Article(id=1153986646123991573, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153986642063905290, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20241023005, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1729612800000, receivedDateStr=2024-10-23, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1753061456470, onlineDateStr=2025-07-21, pubDate=1739548800000, pubDateStr=2025-02-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1753061456470, onlineIssueDateStr=2025-07-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1753061456470, creator=13701087609, updateTime=1753061456470, updator=13701087609, issue=Issue{id=1153986642063905290, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='3', pageStart='1', pageEnd='316', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1753061455502, creator=13701087609, updateTime=1760070725729, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1183385652272968023, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153986642063905290, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1183385652272968024, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1153986642063905290, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=17, endPage=24, ext={EN=ArticleExt(id=1153986646501478936, articleId=1153986646123991573, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Establishment of an on-site rapid detection system for the risk of deoxynivalenol contamination, columnId=1151895321526759957, journalTitle=Journal of Food Safety & Quality, columnName=Special Topic: Detection and Prevention and Control of Biotoxins in Food, runingTitle=null, highlight=null, articleAbstract=

Objective To establish an on-site rapid detection system for the risk of deoxynivalenol (DON) contamination based on multienzyme isothermal rapid amplification (MIRA) technology. Methods Highly homologous sequences of Tri toxin-producing gene clusters from the major DON-producing Fusarium species (including Fusarium graminearum, Fusarium asiaticum, Fusarium pseudograminearum and Fusarium culmorum) in China were obtained through gene sequence query and comparison by the National Centre for Biotechnology Information (NCBI) of the United States of America. By designing specific fluorescent probes and screening primers, a MIRA detection method for DON-producing Fusarium was established, and an on-site rapid detection system was constructed by combining the rapid paper-based DNA extraction technique. Results The limit of detection of this assay system was 1.95×101 copies/μL for plasmid templates and 15 fg/μL for genomic DNA. The results of 27 positive wheat samples at the filling stage (spike) showed a highly significant correlation with those of the quantitative real-time polymerase chain reaction (qPCR) method (r=0.820, P=0.000). When the MIRA detection threshold line was set at the 43rd scan point (peak onset time of 7 min), the combined discrimination accuracy between high (DON>1000 μg/kg) and low (DON<1000 μg/kg) DON contamination risk for 89 wheat samples was 87.15%. Conclusion The detection system demonstrates speed, economy, practicality, and portability in terms of reagents and instrumentation, and is capable of effectively achieving the objective of rapid on-site detection. This will facilitate early warning of the risk of DON contamination in wheat production in the field, thereby guiding interventions to prevent or minimise losses.

, correspAuthors=Jin YE, 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=Hua CUI, Meng-Ze CHEN, Shu-Qing GAO, Song-Shan WANG, Sen LI, Yu WU, Li LI, Jin YE, Song-Xue WANG), CN=ArticleExt(id=1153986684568982054, articleId=1153986646123991573, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=脱氧雪腐镰刀菌烯醇污染风险现场快速检测系统的建立, columnId=1151895321669366295, journalTitle=食品安全质量检测学报, columnName=本期专题:食品中生物毒素检测与防控, runingTitle=null, highlight=null, articleAbstract=

目的 建立一种基于多酶恒温核酸快速扩增(multienzyme isothermal rapid amplification, MIRA)技术的脱氧雪腐镰刀菌烯醇(deoxynivalenol, DON)污染风险现场快速检测系统。方法 通过美国国家生物技术信息中心(National Center for Biotechnology Information, NCBI)基因序列查询比对, 获取了我国主要产DON镰刀菌(包括禾谷镰刀菌、亚洲镰刀菌、假禾谷镰刀菌和黄色镰刀菌)的Tri产毒基因簇高度同源序列, 设计特异性荧光探针并筛选引物, 建立了产DON镰刀菌的MIRA快速检测方法, 同时结合纸基DNA快速提取技术, 构建了一套现场快速检测系统。结果 该检测系统对质粒模版的检出限为1.95×101 copies/μL, 对基因组DNA的检出限为15 fg/μL, 对小麦灌浆期(穗)部样品的检测结果(共27个阳性)与实时荧光定量聚合酶链式反应技术(quantitative real-time polymerase chain reaction, qPCR)结果高度相关(r=0.820, P=0.000)。将MIRA检测的阈值线设定在第43个扫描点(起峰时间为7 min)时, 对89个小麦样品的高DON污染风险(DON>1000 μg/kg)与低DON污染风险(DON<1000 μg/kg)的综合判别准确率为87.15%。结论 该检测系统快速、经济、实用, 且试剂和仪器便携, 能够有效实现现场快速检测。这将有助于实施田间小麦DON污染风险早期预警, 指导干预, 防止或减少损失。

