Adaptive response of Listeria monocytogenes to heat and its impact on food safety

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Food Control 20 (2009) 1–10 www.elsevier.com/locate/foodcont

Review

Adaptive response of Listeria monocytogenes to heat and its impact on food safety Daniil Sergelidis *, Amin Abrahim Laboratory of Hygiene of Foods of Animal Origin, Department of Hygiene and Technology of Foods of Animal Origin, School of Veterinary Medicine, Aristotle University, 54 124 Thessaloniki, Greece Received 17 October 2007; received in revised form 10 January 2008; accepted 15 January 2008

Abstract Listeria monocytogenes is an important food associated pathogen because of its relatively high heat resistance and ability to multiply in refrigeration temperatures. Its thermotolerance can be increased when its cells are subjected to heat shock. One- to eight-fold increase of D values of L. monocytogenes have been reported, depending on the heat shock duration, the temperature and the heating menstrum. This acquisition of heat tolerance is related to the induction of the synthesis of heat shock proteins (HSPs). The adaptive response of food pathogens has important consequences on the safety of thermally processed foods. It is believed that this is responsible for the frequent occurrence of deviations (tails and shoulders) during heat treatments that are observed in the exponential model of microbial inactivation. These deviations from log-linear kinetic especially encountered under mild heat treatments, mean that prediction of food safety can no longer rely upon D and z values. Adaptive response to heat must be considered when quantifying and modeling microbial inactivation during thermal processing in order to achieve microbiologically safe products without overly conservative heat processes. Therefore a more mechanistic approach is needed for more accurate predictions of thermal inactivation. Prerequisite to this model are thorough studies to understand how L. monocytogenes and other pathogens adapt their cellular physiology to overcome heat and other stresses. Ó 2008 Elsevier Ltd. All rights reserved. Keywords: Listeria monocytogenes; Heat shock response; Heat shock proteins; Modeling thermal treatment

Contents 1. 2. 3. 4. 5. 6. 7.

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Introduction . . . . . . . . . . . . . . . . . . Literature review . . . . . . . . . . . . . . . Mechanism of heat shock response . . Heat shock proteins (HSP) . . . . . . . . Effects of heat shock on susceptibility Discussion. . . . . . . . . . . . . . . . . . . . Conclusion remarks . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . .

...................................................... ...................................................... ...................................................... ...................................................... of L. monocytogenes to other stress factors and production of listeriolysin. ...................................................... ...................................................... ......................................................

Corresponding author. Tel.: +30 2310 999970; fax: +30 2310 999833. E-mail address: [email protected] (D. Sergelidis).

0956-7135/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodcont.2008.01.006

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1. Introduction Illnesses caused due to the consumption of contaminated foods have a wide public health and economic impact. According to The Centers for Disease Control and Prevention (CDC), foodborne diseases are responsible for about 76 million illnesses, which result in 325,000 hospitalizations and 5000 deaths in the USA each year (Mead et al., 1999). In the past decades, Listeria monocytogenes has become increasingly important as food associated pathogen. Most European Union countries have an annual incidence of human listeriosis between two and ten cases per million (Jemmi & Stephan, 2006). L. monocytogenes infections are responsible for the highest hospitalization rates (91%) amongst known food borne pathogens, have been linked to sporadic episodes and large outbreaks of human illness worldwide with 500 deaths each year in the USA (Mead et al., 1999) showing a 20% mortality rate (Gellin & Broome, 1989). L. monocytogenes has been isolated from a wide variety of raw and processed foods. Milk and dairy products, meat and meat products such as beef, pork, fermented sausages, fresh produce such as radishes, cabbage, as well as seafood and fish products have been associated with L. monocytogenes contamination (Gudbjonsdottir et al., 2004; Rocourt & Cossart, 1997). Even though statistics show that the incidence of listeriosis has declined, outbreaks continue to occur and L. monocytogenes contamination is one of the leading microbial causes of food recalls, mainly meat, poultry, seafood and dairy products (Jemmi & Stephan, 2006). Several factors influence food contamination by Listeria. Among them are modifications in food processing practices and growing demand for ethnic foods. Trends towards consumption of minimally processed ready to eat and refrigerated foods have also affected the incidence of listeriosis over the past years (Rocourt & Bille, 1997). Thermal processing is the most commonly applied technique to control pathogens in foods and thus CCP for microbial hazards of thermally processed foods. Effective control of heat tolerant non-spore-forming foodborne pathogens is a challenge for food processors. Microbial heat resistance is a key factor for the calculation of an effective heat treatment of a food so as to be safe for the consumer. Several environmental factors affect bacterial heat resistance, exerting their effect before, during or after heat treatment (Hansen & Riemann, 1963; Tomlins & Ordal, 1976). Microorganisms increase their thermotolerance when they are exposed to environmental stresses such as sub lethal heat shock, osmotic stress, starvation, exposure to acid, alkali, ethanol or hydrogen peroxide (Farber & Brown, 1990; Jorgensen, Stephens, & Knochel, 1995; Lou & Yousef, 1996, 1999; Mazzota & Gombas, 2001; McClain & Lee, 1988). Several bacteria increase their heat resistance when they are exposed, for a short time, to moderately elevated tem-

