Background: Diverse alpha-synuclein [aS] conformers or “strains” have been implicated in synucleinopathies including Parkinson’s disease (PD). Moreover, proteinaceous inclusions that form in CNS cells exhibit heterogeneous ultrastructure and poorly correlate with cell loss. iPSc models could provide the human disease context to better understand this heteroegeneity, but they do not robustly form mature inclusions in a reasonable experimental timeframe. Here, we aimed to (1) induce rapid inclusion formation in human iPSc-derived cortical neurons, (2) identify the impact of distinct inclusions on neuronal survival and (3) utilize these models to shed light on distinct inclusion subtypes in synucleinopathy brains.
Methods: We developed a PiggyBac-based system to express transcription factors for rapid, scalable and virus-free conversion of iPSc to CNS cells under a tetracycline-inducible promoter. aS is simultaneously over-expressed in this system, either physiologically through altered copy-number at the SNCA locus, or through targeted transgenic over-expression of tagged or untagged aS constructs. Inclusion formation can be dramatically accelerated either by exposure to recombinant or patient brain-derived aS fibrils or by expressing aggregation-prone aS mutants. We characterized inclusions in iPSc-derived cortical neurons induced by Ngn2 expression and applied machine-learning algorithms to longitudinally track their formation and consequences on cell survival.
Results: The PiggyBac induced inclusion neuron models form heterogeneous inclusions and recapitulate pathologic aS markers. Furthermore, this model recapitulates advanced pathologies found in postmortem synucleinopathy brains and can guide us on novel markers that distinguish inclusion subtypes. Notably, we find that distinct subsets of inclusions in this model differentially impact neuronal survival.
Conclusion: Rapid-scale production of patient-specific neurons “in the dish” offers promise for modeling disease biology in an appropriate human cellular context. We envisage these models will be useful for biological and drug discovery in alpha-synucleinopathies.