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Article(id=1198628675659854182, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1198628666650493481, articleNumber=null, orderNo=null, doi=10.16438/j.0513-4870.2022-1269, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1668441600000, receivedDateStr=2022-11-15, revisedDate=1675440000000, revisedDateStr=2023-02-04, acceptedDate=null, acceptedDateStr=null, onlineDate=1763704945720, onlineDateStr=2025-11-21, pubDate=1689091200000, pubDateStr=2023-07-12, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1763704945720, onlineIssueDateStr=2025-11-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1763704945720, creator=13701087609, updateTime=1763704945720, 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=1859, endPage=1866, ext={EN=ArticleExt(id=1198628675932483962, articleId=1198628675659854182, tenantId=1146029695717560320, journalId=1189982191388893191, language=EN, title=Targeted metabolomic analysis of phenylpropanoid metabolites in Astragalus membranaceus var. mongholicus in response to Fusarium solani infection, columnId=1190335348761793317, journalTitle=Acta Pharmaceutica Sinica, columnName=Original Articles, runingTitle=null, highlight=null, articleAbstract=

Root rot severely restricts the sustainable development of Astragalus membranaceus var. mongholicus (AMM) industry. Resistance breeding is an economical and environmentally safe way to manage the disease and its key lies in the obtaining of resistance indicators. This study aimed to quickly and accurately screen the resistance-related (RR) metabolites so as to provide reference for the screening of indicators of AMM breeding for resistance. LC-MS-based targeted metabolomics and real-time quantitative PCR technology were employed, in combination with multivariate statistical analysis, in analyzing the dynamic changes of phenylpropanoid metabolites in AMM in response to root rot pathogen Fusarium solani (FS) infection and identifying the differential metabolites. The LC-MS method established showed high sensitivity; each metabolite had a good linear relationship (R2 ≥ 0.968 9) in the corresponding linear range of the respective standard curve; the recoveries and the relative standard deviations (RSDs) (n = 6) ranged from 70% to 107% and from 1.2% to 9.9%, respectively. Obvious disturbances were observed in the changes of the targeted metabolites in AMM infected by FS. These metabolites, compared with the mock-inoculated (CK) group, showed different up or down regulation with time series. Calycosin-7-O-β-D-glucoside, ononin, calycosin and formononetin were identified as differential metabolites, and they all belong to flavonoids. The first three compounds were significantly negatively correlated (r ≤ -0.97, P < 0.05) with the content of FS in the root of AMM. As potential RR metabolites, they are helpful in obtaining promising resistance indicators for AMM against FS infection.

, correspAuthors=Fen GAO, 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=Zi-qing ZHAO, Hai-qing SONG, Li-mei ZHAO, Zhen-yu LI, Rui-jie WU, Fen GAO), CN=ArticleExt(id=1198628678721696273, articleId=1198628675659854182, tenantId=1146029695717560320, journalId=1189982191388893191, language=CN, title=基于靶向代谢组学分析黄芪苯丙烷代谢物对根腐病菌Fusarium solani侵染的响应, columnId=1190335348896011050, journalTitle=药学学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=

根腐病是制约黄芪产业可持续发展的重要因素。选育抗性品种作为防治病害最为经济有效且安全的措施, 其关键在于抗病性状指标的获得。本研究采用基于LC-MS的靶向代谢组学与实时荧光定量PCR技术, 分析苯丙烷途经代谢物响应根腐病菌腐皮镰刀菌(Fusarium solani, FS) 侵染的动态变化, 结合多元统计分析指认差异代谢物, 以期精准挖掘抗病相关(resistance-related, RR) 代谢物, 为黄芪抗病性状指标的筛选提供依据。研究建立的LC-MS测定方法灵敏度高, 各组分在各自浓度范围内, 线性关系良好(R2 ≥ 0.968 9), 回收率在70%~107%, 相对标准偏差(n = 6) 在1.2%~9.9%。研究发现, FS侵染对目标代谢物变化造成了明显扰动, 使其含量随时间序列与模拟接种组相比呈不同程度的上调或下调, 指认的差异代谢物毛蕊异黄酮葡萄糖苷、芒柄花苷、毛蕊异黄酮和芒柄花素, 都属于黄酮类化合物。前3种化合物与FS在黄芪根中的含量显著负相关(r ≤ -0.97, P < 0.05), 作为潜在RR代谢物, 可为研究获得有实际应用前景的黄芪抗根腐病指标提供参考。

, correspAuthors=高芬, authorNote=null, correspAuthorsNote=
*高芬, E-mail:
, copyrightStatement=版权所有©《药学学报》编辑部2023, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=BqmKBiYGoIFa5uUfhB+a+A==, magXml=cyEfDnuHQwGGzebzKRez4g==, pdfUrl=null, pdf=CcwBbSBlkQ5C40R+TgGrBQ==, pdfFileSize=1944932, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=Had6EYzeUT3J2D97eN46dg==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=7GmYInZKutMiYwmrBdkdJg==, mapNumber=null, authorCompany=null, fund=null, authors=

#共同第一作者.

