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Article(id=1198628676909756825, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1198628666650493481, articleNumber=null, orderNo=null, doi=10.16438/j.0513-4870.2022-1376, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1671120000000, receivedDateStr=2022-12-16, revisedDate=1680451200000, revisedDateStr=2023-04-03, acceptedDate=null, acceptedDateStr=null, onlineDate=1763704946019, onlineDateStr=2025-11-21, pubDate=1689091200000, pubDateStr=2023-07-12, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1763704946019, onlineIssueDateStr=2025-11-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1763704946019, creator=13701087609, updateTime=1763704946019, updator=13701087609, issue=Issue{id=1198628666650493481, tenantId=1146029695717560320, journalId=1189982191388893191, year='2023', volume='58', issue='7', pageStart='0', pageEnd='1980', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1763704943573, creator=13701087609, updateTime=1766137716668, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1208832456644490122, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1198628666650493481, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1208832456644490123, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1198628666650493481, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1963, endPage=1970, ext={EN=ArticleExt(id=1198628677677314487, articleId=1198628676909756825, tenantId=1146029695717560320, journalId=1189982191388893191, language=EN, title=Quality evaluation of Bupleuri Radix in Shanxi Province by LC-MS based pseudotargeted metabonomics, columnId=1190335348761793317, journalTitle=Acta Pharmaceutica Sinica, columnName=Original Articles, runingTitle=null, highlight=null, articleAbstract=

Bupleuri Radix is commonly used in the traditional Chinese medicine, and saikosaponins are the important active ingredients. In this study, we first established a relative quantitative method for 25 saikosaponins using ultra high performance liquid chromatography-triple quadrupole mass spectrometry (UHPLC-QTrap-MS) in the scheduled multiple reaction monitoring (sMRM) mode. The established method showed good intra-day and intra-day precision, linearity, repeatability and stability. Then the method was applied to compare 37 batches of Bupleuri Radix from different planting areas. The results showed that there was no significant difference in the saikosaponins composition of Bupleuri Radix from different planting areas in Shanxi Province, which indicating that Bupleuri Radix is well adapted to the environment, so it is suitable for widely planting. However, Bupleuri Radix harvested at spring and autumn were differed from those harvested at summer, which indicated that the traditional harvesting experience was reasonable. Correlation analysis showed that saikosaponins a and d were positively correlated with some saponins, and 4 saponins (such as clinoposaponin Ⅻ) showed bigger content variation were identified by coefficient of variation analysis. The LC-MS based pseudotargeted metabonomic method established in this study can be applied to the comprehensive detection of saikosaponins, which providing new method for the quality evaluation of Bupleuri Radix.

, correspAuthors=Xiao-min WANG, Zhen-yu LI, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright ©2023 Acta Pharmaceutica Sinica. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Xue BAI, Ya-xuan GUO, Ai-ling XU, Xiao-xia GAO, Xue-mei QIN, Xiao-min WANG, Zhen-yu LI), CN=ArticleExt(id=1198628679531197025, articleId=1198628676909756825, tenantId=1146029695717560320, journalId=1189982191388893191, language=CN, title=基于LC-MS拟靶向代谢组学的山西北柴胡质量分析, columnId=1190335348896011050, journalTitle=药学学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=

柴胡是中医临床常用中药材, 皂苷是其重要的活性成分。本研究首先利用超高效液相色谱-三重四极杆复合线性离子阱质谱(UHPLC-QTrap-MS) 在智能化分时间段-多反应选择离子监测(scheduled multiple reaction monitoring, sMRM) 模式下建立了25种柴胡皂苷的拟靶向相对定量方法, 所建立的方法具有良好的精密度、线性、重复性和稳定性。将该方法应用于37批不同产地北柴胡样本的比较, 结果显示山西不同产地北柴胡皂苷差异不大, 表明北柴胡生长适应力强, 受产地环境因素影响小, 适合广泛种植。夏季采收的柴胡与传统的春秋采收期采收的柴胡的皂苷类成分存在一定差异, 说明传统采收经验的合理性。相关性分析表明, 柴胡皂苷a和d与部分皂苷类成分存在显著的正相关, 通过变异系数分析确定了clinoposaponin Ⅻ等4种波动较大的皂苷类成分。本研究建立的LC-MS拟靶向代谢组学方法, 可以应用于柴胡皂苷类成分的全面检测, 为柴胡的质量评价研究提供新的方法。

