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

### Abstract

Background: 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 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.

Results: We present an 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 the cell and (vi) increase of dopamine synthesis. The SBML model is available in BioModels database with identifier MODEL1302200000.

Conclusion: It 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 \alhpaSYN induces apoptosis and we observed an increased flux of αSYN to the extracellular space.

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### BibTeX

@article{Buechel2013c,
author = {B\"uchel, Finja and Saliger, Sandra and Dr\"ager, Andreas and Hoffmann,
Stephanie and Wrzodek, Clemens and Zell, Andreas and Kahle, Philipp
J.},
title = {{Parkinson's disease: dopaminergic nerve cell model is consistent
with experimental finding of increased extracellular transport of
$\alpha$-synuclein}},
journal = {BMC Neuroscience},
year = {2013},
volume = {14},
number = {136},
month = nov,
abstract = {Background: 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 easily transferred to humans.
Therefore, mathematical or probabilistic models for the human disease
are to be constructed \emph{in-silico} in order to predict specific
processes within a cell, such as the dopamine metabolism and transport
processes in a neuron.

Results: We present an 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 $\alpha$-synuclein ($\alpha$SYN), 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 O\textsubscript{2}, (iii) increase of ATP, (iv) influence
of neurotoxins, (v) increase of $\alpha$SYN the cell and (vi) increase
of dopamine synthesis. The SBML model is available in BioModels database
with identifier MODEL1302200000.

Conclusion: It is possible to simulate the normal behavior of an
\emph{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 $\alhpa$SYN induces apoptosis and we observed an increased flux of
$\alpha$SYN to the extracellular space.},
doi = {10.1186/1471-2202-14-136},
issn = {1471-2202},
keywords = {Parkinson's disease, Dopaminergic nerve cell model, SBML model,
Flux balance analysis},
pdf = {http://www.biomedcentral.com/content/pdf/1471-2202-14-136.pdf},
url = {http://www.biomedcentral.com/1471-2202/14/136}
}