Figure 1. Oleochemical biosynthesis in E. coli . The fatty acid synthase (FAS) ofE. coli (orange) can supply precursors for a broad set of oleochemicals. Engineered pathways tend to exploit either (i) acyl-ACPs, which are important intermediates in fatty acid synthesis, or (ii) free fatty acids, which are released by thioesterase-catalyzed hydrolysis of acyl-ACPs. This study focuses on a subset of oleochemicals (boxes) and enzymatic steps (solid lines). Colors denote enzymatic steps unique to specific products (see Nomenclature for full enzyme names). Pathways not included in this study appear as dotted lines; enzymes that are not included appear in gray.
Unfortunately, these models typically rely on fixed metabolite concentrations and steady-state assumptions that limit their ability to capture cellular dynamics. Kinetic models derived from reduced genome-scale models can reproduce some dynamic responses to cellular perturbations (e.g., a glucose spike; (van Rosmalen et al., 2021; Stanford et al., 2013)). These models, however, typically lack the resolution required to predict how experimentally relevant changes in the concentrations, kinetics, or substrate specificities of multiple enzymes affect the outputs of complex metabolic processes.
In recent work, we developed a mechanistic kinetic model of the type II FAS of E. coli and used it to determine how different FAS components work together to control fatty acid synthesis. Type II FASs, which consist of discrete monofunctional subunits, are common in bacteria and plant plastids. We modeled the E. coli FAS as a well-mixed reaction with fixed enzyme concentrations, a constraint supported by the tendency of engineered strains to overproduce free fatty acids in stationary phase (Cho and Cronan, 1995). Our model explained a variety of perplexing results from the literature (e.g., the inhibitory effects of enzyme overexpression) and provided new strategies for engineering FAS systems. Recently, we used it to explore the effects of enzyme concentration on fatty acid synthesis. Using our model alongside in vitro and in vivo experiments, we showed that simple changes in enzyme concentration can enhance the titers of specific chain lengths by as much as 125-fold (Mains et al., 2022). Our analysis illustrates how kinetic models can guide metabolic engineering.
In this study, we expanded our kinetic model by adding pathways for a diverse set of oleochemicals. These pathways pose a challenge because they include enzymes that are poorly characterized, relative to FAS components. In adding them, we focused on three goals: (i) to develop a framework for incorporating new biosynthetic steps, including those catalyzed by poorly characterized enzymes, (ii) to identify the most influential steps within each pathway, and (iii) to build a graphical user interface (gui) that facilitates model implementation. With these tasks, we sought to build a versatile set of tools for designing oleochemical-producing microbes.