Potential antidepressant effects of Traditional Chinese botanical drug formula Chaihu-Shugan-San and its active ingredients

Background: Depression is a severe mental disorder that poses a significant threat to both the physical and mental wellbeing of individuals. Currently, there are various methods for treating depression, including traditional Chinese herbal formulations like Chaihu-Shugan-San (CSS), which have shown effective antidepressant effects in both clinical and animal research. Objective: This review aims to provide a comprehensive synthesis of evidence related to CSS, considering both preclinical and clinical studies, to uncover its potential multi-level, multi-pathway, and multi-target mechanisms for treating depression and identify its active ingredients. Methods: A thorough search was conducted in electronic databases, including PubMed, MEDLINE, Web of Science, Google Scholar, CNKI, and Wanfang, using keywords such as "Chaihu Shugan" and "depression" to retrieve relevant literature on CSS and its active ingredients. The review process adhered to the PRISMA guidelines. Results: This review consolidates the mechanisms underlying antidepressant effects of CSS and its active ingredients. It emphasizes its involvement in the regulation of monoaminergic neurotransmitter systems, synaptic plasticity, and the hypothalamic-pituitary-adrenal axis, among other aspects. Conclusion: CSS exerts a pivotal role in treating depression through various pathways, including the monoaminergic neurotransmitter system, the hypothalamic-pituitary-adrenal axis, synaptic plasticity, inflammation, brain-derived neurotrophic factor levels, and the brain-gut axis. This review facilitates a comprehensive understanding of the current state of CSS research, fostering an in-depth exploration of the etiological mechanisms of depression and the potential discovery of novel antidepressant drugs.

Identification strategy of Fructus Gardeniae and its adulterant based on UHPLC/Q-orbitrap-MS and UHPLC-QTRAP-MS/MS combined with PLS regression model

Fructus Gardeniae (FG) is the desiccative and ripe fruits of Gardenia jasminoides Ellis in the Rubiaceae family, which is a commonly used in traditional Chinese medicine (TCM) for clearing away heat, detoxification, relieving restlessness, and eliminating blood stasis. At the same time, it has also been announced as the first batch of TCM with homology of medicine and food. Fructus Gardeniae Grandiflorae (FGG), the fruit of Gardenia jasminoides Ellis var. grandiflora Nakai (Rubiaceae), is a common counterfeit herbal medicine of FG, which still appears in the TCM market, and causes a certain degree of confusion. In order to effectively distinguish FG and its adulterant, the compounds in these two species were thoroughly characterized firstly by ultrahigh-performance liquid chromatography/quadrupole-orbitrap mass spectrometry (UHPLC/Q-Orbitrap MS). Furthermore, a pseudo-targeted metabonomics method with 60 targeted ion pairs was established based on UHPLC-triple quadrupole-linear ion trap mass spectrometry (UHPLC-QTRAP-MS) for discrimination. Multivariate statistical analysis showed that FG and FGG were clustered obviously, and 13 significantly differential markers were screened out by variable importance for projection (VIP) > 1 and p < 0.05 for the construction of the partial least squares (PLS) regression prediction model. The validation of the model proved that its prediction ability was quite satisfactory. Moreover, based on the absolute quantitative analysis of these 13 characteristics, the quality control standards of FG and FFG were established. In summary, an integral method of pseudo-targeted metabonomics combined with chemometrics analysis and a PLS regression model was proposed to provide an effective identification strategy for discrimination FG and FGG.

Exploring the mechanism of Si-Ni-San against depression by UPLC-Q-TOF-MS/MS integrated with network pharmacology: experimental research

Background

Depression is becoming an urgent mental health problem. Si-Ni-San has been widely used to treat depression, yet its underlying pharmacological mechanism is poorly understood. Thus, we aim to explore the antidepressant mechanism of Si-Ni-San by chemical analysis and in-silico methods.

Methods

Compounds in Si-Ni-San were determined by ultra-high performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS). Then, bioactive compounds were obtained from Traditional Chinese Medicines for Systems Pharmacology Database and Analysis Platform and SwissADME, and the potential targets of which were acquired from SwissTargetPrediction. Depression-related targets were collected from GeneCards. The intersection between compound-related targets and depression-related targets were screened out, and the overlapped targets were further performed protein-protein interaction, biological functional and pathway enrichment analysis. Finally, networks of Si-Ni-San against depression were constructed and visualized by Cytoscape.

