Meeting Abstract
46.4 Thursday, Jan. 5 The mathematical biology of metabolic scaling: using a model insect as the basis for interdisciplinary undergraduate science training and research KERKHOFF, A.J.*; GILLEN, C.M.; HARTLAUB, B.A.; HOLDENER, J.A.; ITAGAKI, H.; Kenyon College; Kenyon College; Kenyon College; Kenyon College; Kenyon College kerkhoffa@kenyon.edu
Interdisciplinary training in biology and math is deemed essential for scientific progress, but it represents a challenge for undergraduate educators. Collaborative research involving faculty and students from both disciplines provides an authentic training opportunity while maintaining the rigor of disciplinary curricula. Here we summarize the results of an undergraduate research and training program investigating the mathematical biology of metabolic scaling using the tobacco hornworm, Manduca sexta, as a model system. Focusing on the role of the larval midgut, we have documented the allometric scaling of gut dimensions as well as ontogenetic changes in the expression of transport proteins and digestive enzymes. We have also tested existing theories relating metabolic scaling to growth and developed new models of how microvilli increase midgut surface area and allometric changes in the dynamics of assimilation. These projects have provided technical training to dozens of undergraduates in both mathematics and biology. More importantly, students have been able to participate in authentic, collaborative interdisciplinary research, resulting in the tangible products of science: knowledge shared via publications and presentations. The use of a common suite of questions centered on metabolic scaling has given a unified focus to student research while allowing them to find the topic that interests them most. Our approach requires that faculty mentors be willing to find common ground with their mathematical and biological collaborators, but the excitement and productivity of the project, in terms of both research products and student training outcomes, can more than offset this challenge
