A CRISPR-CAS9 high throughput machine-learning platform for modulation of genes involved in Parkinson's disease-associated PINK1-mitophagy in iPSC-derived dopaminergic neurons
Parkinsons disease (PD) is a progressive neurodegenerative disorder characterised by the loss of dopaminergic neurons, driven by complex molecular mechanisms that are not fully understood. To address this issue, we have developed a novel high-content phenotypic screening platform using human induced pluripotent stem cell-derived dopaminergic neurons to investigate the PINK1-PARKIN mitophagy pathway, a critical process in PD pathogenesis. Utilising high throughput, 384 well arrayed CRISPR-CAS9 genetic manipulation and high-content immunofluorescence imaging complemented with machine learning analysis, we examined ubiquitin (Ub) pSer65 levels. Ub pSer65, a potential PD clinical biomarker, is a key marker of mitophagy initiation in dopaminergic neurons upon mitophagy initiation using exogenous stimuli to mimic the disease relevant environment. The CRISPR-CAS9 knockout (KO) screen revealed two distinct phenotypic classes: essential genes causing cell death upon deletion, and genes modulating Ub pSer65 levels. Notably, KO of PINK1, PARKIN, and TOM7 genes decreased Ub pSer65 upregulation during mitophagy activation, confirming their established roles in the pathway and validating the suitability of the platform for target identification. This innovative platform provides a precise tool to further interrogate PD-associated genes, offering insights into mitophagy-related pathogenic mechanisms and identification of potential therapeutic targets. By bridging functional genomics with disease-specific neuronal models, this approach presents a promising strategy for advancing PD research and developing targeted interventions. To our knowledge, this is the first reported use of a human, translationally relevant cell model to study genetic perturbation within a disease relevant phenotype.