Investigation of the chemical compounds in Pheretima aspergillum (E. Perrier) using a combination of mass spectral molecular networking and unsupervised substructure annotation topic modeling together with in silico fragmentation prediction

Exploring the mechanism of Sendeng-4 against rheumacid arthritis through integrated serum pharmacochemistry, transcriptomics, and network pharmacology

Mongolian medicine Sendeng-4 (SD-4) has demonstrated satisfactory clinical treatment outcomes for rheumatoid arthritis (RA); nevertheless, its bioactive components and the related mechanisms have not yet been clearly elucidated. To explore the bioactive chemical components of SD-4 in the treatment of RA and its possible mechanisms, an High Performance Liquid Chromatography-tandem mass spectrometry (HPLC-MS/MS) method was established to simultaneously quantify the main components in SD-4, and ultraperformance LC-Q-Exactive-MS/MS (UPLC-Q-Exactive-MS/MS) was used to identify the phytochemicals absorbed in the serum. Then, using network pharmacology methods, these components were constructed into a compound-target network of RA to predict possible biological targets of SD-4 as well as potential signaling pathways. Transcriptomics analysis and molecular docking were used to validate the results of network pharmacology. Subsequently, we established a complete Freund's adjuvant-induced RA rat model and observed the anti-RA effects of SD-4 through assessments of foot swelling, ankle diameter, arthritis score, morphology, serum inflammatory factors, and histopathological analysis of synovial tissue. Specifically, reverse transcription-quantitative polymerase chain reaction, Western blot, and immunohistochemical analysis were used in animal experiments to validate the pathways of serum phytochemistry, network pharmacology, and transcriptomics. Tannic acid, gallic acid, corilagin, crocin I, gardenoside, ferulic acid, quercetin, limonin, rutin, chlorogenic acid, verbascoside, catechin, epicatechin, myricetin, and dihydromyricetin in SD-4 showed good linearity within their respective concentration ranges (r ≥ 0.9991); the average recovery rate was 93.77%-109.17% (relative standard deviation < 2%). A total of 37 compounds were identified in serum samples. Based on this, network pharmacology methods collected 739 genes related to these identified compounds in SD-4 and 3807 genes related to RA. Network pharmacology and transcriptomic analysis demonstrated that the phosphatidylinositol 3-kinase (PI3K)-protein kinase B (Akt) signaling pathway is the most relevant pathway affected by SD-4 in RA. In the experiments, SD-4 treatment reduced ankle swelling and arthritis scores in RA rats, improved symptoms, and reduced the production of inflammatory factors. Compared with the RA model group, SD-4 treatment significantly reduced the expression of PI3K-Akt pathway-related messenger RNA and proteins. In addition, immunohistochemical analysis confirmed these results. This study combined serum phytochemistry, network pharmacology, and transcriptomics to demonstrate that SD-4 can alleviate RA by regulating the PI3K-Akt signaling pathway. This research provides a theoretical basis for the clinical application of SD-4 and offers an effective strategy for the identification of bioactive substances in traditional Chinese medicine formulas and the study of their potential mechanisms.

Identification of chemical components and rat serum metabolites in Danggui Buxue decoction based on UPLC-Q-TOF-MS, the UNIFI platform and molecular networks

Danggui Buxue Decoction (DBD), consisting of Astragalus membranaceus (Fisch.) Bge. var. mongholicus (Bge.) Hsiao (Huangqi, HQ) and Angelica sinensis (Oliv.) Diels (Danggui, DG), is a traditional Chinese medicine (TCM) formula with the function of tonifying Qi and promoting blood. In this study, ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) was used to comprehensively identify the chemical constituents in DBD and those entering into the rat serum after gastric perfusion. A combination of the UNIFI platform and Global Natural Product Social molecular networking (GNPS) was used to analyze the chemical composition of DBD. As a result, 207 compounds were unambiguously or tentatively identified including 60 flavonoids, 38 saponins, 35 organic acids, 26 phthalides, 12 phenylpropanoids, 11 amino acids and 25 others. Furthermore, a total of 80 compounds, including 29 prototype components and 51 exogenous metabolites, were detected in the serum of rats. Phase I reactions (oxidation, reduction, and hydration), phase II reactions (methylation, sulfation, and glucuronidation), and their combinations were the main metabolic pathways of DBD. The results provided fundamental information for further studying the pharmacological mechanisms of DBD, as well as its quality control research.

