Model intestinal microflora in computer simulation: a simulation and modeling package for host-microflora interactions

The translational roadmap of the gut models, focusing on gut-on-chip

It is difficult to model in vitro the intestine when seeking to include crosstalk with the gut microbiota, immune and neuroendocrine systems. Here we present a roadmap of the current models to facilitate the choice in preclinical and translational research with a focus on gut-on-chip. These micro physiological systems (MPS) are microfluidic devices that recapitulate in vitro the physiology of the intestine. We reviewed the gut-on-chips that had been developed in academia and industries as single chip and that have three main purpose: replicate the intestinal physiology, the intestinal pathological features, and for pharmacological tests.

The translational roadmap of the gut models, focusing on gut-on-chip

It is difficult to model in vitro the intestine when seeking to include crosstalk with the gut microbiota, immune and neuroendocrine systems. Here we present a roadmap of the current models to facilitate the choice in preclinical and translational research with a focus on gut-on-chip. These micro physiological systems (MPS) are microfluidic devices that recapitulate in vitro the physiology of the intestine. We reviewed the gut-on-chips that had been developed in academia and industries as single chip and that have three main purpose: replicate the intestinal physiology, the intestinal pathological features, and for pharmacological tests.

Flux analysis of the human proximal colon using anaerobic digestion model 1

The colon can be regarded as an anaerobic digestive compartment within the gastro intestinal tract (GIT). An in silico model simulating the fluxes in the human proximal colon was developed on basis of the anaerobic digestion model 1 (ADM1), which is traditionally used to model waste conversion to biogas. Model calibration was conducted using data from in vitro fermentation of the proximal colon (TIM-2), and, amongst others, supplemented with the bio kinetics of prebiotic galactooligosaccharides (GOS) fermentation. The impact of water and solutes absorption by the host was also included. Hydrolysis constants of carbohydrates and proteins were estimated based on total short chain fatty acids (SCFA) and ammonia production in vitro. Model validation was established using an independent dataset of a different in vitro model: an in vitro three-stage continuous culture system. The in silico model was shown to provide quantitative insight in the microbial community structure in terms of functional groups, and the substrate and product fluxes between these groups as well as the host, as a function of the substrate composition, pH and the solids residence time (SRT). The model confirms the experimental observation that methanogens are washed out at low pH or low SRT-values. The in silico model is proposed as useful tool in the design of experimental setups for in vitro experiments by giving insight in fermentation processes in the proximal human colon.

Anisotropic nutrient transport in three-dimensional single species bacterial biofilms

The ability for a biofilm to grow and function is critically dependent on the nutrient availability, and this in turn is dependent on the structure of the biofilm. This relationship is therefore an important factor influencing biofilm maturation. Nutrient transport in bacterial biofilms is complex; however, mathematical models that describe the transport of particles within biofilms have made three simplifying assumptions: the effective diffusion coefficient (EDC) is constant, the EDC is that of water, and/or the EDC is isotropic. Using a Monte Carlo simulation, we determined the EDC, both parallel to and perpendicular to the substratum, within 131 real, single species, three-dimensional biofilms that were constructed from confocal laser scanning microscopy images. Our study showed that diffusion within bacterial biofilms was anisotropic and depth dependent. The heterogeneous distribution of bacteria varied between and within species, reducing the rate of diffusion of particles via steric hindrance. In biofilms with low porosity, the EDCs for nutrient transport perpendicular to the substratum were significantly lower than the EDCs for nutrient transport parallel to the substratum. Here, we propose a reaction-diffusion model to describe the nutrient concentration within a bacterial biofilm that accounts for the depth dependence of the EDC.

