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Modelling the effect of a heat shock and germinant concentration on spore germination of a wild strain of Bacillus cereus
International Journal of Food Microbiology 106 (2006) 85 – 89 www.elsevier.com/locate/ijfoodmicro
Short communication
Modelling the effect of a heat shock and germinant concentration on spore germination of a wild strain of Bacillus cereus J. Collado 1, A. Ferna´ndez, M. Rodrigo, A. Martı´nez * Instituto de Agroquı´mica y Tecnologı´a de Alimentos (CSIC), Apartado de Correos 73, 46100 Burjassot, Valencia, Espan˜a (Spain) Received 5 March 2005; accepted 11 June 2005
Abstract The effect of different concentrations of l-alanine on the germination kinetics of a strain of Bacillus cereus isolated from liquid egg after heat shock during sporulation was studied. Germination at 30 -C and was followed by spectrophotometry. The higher the concentration of l-alanine within the range 100 – 1 mM the faster was the germination obtained. On the other hand, the application of a heat shock had an effect on the germination producing a diminution on the germination kinetic rates. The Weibull distribution function, a model that has been used for describing inactivation kinetics [Collado, J., Ferna´ndez, A., Cunha, L., Ocio, M.J., Martı´nez, 2003. Improved model based on the Weibull distribution to describe the combined effect of pH and temperature on the heat resistance of three strains of Bacillus cereus in carrot juice. Journal of Food Protection 66 (6), 978 – 984; Loss, C.R., Hotchkiss, S.H., 2004. Determination of thermal inactivation kinetics of microorganisms with continuous micro flow apparatus. Journal of Food Protection 67 (11) 2560 – 2564; Chen, H., Hoover, D.G., 2004. Use of Weibull model to describe and predict pressure inactivation of Lysteria monocytogenes Scott A in whole milk. Innovative Food Science and Emerging Technologies 5 (3) 269 – 276; Guerrero, S., Tognom, M., Alzamora, S.M., 2005. Response of Saccharomyces cerevisiae to the combined action of ultrasound and low weight chitosan. Food Control 16 (2) 131 – 139], was used for modelling germination experimental data. Results indicated that the Weibull distribution function model produced a good description of experimental data. D 2005 Elsevier B.V. All rights reserved. Keywords: Weibull distribution; Spore germination kinetic; l-Alanine; Heat shock
1. Introduction Bacillus cereus is capable of producing several toxins (Finlay et al., 2000). Spores of Bacillus cereus are highly resistant to chemical and physical agents (Kanda et al., 1991). A severe heat treatment can destroy the majority of spores and it can also negatively affect the standards of quality and freshness demanded by modern consumers. Because of that, new technologies based on mild heat treatments have been applied by the food industry but food safety could be endangered. Additionally, some products like raw liquid egg, due to the coagulation of its proteins, cannot be processed at temperatures above 65 –70 -C. The presence of spores in those products could be a food safety problem.
* Corresponding author. Tel.: +34 96 3900022; fax: +34 96 363 6301. E-mail address: [email protected] (A. Martı´nez). 1 This is a part of J. Collado’s PhD Thesis. 0168-1605/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.ijfoodmicro.2005.06.009
Attempts to model germination of bacterial spores are scarce. McCormick (1964) developed an empirically derived equation that described the time-course of the decrease in optical density during spore germination. Vary and Halvorson (1965) also used the McCormick equation to describe the germination process, but no kinetic parameters were deduced. More recently, Mafart (1995) proposed an empirical equation with three parameters in order to describe the timecourse of germination. Modelling germination can be of great value since the use of predictive microbiology can help to unveil how environmental factors affect microbial behaviour and provide a rational framework for understanding the microbiology ecology of food (Ross and McMeekin, 1994) and for risk assessment. Germination models can be used together with inactivation and growth models in order to provide an estimate of the level of a pathogen in a product at the point of consumption. In this study, the effect of l-alanine concentration on the germination properties of Bacillus cereus after a heat shock during sporulation was studied and modelled.
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J. Collado et al. / International Journal of Food Microbiology 106 (2006) 85 – 89
a shaker thermostatic water bath (J.P. Selecta) was employed. The heat shock was applied 1 h after the end of the exponential growth phase (Movahedi and Waites, 2000).
