Abstract Genetic manipulation of cells to couple byproduct production and growth rate is important in bioengineering and biotechnology. In this way, we can use growth rate as a selective pressure, where the mutants with higher growth have higher production capacity. Computational methods have been proposed to find knockouts that couple growth and byproduct production. However, none of these methods consider the energetic and thermodynamic feasibility of such knockout strategies. Furthermore, there is no computational study of how variations in metabolite concentrations affect the coupling between growth and byproduct formation. One of the computational methods to find knockouts that couple growth and byproduct formation is OptKnock. OptKnock is a bi-level optimization problem. Here, we integrated thermodynamic constraints into the bilevel formulation of OptKnock to create TOptKnock. We show that the computational efficiency of TOptKnock is comparable to that of OptKnock. TOptKnock can account for the thermodynamic viability of the knockouts and examine how variations in metabolite concentrations affect the coupling. We have shown that the coupling between growth and byproduct formation can change in response to variations in concentrations. Thus, a knockout strategy might be optimal for one intracellular condition but suboptimal for another. If metabolomics data are available, TOptKnock can search for optimal knockout interventions under the given condition. We also envision that the TOptKnock framework will help develop strategies for manipulating metabolite concentrations to couple growth and byproduct formation.

Thermodynamics determines the coupling between growth and byproduct production