Authors:
O. Haykir Department of Food Microbiology, Hygiene and Safety, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), Somlói út 14–16, 1118, Budapest, Hungary

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Cs. Mohácsi-Farkas Department of Food Microbiology, Hygiene and Safety, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), Somlói út 14–16, 1118, Budapest, Hungary

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T. Engelhardt Digital Food Chain Education, Research, Development and Innovation Institute, University of Veterinary Medicine, István u. 2, 1078, Budapest, Hungary

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Abstract

Its ability to survive under different environmental conditions makes Listeria monocytogenes a critical concern for food safety. When the microorganisms are exposed to sublethal heat treatment above their optimum growth temperature, they increase stress adaptation for further heat treatments. In order to investigate heat stress resistance of L. monocytogenes, L. innocua as a surrogate was exposed to sublethal heat at 46 °C for 30 and 60 min, prior to heat treatment at 60 °C. There was no significant difference in D60°C values between samples exposed to sublethal heat for 30 min and non-pre-heat-treated samples (control) (P > 0.05). In comparison, sublethal heat treatment for 60 min caused a significant increase in D60°C values compared to control samples (P < 0.05). Additionally, cluster analysis of mass spectra obtained from MALDI-TOF was analysed by discriminant analysis of principal components (DAPC) for sublethal heat treatment at 46 °C for 30 min and control group to check stress response at the proteomic level. However, differentiation of stress responses by distinct clusters was not revealing.

Abstract

Its ability to survive under different environmental conditions makes Listeria monocytogenes a critical concern for food safety. When the microorganisms are exposed to sublethal heat treatment above their optimum growth temperature, they increase stress adaptation for further heat treatments. In order to investigate heat stress resistance of L. monocytogenes, L. innocua as a surrogate was exposed to sublethal heat at 46 °C for 30 and 60 min, prior to heat treatment at 60 °C. There was no significant difference in D60°C values between samples exposed to sublethal heat for 30 min and non-pre-heat-treated samples (control) (P > 0.05). In comparison, sublethal heat treatment for 60 min caused a significant increase in D60°C values compared to control samples (P < 0.05). Additionally, cluster analysis of mass spectra obtained from MALDI-TOF was analysed by discriminant analysis of principal components (DAPC) for sublethal heat treatment at 46 °C for 30 min and control group to check stress response at the proteomic level. However, differentiation of stress responses by distinct clusters was not revealing.

1 Introduction

Because of its high fatality rate, survival in different environmental conditions such as refrigeration temperatures, acidic foods, high salt content, Listeria monocytogenes is a considerable concern in the food industry (Doyle et al., 2001; Gandhi and Chikindas, 2007; Sergelidis and Abrahim, 2009). In 2018, a multi-country outbreak of Listeria monocytogenes serogroup IVb, caused by frozen vegetables produced in Hungary, was reported. According to the report, the strain remained persistent after cleaning and sanitisation treatment in the factory for years. This outbreak caused 47 cases with nine deaths (case fatality rate 19%) (European Food Safety Authority (EFSA), 2018).

Yousef and Courtney (2002) define stress as any deleterious factor or condition that negatively influences microbial growth or survival. Microorganisms respond to these stresses in various ways, such as protein synthesis for damage and cell transformation to a viable but non-culturable state (VBNC). These responses enhance the tolerance of the microorganisms to the following same or different types of stress. This phenomenon is called stress adaptation (Sergelidis and Abrahim, 2009). Stress adaptation to heat and other types of stresses, its mechanisms and its impact on the food industry have been reviewed previously (Doyle et al., 2001; Gandhi and Chikindas, 2007; NicAogáin and O’Byrne, 2016; Bucur et al., 2018). Strain variation, age of microorganism, growth conditions, test conditions, and food matrix are the main factors that affect heat resistance of L. monocytogenes and other microorganisms (Doyle et al., 2001).

