A novel hybrid scan approach enabling the ion-mobility separation and the alternate data-dependent and data-independent acquisitions (HDDIDDA): Its combination with off-line two-dimensional liquid chromatography for comprehensively characterizing the multicomponents from Compound Danshen Dripping Pill

Evaluation and comparison of liquid chromatography/high-resolution mass spectrometry platforms for the separation and characterization of ginsenosides from the leaves of Panax ginseng

The measurement of data repeatability in small-molecule metabolites acquired within and among different liquid chromatography-mass spectrometry (LC-MS) platforms is crucial for data sharing or data transfer in natural products research. This work was designed to investigate and evaluate the separation and detection performance of three commercial high-resolution LC-MS platforms (e.g., Agilent 6550 QTOF, Waters Vion IM-QTOF, and Thermo Scientific Orbitrap Exploris 120) using 68 ginsenoside references and the extract of Panax ginseng leaf. The retention time (tR), measured on these three platforms (under the same chromatography condition), showed good stability in different concentration tests, and within/among different instruments for both intra-day and inter-day precision examinations. Correlation in tR of ginsenosides was also highly determined on these three platforms. In spite of the different mass analyzers involved, these three platforms gave the accurate mass determination ability, especially enhanced resolution gained because of the ion mobility (IM) separation facilitated by IM-quadrupole time-of-flight. The current study has systematically evaluated the separation and MS detection performance enabled by three high-resolution LC-MS platforms taking ginsenosides as the template, and the reported findings can benefit the researchers for the selection of analytical platforms and the purpose of data sharing or data transfer.

Machine learning prediction for constructing a universal multidimensional information library of Panax saponins (ginsenosides)

Accurate characterization of Panax herb ginsenosides is challenging because of the isomers and lack of sufficient reference compounds. More structural information could help differentiate ginsenosides and their isomers, enabling more accurate identification. Based on the VionTM ion-mobility high-resolution LC-MS platform, a multidimensional information library for ginsenosides, namely GinMIL, was established by predicting retention time (tR) and collision cross section (CCS) through machine learning. Robustness validation experiments proved tR and CCS were suitable for database construction. Among three machine learning models we attempted, gradient boosting machine (GBM) exhibited the best prediction performance. GinMIL included the multidimensional information (m/z, molecular formula, tR, CCS, and some MS/MS fragments) for 579 known ginsenosides. Accuracy in identifying ginsenosides from diverse ginseng products was greatly improved by a unique LC-MS approach and searching GinMIL, demonstrating a universal Panax saponins library constructed based on hierarchical design. GinMIL could improve the accuracy of isomers identification by approximately 88%.

A quantitative chemomics strategy for the comprehensive comparison of Murraya paniculata and M. exotica using liquid chromatography coupled with mass spectrometry

Murrayae Folium et Cacumen (MFC) is a traditional Chinese medicine (TCM) derived from two plant species, Murraya exotica L. and Murraya paniculata (L.) Jack, as recorded in the Chinese Pharmacopoeia. However, there is no research available on the comprehensive analysis and comparison of the chemical constituents of these two species. In the present study, an integrated LC-MS-based quantitative metabolome strategy was proposed to conduct a comprehensive and in-depth qualitative and quantitative analysis and comparison of the chemome of M. exotica and M. paniculata. Firstly, the universal chemical information of two plants was obtained by quadrupole-time-of-flight mass spectrometry (Q-TOF-MS) combined with hybrid triple quadrupole-linear ion trap mass spectrometry (Qtrap-MS). Subsequently, a UNIFI in house database, the proposed fragmentation patterns, and a quantitative structure chromatographic retention relationship (QSRR) model were integrated for the rapid, comprehensive, and accurate structural elucidation of the chemical constituents of these two species. Thirdly, a large-scale quantitation method was established using scheduled multiple reaction monitoring mode (sMRM) and 76 primary components were selected as quantitative markers for the method validation. The obtained dataset was then subjected for multivariate statistical analysis to comprehensive comparison of these two plants. As a result, a total of 209 and 212 compounds were identified from M. exotica and M. paniculata, respectively. Among them, 103 common constituents were disclosed in both plants. The multivariate statistical analysis and absolute quantitative analysis revealed noticeable differences in the contents of specific chemical constituents between these two plants. The higher quantity constituents in M. exotica are 7-methoxycoumarins, while polymethoxylated flavonoids are the major constituents in M. paniculata. The common compounds accounted for approximately 80 % of the quantitative components in both plants, which provides a theoretical basis for their common use as the official source of MFC. In sum, the established quantitative chemomics strategy supplies an effective means for comprehensive chemical comparison of multi-source TCMs.

