Quantitative Analysis of the Gene Regulatory Network Activated by Angiotensin II Type 1 Receptor in the Brainstem

The angiotensin II type 1 receptor (AT1R) in the brainstem mediates a wide range of autonomic functions, and the dysregulation of AT1R signaling causes serious diseases such as hypertension. However, the molecular mechanisms underlying AT1R function in the brain are not well- understood, and an improvement in understanding is necessary in order to develop effective treatments of hypertension. In this work, we investigate the dynamics of the AT1R activation of tyrosine hydroxylase—a critical mechanism for the central regulation of blood pressure—by taking a quantitative modeling and analysis approach.

Using the regulatory mechanisms established in the literature (Veerasingham and Raizada, 2003), we constructed a mechanistic, ordinary differential equations model for the induction of tyrosine hydroxylase gene expression modulated by the gene regulatory network activated by AT1R. Our model simulations predict that AT1R regulates tyrosine hydroxylase gene expression by activating a combination of AP-1 transcription factor dimers. Specifically, c-Fos:c-Jun is predicted to be the dominant AP-1 dimer activated during the first 40 minutes of AT1R stimulation, with c-Jun:c-Jun subsequently becoming the dominant AP-1 dimer in the long-term AP-1 response. By predicting an activation of multiple AP-1 dimers, our simulation results suggest that the AT1R induction of tyrosine hydroxylase utilizes redundant mechanisms to ensure robustness in the face of perturbations in network components. To understand how reaction mechanisms influence model output combinatorially, we performed a multivariate sensitivity analysis of the AT1R gene regulatory network (Saltelli, 2002; Hua et al., 2006). This model analysis suggests that the initial activation of AP-1 is sensitive to reactions related to c-Fos activation and c-Fos:c-Jun dephosphorylation, while the long-term activation of AP-1 is sensitive to mechanisms related to c-Jun activation. These predicted shifts in sensitive network nodes are supported by experimental data from pathway inhibitor studies. The implications of these sensitivity analysis results are that manipulating the AT1R induction of tyrosine hydroxylase gene expression would require affecting specific reaction modules at particular times. In our presentation, we will discuss the model development, present a detailed analysis, and suggest alterations in specific reaction mechanisms to manipulate AT1R network function. For instance, we will present our predictions describing how perturbations leading to increased c-Jun activation without increased FRK signaling would lead to a shift of the activated AP-1 dimers to favor c-Jun:c-Jun. Such quantitative insights into the dynamics of key molecular mechanisms underlying blood pressure control mechanisms as these could provide new targets for developing effective treatments of hypertension.

References

Hua F., Hautaniemi S., Yokoo, R., Lauffenburger D.A (2006) Integrated mechanistic and data-driven modeling for multivariate analysis of signaling pathways. J. R. Soc. Interface. 3(9): 515:26.

Saltelli, A. (2002) Making best use of model evaluations to compute sensitivity indices. Comp. Phys. Comm. 145, 280-297.

Veerasingham S.J. & Raizada M.K. (2003) Brain renin–angiotensin system dysfunction in hypertension: recent advances and perspectives. Br. J. Pharmacol. 139(2):191-202.