Time-to-turbidity model for non-protective type B Clostridium botulinum

Cardinal parameter growth and growth boundary model for non-proteolytic Clostridium botulinum - Effect of eight environmental factors

A new cardinal parameter growth and growth boundary model for non-proteolytic C. botulinum was developed and validated for fresh and lightly preserved seafood and poultry products. 523 growth rates in broth were used to determine cardinal parameter values and terms for temperature, pH, NaCl/water activity, acetic, benzoic, citric, lactic and sorbic acids. The new growth and growth boundary model included the inhibiting interactive effect between these factors and it was calibrated using growth curves from 10 challenge tests with unprocessed seafood. For model evaluation, 40 challenge tests with well characterized fresh and lightly preserved seafood were performed. Comparison of these observed growth curves and growth rates (μ_max-values) predicted by the new model resulted in a bias factor (B_f) of 1.12 and an accuracy factor (A_f) of 1.40. Furthermore, the new model was evaluated with 94 growth rates and 432 time to toxin formation data extracted from the scientific literature for seafood, poultry, meat, pasta and prepared meals. These data included responses for 36 different toxigenic strains of non-proteolytic C. botulinum. The obtained B_f-/A_f-values were 0.97/2.04 for μ_max-values and 0.96/1.80 for time to toxin formation. The model correctly predicted 93.8% of the growth responses with 5.6% being fail-safe and <1% fail-dangerous. A cocktail of four non-toxin producing Clostridium spp. isolates was used to develop the new model and these isolates had more than 99.8% 16S rRNA gene similarity to non-proteolytic C. botulinum (Group II). The high number of environmental factors included in the new model makes it a flexible tool to facilitate development or reformulation of seafood and poultry products that do not support the growth of non-proteolytic C. botulinum. Further, evaluation of the new model with well characterized products is desirable particularly for meat, vegetables, pasta and prepared meals as well as for dairy products that was not included in the present study.

New Elements To Consider When Modeling the Hazards Associated with Botulinum Neurotoxin in Food

Botulinum neurotoxins (BoNTs) produced by the anaerobic bacterium Clostridium botulinum are the most potent biological substances known to mankind. BoNTs are the agents responsible for botulism, a rare condition affecting the neuromuscular junction and causing a spectrum of diseases ranging from mild cranial nerve palsies to acute respiratory failure and death. BoNTs are a potential biowarfare threat and a public health hazard, since outbreaks of foodborne botulism are caused by the ingestion of preformed BoNTs in food. Currently, mathematical models relating to the hazards associated with C. botulinum, which are largely empirical, make major contributions to botulinum risk assessment. Evaluated using statistical techniques, these models simulate the response of the bacterium to environmental conditions. Though empirical models have been successfully incorporated into risk assessments to support food safety decision making, this process includes significant uncertainties so that relevant decision making is frequently conservative and inflexible. Progression involves encoding into the models cellular processes at a molecular level, especially the details of the genetic and molecular machinery. This addition drives the connection between biological mechanisms and botulism risk assessment and hazard management strategies. This review brings together elements currently described in the literature that will be useful in building quantitative models of C. botulinum neurotoxin production. Subsequently, it outlines how the established form of modeling could be extended to include these new elements. Ultimately, this can offer further contributions to risk assessments to support food safety decision making.

The pattern of growth observed for Clostridium botulinum type A1 strain ATCC 19397 is influenced by nutritional status and quorum sensing: a modelling perspective

Botulinum neurotoxins (BoNTs) produced by the anaerobic bacterium Clostridium botulinum are the most poisonous substances known to mankind. However, toxin regulation and signals triggering synthesis as well as the regulatory network and actors controlling toxin production are unknown. Experiments show that the neurotoxin gene is growth phase dependent for C. botulinum type A1 strain ATCC 19397, and toxin production is influenced both by culture conditions and nutritional status of the medium. Building mathematical models to describe the genetic and molecular machinery that drives the synthesis and release of BoNT requires a simultaneous description of the growth of the bacterium in culture. Here, we show four plausible modelling options which could be considered when constructing models describing the pattern of growth observed in a botulinum growth medium. Commonly used bacterial growth models are unsuitable to fit the pattern of growth observed, since they only include monotonic growth behaviour. We find that a model that includes both the nutritional status and the ability of the cells to sense their surroundings in a quorum-sensing manner is most successful at explaining the pattern of growth obtained for C. botulinum type A1 strain ATCC 19397.

