Influence of stress on single-cell lag time and growth probability for Listeria monocytogenes in half Fraser broth

Abstract

The impacts of 12 common food industry stresses on the single-cell growth probability and single-cell lag time distribution of Listeria monocytogenes were determined in half Fraser broth, the primary enrichment broth of the International Organization for Standardization detection method. First, it was determined that the ability of a cell to multiply in half Fraser broth is conditioned by its history (the probability for a cell to multiply can be decreased to 0.05), meaning that, depending on the stress in question, the risk of false-negative samples can be very high. Second, it was established that when cells are injured, the single-cell lag times increase in mean and in variability and that this increase represents a true risk of not reaching the detection threshold of the method in the enrichment broth. No relationship was observed between the impact on single-cell lag times and that on growth probabilities. These results emphasize the importance of taking into account the physiological state of the cells when evaluating the performance of methods to detect pathogens in food.

FIG. 1.

Plots of single-cell growth probability (a) and of means of single-cell lag times (b) of L. monocytogenes in 1/2FB at 30°C versus the percentages of injury resulting from BAC (1), nitrite (2), starvation (3), HCl (4), freezing (5), peracetic acid (6), phenol (7), NaOH (8), acetic acid (9), NaCl (10), lactic acid (11), and heat (12) stresses.

FIG. 2.

Plot of single-cell growth probability in 1/2FB at 30°C versus the loss of cultivability on TSAye for Listeria monocytogenes strains INRA101 (1), ADQP101 (2), UNIR100 (3), LM14 (4), Scott A (5), and EGDe (6) after starvation stress (a) and osmotic stress (b). Points and error bars represent the means and standard deviations of parameters for replicated experiments, respectively.

FIG. 3.

Proportions of Listeria monocytogenes cells able to initiate growth, after a stress with low impact, the starvation stress (black bars), or after one with high impact (white bars)—BAC stress (a), heat stress (b), or osmotic stress (c)—in 1/2FB at 30°C supplemented with microflora and/or food components to simulate the enrichment phase of fermented meat product (a) and core of red-smear soft cheese (b) and to study the effect of wild microflora isolated from various food samples and multiplying in 1/2FB (c). Error bars represent the between-experiment standard deviations.

FIG. 4.

Observed cumulative distributions (•) of single-cell lag times of Listeria monocytogenes in 1/2FB at 30°C with fitted EVIIb distributions (solid lines) and best-fitting distributions other than EVIIb (dashed lines for lognormal [LN] or Weibull [Weib] distributions). Cells were previously stressed by BAC (a), nitrite (b), starvation (c), HCl (d), freezing (e), peracetic acid (f), phenol (g), NaOH (h), acetic acid (i), NaCl (j), and lactic acid (k). x axes show τ_i (h); y axes show cumulative distribution function.

FIG. 5.

Relationship between means and standard deviations of the single-cell lag times of Listeria monocytogenes. Shown are data obtained in this study in 1/2FB at 30°C and calculated from the EVIIb parameter values (•) and data obtained by Guillier and Augustin (22) (▪) for 54 different physiological states, growth conditions, and strains in TSBye. The solid line is the major axis regression line. (Adapted from reference with permission from Elsevier.)

FIG. 6.

Plot of means of single-cell lag times versus the single-cell growth probability of Listeria monocytogenes in 1/2FB at 30°C resulting from BAC (1), nitrite (2), starvation (3), HCl (4), freezing (5), peracetic acid (6), phenol (7), NaOH (8), acetic acid (9), NaCl (10), lactic acid (11), and heat (12) stresses.