Physiological cellular responses like thermotolerance are caused by the synthesis of different proteins called heat shock proteins (HSPs). These heat-shock proteins are mainly protein chaperons that cause the folding and assembly of damaged proteins. Stress adaptation causes changes in protein expression, which are reflected in the proteome of the microorganisms. For this reason, investigating the proteome of the microorganisms under various stress conditions can give illustrative thoughts about stress adaptation of the microorganisms. Since it is much faster than two-dimensional gel electrophoresis (2D GE) and able to catch low molecular weight stress proteins, Matrix-Assisted Laser Desorption Ionization - Time of Flight Mass Spectrometry (MALDI-TOF MS) protein profiling also makes it possible to detect stress responses. Ribosomal and cell structure proteins show up as peaks in MALDI-TOF mass spectra. The changes in the characteristics of the peaks enable us to analyse the stress response of the microorganisms (Schott et al., 2016).

The overall objective of this study was to investigate the enhanced heat tolerance of L. innocua as a surrogate of L. monocytogenes after sub-lethal heat exposure. The aim of the current work focused on the survival characteristics and changes in the proteome of the bacterium.

2 Materials and methods

2.1 Strain

Listeria innocua strain (T1), a strain from the collection of MATE, was inoculated into Trypto-Casein Soy Broth (TSB, Biokar, France) (pH 7.3) at 37 °C to yield a cell population of approximately 8 lg CFU mL−1.

2.2 Identification of enhanced heat resistance

Sublethal stress conditions were applied according to the protocol of Ágoston et al. (2010). The time-temperature combinations used for sub-lethal heat stress were 46 °C for 30 and 60 min. After exposure to the sublethal heat stress, the samples were immediately transferred to a water bath (Haake, Germany) set appropriately so that the samples were exposed to temperatures of 60 °C for 0, 3, 6, and 9 min. For control, samples without prior heat treatment were placed into the water bath at 60 °C. The heat-treated samples were immediately placed into an ice-bath prior to serial dilution in tubes containing 9 mL of peptone-NaCl (0.85%) buffer. The diluted samples were spread plated on Trypto-Casein Soy Agar (TSA, Biokar, France). The plates were incubated for 24 h at 37 °C prior to enumeration.

2.3 Sample preparation and MALDI-TOF MS analysis

Sample preparation for cluster analysis of MALDI-TOF peaks was made with modifications to the previous work of Schott et al. (2016). In order to obtain mass spectra, samples were taken from a water bath every 3 min for 15 min for both control and sub-lethal heat exposed samples for 46 °C for 30 min. Mass spectra of the samples for mass range 2–20 kDa are obtained in MALDI-TOF MS (BrukerDaltonics, Bremen, Germany) by 280 accumulated laser shots. All experiments were carried out in triplicates on three different days.

2.4 Data processing and statistical analysis

2.4.1 Determination of D-value

The D60°C -values of the strain after the sub-lethal heat exposure of 30 and 60 min at 46 °C with the control samples were calculated to determine whether the sub-lethal heat exposure increased the D-value as previously described by Farber and Brown (1990).

2.4.2 Cluster analysis of the peaks from MALDI-TOF MS

The baseline of the exported mass spectra of each sample was subtracted as pre-processing. Peak-based cluster analysis was applied to these pre-processed mass spectra to illustrate the stress response dynamics. Visualisation by dendrogram was carried out with the KNIME Analytics Platform (Version 4.2.1) with R Foundation for Statistical Computing (Vienna, Austria). A package for RStudio software, adegenet was used for discriminant analysis of principal components (DAPC) to analyse the differentiation of stress responses (Jombart, 2008). Clusters were defined as previously described by Schott et al. (2016). In the end, DAPC maintains a barplot of eigenvalues and a scatterplot representing individuals as dots and groups as inertia ellipses.

3 Results and discussion

The inactivation kinetics of L. innocua T1 after the sub-lethal heat exposure for 30 and 60 min and without prior exposure (control) are shown in Figs 1 and 2, respectively.

Fig. 1.
Fig. 1.

Enhanced heat resistance of L. innocua T1 at 60 °C when pre-exposed for 30 min at 46 °C, y control = 0.2479x + 7.2605, R 2 control = 0.9628, D60°C control = 4.03 min, y pre-exposure at 46°C for 30 min = 0.2345x + 7.774, R 2 pre-exposure at 46°C for 30 min = 0.9043, D60°C, pre-exposure at 46°C for 30 min = 4.26 min

Citation: Acta Alimentaria 51, 2; 10.1556/066.2022.00013

Fig. 2.
Fig. 2.

