TFEB activator tanshinone IIA and derivatives derived from Salvia miltiorrhiza Bge. Attenuate hepatic steatosis and insulin resistance.

ETHNOPHARMACOLOGICAL RELEVANCE: Salvia miltiorrhiza Bge. (SMB) is an herbal medicine extensively used for improving metabolic disorders, including Nonalcoholic fatty liver disease (NAFLD). However, the potential material basis and working mechanism still remained to be elucidated. AIM OF THE STUDY: To find potential ingredients for therapy of NAFLD by high content screening and further verify the efficacy on restoring hepatic steatosis and insulin resistance, and clarify the potential working mechanism. MATERIALS AND METHODS: The mouse transcription factor EB (Tfeb) in preadipocytes was knocked out by CRISPR-Cas9 gene editing. High content screening of TFEB nuclear translocation was performed to identify TFEB activators. The effect of candidate compounds on reducing lipid accumulation was evaluated using Caenorhabditis elegans (C. elegans). Then the role of Salvia miltiorrhiza extract (SMB) containing Tanshinone IIA and the derivatives were further investigated on high-fat diet (HFD) fed mice. RNA-seq was performed to explore potential molecular mechanism of SMB. Finally, the gut microbiota diversity was evaluated using 16S rRNA sequencing to investigate the protective role of SMB on regulating gut microbiota homeostasis. RESULTS: Knockout of Tfeb led to excessive lipid accumulation in adipocytes while expression of TFEB homolog HLH-30 in C. elegans (MAH240) attenuated lipid deposition. Screening of TFEB activators identified multiple candidates from Salvia miltiorrhiza, all of them markedly induced lysosome biogenesis in HepG2 cells. One of the candidate compounds Tanshinone IIA significantly decreased lipid droplet deposition in HFD fed C. elegans. Administration of SMB on C57BL/6J mice via gastric irrigation at the dose of 15 g/kg/d markedly alleviated hepatic steatosis, restored serum lipid profile, and glucose tolerance. RNA-seq showed that gene expression profile was altered and the genes related to lipid metabolism were restored. The disordered microbiome was remodeled by SMB, Firmicutes and Actinobacteriotawere notably reduced, Bacteroidota and Verrucomicrobiota were significantly increased. CONCLUSION: Taken together, the observations presented here help address the question concerning what were the main active ingredients in SMB for alleviating NAFLD, and established that targeting TFEB was key molecular basis for the efficacy of SMB.

Mechanism analysis of essential oil from Radix Bupleuri for the treatment of asthma through regulation of ectopic olfactory receptor.

ETHNOPHARMACOLOGICAL RELEVANCE: Radix Bupleuri is the root of Bupleurum chinense DC. (BC) and a classic aromatic traditional Chinese medicine. The traditional pharmacological effects of Radix Bupleuri are alleviating bronchial spasms, dilating airways, and promoting the resolution of respiratory inflammation, thereby reducing asthma symptoms. AIM OF THE STUDY: Studies have demonstrated the efficacy of water extracts from BC in asthma treatment. However, the potential role of volatile oil, another active constituent in BC, remains unexplored with asthma. Notably, volatile oil is renowned for its ease of absorption and direct targeting of affected areas, offering distinct advantages in alleviating airway inflammation. This study aims to explain the anti-asthmatic mechanism of BC-oil through in vivo and in vitro pharmacological experiments. MATERIALS AND METHODS: Firstly, the OVA-induced SD rat asthma model was utilized to evaluate the pharmacological effect of BC-oil by lung function monitoring, HE staining, flow cytometry, ELISA, and RT-qPCR. The anti-asthmatic mechanism was further analyzed by combining transcriptomic analysis of lung tissue from rat model and airway smooth muscle tissue from public database. Initially, GC-MS was used to analyze the components of BC-oil. The anti-asthmatic activity was evaluated in 16-HBE, RBL-2H3, and ASMC cells using CAMKII inhibitors to explore of the critical signal transduction regulated by BC-oil. Furthermore, molecular docking and calcium flow assay were utilized to screen and identify the active components from BC-oil. RESULTS: Oral administration of BC-oil significantly enhanced pulmonary function in asthmatic SD rats by reducing airway resistance and elastic resistance. Additionally, BC-oil inhibited inflammatory cytokines, including serum IL-2, pulmonary Il1b, Tnf, and Cxcl13, demonstrating potent anti-inflammatory and immunomodulatory effects. In this study, we analyzed the significant role of OR2W3 in asthma using public transcriptomic data. Furthermore, we indicated that BC-oil regulated the expression of Olr1433 and GNAL in rat lung tissue. BC-oil reduced degranulation and inhibited gene expression of Il3 and Tnf in RBL-2H3 cells and suppressed gene expression of IL8 and TNF in 16-HBE cells. BC-oil also attenuated airway smooth muscle cell proliferation and expression of Acta2 and Ccnd1. Furthermore, BC-oil regulates asthma-related cellular processes by activating CAMKII. GC-MS analysis identified 11 components of BC-oil, and n-hexadecanoic acid, linoleic acid and oleic acid from BC-oil were identified to interact with OR2W3 by molecular docking. The calcium flow assay revealed linoleic acid as a significant activator of OR2W3 and indicated that BC-oil alleviated asthma through the ectopic olfactory signaling pathway. CONCLUSIONS: The mechanism of BC-oil in treating asthma through signal transduction of OR2W3 is revealed at the molecular and cellular levels.

SYSTCM: A systemic web platform for objective identification of pharmacological effects based on interplay of "traditional Chinese Medicine-components-targets".

Mechanism analysis is essential for the use and promotion of Traditional Chinese Medicine (TCM). Traditional methods of network analysis relying on expert experience lack an explanatory framework, prompting the application of deep learning and machine learning for objective identification of TCM pharmacological effects. A dataset was used to construct an interacted network graph between 424 molecular descriptors and 465 pharmacological targets to represent the relationship between components and pharmacological effects. Subsequently, the optimal identification model of pharmacological effects (IPE) was established through convolution neural networks of GoogLeNet structure. The AUC values are greater than 0.8, MCC values are greater than 0.7, and ACC values are greater than 0.85 across various test datasets. Subsequently, 18 recognition models of TCM efficacy (RTE) were created using support vector machines (SVM). Integration of pharmacological effects and efficacies led to the development of the systemic web platform for identification of pharmacological effects (SYSTCM). The platform, comprising 70,961 terms, including 636 Traditional Chinese Medicines (TCMs), 8190 components, 40 pharmacological effects, and 18 efficacies. Through the SYSTCM platform, (1) Total 100 components were predicted from TCMs with anti-inflammatory pharmacological effects. (2) The pharmacological effects of complete constituents were predicted from Coptidis Rhizoma (Huang Lian). (3) The principal components, pharmacological effects, and efficacies were elucidated from Salviae Miltiorrhizae radix et rhizome (Dan Shen). SYSTCM addresses subjectivity in pharmacological effect determination, offering a potential avenue for advancing TCM drug development and clinical applications. Access SYSTCM at http://systcm.cn.