Rotenone and paraquat perturb dopamine metabolism: A computational analysis of pesticide toxicity

• Type of Material: Article
• Authors: Zhen Qi, Georgia Institute of Technology; Eberhard Otto Voit, Emory University; Gary W Miller, Emory University
• Language: English
• Date: 2014-01-06
• Publisher: Elsevier: 12 months
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2013 Elsevier Ireland Ltd. All rights reserved.
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1016/j.tox.2013.11.003
• Title of Journal or Parent Work: Toxicology
• ISSN: 0300-483X
• Volume: 315
• Issue: 1
• Start Page: 92
• End Page: +
• Grant/Funding Information: This work was supported by grants from the National Institutes of Health (P01-ES016731, P30-ES019776); and an endowment from the Georgia Research Alliance (EOV, PI).
• Keywords: Mathematical model; Dopamine; Rotenone; SH-SY5Y CELLS; Life Sciences & Biomedicine; TRANSPORTER; NEUROTOXICITY; Science & Technology; Mode of action; Pharmacology & Pharmacy; COMPLEX-I; SYSTEMS-ANALYSIS; Parkinson's disease; NEUROTRANSMISSION; MODEL; NEURONS; EXPOSURE; Toxicology; PARKINSONS-DISEASE; Paraquat
• Research Categories: Environmental Sciences; Engineering, Biomedical; Biology, Neuroscience

Abstract

Pesticides, such as rotenone and paraquat, are suspected in the pathogenesis of Parkinson's disease (PD), whose hallmark is the progressive loss of dopaminergic neurons in the substantia nigra pars compacta. Thus, compounds expected to play a role in the pathogenesis of PD will likely impact the function of dopaminergic neurons. To explore the relationship between pesticide exposure and dopaminergic toxicity, we developed a custom-tailored mathematical model of dopamine metabolism and utilized it to infer potential mechanisms underlying the toxicity of rotenone and paraquat, asking how these pesticides perturb specific processes. We performed two types of analyses, which are conceptually different and complement each other. The first analysis, a purely algebraic reverse engineering approach, analytically and deterministically computes the altered profile of enzyme activities that characterize the effects of a pesticide. The second method consists of large-scale Monte Carlo simulations that statistically reveal possible mechanisms of pesticides. The results from the reverse engineering approach show that rotenone and paraquat exposures lead to distinctly different flux perturbations. Rotenone seems to affect all fluxes associated with dopamine compartmentalization, whereas paraquat exposure perturbs fluxes associated with dopamine and its breakdown metabolites. The statistical results of the Monte-Carlo analysis suggest several specific mechanisms. The findings are interesting, because no a priori assumptions are made regarding specific pesticide actions, and all parameters characterizing the processes in the dopamine model are treated in an unbiased manner. Our results show how approaches from computational systems biology can help identify mechanisms underlying the toxicity of pesticide exposure.