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Long non-coding RNAs expression profile in HepG2 cells reveals the potential role of long non-coding RNAs in the cholesterol metabolism.

Liu G, Zheng X, Xu Y, Lu J, Chen J, Huang X - Chin. Med. J. (2015)

Bottom Line: Our aim was to identify important lncRNAs that might play an important role in contributing to the benefits of epigallocatechin-3-gallate (EGCG) on cholesterol metabolism.Bioinformatic analysis found five matched lncRNA-mRNA pairs for five differentially expressed lncRNAs and four differentially expressed mRNA.After AT102202 knockdown in HepG2, we observed that the level of HMGCR expression was significantly increased relative to the scrambled small interfering RNA control (P < 0.05).

View Article: PubMed Central - PubMed

Affiliation: Department of Special Medical Treatment Center, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China.

ABSTRACT

Background: Green tea has been shown to improve cholesterol metabolism in animal studies, but the molecular mechanisms underlying this function have not been fully understood. Long non-coding RNAs (lncRNAs) have recently emerged as a major class of regulatory molecules involved in a broad range of biological processes and complex diseases. Our aim was to identify important lncRNAs that might play an important role in contributing to the benefits of epigallocatechin-3-gallate (EGCG) on cholesterol metabolism.

Methods: Microarrays was used to reveal the lncRNA and mRNA profiles in green tea polyphenol(-)-epigallocatechin gallate in cultured human liver (HepG2) hepatocytes treated with EGCG and bioinformatic analyses of the predicted target genes were performed to identify lncRNA-mRNA targeting relationships. RNA interference was used to investigate the role of lncRNAs in cholesterol metabolism.

Results: The expression levels of 15 genes related to cholesterol metabolism and 285 lncRNAs were changed by EGCG treatment. Bioinformatic analysis found five matched lncRNA-mRNA pairs for five differentially expressed lncRNAs and four differentially expressed mRNA. In particular, the lncRNA AT102202 and its potential targets mRNA-3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) were identified. Using a real-time polymerase chain reaction technique, we confirmed that EGCG down-regulated mRNA expression level of the HMGCR and up-regulated expression of AT102202. After AT102202 knockdown in HepG2, we observed that the level of HMGCR expression was significantly increased relative to the scrambled small interfering RNA control (P < 0.05).

Conclusions: Our results indicated that EGCG improved cholesterol metabolism and meanwhile changed the lncRNAs expression profile in HepG2 cells. LncRNAs may play an important role in the cholesterol metabolism.

Show MeSH
Knockdown of AT102202 in HepG2 cells. The expression of AT102202 following knockdown by three different siRNA (a). And knockdown efficiency was tested following different concentrations (6, 12, and 18 nmol/L) of siRNA 124 transfection for 24 hours (b). The level of knockdown efficiency was determined by quantitative real-time PCR. Error bars indicate the standard error of the mean for 6 technical replicates and expression values are normalized to scramble siRNA controls.
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Figure 2: Knockdown of AT102202 in HepG2 cells. The expression of AT102202 following knockdown by three different siRNA (a). And knockdown efficiency was tested following different concentrations (6, 12, and 18 nmol/L) of siRNA 124 transfection for 24 hours (b). The level of knockdown efficiency was determined by quantitative real-time PCR. Error bars indicate the standard error of the mean for 6 technical replicates and expression values are normalized to scramble siRNA controls.

Mentions: To investigate the functional role of AT102202, we used siRNA to downregulate AT102202 expression in HepG2 cells. Three different siRNA molecules were tested for their knockdown efficiency, the most efficient of which (siRNA 124) was selected for subsequent functional studies [Figure 2]. To determine the optimal concentration for knockdown, several different concentrations of siRNA were examined. When these cells were transfected with 18 nmol/L of siRNA, at least 60% AT102202 silencing was observed. Therefore, subsequent functional studies were performed with a maximum of 18 nmol/L siRNA.