peratures, normally above their maximum growth temperatures, before actual heat treatment is applied (Jorgensen, Hansen, & Knochel, 1999; Jorgensen, Panaretou, Stephens, & Knochel, 1996; Lin & Chou, 2004; Mackey & Derrick, 1986; Paga`n, Condo´n, & Sala, 1997). Foods, requiring long heating periods at low temperatures, such as egg products and sous-vide, in order to retain flavor and texture, bacterial pathogens might respond to heat shock increasing thermotolerance (Bunning, Crawford, Tierney, & Peeler, 1990; Linton, Webster, Pierson, Bishop, & Cagney, 1992). Heat shock is of great importance for public health especially if it occurs in psychrotrophic species, such as L. monocytogenes and Yersinia enterocolitica, because surviving cells can grow in foods during refrigerated storage faster than the saprophytic flora (Gill & Reichel, 1989). Heat processing procedures should be designed to destroy pathogenic microorganisms in their most heat resistant state, in order to provide an adequate margin of safety. Still there is little knowledge about how the temperature at which cells were grown influences induced thermotolerance. There is a need for additional thermal inactivation data for stressed microorganisms in specific food products (Doyle, Mazzota, Wang, Wiseman, & Scott, 2001). Predictive models permit to estimate the survival of the target organisms within a defined range of food formulation variables (Whiting, 1995). These models, validated in actual food formulations, may offer important data to processors for the formulation of the food products and the heating procedures in order to achieve safe food for the consumer (Ross & McMeekin, 1994). 2. Literature review Fedio and Jackson (1989), reported that preheated L. monocytogenes Scott A serotype 4b at 480 °C for 1 h, and then heated at 60 °C, in TSYE broth and in UHT milk, showed a marked increase in heat resistance, as evidenced by differences in survival by three or more log cycles after 10–20 min. (Table 1 shows the results of the studies concerning induced thermotolerance of L. monocytogenes after heat adaptation response.) Farber and Brown (1990) investigated the thermal resistance of L. monocytogenes in a sausage mix, inoculated with 107 cells/g and subjected to a heat shock of 48 °C for up to 120 min before being finally heated at 62–64 °C. Heat shocked bacteria for 120 min, showed an average 2.4-fold increase in D64 value (3.4 for control cells, 3.85, 4.24 and 11.52 min for 30, 60 and 120 min of shock, respectively). Heat shocked cells shifted to 4 °C appeared to maintain their thermotolerance for at least 24 h after heat shock. Linton et al. (1992) reported that log phase cells of L. monocytogenes strain Scott A, after a heat shock at 48 °C for 10 min, showed 2.1-fold increase in D55, in TSYE broth.

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Table 1 Relative increase in thermotolerance due to heat shock, slowly rising temperatures and heat adaptation in Listeria monocytogenes Growth phase

Sub lethal stress or adaptation

Heating menstrum

pH

strain

Increase in D-value due to prior heat stress or adaptation

Reference

Exponential

46 °C/30 min

7.0

13–249

5–7-fold in D60

Jorgensen et al. (1999)

Late exponential Late exponential Late exponential

7.0 7.3 7.0

Scott A Scott A Scott A

2.2-fold in D58 2.1-fold in D58 2.3-fold in D60

Stephens and Jones (1993) Jorgensen et al. (1996) Stephens et al. (1994)

Stationary

46 °C/30 min 46 °C/30 min 13 min between 37 °C and 46 °C 48 °C/5–60 min

Tryptic phosphate broth with 8 g/l lactic acid Broth Broth Broth Broth

7.3

F 5069

1–3-fold in D62.8

Stationary Late stationary

43 °C/18 h 46 °C/30 min

NR 7.0

F 5069 13–249

6-fold in D62.8 1–8-fold in D60

Exponential Stationary

5.8 NR

13–249 5S

1–7-fold in D60 1–8-fold in D60

NR

46 °C/30 min 18 min between 37 °C and 46 °C 48 °C/120 min

NR

2–4-fold in D64

48 °C/15 min

10-strain mixture F 5069

Jorgensen et al. (1999) Quintavalla and Campanini (1991) Farber and Brown (1990)

NR

1.5-fold in D71.7

Bunning et al. (1992)

Stationary Stationary Late exponential

47.5 °C/180 min 40 °C/24 h 48 °C/10 min

Milk Tryptic phosphate broth with 8 g/l lactic acid Minced beef Pork curing mixture Pork and beef curing mixture Sterile whole bovine milk TSYE broth BHI broth Potato slices

Knabel, Walker, Hartman, and Mendonca (1990) Knabel et al. (1990) Jorgensen et al. (1999)

NR 7.0 NR

4-fold in D65 3–4-fold in D62.5 1.4–2.4-fold in D55

Pagan et al. (1997) Sergelidis et al. (2001) Walsh et al. (2001)

Stationary

48 °C/30 min

Pork meat

NR

4-fold in D58

Stationary Exponential Late exponential

46 °C/60 min 48 °C/10 min 42 °C/60 min

Ground beef TSYE broth Ham (ground)

NR NR 5.5

2-fold in D60 2.1-fold in D55 1.4-fold in D60

Quintavalla and Barbuti (1989) Novak and Juneja (2003) Linton et al. (1992) Carlier et al. (1996)

Stationary

42.8 °C/24 h

Pasteurized whole milk

NR

2.5–3-fold in D56, D60 and D63

Rowan and Anderson (1998)

NR

Bunning, Crawford, Tierney, and Peeler (1992) reported that D71.7 for heat shocked cells of L. monocytogenes in whole bovine milk was 4.6 ± 0.5 s while untreated (control cell) had D71.7 3.0 ± 1.0 s that is 1.5-fold increase. Stephens, Cole, and Jones (1994) examined the effect of the heating rate on the thermal inactivation of L. monocytogenes. They found that when cells were heated to 60 °C at rates P 5.0 °C/min, there was not induced increased thermotolerance. As heating rates decreased from 5 to 0.7 °C/min thermotolerance increased proportionally. At rates of heating 60.7 °C/min maximum thermotolerance was induced. These results confirm that thermal inactivation is a path-dependent process and previous handling or treatment of a contaminated sample, affects thermal resistance of pathogens during a future process. Thermal history of a population of cells is considered to be a fundamental factor influencing that population’s level of sensitivity to heat at any particular time and the induction of thermotolerance during slow heating rates is analogous to that of heat shock response. Carlier, Augustin, and Rozier (1996) studied the effect of sublethal heat shock in the heat resistance of L.

STCC 4031 Scott A NCTC 11994

Scott A Scott A 1992 French outbreak strain 4b

monocytogenes (1992 French outbreak strain) in ham. Experiments were carried out on bacterial cultures in three different states: cultures at the end of the exponential phase, heat shocked cultures at 42 °C for 1 h and subcultures of cells that survived heat treatment at 60 °C for 20 min. The obtained D55 and D60, were 17.8 and 1.82 min, 19.2 and 3.48 min, and 13.4 and 0.97 min, respectively. Paga`n et al. (1997) investigated the influence of the temperature at which L. monocytogenes had been grown (4 or 37 °C) on the response to heat shocks of different durations at different temperatures. For L. monocytogenes grown at 37 °C, the greatest response to heat shock was a 4-fold increase in thermotolerance. For L. monocytogenes grown at 4 °C, the greatest response to heat shock was a 7-fold increase in thermotolerance. The only survival curves of cells to have shoulders were those for cells that had been heat shocked. A 3% concentration of sodium chloride added to the recovery medium made these shoulders disappear and decreased decimal reduction times. The percentage of cells for which thermotolerance increased after a heat shock was smaller the milder the heat shock and the

