gcFront: a tool for determining a Pareto front of growth-coupled cell factory designs

Abstract

Motivation: A widely applicable strategy for developing evolutionarily robust cell factories is to knock out (KO) genes or reactions to couple chemical synthesis with cell growth. Genome-scale metabolic models enable their rational design, but KOs that provide growth-coupling (gc) are rare in the immense design space, making searching difficult and slow, and though several measures determine the utility of those strains, few drive the search. Results: To address these issues we developed a software tool named gcFront - using a genetic algorithm it explores KOs that maximise key performance objectives: cell growth, product synthesis, and coupling strength. Our measure of coupling strength facilitates the search, so gcFront not only finds a gc-design in minutes but also outputs many alternative Pareto optimal gc-designs from a single run - granting users freedom to select designs to take to the lab.