The predicted proteomic network associated with the antiarthritic action of Qingfu Guanjieshu in collagen-II-induced arthritis in rats

Ting Yu Wang, Hua Zhou, Yuen Fan Wong, Pui Kei Wu, Wen Luan Wendy Hsiao, Elaine Lai Han Leung*, Liang Liu

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

7 Citations (Scopus)

Abstract

Qingfu Guanjieshu (QFGJS) is an herbal preparation for treating rheumatoid arthritis (RA). Previous studies revealed that QFGJS significantly inhibited experimental arthritis and acute inflammation, accompanied by reduction of proinflammatory cytokines and elevation of anti-inflammatory cytokines. This study aims to identify the targeted proteins and predict the proteomic network associated with the drug action of QFGJS by using 2D gel and MALDI-TOF-MS/MS techniques. Thirty female Wistar rats were evenly grouped as normal and vehicle- and QFGJS-treated CIA rats. The antiarthritic effect of QFGJS was examined with a 19-day treatment course, and the knee synovial tissues of animals from each group were obtained for 2D gel and MALDI-TOF-MS/MS analysis. Results showed that QFGJS significantly ameliorated collagen II-induced arthritis when administrated at 2.8 g/kg body weight for 19 days. 2D gel image analysis revealed 89 differentially expressed proteins in the synovial tissues among the normal and vehicle- and QFGJS-treated CIA rats from over 1000 proteins of which 63 proteins were identified by MALDI-TOF-MS/MS analysis, and 32 proteins were included for classification of functions using Gene Ontology (GO) method. Finally, 14 proteins were analyzed using bioinformatics, and a predicted proteomic network related to the anti-arthritic effect of QFGJS was established, and Pgk1 plays a central role.

Original languageEnglish
Article number582493
JournalEvidence-based Complementary and Alternative Medicine
Volume2013
DOIs
Publication statusPublished - 2013

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