Comprehensive metabolome characterization and comparison between two sources of Dragon's blood by integrating liquid chromatography/mass spectrometry and chemometrics

Dragon's Blood (DB) serves as a precious Chinese medicine facilitating blood circulation and stasis dispersion. Daemonorops draco (D. draco; Qi-Lin-Jie) and Dracaena cochinchinensis (D. cochinchinenesis; Long-Xue-Jie) are two reputable plant sources for preparing DB. This work was designed to comprehensively characterize and compare the metabolome differences between D. draco and D. cochinchinenesis, by integrating liquid chromatography/mass spectrometry and untargeted metabolomics analysis. Offline two-dimensional liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (2D-LC/IM-QTOF-MS), by utilizing a powerful hybrid scan approach, was elaborated for multicomponent characterization. Configuration of an XBridge Amide column and an HSS T3 column in offline mode exhibited high orthogonality (A0 0.80) in separating the complex components in DB. Particularly, the hybrid high-definition MSE-high definition data-dependent acquisition (HDMSE-HDDDA) in both positive and negative ion modes was applied for data acquisition. Streamlined intelligent data processing facilitated by the UNIFI™ (Waters) bioinformatics platform and searching against an in-house chemical library (recording 223 known compounds) enabled efficient structural elucidation. We could characterize 285 components, including 143 from D. draco and 174 from D. cochinchinensis. Holistic comparison of the metabolomes among 21 batches of DB samples by the untargeted metabolomics workflows unveiled 43 significantly differential components. Separately, four and three components were considered as the marker compounds for identifying D. draco and D. cochinchinenesis, respectively. Conclusively, the chemical composition and metabolomic differences of two DB resources were investigated by a dimension-enhanced analytical approach, with the results being beneficial to quality control and the differentiated clinical application of DB.

UPLC-Q-TOF/MS based metabolite profiling and quality marker constituents screening of root, stem and rhizome extracts of Ilex asprella

OBJECTIVE

The root of Ilex asprella (RIA) is a popular plant resource for treating inflammation-related diseases. The purpose of this study was to identify the secondary metabolites, to compare anti-inflammatory effects and to determine the quality marker components among root, stem and rhizome sections of IA.

METHODS

Chemical fingerprints of stem, root and rhizome of IA was determined by high performance liquid chromatography (HPLC). A reliable method using ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) was established for comprehensively determining the chemical constituents of the plants. Anti-inflammatory activities of IA and its ingredients were screened by in vivo mouse ear swelling and in vitro LPS-induced release of NO from RAW264.7 cells experiments.

RESULTS

Root, stem and rhizome of IA have shown high similarity in chemical fingerprints. Totally 149 compounds were characterized in IA, including triterpenoids, triterpenoid saponins, phenolic acids and lignans. 44 of them were identified based on co-occurring Mass2Motifs, including 19 unreported ones, whilst 17 were tentatively confirmed by comparison with reference compounds. No significant anti-inflammatory activity difference among root, stem and rhizome parts of IA was found. Ilexsaponin B2, protocatechualdehyde, isochlorogenic acid B and quinic acid, were screened out as quality marker compounds in IA.

CONCLUSION

A sensitive and rapid strategy was established to evaluate the differences on secondary metabolites of different parts of IA for the first time, and this study may contribute to the quality evaluation of medicinal herbs and provide theoretically data support for further analysis of different parts of IA.

Two Multidimensional Chromatography/High-Resolution Mass Spectrometry Approaches Enabling the In-Depth Metabolite Characterization Simultaneously from Three Glycyrrhiza Species: Method Development, Comparison, and Integration

Two offline multidimensional chromatography/high-resolution mass spectrometry systems (method 1: fractionation and online two-dimensional liquid chromatography, 2D-LC; method 2: fractionation and offline 2D-LC) were established to characterize the metabolites simultaneously from three Glycyrrhiza species. Ion exchange chromatography in the first-dimensional (1D) separation was well fractionated between the acidic (mainly triterpenoids) and weakly acidic components (flavonoids). These obtained subsamples got sophisticated separation by the second (2D) and third dimension (3D) of chromatography either by online reversed-phase chromatography × reversed-phase chromatography (RPC × RPC) or offline hydrophilic interaction chromatography × RPC (HILIC × RPC). Orthogonality for the 2D/3D separations reached 0.73 for method 1 and 0.81 for method 2, respectively. We could characterize 1097 compounds from three Glycyrrhiza species based on an in-house library and 33 reference standards, involving 618 by method 1 and 668 by method 2, respectively. They exhibited a differentiated performance and complementarity in identifying the multiple subclasses of Glycyrrhiza components.

