Article(id=1216517522287935631, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1216517514570417012, articleNumber=null, orderNo=null, doi=10.19812/j.cnki.jfsq11-5956/ts.20250329001, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1743177600000, receivedDateStr=2025-03-29, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1767969979116, onlineDateStr=2026-01-09, pubDate=1755187200000, pubDateStr=2025-08-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1767969979116, onlineIssueDateStr=2026-01-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1767969979116, creator=13701087609, updateTime=1767969979116, updator=13701087609, issue=Issue{id=1216517514570417012, tenantId=1146029695717560320, journalId=1149652044408987649, year='2025', volume='16', issue='15', pageStart='1', pageEnd='322', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1767969977276, creator=13701087609, updateTime=1768211590858, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1217530915467743720, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1216517514570417012, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1217530915467743721, tenantId=1146029695717560320, journalId=1149652044408987649, issueId=1216517514570417012, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=73, endPage=83, ext={EN=ArticleExt(id=1216517524074709260, articleId=1216517522287935631, tenantId=1146029695717560320, journalId=1149652044408987649, language=EN, title=Research progress on the application of nanozyme biosensors in the detection of mycotoxins in food, columnId=1216517518575980656, journalTitle=Journal of Food Safety & Quality, columnName=Special Topic: Application of Biosensors in Food Safety Detection, runingTitle=null, highlight=null, articleAbstract=

Mycotoxins are secondary metabolites produced by fungi, which accumulate in the food chain and enter the human body, endangering human health. In recent years, nanozymes with controllable morphology and enzyme-mimicking activity have shown significant advantages in the detection of mycotoxins. This paper mainly summarized the application research of nanozyme biosensors in the detection of mycotoxins, divided nanozymes into metal oxide-based, noble metal-based and carbon-based nanozymes according to the material components, analyzed the dynamic regulation mechanism of nanostructure parameters (including size, morphology, surface modification) on enzyme-mimicking activity, and then explored the technical advantages of nanozymes in colorimetric, fluorescence, electrochemical and Raman detection, revealing its application potential in the rapid detection of mycotoxins. In addition, this paper prospected the application of biosensors constructed by nanozymes in the detection of mycotoxins, aiming to provide theoretical support and technical foresight for the application of nanozymes in the field of food safety detection, and it was expected to provide guidance for the industrial development of the detection field.

, correspAuthors=Hong-Shuai ZHU, 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=Lei BAI, Zi-Yue CHEN, Jun-Hao WANG, Xiao-Dong ZHU, Xin-Hua XIE, Bo-Bo ZHANG, Hong-Shuai ZHU), CN=ArticleExt(id=1216517531561542266, articleId=1216517522287935631, tenantId=1146029695717560320, journalId=1149652044408987649, language=CN, title=纳米酶生物传感器在食品中真菌毒素检测的应用研究进展, columnId=1216517518756335730, journalTitle=食品安全质量检测学报, columnName=专题:生物传感器在食品安全检测中的应用, runingTitle=null, highlight=null, articleAbstract=

真菌毒素是由真菌产生的次级代谢产物, 经食物链蓄积进入人体, 危害人类健康。近年来, 具有形貌可控和模拟酶酶活性的纳米酶在真菌毒素检测中展现出显著优势。本文主要对纳米酶生物传感器在真菌毒素检测中的应用研究进行总结, 依据材料组分将纳米酶划分为金属氧化物基、贵金属基及碳基等, 解析纳米结构参数(包括尺寸、形貌、表面改性)对酶模拟活性的动态调控机制, 进而探讨纳米酶在比色、荧光、电化学和拉曼检测中的技术优势, 揭示其在真菌毒素快速检测中的应用潜力。此外, 对纳米酶构建的生物传感器在真菌毒素检测中的应用进行展望, 旨在为纳米酶在食品安全检测领域的应用提供理论支撑和技术前瞻, 期望对检测领域产业化发展提供指导。

, correspAuthors=朱鸿帅, authorNote=null, correspAuthorsNote=
*朱鸿帅(1992—), 男, 博士, 副教授, 主要研究方向为仿生纳米酶开发及其在生物传感器构建和食品污染物检测中的应用。E-mail:
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白蕾(2001—), 女, 硕士研究生, 主要研究方向为仿生纳米酶开发及其在生物传感器构建和食品污染物检测中的应用。E-mail:

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白蕾(2001—), 女, 硕士研究生, 主要研究方向为仿生纳米酶开发及其在生物传感器构建和食品污染物检测中的应用。E-mail:

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注: A. MOF-5; B. HKUST-1; C. ZIF-8; D. MIL-68(Al)。

, figureFileSmall=A8z2NNS4esXcP3zYQWUPxg==, figureFileBig=iwuQ49V++qROwIebXKLaFA==, tableContent=null), ArticleFig(id=1217127898557895243, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517522287935631, language=EN, label=Fig.3, caption=Size and morphology regulation of nanozymes, figureFileSmall=eqkrB6qJl++8UfoqMU3pQg==, figureFileBig=aOQiG0+bTvYClpYSyJEgjQ==, tableContent=null), ArticleFig(id=1217127898679530070, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517522287935631, language=CN, label=图3, caption=纳米酶的尺寸与形貌调控