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longer the prior storage. They reported D65 0.65 min for cells heat shocked at 47.5 °C for 180 min, which was 4-fold higher from that for non-shocked cells. They also observed that the heat shock at 50 °C inactivated approximately 94% of the cell population but the remaining cells (approximately 6%) were still capable of developing a higher thermotolerance (D65 0.36 min for heat shocked cells versus D65 0.16 min for non-heat shocked cells). This probably indicates that, during treatment, two phenomena were taking place simultaneously, one concerning inactivation and the other concerning increase in thermotolerance. This increase in thermotolerance could perhaps explain the formation of tails in survival curves, as suggested by other authors (Cerf, 1977; Moats, Dabbah, & Edwards, 1971). Rowan and Anderson (1998) investigated the thermotolerance of two different cell forms (S- or R-) of L. monocytogenes serotype 4b grown at 37 and 42.8 °C in commercially pasteurized and laboratory-tyndallized whole milk (WM). Test strains, after growth at 37 or 42.8 °C, were suspended in WM and were then heated at 56, 60, and 63 °C for various times. Higher average recovery and higher D values (i.e., seen as a 2.5–3-fold increase in thermotolerance) were obtained when cells were grown at 42.8 °C prior to heat treatment. D56 values ranged from 6.4 to 11.4 min for non-shocked cells and from 16.5 to 31.5 min for heat shocked cells. Differences were depended on culture forms and on the recovery medium. D60 values ranged 0.7–1.5 and 1.8–4.4 min, respectively. D63 values ranged 0.1–0.5 and 0.5–1.4 min, respectively. Jorgensen et al. (1999) investigated the effect of heat shock (46 °C/30 min) on the thermotolerance of L. monocytogenes compared as a function of growth phase (exponential and late stationary phase) and heating medium (broth and minced beef). Lactic acid was added to tryptic phosphate broth (TPB+) to simulate the level found in beef. Furthermore the specific effect of lactic acid was investigated, comparing results obtained in broth with or without lactic acid with pH adjusted to 5.4 and 7.0. In late stationary cultures, heat shock produced only marginal differences in thermotolerance in TPB+ and beef regardless of the pH. For exponential phase cultures, the increase in heat shock induced thermotolerance (HSIT) depended on pH in both TPB+ and beef with gradually larger increases at rising pH. At the highest pH tested (7.0 in TPB+ and 6.2 in beef) the increase was 5.7- and 2.4-fold, respectively. If no lactic acid was present, the HSIT increased both at pH 5.4 and 7.0 for exponential phase cultures. This indicates that the presence of lactic acid in naturally occurring levels will have specific effect on the response of L. monocytogenes to heat shock decreasing its thermotolerance. The D60 were generally 2–6-folds higher in minced beef than in TPB+. Sergelidis, Stefanopoulou, and Genigeorgis (2001) investigated the influence of the temperature at which L. monocytogenes Scott A has been grown on its thermotolerance. They reported D62.5, in BHI broth, 0.25–0.27, 0.66–0.67

and 1.33–1.97 min for cells grown at 30, 37 and 40 °C, respectively. Novak and Juneja (2003) reported that D60, in ground beef, for L. monocytogenes Scott A, heat shocked at 46 °C for 60 min, was 4.3 ± 0.4 versus 2.1 ± 0.2 (2-fold higher) compared to non-heat shocked cells. They also reported that the heat shock effect appeared to be more pronounced when the cells were refrigerated at 4 °C or frozen at 20 °C after heat treatment compared to those which were refrigerated or frozen before. This finding seems to be significant with regards to the safety of precooked meals subsequently chilled for reheating. Lin and Chou (2004) found that the heat shock response of L. monocytogenes varied within strains, the type of heat shock treatment and the type of subsequent stress. In their study, L. monocytogenes Scott A, V7 and CCRC 14930 were subjected to heat shock at 45 °C for 1 h or at 48 °C for 10 min. Compared with the non-heat shocked cells, the heat shocked cells at 45 °C for 1 h of strains Scott A and V7 showed an increased survival after exposure to 55 °C for 60 min. Survival of the heat shocked L. monocytogenes cells at 48 °C for 10 min, regardless the strain, exhibited no significant difference (p > 0.05) compared with the respective control cells. The survival of heat shocked cells of strain V7 at 45 °C for 1 h was comparable to that of the controls during the initial 40-min of exposure. At the end of the 60-min exposure period the heat shocked cells showed a survival percentage of 74.75% which is significantly higher (p < 0.05) than that (58.41%) of the control. The heat shocked cells of strain CCRC 14930 at 45 °C for 1 h exhibited a survival percentage of 9.52% which is significantly lower (p < 0.05) than that of 40.05% found with the controls. According to the reported data it is clear that the thermotolerance response of bacteria is strongly dependent upon the heating menstrum during the heat shock. Farber and Brown (1990) reported no significant increase in thermotolerance of L. monocytogenes, in a pork/beef mixture after a heat shock at 48 °C for 30–60 min, but they did not give any explanation why there was not difference. They used 10 strains isolated during routine analysis of meat; three of them were serotype 4 and seven serotype 1. A 2.3-fold increase of thermotolerance L. monocytogenes strain Scott A was noted by Linton, Pierson, and Bishop (1990) after a heat shock at 48 °C for 10 min in broth of TSYE. 3. Mechanism of heat shock response It is well established that environmental stresses represent external factors that have adverse effects on the welfare of bacterial cells. These effects lead to reduction in growth rate or, in more extreme circumstances, to inhibition of growth and/or death. Extremes of temperature, pH, osmotic pressure, nutrients depletion, presence of toxic or inhibitory compounds, including antibiotics, are examples of such bacteriostatic or bactericidal stresses (Archer, 1996; McDowell, 2004).