Targeted isolation of diterpenoids and sesquiterpenoids from Daphne gemmata E. Pritz. ex Diels using molecular networking together with network annotation propagation and MS2LDA

Investigation of the whole plant of Daphne gemmata E. Pritz. ex Diels (Thymelaeaceae) using molecular networking coupled to Network Annotation Propagation (NAP) and unsupervised substructure annotation (MS2LDA) led to the discovery of five tigliane diterpenoids, 14 guaiane sesquiterpenoids, one rhamnofolane diterpenoid and three carotene sesquiterpenoids. The structures of the eight undescribed compounds, daphnorbol A and daphnegemmatoids A-G, were characterized by detailed spectroscopic analyses, NMR and ECD calculations, application of Snatzke's method and single-crystal X-ray diffraction analysis. All isolated compounds were evaluated for their cytotoxic activities against HepG2, A549, and MCF-7 cells by MTT assay. Daphnorbol A exhibited significant cytotoxic activity against HepG2 and A549 cells with IC50 values of 4.06 μM and 6.35 μM, respectively. Prostratin showed potent cytotoxic activity against HepG2 and A549 cells with IC50 values of 6.06 μM and 5.45 μM, respectively. Further Hoechst 33,258 and AO-EB staining assays indicated that daphnorbol A and prostratin could induce apoptosis in HepG2 and A549 cells.

An Integrated Strategy of Chemical Fingerprint and Network Pharmacology for the Discovery of Efficacy-Related Q-Markers of Pheretima

Pheretima, one of the animal-derived traditional Chinese medicines, has been wildly used in various cardiovascular and cerebrovascular diseases, including stroke, coronary heart disease, hyperlipidemia, and hyperglycemia. However, it was still a big challenge to select the quality markers for Pheretima quality control. The fingerprint and network pharmacology-based strategy was proposed to screen the efficiency related quality markers (Q-Markers) of Pheretima. The ratio of sample to liquid, ultrasonic-extraction time, temperature, and power were optimized by orthogonal design, respectively. The chemical fingerprint of forty batches of Pheretima was established, and six common peaks were screened. The network pharmacology was used to construct the Pheretima-Components-Targets-Pathways-Stroke network. It was found that six potential efficacy Q-markers in Pheretima could exert the relaxing meridians effect to treat stroke through acting on multiple targets and regulating various pathways. A simple HPLC-DAD method was developed and validated to determine the efficacy Q-markers. Grey relational analysis was used to further verify the relation of potential efficiency related quality markers with the anticoagulation activity of Pheretima, which indicated that the contents of these markers exhibited high relationship with the anticoagulation activity. It was concluded that hypoxanthine, uridine, phenylalanine, inosine, guanosine, and tryptophan were selected as quality markers related to relaxing meridians to evaluate the quality of Pheretima. The fingerprint and network pharmacology-based strategy was proved to be a powerful strategy for the discovery of efficiency related Q-markers of Pheretima.

A complementary chromatographic strategy for integrated components characterization of Imperatae Rhizoma based on convergence and liquid chromatography combined with mass spectrometry and molecular network

