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Updated: Jul 2, 2026

Multi-scale Analysis of Bacterial Growth Under Stress Treatments
Published on: November 28, 2019
A study on the variability in the growth limits of individual cells and its effect on the behavior of microbial
1Laboratory of Food Microbiology and Hygiene, Department of Food Science and Technology, Faculty of Agriculture, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece. kkoutsou@agro.auth.gr
Abstract:
The NaCl growth limits of individual Salmonella enteritidis cells were studied. Six different levels of the pathogen (from 10(1) to 10(6) cells) were inoculated on tryptic soy agar plates at NaCl concentrations ranging from 0.5 to 8% and pH values of 5.0, 5.5 or 7.3. The NaCl growth limits of individual cells were estimated from the ratio between the number of colonies formed at each NaCl concentration interval and the number of cells initially inoculated, based on the assumption that each colony was derived from a single cell. The results showed that, as the NaCl concentration increased and the pH decreases, the number of cells able to grow and form a colony gradually decreased indicating variability in the growth limits of individual cells. The distribution of single-cell growth limits was used to predict the behavior of microbial populations. The results showed that as the inoculum size increased the NaCl growth limits of S. enteritidis increased and became less variable. Furthermore, at conditions close to the boundary of growth the presence of a non-growing fraction in the population resulted in a delay of population growth, which we called "pseudo-lag". The extent of "pseudo-lag" is determined by the environment while its variability is affected by both the inoculum size and the growth conditions. At growth-limiting conditions the total "apparent lag" of the population is a convolution of the "pseudo-lag" and the "physiological lag" of the growing cells. The data on the variability in the growth limits of single microbial cells presented in this work stress the need for stochastic approaches in quantitative microbiology especially at environments close to the boundary of growth.
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