Investigation of the antidepressant mechanism of combined Radix Bupleuri and Radix Paeoniae Alba treatment using proteomics analysis of liver tissue

Radix Bupleuri-Radix Paeoniae Alba Inhibits the Development of Hepatocellular Carcinoma through Activation of the PTEN/PD-L1 Axis within the Immune Microenvironment

OBJECTIVE

This study investigated how Radix Bupleuri-Radix Paeoniae Alba (BP) was active against hepatocellular carcinoma (HCC).

METHODS

Traditional Chinese medicine systems pharmacology (TCMSP) database was employed to determine the active ingredients of BP and potential targets against HCC. Molecular docking analysis verified the binding activity of PTEN with BP ingredients. H22 cells were used to establish an HCC model in male balb/c mice. Immunofluorescence staining, immunohistochemistry, flow cytometry, western blotting, enzyme-linked immunosorbent assay, and real-time quantitative PCR were used to study changes in proliferation, apoptosis, PTEN levels, inflammation, and T-cell differentiation in male balb/c mice.

RESULTS

The major active ingredients in BP were found to be quercetin, kaempferol, isorhamnetin, stigmasterol, and beta-sitosterol. Molecular docking demonstrated that these five active BP ingredients formed a stable complex with PTEN. BP exhibited an anti-tumor effect in our HCC mouse model. BP was found to increase the CD8+ and IFN-γ+/CD4+ T cell levels while decreasing the PD-1+/CD8+ T and Treg cell levels in HCC mice. BP up-regulated the IL-6, IFN-γ, and TNF-α levels but down-regulated the IL-10 levels in HCC mice. After PTEN knockdown, BP-induced effects were abrogated.

CONCLUSION

BP influenced the immune microenvironment through activation of the PTEN/PD-L1 axis, protecting against HCC.

Qing-Zhi-Tiao-Gan-Tang (QZTGT) prevents nonalcoholic steatohepatitis (NASH) by expression pattern correction

ETHNOPHARMACOLOGICAL RELEVANCE

Qing-Zhi-Tiao-Gan-Tang or Qing-Zhi-Tiao-Gan Decoction (QZTGT) is based on the compatibility theory of traditional Chinese medicine (TCM), that is a combination of three classical formulae for the treatment of nonalcoholic fatty liver disease (NAFLD). Its pharmacodynamic material basis is made up of quinones, flavanones, and terpenoids.

AIM OF THE STUDY

This study aimed to look for a promising recipe for treating nonalcoholic steatohepatitis (NASH), a more advanced form of NAFLD, and to use a transcriptome-based multi-scale network pharmacological platform (TMNP) to find its therapy targets.

MATERIALS AND METHODS

A classical dietary model of NASH was established using MCD (Methionine- and choline-deficient) diet-fed mice. Liver coefficients like ALT, AST, serum TC, and TG levels were tested following QZTGT administration. A transcriptome-based multi-scale network pharmacological platform (TMNP) was used to further analyze the liver gene expression profile.

RESULTS

The composition of QZTGT was analyzed by HPLC-Q-TOF/MS, a total of 89 compounds were separated and detected and 31 of them were found in rat plasma. QZTGT improved liver morphology, inflammation and fibrosis in a classical NASH model. Transcriptomic analysis of liver samples from NASH animal model revealed that QZTGT was able to correct gene expression. We used transcriptome-based multi-scale network pharmacological platform (TMNP) to predicted molecular pathways regulated by QZTGT to improve NASH. Further validation indicated that "fatty acid degradation", "bile secretion" and "steroid biosynthesis" pathways were involved in the improvement of NASH phenotype by QZTGT.

CONCLUSIONS

Using HPLC-Q-TOF/MS, the compound composition of QZTGT, a Traditional Chinese prescription, was separated, analyzed and identified systematically. QZTGT mitigated NASH symptoms in a classical dietary model of NASH. Transcriptomic and network pharmacology analysis predicted the potential QZTGT regulated pathways. These pathways could be used as therapeutic targets for NASH.

Identification of Radix Bupleuri From Different Geographic Origins Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry and Support Vector Machine Algorithm

BACKGROUND

The geographic origin of Radix bupleuri is an important factor affecting its efficacy, which needs to be effectively identified.

OBJECTIVE

The goal is to enrich and develop the intelligent recognition technology applicable to the identification of the origin of traditional Chinese medicine.

