Parkinson’s disease: dopaminergic nerve cell model is consistent with experimental finding of increased extracellular transport of α-synuclein

Finja Büchel,Sandra Saliger,Stephanie Hoffmann,Philipp J Kahle,Andreas Dräger,Clemens Wrzodek,Andreas Zell

doi:10.1186/1471-2202-14-136

Abstract

BackgroundParkinson’s disease is an age-related disease whose pathogenesis is not completely known. Animal models exist for investigating the disease but not all results can be easily transferred to humans. Therefore, mathematical or probabilistic models for the human disease are to be constructed in silico in order to predict specific processes within a cell, such as the dopamine metabolism and transport processes in a neuron.ResultsWe present a Systems Biology Markup Language (SBML) model of a whole dopaminergic nerve cell consisting of 139 reactions and 111 metabolites which includes, among others, the dopamine metabolism and transport, oxidative stress, aggregation of α-synuclein (αSYN), lysosomal and proteasomal degradation, and mitophagy. The predictive power of the model was investigated using flux balance analysis for the identification of steady model states. To this end, we performed six experiments: (i) investigation of the normal cell behavior, (ii) increase of O2, (iii) increase of ATP, (iv) influence of neurotoxins, (v) increase of αSYN in the cell, and (vi) increase of dopamine synthesis. The SBML model is available in the BioModels database with identifier MODEL1302200000.ConclusionIt is possible to simulate the normal behavior of an in vivo nerve cell with the developed model. We show that the model is sensitive for neurotoxins and oxidative stress. Further, an increased level of αSYN induces apoptosis and an increased flux of αSYN to the extracellular space was observed.

Highlights

Parkinson’s disease is an age-related disease whose pathogenesis is not completely known
The basis of the model comprises the publication by Best et al [11], which mathematically describes the synthesis, metabolism, and the transport of DA in single dopaminergic neuron terminals
We assume that the optimization of the minimizing the output-reaction of the apoptosis (minApo) and maximizing the output-reaction of the degradation (maxDeg) target analyses best reflects the normal neuronal cell behavior because cell death is a late event in neurodegenerative diseases, and before initiating apoptosis the cell degrades damaged cell products [47]. We examined this assumption by minimizing apoptotic processes in the flux balance analysis (FBA) and observed increased degradation and increased reactive oxygen species (ROS) elimination processes but no apoptosis

Summary

Introduction

Parkinson’s disease is an age-related disease whose pathogenesis is not completely known. Animal models exist for investigating the disease but not all results can be transferred to humans. Mathematical or probabilistic models for the human disease are to be constructed in silico in order to predict specific processes within a cell, such as the dopamine metabolism and transport processes in a neuron. Parkinson’s disease (PD) is the second most frequent neurodegenerative disorder after Alzheimer’s disease. The cell death of the dopaminergic neurons in the substantia nigra is responsible for typical disease symptoms: tremor, rigidity, and akinesia. The major genetic factor for PD is α-synuclein (αSYN). Besides αSYN, mutations in the genes encoding LRRK2 [4], parkin [5], PINK1 [6], and DJ-1 [7] are genetically linked to PD

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Results

Conclusion