Computational Modeling of Transforming Growth Factor-β2 Receptor Complex Assembly

2019-12-04T20:52:00Z (GMT) by Michelle N Ingle

Michelle N. Ingle. M.S., Purdue University, December 2019. Computational Modeling of Transforming Growth Factor-β2 Receptor Complex Assembly. Major Professor: David M. Umulis.

Transforming growth factor (TGF)-β1, TGF-β2, and TGF-β3 are secreted signaling proteins that play an essential role in tissue development, immune response, and physiological homeostasis. TGF-β ligands signal through a tetrameric complex made up of two type I receptors (TβRI) and two type II receptors (TβRII). Dysregulation of TGF-β signaling has been linked to uncontrolled cell proliferation and cancer metastasis. An accurate understanding of TGF-β’s receptor complex assembly pathway may allow for pharmacological intervention and/or preservation of proper TGF-β signaling.

Amongst the ligand types, TGF-β1 and TGF-β3 are efficient signalers, presumably by strong binding to both type I and II receptors. However, TGF-β2 has a very weak affinity for TβRII and requires an additional membrane-bound protein called betaglycan (BG) to achieve similar levels of downstream signaling. While computational modeling has been performed on the signaling pathway of the TGF-β system, to date no computational modeling has aimed to decipher BG’s role in the potentiation of TGF-β2 signal. To determine the role of BG in selectively facilitating signaling by TGF-β2, we developed computational models with different assumptions based on the levels of cooperativity between receptor subtypes and types of BG behavior (No Receptor Recruitment model, Single-stage Receptor Recruitment model, and Two-stage Receptor Recruitment model).

With each of the receptor recruitment models we hypothesized that BG uses two domains to successfully enhance TGF-β2 signaling. This model was first proposed in Villarreal et al., 2016 and is further investigated in this work using a two-step computational approach. First, a root mean square error (RMSE) calculation was performed between our computational models with no BG present and published experimental signaling data in cell lines with no BG present. Lower RMSE values indicate the simulated data is more representative of experimental signaling behavior when no BG is present. The second round of model validation was performed by adding BG into the simulations and comparing its behavior to experimentally determined and hypothesized behaviors of BG.

In summary, the simulations indicate there may be more cooperative receptor recruitment present in the system then stated in literature. Furthermore, it appears that BG binding to TGF-β2 ligand through two domains provides an effective transfer mechanism that can be tuned to control differential signaling between TGF-β ligand subtypes. Experiments were then suggested in order to support or refute one of the models offered in this thesis. For the purpose of uncovering how BG enhances TGF-β2 signaling, the computational work performed in this thesis highlights the areas where researchers should focus their experimental efforts and provides a baseline model for further computational work in the TGF-β system.