Physiogenomic Study of LLC-PK1 Renal Tubular Epithelial Cells against Natriuretic Peptides

• Main Authors: Rosa Huang Lin, 劉黃惠珠
• Other Authors: Lee, Tsung-Han
• Format: Others
• Language: en_US
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/00959608668897833353

博士 === 中興大學 === 生命科學系所 === 95 === Natriuretic peptides (NPs) are natural antagonists to the endocrine system, and they serve important roles in regulating blood volume and pressure, muscle hypertrophy, pulmonary hypertension, fat metabolism, and long bone growth. Although the physiologic actions of NPs in humans have been elucidated, the influence of NPs upon the mechanism of gene regulation in the renal system is not fully understood. This study aims to investigate the biological effect of NPs on gene expression profiling in LLC-PK1 renal tubular epithelial cells, and their influence on the mechanism of gene regulation in the renal system. Using DNA microarray analysis, the gene expression profile of atrial natriuretic peptide (ANP) treated LLC-PK1 cells provided 807 differentially expressed genes, containing 483 up-regulated genes and 324 down-regulated genes. In another model, the gene expression profile of C-type natiuretic peptide (CNP) treated LLC-PK1 cells provided 613 differentially expressed genes, containing 312 up-regulated genes and 301 down-regulated genes. The gene ontology of all differentially expressed genes could be classified according to cellular component, molecular function and biological process, which are useful information for functional gene categorization. Interestingly, four ANP-responsive genes (ATP1B1, H3F3A, ITGB1 and RHO) and nine CNP-responsive genes (ANKRD17, CD1A, CKS2, HSPCA, ITGB1, TMEPA1, TRA2A, ZF and ZNF265) were up-regulated genes while only two CNP-responsive genes (NRAS and NRN1) were down-regulated genes. In both ANP and CNP treated models, all of the responsive genes may contribute to alleviation of progressive renal hypertrophy. Based on the observed pathophysiologic correlations under these models, gene expression profiling may become useful differential markers for future diagnostic and therapeutic applications in renal failure or other related diseases.