2. Materials and methods 2.1. Spore preparation A non-collection strain (wild strain) of Bacillus cereus was isolated from raw liquid egg. The strain was identified by amplification of the internal spacer region (ISR) (Ocio et al., 2003) and cultured overnight in nutrient broth according to British pharmacopoeia (Sharlau Chemie, Barcelona, Spain) containing (per l): meat extract, 1 g; yeast extract, 2 g; peptone, 5 g; and NaCl, 5 g. 1 ml of this suspension was inoculated in 2.5-l flasks, which contained 500 ml of liquid sporulation medium adjusted to pH 7.0. The sporulation medium used in this study is that described by Mazas et al. (1995) with slight modifications and without agar containing (per l): nutrient broth according to British pharmacopoeia (Sharlau Chemie), 13 g; agar bacteriological (Sharlau Chemie), 20 g; NaCl (Sharlau Chemie), 3 g; MnSO4IH2O (Sharlau Chemie), 0.05 g; CaCl2 (Panreac, Montplet & Esteban, Barcelona, Spain), 0.06 g; glucose (Panreac, Montplet & Esteban), 0.1 g; (NH4)2SO4 (Merck, Merck KGaA, Darmstadt, Germany), 0.08 g; MnCl2I4H2O (Merck, Merck KGaA), 0.008 g; CuSO4I5H2O (Panreac, Montplet & Esteban), 0.005 g; ZnSO4I7H2O (Panreac, Montplet & Esteban), 0.005 g. The flasks were incubated in an incubator (J.P. Selecta, Barcelona, Spain) at 30 -C and 100 rpm. The evolution of sporulation was checked daily by using phase contrast microscopy. After 4 days, when the spore crop contained approximately 95% of phase bright spores, it was harvested and washed with sterilised distilled water by repeated centrifugation at 2500g and stored at 4 -C until use. A second sporulation was performed; in this case, a heat shock was applied. The heat shock treatment consisted of changing the temperature of sporulation from 30 -C to 48 -C during 30 min (Movahedi and Waites, 2000). For that purpose,
2.2. Spore germination studies l-Alanine, one of the most important amino acids, provided by Sigma-Aldrich Chemie, Steinheim, Germany, was used to trigger germination. An aqueous solution of this amino acid was prepared and sterilised by filtration using a 0.45-Am syringe filter (Millipore, Molsheim, France). After suffering a heat activation process at 65 -C for 20 min, a suspension of spores was mixed with 0.05 mM Tris buffer (pH 7) and different concentrations of l-alanine (100, 10 and 1 mM) in a sterile tube to give a final volume of 2 ml. The tube was incubated in a shaker incubator adjusted at 30 -C and 150 rpm. Every 15 min, a sample of 1 ml was taken and then the germination was followed by the decrease in the optical density by measuring the absorbance at 625 nm using a spectrophotometer (Spectronic Genesys 5.0, Milton Roy Company, New York, USA) (McCormick, 1964). Then the sample was returned to the tube, which remained in the shaker incubator during the entire assay. The experiment lasted 180 min and was carried out in duplicate. The data were randomly split up into two sets (Tejadillos et al., 2003). The first set, the largest one, containing 61.5% of data, was used to fitting the model and the second set was used for validating it. 2.3. Modelling The kinetics of germination of a spore suspension represents the summation of events occurring in the individual spores of that population (Vary and Halvorson, 1965). Consequently, the germination of spores can be described by
1 0.9
1- (ODt/ODi)
0.8 0.7
100mM (a)
0.6
10mM(a) 1mM(a)
0.5
100mM (b)
0.4
10mM(b) 0.3 1mM (b) 0.2 0.1 0 0
50
100 Time(min)
150
200
Fig. 1. Germination of Bacillus cereus for different concentrations of l-alanine. Clear symbols (a): heat shocked. Solid symbols (b): non-heat shocked.
J. Collado et al. / International Journal of Food Microbiology 106 (2006) 85 – 89 Table 1 Results of the analysis of variance with repeated measures Source
Sum of squares type III
df
Square mean
F
p-value
Intercept Cases Error
47.974 2.142 3.541
1 1 10
47.974 2.142 0.354
135.470 6.050
0.000 0.034
Cases = heat shocked or not shocked cells during the sporulation process.
a distribution function. The Weibull model is one of the distribution functions used to describe the behaviour of systems or events having some degree of variability (Ferna´ndez et al., 1999). In our case, the Weibull has been used as follows (Eq. (1)): t b
S ¼ e ð a Þ
ð1Þ
t ODf The value of S is given by the relation OD ODi ODf . This is the fraction of ungerminated spores, where ODt is the optical density at time t, ODi is the initial optical density and ODf is the final limiting value of optical density at the completion of germination. The germination has been expressed as the percentage decrease in OD during a constant time interval (Rode and Foster, 1962). The parameter a can be considered as a reaction rate constant, whereas b can be regarded as a behaviour index (Cunha et al., 1998). One of the main requirements when fitting a model to experimental data is to verify the accuracy of that particular model. Examination of the residuals (defined as the difference between observed and fitted data) was used as a basic tool to check the suitability of the adjusted model. The predictive quality of the model was assessed by an external validation using as mentioned earlier the data set kept in reserve for validation. As an index of the predictive quality, the accuracy factor described by Ross (1996) was used.