Gain deeper insights into traditional Chinese medicines using multidimensional chromatography combined with chemometric approaches

Traditional Chinese medicines (TCMs) possess a rich historical background, unique theoretical framework, remarkable therapeutic efficacy, and abundant resources. However, the modernization and internationalization of TCMs have faced significant obstacles due to their diverse ingredients and unknown mechanisms. To gain deeper insights into the phytochemicals and ensure the quality control of TCMs, there is an urgent need to enhance analytical techniques. Currently, two-dimensional (2D) chromatography, which incorporates two independent separation mechanisms, demonstrates superior separation capabilities compared to the traditional one-dimensional (1D) separation system when analyzing TCMs samples. Over the past decade, new techniques have been continuously developed to gain actionable insights from complex samples. This review presents the recent advancements in the application of multidimensional chromatography for the quality evaluation of TCMs, encompassing 2D-gas chromatography (GC), 2D-liquid chromatography (LC), as well as emerging three-dimensional (3D)-GC, 3D-LC, and their associated data-processing approaches. These studies highlight the promising potential of multidimensional chromatographic separation for future phytochemical analysis. Nevertheless, the increased separation capability has resulted in higher-order data sets and greater demands for data-processing tools. Considering that multidimensional chromatography is still a relatively nascent research field, further hardware enhancements and the implementation of chemometric methods are necessary to foster its robust development.

Characterization and comparison of cardiomyocyte protection activities of non-starch polysaccharides from six ginseng root herbal medicines

Ginseng is rich of polysaccharides, however, the evidence supporting polysaccharides to distinguish various ginseng species is rarely reported. Focusing on six root ginseng (e.g., Panax ginseng-PG, P. quinquefolius-PQ, P. notoginseng-PN, red ginseng-RG, P. japonicus-PJ, and P. japonicus var. major-PJM), the contained non-starch polysaccharides (NPs) were structurally characterized and compared by both the chemical and biological evaluation. Holistic fingerprinting at three levels (the NPs and the acid hydrolysates involving oligosaccharides and monosaccharides) utilized various chromatography methods, and the treatment of H9c2 cells with the NPs by OGD and H2O2-induced injury models was used to assess the protective effect. NPs from six Panax herbal medicines occupied about 20 % of the total polysaccharides, which were of the highest content in RG and the lowest in PN. NPs from six ginseng exhibited weak differentiations in the molecular weight distribution, while marker oligosaccharides were found to distinguish PN and RG from the others. Glc and GalA were more abundant in the NPs for PG and RG, respectively. NPs from PQ (100/200 μg/mL) showed significant cardiomyocyte protection effect by regulating the mitochondrial functions. This work further testifies the role of polysaccharides in quality control of herbal medicine, with new markers discovered beneficial to distinguish the ginseng.

Use of 4-D proteomics to differentiate between bovine and camel lactoferrin

Lactoferrin is a multifunctional protein that has various biological activities and applications. However, different sources of lactoferrin may have different properties and characteristics. In this study, we hypothesized that ultra-performance liquid chromatography quadrupole time-of-flight mass spectroscopy (UPLC-QTOF-IMS) coupled with UNIFI software can differentiate bovine lactoferrin from camel lactoferrin based on the unique peptides produced by trypsin digestion. We enzymatically digested the proteins using trypsin and analyzed the resulting peptides using Uniport software and in silico digestion. We identified 14 marker peptides that were unique to bovine lactoferrin and could be used to distinguish it from camel lactoferrin. We also demonstrated the advantages of 4D proteomics over 3D proteomics in separating and identifying peptides based on their mass, retention time, intensity, and ion mobility. This method can be applied to other lactoferrin sources and improve the quality control and authentication of lactoferrin products.

Multiple heart-cutting two-dimensional liquid chromatography/charged aerosol detector assay of ginsenosides for quality evaluation of ginseng from diverse Chinese patent medicines

For quality control of Chinese patent medicines (CPMs) containing the same herbal medicine or different herbal medicines that have similar chemical composition, current ″one standard for one species″ research mode leads to poor universality of the analytical approaches unfavorable to discriminate easily confused species. Herein, we were aimed to elaborate a multiple heart-cutting two-dimensional liquid chromatography/charged aerosol detector (MHC-2DLC/CAD) approach to quantitatively assess ginseng from multiple CPMs. Targeting baseline resolution of 16 ginsenosides (noto-R1/Rg1/Re/Rf/Ra2/Rb1/Rc/Ro/Rb2/Rb3/Rd/Rh1/Rg2/Rg3/Rg3(R)/24(R)-p-F11), experiments were conducted to optimize key parameters and validate its performance. A Poroshell 120 EC-C18 column and an XBridge Shield RP18 column were separately utilized in the first-dimensional (1D) and the second-dimensional (2D) chromatography. Eight consecutive cuttings could achieve good separation of 16 ginsenosides within 85 min. The developed MHC-2DLC/CAD method showed good linearity (R2 > 0.999), repeatability (RSD < 6.73%), stability (RSD < 5.63%), inter- and intra-day precision (RSD < 5.57%), recovery (93.76-111.14%), and the limit of detection (LOD) and limit of quantification (LOQ) varied between 0.45-2.37 ng and 0.96-4.71 ng, respectively. We applied it to the content determination of 16 ginsenosides simultaneously from 28 different ginseng-containing CPMs, which unveiled the ginsenoside content difference among the tested CPMs, and gave useful information to discriminate ginseng in the preparation samples, as well. The MHC-2DLC/CAD approach exhibited advantages of high specificity, good separation ability, and relative high analysis efficiency, which also justified the feasibility of our proposed ″Monomethod Characterization of Structure Analogs″ strategy in quality evaluation of diverse CPMs that contained different ginseng.