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Any temperature above the optimum growth temperature is supposed to have some lethal effect. However, it has been shown that in most microbial species slow heating or heating for short periods of time at temperatures above the optimum temperature for growth induces higher thermotolerance (Mackey & Derrick, 1986, 1987a, 1987b). The responsible mechanism for a heat-adaptive response is not fully known. Some general observations can be drawn from the information available in scientific literature. It is believed that these temperatures trigger a physiological cellular response (Schlesinger, 1986) that is transient response to stressful stimuli and serves to protect vial cellular proteins from damage and irreversible aggregation (Katchinski, 2004). This response consists of the synthesis of various proteins, which are also known as heat shock proteins (HSPs) (Lindquist, 1986). It is still not clear whether there is a direct cause–effect relationship between the synthesis of these proteins and the induction of a higher thermotolerance (Lindquist, 1986; Parsell & Lindquist, 1993; Schlesinger, 1986). The functions of HSPs include both the stabilization of cellular structures against the physical action of heat and aiding in the proteolysis or refolding of aberrant proteins, which have been denatured during exposure to heat. The latter mechanism is possibly involved in the recovery of heat-injured cells (Lindquist, 1986; Parsell & Lindquist, 1993). Apart from the synthesis of new proteins, other mechanisms of protection may also take place. For instance, it has been reported that heat favours the interaction of low molecular weight components and divalent cations, present in the heating medium, with surface components of Salmonella senftenberg cells, resulting in the stabilization of the outer membrane and the subsequent increase in heat tolerance of the cells (Man˜as, Paga´n, Sala, & Condo´n, 2001). 4. Heat shock proteins (HSP) HSPs are molecular chaperones for protein molecules. They are usually cytoplasmic proteins that perform functions in various intra-cellular processes. They play an important role in protein–protein interactions such as folding and assisting in the establishment of proper protein conformation and prevention of unwanted protein aggregation. By helping to stabilize partially unfolded proteins, HSPs aid in transporting proteins across membranes within the cell. Some members of the HSP family are expressed at low to moderate levels in all prokaryotic as well as in eukaryotic cells; they also occur under non stressful conditions because of their essential role in protein maintenance (Ellis & van der Vies, 1991; Georgopoulos & Welch, 1993). Their increase in expression is transcriptionally regulated, induced mostly by heat shock factor (HSF) and represents a key part of the heat shock response. Production

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of high levels of such proteins can also be triggered by exposing the cells to other environmental stressful conditions, such as exposing the cells to toxic factors such as ethanol, arsenic, trace metals, ultraviolet light etc, starvation, hypoxia, water deprivation or nitrogen deficiency (in plants). Consequently, heat shock proteins are also referred to as stress proteins and their up regulation is sometimes described more generally as part of the stress response. It is not clearly understood how heat shock (or other environmental stressors) activate the heat shock factor. However, some studies suggest that an increase in damaged or abnormal proteins brings HSPs into action. HSPs are divided into several families based on sequence similarity and size, and named according to their molecular weights. To date six HSP families have been characterized, these include the small heat shock proteins (sHSPs), HSP40, HSP60, HSP70 and HSP100 families (Burdon, 1986; Katchinski, 2004; Schlesinger, 1994). Phan-Thanh and Gormon (1995, 1996) reported that proteins induced by different stress in L. monocytogenes cell (heat shock, cold shock, pH, sodium dodecyl sulfate, sodium deoxycholate and ethanol) were specific for each kind of stress. No universal stress proteins were found to be common to all stresses studied, while some proteins were commonly induced by two or three stress conditions. 5. Effects of heat shock on susceptibility of L. monocytogenes to other stress factors and production of listeriolysin Following the induction of thermotolerance, as a result of the adaptive response to heat, L. monocytogenes cells appear to grow tolerance to other stressful conditions. Lin and Chou (2004) reported that L. monocytogenes Scott A, V7 and CCRC 14,930 strains, subjected to heat shock at 45 °C for 1 h increased their tolerance to NaCl (25%), ethanol (18%) and crystal violet (0,01%), but heat shocking at 48 °C for 10 min although increased the resistance to NaCl reduced resistance to H2O2 and crystal violet. Lou and Yousef (1997) observed that susceptibility of L. monocytogenes Scott A to NaCl decreased after heat shocking at 45 °C for 1 h. Sokolovic, Fuchs, and Goebel (1990) reported that the production of listeriolysin by L. monocytogenes serotype 1/2a increased more than 10-fold under heat shock conditions (48 °C for 30 min). At least five heat shock proteins were specifically coinduced with listeriolysin in all L. monocytogenes strains but not in other Listeria species. Keetae, Murano, and Olson (1994) examined the effect of heat shock on listeriolysin O (LLO) production and the ability of injured cells to resume production of LLO after heat treatment at 62 °C for 10 min. Heat shocking of L. monocytogenes cells resulted in almost total reduction in LLO activity. However, during 4 h incubation at 37 °C, heat shocked cells resumed LLO production achieving an activity level 40-times higher than that immediately after heat shock. In comparison, at the same time there was an

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increase of only 2-fold in the haemolytic activity on non heat shocked controls. These results provide additional evidence, besides increased thermotolerance, of how heat shock of pathogenic organisms could affect food safety. 6. Discussion L. monocytogenes is an organism of prime concern with regard to the production of cook-chill foods, due to its psychrotrophic nature, severity of disease, widespread in nature and relatively high heat resistance, compared to other food pathogens (Sofos, 1993). Thermotolerance of L. monocytogenes can be even higher if exposed to sub lethal temperatures slightly above the optimum growth temperature. The significance of this behavior is of great concern for food industry. Meat and meat products that are heated up slowly to a final internal temperature may contain microbial cells with an augmented heat resistance due to a previous heat shock response. It appears that the slower the temperature increase, the larger the increase in heat resistance (Mackey & Derrick, 1986). An example of the slow heating up is sous-vide-type products, which undergo low heating temperatures and long come-up times (Hansen, Knochel, Juncher, & Bertelsen, 1995). Foods left on warming trays before final heating or reheated or when cooking is interrupted due to equipment failure, could possibly acquire an enhanced thermotolerant microbial population (Juneja, Klein, & Marmer, 1998). With the introduction of milder thermal processes the prediction of safety clearly needs to be understood with greater precision and accuracy. Heating rate is important, especially when lower processing temperatures are employed (Quintavalla & Campanini, 1991). Many modern food preservation processes aim to extent the lag phase of bacteria present in food by the application of one or more environmental stresses to slow or prevent bacterial growth. However, absence of growth does not necessarily mean absence of metabolic and/or genetic activity, and stress-inhibited bacteria act to reduce the impact of environmental stresses by making phenotypic and genotypic adaptations. Examples of phenotypic alteration include expression of protective shock proteins, which provide resistance to subsequent challenge with the same stress (stress hardening) (Rowan, 1999) and can also lead to cross-protection against a range apparently unrelated challenges, including resistance to antibiotics (Rowan, 1999; Velkov, 1999). These alterations increase population diversity, increasing the chances that at least some cells may survive and grow under stress conditions. To estimate and adjust properly the thermal treatment intensities needed to guarantee the safety of pasteurized foods, adequate parameters which influence the inactivation kinetics of the target microorganisms are required. It has been generally admitted, for more than 60 years, that the number of survivors of a microbial population, who is subjected to the lethal action of heat, decreases exponen-

