Introduction The term microbiota refers to a community of microorganisms that are located in a certain space that have a symbiotic relationship with the host cells, in this specific case the human gastrointestinal tract. This interaction provides support to the tract in different functional aspects such as trophic functions, protection (immune system) and metabolism. There has been evidenced that intestinal microbiota plays an important role in synthesis, metabolism, and other functions associated to the nutrients and micronutrients that can lead to healthy or obese patients. In this work we aimed to understand and model the population dynamics of the intestinal microbiota. Methods A mathematical model was design based on the gastrointestinal tract seen as a single tubular structure composed of Esophagus, Stomach, Small intestine (Duodenum, Jejunum and ileum) and colon. Only one major phylum of microorganisms (Either Firmicutes or Bacteroidetes) was included according to anatomical and physiological characteristics and in terms of its relative abundance in each part of the tract. The model included the subject's diet and activity level as inputs. Parameters for the model were obtained from a literature review. The model was implemented in Matlab and produced microorganism distribution (i.e. spatial concentration). We model different diets and pathological conditions. Results The model reveals an expected growth of either Firmicutes or Bacteriodetes associated with the amount of nutrient and carrying capacity of the gastrointestinal tract. These results are in agreement with several reports obtained from the literature. In addition, the model showed an interesting stabilization of bacterial population under some circumstances depending on the segment of the gastro intestinal tract. Bacterial population is sensitive to diet and exercise. Conclusions The model can be used to predict the population dynamics under different diets and furthermore could be implemented as an important tool for bariatric surgery patients. The model can also shed some light on how to prevent the progression from overweight to obese just by changing the diet understanding the dynamics of gastrointestinal tract population. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .