An in vitro biofilm model system to facilitate study of microbial communities of the human oral cavity.

The human oral cavity is host to a diverse microbiota. Much of what is known about the behaviour of oral microbes derives from studies of individual or several cultivated species, situations which do not totally reflect the function of organisms within more complex microbiota or multispecies biofilms. The number of validated models that allow examination of the role that biofilms play during oral cavity colonization is also limited. The CDC biofilm reactor is a standard method that has been deployed to study interactions between members of human microbiotas allowing studies to be completed during an extended period under conditions where nutrient availability, and washout of waste products are controlled. The objective of this work was to develop a robust in vitro biofilm-model system from a pooled saliva inoculum to study the development, reproducibility and stability of the oral microbiota. By employing deep sequencing of the variable regions of the 16S rRNA gene, we found that the CDC biofilm reactor could be used to efficiently cultivate microbiota containing all six major phyla previously identified as the core saliva microbiota. After an acclimatisation period, communities in each reactor stabilised. Replicate reactors were predominately populated by a shared core microbiota; variation between replicate reactors was primarily driven by shifts in abundance of shared operational taxonomic units. We conclude that the CDC biofilm reactor can be used to cultivate communities that replicate key features of the human oral cavity and is a useful tool to facilitate studies of the dynamics of these communities.

Integrated kinetic and probabilistic modeling of the growth potential of bacterial populations.

When bacteria are exposed to osmotic stress, some cells recover and grow, while others die or are unculturable. This leads to a viable count growth curve where the cell number decreases before the onset of the exponential growth phase. From such curves, it is impossible to estimate what proportion of the initial cells generates the growth because it leads to an ill-conditioned numerical problem. Here, we applied a combination of experimental and statistical methods, based on optical density measurements, to infer both the probability of growth and the maximum specific growth rate of the culture. We quantified the growth potential of a bacterial population as a quantity composed from the probability of growth and the "suitability" of the growing subpopulation to the new environment. We found that, for all three laboratory media studied, the probability of growth decreased while the "work to be done" by the growing subpopulation (defined as the negative logarithm of their suitability parameter) increased with NaCl concentration. The results suggest that the effect of medium on the probability of growth could be described by a simple shift parameter, a differential NaCl concentration that can be accounted for by the change in the medium composition. Finally, we highlighted the need for further understanding of the effect of the osmoprotectant glycine betaine on metabolism.

Bacterial economics: adaptation to stress conditions via stage-wise changes in the response mechanism.

Common features of microbial adaptation are analysed with mathematical models and extended to stress conditions when the bacterial population declines before growing again. A parallel is drawn between bacterial and human communities in terms of non-mutation-based adaptation (acclimation) to stress. For a case study, the behaviour of Escherichia coli under osmotic stress, is detailed. It is suggested that stress modelling adaptation should be the focus of further developments in predictive food microbiology.

Effect of heat shock and recovery temperature on variability of single cell lag time of Cronobacter turicensis.

The effect of heat stress and subsequent recovery temperature on the individual cellular lag of Cronobacter turicensis was analysed using optical density measurements. Low numbers of cells were obtained through serial dilution and the time to reach an optical density of 0.035 was determined. Assuming the lag of a single cell follows a shifted Gamma distribution with a fixed shape parameter, the effect of recovery temperature on the individual lag of untreated and sublethally heat treated cells of Cr. turicensis were modelled. It was found that the shift parameter (Tshift) increased asymptotically as the temperature decreased while the logarithm of the scale parameter (θ) decreased linearly with recovery temperature. To test the validity of the model in food, growth of low numbers of untreated and heat treated Cr. turicensis in artificially contaminated infant first milk was measured experimentally and compared with predictions obtained by Monte Carlo simulations. Although the model for untreated cells slightly underestimated the actual growth in first milk at low temperatures, the model for heat treated cells was in agreement with the data derived from the challenge tests and provides a basis for reliable quantitative microbiological risk assessments for Cronobacter spp. in infant milk.

Metabolic shift of Escherichia coli under salt stress in the presence of glycine betaine.

