Identification of Daphne genkwa and Its Vinegar-Processed Products by Ultraperformance Liquid Chromatography–Quadrupole Time-of-Flight Mass Spectrometry and Chemometrics

Crude herbs of Daphne genkwa (CHDG) are often used in traditional Chinese medicine to treat scabies baldness, carbuncles, and chilblain owing to their significant purgation and curative effects. The most common technique for processing DG involves the use of vinegar to reduce the toxicity of CHDG and enhance its clinical efficacy. Vinegar-processed DG (VPDG) is used as an internal medicine to treat chest and abdominal water accumulation, phlegm accumulation, asthma, and constipation, among other diseases. In this study, the changes in the chemical composition of CHDG after vinegar processing and the inner components of the changed curative effects were elucidated using optimized ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Untargeted metabolomics, based on multivariate statistical analyses, was also used to profile differences between CHDG and VPDG. Eight marker compounds were identified using orthogonal partial least-squares discrimination analysis, which indicated significant differences between CHDG and VPDG. The concentrations of apigenin-7-O-β-d-methylglucuronate and hydroxygenkwanin were considerably higher in VPDG than those in CHDG, whereas the amounts of caffeic acid, quercetin, tiliroside, naringenin, genkwanines O, and orthobenzoate 2 were significantly lower. The obtained results can indicate the transformation mechanisms of certain changed compounds. To the best of our knowledge, this study is the first to employ mass spectrometry to detect the marker components of CHDG and VPDG.


Introduction
Chinese herbal medicines are processed following a unique pharmacological technology wherein crude drugs are treated in accordance with traditional Chinese medical theory by considering their individual nature and the requirements of drug dispensing, pharmaceutical preparation, and clinical use [1]. As a distinguishing characteristic of ancient pharmaceutical technology, traditional Chinese medicine (TCM) processing involves various techniques, including cleaning, cutting, roasting, steaming, and boiling, which significantly reduce toxicity or side effects, relieve drug irritation, enhance the therapeutic effects, and increase the clinical applicability of the extracts [2][3][4]. Among these techniques, stir-baking with excipients and frying with liquid excipients are regarded as the most effective and common processing methods [5]. Complex chemical changes occur during

UPLC-Q-TOF-MS/MS Analysis and Identification of the Chemical Components of CHDG and VPDG
Using the optimized chromatographic and MS conditions, 67 components were identified, or tentatively characterized, in the negative ion mode after matching with the established UNIFI database or via reference standards and the published literature. Typical total ion chromatograms (TICs) of CHDG and VPDG in the negative ion mode are shown in Figure 1. The retention times, molecular formulas, ion types, detected masses, mass errors, and fragment ions associated with the identified peaks are summarized in Table 1. The constituents identified in DG were mainly classified as flavonoids, daphnane-type diterpene esters, lignans, coumarins, or others. The procedures to identify the major compounds (excluding "others") are summarized as follows.
Molecules 2023, 28, x FOR PEER REVIEW 3 of 16 nebulizer gas, curtain gas, heater gas, ion spray voltage, and declustering potential, were also optimized to improve the response.

UPLC-Q-TOF-MS/MS Analysis and Identification of the Chemical Components of CHDG and VPDG
Using the optimized chromatographic and MS conditions, 67 components were identified, or tentatively characterized, in the negative ion mode after matching with the established UNIFI database or via reference standards and the published literature. Typical total ion chromatograms (TICs) of CHDG and VPDG in the negative ion mode are shown in Figure 1. The retention times, molecular formulas, ion types, detected masses, mass errors, and fragment ions associated with the identified peaks are summarized in Table 1. The constituents identified in DG were mainly classified as flavonoids, daphnane-type diterpene esters, lignans, coumarins, or others. The procedures to identify the major compounds (excluding "others") are summarized as follows.   DG contains various flavonoids that can be classified into several types, including flavones, flavonols, and flavonoid glycosides. The fragmentation behaviors, such as retro-Diels-Alder (RDA) fragmentation and loss of neutral fragments, were mainly observed in the C-and A-rings and resulted in the production of numerous complex mass fragments. The