Results

One hundred nineteen compounds in Si-Ni-San were determined, of which 24 bioactive compounds were obtained. Then, 137 overlapped targets of Si-Ni-San against depression were collected. AKT1, PIK3R1, PIK3CA, mTOR, MAPK1 and MAPK8 were the key targets. Furthermore, PI3K-Akt signalling pathway, serotonergic synapse, MAPK signalling pathway and neurotrophin signalling pathway were involved in the antidepressant mechanism of Si-Ni-San. It showed that components like sinensetin, hesperetin, liquiritigenin, naringenin, quercetin, albiflorin and paeoniflorin were the mainly key active compounds for the antidepressant effect of Si-Ni-San.

Conclusions

This study demonstrated the key components, key targets and potential pharmacological mechanisms of Si-Ni-San against depression. These results indicate that Si-Ni-San is a promising therapeutic approach for treatment of depression, and may provide evidence for the research and development of drugs for treating depression.

Recent Progress in Mass Spectrometry-Based Metabolomics in Major Depressive Disorder Research

Major depressive disorder (MDD) is a serious mental illness with a heavy social burden, but its underlying molecular mechanisms remain unclear. Mass spectrometry (MS)-based metabolomics is providing new insights into the heterogeneous pathophysiology, diagnosis, treatment, and prognosis of MDD by revealing multi-parametric biomarker signatures at the metabolite level. In this comprehensive review, recent developments of MS-based metabolomics in MDD research are summarized from the perspective of analytical platforms (liquid chromatography-MS, gas chromatography-MS, supercritical fluid chromatography-MS, etc.), strategies (untargeted, targeted, and pseudotargeted metabolomics), key metabolite changes (monoamine neurotransmitters, amino acids, lipids, etc.), and antidepressant treatments (both western and traditional Chinese medicines). Depression sub-phenotypes, comorbid depression, and multi-omics approaches are also highlighted to stimulate further advances in MS-based metabolomics in the field of MDD research.

Characterization of the natural peptidome of four leeches by integrated proteogenomics and pseudotargeted peptidomics

Animal-derived drugs are an indispensable part of folk medicine worldwide. However, their chemical constituents are poorly approached, which leads to the low level of the quality standard system of animal-derived drugs and further causes a chaotic market. Natural peptides are ubiquitous throughout the organism, especially in animal-derived drugs. Thus, in this study, we used multi-source leeches, including Hirudo nipponica (HN), Whitmania pigra (WP), Whitmania acranulata (WA), and Poecilobdella manillensis (PM), as a model. A strategy integrating proteogenomics and novel pseudotargeted peptidomics was developed to characterize the natural peptide phenotype and screen for signature peptides of four leech species. First, natural peptides were sequenced against an in-house annotated protein database of closely related species constructed from RNA-seq data from the Sequence Read Archive (SRA) website, which is an open-sourced public archive resource. Second, a novel pseudotargeted peptidomics integrating peptide ion pair extraction and retention time transfer was established to achieve high coverage and quantitative accuracy of the natural peptides and to screen for signature peptides for species authentication. In all, 2323 natural peptides were identified from four leech species whose databases were poorly annotated. The strategy was shown to significantly improve peptide identification. In addition, 36 of 167 differential peptides screened by pseudotargeted proteomics were identified, and about one-third of them came from the leucine-rich repeat domain (LRR) proteins, which are widely distributed in organisms. Furthermore, six signature peptides were screened with good specificity and stability, and four of them were validated by synthetic standards. Finally, a dynamic multiple reaction monitoring (dMRM) method based on these signature peptides was established and revealed that one-half of the commercial samples and all of the Tongxinluo capsules were derived from WP. All in all, the strategy developed in this study was effective for natural peptide characterization and signature peptide screening, which could also be applied to other animal-derived drugs, especially for modelless species that are less studied in protein database annotation.