The safety of pasteurised in-pack chilled meat products with respect to the foodborne botulism hazard

There has been a substantial increase in sales of pasteurised in-pack chilled products over the last decade. It is anticipated that this trend will continue. These foods address consumer demand in being of high quality and requiring little preparation time. The microbiological safety of these foods commonly depends on a combination of a minimal heat treatment, refrigerated storage and a restricted shelf-life. The principal microbiological safety hazard for pasteurised in-pack meat products is foodborne botulism, as presented by non-proteolytic Clostridium botulinum. This review provides a summary of research that has contributed to the safe development of these foods without incidence of botulism.

Does proximity to neighbours affect germination of spores of non-proteolytic Clostridium botulinum?

It is recognised that inoculum size affects the rate and extent of bacterial spore germination. It has been proposed that this is due to spores interacting: molecules released from germinated spores trigger germination of dormant neighbours. This study investigated whether changes to the total number of spores in a system or proximity to other spores (local spore density) had a more significant effect on interaction between spores of non-proteolytic Clostridium botulinum strain Eklund 17B attached to defined areas of microscope slides. Both the number of spores attached to the slides and local spore density (number of spores per mm(2)) were varied by a factor of nine. Germination was observed microscopically at 15 °C for 8 h and the probability of, and time to, germination calculated from image analysis measurements. Statistical analysis revealed that the effect of total spore number on the probability of germination within 8 h was more significant than that of proximity to neighbours (local spore density); its influence on germination probability was approximately four-times greater. Total spore number had an even more significant affect on time to germination; it had a nine-fold greater influence than proximity to neighbours. The applied models provide a means to characterise, quantitatively, the effect of the total spore number on spore germination relative to the effect of proximity to neighbouring spores.

Implications of salt and sodium reduction on microbial food safety

Excess sodium consumption has been cited as a primary cause of hypertension and cardiovascular diseases. Salt (sodium chloride) is considered the main source of sodium in the human diet, and it is estimated that processed foods and restaurant foods contribute 80% of the daily intake of sodium in most of the Western world. However, ample research demonstrates the efficacy of sodium chloride against pathogenic and spoilage microorganisms in a variety of food systems. Notable examples of the utility and necessity of sodium chloride include the inhibition of growth and toxin production by Clostridium botulinum in processed meats and cheeses. Other sodium salts contributing to the overall sodium consumption are also very important in the prevention of spoilage and/or growth of microorganisms in foods. For example, sodium lactate and sodium diacetate are widely used in conjunction with sodium chloride to prevent the growth of Listeria monocytogenes and lactic acid bacteria in ready-to-eat meats. These and other examples underscore the necessity of sodium salts, particularly sodium chloride, for the production of safe, wholesome foods. Key literature on the antimicrobial properties of sodium chloride in foods is reviewed here to address the impact of salt and sodium reduction or replacement on microbiological food safety and quality.

