Abstracts. M. Vialette

Growths kinetics comparison of clinical and seafood Listeria monocytogenes isolates in acid and osmotic environment

M. Vialette, A. Pinon, E. Chasseignaux and M. Lange

Institut Pasteur de Lille, 1 rue du Professeur Calmette, BP 245, 59019, Lille Cedex, France

Received 13 September 2001; revised 2 April 2002; accepted 18 June 2002. ; Available online 12 August 2002.

ABSTRACT

Comparison of pathogenic bacterial strains of clinical origin with strains of the same species isolated from the environment may be a valuable tool for microbial risk assessment, especially for foodborne pathogens. Thus, a number of Listeria monocytogenes strains responsible for human cases of listeriosis, in relation to the consumption of contaminated seafood, have been compared with "natural" L. monocytogenes strains isolated from similar seafood products. Complete factorial designs were used to assess quantitatively the growth abilities of four clinical and four seafood isolates of L. monocytogenes placed in various environmental conditions. The cells were submitted to acid and osmotic stress as they were in stationary phase (constant condition) or in exponential phase (dynamic condition). The effects and interactions of pH (5–7) and NaCl concentration (0.5–8% v/v) were studied at two growth temperatures (10 and 20 °C). Growth parameters (lag and generation times calculated with Gompertz equation) were used to compare the behavior of the strains with respect to the conditions of culture. The results indicated an overall weak effect of acid stress alone, whereas osmotic stress clearly affected bacterial growth and a synergic effect between these two factors was observed. Clinical strains displayed better adaptation than seafood strains in stationary phase, however, this difference was not verified in exponential phase. Low temperature (10 °C) usually confirmed the observations at 20 °C, and the differences between clinical and food strains were more pronounced. Finally, a classification of the eight strains, based on the collected data, showed three groups: (i) seafood strains, (ii) three clinical strains and (iii) the last clinical strain, alone due to its high resistance to adverse conditions.

Author Keywords: Listeria monocytogenes; Clinical strains; Seafood strains; Growth parameters; Variable conditions

1. INTRODUCTION

Listeria monocytogenes assumed public health significance as a result of its presence in foods linked to several outbreaks of listeriosis in Europe and North America. Most cases of human listeriosis occur in immunocompromised individuals, pregnant women and the elderly (Rocourt et al., 2000).

L. monocytogenes is a widespread microorganism that has been isolated from a variety offoods including fish (Farber and Dillon). Although several kinds of food products have been incriminated as source of sporadic or epidemic listeriosis cases (Rocourt and Bille, 1997), the involvement of fish and fishery products is still very rare. In 1992, two perinatal listeriosis cases, which occurred in Auckland, New Zealand, were associated to the consumption of smoked mussels (Brett et al., 1998). Mussels were also involved in cases occurred in Sydney, Australia (Smith, 1991). An outbreak caused by rainbow trout was reported in Sweden (Ericsson et al., 1997).

The prevalence of L. monocytogenes in naturally contaminated seafood was studied by Jorgensen and Huss (1998): the highest prevalence was found in cold-smoked fish (34–60%), while the lowest was found in heat-treated and cured seafood (4–12%). L. monocytogenes has been found in smoked salmon in several studies. Ben Embarek (1994) reported a contamination rate of between 0% and 75%, with an overall prevalence of 10%, in cold-smoked salmon samples.

In fresh as well as in several lightly preserved seafoods including cold-smoked salmon, none of the processing steps eliminate L. monocytogenes. Furthermore, cold-smoked fish products, which are typically consumed without cooking, are among the ready-to-eat foods of particular concern due to the lack of a heat inactivation step during processing. The ability of a microorganism to survive in various foods depends on several combined parameters in the foods such as temperature, pH, salt concentration (water activity). A range of seafoods, particularly the lightly preserved products (<6% salt concentration, pH>5) such as smoked fish products (hot and cold smoked), lightly salted products (brined cooked shrimp) or marinated products, are capable of supporting the growth of L. monocytogenes (Huss et al., 2000). Moreover, L. monocytogenes is able to survive or grow at refrigeration temperatures (Pearson and Marth, 1990). The pathogen growth was observed in vacuum-packed smoked salmon stored at 10 or 2 °C (Cortesi et al., 1997). It is important to note that cold smoking is conducted at temperatures below 30 °C, most frequently 19–22 °C, for 2 to 3 h and, therefore, provides a possible environment for bacterial growth (Rorvik and Sabanadesan).

