L.G.M. Gorris

Occurrence of Enterobacter sakazakii in food production environments and households

Enterobacter sakazakii occasionally causes illness in premature babies and neonates. Contamination of infant formulae during factory production or bottle preparation is implicated. Advice to health-care professionals focuses on bottle preparation, but the effectiveness of prevention depends on the degree of contamination and contamination sites, which are generally unknown. To keep contamination to a minimum in the finished product depends on knowledge of the occurrence of E sakazakii. We used a refined isolation and detection method to investigate the presence of this micro-organism in various food factories and households. Environmental samples from eight of nine food factories and from five of 16 households contained E sakazakii. The widespread nature of this micro-organism needs to be taken into account when designing preventive control measures.

Effects of Preculturing Conditions on Lag Time and Specific Growth Rate of Enterobacter sakazakii in Reconstituted Powdered Infant Formula

ABSTRACT Enterobacter sakazakii can be present, although in low levels, in dry powdered infant formulae, and it has been linked to cases of meningitis in neonates, especially those born prematurely. In order to prevent illness, product contamination at manufacture and during preparation, as well as growth after reconstitution, must be minimized by appropriate control measures. In this publication, several determinants of the growth of E. sakazakii in reconstituted infant formula are reported. The following key growth parameters were determined: lag time, specific growth rate, and maximum population density. Cells were harvested at different phases of growth and spiked into powdered infant formula. After reconstitution in sterile water, E. sakazakii was able to grow at temperatures between 8 and 47°C. The estimated optimal growth temperature was 39.4°C, whereas the optimal specific growth rate was 2.31 h−1. The effect of temperature on the specific growth rate was described with two secondary growth models. The resulting minimum and maximum temperatures estimated with the secondary Rosso equation were 3.6°C and 47.6°C, respectively. The estimated lag time varied from 83.3 ± 18.7 h at 10°C to 1.73 ± 0.43 h at 37°C and could be described with the hyperbolic model and reciprocal square root relation. Cells harvested at different phases of growth did not exhibit significant differences in either specific growth rate or lag time. Strains did not have different lag times, and lag times were short given that the cells had spent several (3 to 10) days in dry powdered infant formula. The growth rates and lag times at various temperatures obtained in this study may help in calculations of the period for which reconstituted infant formula can be stored at a specific temperature without detrimental impact on health.

Actual distribution of Cronobacter spp. in industrial batches of powdered infant formula and consequences for performance of sampling strategies.

The actual spatial distribution of microorganisms within a batch of food influences the results of sampling for microbiological testing when this distribution is non-homogeneous. In the case of pathogens being non-homogeneously distributed, it markedly influences public health risk. This study investigated the spatial distribution of Cronobacter spp. in powdered infant formula (PIF) on industrial batch-scale for both a recalled batch as well a reference batch. Additionally, local spatial occurrence of clusters of Cronobacter cells was assessed, as well as the performance of typical sampling strategies to determine the presence of the microorganisms. The concentration of Cronobacter spp. was assessed in the course of the filling time of each batch, by taking samples of 333 g using the most probable number (MPN) enrichment technique. The occurrence of clusters of Cronobacter spp. cells was investigated by plate counting. From the recalled batch, 415 MPN samples were drawn. The expected heterogeneous distribution of Cronobacter spp. could be quantified from these samples, which showed no detectable level (detection limit of -2.52 log CFU/g) in 58% of samples, whilst in the remainder concentrations were found to be between -2.52 and 2.75 log CFU/g. The estimated average concentration in the recalled batch was -2.78 log CFU/g and a standard deviation of 1.10 log CFU/g. The estimated average concentration in the reference batch was -4.41 log CFU/g, with 99% of the 93 samples being below the detection limit. In the recalled batch, clusters of cells occurred sporadically in 8 out of 2290 samples of 1g taken. The two largest clusters contained 123 (2.09 log CFU/g) and 560 (2.75 log CFU/g) cells. Various sampling strategies were evaluated for the recalled batch. Taking more and smaller samples and keeping the total sampling weight constant, considerably improved the performance of the sampling plans to detect such a type of contaminated batch. Compared to random sampling, stratified random sampling improved the probability to detect the heterogeneous contamination.