, correspAuthors=叶金, authorNote=null, correspAuthorsNote=
* 叶金(1988—), 男, 博士, 副研究员, 主要研究方向为粮油质量安全。E-mail:
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崔华(1986—), 女, 硕士, 副研究员, 主要研究方向为粮食质量安全检测。E-mail:

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International Journal of Food Microbiology, 2022, 372: 109682., articleTitle=Development and evaluation of a novel visual and rapid detection assay for toxigenic Fusarium graminearum in maize based on recombinase polymerase amplification and lateral flow analysis, refAbstract=null)], funds=[Fund(id=1183428246042460647, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, awardId=2022YFE0137500, language=CN, fundingSource=国家重点研发计划政府间国际科技创新合作项目(2022YFE0137500), fundOrder=null, country=null), Fund(id=1183428246147318248, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, awardId=ZX2406, language=CN, fundingSource=中央级公益性科研院所基本科研业务费专项资金项目(ZX2406), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1183428241483252079, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, xref=null, ext=[AuthorCompanyExt(id=1183428241491640688, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, companyId=1183428241483252079, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Institute of Grain and Oil Quality and Safety, Academy of National Food and Strategic Reserves Administration, Beijing 102629, China), AuthorCompanyExt(id=1183428241495834993, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, companyId=1183428241483252079, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=国家粮食和物资储备局科学研究院, 粮油质量安全研究所, 北京 102629)])], figs=[ArticleFig(id=1183428244385710535, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, language=EN, label=Fig.1, caption=Schematic diagram of MIRA detection probe sequences and modification sites of DON-producing Fusarium, figureFileSmall=9BnWJBzKjPmwcWVkrVFzow==, figureFileBig=ZY/T61UNJVNRoOu3daTJgQ==, tableContent=null), ArticleFig(id=1183428244457013705, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, language=CN, label=图1, caption=产DON镰刀菌MIRA检测探针序列及修饰位点示意图, figureFileSmall=9BnWJBzKjPmwcWVkrVFzow==, figureFileBig=ZY/T61UNJVNRoOu3daTJgQ==, tableContent=null), ArticleFig(id=1183428244528316875, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, language=EN, label=Fig.2, caption=Schematic diagram of field wheat samples testing, figureFileSmall=3Gwombsm0zDD/oXPOk9BAw==, figureFileBig=8LOksTW8HFurNZ+5jYGREw==, tableContent=null), ArticleFig(id=1183428244670923213, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, language=CN, label=图2, caption=小麦田间样品检测示意图, figureFileSmall=3Gwombsm0zDD/oXPOk9BAw==, figureFileBig=8LOksTW8HFurNZ+5jYGREw==, tableContent=null), ArticleFig(id=1183428244830306767, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, language=EN, label=Fig.3, caption=MIRA primer screening of real-time fluorescent, figureFileSmall=Lejs6IsQbjwgXVUbWqhvdg==, figureFileBig=eqFZ1JO1uxM+96T5bojo/A==, tableContent=null), ArticleFig(id=1183428244922581458, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, language=CN, label=图3, caption=实时荧光MIRA引物筛选

注: A为反向引物筛选; B为正向引物筛选。

, figureFileSmall=Lejs6IsQbjwgXVUbWqhvdg==, figureFileBig=eqFZ1JO1uxM+96T5bojo/A==, tableContent=null), ArticleFig(id=1183428244993884627, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, language=EN, label=Fig.4, caption=Results of the specificity validation of the real-time fluorescence MIRA assay, figureFileSmall=YM82cXYNCepNF3yKRSKMjw==, figureFileBig=0ulEDVykiyPfVrgPsPNsPA==, tableContent=null), ArticleFig(id=1183428245056799188, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, language=CN, label=图4, caption=实时荧光MIRA特异性验证扩增结果, figureFileSmall=YM82cXYNCepNF3yKRSKMjw==, figureFileBig=0ulEDVykiyPfVrgPsPNsPA==, tableContent=null), ArticleFig(id=1183428245136490965, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, language=EN, label=Fig.5, caption=Sensitivity validation results of real-time fluorescence MIRA assay, figureFileSmall=8qRVrxdPbv0/fu6aSDd7bg==, figureFileBig=HefWLpPtgxPDZWK17dv2tg==, tableContent=null), ArticleFig(id=1183428245245542871, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, language=CN, label=图5, caption=实时荧光MIRA灵敏度检测结果

注: A. 质粒检测; B. 基因组DNA检测。

, figureFileSmall=8qRVrxdPbv0/fu6aSDd7bg==, figureFileBig=HefWLpPtgxPDZWK17dv2tg==, tableContent=null), ArticleFig(id=1183428245371371993, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, language=EN, label=Fig.6, caption=Correlation analysis of MIRA and qPCR for detection of wheat samples at the filling stage (spike), figureFileSmall=einmsYH4uNtMrVPrsS7yxA==, figureFileBig=A/pTqFCaFpFbpSt3wnOwlA==, tableContent=null), ArticleFig(id=1183428245467840988, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, language=CN, label=图6, caption=MIRA与qPCR对小麦灌浆期(穗部)样品检测结果相关性分析, figureFileSmall=einmsYH4uNtMrVPrsS7yxA==, figureFileBig=A/pTqFCaFpFbpSt3wnOwlA==, tableContent=null), ArticleFig(id=1183428245564309982, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, language=EN, label=Table 1, caption=