Several studies have shown that the virulence of individual L. monocytogenes strains may differ (Del; Brosch and Datta). Furthermore, Datta (1994) demonstrated that the pathogenicity of this microorganism can be affected by various substrate factors, i.e. in foods. There are fewer published systematic studies in which growths of clinical and food strains of L. monocytogenes under unfavourable conditions (found in industrial environment) were compared. The comparison of pathogenic bacterial strains of clinical origin to strains of the same species isolated from environment may be a valuable tool for microbial risk assessment, especially for foodborne pathogens. Therefore, it was of interest to evaluate and compare the capacity of growth of clinical and food strains, in order to determine whether there was a relationship between strain origin and the growth potentialities in function of environmental factors.

Consequently, the aim of this work was to investigate the growth behaviors of four L. monocytogenes strains responsible for human cases of listeriosis in relation to consumption of contaminated seafood and four L. monocytogenes strains isolated from seafood products, in function of temperature, pH and salt concentration. Furthermore, the effects of the pH and salt concentration variations on the growth of the strains were taken into account, with the objective to simulate the variations which can occur during food processing and induce a stress situation for the microorganism.

2. MATERIALS AND METHODS

2.1. L. monocytogenes strains and media

Experiments were carried out with eight L. monocytogenes strains. Four were clinical strains associated to fish or fish products (Table 1A) and four were isolated from seafoods (Table 1B).

Table 1A. Clinical strains of L. monocytogenes involved with main documented cases of foodborne listeriosis associated with seafood and studied in this present work

Table 1B. Seafood strains of L. monocytogenes studied in this present work

Stock cultures were maintained at −80 °C in cryobank (AES Laboratoires, Combourg, France). All strains were resuscitated before use by inoculations into 10 ml of Brain Heart Infusion (BHI) broth (Oxoid, Basingstoke, Hampshire, UK), followed by incubation at 37 °C for 8 h.

The subculture and culture medium was BHI (Oxoid) supplemented with yeast extract (Oxoid) 3 g l⁻¹, glucose (Prolabo, Fontenay sous bois, France) 2 g l⁻¹ and buffered with a K₂HPO₄–KH₂PO₄ (Merck, Nogent sur Marne, France) 0.1 mol l⁻¹ solution in proportion 1:1 (v/v) to pH 7.0.

2.2. Monitoring of bacterial growth

An automated turbidimeter (Bioscreen C, Labsystem, Labsystem France, Les Ulis, France) was used to follow the growth of L. monocytogenes strains in the micro-titer plates. Optical density (O.D.) was read at a wavelength of 600 nm. The working volume in each well of the micro-titer plate was 400 l.

2.3. Experimental procedure

The ability of the eight L. monocytogenes strains to grow in osmotic and acid environment was determined as described by Cheroutre-Vialette et al. (1998).

After resuscitation, strains were subcultured (1%) in the supplemented BHI 18 h at 20 °C, by which time the strains had reached stationary phase. 0.5% of this inoculum was then transferred in the culture medium for the growth studies. The concentration of cells in the culture medium was about 10⁷ cfu ml⁻¹, in order to be above the detection threshold of the Bioscreen C. The viable number of bacteria was confirmed by PCA plate counts (AES). Plates were incubated for 24 h at 37 °C and enumerated.

For all experiments, three conditions were studied: control, constant and dynamic conditions. Under control condition, cells in stationary phase (after subculture) were grown in culture medium BHI, without addition of salt and acid. In constant conditions, bacteria in stationary phase were grown in culture medium adjusted to the desired a_w and pH values. The osmotic variation was achieved by the addition of NaCl (Merck). A solution 5 M of HCl (Merck, 32%) was added to regulate low pH. The dynamic condition was defined as follows: the bacteria were grown in culture medium (control condition, i.e. without addition of NaCl and HCl) until the beginning of the exponential phase and were then shocked by the abrupt addition of shock solutions. These shock solutions (osmotic and acid) were prepared in order to obtain final values similar to those indicated for the constant conditions. An aliquot (100 l) of concentrated (×4) shock solutions was added when the O.D. was near 0.2, corresponding to the beginning of exponential phase (Cheroutre-Vialette et al., 1998).