tially with treatment time when applied at a given constant temperature (Bigelow & Esty, 1920; Stumbo, 1973). Consequently, if the logarithm of the fraction of survivors is represented as a function of treatment time, a straight line is obtained. This is known as the survival line. The inverse negative of the slope of the survival line corresponds to the decimal reduction time value (DT). DT values allow us to assess the influence of various environmental factors on microbial heat resistance. They also allow the calculation of processing times by multiplying the DT value by the required number of log cycles inactivation. The exponential model is simple and regularly used. However, there are frequently observed deviations in the inactivation course of microbial populations from the exponential model and the usefulness of the DT values is questioned by some researchers (Augustin, Carlier, & Rozier, 1998; Cole, Davies, Munro, Holoyoak, & Kilsby, 1993; Juneja & Marks, 2003; Linton, Carter, Pierson, & Hackney, 1995; Peleg & Cole, 1998). In any case, the exposure of bacterial cells to heat shock may have important practical consequences. A clear example is that of solid foods, where heat penetration by conduction across the pieces is slow. For this reason microbial cells in the food may be subjected, during a given period of time, to a temperature gradient that may act as a heat shock, provoking the increase of their heat resistance to the final treatment temperature (Hassani, Alvarez, Raso, Condo´n, & Paga`n, 2005; Hassani, Man˜as, Raso, Condo´n, & Paga`n, 2005; Jorgensen et al., 1996; Mackey & Derrick, 1987a, 1987b; Man˜as, Paga´n, Alvarez, & Condon, 2003). In a similar way, slow gradual increases in temperature have to be used during the processing of some liquid foods, such as liquid whole egg, due to the thermal sensitivity of some components, which cannot withstand contact with hot surfaces in heat exchangers (Man˜as et al., 2003). During the last two decades much research has been directed towards the characterization of the heat shock response of various bacterial species. It is clearly demonstrated that the acquisition of heat tolerance rises up to a maximum as the heat shock duration increases, within a range. The maximum attained depends on the bacterial species, the composition of the heat shock medium and its temperature (Farber & Brown, 1990; Juneja et al., 1998; Linton et al., 1990; Mackey & Derrick, 1990; Man˜as et al., 2003; Paga`n et al., 1997). The temperature at which cells are subjected during heat shock is restricted by the commencement of the death of the cell population, which may occur simultaneously to the acquisition of thermotolerance in the surviving cells (Paga`n et al., 1997). However, comparisons among the relative acquisition of thermotolerance on different bacterial species are hampered by the frequent occurrence of deviations from the exponential kinetics of inactivation (Cole et al., 1993; Geeraerd, Herremans, & Van Impe, 2000; Peleg, 2006; Peleg & Cole, 1998). Under these circumstances, DT parameter of the traditional exponential model is inadequate to make comparisons since deviations are neither included nor described by the

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model. Paga`n et al. (1997) proposed a novel mathematical approach, ‘‘TFLCR” (Time for the First Log Cycle Reduction), to sort out this problem. Mackey and Derrick (1986) also proposed the use of the Alderton and Snell equation (Alderton & Snell, 1970), which had been initially developed to describe kinetics of inactivation of bacterial spores. Since then, Predictive Microbiology has reached a great expansion and it is currently widely used in thermobacteriology (Fernandez, Collado, Cunha, Osio, & Martinez, 2002; Hassani, Alvarez, et al., 2005; Hassani, Man˜as, et al., 2005; Peleg & Cole, 1998; Peleg & Penchina, 2000). Various mathematical models have been proposed to fit non-exponential survival curves (Augustin et al., 1998; Cole et al., 1993; Geeraerd et al., 2000; Juneja & Marks, 2003; Linton et al., 1995; Peleg & Cole, 1998). All of them have their drawbacks and advantages. Among the models proposed to date, those based on the existence of a Weibull distribution are the most widely used to describe both heat inactivation kinetics (Fernandez et al., 2002; Hassani, Alvarez, et al., 2005; Hassani, Man˜as, et al., 2005; Peleg & Cole, 1998; Peleg & Penchina, 2000) and high pressure and pulsed electric field kinetics as well (Alvarez, Vitro, Condo´n, & Raso, 2003; Rodrigo, Ruı`z, Barbosa-Ca`novas, Martinez, & Rodrigo, 2003). Models based on the Weibull distribution are characterized by their simplicity and their versatility. Simplicity since they only include two parameters, the so-called scale and shape parameters; and versatility as they allow to accurately describing linear, concave upwards and convex survival curves. The most frequently used equations based on the Weibull distribution are those developed by Peleg and Cole (1998), Van Boekel (2002), Mafart, Couvert, Gaillard, and Lequerinel (2002). Hassani, Man˜as, et al. (2005) have successfully applied models based on the Weibull distribution to describe the evolution of microbial populations from different bacterial species subjected to anisothermal heating. Nevertheless, as far as we know, these equations have not been previously used to describe the kinetics of inactivation of cells subjected to isothermal heat shocks. It can be foreseen that these models may be useful to describe the non-linear survival curves that frequently occur after exposure of the bacterial cells to heat shocks. However, for a more appropriate use of these models, the effect of isothermal heat shocks on every parameter of the equation should be determined. Another aspect of interest is the effect of the pH of the medium where cells receive the heat shock. It seems clear that the pH of the medium may influence the adaptive response developed by the bacterial cells whatever the mechanism involved. For instance, if the increase in heat resistance is due to the presence of newly formed proteins, an acidic environment could interfere with protein synthesis processes or even provoke the unfolding of formed proteins, as it has been reported (Lund, Baird-Parker, & Gould, 2000). On the other hand, if the adaptive response is due to a stabilization of the cellular envelope via divalent cations binding, it can be foreseen that the pH of the med-

