Rapid detection of pathogenic E. coli based on CRISPR Cas system - Rathore, Pallavi; Basnet, Ashesh; Kilonzo-Nthenge, Agnes; Dumenyo, Korsi; Yadegari, Zeinab; Taheri, Ali (Frontiers in Microbiology, 2024)
Access to safe and nutritious food is critical for maintaining life and supporting good health. Eating food that is contaminated with pathogens leads to serious diseases ranging from diarrhea to cancer.Many foodborne infections can cause long-term impairment or even death. Hence, early detection of foodborne pathogens such as pathogenic Escherichia coli strains is essential for public safety.Conventional methods for detecting these bacteria are based on culturing on selective media and following standard biochemical identification. Despite their accuracy, these methods are timeconsuming. PCR-based detection of pathogens relies on sophisticated equipment and specialized technicians which are difficult to find in areas with limited resources. Whereas CRISPR technology is more specific and sensitive for identifying pathogenic bacteria because it employs programmable CRISPR-Cas systems that target particular DNA sequences, minimizing nonspecific binding and cross-reactivity.In this project, a robust detection method based on CRISPR-Cas12a sensing was developed, which is rapid, sensitive and specific for detection of pathogenic E. coli isolates that were collected from the fecal samples from adult goats from 17 farms in Tennessee. Detection reaction contained amplified PCR products for the pathogenic regions, reporter probe, Cas12a enzyme, and crRNA specific to three pathogenic genes -stx1, stx2, and hlyA. The CRISPR reaction with the pathogenic bacteria emitted fluorescence when excited under UV light. To evaluate the detection sensitivity and specificity of this assay, its results were compared with PCR based detection assay. Both methods resulted in similar results for the same samples. This technique is very precise, highly sensitive, quick, cost effective, and easy to use, and can easily overcome the limitations of the present detection methods. This project can result in a versatile detection method that is easily adaptable for Rapid Response in the detection and surveillance of diseases that pose large-scale biosecurity threats to human health, and plant and animal production.