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Article(id=1153429494569361927, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153429493357203682, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20241209003, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1733673600000, receivedDateStr=2024-12-09, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1752928621188, onlineDateStr=2025-07-19, pubDate=1741968000000, pubDateStr=2025-03-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752928621188, onlineIssueDateStr=2025-07-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752928621188, creator=13701087609, updateTime=1752928621188, updator=13701087609, issue=Issue{id=1153429493357203682, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='5', pageStart='1', pageEnd='326', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752928620900, creator=13701087609, updateTime=1758690311058, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1177595773500932351, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153429493357203682, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1177595773500932352, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153429493357203682, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=76, endPage=85, ext={EN=ArticleExt(id=1153429495404028430, articleId=1153429494569361927, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Analysis of solvent effects differences in extracting substances from flower disc of Helianthus annuus L. using non-targeted metabolomics, columnId=1151895322591638525, journalTitle=Journal of Food Safety & Quality, columnName=Special Topic: Functional Foods and Functional Components, runingTitle=null, highlight=null, articleAbstract=

Objective To investigate the solvent effect differences in the extraction of substances from flower discs of Helianthus annuus L. using non-targeted metabolomics technology, and to explore the impact of different solvent extraction methods on the metabolic composition of flower disc of Helianthus annuus L.. Methods Liquid chromatography-mass spectrometer (LC-MS) combined with non-targeted metabolomics was utilized to preprocess and statistically analyze the data. Results The study revealed that lipids and lipid-like molecules constituted the largest proportion of metabolites (21.5%), followed by shikimate and phenylpropanoid metabolites (13.4%), and organic heterocyclic compound metabolites (11.1%). Further identification led to the discovery of 8407 kinds of up-regulated and 1054 kinds of down-regulated metabolites, highlighting significant differences in metabolite composition resulting from various extraction methods. The main differential metabolites between the 2 kinds of solvent extraction methods encompassed lipids, shikimate and phenylpropanoids, terpenoids, etc., involving 96 metabolic pathways, with 20 pathways exhibiting significant differences. Based on fold change (FC), using criteria of log2(FC)>0.6 or -0.2<log2(FC)<0, and P<0.05 to screen for significantly differential metabolites between alcohol and water extracts, only 11 substances had a log2(FC) value less than 1, indicating that alcohol extraction significantly increased the content of bioactive components extracted from the flower disc of Helianthus annuus L.. Conclusion The research method is simple and reliable, confirming the importance of non-targeted metabolomics analysis in studying solvent effect differences in flower disc of Helianthus annuus L.. It provides a novel approach for the analysis of flower disc of Helianthus annuus L. products and offers theoretical support for the subsequent development of health foods and pharmaceuticals.

, correspAuthors=Yuan-Yuan ZHANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, 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=Shu-Ning ZHONG, Jia-Ning LI, Kai-Hong TANG, Tong-Xi LIU, Yuan-Dong ZHANG, Yuan-Yuan ZHANG), CN=ArticleExt(id=1153429524990648396, articleId=1153429494569361927, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=基于非靶向代谢组学的葵花盘物质提取溶剂效应差异分析, columnId=1151895323909124661, journalTitle=食品安全质量检测学报, columnName=本期专题：功能性食品与功能性成分, runingTitle=null, highlight=null, articleAbstract=

目的 基于非靶向代谢组学技术, 开展葵花盘物质提取溶剂效应差异分析, 探究不同溶剂提取对葵花盘代谢物质组成的影响。方法 运用液相色谱-质谱法(liquid chromatography-mass spectrometer, LC-MS)结合非靶向代谢组学, 对数据进行预处理和统计分析。结果 脂质和类脂分子代谢物数量占比最大(21.5%), 其次是莽草酸和苯丙酸代谢物(13.4%)以及有机杂环化合物代谢物(11.1%)。进一步鉴定出8407种上调和1054种下调代谢物质, 揭示了不同提取方法导致的显著代谢物组成差异。两种溶剂提取方式下的主要差异代谢物涵盖脂质、莽草酸和苯丙酸、萜类化合物等, 涉及96条代谢途径, 其中20条途径有显著差异。基于差异倍数(fold change, FC), 以log2(FC)>0.6或-0.2<log2(FC)<0, P<0.05为标准筛选醇提和水提的显著差异代谢物, 仅有11个物质的log2(FC)值小于1, 表明醇提方式显著增加了葵花盘中提取出的生物活性成分的含量。结论 本研究方法简单可靠, 证实了非靶向代谢组学分析对葵花盘溶剂效应差异研究的重要意义, 为葵花盘产品分析提供了新途径, 研究结果为后续保健食品和药品开发提供了理论依据。

, correspAuthors=张园园, authorNote=null, correspAuthorsNote=
* 张园园(1983—), 女, 副教授, 主要研究方向为功能性食品加工技术。E-mail:
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钟姝凝(1993—), 女, 博士, 讲师, 主要研究方向为食品生物技术。E-mail:

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钟姝凝(1993—), 女, 博士, 讲师, 主要研究方向为食品生物技术。E-mail:

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钟姝凝(1993—), 女, 博士, 讲师, 主要研究方向为食品生物技术。E-mail:

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College of Grain Science and Technology, Jilin Business and Technology College, Changchun 130507, China), AuthorCompanyExt(id=1177619625404678981, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, companyId=1177619625392096067, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.吉林工商学院粮食学院, 长春 130507)])])], keywords=[Keyword(id=1177619627745100675, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=EN, orderNo=1, keyword=flower disc of Helianthus annuus L.), Keyword(id=1177619627866735493, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=EN, orderNo=2, keyword=non-targeted metabolomics), Keyword(id=1177619628005147526, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=EN, orderNo=3, keyword=extraction methods), Keyword(id=1177619628072256391, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=EN, orderNo=4, keyword=differential metabolites), Keyword(id=1177619628143559563, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=CN, orderNo=1, keyword=葵花盘), Keyword(id=1177619628248417167, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=CN, orderNo=2, keyword=非靶向代谢组学), Keyword(id=1177619628323914641, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=CN, orderNo=3, keyword=提取方式), Keyword(id=1177619628399412116, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=CN, orderNo=4, keyword=差异代谢物)], refs=[Reference(id=1177619630458815425, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, doi=null, pmid=null, pmcid=null, year=2024, volume=null, issue=null, pageStart=1, pageEnd=12, url=null, language=null, rfNumber=[1], rfOrder=0, authorNames=İREM P, NURŞAH K, HAVANUR D, journalName=Chemical Papers, refType=null, unstructuredReference=İREM P, NURŞAH K, HAVANUR D. 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Journal of King Saud University-Science, 2024, 36(4): 103115., articleTitle=Exploring metabolic pathway alterations in obese fermented feces mediated by individual fruit extracts of Triphala components using untargeted metabolomics, refAbstract=null)], funds=[Fund(id=1177619630223934396, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, awardId=20220508060RC, language=CN, fundingSource=吉林省科技厅人才专项(20220508060RC), fundOrder=null, country=null), Fund(id=1177619630286848958, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, awardId=202411261004, language=CN, fundingSource=2024年吉林省大学生创新创业训练计划项目(202411261004), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1177619625392096067, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, xref=null, ext=[AuthorCompanyExt(id=1177619625400484676, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, companyId=1177619625392096067, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. College of Grain Science and Technology, Jilin Business and Technology College, Changchun 130507, China), AuthorCompanyExt(id=1177619625404678981, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, companyId=1177619625392096067, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.吉林工商学院粮食学院, 长春 130507)]), AuthorCompany(id=1177619625593422664, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, xref=null, ext=[AuthorCompanyExt(id=1177619625597616969, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, companyId=1177619625593422664, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2. Physical and Chemical Testing Institute of Changchun Center for Disease Control and Prevention, Changchun 130119, China), AuthorCompanyExt(id=1177619625606005578, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, companyId=1177619625593422664, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.长春市疾病预防控制中心理化检验所, 长春 130119)])], figs=[ArticleFig(id=1177619628588155801, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=EN, label=Fig.1, caption=TIC diagram of WE and EE, figureFileSmall=94bVjoV35JIDBRGzoK39SA==, figureFileBig=hCyCRh91RdyAY71uB7HQpA==, tableContent=null), ArticleFig(id=1177619628659458971, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=CN, label=图1, caption=WE与EE的TIC图, figureFileSmall=94bVjoV35JIDBRGzoK39SA==, figureFileBig=hCyCRh91RdyAY71uB7HQpA==, tableContent=null), ArticleFig(id=1177619628852396959, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=EN, label=Fig.2, caption=Number and proportion of metabolites identified in each chemical classification, figureFileSmall=xt1ORg3jiFebb+IjW2c3Pg==, figureFileBig=lkwNXItWpsAiZjpiYtl/qw==, tableContent=null), ArticleFig(id=1177619628944671649, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=CN, label=图2, caption=鉴定代谢物在各化学分类的数量占比, figureFileSmall=xt1ORg3jiFebb+IjW2c3Pg==, figureFileBig=lkwNXItWpsAiZjpiYtl/qw==, tableContent=null), ArticleFig(id=1177619629087277986, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=EN, label=Fig.3, caption=PCA score chart and OPLS-DA score chart of WE and EE, figureFileSmall=6CoFj+e2w/bbwCW0YMHDzw==, figureFileBig=UkwfblZBRuKdD8XrUcJ62A==, tableContent=null), ArticleFig(id=1177619629250855844, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=CN, label=图3, caption=WE与EE的PCA得分图及OPLS-DA得分图

