Gene Circuits for Self-Tuning Metabolic Pathways

Metabolic imbalances impair growth and limit the performance of engineered pathways. These imbalances arise from, for example, the accumulation of toxic intermediates, the depletion of metabolites for survival of the host, or the onset of native regulatory mechanisms that counteract pathway activity. Such limitations can be overcome with gene circuits that adapt pathway expression in response to the metabolic state of the host or changes in conditions of the bioreactor. When appropriately designed, gene circuits cause a pathway to self-tune its expression levels and match production goals with a reduced impact on the host. Recent implementations have showcased how gene circuits can improve pathway yield, yet so far we do not have quantitative procedures for the rational design of circuit architectures or their components, including e.g. the strength and sensitivity of promoters.

Here I will discuss our recent progress in the design of gene circuits for robust pathway engineering. We use a combination of mathematical modelling and computer simulations to learn how promoter design and circuit architecture shape pathway activity. We aim to obtain design guidelines to achieve pathway self-tuning, to control variability of fluxes across a culture, and to engineer novel phenotypes for large-scale multicellular circuitry. I will first show how promoter design affects a pathway’s response to perturbations and the accumulation of toxic intermediates. I will then introduce the notion of “metabolic noise”, i.e. variability caused by stochastic fluctuations in the expression of enzymes, to explain how promoter strengths can be used to control the amplification or attenuation of pathway variability across a culture. To conclude I will discuss recent results on multi-promoter architectures to implement novel metabolic responses, ultimately scaling-up the functionality of circuits that interface metabolism with the genetic machinery.

Related references

[1] Oyarzún et al., ACS Synthetic Biology, special issue “Circuits in Metabolic Engineering”, 2014.

[2] Oyarzún & Stan, Journal of the Royal Society, Interface, 10(78), 2013.