Metabolomics analysis shows regulatory effects of Zhuye Shigao Decoction on inflammatory markers in mice with acute pneumonia, indicating its therapeutic potential.
Zhuye Shigao Decoction (ZSD), a classic traditional Chinese medicine (TCM) formula, has demonstrated therapeutic efficacy in clinical settings for acute pneumonia; however, its mechanism of action remains elusive. This study aims to investigate the therapeutic effects and potential mechanisms of ZSD in lipopolysaccharide (LPS)-induced acute pneumonia in mice. A liquid chromatography-mass spectrometry (LC-MS)-based metabolomics approach, integrated with a gene expression omnibus (GEO) data mining technique, was employed in this investigation. The results indicated that ZSD administration significantly alleviated LPS-induced pathological changes in lung tissue. In the model group, the concentrations of interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) were increased, whereas the levels of immunoglobulin A (IgA) and immunoglobulin M (IgM) were significantly decreased. These indicators were reversed considerably in the ZSD-high dose (ZSD-H) group. A total of 118 metabolites exhibiting significant alterations in lung tissue were identified through metabolomics analysis. Following ZSD treatment, 84 of these metabolites were negatively regulated, and the associated metabolic processes implicated multiple pathways, including sphingolipid and arachidonic acid (AA) metabolism. Differentially expressed genes (DEGs) were identified through a comprehensive analysis of GEO datasets. Integrative pathway analysis identified signaling pathways associated with ZSD treatment effects in acute pneumonia. Notably, the Janus kinase/signal transducer and activator of transcription (JAK-STAT) and Toll-like receptor (TLR) signaling pathways emerged as critical contributors to these effects. This study indicates that ZSD can exert therapeutic effects on LPS-induced acute pneumonia through a regulatory mechanism involving multiple components, targets, and pathways.
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Tang et al. (2026) studied this question.
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