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Non-targeted metabolite profiling and specific targeted discrimination strategy for quality evaluation of Cortex Phellodendri from different varieties

Cortex Phellodendri is derived from two species of Phellodendron amurense Rupr. and Phellodendron chinense Schneid. Traditionally, the two species are utilized interchangeably under the name of “huangbo” in the clinic because they are believed to share the same clinical efficacy. However, the chemical analysis in vitro couldn't directly reflect the pharmacological effects. Therefore, whether the constituents could be absorbed into the blood becomes the uppermost problem to account for the clinical efficacy differences of the two species. Therefore, a rapid and sensitive approach to differentiate the two species of Cortex Phellodendri based on non-targeted metabolite profiling and the specific targeted discrimination strategy was first established. Samples from different cultivars were clearly discriminated by principal component analysis and orthogonal partial least squares discriminant analysis. 17 prototype compounds and 22 metabolites contributing to the group separation were identified and tentatively characterized, three of which were found for the first time. Moreover, six of them were screened out as the chemical markers which contribute most to the differences between the two species. Taken together, the application of the non-targeted metabolite profiling and specific targeted discrimination strategy is suitable for the assessment of Cortex Phellodendri.


Introduction
Traditional Chinese medicine (TCM) has been widely utilized in the prevention and treatment of human diseases and has an indispensable role in the healthcare system in China. 1 Up to now, TCM has garnered increasing attention, not only because of its inspiring and reliable clinical efficacy, but also its outstanding sources of bioactive compounds in the search for new drugs. [2][3][4][5] Nevertheless, in the procedure of "modernization" and "globalization" of TCM, a pivotal problem is the consistency and controllability of the quality of TCM. Cortex Phellodendri (huangbo in TCM), derived from the dried bark of Phellodendron chinensis Schneid. and Phellodendron amurense Rupr., is one of the 50 fundamental herbs of TCM and is utilized as an essential part of herbal medicine in curing diarrhea, jaundice and other syndromes. 6 The two species of herbs are known as Cortex Phellodendri chinensis (HB, chuanhuangbo in China) and Cortex Phellodendri amurensis (GHB, guanhuangbo in China) respectively, which are usually utilized interchangeably in clinical applications because they are believed to have similar pharmacological effects. Accordingly, they are included in the Chinese Pharmacopoeia as official drugs in a single monograph. 7 However, some researchers discovered that the constituents existing among these two species are signicant differences. And the doubt has been begun on whether their clinical efficacy is similar. Therefore, it is essential and urgent to search for a rapid and reliable analytical method for identify and control the quality of Cortex Phellodendri.
Nowadays, liquid chromatography coupled with tandem mass spectrometry (LC-MS) lays a foundation for the analysis of herbal constituents in vivo. 8 It has already become a powerful technique for rapid identication of constituents in TCM and biological samples, which can be utilized to clarify underlying mechanisms. However, content change of trace constituents between species may not be detected but largely affect the health of human beings. Multivariate statistical analysis such as principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) is concerned with the analysis and explication of intricate data types built up by numerous and highly related variables. [9][10][11] Using the LC-MS coupled with multivariate statistical analysis approaches, the constituents can be ltered easily with no previous study of the compound structure.
Several analytical methods on chemical analysis have been utilized to evaluate TCM quality, such as ngerprint analysis and quantitative determination of HPLC et al. [12][13][14] However, whether these alleged bioactive constituents can be absorbed into blood to produce pharmacological function is still uncertain. In this study, quality evaluation and species discrimination of Cortex Phellodendri from different varieties was performed to deliver the strategy based on both non-targeted and targeted analysis. The schematic ow is illustrated in Fig. 1. In the research, non-targeted metabolite proling method based on multivariate statistical analysis was developed and fully validated to screen out the constituents absorbed into blood for conrming the xenobiotic structures. For the purpose of nding the potential chemical markers, specic targeted discrimination approach was employed to analyze the discrimination of two species of Cortex Phellodendri. In general, a systematic strategy was established for comprehensive quality evaluation of Cortex Phellodendri from different varieties.

Chemicals and reagent
Acetonitrile and formic acid of HPLC grade were purchased from Merck (Darmstadt, Germany), and HPLC grade methanol was obtained from Fisher Scientic (Pittsburgh, USA). Ultra high purity water was freshly produced by Millipore-Q water purication system (Bedford, USA). All other chemicals and reagents were of analytical grade and commercially available.

Plant material
Five batches of Cortex Phellodendri chinensis and ve batches of Cortex Phellodendri amurensis were purchased from Kangmei pharmaceutical Co., Ltd. and authenticated by Professor Minjian Qin (Department of Chinese Materia Medica, China Pharmaceutical University, Nanjing, China). The quality of these crude drugs was controlled and processed according to the Chinese Pharmacopoeia (2015).