Identification of Diterpene Esters
Daphnane-type diterpene esters are a class of important natural compounds with non-negligible toxicity [33]. Diterpene esters typically produce a series of predominant fragment ions originating from the successive or simultaneous loss of H2O, CO, CH3O, a chain of fatty acids and benzene groups, or a chain of fatty and benzoic acids. Yuanhuacine, which is found in DG, was selected as a representative daphnane-type diterpene ester to elucidate the fragmentation behavior and facilitate the structural characterization of other diterpenoids. With a molecular formula of C37H44O10, the quasi-molecular .1108, respectively. These important ions indicated the substitution or lack of the hydroxyl groups at the C20 position. Finally, the fragment ion detected at m/z 327.1231 led to further successive or simultaneous losses of CO, H2O, and C3H6, resulting in the product ions with peaks at m/z 299.1278, 281.1182, and 267.1012, respectively. The identification of yuanhuacine was validated using previous reports [34] and the MS2 spectrum of the yuanhuacine standard solution. Figure 2D illustrates the probable fragmentation pathways of yuanhuacine. Subsequently, other daphnane-type diterpene esters were also identified and confirmed.

Identification of Lignan and Coumarin
In addition to flavonoids and diterpene esters, DG contained lignans and coumarins, which were obtained using traditional extraction and isolation techniques.
The representative lignan, pinores inoldiglucoside, readily forms [M−H] − quasi-molecular ions in the negative ion mode and exhibits a common pattern of mass spectrometric cleavage: the quasi-molecular ion first loses 1-2 glucose molecules, after which the tetrahydrofuran ring opens with the loss of CH3, CH2O, CO, CH3O, CH3OH, and other groups, generating characteristic fragment ions above m/z 151. Figure 2E

Identification of Diterpene Esters
Daphnane-type diterpene esters are a class of important natural compounds with non-negligible toxicity [33]. Diterpene esters typically produce a series of predominant fragment ions originating from the successive or simultaneous loss of H 2 O, CO, CH 3 O, a chain of fatty acids and benzene groups, or a chain of fatty and benzoic acids. Yuanhuacine, which is found in DG, was selected as a representative daphnane-type diterpene ester to elucidate the fragmentation behavior and facilitate the structural characterization of other diterpenoids. With a molecular formula of C 37  .1108, respectively. These important ions indicated the substitution or lack of the hydroxyl groups at the C20 position. Finally, the fragment ion detected at m/z 327.1231 led to further successive or simultaneous losses of CO, H 2 O, and C 3 H 6 , resulting in the product ions with peaks at m/z 299.1278, 281.1182, and 267.1012, respectively. The identification of yuanhuacine was validated using previous reports [34] and the MS2 spectrum of the yuanhuacine standard solution. Figure 2D illustrates the probable fragmentation pathways of yuanhuacine. Subsequently, other daphnane-type diterpene esters were also identified and confirmed.

Identification of Lignan and Coumarin
In addition to flavonoids and diterpene esters, DG contained lignans and coumarins, which were obtained using traditional extraction and isolation techniques.
The representative lignan, pinores inoldiglucoside, readily forms [M−H] − quasimolecular ions in the negative ion mode and exhibits a common pattern of mass spectrometric cleavage: the quasi-molecular ion first loses 1-2 glucose molecules, after which the tetrahydrofuran ring opens with the loss of CH 3 , CH 2 O, CO, CH 3 O, CH 3 OH, and other groups, generating characteristic fragment ions above m/z 151. Figure 2E  may be a lignin disaccharide compound. The combination of control experiments and literature reports [35] led to the identification of this compound and other lignans.
Dicoumarin daphnoretin was used as a reference standard to explore the cleavage pattern of coumarin under the aforementioned conditions. The dicoumarin daphnoretin molecule contains oxygen atoms and hydroxyl groups connected with aromatic rings and generally loses CH 3 and CO fragment ions in succession. Daphnoretin first fragments into monocoumarin, with an m/z of 190.9987. The fragment ion with m/z 190.9987 is then released from the middle of the double coumarin, followed by the loss of two molecules of CO, which yield the fragment ion peaks at m/z 163.0013 and 135.0093 [35]. The proposed fragmentation patterns are depicted in Figure 2F.