注: A. 正离子模式PCA得分图; B. 负离子模式PCA得分图; C. 正离子模式OPLS-DA得分图; D. 负离子模式OPLS-DA得分图。

, figureFileSmall=6CoFj+e2w/bbwCW0YMHDzw==, figureFileBig=UkwfblZBRuKdD8XrUcJ62A==, tableContent=null), ArticleFig(id=1177619629376684968, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=EN, label=Fig.4, caption=Volcanic map of WE and EE metabolites, figureFileSmall=jUiYhNrH0iZ6IJW/RHKDFg==, figureFileBig=UlOqLmJ68n5RMsYTsUBQSw==, tableContent=null), ArticleFig(id=1177619629473153962, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=CN, label=图4, caption=WE与EE代谢物火山图, figureFileSmall=jUiYhNrH0iZ6IJW/RHKDFg==, figureFileBig=UlOqLmJ68n5RMsYTsUBQSw==, tableContent=null), ArticleFig(id=1177619629548651436, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=EN, label=Fig.5, caption=Hierarchical clustering heat map of different metabolites of WE and EE, figureFileSmall=9GFQr12BqaZTkL2uvtrFSw==, figureFileBig=8sru7qxZukbPmHR5YqpBLQ==, tableContent=null), ArticleFig(id=1177619629611566000, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=CN, label=图5, caption=WE与EE差异代谢物层次聚类热图

注: 此图为正离子模式, WE与EE各有3组平行样品。

, figureFileSmall=9GFQr12BqaZTkL2uvtrFSw==, figureFileBig=8sru7qxZukbPmHR5YqpBLQ==, tableContent=null), ArticleFig(id=1177619629695452082, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=EN, label=Fig.6, caption=Critical path analysis of WE and EE, figureFileSmall=jw3fnFZjOIAu2P6pC6VyHw==, figureFileBig=viYZM+g6AnMBfA0008phEw==, tableContent=null), ArticleFig(id=1177619629808698292, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=CN, label=图6, caption=WE和EE关键通路分析, figureFileSmall=jw3fnFZjOIAu2P6pC6VyHw==, figureFileBig=viYZM+g6AnMBfA0008phEw==, tableContent=null), ArticleFig(id=1177619629892584376, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=EN, label=Table 1, caption=

Analysis of significantly different metabolic compounds detected in both positive and negative ion modes

