Article(id=1198652610627596945, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1198652605778985059, articleNumber=null, orderNo=null, doi=10.16438/j.0513-4870.2023-0525, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1682611200000, receivedDateStr=2023-04-28, revisedDate=1688572800000, revisedDateStr=2023-07-06, acceptedDate=null, acceptedDateStr=null, onlineDate=1763710652262, onlineDateStr=2025-11-21, pubDate=1691769600000, pubDateStr=2023-08-12, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1763710652262, onlineIssueDateStr=2025-11-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1763710652262, creator=13701087609, updateTime=1763710652262, updator=13701087609, issue=Issue{id=1198652605778985059, tenantId=1146029695717560320, journalId=1189982191388893191, year='2023', volume='58', issue='8', pageStart='0', pageEnd='2540', issueExtLink='null', onlineDate='null', pubDate='1691769600000', pubDateStr='2023-08-12', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1763710651106, creator='13701087609', updateTime=1763710739504, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1198652976601596347, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1198652605778985059, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1198652976601596348, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1198652605778985059, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2454, endPage=2460, ext={EN=ArticleExt(id=1198652611109941913, articleId=1198652610627596945, tenantId=1146029695717560320, journalId=1189982191388893191, language=EN, title=Analysis of eight Murraya species by flow injection-Qtrap-mass spectrometry, columnId=null, journalTitle=Acta Pharmaceutica Sinica, columnName=null, runingTitle=null, highlight=null, articleAbstract=

In this study, the flow injection (FI) technology combined with the unique step wise multiple ions monitoring scanning (step-wise MIM) mode of Qtrap-MS was first established for the identification and discrimination of eight Murraya species. It only takes 5 min for each sample to detect approximate 600 compounds. The characteristic MS chromatograms of eight Murraya plants were analyzed by Analyst and SIMCA-P. The results of PCA showed that sect. Murraya and sect. Bergera were clearly divided into two categories, suggesting that there is difference in the chemical compositions between these two groups. Further detail analysis of the MS data could realize the preliminary structure elucidation of the component types contained in different plants. The main components in M. exotica and M. alata are coumarins, and polymethoxyflavones are rich in M. paniculata, while carbazole alkaloids are the major ones in sect. Bergera plants. The results are consistent with our previous comprehensive analysis of the chemical components of Murraya species. In conclusion, our research confirmed that FI-Qtrap-MS technology can be used for rapid identification and differentiation of similar plant species, providing reference for chemical taxonomy and a new method for the quality evaluation of medicinal materials.

, authors=null, authorsList=Hai-zhen LIANG, Shuo YUAN, Peng GAO, Peng-fei TU, Yong JIANG, authorCompany=null, correspAuthors=Yong JIANG, 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, fund=null), CN=ArticleExt(id=1198652614771569399, articleId=1198652610627596945, tenantId=1146029695717560320, journalId=1189982191388893191, language=CN, title=基于流动注射-Qtrap质谱技术的九里香属植物的鉴别分析, columnId=1190335348896011050, journalTitle=药学学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=

本文采用流动注射(flow injection, FI) 技术结合Qtrap质谱(Qtrap-MS) 特有的分步多离子监测扫描方式(step-wise multiple ion monitoring, step-wise MIM), 首次对8种九里香属Murraya植物进行了较为快速的鉴别区分。每个样品分析仅需要5 min, 便可检测约600个化合物。将质谱信息经过处理后, 采用多元统计软件进行分析, 发现九里香组sect. Murraya和棕茎组sect. Bergera植物各自聚集, 分类明显, 表明两组植物间的化学成分存在差异。进一步对质谱数据进行分析, 发现其能直观反映不同植物中的成分类别: 其中九里香和翼叶九里香主要含有香豆素类成分, 千里香富含多甲氧基黄酮, 棕茎组植物则主要含有咔唑生物碱类成分, 与作者之前对该属植物的系统化学成分分析结果一致。总之, 本研究证实FI-Qtrap-MS技术可用于药用植物的快速鉴别, 实现同属植物的快速区分, 为其化学分类学提供参考, 同时该技术也为中药材的质量评价提供新方法。

, authors=

#共同第一作者.