MIRA amplification primer, probes, and fragment sequences

, figureFileSmall=null, figureFileBig=null, tableContent=
名称 序列(5’-3’) 碱基数/
bp
MIRA-Fus-F9 CTGTTGTGCCTCGATCCATCGC
TCAGGCTTGAACT
35
MIRA-Fus-R4 CAGTCCACCTATTTCATGCACA
CCGATCCCAAGA
34
MIRA-Fus-Pro GTTGTGCCTCGATCCATCGCTCA
GGCTTGAACT /i6FAMdT/idSp/iBHQ1dT/CGGGCT
CGGGGAAA/C3-Spacer
51
扩增片段 CTGTTGTGCCTCGATCCATCGCTCA
GGCTTGAACTTTTCGGGCTCGGGGA
AATTCTTGGGATCGGTGTGCATGA
AATAGGTGGACTG
87
), ArticleFig(id=1183428245719499232, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, language=CN, label=表1, caption=

MIRA扩增引物探针及片段序列

, figureFileSmall=null, figureFileBig=null, tableContent=
名称 序列(5’-3’) 碱基数/
bp
MIRA-Fus-F9 CTGTTGTGCCTCGATCCATCGC
TCAGGCTTGAACT
35
MIRA-Fus-R4 CAGTCCACCTATTTCATGCACA
CCGATCCCAAGA
34
MIRA-Fus-Pro GTTGTGCCTCGATCCATCGCTCA
GGCTTGAACT /i6FAMdT/idSp/iBHQ1dT/CGGGCT
CGGGGAAA/C3-Spacer
51
扩增片段 CTGTTGTGCCTCGATCCATCGCTCA
GGCTTGAACTTTTCGGGCTCGGGGA
AATTCTTGGGATCGGTGTGCATGA
AATAGGTGGACTG
87
), ArticleFig(id=1183428245832745442, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, language=EN, label=Table 2, caption=

Risk discrimination of DON contamination by MIRA test in wheat samples at the filling stage (spike)

, figureFileSmall=null, figureFileBig=null, tableContent=
检出性质 检出率/% 风险类型 数量 风险划分阈值线
43 34 32 25
阳性 86.96 高风险
(DON>1000 μg/kg)
样品数量 19
判别准确数量 19 18 16 14
判别准确率/% 100.00 94.74 84.21 73.68
阴性 100.00 低风险
(DON<1000 μg/kg)
样品数量 70
判别准确数量 52 55 53 62
判别准确率/% 74.29 78.57 75.71 88.57
综合判别准确率/% 87.15 86.66 79.96 81.13
), ArticleFig(id=1183428245920825828, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1153986646123991573, language=CN, label=表2, caption=

小麦灌浆期(穗部)样品MIRA检测DON污染风险判别

, figureFileSmall=null, figureFileBig=null, tableContent=
检出性质 检出率/% 风险类型 数量 风险划分阈值线
43 34 32 25
阳性 86.96 高风险
(DON>1000 μg/kg)
样品数量 19
判别准确数量 19 18 16 14
判别准确率/% 100.00 94.74 84.21 73.68
阴性 100.00 低风险
(DON<1000 μg/kg)
样品数量 70
判别准确数量 52 55 53 62
判别准确率/% 74.29 78.57 75.71 88.57
综合判别准确率/% 87.15 86.66 79.96 81.13
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脱氧雪腐镰刀菌烯醇污染风险现场快速检测系统的建立
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崔华 , 陈梦泽 , 高树青 , 王松山 , 李森 , 吴宇 , 李丽 , 叶金 * , 王松雪
食品安全质量检测学报 | 本期专题:食品中生物毒素检测与防控 2025,16(3): 17-24
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食品安全质量检测学报 | 本期专题:食品中生物毒素检测与防控 2025, 16(3): 17-24
脱氧雪腐镰刀菌烯醇污染风险现场快速检测系统的建立
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崔华 , 陈梦泽, 高树青, 王松山, 李森, 吴宇, 李丽, 叶金* , 王松雪
作者信息
  • 国家粮食和物资储备局科学研究院, 粮油质量安全研究所, 北京 102629
  • 崔华(1986—), 女, 硕士, 副研究员, 主要研究方向为粮食质量安全检测。E-mail:

通讯作者:

