Distribution of control in the sulfur assimilation in Arabidopsis thaliana depends on environmental conditions.

Sulfur assimilation is central to the survival of plants and has been studied under different environmental conditions. Multiple studies have been published trying to determine rate-limiting or controlling steps in this pathway. However, the picture remains inconclusive with at least two different enzymes proposed to represent such rate-limiting steps. Here, we used computational modeling to gain an integrative understanding of the distribution of control in the sulfur assimilation pathway of Arabidopsis thaliana. For this purpose, we set up a new ordinary differential equation (ODE)-based, kinetic model of sulfur assimilation encompassing all biochemical reactions directly involved in this process. We fitted the model to published experimental data and produced a model ensemble to deal with parameter uncertainties. The ensemble was validated against additional published experimental data. We used the model ensemble to subsequently analyse the control pattern and robustly identified a set of processes that share the control in this pathway under standard conditions. Interestingly, the pattern of control is dynamic and not static, that is it changes with changing environmental conditions. Therefore, while adenosine-5 '-phosphosulfate reductase (APR) and sulfite reductase (SiR) share control under standard laboratory conditions, APR takes over an even more dominant role under sulfur starvation conditions.