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*姜勇, Tel / Fax: 86-10-82802719, E-mail:
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A: The score chart; B: The volcano plot

, figureFileSmall=RalfPRwyQWxBZLs/OWPjuQ==, figureFileBig=EKOdRj0pLQuPWdrgHr2E9Q==, tableContent=null), ArticleFig(id=1198960117975707915, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198652610627596945, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
No. Habitat No. Habitat
ME-1 Pingyuan County, Meizhou, Guangdong MA-3 Lingshui Monkey Island, Hainan
ME-2 Guangdong Pingyuan Nantai Pharmaceutical Co., Ltd MA-4 Lingshui Yingzhou Chiling, Hainan
ME-3 Boluo County, Huizhou, Guangdong MA-5 Lingshui Guangpo Fuliwan, Hainan
ME-4 Longhu Mountain, Guangxi MA-6 Ledong Jianfengling, Hainan
ME-5 Fuhe River, Banba Township, Fangcheng District, Guangxi MA-7 Ledong Jianfengling Chenlonggou, Hainan
ME-6 Siding Town, Rong'an County, Duzhou, Guangxi MA-8 Back slope of Dongfangxin Street Border Police Station, Hainan
ME-7 Beihuan Avenue, Shenzhen, Guangdong MA-9 Sanya-1, Hainan
ME-8 Luzhai-1, Guangxi, MA-10 Sanya-2, Hainan
ME-9 Luzhai-2, Guangxi MM-1 Sanya Yalong Bay, Hainan
ME-10 Hengpo Town, Wuhua, Guangdong (Wild) MM-2 Lingshui Monkey Island, Hainan
MP-1 Dongxia Tun, Layou Village, Nandan County, Guangxi MM-3 Lingshui Guangpo perfume Bay, Hainan
MP-2 Longshan Village, Lianshan Town, Fuchuan County, Guangxi MM-4 Back slope of Dongfangxin Street Border Police Station, Hainan
MP-3 Xiushui Village, Chaodong Town, Guangxi MM-5 Haikou, Hainan
MP-4 Chashan Village, Chaodong Town, Guangxi MT-1 Jingxi, Guangxi
MP-5 Shilong Village, Chengbei Town, Guangxi MT-2 Guangxi-1
MP-6 Longshan Village, Yangtou Town, Zhongshan County, Guangxi MT-3 Guangxi-2
MP-7 Shiba Gongling, Zhongshan County, Guangxi MKw-1 Guangxi-1
MP-8 Laide Village, Gong'an Town, Zhongshan County, Guangxi MKw-2 Southtern of China
MP-9 Baixia Village, Gong'an Town, Zhongshan County, Guangxi MKw-3 Guangxi
MP-10 Hetang Village, Gong'an Town, Zhongshan County, Guangxi MEu-1 Longzhou, Guangxi
MA-1 Longhai Village, Haitang Bay, Sanya, Hainan MEu-2 Sicheng Town, Lingyun County, Guangxi
MA-2 Sanya Big and Small Cave, Sanya, Hainan MKo-1 South China Botanical Garden, Guangdong
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Sample information of 44 batches of Murraya species. ME: M. exotica; MP: M. paniculata; MA: M. alata; MM: M. microphylla; MT: M. tetramera; MKw: M. kwangsiensis; MEu: M. euchrestifolia; MKo: M. koenigii

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No. Habitat No. Habitat
ME-1 Pingyuan County, Meizhou, Guangdong MA-3 Lingshui Monkey Island, Hainan
ME-2 Guangdong Pingyuan Nantai Pharmaceutical Co., Ltd MA-4 Lingshui Yingzhou Chiling, Hainan
ME-3 Boluo County, Huizhou, Guangdong MA-5 Lingshui Guangpo Fuliwan, Hainan
ME-4 Longhu Mountain, Guangxi MA-6 Ledong Jianfengling, Hainan
ME-5 Fuhe River, Banba Township, Fangcheng District, Guangxi MA-7 Ledong Jianfengling Chenlonggou, Hainan
ME-6 Siding Town, Rong'an County, Duzhou, Guangxi MA-8 Back slope of Dongfangxin Street Border Police Station, Hainan
ME-7 Beihuan Avenue, Shenzhen, Guangdong MA-9 Sanya-1, Hainan
ME-8 Luzhai-1, Guangxi, MA-10 Sanya-2, Hainan
ME-9 Luzhai-2, Guangxi MM-1 Sanya Yalong Bay, Hainan
ME-10 Hengpo Town, Wuhua, Guangdong (Wild) MM-2 Lingshui Monkey Island, Hainan
MP-1 Dongxia Tun, Layou Village, Nandan County, Guangxi MM-3 Lingshui Guangpo perfume Bay, Hainan
