Reconstruction of Dopaminergic Neuronal Metabolism: A Platform for Deciphering Metabolic Dysfunction in Parkinson's Disease

Sporadic Parkinson's disease (PD) is one of the most common neurodegenerative disorders. One of the hallmarks of PD is degeneration of dopaminergic neurons (DNs) in the pars compacta of the substantia nigra, with dysfunction of many biochemical pathways in different subsystems suggested to be involved. To identify aberrant molecular pathways in PD-affected DNs, a rapid explosion of "omics" analyses has been deployed. However, the aetiopathogenesis of degeneration is still not understood. Metabolic reconstruction and constraint-based modelling are effective means to gain insight into the biological complexity of diseases. To construct a comprehensive representation of the biochemical pathways implicated in DN degeneration, we developed a computational framework to tailor a global reconstruction of human metabolism, Recon 2, into a genome-scale cell-type-specific model of DN metabolism using relevant omics data. Specifically, a novel statistical workflow is presented that retrieves relevant multi-scale, versatile omics datasets from online databases, leverages omics data according to their biological strength, assembles and transforms them into structured and manageable lower dimensional forms through meta-omics analysis. An improved version of FASTCORE algorithm was then implemented to generate a context-specific DN model. Sensitivity analysis was employed to determine the relative importance of various metabolic pathways with respect to maintenance of the normal metabolic objectives of a DN, as defined during the reconstruction process.