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A: Calycosin and formononetin; B: Calycosin-7-<i>O</i>-<i>β</i>-<i>D</i>-glucoside and ononin , figureFileSmall=hWsb4PkkrxofBOqzsToraA==, figureFileBig=NEc+aIfNjlebeRFkrJBtNg==, tableContent=null), ArticleFig(id=1198960104709124225, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1198628675659854182, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
Metabolite LOQ/mg·L-1 LOD/mg·L-1 Linear range/mg·L-1 Linear equation R2
Calycosin-7-O-β-D-glucoside 1.18 0.39 119.38-3 820.00 y = 14 086.90x + 97 966.00 0.999 5
Ononin 0.61 0.20 58.75-7 520.00 y = 18 522.00x + 122 915.00 0.998 3
Coumarin 10.77 3.55 31.25-4 000.00 y = 2 612.83x + 2 342.26 0.998 5
Daidzein 9.63 3.18 35.62-2 280.00 y = 2 376.35x + 19 319.20 0.994 8
Calycosin 1.66 0.55 33.75-4 320.00 y = 11 683.60x + 29 788.40 0.998 7
Formononetin 0.24 0.08 42.50-680.00 y = 52 581.00x + 915 438.00 0.981 4
Caffeic acid 13.51 4.46 48.75-6 240.00 y = 2 695.54x + 1 653.38 0.998 6
Ferulic acid 5.05 1.67 32.19-4 120.00 y = 483.20x + 11.09 0.996 3
p-Coumaric acid 22.70 7.49 25.00-3 200.00 y = 1 999.03x + 5 668.22 0.997 4
Naringenin 0.29 0.09 35.06-3 780.00 y = 10 707.00x + 18 013.70 0.997 3
Kaempferol 6.19 2.04 31.88-2 040.00 y = 521.00x - 1 887.59 0.987 1
Quercetin 139.86 46.15 125.00-1 000.00 y = 609.02x - 63 430.00 0.968 9
Liquiritigenin 0.73 0.24 41.25-2 640.00 y = 8 351.95x - 1 344.83 0.997 3
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The detection limits, quantification limits and standard curves of metabolites to be tested

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Metabolite LOQ/mg·L-1 LOD/mg·L-1 Linear range/mg·L-1 Linear equation R2
Calycosin-7-O-β-D-glucoside 1.18 0.39 119.38-3 820.00 y = 14 086.90x + 97 966.00 0.999 5
Ononin 0.61 0.20 58.75-7 520.00 y = 18 522.00x + 122 915.00 0.998 3
Coumarin 10.77 3.55 31.25-4 000.00 y = 2 612.83x + 2 342.26 0.998 5
Daidzein 9.63 3.18 35.62-2 280.00 y = 2 376.35x + 19 319.20 0.994 8
Calycosin 1.66 0.55 33.75-4 320.00 y = 11 683.60x + 29 788.40 0.998 7
Formononetin 0.24 0.08 42.50-680.00 y = 52 581.00x + 915 438.00 0.981 4
Caffeic acid 13.51 4.46 48.75-6 240.00 y = 2 695.54x + 1 653.38 0.998 6
Ferulic acid 5.05 1.67 32.19-4 120.00 y = 483.20x + 11.09 0.996 3
p-Coumaric acid 22.70 7.49 25.00-3 200.00 y = 1 999.03x + 5 668.22 0.997 4
Naringenin 0.29 0.09 35.06-3 780.00 y = 10 707.00x + 18 013.70 0.997 3
Kaempferol 6.19 2.04 31.88-2 040.00 y = 521.00x - 1 887.59 0.987 1
Quercetin 139.86 46.15 125.00-1 000.00 y = 609.02x - 63 430.00 0.968 9
Liquiritigenin 0.73 0.24 41.25-2 640.00 y = 8 351.95x - 1 344.83 0.997 3
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Time/dpi Calycosin-7-O-β-D-glucoside Calycosin Ononin Formononetin
VIP FC VIP FC VIP FC VIP FC
0 1.69 1.58 1.93 1.69 1.27 1.35 1.29 1.52
7 2.27 0.11 0.37 0.81 2.13 0.15 0.03 1.03
14 2.01 0.03 1.16 0.31 1.89 0.03 0.95 0.10
21 1.79 0.02 1.36 0.10 1.94 0.02 1.00 0.07
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The differential metabolites of FI and CK group. VIP: Variable importance in projection; FC: Fold change

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Time/dpi Calycosin-7-O-β-D-glucoside Calycosin Ononin Formononetin
VIP FC VIP FC VIP FC VIP FC
0 1.69 1.58 1.93 1.69 1.27 1.35 1.29 1.52
7 2.27 0.11 0.37 0.81 2.13 0.15 0.03 1.03
14 2.01 0.03 1.16 0.31 1.89 0.03 0.95 0.10
21 1.79 0.02 1.36 0.10 1.94 0.02 1.00 0.07
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基于靶向代谢组学分析黄芪苯丙烷代谢物对根腐病菌Fusarium solani侵染的响应
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赵子青 1, # , 宋海清 2, 3, # , 赵丽梅 2, 3 , 李震宇 2, 3, 4 , 武瑞杰 1 , 高芬 5, *
