Comparative Analysis of Aristolochic Acids in Aristolochia Medicinal Herbs and Evaluation of Their Toxicities

Aristolochic acids (AAs) are a group of nitrophenanthrene carboxylic acids present in many medicinal herbs of the Aristolochia genus that may cause irreversible hepatotoxicity, nephrotoxicity, genotoxicity and carcinogenicity. However, the specific profile of AAs and their toxicity in Aristolochia plants, except for AAs Ι and ΙΙ, still remain unclear. In this study, a total of 52 batches of three medicinal herbs belonging to the Aristolochia family were analyzed for their AA composition profiles and AA contents using the UPLC-QTOF-MS/MS approach. The studied herbs were A. mollissima Hance (AMH), A. debilis Sieb.etZucc (ADS), and A. cinnabaria C.Y.Cheng (ACY). Chemometrics methods, including PCA and OPLS-DA, were used for the evaluation of the Aristolochia medicinal herbs. Additionally, cytotoxicity and genotoxicity of the selected AAs and the extracts of AMH and ADS were evaluated in a HepG2 cell line using the MTT method and a Comet assay, respectively. A total of 44 AAs, including 23 aristolochic acids and 21 aristolactams (ALs), were detected in A. mollissima. Moreover, 41 AAs (23 AAs and 18 ALs) were identified from A. debilis Sieb, and 45 AAs (29 AAs and 16 ALs) were identified in A. cinnabaria. Chemometrics results showed that 16, 19, and 22 AAs identified in AMH, ADS, and ACY, respectively, had statistical significance for distinguishing the three medicinal herbs of different origins. In the cytotoxicity assay, compounds AL-BΙΙ, AAΙ and the extract of AMH exhibited significant cytotoxicities against the HepG2 cell line with the IC50 values of 0.2, 9.7 and 50.2 μM, respectively. The results of the Comet assay showed that AAΙ caused relatively higher damage to cellular DNA (TDNA 40–95%) at 50 μM, while AAΙΙ, AMH and ADS extracts (ranged from 10 to 131 μM) caused relatively lower damage to cellular DNA (TDNA 5–20%).


Introduction
Aristolochic acids (AAs) are a group of nitrophenanthrene carboxylic acids mainly produced by plants of the Aristolochia and Asarum genera in the Aristolochiaceae family [1][2][3]. Currently, over 180 AAs analogues have been discovered, and AAI, AAII, AAIIIa (AA C) and AAIVa (AA D) are the most common in the Aristolochia genus [4]. It is worth

Identification of AAs Components by UPLC-QTOF-MS/MS
The UPLC-QTOF-MS/MS technique was applied to identify AAs in the three species of the Aristochia genus herbs, including AMH, ADS and ACY. The chemical structure of each individual AA was identified based on the chemical standard and their chromatographic and mass spectrometric properties, such as elementary composition analysis, the retention behavior and mass fragments reported in the literature [13,27,28]. The MS data

