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

A stochastic model for the bacterial growth exhibiting staged growth, desynchronization, saturation and persistence

We consider a model of population growth based on the stochastic variation of the population size-controlled duplication of bacterial cells. It is shown that the proper choice of the control function allows for reproducing a variety of regimes: a logistic growth with saturation, a hindered growth typical for persistent bacterial systems, and a linear population growth detected for some mycobacterial populations. When supplied with the rectangular function having the width equal to the generation time, this approach represents the solution generalizing Rubinow's age-maturity model reproducing systems with desynchronization and saturation. The model's plausibility is confirmed by the direct comparison with real data for the growth of M. tuberculosis populations obtained with the BACTEC MGIT system under different conditions of growth synchronization.

Influence of Plant Species, Tissue Type, and Temperature on the Capacity of Shiga-Toxigenic Escherichia coli To Colonize, Grow, and Be Internalized by Plants

Contamination of fresh produce with pathogenic Escherichia coli, including Shiga-toxigenic E. coli (STEC), represents a serious risk to human health. Colonization is governed by multiple bacterial and plant factors that can impact the probability and suitability of bacterial growth. Thus, we aimed to determine whether the growth potential of STEC for plants associated with foodborne outbreaks (two leafy vegetables and two sprouted seed species) is predictive of the colonization of living plants, as assessed from growth kinetics and biofilm formation in plant extracts. The fitness of STEC isolates was compared to that of environmental E. coli isolates at temperatures relevant to plant growth. Growth kinetics in plant extracts varied in a plant-dependent and isolate-dependent manner for all isolates, with spinach leaf lysates supporting the highest rates of growth. Spinach extracts also supported the highest levels of biofilm formation. Saccharides were identified to be the major driver of bacterial growth, although no single metabolite could be correlated with growth kinetics. The highest level of in planta colonization occurred on alfalfa sprouts, though internalization was 10 times more prevalent in the leafy vegetables than in sprouted seeds. Marked differences in in planta growth meant that the growth potential of STEC could be inferred only for sprouted seeds. In contrast, biofilm formation in extracts related to spinach colonization. Overall, the capacity of E. coli to colonize, grow, and be internalized within plants or plant-derived matrices was influenced by the isolate type, plant species, plant tissue type, and temperature, complicating any straightforward relationship between in vitro and in planta behaviors.IMPORTANCE Fresh produce is an important vehicle for STEC transmission, and experimental evidence shows that STEC can colonize plants as secondary hosts, but differences in the capacity to colonize occur between different plant species and tissues. Therefore, an understanding of the impact that these plant factors have on the ability of STEC to grow and establish is required for food safety considerations and risk assessment. Here, we determined whether growth and the ability of STEC to form biofilms in plant extracts could be related to specific plant metabolites or could predict the ability of the bacteria to colonize living plants. Growth rates for sprouted seeds (alfalfa and fenugreek) but not those for leafy vegetables (lettuce and spinach) exhibited a positive relationship between plant extracts and living plants. Therefore, the detailed variations at the level of the bacterial isolate, plant species, and tissue type all need to be considered in risk assessment.

Piecewise linear approximations to model the dynamics of adaptation to osmotic stress by food-borne pathogens

Addition of salt to food is one of the most ancient and most common methods of food preservation. However, little is known of how bacterial cells adapt to such conditions. We propose to use piecewise linear approximations to model the regulatory adaptation of Escherichiacoli to osmotic stress. We apply the method to eight selected genes representing the functions known to be at play during osmotic adaptation. The network is centred on the general stress response factor, sigma S, and also includes a module representing the catabolic repressor CRP-cAMP. Glutamate, potassium and supercoiling are combined to represent the intracellular regulatory signal during osmotic stress induced by salt. The output is a module where growth is represented by the concentration of stable RNAs and the transcription of the osmotic gene osmY. The time course of gene expression of transport of osmoprotectant represented by the symporter proP and of the osmY is successfully reproduced by the network. The behaviour of the rpoS mutant predicted by the model is in agreement with experimental data. We discuss the application of the model to food-borne pathogens such as Salmonella; although the genes considered have orthologs, it seems that supercoiling is not regulated in the same way. The model is limited to a few selected genes, but the regulatory interactions are numerous and span different time scales. In addition, they seem to be condition specific: the links that are important during the transition from exponential to stationary phase are not all needed during osmotic stress. This model is one of the first steps towards modelling adaptation to stress in food safety and has scope to be extended to other genes and pathways, other stresses relevant to the food industry, and food-borne pathogens. The method offers a good compromise between systems of ordinary differential equations, which would be unmanageable because of the size of the system and for which insufficient data are available, and the more abstract Boolean methods.