Mengyang Hu, Meng Cheng, Na Wang, Yidan Sang, Yafei Dong, Luhui Wang
{"title":"A label free fluorescent aptamer sensor based on the combined action of Graphene oxide and SYBR Green I for the detection of Aflatoxin B1.","authors":"Mengyang Hu, Meng Cheng, Na Wang, Yidan Sang, Yafei Dong, Luhui Wang","doi":"10.1109/TNB.2024.3403158","DOIUrl":null,"url":null,"abstract":"<p><p>Here, based on the characteristics of Graphene oxide(GO) and SYBR Green I(SGI) dye, an enzyme-free and label-free fluorescent biosensor with signal amplification through DNA strand reaction is proposed for the detection of Aflatoxin B1(AFB1) in food safety. Firstly, without the addition of AFB1, the substrate in the system includes a double stranded Apt-S with a long sticky end and two hairpins H1 and H2. Although the complementary pairing of bases may exhibit fluorescence due to the insertion of SGI dyes, the use of GO, which is highly capable of adsorbing single stranded parts and quenching fluorescence, cleverly reduces the background fluorescence. Adding the target AFB1 triggers DNA inter chain reactions, generating a large amount of long double stranded DNA H1-H2, thereby generating strong fluorescence signals under the action of SGI. More importantly, logical theory verification and computer simulation were conducted before biological experiments, providing a theoretical basis for the implementation of the biosensor. After analysis, the fluorescence biosensor exhibits a good linear relationship with AFB1 concentration in the range of 5-50nM, with a detection limit of 0.76nM. It also has good specificity, anti-interference ability, and practical application ability, and has broad application prospects in the field of food safety.</p>","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"PP ","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on NanoBioscience","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1109/TNB.2024.3403158","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Here, based on the characteristics of Graphene oxide(GO) and SYBR Green I(SGI) dye, an enzyme-free and label-free fluorescent biosensor with signal amplification through DNA strand reaction is proposed for the detection of Aflatoxin B1(AFB1) in food safety. Firstly, without the addition of AFB1, the substrate in the system includes a double stranded Apt-S with a long sticky end and two hairpins H1 and H2. Although the complementary pairing of bases may exhibit fluorescence due to the insertion of SGI dyes, the use of GO, which is highly capable of adsorbing single stranded parts and quenching fluorescence, cleverly reduces the background fluorescence. Adding the target AFB1 triggers DNA inter chain reactions, generating a large amount of long double stranded DNA H1-H2, thereby generating strong fluorescence signals under the action of SGI. More importantly, logical theory verification and computer simulation were conducted before biological experiments, providing a theoretical basis for the implementation of the biosensor. After analysis, the fluorescence biosensor exhibits a good linear relationship with AFB1 concentration in the range of 5-50nM, with a detection limit of 0.76nM. It also has good specificity, anti-interference ability, and practical application ability, and has broad application prospects in the field of food safety.
期刊介绍:
The IEEE Transactions on NanoBioscience reports on original, innovative and interdisciplinary work on all aspects of molecular systems, cellular systems, and tissues (including molecular electronics). Topics covered in the journal focus on a broad spectrum of aspects, both on foundations and on applications. Specifically, methods and techniques, experimental aspects, design and implementation, instrumentation and laboratory equipment, clinical aspects, hardware and software data acquisition and analysis and computer based modelling are covered (based on traditional or high performance computing - parallel computers or computer networks).