Computational Modelling and Biochemical Experimentation Show Novel Regulatory Network Controlling P53 Expression in Response to Genotoxic Stress

Parasar, Bibudha (2015) Computational Modelling and Biochemical Experimentation Show Novel Regulatory Network Controlling P53 Expression in Response to Genotoxic Stress. Masters thesis, Indian Institute of Science Education and Research Kolkata.

PDF (MS dissertation of Bibudha Parasar (10MS16)) Bibudha_Parasar-10MS16-MS_thesis.pdf - Submitted Version Restricted to Repository staff only Download (2MB)

Abstract

The tumor suppressor protein p⁵³ plays a crucial role in mediating cell cycle arrest and apoptosis in response to genotoxic stress. p⁵³ expression is regulated at multiple molecular levels and disruption of these regulatory mechanisms leads to altered expression of p53 and tumorigenesis. In order to elucidate the regulatory network that controls p⁵³ expression in response to DNA damage, we have adopted a novel approach combining dynamic systems modelling and experimental validation. Starting with the minimal model of the p⁵³-mdm2 negative feedback oscillatory system, we have added nodes (molecules) and edges (interactions), gradually building up the model in concurrence with experimental observations. The RNA-binding protein HuR is known to activate p⁵³ mRNA translation in response to UV irradiation. We have found that both p⁵³ and HuR show an oscillatory pattern of expression after UV irradiation. However, computational modelling of the HuR-p⁵³-Mdm2 network showed an expression pattern different from that obtained experimentally. Further dynamic modelling that fitted the experimental observations suggested the presence of a translation inhibitor and degradation inducer of HuR. We have found that a microRNA miR-125b, a known translation inhibitor of p⁵³, is induced by UV and represses the translation of HuR. Also, UV irradiation significantly enhanced the proteasomal degradation of HuR, thereby suggesting the activation of an E3 ubiquitin ligase. Together these observations have provided the basis of a novel approach consisting of computational modelling and biochemical experimentation which has allowed the discovery of an intricate regulatory network controlling p⁵³ expression in response to genotoxic stress.

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