* 叶金(1988—), 男, 博士, 副研究员, 主要研究方向为粮油质量安全。E-mail:
Establishment of an on-site rapid detection system for the risk of deoxynivalenol contamination
Hua CUI , Meng-Ze CHEN, Shu-Qing GAO, Song-Shan WANG, Sen LI, Yu WU, Li LI, Jin YE* , Song-Xue WANG
Affiliations
  • Institute of Grain and Oil Quality and Safety, Academy of National Food and Strategic Reserves Administration, Beijing 102629, China
出版时间: 2025-02-15 doi: 10.19812/j.cnki.jfsq11-5956/ts.20241023005
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目的 建立一种基于多酶恒温核酸快速扩增(multienzyme isothermal rapid amplification, MIRA)技术的脱氧雪腐镰刀菌烯醇(deoxynivalenol, DON)污染风险现场快速检测系统。方法 通过美国国家生物技术信息中心(National Center for Biotechnology Information, NCBI)基因序列查询比对, 获取了我国主要产DON镰刀菌(包括禾谷镰刀菌、亚洲镰刀菌、假禾谷镰刀菌和黄色镰刀菌)的Tri产毒基因簇高度同源序列, 设计特异性荧光探针并筛选引物, 建立了产DON镰刀菌的MIRA快速检测方法, 同时结合纸基DNA快速提取技术, 构建了一套现场快速检测系统。结果 该检测系统对质粒模版的检出限为1.95×101 copies/μL, 对基因组DNA的检出限为15 fg/μL, 对小麦灌浆期(穗)部样品的检测结果(共27个阳性)与实时荧光定量聚合酶链式反应技术(quantitative real-time polymerase chain reaction, qPCR)结果高度相关(r=0.820, P=0.000)。将MIRA检测的阈值线设定在第43个扫描点(起峰时间为7 min)时, 对89个小麦样品的高DON污染风险(DON>1000 μg/kg)与低DON污染风险(DON<1000 μg/kg)的综合判别准确率为87.15%。结论 该检测系统快速、经济、实用, 且试剂和仪器便携, 能够有效实现现场快速检测。这将有助于实施田间小麦DON污染风险早期预警, 指导干预, 防止或减少损失。

脱氧雪腐镰刀菌烯醇  /  镰刀菌  /  多酶恒温核酸快速扩增技术  /  现场检测

Objective To establish an on-site rapid detection system for the risk of deoxynivalenol (DON) contamination based on multienzyme isothermal rapid amplification (MIRA) technology. Methods Highly homologous sequences of Tri toxin-producing gene clusters from the major DON-producing Fusarium species (including Fusarium graminearum, Fusarium asiaticum, Fusarium pseudograminearum and Fusarium culmorum) in China were obtained through gene sequence query and comparison by the National Centre for Biotechnology Information (NCBI) of the United States of America. By designing specific fluorescent probes and screening primers, a MIRA detection method for DON-producing Fusarium was established, and an on-site rapid detection system was constructed by combining the rapid paper-based DNA extraction technique. Results The limit of detection of this assay system was 1.95×101 copies/μL for plasmid templates and 15 fg/μL for genomic DNA. The results of 27 positive wheat samples at the filling stage (spike) showed a highly significant correlation with those of the quantitative real-time polymerase chain reaction (qPCR) method (r=0.820, P=0.000). When the MIRA detection threshold line was set at the 43rd scan point (peak onset time of 7 min), the combined discrimination accuracy between high (DON>1000 μg/kg) and low (DON<1000 μg/kg) DON contamination risk for 89 wheat samples was 87.15%. Conclusion The detection system demonstrates speed, economy, practicality, and portability in terms of reagents and instrumentation, and is capable of effectively achieving the objective of rapid on-site detection. This will facilitate early warning of the risk of DON contamination in wheat production in the field, thereby guiding interventions to prevent or minimise losses.

