The long term goal of the proposed project is to define the development of signaling networks that induce differentiation of cells into mature salivary serous acinar cells to allow gene therapy approaches to regenerating or replacing salivary tissue in patients. Millions of patients suffer loss of salivary gland function due to Sj""""""""gren's syndrome or radiation therapy. Understanding the differentiation of salivary cells is a necessary step to enable the restoration of diseased or destroyed parotid salivary tissue. Previous work has described terminal differentiation of acinar cells histologically, and by characterizing the expression of markers of differentiation, but has not used genomics-level approaches, or mathematical models, to define regulatory pathways. The primary goal of the current application is to develop formal mathematical and statistical models that will identify networks which cause terminal differentiation of parotid acinar cells. The dynamic mathematical models will serve to generate hypotheses which will be tested, and the model will be repeatedly refined by the incorporation of new data. This application is in response to the RFA """"""""A Systems Approach to Salivary Gland Biology."""""""" Our overall hypothesis for these studies is that a mathematical model can identify key regulatory pathways that control parotid acinar cell differentiation.
Specific Aim 1 will use Laser Capture Microdissection (LCM) to obtain RNA from embryonic and newborn rat parotid acinar cells for microarray analysis of the patterns of gene expression across the period of differentiation. A coupled Ordinary Differential Equation (ODE) model will be created to describe the hypothetical interactions that direct the process of differentiation. The hypotheses will be tested, and the ODE model refined, by a combination of RT-PCR, IHC, and Western blots. Since microRNAs are important regulators of development, Specific Aim 2 will define the expression of microRNAs in acinar cells, and the pattern of changes during differentiation. There are currently no publications describing microRNAs in the parotid tissue. The results will be used to revise the mathematical model of differentiation.
Specific Aim 3 will create a statistical algorithm to validate and revise the ODE model by defining the sources of bias and variation as well as by assessing the model's predictive power overall, and in its various sub-modules. This will allow confidence intervals to be associated with different pathways within the ODE model.
Specific Aim 4 will use the ODE model to make hypotheses about specific pathways regulating gene expression in the parotid acinar cells. These hypotheses will be tested by transfection and transduction experiments, and the results shall be used to refine and validate the mathematical model. This systems biology approach should identify molecular pathways that drive cytodifferentiation of parotid acinar cells. Project Narrative: The overall goal of this research is to define the molecular mechanisms which control differentiation of cells into secretory salivary acinar cells. This addresses the needs of millions of Americans who suffer from salivary gland dysfunction due to Sj""""""""gren's Syndrome, radiation therapy, or xerostomia due to essential medications. This research is a necessary foundation for developing new technologies such as gene transfer therapy and biologics for treating or alleviating the oral symptoms of xerostomia.

Agency
National Institute of Health (NIH)
Institute
National Institute of Dental & Craniofacial Research (NIDCR)
Type
Research Project (R01)
Project #
5R01DE019243-03
Application #
7848326
Study Section
Special Emphasis Panel (ZDE1-RW (17))
Program Officer
Burgoon, Penny W
Project Start
2008-09-16
Project End
2013-05-31
Budget Start
2010-06-01
Budget End
2011-05-31
Support Year
3
Fiscal Year
2010
Total Cost
$366,460
Indirect Cost
Name
University of Louisville
Department
Dentistry
Type
Schools of Dentistry
DUNS #
057588857
City
Louisville
State
KY
Country
United States
Zip Code
40292
Llorens, M Candelaria; Lorenzatti, Guadalupe; Cavallo, Natalia L et al. (2016) Phosphorylation Regulates Functions of ZEB1 Transcription Factor. J Cell Physiol 231:2205-17
Metzler, Melissa A; Appana, Savitri; Brock, Guy N et al. (2015) Use of multiple time points to model parotid differentiation. Genom Data 5:82-8
Metzler, Melissa A; Venkatesh, Srirangapatnam G; Lakshmanan, Jaganathan et al. (2015) A systems biology approach identifies a regulatory network in parotid acinar cell terminal differentiation. PLoS One 10:e0125153
Kim, Jaejik; Li, Jiaxu; Venkatesh, Srirangapatnam G et al. (2013) Model discrimination in dynamic molecular systems: application to parotid de-differentiation network. J Comput Biol 20:524-39
Wang, Minghu; Li, Jiaxu; Lim, Gareth E et al. (2013) Is dynamic autocrine insulin signaling possible? A mathematical model predicts picomolar concentrations of extracellular monomeric insulin within human pancreatic islets. PLoS One 8:e64860
Rempala, Grzegorz A; Yang, Yuhong (2013) On Permutation Procedures for Strong Control in Multiple Testing with Gene Expression Data. Stat Interface 6:
Craciun, Gheorghe; Kim, Jaejik; Pantea, Casian et al. (2013) Statistical Model for Biochemical Network Inference. Commun Stat Simul Comput 42:121-137
Choi, Boseung; Rempala, Grzegorz A (2012) Inference for discretely observed stochastic kinetic networks with applications to epidemic modeling. Biostatistics 13:153-65
Li, Jiaxu; Wang, Minghu; De Gaetano, Andrea et al. (2012) The range of time delay and the global stability of the equilibrium for an IVGTT model. Math Biosci 235:128-37
Ohashi, Shinya; Natsuizaka, Mitsuteru; Naganuma, Seiji et al. (2011) A NOTCH3-mediated squamous cell differentiation program limits expansion of EMT-competent cells that express the ZEB transcription factors. Cancer Res 71:6836-47

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