注: A. 纳米线状BSDMF; B. 纳米花状BSEG; C. 纳米蜂窝状BSEG/W; D. 纳米棒状BSDMF/W;

, figureFileSmall=eqkrB6qJl++8UfoqMU3pQg==, figureFileBig=aOQiG0+bTvYClpYSyJEgjQ==, tableContent=null), ArticleFig(id=1217127898817942116, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517522287935631, language=EN, label=Fig.4, caption=Geometric model and surface atomic structure model of Co3O4 corresponding crystal plane, figureFileSmall=ePkGjnV0kZJ7DFzJowoKcA==, figureFileBig=nivVEcarB/bDK7D/ydSSeQ==, tableContent=null), ArticleFig(id=1217127898939576945, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517522287935631, language=CN, label=图4, caption=Co3O4对应晶面的几何模型及表面原子结构模型

注: (A~A2)棒状; (B~B2)片状; (C~C2)立方状。A~A1、B~B1、C~C1: Co3O4的SEM和TEM图像; A2~C2: Co3O4对应的几何模型。

, figureFileSmall=ePkGjnV0kZJ7DFzJowoKcA==, figureFileBig=nivVEcarB/bDK7D/ydSSeQ==, tableContent=null), ArticleFig(id=1217127899069600378, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517522287935631, language=EN, label=Fig.5, caption=Schematic illustration of synthesis of GOx@HKUST-1@antibody and colorimetric biosensor detection mechanism diagram of AFB1 sensor, figureFileSmall=8SniJesArDlmreJDmQ81iA==, figureFileBig=zRnAfpPEzDtSrBOi9G6xXA==, tableContent=null), ArticleFig(id=1217127899153486465, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517522287935631, language=CN, label=图5, caption=GOx@HKUST-1@抗体合成示意图及AFB1比色生物传感器检测机制图, figureFileSmall=8SniJesArDlmreJDmQ81iA==, figureFileBig=zRnAfpPEzDtSrBOi9G6xXA==, tableContent=null), ArticleFig(id=1217127899283509899, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517522287935631, language=EN, label=Fig.6, caption=Application of fluorescent biosensors in fungal toxins detection, figureFileSmall=QJf2OSp4iiS7e4o6IQDoBg==, figureFileBig=YDQbL9tLL/NDS1YLVrYbew==, tableContent=null), ArticleFig(id=1217127899421921946, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517522287935631, language=CN, label=图6, caption=荧光生物传感器在真菌毒素检测中的应用

注: A. 基于Fe3O4@NPC-UCNPs组装纳米酶灵敏检测AFB1的荧光生物传感器机制图; B. 基于(PEI/PSS)4的免疫层析竞争检测AFM1的原理图; C. 基于CQDs/Ab侧向流免疫分析技术的检测原理; D. 通过智能手机设备通过RGB颜色分析定量检测AFM1的原理图。

, figureFileSmall=QJf2OSp4iiS7e4o6IQDoBg==, figureFileBig=YDQbL9tLL/NDS1YLVrYbew==, tableContent=null), ArticleFig(id=1217127899522585255, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517522287935631, language=EN, label=Fig.7, caption=Application of electrochemical biosensors in the detection of fungal toxins, figureFileSmall=YLQQOYl/5N1HjQaoKYYB7A==, figureFileBig=egHlSWNB9i7WYwn/+ds7KQ==, tableContent=null), ArticleFig(id=1217127899644220087, tenantId=1146029695717560320, journalId=1149652044408987649, articleId=1216517522287935631, language=CN, label=图7, caption=电化学生物传感器在真菌毒素检测中的应用

注: A. 基于间接竞争测定的生物碱电化学免疫传感器构建示意图; B. 用于葡萄酒样品中AFB1检测的电化学免疫传感器示意图; C. WO3/CdS和PDA/Au的制备和PEC免疫传感器示意图。

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纳米酶生物传感器在食品中真菌毒素检测的应用研究进展
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白蕾 1 , 陈子悦 1 , 王俊豪 1 , 朱效东 1 , 谢新华 1, 2 , 张波波 1, 2 , 朱鸿帅 1, 2, *
食品安全质量检测学报 | 专题:生物传感器在食品安全检测中的应用 2025,16(15): 73-83
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食品安全质量检测学报 | 专题:生物传感器在食品安全检测中的应用 2025, 16(15): 73-83
纳米酶生物传感器在食品中真菌毒素检测的应用研究进展
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白蕾1 , 陈子悦1, 王俊豪1, 朱效东1, 谢新华1, 2, 张波波1, 2, 朱鸿帅1, 2, *
作者信息
  • 1 河南农业大学食品科学技术学院, 郑州 450002
  • 2 农业农村部大宗粮食加工重点实验室, 郑州 450002
  • 白蕾(2001—), 女, 硕士研究生, 主要研究方向为仿生纳米酶开发及其在生物传感器构建和食品污染物检测中的应用。E-mail:

