Simulating the Influence of Diet on the Intestinal Microbiome Composition — ASN Events

Simulating the Influence of Diet on the Intestinal Microbiome Composition (#16)

Mark Read 1 , Andrew J Holmes 1 , Madison Hartill-Law 1 , Samantha Solon-Biet 1 , David Raubenheimer 1 , Stephen J Simpson 1
  1. University of Sydney, Darlington, NSW, Australia

Diet is a driving factor in the emergence of western lifestyle disease, and of the gut microbiota composition, which has been linked to a host of diseases. `Diet' comprises many dimensions: the proportion of protein, carbohydrate and fat in food; the food’s caloric concentration; the incorporation of fasting periods; and macronutrient source, such as carbohydrates in the form of sugar, complex carbohydrates or fibre. The rational design of diet interventions requires the integration of all these dimensions, which is experimentally intractable. We are developing a simulation that integrates these diet dimensions to investigate how diet drives microbiota community composition.

We simulate a community of bacteria cells and their location in the gut. We assume bacteria require access to carbon (C) and nitrogen (N) in a ratio of 5.2:1, one of which is always limiting on growth; all other nutrients are freely available. Bacteria internalise C and N from their substrates in the local environment. Internalised stores of C and N decay, representing the `cost of living', and their absolute quantity determines a cell's probability of division or death. The microbiota community composition is defined in terms of six `functional guilds', based on bacteria substrates, which may be diet-derived macronutrients or mucin glycoprotein host-secretions. Fully- and partially digestion resistant carbohydrates are represented, as is casein; these are components of real diet formulations input to the simulation. The mucin secretion rate has been estimated. Guild members compete for substrates, but do not otherwise interact.

A real-world data set of 30 diets, comprising 10 macronutrient distributions and 3 energy densities, administered to 250 cages of mice is used to parameterize the simulation. The averaged food consumption of each cage is known. Analysis across these 250 simulations reveals how different diets promote or disadvantage particular guilds. We examine how the relative provision of host-secreted and diet-derived bacteria substrates, periodic fasting and the administration prebiotic fibres, both individually and in concert, shape the microbiota.

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