A Live-Cell Imaging System for the Identification of Pro- and Anti-Aggregatory α-Synuclein Modulators.

α-Synuclein (αSyn) aggregation is a defining pathological feature of synucleinopathies, including Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy (MSA). However, existing in vitro methods to monitor αSyn aggregation often rely on endpoint assays that cannot distinguish monomeric from oligomeric species or capture early aggregation dynamics. Here, we implement an αSyn bimolecular fluorescence complementation (αSyn-BiFC) strategy in a stable human glial-derived cell system optimized for real-time, high-content analysis of early αSyn self-association events and their modulation. In this strategy, αSyn is fused to complementary fragments of the Venus fluorescent protein, enabling real-time visualization of αSyn-αSyn interactions during oligomer formation. Using U373 human astrocytoma cells, a scalable glial-derived cell line previously used in studies of MSA, we established both transient and stable αSyn-BiFC expression systems. We demonstrate that reconstituted Venus fluorescence correlates with pSer129 αSyn immunostaining, supporting the association of the BiFC signal with pathology-related αSyn assemblies. The model responded robustly to multiple stressors known to promote αSyn aggregation, including proteostasis(definition) disruption (leupeptin, MG132), ER stress (tunicamycin), and environmental toxins (rotenone), while iron, particularly Fe³⁺, also enhanced αSyn self-association. Furthermore, testing two small molecules previously shown to attenuate αSyn aggregation and pathology in vivo revealed a reduction in Venus fluorescence, consistent with reduced αSyn self-association and supporting the platform's utility for drug discovery screens. By providing a dynamic, sensitive, and physiologically relevant readout of early αSyn assemblies, the αSyn-BiFC model overcomes limitations of conventional assays and offers a scalable framework for mechanistic studies, compound screening, and integration into more disease-relevant neuronal and aging-enhanced models for future synucleinopathies research.