The complexity of natural ingredients and the diversity of preparations are the major obstacles to the quality evaluation of traditional Chinese medicines (TCMs). A more comprehensive characterization of herbal compounds using different types of chromatographic separation techniques and covering a diverse polarity range can help evaluate the quality of TCMs. In this study, we first proposed a comprehensive method for characterizing compounds derived from Imperatae Rhizoma by combining the complementary strengths of UPCC-QTOF-MS (ultra-performance convergence chromatography coupled with quadrupole-time of flight mass spectrometry) with UPLC-QTOF-MS (ultra-performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry). The method based on the UNIFI scientific platform significantly shortened the analysis time and enabled a more comprehensive characterization of known and unreported compounds. Meanwhile, a feature-based molecular network (FBMN) was established on the Global Natural Product Social (GNPS) to infer potential compounds by rapidly classifying and visualizing these components. A total of 62 compounds in Imperatae Rhizoma were jointly characterizedand classified into six types. In comparison, the UPCC-QTOF-MS technology individually characterized 17 components, including lactones, phenols, aldehydes, phenylpropanoids, and small polar organic acids. The UPLC-QTOF-MS technology characterized 16 compounds mainly phenylpropionic acids, flavonoid glycosides, and chromone glycosides. Furthermore, three types of characteristic compounds could be well aggregated into an FBMN approach. Five possible potential new compounds were detected through the supplementary identification of GNPS and the correlation analysis of vicinal known compounds. The strategy was first applied to Imperatae Rhizoma and facilitated the characterization of a large quantity of data to provide comprehensive chemical composition results. This approach can be easily extended to the study of the material basis of other herbs or preparations in order to improve the accuracy of herb quality evaluation.

Software Assisted Multi-Tiered Mass Spectrometry Identification of Compounds in Traditional Chinese Medicine: Dalbergia odorifera as an Example

The complexity of metabolites in traditional Chinese medicine (TCM) hinders the comprehensive profiling and accurate identification of metabolites. In this study, an approach that integrates enhanced column separation, mass spectrometry post-processing and result verification was proposed and applied in the identification of flavonoids in Dalbergia odorifera. Firstly, column chromatography fractionation, followed by liquid chromatography–tandem mass spectrometry was used for systematic separation and detection. Secondly, a three-level data post-processing method was applied to the identification of flavonoids. Finally, fragmentation rules were used to verify the flavonoid compounds. As a result, a total of 197 flavonoids were characterized in D. odorifera, among which seven compounds were unambiguously identified in level 1, 80 compounds were tentatively identified by MS-DIAL and Compound Discoverer in level 2a, 95 compounds were annotated by Compound discoverer and Peogenesis QI in level 2b, and 15 compounds were exclusively annotated by using SIRIUS software in level 3. This study provides an approach for the rapid and efficient identification of the majority of components in herbal medicines.

Zhilong Huoxue Tongyu Capsules Ameliorate Early Brain Inflammatory Injury Induced by Intracerebral Hemorrhage via Inhibition of Canonical NFкβ Signalling Pathway

Background: Intracerebral hemorrhage (ICH) is a debilitating and fatal condition with continuously rising incidence globally, without effective treatment available. Zhilong Huoxue Tongyu (ZLHXTY) capsule is a traditional Chinese medicine that is used for ICH treatment in China. However, the evidence based mechanism is not clear.

Purpose: To study the protective effects of ZLHXTY capsules against ICH pathogenesis via targetting nuclear factor kappa β (NFкβ) canonical signalling pathway.

Methods: C57BL/6 J mice ICH models using autologous blood injection were used to study the effect of ZLHXTY (1.4 g/kg P.O.) after 24 and 72 hrs of ICH induction. The neurological scoring, corner turn test and balance beam with scoring was performed to assess neurological damage. Hematoxylin/eosin and nissl staining was used for histopathological evaluation. Levels of TNFα, NFкB, iNOS, COX2, IL1, IL6 were measured using real time qPCR and western blotting. Protein levels of IKKβ and IкBα were analyzed through western blotting. Immunofluorescence for co-expression of NeuN/TNFα, NeuN/NFкB, Iba1/TNFα, and Iba1/NFкB was also performed.

Results: Treatment with ZLHXTY capsules after ICH ameliorated inflammatory brain injury after 24 and 72 h; revealed by neurological scoring, hematoxylin/eosin and nissl staining. The qPCR and western blot analyses demonstrated significant downregulation of TNFα, NFкB, iNOS, COX2, IL1β and IL6. Further, the IKKβ and IкBα revealed significant downregulation and upregulation respectively in western blot. Immunofluorescence also revealed attenuated expression of TNFα and NFкB in neurons and also low expression of Iba1.