MP-2 Longshan Village, Lianshan Town, Fuchuan County, Guangxi MM-4 Back slope of Dongfangxin Street Border Police Station, Hainan
MP-3 Xiushui Village, Chaodong Town, Guangxi MM-5 Haikou, Hainan
MP-4 Chashan Village, Chaodong Town, Guangxi MT-1 Jingxi, Guangxi
MP-5 Shilong Village, Chengbei Town, Guangxi MT-2 Guangxi-1
MP-6 Longshan Village, Yangtou Town, Zhongshan County, Guangxi MT-3 Guangxi-2
MP-7 Shiba Gongling, Zhongshan County, Guangxi MKw-1 Guangxi-1
MP-8 Laide Village, Gong'an Town, Zhongshan County, Guangxi MKw-2 Southtern of China
MP-9 Baixia Village, Gong'an Town, Zhongshan County, Guangxi MKw-3 Guangxi
MP-10 Hetang Village, Gong'an Town, Zhongshan County, Guangxi MEu-1 Longzhou, Guangxi
MA-1 Longhai Village, Haitang Bay, Sanya, Hainan MEu-2 Sicheng Town, Lingyun County, Guangxi
MA-2 Sanya Big and Small Cave, Sanya, Hainan MKo-1 South China Botanical Garden, Guangdong
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基于流动注射-Qtrap质谱技术的九里香属植物的鉴别分析
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梁海珍 # , 袁硕 # , 高鹏 , 屠鹏飞 , 姜勇 *
药学学报 | 研究论文 2023,58(8): 2454-2460
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药学学报 |研究论文 2023 , 58 (8) : 2454 -2460
基于流动注射-Qtrap质谱技术的九里香属植物的鉴别分析
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梁海珍#, 袁硕#, 高鹏, 屠鹏飞, 姜勇*
作者信息
  • 北京大学药学院, 天然药物及仿生药物国家重点实验室, 北京 100191
通讯作者:
*姜勇, Tel / Fax: 86-10-82802719, E-mail:
Analysis of eight Murraya species by flow injection-Qtrap-mass spectrometry
Hai-zhen LIANG, Shuo YUAN, Peng GAO, Peng-fei TU, Yong JIANG*
Affiliations
  • State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing 100191, China
出版时间: 2023-08-12 doi: 10.16438/j.0513-4870.2023-0525
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本文采用流动注射(flow injection, FI) 技术结合Qtrap质谱(Qtrap-MS) 特有的分步多离子监测扫描方式(step-wise multiple ion monitoring, step-wise MIM), 首次对8种九里香属Murraya植物进行了较为快速的鉴别区分。每个样品分析仅需要5 min, 便可检测约600个化合物。将质谱信息经过处理后, 采用多元统计软件进行分析, 发现九里香组sect. Murraya和棕茎组sect. Bergera植物各自聚集, 分类明显, 表明两组植物间的化学成分存在差异。进一步对质谱数据进行分析, 发现其能直观反映不同植物中的成分类别: 其中九里香和翼叶九里香主要含有香豆素类成分, 千里香富含多甲氧基黄酮, 棕茎组植物则主要含有咔唑生物碱类成分, 与作者之前对该属植物的系统化学成分分析结果一致。总之, 本研究证实FI-Qtrap-MS技术可用于药用植物的快速鉴别, 实现同属植物的快速区分, 为其化学分类学提供参考, 同时该技术也为中药材的质量评价提供新方法。

流动注射  /  Qtrap-MS  /  多离子监测  /  九里香属  /  植物鉴别  /  质量评价

In this study, the flow injection (FI) technology combined with the unique step wise multiple ions monitoring scanning (step-wise MIM) mode of Qtrap-MS was first established for the identification and discrimination of eight Murraya species. It only takes 5 min for each sample to detect approximate 600 compounds. The characteristic MS chromatograms of eight Murraya plants were analyzed by Analyst and SIMCA-P. The results of PCA showed that sect. Murraya and sect. Bergera were clearly divided into two categories, suggesting that there is difference in the chemical compositions between these two groups. Further detail analysis of the MS data could realize the preliminary structure elucidation of the component types contained in different plants. The main components in M. exotica and M. alata are coumarins, and polymethoxyflavones are rich in M. paniculata, while carbazole alkaloids are the major ones in sect. Bergera plants. The results are consistent with our previous comprehensive analysis of the chemical components of Murraya species. In conclusion, our research confirmed that FI-Qtrap-MS technology can be used for rapid identification and differentiation of similar plant species, providing reference for chemical taxonomy and a new method for the quality evaluation of medicinal materials.

