It has been estimated by the U.S. Centers for Disease Control and Prevention (CDC) that 48million people get sick and 128,000 people are hospitalized from a foodborne illness in the USA each year. Conventional methods for the detection of pathogens on food often involve time consuming methods involving the use of cultures and other biochemical procedures. More modern methods utilize real time PCR based primers and probes to detect specific bacteria, however the complex matrices of these samples can sometimes limit sensitivity and specificity. A potential alternative to these methods is nanoplate digital PCR. This procedure subdivides the samples into thousands of individual wells, (8.5K or 26K) improving specificity and limiting problems with PCR inhibition. The results are then quantified using a Poisson distribution that is based on the target gene's presence or absence in each discrete well.
Thus, the goal of this study was to develop a method using digital PCR to detect fecal contamination on agricultural produce (strawberries) and compare these results with more standard real time PCR based methods. Fecal samples from cattle, rodents, poultry, and other animals were collected and bacterial DNA (bacteroides) from these samples was collected and analyzed. In order to determine the origin of the fecal contamination, mtDNA primers and probes were also developed to detect individual vertebrate species. Multiplex amplifications were developed and validated, and the resultant procedures were tested on inoculated and unwashed fruit. The results indicated the procedure was capable of detecting femtogram levels of bacteria in a sample and the mtDNA probes were species specific and useful in determining the origin of the contamination.