87
Table 2 Values of a (rate index) and b (behaviour index) for Bacillus cereus spore germination using the Weibull model (spores coming from non-heat shocked cells during the sporulation process) and their 95% confidence intervals l-Alanine concentration
a
b
100 mM 10 mM 1 mM
26.59 T 0.89 29.01 T 4.75 45.02 T 4.99
0.77 T 0.03 0.75 T 0.14 0.91 T 0.15
Model assessment and parameter estimation were performed by statistical software SPSS version 9.0 (SPSS Inc., Chicago, IL, USA). 3. Results and discussion Fig. 1 shows the effect of l-alanine concentration on spore t reduction. Germination, expressed as 1 OD ODi , increased with increasing concentrations of germinant, obtaining the highest rate and level of germination for 100 mM. This result is similar to that obtained by McCormick (1964) using other l-alanine concentrations for Bacillus cereus T spores. On the other hand, the germination level reached when Bacillus cereus underwent a heat shock of 30 min at 40 -C (clear symbols), during the sporulation process, was lower as compared with those of nonheat shocked experiments (solid symbols). The influence of the heat shock on the germination level was analysed by performing an analysis of variance with repeated measures (Crowder and Hand, 1990). Table 1 shows the results of this analysis. Since the p-value associated with the heat shock is lower than 0.05, there is a significant effect of the heat shock on the decrease in the concentration of spores. These results might reflect an alteration on the germination mechanism due to the heat shock received by cells during sporulation. This can be important, because temperature changes during the production, storage and distribution of food could affect the germination response of spores present in foodstuffs. This fact should be taken into account on exposure
1,2 1 100Mm (a) 10mM (a) 1mM (a) 100mM (b) 10 mM (b) 1mM (b)
1-S
0,8 0,6 0,4 0,2 0 0
50
100 Time (min)
150
200
Fig. 2. Fit of the Weibull model to the experimental for different concentrations of l-alanine. Clear symbols (a): heat shocked. Solid symbols (b): non-heat shocked.
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J. Collado et al. / International Journal of Food Microbiology 106 (2006) 85 – 89
assessment analysis because it is likely to influence the contamination level at consumption. Fig. 2 illustrates the fit of the Weibull model to the experimental data. Tables 2 and 3 show the values of parameters a and b for the fitted model. Parameter a can be considered as a rate index indicating that the germination process accelerates when the germinant concentration is increased. The values of a obtained for spores coming from not heat-shocked cells were lower than those obtained for spores coming from cells that had suffered a heat shock during sporulation. A higher value of a means that, in some way, the heat shock slows down the process of germination. As indicated by Cunha (1998) and Cunha et al. (1998), the b parameter can be considered as a behaviour index that indicates the kinetic pattern of the mechanism controlling the process, and therefore it should be independent of external factors. This fact has been reported by other authors (Knorr and Heinz, 1996; Mafart et al., 2002; Ferna´ndez et al., 2002). The similarity of the values obtained for the b parameter led us to consider the possibility of maintaining the b parameter as a constant in order to simplify the construction of a secondary model in the near future. To check the suitability of this assumption, an F-test was performed. The results indicated ( pvalue < 0.05) that, from the statistical point of view, the assumption of maintaining the b parameter as a constant is not advisable. Finally we applied an external validation of the model. The result obtained indicated that the accuracy factor ranged from 1.03 to 1.15. These accuracy factors indicate that the predictions, as an average, differ between 3% and 15% from experimental data. Due to its biological importance, spore germination has been investigated in this century. Although germination properties of many strains of different spore formers, such as Clostridium botulinum (Ismaiel and Pierson, 1990; Chea et al., 2000), Bacillus subtilis (Yasuda and Tochikubo, 1985; Paidhungat et al., 2001), Bacillus stearothermophilus (Cheung et al., 1998) or Bacillus cereus (Knaysi, 1964; Chaibi et al., 1996; Clements and Moir, 1998), have been studied, data about strains isolated from food are scarce. However, the study of kinetics of germination, death or growth considering these strains is of great importance because they are the ones best adapted to a particular food and consequently they can create food safety problems (Gaulin et al., 2002). Besides, it is essential to consider that the response of strains isolated from foodstuffs to environ-
Table 3 Values of a (rate index) and b (behaviour index) for Bacillus cereus spore germination using the Weibull model (spores coming heat shocked cells during the sporulation process) and their 95% confidence intervals l-Alanine concentration
a
b
100 mM 10 mM 1 mM
74.15 T 6.37 87.86 T 7.48 87.82 T 7.67
1.54 T 0.30 0.89 T 0.13 1.14 T 0.20