Identification of Five Gelatins Based on Marker Peptides from Type I Collagen by Mass Spectrum in Multiple Reaction Monitoring Mode

In this study, a novel pseudo-targeted peptidomics strategy, integrating the transition list generated by an in-house software (Pep-MRMer) and the retention time transfer by high-abundance ion-based retention time calibration (HAI-RT-cal), was developed to screen marker peptides of gelatins from five closely related animal species, including porcine, bovine, horse, mule, and donkey. Five marker peptides were screened from the molecular phenotypic differences of type I collagen. Furthermore, a simple and robust 10 min multiple reaction monitoring (MRM) method was established and performed well in distinguishing different gelatins, particularly in discerning horse-hide gelatin (HHG) and mule-hide gelatin (MHG) from donkey-hide gelatin (DHG). The market investigation revealed the serious adulteration of DHG. Meantime, the pseudo-targeted peptidomics could be used to screen marker peptides of other gelatin foods.

Untargeted Metabolomics Reveals Antidepressant Effects in a Marine Photosynthetic Organism: The Diatom Phaeodactylum tricornutum as a Case Study

The increased use of antidepressants, along with their increased occurrence in aquatic environments, is of concern for marine organisms. Although these pharmaceutical compounds have been shown to negatively affect marine diatoms, their mode of action in these non-target, single-cell phototrophic organisms is yet unknown. Using a Fourier-transform ion cyclotron-resonance mass spectrometer (FT-ICR-MS) we evaluated the effects of fluoxetine in the metabolomics of the model diatom Phaeodactylum tricornutum, as well as the potential use of the identified metabolites as exposure biomarkers. Diatom growth was severely impaired after fluoxetine exposure, particularly in the highest dose tested, along with a down-regulation of photosynthetic and carbohydrate metabolisms. Notably, several mechanisms that are normally down-regulated by fluoxetine in mammal organisms were also down-regulated in diatoms (e.g., glycerolipid metabolism, phosphatidylinositol signalling pathway, vitamin metabolism, terpenoid backbone biosynthesis and serotonin remobilization metabolism). Additionally, the present work also identified a set of potential biomarkers of fluoxetine exposure that were up-regulated with increasing fluoxetine exposure concentration and are of high metabolic significance following the disclosed mode of action, reinforcing the use of metabolomics approaches in ecotoxicology.

Revealing the pharmacological effect and mechanism of darutoside on gouty arthritis by liquid chromatography/mass spectrometry and metabolomics

Darutoside is a diterpenoids compound with significant anti-inflammatory activity, however the pharmacological action and mechanism are still unclear. Metabolomics strategy was used to uncovering the pharmacological action and effective mechanism of darutoside against acute gouty arthritis rats. Liquid chromatography coupled with mass spectrometry technique was performed to explore the serum metabolites and potential pathways. We found that darutoside can up-regulate the level of glutamate, alanine, chenodeoxycholic acid, 1-methyladenosine, aspartic acid, citric acid, and down-regulate the level of valine, isoleucine, glutamine, alanyl-threonine, pyruvic acid, gamma-aminobutyric acid, uric acid. Metabolic pathway analysis showed that the therapeutic effect of darutoside was involved in amino acid metabolism, sugar metabolism, fatty acid metabolism, energy metabolism, purine metabolism and butanoate metabolism. It indicated that darutoside protect against acute gouty arthritis by regulating the expression of the key protein targets. It revealed that the mechanism of darutoside on acute gouty arthritis, which may be leading to the changes of serum metabolites, metabolic pathways and key protein targets to improve immune system response, inhibit oxidative stress and inflammatory response. It provides a novel method for molecular mechanisms of natural product in the disease treatment.

Comprehensive pseudotargeted metabolomics analysis based on two-phase liquid extraction-UHPLC-MS/MS for the investigation of depressive rats

