Integrating Transcriptomics, Proteomics, and Metabolomics Profiling with System Pharmacology for the Delineation of Long-Term Therapeutic Mechanisms of Bufei Jianpi Formula in Treating COPD.
Peng ZhaoJian-Sheng LiYa LiYange TianLiping YangSuyun LiPublished in: BioMed research international (2017)
In previous work, we identified 145 active compounds from Bufei Jianpi formula (BJF) by system pharmacology and found that BJF showed short-term effect on chronic obstructive pulmonary disease (COPD) rats. Here, we applied the transcriptomic, proteomic, and metabolomics approaches to illustrate the long-term anti-COPD action and its system mechanism of BJF. BJF has obvious anti-COPD effect through decreasing inflammatory cytokines level, preventing protease-antiprotease imbalance and collagen deposition on week 32 by continuous oral administration to rats from weeks 9 to 20. Subsequently, applying the transcriptomic, proteomic, and metabolomics techniques, we detected a number of regulated genes, proteins, and metabolites, mainly related to antioxidant activity, focal adhesion, or lipid metabolism, in lung tissues of COPD and BJF-treated rats. Afterwards, we integrated system pharmacology target, transcript, protein, and metabolite data sets and found that many genes, proteins, and metabolites in rats BJF-treated group and the target proteins of BJF were mainly attributed to lipid metabolism, inflammatory response, oxidative stress, and focal adhesion. Taken together, BJF displays long-term anti-COPD effect probably by system regulation of the lipid metabolism, inflammatory response pathways oxidative stress, and focal adhesion.
Keyphrases
- chronic obstructive pulmonary disease
- lung function
- inflammatory response
- oxidative stress
- mass spectrometry
- single cell
- ms ms
- cystic fibrosis
- genome wide
- lipopolysaccharide induced
- randomized controlled trial
- biofilm formation
- air pollution
- gene expression
- dna damage
- clinical trial
- ischemia reperfusion injury
- small molecule
- staphylococcus aureus
- machine learning
- candida albicans
- cell adhesion
- protein protein