4.7 Article

Development of a Dual Mode UCNPs-MB Biosensor in Combination with PCR for Sensitive Detection of Salmonella

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BIOSENSORS-BASEL
卷 13, 期 4, 页码 -

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MDPI
DOI: 10.3390/bios13040475

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UCNPs; methylene blue; colorimetric-fluorescence dual mode; PCR biosensor; inner filter effect; Salmonella

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In recent years, the high prevalence of Salmonella has become a serious threat to public safety, leading to the development of accurate and rapid methods for food safety. This study proposed a multifunctional platform combining colorimetric and fluorescence detection channels with PCR for the sensitive and rapid detection of Salmonella. The results showed that this dual-mode PCR biosensor, incorporating internal filter effect and PCR amplification, achieved a limit of detection of 21.8 CFU/mL and produced satisfactory results for Salmonella detection in food samples.
In recent years, the high prevalence of Salmonella has emerged as a serious threat to public safety, prompting attempts to utilize accurate, rapid, and direct methods to ensure food safety. In this study, a multifunctional platform featuring dual-mode detection channels (colorimetric-fluorescence) combined with polymer chain reaction (PCR) was proposed for the sensitive and rapid detection of Salmonella. Additionally, the colorimetric measurements were achieved by color changes induced by methylene blue (MB) insertion into the double-stranded DNA, and the fluorescence measurements were performed by internal filter effect (IFE)-induced fluorescence quenching of upconversion nanoparticles (UCNPs) by MB. The results showed that the IFE and PCR amplification processes improved the sensitivity of the sensor towards Salmonella detection, with a limit of detection (LOD) of 21.8 CFU/mL. Moreover, this colorimetric-fluorescence dual-mode PCR biosensor was applied to determine Salmonella in food samples, such as chicken, egg, and fish, which produced satisfactory results. Overall, the present study results demonstrate the potential for combining PCR amplification with IFE to develop an efficient and reliable dual-mode analysis platform to safeguard food security.

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