Two complementary approaches to quantify variability in heat resistance of spores of  Bacillus subtilis

Besten, H.M.W. den; Berendsen, Erwin M.; Wells-Bennik, M.H.J.; Straatsma, Han; Zwietering, Marcel H.

doi:10.1016/j.ijfoodmicro.2017.04.014

Cited by 28 publications

(19 citation statements)

References 17 publications

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“…When log t 4D -values are plotted against temperature, the reciprocal of the slope is equal to z-value (z = -1/slope). The one-step model we used to fit the Weibull model according to den Besten et al (2017) to estimate t 4D along with z-value. The goodness of fit and variation between the experimental data set and used mathematical models were evaluated by estimating the root mean sum of square errors (RMSSE) and coefficient of determination (R 2 ).…”

Section: Methodsmentioning

confidence: 99%

Modelling the inactivation of Staphylococcus aureus at moderate heating temperatures

Lehotová¹,

Miháliková²,

Medveďová³

et al. 2021

Czech J. Food Sci.

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The survival of bacterial contaminants at moderate processing temperatures is of interest to many food producers, especially in terms of the safety and quality of the final products. That is why the heat resistance of Staphylococcus aureus 2064, an isolate from artisanal Slovakian cheese, was studied in the moderate temperature range (57–61 °C) by the capillary method. The fourth decimal reduction time t4D- and z-values were estimated in two steps by traditional log-linear Bigelow and non-linear Weibull models. In addition, a one-step fitting procedure using the Weibull model was also applied. All the approaches provided comparable t4D-values resulting in the following z-values of 11.8 °C, 12.3 °C and 11.3 °C, respectively. Moreover, the one-step approach takes all the primary data into z-value calculation at once, thus providing a more representative output at the reasonable high coefficient of determination R2 = 0.961

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Section: Methodsmentioning

confidence: 99%

Modelling the inactivation of Staphylococcus aureus at moderate heating temperatures

Lehotová¹,

Miháliková²,

Medveďová³

et al. 2021

Czech J. Food Sci.

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“…Variability of heat resistance among different microbial strains to the same treatment has been previously studied (den Besten et al, 2017 ). Traditionally, this comparison is performed by fitting a microbial inactivation model to experimental data and assessing statistical differences between the estimated model parameters.…”

Section: Resultsmentioning

confidence: 99%

Relevance of the Induced Stress Resistance When Identifying the Critical Microorganism for Microbial Risk Assessment

et al. 2018

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Decisions regarding microbial risk assessment usually have to be carried out with incomplete information. This is due to the large number of possible scenarios and the lack of specific data for the problem considered. Consequently, risk assessment studies are based on the information obtained with a small number of bacterial cells which are considered the most heat resistant and/or more capable of multiplying during storage. The identification of the most resistant strains is usually based on D and z-values, normally estimated from isothermal experiments. This procedure omits the potential effect that the shape of the dynamic thermal profile applied in industry has on the microbial inactivation. One example of such effects is stress acclimation, which is related to a physiological response of the cells during sub-lethal treatments that increases their resistance. In this article, we use a recently published mathematical model to compare the development of thermal resistance for Escherichia coli K12 MG1655 and E. coli CECT 515 using inactivation data already published for these strains. Based only on the isothermal experiments, E. coli K12 MG1655 would be identified as more resistant to the thermal treatment than the CECT 515 strain in the 50–65°C temperature range. However, we conclude that stress acclimation is strain (and/or media)-dependent; the CECT 515 strain has a higher capacity for developing a stress acclimation than K12 MG1655 (300% increase of the D-value for CECT 515, 50% for K12 MG1655). It, thus, has the potential to be more resistant to the thermal treatment than the K12 MG1655 strain for some conditions allowing acclimation. A methodology is proposed to identify for which conditions this may be the case. After calibrating the model parameters representing acclimation using real experimental data, the applicability of the proposed approach is demonstrated using numerical simulations, showing how the CECT 515 strain can be more resistant for some heating profiles. Consequently, the most resistant bacterial strain to a dynamic heating profile should not be identified based only on isothermal experiments (D- and z-value). The relevance of stress acclimation for the treatment studied should also be evaluated.

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“…This selective pressure is likely exerted on spore survival. The spoVA 2mob operon is controlled by a sporulation-specific promoter, and the genes in this operon are specifically expressed during sporulation (37); accordingly, the operon impacts heat resistance of spores but not of vegetative cells ( Fig. 3 and 4).…”

Section: Discussionmentioning

confidence: 99%

Daqu Fermentation Selects for Heat-Resistant Enterobacteriaceae and Bacilli

Wang

Pan

et al. 2018

Appl Environ Microbiol

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Daqu is a spontaneous solid-state cereal fermentation used as saccharification and starter culture in Chinese vinegar and liquor production. The evolution of microbiota in this spontaneous fermentation is controlled by the temperature profile, which reaches temperatures from 50 to 65°C for several days. Despite these high temperatures, mesophilic (including) and bacilli are present throughout Daqu fermentation. This study aimed to determine whether Daqu spontaneous solid-state fermentation selects for heat-resistant variants of these organisms. Heat resistance in is mediated by the locus of heat resistance (LHR). One LHR-positive strain of was identified in Daqu, and it exhibited higher heat resistance than the LHR-negative isolated from malted oats. Heat resistance in endospores is mediated by the operon. Out of 10 Daqu isolates of the species, ,, , and, 5 did not contain , 3 contained one copy, and 2 contained two copies. The presence and copy number of the operon increased the resistance of spores to treatment with 110°C. To confirm the selection of LHR- and -positive strains during Daqu fermentation, the copy numbers of these genetic elements in Daqu samples were quantified by quantitative PCR (qPCR). The abundance of LHR and the operon in community DNA relative to that of total bacterial 16S rRNA genes increased 3-fold and 5-fold, respectively, during processing. In conclusion, culture-dependent and culture-independent analyses suggest that Daqu fermentation selects for heat-resistant and bacilli. Daqu fermentations select for mobile genetic elements conferring heat resistance in and bacilli. The locus of heat resistance (LHR), a genomic island conferring heat resistance in, and the operon, conferring heat resistance on bacterial endospores, were enriched 3- to 5-fold during Daqu fermentation and maturation. It is therefore remarkable that the LHR and the operon are accumulated in the same food fermentation. The presence of heat-resistant spp. and spp. in Daqu is not of concern for food safety; however, both genomic islands are mobile and transferable to pathogenic bacteria or toxin-producing bacteria by horizontal gene transfer. The identification of the LHR and the operon as indicators of fitness of and bacilli in Daqu fermentation provides insights into environmental sources of heat-resistant organisms that may contaminate the food supply.

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Two complementary approaches to quantify variability in heat resistance of spores of Bacillus subtilis

Cited by 28 publications

References 17 publications

Modelling the inactivation of Staphylococcus aureus at moderate heating temperatures

Modelling the inactivation of Staphylococcus aureus at moderate heating temperatures

Relevance of the Induced Stress Resistance When Identifying the Critical Microorganism for Microbial Risk Assessment

Daqu Fermentation Selects for Heat-Resistant Enterobacteriaceae and Bacilli

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