摘要
Food and waterborne diseases pose considerable public health threats even in highly industrialized parts of the world.Examples of these pathogens in food can be Escherichia coli O157:H7,Salmonella sp.,and Listeria monocytogenes.Rapid,reliable detection of pathogens mitigates serious health problems and economic losses due to outbreaks and robust tests safeguard the food supply.In this study,a smartphone-based apparatus was employed to demonstrate quantitative detection of E.coli.To validate the applicability of the present smartphone-based fluorescence device,RNA was extracted from the E.coli K-12 strain and amplified using two different primers(dnaK and rpoA)via quantitative polymerase chain reaction(qPCR).Serial dilutions of RNA from 10 to 0.0001 ng/μL were prepared at the start of the PCR amplification and the PCR products were detected by CYBR Green1-based fluorescence.For a proof-of-concept test for the smartphone system,samples from these PCR products were then analyzed.The detection system employed a novel algorithm to analyze fluorescence signals and read changes in E.coli DNA concentration.The correlations between the fluorescence percentage and DNA concentrations were R=0.945 for the dnaK primer and R=0.893 for the rpoA primer,respectively.Utilizing this new fluorescent analysis technique resulted in comparable accuracy to the real-time PCR fluorescent signal detection.The key innovation of this approach was to combine efficient image processing encoded into a smartphone application with a low-cost 3-D printed device that allowed quantification of bacterial nucleic acid.
基金
This work was supported in part by WorkFoS-Ag Program(Grant No.2021-67037-34163)
the ALFA-IoT Program(Grant No.2018-38422-28564)from the USDA National Institute of Food and Agriculture.