Effects of Citrus sinensis Essential Oil and Intrinsic and Extrinsic Factors on the Growth and ToxinProducing Ability of Clostridium botulinum Type A

Background: Considering the high fatality of botulism, the control of Clostridium botulinum and its neurotoxins has clinical importance. In this regard, using chemical preservatives, natural essential oils (Eos), and changes in the growth predisposing factors of bacteria are suitable methods to control the growth and toxin producing of C. botulinum in foods. Objective: The current survey was done to assess the effects of Citrus sinensis EO and intrinsic and extrinsic factors on the growth and toxin producing of C. botulinum type A. Materials and Methods: In this experiment with a factorial design, C. sinensis EO (0.0%, 0.015%, 0.03%, and 0.045%), nisin (0, 500, and 1500 IU/mL), nitrite (0, 20, and 60 ppm), pH (5.5 and 6.5), storage temperature (25 and 35° C), and sodium chloride (NaCl, 0.5% and 3%) were used to assess bacterial growth in the brain heart infusion medium. Finally, the mouse bioassay method was also used to assess toxicity. Results: Clostridium sinensis EO with a concentration of 0.045%, as well as the reduction of pH and temperature could significantly delay the growth of bacteria (P≤0.05) in contrast to the use of NaCl and nisin alone. However, all concentrations of sodium chloride (NaCl), nisin, and C. sinensis EO (< 0.045%) in interaction with each other, especially in combination with nitrite, showed good synergistic effects. Conclusion: These results suggested that using certain concentrations of C. sinensis EO and nisin, along with other suboptimal factors caused a significant decrease in the nitrite contents of foods with a significant reduction in the growth and toxin-producing ability of C. botulinum.

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.

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.

Influence of several methodological factors on the growth of Clostridium perfringens in cooling rate challenge studies

Proper temperature control is essential in preventing Clostridium perfringens food poisoning. The U.S. Department of Agriculture Food Safety and Inspection Service cooling guidelines offer two options for the cooling of meat products: follow a standard time-temperature schedule or validate that alternative cooling regimens result in no more than a 1-log CFU/g increase of C. perfringens and no growth of Clostridium botulinum. The latter option requires laboratory challenge studies to validate the efficacy of a given cooling process. Accordingly, the objective of this study was to investigate the role of several methodological variables that might be encountered during typical C. perfringens challenge studies. Variables studied included plastic bag type (Whirlpak or Spiral Biotech), sealing method (Multivac or FoodSaver), initial spore inoculum size (1 to approximately 3 log CFU/g), and growth environment (ground beef or Trypticase-peptone-glucose-yeast extract [TPGY] broth). The major factors that affected growth were sample bag type and growth environment. Samples incubated in Whirlpak bags showed significantly less growth than those incubated in Spiral Biotech bags, which was likely due to the former bag's greater oxygen permeability. C. perfringens spores showed shorter germination, outgrowth, and lag times and C. perfringens cells showed faster growth rates in ground beef compared with TPGY broth. No significant difference was observed between two different sealing methods. Initial spore inoculum levels in the range studied had no significant effect on final C. perfringens cell concentration.

Evaluation of a Clostridium perfringens predictive model, developed under isothermal conditions in broth, to predict growth in ground beef during cooling

Proper temperature control is essential in minimizing Clostridium perfringens germination, growth, and toxin production. The U.S. Department of Agriculture (USDA) Food Safety and Inspection Service (FSIS) offers two options for the cooling of meat products: follow a standard time-temperature schedule or validate that alternative cooling regimens result in no more than a 1-log(10) CFU/g increase of C. perfringens and no growth of Clostridium botulinum. A mathematical model developed by Juneja et al. (Food Microbiol. 16:335-349, 1999) may be helpful in determining if the C. perfringens performance standard has been achieved, but this model has not been extensively validated. The objective of this study was to validate the Juneja 1999 model in ground beef under a variety of changing temperature and temperature abuse situations. The Juneja 1999 model consistently underpredicted growth of C. perfringens during exponential cooling of ground beef. The model also underpredicted growth of C. perfringens in ground beef cooled at two different rates. The results presented here show generally good agreement with published data on the growth of C. perfringens in similar products. The model error may be due to faster-than-expected exponential growth rates in ground beef during cooling or an error in the mathematical formulation of the model.

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.

Proposal of a novel parameter to describe the influence of pH on the lag phase of Listeria monocytogenes

Predictive models for lag phase duration (lambda) have been less reliable than specific growth rate (mu) models due, in part, to the influence of the pre-growth environment on lambda. A discrete modelling approach was taken to more completely define the response of individual cells to new environments. Time to detection (td) data was obtained from serial twofold dilutions of Listeria monocytogenes growing in a Bioscreen at 30 degrees C. Comparison of the inoculum densities required to achieve maximum td at growth pH values from 7.2 to 4.7 revealed that, as the growth pH decreased, fewer cells were capable of making the transition to the exponential phase. The proportion of these cells (termed "adaptable cells") in the original inoculum was used to define a new parameter (r0) which, when combined with the constant mean individual cell physiological state parameter (p0), the variation in p0 (SDp0), the inital inoculum (N0) and the maximum population density (Nmax) was able to simulate a complete growth curve. Power transformations with rescaled explanatory variables provided suitable models for the influence of pH on mu, r0, and SDp0, (r2>0.70).

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.