A mathematical model of Bacteroides thetaiotaomicron, Methanobrevibacter smithii, and Eubacterium rectale interactions in the human gut

The human gut microbiota is a complex ecosystem that affects a range of human physiology. In order to explore the dynamics of the human gut microbiota, we used a system of ordinary differential equations to model mathematically the biomass of three microorganism populations: Bacteroides thetaiotaomi...

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Bibliographic Details
Published in:Scientific reports 2023-12, Vol.13 (1), p.21192-21192, Article 21192
Main Authors: Adrian, Melissa A., Ayati, Bruce P., Mangalam, Ashutosh K.
Format: Article
Language:English
Subjects:
631/114/2397
692/4020/2199
Bacteroides
Bacteroides thetaiotaomicron
Biomass
Differential equations
Digestive system
Ecosystem
Eubacterium
Gastrointestinal tract
Humanities and Social Sciences
Humans
Intestinal microflora
Mathematical models
Methanobrevibacter
Methanobrevibacter smithii
Microbiota
Microorganisms
Models, Theoretical
multidisciplinary
Nutrient concentrations
Nutrient flow
Nutrients
Ordinary differential equations
Science
Science (multidisciplinary)
Sensitivity analysis
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Summary:The human gut microbiota is a complex ecosystem that affects a range of human physiology. In order to explore the dynamics of the human gut microbiota, we used a system of ordinary differential equations to model mathematically the biomass of three microorganism populations: Bacteroides thetaiotaomicron , Eubacterium rectale , and Methanobrevibacter smithii . Additionally, we modeled the concentrations of relevant nutrients necessary to sustain these populations over time. Our model highlights the interactions and the competition among these three species. These three microorganisms were specifically chosen due to the system’s end product, butyrate, which is a short chain fatty acid that aids in developing and maintaining the intestinal barrier in the human gut. The basis of our mathematical model assumes the gut is structured such that bacteria and nutrients exit the gut at a rate proportional to its volume, the rate of volumetric flow, and the biomass or concentration of the particular population or nutrient. We performed global sensitivity analyses using Sobol’ sensitivities to estimate the relative importance of model parameters on simulation results.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-023-48524-4