mental factors can be very different when compared to the response observed in collection strains. It is important to note that the food industry, commonly, applies mild heat treatments, such as pasteurisation in order to destroy vegetative cells of a pathogenic bacterium. It should also be noted that this pasteurisation process can activate the dormant spores present in the food. As a consequence if appropriate temperature and time are given, for instance when delays in the cooling process occur, these spores could germinate easily and become new vegetative cells. This is of great importance since even at low temperatures (12 -C), vegetative cells of Bacillus cereus can produce emetic toxin (Finlay et al., 2000). Induced germination, by applying a germinant before the pasteurisation process, can give technological advantages because, as germinated spores can be easily eliminated at temperatures around 65 -C – 70 -C, it can prevent excessive spore concentration after this mild heat treatment. Therefore, a good knowledge of the germination process and its associate kinetics could lead to obtaining a higher safety level, especially when dealing with minimally heat-treated or non-thermal preserved products. This study confirmed that Bacillus cereus spores germinates well in the presence of l-alanine and showed that changes of temperature during sporulation can affect to spore germination since it could affect, in some way, the mechanism that controls the process. Consequently, when dealing with foods, in which spores can be present, it is important to consider that changes of temperature during its elaboration, distribution and storage might have taken place and have an effect on the germination response of the spores that are present. Due to its importance, the germination process should be taken into account in modelling microbial food safety. Additionally, non-deterministic models for germination, growth and inactivation are needed in order to develop appropriate exposure assessment models. This study has demonstrated the usefulness of the Weibull model to describe the germination kinetics of a wild strain of Bacillus cereus. Acknowledgments Authors want to thank CICYT through the project AGL2000-1511, the Ministerio de Educacio´n, Cultura y Deporte and the European Union for supporting this work through a Marie Curie Fellowship awarded to J. Collado. Author J. Collado wants to thank The University of Nottingham and specially Professor William Waites for his valuable advice. References Chaibi, A., Ababouch, L.H., Busta, F., 1996. Inhibition of monoglycerides of lalanine-triggered Bacillus cereus and Clostridium botulinum spore germination and outgrowth. Journal of Food Protection 59, 832 – 837. Chea, F., Chen, Y., Montville, T.J., Schaffner, D., 2000. Modelling the germination kinetics of Clostridium botulinum 56A as affected by
J. Collado et al. / International Journal of Food Microbiology 106 (2006) 85 – 89 temperature, pH and sodium chloride. Journal of Food Protection 63, 1071 – 1079. Chen, H., Hoover, D.G., 2004. Use of Weibull model to describe and predict pressure inactivation of Lysteria monocytogenes Scott A in whole milk. Innovative Food Science and Emerging Technologies 5 (3), 269 – 276. Cheung, H.Y., So, C.W., Sun, S.Q., 1998. Interfering mechanism of sodium bicarbonate on spore germination of Bacillus stearothermophilus. Journal of Applied Microbiology 84, 619 – 626. Clements, M., Moir, A., 1998. Role of the gerI operon of Bacillus cereus 569 in the response of spores to germinants. Journal of Bacteriology 180, 6729 – 6735. Collado, J., Ferna´ndez, A., Cunha, L., Ocio, M.J., Martı´nez, A., 2003. Improved model based on the Weibull distribution to describe the combined effect of pH and temperature on the heat resistance of three strains of Bacillus cereus in carrot juice. Journal of Food Protection 66 (6), 978 – 984. Crowder, M.J., Hand, D.J., 1990. Analysis of Repeated Measures. Chapman & Hall, London. Cunha, L.M., 1998. Experimental design procedures and data analysis strategies for improved estimation of the kinetic parameters of non-linear models used in food research. PhD thesis, Catholic University of Portugal, Porto, Portugal. Cunha, L.M., Oliveira, F.A.R., Oliveira, J.C., 1998. Optimal experimental design for estimating the kinetic parameters of processes described by the Weibull probability distribution function. Journal of Food Engineering 37, 175 – 191. Ferna´ndez, A., Salmero´n, C., Ferna´ndez, P.S., Martı´nez, A., 1999. Application of a frequency distribution model to describe the thermal inactivation of two strains of Bacillus cereus. Trends in Food Science and Technology 10, 158 – 162. Ferna´ndez, A., Collado, J., Cunha, L., Ocio, M.J., Martı´nez, A., 2002. Empirical model building based on the Weibull distribution to describe the joint effect of pH and temperature on the thermal resistance of Bacillus cereus in vegetable substrate. International Journal of Food Microbiology 77, 147 – 153. Finlay, W.J., Logan, N.A., Sutherland, A.D., 2000. Bacillus cereus produces most emetic toxin at lower temperature. Letters in Applied Microbiology 31, 385 – 389. Gaulin, C., Viger, YB., Fillion, L., 2002. An outbreak of Bacillus cereus implicating a part-time banquet caterer. Canadian Journal of Public Health 93 (5), 353 – 355. Guerrero, S., Tognom, M., Alzamora, S.M., 2005. Response of Saccharomyces cerevisiae to the combined action of ultrasound and low weight chitosan. Food Control 16 (2), 131 – 139. Ismaiel, A., Pierson, M., 1990. Inhibition of growth and germination of C. botulinum 33A, 40B and 1623E by essential oil of spices. Journal of Food Science 65, 1676 – 1678. Kanda, K., Yasuda, Y., Tochikubo, K., 1991. Germination response of Bacillus subtilis PCI219 spores to caramelized sugar and l-asparagine. Journal of Food Science 56, 1399 – 1403.
