Highly sensitive smartphone-based detection of Listeria monocytogenes using SYTO9

Abstract Listeriosis is caused by Listeria monocytogenes (LM) and is currently considered to be one of the leading food-borne diseases worldwide, with mortality rate of 20%∼30%. Currently, detection methods for LM are time-consuming with low sensitivity, and delayed detection results. SYTO9 has a high affinity for DNA and exhibits enhanced fluorescence upon binding. Therefore, this study used SYTO9 staining and image processing to develop a rapid loop mediated isothermal amplification (LAMP) detection method for LM. Smartphone was successfully used for detecting the color change in different concentrations of LM. Besides, the optimized LAMP reaction temperature was 63 °C by color identification, and the limit of detection for LM was 6 copies/μL in the green channel. So, the developed method, based on image processing, is simple, sensitive and rapid, which provides a new idea and method for rapid detection of LM and other food-borne bacterial pathogens.