For each combination, five growth repetitions were carried out.

2.4. Experimental design

A factorial design was used to assess quantitatively the effects and interactions of NaCl and pH (HCl) conditions on the growth of L. monocytogenes clinical or seafood strains at two temperatures. The combinations of the following conditions were used:

For each combination, the constant and dynamic conditions of pH and NaCl concentration were studied. At least, for each strain, 36 experiments were performed according to 18 growths in constant condition and 18 growths in dynamic condition.

2.5. Statistical analysis of data

Experimental data were statistically analysed by the use of S-PLUS 2000 software (MathSoft, Seattle, WA, USA).

Averages of the O.D. were calculated for the five repetitions of inoculated media and for the two repetitions of non-inoculated media. The data were then analysed using the procedure described by Bégot et al. (1996). Four quantities were calculated at time t:




Y_t=log₁₀[(ΔO.D.)_t/(ΔO.D._min)], where ΔO.D._min was the lowest ΔO.D. value above the detection threshold.

As indicated by Cheroutre-Vialette et al. (1998), a modified Gompertz equation (Zwietering et al., 1990) was used to fit the growth curves Y_t=f(t). Growth parameters, A (logarithmic increase of population), (lag time) and (maximal growth rate), were determined by non-linear regression (S-PLUS software). GT (generation time) was derived from using the relation: GT=log₁₀(2)/.

In control and constant conditions, the time of inoculation was taken as zero time when considering the growth curve. In dynamic condition, the time of addition of the shock solution was taken as zero time in the calculation of the growth parameters.

To summarize the similarities in behavior of the strains, a hierarchical clustering method was used (Saporta, 1990). A global data set, including all the conditions of the experimental design, was built. Lag and generation times for the 36 treatments (two temperatures, three pH, three NaCl concentrations, static and dynamic conditions) were used as variables measured on the eight strains. Data were standardized for each variable. The first stage of this method is the computation of a distance measure between the individuals. Each individual is considered as an initial cluster. The two "closest" clusters are merged in a bigger one at each step of the process. The distance between clusters is calculated using the average distance method: the distance between clusters A and B is the average of the distances between the points of A and the points of B. The algorithm stops when there is only one cluster left. The distances between merged clusters are retained: this will allow the program to produce a graph in the form of a classification tree. Each node in the tree appears at a height equal to the distance at which the clusters were merged.

3. RESULTS

3.1. Growth of L. monocytogenes strains in constant acid and osmotic environment

At 20 °C in control condition (i.e. in culture medium BHI), all the strains, clinical or food isolates, presented similar growth parameters, i.e. lag and generation times. The data of clinical strains in this control condition are indicated in Table 2.

Table 2. Lag () and generation times (GT), expressed in hours, observed in control and constant conditions, for the different strains of L. monocytogenes (for origin of strains, see Table 1A and Table 1B), at 20 °C, pH 7.0 and the % NaCl indicated

The pH had negligible effect on the different strains. Indeed, whatever the strain origin, the calculated lag and generations times at pH 6.0 were similar to those obtained with the control growths. Fig. 1 compared the growth parameters values of a clinical strain, Lm-C4, and a food strain, Lm-E4 in control condition and in acid constant condition (pH 6.0 and pH 5.0). The growths at pH 5.0 have shown longer lag times. On the other hand, at 20 °C, the strains were more sensitive to NaCl. As indicated in Table 2 for the studied strains, the presence of salt (8%) induced longer lag phase and increased the generation time by a factor 2.5, on average, compared to the corresponding control condition. All the results obtained at 20 °C showed that no differences were observed between clinical and seafood strains when testing acid environment alone or osmotic environment alone. On the other hand, at this growth temperature, it was observed differences between strains when the two factors were considered simultaneously. On the whole, the calculated generation times of the clinical strains were lower than those of food strains for pH≤6.0 combined with 4% or 8% NaCl, as illustrated in Fig. 2. Among the clinical strains, Lm-C1 was less affected by the combined acid and osmotic conditions, more particularly in the most severe culture condition. Variations in lag times were noted among the strains in the tested conditions.

