Intracellular pH Response to Weak Acid Stress in Individual Vegetative Bacillus subtilis Cells.

Unlabelled: Intracellular pH (pH) critically affects bacterial cell physiology. Hence, a variety of food preservation strategies are aimed at perturbing pH homeostasis. Unfortunately, accurate pH quantification with existing methods is suboptimal, since measurements are averages across populations of cells, not taking into account interindividual heterogeneity.

Quantifying the effect of sorbic acid, heat and combination of both on germination and outgrowth of Bacillus subtilis spores at single cell resolution.

Bacillus subtilis spores are a problem for the food industry as they are able to survive preservation processes. The spores often reside in food products, where their inherent protection against various stress treatments causes food spoilage. Sorbic acid is widely used as a weak acid preservative in the food industry.

Simulation of the rate of transfer of antibiotic resistance between Escherichia coli strains cultured under well controlled environmental conditions.

It was demonstrated that the tetracycline resistance plasmid in Escherichia coli resembling K-12 23:06 containing the E. coli plasmid DM0133 could be transferred to tetracycline sensitive E. coli K-12 MG1655 YFP.

Quantitative analysis of the effect of specific tea compounds on germination and outgrowth of Bacillus subtilis spores at single cell resolution.

Tea is one of the most widely consumed beverages in the world and known for its antimicrobial activity against many microorganisms. Preliminary studies have shown that tea polyphenols can inhibit the growth of a wide range of Gram-positive bacteria. However, the effect of these compounds on germination and outgrowth of bacterial spores is unclear.

Live cell imaging of germination and outgrowth of individual bacillus subtilis spores; the effect of heat stress quantitatively analyzed with SporeTracker.

Spore-forming bacteria are a special problem for the food industry as some of them are able to survive preservation processes. Bacillus spp. spores can remain in a dormant, stress resistant state for a long period of time.

Models of the behaviour of (thermally stressed) microbial spores in foods: tools to study mechanisms of damage and repair.

The 'Omics' revolution has brought a wealth of new mechanistic insights in many fields of biology. It offers options to base predictions of microbial behaviour on mechanistic insight. As the cellular mechanisms involved often turn out to be highly intertwined it is crucial that model development aims at identifying the level of complexity that is relevant to work at.

On the origin of heterogeneity in (preservation) resistance of Bacillus spores: input for a 'systems' analysis approach of bacterial spore outgrowth.

Bacterial spores are the ultimate (stress) 'survival capsules'. They allow strains from the Bacillus and Clostridium species to survive harsh environmental conditions. In addition to the decision to enter sporulation the decision to do the reverse (germinate) is also a decisive event after which there is no return.

Physiological and mathematical aspects in setting criteria for decontamination of foods by physical means.

In heat processing, microbial inactivation is traditionally described as log-linear. As a general rule, the relation between rate of inactivation and temperature is also described as a log-linear relation. The model is also sometimes applied in pressure and in pulsed electric field (PEF) processing.

Modelling the effect of sublethal injury on the distribution of the lag times of individual cells of Lactobacillus plantarum.

The effect of heat stress on subsequent duration of the lag time of individual cells of Lactobacillus plantarum was analysed by flow cytometry. The results show clearly that both the mean and the standard deviation of the distribution of the lag time increased after sublethal heat treatment. The distributions of the lag times or the log lag times of untreated and treated cells, respectively, could be described as extreme value distributions.