Perspective on the risk to infants in the Netherlands associated with Cronobacter spp. occurring in powdered infant formula

Cronobacter spp. has been responsible for severe infections in infants. Relative risks associated with this organism in powdered infant formula (PIF) have been described in several studies. To set priorities and decide on risk management options, it is important for risk managers to have a quantitative perspective on the absolute level of risk of this pathogen within the totality of the burden of illnesses in the population. This study set-out to establish such a perspective for The Netherlands. It addresses the impact of heterogeneity in the distribution of the micro-organism in PIF on risk levels. Based on the assumptions in this study, 60% of formula-fed infants are estimated not to be exposed to Cronobacter spp. during their neonatal period. The mean exposure was calculated to be about 1cfu per infant over the total neonatal period. Even after thorough mixing, artificially contaminated powder shows counts which are more variable than expected from a normal, homogeneous distribution. Therefore, mean exposure levels may not represent a good basis for calculating risks. The burden of disease of Cronobacter infections to the Dutch population was estimated to be 19-24 Disability Adjusted Life Years (DALYs) per year, of which 95% are due to meningitis. As compared to other illnesses Cronobacter infections represent 0.5-2.4% of the total estimated burden of foodborne infections and intoxications. The organism is estimated to be responsible for 0.5-0.7% of the meningitis burden to the entire population of The Netherlands.

Modelling homogeneous and heterogeneous microbial contaminations in a powdered food product

The actual physical distribution of microorganisms within a batch of food influences quantification of microorganisms in the batch, resulting from sampling and enumeration by microbiological tests. Quantification may be most accurate for batches in which microorganisms are distributed homogeneously. However, when the distribution is non-homogeneous, quantification may result in an under-, or overestimation. In the case of pathogens being non-homogeneously distributed, this heterogeneity will impact on public health. Enumeration data are commonly modelled by the Lognormal distribution. Although the Lognormal distribution can model heterogeneity, it does not allow for complete absence of microorganisms. Studies that validate the appropriateness of using Lognormal or other statistical distributions are scarce. This study systematically investigated laboratory and industrial scale batches of powdered infant formula, modelled the enumeration data using a range of statistical distributions, and assessed the appropriateness of individual models. For laboratory scale experiments, batches of milk powder were contaminated by distributing similar numbers of cells of Cronobacter sakazakii either homogeneously throughout a batch of milk powder or by distributing the cells in a localised part of the batch. Each batch was then systematically sampled and the distribution determined by enumerating the samples. By also enumerating the remainder of the batch, a balance could be made of the total number of microorganisms added and of the number retrieved from a batch. Discrete, as well as continuous statistical distributions, were fitted to enumeration data and the parameters estimated by Maximum Likelihood. The data were fitted both as censored and uncensored data. Enumeration data obtained for an industrial batch of powdered infant formula were investigated in this way as well. It was found that Normal, Poisson and Zero-Inflated Poisson distributions fitted the data sets very poorly. In case of homogeneous contamination, there was not a notable difference between the ability of Negative Binomial, Poisson-Lognormal, Weibull, Gamma, and Lognormal distributions to model the data. Overall, either the Negative Binomial distribution or the Poisson-Lognormal distribution fitted the data best in the 10 batches studied, especially when part of a data set contained zeros and/or the numbers were low. The Negative Binomial fitted the laboratory batches best and the Poisson-Lognormal fitted the industrial batch best.

Factors influencing the accuracy of the plating method used to enumerate low numbers of viable micro-organisms in food

This study aims to assess several factors that influence the accuracy of the plate count technique to estimate low numbers of micro-organisms in liquid and solid food. Concentrations around 10CFU/mL or 100CFU/g in the original sample, which can still be enumerated with the plate count technique, are considered as low numbers. The impact of low plate counts, technical errors, heterogeneity of contamination and singular versus duplicate plating were studied. Batches of liquid and powdered milk were artificially contaminated with various amounts of Cronobacter sakazakii strain ATCC 29544 to create batches with accurately known levels of contamination. After thoroughly mixing, these batches were extensively sampled and plated in duplicate. The coefficient of variation (CV) was calculated for samples from both batches of liquid and powdered product as a measure of the dispersion within the samples. The impact of technical errors and low plate counts were determined theoretically, experimentally, as well as with Monte Carlo simulations. CV-values for samples of liquid milk batches were found to be similar to their theoretical CV-values established by assuming Poisson distribution of the plate counts. However, CV-values of samples of powdered milk batches were approximately five times higher than their theoretical CV-values. In particular, powdered milk samples with low numbers of Cronobacter spp. showed much more dispersion than expected which was likely due to heterogeneity. The impact of technical errors was found to be less prominent than that of low plate counts or of heterogeneity. Considering the impact of low plate counts on accuracy, it would be advisable to keep to a lower limit for plate counts of 25 colonies/plate rather than to the currently advocated 10 colonies/plate. For a powdered product with a heterogeneous contamination, it is more accurate to use 10 plates for 10 individual samples than to use the same 10 plates for 5 samples plated in duplicate.

