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Variability in Cell Response of Cronobacter sakazakii after Mild-Heat Treatments and Its Impact on Food Safety.

Parra-Flores J, Juneja V, Garcia de Fernando G, Aguirre J - Front Microbiol (2016)

Bottom Line: Stochastic approaches can better describe microbial single cell response than deterministic models as we prove in this study.This variability increased as the heat shock increased and growth temperature decreased.The mean probability of illness from initial inoculum size of 1 cell was below 0.2 in all the cases and for inoculum size of 50 cells the mean probability of illness, in most of the cases, was above 0.7.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Nutrición y Salud Pública, Universidad del Bío-Bío Chillán, Chile.

ABSTRACT
Cronobacter spp. have been responsible for severe infections in infants associated with consumption of powdered infant formula and follow-up formulae. Despite several risk assessments described in published studies, few approaches have considered the tremendous variability in cell response that small micropopulations or single cells can have in infant formula during storage, preparation or post process/preparation before the feeding of infants. Stochastic approaches can better describe microbial single cell response than deterministic models as we prove in this study. A large variability of lag phase was observed in single cell and micropopulations of ≤50 cells. This variability increased as the heat shock increased and growth temperature decreased. Obviously, variability of growth of individual Cronobacter sakazakii cell is affected by inoculum size, growth temperature and the probability of cells able to grow at the conditions imposed by the experimental conditions should be taken into account, especially when errors in bottle-preparation practices, such as improper holding temperatures, or manipulation, may lead to growth of the pathogen to a critical cell level. The mean probability of illness from initial inoculum size of 1 cell was below 0.2 in all the cases and for inoculum size of 50 cells the mean probability of illness, in most of the cases, was above 0.7.

No MeSH data available.


Related in: MedlinePlus

Simulation output of stochastic (gray diamonds) and deterministic (continuos black lines) growth models of an individual C. sakazakii at 5 (A), 10 (B), 15 (C), and 25 °C (D) and treated with 50°C by 0, 5, and 10 min (numbers 1, 2, and 3, respectively). Discontinuous vertical lines (A2) represent the time at which deterministic and stochastic models reach the concentration of 103 CFU/ml. Stochastic predictions for the growth of a single cell using Monte Carlo simulation with 10,000 iterations.
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Figure 3: Simulation output of stochastic (gray diamonds) and deterministic (continuos black lines) growth models of an individual C. sakazakii at 5 (A), 10 (B), 15 (C), and 25 °C (D) and treated with 50°C by 0, 5, and 10 min (numbers 1, 2, and 3, respectively). Discontinuous vertical lines (A2) represent the time at which deterministic and stochastic models reach the concentration of 103 CFU/ml. Stochastic predictions for the growth of a single cell using Monte Carlo simulation with 10,000 iterations.

Mentions: Figure 3 shows the fitted distributions together with the density data for λ and μmax of one cell based on the stochastic growth model (Eq. 2) in TSB at 5 (A), 10 (B), 15 (C), and 25°C (D) and simulated using Monte Carlo approach with 10.000 iterations and the deterministic growth model of Baranyi and Roberts (1994) fitted to data of C. sakazakii in PIF. From the stochastic approach it can be observed that the higher the heat treatment, the higher the dispersion of the data [from right (3) to the left (1)]. This dispersion decreased as the growth temperature increased [from 5°C (A) to 25°C (D], indeed deterministic and stochastic approaches were similar at 25°C (Figures 3D1–D3). In addition, it can be observed that the tendency of the fitted model is situated in the average of the stochastic outputs. For example, at 5°C, the stochastic growth model predicted that the dangerous dose level of 1000 CFU/ml was reached at 250 min (discontinuous black line Figure 3A2), while the deterministic approach indicated that this concentrations was reached after 490 min (discontinuous gray line Figure 3A2) from a single survivor that was heat shocked at 50°C for 5 min and growing at 5°C. A similar tendency was observed in the simulations of an inoculum size of 50 cells (results not shown). In addition, it can be observed in the vertical discontinuous gray line in Figure 3B2, the differences in the concentrations at the time 190 min (when deterministic model reaches 1000 CFU/ml), the stochastic growth model at the same time can have concentrations ranging from 0 to 107 CFU/ml.