Fig. 1. Lag (A) and generation times (B), expressed in hours, calculated in control and constant conditions, for the food L. monocytogenes strain Lm-F4 and the clinical L. monocytogenes strain Lm-C4 at 20 °C and the combination of pH and the % NaCl indicated in graphs.

Fig. 2. Comparison of growth curves observed with the food L. monocytogenes strain Lm-F3 (————) and the clinical L. monocytogenes strain Lm-C1 () at 20 °C, in control condition and in the constant condition pH 5.0, 8% NaCl.

At refrigerated temperature (10 °C), the strains were more sensitive to low pH (Table 3). The interactive effect of the factors pH and concentration of NaCl on the L. monocytogenes growth were more pronounced at 10 °C than at 20 °C. Furthermore, the differences between clinical and seafood strains were more underlined, especially as the culture conditions were severe, i.e. low pH and presence of NaCl, as seen in Table 3. No food strains could grow in medium regulated to pH 5.0 supplemented to 4% of NaCl, whereas the growth recovery of the whole clinical strains could be observed. The ability of Lm-C1 to grow in severe conditions was confirmed by these results. No strains were able to grow, i.e. no increase of optical density was observed during the experiment duration (14 days), at 10 °C, pH 5.0, 8% NaCl (results not shown).

Table 3. Lag () and generation times (GT), expressed in hours, observed in control and constant conditions, for the different strains of L. monocytogenes (for origin of strains, see Table 1A and Table 1B), at 10 °C, and the combination of pH and % NaCl indicated

3.2. Comparison with growths in dynamic conditions

In dynamic condition, L. monocytogenes strains were subject to abrupt variations of pH and salt concentration during the beginning of exponential phase at 20 or 10 °C. The stress induced by these variations could induce a lag phase, i.e. an adaptation period to new environment (Fig. 3). The duration of this period was variable and no relation between this period value (lag time) and the strain origin or the environmental factors could be established.

Fig. 3. Growth kinetics of the clinical L. monocytogenes strain Lm-C1 in the different growth conditions: control, constant and dynamic at the combination 20 °C, pH 7.0, 8% NaCl. The moment of shock solution administration is represented by →.

The generation times associated to growth recovery consecutively to the environmental variation was different from those calculated in constant condition. For example, in Table 4, the values of ratios of GT calculated in dynamic condition and GT in constant condition for strains Lm-F4 and Lm-C4 are indicated. In most cases, the growth recovery of the L. monocytogenes strains exposed to environmental variations in exponential phase, i.e. dynamic condition, showed a generation time longer than in constant condition, when the strains were in stationary phase. The conditions of culture in correlation with the presence of NaCl induced the higher ratios, i.e. the generation time observed in dynamic condition was longer than in constant condition.

Table 4. Values of the ratios (generation time (GT) calculated in dynamic condition/GT calculated in constant condition) for all the combinations of factors studied in this work for the seafood L. monocytogenes strain Lm-F4 and the clinical L. monocytogenes strain Lm-C4

The better adaptation of clinical strains, as compared to food strains observed in constant condition was not established in dynamic condition. The parameters values of the strains were comparable. It must be noted that, contrary to results in constant conditions, all the strains were capable to grow in the condition pH 5.0, 4% NaCl, 10 °C. At this temperature, no growths were observed at the most severe condition, pH 5.0, 8% NaCl, as shown in constant condition.

Among the clinical strains used in this work, two strains, Lm-C3 and Lm-C4, were implicated in the same outbreak, but isolated from different patients and had different clonal types (Table 1A). Therefore, it was interesting to analyze their characteristics of growths. At 20 °C, Lm-C3 and Lm-C4 had a similar behavior in front of the studied factors and their variations (Fig. 4). The growth parameter values, i.e. lag and generation times, did not show significative difference. As shown in Fig. 4 for 10 °C, few differences could be observed whatever the studied condition. In constant condition, at pH 6.0–8% NaCl or pH 5.0–4% NaCl, Lm-C4 presented longer lag and generation times, e.g. at the last combination the lag time of Lm-C4 was elongated of 17 h compared to Lm-C3 (Table 3).

Fig. 4. Observed lag times (A) and generation times (B), expressed in hours, for the clinical L. monocytogenes strains Lm-C3 and Lm-C4 in all studied conditions, i.e. control, constant and dynamic, at 10 °C.