Pseudotargeted analysis combines the advantages of untargeted and targeted metabolomics methods. This study proposed a comprehensive pseudotargeted metabolomics method based on two-phase liquid extraction using ultra-high-performance liquid chromatography-tandem mass spectrometry. Two-phase liquid extraction, composed of both aqueous and organic phases, extracted a wide range of metabolites from polar to nonpolar in plasma samples. Besides, the two phases were combined and detected in a single injection to save analytical time. A total of 486 potential metabolites were detected by the developed approach. Compared with the conventional methanol-based protein precipitation method, the two-phase liquid extraction method significantly increased the metabolite coverage by 20.29%. Besides, the proposed pseudotargeted metabolomics method exhibited higher sensitivity and better repeatability than the untargeted method. Finally, we applied the established pseudotargeted method to the metabolomics study of depressive rats and screened 53 differential variables. Sixteen determined differential metabolites were mainly in four metabolic pathways, including glycerophospholipid, arachidonic acid, sphingolipid metabolisms, pentose and glucuronate interconversions. The results indicated that the pseudotargeted method based on two-phase liquid extraction broadened the metabolite coverage with good sensitivity and repeatability, exhibiting significant potential for discovering differential metabolites in metabolomics studies. This article is protected by copyright. All rights reserved.

Peripheral blood and urine metabolites and biological functions in post-stroke depression

Post-stroke depression (PSD) is the most common and severe neuropsychiatric complication after stroke. However, the molecular mechanism of PSD is still unclear. Previous studies have identified peripheral blood and urine metabolites associated with PSD using metabolomics techniques. We searched and systematically summarized metabolites that may be involved in metabolic changes in peripheral blood and urine of patients with PSD from the Metabolite Network of Depression Database (MENDA) and other biomedical databases. MetaboAnalyst5.0 software was used for pathway analysis and enrichment analysis of differential metabolites, and subgroup analyses were performed according to tissue types and metabolomics techniques. We identified 47 metabolites that were differentially expressed between patients with and without PSD. Five differential metabolites were found in both plasma and urine, including L-glutamic acid, pyroglutamic acid, palmitic acid, L-phenylalanine, and L-tyrosine. We integrated these metabolites into metabolic pathways, and six pathways were significantly altered. These pathways could be roughly divided into three modules including amino acid metabolism, nucleotide metabolism, and glucose metabolism. Among them, the most significantly altered pathway was "phenylalanine metabolism" and the pathway containing the most associated metabolites was "aminoacyl-tRNA biosynthesis", which deserve further study to elucidate their role in the molecular mechanism of PSD. In summary, metabolic changes in peripheral blood and urine are associated with PSD, especially the disruption of "phenylalanine metabolism" and "aminoacyl-tRNA biosynthesis" pathways. This study provides clues to the metabolic characteristics of patients with PSD, which may help to elucidate the molecular pathogenesis of PSD.

Immunometabolism at the service of traditional Chinese medicine

To enhance therapeutic efficacy and reduce adverse effects, ancient practitioners of traditional Chinese medicine (TCM) prescribe combinations of plant species/animal species and minerals designated "TCM formulae" developed based on TCM theory and clinical experience. TCM formulae have been shown to exert curative effects on complex diseases via immune regulation but the underlying mechanisms remain unknown at present. Considerable progress in the field of immunometabolism, referring to alterations in the intracellular metabolism of immune cells that regulate their function, has been made over the past decade. The core context of immunometabolism is regulation of the allocation of metabolic resources supporting host defense and survival, which provides a critical additional dimension and emerging insights into how the immune system and metabolism influence each other during disease progression. This review summarizes research findings on the significant association between the immune function and metabolic remodeling in health and disease as well as the therapeutic modulatory effects of TCM formulae on immunometabolism. Progressive elucidation of the immunometabolic mechanisms involved during the course of TCM treatment continues to aid in the identification of novel potential targets against pathogenicity. In this report, we have provided a comprehensive overview of the benefits of TCM based on regulation of immunometabolism that are potentially applicable for the treatment of modern diseases.

A pseudotargeted method based on sequential window acquisition of all theoretical spectra mass spectrometry acquisition and its application in quality assessment of traditional Chinese medicine preparation-Yuanhu Zhitong tablet

Quality control plays a key role in the application of Chinese materia medica, especially in the preparation of traditional Chinese medicine. A pseudotargeted analysis method using an ultra-high-performance liquid chromatography-quadrupole-time-of-flight-mass spectrometry that was operated in the sequential window acquisition of all theoretical spectra mode was proposed to explore the chemical markers of traditional Chinese medicine preparation. Full-scan-based untargeted analysis was applied to extract the target ions. After data preprocessing, 302 target ions were extracted and used for the subsequent sequential window acquisition of all theoretical spectra analyses. The established sequential window acquisition of all theoretical spectra-based pseudotargeted approaches exhibited good repeatability and a wide linear range. The established method was successfully applied to discover analytical markers for the Yuanhu Zhitong tablet. After multivariate statistical analysis, 94 potential markers were identified. Ten markers were annotated by matching accurate m/z and product ion information obtained from previous reports. It is clearly indicated that the pseudotargeted analysis could make a great contribution to the quality assessment of traditional Chinese medicine preparation as a newly emerging technique.