药学学报 | 研究论文 2023,58(7): 1859-1866
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药学学报 | 研究论文 2023, 58(7): 1859-1866
基于靶向代谢组学分析黄芪苯丙烷代谢物对根腐病菌Fusarium solani侵染的响应
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赵子青1, #, 宋海清2, 3, #, 赵丽梅2, 3, 李震宇2, 3, 4, 武瑞杰1, 高芬5, *
作者信息
  • 1.山西锦烁生物科技有限公司, 山西 晋中 030600
  • 2.山西大学中医药现代研究中心, 山西 太原 030006
  • 3.山西大学化学生物学与分子工程教育部重点实验室, 山西 太原 030006
  • 4.地产中药功效物质研究与利用山西省重点实验室, 山西 太原 030006
  • 5.山西大学应用化学研究所, 山西 太原 030006

通讯作者:

*高芬, E-mail:
Targeted metabolomic analysis of phenylpropanoid metabolites in Astragalus membranaceus var. mongholicus in response to Fusarium solani infection
Zi-qing ZHAO1, Hai-qing SONG2, 3, Li-mei ZHAO2, 3, Zhen-yu LI2, 3, 4, Rui-jie WU1, Fen GAO5, *
Affiliations
  • 1. Shanxi Jinshuo Biomedical Technology Co. Ltd., Jinzhong 030600, China
  • 2. Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan 030006, China
  • 3. The Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Shanxi University, Taiyuan 030006, China
  • 4. The Key Laboratory of Effective Substances Research and Utilization in TCM of Shanxi Province, Taiyuan 030006, China
  • 5. Institute of Applied Chemistry, Shanxi University, Taiyuan 030006, China
出版时间: 2023-07-12 doi: 10.16438/j.0513-4870.2022-1269
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摘要
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根腐病是制约黄芪产业可持续发展的重要因素。选育抗性品种作为防治病害最为经济有效且安全的措施, 其关键在于抗病性状指标的获得。本研究采用基于LC-MS的靶向代谢组学与实时荧光定量PCR技术, 分析苯丙烷途经代谢物响应根腐病菌腐皮镰刀菌(Fusarium solani, FS) 侵染的动态变化, 结合多元统计分析指认差异代谢物, 以期精准挖掘抗病相关(resistance-related, RR) 代谢物, 为黄芪抗病性状指标的筛选提供依据。研究建立的LC-MS测定方法灵敏度高, 各组分在各自浓度范围内, 线性关系良好(R2 ≥ 0.968 9), 回收率在70%~107%, 相对标准偏差(n = 6) 在1.2%~9.9%。研究发现, FS侵染对目标代谢物变化造成了明显扰动, 使其含量随时间序列与模拟接种组相比呈不同程度的上调或下调, 指认的差异代谢物毛蕊异黄酮葡萄糖苷、芒柄花苷、毛蕊异黄酮和芒柄花素, 都属于黄酮类化合物。前3种化合物与FS在黄芪根中的含量显著负相关(r ≤ -0.97, P < 0.05), 作为潜在RR代谢物, 可为研究获得有实际应用前景的黄芪抗根腐病指标提供参考。

黄芪  /  腐皮镰刀菌  /  靶向代谢组  /  苯丙烷代谢物  /  响应

Root rot severely restricts the sustainable development of Astragalus membranaceus var. mongholicus (AMM) industry. Resistance breeding is an economical and environmentally safe way to manage the disease and its key lies in the obtaining of resistance indicators. This study aimed to quickly and accurately screen the resistance-related (RR) metabolites so as to provide reference for the screening of indicators of AMM breeding for resistance. LC-MS-based targeted metabolomics and real-time quantitative PCR technology were employed, in combination with multivariate statistical analysis, in analyzing the dynamic changes of phenylpropanoid metabolites in AMM in response to root rot pathogen Fusarium solani (FS) infection and identifying the differential metabolites. The LC-MS method established showed high sensitivity; each metabolite had a good linear relationship (R2 ≥ 0.968 9) in the corresponding linear range of the respective standard curve; the recoveries and the relative standard deviations (RSDs) (n = 6) ranged from 70% to 107% and from 1.2% to 9.9%, respectively. Obvious disturbances were observed in the changes of the targeted metabolites in AMM infected by FS. These metabolites, compared with the mock-inoculated (CK) group, showed different up or down regulation with time series. Calycosin-7-O-β-D-glucoside, ononin, calycosin and formononetin were identified as differential metabolites, and they all belong to flavonoids. The first three compounds were significantly negatively correlated (r ≤ -0.97, P < 0.05) with the content of FS in the root of AMM. As potential RR metabolites, they are helpful in obtaining promising resistance indicators for AMM against FS infection.