, figureFileSmall=null, figureFileBig=null, tableContent=
种类 物质中文名称 m/z CAS号 化学分子式 KEGG HMDB log2(FC) 显著性 调控
生物碱 7-羟基鸟氨酸 415.22 174418-82-7 C23H30N2O5 3.78 2.09×10-3 ⬆
原阿片碱 354.13 130-86-9 C20H19NO5 C05189 HMDB0003920 3.55 1.44×10-3 ⬆
天芥菜碱 314.20 303-33-3 C16H27NO5 3.54 9.42×10-3 ⬆
苯乙胺 122.10 64-04-0 C8H11N 2.91 3.44×10-3 ⬆
核黄素 377.15 83-88-5 C17H20N4O6 C00255 HMDB0000244 2.74 7.29×10-4 ⬆
肉叶芸香碱 213.10 442-51-3 C13H12N2O C06538 HMDB0030311 2.22 8.42×10-4 ⬆
烟酰胺 123.06 98-92-0 C6H6N2O C00153 HMDB0001406 1.32 1.78×10-2 ⬆
鸟嘌呤 152.06 73-40-5 C5H5N5O C00242 HMDB0000132 1.21 6.58×10-3 ⬆
脱硫生物素 197.13 533-48-2 C10H18N2O3 C01909 HMDB0003581 -1.09 3.95×10-2 ⬇
番茄素 1072.49 17406-45-0 C50H83NO21 C10827 HMDB0034103 -12.58 2.41×10-5 ⬇
氨基酸和多肽 γ-谷氨酰苯丙氨酸 295.13 7432-24-8 C14H18N2O5 HMDB0000594 4.64 6.55×10-4 ⬆
亮氨酰苯丙氨酸 279.17 56217-82-4 C15H22N2O3 HMDB0013243 3.47 7.16×10-3 ⬆
色氨酸 205.10 73-22-3 C11H12N2O2 C00078 HMDB0030396 3.25 1.74×10-3 ⬆
正亮氨酸 132.10 104809-14-5 C10H19N3O3S C01933 HMDB0251526 2.68 1.45×10-4 ⬆
亮氨酸 132.10 61-90-5 C6H13NO2 C00123 HMDB0062203 2.68 1.45×10-4 ⬆
苯丙氨酸 166.09 63-91-2 C9H11NO2 C00079 HMDB0000159 2.54 1.07×10-3 ⬆
香兰素胺 154.09 1196-92-5 C8H11NO2 C16666 HMDB0012309 0.98 9.77×10-3 ⬆
4-硝基苯酚 140.03 100-02-7 C6H5NO3 C00870 HMDB0001232 -0.98 4.01×10-3 ⬇
碳水化合物 木糖 133.05 58-86-6 C5H10O5 C00181 HMDB0060254 14.78 2.21×10-5 ⬆
阿拉伯糖 133.05 10323-20-3 C5H10O5 C11476 HMDB0000646 14.78 2.21×10-5 ⬆
松三糖 505.18 597-12-6 C18H32O16 6.15 3.21×10-3 ⬆
葡萄糖 203.05 492-62-6 C6H12O6 C00267 HMDB0003345 -0.69 1.22×10-2 ⬇
果糖 203.05 53188-23-1 C6H12O6 C02336 HMDB0000660 -0.69 1.22×10-2 ⬇
塔格糖 203.05 87-81-0 C6H12O6 C00795 HMDB0003418 -0.69 1.22×10-2 ⬇
脂肪酸 δ-癸内酯 171.14 705-86-2 C10H18O2 HMDB0037116 3.01 2.55×10-3 ⬆
双乙酰 87.04 431-03-8 C4H6O2 C00741 HMDB0003407 2.77 2.53×10-3 ⬆
N-酰基乙醇胺(18:1) 326.30 111-58-0 C20H39NO2 C20792 HMDB0002088 1.79 2.02×10-2 ⬆
木脂素 (+)-辛夷脂素 371.15 68296-27-5 C21H22O6 HMDB0038236 2.46 1.57×10-2 ⬆
愈创木脂素 329.18 36531-08-5 C20H24O4 HMDB0034178 2.04 6.34×10-3 ⬆
脂质/类脂分子 庚酸 187.11 111-14-8 C7H14O2 C17714 HMDB0000666 5.29 5.90×10-5 ⬆
莪术醇 235.17 19431-84-6 C15H22O2 C16942 HMDB0033960 3.70 1.46×10-3 ⬆
木香烃内酯 233.16 553-21-9 C15H20O2 HMDB0036688 3.30 9.14×10-4 ⬆
苦木素 406.22 76-78-8 C22H28O6 HMDB0036587 3.26 6.47×10-3 ⬆
姜黄新酮 219.17 87440-60-6 C15H22O HMDB0037068 2.83 5.63×10-4 ⬆
前花椒酚 315.20 119817-27-5 C20H26O3 HMDB0034712 1.29 2.78×10-2 ⬆
有机酸及其衍生物 N-(5-甲基-3-氧代己基)丙氨酸 265.15 3918-92-1 C14H20N2O3 HMDB0029134 3.59 2.83×10-3 ⬆
异亮氨酸 132.10 443-79-8 C6H13NO2 C16434 HMDB0033923 2.68 1.45×10-4 ⬆
甜菜碱 118.09 107-43-7 C5H11NO2 C00719 HMDB0000043 2.59 6.05×10-5 ⬆
水苏碱 144.10 4136-37-2 C7H14ClNO2 C10172 HMDB0004827 2.33 1.80×10-4 ⬆
N-酰基乙醇胺(16:0) 300.29 544-31-0 C18H37NO2 C16512 HMDB0002100 1.65 1.34×10-2 ⬆
环己胺 100.11 108-91-8 C6H13N C00571 HMDB0031404 3.57 9.10×10-4 ⬆
含氮有机化合物 铃兰毒原苷 713.34 13473-51-3 C35H52O15 HMDB0034195 1.73 1.71×10-2 ⬆
胆碱 104.11 62-49-7 C5H14NO+ C00114 HMDB0000097 1.38 6.24×10-3 ⬆
戊二醛 118.09 111-30-8 C5H8O2 C12518 HMDB0029599 2.79 8.44×10-3 ⬆
苯丙素类/聚酮类 山梨糖 203.05 87-79-6 C6H12O6 C00247 HMDB0246950 -0.69 1.22×10-2 ⬇
半乳糖 203.05 59-23-4(D) C6H12O6 C00984 HMDB0000143 -0.69 1.22×10-2 ⬇
阿洛糖 203.05 6038-51-3 C6H12O6 C01487 HMDB0001151 -0.69 1.22×10-2 ⬇
苯并野花椒碱 306.15 198336-58-2 C20H19NO2 HMDB0031930 15.03 4.30×10-7 ⬆
苯丙素类/聚酮类 八氢甲基喹嗪酮 168.14 66835-10-7 C10H17NO HMDB0030371 3.88 3.83×10-2 ⬆
6-脱氧法戈明 132.10 197449-09-5 C6H13NO2 HMDB0036382 3.70 2.41×10-4 ⬆
环匹罗司乙醇胺 208.13 29342-05-0 C12H17NO2 HMDB0015319 3.44 7.28×10-4 ⬆
硫胺素 266.12 59-43-8 C12H17ClN4OS C00378 HMDB0000235 1.28 4.90×10-2 ⬆
胡椒亭碱 312.16 583-34-6 C19H21NO3 HMDB0034371 1.24 6.58×10-5 ⬆
青花椒碱 242.11 149998-56-1 C15H15NO2 HMDB0040380 -3.07 2.95×10-2 ⬇
白芥子碱 310.17 18696-26-9 C16H24NO5+ C00933 HMDB0029379 3.67 5.03×10-3 ⬆
柠檬油素 207.06 487-06-9 C11H10O4 HMDB0032952 2.90 2.50×10-3 ⬆
异丁苯丙酸 207.14 15687-27-1 C13H18O2 C01588 HMDB0001925 2.57 5.40×10-3 ⬆
1-甲氧哌啶 355.15 65428-13-9 C21H22O5 HMDB0029319 2.31 2.45×10-2 ⬆
鼠曲草黄素 315.09 33803-42-8 C17H14O6 HMDB0030544 2.28 1.49×10-2 ⬆
7-甲氧基-4-
甲基香豆素		 191.07 2555-28-4 C11H10O3 2.15 3.76×10-3 ⬆
红车轴草素 301.07 2284-31-3 C16H12O6 C10520 HMDB0030617 2.02 1.43×10-2 ⬆
聚酮化合物 菊苣苷 341.09 531-58-8 C15H16O9 C09206 HMDB0030821 1.96 1.75×10-3 ⬆
沼泽向日葵素 375.11 56003-01-1 C19H18O8 HMDB0033306 1.79 1.82×10-2 ⬆
柚皮素 273.08 480-41-1 C15H12O5 C00509 HMDB0002670 1.77 9.01×10-3 ⬆
柠檬素 347.08 489-33-8 C17H14O8 HMDB0029516 1.52 1.66×10-2 ⬆
肉桂醛 133.06 104-55-2 C9H8O C00903 HMDB0003441 1.22 5.50×10-3 ⬆
秦椒素 197.08 90-24-4 C10H12O4 C10726 HMDB0029645 4.69 1.87×10-2 ⬆
3,5-二甲氧基苯酚 155.07 500-99-2 C8H10O3 HMDB0059966 3.19 1.57×10-3 ⬆
莽草酸酯类 5-羟甲基糠醛 127.04 67-47-0 C6H6O3 C11101 HMDB0034355 0.91 4.32×10-2 ⬆
香柠檬酚 203.03 486-60-2 C11H6O4 C00758 HMDB0013679 3.02 2.48×10-3 ⬆
柑桔黄酮 373.13 481-53-8 C20H20O7 2.93 5.79×10-3 ⬆
萜类化合物 花椒毒醇 203.03 2009-24-7 C11H6O4 C00841 HMDB0029457 2.80 5.04×10-3 ⬆
乙酰丁香油酚 207.10 93-28-7 C12H14O3 2.76 7.61×10-4 ⬆
蜜桔黄素 403.14 478-01-3 C21H22O8 C10112 HMDB0029540 2.48 1.13×10-2 ⬆
橙黄酮 373.13 2306-27-6 C20H20O7 C10186 HMDB0036633 2.24 7.85×10-3 ⬆
七叶苷 341.09 531-75-9 C15H16O9 C09264 HMDB0030820 1.96 1.75×10-3 ⬆
7-甲氧基香豆素 177.05 531-59-9 C10H8O3 C09268 HMDB0029758 1.78 7.02×10-3 ⬆
高藜芦酸 179.07 93-40-3 C10H12O4 HMDB0000434 -0.98 4.39×10-2 ⬇
香桧烯 137.13 3387-41-5 C10H16 1.19 2.51×10-2 ⬆
), ArticleFig(id=1177619630039385018, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153429494569361927, language=CN, label=表1, caption=