An important area of food safety focuses on bacterial survival and growth in unfavorable environments. In order to understand how bacteria adapt to stresses other than nutrient limitation in batch cultures, we need to develop mechanistic models of intracellular regulation and metabolism under stress. We studied the growth of Escherichia coli in minimal medium with added salt and different osmoprotectants. To characterize the metabolic efficiency with a robust parameter, we identified the optical density (OD) values at the inflection points of measured "OD versus time" growth curves and described them as a function of glucose concentration. We found that the metabolic efficiency parameter did not necessarily follow the trend of decreasing specific growth rate as the salt concentration increased. In the absence of osmoprotectant, or in the presence of proline, the metabolic efficiency decreased with increasing NaCl concentration. However, in the presence of choline or glycine betaine, it increased between 2 and 4.5% NaCl before declining at 5% NaCl and above. Microarray analysis of the transcriptional network and proteomics analysis with glycine betaine in the medium indicated that between 4.5 and 5% NaCl, the metabolism switched from aerobic to fermentative pathways and that the response to osmotic stress is similar to that for oxidative stress. We conclude that, although the growth rate appeared to decrease smoothly with increasing NaCl, the metabolic strategy of cells changed abruptly at a threshold concentration of NaCl.

Lag phase of Salmonella enterica under osmotic stress conditions.

Salmonella enterica serovar Typhimurium was grown at salt concentrations ranging from 0.5 to 7.5% in minimal medium with and without added osmoprotectant and in a rich medium. In minimal medium, the cells showed an initial decline period, and consequently the definition of the lag time of the resultant log count curve was revised. The model of Baranyi and Roberts (Int. J. Food Microbiol. 23:277-294, 1994) was modified to take into account the initial decline period, based on the assumption that the log count curve of the total population was the sum of a dying and a surviving-then-growing subpopulation. The lag time was defined as the lag of the surviving subpopulation. It was modeled by means of a parameter quantifying the biochemical work the surviving cells carry out during this phase, the "work to be done." The logarithms of the maximum specific growth rates as a function of the water activity in the three media differed only by additive constants, which gave a theoretical basis for bias factors characterizing the relationships between different media. Models for the lag and the "work to be done" as a function of the water activity showed similar properties, but in rich medium above 5% salt concentrations, the data showed a maximum for this work. An accurate description of the lag time is important to avoid food wastage, which is an issue of increasing significance in the food industry, while maintaining food safety standards.

Modeling the variability of single-cell lag times for Listeria innocua populations after sublethal and lethal heat treatments.

Optical density measurements were used to estimate the effect of heat treatments on the single-cell lag times of Listeria innocua fitted to a shifted gamma distribution. The single-cell lag time was subdivided into repair time (the shift of the distribution assumed to be uniform for all cells) and adjustment time (varying randomly from cell to cell). After heat treatments in which all of the cells recovered (sublethal), the repair time and the mean and the variance of the single-cell adjustment time increased with the severity of the treatment. When the heat treatments resulted in a loss of viability (lethal), the repair time of the survivors increased with the decimal reduction of the cell numbers independently of the temperature, while the mean and variance of the single-cell adjustment times remained the same irrespective of the heat treatment. Based on these observations and modeling of the effect of time and temperature of the heat treatment, we propose that the severity of a heat treatment can be characterized by the repair time of the cells whether the heat treatment is lethal or not, an extension of the F value concept for sublethal heat treatments. In addition, the repair time could be interpreted as the extent or degree of injury with a multiple-hit lethality model. Another implication of these results is that the distribution of the time for cells to reach unacceptable numbers in food is not affected by the time-temperature combination resulting in a given decimal reduction.

Use of optical density detection times to assess the effect of acetic acid on single-cell kinetics.

The growth of Listeria innocua at different acetic acid concentrations (0 to 2,000 ppm) was monitored by optical density measurements in a Bioscreen (Labsystems, Vantaa, Finland). The generated populations came from low inocula that were obtained by serial dilution. A new method to estimate both the growth rate and the lag time of single cells from the detection times (time to reach an optical density of 0.11) was developed. It assumes that the single-cell lag times follow a gamma distribution and takes into account the randomness of the inoculation level. (The initial cell number per well was assumed to follow a Poisson distribution.) In this way, relatively small numbers of replicates are sufficient to obtain a robust estimation of the distribution of single-cell lag times. The results were validated with plate count experiments. It was found that logarithms of both the growth rates and of population lag times increased linearly with the acetic acid concentration. The logarithm of the scale parameter of the gamma distribution of the single-cell lag times also increased linearly with the acetic acid concentration irrespective of the phase of the inoculum.

Modelling the variability of lag times and the first generation times of single cells of E. coli.

A mathematical model combining deterministic and stochastic elements describes the growth and division of single cells. Its deterministic part is based on the model of Baranyi and Roberts [International Journal of Food Microbiology 23 (1994) 277] modelling the gradual adjustment of the cells to a new environment. The stochastic part assumes a random threshold size for the division of a single cell, which accounts for the variability of the individual generation times. Experimental results of the first division times of thousands of single cells using a microscopic flow system could be reproduced with this model, and it has the potential to be used to study the effects of different stress and environmental factors on the distribution of the lag and generation times of individual cells.