Date of Award

2016

Document Type

Thesis

Degree Name

Bachelors

Department

Natural Sciences

First Advisor

Ryba, Tyrone

Area of Concentration

Computer Science

Abstract

Background: The Tesfaigzi laboratory has reported on the role of the variant that modifies the amino acid arginine to proline at codon 72 of P53 on affecting mucous cell differentiation. This variant modifies the regulation of Bcl-2 and SPDEF to mRNA stability and promoter activation, respectively (Tesfaigzi et al, 2015). In the present study, we wanted to expose other pathways that may be affected by the P53Arg/Pro variant. Therefore, we analyzed the gene expression data in primary human airway epithelial cells (HAECs) before and after exposure to cigarette smoke extract. Methods: Primary NHBEs were genotyped for the P53 variants using allelic discrimination. P53Pro and P53Arg cells were cultured in Bronchial Epithelial Cell Growth Medium (BEGM Lonza, Wakersville, MD) and differentiated on air-liquid interface cultures for 15-20 days. Cultures were then either left untreated or were treated twice per week with 1, 4, or 40 μg/mL cigarette smoke extract (CSE) over 10 weeks. The cigarette smoke extract was prepared by incubating cigarette smoke particulates that were collected on filters in cell culture media for one hour at 37C. RNA was isolated from the cultures using Qiagen Kits (Valencia, CA) and hybridized to Affymetrix’s GeneChip arrays to determine whole genome expression. GSEA software from the Broad Institute was used to identify a biologically significant subset of upregulated and down-regulated genes, which were then validated in similar analyses with mice using differential expression analysis. A consolidated analysis was run on the 40μg/mL exposure condition, comparing their differential expression before and after CSE exposure to identify genes that are consistently differentially expressed among human and mice samples. Results: The consolidated analysis uncovered a novel mechanism in the down-regulation of CHD2 in P53Arg cells, which implies the oxidative stress from the CSE-exposure activates the HGDF (Hepatoma-derived Growth Factor), whereas P53Pro mitigates HDGF through a checkpoint. Also of interest was the discovery of a clear distinction between HAECs that responded to CSE (which we define as having >= 200 genes differential expressed at a nominal p-value of < 0.05) and HAECs that did not respond to CSE (5 >= genes differentially expressed at a nominal p-value of p<0.05). Future work will increase the number of samples, and continue to validate the genes identified in analysis with real-time PCR.

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