A practical strategy enabling more reliable identification of ginsenosides from Panax quinquefolius flower by dimension-enhanced liquid chromatography/mass spectrometry and quantitative structure-retention relationship-based retention behavior prediction

To accurately identify the metabolites is crucial in a number of research fields, and discovery of new compounds from the natural products can benefit the development of new drugs. However, the preferable phytochemistry or liquid chromatography/mass spectrometry approach is time-/labor-extensive or receives unconvincing identifications. Herein, we presented a strategy, by integrating offline two-dimensional liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (2D-LC/IM-QTOF-MS), exclusion list-containing high-definition data-dependent acquisition (HDDDA-EL), and quantitative structure-retention relationship (QSRR) prediction of the retention time (tR), to facilitate the in-depth and more reliable identification of herbal components and thus to discover new compounds more efficiently. Using the saponins in Panax quinquefolius flower (PQF) as a case, high orthogonality (0.79) in separating ginsenosides was enabled by configuring the XBridge Amide and CSH C18 columns. HDDDA-EL could improve the coverage in MS2 acquisition by 2.26 folds compared with HDDDA (2933 VS 1298). Utilizing 106 reference compounds, an accurate QSRR prediction model (R2 = 0.9985 for the training set and R2 = 0.88 for the validation set) was developed based on Gradient Boosting Machine (GBM), by which the predicted tR matching could significantly reduce the isomeric candidates identification for unknown ginsenosides. Isolation and establishment of the structures of two malonylginsenosides by NMR partially verified the practicability of the integral strategy. By these efforts, 421 ginsenosides were identified or tentatively characterized, and 284 thereof were not ever reported from the Panax species. The current strategy is thus powerful in the comprehensive metabolites characterization and rapid discovery of new compounds from the natural products.

Characterization of ginsenosides from Panax japonicus var. major (Zhu-Zi-Shen) based on ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry and desorption electrospray ionization-mass spectrometry imaging

BACKGROUND

Panax japonicus var. major (PJM) belongs to the well-known ginseng species used in west China for hundreds of years, which has the effects of lung tonifying and yin nourishing, and exerts the analgesic, antitussive, and hemostatic activities. Compared with the other Panax species, the chemical composition and the spatial tissue distribution of the bioactive ginsenosides in PJM have seldom been investigated.

METHODS

Ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC/QTOF-MS) and desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) were integrated for the systematic characterization and spatial tissue distribution studies of ginsenosides in the rhizome of PJM. Considering the great difficulty in exposing the minor saponins, apart from the conventional Auto MS/MS (M1), two different precursor ions list-including data-dependent acquisition (PIL-DDA) approaches, involving the direct input of an in-house library containing 579 known ginsenosides (M2) and the inclusion of the target precursors screened from the MS1 data by mass defect filtering (M3), were developed. The in situ spatial distribution of various ginsenosides in PJM was profiled based on DESI-MSI with a mass range of m/z 100-1500 in the negative ion mode, with the imaging data processed by the High Definition Imaging (HDI) software.

RESULTS

Under the optimized condition, 272 ginsenosides were identified or tentatively characterized, and 138 thereof were possibly not ever reported from the Panax genus. They were composed by 75 oleanolic acid type, 22 protopanaxadiol type, 52 protopanaxatriol type, 16 octillol type, 19 malonylated, 35 C-17 side-chain varied, and 53 others. In addition, the DESI-MSI experiment unveiled the differentiated distribution of saponins, but the main location in the cork layer and phloem of the rhizome. The abundance of the oleanolic acid ginsenosides was high in the rhizome slice of PJM, which was consistent with the results obtained by UHPLC/QTOF-MS.

CONCLUSION

Comprehensive characterization of the ginsenosides in the rhizome of PJM was achieved, with a large amount of unknown structures unveiled primarily. We, for the first time, reported the spatial tissue distribution of different subtypes of ginsenosides in the rhizome slice of PJM. These results can benefit the quality control and further development of PJM and the other ginseng species.

