Scientific Reports · 2020 · 11 citations · 30 references
EngineeringBiotechnologyMolecular BiologyBiosensorsDiagnostic MicrobiologyMolecular DiagnosticsDna BiosensorsMolecular Probe DevelopmentNucleic Acid Amplification TestingNucleic Acid BiosensorsPathogen DetectionPoint-of-care BiosensingFluorescent ProbesIsothermal AmplificationIsothermal Amplification AssaysIsothermal Amplification BiosensorsLoop-mediated Isothermal AmplificationLoop-mediated Isothermal Amplification (Lamp)Nucleic Acid AmplificationPathogen Dna Detection
Fluorescence detection of nucleic acid isothermal amplification utilizing energy-transfer-tagged oligonucleotide probes provides a highly sensitive and specific method for pathogen detection. However, currently available probes suffer from relatively weak fluorescence signals and are not suitable for simple, affordable smartphone-based detection at the point of care. Here, we present a cleavable hairpin beacon (CHB)-enhanced fluorescence detection for isothermal amplification assay. The CHB probe is a single fluorophore-tagged hairpin oligonucleotide with five continuous ribonucleotides which can be cleaved by the ribonuclease to specifically initiate DNA amplification and generate strong fluorescence signals. By coupling with loop-mediated isothermal amplification (LAMP), the CHB probe could detect Borrelia burgdorferi (B. burgdorferi) recA gene with a sensitivity of 100 copies within 25 min and generated stronger specific fluorescence signals which were easily read and analysed by our programmed smartphone. Also, this CHB-enhanced LAMP (CHB-LAMP) assay was successfully demonstrated to detect B. burgdorferi DNA extracted from tick species, showing comparable results to real-time PCR assay. In addition, our CHB probe was compatible with other isothermal amplifications, such as isothermal multiple-self-matching-initiated amplification (IMSA). Therefore, CHB-enhanced fluorescence detection is anticipated to facilitate the development of simple, sensitive smartphone-based point-of-care pathogen diagnostics in resource-limited settings.
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