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

9Citations
Citations of this article
19Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Motivation: A widely applicable strategy to create cell factories is to knockout (KO) genes or reactions to redirect cell metabolism so that chemical synthesis is made obligatory when the cell grows at its maximum rate. Synthesis is thus growth-coupled, and the stronger the coupling the more deleterious any impediments in synthesis are to cell growth, making high producer phenotypes evolutionarily robust. Additionally, we desire that these strains grow and synthesize at high rates. Genome-scale metabolic models can be used to explore and identify KOs that growthcouple synthesis, but these are rare in an immense design space, making the search difficult and slow. Results: To address this multi-objective optimization problem, we developed a software tool named gcFront-using a genetic algorithm it explores KOs that maximize cell growth, product synthesis and coupling strength. Moreover, our measure of coupling strength facilitates the search so that gcFront not only finds a growth-coupled design in minutes but also outputs many alternative Pareto optimal designs from a single run-granting users flexibility in selecting designs to take to the lab.

Cite

CITATION STYLE

APA

Legon, L., Corre, C., Bates, D. G., & Mannan, A. A. (2022). gcFront: a tool for determining a Pareto front of growth-coupled cell factory designs. Bioinformatics, 38(14), 3657–3659. https://doi.org/10.1093/bioinformatics/btac376

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free