Astragalus membranaceus var. mongholicus  /  Fusarium solani  /  targeted metabolomic  /  phenylpropanoid metabolites  /  response
赵子青, 宋海清, 赵丽梅, 李震宇, 武瑞杰, 高芬. 基于靶向代谢组学分析黄芪苯丙烷代谢物对根腐病菌Fusarium solani侵染的响应. 药学学报, 2023 , 58 (7) : 1859 -1866 . DOI: 10.16438/j.0513-4870.2022-1269
Zi-qing ZHAO, Hai-qing SONG, Li-mei ZHAO, Zhen-yu LI, Rui-jie WU, Fen GAO. Targeted metabolomic analysis of phenylpropanoid metabolites in Astragalus membranaceus var. mongholicus in response to Fusarium solani infection[J]. Acta Pharmaceutica Sinica, 2023 , 58 (7) : 1859 -1866 . DOI: 10.16438/j.0513-4870.2022-1269
正文
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黄芪为豆科植物蒙古黄芪[Astragalus membranaceus var. mongholicus, AMM] 或膜荚黄芪[A. membranaceus] 的干燥根, 是中医药学公认的道地大宗药材和保健品原料, 具有提高免疫力、保护肝脏、滋养补益、利尿消肿、抗糖尿病等多种药理功效[1]。蒙古黄芪(以下简称: 黄芪) 作为市场主流商品, 种植面积逐年扩大, 素有“植物癌症”之称的根腐病也随之在各主产区(甘肃、山西、内蒙古等地) 普遍发生[2], 给黄芪的产量和质量造成了严重影响。选育抗性品种是防治病害最为经济有效且安全的措施[3]。寻找抗病性状指标, 发掘有重要育种价值的抗病基因资源, 是抗病育种的关键[4]。
植物代谢组学是研究植物响应生物和非生物胁迫的成熟方法, 已被广泛用于分析多种植物响应不同镰刀菌属Fusarium spp.真菌胁迫下代谢物谱的变化和抗病相关(resistance-related, RR) 代谢物指认。这些研究不仅有助于深入理解植物的抗病机制, 为抗病育种提供合理、有效的抗病性状指标, 还可为挖掘抗病基因提供线索和依据[5]。液质联用技术(LC-MS) 灵敏度高且利于次级代谢产物的分析, 是一种能更加全面地体现生物应激反应的代谢组学工具。利用基于LC-MS的非靶向代谢组技术, 分析大麦响应F. culmorum[6]、小麦响应F. graminearum[7]、玉米响应F. verticillioides[8]侵染等的代谢物谱变化, 发现各类植物的不同抗性水平品种在响应病原菌侵染时具有不同的代谢物谱变化, 且苯丙素类、酚类、黄酮类、脂肪酸和萜类等多种化合物被指认为RR代谢物。
靶向代谢组学是代谢组学研究的重要组成部分, 具有特异性强, 检测敏感度高和定量准确等特点。该方法通常对特定的几个或几类代谢物群进行针对性的检测与分析, 并通过采集候选代谢物所对应的代谢通路及其上下游中所有成分的精准定量数据, 来揭示发生变化的代谢机制[9]。苯丙烷代谢是植物抗病防卫反应的重要途径[10]。植物对镰刀菌侵染的响应, 也反映在苯丙烷途径代谢产物的含量变化上。以大麦/小麦与F. graminearum互作体系为例, 在指认出的340多种RR代谢物中, 178种归属于苯丙烷代谢途径, 包括酚类、类黄酮类、植保素、木质素等[11]。亚麻被F. oxysporum侵染后, 苯丙烷途径的对香豆酸、咖啡酸的含量与对照相比均显著升高; 被F. culmorum侵染后, 黄酮类化合物芹菜素的含量显著高于对照[12]。
腐皮镰刀菌(F. solani, FS) 作为山西、甘肃、内蒙等黄芪主产区根腐病的主要致病菌之一[2], 可侵染激活黄芪的苯丙烷代谢途径[10]。为此, 本研究根据文献报道, 靶向性地选择阿魏酸、对香豆酸、大豆苷元、柚皮素、甘草素、芒柄花苷、芒柄花素、毛蕊异黄酮、毛蕊异黄酮葡萄糖苷、咖啡酸、槲皮素、山柰酚、香豆素等13种在其他病原真菌与植物互作体系中被指认为RR代谢物的苯丙烷途径代谢物, 采用基于LC-MS的靶向代谢组学与实时荧光定量PCR (real-time quantitative PCR, RT-qPCR) 相结合的技术, 分析黄芪苯丙烷途经代谢物/谱响应FS侵染的变化, 以期精准挖掘黄芪抗FS侵染的相关代谢物, 为抗根腐病性状指标的获得提供依据和思路。
材料与方法
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黄芪与病原菌   一年生健康黄芪, 由山西省宁武县种植基地提供, 经山西大学中医药现代研究中心秦雪梅教授鉴定为蒙古黄芪。选择根长约10~15 cm, 粗约5~7 mm的植株作为实验材料。根腐病菌FS由本课题组分离自典型黄芪根腐病根, 经形态学和分子鉴定确定分类地位[2], 并保存于本实验室。