Simultaneous Analysis of the Metabolome and Lipidome Using Polarity Partition Two-Dimensional Liquid Chromatography-Mass Spectrometry

Comprehensive metabolic profiling is a considerable challenge for systems biology since the metabolites in biological samples have significant polarity differences. A heart-cutting two-dimensional liquid chromatography-mass spectrometry (2D-LC-MS) method-based polarity partition was established to analyze both the metabolome and lipidome in a single run. Based on the polarity partition strategy, metabolites with high polarity were retained and separated by one-dimensional hydrophilic chromatography, while low- and medium-polarity lipids were collected into a sample loop and injected into two-dimensional reversed-phase chromatography for separation. A simple online dilution strategy realized the online coupling of the 2D-LC-MS, which effectively solved band broadening and peak distortion caused by solvent incompatibility. Moreover, a dual gradient elution procedure was introduced to further broaden the coverage of low-polarity lipids. The metabolites' log P values, which this 2D-LC-MS method could analyze, ranged from -8.79 to 26.86. The feasibility of the 2D-LC-MS system was demonstrated by simultaneous analysis of the metabolome and lipidome in rat plasma related to depression. A total of 319 metabolites were determined within 40 min, including organic acids, nucleosides, carbohydrate derivatives, amino acids, lipids, and other organic compounds. Finally, 44 depression-related differential metabolites were screened. Compared with conventional LC-MS-based methods, the 2D-LC method covered over 99% of features obtained by two conventional methods. In addition, the selectivity and resolution of the hydrophilic metabolites were improved, and the matrix effects of the hydrophobic metabolites were reduced in the developed method. The results indicated that the established 2D-LC system is a powerful tool for comprehensive metabolomics studies.

Determination of inflammation-related lipids in depressive rats by on-line supercritical fluid extraction-supercritical fluid chromatography-tandem mass spectrometry

An on-line supercritical fluid extraction coupled with supercritical fluid chromatography-quadrupole tandem mass spectrometry method was developed to determine lipids related to inflammation in brain tissues of depressed rats. The analysis of 23 lipids from extraction to separation and detection only took 15 min and required 1 mg of brain tissue powder. The matrix effect of the on-line method for endogenous lipids was systematically investigated, and targeted lipids were quantified by matrix effect corrected calibration curves in this study. The on-line method was comprehensively optimized and evaluated. All calibration curves for lipids showed good linearity (correlation coefficient >0.99). The limits of detection and the limits of quantification were in the range of 0.0261-0.396 pg and 0.0791-1.20 pg. The recoveries and the matrix effect were in the range of 85.3-117.5% and 51.9-176.6%, respectively. The relative standard deviations of precision ranged from 2.7 to 14.2%, with accuracies higher than 87.2%. Compared with liquid-liquid extraction coupled with liquid chromatography-tandem mass spectrometry method, the on-line method obtained higher recovery and sensitivity with significantly reduced analytical time, manual operations, and sample amounts. Finally, this on-line method was applied to analyses of brain tissues of depressed rats. Six pro-inflammatory lipids increased in depressed rats, while six anti-inflammatory lipids decreased. Liquiritin and fluoxetine were presumed to promote a similar synthesis of anti-inflammatory lipids. Based on the results, this on-line method showed great promise in analyzing lipids in complex biological samples.