3.3. Classification of the different strains

The data base collected in this present work allowed the constitution of a classification of the different strains, with the objective to verify the global behavior of the clinical and food strains. The result, presented in Fig. 5, confirmed the previous conclusions. Three groups were created. One of the groups was constituted by all the seafood L. monocytogenes strains (Lm-F1, Lm-F2, Lm-F3, Lm-F4), a second one contained three of the clinical L. monocytogenes strains (Lm-C2, Lm-C3, Lm-C4). This means that the food strains were in general "closer" to each other than to the clinical strains. The particular behavior of the clinical strain Lm-C1 (associated to the Australia foodborne listeriosis in 1991) underlined in our results was confirmed by this classification, since it was isolated from the other ones. Indeed, as indicated by the experimental results, this clinical strain presented a better adaptation to unfavorable environment of temperature, acid pH and salt concentration.

Fig. 5. Classification tree of seafood and clinical L. monocytogenes strains (for the origin of strains, see Table 1A and Table 1B). Dissimilarity measures were based on the lag and generation times obtained in this work (in various growth conditions).

4. DISCUSSION

It is well known that L. monocytogenes is a microorganism which is able to survive, and frequently grow, under a wide range of adverse conditions such as low temperature, low pH and high osmolarity (Sorrells and Sorrells). In this work, significant differences in growth kinetics were found between clinical and seafood strains in acid and/or osmotic environment, at different temperatures. Indeed, the clinical strains, in stationary phase, were revealed to be more resistant to these environmental conditions, in comparison to environmental strains. These results are in accordance with the study of Dykes and Moorhead (2000) who examined the acid stress response of clinical or meat L. monocytogenes strains and demonstrated the ability of clinical strains to survive an acid shock. Likewise, Avery and Buncic (1997) focused on another environmental factor, the temperature, and showed that 15 clinical strains of L. monocytogenes had higher resistance to the effects of unfavorable storage conditions, compared with 15 meat strains.

Our results confirmed that more investigations were necessary to allow the evaluation of the growth characteristics of clinical strains, compared to food strains, in particular in conditions found in the food environment, with the objective to improve the risk assessment. Eight strains were studied in the present work. The behavior of a larger number of strains (implicated in the main listeriosis cases in the world or associated with different foods) in function of different environmental factors should now be explored to consolidate our conclusions. Indeed, when foodborne listeriosis is considered, it could be hypothesized that a high resistance of some L. monocytogenes strains to environmental factors found in foods or industrial environment may contribute to the particular capability of certain strains to cause illness and, consequently, to become clinical strains (Avery and Buncic, 1997). The influence of environmental factors (such as temperature, acid, etc.) on the expression of virulence markers was also highlighted (Datta and Avery).

The experiments of the present study, comparing the strains behavior in constant and dynamic condition, showed differences on the calculated generation times. This observation is in agreement with the previous studies of Cheroutre-Vialette et al. (1998) and Cheroutre-Vialette and Lebert (2000a). They observed that cells of L. monocytogenes isolated from meat products or food processing environment submitted to environmental variations of pH/aw in exponential phase were usually more sensitive than cells in stationary phase. It was largely demonstrated that, phenotypically, bacteria in stationary-phase growth are more thermotolerant, acid-resistant and are better equipped to survive osmotic stress (Hill and Rees). Nevertheless, in this work, for a studied combination (pH 5.0, 4% NaCl, 10 °C), the food strains were able to overcome the stress in exponential phase but not in stationary phase (this experiment was repeated three times with different inoculum).

The presence of L. monocytogenes in seafoods has been examined by several authors (Dillon; Ben; Loncarevic and Jorgensen). The prevalence of this pathogen can be associated to the light preservation process (salting, etc.), the extended shelf life at refrigerated temperatures, capable of supporting the growth of L. monocytogenes, the consumption without further cooking. Therefore, it is important to evaluate the adaptation of this microorganism in the food processing environment which could include variations (temperature, salting, acidification, etc.) during time. Mathematical modeling techniques are gradually becoming recognized and accepted as powerful tools for predicting the effects of food-preservation systems on bacterial growth kinetics. The applicability of available predictive models to fish products, considering the products characteristics, was approached (Dalgaard and Vigel Jorgensen, 1998). Recently, several studies (Cheroutre and Cheroutre) have demonstrated the significative interest to take into account the dynamic condition in the field of predictive microbiology, and to collect experimental data in this way.

