A new research paradigm in modernization of traditional Chinese medicine: single cell pharmacology / 药学学报

Single cell "omics" technology enables the capture of genome, transcriptome, proteome and other omics information in a high-throughput and unbiased manner at single-cell resolution, allowing the characterization of the functional state of individual cells to reveal their heterogeneity and differential responses to drug treatment. This technology has wide application in pharmacological research, facilitating drug screening, efficacy evaluation, and mechanistic studies. We envision that, in the field of traditional Chinese medicine (TCM), single cell omics technology can be applied in the identification of active ingredients and drug targets, and elucidation of drug mechanism of action. In this article, we briefly introduce the single cell omics technology - particularly single cell transcriptome sequencing, and review its application in the field of modern drug research. Based on that, we propose the concept of "single cell pharmacology" and articulate how it can be applied to transform the pharmacological research of TCM and promote TCM modernization.

Identification of biomarkers to response of Tripterygium Glycosides Tablets acting on rheumatoid arthritis by integrating transcriptional data mining and biomolecular network analysis / 中国中药杂志

Growing clinical evidence shows that a partial rheumatoid arthritis( RA) patient treated with Tripterygium Glycosides Tablets( TGT) may fail to achieve clinical improvement. It is of great clinical significance to predict the therapeutic effect of TGT in RA. Therefore,the aim of the current study was to identify potential biomarkers for TGT treatment in RA. Affymetrix EG1.0 arrays were applied to detect gene expression in peripheral blood mononuclear cells obtained from 6 RA patients( 3 responders and 3 non-responders) treated with TGT. By integrating differential expression data analysis and biomolecular network analysis,360 mRNAs( 185 up-regulated and 175 down-regulated) and 24 miRNAs( 7 up-regulated and 17 down-regulated) which were differentially expressed between TGT responder and non-responder groups were identified. A total of 206 candidate target genes for the differentially expressed miRNAs were obtained based on miRanada and Target Scan databases,and then the miRNA target gene coexpression network and miRNA-mediated gene signal transduction network were constructed. Following the network analyses,three candidate miRNAs biomarkers( hsa-miR-4720-5 p,hsa-miR-374 b-5 p,hsa-miR-185-3 p) were identified as candidate biomarkers predicting individual response to TGT. Partialleast-squares( PLS) was applied to construct a model for predicting response to TGT based on the expression levels of the candidate gene biomarkers in RA patients. The five-fold cross-validation showed that the prediction accuracy( ACC) of this PLS-based model efficacy was 100.00%,100.00%,100.00%,66.67% and 66.67% respectively,and all the area under the receiver operating characteristic curve( AUC) were 1.00,indicating the highly predictive efficiency of this PLS-based model. In conclusion,the integrating transcription data mining and biomolecular network investigation show that hsa-mir-4720-5 p,hsa-mir-374 b-5 p and hsa-mir-185-3 p may be candidate biomarkers predicting individual response to TGT. In addition,the PLS model based on the expression levels of these candidate biomarkers may be helpful for the clinical screen of RA patients,which potentially benefit individualized therapy of RA in a daily clinical setting.

A comparative study on the mechanisms of two classical herbal formulae for rheumatoid arthritis applying cold and heat patterns based on target network / 药学学报

Wu-tou decoction (WTD) and Baihu-Guizhi decoction (BHGZD) as described in the Synopsis of the Golden Chamber have been used extensively for the treatment of rheumatoid arthritis (RA) with apparent therapeutic efficacy. However, characteristics of pharmacological effects and their underlying molecular mechanisms have not been fully elucidated due to a lack of appropriate scientific methodology. In the current study, we performed an integrative approach applying gene expression profiling and network analysis to examine the therapeutic effects and molecular mechanisms of WTD and BHGZD based on adjuvant-induced arthritis (AIA) animal model. Results demonstrated that both WTD and BHGZD could relieve the severity of arthritis in AIA rats, while the significant differences were observed in the changes of the withdrawal response scores and latency time of AIA rats treated with WTD and BHGZD. Mechanistically, our network pharmacology-based investigation demonstrated that the major candidate targets of WTD and BHGZD were significantly associated with several inflammation-immune regulatory pathways, such as Toll-like receptor signaling pathway, T cell receptor signaling pathway, cytokine-cytokine receptor interaction, chemokine signaling pathway, B cell receptor signaling pathway, antigen processing and presentation, Fc epsilon RI signaling pathway, natural killer cell mediated cytotoxicity, as well as leukocyte transendothelial migration. In particular, the major candidate targets of WTD were also involved in the regulation of hormone and energy metabolism, which might be imbalanced during RA progression. In conclusion, the current study revealed differences and similarities regarding the effects and network regulatory mechanisms of WTD and BHGZD. These findings may present a scientific basis for elucidation of mechanisms by which WTD and BHGZD alleviates RA.