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An AIEgen/graphene oxide nanocomposite(AIEgen@GO)-based two-stage“turn-on”nucleic acid biosensor for rapid detection of SARS-CoV-2 viral sequence

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摘要 The ongoing outbreak of Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2)pandemic has posed significant challenges in early viral diagnosis.Hence,it is urgently desirable to develop a rapid,inexpensive,and sensitive method to aid point-of-care SARS-CoV-2 detection.In this work,we report a highly sequence-specific biosensor based on nanocomposites with aggregationinduced emission luminogens(AIEgen)-labeled oligonucleotide probes on graphene oxide nanosheets(AIEgen@GO)for one step-detection of SARS-CoV-2-specific nucleic acid sequences(Orf1ab or N genes).A dual“turn-on”mechanism based on AIEgen@GO was established for viral nucleic acids detection.Here,the first-stage fluorescence recovery was due to dissociation of the AIEgen from GO surface in the presence of target viral nucleic acid,and the second-stage enhancement of AIEbased fluorescent signal was due to the formation of a nucleic acid duplex to restrict the intramolecular rotation of the AIEgen.Furthermore,the feasibility of our platform for diagnostic application was demonstrated by detecting SARS-CoV-2 virus plasmids containing both Orf1ab and N genes with rapid detection around 1 h and good sensitivity at pM level without amplification.Our platform shows great promise in assisting the initial rapid detection of the SARS-CoV-2 nucleic acid sequence before utilizing quantitative reverse transcription-polymerase chain reaction for second confirmation.
出处 《Aggregate》 2023年第1期219-230,共12页 聚集体(英文)
基金 Shenzhen-Hong Kong-Macao Science and Technology Plan Project,Grant/Award Number:SGDX2020110309260000 Research Grants Council(RGC)Collaborative Research Fund,Grant/Award Number:C5110-20GF Research Grants Council(RGC)General Research Fund,Grant/Award Numbers:PolyU 15214619,PolyU 15210818 Hong Kong Polytechnic University Internal Fund,Grant/Award Numbers:1-ZE1E,1-ZVVQ National Natural Science Foundation of China,Grant/Award Number:31771077。
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