通讯作者:

*朱鸿帅(1992—), 男, 博士, 副教授, 主要研究方向为仿生纳米酶开发及其在生物传感器构建和食品污染物检测中的应用。E-mail:
Research progress on the application of nanozyme biosensors in the detection of mycotoxins in food
Lei BAI1 , Zi-Yue CHEN1, Jun-Hao WANG1, Xiao-Dong ZHU1, Xin-Hua XIE1, 2, Bo-Bo ZHANG1, 2, Hong-Shuai ZHU1, 2, *
Affiliations
  • 1 College of Food Science and Technology, Henan Agricultural University, Zhengzhou 450002, China
  • 2 Key Laboratory of Staple Grain Processing, Ministry of Agriculture and Rural Affairs, Zhengzhou 450002, China
出版时间: 2025-08-15 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250329001
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真菌毒素是由真菌产生的次级代谢产物, 经食物链蓄积进入人体, 危害人类健康。近年来, 具有形貌可控和模拟酶酶活性的纳米酶在真菌毒素检测中展现出显著优势。本文主要对纳米酶生物传感器在真菌毒素检测中的应用研究进行总结, 依据材料组分将纳米酶划分为金属氧化物基、贵金属基及碳基等, 解析纳米结构参数(包括尺寸、形貌、表面改性)对酶模拟活性的动态调控机制, 进而探讨纳米酶在比色、荧光、电化学和拉曼检测中的技术优势, 揭示其在真菌毒素快速检测中的应用潜力。此外, 对纳米酶构建的生物传感器在真菌毒素检测中的应用进行展望, 旨在为纳米酶在食品安全检测领域的应用提供理论支撑和技术前瞻, 期望对检测领域产业化发展提供指导。

纳米酶  /  活性调控  /  生物传感器  /  真菌毒素

Mycotoxins are secondary metabolites produced by fungi, which accumulate in the food chain and enter the human body, endangering human health. In recent years, nanozymes with controllable morphology and enzyme-mimicking activity have shown significant advantages in the detection of mycotoxins. This paper mainly summarized the application research of nanozyme biosensors in the detection of mycotoxins, divided nanozymes into metal oxide-based, noble metal-based and carbon-based nanozymes according to the material components, analyzed the dynamic regulation mechanism of nanostructure parameters (including size, morphology, surface modification) on enzyme-mimicking activity, and then explored the technical advantages of nanozymes in colorimetric, fluorescence, electrochemical and Raman detection, revealing its application potential in the rapid detection of mycotoxins. In addition, this paper prospected the application of biosensors constructed by nanozymes in the detection of mycotoxins, aiming to provide theoretical support and technical foresight for the application of nanozymes in the field of food safety detection, and it was expected to provide guidance for the industrial development of the detection field.

