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Computational Modeling of Transforming Growth Factor-β2 Receptor Complex Assembly

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

<p> </p>

<p> 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.</p>

<p> 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). </p>

<p> 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. </p>

<p> 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.</p>

  1. 10.25394/pgs.11317454.v1
Identiferoai:union.ndltd.org:purdue.edu/oai:figshare.com:article/11317454
Date04 December 2019
CreatorsMichelle N Ingle (8081288)
Source SetsPurdue University
Detected LanguageEnglish
TypeText, Thesis
RightsCC BY 4.0
Relationhttps://figshare.com/articles/Computational_Modeling_of_Transforming_Growth_Factor-_2_Receptor_Complex_Assembly/11317454

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