A compounds annotation strategy using targeted molecular networking for offline two-dimensional liquid chromatography-mass spectrometry analysis: Yupingfeng as a case study

Component overlapping and long-time consumption hinder the data processing of offline two-dimensional liquid chromatography mass spectrometry (offline 2D-LC MS) system. Although molecular networking has been commonly employed in data processing of liquid chromatography mass spectrometry (LC-MS), its application in offline 2D-LC MS is challenged by voluminous and redundant data. In light of this, for the first time, a data deduplication and visualization strategy combining hand-in-hand alignment with targeted molecular networking (TMN) for compounds annotation of offline 2D-LC MS data was developed and applied to the chemical profile of Yupingfeng (YPF), a classical traditional Chinese medicine (TCM) prescription, as a case study. Firstly, an offline 2D-LC MS system was constructed for the separation and data acquisition of YPF extract. Then the data of 12 fractions derived from YPF were deconvoluted and aligned as a whole data file by hand-in-hand alignment, resulting in a 49.2% reduction in component overlapping (from 17951 to 9112 ions) and an improvement in the MS² spectrum quality of precursor ions. Subsequently, the MS²-similarity adjacency matrix of focused parent ions was computed by a self-building Python script, which realized the construction of an innovative TMN. Interestingly, the TMN was found to be able to efficiently distinguish and visualize the co-elution, in-source fragmentations and multi-type adduct ions in a clustering network. Consequently, a total of 497 compounds were successfully identified depending on only seven TMN analysis guided by product ions filtering (PIF) and neutral loss filtering (NLF) for the targeted compounds in YPF. This integrated strategy improved the efficiency of targeted compound discovery in offline 2D-LC MS data, also shown a huge scalability in accurate compound annotation of complex samples. In conclusion, our study developed available concepts and tools while providing a research paradigm for efficient and rapid compound annotation in complex samples such as TCM prescriptions, with YPF as an example.

Collision Cross Section Prediction Based on Machine Learning

Ion mobility-mass spectrometry (IM-MS) is a powerful separation technique providing an additional dimension of separation to support the enhanced separation and characterization of complex components from the tissue metabolome and medicinal herbs. The integration of machine learning (ML) with IM-MS can overcome the barrier to the lack of reference standards, promoting the creation of a large number of proprietary collision cross section (CCS) databases, which help to achieve the rapid, comprehensive, and accurate characterization of the contained chemical components. In this review, advances in CCS prediction using ML in the past 2 decades are summarized. The advantages of ion mobility-mass spectrometers and the commercially available ion mobility technologies with different principles (e.g., time dispersive, confinement and selective release, and space dispersive) are introduced and compared. The general procedures involved in CCS prediction based on ML (acquisition and optimization of the independent and dependent variables, model construction and evaluation, etc.) are highlighted. In addition, quantum chemistry, molecular dynamics, and CCS theoretical calculations are also described. Finally, the applications of CCS prediction in metabolomics, natural products, foods, and the other research fields are reflected.

Three-dimensional characteristic chromatogram by online comprehensive two-dimensional liquid chromatography: Application to the identification and differentiation of ginseng from herbal medicines to various Chinese patent medicines

One bottleneck problem in the quality control of traditional Chinese medicine (TCM) is the accurate identification of easily confused herbal medicines from Chinese patent medicine (CPM). Ginseng products derived from the multiple parts (e.g., root/rhizome, leaf, and flower bud) of multiple Panax species (P. ginseng, P. quinquefolius, P. notoginseng, P. japonicus, and P. japonicus var. major) are globally popular; however, their authentication is very challenging. Using online comprehensive two-dimensional liquid chromatography (LC × LC), we propose the concept of a three-dimensional characteristic chromatogram (3D CC) by integrating enhanced LC × LC separation and a contour plot that visualizes the stereoscopic chromatographic peaks and examine its performance in authenticating various ginseng products. Targeted at the resolution of 17 ginsenoside markers, an online LC × LC/UV system with a 56 min analysis time was constructed: a CORTECS UPLC Shield RP 18 column running at 0.1 mL/min for the first-dimensional chromatography and a Poroshell SB-Aq column at 2.0 mL/min in shift gradient mode in the second dimension of separation. In particular, ginsenosides Rg1/Re and Rc/Ra1 were well resolved. According to the presence/absence of stereo peaks consistent with the main ginsenoside markers in the 3D CC and the depth of shade (depending on peak volume), it was feasible to use a single method to identify and distinguish among 12 different ginseng species as the drug materials and the use of ginseng simultaneously from 21 CPMs. Conclusively, a practical solution enabling the accurate identification of easily confused TCMs was provided, covering both the drug materials and the compound preparations.

