Growth balance analysis models of cyanobacteria for understanding resource allocation strategies

Abstract

Cyanobacteria have emerged as attractive microbial cell factories, as they can convert atmospheric CO2 and sunlight into valuable chemicals. To increase their growth and productivity, one should aim to optimize the allocation of limited cellular resources across different metabolic processes. Here, we developed two growth balance analysis (GBA) models for the cyanobacterium Synechocystis sp. PCC 6803. In its biological assumptions, the models closely related to an existing coarse-grained model, while its mathematical formulation is heavily streamlined. We show that the GBA models provide virtually identical predictions about cellular resource allocation among photosynthesis, carbon metabolism, and the protein translation machinery under different environmental conditions as the previous, mathematically more involved model. Our model also captures the effects of photodamage on proteome allocation and the resulting growth rates. We further show how the GBA model can be easily extended to include more reactions, leading to a second GBA model capable of new predictions about the cellular resource allocation. Balanced growth models of the type presented here can easily expanded to include more biological details, providing a useful toolbox for the understanding of the physiological capabilities of cyanobacteria, their allocation of cellular resources, and the potential of their bioengineering for optimized biomass production.