, correspAuthors=王晓民, 李震宇, authorNote=null, correspAuthorsNote=
*王晓民, Tel: 86-359-2121243, E-mail: ;
李震宇, Tel: 86-351-7011202, E-mail:
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Acta Pharm Sin (药学学报), 2018, 53: 1887-1893., articleTitle=Determination of six saikosaponins in Bupleurum chinense DC. samples collected from different producing areas at different harvest time with different processing methods, refAbstract=null)], funds=[Fund(id=1198960106089050328, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, awardId=2019YFC1710805, language=CN, fundingSource=国家重点研发计划项目(2019YFC1710805), fundOrder=null, country=null), Fund(id=1198960106244239588, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, awardId=CARS-21, language=CN, fundingSource=国家现代农业产业技术体系资助(CARS-21), fundOrder=null, country=null), Fund(id=1198960106428788974, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, awardId=YCKJ-2021017, language=CN, fundingSource=山药柴胡种质资源利用及规范生产关键技术研究(YCKJ-2021017), fundOrder=null, country=null), Fund(id=1198960106554618098, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, awardId=2021YNGG05, language=CN, fundingSource=运城道地药材柴胡高质量栽培关键技术研究(2021YNGG05), fundOrder=null, country=null), Fund(id=1198960106739167485, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, awardId=2021-11, language=CN, fundingSource=山西省现代农业产业技术体系建设专项资金资助(2021-11), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1198960096291156310, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, xref=null, ext=[AuthorCompanyExt(id=1198960096316322137, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, companyId=1198960096291156310, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. Modern Research Center of Traditional Chinese Medicine, Shanxi University, Taiyuan 030006, China), AuthorCompanyExt(id=1198960096333099355, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, companyId=1198960096291156310, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.山西大学中医药现代研究中心, 山西 太原 030006)]), AuthorCompany(id=1198960096446345573, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, xref=null, ext=[AuthorCompanyExt(id=1198960096475705706, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, companyId=1198960096446345573, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2. Cotton Research Institute, Shanxi Agricultural University, Yuncheng 044000, China), AuthorCompanyExt(id=1198960096492482923, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, companyId=1198960096446345573, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.山西农业大学棉花研究所, 山西 运城 044000)])], figs=[ArticleFig(id=1198960101877969844, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=EN, label=null, caption=null, figureFileSmall=9xosVynbN/d6KD6JDTB3pA==, figureFileBig=amcJy4Oj4YDCSay/aaeYGw==, tableContent=null), ArticleFig(id=1198960102049936325, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=CN, label=Figure 1, caption= The selection of MRM ion-pair (A) and the optimization of DP (B) of hydroxyl saikosaponin a (DP: Declustering potential) , figureFileSmall=9xosVynbN/d6KD6JDTB3pA==, figureFileBig=amcJy4Oj4YDCSay/aaeYGw==, tableContent=null), ArticleFig(id=1198960102259651551, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=EN, label=null, caption=null, figureFileSmall=zNt9XmZT6uEFQg2ya3qb+g==, figureFileBig=Zb4fD0rxw86o7dAjxXE4xw==, tableContent=null), ArticleFig(id=1198960102532281323, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=CN, label=Figure 2, caption= UHPLC-sMRM pseudo-targeted analysis of ion flow pattern in the negative ion mode. The peak numbers hereby are consistent with those in <a href="javascript:;" class="mag_content_a mag_xref_table" onclick="clickTabXref(this,'Table2')" rid="Table2">Table 2</a> , figureFileSmall=zNt9XmZT6uEFQg2ya3qb+g==, figureFileBig=Zb4fD0rxw86o7dAjxXE4xw==, tableContent=null), ArticleFig(id=1198960102695859190, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=EN, label=null, caption=null, figureFileSmall=2VVAZdEot5A8rvW6sOYImA==, figureFileBig=+qabFgarW0ANXHrAGArRFg==, tableContent=null), ArticleFig(id=1198960102855241733, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=CN, label=Figure 3, caption= PCA (A) score plot of Bupleuri Radix from different planting areas; PLS-DA (B) score plot of Bupleuri Radix collected at different harvesting seasons (X: Summer; CQ: Spring and autumn) , figureFileSmall=2VVAZdEot5A8rvW6sOYImA==, figureFileBig=+qabFgarW0ANXHrAGArRFg==, tableContent=null), ArticleFig(id=1198960102976876561, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=EN, label=null, caption=null, figureFileSmall=2ZaLKS9yyLP9h1nWpCrO9Q==, figureFileBig=4he1tUPN7jeC+2Qlje+cUg==, tableContent=null), ArticleFig(id=1198960103140454427, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=CN, label=Figure 4, caption= Total saponins content of Bupleuri Radix from different planting areas , figureFileSmall=2ZaLKS9yyLP9h1nWpCrO9Q==, figureFileBig=4he1tUPN7jeC+2Qlje+cUg==, tableContent=null), ArticleFig(id=1198960103308226597, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=EN, label=null, caption=null, figureFileSmall=6ZaBA8OBnXy42uMX3aNK0Q==, figureFileBig=a+CHpiPSxfYIxaJ+f8ksWw==, tableContent=null), ArticleFig(id=1198960103488581679, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=CN, label=Figure 5, caption= Heat map of different metabolites at different harvesting seasons (CQ: Spring and autumn; X: Summer) , figureFileSmall=6ZaBA8OBnXy42uMX3aNK0Q==, figureFileBig=a+CHpiPSxfYIxaJ+f8ksWw==, tableContent=null), ArticleFig(id=1198960103673131069, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=EN, label=null, caption=null, figureFileSmall=q7CP0y6CfQUZeJQCuXBr3w==, figureFileBig=GhCMXCePI77l2J8LXDc9uA==, tableContent=null), ArticleFig(id=1198960103861874767, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=CN, label=Figure 6, caption= Correlation map of 25 saponins (<sup>*</sup><i>P</i> < 0.05, <sup>**</sup><i>P</i> < 0.01, <sup>***</sup><i>P</i> < 0.001 between the two components being compared) , figureFileSmall=q7CP0y6CfQUZeJQCuXBr3w==, figureFileBig=GhCMXCePI77l2J8LXDc9uA==, tableContent=null), ArticleFig(id=1198960104075784281, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
Serial No. Time of harvest Area of collection Serial No. Time of harvest Area of collection
CH-19-02 2019.11 Yuncheng CH-20-28 2020.01 Shaanxi
CH-20-01 2020.03 Jinzhong CH-20-29 2020.01 Gansu
CH-20-02 2020.09 Jinzhong CH-20-30 2020.09 Gansu
CH-20-03 2020.08 Yuncheng CH-20-32 2020.01 Gansu
CH-20-04 2020.03 Yuncheng CH-20-33 2020.01 Gansu
CH-20-05 2020.01 Yuncheng CH-20-34 2021.11 Hebei
CH-20-06 2020.07 Yuncheng CH-21-01 2021.06 Linfen
CH-20-07 2020.07 Yuncheng CH-21-02 2021.06 Linfen
CH-20-08 2020.09 Linfen CH-21-03 2021.06 Linfen
CH-20-09 2020.09 Linfen CH-21-04 2021.06 Linfen
CH-20-11 2020.11 Datong CH-21-05 2021.06 Linfen
CH-20-12 2020.11 Datong CH-21-06 2021.06 Linfen
CH-20-13 2020.11 Datong CH-21-08 2021.06 Linfen
CH-20-15 2020.11 Xinzhou CH-21-09 2021.06 Linfen
CH-20-23 2020.09 Yuncheng CH-21-11 2021.06 Linfen
CH-20-24 2020.09 Yuncheng CH-21-12 2021.06 Linfen
CH-20-25 2020.01 Yuncheng CH-21-13 2021.06 Datong
CH-20-26 2020.01 Linfen CH-21-14 2021.06 Datong
CH-20-27 2020.09 Datong
), ArticleFig(id=1198960104239362148, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=CN, label=Table 1, caption=