Safety-based shelf life model for frankfurters based on time to detect Listeria monocytogenes with initial inoculum below detection limit

The growth of Listeria monocytogenes inoculated on frankfurters at four inoculum levels (0.1, 0.04, 0.01, and 0.007 CFU/g) was examined at 4, 8, and 12 degrees C until the time L. monocytogenes populations reached a detectable limit of at least 2 CFU/g. A scaled-down assumption was made to simulate a 25-g sample from a 100-lb batch size in a factory setting by using a 0.55-g sample from a 1,000-g batch size in a laboratory. Samples of 0.55 g were enriched in PDX-LIB selective medium, and presumptive results were confirmed on modified Oxford agar. Based on the time to detect (TTD) from each inoculum level and at each temperature, a shelf life model was constructed to predict the detection or risk levels reached by L. monocytogenes on frankfurters. The TTD increased with reductions in inoculum size and storage temperature. At 4 degrees C the TTDs (+/- standard error) observed were 42.0 +/- 1.0, 43.5 +/- 0.5, 50.7 +/- 1.5, and 55.0 +/- 3.0 days when the inoculum sizes were 0.1, 0.04, 0.01, and 0.007 CFU/g, respectively. From the same corresponding inoculum sizes, the TTDs at 8 degrees C were 4.5 +/- 0.5, 6.5 +/- 0.5, 7.0 +/- 1.0, and 8.5 +/- 0.5 days. Significant differences (P < 0.05) between TTDs were observed only when the inoculum sizes differed by at least 2 log. On a shelf life plot of 1n (TTD) versus temperature, the Q10 (increase in TTD for a 10 degrees C increase in temperature) values ranged from 24.5 to 44.7 and with no significant influence from the inoculum densities. When the observed TTDs were compared with the expected detection times based on the data obtained from a study with an inoculum size of 10 to 20 CFU/g, significant deviations were noted at lower inoculum levels. These results can be valuable in designing a safety-based shelf life model for frankfurters and in performing quantitative risk assessment of listeriosis at low and practical contamination levels.

Estimating risk from small inocula by using population growth parameters

Risk from an uncertain small inoculum depends on variability of single-cell lag times. However, quantifying single-cell variability is technically challenging. It is possible to estimate this variability using population growth parameters. We demonstrate this possibility using data from literature and show a Bayesian scheme for performing this task.

Clostridium botulinum and the safety of minimally heated, chilled foods: an emerging issue?

Foodborne botulism is caused by consumption of preformed botulinum neurotoxin, with as little as 30 ng of neurotoxin being potentially lethal. Consumption of minute quantities of neurotoxin-containing food can result in botulism. In view of the severity of foodborne botulism, it is essential that new foods be developed safely without an increase in incidence of this disease. Minimally heated, chilled foods are a relatively new type of food, sales of which are currently increasing by about 10% per annum. These products meet consumer demand for high-quality foods that require little preparation time. Their safety and quality depends on mild heat treatment, chilled storage, restricted shelf life and sometimes on intrinsic properties of the foods. The principal microbiological hazard is nonproteolytic Clostridium botulinum, and there is a concern that this may become an emerging issue. A considerable amount of research and development over the last 15 years has underpinned the safe production of commercial, minimally heated, chilled foods with respect to foodborne botulism, and it is essential that safe food continues to be developed. In particular, the desire to use lighter heat processes and a longer shelf life presents a challenge that will only be met by significant developments in quantitative microbiological food safety.

Historical and contemporary NaCl concentrations affect the duration and distribution of lag times from individual spores of nonproteolytic clostridium botulinum

In this study we determined the effect of NaCl concentration during sporulation (0 or 3.0% [wt/vol] added NaCl) and subsequent growth (0 or 2.0% [wt/vol] added NaCl) on the distributions of times associated with various stages of the lag phase of individual spores of nonproteolytic Clostridium botulinum strain Eklund 17B. The effects of NaCl on the probability of germination and the probability of subsequent growth were also determined. Spore populations exhibited considerable heterogeneity at all stages of lag phase for each condition tested. Germination time did not correlate strongly with the times for later stages in the lag phase, such as outgrowth and doubling time. Addition of NaCl to either the sporulation or growth media increased the mean times for, and variability of, all the measured stages of the lag phase (germination, emergence, time to one mature cell, and time to first doubling). There was a synergistic interaction between the inhibitory effects of NaCl in the sporulation medium and the inhibitory effects of NaCl in the subsequent growth medium on the total lag time and each of its stages. Addition of NaCl to either the sporulation medium or the growth medium reduced both the probability of germination and the probability of a germinated spore developing into a mature cell, but the interaction was not synergistic. Spores formed in medium with added NaCl were not better adapted to subsequent growth in suboptimal osmotic conditions than spores formed in medium with no added NaCl were. Knowledge of the distribution of lag times for individual spores and quantification of the biovariability within lag time distributions may provide insight into the underlying mechanisms and can be used to improve predictions of growth in food and to refine risk assessments.