A high coverage pseudotargeted lipidomics method based on three-phase liquid extraction and segment data-dependent acquisition using UHPLC-MS/MS with application to a study of depression rats

Pseudotargeted analysis combines the advantages of untargeted and targeted lipidomics methods based on chromatography-mass spectrometry (MS). This study proposed a comprehensive pseudotargeted lipidomics method based on three-phase liquid extraction (3PLE) and segment data-dependent acquisition (SDDA). We used a 3PLE method to extract the lipids with extensive coverage from biological matrixes. 3PLE was composed of one aqueous and two organic phases. The upper and middle organic phases enriched neutral lipids and glycerophospholipids, respectively, combined and detected together. Besides, the SDDA strategy improved the detection of co-elution ions in the lipidomics analysis. A total of 554 potential lipids were detected by the developed approach in both positive and negative modes using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Compared with the conventional liquid-liquid extraction (LLE) approaches, including methyl tert-butyl ether (MTBE) and Bligh-Dyer (BD) methods, 3PLE combined with SDDA significantly increased the lipid coverage 87.2% and 89.7%, respectively. Also, the proposed pseudotargeted lipidomics approach exhibited higher sensitivity and better repeatability than the untargeted approach. Finally, we applied the established pseudotargeted method to the plasma lipid profiling from the depressed rats and screened 61 differential variables. The results demonstrated that the pseudotargeted method based on 3PLE and SDDA broadened lipid coverage and improved the detection of co-elution ions with excellent sensitivity and precision, indicating significant potential for the lipidomics analysis.

A green and efficient pseudotargeted lipidomics method for the study of depression based on ultra-high performance supercritical fluid chromatography-tandem mass spectrometry

The pseudotargeted lipidomics method integrates the advantages of untargeted andtargeted lipidomics methods as a novel emerging approach. In this study, a green andefficient pseudotargeted lipidomics method based on ultra-high performancesupercritical fluid chromatography-tandem mass spectrometry (UHPSFC-MS/MS) wasdeveloped. The tandem mass spectra of the analytes were obtained by using UHPSFCwith quadrupole-time of flight MS (Q-TOF MS) in MS E mode and the multiplereaction monitoring (MRM) transitions of the lipidome were defined. Then, thecandidate MRM transitions were verified by UHPSFC with triple quadrupole massspectrometry (QqQ MS) in the scheduled MRM mode. In total, 758 potential lipidscorresponding to 509 and 249 MRM transitions were detected within 8 min in positiveand negative modes, respectively. The established pseudotargeted lipidomics methodwas validated to have excellent analytical characteristics. Compared with thepseudotargeted method based on ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), the UHPSFC-MS/MS-basedpseudotargeted method not only reduced the analytical time by half but also improvedthe sensitivity and resolution for most analytes, especially had better separation forlipid isomers. Besides, the UHPSFC-MS/MS-based pseudotargeted method showedhigher sensitivity and better repeatability for most analytes than the UHPSFC-MS/MS-based untargeted method. The established method was finally applied to investigatingthe lipid profiles of the plasma from the depressed rats and 33 differential variableswere screened, which related to three metabolic pathways. The results indicated thatthe UHPSFC-MS/MS-based pseudotargeted method is reliable and efficient and couldbe used in the lipidomics studies.

Development of a plasma pseudotargeted metabolomics method based on ultra-high-performance liquid chromatography-mass spectrometry

Untargeted methods are typically used in the detection and discovery of small organic compounds in metabolomics research, and ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) is one of the most commonly used platforms for untargeted metabolomics. Although they are non-biased and have high coverage, untargeted approaches suffer from unsatisfying repeatability and a requirement for complex data processing. Targeted metabolomics based on triple-quadrupole mass spectrometry (TQMS) could be a complementary tool because of its high sensitivity, high specificity and excellent quantification ability. However, it is usually applicable to known compounds: compounds whose identities are known and/or are expected to be present in the analyzed samples. Pseudotargeted metabolomics merges the advantages of untargeted and targeted metabolomics and can act as an alternative to the untargeted method. Here, we describe a detailed protocol of pseudotargeted metabolomics using UHPLC-TQMS. An in-depth, untargeted metabolomics experiment involving multiple UHPLC-HRMS runs with MS at different collision energies (both positive and negative) is performed using a mixture obtained using small amounts of the analyzed samples. XCMS, CAMERA and Multiple Reaction Monitoring (MRM)-Ion Pair Finder are used to find and annotate peaks and choose transitions that will be used to analyze the real samples. A set of internal standards is used to correct for variations in retention time. High coverage and high-performance quantitative analysis can be realized. The entire protocol takes ~5 d to complete and enables the simultaneously semiquantitative analysis of 800-1,300 metabolites.