Risk assessment strategies as a tool in the application of the Appropriate Level of Protection (ALOP) and Food Safety Objective (FSO) by risk managers.

In the course of the last decade, the Appropriate Level of Protection (ALOP), the Food Safety Objective (FSO) and their associated metrics have been proposed by the World Trade Organization and Codex Alimentarius as a means for competent authorities to ultimately translate governmental public health policy regarding food safety into risk-based targets for the food industry. The industry needs to meet these targets through the effective choice of control measures that are part of its operational food safety management system. The aim of this study was to put the practical application of ALOP and FSO to the test in the case of Salmonella in chicken meat in the Netherlands. Two different risk assessment approaches were applied to derive potential ALOP and FSO values, a top-down approach based on epidemiological data and a bottom-up approach based on food supply chain data. To this end, two stochastic models specific to the Dutch situation were built. Comparisons between 23 countries in Europe were also made using the top-down model. The mean estimated current Level Of Protection values were similar for the two approaches applied, with the bottom-up model yielding 87 cases per 100,000 inhabitants per year (95% CI: 0.03, 904) and the top-down model 71 (95% CI: 9.9, 155). The estimated FSO values on the other hand were considerably different with the mean top down FSO being -4.6 log CFU/g (95% CI: -5.4, -4.1) and the mean bottom-up FSO -6.0 log CFU/g (95% CI: -8.1, -2.9) reflecting major differences in the output distributions of this parameter obtained with the two approaches. Significant differences were observed between current LOP values for different EU countries, although it was not clear whether this was due to actual differences in the factors influencing the risk of salmonellosis or due to the quality of the available data.

Inactivation rates of Cronobacter spp. and selected other bacterial strains in powdered infant formulae stored at different temperatures

The aim of this study was to determine the survival of two strains of Cronobacter (Enterobacter sakazakii) and six other bacterial strains inoculated into dry powdered infant formula (PIF) stored for 22 weeks at several temperatures between 7 and 42 degrees C. The experimental setup involved a relatively high initial concentration of bacteria, around 10(4) CFU/g of powder, and enumeration of survivors with a minimum detection level of 100 CFU/g. For all strains tested, it was found that the number of bacterial cells decreased faster with increasing temperature. Cronobacter spp. cells generally survived better at high temperatures (37 and 42 degrees C) than the other bacteria, while such a difference in survival was not apparent at other temperatures. To describe the effect of temperature on survival, both the Weibull distribution model and the log-linear model were tested. At 22 degrees C, decline rates of 0.011 and 0.008 log units per day were found for Cronobacter sakazakii ATCC 29544 and Cronobacter strain MC10, respectively. Assuming a linear relationship between log-transformed D-values and temperature, z-values estimated for C. sakazakii ATCC 29544 and Cronobacter MC10 were 13.3 and 23.5 degrees C, respectively. Such differences found in resistance among Cronobacter spp. would be relevant to consider when establishing quantitative risk assessments on consumer risks related to PIF.

Comparing Nonsynergy Gamma Models and Interaction Models To Predict Growth of Emetic Bacillus cereus for Combinations of pH and Water Activity Values

ABSTRACT This research aims to test the absence (gamma hypothesis) or occurrence of synergy between two growth-limiting factors, i.e., pH and water activity (aw), using a systematic approach for model selection. In this approach, preset criteria were used to evaluate the performance of models. Such a systematic approach is required to be confident in the correctness of the individual components of the combined (synergy) models. With Bacillus cereus F4810/72 as the test organism, estimated growth boundaries for the aw-lowering solutes NaCl, KCl, and glucose were 1.13 M, 1.13 M, and 1.68 M, respectively. The accompanying aw values were 0.954, 0.956, and 0.961, respectively, indicating that equal aw values result in similar effects on growth. Out of the 12 models evaluated using the preset criteria, the model of J. H. T. Luong (Biotechnol. Bioeng. 27:280–285, 1985) was the best model to describe the effect of aw on growth. This aw model and the previously selected pH model were combined into a gamma model and into two synergy models. None of the three models was able to describe the combined pH and aw conditions sufficiently well to satisfy the preset criteria. The best matches between predicted and experimental data were obtained with the gamma model, followed by the synergy model of Y. Le Marc et al. (Int. J. Food Microbiol. 73:219–237, 2002). No combination of models that was able to predict the impact of both individual and combined hurdles correctly could be found. Consequently, in this case we could not prove the existence of synergy nor falsify the gamma hypothesis.