仪器和试剂   LC-MS 8045三重四极杆质谱仪和LC-20ADXR超高效液相色谱仪(Shimadzu, 日本); Bio-Rad CFX96实时荧光定量PCR仪和Bio-Rad凝胶成像系统(Bio-Rad, 美国)。甲醇(Merck, 德国), 甲酸(北京迪科马科技有限公司), 乙酸铵(Sigma, 美国), 以上试剂为质谱纯; 超纯水, Millipore制水机制备(Millipore, 美国)。标准品阿魏酸(98.7%, CAS: 1135-24-6)、大豆苷元(99.0%, CAS: 486-66-8)、柚皮素(99.0%, CAS: 480-41-1)、芒柄花苷(99.0%, CAS: 486-62-4)、芒柄花素(99.0%, CAS: 485-72-3)、毛蕊异黄酮(99.0%, CAS: 20575-57-9)、毛蕊异黄酮葡萄糖苷(99.5%, CAS: 20633-67-4)、咖啡酸(98.0%, CAS: 331-39-5)、槲皮素(99.0%, CAS: 117-39-5) 和山柰酚(99.0%, CAS: 520-18-3) 购自江苏永健医药科技有限公司; 对香豆酸(99.0%, CAS: 501-98-4)、甘草素(98.7%, CAS: 578-86-9) 和香豆素(98.0%, CAS: 91-64-5) 购自南京源植生物科技有限公司; RT-qPCR所用试剂及试剂盒均购自生工生物(上海) 股份有限公司。
根腐病菌FS在黄芪根中含量的测定
病菌的培养、接种及样本培育   参照本课题组建立的方法[13]。将FS菌片接种于马铃薯葡萄糖(potato dextrose, PD) 培养液, 恒温振荡(25 ℃, 180 r·min-1) 培养3~5天, 得孢子悬液后, 调整终浓度至1.0×106~1.0×107 cfu·mL-1。黄芪根经无菌水和75%酒精消毒, 用无菌针在平滑健康的相同部位作梅花状五点刺伤, 每株5处, 间隔约2 cm。刺伤的黄芪根在孢子悬液中浸泡接种1 h, 每隔10 min翻动一次。以无菌水模拟接种为对照(CK), 3次重复。接种组与对照组分别移栽于装有无菌土的花盆中, 室温常规培养。在0 (接种1 h)、7、14和21 dpi (days of post inoculation) 时分别整根取样, 液氮速冻, -80 ℃保存。
FS含量的检测  采用本课题组建立的基于荧光染料SYBR Green Ⅰ的RT-qPCR法进行。切取相同大小的发病部位, 用Ezup柱式真菌基因组DNA抽提试剂盒提取各样本DNA为模板, 用特异性引物FP.F/FP.R (FP.F: 5′-CTGCTTATCTCGGGTCGTGG-3′/FP.R: 5′-CTT GTCGATACCACCGCACT-3′) 进行扩增。反应体系20 μL: SYBR Green Ⅰ荧光染料10 μL, 模板DNA 2 μL, 引物各2 μL (浓度为2 μmol·L-1), ddH2O补足。扩增程序: 95 ℃, 3 min; 95 ℃, 5 s; 64 ℃, 20 s。35个循环, 溶解曲线分析温度设于65~95 ℃之间。测定完成后依据已建立的标准曲线(y = -2.864x + 20.998, R2 = 0.981 6) 计算样本中FS的含量。
黄芪响应FS侵染的靶向代谢组分析
色谱条件  日本岛津Shim-pack GIST C18柱(250 mm × 4.6 mm, 5 μm); 以含0.1%甲酸和乙腈的超纯水为流动相, 流速0.2 mL·min-1, 30 ℃; 溶剂梯度在22 min内从5%乙腈线性增加到50%, 然后在1 min内返回5%乙腈, 并在该水平上保持2 min, 以便系统在下一次进样前重新平衡。
质谱条件  MS在正电喷雾电离(ESI) 中运行, 数据以多反应监测(MRM) 模式收集。优化的ESI参数如下: 毛细管电压3.5 kV, 源温度125和400 ℃下的去溶剂气体(N2) 流速为800 L·h-1。氮气(纯度99.99%) 由氮气发生器(马来西亚泰勒沃顿气体设备有限公司) 制备, 并以50 L·h-1的流速用作锥孔气体。氩气(纯度99.999%) 由北京延安燃气有限公司提供, 用作碰撞气体。
标准曲线绘制  分别精密称取标准品毛蕊异黄酮葡萄糖苷、芒柄花苷、毛蕊异黄酮、芒柄花素、阿魏酸、大豆苷元、柚皮素、对香豆酸、甘草素、咖啡酸、山柰酚、香豆素和槲皮素至10 mL量瓶中, 用甲醇各自溶解, 摇匀, 制备每种对照品(1 000 mg·L-1) 的单个标准溶液, 再用甲醇稀释至终浓度为10 mg·L-1, 制备含所有化合物的多组分混合标准溶液; 混标溶液经0.22 µm滤膜过滤后, 进样1 μL进行测定; 以待测化合物浓度为横坐标, 峰面积为纵坐标, 外标法绘制标准曲线, 并计算检出限和定量限。上述溶液配制好后均储存于4 ℃。