Multivariate Statistical Analysis
To identify the marker compounds that characterize the differences between CHDG and VPDG, the two sample groups were subjected to UPLC-Q-TOF-MS analysis, and the tandem mass spectrometry (MSE) raw data were processed for alignment, deconvolution, and data reduction using the Progenesis QI software (Waters, Milford, MA, USA) [36]. Progenesis QI detects chromatographic peaks to extract variables (tR, m/z, and intensity), normalizes, aligns similar variables, and creates a data matrix before presenting the results in a marker table. A Progenesis QI processing method was created, and the main parameters were as follows: retention time range, 0−38 min; minimum intensity, 5%; mass range, 50−1500 Da; mass tolerance, 0.10; mass window, 0.20; marker intensity threshold, 2000 counts; retention time window, 0.20; noise elimination level, 6. All processed data, including the m/z−tR pairs from each data file and the corresponding intensities of all the detected peaks, were exported and analyzed using the SIMCA 14.1 software. In different batches of samples, components with the same tR and m/z values were regarded as identical. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) was performed to obtain the maximum separation between two different samples and explore the potential chemical markers responsible for the differences. In the sufficient permutation test, the R2Y and Q2 of the OPLS-DA model were 0.92 and 0.82, respectively, which indicated an acceptable validity for the subsequent identification of the characteristic markers ( Figure 3A). S plots were then created to visualize the OPLS-DA predictive component loading to facilitate the interpretation of the model, in which each point represented an ion RT-m/z pair. The x-axis represented the variable contribution; ion RT-m/z pair points that are located further away from zero indicate a higher contribution of the ion to the difference between the two groups. The y-axis represented the variable confidence; ion RT-m/z pair points that are located further away from zero indicate a higher confidence level that the ion contributed to the difference between the two groups. Therefore, the RT-m/z pair points at the two ends of the "S" shape represent the components that are the most responsible for the difference between these two types of samples, which can be regarded as the components that most differentiate between CHDG and VPDG [28,[37][38][39][40] (Figure 3B). To investigate whether data overfitting occurred in the OPLS-DA model, 200 iterations of the permutation test were performed using the SIMCA 14.1 software, in which R2Y and Q2 described the explanation level of the model in the y-axis direction and the forecasted level of the model, respectively. Based on the permutation test, the intercept of the R2 regression curve was less than 0.4, and that of the Q2 regression curve was less than 0, indicating that the model was not overfitted and that the modeling was successful [39,41,42] (Figure 3C,D).

Analysis of Chemicals of DG after Processing
In univariate statistical analysis, the multivariate statistical analysis condition, the variable importance for the projection (VIP) value, was set to >1. The t-test (p < 0.05) showed that 241 characteristic ions exhibited significant differences. Along with the component analysis, this test excluded the interference fragments and confirmed the molecular ions. A total of eight potential chemical markers were identified ( Table 2). The mass accuracy of all assigned components was less than 5 ppm, relative to the empirical molecular formulas of the compounds known to exist in DG. To present the level of change in the differential compounds, a heat map was generated to show the relative levels of each compound in CHDG and VPDG [43] (Figure 4). The intensities of ions a and b were higher in VPDG than those in CHDG, indicating that the two components correlated to ions a and b could be used as potential characteristic markers to distinguish between VPDG and CHDG. Meanwhile, the intensities of ions c, d, e, f, g, and h were higher in CHDG than those in VPDG, indicating that the six components correlated to ions c-h may also be used as potential characteristic markers to distinguish CHDG from VPDG. The identities of the components a-g (Table 2) were further confirmed by comparing the mass/UV spectra and retention times with those of the reference compounds. Considering the identification of the most differentiating components between CHDG and VPDG, certain prominent ions were found to correspond to the deprotonated molecular ions of all components. The ions a-h correlated to compounds 15, 32, 38, 39, 26, 23, 6, and 28, respectively. The differentiating components 38 and 39 are well-known toxic components of DG; therefore, a reduction in their contents in VPDG suggests that stir-baking with vinegar could reduce the toxicity of CHDG.