Variability in Cell Response of Cronobacter sakazakii after Mild-Heat Treatments and Its Impact on Food Safety.

Parra-Flores J, Juneja V, Garcia de Fernando G, Aguirre J - Front Microbiol (2016)

Simulation output of stochastic (gray diamonds) and deterministic (continuos black lines) growth models of an individual C. sakazakii at 5 (A), 10 (B), 15 (C), and 25 °C (D) and treated with 50°C by 0, 5, and 10 min (numbers 1, 2, and 3, respectively). Discontinuous vertical lines (A2) represent the time at which deterministic and stochastic models reach the concentration of 103 CFU/ml. Stochastic predictions for the growth of a single cell using Monte Carlo simulation with 10,000 iterations.
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4836016&req=5

Figure 3: Simulation output of stochastic (gray diamonds) and deterministic (continuos black lines) growth models of an individual C. sakazakii at 5 (A), 10 (B), 15 (C), and 25 °C (D) and treated with 50°C by 0, 5, and 10 min (numbers 1, 2, and 3, respectively). Discontinuous vertical lines (A2) represent the time at which deterministic and stochastic models reach the concentration of 103 CFU/ml. Stochastic predictions for the growth of a single cell using Monte Carlo simulation with 10,000 iterations.
Mentions: Figure 3 shows the fitted distributions together with the density data for λ and μmax of one cell based on the stochastic growth model (Eq. 2) in TSB at 5 (A), 10 (B), 15 (C), and 25°C (D) and simulated using Monte Carlo approach with 10.000 iterations and the deterministic growth model of Baranyi and Roberts (1994) fitted to data of C. sakazakii in PIF. From the stochastic approach it can be observed that the higher the heat treatment, the higher the dispersion of the data [from right (3) to the left (1)]. This dispersion decreased as the growth temperature increased [from 5°C (A) to 25°C (D], indeed deterministic and stochastic approaches were similar at 25°C (Figures 3D1–D3). In addition, it can be observed that the tendency of the fitted model is situated in the average of the stochastic outputs. For example, at 5°C, the stochastic growth model predicted that the dangerous dose level of 1000 CFU/ml was reached at 250 min (discontinuous black line Figure 3A2), while the deterministic approach indicated that this concentrations was reached after 490 min (discontinuous gray line Figure 3A2) from a single survivor that was heat shocked at 50°C for 5 min and growing at 5°C. A similar tendency was observed in the simulations of an inoculum size of 50 cells (results not shown). In addition, it can be observed in the vertical discontinuous gray line in Figure 3B2, the differences in the concentrations at the time 190 min (when deterministic model reaches 1000 CFU/ml), the stochastic growth model at the same time can have concentrations ranging from 0 to 107 CFU/ml.

Bottom Line: Stochastic approaches can better describe microbial single cell response than deterministic models as we prove in this study.This variability increased as the heat shock increased and growth temperature decreased.The mean probability of illness from initial inoculum size of 1 cell was below 0.2 in all the cases and for inoculum size of 50 cells the mean probability of illness, in most of the cases, was above 0.7.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Nutrición y Salud Pública, Universidad del Bío-Bío Chillán, Chile.

ABSTRACT
Cronobacter spp. have been responsible for severe infections in infants associated with consumption of powdered infant formula and follow-up formulae. Despite several risk assessments described in published studies, few approaches have considered the tremendous variability in cell response that small micropopulations or single cells can have in infant formula during storage, preparation or post process/preparation before the feeding of infants. Stochastic approaches can better describe microbial single cell response than deterministic models as we prove in this study. A large variability of lag phase was observed in single cell and micropopulations of ≤50 cells. This variability increased as the heat shock increased and growth temperature decreased. Obviously, variability of growth of individual Cronobacter sakazakii cell is affected by inoculum size, growth temperature and the probability of cells able to grow at the conditions imposed by the experimental conditions should be taken into account, especially when errors in bottle-preparation practices, such as improper holding temperatures, or manipulation, may lead to growth of the pathogen to a critical cell level. The mean probability of illness from initial inoculum size of 1 cell was below 0.2 in all the cases and for inoculum size of 50 cells the mean probability of illness, in most of the cases, was above 0.7.

No MeSH data available.


Related in: MedlinePlus