Abstract
Parkinson's disease (PD) is a basal ganglia movement disorder characterized by progressive degeneration of the nigrostriatal dopaminergic system. Immunohistochemical methods have been widely used for characterization of dopaminergic neuronal injury in animal models of PD, including the MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) mouse model. However, conventional immunohistochemical techniques applied to tissue sections have inherent limitations with respect to loss of 3D resolution, yielding insufficient information on the architecture of the dopaminergic system. To provide a more comprehensive and non-biased map of MPTP-induced changes in central dopaminergic pathways, we used iDISCO immunolabeling, light-sheet fluorescence microscopy (LSFM) and deep-learning computational methods for whole-brain three-dimensional visualization and automated quantitation of tyrosine hydroxylase (TH)-positive neurons in the adult mouse brain. Mice terminated 7 days after acute MPTP administration demonstrated widespread alterations in TH expression. Compared to vehicle controls, MPTP-dosed mice showed a significant loss of TH-positive neurons in the substantia nigra pars compacta and ventral tegmental area. Also, MPTP dosing reduced overall TH signal intensity in basal ganglia nuclei, i.e. the substantia nigra, caudate-putamen, globus pallidus and subthalamic nucleus. In contrast, increased TH signal intensity was predominantly observed in limbic regions, including several subdivisions of the amygdala and hypothalamus. In conclusion, mouse whole-brain 3D imaging is ideal for unbiased automated counting and densitometric analysis of TH-positive cells. The LSFM-deep learning pipeline tracked brain-wide changes in catecholaminergic pathways in the MPTP mouse model of PD, and may be applied for preclinical characterization of compounds targeting dopaminergic neurotransmission.