Identification of AAs Components by UPLC-QTOF-MS/MS
The UPLC-QTOF-MS/MS technique was applied to identify AAs in the three species of the Aristochia genus herbs, including AMH, ADS and ACY. The chemical structure of each individual AA was identified based on the chemical standard and their chromatographic and mass spectrometric properties, such as elementary composition analysis, the retention behavior and mass fragments reported in the literature [13,27,28]. The MS data libraries were also referred to using the TCM Systematic Pharmacology Database and Analysis Platform (TCMSP), the GNPS database and Waters Traditional Medicine Library, The University of Mississippi Botanical Library, and the University of Ottawa Phytochemical Library.
The high resolution of TOF-MS provided accurate mass determination and calculated reasonable chemical formulas according to molecular weight. AA structures were classified into two groups, aristolochic acids and aristolactams, as identified by their chemical formulas and typical mass fragments (Figures 2 and S1). A total of 76 compounds, including 44 AAs (Table 1 and Figure 3) and 32 other types of components (Table S1 and Figure S2), were detected in AMH. In addition, 72 compounds in total were determined from ADS, including 41 AAs (Table 1 and Figure 3) and 31 other compounds (Table S2 and Figure S3), and 45 AAs were identified in A. cinnabaria (Table S3 and Figure S4).        Table 1 and Table S3, we firstly compared the contents of AAs and ALs between ACY and the other two medicinal herbs. We found that the contents of 26 AAs and ALs in ACY were higher than those in ADS and AMH. For instance, compounds such as cinnabarin, AL-IVa-O-β-D-glucoside, aristoliukine C, aristophyllides C, aristchamic A, 7-OH-AAI and AAI, a methyl ester, were only detected in ACY. Moreover, the primary components of AAI, AAII, AA C and AL-I produced by ACY exceeded by about 30-400% those in AMH, but AAD and AL-FI in ACY were 50% less than those in AMH. Secondly, compounds 9-OH-AAI, AA E, ariskanin E, and AL-BII were determined to exist only in AMH. However, compounds Ariskanin B and aristoloterpenate IV were only detected in ADS. AAI and AAII in ADS were reduced by 30-60% compared with AMH, but its AA D and AL-I were 200-400% less than those in AMH. It can be speculated that the toxicity caused by ACY was the most potent.
The medicinal herb AMH collected in Hubei and Shandong Provinces exhibited great differences in AA content. Compounds AL-IIIa-N-β-D-glucoside, AL-I-N-β-D-glucoside, AL-AIIIa, AL-II, AL-II-N-β-D-glucoside and AL-Ia-N-β-D-glucoside in AMH, which originated from Hubei province, increased by 800-1200% compared to the ALs from herbs from Shandong province. Similarly, compounds AL-I-N-β-D-glucoside, aristoliukine A, AL-IIIa-N-β-D-glucoside, aristoloterpenate IV, 6-methoxydenitroaristolochic acid methyl ester, and aristolic acid II-8-O-β-D-glucoside in ADS from Guangxi province decreased by 5-30% compared to ADS from Hubei province. Additionally, compounds aristchamic B, AL-I-N-β-D-glucoside, aristophyllides C, AL-II and AL-Ia in ACY from Sichuan province showed a 200-300% increase compared with those from Yunnan province. In this case, the possibility of kidney and liver injury may increase, if the patients take these toxic components in the long term.