The sample information of Radix Bupleurum

, figureFileSmall=null, figureFileBig=null, tableContent=
Serial No. Time of harvest Area of collection Serial No. Time of harvest Area of collection
CH-19-02 2019.11 Yuncheng CH-20-28 2020.01 Shaanxi
CH-20-01 2020.03 Jinzhong CH-20-29 2020.01 Gansu
CH-20-02 2020.09 Jinzhong CH-20-30 2020.09 Gansu
CH-20-03 2020.08 Yuncheng CH-20-32 2020.01 Gansu
CH-20-04 2020.03 Yuncheng CH-20-33 2020.01 Gansu
CH-20-05 2020.01 Yuncheng CH-20-34 2021.11 Hebei
CH-20-06 2020.07 Yuncheng CH-21-01 2021.06 Linfen
CH-20-07 2020.07 Yuncheng CH-21-02 2021.06 Linfen
CH-20-08 2020.09 Linfen CH-21-03 2021.06 Linfen
CH-20-09 2020.09 Linfen CH-21-04 2021.06 Linfen
CH-20-11 2020.11 Datong CH-21-05 2021.06 Linfen
CH-20-12 2020.11 Datong CH-21-06 2021.06 Linfen
CH-20-13 2020.11 Datong CH-21-08 2021.06 Linfen
CH-20-15 2020.11 Xinzhou CH-21-09 2021.06 Linfen
CH-20-23 2020.09 Yuncheng CH-21-11 2021.06 Linfen
CH-20-24 2020.09 Yuncheng CH-21-12 2021.06 Linfen
CH-20-25 2020.01 Yuncheng CH-21-13 2021.06 Datong
CH-20-26 2020.01 Linfen CH-21-14 2021.06 Datong
CH-20-27 2020.09 Datong
), ArticleFig(id=1198960104444883058, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
No. Name RT /min DP /V CE /eV m/z
Parent ion Daughter ion
1 HOSSa 13.14 -40 -30 843.466 4 797.492 3
2 Bupleuroside Ⅳ 13.18 -20 -50 797.462 6 635.440 6
3 HOSSd 13.69 -60 -30 843.467 2 797.497 3
4 Magnoside B 14.00 -20 -40 1 135.591 9 1 089.587 0
5 Malonyl-acetyl-hydroxy-SSa 14.10 -60 -50 883.461 5 635.433 4
6 HOSSc 14.79 -60 -40 989.522 8 943.547 9
7 Clinoposaponin Ⅻ 15.46 -60 -30 841.459 7 795.456 5
8 SSc 16.03 -40 -50 971.522 9 925.518 3
9 SSf 16.34 -40 -40 973.537 2 927.533 8
10 Acetyl-SSf 16.76 -20 -40 969.543 1 909.528 6
11 Malonyl-SSf 17.20 -60 -50 1 013.523 7 909.541 2
12 SSb3/SSb4 17.62 -60 -40 857.491 8 811.488 9
13 SSn 17.83 -40 -50 987.508 1 779.477 9
14 Rotundioside N 18.06 -40 -50 987.517 9 779.460 9
15 Chinoposaponin XVIII 18.12 -80 -50 941.511 1 779.458 6
16 SSa 18.63 -20 -50 779.459 5 617.408 4
17 Bupleuroside X 19.00 -80 -50 941.511 0 795.477 0
18 2″‐O‐Acetyl‐SSa 19.20 -20 -30 821.470 6 779.463 1
19 Malonyl-SSa 19.34 -60 -40 865.450 8 779.476 2
20 Dimalonyl-SSa 19.73 -40 -20 951.470 1 907.474 7
21 3″‐O‐Acetyl‐SSa 19.87 -20 -40 821.469 8 779.462 3
22 SSe/SSm 19.95 -20 -30 763.464 1 601.411 9
23 Prosaikegenin A 20.11 -60 -30 663.411 7 617.405 9
24 Acetyl-SSm 20.74 -60 -30 851.480 4 805.477 4
25 Malonyl-SSe 20.97 -40 -20 849.464 8 805.477 8
26 Malonyl-SSn 21.21 -80 -40 1 027.513 2 983.526 1
27 SSb1 21.42 -20 -50 779.459 2 617.406 4
28 Malonyl-SSd 22.11 -40 -30 865.460 5 821.472 6
29 SSd 22.37 -20 -50 779.459 4 617.407 6
30 4″‐O‐Acetyl‐SSa 22.54 -80 -40 821.461 8 779.485 6
31 Diacetyl-SSd 23.12 -20 -30 863.480 8 821.471 8
32 Prosaikegenin D 23.17 -80 -20 663.411 0 617.409 0
33 6″‐O‐Acetyl‐SSa 23.60 -80 -40 821.470 1 779.469 7
34 Astragaloside Ⅳ 17.05 -80 -30 783.500 0 179.200 0
), ArticleFig(id=1198960104654598268, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=CN, label=Table 2, caption=

Optimal ion pairs and optimal CE and DP (CE: Collision energy; HOSSa: Hydroxyl saikosaponin a; HOSSd: Hydroxyl saikosaponin d; HOSSc: Hydroxyl saikosaponin c; SSc: Saikosaponin c; SSf: Saikosaponin f; SSb3: Saikosaponin b3; SSb4: Saikosaponin b4; SSn: Saikosaponin n; SSa: Saikosaponin a; SSe: Saikosaponin e; SSm: Saikosaponin m; SSb1: Saikosaponin b1; SSd: Saikosaponin d)

