Strain Variability in Growth and Thermal Inactivation Characteristics of Listeria monocytogenes Strains after Acid Adaptation

Abstract

ABSTRACT Given the importance of strain variability to predictive microbiology and risk assessment, this study aimed to quantify the magnitude of strain variability in growth and thermal inactivation kinetics behaviors after acid adaptation. Thirty-three Listeria monocytogenes strains were exposed to acid-adapted tryptic soy broth supplemented with yeast extract (TSBYE; pH 5.5) and non–acid-adapted TSBYE (pH 7.0) for 20 h. Next, the growth parameters of these adapted and nonadapted strains that grew in nonbuffered TSBYE at 25°C were estimated. The tested strains were inactivated at 60°C in nonbuffered broth to obtain the heat resistance parameters. The results revealed that strain variability was present in the growth and thermal inactivation characteristics. The maximum specific growth rate ranged from 0.21 to 0.44 h−1 and from 0.20 to 0.45 h−1 after acid and nonacid adaptation, respectively. The lag times were from 0.69 to 2.56 h and from 0.24 to 3.36 h for acid-adapted and non–acid-adapted cells, respectively. The apparent D-values at 60°C of the pathogen ranged between 0.56 and 3.93 min and between 0.52 and 3.63 min for the presence and absence of acid adaptation condition, respectively. Acid adaptation significantly (P < 0.05) increased the magnitude of strain variability in the thermal inactivation characteristics of L. monocytogenes, with the coefficient of variation increasing to 0.17, whereas acid adaptation did not significantly (P ≥ 0.05) influence the variabilities in the growth parameters of the tested strains. Furthermore, the subsequent growth behaviors of all strains did not exhibit significant (P > 0.05) changes after exposure to acidic broth. However, the thermal resistance of most (25 of 33) of the tested strains increased (P < 0.05) after growing in acid-adapted broth. The relevant data generated in the present study can be used to describe the strain variability in predictive microbiology and to deeply understand the behavioral responses of different strains to acid adaptation. HIGHLIGHTS