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Multiplex analysis in a Drosophila gene‐environment model identifies interactions among LRRK2, rotenone and α‐synuclein

Epidemiological studies strongly support a role for environmental factors, particularly pesticide exposure, in the pathogenesis of Parkinson’s disease (PD). Genetic risk factors, including penetrant single gene mutations and risk factors identified from genome‐wide associated studies (GWAS) also contribute to PD risk and progression, but available model systems are limited in their ability to interrogate gene‐environment crosstalk in vivo and at scale. Here we use Drosophila as a model system to understand complex gene‐environment interactions in PD. We developed a multiplex model in Drosophila in which we knocked down GWAS candidate genes in neurons in a robust new α‐synucleinopathy model and exposed the flies to environmental neurotoxicants. We identified an interaction between LRRK2, rotenone and α‐synuclein. Expression of the disease‐causing Lrrk‐G2019S mutant in the presence of rotenone and alpha‐synuclein induced behavioral deficits and mitochondrial dysfunction. Further, super resolution microscopy analysis revealed that the interaction of LRRK2, α‐synuclein and rotenone leads to hyperstabilization of actin cytoskeleton. We have previously shown that LRRK2 has actin severing activity and previous studies have implicated the GTPase domain in regulating actin severing. We next expressed a GTPase domain mutant, Lrrk‐Q1003H, designed to mimic the human protective mutant LRRK2‐R1398H. Interestingly, expression of the LRRK2 protective mutant attenuated behavioral deficits mediated by LRRK2‐rotenone‐synuclein interactions. Further, expression of the protective mutant also attenuated the actin stabilization and mitochondrial deficits. Together, using our novel multiplex model in Drosophila we have identified an interaction between LRRK2, α‐synuclein, and rotenone which is modulated by actin stabilization and mitochondrial dysfunction. Our findings have implication towards development of a personalized approach for drug discovery and lead identification.