Abstract

Probiotics are living microorganisms which have beneficial effects and which can promote good health. While bacterial population dynamics is one of the classical and oldest areas of mathematical biology, it appears that the cholesterol assimilation phenomena by probiotics and its implications for health effects were so far ignored in modeling studies. In this paper, a dynamic model based on a qualitative-phenomenological description of cholesterol assimilation by probiotics is presented. The model consists of three autonomous differential equations and is able to describe the reduction of cholesterol by 11 different strains of lactobacilli. The model was solved numerically and was validated against an existing set of experimental observations. An optimization scheme that can perform parameter estimation using a multi-start approach was prepared and used to find the set of parameters that gives a best fit between the experimental observations and the model predictions. An important feature of this implementation is that the dynamic microbial model was introduced as a constraint in the optimization problem and this allows for the use of efficient differential equations solvers. The model proved to offer robust predictions for cholesterol assimilation by strains of lactobacilli and was also able to capture a number of experimental observations including that microbial growth is enhanced by the presence of cholesterol. This work is a first effort in modeling such phenomena and the ability of the model to represent different strains will allow for future work on optimizing an ecological mix of strains that will be able to reduce cholesterol levels in an efficient manner.