Final Project: Niamh Connolly – Parameter optimisation for a model of AMPK-mediated survival signaling

Glutamate excitotoxicity is a pathological process implicated in stroke, traumatic brain injury and numerous neurodegenerative diseases. In culture, neurons exposed to the same excitotoxic stimulus can either survive the insult or undergo rapid necrotic or delayed apoptotic cell death. In our lab we are investigating the regulation of this switch-like behaviour. Using fluorescence data obtained in single neurons, we observed that ATP and AMPK rapidly recovered to homeostasis following transient excitotoxic perturbation. In contrast, the recovery of glucose was significantly slower. Interestingly, the extent of this delay correlated with the duration of subsequent survival.

To investigate this behavior from a computational perspective, I previously developed a MATLAB ODE-based model based on prior knowledge of signalling pathways. The model correctly resembled ATP and AMPK kinetics, but failed to resemble the delayed glucose recovery.

In this project, I implemented my model in both Virtual Cell and COPASI, and used the inbuilt parameter estimation functions to fit the glucose response. I confirmed that the model in its current state cannot completely explain the observed glucose kinetics. I next incorporated additional model reactions in an attempt to explain the discrepancy in glucose behaviour. However, extensive parameter estimation for this updated model failed to simultaneously fit the glucose response curve for both the steady-state and perturbation situations. Further analysis is necessary to identify specific reactions that can delay the glucose recovery without simultaneously affecting ATP.

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