of a large variety of novel compounds, hybrid PKS modules often show significantly decreased activities. Using monomodular PKSs as models, we have systematically analyzed the segments of AT domains and associated linkers in AT exchanges in vitro and have identified the boundaries within a module that can be used to exchange AT domains while maintaining protein stability and enzyme activity. Importantly, the optimized domain boundary is highly conserved, which facilitates AT domain replacements in most type I PKS modules. To further demonstrate the utility of the optimized AT domain boundary, we have constructed hybrid PKSs to produce industrially important short-chain ketones. Our in vitro and in vivo analysis demonstrated production of predicted ketones without significant loss of activities of the hybrid enzymes. These results greatly enhance the mechanistic understanding of PKS modules and prove the benefit of using engineered PKSs as a synthetic biology tool for chemical production.

The Design–Build–Test–Learn (DBTL) cycle, facilitated by exponentially improving capabilities in synthetic biology, is an increasingly adopted metabolic engineering framework that represents a more systematic and efficient approach to strain development than historical efforts in biofuels and biobased products. Here, we report on implementation of two DBTL cycles to optimize 1-dodecanol production from glucose using 60 engineered Escherichia coli MG1655 strains. The first DBTL cycle employed a simple strategy to learn efficiently from a relatively small number of strains (36), wherein only the choice of ribosome-binding sites and an acyl-ACP/acyl-CoA reductase were modulated in a single pathway operon including genes encoding a thioesterase (UcFatB1), an acyl-ACP/acyl-CoA reductase (Maqu_2507, Maqu_2220, or Acr1), and an acyl-CoA synthetase (FadD). Measured variables included concentrations of dodecanol and all proteins in the engineered pathway. We used the data produced in the first DBTL cycle to train several machine-learning algorithms and to suggest protein profiles for the second DBTL cycle that would increase production. These strategies resulted in a 21% increase in dodecanol titer in Cycle 2 (up to 0.83 g/L, which is more than 6-fold greater than previously reported batch values for minimal medium). Beyond specific lessons learned about optimizing dodecanol titer in E. coli, this study had findings of broader relevance across synthetic biology applications, such as the importance of sequencing checks on plasmids in production strains as well as in cloning strains, and the critical need for more accurate protein expression predictive tools.