High-throughput transcriptional profiling of perturbations by Panax ginseng saponins and Panax notoginseng saponins using TCM-seq.

Panax ginseng (PG) and Panax notoginseng (PN) are highly valuable Chinese medicines (CM). Although both CMs have similar active constituents, their clinical applications are clearly different. Over the past decade, RNA sequencing (RNA-seq) analysis has been employed to investigate the molecular mechanisms of extracts or monomers. However, owing to the limited number of samples in standard RNA-seq, few studies have systematically compared the effects of PG and PN spanning multiple conditions at the transcriptomic level. Here, we developed an approach that simultaneously profiles transcriptome changes for multiplexed samples using RNA-seq (TCM-seq), a high-throughput, low-cost workflow to molecularly evaluate CM perturbations. A species-mixing experiment was conducted to illustrate the accuracy of sample multiplexing in TCM-seq. Transcriptomes from repeated samples were used to verify the robustness of TCM-seq. We then focused on the primary active components, Panax notoginseng saponins (PNS) and Panax ginseng saponins (PGS) extracted from PN and PG, respectively. We also characterized the transcriptome changes of 10 cell lines, treated with four different doses of PNS and PGS, using TCM-seq to compare the differences in their perturbing effects on genes, functional pathways, gene modules, and molecular networks. The results of transcriptional data analysis showed that the transcriptional patterns of various cell lines were significantly distinct. PGS exhibited a stronger regulatory effect on genes involved in cardiovascular disease, whereas PNS resulted in a greater coagulation effect on vascular endothelial cells. This study proposes a paradigm to comprehensively explore the differences in mechanisms of action between CMs based on transcriptome readouts.

Danshen-Chuanxiongqin Injection attenuates cerebral ischemic stroke by inhibiting neuroinflammation via the TLR2/ TLR4-MyD88-NF-κB Pathway in tMCAO mice.

Danshen-Chuanxiongqin Injection (DCI) is a commonly used traditional Chinese medicine for the treatment of cerebral ischemic stroke in China. However, its underlying mechanisms remain completely understood. The current study was designed to explore the protective mechanisms of DCI against cerebral ischemic stroke through integrating whole-transcriptome sequencing coupled with network pharmacology analysis. First, using a mouse model of cerebral ischemic stroke by transient middle cerebral artery occlusion (tMCAO), we found that DCI (4.10 mL·kg-1) significantly alleviated cerebral ischemic infarction, neurological deficits, and the pathological injury of hippocampal and cortical neurons in mice. Next, the whole-transcriptome sequencing was performed on brain tissues. The cerebral ischemia disease (CID) network was constructed by integrating transcriptome sequencing data and cerebrovascular disease-related genes. The results showed CID network was imbalanced due to tMCAO, but a recovery regulation was observed after DCI treatment. Pathway analysis of the key genes with recovery efficiency showed that the neuroinflammation signaling pathway was highly enriched, while the TLR2/TLR4-MyD88-NF-κB pathway was predicted to be affected. Consistently, the in vivo validation experiments confirmed that DCI exhibited protective effects against cerebral ischemic stroke by inhibiting neuroinflammation via the TLR2/TLR4-MyD88-NF-κB pathway. More interestingly, DCI markedly suppressed the neutrophils infiltrated into the brain parenchyma via the choroid plexus route and showed anti-neuroinflammation effects. In conclusion, our results provide dependable evidence that inhibiting neuroinflammation via the TLR2/TLR4-MyD88-NF-κB pathway is the main mechanism of DCI against cerebral ischemic stroke in mice.

Copy number variation is highly correlated with differential gene expression: a pan-cancer study.

BACKGROUND: Cancer is a heterogeneous disease with many genetic variations. Lines of evidence have shown copy number variations (CNVs) of certain genes are involved in development and progression of many cancers through the alterations of their gene expression levels on individual or several cancer types. However, it is not quite clear whether the correlation will be a general phenomenon across multiple cancer types. METHODS: In this study we applied a bioinformatics approach integrating CNV and differential gene expression mathematically across 1025 cell lines and 9159 patient samples to detect their potential relationship. RESULTS: Our results showed there is a close correlation between CNV and differential gene expression and the copy number displayed a positive linear influence on gene expression for the majority of genes, indicating that genetic variation generated a direct effect on gene transcriptional level. Another independent dataset is utilized to revalidate the relationship between copy number and expression level. Further analysis show genes with general positive linear influence on gene expression are clustered in certain disease-related pathways, which suggests the involvement of CNV in pathophysiology of diseases. CONCLUSIONS: This study shows the close correlation between CNV and differential gene expression revealing the qualitative relationship between genetic variation and its downstream effect, especially for oncogenes and tumor suppressor genes. It is of a critical importance to elucidate the relationship between copy number variation and gene expression for prevention, diagnosis and treatment of cancer.