Sample preparation
All crude drugs were ground into powder before use. HB and GHB were percolated in water (1 : 10, w/v) for 0.5 h and decocted by boiling for 1 h. The extracted solution was then decanted, ltered through six layer gauze. The procedure was repeated and the ratio of the total weight of the herbs and the volume of water for the second were 1 : 8. The extracts were combined and Fig. 1 Schematic representation of chemical markers analysis strategy utilized for HB and GHB. evaporated to dry under reduced pressure, and then the solution was freeze-dried and stored in a vacuum desiccator before use. The nal ratio of powder to raw herb of HB and GHB were 30.31% and 26.02%, respectively. Before given to rats, appropriate amounts of the freeze-dried powders were dispersed in normal saline.

Animal experiments
Fieen male Sprague-Dawley (SD) rats with the weight of 200 AE 20 g were obtained from the Animal Multiplication Center of Qinglong mountain (Permission No. SCXK-ZHE 2014-0001). All animals were adapted for one week under 50 AE 20% humidity and 25 AE 2 C with a 12 h light/dark cycle circumstances with puried water and standard chow ad libitum before experiment. All rats were fasted for 12 h with free access to water prior to the experiment. All protocols and care of the rats were in accordance with the Guidelines for the Care and Use of Laboratory Animals of China Pharmaceutical University and approved by the Animal Ethics Committee of China Pharmaceutical University. The rats were stochastically divided into the HB-dosed group, GHB-dosed group and control group (n ¼ 5 for each group). HB and GHB were dissolved in normal saline and intragastrically administered to rats at a dose of 20 g kg À1 d À1 for consecutive three days. While the rats serving as control received normal saline with equivalent volume. Aer three days, blood samples (approximately 0.5 mL) were collected from the fosse orbital vein using heparinized 1.5 mL polythene tubes aer dosing at 0.5, 0.75, and 1 h, which were selected by the T max reported of related compounds and preliminary experiment, then centrifuged immediately at 12,000 rpm for 10 min at 4 C to obtain plasma. The plasma samples at different time points of a single rat were mixed, then labeled and stored at À80 C until analysis.

Sample preparation
One milliliter of thawed serum samples and 3 mL of acetonitrile were transferred to a polypropylene tube, and the solution was then mixed stand for 20 min at 4 C before use. The mixture was centrifuged at 3500 rpm for 10 min at 4 C and evaporated to dryness at 30 C under nitrogen gas. The residues were redissolved in 200 mL of 50% methanol, centrifuged at 12000 rpm for 10 min at 4 C and then ltered through a 0.22 mm membrane to obtain the injection samples.
2.6.2 Mass spectrometry experiments. Analysis was performed on a Q-Exactive Plus Orbitrap (Thermo Fisher Scientic, San Jose, USA) with an HESI ion source as interface. The full scan spectra were acquired using negative and positive switch modes over an m/z range of 100-1000 and 3200 V electrospray ionization interface voltage. The temperature and desolvation gas were set at 110 C, 300 C respectively. Orbitrap resolution was set to 70 000 full-width at half-maximum (FWHM) at m/z ¼ 200, which provided approximately three full scan-ddMS2 (data points) per second.
2.7 Data processing 2.7.1 Data extraction. For global analysis, LC-MS raw les were converted to mzXML format using MSConvert. Peak detection and integration was performed using XCMS online platform (https://xcmsonline.scripps.edu). And the method parameters for data processing were set as follows: job style (multigroup job); feature detection (method ¼ centwave, ppm The resulting data matrix was then exported as comma separated values (CSV) les. Data from positive and negative ionization modes were included in two separate data sets in order to analyze them individually.
2.7.2 Non-targeted metabolite proling analysis. This step was to differentiate the variables (retention time vs. m/z vs. response) between the control group, HB-dosed group and GHB-dosed group by the pattern recognition approach. SIMCA-P soware (13.0 demo version, Umetrics, Sweden) was utilized to perform multivariate statistical analysis. Principal component analysis and orthogonal partial least squares discriminant analysis were applied to build descriptive and predictive models in order to identify discriminant t R -m/z pairs in rat plasma between the control group vs. HB-dosed group and control group vs. GHB-dosed group. The validity and stability of the models were evaluated by R 2 (Y) and Q 2 (Y) parameters. The OPLS-DA model was validated based on the variance of crossvalidated predictive residuals (CV-ANOVA) (p < 0.05). Variable characteristics in multivariate analysis were ranked according to their Variable Importance in Projection (VIP) values and it was selected as potential discriminant variables with VIP scores greater than 1.
2.7.3 Prototype compounds and metabolites identication. In order to clarify the structures of the potential chemical markers, accurate m/z were rst matched to metabolites from online databases [METLIN (https://metlin.scripps.edu/) and HMDB (http://www.hmdb.ca/)] indicating tentative assignment. Prototype compounds were identied on the basis of HB and GHB chemical composition database, fragmentation in MS/MS. Related metabolites were characterized by the comprehension of the product ions, cleavage patterns of the parent compounds and characteristic neutral losses database corresponding to conjugates, such as SO 3 (80 Da) for sulfate conjugates and C 6 H 8 O 6 (176 Da) for glucuronide conjugates.
2.7.4 Chemical markers screening by specic targeted discrimination analysis. Chemical marker screening (variable selection) plays a signicant role in metabolomics. Chemical markers are dened as biological entities that can be utilized to better discriminate HB and GHB. Import the variables, which were identied above among HB and GHB, into SIMCA-P soware for OPLS-DA analysis based on specic targeted discrimination. Furthermore, the ions appearing at the corner of S-plot with "VIP > 1.00" and "P < 0.05"contribute most to discriminate HB and GHB.