样品制备与测定  黄芪样品用液氮研磨至粉末状后冷冻干燥, 存于-80 ℃备用。测定时精密称取1 g于50 mL三角瓶中, 加入30 mL甲醇浸渍过夜, 超声提取30 min, 转入50 mL离心管中, 离心15 min取上清后, 残渣再加30 mL相同的提取剂重复提取两次, 合并三次上清液, 转移到250 mL圆底烧瓶中52 ℃浓缩至干; 用质谱级甲醇溶解残渣并转移至10 mL量瓶中定容。吸取1~1.5 mL进样小瓶中, 样品测定前经0.22 μm微孔滤膜过滤。进样量1 μL, 每样品重复3次。
数据分析   采用SIMCA-P14.1 (Umetrics, Umea, Sweden) 软件进行主成分分析(PCA) 和正交偏最小二乘判别分析(OPLS-DA) 分析; 模型变量的变量权重值(variable importance in projection, VIP) 结合变化倍数(fold change, FC) 筛选差异代谢物(VIP ≥ 1, FC > 1.2或FC < 0.8); 采用TBtools (v 1.09876) 绘制热图对代谢物含量变化进行层次聚类分析; 采用SPSS16.0对差异代谢物含量变化率与FS含量进行皮尔森相关性分析。各时间点代谢物含量变化率(%) = [(FS接种组含量-模拟接种组含量)/模拟接种组含量]×100。
结果
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1 发病黄芪根内FS的含量
FS接种黄芪可明显引起发病症状, 7 dpi时根部接种部位出现浅褐色病斑; 14 dpi时病斑颜色加深, 呈褐色或深褐色, 面积扩大; 21 dpi时病斑面积继续扩大, 病斑呈连片趋势, 个别样本有腐烂发生。RT-qPCR是定量检测植物体内病原菌含量的有力工具, 可准确反映病原菌对植物的侵染状况。检测结果显示: FS在黄芪根中的含量随侵染时间延长逐渐增加; 7 dpi时FS含量与0 dpi无显著差异, 14和21 dpi时含量较0 dpi时显著升高(图 1)。
2 LC-MS方法的建立与目标代谢物测定
对毛蕊异黄酮葡萄糖苷等13种目标代谢物进行色谱分离优化, 在Shim-pack GIST色谱柱上各组分保留适中, 分离良好。各组分在各自浓度范围内, 线性关系良好, 相关系数R2在0.968 9~0.999 5之间(表 1)。方法灵敏度高, 使用LabSolutions软件, ASTM法计算信噪比, 由信噪比计算得到的目标组分检出限(LOD, 信噪比为3) 和定量限(LOQ, 信噪比为10) 见表 1。优化影响分析程序的因素后, 对方法进行重复性验证。将标准分析物在3个浓度水平(10、20、100 µg·kg-1) 下重复6次, 所有化合物的回收率在70%~107%, 相对标准偏差在1.2%~9.9%。上述结果表明, 所建立的测定方法可用于目标代谢物的定量测定。
采用上述方法对黄芪样本进行测定, 共检测到10种目标代谢物, 即毛蕊异黄酮葡萄糖苷、芒柄花苷、毛蕊异黄酮、芒柄花素、阿魏酸、大豆苷元、柚皮素、对香豆酸、甘草素和咖啡酸(图 2)。其中, 毛蕊异黄酮葡萄糖苷、芒柄花苷、毛蕊异黄酮、芒柄花素的含量以500倍稀释样测定值计算; 其余化合物含量以未稀释样测定值计算。槲皮素、香豆素和山柰酚未被检出。
3 目标代谢物对FS侵染的响应变化
根据每种目标代谢物的定量结果, 利用TBtools对其在各时间点下的均值进行标准化, 并绘制热图, 结果显示FS接种组与模拟接种组中目标代谢物含量随FS侵染时间的变化(图 3), 并据此将10种代谢物分为4组。第一组包括对香豆酸、咖啡酸和阿魏酸。三种代谢物依时间序列, 在模拟接种组中均逐渐上调; 在FS接种组中, 0~14 dpi时三者逐渐上调, 21 dpi时则下调。第二组包括毛蕊异黄酮、芒柄花素、毛蕊异黄酮葡萄糖苷和芒柄花苷。这四种代谢物在模拟接种组和FS接种组中分别依时间序列呈明显下调趋势。第三组包括大豆苷元和柚皮素。二者在FS接种组中依时间序列显著下调, 在模拟接种组中0~14 dpi时轻微下调, 至21 dpi时又上调。第四组仅甘草素一种, 在7 dpi时在FS接种组与模拟接种组中与0 dpi相比均显示上调, 此后逐渐下调。上述化合物在响应FS侵染的过程中, 其含量随时间与模拟接种组相比呈现不同类型的变化模式与不同的上、下调幅度, 表明FS侵染对各代谢物变化造成了扰动, 导致各代谢物随时间的变化规律发生了改变。
无监督的PCA分析可以同时反映组内和组间的差异。为判别FS侵染对黄芪目标代谢物累积的影响, 对模拟接种组和FS接种组的数据分别进行PCA分析(图 4)。结果发现: 各组样本重复性良好, 均处在95%置信区间以内。模拟接种组的代谢物轮廓分析中, PC1为41.5%, PC2为27.6%, 两个主要成分共解释了原始数据的69.1%; 0、7和14 dpi组的样本基本聚在一起, 21 dpi组则与其他组明显分开(图 4A)。FS接种组中, PC1为63.1%, PC2为22.5%, 两个主要成分共解释了原始数据的85.6%; 代谢物轮廓变化与模拟接种组明显不同, 不同时间点样本按逆时针方向分别聚集在一起并明显分开, 其中主成分1将0 dpi组与其他组显著分开, 位于PC1正半轴; 7 dpi组及以后时间点的样本被主成分1划分在一起, 位于PC1负半轴。上述分析表明, 与模拟接种组相比, FS接种组中目标代谢物的积累发生了显著变化; 7 dpi时FS侵染造成的影响最为剧烈, 此后的影响程度趋缓(图 4B)。
