(9b) Design Principles of Compartmentalization for Engineering Enzymatic Reactions

The main goal of metabolic engineering is to increase molecular fluxes towards metabolites of interest to maximize their production [1]. One common approach to achieve this goal is to manipulate expression levels of relevant enzymes involved in the production of the target metabolites. However, it is technically nontrivial to achieve the desired alteration in gene expressions; furthermore, such manipulation could cause detrimental effects on cells’ growth and survival [1]. As an alternative, engineering methods that alter pathway fluxes without changing enzyme expression levels are more advantageous [1-5].

Among different approaches, compartmentalization of enzymatic reactions has been one of the most popular approaches, where enzymes are spatially co-localized to enhance reaction rates [1,3,6]. Specifically, it is believed that overall reaction rates are enhanced since the local enzyme concentrations are increased due to their colocalization. However, recent studies have revealed that the compartmentalization does not always lead to an increase in the reaction rate [3,7,8]. For example, it is suggested that the compartmentalization may lead to molecular crowding, which may decrease enzymes’ activities and limit the effectiveness of the strategy.

In this study, we aim to analyze the effectiveness of the compartmentalization strategy systematically by taking into account its key physics with a two-enzyme cascade system as a case study. To this end, we develop an ordinary differential equation model to compute the steady state concentration of the target metabolite with and without the compartmentalization. In this model, various physical factors are parameterized to assess their effects on the system. Specifically, the model contains the parameters capturing 1) the degree of enzyme localization, 2) the degree of changes in enzymes’ activity, 3) the effect of enzyme saturation, and 4) the mass transfer of metabolites. To capture the impact of each parameter, we derive an analytical equation that approximates the relationship between the model parameters and the effectiveness of the compartmentalization. Through this quantitative measure, we will explore general design principles of the compartmentalization for an enzyme cascade system and identify the most important physical parameters. In future, this approach will be implemented to develop quantitative measures for different metabolic network structures, such as a branch network, commonly found in in vivo metabolic pathways for optimal strategies for compartmentalization.

Reference

[1] Zhao, E.M., Suek, N., Wilson, M.Z., Dine, E., Pannucci, N.L., Gitai, Z., Avalos, J.L. and Toettcher, J.E., 2019. Light-based control of metabolic flux through assembly of synthetic organelles. Nature chemical biology, 15(6), pp.589-597.

[2] Burgard, A.P., Pharkya, P. and Maranas, C.D., 2003. Optknock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Biotechnology and bioengineering, 84(6), pp.647-657.

[3] O'Flynn, B.G. and Mittag, T., 2021. The role of liquid–liquid phase separation in regulating enzyme activity. Current Opinion in Cell Biology, 69, pp.70-79.

[4] Lin, J.L., Zhu, J. and Wheeldon, I., 2017. Synthetic protein scaffolds for biosynthetic pathway colocalization on lipid droplet membranes. ACS synthetic biology, 6(8), pp.1534-1544.

[5] Hammer, S.K., Zhang, Y. and Avalos, J.L., 2020. Mitochondrial compartmentalization confers specificity to the 2-ketoacid recursive pathway: increasing isopentanol production in Saccharomyces cerevisiae. ACS synthetic biology, 9(3), pp.546-555.

[6] Schmid-Dannert, C. and López-Gallego, F., 2019. Advances and opportunities for the design of self-sufficient and spatially organized cell-free biocatalytic systems. Current opinion in chemical biology, 49, pp.97-104.

[7] Tsitkov, S. and Hess, H., 2019. Design Principles for a Compartmentalized Enzyme Cascade Reaction. ACS Catalyst, 9, pp. 2432-2439.

[8] Davis, B.D., Aumiler, W. M., Hashemian, N., An, S., Armaou, A., and Keating, C. D., 2015. Colocalization and sequential enzyme activity in aqueous biphasic systems: experiments and modeling, Biophysical Journal, 109, pp. 2182-2194.