Enhanced heat resistance of L. innocua T1 at 60 °C when pre-exposed for 60 min at 46 °C, y control = 0.2732x + 8.5395, R 2 control = 0.9639, D60°C, control = 3.66 min, y pre-exposure at 46°C for 60 min = 0.1751x + 8.2021, R 2 pre-exposure at 46°C for 60 min = 0.8833, D60°C, pre-exposure at 46°C for 60 min = 5.71 min

Citation: Acta Alimentaria 51, 2; 10.1556/066.2022.00013

Table 1 shows D60°C values of sub-lethal heat exposed samples at 46 °C for 30 and 60 min and non-prior heat exposured (control) samples. There was no significant difference in D60°C values between the samples after prior exposure of 46 °C for 30 min and the control (P > 0.05). Instead, treatment of 46 °C for 60 min enhanced survival of the strain at 60 °C (P < 0.05).

Table 1.

Effect of pre-exposure to sub-lethal temperatures of 46 °C for 30 and 60 min on the D60°C values for Listeria innocua T1 in Tryptic Soy Broth

Exposure time to sub-lethal temperature (min) D60°C values ( ± Standard Deviation ) (min)
Control Pre-exposured
30 4.03 (±1.06)a 4.26 (±0.36)a
60 3.66 (±0.47)a 5.71 (±0.85)b

a-b For each row, different superscripts denote statistically significant difference P < 0.05.

Thirty-four mass spectra from control samples and sub-lethal heat exposed samples at 46 °C for 30 min were analysed to check possible differentiation at the proteome level. Of these 34 samples, 18 belong to sub-lethal heat treatment samples, while 16 of these samples belong to control samples. Two samples from the control group were excluded since no mass spectra were obtained because of a mistake during the sample preparation procedure. These thirty-four samples were grouped into three different clusters (Fig. 3). This separation lies in the mathematical approach, discriminant analysis of principal components (DAPC). Briefly, Principal Component Analysis (PCA) is a statistical method that looks at each spectrum with the most variation, while Discriminant Analysis (DA) aims to maximise the separation of known categories. If we look at these clusters, cluster 1 contains 12 samples, cluster 2 contains four samples, and cluster 3 contains 18 samples. Seven of the control samples were in the first cluster, two were in the second cluster, and seven were in the third cluster. For the sub-lethal heat-treated samples, five were in the first cluster, two were in the second cluster, and eleven were in the third cluster (data not shown). Overall, there was no meaningful separation of the samples into the different groups.

Fig. 3.
Fig. 3.

Clusters of the MALDI-TOF MS peaks, obtained from the DAPC analysis of the peaks from control and pre-heat exposed samples at 46 °C to 30 min

Citation: Acta Alimentaria 51, 2; 10.1556/066.2022.00013

Ágoston et al. (2010) studied enhanced heat resistance on L. monocytogenes after prior heat exposure to 46 °C for 30 and 60 min. There were 1.7 and 5.3 fold increase in D60°C values, respectively, compared to the samples heated at 60 °C without prior heat-treatment. However, there was a decrease in heat resistance after the treatment of 50 °C for 60 min, compared to 30 min. They concluded an upper limit in terms of sub-lethal heat resistance. Farber and Brown (1990) investigated the effect of prior exposure of different L. monocytogenes strains to sub-lethal temperature exposure in sausage mix. No significant difference was reported in D64°C values when they treated samples at 48 °C for 30 and 60 min. Instead, there was a 2.4 fold increase in D64°C values after the pre-exposure of 48 °C for 120 min, compared to untreated cells. In our study, there was no significant increment in D60°C values after sub-lethal heat treatment at 46 °C for 30 min, while there was a 1.6 fold increase in D60°C values after 60 min of treatment. Shen et al. (2014) examined D60°C values of 3 different heat-tolerant strains of L. monocytogenes to search for enhanced heat adaptation after subjecting to sublethal heat stress at 46 °C for 30 and 60 min. There was a significant heat resistance in all strains after 30 and 60 min sublethal heat treatment. However, sublethal heat treatment for 90 min caused no significant difference in D60°C value in one of the strains, compared to control. Also no difference in D60°C value after 15 min of heat treatment was found in one of the strains. Our results and previous results show that heat stress adaptation depends on the duration of sublethal heat exposure. Stephens et al. (1994) demonstrated the food safety risk in slow-cooked foods by investigating the effect of heating rate on the thermal inactivation of L. monocytogenes.