Technical reproducibility of the analytical approach
Preliminary preparation treatment including organic solvent precipitation and C18 solid-phase extraction (SPE) were compared to conrm the appropriate method for different plasma samples. In the result, organic solvent precipitation could obtain more integrated information of exogenous constituents and the interference of endogenous constituents was acceptable. Among the method of organic solvent precipitation, methanol and acetonitrile were compared and the result showed that acetonitrile has lower endogenous interference.
Meanwhile, different mobile phases were screened for the purpose of obtain LC chromatograms with better peak shape and separation. Finally, 0.1% formic acid in acetonitrile and 0.1% formic acid in water were selected as the most suitable eluting solvent system. The majorization of MS spectra which associated with baseline stability and higher ionization efficiency, including capillary voltage, nebulizer pressure, fragmentor voltage, drying gas ow rate and temperature were realized. And the typical global proling about HB-containing plasma sample in positive and negative ion modes was showed in Fig. S1 (ESI). †

Metabolic prole identication based on non-targeted metabolic prole strategy
Aer Pareto scaling with mean-centering, the ltered data were analyzed by PCA and OPLS-DA. PCA, an unsupervised analysis, was rstly employed to observe the classication trends. In the score plots of PCA, it was found that the blank plasma sample (green dots) and HB-containing plasma (blue 4-point star) and GHB-containing plasma (red diamond) were showed a quite clear discrimination ( Fig. 2A and B). Aerwards, supervised OPLS-DA model was investigated to identify potential markers accounting for the group separation. And the prototype compounds and metabolites of HB and GHB which absent in blank plasma sample but present in drug-containing plasma sample were obtained by using S-plot analysis. It can be seen from Fig. S2A to D, † in the green 4-point star S-plot, variables that signicantly contributed to the discrimination were screened according to a threshold of variable importance in the projection (VIP) values (VIP > 1.0) and p-value (cross-validated predictive residuals, CV-ANOVA, p < 0.05). Finally, 39 compounds, including 17 prototype constituents and 22 metabolites, were ltered out and their fragment pathways have been tentatively identied by searching their accurate masses and MS fragmentation behaviors compared with an online biochemical database service METLIN.
3.3 Specic targeted discrimination of HB and GHB in rat 3.3.1 Identication of prototype constituents of HB and GHB aer intragastric administration. Seventeen compounds (8 berberine alkaloids, 3 isoquinoline alkaloids, 2 aporphine alkaloids, 4 other compounds), which could be absorbed into blood aer intragastric administration, were detected and identied based on characteristics MS and mass spectral fragmentation pathways (ESI Table S1 †). Among of which, peaks 3, 8, 11, 12, 13, 15, 16 and 17 were further unequivocal identied as phellodendrine, oxyberberine, berberrubine, tetrahydropalmatine, berberine, palmatine, columbamine and jatrorrhizine, respectively, according to the retention time and MS/ MS information with the standard compounds. Ulteriorly, peaks 4, 5, 7, 9 and 10 were determined as oblongine, magno-orine, lotusine, menisperine, armepavine. To explain the procedure of discriminate about the prototype compounds which were absorbed into blood, taking P13 as an example. This compound was ltrated out which absent in blank plasma sample but present in drug-containing plasma sample and the quasi-molecular ion was 336.1230 [M] + in positive mode and molecular formula was calculated as C 20     3.3.2 Identication of metabolites of HB and GHB aer intragastric administration. The prototype constituents could be further metabolized in rats aer intragastric administration. Reduction, demethylation, oxidative deamination, as well as glucuronide conjugation and sulfate conjugation, were the common metabolic processes affecting HB and GHB in vivo. In this study, a total of 22 metabolites have been identied in rat plasma aer oral administration and mass spectral fragmentation pathways were summarized in Table S2. † Taking the t Rm/z 3.49-676.1898 in positive mode and t R -m/z 2.96-447.0613 in negative mode for example, the t R -m/z pairs were extracted easily at the corner of the S-plot (Fig. 3A and D). Then, extracted ion chromatograms (EICs) in the AE10 ppm narrow mass window ( Fig. 3B and E) and mass spectral fragmentation pathways ( Fig. 3C and F) in MS/MS information was utilized to conform. And in order to research the metabolic mechanism of compounds in vivo, taking the berberine as the example and the proposed metabolic process were showed in Fig. 4