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ium may exert an influence through modification of the ionization degree of proteins and other components of the bacterial surface and medium as well. The effect of pH on the adaptive response of microorganisms to heat is a particularly relevant aspect given the increased interest in combined processes for food preservation. Furthermore there are other intrinsic product factors, such as fat content and water activity, which affect thermal resistance of microbial cells. These factors coupled with the complex environmental conditions during thermal processing, such as heating temperature and cooking time, air velocity, humidity, heating and/or cooling rates, and other process parameters, affect thermal resistance and destruction of pathogens. However, mere knowledge that these effects exist is insufficient to aid processors in designing, operating and evaluating the efficacy of thermal processing, in terms of the relevant lethality performance standards. 7. Conclusion remarks Food bacterial pathogens are stressed during food processing, distribution and storage, by the application of several hurdles (Leistner, 1995). The adaptive stress response of bacteria during minimal processing has important implications for food safety as the response to the one hurdle may render the cells more resistant to the other hurdles that follow and may counteract the effectiveness of food preservation and compromise food safety (Rowan, 1999). Processors should be cautious calculating the intensity of heat treatments, based on the assumption that microbial inactivation by heat is an irreversible first order event, applying D and z values to integrated time–temperature histories from process data (Bigelow & Esty, 1920; Stumbo, 1973). It is no longer possible, with the introduction of milder thermal processes, to build in the relatively large safety margins traditionally used in thermal processing. The significant deviations from log-linear kinetic encountered under mild heating regimes, mean that the method incorporated D and z values cannot be relied upon to predict product safety (Stephens et al., 1994). There is need for more accurate predictions of thermal inactivation, especially over more complex time/temperature profiles than that at constant temperatures. The development of a more mechanistic approach is an important alley towards the future, and may require thorough studies that focus on the quantification of the molecular adaptations (e.g. production of heat shock proteins) or on the exploitation of microscopical experiments (Valdramidis, Geeraerd, & Van Impe, 2007). There is also a need for more research concerning the influence of the composition of the food system and the changes of it that occur during thermal processing on the induction of thermotolerance because it would be difficult to predict the extent of heat tolerance in foods based on data obtained in media.

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Where the food industry contemplates modification to existing preservation strategies develops new ones and changes the composition of food products towards more natural foods preserved using a combination of sub lethal methods, the true level of susceptibility of stress resistant bacterial populations has yet to be determined. Even though there has been a decline in widespread food safety problems from undercooking, ongoing development of new products and processes necessitate a proactive stance in ensuring proper evaluation of thermal process lethality. The multiplicity of sub lethal stresses that the food borne bacterial pathogens are experienced during food processing, distribution and storage need to be studied and the obtained data to be translated into predictive models for food safety References Alderton, J., & Snell, N. (1970). Chemical sates of bacterial spores: Heat resistance its kinetics at intermediate water activity. Applied Microbiology, 19, 565–572. Alvarez, I., Vitro, R., Condo´n, S., & Raso, J. (2003). Comparing predicting models for the Escherichia coli inactivation by pulsed electronic fields. Innovative Food Science and Emerging Technologies, 4, 195–202. Archer, D. L. (1996). Preservation microbiology and safety: Evidence that stress enhances virulence and triggers adaptive mutations. Trends in Food Science and Technology, 7, 91–95. Augustin, J. C., Carlier, V., & Rozier, J. (1998). Mathematical modeling of the heat resistance of Listeria monocytogenes. Journal of Applied Microbiology, 84, 185–191. Bigelow, W. A., & Esty, J. R. (1920). Thermal death point of thermophiles and time. Journal of Infectious Diseases, 27, 602–617. Bunning, V. K., Crawford, R. G., Tierney, J. T., & Peeler, J. T. (1990). Thermotolerance of Listeria monocytogenes and Salmonella typhimurium after sub lethal heat shock. Applied and Environmental Microbiology, 56, 3216–3219. Bunning, V. K., Crawford, R. G., Tierney, J. T., & Peeler, J. T. (1992). Thermotolerance of heat-shocked Listeria monocytogenes in milk exposed to high-temperature, short-time pasteurization. Applied and Environmental Microbiology, 58, 2096–2098. Burdon, R. H. (1986). Heat shock and the heat shock proteins. Biochemical Journal, 240, 313–324. Carlier, V., Augustin, J. C., & Rozier, J. (1996). Heat resistance of Listeria monocytogenes (phagovar 2389/2425/3274/47/108/340): D- and zvalues in Ham. Journal of Food Protection, 59, 588–591. Cerf, O. (1977). A review: Tailing of survival curves of bacterial spores. Journal of Applied Bacteriology, 42, 1–19. Cole, M. B., Davies, K. W., Munro, G., Holoyoak, C. D., & Kilsby, D. C. (1993). A vitalistic model to describe the thermal inactivation of Listeria monocytogenes. Journal of Industrial Microbiology, 12, 232–239. Doyle, M. E., Mazzota, A. S., Wang, T., Wiseman, D. W., & Scott, V. N. (2001). Heat resistance of Listeria monocytogenes. Journal of Food Protection, 64, 410–425. Ellis, R. J., & van der Vies, S. M. (1991). Molecular chaperones. Annual Review of Biochemistry, 60, 321–347. Farber, J. M., & Brown, B. E. (1990). Effect of prior heat shock on heat resistance of Listeria monocytogenes in meat. Applied and Environmental Microbiology, 56, 1584–1587. Fedio, W. M., & Jackson, H. (1989). Effect of tempering on the heat resistance of Listeria monocytogenes. Letters in Applied Microbiology, 9, 157–160.

