RESUMEN
Self-propagating, amyloidogenic mutant huntingtin (mHTT) aggregates may drive progression of Huntington's disease (HD). Here, we report the development of a FRET-based mHTT aggregate seeding (FRASE) assay that enables the quantification of mHTT seeding activity (HSA) in complex biosamples from HD patients and disease models. Application of the FRASE assay revealed HSA in brain homogenates of presymptomatic HD transgenic and knockin mice and its progressive increase with phenotypic changes, suggesting that HSA quantitatively tracks disease progression. Biochemical investigations of mouse brain homogenates demonstrated that small, rather than large, mHTT structures are responsible for the HSA measured in FRASE assays. Finally, we assessed the neurotoxicity of mHTT seeds in an inducible Drosophila model transgenic for HTTex1. We found a strong correlation between the HSA measured in adult neurons and the increased mortality of transgenic HD flies, indicating that FRASE assays detect disease-relevant, neurotoxic, mHTT structures with severe phenotypic consequences in vivo.
Asunto(s)
Biomarcadores/metabolismo , Proteína Huntingtina/metabolismo , Enfermedad de Huntington/metabolismo , Enfermedad de Huntington/patología , Animales , Animales Modificados Genéticamente/genética , Animales Modificados Genéticamente/metabolismo , Encéfalo/metabolismo , Encéfalo/patología , Caenorhabditis elegans/genética , Caenorhabditis elegans/metabolismo , Modelos Animales de Enfermedad , Progresión de la Enfermedad , Drosophila/genética , Drosophila/metabolismo , Femenino , Humanos , Proteína Huntingtina/genética , Enfermedad de Huntington/genética , Masculino , Ratones , Ratones Endogámicos C57BL , Ratones Endogámicos CBA , Mutación/genética , Neuronas/metabolismo , Neuronas/patología , Proteínas Nucleares/genética , Proteínas Nucleares/metabolismoRESUMEN
Numerous genetic methods facilitate the detection of binary protein-protein interactions (PPIs) by exogenous overexpression, which can lead to false results. Here, we describe CellFIE, a CRISPR- and cell fusion-based PPI detection method, which enables the mapping of interactions between endogenously tagged two-hybrid proteins. We demonstrate the specificity and reproducibility of CellFIE in a matrix mapping approach, validating the interactions of VCP with ASPL and UBXD1, and the self-interaction of TDP-43 under endogenous conditions. Furthermore, we show that CellFIE can be used to quantify changes of endogenous PPIs upon stress induction or drug treatment. For the first time, CellFIE facilitates systematic mapping of interactions between endogenously tagged proteins and represents a novel tool to characterize PPIs in live cells under dynamic conditions.