Results of PCA and OPLS-DA
Unsupervised principal component analysis (PCA) was established using AA contents as the variables in order to distinguish herbal samples collected from different species and origins ( Figure 4). All the mass spectroscopic data acquired by UPLC-Q-TOF-MS/MS were converted into a three-dimensional matrix, including the retention time, m/z values, and peak intensities. A total of 66 variables were generated and subjected to PCA analysis on the SIMCA software. The PCA scores plot showed a considerable separation tendency among the three species of AMH, ADS and ACY, with an R 2 X of 0.609. Distinct from other samples, all the samples of ACY cluster were in one region. Samples of ADS were in the lower left quadrant, while the samples of AMH were in both the upper and lower left quadrants ( Figure 4A). As shown in Figure 4B, the PCA scores plot that displayed the separation between Hubei and Shandong provinces were obviously significant (R 2 X = 79.7%), indicating that the AAs/ALs contents of the AMH from the two provinces were different. However, the PCA scores plot of ADS (R 2 X = 0.634) and ACY (R 2 X = 0.704) could not reveal a considerable separation either between Hubei and Guangxi provinces, or Sichuan and Yunnan provinces, indicating that the samples of ADS and ACY from the above four provinces could not be well distinguished according to the content of the AAs/ALs ( Figure 4C,D).
To evaluate the intra-group differences among the samples from different species and origins, supervised OPLS-DA was further performed to obtain the corresponding model. As shown in Figure 5A, all the samples were obviously clustered into the distinct groups corresponding to the species (R 2 X = 0.627, R 2 Y = 0.982, Q 2 = 0.922).
In Figure 5B, OPLS-DA analysis gave similar robust differentiation of the AMH samples from Hubei and Shandong provinces (R 2 X = 0.764, R 2 Y =0.995, Q 2 = 0.968). The OPLS-DA scores plot also showed an obvious separation between Hubei and Guangxi provinces, with R 2 X of 0.740, R 2 Y of 0.995, Q 2 = 0.803 ( Figure 5C), indicating that the AAs/ALs contents of ADS from the two provinces were different. However, the OPLS-DA scores plot of ACY could not reveal an obvious separation between Sichuan and Yunnan provinces, indicating that the samples of ACY from the two provinces could not be well distinguished according to the contents of the AAs/ALs ( Figure 5D). analysis on the SIMCA software. The PCA scores plot showed a considerable separation tendency among the three species of AMH, ADS and ACY, with an R 2 X of 0.609. Distinct from other samples, all the samples of ACY cluster were in one region. Samples of ADS were in the lower left quadrant, while the samples of AMH were in both the upper and lower left quadrants ( Figure 4A). As shown in Figure 4B, the PCA scores plot that displayed the separation between Hubei and Shandong provinces were obviously significant (R 2 X = 79.7%), indicating that the AAs/ALs contents of the AMH from the two provinces were different. However, the PCA scores plot of ADS (R 2 X = 0.634) and ACY (R 2 X = 0.704) could not reveal a considerable separation either between Hubei and Guangxi provinces, or Sichuan and Yunnan provinces, indicating that the samples of ADS and ACY from the above four provinces could not be well distinguished according to the content of the AAs/ALs ( Figure 4C,D).  To evaluate the intra-group differences among the samples from different species and origins, supervised OPLS-DA was further performed to obtain the corresponding model. As shown in Figure 5A, all the samples were obviously clustered into the distinct groups corresponding to the species (R 2 X = 0.627, R 2 Y = 0.982, Q 2 =0.922). In Figure 5B, OPLS-DA analysis gave similar robust differentiation of the AMH samples from Hubei and Shandong provinces (R 2 X = 0.764, R 2 Y =0.995, Q 2 = 0.968). The OPLS-DA scores plot also showed an obvious separation between Hubei and Guangxi provinces, with R 2 X of 0.740, R 2 Y of 0.995, Q 2 = 0.803 ( Figure 5C), indicating that the AAs/ALs contents of ADS from the two provinces were different. However, the OPLS-DA scores plot of ACY could not reveal an obvious separation between Sichuan and Yunnan provinces, indicating that the samples of ACY from the two provinces could not be well distinguished according to the contents of the AAs/ALs ( Figure 5D).

Identification of Differential Components
Compounds with variable importance in projection (VIP) values larger than 1 and p < 0.05 were viewed as differential compounds and discriminate quality markers. On the basis of the results of VIP value and t test, the AAs labeled with different origins were screened and identified.
A total of 33 significant markers were determined to facilitate discrimination of three kinds of medicinal materials ( Figure 6A). The components were tentatively identified as cinnabarin, aristoliukine C, 9-OH-AAI, AAI

Identification of Differential Components
Compounds with variable importance in projection (VIP) values larger than 1 and p < 0.05 were viewed as differential compounds and discriminate quality markers. On the basis of the results of VIP value and t test, the AAs labeled with different origins were screened and identified.
A total of 33 significant markers were determined to facilitate discrimination of three kinds of medicinal materials ( Figure 6A). The components were tentatively identified as cinnabarin, aristoliukine C, 9-OH-AAI, AAI   A total of 19 differential markers from AMH samples in Hubei and Shandong province, 16 differential markers from ADS samples in Hubei and Guangxi province and 22 differential markers from ACY samples in Sichuan and Yunnan province were screened out, respectively ( Figure 6B−D). The above AA components may be the main reason for the differences in the three Aristolochiaceae medicinal herbs from different origins.

Method Validation
An efficient UPLC-QTOF-MS/MS method for quantitative analysis was validated based on linearity, limits of detection (LOD), limits of quantitation (LOQ), intra-day and inter-day precision, stability, and accuracy (Tables 2 and 3). All calibration curves showed good linearity (R 2 > 0.9964) within the test ranges (Table 3). This analysis method was experimentally demonstrated to have good precision, stability and reproducibility (RSD < 5%). The recovery of quantitative AAs ranged from 97.23% to 103.19% (RSD from 3.87% to 4.68%, respectively) ( Table 2). In addition, the peak purity was investigated by analyzing the UPLC and MS/MS data, and no indication of impurity was found. The results indicated that the proposed method was effective and accurate for the determination of AA standards.