Response surface model for prediction of growth parameters from spores of Clostridium sporogenes under different experimental conditions

Clostridium sporogenes is considered to be a non-toxingenic equivalent of proteolytic Clostridium botulinum, and it also causes food spoilage. The effects of temperature (16.6-33.4 degrees C), pH value (5.2-6.8) and concentration of sodium chloride (0.6-7.4%) on the growth parameters of C. sporogenes spores were investigated. The growth curves generated within different conditions were fitted using Baranyi function. Two growth parameters (growth rate, GR; lag-time, LT) of the growth curves under combined effects of temperature, pH and sodium chloride were modeled using a quadratic polynomial equation of response surface (RS) model. Mathematical evaluation demonstrated that the standard error of prediction (%SEP) obtained by RS model was 1.033% for GR and was 0.166% for LT for model establishing. The %SEP for model validation were 43.717% and 5.895% for GR and LT, respectively. The root-mean-squares error (RMSE) was in acceptable range which was less than 0.1 for GR and was less than 8.0 for LT. Both the bias factor (B(f)) and accuracy factor (A(f)) approached 1.0, which were within acceptable range. Therefore, RS model provides a useful and accurate method for predicting the growth parameters of C. sporogenes spores, and could be applied to ensure food safety with respect to proteolytic C. botulinum control.

Heterogeneity of times required for germination and outgrowth from single spores of nonproteolytic Clostridium botulinum

Knowledge of the distribution of growth times from individual spores and quantification of this biovariability are important if predictions of growth in food are to be improved, particularly when, as for Clostridium botulinum, growth is likely to initiate from low numbers of spores. In this study we made a novel attempt to determine the distributions of times associated with the various stages of germination and subsequent growth from spores and the relationships between these stages. The time to germination (t(germ)), time to emergence (t(emerg)), and times to reach the lengths of one (t(C1)) and two (t(C2)) mature cells were quantified for individual spores of nonproteolytic C. botulinum Eklund 17B using phase-contrast microscopy and image analysis. The times to detection for wells inoculated with individual spores were recorded using a Bioscreen C automated turbidity reader and were compatible with the data obtained microscopically. The distributions of times to events during germination and subsequent growth showed considerable variability, and all stages contributed to the overall variability in the lag time. The times for germination (t(germ)), emergence (t(emerg) - t(germ)), cell maturation (t(C1) - t(emerg)), and doubling (t(C2) - t(C1)) were not found to be correlated. Consequently, it was not possible to predict the total duration of the lag phase from information for just one of the stages, such as germination. As the variability in postgermination stages is relatively large, the first spore to germinate will not necessarily be the first spore to produce actively dividing cells and start neurotoxin production. This information can make a substantial contribution to improved predictive modeling and better quantitative microbiological risk assessment.