flow injection  /  Qtrap-MS  /  multiple ions monitoring  /  Murraya genus  /  plant identification  /  quality evaluation
梁海珍, 袁硕, 高鹏, 屠鹏飞, 姜勇. 基于流动注射-Qtrap质谱技术的九里香属植物的鉴别分析. 药学学报, 2023 , 58 (8) : 2454 -2460 . DOI: 10.16438/j.0513-4870.2023-0525
Hai-zhen LIANG, Shuo YUAN, Peng GAO, Peng-fei TU, Yong JIANG. Analysis of eight Murraya species by flow injection-Qtrap-mass spectrometry[J]. Acta Pharmaceutica Sinica, 2023 , 58 (8) : 2454 -2460 . DOI: 10.16438/j.0513-4870.2023-0525
九里香属Murraya植物属于芸香科Rutaceae, 主要分布于亚洲热带及亚热带地区, 全世界约有14种及2变种, 我国有9种及1变种, 主要分布于广东、广西、海南等地。该属植物在我国和东南亚地区被广泛药用, 主要用于治疗头痛、牙痛、胃痛、风湿骨痛、跌打肿痛等疾病[1]。其中九里香Murraya exotica和千里香Murraya paniculata为中药九里香药材的法定基原植物, 收载于《中华人民共和国药典》 (2020版), 具有行气止痛, 活血散瘀之功效[2]
植物学家根据植物形态分类学和化学分类学将九里香属植物分为两个组: 九里香组Sect. Murraya和棕茎组Sect. Bergera。九里香组包括九里香M. exotica (ME)、千里香M. paniculata (MP) 和翼叶九里香M. alata (MA)。棕茎组包括小叶九里香M. microphylla (MM)、广西九里香M. kwangsiensis (MKw)、四数九里香M. tetramera (MT)、豆叶九里香M. euchrestifolia (MEu)、调料九里香M. koenigii (MKo)、兰屿九里香M. crenulata和大叶九里香M. kwangsiensis var.macrophylla[3]。研究表明, 两组植物所含的化学成分类型不同, 九里香组植物主要含有8-异戊烯基香豆素和多甲氧基黄酮等, 棕茎组植物则富含咔唑生物碱类化合物[4-10]。然而, 目前关于该属的研究主要集中于各种化学成分的分离与结构鉴定, 关于该属植物化学成分的系统分析未见报道。另外, 由于同属植物外观的相似性, 使得根据形态区分九里香组与棕茎组植物, 以及同一组内的植物, 如九里香和千里香, 存在一定难度, 因此, 寻找简便、准确、高效的鉴别和区分方法尤为重要。
流动注射-质谱技术(flow injection-mass spectrometry, FI-MS) 是指样品无须经过色谱分离, 直接进样到质谱进行分析的方法。短时间内即可得到样品的总离子流图和质谱信息, 近年来逐渐被用于快速代谢组学研究及指纹图谱分析[11, 12]。FI-MS技术虽然具有高通量和节省时间的优势, 但由于没有液相色谱的分离功能, 且经常发生质量偏移, 故对其结果的分析非常困难[13]。为了解决FI-MS存在的问题, 以九里香属植物为例, 将FI-MS技术与Qtrap质谱特有的分步多离子检测(step wise multiple ion monitoring, step-wise MIM) 方式相结合, 对所有的离子信息进行检测, 通过固定离子对的数目, 获得不同样品包含相同数目变量的数据文件, 以此实现对药用植物的快速鉴别和相似植物的快速区分。
AB SCIEX Qtrap 4500三重四极杆线性离子阱复合型串联质谱仪: 配有Turbo V ESI离子源(美国AB SCIEX公司); KQ2200DB型数控超声波清洗器(昆山市超声仪器有限公司)。
色谱甲醇为液质级别(美国Thermo Fisher公司, 批号: 219089); 超纯水(美国Waston公司, 批号: 1044725); 标准品(本课题组自制)。
