Fluorescent dual-mode assay of plant viral disease with polymerase chain reaction amplification
[Display omitted] •A fluorescent dual-mode assay was designed for plant viral diseases detection with PCR.•The exponential amplification power of PCR could improve detection sensitivity.•Such dual-mode platform effectively reduced the interference of external conditions.•This sensor was applied for...
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Veröffentlicht in: | Microchemical journal 2023-10, Vol.193, p.109217, Article 109217 |
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Sprache: | eng |
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•A fluorescent dual-mode assay was designed for plant viral diseases detection with PCR.•The exponential amplification power of PCR could improve detection sensitivity.•Such dual-mode platform effectively reduced the interference of external conditions.•This sensor was applied for the detection of tobacco mosaic virus infections in field samples.
Plant viral diseases pose serious risk to the quality and yield of different crops. Herein, we described a highly sensitive and accurate immunosensor for early diagnosis of plant viral disease by using dual-signal readout with polymerase chain reaction (PCR) amplification. The sensor utilizes 6-carboxyfluorescein group (FAM) and tetramethyl-6-carboxyrhodamine (TAMRA) labeled primers as signal probes and their fluorescence signals were effectively quenched by graphene oxide (GO). In the presence of target plant viral related nucleic acid, the cDNA template could initiate the formation of long duplex PCR products with multiple signal probes. Such duplex PCR products cannot be quenched with GO, resulting in an obvious fluorescence signal. The results showed that FAM and TAMRA signals were proportional to the logarithm of the target cDNA concentration in the range of 10 fM–100 pM. The detection limit for the target cDNA was 0.08 fM for FAM and 0.07 fM for TAMRA, respectively. The practical application of our proposed strategy was successfully demonstrated by detection of emerging tobacco mosaic virus (TMV) infections in tobacco samples collected in the field, illuminating the possibility of applying this sensing platform for early diagnosis of plant disease. |
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ISSN: | 0026-265X 1095-9149 |
DOI: | 10.1016/j.microc.2023.109217 |