Sörqvist (2003) stated that to use an indicator organism to evaluate the heat resistance of an actual microorganism, indicator bacteria should have equal or more heat resistance. It is suggested that the heat resistance of L. innocua may have higher average heat resistance than L. monocytogenes. It is also stated that research on the heat resistance of L. innocua as a surrogate is insufficient. Therefore, non-pathogenic L. innocua is used in our research as an indicator for heat resistance of L. monocytogenes.

As said before, there are some genomic and proteomic responses after exposing L. monocytogenes to sublethal heat temperature conditions. Van der Veen et al. (2007) showed that some genes of L. monocytogenes were differentially expressed when the cells were exposed to a prior sublethal temperature of 48 °C. In similar research done by Agoston et al. (2009), 20 proteins were differentially expressed (ten up-regulated and ten down-regulated) when cells were initially exposed to 48 °C for 30 min before 60 °C for 9 min. In order to investigate the changes on the molecular level in L. innocua after sublethal heat exposure of 46 °C for 30 min, mass spectra obtained from MALDI-TOF were analysed in our research. The hypothesis was that after the changes in the proteome of the samples, control and pre-heat exposed samples might be positioned in different clusters. Alternatively, that samples could be separated from each other after a particular exposure time, so it can be proven that there is a specific time needed for the changes in the proteome of the samples to appear. However, the separation of the samples did not give a revealing result. The three clusters were not meaningful, proving our results that there was no significant difference (P > 0.05) in the D60°C values of sublethal heat-treated samples for 46 °C for 30 min and control samples. According to our knowledge, this is the first research on peak based cluster analysis of heat stressed samples of L. innocua or L. monocytogenes.

4 Conclusions

Enhanced heat resistance of L. innocua T1 as a surrogate of L. monocytogenes was investigated. There was no significant difference in D60°C values between control samples and sublethal heat exposed samples at 46 °C for 30 min (P > 0.05). Instead, when the cells were exposed to 46 °C for 60 min, there was a significant increase in the D60°C value (P < 0.05). Additionally, no meaningful differentiation was found after analysing MALDI-TOF MS spectra of control and sublethal heat exposed samples at 46 °C for 30 min. These results suggest that heat stress adaptation depends on the duration of the heat treatment.

Acknowledgements

The author and this research were funded by the Stipendium Hungaricum Programme and the Doctoral School of Food Sciences at the Hungarian University of Agriculture and Life Sciences.

References

  • Ágoston, R. , Mohácsi-Farkas, C. , and Pillai, S. (2010). Exposure to sub-lethal temperatures induces enhanced heat resistance in Listeria monocytogenes. Acta Alimentaria, 39: 327336. https://doi.org/10.1556/AAlim.39.2010.3.9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Agoston, R. , Soni, K. , Jesudhasan, P.R. , Russell, W.K. , Mohácsi-Farkas, C. , and Pillai, S.D. (2009). Differential expression of proteins in Listeria monocytogenes under thermotolerance-inducing, heat shock, and prolonged heat shock conditions. Foodborne Pathogens and Disease ,6: 11331140. https://doi.org/10.1089/fpd.2009.0286.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bucur, F.I. , Grigore-Gurgu, L. , Crauwels, P. , Riedel, C.U. , and Nicolau, A.I. (2018). Resistance of Listeria monocytogenes to stress conditions encountered in food and food processing environments. Frontiers in Microbiology, 9: 2700. https://doi.org/10.3389/fmicb.2018.02700.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doyle, M.E. , Mazzotta, A.S. , Wang, T. , Wiseman, D.W. , and Scott, V.N. (2001). Heat resistance of Listeria monocytogenes. Journal of Food Protection, 64: 410429. https://doi.org/10.4315/0362-028x-64.3.410.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • European Food Safety Authority (EFSA) (2018). Multi-country outbreak of Listeria monocytogenes serogroup IVb, multi-locus sequence type 6, infections linked to frozen corn and possibly to other frozen vegetables – first update. EFSA Supporting Publications, 15(7): 1448E. https://doi.org/10.2903/sp.efsa.2018.EN-1448.