44批九里香属植物从广东、广西及海南等地采集, 经北京大学药学院屠鹏飞教授鉴定, 分别为10批九里香Murraya exotica L.、10批千里香Murraya paniculata (L.) Jack、10批翼叶九里香Murraya alata Drake、5批小叶九里香Murraya microphylla (Merr. et Chun) Swingle、3批广西九里香Murraya kwangsiensis (Huang) Huang、3批四数九里香Murraya tetramera Huang、2批豆叶九里香Murraya euchrestifolia Hayata及1批调料九里香Murraya koenigii (L.) Spreng.的干燥叶和带叶嫩枝。具体样品信息见表 1
将干燥的植物样品粉碎, 过40目筛后, 置密封袋中, 干燥、避光保存。取不同基原、不同批次九里香属药用植物粉末各0.1 g, 混合均匀, 获得包含不同基原、不同批次样品所有化学成分信息的药材对照物质(reference substance, RS), 置密封袋, 干燥、避光保存。
称取不同批次药材的嫩枝叶干燥粉末及药材对照物质粉末各0.1 g, 置于250 mL的具塞三角瓶中, 分别加入80%甲醇100 mL, 摇匀, 称定, 超声(功率500 W, 频率25 kHz) 提取30 min后, 放冷, 再称定重量, 用80%甲醇补足减失的重量, 摇匀; 10 000 r·min-1离心10 min, 取上清液过微孔滤膜(0.22 μm), 取续滤液, 即得。
Waters BEH C18保护柱(30 mm × 2.1 mm, 1.7 μm, 美国Waters公司); 流动相: 乙腈-水溶液(80∶20) 等度洗脱; 采用改变流速的方法来对样品进行洗脱, 洗脱方法: 0~0.25 min, 0.20 mL·min-1; 0.25~0.26 min, 0.20~0.01 mL·min-1; 0.26~3.20 min, 0.01 mL·min-1; 3.20~3.21 min, 0.01~0.50 mL·min-1; 3.21~4.70 min, 0.50 mL·min-1; 4.70~4.71 min, 0.50~0.20 mL·min-1; 4.71~5.00 min, 0.20 mL·min-1; 柱温: 30 ℃; 进样量: 3 μL。
离子源使用ESI, 正离子模式。质谱ESI离子源参数: 气帘气(CUR): 35.0 psi; 碰撞气(CAD): high; 离子喷雾电压(IS): 5 500 V; GS1: 55 psi; GS2: 55 psi; 温度: 550 ℃。采用step-wise MIM模式对化合物分子量较为集中的m/z 99~674 Da进行扫描, 1 Da为一个步长, 如m/z 99、100、101, 共设576对离子对; 每个离子对的去簇电压(DP) 设为50 V, 碰撞能(CE) 设为5 eV; 扫描每对离子对的驻留时间为50 ms, 共采集10个循环。
用Analyst 1.6.2 (美国SCIEX公司) 将所有离子对扣除背景后的响应值导出, 生成矩阵, 用SIMCA-P进行多元统计分析。
因九里香属植物含有香豆素、多甲氧基黄酮和生物碱类化合物, 其分子量范围集中于m/z 99~674 Da[8], 分子离子峰既有奇数又有偶数, 所以针对MIM扫描模式的离子对, 以1 Da为一个步长, 共设置了578个离子对。同时, 根据文献调研和实验室前期基础[14, 15], 发现这三类主成分均在质谱正离子模式下具有更好的响应。因此, 选择在正离子模式展开研究。
本研究中, 因收集九里香属样品较多, 为了能够获得该属不同基原、不同批次植物所有的化学成分信息, 将不同种的药材各取等量混合均匀, 从而得到包含所有种信息的药材混标, 并以此为研究对象, 进行了FI-MS条件的优化。为了减少样品提取物直接进入离子源所带来的污染, 选取了C18保护柱来滤除杂质。样品经高效液相色谱自动进样系统吸取, 只通过保护柱而不经色谱柱分离直接进入质谱检测器检测。因液相系统到质谱检测器间有一段连接管路, 流速过小时, 分析时间内会较长; 又因质谱扫描的单个cycle时间较长, 流速过大时, 化合物很快被冲出, 检测到的化学成分信息不全。因此选取了变流速法来进行分析, 经过优化, 从而使样品可以在合适的时间进入质谱分析(图 1)。