Comprehensive multicomponent characterization and quality assessment of Shuang-Huang-Lian powder injection using ultra-high-performance liquid chromatography-quadrupole time-of-flight-mass spectrometry and ultra-high-performance liquid chromatography-quadrupole-Orbitrap-mass spectrometry

RATIONALE

Shuang-Huang-Lian powder injection (SHLPI) is a well-known modern traditional Chinese medicine formula preparation (TCMFP) widely used to treat acute upper respiratory infections. However, SHLPI is extracted from pure Chinese medicine and administered through an injection, and many adverse reactions have been reported clinically. Therefore, it is necessary to characterize in depth the chemical composition of SHLPI and quantitatively analyze its potential allergenic components.

METHODS

In this study, the samples were analyzed using ion mobility ultra-high-performance liquid chromatography-quadrupole time-of-flight-mass spectrometry (UHPLC-QTOF-MS) combined with a self-built database. Furthermore, the parallel reaction monitoring (PRM) model of ultra-high-performance liquid chromatography-quadrupole-Orbitrap-mass spectrometry (UHPLC-Q-Orbitrap-MS) was used to successfully quantify 10 representative bioactive components.

RESULTS

Using this strategy 90 compounds were identified, the fragmentation pathways of five representative compounds in the five main components of SHLPI were summarized, and 10 components (neochlorogenic acid, chlorogenic acid, sweroside, forsythiaside A, luteoloside, isochlorogenic acid B, isochlorogenic acid C, baicalin, phillyrin, and baicalein) were determine as the quality markers of SHLPI based on UPLC-Q-Orbitrap-MS.

CONCLUSIONS

This work comprehensively characterized the material basis of SHLPI, summarized the cracking laws of representative substances, and quantitatively analyzed 10 potential allergenic components. Therefore, this study could provide a basis for the quality control of SHLPI and the clinical rational use of drugs to reduce its adverse reactions.

A multidimensional chromatography/high-resolution mass spectrometry approach for the in-depth metabolites characterization of two Astragalus species

To address the chemical complexity is indispensable in a number of research fields. Herb metabolome is typically composed by more than one class of structure analogs produced via different biosynthetic pathways. Multidimensional chromatography (MDC), due to the greatly enhanced separation space, offers the potential solution to comprehensive characterization of herbal metabolites. Here, we presented a strategy, by integrating MDC and quadrupole time-of-flight mass spectrometry (QTOF-MS), to accomplish the in-depth herbal metabolites characterization. Using the metabolome of two Astragalus species (A. membranaceus var. mongholicus,AMM; A. membranaceus, AM) as the case, an off-line three-dimensional liquid chromatography (3D-LC) system was established: hydrophilic interaction chromatography using an XAmide column as the first dimension (¹D) for fractionating the total extract, on-line reversed-phase × reversed-phase liquid chromatography separately configuring a CSH Fluoro-Phenyl column and a Cosmocore C18 column as the second dimension (²D) and the third dimension (³D) of chromatography to enable the explicit separation of three well fractionated samples. Moreover, the negative-mode collision-induced dissociation by QTOF-MS under the optimized condition could provide diversified fragments that were useful for the structural elucidation of AMM and AM. An in-house library (composed by 247 known compounds) and comparison with 43 reference standards were utilized to assist more reliable characterization. We could characterize 513 compounds from two Astragalus species (344 from AMM and 323 from AM), including 236 flavonoids, 150 triterpenoids, 18 organic acids, and 109 others. Conclusively, the established MDC approach gained excellent performance favoring the analogs-oriented in-depth characterization of herbal metabolites, but received uncompromising analytical efficiency.

Multicomponent Characterization of the Flower Bud of Panax notoginseng and Its Metabolites in Rat Plasma by Ultra-High Performance Liquid Chromatography/Ion Mobility Quadrupole Time-of-Flight Mass Spectrometry

The flower bud of Panax notoginseng (PNF) consumed as a tonic shows potential in the prevention and treatment of cardiovascular diseases. To identify the contained multi-components and, in particular, to clarify which components can be absorbed and what metabolites are transformed, unveiling the effective substances of PNF is of vital significance. A unique ultrahigh-performance liquid chromatography/ion mobility quadrupole time-of-flight mass spectrometry (UHPLC/IM-QTOF-MS) profiling approach and efficient data processing by the UNIFI^TM bioinformatics platform were employed to comprehensively identify the multi-components of PNF and the related metabolites in the plasma of rats after oral administration (at a dose of 3.6 g/kg). Two MS² data acquisition modes operating in the negative electrospray ionization mode, involving high-definition MS^E (HDMS^E) and data-dependent acquisition (DDA), were utilized aimed to extend the coverage and simultaneously ensure the quality of the MS² spectra. As a result, 219 components from PNF were identified or tentatively characterized, and 40 thereof could be absorbed. Moreover, 11 metabolites were characterized from the rat plasma. The metabolic pathways mainly included the phase I (deglycosylation and oxidation). To the best of our knowledge, this is the first report that systematically studies the in vivo metabolites of PNF, which can assist in better understanding its tonifying effects and benefit its further development.