, figureFileSmall=null, figureFileBig=null, tableContent=
No. Name RT /min DP /V CE /eV m/z
Parent ion Daughter ion
1 HOSSa 13.14 -40 -30 843.466 4 797.492 3
2 Bupleuroside Ⅳ 13.18 -20 -50 797.462 6 635.440 6
3 HOSSd 13.69 -60 -30 843.467 2 797.497 3
4 Magnoside B 14.00 -20 -40 1 135.591 9 1 089.587 0
5 Malonyl-acetyl-hydroxy-SSa 14.10 -60 -50 883.461 5 635.433 4
6 HOSSc 14.79 -60 -40 989.522 8 943.547 9
7 Clinoposaponin Ⅻ 15.46 -60 -30 841.459 7 795.456 5
8 SSc 16.03 -40 -50 971.522 9 925.518 3
9 SSf 16.34 -40 -40 973.537 2 927.533 8
10 Acetyl-SSf 16.76 -20 -40 969.543 1 909.528 6
11 Malonyl-SSf 17.20 -60 -50 1 013.523 7 909.541 2
12 SSb3/SSb4 17.62 -60 -40 857.491 8 811.488 9
13 SSn 17.83 -40 -50 987.508 1 779.477 9
14 Rotundioside N 18.06 -40 -50 987.517 9 779.460 9
15 Chinoposaponin XVIII 18.12 -80 -50 941.511 1 779.458 6
16 SSa 18.63 -20 -50 779.459 5 617.408 4
17 Bupleuroside X 19.00 -80 -50 941.511 0 795.477 0
18 2″‐O‐Acetyl‐SSa 19.20 -20 -30 821.470 6 779.463 1
19 Malonyl-SSa 19.34 -60 -40 865.450 8 779.476 2
20 Dimalonyl-SSa 19.73 -40 -20 951.470 1 907.474 7
21 3″‐O‐Acetyl‐SSa 19.87 -20 -40 821.469 8 779.462 3
22 SSe/SSm 19.95 -20 -30 763.464 1 601.411 9
23 Prosaikegenin A 20.11 -60 -30 663.411 7 617.405 9
24 Acetyl-SSm 20.74 -60 -30 851.480 4 805.477 4
25 Malonyl-SSe 20.97 -40 -20 849.464 8 805.477 8
26 Malonyl-SSn 21.21 -80 -40 1 027.513 2 983.526 1
27 SSb1 21.42 -20 -50 779.459 2 617.406 4
28 Malonyl-SSd 22.11 -40 -30 865.460 5 821.472 6
29 SSd 22.37 -20 -50 779.459 4 617.407 6
30 4″‐O‐Acetyl‐SSa 22.54 -80 -40 821.461 8 779.485 6
31 Diacetyl-SSd 23.12 -20 -30 863.480 8 821.471 8
32 Prosaikegenin D 23.17 -80 -20 663.411 0 617.409 0
33 6″‐O‐Acetyl‐SSa 23.60 -80 -40 821.470 1 779.469 7
34 Astragaloside Ⅳ 17.05 -80 -30 783.500 0 179.200 0
), ArticleFig(id=1198960104788816007, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
No. Name Equation of regression
1 HOSSa y = 49.570 21 x + 0.459 18 (r = 0.996 34)
2 Bupleuroside Ⅳ y = 1.029 37 x + 0.009 79 (r = 0.999 07)
3 HOSSd y = 19.724 48 x + 0.017 45 (r = 0.999 02)
5 Malonyl-acetyl-hydroxy-SSa y = 1.173 21 x + 7.181 66×10-5 (r = 0.994 78)
7 Clinoposaponin Ⅻ y = 9.544 07 x + 0.259 61 (r = 0.999 73)
9 SSf y = 0.705 38 x + 0.060 18 (r = 0.998 74)
10 Acetyl-SSf y = 0.152 16 x + 0.006 52 (r = 0.992 22)
11 Malonyl-SSf y = 0.375 02 x + 0.031 62 (r = 0.998 43)
12 SSb3/SSb4 y = 1.970 07 x + 0.073 31 (r = 0.992 78)
15 Chinoposaponin XVIII y = 0.904 87 x - 0.029 07 (r = 0.992 87)
16 SSa y = 71.119 51 x + 0.515 52 (r = 0.999 41)
17 Bupleuroside X y = 0.431 50 x + 2.82675×10-4 (r = 0.992 73)
18 2″‐O‐Acetyl‐SSa y = 2.363 23 x + 0.072 38 (r = 0.998 17)
19 Malonyl-SSa y = 10.899 58 x - 0.008 90 (r = 0.999 18)
21 3″‐O‐Acetyl‐SSa y = 1.670 58 x + 0.087 61 (r = 0.997 35)
23 Prosaikegenin A y = 120.071 13 x + 6.444 78 (r = 0.999 35)
24 Acetyl-SSm y = 0.928 55 x + 7.912 41×10-4 (r = 0.995 99)
25 Malonyl-SSe y = 2.257 51 x + 0.126 70 (r = 0.996 92)
27 SSb1 y = 17.147 99 x + 0.536 27 (r = 0.999 92)
28 Malonyl-SSd y = 50.900 33 x + 1.136 04 (r = 0.999 61)
29 SSd y = 12.677 61 x + 0.334 23 (r = 0.999 33)
30 4″‐O‐Acetyl‐SSa y = 4.062 47 x + 0.163 83 (r = 0.994 03)
31 Diacetyl-SSd y = 2.470 65 x - 0.002 52 (r = 0.993 66)
32 Prosaikegenin D y = 7.491 24 x + 0.348 36 (r = 0.999 85)
33 6″‐O‐Acetyl‐SSa y = 2.034 60 x + 0.033 12 (r = 0.999 07)
), ArticleFig(id=1198960104935616659, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=CN, label=Table 3, caption=

Linear regression equation. The numbers hereby are consistent with those in Table 2

, figureFileSmall=null, figureFileBig=null, tableContent=
No. Name Equation of regression
1 HOSSa y = 49.570 21 x + 0.459 18 (r = 0.996 34)
2 Bupleuroside Ⅳ y = 1.029 37 x + 0.009 79 (r = 0.999 07)
3 HOSSd y = 19.724 48 x + 0.017 45 (r = 0.999 02)
5 Malonyl-acetyl-hydroxy-SSa y = 1.173 21 x + 7.181 66×10-5 (r = 0.994 78)
7 Clinoposaponin Ⅻ y = 9.544 07 x + 0.259 61 (r = 0.999 73)
9 SSf y = 0.705 38 x + 0.060 18 (r = 0.998 74)
10 Acetyl-SSf y = 0.152 16 x + 0.006 52 (r = 0.992 22)
11 Malonyl-SSf y = 0.375 02 x + 0.031 62 (r = 0.998 43)
12 SSb3/SSb4 y = 1.970 07 x + 0.073 31 (r = 0.992 78)
15 Chinoposaponin XVIII y = 0.904 87 x - 0.029 07 (r = 0.992 87)
16 SSa y = 71.119 51 x + 0.515 52 (r = 0.999 41)
17 Bupleuroside X y = 0.431 50 x + 2.82675×10-4 (r = 0.992 73)
18 2″‐O‐Acetyl‐SSa y = 2.363 23 x + 0.072 38 (r = 0.998 17)
19 Malonyl-SSa y = 10.899 58 x - 0.008 90 (r = 0.999 18)
21 3″‐O‐Acetyl‐SSa y = 1.670 58 x + 0.087 61 (r = 0.997 35)
23 Prosaikegenin A y = 120.071 13 x + 6.444 78 (r = 0.999 35)
24 Acetyl-SSm y = 0.928 55 x + 7.912 41×10-4 (r = 0.995 99)
25 Malonyl-SSe y = 2.257 51 x + 0.126 70 (r = 0.996 92)
27 SSb1 y = 17.147 99 x + 0.536 27 (r = 0.999 92)
28 Malonyl-SSd y = 50.900 33 x + 1.136 04 (r = 0.999 61)
29 SSd y = 12.677 61 x + 0.334 23 (r = 0.999 33)
30 4″‐O‐Acetyl‐SSa y = 4.062 47 x + 0.163 83 (r = 0.994 03)
31 Diacetyl-SSd y = 2.470 65 x - 0.002 52 (r = 0.993 66)
32 Prosaikegenin D y = 7.491 24 x + 0.348 36 (r = 0.999 85)
33 6″‐O‐Acetyl‐SSa y = 2.034 60 x + 0.033 12 (r = 0.999 07)
), ArticleFig(id=1198960105233412258, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
Name FC P
Malonyl-acetyl-hydroxy-SSa 1.471 7 0.015 3
Acetyl-SSf 1.307 7 0.004 6
Malonyl-SSa 1.808 8 0.009 4
3″‐O‐Acetyl‐SSa 1.313 6 0.029 1
Acetyl-SSm 1.449 4 0.044 8
Malonyl-SSd 1.648 0 0.020 0
6″‐O‐Acetyl‐SSa 1.380 4 0.006 8
Clinoposaponin Ⅻ 0.342 1 0.032 5
Prosaikegenin D 0.383 4 0.009 9
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Differential metabolites between different harvesting seasons (FC: Fold change)

