Gene Ontology and Biological Networks Analysis in Primary Normal Human Epidermal Keratinocytes (NHEK) Treated by Resveratrol

Gene Ontology and Biological Networks Analysis in Primary Normal Human Epidermal Keratinocytes (NHEK) Treated by Resveratrol
Farshad Qalekhani,^1,* Mahnaz Ghowsi,² Fahimeh Haghshenas,³
1. Pharmaceutical Sciences Research Center, Health Institute, Kermanshah University of Medical Sciences (KUMS), Kermanshah, Iran
2. Pharmaceutical Sciences Research Center, Health Institute, Kermanshah University of Medical Sciences (KUMS), Kermanshah, Iran
3. Biology Department, Razi University, Kermanshah, Iran
Introduction: Resveratrol is a plant polyphenol found in high concentrations in red grapes that has been proposed as a treatment for hyperlipidemia and to prevent fatty liver, diabetes, atherosclerosis, inflammation and aging. Resveratrol use has not been associated with serum enzyme elevations or with clinically apparent liver injury [1]. The fact that resveratrol is found in the skin of red grapes and as a constituent of red wine may explain the "French paradox". This paradox is based on the observation that the incidence of coronary heart disease is relatively low in southern France despite high dietary intake of saturated fats [2]. Resveratrol is a natural product that has gained tremendous interest due to multiple reported health-beneficial effects. However, the underlying mechanisms of its actions remained largely controversial. Major biological effects of resveratrol might be attributed to its bicarbonate-induced production of phenolic radicals and reactive oxygen species (ROS) such as superoxide and hydrogen peroxide under physiologically relevant conditions. Resveratrol treatment led to mild, Nrf2-specific gene expression reprogramming [3]. Here, we have analyzed transcriptome data produced by Annabell Plauth and colleagues, and by using system biology approaches, we examined gene ontology and networks analysis effect of resveratrol in primary normal human epidermal keratinocytes (NHEK).
Methods: We have used a microarray data (GEO accession number: GSE72119) that includes samples of Resveratol (RSV) versus control samples. First all, the data quality control was checked using boxplot, heatmap and principal component (PC) analysis. To obtain DEGs (Differentially Expressed Genes) between control and RSV, the Limma package was used, which is embedded in the R programming language. We have discarded all DEGs with adjusted P-value >0.05 and log 2 FC between ±1. We have used the Enrichr database to annotate DEGs. To build the gene network interaction, we entered the DEGs into the GeneMANIA server and the Protein-Protein Interaction network (PPI) was created with the STRING server. Finally, the transcription factors (TFs) and protein kinases (PTKs) were re-examined using the X2K web server.
Results: According to the boxplot, samples haves a median center, also PC analysis and heatmap confirmed that the dataset had a high quality. Microarray samples of RSV and controls were compared to identify DEGs. We detected the 1514 number of DEGs in the comparison between RSV and control. The DEGs were submitted to Enrichr database to identify genes related to annotations including Cellular Component, biological process, and molecular function. Gene network interaction and protein-protein interaction network were calculated and constructed. Important transcription factors include: MYC, E2F1, SIN3A, E2F4, MAX, FOXM1, NFYA, NFYB and E2F6. Important protein kinases include: MAPK14, CDC2, CK2ALPHA and CDK4.
Conclusion: The gene expression profile of normal human epidermal keratinocytes was strongly changed by the treatment with 50µM concentration of Resveratrol. We predicted potentially important transcription factors and Protein kinases in gene regulatory networks. We have provided a list of possible new key regulators that could be further explored and also identified the role of hub proteins. The results of this study would be useful to develop new drug development.
Keywords: GeneMANIA, Microarray, NHEK, STRING, System Biology.