Long non-coding RNAs expression profile in HepG2 cells reveals the potential role of long non-coding RNAs in the cholesterol metabolism.

Liu G, Zheng X, Xu Y, Lu J, Chen J, Huang X - Chin. Med. J. (2015)

Knockdown of AT102202 in HepG2 cells. The expression of AT102202 following knockdown by three different siRNA (a). And knockdown efficiency was tested following different concentrations (6, 12, and 18 nmol/L) of siRNA 124 transfection for 24 hours (b). The level of knockdown efficiency was determined by quantitative real-time PCR. Error bars indicate the standard error of the mean for 6 technical replicates and expression values are normalized to scramble siRNA controls.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4837827&req=5

Figure 2: Knockdown of AT102202 in HepG2 cells. The expression of AT102202 following knockdown by three different siRNA (a). And knockdown efficiency was tested following different concentrations (6, 12, and 18 nmol/L) of siRNA 124 transfection for 24 hours (b). The level of knockdown efficiency was determined by quantitative real-time PCR. Error bars indicate the standard error of the mean for 6 technical replicates and expression values are normalized to scramble siRNA controls.
Mentions: To investigate the functional role of AT102202, we used siRNA to downregulate AT102202 expression in HepG2 cells. Three different siRNA molecules were tested for their knockdown efficiency, the most efficient of which (siRNA 124) was selected for subsequent functional studies [Figure 2]. To determine the optimal concentration for knockdown, several different concentrations of siRNA were examined. When these cells were transfected with 18 nmol/L of siRNA, at least 60% AT102202 silencing was observed. Therefore, subsequent functional studies were performed with a maximum of 18 nmol/L siRNA.

Bottom Line: Our aim was to identify important lncRNAs that might play an important role in contributing to the benefits of epigallocatechin-3-gallate (EGCG) on cholesterol metabolism.Bioinformatic analysis found five matched lncRNA-mRNA pairs for five differentially expressed lncRNAs and four differentially expressed mRNA.After AT102202 knockdown in HepG2, we observed that the level of HMGCR expression was significantly increased relative to the scrambled small interfering RNA control (P < 0.05).

View Article: PubMed Central - PubMed

Affiliation: Department of Special Medical Treatment Center, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China.

ABSTRACT

Background: Green tea has been shown to improve cholesterol metabolism in animal studies, but the molecular mechanisms underlying this function have not been fully understood. Long non-coding RNAs (lncRNAs) have recently emerged as a major class of regulatory molecules involved in a broad range of biological processes and complex diseases. Our aim was to identify important lncRNAs that might play an important role in contributing to the benefits of epigallocatechin-3-gallate (EGCG) on cholesterol metabolism.

Methods: Microarrays was used to reveal the lncRNA and mRNA profiles in green tea polyphenol(-)-epigallocatechin gallate in cultured human liver (HepG2) hepatocytes treated with EGCG and bioinformatic analyses of the predicted target genes were performed to identify lncRNA-mRNA targeting relationships. RNA interference was used to investigate the role of lncRNAs in cholesterol metabolism.

Results: The expression levels of 15 genes related to cholesterol metabolism and 285 lncRNAs were changed by EGCG treatment. Bioinformatic analysis found five matched lncRNA-mRNA pairs for five differentially expressed lncRNAs and four differentially expressed mRNA. In particular, the lncRNA AT102202 and its potential targets mRNA-3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) were identified. Using a real-time polymerase chain reaction technique, we confirmed that EGCG down-regulated mRNA expression level of the HMGCR and up-regulated expression of AT102202. After AT102202 knockdown in HepG2, we observed that the level of HMGCR expression was significantly increased relative to the scrambled small interfering RNA control (P < 0.05).

Conclusions: Our results indicated that EGCG improved cholesterol metabolism and meanwhile changed the lncRNAs expression profile in HepG2 cells. LncRNAs may play an important role in the cholesterol metabolism.

Show MeSH