Integrating simulated and experimental data to identify mitochondrial bioenergetic defects in Parkinson's Disease models

Abstract

Mitochondrial bioenergetics are vital for ATP production and are associated with several diseases, including Parkinsons Disease. Here, we simulated a computational model of mitochondrial ATP production to interrogate mitochondrial bioenergetics under physiological and pathophysiological conditions, and provide a data resource that can be used to interpret mitochondrial bioenergetics experiments. We first characterised the impact of several common respiratory chain impairments on experimentally-observable bioenergetic parameters. We then established an analysis pipeline to integrate simulations with experimental data and predict the molecular defects underlying experimental bioenergetic phenotypes. We applied the pipeline to data from Parkinsons Disease models. We verified that the impaired bioenergetic profile previously measured in Parkin knockout neurons can be explained by increased mitochondrial uncoupling. We then generated primary cortical neurons from a Pink1 KO mouse model of Parkinsons, and measured reduced OCR capacity and increased resistance to Complex III inhibition. Here, our pipeline predicted that multiple respiratory chain impairments are required to explain this bioenergetic phenotype. Finally, we provide all simulated data as a user-friendly resource that can be used to interpret mitochondrial bioenergetics experiments, predict underlying molecular defects, and inform experimental design. HighlightsO_LIThe complexity of mitochondrial bioenergetics can make experimental data difficult to interpret. C_LIO_LIWe simulated a computational model of mitochondrial bioenergetics in healthy and pathological conditions, and established an analysis pipeline to integrate model simulations with experimental data. C_LIO_LIWe applied the pipeline to data from Parkinsons Disease models to predict the molecular defects underlying Parkinsons-related pathology. C_LIO_LIWe provide all outputs in a user-friendly Excel file, which serves as a valuable resource to the community for insight into the effects of pathology on mitochondrial bioenergetics and for interpretation of experimental results. C_LI