Design principles for engineering bacteria to maximise chemical production from batch cultures

Abstract

Bacteria can be engineered to manufacture chemicals, but it is unclear how to optimally engineer a single cell to maximise production performance from batch cultures. Moreover, the performance of engineered production pathways is affected by competition for the host's native resources. Here, using a 'host-aware' computational framework which captures competition for both metabolic and gene expression resources, we uncover design principles for engineering the expression of host and production enzymes at the cell level which maximise volumetric productivity and yield from batch cultures. However, this does not break the fundamental growth-synthesis trade-off which limits production performance. We show that engineering genetic circuits to switch cells to a high synthesis-low growth state after first growing to a large population can further improve performance. By analysing different circuit topologies, we show that highest performance is achieved by circuits that inhibit host metabolism to redirect it to product synthesis. Our results should facilitate construction of microbial cell factories with high and efficient production capabilities.

Fig. 1. Selecting single strains with lower growth but higher synthesis can maximise productivity and yields from the culture.

a Green-to-yellow crosses show the Pareto front from maximising synthesis and growth rates of the single cell. The calculated productivity and yields of these optimal designs are shown by the green-to-yellow crosses in (b). Schematic (top) highlights the three enzyme transcription rates explored over for engineering the production strain, and the cell production metrics. b Red-to-yellow dots show the Pareto front from maximising productivity and yield from a batch culture. The calculated synthesis and growth rates of these optimal designs are shown by the red-to-yellow dots in (a). Schematic (top) illustrates culture-level production metrics. c Time-course simulation of batch culture of three designs selected from fronts in (a) and (b), spanning designs with high synthesis-low growth to high growth-low synthesis. d, e Plots of the optimal scaling on transcription rates of each of the Pareto optimal 'designs' when maximising on synthesis and growth (d) or volumetric productivity and yield (e).

Fig. 2. Pareto front of optimal dynamic control circuits.

a Pareto fronts of optimal designs for each circuit topology shown. Schematics indicate the circuit topology of the dynamic control by TF and the dials indicate the enzymes whose constitutive expression was tuned. b Scatter plots of optimal values of three key parameters which suggest tuning to increase or decrease their values will shift circuit performance to achieve higher productivity but at a cost to yield, or higher yields at a cost to productivity.

Fig. 3. Pareto front and optimal designs for engineering the control on expression of the substrate transporter T to maximise productivity and yield.

a Pareto fronts of optimal designs for the bifunctional controller circuit extended to control expression of the substrate transporter T (yellow or blue arrows) or constitutively tune T expression (red tuning dial). Gray dashed curve shows Pareto front of optimal designs before also tuning the expression or control of T. b Scatter plots of the Pareto optimal values of two key parameters of the circuit with highest performance, which suggests to increase constitutive expression of the substrate and product transporters 2-fold, compared to no tuning (dashed vertical lines). c Pareto optimal values of the parameter scaling the transcription rate of host enzyme E for the circuit with highest performance.

Fig. 4. Top performing dynamic control circuits for when the product of interest directly drains translation precursors.

a Pareto fronts of the top six performing dynamic control circuits. Their Pareto fronts are overlapping. b Pareto fronts of the circuit in which TF de-represses expression of pathway enzymes after induction and TF is constitutively expressed, is extended to control expression of nutrient transporter T.