, figureFileSmall=null, figureFileBig=null, tableContent=
Name FC P
Malonyl-acetyl-hydroxy-SSa 1.471 7 0.015 3
Acetyl-SSf 1.307 7 0.004 6
Malonyl-SSa 1.808 8 0.009 4
3″‐O‐Acetyl‐SSa 1.313 6 0.029 1
Acetyl-SSm 1.449 4 0.044 8
Malonyl-SSd 1.648 0 0.020 0
6″‐O‐Acetyl‐SSa 1.380 4 0.006 8
Clinoposaponin Ⅻ 0.342 1 0.032 5
Prosaikegenin D 0.383 4 0.009 9
), ArticleFig(id=1198960105552179380, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628676909756825, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
Name V1 Name V2 Name V3
Clinoposaponin Ⅻ 3.63 Clinoposaponin Ⅻ 20.51 Clinoposaponin Ⅻ 1.47
Prosaikegenin D 1.99 Prosaikegenin D 9.85 Prosaikegenin D 1.12
Prosaikegenin A 1.50 SSb3/SSb4 7.30 SSb3/SSb4 1.10
Malonyl-SSa 1.18 Prosaikegenin A 6.30 Prosaikegenin A 0.99
Bupleuroside Ⅳ 0.99 Malonyl-SSa 3.31 Malonyl-SSa 0.65
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Compounds with large variation (V1, V2 and V3 are the coefficient of variation calculated by three different calculation methods)

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Name V1 Name V2 Name V3
Clinoposaponin Ⅻ 3.63 Clinoposaponin Ⅻ 20.51 Clinoposaponin Ⅻ 1.47
Prosaikegenin D 1.99 Prosaikegenin D 9.85 Prosaikegenin D 1.12
Prosaikegenin A 1.50 SSb3/SSb4 7.30 SSb3/SSb4 1.10
Malonyl-SSa 1.18 Prosaikegenin A 6.30 Prosaikegenin A 0.99
Bupleuroside Ⅳ 0.99 Malonyl-SSa 3.31 Malonyl-SSa 0.65
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基于LC-MS拟靶向代谢组学的山西北柴胡质量分析
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白雪 1 , 郭雅璇 1 , 许爱玲 2 , 高晓霞 1 , 秦雪梅 1 , 王晓民 2, * , 李震宇 1, *
药学学报 | 研究论文 2023,58(7): 1963-1970
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药学学报 | 研究论文 2023, 58(7): 1963-1970
基于LC-MS拟靶向代谢组学的山西北柴胡质量分析
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白雪1, 郭雅璇1, 许爱玲2, 高晓霞1, 秦雪梅1, 王晓民2, * , 李震宇1, *
作者信息
  • 1.山西大学中医药现代研究中心, 山西 太原 030006
  • 2.山西农业大学棉花研究所, 山西 运城 044000

通讯作者:

*王晓民, Tel: 86-359-2121243, E-mail: ;
李震宇, Tel: 86-351-7011202, E-mail:
Quality evaluation of Bupleuri Radix in Shanxi Province by LC-MS based pseudotargeted metabonomics
Xue BAI1, Ya-xuan GUO1, Ai-ling XU2, Xiao-xia GAO1, Xue-mei QIN1, Xiao-min WANG2, * , Zhen-yu LI1, *
Affiliations
  • 1. Modern Research Center of Traditional Chinese Medicine, Shanxi University, Taiyuan 030006, China
  • 2. Cotton Research Institute, Shanxi Agricultural University, Yuncheng 044000, China
出版时间: 2023-07-12 doi: 10.16438/j.0513-4870.2022-1376
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摘要
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柴胡是中医临床常用中药材, 皂苷是其重要的活性成分。本研究首先利用超高效液相色谱-三重四极杆复合线性离子阱质谱(UHPLC-QTrap-MS) 在智能化分时间段-多反应选择离子监测(scheduled multiple reaction monitoring, sMRM) 模式下建立了25种柴胡皂苷的拟靶向相对定量方法, 所建立的方法具有良好的精密度、线性、重复性和稳定性。将该方法应用于37批不同产地北柴胡样本的比较, 结果显示山西不同产地北柴胡皂苷差异不大, 表明北柴胡生长适应力强, 受产地环境因素影响小, 适合广泛种植。夏季采收的柴胡与传统的春秋采收期采收的柴胡的皂苷类成分存在一定差异, 说明传统采收经验的合理性。相关性分析表明, 柴胡皂苷a和d与部分皂苷类成分存在显著的正相关, 通过变异系数分析确定了clinoposaponin Ⅻ等4种波动较大的皂苷类成分。本研究建立的LC-MS拟靶向代谢组学方法, 可以应用于柴胡皂苷类成分的全面检测, 为柴胡的质量评价研究提供新的方法。

柴胡  /  柴胡皂苷  /  UHPLC-QTrap-MS  /  拟靶向代谢组学  /  质量评价

Bupleuri Radix is commonly used in the traditional Chinese medicine, and saikosaponins are the important active ingredients. In this study, we first established a relative quantitative method for 25 saikosaponins using ultra high performance liquid chromatography-triple quadrupole mass spectrometry (UHPLC-QTrap-MS) in the scheduled multiple reaction monitoring (sMRM) mode. The established method showed good intra-day and intra-day precision, linearity, repeatability and stability. Then the method was applied to compare 37 batches of Bupleuri Radix from different planting areas. The results showed that there was no significant difference in the saikosaponins composition of Bupleuri Radix from different planting areas in Shanxi Province, which indicating that Bupleuri Radix is well adapted to the environment, so it is suitable for widely planting. However, Bupleuri Radix harvested at spring and autumn were differed from those harvested at summer, which indicated that the traditional harvesting experience was reasonable. Correlation analysis showed that saikosaponins a and d were positively correlated with some saponins, and 4 saponins (such as clinoposaponin Ⅻ) showed bigger content variation were identified by coefficient of variation analysis. The LC-MS based pseudotargeted metabonomic method established in this study can be applied to the comprehensive detection of saikosaponins, which providing new method for the quality evaluation of Bupleuri Radix.