nanozymes  /  activity regulation  /  biosensors  /  mycotoxins
白蕾, 陈子悦, 王俊豪, 朱效东, 谢新华, 张波波, 朱鸿帅. 纳米酶生物传感器在食品中真菌毒素检测的应用研究进展. 食品安全质量检测学报, 2025 , 16 (15) : 73 -83 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250329001
Lei BAI, Zi-Yue CHEN, Jun-Hao WANG, Xiao-Dong ZHU, Xin-Hua XIE, Bo-Bo ZHANG, Hong-Shuai ZHU. Research progress on the application of nanozyme biosensors in the detection of mycotoxins in food[J]. Journal of Food Safety & Quality, 2025 , 16 (15) : 73 -83 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250329001
真菌毒素是由曲霉属(Aspergillus)、镰刀菌属(Fusarium)及青霉属(Penicillium)等丝状真菌产生的低分子量(<1500 Da)次生代谢产物, 具有显著的热稳定性和化学惰性等特征[1]。这类化合物通过污染谷物、坚果及乳制品等食品基质进入食物链, 并在生物体内表现出明显的生物蓄积效应, 其中黄曲霉毒素B1 (aflatoxin B1, AFB1)因其强致癌性已被国际癌症研究机构(International Agency for Research on Cancer, IARC)列为I类致癌物[2]。从分子结构层面分析, 典型真菌毒素如黄曲霉毒素(aflatoxins, AFs)、赭曲霉毒素(ochratoxins, OTs)及玉米赤霉烯酮(zearalenone, ZEN)等均含有共轭芳香环体系, 其中AFs特有的双呋喃环与香豆素结构不仅赋予其强荧光特性, 更通过嵌入DNA碱基对引发基因突变, 此种结构也进一步表明了AFs的较强的毒性和致癌性[3-4]
在检测技术领域, 现行国家标准主要采用薄层色谱法(thin-layer chromatography, TLC)、高效液相色谱-质谱法(high performance liquid chromatography-mass spectrometry, HPLC-MS)及酶联免疫吸附法(enzyme linked immunosorbent assay, ELISA)。其中TLC虽成本低廉但灵敏度有限, HPLC-MS可实现多毒素同步检测却需昂贵仪器和专业人员, 而ELISA所用的天然酶易受基质干扰, 且抗体稳定性不足[5]。此外, 紫外-可见光谱法等光学检测手段在面对复杂食品基质时普遍存在选择性差、前处理复杂等问题。这些瓶颈促使研究者将目光转向纳米材料科学领域, 特别是具有模拟天然酶催化功能的纳米酶, 为开发新型生物传感器提供了创新突破口。
基于纳米酶的生物传感器因其独特的纳米材料特性(如表面效应和量子尺寸效应)与高效的酶催化活性的协同作用, 在真菌毒素检测领域展现出显著的技术优势[6-8]。与天然酶相比, 纳米酶具有成本低、制备简便等特点, 同时得益于纳米酶独特的材料特性(如表面效应和量子尺寸效应)与高效的酶催化活性的协同作用, 显著提升了传感器的性能, 例如更高的灵敏度和更低的检出限等。近年来, 基于可控合成技术制备的功能化纳米酶凭借其可定制的催化活性和选择性识别能力, 在真菌毒素检测领域得到了飞速发展[9-10]
本研究综述了基于纳米酶构建的生物传感器在食品真菌毒素检测领域的最新研究进展, 介绍了当前新型纳米酶的分类、纳米结构对催化活性的调节以及构建的生物传感器的类型, 不仅为高性能纳米酶的开发提供理论指导, 还推动了便携式检测技术的发展[11-12], 对完善食品安全监测体系具有重要意义。
纳米酶是一类兼具纳米材料特性与类天然酶催化功能的人工模拟酶, 其相较于天然酶具有制备简便、成本低廉、活性可调及环境稳定性突出等优势。根据催化反应类型, 纳米酶可系统分为5类(图1): 氧化酶(oxidase, OXD)、过氧化物酶(peroxidase, POD)、过氧化氢酶(catalase, CAT)、脱氢酶(dehydrogenases, DH)以及水解酶(如蛋白酶/核酸酶)、异构酶和转移酶等[13-16]。目前研究体系主要涵盖4大类: (1)贵金属基(如Au、Pt纳米颗粒)[17-18], 凭借表面等离子体效应增强氧化还原活性; (2)金属氧化物基材料(如Fe3O4、CeO2、MnO2)[19-21], 通过可变价态实现类POD活性调控; (3)碳基材料(如氧化石墨烯、g-C3N4)[22-23], 依托电子传递特性提升催化效率; (4)新型杂化材料(如金属-有机框架(metal organic framework, MOF)、普鲁士蓝类似物、单原子催化剂)[24], 其中MOFs因其周期性多孔结构、超高比表面积(>1000 m2/g)及配位可调性, 在传感领域展现出优异的分子识别与信号放大能力。这类材料的仿生催化界面设计, 为构建高灵敏、高稳定性的生物传感器提供了创新材料基础。
