Enabling Cost-Effective Screening for Antimicrobials against Listeria monocytogenes in Ham

Abstract

ABSTRACT Ready-to-eat meat products, such as deli ham, can support the growth of Listeria monocytogenes (LM), which can cause severe illness in immunocompromised individuals. The objectives of this study were to validate a miniature ham model (MHM) against the ham slice method and to screen antimicrobial combinations to control LM on ham by using response surface methology (RSM) as a time- and cost-effective high-throughput screening tool. The effect of nisin (Ni), potassium lactate and sodium diacetate, lauric arginate (LAG), lytic bacteriophage (P100), and ε-polylysine (EPL) added alone, or in combination, were determined on the MHM over 12 days of storage. Results showed the MHM accurately mimics the ham slice method because no statistical differences were found (P = 0.526) in the change of LM cell counts in MHM and slice counts after 12 days of storage at 4°C for treated and untreated hams. The MHM was then used to screen antimicrobial combinations by using an on-face design and three center points in a central composite design. The RSM was tested by using a cocktail of five LM strains isolated from foodborne disease outbreaks. Three levels of the previously mentioned antimicrobials were used in combination for a total of 28 runs performed in triplicate. The change of LM cell counts were determined after 12 days of storage at 4°C. All tested antimicrobials were effective on reducing LM cell counts on ham when added alone. A significant antagonistic interaction (P = 0.002) was identified by the RSM between LAG and P100, where this antimicrobial combination caused a 2.2-log CFU/g change of LM cell counts after 12 days of storage. Two interactions, between Ni and EPL (P = 0.058), and Ni and P100 (P = 0.068), showed possible synergistic effects against LM on the MHM. Other interactions were clearly nonsignificant, suggesting additive effects. In future work, the developed MHM in combination with RSM can be used as a high-throughput method to analyze novel antimicrobial treatments against LM. HIGHLIGHTS