Effect of ethanol on the growth of Clostridium botulinum

Model broth studies were carried out to investigate the effect of ethanol on the growth of proteolytic (group I) strains of Clostridium botulinum. Ethanol extended the pathogen's lag phase, decreased its exponential growth rate, and decreased its final level of growth in the stationary phase. In all cases, botulinum neurotoxin production was associated with growth. Micrographs of C. botulinum cultures grown at 37 degrees C in trypticase peptone glucose yeast extract (TPGY) broths containing 2 and 4% ethanol showed elongation of vegetative cells and interference with cell division. The inhibition of growth and toxin production at the ethanol level predicted (5.5%, wt/wt) was confirmed by microscopy and by the mouse bioassay. A subsequent study was carried out to determine the combined effect of ethanol (0 to 8% [wt/wt]), water activity (aw; 0.953 to 0.997), and pH (6.2 to 8.2) on the probability of the growth of and neurotoxin production by proteolytic strains of C. botulinum (10(3) spores per ml). Growth and neurotoxin production occurred in 1 to 3 days in TPGY broths without ethanol (0%) and in 2 to 4 days in broths containing 2% ethanol regardless of the aw or pH levels (P < 0.005). Growth and neurotoxin production were delayed by an ethanol concentration of 4% ethanol and completely inhibited by a concentration of 6%. At an ethanol concentration of 4%, the probability of growth and toxin production over 365 days (Pt) was influenced by aw and pH. After 365 days, the maximum probability of growth and toxin production (Pmax) was 1 for all but one combination. However, tau, the time it took for 50% of all eventually positive replicates for any given combination of barriers to show growth and/or turbidity, ranged from <3 to 229 days. All tubes of TPGY broths that showed no growth after 365 days were subcultured in fresh TPGY broths. In all cases, growth and toxin production occurred within 24 h at 37 degrees C, indicating the reversible (sporostatic and/or bacteriostatic) effect of ethanol on C. botulinum.

Time-to-detection, percent-growth-positive and maximum growth rate models for Clostridium botulinum 56A at multiple temperatures

We previously developed models for the influence of inoculum size on the growth kinetics (time-to-detection and maximum growth rate) and percent-growth-positive samples of Clostridium botulinum 56A with factors of inoculum size (1, 100, and 10,000 spores/sample). pH (5.5. 6.0 and 6.5) and sodium chloride concentration (0.5%, 2% and 4%) at 30 degrees C. In this present study, data were collected at two more temperatures (15 and 22 degrees C), making the final design a complete 3 X 3 X 3 X 3 factorial with a total of 81 conditions. Growth was followed hourly as change in A620. The Gompertz equation was fit to the growth data, and the parameters derived were used to calculate the maximum growth rate and time-to-detection. Linear regression with polynomial terms was used to analyze the effect of environmental factors on time-to-detection and maximum growth rate. Logistic regression with polynomial terms was used to analyze the data for percent-growth-positive. Despite the fact that the variance is larger in this extended data set (which includes two temperatures that are further away from the optimum), the inoculum size effect is clearly demonstrated. When inoculum size increased, the percent-growth-positive samples increased and the time-to-detection decreased. When the inoculum was 1000 spores/sample or higher, little additional effect on time-to-detection was observed. Inoculum size might influence results through simple probability or quorum sensing. Our results show that the observed effect of inoculum size from the previous report at a single temperature is not restricted to a specific growth condition, but rather a general phenomenon. The maximum growth rate was independent of inoculum levels, confirming our previous results.

Bacillus megaterium spore germination is influenced by inoculum size

AIMS

The effect of spore density on the germination (time-to-germination, percent germination) of Bacillus megaterium spores on tryptic soy agar was determined using direct microscopic observation.

METHODS AND RESULTS

Inoculum size varied from approximately 10(3) to 10(8) cfu ml(-1) in a medium where pH=7 and the sodium chloride concentration was 0.5% w/v. Inoculum size was measured by global inoculum size (the concentration of spores on a microscope slide) and local inoculum size (the number of spores observed in a given microscope field of observation). Both global and local inoculum sizes had a significant effect on time-to-germination (TTG), but only the global inoculum size influenced the percentage germination of the observed spores.

CONCLUSIONS

These results show that higher concentrations of Bacillus megaterium spores encourage more rapid germination and more spores to germinate, indicating that low spore populations do not behave similarly to high spore populations.

SIGNIFICANCE AND IMPACT OF THE STUDY

A likely explanation for the inoculum size-dependency of germination would be chemical signalling or quorum sensing between Bacillus spores.