deoxynivalenol  /  Fusarium  /  multienzyme isothermal rapid amplification technique  /  on-site detection
崔华, 陈梦泽, 高树青, 王松山, 李森, 吴宇, 李丽, 叶金, 王松雪. 脱氧雪腐镰刀菌烯醇污染风险现场快速检测系统的建立. 食品安全质量检测学报, 2025 , 16 (3) : 17 -24 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20241023005
Hua CUI, Meng-Ze CHEN, Shu-Qing GAO, Song-Shan WANG, Sen LI, Yu WU, Li LI, Jin YE, Song-Xue WANG. Establishment of an on-site rapid detection system for the risk of deoxynivalenol contamination[J]. Journal of Food Safety & Quality, 2025 , 16 (3) : 17 -24 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20241023005
镰刀菌是一类常见的植物病原菌, 能够侵染小麦、玉米和水稻等禾本科作物, 并产生真菌毒素, 严重影响谷物的产量和质量。真菌毒素是威胁粮食质量安全的主要风险因素, 其中脱氧雪腐镰刀菌烯醇(deoxynivalenol, DON), 也称为呕吐毒素, 是小麦中检出率最高的真菌毒素之一[1-2], 对人类和动物的免疫系统及生殖功能造成损害, 甚至可能导致动物死亡。小麦中DON污染在全球范围内普遍存在[3]。目前已知的DON产生菌主要包括禾谷镰刀菌复合群(Fusarium graminearum species complex, FGSC)、黄色镰刀菌(Fusarium culmorum)和假禾谷镰刀菌(Fusarium pseudograminearum)[4]。其中, FGSC包含了16个目前已确认的系统发育种类[5], 而在我国, 以禾谷镰刀菌(Fusarium graminearum, F. graminearum)和亚洲镰刀菌(Fusarium asiaticum)为主[6-7]。因此, 控制禾谷镰刀菌、亚洲镰刀菌、假禾谷镰刀菌[8]和黄色镰刀菌污染是我国小麦DON防控的关键。
小麦遭受产DON镰刀菌侵染的途径多种多样, 其中最常见的是土壤污染, 其次是通过雨水和风力传播[9-10]。该类病原菌通常在扬花期开始入侵, 灌浆期出现症状, 并在成熟期引发严重损害[11], 如果错过了防治的关键“窗口期”, 感染将导致小麦产量下降、品质降低, 甚至产生有害毒素, 威胁食品安全[12]。DON的生物合成途径已被广泛研究, 该生物合成涉及超过15个不同的生化步骤, 并受到许多调控和转录基因的调控, 包括TRI4TRI5TRI6TRI10TRI12TRI13和可能的TRI14, 其中TRI5基因是DON生物合成的第一步, 被认为是所有产毒素镰刀菌中DON生物合成过程中最重要的关键基因之一[13]。相关研究表明, 小麦样品中TRI5基因拷贝数与DON毒素含量成正相关, 基于毒素基因拷贝数与毒素产量存在的相关性[14]。目前基于TRI5基因核酸扩增的实验室检测技术, 如: 实时荧光定量聚合酶链式反应技术(quantitative real-time polymerase chain reaction, qPCR)[15]、数字PCR (digital PCR, dPCR)[16]等已广泛应用于镰刀菌的检测[17]。然而, 这些方法对人员和设备的要求较高, 耗时耗力。此外, 田间样品在采集和运输过程中, 病菌易发生变化, 可能导致检测结果不准确。因此, 亟需开发一种现场快速检测方法, 以便及时监控小麦产DON镰刀菌的污染风险, 采取干预措施, 保障小麦的产量和质量。
等温扩增技术因其仅需单一恒温条件, 能够在简单的设备如水浴锅、金属浴, 甚至保温杯中运行, 从而彻底摆脱了核酸扩增对复杂精密变温设备的依赖。这项技术具有特异性强、灵敏度高、操作简单、无需专业技术人员等优点, 非常适合资源匮乏地区和现场检测等应用场景[18]。常用的等温扩增技术包括链置换扩增(strand displacement amplification, SDA)、滚环扩增(rolling circle amplification, RCA)、环介导等温扩增(loop-mediated isothermal amplification, LAMP)、重组酶聚合酶扩增(recombinase polymerase amplification, RPA)、重组酶介导扩增(recombinase-aid amplification, RAA)、多酶恒温核酸快速扩增(multienzyme isothermal rapid amplification, MIRA)等[19-20]。