| Author: Antwan Green, 3rd year undergraduate Neuroscience major |
| Author: Joshua Kaste, plant biology graduate student |
| Mentor: Yair Shachar-Hill Plant Biology faculty |
Abstract:
Metabolic flux is defined as the rate at which metabolic reactions proceed. The analysis of these fluxes is done through the lens of Metabolic Flux Analysis (MFA), where reaction kinetics are represented mathematically to describe flux over time for a set of metabolites in a pathway or network. Ultimately, the aim of MFA is the complete understanding of biological flux through metabolic networks under physiologic conditions. Concepts as complex as MFA must be broken down into understandable pieces before they can be understood, which has not (to our knowledge) been implemented in a structured, accessible, and hands-on way previously. To teach students about this process, we take advantage of the coding language Python. This gives students a chance to observe the kinetics used in the study of metabolic flux and actively observe how different kinetics equations can be applied, and their real-life consequences. We have selected Python as a teaching tool because it has been implemented before in many schools and institutions, mostly due to its beginner-friendly language allowing “common-sense” code strings that are easily readable. Using Python, I developed interactive simulations of metabolic activity that allow students to learn various concepts related to metabolism, including the impact of different assumed kinetics and how isotopic labels can move through a metabolic pathway.
You can find the recorded presentation at:
https://mediaspace.msu.edu/media/LBC+Research+Symposium+Presentation+/1_usn86lxg