正负离子模式下共有显著差异代谢化合物分析

, figureFileSmall=null, figureFileBig=null, tableContent=
种类 物质中文名称 m/z CAS号 化学分子式 KEGG HMDB log2(FC) 显著性 调控
生物碱 7-羟基鸟氨酸 415.22 174418-82-7 C23H30N2O5 3.78 2.09×10-3 ⬆
原阿片碱 354.13 130-86-9 C20H19NO5 C05189 HMDB0003920 3.55 1.44×10-3 ⬆
天芥菜碱 314.20 303-33-3 C16H27NO5 3.54 9.42×10-3 ⬆
苯乙胺 122.10 64-04-0 C8H11N 2.91 3.44×10-3 ⬆
核黄素 377.15 83-88-5 C17H20N4O6 C00255 HMDB0000244 2.74 7.29×10-4 ⬆
肉叶芸香碱 213.10 442-51-3 C13H12N2O C06538 HMDB0030311 2.22 8.42×10-4 ⬆
烟酰胺 123.06 98-92-0 C6H6N2O C00153 HMDB0001406 1.32 1.78×10-2 ⬆
鸟嘌呤 152.06 73-40-5 C5H5N5O C00242 HMDB0000132 1.21 6.58×10-3 ⬆
脱硫生物素 197.13 533-48-2 C10H18N2O3 C01909 HMDB0003581 -1.09 3.95×10-2 ⬇
番茄素 1072.49 17406-45-0 C50H83NO21 C10827 HMDB0034103 -12.58 2.41×10-5 ⬇
氨基酸和多肽 γ-谷氨酰苯丙氨酸 295.13 7432-24-8 C14H18N2O5 HMDB0000594 4.64 6.55×10-4 ⬆
亮氨酰苯丙氨酸 279.17 56217-82-4 C15H22N2O3 HMDB0013243 3.47 7.16×10-3 ⬆
色氨酸 205.10 73-22-3 C11H12N2O2 C00078 HMDB0030396 3.25 1.74×10-3 ⬆
正亮氨酸 132.10 104809-14-5 C10H19N3O3S C01933 HMDB0251526 2.68 1.45×10-4 ⬆
亮氨酸 132.10 61-90-5 C6H13NO2 C00123 HMDB0062203 2.68 1.45×10-4 ⬆
苯丙氨酸 166.09 63-91-2 C9H11NO2 C00079 HMDB0000159 2.54 1.07×10-3 ⬆
香兰素胺 154.09 1196-92-5 C8H11NO2 C16666 HMDB0012309 0.98 9.77×10-3 ⬆
4-硝基苯酚 140.03 100-02-7 C6H5NO3 C00870 HMDB0001232 -0.98 4.01×10-3 ⬇
碳水化合物 木糖 133.05 58-86-6 C5H10O5 C00181 HMDB0060254 14.78 2.21×10-5 ⬆
阿拉伯糖 133.05 10323-20-3 C5H10O5 C11476 HMDB0000646 14.78 2.21×10-5 ⬆
松三糖 505.18 597-12-6 C18H32O16 6.15 3.21×10-3 ⬆
葡萄糖 203.05 492-62-6 C6H12O6 C00267 HMDB0003345 -0.69 1.22×10-2 ⬇
果糖 203.05 53188-23-1 C6H12O6 C02336 HMDB0000660 -0.69 1.22×10-2 ⬇
塔格糖 203.05 87-81-0 C6H12O6 C00795 HMDB0003418 -0.69 1.22×10-2 ⬇
脂肪酸 δ-癸内酯 171.14 705-86-2 C10H18O2 HMDB0037116 3.01 2.55×10-3 ⬆
双乙酰 87.04 431-03-8 C4H6O2 C00741 HMDB0003407 2.77 2.53×10-3 ⬆
N-酰基乙醇胺(18:1) 326.30 111-58-0 C20H39NO2 C20792 HMDB0002088 1.79 2.02×10-2 ⬆
木脂素 (+)-辛夷脂素 371.15 68296-27-5 C21H22O6 HMDB0038236 2.46 1.57×10-2 ⬆
愈创木脂素 329.18 36531-08-5 C20H24O4 HMDB0034178 2.04 6.34×10-3 ⬆
脂质/类脂分子 庚酸 187.11 111-14-8 C7H14O2 C17714 HMDB0000666 5.29 5.90×10-5 ⬆
莪术醇 235.17 19431-84-6 C15H22O2 C16942 HMDB0033960 3.70 1.46×10-3 ⬆
木香烃内酯 233.16 553-21-9 C15H20O2 HMDB0036688 3.30 9.14×10-4 ⬆
苦木素 406.22 76-78-8 C22H28O6 HMDB0036587 3.26 6.47×10-3 ⬆
姜黄新酮 219.17 87440-60-6 C15H22O HMDB0037068 2.83 5.63×10-4 ⬆
前花椒酚 315.20 119817-27-5 C20H26O3 HMDB0034712 1.29 2.78×10-2 ⬆
有机酸及其衍生物 N-(5-甲基-3-氧代己基)丙氨酸 265.15 3918-92-1 C14H20N2O3 HMDB0029134 3.59 2.83×10-3 ⬆
异亮氨酸 132.10 443-79-8 C6H13NO2 C16434 HMDB0033923 2.68 1.45×10-4 ⬆
甜菜碱 118.09 107-43-7 C5H11NO2 C00719 HMDB0000043 2.59 6.05×10-5 ⬆
水苏碱 144.10 4136-37-2 C7H14ClNO2 C10172 HMDB0004827 2.33 1.80×10-4 ⬆
N-酰基乙醇胺(16:0) 300.29 544-31-0 C18H37NO2 C16512 HMDB0002100 1.65 1.34×10-2 ⬆
环己胺 100.11 108-91-8 C6H13N C00571 HMDB0031404 3.57 9.10×10-4 ⬆
含氮有机化合物 铃兰毒原苷 713.34 13473-51-3 C35H52O15 HMDB0034195 1.73 1.71×10-2 ⬆
胆碱 104.11 62-49-7 C5H14NO+ C00114 HMDB0000097 1.38 6.24×10-3 ⬆
戊二醛 118.09 111-30-8 C5H8O2 C12518 HMDB0029599 2.79 8.44×10-3 ⬆
苯丙素类/聚酮类 山梨糖 203.05 87-79-6 C6H12O6 C00247 HMDB0246950 -0.69 1.22×10-2 ⬇
半乳糖 203.05 59-23-4(D) C6H12O6 C00984 HMDB0000143 -0.69 1.22×10-2 ⬇
阿洛糖 203.05 6038-51-3 C6H12O6 C01487 HMDB0001151 -0.69 1.22×10-2 ⬇
苯并野花椒碱 306.15 198336-58-2 C20H19NO2 HMDB0031930 15.03 4.30×10-7 ⬆
苯丙素类/聚酮类 八氢甲基喹嗪酮 168.14 66835-10-7 C10H17NO HMDB0030371 3.88 3.83×10-2 ⬆
6-脱氧法戈明 132.10 197449-09-5 C6H13NO2 HMDB0036382 3.70 2.41×10-4 ⬆
环匹罗司乙醇胺 208.13 29342-05-0 C12H17NO2 HMDB0015319 3.44 7.28×10-4 ⬆
硫胺素 266.12 59-43-8 C12H17ClN4OS C00378 HMDB0000235 1.28 4.90×10-2 ⬆
胡椒亭碱 312.16 583-34-6 C19H21NO3 HMDB0034371 1.24 6.58×10-5 ⬆
青花椒碱 242.11 149998-56-1 C15H15NO2 HMDB0040380 -3.07 2.95×10-2 ⬇
白芥子碱 310.17 18696-26-9 C16H24NO5+ C00933 HMDB0029379 3.67 5.03×10-3 ⬆
柠檬油素 207.06 487-06-9 C11H10O4 HMDB0032952 2.90 2.50×10-3 ⬆
异丁苯丙酸 207.14 15687-27-1 C13H18O2 C01588 HMDB0001925 2.57 5.40×10-3 ⬆
1-甲氧哌啶 355.15 65428-13-9 C21H22O5 HMDB0029319 2.31 2.45×10-2 ⬆
鼠曲草黄素 315.09 33803-42-8 C17H14O6 HMDB0030544 2.28 1.49×10-2 ⬆
7-甲氧基-4-
甲基香豆素		 191.07 2555-28-4 C11H10O3 2.15 3.76×10-3 ⬆
红车轴草素 301.07 2284-31-3 C16H12O6 C10520 HMDB0030617 2.02 1.43×10-2 ⬆
聚酮化合物 菊苣苷 341.09 531-58-8 C15H16O9 C09206 HMDB0030821 1.96 1.75×10-3 ⬆
沼泽向日葵素 375.11 56003-01-1 C19H18O8 HMDB0033306 1.79 1.82×10-2 ⬆
柚皮素 273.08 480-41-1 C15H12O5 C00509 HMDB0002670 1.77 9.01×10-3 ⬆
柠檬素 347.08 489-33-8 C17H14O8 HMDB0029516 1.52 1.66×10-2 ⬆
肉桂醛 133.06 104-55-2 C9H8O C00903 HMDB0003441 1.22 5.50×10-3 ⬆
秦椒素 197.08 90-24-4 C10H12O4 C10726 HMDB0029645 4.69 1.87×10-2 ⬆
3,5-二甲氧基苯酚 155.07 500-99-2 C8H10O3 HMDB0059966 3.19 1.57×10-3 ⬆
莽草酸酯类 5-羟甲基糠醛 127.04 67-47-0 C6H6O3 C11101 HMDB0034355 0.91 4.32×10-2 ⬆
香柠檬酚 203.03 486-60-2 C11H6O4 C00758 HMDB0013679 3.02 2.48×10-3 ⬆
柑桔黄酮 373.13 481-53-8 C20H20O7 2.93 5.79×10-3 ⬆
萜类化合物 花椒毒醇 203.03 2009-24-7 C11H6O4 C00841 HMDB0029457 2.80 5.04×10-3 ⬆
乙酰丁香油酚 207.10 93-28-7 C12H14O3 2.76 7.61×10-4 ⬆
蜜桔黄素 403.14 478-01-3 C21H22O8 C10112 HMDB0029540 2.48 1.13×10-2 ⬆
橙黄酮 373.13 2306-27-6 C20H20O7 C10186 HMDB0036633 2.24 7.85×10-3 ⬆
七叶苷 341.09 531-75-9 C15H16O9 C09264 HMDB0030820 1.96 1.75×10-3 ⬆
7-甲氧基香豆素 177.05 531-59-9 C10H8O3 C09268 HMDB0029758 1.78 7.02×10-3 ⬆
高藜芦酸 179.07 93-40-3 C10H12O4 HMDB0000434 -0.98 4.39×10-2 ⬇
香桧烯 137.13 3387-41-5 C10H16 1.19 2.51×10-2 ⬆
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基于非靶向代谢组学的葵花盘物质提取溶剂效应差异分析
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钟姝凝 1 , 李佳宁 1 , 唐开红 2 , 刘桐汐 1 , 张远东 1 , 张园园 1, *
食品安全质量检测学报 | 本期专题：功能性食品与功能性成分 2025,16(5): 76-85
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食品安全质量检测学报 | 本期专题：功能性食品与功能性成分 2025, 16(5): 76-85
基于非靶向代谢组学的葵花盘物质提取溶剂效应差异分析
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钟姝凝1 , 李佳宁1, 唐开红2, 刘桐汐1, 张远东1, 张园园1, *
作者信息
  • 1.吉林工商学院粮食学院, 长春 130507
  • 2.长春市疾病预防控制中心理化检验所, 长春 130119