Quantitative Analysis of AAs in Herbal Samples in Aristolochia
AAs were mainly distributed in the medicinal plants of Aristolochia family, such as A. debilis, A. contorta, A. fangchi, A. mollissima and A. cinnabaria. In this study, fifty-two herbal samples, belonging to three representative AA-containing species in the Aritolochia family, were analyzed for their content of AAs. The samples included 15 batches of aerial part of A. debilis (ADS), 16 batches of A. mollissima (AMS) herb, and 21 batches of A. cinnabaria (ACY) root. The AAs exhibited strong mass spectrum signals in the positive mode. Multiple reaction monitoring (MRM) of UPLC-QTOF-MS/MS was performed for quantification. Indometacin was used as an internal standard.
The established analysis method was suitable for the quantification of seven AAs in AMH sample and five AAs in the ADS sample ( Figure 7). As can be seen from the results in Tables S4-S6 (Table S4), with the content of AAI being the highest. AAI and AAII were undoubtedly the main toxic components, with high contents in AMH. Moreover, the contents of AAI, AAII, AA C, AA D, and AL-I in 15 batches of ADS were 6.734-17.256, 4.438-33.322, 0.945-2.297, 2.792-120.623, and 0.894-32.102 µg/g, respectively (Table S5). As a result, as shown in Table S5, ADS contained a smaller amount of AAs compared to the other two herbs. However, AA D possessed the highest contents among the quantified AAs in ADS, a feature which was different from most medicinal herbs in the Aristolochia genus. The determination of the AA contents in ACY was part of a previous study by our team (Table S6), where quantitative results were compared with the above AA contents in AMH and ADS [27].
The contents of medicinal herbs from different origins were compared, and it was found that the origins had obvious impact on the AA contents of the three medicinal herbs ( Figure 8A-C). The three groups of herbal samples with high AA contents could be easily visualized according to their different origins. Furthermore, each AA's content could be easily compared with the other analogues in all three herbs of the Aristolochia family ( Figure 8D). The total contents of AAs in ACY were considerably higher than those in the other species of AMH and ADS. Thus, we could conclude that ACY is the most toxic.  (Table S4), with the content of AAΙ being the highest. AAΙ and AAΙΙ were undoubtedly the main toxic components, with high contents in AMH. Moreover, the contents of AAΙ, AAΙΙ, AA C, AA D, and AL-Ι in 15 batches of ADS were 6.734-17.256, 4.438-33.322, 0.945-2.297, 2.792-120.623, and 0.894-32.102 μg/g, respectively ( Table S5). As a result, as shown in Table S5, ADS contained a smaller amount of AAs compared to the other two herbs. However, AA D possessed the highest contents among the quantified AAs in ADS, a feature which was different from most medicinal herbs in the Aristolochia genus. The determination of the AA contents in ACY was part of a previous study by our team (Table S6), where quantitative results were compared with the above AA contents in AMH and ADS [27].
The contents of medicinal herbs from different origins were compared, and it was found that the origins had obvious impact on the AA contents of the three medicinal herbs ( Figure 8A-C). The three groups of herbal samples with high AA contents could be easily visualized according to their different origins. Furthermore, each AA's content could be easily compared with the other analogues in all three herbs of the Aristolochia family ( Figure 8D). The total contents of AAs in ACY were considerably higher than those in the other species of AMH and ADS. Thus, we could conclude that ACY is the most toxic.     Data are expressed as the mean ± SD. *: p < 0.05 and **: p < 0.01 analyzed by Mann Whitney U test. # represents p < 0.05; ## represents p < 0.01; ### represents p < 0.001. It was analyzed by Dunn's test using Bonferroni method. "ns" represents no significant differences.