With the objective to introduce more advances into the field of predictive microbiology and increase the safety of products, studies allowing correlations between clinical strains characteristics (such as growth kinetics, cell physiology, e.g. stress condition, expression of pathogenicity in function of particular environment found in food) prove to be necessary. Another prospect is to study the genetical background of environmental strains in order to select the ones that may be most representative of the whole natural population. The knowledge of typing data (serotype, ribotype, pulse field gel electrophoresis) for such strains and their comparison to the corresponding epidemiological data should provide a useful tool for the Listeria risk assessment.

ACKNOWLEDGEMENTS

We wish to thank Dr. McLaughlin (Central Public Health Laboratory, PHLS, London), Dr. Pat Short (Institute of Environmental Science and Research, New Zealand) and Dr. Wilhelm Tham (Faculty of Veterinary Medicine, Sweden) for providing the different clinical strains of L. monocytogenes studied in this present work.

REFERENCES

Avery and Buncic, 1997. S.M. Avery and S. Buncic , Differences in pathogenicity for chick embryos and growth kinetics at 37 °C between clinical and meat isolates of Listeria monocytogenes previously stored at 4 °C. International Journal of Food Microbiology 34 (1997), pp. 319-327.

Bégot et al., 1996. C. Bégot, I. Desnier, J.-D. Daudin, J. Labadie and A. Lebert , Recommendations for calculating growth parameters by optical density measurements. Journal of Microbiological Methods 25 (1996), pp. 225-232.

Ben Embarek, 1994. P.K. Ben Embarek , Presence, detection and growth of Listeria monocytogenes in seafoods: a review. International Journal of Food Microbiology 23 (1994), pp. 17-34.

Brett et al., 1998. M.S.Y. Brett, P. Short and J. McLauchlin , A small outbreak of listeriosis associated with smoked mussels. International Journal of Food Microbiology 43 (1998), pp. 223-229.

Brosch et al., 1993. R. Brosch, B. Catimel, G. Milon, C. Buchrieser, E. Vindel and J. Rocourt , Virulence heterogeneity of Listeria monocytogenes strains from various sources (food, human, animal) in immunocompetent mice and its association with typing characteristics. Journal of Food Protection 56 (1993), pp. 296-301.

Cheroutre-Vialette and Lebert, 2000a. M. Cheroutre-Vialette and A. Lebert , Growth of Listeria monocytogenes as a function of dynamic environment at 10 °C and accuracy of growth predictions with available models. Food Microbiology 17 (2000), pp. 83-92.

Cheroutre-Vialette and Lebert, 2000b. M. Cheroutre-Vialette and A. Lebert , Modelling the growth of Listeria monocytogenes in dynamic conditions. International Journal of Food Microbiology 55 (2000), pp. 201-207.

Cheroutre-Vialette et al., 1998. M. Cheroutre-Vialette, I. Lebert, M. Hebraud, J.C. Labadie and A. Lebert , Effects of pH or aw stress on growth of Listeria monocytogenes. International Journal of Food Microbiology 42 (1998), pp. 71-77.

Cortesi et al., 1997. M.L. Cortesi, T. Sarli, A. Santoro, N. Murru and T. Pepe , Distribution and behavior of Listeria monocytogenes in three lots of naturally-contaminated vacuum-packed smoked salmon stored at 2 and 10 °C. International Journal of Food Microbiology 37 (1997), pp. 209-214.

Dalgaard and Vigel Jorgensen, 1998. P. Dalgaard and L. Vigel Jorgensen , Predicted and observed growth of Listeria monocytogenes in seafood challenge tests and in naturally contaminated cold-smoked salmon. International Journal of Food Microbiology 40 (1998), pp. 105-115.

Datta, 1994. A.R. Datta , Factors controlling expression of virulence genes in Listeria monocytogenes. Food Microbiology 11 (1994), pp. 123-129.

Del Corral et al., 1990. F. Del Corral, R.L. Buchanan, M.M. Bencivengo and P.H. Cooke , Quantitative comparison of selected virulence associated characteristics in food and clinical isolates of Listeria. Journal of Food Protection 53 (1990), pp. 1003-1009.

