An integrated strategy based on characteristic fragment filter supplemented by multivariate statistical analysis in multi-stage mass spectrometry chromatograms for the large-scale detection and identification of natural plant-derived components in rat: The rhubarb case

Chemical Profiling of Shen-Wu-Yi-Shen Tablets Using UPLC-Q-TOF-MS/MS and Its Quality Evaluation Based on UPLC-DAD Combined with Multivariate Statistical Analysis

Shen-Wu-Yi-Shen tablets (SWYST) is a traditional Chinese medicine prescription used for treating chronic kidney disease (CKD). This study aims to characterize the constituents in SWYST and evaluate the quality based on the quantification of multiple bioactive components. SWYST samples were analyzed with ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and a data-processing strategy. As a result, 215 compounds in SWYST were unambiguously identified or tentatively characterized, including 14 potential new compounds. Meanwhile, strategies based on characteristic fragments for rapid identification were summarized, indicating that the qualitative method is accurate and feasible. Notably, the glucose esters of laccaic acid D-type anthraquinone were first found and their fragmentation patterns were described by comparing that of O-glycoside isomers. Besides, based on comparisons of the cleavage ways of mono-acyl glucose with different acyl groups or acylation sites, differences in fragmentation pathways between 1,2-di-O-acyl glucose and 1,6-di-O-acyl glucose were proposed for the first time and verified by reference substances. In addition, a validated UPLC-DAD was established for the determination of 11 major bioactive components related to treatment of CKD (albiflorin, paeoniflorin, 2,3,5,4'-tetrahydroxy-stilbene-2-O-β-d-glucoside (TSG), 1-O-galloyl-2-O-cinnamoyl-β-d-glucose, emodin-8-O-β-d-glucoside, chrysophanol-O-β-d-glucoside, aloe-emodin, rhein, emodin, chrysophanol and physcion). Moreover, TSG and 1-O-galloyl-2-O-cinnamoyl-β-d-glucose were found as the quality markers related to the origins of SWYST based on multivariate statistical analysis. Conclusively, the findings in this work provide a feasible reference for further studies on quality research and mechanisms of action in treating CKD.

Structural annotation of unknown molecules in a miniaturized mass spectrometer based on a transformer enabled fragment tree method

Structural annotation of small molecules in tandem mass spectrometry has always been a central challenge in mass spectrometry analysis, especially using a miniaturized mass spectrometer for on-site testing. Here, we propose the Transformer enabled Fragment Tree (TeFT) method, which combines various types of fragmentation tree models and a deep learning Transformer module. It is aimed to generate the specific structure of molecules de novo solely from mass spectrometry spectra. The evaluation results on different open-source databases indicated that the proposed model achieved remarkable results in that the majority of molecular structures of compounds in the test can be successfully recognized. Also, the TeFT has been validated on a miniaturized mass spectrometer with low-resolution spectra for 16 flavonoid alcohols, achieving complete structure prediction for 8 substances. Finally, TeFT confirmed the structure of the compound contained in a Chinese medicine substance called the Anweiyang capsule. These results indicate that the TeFT method is suitable for annotating fragmentation peaks with clear fragmentation rules, particularly when applied to on-site mass spectrometry with lower mass resolution.

Three new glycosides from the stems of Eurya chinensis R. Br

Two new phenolic glycosides (1 and 2), one known analogue (3), along with a new diterpene glucoside (4) were obtained from ethanolic extract of the stems of Eurya chinensis R. Br. The structures of these isolated compounds were identified by extensive analysis of HRESIMS and NMR spectroscopic data. The cytotoxicities of these compounds were evaluated on MCF-7, A549, HepG2, CaCo2 and 5-8 F cell lines by MTT method, but no obvious activities were observed.

Exploration of Q-Marker of Rhubarb Based on Intelligent Data Processing Techniques and the AUC Pooled Method

Rhubarb, as a traditional Chinese medicine, has several positive therapeutic effects, such as purging and attacking accumulation, clearing heat and purging fire, cooling blood, and detoxification. Recently, Rhubarb has been used in prescriptions for the prevention and treatment of COVID-19, with good efficacy. However, the exploration of effective quantitative approach to ensure the consistency of rhubarb’s therapeutic efficacy remains a challenge. In this case, this study aims to use non-targeted and targeted data mining technologies for its exploration and has comprehensively identified 72 rhubarb-related components in human plasma for the first time. In details, the area under the time-concentration curve (AUC)-pooled method was used to quickly screen the components with high exposure, and the main components were analyzed using Pearson correlation and other statistical analyses. Interestingly, the prototype component (rhein) with high exposure could be selected out as a Q-marker, which could also reflect the metabolic status changes of rhubarb anthraquinone in human. Furthermore, after comparing the metabolism of different species, mice were selected as model animals to verify the pharmacodynamics of rhein. The in vivo experimental results showed that rhein has a positive therapeutic effect on pneumonia, significantly reducing the concentration of pro-inflammatory factors [interleukin (IL)-6 and IL-1β] and improving lung disease. In short, based on the perspective of human exposure, this study comprehensively used intelligent data post-processing technologies and the AUC-pooled method to establish that rhein can be chosen as a Q-marker for rhubarb, whose content needs to be monitored individually.

Qualitative analysis of chemical components in Lianhua Qingwen capsule by HPLC-Q Exactive-Orbitrap-MS coupled with GC-MS

The Lianhua Qingwen (LHQW) capsule is a popular traditional Chinese medicine for the treatment of viral respiratory diseases. In particular, it has been recently prescribed to treat infections caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, due to its complex composition, little attention has been directed toward the analysis of chemical constituents present in the LHQW capsule. This study presents a reliable and comprehensive approach to characterizing the chemical constituents present in LHQW by high-performance liquid chromatography-Q Exactive-Orbitrap mass spectrometry (HPLC-Q Exactive-Orbitrap-MS) coupled with gas chromatography-mass spectrometry (GC-MS). An automated library alignment method with a high mass accuracy (within 5 ppm) was used for the rapid identification of compounds. A total of 104 compounds, consisting of alkaloids, flavonoids, phenols, phenolic acids, phenylpropanoids, quinones, terpenoids, and other phytochemicals, were successfully characterized. In addition, the fragmentation pathways and characteristic fragments of some representative compounds were elucidated. GC-MS analysis was conducted to characterize the volatile compounds present in LHQW. In total, 17 compounds were putatively characterized by comparing the acquired data with that from the NIST library. The major constituent was menthol, and all the other compounds were terpenoids. This is the first comprehensive report on the identification of the major chemical constituents present in the LHQW capsule by HPLC-Q Exactive-Orbitrap-MS, coupled with GC-MS, and the results of this study can be used for the quality control and standardization of LHQW capsules.

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The chemical components of LHQW capsule were revealed using HPLC-Q Exactive-Orbitrap-MS and GC-MS.

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The approach combined HPLC-Q Exactive-Orbitrap-MS and GC-MS methods.

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A library alignment method was used for the rapid identification of the chemical components.

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In total, 120 compounds were putatively identified.