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Knaysi, G., 1964. Effect of temperature on the rate of germination in Bacillus cereus. Journal of Bacteriology 87, 619 – 622. Knorr, D., Heinz, V., 1996. High pressure inactivation kinetics of Bacillus subtilis cells by a three-state-model considering distributed resistance mechanism. Food Technology 10, 149 – 161. Loss, C.R., Hotchkiss, S.H., 2004. Determination of thermal inactivation kinetics of microorganisms with continuous micro flow apparatus. Journal of Food Protection 67 (11), 2560 – 2564. Mafart, P., 1995. Modelling germination kinetics of spores of Clostridium tyrobutyricum: a tool for predictive microbiology. Journal of Applied Bacteriology 78, 477 – 480. Mafart, P., Couvert, O., Gaillard, S., Leguerinel, I., 2002. On calculating sterility in thermal preservation methods: application of the Weibull frequency distribution model. International Journal of Food Microbiology 72, 107 – 113. Mazas, M., Gonza´lez, I., Lo´pez, M., Gonza´lez, J., Martı´n, R., 1995. Effects of sporulation media and strain on thermal resistance of Bacillus cereus spores. International Journal of Food Science & Technology 30, 71 – 78. McCormick, N., 1964. Kinetics of spore germination. Journal of Bacteriology 89, 1180 – 1185. Movahedi, S., Waites, W., 2000. A two-dimensional protein gel electrophoresis study of the heat stress response of Bacillus subtilis cells during sporulation. Journal of Bacteriology 182, 4758 – 4763. Ocio, M.J., Estrada, B., Pinto, B., Aznar, R., 2003. Identification of Bacillus cereus group isolates by ISR amplification. Bacillus 2003. Applications and systematics of Bacillus and relatives. Programme book. Ljubljana, Slovenia. Paidhungat, M., Ragkousi, K., Setlow, P., 2001. Genetic requirements for induction of germination of spores of Bacillus stearothermophilus by Ca2+dipicolinate. Journal of Bacteriology 183, 4886 – 4893. Rode, L.J., Foster, J.W., 1962. Ionic germination of spores of Bacillus megaterium QMB1551. Archives of Microbiology 43, 183 – 200. Ross, T., 1996. Indices of performance evaluation of predictive models in food microbiology. Journal of Applied Bacteriology 81, 501 – 508. Ross, T., McMeekin, T.A., 1994. Predictive microbiology. Review paper. International Journal of Food Microbiology 23, 241 – 264. Tejadillos, S., Armero, C., Periago, P., Martı´nez, A., 2003. A regression model describing the effect of pH, NaCl and temperature on D values of Bacillus stearothermophilus. European Food Research and Technology 216, 535 – 538. Vary, J.C., Halvorson, H.O., 1965. Kinetics of germination of Bacillus cereus. Journal of Bacteriology 89, 1340 – 1347. Yasuda, Y., Tochikubo, K., 1985. Disappearance of the co-operative effect of glucose on l-alanine binding during heat activation of germination of Bacillus subtilis spores. Microbiology and Immunology 29, 229 – 235.
Short communication
Modelling the effect of a heat shock and germinant concentration on spore germination of a wild strain of Bacillus cereus J. Collado 1, A. Ferna´ndez, M. Rodrigo, A. Martı´nez * Instituto de Agroquı´mica y Tecnologı´a de Alimentos (CSIC), Apartado de Correos 73, 46100 Burjassot, Valencia, Espan˜a (Spain) Received 5 March 2005; accepted 11 June 2005
Abstract The effect of different concentrations of l-alanine on the germination kinetics of a strain of Bacillus cereus isolated from liquid egg after heat shock during sporulation was studied. Germination at 30 -C and was followed by spectrophotometry. The higher the concentration of l-alanine within the range 100 – 1 mM the faster was the germination obtained. On the other hand, the application of a heat shock had an effect on the germination producing a diminution on the germination kinetic rates. The Weibull distribution function, a model that has been used for describing inactivation kinetics [Collado, J., Ferna´ndez, A., Cunha, L., Ocio, M.J., Martı´nez, 2003. Improved model based on the Weibull distribution to describe the combined effect of pH and temperature on the heat resistance of three strains of Bacillus cereus in carrot juice. Journal of Food Protection 66 (6), 978 – 984; Loss, C.R., Hotchkiss, S.H., 2004. Determination of thermal inactivation kinetics of microorganisms with continuous micro flow apparatus. Journal of Food Protection 67 (11) 2560 – 2564; Chen, H., Hoover, D.G., 2004. Use of Weibull model to describe and predict pressure inactivation of Lysteria monocytogenes Scott A in whole milk. Innovative Food Science and Emerging Technologies 5 (3) 269 – 276; Guerrero, S., Tognom, M., Alzamora, S.M., 2005. Response of Saccharomyces cerevisiae to the combined action of ultrasound and low weight chitosan. Food Control 16 (2) 131 – 139], was used for modelling germination experimental data. Results indicated that the Weibull distribution function model produced a good description of experimental data. D 2005 Elsevier B.V. All rights reserved. Keywords: Weibull distribution; Spore germination kinetic; l-Alanine; Heat shock
1. Introduction Bacillus cereus is capable of producing several toxins (Finlay et al., 2000). Spores of Bacillus cereus are highly resistant to chemical and physical agents (Kanda et al., 1991). A severe heat treatment can destroy the majority of spores and it can also negatively affect the standards of quality and freshness demanded by modern consumers. Because of that, new technologies based on mild heat treatments have been applied by the food industry but food safety could be endangered. Additionally, some products like raw liquid egg, due to the coagulation of its proteins, cannot be processed at temperatures above 65 –70 -C. The presence of spores in those products could be a food safety problem.