    • 钟姝凝(1993—), 女, 博士, 讲师, 主要研究方向为食品生物技术。E-mail:

通讯作者:

* 张园园(1983—), 女, 副教授, 主要研究方向为功能性食品加工技术。E-mail:
Analysis of solvent effects differences in extracting substances from flower disc of Helianthus annuus L. using non-targeted metabolomics
Shu-Ning ZHONG1 , Jia-Ning LI1, Kai-Hong TANG2, Tong-Xi LIU1, Yuan-Dong ZHANG1, Yuan-Yuan ZHANG1, *
Affiliations
  • 1. College of Grain Science and Technology, Jilin Business and Technology College, Changchun 130507, China
  • 2. Physical and Chemical Testing Institute of Changchun Center for Disease Control and Prevention, Changchun 130119, China
出版时间: 2025-03-15 doi: 10.19812/j.cnki.jfsq11-5956/ts.20241209003
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摘要
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目的 基于非靶向代谢组学技术, 开展葵花盘物质提取溶剂效应差异分析, 探究不同溶剂提取对葵花盘代谢物质组成的影响。方法 运用液相色谱-质谱法(liquid chromatography-mass spectrometer, LC-MS)结合非靶向代谢组学, 对数据进行预处理和统计分析。结果 脂质和类脂分子代谢物数量占比最大(21.5%), 其次是莽草酸和苯丙酸代谢物(13.4%)以及有机杂环化合物代谢物(11.1%)。进一步鉴定出8407种上调和1054种下调代谢物质, 揭示了不同提取方法导致的显著代谢物组成差异。两种溶剂提取方式下的主要差异代谢物涵盖脂质、莽草酸和苯丙酸、萜类化合物等, 涉及96条代谢途径, 其中20条途径有显著差异。基于差异倍数(fold change, FC), 以log2(FC)>0.6或-0.2<log2(FC)<0, P<0.05为标准筛选醇提和水提的显著差异代谢物, 仅有11个物质的log2(FC)值小于1, 表明醇提方式显著增加了葵花盘中提取出的生物活性成分的含量。结论 本研究方法简单可靠, 证实了非靶向代谢组学分析对葵花盘溶剂效应差异研究的重要意义, 为葵花盘产品分析提供了新途径, 研究结果为后续保健食品和药品开发提供了理论依据。

