Synergistic Effect of Heat and Elevated Hydrostatic Pressure for Inactivation of Listeria monocytogenes
Recent epidemiological investigations derived from CDC active surveillance data indicates 99% of illnesses caused by Listeria monocytogenes are foodborne in nature, leading to hospitalizations in 94% of episodes, and are collectively responsible for estimated 266 annual deaths of American adults. Current study investigates effects of elevated hydrostatic pressure on cell reduction and inactivation rates of Listeria monocytogenes at 4 and 55ºC. Various times (0 to 10 minutes) and intensity levels (0 to 380 MPa) of elevated hydrostatic pressure were investigated for inactivation of Listeria monocytogenes inoculated into phosphate-buffered saline at target population of 7.5 log CFU/mL. Temperature was monitored, and maintained at 4 and 55 ºC by a circulating water bath and a stainless steel water jacket surrounding the chamber. The experiment was conducted in two biologically independent repetitions, as blocking factors of a randomized complete block design, containing three repetitions per time/temperature/pressure within each block. Experiment was analyzed by GLM procedure of SAS using Tukey- and Dunnett-adjusted ANOVA. The inactivation Kmax and D-values were calculated using best-fitted (maximum R2) model obtained by GInaFiT software. At 380 MPa (0 to 10 minutes), D-value of 2.81 min and inactivation Kmax of 1.60±0.41 1/min were observed at 4 ºC. At 55 ºC, these values were 1.59, and 3.94±0.96, respectively. At 4 ºC, the pathogen were reduced (P< 0.05) by 3.84, 2.44, and 1.05 log CFU/mL after exposure to 10 minutes of hydrostatic pressure at 380, 310, and 240 MPa, respectively. These reductions (P< 0.05) were >7.13, 6.36, and 4.53 for 10-minute treatments at 55 ºC, respectively. Treatments below two minutes were less efficacious (P ≥ 0.05) against the pathogen in vast majority of the tested time, temperature, and pressure combinations. Results of this study could be incorporated as part of a risk assessment modeling and predictive microbiology for reducing the public health burden of listeriosis.