Cytotoxicity and Genotoxicity of AAs and the Extracts
AAI and AAII are the most common aristolochic acids produced by the plants of the Aristolochiaceae family. Both nitro and methoxy groups in their structures exert the toxicity, and substitutions of nitro groups possess more toxicity those of methoxy. Similarly, aristolactams are divided into two types, I and II, according to their structures, with or without the methylenedioxy group, respectively. Some of the type II ALs displayed cytotoxicities against the tumor cells [9]. AAs and their analogues have been reported to implicate liver cancer, suggesting that their related herbal extracts and their products may induce hepatotoxicity [29]. Therefore, in this study, we evaluated cytotoxicity against HepG2 tumor cells and genotoxicity of AAs and the extracts of AMH and ADS.
The results of the cytotoxicity assay indicated that AAI showed moderate cytotoxicity against HepG2 cell line, but AAD had no cytotoxicity. Among the AA derivatives, AL-BII exhibited the most potent cytotoxicity, and possessed selective cytotoxicity against the NCI-H187 cell line, but no cytotoxicity against A549 and MCF7 [30,31]. Particularly worth mentioning is that AMH extract displayed potent toxicity with an IC 50 value of 9.7 µM, but ADS extract only had weak cytotoxicity (IC 50 value of 92.9 µM) against the HepG2 cell line (Table 4). Adriamycin and DMSO were used as positive and negative controls, respectively, and the data are expressed as means ± SD (n = 3). "-" indicates IC 50 values more than 1 mM.
Comet assay was used to evaluate the effects of AAI, AAII, ADS and AMH extracts on DNA damage of the HepG2 cells (Figures 9 and S5).
Statistical significance for the comet assays was determined by analysis of Kruskal-Wallis test with Bonferroni correction. In Figure 9A, Kruskal-Wallis test comparisons revealed significant differences in the tail DNA content between the blank control group and the other four groups, while the AAII group showed no significance (Kruskal-Wallis test comparisons of blank vs. AAI or AMH or ADS or ADM, p < 0.001; and blank vs. AAII, p > 0.05). The tail DNA content of AAI was much higher than those of AAII and ADS, increasing by 16 times and 4.7 times, respectively, and exhibited no obvious difference with that of the positive control ADM group (Dunn's test comparisons of AAI vs. AAII or ADS, p < 0.001; and AAI vs. ADM, p > 0.05). The above results indicate that AAI obviously caused damage to the DNA. Therefore, AMH with high AAI causes more serious damage than ADS.
As shown in Figure 9B, the tail length of the AAI, AMH, ADS and ADM groups was significantly higher than that of the blank control group, while the tail DNA content of AAII displayed no significance (Kruskal-Wallis test comparisons of blank vs. AAI or AMH or ADS or ADM, p < 0.001; and blank vs. AAII, p > 0.05). Similarly, the tail length of AAI was much higher than that of AAII and ADS, increasing by 12.8 times and 6.8 times, respectively, with no significant difference from those of the positive control ADM group and the AMH group (Dunn's test comparisons of AAI vs. AAII or ADS, p < 0.001; and AAI vs. ADM or AMH, p > 0.05).
The tail moment values of AAI, AMH, ADS, ADM, and AAII groups were significantly higher than that of the blank control group (Kruskal-Wallis test comparisons of blank vs. AAI or AMH or ADS or ADM or AAII, p < 0.001). Surprisingly, AAI and ADM exhibited markedly enhanced comet tail moment, reaching values significantly higher than other groups. Compared with AAII group, the value of tail moment of AAI significantly increased, by 110 times. Moreover, the value of tail moment of AAI increased approximately 70 times compared with ADS group. However, there were no obvious differences between the AAI group and the AMH and ADM groups (Dunn's test comparisons of AAI vs. ADS, p < 0.001; and AAI vs. ADM or AMH, p > 0.05) ( Figure 9C).
Combined with the cytotoxic results, the comet assay indicated that both medicinal herbs could cause cellular DNA damage. AMH was more toxic than ADS, which was consistent with the quantitative results. The AAII group was not statistically significant compared with the negative control group, indicating that AAII caused no obvious damage to the DNA of HepG2 cells.
NCI-H187 cell line, but no cytotoxicity against A549 and MCF7 [30,31]. Particularly worth mentioning is that AMH extract displayed potent toxicity with an IC50 value of 9.7 µM, but ADS extract only had weak cytotoxicity (IC50 value of 92.9 µM) against the HepG2 cell line (Table 4).
Comet assay was used to evaluate the effects of AAI, AAII, ADS and AMH extracts on DNA damage of the HepG2 cells (Figures 9 and S5). Compared with the negative control group, * represents p < 0.05; ** represents p < 0.01; **** represents p < 0.0001. Statistical significance for the comet assays was determined by analysis of Kruskal-Wallis test with Bonferroni correction. "ns" represents no significant differences.