Conclusion: ZLHXTY capsules elicit its neuroprotective effect by targetting the NFкβ canonical signalling pathway, thereby ameliorating the ICH induced brain injury.

The antifibrotic effect of pheretima protein is mediated by the TGF-β1/Smad2/3 pathway and attenuates inflammation in bleomycin-induced idiopathic pulmonary fibrosis

ETHNOPHARMACOLOGICAL RELEVANCE

Pheretima is a traditional Chinese medicine that could treat various lung diseases such as asthma, pneumonia, and lung cancer effectively; however, limited studies on the use of Pheretima protein in the treatment of lung diseases have been conducted to date.

AIM OF THE STUDY

The aim of this study was to explain the antipulmonary fibrosis mechanism of the Pheretima protein and elucidate its possible cell signaling pathways.

MATERIAL AND METHODS

Fresh pheretima was freeze-dried to obtain the Pheretima protein. Divide C57BL/6 mice into control and bleomycin (BLM)-induced models, pirfenidone, and Pheretima protein-treatment groups. Three weeks later, they were treated with H&E and Masson's trichrome staining to assess lung injury and fibrosis. Pulmonary fibrosis was assessed using immunohistochemistry (IHC), realtime-PCR (RT-PCR), and western blotting. Inflammation was assessed using the alveolar lavage fluid.

RESULTS

Pheretima protein inhibited epithelial-mesenchymal transition (EMT) and extracellular matrix (ECM) deposition and reduced inflammation. It also reduced the levels of Smad2/3, pSmad2/3, and transforming growth factor-beta 1 (TGF-β1). Thus, our results indicate that Pheretima protein can alleviate BLM-induced pulmonary fibrosis in a mouse model.

CONCLUSION

Pheretima protein inhibits ECM, EMT, and antiinflammatory markers, which in turn ameliorates BLM-induced pulmonary fibrosis. Preliminary mechanistic studies indicated that Pheretima protein can exert its biological activity by downregulating the TGF-β1/Smad2/3 pathway.

Combining multiple acquisition modes and computational data annotation for structural characterization in traditional Chinese medicine: Miao Nationality medicine Qijiao Shengbai Capsule as a case study

Qijiao Shengbai Capsule (QSC) is a reputable Miao Nationality medicine used for treating leukopenia, but its chemical composition has not yet been elucidated. We herein present a strategy, by integrating multiple data acquisition, computational data annotation and processing methods to visualize and identify the complicated constituents in QSC based on ultra-high-performance liquid chromatography coupled with traveling wave ion mobility quadrupole time-of-flight mass spectrometry (UPLC-TWIMS-QTOF-MS). The multiple data acquisition modes, including data-independent mass spectrometry^Energy (MS^E), data-independent high-definition mass spectrometry^Energy (HDMS^E), and fast data-dependent acquisition (fast-DDA), in both positive and negative ion modes, were conducted on a Waters-SYNAPT G2-Si mass spectrometer with an ESI source. An in-house library built by the UNIFI platform could efficiently process the peak annotation of known compounds, whilst different structural types were clustered in the molecular networks for the analogous classification and structural annotation of the unknown ones. Neutral loss, diagnostic ions, feature fragmentation behaviors, and community curation of mass spectrometry data of known compounds helped exploit those similar neighboring nodes of unknown compounds. Moreover, by combination of the predicted CCS values from CCS platform with the experimental CCS values from HDMS^E, as well as diagnostic fragment ions, isomer compounds were annotated. By integrating reference compound comparison, a total of 202 constituents, including 94 flavonoids, 12 saponins, 30 phthalides, 38 organic acids, 3 amino acids, 7 alkaloids and 18 others, were unambiguously characterized or tentatively identified in QSC. Among them, 5 potential new compounds were detected and 12 pairs of isomers were comprehensively distinguished. Conclusively, the established multiple acquisition modes, computational data processing and analysis strategy proved to be useful for the in-depth structural identification of QSC.

Qijiao Shengbai Capsule (QSC) is a reputable Miao Nationality medicine used for treating leukopenia, but its chemical composition has not yet been elucidated.