Bupleuri Radix  /  saikosaponin  /  UHPLC QTrap-MS  /  pseudotargeted metabonomics  /  quality evaluation
白雪, 郭雅璇, 许爱玲, 高晓霞, 秦雪梅, 王晓民, 李震宇. 基于LC-MS拟靶向代谢组学的山西北柴胡质量分析. 药学学报, 2023 , 58 (7) : 1963 -1970 . DOI: 10.16438/j.0513-4870.2022-1376
Xue BAI, Ya-xuan GUO, Ai-ling XU, Xiao-xia GAO, Xue-mei QIN, Xiao-min WANG, Zhen-yu LI. Quality evaluation of Bupleuri Radix in Shanxi Province by LC-MS based pseudotargeted metabonomics[J]. Acta Pharmaceutica Sinica, 2023 , 58 (7) : 1963 -1970 . DOI: 10.16438/j.0513-4870.2022-1376
正文
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柴胡为伞形科植物柴胡(Bupleurum chinense DC.) 或狭叶柴胡(Bupleurum scorzonerifolium Willd.) 的干燥根, 前者习称为“北柴胡”, 后者也称为“南柴胡”“红柴胡”。柴胡始载于《神农本草经》, 列为上品, 是中医临床常用中药。柴胡具有疏散退热, 疏肝解郁, 升举阳气之功效[1], 用于感冒发热、寒热往来、胸胁胀痛、月经不调、子宫脱垂、脱肛等病症。柴胡内在品质优劣直接影响着中药临床疗效, 皂苷类成分是柴胡中主要的药理活性成分之一[2], 也是柴胡研究较为广泛和深入的一类化合物。北柴胡是山西的道地药材, 在山西省的种植规模较大[3], 主要集中在山西运城、临汾、长治等地, 此外, 山西大同、吕梁、忻州等地区也有相当规模的种植基地, 使山西北柴胡在药材市场具有较大影响。
按照《中华人民共和国药典》的规定, 柴胡的质量评价指标为柴胡皂苷a (saikosaponin a, SSa) 和柴胡皂苷d (saikosaponin d, SSd)。已有研究表明, 除了柴胡皂苷a和柴胡皂苷d外, 柴胡中还含有结构多样的其他皂苷类成分[2]。因此, 建立一种可同时检测多种皂苷类成分的方法, 对于柴胡的质量评价很有必要。拟靶向代谢组学分析方法结合了非靶向和靶向代谢组学分析的优势, 具有较宽的线性动态范围、高灵敏度、高扫描速率以及良好的重复性[4]。拟靶向代谢组学检测一般采用sMRM模式, 它是在常规多重反应监测(multiple reaction monitoring, MRM) 模式的基础上增设了保留时间, 可以在预设时间窗口内对设定离子对进行扫描, 从而显著提高检测效率和精度[5], 适合组学的大样本分析。拟靶向代谢组学分析目前已经应用于中药的质量评价, 如舒血宁[4]、广陈皮[6]、肉苁蓉[7]、前胡等[8]。
本研究旨在建立一种针对柴胡皂苷类成分的拟靶向代谢组学方法。首先使用超高效液相色谱结合四极杆飞行时间质谱(QTOF-MS) 方法对柴胡皂苷类成分进行定性表征, 然后运用超高效液相色谱结合三重四极杆复合线性离子阱质谱, 在sMRM模式下建立一种柴胡拟靶向代谢组学检测方法, 并对不同产地、不同采收时间的北柴胡中的皂苷类成分进行检测和差异分析。
材料与方法
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化学药品和试剂  质谱级乙腈、质谱级甲醇、质谱级甲酸均购自美国Thermo Fisher Scientific公司; 超纯水(Milli-Q Integral Water Purification System制备, 美国Millipore公司); 黄芪甲苷标准品(批号: HA012079198), 购自宝鸡市辰光生物科技有限公司; 柴胡皂苷a标准品(批号: 000214-201907), 购自江西佰草源生物科技有限公司; 柴胡皂苷b1标准品(批号: PS2121-0025), 购自成都普斯生物科技股份有限公司; 柴胡皂苷c标准品(批号: MUST-17031402) 和柴胡皂苷d标准品(批号: MUST-17050106) 均购自成都曼思特生物科技有限公司。
样本收集  收集山西省内外不同产地、采收期及不同种植方式的柴胡37批, 其中山西省内的北柴胡31批, 分别来自山西大同、运城、临汾、吕梁、晋中、忻州等地。省外北柴胡6批, 分别来自甘肃和陕西。其中, 春秋采收的北柴胡22批, 夏季采收的北柴胡15批, 详情见表 1。样品经山西大学中医药现代研究中心秦雪梅教授鉴定为北柴胡(B. chinense DC.) 的干燥根, 样品保存于山西大学中医药现代研究中心。
供试品溶液制备
内标溶液制备  精密称取黄芪甲苷标准品10 mg置于2 mL量瓶中, 用质谱级甲醇定容, 超声至溶解, 得5 mg·mL-1黄芪甲苷标准溶液。
定性分析用供试品溶液制备  取北柴胡粉末(过四号筛) 2 g置于50 mL锥形瓶中, 封口膜密封, 加甲醇10 mL, 超声处理30 min, 取上清室温下以3 500 r·min-1离心10 min。取上清过0.22 µm微孔滤膜, 得供试品溶液。
拟靶向供试品溶液制备  取上述定性分析供试品溶液1 mL, 加40 µL黄芪甲苷标准溶液。
质控样本(quality control, QC) 制备  取等体积(3 mL) 的37个供试品溶液混合即得QC溶液。另将QC溶液浓缩并梯度稀释, 得到5、4、3.5、3、2.5、2、1.5、1、0.8、0.6、0.4、0.2、0.1、0.05、0.01倍浓度的QC溶液。分别精确量取各个梯度的QC溶液1 mL, 加40 µL黄芪甲苷对照溶液, 得线性供试品溶液。
高分辨质谱数据采集  使用UHPLC (Agilent 1290) 与Triple TOF 5600+质谱仪(AB SCIEX) 联用, 采用T3 (100 mm × 2.1 mm, 1.8 µm) 色谱柱, 流速0.3 mL·min-1, 柱温35 ℃, 进样量3 µL。流动相组成为0.1%甲酸-水(A) 和0.1%甲酸-乙腈(B)。洗脱梯度条件: 0~15 min (10%~40% B), 15~28 min (40%~75% B), 28~33 min (75%~95% B), 33~35 min (95%~95% B), 35~37 min (95%~10% B)。质谱条件: 采用ESI电喷雾离子源, 离子化电压: -4 500 V; 离子源温度: 550 ℃; 去簇电压(declustering potential, DP): 60 V; 碰撞能量(collision energy, CE): 40 ± 15 eV; 气帘气(curtain gas, CUR): 30 psi; 喷雾气(ion source gas 1, GS1): 55 psi; 辅助加热气(ion source gas 2, GS2): 55 psi; 一级扫描模式: Full MS; 二级扫描模式: Full MS/dd-MS2; 扫描范围m/z 100~1 500。此外, 另将CE分别设置为20、30、40和50 eV, 其余条件不变, 以采集不同CE下的图谱。