Conclusions
In this study, UPLC-QTOF-MS/MS was used to establish a qualitative and quantitative method for the analysis of AA components of Aristolochia herbs. A comparative analysis of AAs was applied to different medicinal herbs in Aristolochia family. Over forty AA analogues, including AAs and ALs types, were identified from each studied herb, whereby AAI was the principle component in both AMH and ACY. However, AAIVa (AA D) was the main component in ADS. It is worth mentioning that ACY possesses large amounts of AAsI, II, III and IVa, which should be the most toxic among the three medicinal herbs. Chemometric results indicate that more than 14 AAs have statistical significance for differentiating the three herbal samples from different origins. The toxicity of AAs and the herbal extracts were evaluated by MTT method and Comet assay in HepG2 cell line. The compound of AL-BII exhibited the most potent toxicity, and the herbal extract of AMH also had strong toxicity. Similarly, comet assay showed that the DNA damage caused by AMH was greater than that caused by ADS. Thus, the quantitative results are consistent with the experimental data on toxicity, suggesting that long-term exposure to high levels of AMH and ADS would cause a risk of liver injury. The dosages of AMH and ADS should be paid more attention and limited in the clinical application. Our findings will have important significance for the safety control of such AA-containing herbs and their related prescriptions.

Preparation of Standard and Sample Solutions
The stock solutions were prepared separately by dissolving the reference compounds in methanol to obtain solutions of AAI, AAII, AA C, AA D, AL-I, AL-BII, and AL-FI, respectively. Then, fix the volume in a volumetric flask and prepare the mixed reference substance solution with the corresponding mass concentrations of 140.00, 90.00, 20.00, 30.00, 10.00, 0.20, and 9.00 µg/mL, respectively, and store at 4 • C for later use. The stock solution was prepared by dissolving the internal standard substance in methanol to obtain a solution of indomethacin (50.00 µg/mL), which was stored at 4 • C for later use.
A total of 5.0 g powdered sample was extracted with 100 mL 75% ethanol for 2 h under reflux. The organic solvent was removed under reduced pressure to yield the extract. Then the extract was filled to a 25 mL volumetric flask with methanol to get the test solution. Then, 180 µL of the test solution and 20 µL of the internal standard solution were mixed and successively filtered through a 0.22 µm membrane filter before injection. Each sample preparation and injection were repeated. The solution was stored at 4 • C before quantitative analysis.
For the qualitative experiment, the above ethanol sample was further extracted with petroleum ether and ethyl acetate. The ethyl acetate layer was concentrated and dissolved in methanol to make a solution of 0.5 mg/mL. Finally, the solution was filtered through a 0.22 µm membrane filter before injection. The preparation and injection of each sample was repeated. The solution was stored at 4 • C.
For MS detection, a Q-TOF MS spectrometer was fit with electrospray ionization (ESI) in positive ionization mode at full scan mode ranged m/z 50-1500. The MS parameters were as follows: cone voltage 30 V, capillary voltage 3.0 kV, cone gas flow rate (N 2 ) 50 L/h, desolvation gas flow rate 800 L/h, ion source temperature 120 • C, desolvation gas temperature 450 • C, and spectrum acquisition frequency 0.2 s.
All the data were analyzed using UNIFITM1.9.4.053, Progenesis QI, simca14.0 and GraphPad Prism 7. The mass spectrum parameters of quantitative compounds are shown in Table 5. Using the peak area Y (the ratio of the peak area of the reference to that of the internal standard) versus the mass concentration X (the ratio of the reference to the internal standard), the standard curve was drawn and calculated to obtain a linear regression equation and a linear range. The limits of detection (LODs) and limits of quantification (LOQs) of the samples were estimated at signal-to-noise ratios (S/N) of 3 and 10, respectively.