    • Search Google Scholar
    • Export Citation
  • Farber, J.M. and Brown, B.E. (1990). Effect of prior heat shock on heat resistance of Listeria monocytogenes in meat. Applied and Environmental Microbiology, 56: 15841587. https://doi.org/10.1128/aem.56.6.1584-1587.1990.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gandhi, M. and Chikindas, M.L. (2007). Listeria: a foodborne pathogen that knows how to survive. International Journal of Food Microbiology ,113(1): 115. https://doi.org/10.1016/j.ijfoodmicro.2006.07.008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jombart, T. (2008). adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics Oxford England 24: 14031405. https://doi.org/10.1093/bioinformatics/btn129.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • NicAogáin, K. and O’Byrne, C.P. (2016). The role of stress and stress adaptations in determining the fate of the bacterial pathogen Listeria monocytogenes in the food chain. Frontiers in Microbiology, 7: 1865. https://doi.org/10.3389/fmicb.2016.01865.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schott, A.-S. , Behr, J. , Quinn, J. , and Vogel, R.F. (2016). MALDI-TOF mass spectrometry enables a comprehensive and fast analysis of dynamics and qualities of stress responses of Lactobacillus paracasei subsp. paracasei F19. PloS One, 11: e0165504. https://doi.org/10.1371/journal.pone.0165504.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sergelidis, D. and Abrahim, A. (2009). Adaptive response of Listeria monocytogenes to heat and its impact on food safety. Food Control, 20: 110. https://doi.org/10.1016/j.foodcont.2008.01.006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shen, Q. , Jangam, P.M. , Soni, K.A. , Nannapaneni, R. , Schilling, W. , and Silva, J.L. (2014). Low, medium, and high heat tolerant strains of Listeria monocytogenes and increased heat stress resistance after exposure to sublethal heat. Journal of Food Protection, 77: 12981307. https://doi.org/10.4315/0362-028X.JFP-13-423.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sörqvist, S. (2003). Heat resistance in liquids of Enterococcus spp., Listeria spp., Escherichia coli, Yersinia enterocolitica, Salmonella spp. and Campylobacter spp. Acta Veterinaria Scandinavica, 44(1–2): 119. https://doi.org/10.1186/1751-0147-44-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stephens, P.J. , Cole, M.B. , and Jones, M.V. (1994). Effect of heating rate on the thermal inactivation of Listeria monocytogenes. The Journal of Applied Bacteriology, 77: 702708. https://doi.org/10.1111/j.1365-2672.1994.tb02822.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van der Veen, S. , Hain, T. , Wouters, J.A. , Hossain, H. , de Vos, W.M. , Abee, T. , Chakraborty, T. , and Wells-Bennik, M.H.J. (2007). The heat-shock response of Listeria monocytogenes comprises genes involved in heat shock, cell division, cell wall synthesis, and the SOS response. Microbiology Reading England, 153: 35933607. https://doi.org/10.1099/mic.0.2007/006361-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yousef, A.E. and Courtney, P.D. (2002). Basics of stress adaptation and implications in new-generation foods. In: Yousef, A.E. and Juneja, V.K. (Eds.) Microbial stress adaptation and food safety. CRC Press, pp. 125.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ágoston, R. , Mohácsi-Farkas, C. , and Pillai, S. (2010). Exposure to sub-lethal temperatures induces enhanced heat resistance in Listeria monocytogenes. Acta Alimentaria, 39: 327336. https://doi.org/10.1556/AAlim.39.2010.3.9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Agoston, R. , Soni, K. , Jesudhasan, P.R. , Russell, W.K. , Mohácsi-Farkas, C. , and Pillai, S.D. (2009). Differential expression of proteins in Listeria monocytogenes under thermotolerance-inducing, heat shock, and prolonged heat shock conditions. Foodborne Pathogens and Disease ,6: 11331140. https://doi.org/10.1089/fpd.2009.0286.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bucur, F.I. , Grigore-Gurgu, L. , Crauwels, P. , Riedel, C.U. , and Nicolau, A.I. (2018). Resistance of Listeria monocytogenes to stress conditions encountered in food and food processing environments. Frontiers in Microbiology, 9: 2700. https://doi.org/10.3389/fmicb.2018.02700.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doyle, M.E. , Mazzotta, A.S. , Wang, T. , Wiseman, D.W. , and Scott, V.N. (2001). Heat resistance of Listeria monocytogenes. Journal of Food Protection, 64: 410429. https://doi.org/10.4315/0362-028x-64.3.410.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • European Food Safety Authority (EFSA) (2018). Multi-country outbreak of Listeria monocytogenes serogroup IVb, multi-locus sequence type 6, infections linked to frozen corn and possibly to other frozen vegetables – first update. EFSA Supporting Publications, 15(7): 1448E. https://doi.org/10.2903/sp.efsa.2018.EN-1448.

