NeuronNeurosciencePeer-reviewed journal article
Rapid iPSC inclusionopathy models shed light on formation, consequence and molecular subtype of alpha-synuclein inclusions
Isabel LamiD, Alain NdayisabaiD, Amanda J. LewisiD, YuHong FuiD, Giselle T. Sagredo, Anastasia KuzkinaiD, Ludovica Zaccagnini, Meral CelikagiD, Jackson Sandoe, Ricardo L. Sanz, Aazam Vahdatshoar, Timothy D. MartiniD, Nader MorshediD, Toru Ichihashi, Arati TripathiiD, Nagendran RamalingamiD, Charlotte Oettgen-Suazo, Theresa BartelsiD, Manel L. N. BoussoufiD, Max Schäbinger, Erinc HallacliiD, Xin Jian JiangiD, Amrita Verma, Challana TeaiD, Zichen WangiD, , Vikram KhuranaiD
Abstract
Intracellular inclusions accompanying neurodegeneration are histopathologically and ultrastructurally heterogeneous but the significance of this heterogeneity is unclear. iPSC models, while promising for disease modeling, do not form inclusions in a reasonable timeframe and suffer from limited tractability. Here, we developed an iPSC toolbox utilizing piggyBac-based or targeted transgenes to rapidly induce CNS cells with concomitant expression of aggregation-prone proteins. This system is amenable to screening and longitudinal tracking at single-cell and single-inclusion resolution. For proof-of-principle, cortical neuron -synuclein "inclusionopathy" models were engineered to form inclusions through exogenous seeding or -synuclein mutation. These models recapitulated known fibril- and lipid-rich inclusion subtypes, uncovering dynamic interactions between them, and refined the classification of inclusions in postmortem brain. Genetic-modifier and protein-interaction screens pinpointed proteins like RhoA whose sequestration into specific inclusion subtypes is likely to be toxic. This iPSC platform should enhance our understanding of proteinaceous pathologies in neurodegeneration and facilitate therapeutics development.
- organism: human
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- approach: experimental assay
- Citations
- 37
- FWCI
- 9.58
- Field percentile
- top 1%
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