Integrated Solid-Phase Extraction, Ultra-High-Performance Liquid Chromatography-Quadrupole-Orbitrap High-Resolution Mass Spectrometry, and Multidimensional Data-Mining Techniques to Unravel the Metabolic Network of Dehydrocostus Lactone in Rats

Dehydrocostus lactone (DL) is among the representative ingredients of traditional Chinese medicine (TCM), with excellent anticancer, antibacterial, and anti-inflammatory activities. In this study, an advanced strategy based on ultra-high-performance liquid chromatography-quadrupole-Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS) was integrated to comprehensively explore the metabolic fate of DL in rats. First, prior to data collection, all biological samples (plasma, urine, and feces) were concentrated and purified using solid-phase extraction (SPE) pre-treatment technology. Then, during data collection, in the full-scan (FS) data-dependent acquisition mode, FS-ddMS² was intelligently combined with FS-parent ion list (PIL)-dynamic exclusion (DE) means for targeted monitoring and deeper capture of more low-abundance ions of interest. After data acquisition, data-mining techniques such as high-resolution extracted ion chromatograms (HREICs), multiple mass defect filters (MMDFs), diagnostic product ions (DPIs), and neutral loss fragments (NLFs) were incorporated to extensively screen and profile all the metabolites in multiple dimensions. As a result, a total of 71 metabolites of DL (parent drug included) were positively or tentatively identified. The results suggested that DL in vivo mainly underwent hydration, hydroxylation, dihydrodiolation, sulfonation, methylation, dehydrogenation, dehydration, N-acetylcysteine conjugation, cysteine conjugation, glutathione conjugation, glycine conjugation, taurine conjugation, etc. With these inferences, we successfully mapped the "stepwise radiation" metabolic network of DL in rats, where several drug metabolism clusters (DMCs) were discovered. In conclusion, not only did we provide a refined strategy for inhibiting matrix effects and fully screening major-to-trace metabolites, but also give substantial data reference for mechanism investigation, in vivo distribution visualization, and safety evaluation of DL.

Enhanced Identification of Ginsenosides Simultaneously from Seven Panax Herbal Extracts by Data-Dependent Acquisition Including a Preferred Precursor Ions List Derived from an In-House Programmed Virtual Library

Data-dependent acquisition (DDA) is widely utilized for metabolite identification in natural product research and food science, which, however, can suffer from low coverage. A potential solution to improve DDA coverage is to include the precursor ions list (PIL). Here, we aimed to construct a PIL-containing DDA strategy based on an in-house library of ginsenosides (VLG) and identify ginsenosides simultaneously from seven Panax herbal extracts. VLG, combined with mass defect filtering, could efficiently screen the ginsenoside precursors and elaborate the separate PIL involved in DDA for each ginseng extract. Consequently, we could characterize 500 ginsenosides, including 176 ones with unknown masses. Using the Panax ginseng extract, the superiority of this strategy was embodied in targeting more known ginsenoside masses and newly acquiring the MS² spectra of 13 components. Conclusively, knowledge-based large-scale molecular prediction and PIL-DDA can represent a powerful targeted/untargeted strategy beneficial to novel natural compound discovery.

Integrating Enhanced Profiling and Chemometrics to Unveil the Potential Markers for Differentiating among the Leaves of Panax ginseng, P. quinquefolius, and P. notoginseng by Ultra-High Performance Liquid Chromatography/Ion Mobility-Quadrupole Time-of-Flight Mass Spectrometry

The leaves of Panax species (e.g., Panax ginseng-PGL, P. quinquefolius-PQL, and P. notoginseng-PNL) can serve as a source for healthcare products. Comprehensive characterization and unveiling of the metabolomic difference among PGL, PQL, and PNL are critical to ensure their correct use. For this purpose, enhanced profiling and chemometrics were integrated to probe into the ginsenoside markers for PGL/PQL/PNL by ultra-high performance liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (UHPLC/IM-QTOF-MS). A hybrid scan approach (HDMS^E-HDDDA) was established achieving the dimension-enhanced metabolic profiling, with 342 saponins identified or tentatively characterized from PGL/PQL/PNL. Multivariate statistical analysis (33 batches of leaf samples) could unveil 42 marker saponins, and the characteristic ginsenosides diagnostic for differentiating among PGL/PQL/PNL were primarily established. Compared with the single DDA or DIA, the HDMS^E-HDDDA hybrid scan approach could balance between the metabolome coverage and spectral reliability, leading to high-definition MS spectra and the additional collision-cross section (CCS) useful to differentiate isomers.