The evolution of bacteriocin production in bacterial biofilms

Bacteriocin production is a spiteful behavior of bacteria that is central to the competitive dynamics of many human pathogens. Social evolution predicts that bacteriocin production is favored when bacteriocin-producing cells are mixed at intermediate frequency with their competitors and when competitive neighborhoods are localized. Both predictions are supported by biofilm experiments. However, the means by which physical and biological processes interact to produce conditions that favor the evolution of bacteriocin production remain to be investigated. Here we fill this gap using analytical and computational approaches. We identify and collapse key parameters into a single number, the critical bacteriocin range, that measures the threshold distance from a focal bacteriocin-producing cell within which its fitness is higher than that of a sensitive cell. We develop an agent-based model to test our predictions and confirm that bacteriocin production is most favored when relatedness is intermediate and competition is local. We then use invasion analysis to determine evolutionarily stable strategies for bacteriocin production. Finally, we perform long-term evolutionary simulations to analyze how the critical bacteriocin range and genetic lineage segregation affect biodiversity in multistrain biofilms. We find that biodiversity is maintained in highly segregated biofilms for a wide array of critical bacteriocin ranges. However, under conditions of high nutrient penetration leading to well-mixed biofilms, biodiversity rapidly decreases and becomes sensitive to the critical bacteriocin range.

Mathematical modelling of carbohydrate degradation by human colonic microbiota

The human colon is an anaerobic ecosystem that remains largely unexplored as a result of its limited accessibility and its complexity. Mathematical models can play a central role for a better insight into its dynamics. In this context, this paper presents the development of a mathematical model of carbohydrate degradation. Our aim was to provide an in silico approach to contribute to a better understanding of the fermentation patterns in such an ecosystem. Our mathematical model is knowledge-based, derived by writing down mass-balance equations. It incorporates physiology of the intestine, metabolic reactions and transport phenomena. The model was used to study various nutritional scenarios and to assess the role of the mucus on the system behavior. Model simulations provided an adequate qualitative representation of the human colon. Our model is complementary to experimental studies on human colonic fermentation, which, of course, is not meant to replace. It may be helpful to gain insight on questions that are still difficult to elucidate by experimentation and suggest future experiments.

In silico model as a tool for interpretation of intestinal infection studies

In nutrition research the number of human in vivo experiments is limited because of the many restrictions and the high costs of testing in humans. Up to now predictive computer models aiming to enhance research have been rare or too complex, with many nonmeasurable adjustable parameters. This study aimed to develop a basic physicochemical computer model for a first quantitative interpretation of results obtained from in vivo intestinal experiments with bacteria. This new modeling approach is validated with results obtained from gut infection studies in vivo. The design of the model is described, and its ability to reproduce experimental data is evaluated. The model predictions are compared with new experimental data. The phenomena that take place in the gastrointestinal tract are summarized by model constants for growth, adherence, and release of bacteria. Although the model is far from describing all details and many processes in the intestine are combined, the model calculation results lead to reasonable conclusions and interesting hypotheses. One of these hypotheses concluded from the model outcomes is that Escherichia coli bacteria have a much lower intestinal growth rate in humans than in rats. Extra laboratory validation experiments proved the reliability of this hypothesis predicted by the model. In addition, the known protective effect of dietary calcium and detrimental effect of clindamycin on the growth and adherence of Salmonella bacteria could be quantified. From these results it is clear that the model enhances the interpretation of in vivo gastrointestinal experiments and will facilitate research trajectories towards new functional foods that improve resistance to pathogenic bacteria in humans.

Modification of the biophysical characteristics of membranes in commensal Escherichia coli strains from breast cancer patients

Escherichia coli G35 N49 strain, from the gut of breast cancer patients, in comparison with the E. coli G35 N61 strain, from the gut of healthy people, shows in vitro reduction in growth rates and maximal growth yield. The changes in certain membrane characteristics, such as low membrane potential and disturbance in intramembrane interaction of H+ -ATPase F0F1 with the TrkA system, indicate a dysfunction in ion transport and enzymatic activity. These changes can be detected during fermentation and in anaerobic conditions (in the gut, for example) and may be influenced by unfavorable conditions in the gut of cancer patients.