Modeling Antibiotic Effects on the Microbiome

Interns

Jason Corbin - Physics (CCS)

Jessica Martinez - Physics

Justin Nilsen - Computer Science

Shelby Vexler - Biology

Project Description

Within our bodies there is an ecosystem called the microbiome, consisting of microbes that compete with each other and interacting with the body. Recent discoveries have found that the microbiome is associated with a myriad of diseases including obesity, diabetes, inflammatory bowel disease, and autism. Accordingly, there is a growing body of research attempting to better understand the microbiome, so that medical treatments- inspired by research- can be applied to ameliorate the aforementioned conditions. My lab (with Jean Carlson), broadly studies complex systems, in a subfield of physics called "biophysics". My project specifically studies the complex interactions within the microbiome. We pursue different ways to represent the microbiome quantitatively, with methods called mathematical models. With a perfect mathematical model we could run simulations which reflect what is happening in the microbiome, and experiment on computers rather than with clinical patients. However, mathematical models for complicated systems (such as the microbiome) are not perfect! As such, in my research I have investigated the legitimacy of existing mathematical models, and proposed new models where old models fail. Specifically, I have been studying the development of antibiotic resistance. When people have an infection, they are often prescribed antibiotics by a doctor in order to clear the infection. These antibiotics, while often eliminating the infectious agent, have a profound effect on the other microbiota. In some cases, the infection will have mutated to an antibiotic resistant strain, which the administered antibiotic will fail to completely eliminate. This phenomena- the emergence of antibiotic resistant strains of bacteria- is a growing hazard in the medical community: if bacterial strains develop antibiotic resistance to many different antibiotics, we could become unable to effectively treat infection. The intern's project would consist of testing a simple model of how infectious agents acquire antibiotic resistance, evaluating what behavior the model would predict, and investigating the shortcomings of such a model. The investigation of this naive model can inform future explorations into models of antibiotic resistance, and once an accurate model is developed it can be used to recommend different antibiotic administration treatments to the healthcare community.

Project Files

modeling_antibiotic_effects_on_the_microbiome.pdf