An integrated approach for structural characterization of Gui Ling Ji by traveling wave ion mobility mass spectrometry and molecular network

Gui Ling Ji (GLJ), an ancient reputable traditional Chinese medicine (TCM) formula prescription, has been applied for the treatment of oligospermia and asthenospermia in clinical practice. However, its inherent compounds have not yet been systematically elucidated, which hampers developing standards or guidelines for quality evaluation and even the understanding of pharmacological effects. In this study, an integrated approach has been established for comprehensive structural characterization of GLJ. Mass spectrometry datasets of GLJ and each of the single herb medicines in this prescription have been developed by dynamic exclusion fast data-dependent acquisition and high-definition data-independent acquisition modes on ultra-high-performance liquid chromatography coupled with travelling wave ion mobility quadrupole time-of-flight mass spectrometry (UPLC-TWIMS-QTOF-MS). A global natural product social molecular networking (GNPS) platform was then applied for the visualization of chemical space of GLJ and further for the high throughput identification of the targeted or untargeted compounds due to the support of data-transmitting from each single herbal medicine to the formula GLJ. Moreover, drift time, predicted CCS, and diagnostic fragment ions were induced for annotating isomer compounds. Consequently, based on molecular network and library hits, a total of 257 compounds from GLJ, which were classified into 4 structural types, were positively or tentatively characterized. Among them, 20 potential new compounds were detected and 30 pairs of isomers were comprehensively distinguished. The established strategy was effective for attribution, classification, recognition of various constituents, and also was valuable for integrating large amounts of disordered MS/MS data and mining trace compounds in other complex chemical or biochemical systems.

An integrated approach for structural characterization of Gui Ling Ji by traveling wave ion mobility mass spectrometry and molecular network.

Metabolic Signatures of the Exposome-Quantifying the Impact of Exposure to Environmental Chemicals on Human Health

Human health and well-being are intricately linked to environmental quality. Environmental exposures can have lifelong consequences. In particular, exposures during the vulnerable fetal or early development period can affect structure, physiology and metabolism, causing potential adverse, often permanent, health effects at any point in life. External exposures, such as the “chemical exposome” (exposures to environmental chemicals), affect the host’s metabolism and immune system, which, in turn, mediate the risk of various diseases. Linking such exposures to adverse outcomes, via intermediate phenotypes such as the metabolome, is one of the central themes of exposome research. Much progress has been made in this line of research, including addressing some key challenges such as analytical coverage of the exposome and metabolome, as well as the integration of heterogeneous, multi-omics data. There is strong evidence that chemical exposures have a marked impact on the metabolome, associating with specific disease risks. Herein, we review recent progress in the field of exposome research as related to human health as well as selected metabolic and autoimmune diseases, with specific emphasis on the impacts of chemical exposures on the host metabolome.

Comprehensive profiling of the chemical components and potential markers in raw and processed Cistanche tubulosa by combining ultra-high-performance liquid chromatography coupled with tandem mass spectrometry and MS/MS-based molecular networking

Chinese materia medica processing is a distinguished and unique pharmaceutical technique in traditional Chinese medicine (TCM), which has played an important role in reducing side effects, increasing medical potencies, altering the properties and even changing the curative effects of raw herbs. The efficacy improvement in medicinal plants is mainly caused by changes in the key substances through an optimized processing procedure. Thus, the use of a rapid method for determining suitable chemical markers between raw and processed TCM is critical in order to elucidate how the bioactive compounds influence the clinical effects. In this study, ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry combined with MS/MS-based molecular networking (MN) and a multivariate statistical analysis method is proposed for the first time. This combination was used to identify the complex chemical composition and clarify the changed constituents between raw and processed Cistanche tubulosa (C. tubulosa). The chemical analysis results demonstrated that a total of 85 compounds were identified in the crude and processed C. tubulosa. Moreover, 34 compounds were detected as chemical markers. This systematic research into chemical constituents and chemical markers of crude and processed C. tubulosa lays a solid foundation for further study of the quality control of C. tubulosa. Moreover, the study provides a new and valuable technical strategy for analyzing chemical components and identifying potential chemical markers for the processing of herbal medicines.Graphical abstract.