Comparison of logistic regression and linear regression in modeling percentage data

Percentage is widely used to describe different results in food microbiology, e.g., probability of microbial growth, percent inactivated, and percent of positive samples. Four sets of percentage data, percent-growth-positive, germination extent, probability for one cell to grow, and maximum fraction of positive tubes, were obtained from our own experiments and the literature. These data were modeled using linear and logistic regression. Five methods were used to compare the goodness of fit of the two models: percentage of predictions closer to observations, range of the differences (predicted value minus observed value), deviation of the model, linear regression between the observed and predicted values, and bias and accuracy factors. Logistic regression was a better predictor of at least 78% of the observations in all four data sets. In all cases, the deviation of logistic models was much smaller. The linear correlation between observations and logistic predictions was always stronger. Validation (accomplished using part of one data set) also demonstrated that the logistic model was more accurate in predicting new data points. Bias and accuracy factors were found to be less informative when evaluating models developed for percentage data, since neither of these indices can compare predictions at zero. Model simplification for the logistic model was demonstrated with one data set. The simplified model was as powerful in making predictions as the full linear model, and it also gave clearer insight in determining the key experimental factors.

Modeling the germination kinetics of clostridium botulinum 56A spores as affected by temperature, pH, and sodium chloride

The germination kinetics of proteolytic Clostridium botulinum 56A spores were modeled as a function of temperature (15, 22, 30 degrees C), pH (5.5, 6.0, 6.5), and sodium chloride (0.5, 2.0, 4.0%). Germination in brain heart infusion (BHI) broth was followed with phase-contrast microscopy. Data collected were used to develop the mathematical models. The germination kinetics expressed as cumulated fraction of germinated spores over time at each environmental condition were best described by an exponential distribution. Quadratic polynomial models were developed by regression analysis to describe the exponential parameter (time to 63% germination) (r2 = 0.982) and the germination extent (r2 = 0.867) as a function of temperature, pH, and sodium chloride. Validation experiments in BHI broth (pH: 5.75, 6.25; NaCl: 1.0, 3.0%; temperature: 18, 26 degrees C) confirmed that the model's predictions were within an acceptable range compared to the experimental results and were fail-safe in most cases.

The effect of 100% CO2 on the growth of nonproteolytic Clostridium botulinum at chill temperatures

The growth of a cocktail of spores from six nonproteolytic Clostridium botulinum type B and E isolates at 5 and 10 degrees C was used to assess the combined effect of NaCl (0.5-4.5% w/v), pH (5.5-6.5) and atmosphere (10% H2:90% N2, 5% CO2:10% H2:85% N2, or 100% CO2) in buffered peptone, yeast, glucose, starch broth with an Eh of approximately -350 mV. Under all atmospheres growth tended to be slower as the concentration of NaCl increased and with NaCl combined with pH levels below 6.0. Of the atmospheres tested, growth occurred at a slower rate and over a narrower range of conditions when C. botulinum was exposed to 100% CO2. This effect was enhanced when the incubation temperature was 5 degrees C. The results indicate that while CO2 decreased C. botulinum growth at chill temperatures, prevention of growth also depended on the NaCl concentration and the pH of the medium.

Probabilistic modeling of Saccharomyces cerevisiae inhibition under the effects of water activity, pH, and potassium sorbate concentration

Probabilistic microbial modeling using logistic regression was used to predict the boundary between growth and no growth of Saccharomyces cerevisiae at selected incubation periods (50 and 350 h) in the presence of growth-controlling factors such as water activity (a(w); 0.97, 0.95, and 0.93), pH (6.0, 5.0, 4.0, and 3.0), and potassium sorbate (0, 50, 100, 200, 500, and 1,000 ppm). The proposed model predicts the probability of growth under a set of conditions and calculates critical values of a(w), pH, and potassium sorbate concentration needed to inhibit yeast growth for different probabilities. The reduction of pH increased the number of combinations of a(w) and potassium sorbate concentration with probabilities to inhibit yeast growth higher than 0.95. With a probability of growth of 0.05 and using the logistic models, the critical pH values were higher for 50 h of incubation than those required for 350 h. With lower a(w) values and increasing potassium sorbate concentration the critical pH values increased. Logistic regression is a useful tool to evaluate the effects of the combined factors on microbial growth.