4 差异代谢物分析
OPLS-DA分析是一种具有监督模式的多元统计分析方法, 能有效剔除与研究无关的影响。为了成对比较各时间点FS接种组与模拟接种组之间的代谢差异, 进行OPLS-DA分析并绘制得分图(图 5)。各时间点下, 两处理组均分别分布于纵轴两侧, 且随时间延长分离趋势更加显著(图 5A~D), 表明在整个侵染过程中, 目标代谢物在FS接种组和模拟接种组中的变化存在明显差异, 且具有时间依赖性。
OPLS-DA模型可用于筛选差异代谢物。R2X和R2Y分别表示所建模型对X和Y矩阵的解释率, Q2表示模型的预测能力。R2Y和Q2越接近1表明模型越稳定可靠, 且通常情况下Q2高于0.4即表示模型可接受。在各时间点下, 模型的参数分别为: 0 dpi (R2X = 0.956, R2Y = 0.747, Q2 = 0.476)、7 dpi (R2X = 0.993, R2Y = 0.882, Q2 = 0.675)、14 dpi (R2X = 0.998, R2Y = 0.884, Q2 = 0.559)、21 dpi (R2X = 0.999, R2Y = 0.996, Q2 = 0.993), 表明所构建模型的稳定性和预测能力均较好, 满足建模要求。为避免OPLS-DA模型能有效区分组间样本, 却无法有效预测新样本数据集的过拟合现象, 采用置换检验(permutation test) 来验证模型的可靠性, 结果显示, OPLS-DA模型置换检验(n = 200) 中, 0、14和21 dpi的Q2回归线的截距均为负值, 7 dpi左端任何一次随机排列产生的R2、Q2值均小于右端的原始值, 表明统计模型有效, 没有过拟合(图 5E~H)。
在OPLS-DA分析中, VIP值可以衡量各代谢物积累差异对各组样本差异判别的影响强度和解释能力, 挖掘具有生物学意义的差异代谢物。本研究以VIP值结合变化倍数FC值进行差异代谢物筛选(VIP ≥ 1, 且FC > 1.2或FC < 0.8)。结果显示, FS接种组与模拟接种组间的差异代谢物共有4种: 毛蕊异黄酮葡萄糖苷、芒柄花苷、毛蕊异黄酮和芒柄花素(表 2)。其中, 前两者在侵染过程中的4个时间点均为差异代谢物; 其余两种则在部分时间点为差异代谢物。这一现象可能意味着差异代谢物在响应FS侵染的过程中, 在不同阶段发挥不同的作用, 进而呈现波动性的变化。
5 差异代谢物与FS含量的相关性分析
为了更好地可视化差异代谢物含量变化的模式并比较其积累变化模式的异同, 将各差异代谢物在每个时间点下含量的均值通过SPSS进行正态标准化(Z-score) 后, 按时间过程描绘为叠加图(图 6A、B)。由图可知, 毛蕊异黄酮和芒柄花素、毛蕊异黄酮葡萄糖苷和芒柄花苷两两对应为一组, 分别在模拟接种组和FS接种组中, 依时间序列呈基本一致的变化模式。在0 dpi时, 4种代谢物在FS接种组中的含量与模拟接种组相比, 均显著升高, 其含量分别上升69.4%、52.38%、58.18%和35.25%; 此后, 毛蕊异黄酮和芒柄花素在14和21 dpi时显著降低, 分别减少69.18%和89.76%; 89.63%和92.84%。毛蕊异黄酮葡萄糖苷和芒柄花苷在7、14和21 dpi时均显著降低, 分别为89.06%和85.17%; 97.05%和97.24%; 97.77%和97.78%。差异代谢物的这种规律性变化, 可能暗示着与病菌侵染的某种内在联系。有研究表明, 一些反应性代谢物的丰度与感染过程有显著的正或负相关性[14]。因此, 将上述差异代谢物的含量变化率与FS含量进行相关性分析。结果显示: 毛蕊异黄酮(r = -0.99, P = 0.01 < 0.05)、毛蕊异黄酮葡萄糖苷(r = -0.97, P = 0.03 < 0.05) 和芒柄花苷(r = -0.98, P = 0.02 < 0.05) 的变化与FS含量呈显著负相关; 芒柄花素也呈负相关但不显著(r = -0.93, P = 0.07)。这表明4种差异代谢物含量的改变与FS在黄芪根中的定植和扩展进程密切相关, 其含量的降低可能是导致FS引起的根腐病加重的原因之一。
讨论
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苯丙烷类生物合成是黄酮类生物合成途径的上游途径, 并由此产生各种化合物, 包括黄烷酮、花青素、异黄酮等[15]。黄酮类化合物是植物抵御逆境的重要代谢产物, 对多种病原菌具有防御作用。镰刀菌属真菌与植物的互作中, 黄酮类代谢也被广泛报道与植物抵抗病菌侵染的机制有关。Li等[16]报道黄酮代谢主导花椒对干腐病菌F. zanthoxyli侵染引起的茎溃疡病的抗性; Gill等[17]研究表明黄酮类途径代谢流的增强可以增加苜蓿对F. oxysporum f. sp. medicaginis的抗性; Wang等[15]发现千年桐根部苯丙烷类生物合成途径在枯萎病菌F. oxysporum f. sp. fordii (Fof-1) 入侵后发生响应, 产生芒柄花苷、橙皮苷等黄酮类化合物, 抵御病菌入侵。而在大麦/小麦与F. graminearum互作的研究中, 有近100种推定的黄酮类化合物被报道有助于小麦和大麦抗F. graminearumd的侵染[11]。