葵花盘  /  非靶向代谢组学  /  提取方式  /  差异代谢物

Objective To investigate the solvent effect differences in the extraction of substances from flower discs of Helianthus annuus L. using non-targeted metabolomics technology, and to explore the impact of different solvent extraction methods on the metabolic composition of flower disc of Helianthus annuus L.. Methods Liquid chromatography-mass spectrometer (LC-MS) combined with non-targeted metabolomics was utilized to preprocess and statistically analyze the data. Results The study revealed that lipids and lipid-like molecules constituted the largest proportion of metabolites (21.5%), followed by shikimate and phenylpropanoid metabolites (13.4%), and organic heterocyclic compound metabolites (11.1%). Further identification led to the discovery of 8407 kinds of up-regulated and 1054 kinds of down-regulated metabolites, highlighting significant differences in metabolite composition resulting from various extraction methods. The main differential metabolites between the 2 kinds of solvent extraction methods encompassed lipids, shikimate and phenylpropanoids, terpenoids, etc., involving 96 metabolic pathways, with 20 pathways exhibiting significant differences. Based on fold change (FC), using criteria of log2(FC)>0.6 or -0.2<log2(FC)<0, and P<0.05 to screen for significantly differential metabolites between alcohol and water extracts, only 11 substances had a log2(FC) value less than 1, indicating that alcohol extraction significantly increased the content of bioactive components extracted from the flower disc of Helianthus annuus L.. Conclusion The research method is simple and reliable, confirming the importance of non-targeted metabolomics analysis in studying solvent effect differences in flower disc of Helianthus annuus L.. It provides a novel approach for the analysis of flower disc of Helianthus annuus L. products and offers theoretical support for the subsequent development of health foods and pharmaceuticals.