A predictive model that describes the effect of prolonged heating at 70 to 90 degrees C and subsequent incubation at refrigeration temperatures on growth from spores and toxigenesis by nonproteolytic Clostridium botulinum in the presence of lysozyme

Refrigerated processed foods of extended durability such as cook-chill and sous-vide foods rely on a minimal heat treatment at 70 to 95 degrees C and then storage at a refrigeration temperature for safety and preservation. These foods are not sterile and are intended to have an extended shelf life, often up to 42 days. The principal microbiological hazard in foods of this type is growth of and toxin production by nonproteolytic Clostridium botulinum. Lysozyme has been shown to increase the measured heat resistance of nonproteolytic C. botulinum spores. However, the heat treatment guidelines for prevention of risk of botulism in these products have not taken into consideration the effect of lysozyme, which can be present in many foods. In order to assess the botulism hazard, the effect of heat treatments at 70, 75, 80, 85, and 90 degrees C combined with refrigerated storage for up to 90 days on growth from 10(6) spores of nonproteolytic C. botulinum (types B, E, and F) in an anaerobic meat medium containing 2,400 U of lysozyme per ml (50 microg per ml) was studied. Provided that the storage temperature was no higher than 8 degrees C, the following heat treatments each prevented growth and toxin production during 90 days; 70 degrees C for >/=2,545 min, 75 degrees C for >/=463 min, 80 degrees C for >/=230 min, 85 degrees C for >/=84 min, and 90 degrees C for >/=33.5 min. A factorial experimental design allowed development of a predictive model that described the incubation time required before the first sample showed growth, as a function of heating temperature (70 to 90 degrees C), period of heat treatment (up to 2,545 min), and incubation temperature (5 to 25 degrees C). Predictions from the model provided a valid description of the data used to generate the model and agreed with observations made previously.

Analysis of the influence of environmental parameters on Clostridium botulinum time-to-toxicity by using three modeling approaches

This study used the technique of waiting time modeling to analyze the combined effects of temperature, pH, carbohydrate, protein, and lipid on the time-to-toxicity of Clostridium botulinum 56A. Waiting time models can be used whenever the time to the occurrence of some event is the variable of interest. In the case of the time-to-toxicity data, the variable is the time from the beginning of an experiment until a tube is identified as positive. The statistical analysis used the SAS procedure LIFEREG and included determination of the form of the response surface, identification of the error distribution, and simplification of the response surface. We found that increasing the macromolecule concentration decreased the probability of toxin formation. The probability of toxin formation also decreased at lower temperatures and at pHs further from the optimum. The waiting time modeling approach to developing models for botulinal toxin formation compared favorably with other approaches but had one specific advantage. Waiting time models have the inherent advantage that safety concerns regarding predictions are automatically quantified in the analysis by formally identifying a distribution of times-to-toxicity. The use of this time-to-toxicity distribution permits a customizable margin of safety (e.g., one in a million) not possible with other approaches.

The effect of temperature on the germination of single spores of Clostridium botulinum 62A

Phase-contrast microscopy coupled with image analysis has been used to study the germination of single spores of Clostridium botulinum and to investigate the variation of germination lag of individual spores in a population (biovariability). The experiment was repeated at five different temperatures between 20 degrees C and 37 degrees C to look at the effect of temperature on the biovaribility of the spore germination. Data analysis shows that the germination lag distribution is skewed, with a tail, and that its shape is affected by the temperature. The origin of this biovariability is not exactly known, but could be due to a distribution of characteristics (e.g. permeabilities) or molecules (e.g. lytic enzymes) in the spore population. The method developed in this study will help us to describe and better understand the kinetics of spore germination and how this is influence by different environmental factors such as temperature and other factors that influence germination.