在本研究中, 共对8种九里香属植物进行了FI-Qtrap-MS数据采集。为了获得其完整的质谱信息, 选取了1.064、1.595、2.127、2.659 min四个离子对响应最高的时间点, 通过将这四个时间点的MS图信号进行平均获得了8种植物在正离子模式下的特征MS图(图 2)。
在九里香样品中, 响应最高的5个离子依次为m/z 336、261、231、296、243, 通过与之前的研究比对, 发现其均与九里香中香豆素类化合物的离子碎片及加铵峰一致[8]; 在千里香样品中, 响应最高的5个离子依次为m/z 374、404、375、359、343, 这与千里香文献[8, 16]报道中的部分多甲氧基黄酮的分子离子峰一致, 偶数离子374推测可能是香豆素类化合物加铵峰, 404可能是m/z 403的同位素峰; 在翼叶九里香样品中, 响应最高的5个离子依次为m/z 336、231、294、291、259, 均与翼叶九里香中香豆素类化合物的离子碎片及加铵峰一致[7]。对于棕茎组的5种植物来说, MS图中响应最高的5个离子基本均为m/z 168、151、150、131、130、166、169等不同组合, 其中m/z 168与咔唑生物碱母核的加氢峰一致[17] (图 3)。
m/z 99~674共578个离子对的离子强度为变量, 对8种九里香属植物共44批样本进行主成分(PCA) 分析。矩阵经UV (unit variance scaling) 标准化处理后进行主成分析。PCA模型R2X = 0.802, Q2 = 0.709, 说明该模型在解释以及预测度上均有较好的可信度。由PCA得分图(图 4) 可以看出, 九里香组和棕茎组均有各自的聚集区域, 表明两个组植物的化学成分的确存在较大差异。值得注意的是, 千里香单独聚集为一组, 表明其化学成分与其他同组物种区分较大, 与课题组前期LC/MS定性研究结果一致: 千里香主要成分为多甲氧基黄酮类, 九里香与翼叶九里香主要为香豆素类[8]
根据课题组前期对中药九里香两基原的药效对比可以发现, 九里香与千里香在行气止痛、活血散瘀的传统功效上具有药效一致性[18], 为千里香与九里香归为同一组提供了理论依据。利用PLS-DA分析发现, 九里香组与棕茎组分布于两个象限, 区分明显(图 5)。利用t检验分析发现, 在所检测的578个离子对中差异离子对数目(P < 0.05) 为499个。对两组的差异成分进行火山图分析发现, 在九里香组含量较高的差异离子为m/z 361、420、259、231等, 与前期研究报道的香豆素类及多甲氧基黄酮类化合物的加氢峰或加铵峰质量数符合[8]。在棕茎组较高的差异离子为m/z 137、144、168等, 其中m/z 168与前期报道的咔唑生物碱母核的加氢峰一致[17]
对于九里香组植物来说, 九里香和翼叶九里香中富含香豆素类成分, 因此两者样本虽基本分离, 但部分产地聚集到一起, 而千里香因主要成分为多甲氧基黄酮, 因此单独聚为一类。对于棕茎组的植物来说, 各个种的植物均有各自的聚集区域, 表明这几种植物的化学成分虽有一定的差异, 但整体轮廓比较相似, 分离趋势不甚明显。
快速识别和鉴定药用植物和中药材对于开展中药材采收、加工和生产, 以及对其质量评价与控制是非常重要的。研究表明, 九里香属植物具有重要的药用价值, 如著名的中成药三九胃泰就是以九里香为主要原料生产的。九里香属分布于亚洲的热带与亚热带地区, 以及澳大利亚东北部。我国有9种1变种, 主要分布于南方的各个省[19]。九里香属植物根据茎皮的颜色、花的大小及所含成分, 分为九里香组和棕茎组。其中九里香组的枝条灰白色, 花较大, 果朱红色, 种皮有绵质毛, 植株含8-异戊烯基类香豆素类成分, 并且根部含有月橘烯碱; 而棕茎组的枝条暗黑褐色, 花较小, 果暗蓝黑, 种皮无毛, 根部主要含咔唑类生物碱。由此可见, 九里香组和棕茎组所含成分存在较大差异。不同的化学成分可能会对药效产生较大影响[20], 因此对九里香属植物进行快速鉴别及高效区分对于该属植物的开发应用十分必要。
