SUMMARY: This article uses a computer program to model how different factors contribute to the rate of antibiotic resistance in bacteria. The results aren’t predicting anything, they’re just showing the number of possibilities this program can take into account to help give a better picture of how bacteria gain antibiotic resistance. Factors include: the different phenotypes of E Coli found in hospitals, different bacterial species and how antibiotic use affects them, population of the bacteria and what percentages are resistant/sensitive to antibiotics, different genetic traits, different environmental conditions such as how many patients come in and out of the hospital, how much bacteria is transmitted each time, and how strongly antibiotics affect a certain bacteria population.
LESSON COMMENTS: This article is a good way to connect a computer programming class with biology. Depending on the level of proficiency of the programming teacher, one can go as in-depth or as superficial as one wants. This article goes over a lot of the parameters that can be put into the computer program and it could be a good way to show students the complex levels of trying to model biological phenomenons.
Campos, M., Capilla, R., Naya, F., Futami, R., Coque, T., Moya, A., Fernandez-Lanza, V., Cantón, R., Sempere, J. M., Llorens, C., … Baquero, F. (2019). Simulating Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model. mBio, 10(1), e02460-18. doi:10.1128/mBio.02460-18