The effect of inoculum size and sublethal injury on the ability of Listeria monocytogenes to initiate growth under suboptimal conditions

Abstract

Aims: To investigate the effect of inoculum size and physiological state on the ability of Listeria monocytogenes cells to initiate growth under suboptimal conditions of salt concentration and pH. Methods and Results: Cell suspensions were serially diluted in media of different salt concentration or pH and replicate inocula distributed into 96-well microplates. The proportion of wells showing growth at each dilution level was determined after incubation for 6 weeks for each set of conditions. Growth occurred from single cells up to a concentration of 1á2 mol l )1 NaCl; above this threshold, the inoculum size needed to initiate growth became progressively larger. A similar effect was seen with decreasing pH but only very close to the growth/no growth boundary. The threshold for inoculum-dependent growth was lower in exponential phase cells than in stationary phase ones and sublethal injury greatly decreased the probability of growth from small inocula. Conclusions: The growth/no growth boundary for L. monocytogenes is not an absolute cut-off point but represents a region where the probability of growth rapidly decreases as conditions become more extreme. We interpret the requirement for a critical inoculum size for growth as being due to death of a proportion of cells in the inoculum rather than to co-operative population effects. Signi®cance and Impact of the Study: Physiological heterogeneity within the cell population and inoculum size will affect the risk of L. monocytogenes growing in food.

Evaluation of a challenge testing protocol to assess the stability of ready-to-eat cooked meat products against growth of Listeria monocytogenes

“…No growth of the L. monocytogenes strains was observed for the BHI adjusted to pâté conditions after 21 days when a low inoculum level was used. It was established that under more severe stress conditions none of the cultures grew when the inoculum size was too low (less than 10 3 cells) whereas growth is noted with a higher inoculum Pascual et al, 2001). The experiment for the BHI adjusted to pâté conditions was repeated with a high inoculum level (10 7 -10 5 cfu/ml) and these results are shown in Fig.…”

“…A challenge test in which the inoculum contains too many organisms may overstress the preservative system of a product which would not normally be at risk and lead to an overestimation of the risk, whereas too few organisms may give false negative results (Rose and Stringer, 1987). Studies have shown that beneath the common inoculation level of 1000 cfu/ml, the lag phase becomes longer and the probability of growth is less (Gay et al, 1996;Robinson et al, 2001;Pascual et al, 2001). Farber and Daley (1994) found that when L. monocytogenes was present in very low numbers on meats such as sliced ham, turkey breasts, wieners, and pâté stored at 4 jC, its numbers did not increase.…”

“…It was shown that in media with suboptimal conditions for growth, both the mean lag time and variation between replicate inoculum increased as the inoculum size became smaller . The effect of inoculum size for stationary phase cells would only be affected for numbers of less than 100 cells Gay et al, 1996) except for extreme stress conditions (growth/ no growth boundary) Pascual et al, 2001). As low numbers were inoculated on the RTE meat products, initially enumeration of the pathogen on the samples was not possible.…”

Influence of Stress on Individual Lag Time Distributions of Listeria monocytogenes

“…Recently, some individual lag time distributions have been characterized (23,33). The variability of individual lag times seems to be wider as microorganisms are injured (4,33,34,39) or as growth conditions are unfavorable (23,24,27).…”

Alternative Approach To Modeling Bacterial Lag Time, Using Logistic Regression as a Function of Time, Temperature, pH, and Sodium Chloride Concentration

“…The bacterial lag time is affected by the current environmental conditions, as well as various other factors, such as the history of the population or cell, preculturing conditions, the magnitude and rate of change in the environment (11,21,22,35), initial cell counts (3,27,30), and strain variability. In the present study, we did not employ these factors as parameters; however, we could use the effects of the population history, initial cell counts, and strain variability as parameters in a logistic regression model due to the flexible nature of the model.…”