flower disc of Helianthus annuus L.  /  non-targeted metabolomics  /  extraction methods  /  differential metabolites
钟姝凝, 李佳宁, 唐开红, 刘桐汐, 张远东, 张园园. 基于非靶向代谢组学的葵花盘物质提取溶剂效应差异分析. 食品安全质量检测学报, 2025 , 16 (5) : 76 -85 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20241209003
Shu-Ning ZHONG, Jia-Ning LI, Kai-Hong TANG, Tong-Xi LIU, Yuan-Dong ZHANG, Yuan-Yuan ZHANG. Analysis of solvent effects differences in extracting substances from flower disc of Helianthus annuus L. using non-targeted metabolomics[J]. Journal of Food Safety & Quality, 2025 , 16 (5) : 76 -85 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20241209003
正文
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0 引言
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向日葵(Helianthus annuus L.), 别名朝阳花, 系桔梗目菊科向日葵属植物, 作为全球第4大油料作物, 广泛用于观赏、药用以及油料生产[1]。其耐盐碱、抗旱性强, 全球种植面积广, 我国是主要种植国之一, 尤以油用葵和食用葵杂交品种为主, 但其副产物如葵花盘、秸秆等利用率低, 多作饲料或废弃处理, 资源浪费且附加值低[2]。葵花盘实际上富含挥发油、果胶[3]、黄酮[4]等活性成分, 具有抗菌、抗氧化、降血糖及抗肿瘤等药理潜力, 因此亟待深入研究与开发。吉林省食品安全地方标准已明确了食用葵花盘的安全性, 为葵花盘作为食品成分的应用提供了规范指导, 进一步凸显了其开发价值。
尽管葵花盘具有丰富的活性成分和潜在的药理作用, 但当前针对葵花盘提取物的研究多集中于基于色谱、质谱技术的成分鉴定, 缺乏系统性的组学研究。特别是非靶向代谢组学[5], 其在发现新代谢产物[6]及路径上的独特优势[7]尚未在葵花盘的研究中得到充分利用。
为了更全面地挖掘葵花盘的活性成分和潜在价值, 本研究创新性地采用液相色谱-质谱法(liquid chromatography-mass spectrometer, LC-MS)非靶向代谢组学技术, 对比分析醇提与水提两种提取方式下葵花提取物中代谢物的种类和含量。这一技术手段的应用, 将为葵花盘天然产物的深度开发提供理论依据和技术支持, 有助于揭示葵花盘在不同提取条件下的代谢物变化特征。
本研究以植物天然小分子库为基础, 聚焦于葵花盘这一富含活性成分的天然资源。通过水提/醇提法保留葵花盘的活性物质完整性, 制备得到葵花盘乙醇提取物(ethanol extraction, EE)和水提物(water extraction, WE)。利用LC-MS技术, 深入探讨葵花盘提取及加工过程中内含活性成分的变化, 挖掘代谢物变化的特征, 探索葵花盘独特功能成分和潜在保健作用的形成机制。
通过代谢组学的先进分析技术, 对EE和WE中的天然产物组分进行鉴定与分类统计, 为细胞及分子水平的靶向研究提供物质基础。本研究期望为葵花盘提取技术优化、产品品质提升以及功能性成分富集提供参考, 并为开发如新型抗高尿酸血症天然药物等提供理论依据, 从而拓展葵花盘在医药、保健品、功能食品等领域的应用前景, 实现资源的高效利用。
1 材料与方法
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1.1 材料与试剂
葵花盘(陕西慧科植物开发有限公司)。
甲醇、乙腈、异丙醇(色谱纯, 德国CNW Technologies公司); 超纯水(广州屈臣氏有限公司); 乙酸(色谱纯, 美国SIGMA-ALDRICH公司)。
1.2 仪器与设备
Vanquish超高效液相色谱仪、Orbitrap Exploris 120高分辨质谱仪、Phenomenex Kinetex C18液相色谱柱(2.1 mm× 50 mm, 2.6 μm)(美国菲诺门克斯公司); Heraeus Fresco17离心机(美国Thermo Fisher Scientific公司); BSA124S-CW万分之一电子天平(德国Sartorius公司); 超声仪PS-60AL(深圳市雷德邦电子有限公司); JXFSTPRP-24匀浆机(上海净信科技有限公司); LGJ-10C冷冻干燥机(四环福瑞科仪科技发展有限公司)。
1.3 实验方法
1.3.1 葵花盘提取物制备与初步分离
称取25 kg葵花盘, 粉碎后过40目筛, 分批按照料液比1:10 (kg/L)加入体积分数75%的乙醇, 置于100 L萃取罐中, 60 ℃条件下搅拌提取3 h, 过滤, 取滤液减压浓缩[8]。滤渣在上述条件(60 ℃、3 h)重复提取2次, 合并减压浓缩, 得到EE, 于-20 ℃条件下保存备用。葵花盘醇提后滤渣中加入100 L去离子水, 并于60 ℃条件下搅拌提取3 h, 重复提取2次, 过滤取滤液减压浓缩, 得到WE, 旋转蒸发后干燥冷冻保存备用[9]。
1.3.2 葵花盘活性成分/代谢物提取
移取100 μL待测样品至无菌EP管中, 加入400 μL预混提取液(甲醇与乙腈按体积比1:1配制, 并预先掺入同位素标记内标以确保检测准确性)[10]。涡旋混合30 s, 冰水浴条件下超声处理10 min以促进目标物释放。-40 ℃下静置1 h后将样品置于离心机中, 于4 ℃条件下以12000 r/min(离心力13800×g, 转子半径8.6 cm)离心15 min, 分离出上清液, 并转移至进样瓶中, 准备进行后续的仪器检测分析。
1.3.3 上机检测
针对非极性代谢物本项目使用Vanquish超高效液相色谱仪, 通过Phenomenex Kinetex C18 (2.1 mm×50 mm, 2.6 μm)液相色谱柱对目标化合物进行色谱分离。液相色谱A相为水相, 含0.01%乙酸, B相为异丙醇:乙腈(1:1, V:V); 检测波长为510 nm; 样品盘温度: 4 ℃; 进样体积: 2 μL。Orbitrap Exploris 120质谱仪能够在控制软件(Xcalibur, 版本: 4.4)控制下进行一级、二级质谱数据采集。详细参数如下: 载气流量: 50 Arb, 辅助气流量: 15 Arb, 毛细管温度: 320 ℃, 全扫描质谱分辨率: 60000, 串联质谱分辨率: 15000, 碰撞能量: SNCE 20/30/40, 喷雾电压: 3.8 kV(正模式)或-3.4 kV (负模式)。
1.3.4 代谢物分析
项目采用本地自建数据库和公共库搜库[HumanMetabolome Database (HMDB)、massbank (http://www.massbank.jp/)、mzclound (https://www.mzcloud.org)]。在本研究中, 通过将生物样本中的代谢物与数据库中记录的保留时间、分子质量(质量误差控制在<10 ppm)、二级碎裂谱图及碰撞能等特征参数进行匹配, 完成代谢物的结构鉴定[11]。为了确保鉴定结果的准确性和可靠性, 所有鉴定结果均经过严格的人工二次核对与确认, 所有代谢物的鉴定等级均达到了Level 2及以上的标准要求。
1.3.5 两两比较差异分析
单元统计分析: 两组样本间的差异分析时, 使用差异倍数(fold change, FC)分析、T检验/非参检验等单元统计分析方法, 并默认分析使用FC分析与T检验来计算P, 并对样本进行差异性统计分析。基于单元统计分析, 对正、负离子模式下检测到的所有代谢物(含未被鉴定的代谢物)进行差异分析, 筛选出P小于0.05的差异代谢物, 通过火山图直观体现代谢物的显著性和FC。
多元统计主成分分析(principal component analysis, PCA): 代谢物变量按一定的权重通过线性组合后产生新的特征变量, 通过主要新变量对各组数据进行归类, 去除重复性差的离群样本和异常样本。通过计算的数学模型, 将各个样本在各个主成分的得分制作成PCA得分图, 通过样本的聚集、离散程度, 直观反映各个样本在数学模型空间中的分布情况[12]。
多元统计正交-偏最小二乘判别分析(orthogonal- partial least squares discriminant analysis, OPLS-DA): 在多元统计PCA分析的基础上对样本进行指定并分组, 模型自动引入一个隐含的数据集Y, 该隐含数据集中的变量数量等于组别的数量, 用于进一步描述各分组间的潜在关联或差异[13]。
差异物质富集分析: 以京都基因与基因组百科全书(kyoto encyclopedia of genes and genomes pathways, KEGG)通路为单位, 基于葵花盘及其近缘物种参与的代谢通路, 通过Fisher精确检验对各通路中代谢物的富集情况进行显著性分析。通过计算每条通路的P, 评估其差异性, P越小, 表明该通路的差异显著性越高。采用错误发现率(false discovery rate, FDR)校正(取值范围0~1), FDR值越接近0, 富集显著性越强。选择FDR值最小的前20条KEGG通路进行气泡图展示。
1.4 数据处理
所有数据以平均值±标准偏差(n=3)表示。使用SPSS 25.0软件中的单因素方差进行差异显著性统计分析(P<0.05为差异显著), 使用GraphPad Prism 8软件对数据进行计算和绘图。
2 结果与分析
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2.1 质量控制质谱峰图对比
