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.