Composition of the human gut microbiota is a direct consequence of bacterial growth behavior and its strain to strain variation. Sure, faster growing bacterial species are more abundant than slower growing ones, but the exact growth rates depend in a complex way on the physiological conditions bacteria encounter locally throughout the intestine. Thus, to mechanistically understand the composition of our gut microbiota, we have to understand all the major factors influencing bacterial growth, how these factors are varying in space and time, and how their impact on growth behavior is varying from one bacterial species to the next.
These are very challenging tasks indeed. However we can already learn a lot about bacterial growth within the large intestine by quantitatively considering only a few major factors and their interactions. In our model we explicitly considered the interactions of nutrient inflow (the complex carbohydrates feeding the bacteria), local pH values, and intestinal flow (transit time).
Aspects of bacterial growth considered in our spatio-temporal model.
To setup this model, we invested some time and effort to quantify different physiological processes and to find a reasonable level of mathematical description (simple but realistic enough to derive novel understanding). For students eager to dive into the details, a full description is provided in the Supplementary Information of our PNAS2017 paper (click on image).
Our findings suggest that pH and flow conditions are major factors affecting microbiota composition, capable of explaining the huge person to person variation in microbiota composition observed on the phyla level.
We are currently extending these modeling considerations to better link bacterial growth dynamics to diet, eating manners, and host-physiological changes.
Jonas Cremer*, Igor Segota*, Chih-yu Yang, Markus Arnoldini, John T Sauls, Zhongge Zhang, Edgar Gutierrez, Alex Groisman, Terence Hwa: Effect of flow and peristaltic mixing on bacterial growth in a gut-like channel. In: Proceedings of the National Academy of Science of the United States of America, 113 (41), pp. 11414–11419, 2016, ISSN: 0027-8424.