METHOD

This article establishes an identification method of Radix bupleuri geographic origin based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and support vector machine (SVM) algorithm. The Euclidean distance method is used to measure the similarity between Radix bupleuri samples, and the quality control chart method is applied to quantitatively describe their quality fluctuation.

RESULTS

It is found that the samples from the same origin are relatively similar and mainly fluctuate within the control limit, but the fluctuation range is large, and it is impossible to distinguish the samples from different origins. The SVM algorithm can effectively eliminate the impact of intensity fluctuations and huge data dimensions by combining the normalization of MALDI-TOF MS data and the dimensionality reduction of principal components, and finally achieve efficient identification of the origin of Radix bupleuri, with an average recognition rate of 98.5%.

CONCLUSIONS

This newly established approach for identification of the geographic origin of Radix bupleuri has been realized, and it has the advantages of objectivity and intelligence, which can be used as a reference for other medical and food-related research.

HIGHLIGHTS

A new intelligent recognition method of medicinal material origin based on MALDI-TOF MS and SVM has been established.

Assessment of Genetic Diversity in Bupleurum spp. Basing Agronomic Traits, Medicinal Components and ISSR Markers

Radix bupleuri is one of the bulk medicinal materials in China and it is widely adopted in clinical applications and drug discovery. The investigation of agronomic traits, active component content and genetic diversity in diverse Radix bupleuri germplasms may provide evidence to promote the selection of better strains. In this research, 13 germplasms from various sources were used to investigate the variations between different Radix bupleuri germplasms. Nine biological characteristics were noted in the field, and the levels of the two primary active ingredients were determined using high performance liquid chromatography (HPLC). Moreover, the molecular marker technique of inter-simple sequence repeat (ISSR) and the unweighted pair group method with arithmetic means (UPGMA) were employed to evaluate the molecular genetic diversity. The findings showed that there was a wide range of variation among the many varieties of Radix bupleuri, with coefficients of variation for agronomic traits and active component content ranging from 7.62% to 41.54% and 36.47% to 53.70%, respectively. Moreover, there are different degrees of relationship between the two. Since there was a significant correlation between root weight and saikosaponin content, it was possible to classify a plant based on its weight and anticipate its saikosaponin content. The 13 species were divided into four groups based on their germplasm by genetic markers-based cluster analysis. This indicated the possibility that the component content would not necessarily be related to germplasm and might easily be influenced by environmental factors. The use of ISSR marker technology made it possible to precisely identify the various Radix bupleuri provenances and its counterfeit products. There may be a way to prevent the misunderstandings caused by the appearance and composition of Chinese medicinal substances. In our study, the germplasm of Radix bupleuri that was widely circulated in the market was comprehensively evaluated in terms of agronomic traits, active components and molecular level, and identified by simple means, to provide a theoretical basis for the evaluation and screening of fine germplasms of Radix bupleuri.

An integrated strategy to study the combination mechanisms of Bupleurum chinense DC and Paeonia lactiflora Pall for treating depression based on correlation analysis between serum chemical components profiles and endogenous metabolites profiles

ETHNOPHARMACOLOGICAL RELEVANCE

Bupleurum chinense DC-Paeonia lactiflora Pall (BCD-PLP) is a common clinical herb pair in traditional Chinese medicine (TCM) prescriptions commonly used to treat depression. However, its combination mechanisms with its anti-depressive effects remain highly unclear.

AIM OF THE STUDY

Here, an effective strategy has been developed to study the combination mechanisms of Bupleurum chinense DC (BCD) and Paeonia lactiflora Pall (PLP) by integrating serum pharmacochemistry analysis, metabolomics technology, and molecular docking technology.

MATERIALS AND METHODS

First, the depression model rats were replicated by the chronic unpredictable mild stress (CUMS) procedure, and the difference in the chemical composition in vivo before and after the combination of BCD and PLP was analyzed by integrating background subtraction and multivariate statistical analysis techniques. Then, UPLC/HRMS-based serum metabolomics was performed to analyze the synergistic effect on metabolite regulation before and after the combination of BCD and PLP. Further, the correlation analysis between the differential exogenous chemical components and the differential endogenous metabolites before and after the combination was employed to dissect the combination mechanisms from a global perspective of combining metabolomics and serum pharmacochemistry. Finally, the molecular docking between the differential chemical components and the key metabolic enzymes was applied to verify the regulatory effect of the differential exogenous chemical components on the differential endogenous metabolites.

RESULTS

The serum pharmacochemistry analysis results demonstrated that the combination of BCD and PLP could significantly affect the content of 10 components in BCD (including 5 prototype components were significantly decreased and 5 metabolites were significantly increased) and 8 components in PLP (including 4 prototype components and 3 metabolites were significantly increased, 1 metabolite was significantly decreased), which indicated that the combination could enhance BCD prototype components' metabolism and the absorption of the PLP prototype components. Besides, metabolomics results indicated that the BCD-PLP herb pair group significantly reversed more metabolites (8) than BCD and PLP single herb group (5 & 4) and has a stronger regulatory effect on metabolite disorders caused by CUMS. Furthermore, the correlation analysis results suggested that saikogenin F and saikogenin G were significantly positively correlated with the endogenous metabolite itaconate, an endogenous anti-inflammatory metabolite; and benzoic acid was significantly positively correlated with D-serine, an endogenous metabolite with an antidepressant effect. Finally, the molecular docking results further confirmed that the combination of BCD and PLP could affect the activities of cis-aconitic acid decarboxylase and D-amino acid oxidase by increasing the in vivo concentration of saikogenin F and benzoic acid, which further enhances its anti-inflammatory activity and anti-depressive effect.

CONCLUSIONS

In this study, an effective strategy has been developed to study the combination mechanisms of BCD and PLP by integrating serum pharmacochemistry analysis, multivariate statistical analysis, metabolomics technology, and molecular docking technology. Based on this strategy, the present study indicated that the combination of BCD and PLP could affect the activities of cis-aconitic acid decarboxylase and D-amino acid oxidase by increasing the concentration of saikogenin F and benzoic acid in vivo, which further enhances its anti-depressive effect. In short, this strategy will provide a reliable method for elucidating the herb-herb compatibility mechanism of TCM.

Effect of different drying techniques on rose (Rosa rugosa cv. Plena) proteome based on label-free quantitative proteomics

To explore the molecular mechanisms of different processing technologies on rose tea (Rosa rugosa cv. Plena), we investigated the rose tea proteome (fresh rose tea [CS], vacuum freeze-drying rose tea [FD], and vacuum microwave rose tea [VD]) using label-free quantification proteomics (LFQ). A total of 2187 proteins were identified, with 1864, 1905, and 1660 proteins identified in CS, FD, and VD, respectively. Of those, 1500 proteins were quantified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation and enrichment analysis of differential expression proteins (DEPs) in VD vs. CS, FD vs. CS, and FD vs. VD showed that these pathways were associated with energy metabolism, the metabolic breakdown of energy substances and protein biosynthesis, such as oxidative phosphorylation, citrate cycle, carbon metabolism pathways, and ribosome and protein processing in endoplasmic reticulum. FD could ensure the synthesis of protein translation and energy metabolism, thereby maintaining the high quality of rose tea.

Antidepressant effects of the traditional Chinese herbal formula Xiao-Yao-San and its bioactive ingredients

BACKGROUND

Depression is one of the most debilitating and severe psychiatric disorders and a serious public health concern. Currently, many treatments are indicated for depression, including traditional Chinese medicinal formulae such as Xiao-Yao-San (XYS), which has effective antidepressant effects in clinical and animal studies.

PURPOSE

To summarize current evidence of XYS in terms of the preclinical and clinical studies and to identify the multi-level, multi-approach, and multi-target potential antidepressant mechanisms of XYS and active components of XYS by a comprehensive search of the related electronic databases.

METHODS

The following electronic databases were searched from the beginning to April 2022: PubMed, MEDLINE, Web of Science, Google Scholar, and China National Knowledge Infrastructure.

RESULTS

This review summarizes the antidepressant mechanisms of XYS and its active ingredients, which are reportedly correlated with monoamine neurotransmitter regulation, synaptic plasticity, and hypothalamic-pituitary-adrenal axis, etc. CONCLUSION: XYS plays a critical role in the treatment of depression by the regulation of several factors, including the monoaminergic systems, hypothalamic-pituitary-adrenal axis, synaptic plasticity, inflammation, brain-derived neurotrophic factor levels, brain-gut axis, and other pathways. However, more clinical and animal studies should be conducted to further investigate the antidepressant function of XYS and provide more evidence and recommendations for its clinical application. Our review provides an overview of XYS and guidance for future research direction.

Causality of genetically determined metabolites on anxiety disorders: a two-sample Mendelian randomization study

BACKGROUND

Although anxiety disorders are one of the most prevalent mental disorders, their underlying biological mechanisms have not yet been fully elucidated. In recent years, genetically determined metabolites (GDMs) have been used to reveal the biological mechanisms of mental disorders. However, this strategy has not been applied to anxiety disorders. Herein, we explored the causality of GDMs on anxiety disorders through Mendelian randomization study, with the overarching goal of unraveling the biological mechanisms.

METHODS

A two-sample Mendelian randomization (MR) analysis was implemented to assess the causality of GDMs on anxiety disorders. A genome-wide association study (GWAS) of 486 metabolites was used as the exposure, whereas four different GWAS datasets of anxiety disorders were the outcomes. Notably, all datasets were acquired from publicly available databases. A genetic instrumental variable (IV) was used to explore the causality between the metabolite and anxiety disorders for each metabolite. The MR Steiger filtering method was implemented to examine the causality between metabolites and anxiety disorders. The standard inverse variance weighted (IVW) method was first used for the causality analysis, followed by three additional MR methods (the MR-Egger, weighted median, and MR-PRESSO (pleiotropy residual sum and outlier) methods) for sensitivity analyses in MR analysis. MR-Egger intercept, and Cochran's Q statistical analysis were used to evaluate possible heterogeneity and pleiotropy. Bonferroni correction was used to determine the causative association features (P < 1.03 × 10^-4). Furthermore, metabolic pathways analysis was performed using the web-based MetaboAnalyst 5.0 software. All statistical analysis were performed in R software. The STROBE-MR checklist for the reporting of MR studies was used in this study.

RESULTS

In MR analysis, 85 significant causative relationship GDMs were identified. Among them, 11 metabolites were overlapped in the four different datasets of anxiety disorders. Bonferroni correction showing1-linoleoylglycerophosphoethanolamine (OR_{fixed-effect IVW} = 1.04; 95% CI 1.021-1.06; P_{fixed-effect IVW} = 4.3 × 10^-5) was the most reliable causal metabolite. Our results were robust even without a single SNP because of a "leave-one-out" analysis. The MR-Egger intercept test indicated that genetic pleiotropy had no effect on the results (intercept = - 0.0013, SE = 0.0006, P = 0.06). No heterogeneity was detected by Cochran's Q test (MR-Egger. Q = 7.68, P = 0.742; IVW. Q = 12.12, P = 0.436). A directionality test conducted by MR Steiger confirmed our estimation of potential causal direction (P < 0.001). In addition, two significant pathways, the "primary bile acid biosynthesis" pathway (P = 0.008) and the "valine, leucine, and isoleucine biosynthesis" pathway (P = 0.03), were identified through metabolic pathway analysis.

CONCLUSION

This study provides new insights into the causal effects of GDMs on anxiety disorders by integrating genomics and metabolomics. The metabolites that drive anxiety disorders may be suited to serve as biomarkers and also will help to unravel the biological mechanisms of anxiety disorders.

Efficacy and Safety of Xiaoyao Recipe in the Treatment of Poststroke Depression: A Systematic Review and Meta-Analysis

Background

Poststroke depression (PSD) is a common neuropsychiatric disorder that affects the disability, mortality, functional recovery, and quality of daily life of patients. Xiaoyao Recipe (XYR) is often used to treat PSD and has achieved good clinical effects, but it lacks reliable evidence.

Objective

This study aims to evaluate the effectiveness and safety of XYR on PSD through meta-analysis.

Methods

A comprehensive literature search was carried out in multiple databases, including PubMed, the Cochrane Library, Chinese Biomedical Literature Service System, China National Knowledge Infrastructure, Wanfang Database, VIP Database, and ClinicalTrials, from inception to July 1, 2021, to collect randomized controlled trials that applied XYR for patients with PSD. For a controlled trial, the search time limit was set from the time of the database's establishment to July 2021. Two experienced researchers independently screened the literature according to the inclusion and exclusion criteria, extracted data, evaluated the quality of the literature, and used RevMan 5.3 software for meta-analysis.

Results

A total of 12 studies were included in this study, involving 882 patients with PSD who were hospitalized or outpatients. The meta-analysis results showed that the total effective rate (p < 0.00001) of the test group (XYR or XYR combined with antidepressants) after treatment was high; Hamilton's Depression Scale score (p < 0.000001), Scandinavian Stroke Scale score (p=0.004 < 0.05), and Barthel index (p < 0.00001) were improved; the incidence of adverse reactions (p < 0.00001) was low; and the serum serotonin content (p < 0.00001) was high.

Conclusion

Compared with antidepressant drugs, XYR is more effective and safer in the treatment of PSD patients. However, more high-quality studies are needed to further support the above conclusions.