其中, LAMP法因其仅需一种酶且扩增效率高, 是目前应用最为广泛的等温扩增技术之一, 相关论文发表量也最大。但该方法存在引物设计复杂、假阳性率较高、试剂价格昂贵等缺点[21], 并且由于日本知识产权的保护, LAMP法在中国的转化和应用受到限制。RPA、RAA和MIRA是同源技术[22-23], 其中, RPA由英国TwistDx公司开发, 成本较高且供货周期长, 推广应用存在困难。相比之下, RAA和MIRA是纯国产技术, 主要区别在于它们所用功能酶的来源和生产工艺不同。MIRA的成品试剂抗干扰能力和稳定性更强[24-26]。MIRA技术近年来发展迅速, 依靠DNA聚合酶、单链DNA结合蛋白和重组酶的协同作用, 实现快速高效的扩增。该技术的引物设计简单, 检测试剂成本相对较低, 还可以根据需求进行个性化定制, 供货周期短, 有效提高了检测的准确性和时效性[27]
对于现场检测, 另一个关键限制是基因组DNA的提取。传统DNA提取方法通常需要多种设备, 这在检测现场通常难以实现。然而, 基于纸基纯化的快速DNA提取方法使得现场DNA提取成为可能[28-29]。这些方法可以从多种生物材料中分离出粗的基因组DNA, 并且对设备需求较低。然而, 使用这些方法提取的粗DNA可能含有一些会干扰扩增反应的成分。因此, 在选择DNA提取方法时, 还需考虑其与后续扩增系统的兼容性。
本研究基于MIRA检测技术和DNA纸基纯化技术, 建立了一套适用于现场应用的DON污染风险快速检测系统。该系统操作简便, 设备便携, 检测结果直观易读, 能够满足粮食生产和收获等现场检测的需求, 有助于实现DON污染风险早期预警, 从而指导及时干预, 减少甚至避免损失。此外, 本研究还为产DON镰刀菌污染发生机制及产毒影响因素的研究提供了数据支持, 助力构建精准的产前小麦DON污染预测模型。
阳性菌株: 禾谷镰刀菌、亚洲镰刀菌(F. asiaticum)、假禾谷镰刀菌(F. pseudograminearum)、黄色镰刀菌(F. culmorum); 阴性菌株: 拟轮枝镰刀菌(F. verticillioides)、藤仓镰刀菌(F. fujikuroi)、层出镰刀菌(F. proliferatum)、木贼镰刀菌(F. equiseti)、三线镰刀菌(F. tricinctum)、尖孢镰刀菌(F. oxysporum)、枝顶孢(Acremonium sp)、互生枝顶孢(Acremonium alternatum)、黄曲霉(Aspergillus flavus, A. flavus)、黑曲霉(A. niger)、杂色曲霉(A. versicolor)、阿姆斯特丹曲霉(A. amstelodami)、交链孢霉(Alternaria alternata)、链格孢霉(Alternaria tenuissima)、篮状菌(Talaromyces assiutensis)、球毛壳菌(Chaetomium globosum)、桔灰青霉(Penicillium aurantiogriseum)、产黄青霉(Penicillium Chrysogenum)、金灰青霉(Penicillium aurantiogriseum), 以上菌株均为本实验室分离鉴定保藏; 十二烷基肌氨酸钠、乙二胺四乙酸二钠、Tween 20(分析纯, 国药基团化学试剂有限公司); Tris-HCl[生物级, 生工生物工程(上海)股份有限公司]; ε-聚赖氨酸(生物级, 上海源叶生物科技有限公司); DNA恒温快速扩增试剂盒(荧光型, 潍坊安普未来生物科技有限公司); JXYM-0510研磨管(上海净信实业发展有限公司)。
Tissue-prp-01快速组织细胞破碎仪(上海净信实业发展有限公司); AmpliFire®便携式恒温荧光检测仪(美国Agdia公司); CFX96 Touch实时荧光定量PCR仪(美国BIO-RAD公司); UltiMate 3000快速液相色谱仪、Q-Exactive四极杆/静电场轨道阱高分辨质谱仪(美国Thermo Fisher Scientific公司)。
根据种植信息, 在河南、安徽、湖北、江苏等黄淮海小麦主产区选取代表性采样点位, 在小麦灌浆期采集(穗部)样品, 每个采样点选取2至3块田地, 每块田地随机分散采集50个麦穗; 在小麦收获期采集(籽粒)样品, 每个采样点选取5家农户, 每家分散采集500 g至1000 g小麦籽粒, 将5份样品混合均匀后, 取500 g至1000 g磨粉, 用于毒素检测。
基于ZOU等[30]报道的纸基DNA快速粗提取方法以及实验室前期开发的粮食真菌DNA快速高通量提取—SLS磁珠法[31], 进行样品DNA提取。具体操作步骤如下:
小麦穗样品: 每块田地选取10个麦穗, 用无菌镊子从每个麦穗上随机摘取3片外颖, 收集至研磨管。加入1.2 mL裂解液(2%十二烷基肌氨酸钠、20 mmol/L乙二胺四乙酸二钠、50 mmol/L Tris-HCl、1 mol/L NaCl、20 mmol/L ε-聚赖氨酸), 并将管子置于快速组织细胞破碎仪中, 高速处理2次, 每次30 s, 间隔120 s; 将DNA吸附纸基浸入样品裂解液中, 保持15 s; 转移纸基至含有200 μL清洗液(10 mmol/L Tris-HCl、0.1% Tween 20)的离心管中, 保持10 s; 然后, 将纸基转移至含有50 μL TE缓冲液(10 mmol/L Tris-HCl, 1 mmol/L乙二胺四乙酸二钠, pH=8.0)的离心管中, 保持5 s后取出。