将质量控制(quality control, QC)样本的总离子流(total ion chromatogram, TIC)图进行谱图叠加对比分析, 图1展示的是两种不同提取溶剂——乙醇和水应用于提取葵花盘代谢产物所得到的结果。在图1中, EE、WE分别代表了乙醇提取和水提取后葵花盘代谢产物的实验数据谱图, 而每组实验均包含了3次平行的重复测试, 以确保数据的可靠性和准确性, 平行实验的结果用不同的颜色进行区分, 以便于视觉上的辨识和分析。如图1所示, 无论是乙醇提取组还是水提取组, 各色谱峰的响应强度与保留时间都呈现出高度的一致性, 几乎完全重叠。结果证明在整个实验流程中, 由仪器误差所导致的变异被控制在了一个极小的水平, 从而确保了实验数据的准确性和可比性[14]。
2.2 代谢物鉴定分析
通过超高效液相色谱仪(ultra performance liquid chromatograph, UPLC)检测WE与EE的所有代谢产物, 与公共数据库(HMDB、KEGG、Metlin、massbank、mzclound)中代谢物的保留时间、分子质量(分子质量误差在<10 ppm内)、二级碎裂谱图、碰撞能等信息进行匹配[15], 共鉴定到787个代谢物, 其中注释到HMDB数据库中的代谢物共281个, 注释到KEGG数据库中的代谢物共205个。各类代谢物数量所占比例如图2所示, 其中脂质和类脂分子(21.5%)、莽草酸和苯丙酸(13.4%)、有机杂环化合物(11.1%)、生物碱(10.2%)等4类物质占比较大, 共占比56.2%。
2.3 差异代谢物分析
2.3.1 多元统计PCA分析与OPLS-DA分析
PCA将WE与EE代谢物变量通过线性组合产生新的特征变量, 掌握数据的整体情况。参考R2X(模型的可解释度)进行模型的交叉验证, R2X为0.773, 高于0.5, 表明该模型可靠。图3中点表示各组内生物学重复, 同一颜色点为组间样本点, 分布较集中, 表明样本中所含分子的组成和浓度接近[16]。不同颜色点的分布状态可明显区分两组样本, 说明WE与EE的代谢物存在一定的差异, 可对样本数据进行下一步分析研究。
OPLS-DA在不降低模型预测能力的前提下, 有效减少模型的复杂性, 能够最大程度查看组间差异[17]。样本经OPLS-DA分析, R2X为0.825, R2Y为1.000, Q2为0.987, 均大于0.5, 表明该模型可靠, 不存在过度拟合现象, 可进行后续差异代谢物的筛选及分析。
2.3.2 单变量统计分析
基于单元统计分析, 对正、负离子模式下检测到的所有EE与WE的代谢物(含未被鉴定的代谢物)进行差异分析。P小于0.05的差异代谢物, 通过火山图直观体现代谢物的显著性和FC, 详见图4。以log2(FC)>1或log2(FC)<1, P<0.05的筛选标准[18], 对WE和EE显著差异代谢物进行筛查, 共有8407个上调差异代谢物, 1054个下调差异代谢物, 4890个非显著差异代谢物, 两个样本数据差异显著。
2.3.3 差异代谢物筛选及分析
以log2(FC)>0.6或-0.2<log2(FC)<0, P<0.05的筛选标准, 对WE和EE显著差异代谢物进行筛选。结合KEGG、HMDB、PUBCHEM等在线数据库, 通过化合物m/z和保留时间进行代谢物的鉴定, 从两种提取方式的样品种共筛选出15大类96种差异代谢物, 物质具体信息可通过CAS号在PUBCHEM网站中进行查询, 部分结果如表1所示。差异代谢物主要为莽草酸酯类和苯丙素类化合物、萜类化合物、苯丙素类和聚酮类化合物、生物碱、脂质和类脂分子, 其中部分物质如甲苯、胆碱、甜菜碱, 与赖薪宇等[19]葵花盘活性成分一致, 在此基础上有多种新物质被检出。
2.3.4 差异物质聚类分析
为直观观察不同提取方法差异代谢物的浓度变化趋势, 以WE和EE代谢物的相对值为代谢水平, 做差异代谢物相对含量变化热图并进行聚类分析。图5中每一列代表一个样本, 每一行代表一个代谢物, WE与EE各取3组样本, 取其FC值最高的35个物质进行比较分析。颜色用以指示代谢物的相对含量, 蓝色色调的加深意味着代谢物含量趋低, 而红色色调的加深则表明代谢物含量趋高。由于葵花盘中含有的物质大多为醇溶性物质, WE中代谢物含量明显较低, 与EE代谢物有明显区分。其中EE组相对含量较高的15种代谢物有套索酮醇、去甲氧基淫羊藿苷、庚酸、醋酸瑞香素、N1-(5-磷酸-α-D-核糖基)-5,6-二甲基苯并咪唑、咖啡酰腐胺、5-苯并呋喃丙酸、6-(β-D-葡糖基)-7-甲氧基-、苍术酮、交链孢菌酚、paleatin A、annoglabasin_C、(2S,3R,4S,5S,6R)-2-[4-(2-羟乙基)苯氧基]-6-(羟甲基)氧杂环-3,4,5-三醇、(+)-麦由酮、3,5,8-巨豆三烯-7-酮6-磷。上述化合物为有机杂环化合物, 萜类化合物和生物碱类物质, 对其中典型物质进行分析, 发现差异性物质产生的原因与葵花盘提取方式有关。葵花盘中富含多种生物活性成分, 其提取方式的不同直接导致代表性成分的差异。这一差异主要源于提取过程中溶剂选择、温度控制及时间安排的差异, 这些因素显著影响成分的溶解度和活性。具体而言, 溶剂类型决定成分溶解度, 而温度和时间则影响成分的稳定性和提取效率。综合考虑多重因素以高效提取并保持成分活性, 不仅能提升资源利用, 还能为开发功能性食品或药物提供科学支撑。
葵花盘提取物中含有苍术酮, 这是一种具降脂、抗菌、抗炎[20]及抗病毒活性的倍半萜类化合物[21], 对抗甲型流感病毒有效, 能减轻肺损伤、降低炎症因子并提升干扰素-β水平[22]。生物碱是一类碱性有机化合物, 研究表明, 其具有抗氧化、抗肿瘤、治疗痛风等功效。葵花盘中的生物碱如原阿片碱、天芥菜碱、去甲替林, 在药品中具有良好的前景。其中, 去氢吴茱萸碱作为一种喹唑啉类生物碱, 最早分离自中药吴茱萸, 具抗肿瘤、抗心律失常等多药理活性, 尤其抗阿尔茨海默病效果显著[23]。葵花盘提取物中碳水化合物类差异代谢物大多数为多糖, 木糖、阿拉伯糖等功能性糖类, 且代谢物含量相差较大。L-阿拉伯糖能减缓蔗糖吸收, 控制血糖上升[24], 减少体内新脂肪形成[25]。木糖是一种无热量甜味剂, 广泛存在于植物中, 能改善口感, 促进肠道健康, 防龋齿, 适合肥胖及糖尿病患者。木糖在健康饮食和工业生产中应用前景广阔[26]。没食子酸甲酯是源自植物的多酚化合物, 具有抗氧化、抗菌、抗肿瘤[27]等功效。由此可见, 葵花盘提取物具有开发成具有抗氧化、抗菌抗炎及调节脂类代谢作用的一系列产品的潜能。
2.4 代谢物通路分析
通过分析富集因子、FDR值和富集到代谢途径上的WE和EE代谢产物个数, 得到各物质富集的程度[28]。富集因子指代谢途径中富集到的差异代谢产物个数与注释到的差异代谢产物个数的比值, 该数值越大, 富集的程度越大。FDR一般取值范围为0~1, 越接近于零, 表示富集越显著[29]。
挑选FDR值最小即富集最显著的前20条KEGG通路进行图标绘制, WE和EE关键通路分析如图6所示。每个点代表一个代谢通路, 横坐标是富集到不同代谢通路中的富集因子, 纵坐标是富集通路, 圆点表示通路上对应的代谢分子数目[30]。WE和EE之间筛选出的5条最为显著的具体关键代谢通路的分别为: ABC转运蛋白、氨基糖和核苷酸糖代谢、辅因子的生物合成、半乳糖代谢、甘氨酸、丝氨酸和苏氨酸代谢。其中ABC转运蛋白和氨基糖和核苷酸糖代谢涉及负责包括营养物质、代谢产物、药物以及毒素在内的多种物质的跨膜转运, 气泡相对最大、颜色相对最深, 说明WE与EE两组之间在物质转运和交换上存在显著差异。其他代谢通路表明, 二者酶促反应的效率和方向不同, 并在细胞结构、生长速率或遗传物质稳定性方面、乳糖处理能力或相关疾病易感性及蛋白质合成及能量代谢或抗氧化防御机制上存在差异。
3 结论
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本研究运用LC-MS非靶向代谢组学技术, 系统探究了不同溶剂提取方式对葵花盘代谢物质组成的影响, 共鉴定出8407种上调及1054种下调代谢物质, 证明了提取溶剂选择对葵花盘代谢物谱的显著调制作用。该方法简便、快捷且可靠, 为葵花盘非挥发性成分的差异解析开辟了新路径, 丰富了其物质基础数据。非靶向代谢组学的应用展现了在全面深挖葵花盘活性成分方面的独特优势, 并为后续针对关键核心物质进行靶向分析提供基础。通过HMDB和KEGG数据库的解析, 识别了281种关键代谢物, 涵盖脂质、莽草酸、萜类、有机杂环化合物及生物碱等, 这些代谢物涉及96条代谢途径, 其中20条途径呈现显著性差异, 为阐释葵花盘的生物活性提供了宝贵信息。进一步依托PLS-DA模型筛选出80种关键代谢物, 并通过对典型物质的深入分析, 发现醇提法提取的溶液代谢物含量高于水提法, 预示着其在增强葵花盘抗氧化、降尿酸、抗炎等生理功效方面的潜力。综上, 本研究不仅揭示了葵花盘代谢物组成的多样性和提取方法产生的差异影响, 还指明了未来研究方向——即深入探索葵花盘提取物在医药、保健品及功能食品领域的应用潜力, 明确物质基础及作用机理, 以期为其产品开发的前景奠定科学基础。
基金
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  • 吉林省科技厅人才专项(20220508060RC)
  • 2024年吉林省大学生创新创业训练计划项目(202411261004)
文献
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20241209003
  • 接收时间：2024-12-09
  • 首发时间：2025-07-19
  • 出版时间：2025-03-15
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  • 收稿日期：2024-12-09
基金
吉林省科技厅人才专项(20220508060RC)
2024年吉林省大学生创新创业训练计划项目(202411261004)
作者信息
    1.吉林工商学院粮食学院, 长春 130507
    2.长春市疾病预防控制中心理化检验所, 长春 130119

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* 张园园(1983—), 女, 副教授, 主要研究方向为功能性食品加工技术。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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