Analysis of Chemicals of DG after Processing
In univariate statistical analysis, the multivariate statistical analysis condition, the variable importance for the projection (VIP) value, was set to >1. The t-test (p < 0.05) showed that 241 characteristic ions exhibited significant differences. Along with the component analysis, this test excluded the interference fragments and confirmed the molecular ions. A total of eight potential chemical markers were identified ( Table 2). The mass accuracy of all assigned components was less than 5 ppm, relative to the empirical molecular formulas of the compounds known to exist in DG. To present the level of change in the differential compounds, a heat map was generated to show the relative levels of each compound in CHDG and VPDG [43] (Figure 4). The intensities of ions a and b were higher in VPDG than those in CHDG, indicating that the two components correlated to ions a and b could be used as potential characteristic markers to distinguish between VPDG and CHDG. Meanwhile, the intensities of ions c, d, e, f, g, and h were higher in CHDG than those in VPDG, indicating that the six components correlated to ions c-h may also be used as potential characteristic markers to distinguish CHDG from VPDG. The identities of the components a-g ( Table 2) were further confirmed by comparing the mass/UV spectra and retention times with those of the reference compounds. Considering the identification of the most differentiating components between CHDG and VPDG, certain prominent ions were found to correspond to the deprotonated molecular ions of all components. The ions a-h correlated to compounds 15,32,38,39,26,23,6, and 28, respectively. The differentiating components 38 and 39 are well-known toxic components of DG; therefore, a reduction in their contents in VPDG suggests that stir-baking with vinegar could reduce the toxicity of CHDG.   . Heat map analysis of the potential biomarkers in both CHDG and VPDG. X-axis represents the different groups; y-axis represents the different metabolites. Metabolites represented by the letters a−g are presented in Table 2.

Materials, Chemicals, and Reagents
Methanol (LC-MS grade) and acetonitrile (LC-MS grade) were purchased from Fisher (Pittsburgh, PA, USA). LC-MS grade formic acid was purchased from Merck Millipore (Darmstadt, Germany). Purified water was obtained using a Milli-Q purification system (Millipore, Bedford, MA, USA).
A total of 21 batches of CHDG were collected from different areas in China and authenticated by the authors. The corresponding voucher specimens were deposited in the Museum of Traditional Chinese Medicine Specimens, Institute for the Control of Traditional Chinese Medicine and Ethnic Medicine. A total of 24 batches of VPDG were prepared according to the standards of the Chinese Pharmacopoeia 2020. Details of the samples, including their source and batch number, are provided in Table 3.  Table 2.

Materials, Chemicals, and Reagents
Methanol (LC-MS grade) and acetonitrile (LC-MS grade) were purchased from Fisher (Pittsburgh, PA, USA). LC-MS grade formic acid was purchased from Merck Millipore (Darmstadt, Germany). Purified water was obtained using a Milli-Q purification system (Millipore, Bedford, MA, USA).
A total of 21 batches of CHDG were collected from different areas in China and authenticated by the authors. The corresponding voucher specimens were deposited in the Museum of Traditional Chinese Medicine Specimens, Institute for the Control of Traditional Chinese Medicine and Ethnic Medicine. A total of 24 batches of VPDG were prepared according to the standards of the Chinese Pharmacopoeia 2020. Details of the samples, including their source and batch number, are provided in Table 3. mode. During acquisition, data were collected in the continuum mode for screening and multivariate statistical analyses.