纯菌样品: 称取100 mg菌丝至研磨管, 加入1 mL裂解液, 其余操作步骤与小麦穗样品相同。
在美国国家生物技术信息中心(National Center for Biotechnology Information, NCBI)基因数据库中检索禾谷镰刀菌、亚洲镰刀菌、假禾谷镰刀菌和黄色镰刀菌的Tri产毒基因簇序列, 经基于局部比对算法的搜索工具(basic local alignment search tool, BLAST)比对, 筛选出4个菌种的高度同源序列, 并以此为靶标设计探针和引物。如图1所示, 探针包含4个修饰位点: 第34位碱基标记荧光基团(FAM), 第35位碱基标记四氢呋喃残基(dSpacer), 第36位碱基标记淬灭基团(BHQ1), 3'末端修饰封闭基团(Spacer C3)。在探针的上下游分别设计了11条正向引物和8条反向引物。所有引物和探针均由生工生物工程(上海)股份有限公司合成。
针对靶标序列设计引物后, 进行PCR扩增, 回收扩增的序列并将其克隆至pUC57载体中。随后, 将载体转化至大肠杆菌DH5α感受态细胞中进行富集培养, 通过抗性筛选阳性菌落并提取重组质粒。根据质粒浓度计算其拷贝数, 计算公式为: 拷贝数/(copies/μL)=6.02×1023×质粒浓度(ng/μL)×10-9/(质粒碱基数×660 Da)。
以禾谷镰刀菌、亚洲镰刀菌、假禾谷镰刀菌和黄色镰刀菌4株阳性菌株DNA混合溶液为扩增模版, 首先固定一条正向引物, 并分别与8条反向引物配对进行扩增。通过比较起峰时间、荧光信号强度和峰型, 筛选出最优的反向引物; 然后, 固定该最优反向引物, 分别与11条正向引物配对扩增, 依据相同的标准筛选出最佳正向引物。
采用DNA恒温快速扩增试剂盒(荧光型)建立反应体系: 首先, 将29.4 μL的A buffer、10 μmol/L的正向和反向引物各2 μL、10 μmol/L的探针0.6 μL, 以及11.5 μL的ddH2O混合均匀, 然后转移至冻干酶粉管中, 上下颠倒甩动离心管, 确保酶粉充分溶解后, 6000 r/min离心5 s, 将溶液平均分配到两个反应管中, 每管加入1 μL的DNA模版, 最后在反应管盖子内侧加入1.25 μL的B buffer, 颠倒混匀5次, 6000 r/min离心5 s, 将反应管置于AmpliFire恒温扩增仪中, 在42 ℃下孵育20 min, 并实时收集FAM荧光信号值。
分别以禾谷镰刀菌、亚洲镰刀菌、假禾谷镰刀菌、黄色镰刀菌、拟轮枝镰刀菌、藤仓镰刀菌、层出镰刀菌、木贼镰刀菌、三线镰刀菌、尖孢镰刀菌、枝顶孢、互生枝顶孢、黄曲霉、黑曲霉、杂色曲霉、阿姆斯特丹曲霉、交链孢霉、链格孢霉、篮状菌、球毛壳菌、桔灰青霉、产黄青霉、金灰青霉共23株菌的DNA为模版, 采用已建立的实时荧光MIRA扩增体系进行检测, 验证该方法的特异性。
质粒检测灵敏度: 将标准质粒溶液进行10倍梯度稀释, 使浓度范围在3.9×100~3.9×106 copies/μL之间, 同时将3.9×101 copies/μL的浓度进行2倍梯度稀释, 直至浓度达到1.95×101 copies/μL。以这些浓度的质粒作为模板, 使用无菌双蒸水作为阴性对照, 进行实时荧光MIRA扩增, 以分析该方法的检测灵敏度。
基因组DNA检测灵敏度: 将阳性菌株DNA混合溶液进行10倍梯度稀释, 使质量浓度范围在1.2×102~1.2×106 fg/μL之间, 同时将1.2×102 fg/μL的质量浓度进行2倍梯度稀释, 最低质量浓度为15 fg/μL。以这些浓度的DNA作为模板, 使用无菌双蒸水作为阴性对照, 进行实时荧光MIRA扩增, 分析其检测灵敏度。
以小麦灌浆期(穗部)样品的DNA为模版, 分别采用新建立的实时荧光MIRA扩增检测法(图2)和实验室先前建立的实时荧光定量PCR检测法进行检测[32]。对于小麦收获期(籽粒)样品的毒素检测, 按照LS/T 6133—2018《粮油检验 主要谷物中16种真菌毒素的测定 液相色谱-串联质谱法》的操作要求进行。
采用实时荧光MIRA扩增法对不同浓度的标准质粒或DNA重复检测3次, 使用Origin 2018软件进行数据分析作图, 同时使用该软件对实时荧光MIRA与qPCR检测结果进行Pearson相关性分析, 并进行线性拟合。
不同引物的实时荧光MIRA扩增结果(图3)显示, 大多数引物均能扩增出典型的荧光曲线, 与其他反向引物相比, R4的起峰时间最早, 且荧光信号整个过程中始终最强。因此, R4被确定为最佳反向引物。正向引物中, F9的起峰时间最早, 前期荧光信号最强, 虽然其后期信号略弱于F5, 但综合分析后确认F9为最佳正向引物。最终, 用于检测产DON镰刀菌的引物组合F9/R4扩增获得的基因片段大小为87 bp(表1)。
