THE PENNSYLVANIA STATE UNIVERSITY SCHREYER HONORS COLLEGE DEPARTMENT OF BIOCHEMISTRY AND MOLECULAR BIOLOGY A SYSTEMATIC METHOD FOR ANALYZING STIMULUS-DEPENDENT ACTIVATION OF THE p53 TRANSCRIPTION NETWORK SARAH L. MOORE SPRING 2013 A thesis submitted in partial fulfillment of the requirements for a baccalaureate degree in Biochemistry and Molecular Biology with honors in Biochemistry and Molecular Biology Reviewed and approved* by the following: Dr. Yanming Wang Associate Professor of Biochemistry and Molecular Biology Thesis Supervisor Dr. Ming Tien Professor of Biochemistry and Molecular Biology Honors Advisor Dr. Scott Selleck Professor and Head, Department of Biochemistry and Molecular Biology * Signatures are on file in the Schreyer Honors College. i ABSTRACT The p53 protein responds to cellular stress, like DNA damage and nutrient depravation, by activating cell-cycle arrest, initiating apoptosis, or triggering autophagy (i.e., self eating). p53 also regulates a range of physiological functions, such as immune and inflammatory responses, metabolism, and cell motility. These diverse roles create the need for developing systematic methods to analyze which p53 pathways will be triggered or inhibited under certain conditions. To determine the expression patterns of p53 modifiers and target genes in response to various stresses, an extensive literature review was conducted to compile a quantitative reverse transcription polymerase chain reaction (qRT-PCR) primer library consisting of 350 genes involved in apoptosis, immune and inflammatory responses, metabolism, cell cycle control, autophagy, motility, DNA repair, and differentiation as part of the p53 network. Using this library, qRT-PCR was performed in cells with inducible p53 over-expression, DNA-damage, cancer drug treatment, serum starvation, and serum stimulation. Heat-map and statistical analyses of these data, organized by cellular pathways or chromosome locations, have yielded insight into the complex response of the p53 network. Ultimately, the expression patterns of these p53-related genes will provide knowledge of cellular decision making mechanisms and allow researchers to evaluate the effect of particular drugs on the p53 pathways. A compilation of this data and analysis can be found at: https://protected.personal.psu.edu/s/l/slm5430/zoombablue/Home.html ii TABLE OF CONTENTS List of Figures………………………………………………………………………………… iii List of Tables…………………………………………………………………………………. iv Acknowledgements…………………………………………………………………………… v Chapter 1: The p53 Network .………………………………………………………………… 1 1.1 - NFκB Immune and Inflammatory Responses ……………………………............... 1 1.2- Apoptosis ………………………………………………………………..………….. 3 1.3- Cell Structure and Motility ....…………………… ………………………................ 4 1.4- Autophagy ……………………………………………........................…………….. 4 1.5- Cell Growth and Proliferation ………………………………………….…………… 5 1.6- Metabolism and Oxidative Stress ………………………………………...………… 6 1.7- DNA Repair ………………………………………………………………………… 7 1.8- Differentiation ……………………………………………………………………… 8 1.9- Upstream Regulation ………………………………………….................................. 9 Chapter 2: Materials and Methods …………………………………………………………… 10 2.1- Gene Selection ……………………………………………………………………… 10 2.2- Primer Design ………………………………………………………………………. 10 2.3- Gene Mapping ………………………………………………………………………. 11 2.4- Cell Culturing and Drug Treatment ………………………………………………… 12 2.5- RNA Collection and Reverse Transcription ……………………………………….. 12 2.6- q-RT PCR ...………………………………………………………………………… 13 Chapter 3: Results ……………………………………………………………………………. 14 3.1- The Gene Set ………………………………………………………………………… 14 3.2- Direct p53 Over-expression …………………………………………………………. 14 3.3- Doxorubicin treatment ………………………………………………………………. 16 3.4- Serum Starvation ……………………………………………………………………. 18 3.5- Serum Stimulation ……………………………………………………………………20 3.6- Testing the cancer drug 6e ………………………………………………………….. 21 Chapter 4: Discussion ………………………………………………………………………… 23 References……………………………………………………………………………………. 49 iii List of Figures Figure 1- The p53 protein responds to a battery of cellular pathways in response to various upstream signals…………………………………………………………………… 24 Figure 2- qRT-PCR data from six treatment conditions reveals context-dependent impact on each of the p53 pathways……………………………………………………………….. 25 Figure 3- p53 over-expression results in pathway trends of activation or inhibition……… 26 Figure 4- Doxorubicin treatment affects the p53 network differently than direct p53 over- expression………………………………………………………………………………….. 27 Figure 5- Numerous NFκB functions are repressed by p53 over-expression but not Doxorubicin treatment……………………………………………………………………... 28 Figure 6: Serum Starvation affects cell metabolism……………………………………….. 29 Figure 7: Serum stimulation rescues starved cells…………………………………………. 