* Corresponding author. Tel.: +34 96 3900022; fax: +34 96 363 6301. E-mail address: [email protected] (A. Martı´nez). 1 This is a part of J. Collado’s PhD Thesis. 0168-1605/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.ijfoodmicro.2005.06.009
Attempts to model germination of bacterial spores are scarce. McCormick (1964) developed an empirically derived equation that described the time-course of the decrease in optical density during spore germination. Vary and Halvorson (1965) also used the McCormick equation to describe the germination process, but no kinetic parameters were deduced. More recently, Mafart (1995) proposed an empirical equation with three parameters in order to describe the timecourse of germination. Modelling germination can be of great value since the use of predictive microbiology can help to unveil how environmental factors affect microbial behaviour and provide a rational framework for understanding the microbiology ecology of food (Ross and McMeekin, 1994) and for risk assessment. Germination models can be used together with inactivation and growth models in order to provide an estimate of the level of a pathogen in a product at the point of consumption. In this study, the effect of l-alanine concentration on the germination properties of Bacillus cereus after a heat shock during sporulation was studied and modelled.
86
J. Collado et al. / International Journal of Food Microbiology 106 (2006) 85 – 89
a shaker thermostatic water bath (J.P. Selecta) was employed. The heat shock was applied 1 h after the end of the exponential growth phase (Movahedi and Waites, 2000).
2. Materials and methods 2.1. Spore preparation A non-collection strain (wild strain) of Bacillus cereus was isolated from raw liquid egg. The strain was identified by amplification of the internal spacer region (ISR) (Ocio et al., 2003) and cultured overnight in nutrient broth according to British pharmacopoeia (Sharlau Chemie, Barcelona, Spain) containing (per l): meat extract, 1 g; yeast extract, 2 g; peptone, 5 g; and NaCl, 5 g. 1 ml of this suspension was inoculated in 2.5-l flasks, which contained 500 ml of liquid sporulation medium adjusted to pH 7.0. The sporulation medium used in this study is that described by Mazas et al. (1995) with slight modifications and without agar containing (per l): nutrient broth according to British pharmacopoeia (Sharlau Chemie), 13 g; agar bacteriological (Sharlau Chemie), 20 g; NaCl (Sharlau Chemie), 3 g; MnSO4IH2O (Sharlau Chemie), 0.05 g; CaCl2 (Panreac, Montplet & Esteban, Barcelona, Spain), 0.06 g; glucose (Panreac, Montplet & Esteban), 0.1 g; (NH4)2SO4 (Merck, Merck KGaA, Darmstadt, Germany), 0.08 g; MnCl2I4H2O (Merck, Merck KGaA), 0.008 g; CuSO4I5H2O (Panreac, Montplet & Esteban), 0.005 g; ZnSO4I7H2O (Panreac, Montplet & Esteban), 0.005 g. The flasks were incubated in an incubator (J.P. Selecta, Barcelona, Spain) at 30 -C and 100 rpm. The evolution of sporulation was checked daily by using phase contrast microscopy. After 4 days, when the spore crop contained approximately 95% of phase bright spores, it was harvested and washed with sterilised distilled water by repeated centrifugation at 2500g and stored at 4 -C until use. A second sporulation was performed; in this case, a heat shock was applied. The heat shock treatment consisted of changing the temperature of sporulation from 30 -C to 48 -C during 30 min (Movahedi and Waites, 2000). For that purpose,
2.2. Spore germination studies l-Alanine, one of the most important amino acids, provided by Sigma-Aldrich Chemie, Steinheim, Germany, was used to trigger germination. An aqueous solution of this amino acid was prepared and sterilised by filtration using a 0.45-Am syringe filter (Millipore, Molsheim, France). After suffering a heat activation process at 65 -C for 20 min, a suspension of spores was mixed with 0.05 mM Tris buffer (pH 7) and different concentrations of l-alanine (100, 10 and 1 mM) in a sterile tube to give a final volume of 2 ml. The tube was incubated in a shaker incubator adjusted at 30 -C and 150 rpm. Every 15 min, a sample of 1 ml was taken and then the germination was followed by the decrease in the optical density by measuring the absorbance at 625 nm using a spectrophotometer (Spectronic Genesys 5.0, Milton Roy Company, New York, USA) (McCormick, 1964). Then the sample was returned to the tube, which remained in the shaker incubator during the entire assay. The experiment lasted 180 min and was carried out in duplicate. The data were randomly split up into two sets (Tejadillos et al., 2003). The first set, the largest one, containing 61.5% of data, was used to fitting the model and the second set was used for validating it. 2.3. Modelling The kinetics of germination of a spore suspension represents the summation of events occurring in the individual spores of that population (Vary and Halvorson, 1965). Consequently, the germination of spores can be described by
1 0.9
1- (ODt/ODi)
0.8 0.7
100mM (a)
0.6
10mM(a) 1mM(a)
0.5
100mM (b)
0.4
10mM(b) 0.3 1mM (b) 0.2 0.1 0 0
50
100 Time(min)
150
200
Fig. 1. Germination of Bacillus cereus for different concentrations of l-alanine. Clear symbols (a): heat shocked. Solid symbols (b): non-heat shocked.