Precision, Stability, Repeatability and Recovery
To verify the precision, Sample X03 was injected six times consecutively and the RSD values of peak areas were calculated. To verify the stability, Sample X03 was analyzed at 0, 2, 4, 8, 12, 16, 20, and 24 h, respectively. To verify the repeatability, we prepared six test samples and performed six replicate analyses. The variability is expressed as RSD (%). The recovery experiment was determined by the standard addition method. The controls of seven components equal to the content in sample X03 were added precisely. The recoveries were calculated based on the difference in mass of these standards before and after addition.

Multivariate Statistical Analysis and Comparison
The data files for the qualitative components and peak areas of 16 batches of AMH (from Hubei and Shandong), 16 batches of ADS (from Hubei and Guangxi) and 21 batches of ACY (from Sichuan and Yunnan) were exported using Progenesis QI software and then imported to simca14. 0 software for PCA principal component analysis. The supervised pattern analysis of OPLS-DA was performed according to the different origins of the same medicinal material and three different medicinal herbs. The compounds that contributed significantly to the isolation between groups were initially screened (VIP value > 1) according to variable importance in projection (VIP), and potential differentially labeled compounds were screened based on independent sample t-test (p < 0.05 for statistically significant difference). 4.6. Cytotoxicity Assay and Comet Assay 4.6.1. Cytotoxicity Assay The cytotoxicity of the compounds to HepG2 was determined using the MTT method. First, the cells were transferred from the culture dish to a centrifuge tube, and centrifuged for 5 min (at 1000 r/min). After discarding the supernatant, the tumor cells were cultured in a complete medium containing 15% fetal bovine serum at 37 C, 5% CO 2 , and saturated humidity. When the cells grew logarithmically, they were spread onto plates, and the cell density was adjusted to 8.0 × 10 4 cells/mL before the cell sap was added into a 96-well plate (200 µL per well). The cells grew adherent for 24 h. After 24 h, 2 µL of two standards, two extracts of medicinal herbs were added to each plate well and incubated for 72 h. Adriamycin was used as the positive control, and the blank control contained 2 µL DMSO. After incubation, 20 µL of 5 mg/mL MTT solution was added, and the plates were incubated for 4 h. The supernatant liquid was removed, and the cells were disrupted with 200 µL of DMSO for 10 min. After the blue crystalline substance was fully dissolved, the absorbance value was measured on a microplate reader with the detection wavelength of 562 nm and the reference wavelength of 630 nm. The IC 50 value of each compound was calculated.

Comet Assay
Cells in the logarithmic growth phase were inoculated in 6-well plates, and the cell density was adjusted to 2.5 × 10 5 cells /mL, 2 mL per well. After 24 h, the experimental group was combined with AAI (50 µM), AAII (131.5 µM), extracts of the AMH (10 mg/mL) and ADS (93 mg/mL), the positive control group was combined with ADM (3.4 µM), and the blank control group were added with the same volume of cell culture solution. After 48 h of culture, the cells were collected. DNA damage was detected according to the operating instructions of comet assay kit. The experiment was repeated 3 times, and 50 cells were selected at each dose in each experiment and analyzed by Comet Assay software (CASP, http://casplab.com/, accessed on 5 October 2022). The mean values of tail DNA percentage, tail length, and tail moment of three experiments were used to express DNA damage. Results one-way ANOVA was used to test the data between groups, and the difference was statistically significant when p < 0.01. Data and statistical results are generated by GraphPad Prism 7 software.
Supplementary Materials: The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/toxins14120879/s1, Figure S1: MS/MS fragments of AAI, AAII, AAD, Al-I, and AL-II. Figure S2: Typical LC-MS/MS total ion chromatograms (TIC) of the whole herb of AMH in positive ion modes. Figure S3: Typical LC-MS/MS total ion chromatograms (TIC) of the whole herb of ADS in positive ion mode. Figure S4: Typical LC-MS/MS total ion chromatograms (TIC) of the whole herb of ACY in positive ion modes. Figure S5 Results of comet assay. Table S1: Constituents identified information of AMH.