Myricetin suppresses LPS-induced MMP expression in human gingival fibroblasts and inhibits osteoclastogenesis by downregulating NFATc1 in RANKL-induced RAW 264.7 cells
ARCHIVES OF ORAL BIOLOGY
Authors: Ko, Seon-Yle
Abstract
Objective: Periodontitis is an inflammatory disease that affects connective tissue attachments and the supporting bone that surrounds the teeth. Gingival fibroblasts induce the overexpression of matrix metalloproteinase (MMP), which is involved in inflammatory progression in periodontitis. Osteoclasts are responsible for skeletal modeling and remodeling but may also destroy bone in several bone diseases, including osteoporosis and periodontitis. This study examined the anti-destructive effects of myricetin on human gingival fibroblasts (HGF) under lipopolysaccharide- (LPS-) induced inflammatory conditions, and the anti-osteoclastogenetic effect of myricetin on the receptor activator of NF-kappa B ligand (RANKL) induced RAW264.7 cells was also investigated. Design: The effects of myricetin on HGF were determined by measuring the cell viability and mRNA expression and enzyme activity of tissue-destructive proteins, including MMP-1, MMP-2 and MMP-8. The effects of myricetin on osteoclasts were examined by measuring the following: (1) the cell viability, (2) the formation of tartrate-resistant acid phosphatase (TRAP)(+) multinucleated cells, (3) MAPK signalling pathways (4) mRNA expression of osteoclast-associated genes and (5) tumor necrosis factor-alpha (TNF-alpha) and interleukin-1 beta (IL-1 beta) secretion. Results: The myricetin had no effects on the cell viability of the HGF and decreased the mRNA expression and enzyme activity of MMP-1, MMP-2 and MMP-8 in the FIGF. Myricetin inhibited the formation of RANKL-stimulated TRAP(+) multinucleated cells. Myricetin also inhibited the RANKL-stimulated activation of p-38, ERK and cSrc signaling, and inhibited the RANKL-stimulated degradation of IkB in the RAW264.7 cells. In addition, the RANKL-stimulated induction of NFATc1 transcription factors was abrogated by myricetin. Myricetin decreased the mRNA expression of osteoclast-associated genes, including cFOS, TRAP and cathepsin K in the RAW264.7 cells. Myricetin inhibited the secretion of LPS-induced TNF-alpha and IL-1 beta in the RAW264.7 cells. Conclusions: These findings suggest that myricetin has therapeutic effects on bone-destructive processes, such as those that occur in periodontal diseases. (C) 2012 Elsevier Ltd. All rights reserved.
Identification of target genes in cardiomyopathy with fibrosis and cardiac remodeling
JOURNAL OF BIOMEDICAL SCIENCE
Authors: Zhao, Jianquan; Lv, Tiewei; Quan, Junjun; Zhao, Weian; Song, Jing; Li, Zhuolin; Lei, Han; Huang, Wei; Ran, Longke
Abstract
Background: Identify genes probably associated with chronic heart failure and predict potential target genes for dilated cardiomyopathy using bioinformatics analyses. Methods: Gene expression profiles (series number GSE3585 and GSE42955) of cardiomyopathy patients and healthy controls were downloaded from the Expression Omnibus Gene (GEO) database. Differential expression of genes (DEGS) between the two groups of total 14 cardiomyopathy patients and 10 healthy controls were subsequently identified by limma package of R. Database for Annotation, Visualization, and Integrated Discovery (DAVID Tool), which is an analysis of enriched biological processes. Search Tool for the Retrieval Interacting Genes (STRING) was used as well for the analysis of protein-protein interaction network (PPI). Prediction of the potential drugs was suggested based on the preliminarily identified genes using Connectivity Map (CMap). Results: Eighty-nine DEGs were identified (57 up-regulated and 32 down-regulated). The most enrichment Gene Ontology (GO) terms (P < 0.05) contain genes involved in extracellular matrix (ECM) and biological adhesion signal pathways (P < 0.05, ES > 1.5) such as ECM-receptors, focal adhesion and transforming growth factor beta (TGF-beta), etc. Fifty-one differentially expressed genes were found to encode interacting proteins. Eleven key genes along with related transcription factors were identified including CTGF, POSTN, CORIN, FIGF, etc. Conclusion: Bioinformatics-based analyses reveal the targeted genes probably associated with cardiomyopathy, which provide clues for pharmacological therapies aiming at the targets.