Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 10/5/2008
Publication Date: N/A
Citation: N/A Interpretive Summary:
Technical Abstract: Methods that can rapidly confirm the identification of foodborne pathogens are highly desired. The USDA has recently entered into a collaborative research agreement with Micro Imaging Technology to evaluate their MIT 1000 microbial identification system for its ability to identify Listeria species including the human pathogen, Listeria monocytogenes. The MIT 1000 is a benchtop instrument that detects laser light (660 nm, 30 mW, 100 'm diameter) scattered from individual bacterial cells, in aqueous suspension, with an array of 35 individually addressed photodiode detectors. Identification is based upon pattern recognition by the automated algorithm-based comparison of averaged scattered light signal and bacteria scatter pattern libraries. Identification times are less than 10 min (often ca. 5 min) and operating costs are extremely low since the detection procedure requires no reagents (e.g., external labels or tags) other than filtered water. Cursory investigations at a USDA research lab have demonstrated the MIT 1000 to have an accuracy of 100% (n=10-30 per species) for the identification of all Listeria spp. with the exception of L. seeligeri. L. seeligeri was only identified with an accuracy of 10% and the reason for this anomaly is currently unknown. Initial attempts at false positive testing have resulted in 0% of incidence for Citrobacter freundii, Brocothrix thermospacta II, Salmonella enterica serovar Typhimurium, Escherichia coli K12, and multiple strains of E. coli O157:H7. However, a 50% false positive rate was observed for Aeromonas hydrophila when tested against the Listeria spp. library. With further development, the MIT 1000 appears to hold promise for use by food producers and regulatory agencies in the microbial testing of foods.