J. Collado et al. / International Journal of Food Microbiology 106 (2006) 85 – 89 Table 1 Results of the analysis of variance with repeated measures Source
Sum of squares type III
df
Square mean
F
p-value
Intercept Cases Error
47.974 2.142 3.541
1 1 10
47.974 2.142 0.354
135.470 6.050
0.000 0.034
Cases = heat shocked or not shocked cells during the sporulation process.
a distribution function. The Weibull model is one of the distribution functions used to describe the behaviour of systems or events having some degree of variability (Ferna´ndez et al., 1999). In our case, the Weibull has been used as follows (Eq. (1)): t b
S ¼ e ð a Þ
ð1Þ
t ODf The value of S is given by the relation OD ODi ODf . This is the fraction of ungerminated spores, where ODt is the optical density at time t, ODi is the initial optical density and ODf is the final limiting value of optical density at the completion of germination. The germination has been expressed as the percentage decrease in OD during a constant time interval (Rode and Foster, 1962). The parameter a can be considered as a reaction rate constant, whereas b can be regarded as a behaviour index (Cunha et al., 1998). One of the main requirements when fitting a model to experimental data is to verify the accuracy of that particular model. Examination of the residuals (defined as the difference between observed and fitted data) was used as a basic tool to check the suitability of the adjusted model. The predictive quality of the model was assessed by an external validation using as mentioned earlier the data set kept in reserve for validation. As an index of the predictive quality, the accuracy factor described by Ross (1996) was used.
87
Table 2 Values of a (rate index) and b (behaviour index) for Bacillus cereus spore germination using the Weibull model (spores coming from non-heat shocked cells during the sporulation process) and their 95% confidence intervals l-Alanine concentration
a
b
100 mM 10 mM 1 mM
26.59 T 0.89 29.01 T 4.75 45.02 T 4.99
0.77 T 0.03 0.75 T 0.14 0.91 T 0.15
Model assessment and parameter estimation were performed by statistical software SPSS version 9.0 (SPSS Inc., Chicago, IL, USA). 3. Results and discussion Fig. 1 shows the effect of l-alanine concentration on spore t reduction. Germination, expressed as 1 OD ODi , increased with increasing concentrations of germinant, obtaining the highest rate and level of germination for 100 mM. This result is similar to that obtained by McCormick (1964) using other l-alanine concentrations for Bacillus cereus T spores. On the other hand, the germination level reached when Bacillus cereus underwent a heat shock of 30 min at 40 -C (clear symbols), during the sporulation process, was lower as compared with those of nonheat shocked experiments (solid symbols). The influence of the heat shock on the germination level was analysed by performing an analysis of variance with repeated measures (Crowder and Hand, 1990). Table 1 shows the results of this analysis. Since the p-value associated with the heat shock is lower than 0.05, there is a significant effect of the heat shock on the decrease in the concentration of spores. These results might reflect an alteration on the germination mechanism due to the heat shock received by cells during sporulation. This can be important, because temperature changes during the production, storage and distribution of food could affect the germination response of spores present in foodstuffs. This fact should be taken into account on exposure
1,2 1 100Mm (a) 10mM (a) 1mM (a) 100mM (b) 10 mM (b) 1mM (b)
1-S
0,8 0,6 0,4 0,2 0 0
50
100 Time (min)
150
200
Fig. 2. Fit of the Weibull model to the experimental for different concentrations of l-alanine. Clear symbols (a): heat shocked. Solid symbols (b): non-heat shocked.