金属纳米材料按其组成与结构可分为4大类: 单金属纳米颗粒、金属氧化物及复合型金属纳米材料。其中, 单金属纳米材料以贵金属(如Au、Ag)和过渡金属(如Fe、Co)体系为主, 其表面等离子体共振(surface plasma resonance, SPR)效应及尺寸/形貌依赖的光学特性(如局域表面等离子的生物传感器性能优异, 在真菌毒素多模式检测中具有体共振波长可调范围达400~1200 nm)使其在生物传感领域独具优势。以典型金纳米颗粒(AuNPs)为例[25], 其粒径(1~100 nm)与形貌(球状、棒状、星状及双锥体等)可通过种子介导生长法精准调控, 其中金纳米星因尖端增强效应可使拉曼信号强度提升106[26], 而金纳米棒的长径比调节可实现近红外区(650~900 nm)光学吸收峰的精准定位[27]。AuNPs可通过比色、荧光淬灭/恢复及表面增强拉曼光谱(surface enhancement of Raman scattering, SERS)等多模式实现真菌毒素检测, 如AFB1检测限低至0.08 pg/mL[28]。这类材料的光热转换效率(>90%)还可与微流控芯片联用, 开发即时检测。
金属氧化物纳米材料凭借成本低廉、可规模化的合成工艺及高比表面积等优势, 在生物传感领域展现出独特竞争力[29]。其晶体缺陷工程赋予的多酶活性尤为突出, 如CeO2纳米酶通过Ce3+/Ce4+氧化还原循环可同时模拟超氧化物歧化酶(superoxide dismutase, SOD)和POD功能[30]。典型体系包括: MnO2纳米酶利用层状结构实现谷胱甘肽特异性识别[31]; GeO2纳米材料经Pd/Fe双金属掺杂后, 类POD活性提升4.3倍, 成功构建比色传感器(检出限0.5 μg/kg)[32]。金属纳米材料发展迅猛, 因其不同于宏观晶体的特殊性质常作为构筑传感器的理想材料, 且基于金属纳米材料构建重要应用价值。
量子点(quantum dots, QDs)是一种低维半导体纳米材料(直径2~20 nm), 由II-VI或III-V族元素[如硒化镉(CdSe)、碲化镉(CdTe)]组成, 分为核心型、核壳型(水溶性/油溶性)[33]和合金型结构。其量子限制效应赋予其宽激发光谱、窄可调发射光谱、高量子产率和优异光稳定性等光学特性。水溶性量子点适用于生物检测(核酸检测、细胞成像等), 油溶性量子点则用于光电器件、太阳能电池及荧光标记。量子点荧光免疫分析技术已广泛应用于兽药残留、毒素和疾病蛋白检测等领域。
MOFs是由金属离子与有机配体通过配位作用形成的晶体多孔材料, 兼具高比表面积和可调控孔隙率, 在材料科学领域具有重要研究价值。MOFs在1995年首次被定义为为多孔配位聚合物(porous coordination polymers, PCPs), 随后通过优化使无机位点与有机连接体组合, 促进了具有不同结构和组成的MOFs合成。目前报道合成的MOFs已经有20000多种, 按类型可以分为网状金属有机框架(isoreticular metal-organic frameworks, IRMOF)、沸石-咪唑框架(zeolitic imidazolate framework, ZIF)、莱瓦希尔框架(materials of institute lavoisier frameworks, MIL)和通道式框架(pocket-channel frameworks, PCN), 其中代表性材料有MOF-5、ZIF-8、MIL-101和HKUST-1等(图2)[34-35]。MOFs因其具有较大的比表面积、简便的合成方法、丰富的官能团和突出的化学稳定性, 在污染物吸附、催化有机物、传感、生物医学等方向都有较为广泛的研究[36], 尤其是在催化的领域方向。MOFs的大比表面积和多孔结构为材料和分析物之间提供了更多的接触界面和活性位点, 同时有机配体的丰富官能团使MOFs易于与各种分子和材料结合, 包括核酸、酶、纳米颗粒等。因此, MOFs作为适配体传感器的核心材料, 通过整合其多孔限域效应与分子识别能力, 在食品安全检测(如毒素分析)和疾病标志物传感等方向展现出重要潜力[37]
单原子纳米酶(single-atom nanozymes, SAzymes)是一类具有原子级分散活性位点的纳米酶, 其活性位点由独立的金属原子构成, 类似于天然金属酶的活性位点。这种结构使得单原子纳米酶在生理条件下能够催化酶底物的反应, 展现出与天然酶类似的催化效率和酶促反应动力学特性。单原子纳米酶的主要特性涵盖高催化活性、卓越的稳定性、明确的配位环境以及结构明确且可调控性。具体而言, 其活性位点的高度分散状态极大地提升了原子利用效率, 从而显著增强了催化反应的效率。通过精细调控单原子位点的配位环境, 可以进一步优化其催化性能。例如, FeN5SA/CNF(碳纳米纤维锚定的五配位铁单原子催化剂)通过构建FeN5活性中心, 展现出高于常规Fe基纳米酶的过氧化物酶活性, 其催化机理与细胞色素P450中轴向配体调控的血红素活性位点具有高度相似性[38]。理论计算与实验研究表明, 该材料在氧化反应(oxidation reaction, OXD)中的催化行为与其碳限域结构及配位环境密切相关[39]。这类精准设计的SAzymes为开发高效仿生催化体系提供了新策略, 在生物传感、疾病治疗及环境催化等领域展现出广阔应用前景。