    • Search Google Scholar
    • Export Citation
  • Farber, J.M. and Brown, B.E. (1990). Effect of prior heat shock on heat resistance of Listeria monocytogenes in meat. Applied and Environmental Microbiology, 56: 15841587. https://doi.org/10.1128/aem.56.6.1584-1587.1990.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gandhi, M. and Chikindas, M.L. (2007). Listeria: a foodborne pathogen that knows how to survive. International Journal of Food Microbiology ,113(1): 115. https://doi.org/10.1016/j.ijfoodmicro.2006.07.008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jombart, T. (2008). adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics Oxford England 24: 14031405. https://doi.org/10.1093/bioinformatics/btn129.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • NicAogáin, K. and O’Byrne, C.P. (2016). The role of stress and stress adaptations in determining the fate of the bacterial pathogen Listeria monocytogenes in the food chain. Frontiers in Microbiology, 7: 1865. https://doi.org/10.3389/fmicb.2016.01865.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schott, A.-S. , Behr, J. , Quinn, J. , and Vogel, R.F. (2016). MALDI-TOF mass spectrometry enables a comprehensive and fast analysis of dynamics and qualities of stress responses of Lactobacillus paracasei subsp. paracasei F19. PloS One, 11: e0165504. https://doi.org/10.1371/journal.pone.0165504.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sergelidis, D. and Abrahim, A. (2009). Adaptive response of Listeria monocytogenes to heat and its impact on food safety. Food Control, 20: 110. https://doi.org/10.1016/j.foodcont.2008.01.006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shen, Q. , Jangam, P.M. , Soni, K.A. , Nannapaneni, R. , Schilling, W. , and Silva, J.L. (2014). Low, medium, and high heat tolerant strains of Listeria monocytogenes and increased heat stress resistance after exposure to sublethal heat. Journal of Food Protection, 77: 12981307. https://doi.org/10.4315/0362-028X.JFP-13-423.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sörqvist, S. (2003). Heat resistance in liquids of Enterococcus spp., Listeria spp., Escherichia coli, Yersinia enterocolitica, Salmonella spp. and Campylobacter spp. Acta Veterinaria Scandinavica, 44(1–2): 119. https://doi.org/10.1186/1751-0147-44-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stephens, P.J. , Cole, M.B. , and Jones, M.V. (1994). Effect of heating rate on the thermal inactivation of Listeria monocytogenes. The Journal of Applied Bacteriology, 77: 702708. https://doi.org/10.1111/j.1365-2672.1994.tb02822.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van der Veen, S. , Hain, T. , Wouters, J.A. , Hossain, H. , de Vos, W.M. , Abee, T. , Chakraborty, T. , and Wells-Bennik, M.H.J. (2007). The heat-shock response of Listeria monocytogenes comprises genes involved in heat shock, cell division, cell wall synthesis, and the SOS response. Microbiology Reading England, 153: 35933607. https://doi.org/10.1099/mic.0.2007/006361-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yousef, A.E. and Courtney, P.D. (2002). Basics of stress adaptation and implications in new-generation foods. In: Yousef, A.E. and Juneja, V.K. (Eds.) Microbial stress adaptation and food safety. CRC Press, pp. 125.

