Parameter Optimization for a Novel Phage-Based Biomolecular Filter for Detection of Pathogens from Large Volumes of Water

Monday, 14 October 2019
Grand Ballroom (The Hilton Atlanta)
A. MacLachlan (Auburn University, Materials Research and Education Center), J. He (Auburn University), S. Du (Materials Research & Education Center, Auburn University), S. Horikawa (Auburn University), I. H. Chen (Material Research & Education Center, Auburn University), Y. Liu (Materials Research & Education Center, Auburn University), B. A. Chin (Auburn University Detection and Food Safety Center), and P. Chen (Auburn University)
Each year in the United States, foodborne pathogens, including bacteria, viruses, and parasites, cause an estimated 48 million illnesses, 128,000 hospitalizations, and 3,000 deaths. Forty-six percent of those illnesses are attributed to fresh produce, with pathogens on leafy greens causing the most illnesses. Pathogen contamination in fresh foods is a threat to public health. Unfortunately, the microbiological testing of a few samples of whole fruits or even hundreds of spinach leaves is inadequate to ensure the safety of a batch of specialty crop produce. Similarly, microbiological testing of only a few milliliters from thousands of liters of irrigation water and wash water used to grow and process a batch of specialty crop produce is woefully inadequate. A revolutionary, non-clogging phage filter system has been developed to capture, concentrate and isolate small numbers of multiple pathogens (100 CFU) from large volumes of irrigation and wash water (1,000 liters <10 minutes), so that foodborne illnesses can be rapidly identified before food is distributed to consumers. To optimize the performance of the filter system, we investigated a broad-spectrum of parameters inclusive of sensor elements, filter configuration, flow velocity, fluid pressure and operation temperature that would contribute to the development of a better system. This project will benefit growers, processors and distributors by rapidly identifying contaminated irrigation water, contaminated lots of produce, and improving production efficiency while reducing recalls and litigation.