H.M.W. den Besten

Quantifying strain variability in modeling growth of Listeria monocytogenes.

Prediction of microbial growth kinetics can differ from the actual behavior of the target microorganisms. In the present study, the impact of strain variability on maximum specific growth rate (μmax) (h(-1)) was quantified using twenty Listeria monocytogenes strains. The μmax was determined as function of four different variables, namely pH, water activity (aw)/NaCl concentration [NaCl], undissociated lactic acid concentration ([HA]), and temperature (T). The strain variability was compared to biological and experimental variabilities to determine their importance. The experiment was done in duplicate at the same time to quantify experimental variability and reproduced at least twice on different experimental days to quantify biological (reproduction) variability. For all variables, experimental variability was clearly lower than biological variability and strain variability; and remarkably, biological variability was similar to strain variability. Strain variability in cardinal growth parameters, namely pHmin, [NaCl]max, [HA]max, and Tmin was further investigated by fitting secondary growth models to the μmax data, including a modified secondary pH model. The fitting results showed that L. monocytogenes had an average pHmin of 4.5 (5-95% prediction interval (PI) 4.4-4.7), [NaCl]max of 2.0mM (PI 1.8-2.1), [HA]max of 5.1mM (PI 4.2-5.9), and Tmin of -2.2°C (PI (-3.3)-(-1.1)). The strain variability in cardinal growth parameters was benchmarked to available literature data, showing that the effect of strain variability explained around 1/3 or less of the variability found in literature. The cardinal growth parameters and their prediction intervals were used as input to illustrate the effect of strain variability on the growth of L. monocytogenes in food products with various characteristics, resulting in 2-4 logCFU/ml(g) difference in growth prediction between the most and least robust strains, depending on the type of food product. This underlined the importance to obtain quantitative knowledge on variability factors to realistically predict the microbial growth kinetics.

Quantifying variability on thermal resistance of Listeria monocytogenes

Knowledge of the impact of strain variability and growth history on thermal resistance is needed to provide a realistic prediction and an adequate design of thermal treatments. In the present study, apart from quantifying strain variability on thermal resistance of Listeria monocytogenes, also biological variability and experimental variability were determined to prioritize their importance. Experimental variability was defined as the repeatability of parallel experimental replicates and biological variability was defined as the reproducibility of biologically independent reproductions. Furthermore, the effect of growth history was quantified. The thermal inactivation curves of 20 L. monocytogenes strains were fitted using the modified Weibull model, resulting in total 360 D-value estimates. The D-value ranged from 9 to 30 min at 55 °C; from 0.6 to 4 min at 60 °C; and from 0.08 to 0.6 min at 65 °C. The estimated z-values of all strains ranged from 4.4 to 5.7 °C. The strain variability was ten times higher than the experimental variability and four times higher than the biological variability. Furthermore, the effect of growth history on thermal resistance variability was not significantly different from that of strain variability and was mainly determined by the growth phase.

Quantification of the impact of single and multiple mild stresses on outgrowth heterogeneity of Bacillus cereus spores.

Outgrowth heterogeneity of bacterial spore populations complicates both prediction and efficient control of spore outgrowth. In this study, the impact of mild preservation stresses on outgrowth of Bacillus cereus ATCC 14579 spores was quantified during the first stages of outgrowth. Heterogeneity in outgrowth of heat-treated (90°C for 10 min) and non-heat-treated germinated single spores to the maximum micro-colony stage of 256 cells was assessed by direct imaging on Anopore strips, placed on BHI plates at pH7 and pH5.5, without and with added NaCl or sorbic acid (HSA). At pH7 non-heated and heat-treated germinated spores required 6h to reach the maximum microcolony stage with limited heterogeneity, and these parameters were only slightly affected with both types of spores when incubated at pH7 with added NaCl. Notably, the most pronounced effects were observed during outgrowth of spores at pH5.5 without and with added NaCl or HSA. Non-heat-treated germinated spores showed again efficient outgrowth with limited heterogeneity reaching the maximum microcolony stage after 6h at pH5.5, which increased to 12h and 16 h with added NaCl and HSA, respectively. In contrast, heat-treated spores displayed a strong delay between initial germination and swelling and further outgrowth at pH5.5, resulting in large heterogeneity and low numbers of fastest growers reaching the maximum microcolony stage after 10, 12 and 24h, without and with added NaCl or HSA, respectively. This work shows that Anopore technology provides quantitative information on the impact of combined preservation stresses on outgrowth of single spores, showing that outgrowth of germinated heat-treated spores is significantly affected at pH5.5 with a large fraction of spores arrested in the early outgrowth stage, and with outgrowing cells showing large heterogeneity with only a small fraction committed to relatively fast outgrowth.

