An integrated quantitative proteomics strategy reveals the dual mechanisms of celastrol against acute inflammation

Guangshan Xie, Lin Zhu, Yuanyuan Song, Wei Huang, Di Hu, Zongwei Cai*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

8 Citations (Scopus)


Inflammation is a defense mechanism associated with a wide range of diseases. Celastrol is a small molecule isolated from traditional Chinese medicine with potent anti-inflammation activity. In this study, we established an integrated quantitative proteomics strategy to investigate the acute response to celastrol treatment in a rat macrophage cell line challenged with lipopolysaccharide (LPS). Both stable-isotopic based non-targeted quantitative profiling and PRM-based targeted quantitation methods were employed. Dimethyl-labeling based non-targeted profiling revealed 28 and 52 proteins that significantly up- and down-regulated by celastrol. Bioinformatics analysis pinpoint key signaling pathways affected. Seven proteins were selected for examining their time-dependent regulatory pattern in response to celastrol using targeted PRM quantitation. The abundance of mRNA at multiple time-points of selected proteins was also examined. Celastrol induced an acute response of selected key transcriptional factors in terms of mRNA or protein abundance within one hour. Interestingly, regulatory trend of mRNA and protein abundance suggested a novel dual mechanism of celastrol in the terms of acute anti-inflammation. The integrated quantitative proteomic strategy established in this study constitutes an efficient workflow to characterize key components and their time-dependent regulatory pattern for monitoring drug response.

Original languageEnglish
Pages (from-to)2164-2168
Number of pages5
JournalChinese Chemical Letters
Issue number7
Publication statusPublished - Jul 2021

Scopus Subject Areas

  • Chemistry(all)

User-Defined Keywords

  • Acute inflammation
  • Celastrol
  • Dual mechanisms
  • Integrated quantitative proteomics


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