与天然酶相似, 纳米酶的催化活性受其自身结构特性(内在因素)及外界环境条件(外在因素)的共同调控。尽管其催化机制尚未完全阐明, 但近年研究已逐步揭示纳米酶 “结构-性能” 的构效关系, 为活性定向调控提供了理论依据[40-41]。各种内在因素, 包括尺寸、形貌、表面修饰、组成成分等, 均被报道能够影响纳米酶的催化性能[42]。此外, 外界因素如温度、光照、pH等同样会显著影响纳米酶活性, 尤其是具有多酶性质的纳米材料, 它们可以根据不同的环境改变其催化活性。这表明, 纳米酶的活性可以通过精准设计和优化特定用途的应用条件实现调控。基于此, 通过理性设计纳米酶结构(如原子级分散活性位点构建)与优化反应条件(如局部微环境调控), 可实现其催化活性与选择性的高效提升, 推动其在疾病诊疗、环境修复及工业催化等领域的应用发展[43]
纳米酶的催化活性与其尺寸和形貌密切相关, 这是由于更高的表面积与孔体积比会使尺寸较小的纳米酶暴露出更多的活性位点, 从而促进与底物的相互作用。因此, 可以通过改变纳米酶的大小来调控其催化活性[44]。例如, LUO等[45]系统研究了AuNPs尺寸(13~50 nm)对其类葡萄糖氧化酶(glucose oxidase, GOx-like)活性的影响, 通过比较相同条件下不同尺寸AuNPs的反应速率, 发现反应速率随尺寸减小显著提升, 这归因于小尺寸AuNPs表面原子比例增加及电子传递路径缩短。类似地(图3), SASIKALA等[46]通过调控硫化铋(Bi2S3)的形貌(纳米线状BSDMF、纳米花状BSEG、纳米蜂窝状BSEG/W及纳米棒状BSDMF/W), 揭示了其过氧化物酶活性与表面铋原子配位环境的关联: 纳米蜂窝状结构(BSEG/W)因结晶度最高, 表现出最优的H2O2活化能力(活性顺序: BSEG/W>BSEG>BSDMF/W>BSDMF)。这些研究表明, 纳米酶的催化性能不仅受比表面积和活性位点数量的调控, 还与晶格畸变、缺陷密度及表面原子配位状态等微观结构特性密切相关。通过精准设计纳米材料的尺寸与形貌, 可实现对催化活性位点的暴露程度及电子结构的优化, 为开发高效纳米酶提供重要策略。
纳米酶的催化性能可通过形貌与晶面工程进行精准调控。不同形貌通常暴露特定晶面, 其表面原子排列差异导致悬空键密度、配位饱和度及缺陷浓度不同, 从而影响底物吸附与活化路径[47]。例如, JIAN等[48]通过溶剂热法合成棒状(Co3O4-R)、片状(Co3O4-S)及立方状(Co3O4-C)Co3O4纳米酶(图4), 分别优先暴露(110)、(111)和(100)晶面。其中(100)晶面因原子排列开放、表面不饱和配位Co3+位点密度高且晶格缺陷丰富, 展现出最优的类过氧化物酶活性。此外, 有研究发现[49], 低结晶度普鲁士蓝纳米颗粒(prussian blue nanoparticles, PBNPs)因结构无序化产生大量边缘缺陷和活性位点, 其类过氧化物酶(peroxidase, POD-like)及类过氧化氢酶(catalase, CAT-like)活性显著高于高结晶度样品, 证实结晶度降低可通过引入缺陷态增强电子转移效率[50]。这些结果表明, 通过调控纳米酶的形貌(晶面择优暴露)、结晶度(有序-无序平衡)等结构参数, 可优化其表面原子配位环境及电子结构, 为设计高活性、高选择性纳米酶提供重要理论依据。
纳米酶的催化性能可通过表面修饰工程实现定向调控, 其核心策略包括: (1)表面电子结构优化: 引入导电聚合物或金属掺杂, 调节纳米酶表面电荷分布及电子转移路径; (2)表面酸碱性与氧化还原电位调控: 通过吸附无机离子(如H+、OH-或过渡金属离子)调节表面酸性位点密度及氧化还原活性, 优化反应能垒[51]; (3)选择性配体修饰: 锚定特异性配体(如适配体、生物分子或功能基团), 增强底物识别能力并抑制非特异性吸附; (4)界面复合结构构建: 以多孔材料(如MOFs)为载体负载贵金属纳米颗粒(Pt、Au等), 通过界面协同效应提升催化活性。例如, LI等[52]将铂纳米颗粒(platinum nanoparticles, PtNPs)负载于Cu-TCPP(Fe)MOF纳米片表面, 构建PtNPs/Cu-TCPP(Fe)杂化材料。该材料中PtNPs与MOF的Fe卟啉活性位点形成强电子耦合, 协同促进H2O2的异相活化, 使其POD-like活性较单一组分显著提升[53]。此外, MOFs的高比表面积和可调孔道结构为纳米酶活性位点的均匀分散及底物传质提供了理想平台。这些表面工程策略不仅增强了纳米酶的催化效率与选择性, 还拓展了其在复杂生物体系中的应用潜力。
纳米酶生物传感器是一种基于纳米酶催化功能与生物识别元件协同作用的新型检测平台。纳米酶能够通过催化反应放大信号, 通过光学、电化学或质谱等技术进行信号转化, 从而提高传感器的检测灵敏度。例如, 过氧化氢(H2O2)作为氧化剂, 可在纳米酶催化下产生显著信号(如颜色变化、电流变化等)。传感器通过结合特定的分子识别元件(如抗体、DNA适配体、分子印迹材料等)来特异性地识别目标物质, 进而生成检测信号。根据信号输出模式不同, 该传感器主要分为4类: 基于纳米酶催化底物显色的比色生物传感器; 基于纳米酶催化产物淬灭/共振能量转移/增强荧光信号的荧光生物传感器; 基于纳米酶电子传递效率变化产生电流响应的电化学生物传感器; 基于纳米酶催化反应调控拉曼探针信号强度的表面增强拉曼型生物传感器。该技术体系在在食品安全、环境监测及临床诊断领域展现出高灵敏、低成本及操作简便的优势。