Prediction of Bacillus weihenstephanensis acid resistance: The use of gene expression patterns to select potential biomarkers

Exposure to mild stress conditions can activate stress adaptation mechanisms and provide cross-resistance towards otherwise lethal stresses. In this study, an approach was followed to select molecular biomarkers (quantitative gene expressions) to predict induced acid resistance after exposure to various mild stresses, i.e. exposure to sublethal concentrations of salt, acid and hydrogen peroxide during 5 min to 60 min. Gene expression patterns of unstressed and mildly stressed cells of Bacillus weihenstephanensis were correlated to their acid resistance (3D value) which was estimated after exposure to lethal acid conditions. Among the twenty-nine candidate biomarkers, 12 genes showed expression patterns that were correlated either linearly or non-linearly to acid resistance, while for the 17 other genes the correlation remains to be determined. The selected genes represented two types of biomarkers, (i) four direct biomarker genes (lexA, spxA, narL, bkdR) for which expression patterns upon mild stress treatment were linearly correlated to induced acid resistance; and (ii) nine long-acting biomarker genes (spxA, BcerKBAB4_0325, katA, trxB, codY, lacI, BcerKBAB4_1716, BcerKBAB4_2108, relA) which were transiently up-regulated during mild stress exposure and correlated to increased acid resistance over time. Our results highlight that mild stress induced transcripts can be linearly or non-linearly correlated to induced acid resistance and both approaches can be used to find relevant biomarkers. This quantitative and systematic approach opens avenues to select cellular biomarkers that could be incremented in mathematical models to predict microbial behaviour.

The effect of different matrices on the growth kinetics and heat resistance of Listeria monocytogenes and Lactobacillus plantarum.

Microbial growth and inactivation kinetics in food can be predicted when the effects of food properties and environmental conditions on microbial responses are available. However the effects of these intrinsic and extrinsic variables on microbial kinetics are often obtained using laboratory media, and deviations between predictions and true behaviour might occur if the specific effect of a food product is not known or considered in the prediction. Therefore, knowing the food specific effect on microbial kinetics might not only result in a more realistic growth and inactivation prediction, but also extend the knowledge on factors influencing growth and heat resistance. In this study, growth predictions of Listeria monocytogenes and Lactobacillus plantarum were validated in laboratory media and in milk and ham as model food products. A good agreement between the predicted and observed growth kinetics in laboratory media highlighted the possibility to predict μmax based on cardinal growth parameters obtained from OD-based measurement in laboratory media. Only in two conditions (BHI pH5.5 at 7°C; and BHI pH5.5, undissociated lactic acid concentration of 1mM at 7°C) a possible interaction between growth limiting factors was observed, yet existing interaction models were not better in predicting growth. Growth validation in the two model foods showed that the food specific effects were strain dependent, which might further complicate accurate prediction. For both species the effect of strain variability on thermal inactivation was similar to the food specific effects, and the latter was mainly determined by the effect of ham as heating medium. The combination of both effects explained (almost) all variability found in literature, however, with some bias.

QSAR-based molecular signatures of prenylated (iso)flavonoids underlying antimicrobial potency against and membrane-disruption in Gram positive and Gram negative bacteria

Prenylated flavonoids and isoflavonoids are phytochemicals with remarkable antibacterial activity. In this study, 30 prenylated (iso)flavonoids were tested against Listeria monocytogenes and Escherichia coli (the latter in combination with an efflux pump inhibitor). Minimum inhibitory concentrations of the most active compounds ranged between 6.3–15.0 µg/mL. Quantitative structure-activity relationships (QSAR) analysis was performed and linear regression models were proposed with R2 between 0.77–0.80, average R2m between 0.70–0.75, Q2LOO between 0.66–0.69, and relatively low amount of descriptors. Shape descriptors (related to flexibility and globularity), together with hydrophilic/hydrophobic volume and surface area descriptors, were identified as important molecular characteristics related to activity. A 3D pharmacophore model explaining the effect of the prenyl position on the activity of compounds was developed for each bacterium. These models predicted active compounds with an accuracy of 71–88%. With regard to the mode of action, good antibacterial prenylated (iso)flavonoids with low relative hydrophobic surface area caused remarkable membrane permeabilization, whereas those with higher relative hydrophobic surface area did not. Based on the QSAR and membrane permeabilization studies, the mode of action of antibacterial prenylated (iso)flavonoids was putatively rationalized.