Fernandez, A., Collado, L. M., Cunha, M., Osio, J., & Martinez, A. (2002). Empirical model building based on 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. Geeraerd, A. H., Herremans, C. H., & Van Impe, J. F. (2000). Structural model requirement to describe microbial inactivation during a mild heat treatment. International Journal of Food Microbiology, 59, 185–209. Gellin, B. G., & Broome, C. V. (1989). Listeriosis. Journal of the American Medical Association, 261, 1313–1320. Georgopoulos, C., & Welch, W. J. (1993). Role of he major heat shock proteins as molecular chaperones. Annual Review of Cell Biology, 9, 601–634. Gill, C. O., & Reichel, M. P. (1989). Growth of the cold-tolerant pathogens Yersinia enterocolitica, Aeromonas hydrophila and Listeria monocytogenes on high – pH beef packaged under vacuum or carbon dioxide. Food microbiology, 6, 223–230. Gudbjonsdottir, B., Suihiko, M. L., Gustavsson, P., Thorkelsson, G., Salo, S., & Sjoberg, A. M. (2004). The incidence of Listeria monocytogenes in meat, poultry and seafood plants in Nordic countries. Food Microbiology, 21, 217–225. Hansen, T. B., Knochel, S., Juncher, D., & Bertelsen, G. (1995). Storage characteristics of sous-vide cooked roast beef. International Journal of Food Science and Technology, 30, 365–379. Hansen, T. B., & Riemann, H. (1963). Factors affecting the heat resistance of nonsporing organisms. Journal of Applied Bacteriology, 26, 314–333. Hassani, M., Alvarez, I., Raso, J., Condo´n, S., & Paga`n, R. (2005). Comparing predicting models for heat inactivation of Listeria monocytogenes and Pseudomonas aeruginosa at different pH. International Journal of Food Microbiology, 100, 213–222. Hassani, M., Man˜as, P., Raso, J., Condo´n, S., & Paga`n, R. (2005). Predicting heat inactivation of Listeria monocytogenes under non isothermal treatments. Journal of Food Protection, 68, 143–736. Jemmi, T., & Stephan, R. (2006). Listeria monocytogenes: Food-borne pathogen and hygiene indicator. Revue Scientifique et Technique de l Office International des Epizooties, 25(2), 571–580. Jorgensen, F., Hansen, T. B., & Knochel, S. (1999). Heat shock-induced thermotolerance in Listeria monocytogenes 13-249 is dependent on growth phase, pH and lactic acid. Food Microbiology, 16, 185–194. Jorgensen, F., Panaretou, B., Stephens, P. J., & Knochel, S. (1996). Effect of pre- and post incubation temperature on thermotolerance and heat shock proteins in Listeria monocytogenes. Journal of Applied Bacteriology, 80, 216–224. Jorgensen, F., Stephens, P. J., & Knochel, S. (1995). The effect of osmotic shock and subsequent adaptation on the thermotolerance and cell morphology of Listeria monocytogenes. Journal of Applied Bacteriology, 79, 274–281. Juneja, V. K., Klein, P. G., & Marmer, B. S. (1998). Heat shock and thermotolerance of Escherichia coli O157:H7 in a model beef gravy system and ground beef. Journal of Applied Microbiology, 84, 677–684. Juneja, V. K., & Marks, H. M. (2003). Mathematical description of non linear survival curves of Listeria monocytogenes. Innovative Food Science and Emerging Technology, 4, 307–317. Katchinski, D. M. (2004). On heat and cells and proteins. News in Physiological Sciences, 19, 11–15. Keetae, K., Murano, E. A., & Olson, D. G. (1994). Effect of heat shock on production of listeriolysin O by Listeria monocytogenes. Journal of Food Safety, 14(4), 273–279. Knabel, S. J., Walker, H. W., Hartman, P. A., & Mendonca, A. F. (1990). Effect of growth temperature and strictly anaerobic recovery on the survival of Listeria monocytogenes during pasteurization. Applied and Environmental Microbiology, 56, 370–376. Leistner, L. (1995). Principles and applications of hurdle technology. In G. W. Gould (Ed.), New methods of food preservation (pp. 1–21). Blackie Academic & Professional. Lin, Y.-D., & Chou, C.-C. (2004). Effect of heat shock on thermal tolerance and susceptibility of Listeria monocytogenes to other environmental stresses. Food Microbiology, 21, 605–610.

D. Sergelidis, A. Abrahim / Food Control 20 (2009) 1–10 Lindquist, S. (1986). The heat-shock response. Annual Review of Biochemistry, 55, 1151–1191. Linton, R. H., Carter, W. H., Pierson, M. D., & Hackney, C. R. (1995). Use of a modified Gompertz equation to model nonlinear survival curves for Listeria monocytogenes Scott A. Journal of Food Protection, 58, 946–954. Linton, R. H., Pierson, M. D., & Bishop, J. R. (1990). Increase in heat resistance of Listeria monocytogenes Scott A by sub lethal heat shock. Journal of Food Protection, 53, 924–927. Linton, R. H., Webster, J. B., Pierson, M. D., Bishop, J. R., & Cagney, C. R. (1992). The effect of sublethal heat shock and growth atmosphere on the heat resistance of Listerria monocytogenes Scott A. Journal of Food Protection, 55, 84–87. Lou, Y., & Yousef, A. E. (1996). Resistance of Listeria monocytogenes to heat after adaptation to environmental stress. Journal of Food Protection, 59, 465–471. Lou, Y., & Yousef, A. E. (1997). Adaptation to sublethal environment stresses protects Listeria monocytogenes against lethal preservation factors. Applied and Environmental Microbiology, 63, 1252–1255. Lou, Y., & Yousef, A. E. (1999). Characteristics of Listeria monocytogenes important to food processors. In E. T. Ryser & E. H. Marth (Eds.), Listeria, listeriosis and food safety (pp. 131–224). New York: Marcel Dekker. Lund, B. M., Baird-Parker, T. C., & Gould, G. W. (2000). The microbiological safety and quality of food. Gaithersburg, MD: Aspen Publishers Inc. Mackey, B. M., & Derrick, C. M. (1986). Elevation of the heat resistance of Salmonella typhimurium by sublethal heat shock. Journal of Applied Bacteriology, 61, 389–393. Mackey, B. M., & Derrick, M. D. (1987a). Changes in the heat resistance of Salmonella typhimurium during heating at rising temperatures. Lett. Applied Microbiology, 4, 13–16. Mackey, B. M., & Derrick, M. D. (1987b). The effect of prior shock on the thermoresistance of Salmonella thompson in foods. Letters in Applied Microbiology, 5, 115–118. Mackey, B. M., & Derrick, M. D. (1990). Heat shock synthesis and thermotolerance in Salmonella typhimurium. Journal of Applied Microbiology, 89, 373–383. Mafart, P., Couvert, O., Gaillard, S., & Lequerinel, I. (2002). On calculating sterility in thermal preservation methods: Application of the Weibull frequency distribution model. International Journal of Food Microbiology, 72, 107–113. Man˜as, P., Paga´n, R., Alvarez, I., & Condon, S. (2003). Survival of Salmonella seftenberg 775W to current liquid whole egg pasteurization treatments. Food Microbiology, 20, 593–600. Man˜as, P., Paga´n, R., Sala, F. J., & Condo´n, S. (2001). Low molecular weight milk whey components protect Salmonella senftenberg 775W against heat by a mechanism involving divalent cations. Journal of Applied Microbiology, 91, 871–877. Mazzota, A. S., & Gombas, D. E. (2001). Heat resistance of an outbreak strain of Listeria monocytogenes in hot dog batter. Journal of Food Protection, 64, 321–324. McClain, D., & Lee, D. H. (1988). Development of a USDA-FSIS method for isolation of Listeria monocytogenes from raw meat and poultry. Journal of the Association of Official Analytical Chemists, 71, 660–664. McDowell, D. A. (2004). Food processing stresses in the spread of antibiotic resistance. In F. J. M. Smulders & J. D. Collins (Eds.). Safety assurance during food processing: Food safety assurance and veterinary public health (Vol. 2, pp. 243–265). Wageningen, The Netherlands: Wageningen Academic Publishers. Mead, P. S., Slutsker, L., Dietz, V., McCaig, L. F., Bresee, J. S., Shapiro, C., et al. (1999). Food-related illness and death in the United States. Emerging Infectious Diseases, 5, 607–625. Moats, W. A., Dabbah, R., & Edwards, V. M. (1971). Interpretation of nonlogarithmic curves of heated bacteria. Journal of Food Science, 36, 526. Novak, J. S., & Juneja, V. K. (2003). Effects of refrigeration or freezing on survival of Listeria monocytogenes Scott A in undercooked ground beef. Food Control, 14(1), 25–35.