比色生物传感器凭借其肉眼可读、操作简便等优势, 在真菌毒素快速检测中备受关注。纳米酶通常通过催化所使用底物的氧化/还原反应, 基于特定的显色底物产生比色信号, 如3,3',5,5'-四甲基联苯胺(3,3',5,5'-tetramethylbenzidine, TMB), 2,2'-氮化二胺-(3-乙基苯并噻唑-6-磺酸)和邻苯二胺, 在氧化酶或过氧化物酶样纳米酶催化的反应中可分别产生蓝色、绿色和橙色。例如, 曾宪冬等[54]构建了一种基于AuNPs的赭曲霉毒素A (ochratoxin A, OTA)适配体传感器: OTA适配体与互补DNA杂交诱导AuNPs聚集(蓝紫色); 当OTA存在时, 适配体优先结合毒素, 使双链解离, AuNPs 因静电排斥重新分散(红色), 通过吸光度变化定量检测OTA, 显著提升灵敏度。该传感器无需复杂仪器即可实现现场快速筛查。ZHANG等[55]开发了一种多功能铜基MOF(GOx@HKUST-1@antibody)比色生物传感器, 研究表明, HKUST-1复合物具有三重功能: 稳定葡萄糖氧化酶(GOx)、模拟过氧化物酶、负载AFB1抗体。苯甲酸配位调节使GOx包封的HKUST-1呈大小均匀的八面体, 利于免疫反应和磁分离。通过免疫组合和磁分离, GOx@HKUST-1@antibody可再分散以放大信号。检测时, AFB1与AFB1-BSA修饰的Fe3O4竞争结合抗体, 减少捕获的GOx@HKUST-1@antibody, 降低葡萄糖氧化产生的H2O2浓度, 从而减弱TMB显色(图5)。该传感器线性范围为0.010~0.100 ng/mL, 检出限低至0.004 ng/mL, 由于HKUST-1对GOx和抗体的保护作用, 该方法具有很高的稳定性。此外, 这种竞争性免疫测定法可以扩展到其他真菌毒素的检测。综上所述, 比色生物传感器结合纳米材料和生物识别元件为真菌毒素的快速、灵敏检测提供了一种高效且低成本的解决方案, 具有广阔的应用前景。
荧光生物传感器凭借其高灵敏度与快速响应特性, 在真菌毒素痕量检测中展现出显著优势。其核心设计策略在于将荧光探针与纳米酶催化/识别功能相结合, 实现信号的双重放大与精准输出。例如, 利用荧光分析法的优点, ZHAO等[56]开发了基于上转换纳米颗粒(upconversion nanoparticles, UCNPs)与磁性纳米多孔碳(Fe3O4@NPC)的荧光生物传感器, 用于AFB1的灵敏检测, 如(图6A)所示, 该研究通过免疫识别将Fe3O4@NPC的催化活性及其异质结构物理性质与UCNPs的光学性质相结合。结果表明, UCNPs在近红外光激发下通过能量转移激活Fe3O4@NPC的类过氧化物酶活性, 催化2',7'-二氯二氢荧光素(2',7'-dichlorodihydrofluorescein, DCFH)氧化为强荧光产物2',7'-二氯荧光素, 其荧光强度高, 对DCFH具有高度亲和力。所建方法在0.1~10 ng/mL范围内的线性良好, 检出限为0.56 pg/mL。
直接信号放大技术将纳米材料作为固定荧光探针的载体, 与传统的荧光染料相比, 荧光纳米材料具有形貌尺寸可控、易于修饰等优势, 在黄曲霉毒素M1 (aflatoxin M1, AFM1)荧光传感器中应用广泛。例如, SU等[57]采用红色荧光二氧化硅纳米颗粒固定AFM1抗体, 作为信号放大探针如(图6B)所示, 建立竞争性免疫层析法对AFM1进行高灵敏度检测; SINGH等[58]构建了氮掺杂碳量子点(nitrogen-doped carbon quantum dots, CQDs)-抗体复合探针, 基于荧光猝灭效应实现AFM1特异性识别; WANG等[59]设计了双功能磁-荧光纳米球(图6C和6D), 结合侧向流免疫分析技术, 利用荧光识别实现对AFM1的可视化定量检测, 将红色量子点(red quantum dots, RQD)标记的抗体探针(FSQS-mAbs)与绿色量子点(gSQS)标记的抗原(T线)结合,通过竞争反应引发红-绿荧光比例变化, 结合智能手机红绿蓝(red green blue, RGB)分析实现AFM1半定量(肉眼)(如量子点荧光可调性、上转换发光抗干扰性)与生物识别元件(抗体/适配体)的特异性, 不仅实现了超灵敏检测, 还发展了多信号输出(比率荧光、颜色切换)及便携式检测(试纸条结合智能手机)等创新模式, 为复杂基质中真菌毒素的现场快速分析提供了高效解决方案。