sMRM最优离子对、CE和DP的优化  使用Onemap软件将不同CE下QC样品的wiff格式文件转换为mgf格式, 随后提取峰表。采用R软件包(https://github.com/zhengfj1994/MRM-Ion_Pair_Finder) 确定每个皂苷类成分最合适的离子对和CE[9]。R语言软件不能优化的成分使用Sciex OS软件自行手动优化, 即根据二级质谱数据, 为每个化合物选择响应度较高的1至2个二级碎片离子作为候选子离子, 分别结合母离子构成离子对, 然后挑选离子对相应强度最高的CE。使用UHPLC (AB SCIEX) 与QTrap3200 (AB SCIEX) 质谱仪联用, 通过sMRM模式下离子跃迁的峰强度最终确定每个化合物响应最高的离子通道, 将该通道所对应的离子对和CE值确定为该化合物的最佳离子对和最佳CE。得到各成分的最佳离子对和最佳CE后, 在sMRM模式下进一步优化DP。将每个离子对的DP分别设置为20、40、60、80 V, 化合物响应最高的离子通道所对应的DP值作为该化合物的最佳DP。
液相色谱和质谱条件  将各化合物的编号、sMRM离子对、保留时间、最佳CE、最佳DP导入sMRM监测列表中, 进行UHPLC-sMRM分析。色谱条件同上述高分辨质谱数据采集, 进样量为5 µL。质谱条件: CUR: 38 psi; 离子化电压: -4 500 V; 温度: 500 ℃; GS1: 50 psi; GS2: 50 psi; 扫描模式为负离子模式。
方法学考察  用浓缩并梯度稀释的QC样本考察线性动态范围, 通过MultiQuant软件计算各个成分峰面积/内标峰面积比值与浓度的关系, 构建回归曲线。选取其中0.6、1、2倍浓度的QC溶液作为低、中、高浓度样本考察日内、日间精密度, 即同一天内三个浓度的QC样本分别连续进6针考察日内精密度, 三个浓度QC样本分别每天进3针, 连续进3天, 考察日间精密度。取1倍浓度QC样本每间隔8针进样1针, 持续24 h, 共5针, 以考察仪器和样本的稳定性。另取柴胡CH21-01平行制备6份供试品溶液, 考察备样方法的重复性。
结果与讨论
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1 皂苷成分鉴定及离子对、CE、DP优化
通过文献[10-17]报道中柴胡皂苷类化合物的质谱信息及裂解规律, 结合标准品对照, 共鉴定柴胡皂苷成分33个。随后通过R语言软件优化出21个皂苷成分的离子对和CE, 其余12个皂苷成分以及内标黄芪甲苷的离子对和CE使用Sciex OS软件手动优化, 最终确定33种皂苷成分和内标黄芪甲苷的最优离子对, 以及最优CE和DP (表 2)。以羟基柴胡皂苷a (hydroxyl saikosaponin a, HOSSa) 为例(图 1), 离子对843.5/797.5和843.5/635.4在不同DP (20 V、40 V、60 V、80 V) 参数下, 均在DP为40 V时响应最高。且DP电压均为40 V时, 离子对843.5/797.5的响应高于843.5/635.4, 故确定最优离子对为843.5/797.5, 其对应的最优DP为40 V。将表 2中的信息导入sMRM列表, 采集负离子模式下的总离子流图(图 2), 峰号与表 2中的编号相一致。利用Multiquant软件提取离子峰, 对峰面积进行积分, 并用内标峰面积进行矫正, 通过相应的回归曲线计算各化合物的相对含量。
2 方法学考察
在33个目标分析物中, 6个皂苷类成分因含量较低导致峰形较差而剔除, 其余的27个成分进一步从线性范围、日间和日内精密度、重复性和稳定性等方面进行方法学考察。重复性考察结果显示, 25个化合物的RSD值均小于20%; 对于24 h内的稳定性, 有24个组分的RSD值小于20%; 日内精密度考察结果显示, 低、中、高浓度下分别有25、25和26个的化合物的RSD值小于20%; 日间精密度考察结果显示, 低、中、高浓度下分别有23、24和24个成分的RSD值小于20%。最终选择的25个柴胡皂苷成分具有良好的稳定性和重复性, 作为拟靶向分析的指标成分。如表 3所示, 这些成分在QC的0.01~5倍浓度范围内均呈现良好的线性关系(r > 0.99)。
3 不同产地、不同采收期北柴胡的皂苷类成分比较
根据上述回归方程计算37批北柴胡中25种皂苷成分的相对含量。首先将37批样本, 按照产地分组进行主成分分析(principal component analysis, PCA) 分析(图 3A), 结果显示不同产地北柴胡之间没有明显的聚类和分离趋势。进一步计算37批北柴胡中25种皂苷成分的总量(图 4), 皂苷总量在不同的柴胡样本中差异也不大。表明北柴胡生长适应力强, 受产地环境因素影响小, 适合广泛种植。
随后将37批北柴胡样本按照传统采收期(春秋) 和非传统采收期(夏) 分组, 采用偏最小二乘法判别分析(partial least squares discriminant analysis, PLS-DA) 分析可见两者具有一定分离趋势(图 3B)。进一步通过倍数差异(fold change, FC) 值(FC > 1.2或FC < 0.8) 和t检验(P < 0.05) 筛选出两组的9个差异成分(表 4)。由热图可以看出, 春秋与夏季采收的北柴胡确定存在差异, clinoposaponin Ⅻ和柴胡次皂苷D在春秋采收的北柴胡样本中含量较高, 而丙二酰基-乙酰基-羟基-柴胡皂苷a、3″-O-乙酰基-柴胡皂苷a、6″-O-乙酰基-柴胡皂苷a、丙二酰基-柴胡皂苷a、丙二酰基-柴胡皂苷d、乙酰基-柴胡皂苷f、乙酰基-柴胡皂苷m等成分在夏季采收的北柴胡样本中较高(图 5)。
进一步计算25种柴胡皂苷成分的相关性, 如图 6所示, 红色越深表示正相关性越强, 蓝色越深则表示负相关性越强。相关系数的绝对值在0.8~1.0表示极强相关, 0.6~0.8表示强相关, 0.4~0.6表示中等程度相关, 0.2~0.4表示弱相关, 0~0.2表示极弱相关或无相关。25种柴胡皂苷之间呈现262组相关(P < 0.05), 其中238个正相关, 24个负相关。可见, 25种皂苷之间正相关的数量远大于负相关的数量。