    • Crossref
    • Search Google Scholar
    • Export Citation
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Editor(s)-in-Chief: András Salgó

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       Editorial Board

  • L. Abrankó (Szent István University, Gödöllő, Hungary)
  • D. Bánáti (University of Szeged, Szeged, Hungary)
  • J. Baranyi (Institute of Food Research, Norwich, UK)
  • I. Bata-Vidács (Agro-Environmental Research Institute, National Agricultural Research and Innovation Centre, Budapest, Hungary)
  • J. Beczner (Food Science Research Institute, National Agricultural Research and Innovation Centre, Budapest, Hungary)
  • F. Békés (FBFD PTY LTD, Sydney, NSW Australia)
  • Gy. Biró (National Institute for Food and Nutrition Science, Budapest, Hungary)
  • A. Blázovics (Semmelweis University, Budapest, Hungary)
  • F. Capozzi (University of Bologna, Bologna, Italy)
  • M. Carcea (Research Centre for Food and Nutrition, Council for Agricultural Research and Economics Rome, Italy)
  • Zs. Cserhalmi (Food Science Research Institute, National Agricultural Research and Innovation Centre, Budapest, Hungary)
  • M. Dalla Rosa (University of Bologna, Bologna, Italy)
  • I. Dalmadi (Szent István University, Budapest, Hungary)
  • K. Demnerova (University of Chemistry and Technology, Prague, Czech Republic)
  • M. Dobozi King (Texas A&M University, Texas, USA)
  • Muying Du (Southwest University in Chongqing, Chongqing, China)
  • S. N. El (Ege University, Izmir, Turkey)
  • S. B. Engelsen (University of Copenhagen, Copenhagen, Denmark)
  • E. Gelencsér (Food Science Research Institute, National Agricultural Research and Innovation Centre, Budapest, Hungary)
  • V. M. Gómez-López (Universidad Católica San Antonio de Murcia, Murcia, Spain)
  • J. Hardi (University of Osijek, Osijek, Croatia)
  • K. Héberger (Research Centre for Natural Sciences, ELKH, Budapest, Hungary)
  • N. Ilić (University of Novi Sad, Novi Sad, Serbia)
  • D. Knorr (Technische Universität Berlin, Berlin, Germany)
  • H. Köksel (Hacettepe University, Ankara, Turkey)
  • K. Liburdi (Tuscia University, Viterbo, Italy)
  • M. Lindhauer (Max Rubner Institute, Detmold, Germany)
  • M.-T. Liong (Universiti Sains Malaysia, Penang, Malaysia)
  • M. Manley (Stellenbosch University, Stellenbosch, South Africa)
  • M. Mézes (Szent István University, Gödöllő, Hungary)
  • Á. Németh (Budapest University of Technology and Economics, Budapest, Hungary)
  • P. Ng (Michigan State University,  Michigan, USA)
  • Q. D. Nguyen (Szent István University, Budapest, Hungary)
  • L. Nyström (ETH Zürich, Switzerland)
  • L. Perez (University of Cordoba, Cordoba, Spain)
  • V. Piironen (University of Helsinki, Finland)
  • A. Pino (University of Catania, Catania, Italy)
  • M. Rychtera (University of Chemistry and Technology, Prague, Czech Republic)
  • K. Scherf (Technical University, Munich, Germany)
  • R. Schönlechner (University of Natural Resources and Life Sciences, Vienna, Austria)
  • A. Sharma (Department of Atomic Energy, Delhi, India)
  • A. Szarka (Budapest University of Technology and Economics, Budapest, Hungary)
  • M. Szeitzné Szabó (National Food Chain Safety Office, Budapest, Hungary)
  • S. Tömösközi (Budapest University of Technology and Economics, Budapest, Hungary)
  • L. Varga (University of West Hungary, Mosonmagyaróvár, Hungary)
  • R. Venskutonis (Kaunas University of Technology, Kaunas, Lithuania)
  • B. Wróblewska (Institute of Animal Reproduction and Food Research, Polish Academy of Sciences Olsztyn, Poland)