电化学生物传感器根据信号类型可分为电流型、阻抗型及光电化学(photoelectrochemistry, PEC)型免疫传感器, 其中, 电流型免疫传感器基于抗原-抗体反应改变电极表面电子转移或离子传输特性, 引起电流变化, 从而用于目标物检测。例如, MUSTAFA等[60]采用多壁碳纳米管/壳聚糖修饰电极构建了一种灵敏、简便的电化学免疫传感器(图7A)。通过微分脉冲伏安法分析在+0.25 V±0.1 V的电位下实现电化学检测。结果表明, 定量限为0.06 μg/mL, R2=0.996呈良好的线性关系。阻抗型传感器的原理是通过向电极施加正弦电压产生交流阻抗, 反应改变阻抗信号, 实现快速检测。KUNENE等[61]将抗AFB1抗体-牛血清白蛋白偶联物固定于L-半胱氨酸层修饰的碳毡电极, 并连接PdNP-BN纳米材料(图7B)。通过电流/阻抗型表征, 证实BN作为PdNPs基底可增强传感器导电性。优化后, 传感器线性范围1~10 ng/mL (r2=0.9987), 葡萄酒加标回收率93%~106%。PEC传感器则将反应电信号转化为光信号进行检测。PEI等[62]构建了一种基于g-C3N4/Au/WO3无标签光电化学免疫传感器(图7C)。该传感器将g-C3N4/Au/WO3偶联物质作为光敏平台, 利用AuNPs固定抗体, 并通过Z型异质结增强电子-空穴分离。其对AFB1的线性浓度范围为1.0 pg/mL~100 ng/mL, 并且在实际样品分析中表现出良好的性能。综上所述, 电化学生物传感器(如电流型、阻抗型、PEC型)凭借高灵敏度、效率及多样化机制, 在生物分析和环境监测中应用潜力巨大, 可为复杂样品目标物提供高效、准确的检测方案。
是基于表面增强拉曼散射(surface-enhanced Raman scattering, SERS)信号的生物传感器凭借免标记、无损、高通量、高灵敏、高选择性和操作简便等优势备受关注。ZHAO等[63]构建了一种基于Ag@Au核壳纳米颗粒的SERS传感器, 通过将4-核苷三磷酸(nucleoside triphosphate, NTP)/4-腺嘌呤核苷三磷酸(adenosine triphosphate, ATP)嵌入核壳界面构建稳定标签, 并利用磁性纳米颗粒(magnetic nanoparticles, MNPs)表面互补DNA探针捕获适配体-SERS标签复合物。当OTA和AFB1存在时, 适配体优先结合毒素, 导致MNPs无法捕获SERS标签, 拉曼信号减弱, 实现双毒素同步检测, 灵敏度达pg/mL级。LI等[64]构建了一种基于DNA纳米嵌和AgNPs的SERS传感器检测AFB1。将DNA分子的5'端标记-SH, 并通过Ag-S键将DNA标记在AgNPs表面。10条单链DNA和适配体自组装成DNA纳米嵌。AFB1存在时, 适配体结合靶标, 破坏纳米嵌结构并诱导一条DNA形成茎环, 使AgNPs聚集, SERS信号增强。通过监测信号变化实现定量检测。与其他SERS传感器相比, 该方法灵敏度高、信号稳定, 但适配体修饰AgNPs耗时。综上所述, 基于SERS的生物传感器通过结合纳米材料和磁性分离技术, 为复杂样品(如霉菌毒素)的高灵敏检测提供了多种创新策略, 显著提升了检测的灵敏度、选择性并简化操作, 应用前景广阔。
本文系统总结了纳米酶在比色、荧光、电化学和拉曼传感器中的最新研究进展, 重点探讨了其在真菌毒素检测领域的应用现状。尽管纳米酶展现出优异的催化性能, 但其内在催化机制尚未完全阐明, 且仍面临复杂基质干扰、识别元件开发瓶颈、多目标检测局限性和性能优化协同性不足等挑战, 未来通过多学科交叉创新有望实现突破性进展。针对基质干扰问题, 可结合分子印迹技术、微流控芯片和背景扣除策略提升抗干扰能力; 人工智能辅助适配体设计、合成生物学构建人工受体将推动高特异性识别元件的开发; 基于多元编码纳米酶和阵列传感技术, 结合机器学习多信号解析, 可实现多组分同步检测; 而原子级活性位点调控、核壳结构保护和便携式设备集成将协同优化检测灵敏度、速度和稳定性。随着纳米酶理性设计的完善及与物联网融合, 基于纳米酶的生物传感器将在分析检测领域发挥更大的作用。为食品安全监测提供高效、低成本的解决方案。
  • 河南省科技攻关项目(242102111044)
  • 中国博士后基金项目(2022M711058)
  • 河南省自然科学基金项目(232300420195)
  • 河南农业大学高层次人才项目(30501354)
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2025年第16卷第15期
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20250329001
  • 接收时间:2025-03-29
  • 首发时间:2026-01-09
  • 出版时间:2025-08-15
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  • 收稿日期:2025-03-29
基金
河南省科技攻关项目(242102111044)
中国博士后基金项目(2022M711058)
河南省自然科学基金项目(232300420195)
河南农业大学高层次人才项目(30501354)
作者信息
    1 河南农业大学食品科学技术学院, 郑州 450002
    2 农业农村部大宗粮食加工重点实验室, 郑州 450002

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*朱鸿帅(1992—), 男, 博士, 副教授, 主要研究方向为仿生纳米酶开发及其在生物传感器构建和食品污染物检测中的应用。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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