柴胡皂苷a和柴胡皂苷d是中国药典规定的质量控制指标成分, 柴胡皂苷a与柴胡皂苷d之间呈现极强的正相关(r = 0.84)。此外, 柴胡皂苷a与羟基柴胡皂苷a (r = 0.88)、柴胡皂苷b1 (r = 0.82) 呈极强正相关, 与羟基柴胡皂苷d (r = 0.73)、2″-O-乙酰基-柴胡皂苷a (r = 0.71) 呈强正相关, 与柴胡皂苷b3/柴胡皂苷b4 (r = 0.56)、丙二酰基-柴胡皂苷f (r = 0.54)、柴胡苷Ⅳ (r = 0.52)、chinoposaponin XVIII (r = 0.46)、柴胡皂苷f (r = 0.45) 呈现中等程度正相关; 柴胡皂苷d与柴胡皂苷b1 (r = 0.96) 呈极强正相关, 与羟基柴胡皂苷a (r = 0.78)、羟基柴胡皂苷d (r = 0.75)、柴胡苷Ⅳ (r = 0.76)、2″-O-乙酰基-柴胡皂苷a (r = 0.69)、chinoposaponin XVIII (r = 0.68)、柴胡皂苷b3/柴胡皂苷b4 (r = 0.6) 呈强正相关, 与丙二酰基-柴胡皂苷f (r = 0.59)、3″-O-乙酰基-柴胡皂苷a (r = 0.54)、6″-O-乙酰基-柴胡皂苷a (r = 0.5)、柴胡苷X (r = 0.43) 等呈现中等程度正相关。因此, 按照《中国药典》 2020年版方法, 测定柴胡皂苷a和柴胡皂苷d的含量也可以间接反映羟基柴胡皂苷a、羟基柴胡皂苷d、柴胡皂苷b1、2″-O-乙酰基-柴胡皂苷a、柴胡皂苷b3/柴胡皂苷b4、chinoposaponin XVIII、柴胡苷Ⅳ、丙二酰基-柴胡皂苷f等成分的含量。
通过(75分位数-25分位数)/中位数、(最大值-最小值)/中位数、标准偏差/平均值三种方法计算25种成分的变异系数V1、V2、V3, 每种算法变异系数最大的前五个成分如表 5所示, 其交集成分为: clinoposaponin Ⅻ、柴胡次皂苷D、柴胡次皂苷A、丙二酰基-柴胡皂苷a, 说明这些成分的含量在不同样本中变异波动较大。
总结与讨论
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皂苷是柴胡的重要活性成分, 本研究建立了基于sMRM的柴胡皂苷拟靶向代谢组学测定方法, 可同时测定25种柴胡皂苷的相对含量。方法学验证表明, 所建立的方法具有较好的日间、日内精密度, 良好的线性、重复性和稳定性, 表明该方法稳定可靠, 可为柴胡皂苷类成分的全面系统检测分析提供依据。
采用所建立的方法, 对37批山西省内外采集的北柴胡样本中的皂苷类成分进行相对定量, 并比较了不同产地北柴胡中皂苷类成分的差异, 结果显示不同产地北柴胡中皂苷类成分组成和总量均没有明显差别。但是传统的春秋采收期与夏季采收的柴胡在皂苷类成分上存在一定差异, 部分皂苷类成分在夏季采收的柴胡中含量高于春秋采收的柴胡。相关性分析显示, 柴胡皂苷a和柴胡皂苷d与羟基柴胡皂苷a、羟基柴胡皂苷d等皂苷类具有正相关, 可以间接反映它们的含量。变异系数分析表明, clinoposaponin Ⅻ、柴胡次皂苷D等4种成分在37批柴胡样本中含量变异较大, 可能影响柴胡质量的均一性。
有研究显示不同产地北柴胡化学一致性较高, 药材质量均一性较好[18], 遗传因素对柴胡代谢物的影响大于产地环境因素[19]。叶耀辉等[20]也发现不同产地北柴胡的指纹图谱相似度极高, 北柴胡药材质量较为稳定。说明北柴胡生长适应力强, 受产地环境因素影响小, 适合广泛种植, 与本研究结果一致。《本草图经》中记载: 柴胡, 二月八月采根[21]。自古以来, 柴胡通常在春秋两季采收。文献[22, 23]也报道柴胡皂苷a和柴胡皂苷d在5月、8月含量最高。现代研究与古籍记载的传统采收经验有一定差异, 但最佳采收期的考量应该综合考虑柴胡中各种成分的含量变化规律, 另外, 是否皂苷成分含量越高就越适宜采收, 还需要从功效、毒性等角度进一步分析。
作者贡献: 白雪负责完成实验、数据处理及文章撰写; 郭雅璇、许爱玲参与部分实验工作; 秦雪梅参与柴胡样品品种的鉴定; 高晓霞、王晓民参与实验样本收集和实验指导; 李震宇负责整个研究工作的设计和指导, 以及对稿件的修改。
利益冲突: 本文的研究无任何利益冲突。
基金
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  • 国家重点研发计划项目(2019YFC1710805)
  • 国家现代农业产业技术体系资助(CARS-21)
  • 山药柴胡种质资源利用及规范生产关键技术研究(YCKJ-2021017)
  • 运城道地药材柴胡高质量栽培关键技术研究(2021YNGG05)
  • 山西省现代农业产业技术体系建设专项资金资助(2021-11)
文献
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2023年第58卷第7期
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doi: 10.16438/j.0513-4870.2022-1376
  • 接收时间：2022-12-16
  • 首发时间：2025-11-21
  • 出版时间：2023-07-12
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  • 收稿日期：2022-12-16
  • 修回日期：2023-04-03
基金
国家重点研发计划项目(2019YFC1710805)
国家现代农业产业技术体系资助(CARS-21)
山药柴胡种质资源利用及规范生产关键技术研究(YCKJ-2021017)
运城道地药材柴胡高质量栽培关键技术研究(2021YNGG05)
山西省现代农业产业技术体系建设专项资金资助(2021-11)
作者信息
    1.山西大学中医药现代研究中心, 山西 太原 030006
    2.山西农业大学棉花研究所, 山西 运城 044000

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*王晓民, Tel: 86-359-2121243, E-mail: ;
李震宇, Tel: 86-351-7011202, E-mail:
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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