采用建立的实时荧光MIRA扩增体系对分离自全国各地粮食样品的23株代表菌种进行扩增反应, 结果(图4)显示, 4株阳性菌株均出现了有显著扩增, 而其他菌株均未出现非特异性扩增, 表明该检测体系具有良好的特异性。
实时荧光MIRA扩增体系对不同浓度的质粒模版进行检测, 如图5, 结果显示检出限最低可达1.95×101 copies/μL, 对不同浓度的DNA模版进行检测, 检出限最低可达15 fg/μL, LIANG等[33]针对玉米中的禾谷镰刀菌建立了侧流动量纸重组酶聚合酶扩增现场检测方法, 检出限为20 fg/μL, 本研究建立的检测方法灵敏度更高一些。
为了便于统计分析, 根据AmpliFire恒温扩增仪扫描频率(10 s/次), 将MIRA对小麦灌浆期(穗部)样品检测的起峰时间值换算为扫描点阈值(整个20 min检测过程共计121个扫描点阈值)。Pearson相关性分析结果显示(图6), MIRA与qPCR两种方法对小麦灌浆期(穗部)样品的检测结果具有极显著的相关性(r=0.820, P=0.000)。
为了确认MIRA检测法对小麦灌浆期(穗部)样品检测结果用于判别收获后小麦籽粒DON污染风险的阈值线(表2), 首先, 通过设定不同的MIRA检测值来进行判别, 大于该检测值的样品划为高DON污染风险组, 小于该检测值的样品划为低DON污染风险组; 然后, 根据我国GB 2761—2017《食品安全国家标准 食品中真菌毒素限量》的规定, 将DON>1000 μg/kg的收获期小麦样品划分为高风险(共19个样本), 将DON<1000 μg/kg的收获期小麦样品划分为低风险(共70个样本); 最后, 对比确认不同MIRA检测值的判别准确率, 最终筛选出综合判别率最佳的值, 即为风险阈值线。分析结果显示, 不同的阈值线在判别高风险和低风险样本时的准确率存在差异, 当MIRA的阈值线设定为43时(<43为高风险; >43为低风险), 高风险判别准确率达到100%, 且综合判别准确率最高, 达87.15%。
MIRA检测法的阈值与qPCR的Ct值相比, 变异性较大, 其主要原因在于MIRA扩增是在等温条件下进行的, 如果反应体系未充分混匀, 尤其是在模板数量较少时, 容易影响反应结果。随着模板数量的减少, 阈值时间的变异会增加。因此, 通常建议在MIRA反应开始后的4 min内取出反应管进行混匀, 以提高检出率。由于MIRA反应启动迅速, 可在室温下立即开始, 因此操作人员的熟练程度对阈值时间有显著影响, 这对模板数量较少的样品尤为重要。此外, 国外研究表明, 将反应体积缩小至5 μL可以提高检测的敏感性, 同时节约成本。相比之下, qPCR在变温条件下进行(包括变性、退火和延伸), 每个循环中的反应液都能得到充分混匀, 因此Ct值的标准差相对较小。
目前建立的MIRA检测系统对于小麦DON污染综合判别准确率最高仅为87.15%, 这主要是由于产DON镰刀菌在小麦生长期间的生命活动受多种因素的影响(如天气、农药使用、品种等)[30], 因此在后续研究中, 需综合这些相关影响因子, 建立更加完善的预警模型, 以进一步提高判别的准确率。另一方面, 需继续优化纸基DNA粗提取方法, 提高DNA的提取效率和质量, 以增加目的基因的检出率。
本研究基于MIRA快速检测技术, 结合纸基DNA纯化技术和便携式仪器设备, 建立了一套小麦DON污染风险快速检测系统。该检测系统具有操作简单、灵敏度高、特异性强等优点, 并且不需要大型仪器, 非常适用于小麦生产现场或基层实验室等检测场景。应用该检测系统对灌浆期小麦样品进行DON污染风险判定, 结果与成熟期小麦样品的实际DON污染风险具有显著正相关性, 这为我国小麦生产中防控DON污染策略的提出提供了关键技术支持和参考依据。
  • 国家重点研发计划政府间国际科技创新合作项目(2022YFE0137500)
  • 中央级公益性科研院所基本科研业务费专项资金项目(ZX2406)
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20241023005
  • 接收时间:2024-10-23
  • 首发时间:2025-07-21
  • 出版时间:2025-02-15
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  • 收稿日期:2024-10-23
基金
国家重点研发计划政府间国际科技创新合作项目(2022YFE0137500)
中央级公益性科研院所基本科研业务费专项资金项目(ZX2406)
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    国家粮食和物资储备局科学研究院, 粮油质量安全研究所, 北京 102629

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* 叶金(1988—), 男, 博士, 副研究员, 主要研究方向为粮油质量安全。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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