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J. Collado et al. / International Journal of Food Microbiology 106 (2006) 85 – 89
assessment analysis because it is likely to influence the contamination level at consumption. Fig. 2 illustrates the fit of the Weibull model to the experimental data. Tables 2 and 3 show the values of parameters a and b for the fitted model. Parameter a can be considered as a rate index indicating that the germination process accelerates when the germinant concentration is increased. The values of a obtained for spores coming from not heat-shocked cells were lower than those obtained for spores coming from cells that had suffered a heat shock during sporulation. A higher value of a means that, in some way, the heat shock slows down the process of germination. As indicated by Cunha (1998) and Cunha et al. (1998), the b parameter can be considered as a behaviour index that indicates the kinetic pattern of the mechanism controlling the process, and therefore it should be independent of external factors. This fact has been reported by other authors (Knorr and Heinz, 1996; Mafart et al., 2002; Ferna´ndez et al., 2002). The similarity of the values obtained for the b parameter led us to consider the possibility of maintaining the b parameter as a constant in order to simplify the construction of a secondary model in the near future. To check the suitability of this assumption, an F-test was performed. The results indicated ( pvalue < 0.05) that, from the statistical point of view, the assumption of maintaining the b parameter as a constant is not advisable. Finally we applied an external validation of the model. The result obtained indicated that the accuracy factor ranged from 1.03 to 1.15. These accuracy factors indicate that the predictions, as an average, differ between 3% and 15% from experimental data. Due to its biological importance, spore germination has been investigated in this century. Although germination properties of many strains of different spore formers, such as Clostridium botulinum (Ismaiel and Pierson, 1990; Chea et al., 2000), Bacillus subtilis (Yasuda and Tochikubo, 1985; Paidhungat et al., 2001), Bacillus stearothermophilus (Cheung et al., 1998) or Bacillus cereus (Knaysi, 1964; Chaibi et al., 1996; Clements and Moir, 1998), have been studied, data about strains isolated from food are scarce. However, the study of kinetics of germination, death or growth considering these strains is of great importance because they are the ones best adapted to a particular food and consequently they can create food safety problems (Gaulin et al., 2002). Besides, it is essential to consider that the response of strains isolated from foodstuffs to environ-
Table 3 Values of a (rate index) and b (behaviour index) for Bacillus cereus spore germination using the Weibull model (spores coming heat shocked cells during the sporulation process) and their 95% confidence intervals l-Alanine concentration
a
b
100 mM 10 mM 1 mM
74.15 T 6.37 87.86 T 7.48 87.82 T 7.67
1.54 T 0.30 0.89 T 0.13 1.14 T 0.20
mental factors can be very different when compared to the response observed in collection strains. It is important to note that the food industry, commonly, applies mild heat treatments, such as pasteurisation in order to destroy vegetative cells of a pathogenic bacterium. It should also be noted that this pasteurisation process can activate the dormant spores present in the food. As a consequence if appropriate temperature and time are given, for instance when delays in the cooling process occur, these spores could germinate easily and become new vegetative cells. This is of great importance since even at low temperatures (12 -C), vegetative cells of Bacillus cereus can produce emetic toxin (Finlay et al., 2000). Induced germination, by applying a germinant before the pasteurisation process, can give technological advantages because, as germinated spores can be easily eliminated at temperatures around 65 -C – 70 -C, it can prevent excessive spore concentration after this mild heat treatment. Therefore, a good knowledge of the germination process and its associate kinetics could lead to obtaining a higher safety level, especially when dealing with minimally heat-treated or non-thermal preserved products. This study confirmed that Bacillus cereus spores germinates well in the presence of l-alanine and showed that changes of temperature during sporulation can affect to spore germination since it could affect, in some way, the mechanism that controls the process. Consequently, when dealing with foods, in which spores can be present, it is important to consider that changes of temperature during its elaboration, distribution and storage might have taken place and have an effect on the germination response of the spores that are present. Due to its importance, the germination process should be taken into account in modelling microbial food safety. Additionally, non-deterministic models for germination, growth and inactivation are needed in order to develop appropriate exposure assessment models. This study has demonstrated the usefulness of the Weibull model to describe the germination kinetics of a wild strain of Bacillus cereus. Acknowledgments Authors want to thank CICYT through the project AGL2000-1511, the Ministerio de Educacio´n, Cultura y Deporte and the European Union for supporting this work through a Marie Curie Fellowship awarded to J. Collado. Author J. Collado wants to thank The University of Nottingham and specially Professor William Waites for his valuable advice. References Chaibi, A., Ababouch, L.H., Busta, F., 1996. Inhibition of monoglycerides of lalanine-triggered Bacillus cereus and Clostridium botulinum spore germination and outgrowth. Journal of Food Protection 59, 832 – 837. Chea, F., Chen, Y., Montville, T.J., Schaffner, D., 2000. Modelling the germination kinetics of Clostridium botulinum 56A as affected by
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