Screening chemical markers by specic targeted discrimination strategy
To further study the chemical disparity between two species of drug-containing plasma sample with the purpose of better veritable and effectively investigate the original dissimilarity. The three-dimensional data (retention time vs. m/z vs. response) in positive mode were subjected to PCA and OPLS-DA analysis. As the result, the PCA scores plots exhibited a good separation among the two species of HB and GHB (Fig. 5A). Supervised OPLS-DA was employed to divide the different groups of decoctions and aid the screening of potential marker chemicals (Fig. 5B). The model statistics, R 2 X ¼ 0.820, R 2 Y ¼ 0.966, and Q 2 ¼ 0.955, indicate that the models are robust and not the result of statistical overtting. 19,20 Moreover, the VIP value plot was utilized to structurally identify these chemical markers (Fig. 5C). In this study, a VIP value above 1.0 scale out by a red box was utilized as a lter standard to select potential chemical markers. Using the method of constituents screening, six ions at the corner of "S" contributed most to the differences between two species drug-containing plasma samples. Thereinto, the concentration levels of berberine, jatrorrhizine, columbamine, berberine-O-sulfate-O-glucuronide detected in HB-containing plasma samples obviously higher than GHB and the compound of 2,3-di-O-glucuronide demethyleneberberine only found in HB-containing plasma samples. In addition, the other compound of magnoorine has higher content in GHBcontaining plasma samples. The intensities difference of 6 potential chemical markers among the HB-containing plasma and GHB-containing plasma were shown in Fig. 6.

Quality assessment of Cortex Phellodendri by hierarchical cluster analysis aer metabolic
Hierarchical cluster analysis (HCA) is one of the most common utilized methods in cluster analysis. The principle of HCA is based on the n samples and each of them is classied as one class. Firstly, calculate the similarities of every two elements and combine it into a class which smallest different samples. Then, calculate the distance of this class with the remained nÀ2 samples. In the procedure of combination, each step is the smallest distance until all samples classied as one class. 21,22 In this study, the result showed that the samples can clearly clustered into three groups. It was demonstrated that HBcontaining plasma and GHB-containing plasma sample had signicant difference so as to indicate that the clinical efficacy is obvious disparity between HB and GHB. HCA results for HBcontaining plasma and GHB-containing plasma sample in positive and negative mode were shown in Fig. 7A and B.

Conclusions
This study provided insights into the chemical proles of Cortex Phellodendri from different cultivars by a non-targeted metabolite proling and specic targeted discrimination strategy. Also, it is noted that 17 prototype compounds and 22 metabolites were annotated and tentatively characterized based on their exact mass and predicted or authentic retention times. And only six of them were ltered out as the potential chemical markers which showed the differences of the two varieties. Alkaloids are the major active compounds in HB and GHB. 6,23,24 Additionally, among them, berberine is known to have anti-inammatory, hepatoprotective, anti-oxidant effects. 25 Besides berberine, the main protoberberine-type alkaloids also exhibited various biological activities similar with that of berberine. 26,27 Recently, considerable attention has been focused on its anticytotoxicity effects with the purpose of developing magnoorine as a potential agent. 28 As the result of Fig. 6, the concentration levels of chemical markers indicated that the pharmacological functions are different among the two varieties. Generally, HB is mainly utilized to anti-diarrheal, antibacterial and anti-inammatory in clinical application. Interestingly, GHB is more potential of the two species to be utilized in traditional medicine as an anti-Alzheimer's disease agent. 29 Previous studies proved that the content of berberine, jatrorrhizine and magnoorine in extraction is different in the two species, however, columbamine has nearly the same. Therefore, whether these alleged bioactive constituents can be absorbed into blood to produce pharmacological function is more important and necessary. 6,13,30 That is to say, these ndings systematically indicate that mix or misuse the two varieties of Cortex Phellodendri are crucial for the safe and effective usage. And in order to better comprehensively explain the reason of diversity, proposed metabolic pathways, taking berberine as an example, have been researched. Taken altogether, the proposed strategy integrating non-targeted and targeted analysis is a promising approach for the quality evaluation of Cortex Phellodendri and the obtained knowledge would be useful for guiding the clinical applications of these herbal drugs.

Conflicts of interest
The authors have declared no conict of interest.