目前关于该属的研究主要集中于植物的化学成分分离, 本团队通过对九里香属植物的化学成分的研究, 分离得到了大量结构新颖的香豆素和咔唑生物碱类化合物[17, 21], 但迄今关于该属植物系统的化学成分分析和属内植物间的横向比较缺少报道。本研究对我国境内能够收集到的8种九里香属植物, 采用FI-Qtrap-MS进行了快速分析, 在5 min内即可对约600个离子对进行全面检测。结合多元统计分析, 如PCA、PLS-DA实现了对九里香组和棕茎组植物的快速区分。发现两组植物间的差异离子对约占总检测离子对数目的86%, 表明两组植物化学成分存在较大差异, 主要的差异离子对为香豆素及咔唑生物碱类成分, 这些成分可以作为快速区分两组植物的标志物。
此外, 九里香组的三种植物之间化学成分也有一定的区别, 其中千里香主要含有多甲氧基黄酮类化合物, 而九里香与翼叶九里香则以香豆素类为主。已有研究发现九里香与千里香虽然化学成分上有较大的差异, 但在多种药效模型上具有一致性[18, 22]。棕茎组植物聚为一类, 表明其化学成分相似度较高, 且主要成分均为咔唑生物碱类, 这类化合物具有抗肿瘤、抗菌、抗疟等多方面的良好活性[15, 23]。通过本研究发现, 棕茎组植物含有丰富的咔唑生物碱, 值得开展进一步的分离及活性评价工作。
FI-MS技术一般是将样品放在注射器中, 用蠕动泵将样品连续并恒定地流入离子源喷口, 但是由于植物样本成分复杂且直接进样往往消耗样品量较大, 因此极易污染离子源。本研究利用预保护柱来滤除杂质, 选择变流速法调整分析时间, 很好地解决了上述问题。此外, 由于FI-MS技术没有LC的在线分离性能, 因此不能为任何离子信息提供数据对比的指标(如保留时间), 且在不同时间的分析中常发生质量偏移[24]。作者将FI-MS与Qtrap质谱特有的step wise MIM扫描方式相结合, 实现对扫描范围内所有离子信息进行检测。通过固定离子对的数目, 从而可以获得不同样品的包含相同数目变量的数据文件。通过该方法, 成功实现了对九里香属植物化学成分的快速分析, 并结合多元统计分析方法, 实现不同九里香属植物的快速区分。相关分类结果的合理性也验证了本研究方法的可信度。
本研究为九里香属植物的快速分析提供了新的技术体系, 证实了FI-MS技术可用于药用植物的快速鉴别与区分, 为中药质量评价提供了新的思路和方法。但是, FI-MS技术因没有在线分离性能且缺少二级质谱碎片, 结构鉴定困难, 仍需要通过其他技术手段来进行深入分析[25, 26]。另外, 本次研究样品中个别品种, 如豆叶九里香和调料九里香的批次较少, 后续研究可以继续进行相关品种的采集, 以扩大样品数目, 开展进一步评价。
作者贡献: 梁海珍负责实验设计及操作、数据整理; 袁硕负责多元统计分析、文章撰写及修改; 高鹏负责文章部分图片及文字内容修改; 屠鹏飞负责实验材料收集与鉴定; 姜勇负责课题资金、指导实验、审阅文章。
利益冲突: 无任何利益冲突。
  • 国家自然科学基金面上项目(81973199)
  • 国家自然科学基金面上项目(81773864)
  • 国家自然科学基金面上项目(81473106)
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2023年第58卷第8期
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doi: 10.16438/j.0513-4870.2023-0525
  • 接收时间:2023-04-28
  • 首发时间:2025-11-21
  • 出版时间:2023-08-12
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  • 收稿日期:2023-04-28
  • 修回日期:2023-07-06
基金
国家自然科学基金面上项目(81973199)
国家自然科学基金面上项目(81773864)
国家自然科学基金面上项目(81473106)
作者信息
    北京大学药学院, 天然药物及仿生药物国家重点实验室, 北京 100191

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*姜勇, Tel / Fax: 86-10-82802719, E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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