An Immunology Course-Based Research Experience for Undergraduate Students that Introduces Computational and Modeling Skills

Abstract

Abstract Previously, we developed a computational modeling lab for undergraduate immunology students that introduced them to the SIR model and the Vensim modeling program. In short, students modeled an epidemic of strep throat and were required to model the Susceptible (S), Infected (I) and Recovered (R) in order to find the best approach to decreasing the length of the epidemic and the number of people infected. While this lab experience was valuable in teaching some basic immunology and modeling skills, the short time frame for the lab provided limited exposure to the importance and potential of modeling skills in immunology. Here we developed a semester-long course-based research experience (CRE) where students develop their own hypothesis, design the experiments, conduct the studies, and analyze their findings. Moreover, in addition to the wet lab component that exposes students to immunology techniques such as flow cytometry, qRT-PCR, cell separation and tissue culture, the students model a signaling pathway providing them with experience in computational modeling. We developed a software package that generates a computational model in Netlogo from the specifications provided by the students. The computational approach allows students to model any type of cell signaling cascade providing a large number of possible hypotheses that can be tested. We piloted this approach with four first-year students with no immunology or modeling/programming experience and the students successfully generated and tested their own hypotheses, and using Netlogo they modeled several different G Protein Coupled Receptor signaling cascades in CD4 and CD8+ T cells. We are in the process of running this CRE with students enrolled in a 200 level immunology class.