Mass Data Processing and Analysis
The raw data were precaptured and processed using the Waters MassLynx V4.2 software. The data were analyzed using the UNIFI and Progenesis QI software, in combination with a self-built compound library and a fragment ion matching strategy, to fully characterize the chemical composition of DG. The main data processing parameters included the retention time, molecular m/z, and mass error range, whereas secondary fragment ion information was used to infer the compound structure. Before identifying the compounds, a comprehensive library of the chemical composition of DG was created by systematically searching CNKI, PubChem, ChemicalBook, and other databases [3,44]. This in-house database includes the names of compounds, molecular formulas, molecular weights, chemical structural formulas, molecular ions, and secondary fragment ions. The chemical components were identified using the UNIFI software. Ion peaks with retention times within 0.2 min and an m/z within 10 ppm of each other were identified as those of the same compound.

Conclusions
DG is a toxic herb used in TCM that requires stir-baking with vinegar to reduce its toxicity prior to oral administration. Studies on HL-7702 cells have shown that vinegar treatment reduces hepatotoxicity induced by DG [45]. However, the potential mechanisms underlying this reduction in hepatotoxicity require further investigation. Our previous research has shown that methanol extracts contain the main hepatotoxic components of DG, particularly diterpene esters [46,47]; therefore, the methanol fraction of DG was selected as the target in this study.
Screening analysis using UPLC-Q-TOF-MS identified a total of 67 compounds from the buds of DG. The quantity and strength of the responses of the identified compounds in the TIC chromatograms indicated that the performance of the negative ionization mode was superior to that of the positive ionization mode. The 67 identified compounds, including flavones, flavonols, flavonoid glycosides, daphnane-type diterpene esters, lignans, and coumarins, were constituents of both CHDG and VPDG, which implied that they were similar in terms of their composition. Eight compounds in the methanol extracts were identified as major contributors to the differences between CHDG and VPDG: apigenin-7-O-β-D-methylglucuronate (a), hydroxygenkwanin (b), genkwanines O (c), orthobenzoate 2 (d), tiliroside (e), quercetin (f), caffeic acid (g), and naringenin (h). Considering their toxicity [48][49][50][51], the reduction in the amount of daphnane-type diterpene ester compounds in VPDG might explain the mechanism through which stir-baking with vinegar reduces the toxicity of CHDG. In addition to the aforementioned compounds, other compounds not listed here contributed to the differences between CHDG and VPDG. Future studies should involve controlling the levels of apigenin-7-O-β-D-methylglucuronate (a) and hydroxygenkwanin (b) to ensure the quality of VPDG, as well as controlling the levels of genkwanines O (c), orthobenzoate 2 (d), tiliroside (e), quercetin (f), caffeic acid (g), and naringenin (h) in CHDG to establish a method for ensuring the quality of this traditional medicine. Furthermore, future studies will focus on establishing standards to ensure the quality of both CHDG and VPDG and examining the ways in which changes in the level of internal chemical compounds affect the pharmacological effects. Future studies should also involve the study of the connotation and mechanism of TCM processing technology.
In this study, we established an efficient method that employs UPLC-Q-TOF-MS coupled with chemometrics to differentiate between and detect CHDG and VPDG by identifying potential chemical markers. This approach enabled the detailed profiling of each sample such that numerous chemical markers could be detected and used as powerful indices to identify and distinguish between CHDG and VPDG. The present approach provides a foundation for the detection of ion pairs derived from the parent ion and a fragment ion of the chemical markers using the MRM mode of LC/MS/MS and for developing a sensitive, stable, and rapid quality control standard for Chinese medicinal materials and relevant processed decoction pieces.