9

Paga`n, R., Condo´n, S., & Sala, F. J. (1997). Effects of several factors on the heat-shock-induced thermotolerance of Listeria monocytogenes. Applied and Environmental Microbiology, 63, 3225–3232. Parsell, D. A., & Lindquist, S. (1993). The function of heat-shock proteins in stress tolerance: Degradation and reactivation of damaged proteins. Annual Review of Genetics, 27, 437–496. Peleg, M. (2006). Advanced quantitative microbiology for foods and biosystems. Models for predicting growth and inactivation. Boca Raton, FL: CRC Press. Peleg, M., & Cole, M. B. (1998). Reinterpretation of microbial survival curves. Critical Reviews in Food Science and Nutrition, 38, 353–380. Peleg, M., & Penchina, C. M. (2000). Modelling microbial survival during exposure to a lethal agent with varying intensity. Critical Review in Food Science and Nutrition, 40, 159–172. Phan-Thanh, L., & Gormon, T. (1995). Analysis of heat and cold shock proteins in Listeria by two-dimensional electrophoresis. Electrophoresis, 16, 444–450. Phan-Thanh, L., & Gormon, T. (1996). Stress proteins in Listeria monocytogenes. Electrophoresis, 18, 1464–1471. Quintavalla, S., & Barbuti, S. (1989). Heat resistance of Listeria inocua and Listeria monocytogenes isolated from pork. Industria Conserve, 63, 8–12. Quintavalla, S., & Campanini, M. (1991). Effect of rising temperature on the heat resistance of Listeria monocytogenes in meat emulsion. Letters in Applied Microbiology, 12, 184–187. Rocourt, J., & Bille, J. (1997). Foodborne listeriosis. World Health Statistics Quarterly, 50(1–2), 67–73. Rocourt, J., & Cossart, P. (1997). Listeria monocytogenes. In M. P. Doyle, L. R. Beuchat, & T. J. Montville (Eds.), Food microbiology – Fundamentals and frontiers (pp. 237–352). Washington DC: American Society for Microbiology (ASM) Press. Rodrigo, D., Ruı`z, P., Barbosa-Ca`novas, G. V., Martinez, A., & Rodrigo, M. (2003). Kinetic model for the inactivation of Lactobacillus plantarum by pulsed electric fields. International Journal of Food Microbiology, 81, 223–229. Ross, T., & McMeekin, T. A. (1994). Predictive microbiology. International Journal of Food Microbiology, 23, 241–264. Rowan, N. J. (1999). Evidence that inimical food preservation barriers alter microbial resistance, cell morphology and virulence. Trends in Food Science and Technology, 10, 261–270. Rowan, N. J., & Anderson, J. G. (1998). Effects of above-optimum growth temperature and cell morphology on thermotolerance of Listeria monocytogenes cells suspended in bovine milk. Applied and Environmental Microbiology, 64(6), 2065–2071. Schlesinger, M. J. (1986). Heat shock proteins: The search for functions. Journal of Cell Biology, 103, 321–325. Schlesinger, M. J. (1994). How the cell copes with stress and the function of heat shock proteins. Pediatric Research, 36, 1–6. Sergelidis, D., Stefanopoulou, A. M., & Genigeorgis, C. (2001). Effect of incubation temperature on the thermal resistance of Listeria monocytogenes and Salmonella typhimurium. In Proceedings of the 2nd Balkan conference of microbiology (p. 237). Sofos, J. N. (1993). Current microbiological considerations in food preservation. International Journal of Food Microbiology, 19, 87–108. Sokolovic, Z., Fuchs, A., & Goebel, W. (1990). Synthesis of species – Specific stress proteins by virulent strains of Listeria monocytogenes. Infection and Immunity, 58(11), 3582–3587. Stephens, P. J., Cole, M. B., & Jones, M. V. (1994). Effect of heating rate on the thermal inactivation of Listeria monocytogenes. Journal of Applied Bacteriology, 77, 702–708. Stephens, P. J., & Jones, M. V. (1993). Reduced ribosomal thermal denaturation in Listeria monocytogenes following osmotic and heat shocks. FEMS Microbiology Letters, 106, 177–182. Stumbo, C. R. (1973). Thermobacteriology in food processing (2nd ed.). New York: Academic Press. Tomlins, R. I., & Ordal, L. (1976). Thermal injury and inactivation in vegetative bacteria. In Society of applied bacteriology symposium (Vol. 5, pp. 153–190).

10

D. Sergelidis, A. Abrahim / Food Control 20 (2009) 1–10

Valdramidis, V. P., Geeraerd, A. H., & Van Impe, J. F. (2007). Stress adaptive responses by heat under the microscope of predictive microbiology. Journal of Applied Microbiology. Online early articles. . Van Boekel, M. A. J. S. (2002). On the use of the Weibull model to describe thermal inactivation of microbial vegetative cells. International Journal of Food Microbiology, 74, 139–159. Velkov, V. V. (1999). How environmental factors regulate mutagenesis and gene transfer in microorganisms. Journal of Bioscience, 24, 529–559.

Walsh, D., Sheridan, J. J., Duffy, G., Blair, I. S., McDowell, D. A., & Harrington, D. (2001). Thermal resistance of wild type and antibiotic resistant Listeria monocytogenes in meat ad potato substrates. Journal of Applied Microbiology, 90, 555–560. Whiting, R. C. (1995). Microbial modeling in foods. Critical Reviews in Food Science and Nutrition, 35, 467–494.