30 Figure 8: Analysis of 6e drug treatment allows prediction of the drug mechanism of action……………………………………………………………………………………….. 31 iv List of Tables Table 1- The p53 gene library responds uniquely to different stimuli…………………….. 32 Table 2- qRT-PCR Primers………………………………………………………………… 41 v Acknowledgements I would like to thank Dr. Wang for all of the support, guidance, and great ideas he has provided in this endeavor. I would also like to thank the graduate students in the lab, Jing Hu, Shu Wang, Amy Chen, and Jinquan Sun for their support and assistance in learning lab protocols. This project was funded by a 2012 Undergraduate Summer Discovery Grant, the Eberly College of Science, and the Penn State Biochemistry Department Whitfield Award. 1 Chapter 1 The p53 Network The p53 protein, commonly referred to as “The Guardian of the Genome,” is a stress- activated tumor suppressor widely known to be one of the most commonly mutated genes in human cancer. As such, extensive research has been conducted to determine the role of the protein, which has revealed downstream targets implicated in numerous cell pathways, including the immune and inflammatory response, apoptosis, cell motility, autophagy, cell cycle arrest, metabolism and oxidative stress, DNA repair, and differentiation (Figure 1). Furthermore, numerous mechanisms that regulate p53 function have been identified, including ubiquitination by the MDM2 protein [1], phosphorylation by ATR [2], and methylation by the lysine methyltransferase Set9 [3]. Acetylation of the p53 protein by KAT5 has been shown to play a role in regulating whether p53 activation induces apoptosis or cell cycle arrest [4]. However, further understanding of the role of p53 in cell-fate decision making mechanisms is needed to develop therapeutic targets for cancer and disease treatment. Information regarding how specific p53 pathways, as well as individual genes within the pathways, are affected by particular cellular stresses will be useful for gaining further insight into p53 function, aid in drug testing and design, and may ultimately provide a starting point for determining genes involved in cross-talk between the pathways. 1.1: NFκB Immune and Inflammatory Response NFκB is a transcription factor constitutively present in the cytoplasm in an inactive form [5]. While there are seven NFκB-family proteins, the heterodimer comprised of p50 (encoded by NFκB1) and RELA is the most prevalent [6]. NFκB activation, triggered as part of an immune 2 response to viral particles and pathogen associated molecular patterns (PAMPs) such as lipopolysaccharide, results in migration of the transcription factor into the nucleus where it stimulates production of cytokines and chemokines central to inflammation [5]. This in turn results in propagation of the immune response. Beyond its role in the immune response, NFκB has been shown to regulate apoptosis, cell proliferation, and differentiation, all of which are also implicated in p53 function [6]. Correspondingly, the NFκB and p53 DNA binding sites are extremely similar, indicating that the two transcription factors may compete [7]. NFκB has also been shown to induce p53 expression. Furthermore, increased p53 expression in a Tet-On Saos2 p53-inducible cell line results in NFκB activation, and this activation is necessary for p53-induced apoptosis [8]. However, NFκB has been implicated in both anti-apoptotic and pro-apoptotic pathways. While promoting p53- induced apoptosis, for example, NFκB inhibits TNFα-mediated cell death, despite the fact that TNFα is one of the primary activators of NFκB. In addition to a clear connection between p53 and NFκB itself, numerous genes within the NFκB immune and inflammatory pathway have also been shown to affect or be affected by p53. For example, the cytokine CCL2 has been shown to be activated by ultraviolet-radiation (UV)-induced p53 [9]. However, it is not clear if this response is consistent when p53 is activated by other stresses. TRAIL (TNFα-related apoptosis-inducing ligand) is a p53 target gene which contributes to apoptosis [10]. It is also, as its name suggests, capable of inducing apoptosis via TNFα independent of p53. Furthermore, TRAIL activation of NFκB has been identified as a mechanism for cell protection [11], possibly reflecting NFκB-mediated inhibition of TNFα- induced apoptosis. Because it is both a pro-apoptotic molecule and NFκB activator in certain 3 contexts, with conflicting results, further analysis of this gene in the context of various stresses is needed to gain an understanding of its role in these pathways. 1.2: Apoptosis The role of the p53 protein in inducing apoptosis, or programmed cell death, has long been known as one of the primary mechanisms for tumor suppression.