 

Acta Alimentaria
E-mail: Acta.Alimentaria@uni-mate.hu

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2021  
Web of Science  
Total Cites
WoS
856
Journal Impact Factor 1,000
Rank by Impact Factor Food Science & Technology 130/143
Nutrition & Dietetics 81/90
Impact Factor
without
Journal Self Cites
0,941
5 Year
Impact Factor
1,039
Journal Citation Indicator 0,19
Rank by Journal Citation Indicator Food Science & Technology 143/164
Nutrition & Dietetics 92/109
Scimago  
Scimago
H-index
30
Scimago
Journal Rank
0,235
Scimago Quartile Score

Food Science (Q3)

Scopus  
Scopus
Cite Score
1,4
Scopus
CIte Score Rank
Food Sciences 222/338 (Q3)
Scopus
SNIP
0,387

 

2020
 
Total Cites
768
WoS
Journal
Impact Factor
0,650
Rank by
Nutrition & Dietetics 79/89 (Q4)
Impact Factor
Food Science & Technology 130/144 (Q4)
Impact Factor
0,575
without
Journal Self Cites
5 Year
0,899
Impact Factor
Journal
0,17
Citation Indicator
 
Rank by Journal
Nutrition & Dietetics 88/103 (Q4)
Citation Indicator
Food Science & Technology 142/160 (Q4)
Citable
59
Items
Total
58
Articles
Total
1
Reviews
Scimago
28
H-index
Scimago
0,237
Journal Rank
Scimago
Food Science Q3
Quartile Score
 
Scopus
248/238=1,0
Scite Score
 
Scopus
Food Science 216/310 (Q3)
Scite Score Rank
 
Scopus
0,349
SNIP
 
Days from
100
submission
 
to acceptance
 
Days from
143
acceptance
 
to publication
 
Acceptance
16%
Rate
2019  
Total Cites
WoS
522
Impact Factor 0,458
Impact Factor
without
Journal Self Cites
0,433
5 Year
Impact Factor
0,503
Immediacy
Index
0,100
Citable
Items
60
Total
Articles
59
Total
Reviews
1
Cited
Half-Life
7,8
Citing
Half-Life
9,8
Eigenfactor
Score
0,00034
Article Influence
Score
0,077
% Articles
in
Citable Items
98,33
Normalized
Eigenfactor
0,04267
Average
IF
Percentile
7,429
Scimago
H-index
27
Scimago
Journal Rank
0,212
Scopus
Scite Score
220/247=0,9
Scopus
Scite Score Rank
Food Science 215/299 (Q3)
Scopus
SNIP
0,275
Acceptance
Rate
15%

 

Acta Alimentaria
Publication Model Hybrid
Submission Fee none
Article Processing Charge 1100 EUR/article
Printed Color Illustrations 40 EUR (or 10 000 HUF) + VAT / piece
Regional discounts on country of the funding agency World Bank Lower-middle-income economies: 50%
World Bank Low-income economies: 100%
Further Discounts Editorial Board / Advisory Board members: 50%
Corresponding authors, affiliated to an EISZ member institution subscribing to the journal package of Akadémiai Kiadó: 100%
Subscription fee 2023 Online subsscription: 776 EUR / 944 USD
Print + online subscription: 896 EUR / 1090 USD
Subscription Information Online subscribers are entitled access to all back issues published by Akadémiai Kiadó for each title for the duration of the subscription, as well as Online First content for the subscribed content.
Purchase per Title Individual articles are sold on the displayed price.

Acta Alimentaria
Language English
Size B5
Year of
Foundation
1972
Volumes
per Year
1
Issues
per Year
4
Founder Magyar Tudományos Akadémia    
Founder's
Address
H-1051 Budapest, Hungary, Széchenyi István tér 9.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 0139-3006 (Print)
ISSN 1588-2535 (Online)

 

Monthly Content Usage

Abstract Views Full Text Views PDF Downloads
Aug 2022 0 15 9
Sep 2022 0 22 24
Oct 2022 0 23 16
Nov 2022 0 17 16
Dec 2022 0 17 13
Jan 2023 0 23 16
Feb 2023 0 0 0