Colonial vs. planktonic type of growth: mathematical modeling of microbial dynamics on surfaces and in liquid, semi-liquid and solid foods

Abstract

Predictive models are mathematical expressions that describe the growth, survival, inactivation, or biochemical processes of foodborne bacteria. During processing of contaminated raw materials and food preparation, bacteria are entrapped into the food residues, potentially transferred to the equipment surfaces (abiotic or inert surfaces) or cross-contaminate other foods (biotic surfaces). Growth of bacterial cells can either occur planktonically in liquid or immobilized as colonies. Colonies are on the surface or confined in the interior (submerged colonies) of structured foods. For low initial levels of bacterial population leading to large colonies, the immobilized growth differs from planktonic growth due to physical constrains and to diffusion limitations within the structured foods. Indeed, cells in colonies experience substrate starvation and/or stresses from the accumulation of toxic metabolites such as lactic acid. Furthermore, the micro-architecture of foods also influences the rate and extent of growth. The micro-architecture is determined by (i) the non-aqueous phase with the distribution and size of oil particles and the pore size of the network when proteins or gelling agent are solidified, and by (ii) the available aqueous phase within which bacteria may swarm or swim. As a consequence, the micro-environment of bacterial cells when they grow in colonies might greatly differs from that when they grow planktonically. The broth-based data used for modeling (lag time and generation time, the growth rate, and population level) are poorly transferable to solid foods. It may lead to an over-estimation or under-estimation of the predicted population compared to the observed population in food. If the growth prediction concerns pathogen bacteria, it is a major importance for the safety of foods to improve the knowledge on immobilized growth. In this review, the different types of models are presented taking into account the stochastic behavior of single cells in the growth of a bacterial population. Finally, the recent advances in the rules controlling different modes of growth, as well as the methodological approaches for monitoring and modeling such growth are detailed.

Food Microstructure and Fat Content Affect Growth Morphology, Growth Kinetics, and Preferred Phase for Cell Growth of Listeria monocytogenes in Fish-Based Model Systems

“…The findings of the present study entail significant implications for the microbial safety of processed fish-based food products, and food safety in general. In literature, assumptions concerning microbial growth morphology tend to be rather simplistic, as three different situations are normally distinguished based on the specific food microstructure, i.e., (i) planktonic growth in liquid products, (ii) submerged colony growth in gelled products, and (iii) surface colony growth on food surfaces (26,68). In the present study, it was demonstrated that this classification does not always adequately describe real microbial behavior, not even in products with a homogeneous microstructure.…”

Predictive Modeling of Microbial Behavior in Food

“…The term "quantitative microbial ecology" has been suggested [42] for the modeling studies of colonizing microflora. However, an alternative to this term, "predictive microbiology," seems to be applied nowadays as it brought solutions to the above-formulated problems by modeling the microflora's evolution, thus allowing the earlier prediction and information about product procedures and quality by similar means [40,43,44].…”

“…Since then, different types of modeling techniques have been developed (Table 2) [62,63]. Multi-factorial models [43,50] predict the growth of microbial populations by analyzing the contribution of essential factors involved in the system. Bi-dimensional and tridimensional models combine the different factors incriminated in the food chain [63].…”

Lactobacillus acidophilus INMIA 9602 Er-2 strain 317/402 probiotic regulates growth of commensal Escherichia coli in gut microbiota of familial Mediterranean fever disease subjects

“…; Fujikawa and Morozumi ; Pla et al . ; Skandamis and Jeanson ). A commonly used model to characterize the growth of bacteria is the logistic function of Verhulst (Peleg and Corradini ).…”

“…Modelling the growth of microbial populations allows for the controllable cultivation of micro-organisms and acts as a tool to effectively monitor and predict the microbial growth in natural and artificial biological communities (Adair et al 1989;Gibson et al 1989). Numerous mathematical models describe microbial growth (Gibson et al 1989;Wijtzes et al 1995;Fujikawa and Morozumi 2005;Pla et al 2015;Skandamis and Jeanson 2015). A commonly used model to characterize the growth of bacteria is the logistic function of Verhulst (Peleg and Corradini 2011).…”