Computational modelling suggests dynamic interactions between Ca2+, IP3 and G protein-coupled modules are key to robust Dictyostelium aggregation

Abstract

Under conditions of starvation, Dictyostelium cells begin a programme of development during which they aggregate to form a multicellular structure by chemotaxis, guided by propagating waves of cyclic AMP that are relayed robustly from cell to cell. In this paper, we develop and analyse a new model for the intracellular and extracellular cAMP dependent processes that regulate Dictyostelium migration. The model allows, for the first time, a quantitative analysis of the dynamic interactions between calcium, IP 3 and G protein-dependent modules that are shown to be key to the generation of robust cAMP oscillations in Dictyostelium cells. The model provides a mechanistic explanation for the transient increase in cytosolic free Ca 2+ concentration seen in recent experiments with the application of the calmodulin inhibitor calmidazolium (R24571) to Dictyostelium cells, and also allows elucidation of the effects of varying both the conductivity of stretch-activated channels and the concentration of external phosphodiesterase on the oscillatory regime of an individual cell. A rigorous analysis of the robustness of the new model shows that interactions between the different modules significantly reduce the sensitivity of the resulting cAMP oscillations to variations in the kinetics of different Dictyostelium cells, an essential requirement for the generation of the spatially and temporally synchronised chemoattractant cAMP waves that guide Dictyostelium aggregation.

Unraveling Adaptation in Eukaryotic Pathways: Lessons from Protocells

“…The concentration of cAMP is also increased through ERK2, which inhibits the phosphodiesterase (PDE) RegA, in turn hydrolyzing cAMP. This pathway is inhibited by PKA, activated by cAMP [19,45,46]. (c) Photo-transduction.…”

Validation and invalidation of systems biology models using robustness analysis

“…Interestingly, the effect of intrinsic noise was to 'enhance' the robustness of cAMP oscillations to variations between cells, whereas synchronisation of oscillations between cells via a shared pool of external cAMP also significantly improved the robustness of the system. Two further studies suggested a significant role for other subnetworks involving calcium and IP3 in generating robust oscillations [64,65]. Using a combination of structural robustness analysis [64] and biophysical modelling [65], an extended model including these subnetworks ( Fig.…”

“…Two further studies suggested a significant role for other subnetworks involving calcium and IP3 in generating robust oscillations [64,65]. Using a combination of structural robustness analysis [64] and biophysical modelling [65], an extended model including these subnetworks ( Fig. 8) was constructed which exhibited significantly higher robustness than the original model, as shown in Fig.…”

Analysis and extension of a biochemical network model using robust control theory

“…Note that, due to their almost linear dependence on other states, the variables PKA, RegA, and CAR1 in the original model have not been included as independent states in the extended model, but appear implicitly in the equations, in order to keep the complexity of the extended model within manageable levels. Owing to space limitations, we do not present here a full description of the derivation of the extended model equations given above, or of the meaning of all of the model parameters-the interested reader is referred to [20] for full details of the model and the underlying experimental results. The key point to be noticed about the extended model for our purposes is that, as shown in Figure 6(a), the newly added modules in the extended model are connected at the point of interaction between the states x 1 (ACA) and x 7 (CAR1) in the original model, i.e.…”