Novel perspectives on the therapeutic role of cryptotanshinone in the management of stem cell behaviors for high-incidence diseases

Cryptotanshinone (CTS), a diterpenoid quinone, is found mostly in Salvia miltiorrhiza Bunge (S. miltiorrhiza) and plays a crucial role in many cellular processes, such as cell proliferation/self-renewal, differentiation and apoptosis. In particular, CTS’s profound physiological impact on various stem cell populations and their maintenance and fate determination could improve the efficiency and accuracy of stem cell therapy for high-incidence disease. However, as much promise CTS holds, these CTS-mediated processes are complex and multifactorial and many of the underlying mechanisms as well as their clinical significance for high-incidence diseases are not yet fully understood. This review aims to shed light on the impact and mechanisms of CTS on the actions of diverse stem cells and the involvement of CTS in the many processes of stem cell behavior and provide new insights for the application of CTS and stem cell therapy in treating high-incidence diseases.

Systematic Qualitative and Quantitative Analyses of Wenxin Granule via Ultra-High Performance Liquid Chromatography Coupled with Ion Mobility Quadrupole Time-of-Flight Mass Spectrometry and Triple Quadrupole–Linear Ion Trap Mass Spectrometry

Wenxin granule (WXG) is a popular traditional Chinese medicine (TCM) preparation for the treatment of arrhythmia disease. Potent analytical technologies are needed to elucidate its chemical composition and assess the quality differences among multibatch samples. In this work, both a multicomponent characterization and quantitative assay of WXG were conducted using two liquid chromatography–mass spectrometry (LC-MS) approaches. An ultra-high performance liquid chromatography–ion mobility quadrupole time-of-flight mass spectrometry (UHPLC/IM-QTOF-MS) approach combined with intelligent peak annotation workflows was developed to characterize the multicomponents of WXG. A hybrid scan approach enabling alternative data-independent and data-dependent acquisitions was established. We characterized 205 components, including 92 ginsenosides, 53 steroidal saponins, 14 alkaloids, and 46 others. Moreover, an optimized scheduled multiple reaction monitoring (sMRM) method was elaborated, targeting 24 compounds of WXG via ultra-high performance liquid chromatography–triple quadrupole linear ion trap mass spectrometry (UHPLC/QTrap-MS), which was validated based on its selectivity, precision, stability, repeatability, linearity, sensitivity, recovery, and matrix effect. By applying this method to 27 batches of WXG samples, the content variations of multiple markers from Notoginseng Radix et Rhizoma (21) and Codonopsis Radix (3) were depicted. Conclusively, we achieved the comprehensive multicomponent characterization and holistic quality assessment of WXG by targeting the non-volatile components.

Recent developments in data acquisition, treatment and analysis with ion mobility-mass spectrometry for lipidomics

Lipids are involved in many biological processes and their study is constantly increasing. To identify a lipid among thousand requires of reliable methods and techniques. Ion Mobility (IM) can be coupled with Mass Spectrometry (MS) to increase analytical selectivity in lipid analysis of lipids. IM-MS has experienced an enormous development in several aspects, including instrumentation, sensitivity, amount of information collected and lipid identification capabilities. This review summarizes the latest developments in IM-MS analyses for lipidomics and focusses on the current acquisition modes in IM-MS, the approaches for the pre-treatment of the acquired data and the subsequent data analysis. Methods and tools for the calculation of Collision Cross Section (CCS) values of analytes are also reviewed. CCS values are commonly studied to support the identification of lipids, providing a quasi-orthogonal property that increases the confidence level in the annotation of compounds and can be matched in CCS databases. The information contained in this review might be of help to new users of IM-MS to decide the adequate instrumentation and software to perform IM-MS experiments for lipid analyses, but also for other experienced researchers that can reconsider their routines and protocols. This article is protected by copyright. All rights reserved.

Application of Large-Scale Molecular Prediction for Creating the Preferred Precursor Ions List to Enhance the Identification of Ginsenosides from the Flower Buds of Panax ginseng

This work was designed to evaluate the coverage of data-dependent acquisition (DDA) extensively utilized in the untargeted metabolite/component identification in the food sciences and pharmaceutical analysis. Using saponins from the flower buds of Panax ginseng (PGF) as an example, precursor ions list (PIL)-including DDA on a Q-Orbitrap mass spectrometer could enable higher coverage than the other four MS² acquisition approaches in characterizing PGF ginsenosides. A "Virtual Library of Ginsenoside" containing 13,536 ginsenoside molecules was established by C-language-programmed large-scale molecular prediction, which in combination with mass defect filtering could create a new PIL involving 1859 PGF saponin precursors. We could newly obtain the MS² spectra of at least 17 components and characterize 36 ginsenosides with unknown masses, among the 164 compounds identified from PGF. Conclusively, a molecular-prediction-oriented PIL in DDA can assist to discover more potentially novel molecules benefiting to the development of functional foods and new drugs.