本研究指认的FS接种组和模拟接种组间的4种差异代谢物毛蕊异黄酮、芒柄花素、毛蕊异黄酮葡萄糖苷和芒柄花苷都属于黄酮类化合物。黄芪被FS侵染1 h后(即0 dpi时), 这4种化合物的含量即开始显著增加。这可能是由于植物受到病菌侵染时, 参与黄酮代谢的相关基因的表达被激活, 促进了黄酮类化合物的积累, 进而抵御病菌的入侵。但随着侵染程度的加重, 其含量开始降低并明显低于模拟接种组, 意味着当病菌侵染到一定程度, 可能严重干扰或破坏了黄酮类代谢合成途径, 导致某些黄酮类化合物含量降低。这种现象在其他病害体系[18]中也有类似报道。
当植物受到逆境胁迫时, 活性氧(ROS) 产生和积累超过一定的阈值, 就会发生膜伤害, 甚至导致植物死亡。植物体内具有活性氧清除系统, 过氧化物酶(POD)、超氧化物歧化酶(SOD)、抗坏血酸过氧化物酶(APX) 等是细胞内活性氧代谢的主要调节酶, 这些酶与植物的抗病性紧密相关[19, 20]。黄酮类化合物被认为是一组非酶活性氧清除系统, 当在压力条件下需要补充抗氧化酶的作用时, 用以清除形成的活性氧。黄酮类还可以被激活为次级抗氧化系统[20]。研究发现, 作为次级抗氧化系统, 在UV辐射条件下, 毛蕊异黄酮葡萄糖苷、毛蕊异黄酮、芒柄花苷和芒柄花素的反应模式与蒙古黄芪中的抗氧化酶系统(SOD、APX) 表现出了惊人的相似性[20], 且前三种化合物的代谢与POD活性呈显著正相关[21]。本研究中毛蕊异黄酮、毛蕊异黄酮葡萄糖苷和芒柄花苷的含量变化与FS在黄芪根中的定殖量呈显著负相关。由此推测, 上述三种黄酮类化合物可能通过增强活性氧清除系统的活性来抵御根腐病菌FS的侵染, 可作为潜在的RR代谢物进一步研究。
选育能够生产更多黄酮类化合物的作物是获得营养价值更高、抗病性更强作物品种的一种极具前景的方法。以花青素为指标选育的番茄品种, 不仅营养价值更高, 而且对番茄灰霉病菌(Botrytis cinerea) 的抗性更强[22]。黄酮类作为黄芪中最重要的活性成分之一, 其含量的高低是评价黄芪质量好坏的客观指标。因此, 挖掘黄酮类RR代谢物作为黄芪抗根腐病的性状指标, 在选育抗病品种的同时, 可兼顾优化黄芪的质量性状。本文的结果为深入挖掘黄芪抗根腐病菌侵染的黄酮类RR代谢物指示了方向, 但是囿于靶向代谢组学较低的检测物质覆盖率, 无法对数量众多的代谢物进行整体性分析, 也就意味着更多潜在的RR代谢物无法被发掘。因此, 后续需采用物质覆盖率更广的非靶向代谢组技术深入分析黄芪响应根腐病菌FS侵染的代谢物/谱变化, 以获取更多黄酮类RR代谢物, 为抗病育种提供有价值的信息。
作者贡献: 高芬负责思路提出、方案设计及论文最终版本修订; 赵子青负责LC-MS测定方法的建立和样品测定; 宋海清负责数据分析与论文起草; 赵丽梅负责RT-qPCR测定; 李震宇负责指导多元统计分析; 武瑞杰负责LC-MS 8045的运行维护并参与测定。赵子青和宋海清对本论文形成有同等重要的贡献。
利益冲突: 本文研究内容无任何利益冲突。
基金
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  • 山西省基础研究计划资助项目(202103021224029)
  • 山西省回国留学人员科研资助项目(2022-023)
文献
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参考文献 引证文献
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2023年第58卷第7期
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doi: 10.16438/j.0513-4870.2022-1269
  • 接收时间：2022-11-15
  • 首发时间：2025-11-21
  • 出版时间：2023-07-12
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  • 收稿日期：2022-11-15
  • 修回日期：2023-02-04
基金
山西省基础研究计划资助项目(202103021224029)
山西省回国留学人员科研资助项目(2022-023)
作者信息
    1.山西锦烁生物科技有限公司, 山西 晋中 030600
    2.山西大学中医药现代研究中心, 山西 太原 030006
    3.山西大学化学生物学与分子工程教育部重点实验室, 山西 太原 030006
    4.地产中药功效物质研究与利用山西省重点实验室, 山西 太原 030006
    5.山西大学应用化学研究所, 山西 太原 030006

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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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