Dillon and Patel, 1992. R.M. Dillon and T.R. Patel , Listeria in seafoods: a review. Journal of Food Protection 55 (1992), pp. 1009-1015.

Dykes and Moorhead, 2000. G.A. Dykes and S.M. Moorhead , Survival of osmotic and acid stress by Listeria monocytogenes strains of clinical or meat origin. International Journal of Food Microbiology 56 (2000), pp. 161-166.

Ericsson et al., 1997. H. Ericsson, A. Eklöw, M.-L. Danielsson-Tham, S. Loncarevic, L.-O. Mentzing, I. Persson, H. Unnerstad and W. Tham , An outbreak of Listeriosis suspected to have been caused by rainbow trout. Journal of Clinical Microbiology 35 (1997), pp. 2904-2907.

Farber, 1991. Farber, J.M., 1991. Listeria monocytogenes in fish products. Journal of Food Protection 54, 922-924, 934.

Hill et al., 1995. C. Hill, B. O'Driscoll and I. Booth , Acid adaptation and food poisoning microorganisms. International Journal of Food Microbiology 28 (1995), pp. 245-254.

Huss et al., 2000. H.H. Huss, L.V. Jorgensen and B.F. Vogel , Control options for Listeria monocytogenes in seafoods. International Journal of Food Microbiology 62 (2000), pp. 267-274.

Jorgensen and Huss, 1998. L.V. Jorgensen and H.H. Huss , Prevalence and growth of Listeria monocytogenes in naturally contaminated seafood. International Journal of Food Microbiology 42 (1998), pp. 127-131.

Loncarevic et al., 1996. S. Loncarevic, W. Tham and M.-L. Danielsson-Tham , Prevalence of Listeria monocytogenes and other Listeria spp. in smoked and "Gravad" fish. Acta Veterinary Scandinavia 37 (1996), pp. 13-18.

Pearson and Marth, 1990. L. Pearson and E. Marth , Listeria monocytogenes threat to a safe food supply: a review. Journal of Dairy Science 73 (1990), pp. 912-928.

Rees et al., 1995. C.E.D. Rees, C.E.R. Dodd, P.T. Gibson, I. Booth and G.S.A. Stewart , The significance of bacteria in stationary phase to food microbiology. International Journal of Food Microbiology 28 (1995), pp. 263-275.

Rocourt and Bille, 1997. J. Rocourt and J. Bille , Foodborne listeriosis. World Health Statistics Quarterly 50 (1997), pp. 67-73.

Rocourt et al., 2000. J. Rocourt, C. Jacquet and A. Reilly , Epidemiology of human listeriosis and seafoods. International Journal of Food Microbiology 62 (2000), pp. 197-209.

Rorvik, 2000. L.M. Rorvik , Listeria monocytogenes in the smoked salmon industry. International Journal of Food Microbiology 62 (2000), pp. 183-190.

Sabanadesan et al., 2000. S. Sabanadesan, A.M. Lammerding and M.W. Griffiths , Survival of Listeria innocua in Salmon following cold-smoke application. Journal of Food Protection 63 (2000), pp. 715-720.

Saporta, 1990. G. Saporta , Méthodes de classification. In: Probabilités, Analyse des données et statistiqueEditions Technip (1990), pp. 241-261.

Smith, 1991. W. Smith , Listeriosis in Western Sydney. Public Health Bulletin 2 (1991), pp. 133-134.

Sorrells and Enigl, 1990. K.M. Sorrells and D.C. Enigl , Effect pf pH, sodium chloride and temperature on the growth of Listeria monocytogenes. Journal of Food Safety 11 (1990), pp. 31-37.

Sorrells et al., 1989. K.M. Sorrells, D.C. Enigl and J.R. Hatfield , Effect of pH, acidulant, time and temperature on growth and survival of Listeria monocytogenes. Journal of Food Protection 52 (1989), pp. 571-573.

Zwietering et al., 1990. M.H. Zwietering, I. Jongenburger, F.M. Rombouts and K. Van't Riet , Modeling of the bacterial growth curve. Applied and Environmental Microbiology 56 (1990), pp. 1875-1881.

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Growths kinetics comparison of clinical and seafood Listeria monocytogenes isolates in acid and osmotic environment