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High content organelle trafficking enables disease state profiling as powerful tool for disease modelling.
Pal, Arun; Glaß, Hannes; Naumann, Marcel; Kreiter, Nicole; Japtok, Julia; Sczech, Ronny; Hermann, Andreas.
Afiliación
  • Pal A; Division of Neurodegenerative Diseases, Department of Neurology, Technische Universität Dresden, Dresden, Germany.
  • Glaß H; Division of Neurodegenerative Diseases, Department of Neurology, Technische Universität Dresden, Dresden, Germany.
  • Naumann M; Division of Neurodegenerative Diseases, Department of Neurology, Technische Universität Dresden, Dresden, Germany.
  • Kreiter N; German Center for Neurodegenerative Diseases (DZNE) Dresden, Dresden, Germany.
  • Japtok J; Division of Neurodegenerative Diseases, Department of Neurology, Technische Universität Dresden, Dresden, Germany.
  • Sczech R; German Center for Neurodegenerative Diseases (DZNE) Dresden, Dresden, Germany.
  • Hermann A; Division of Neurodegenerative Diseases, Department of Neurology, Technische Universität Dresden, Dresden, Germany.
Sci Data ; 5: 180241, 2018 11 13.
Article en En | MEDLINE | ID: mdl-30422121
Neurodegenerative diseases pose a complex field with various neuronal subtypes and distinct differentially affected intra-neuronal compartments. Modelling of neurodegeneration requires faithful in vitro separation of axons and dendrites, their distal and proximal compartments as well as organelle tracking with defined retrograde versus anterograde directionality. We use microfluidic chambers to achieve compartmentalization and established high throughput live organelle imaging at standardized distal and proximal axonal readout sites in iPSC-derived spinal motor neuron cultures from human amyotrophic lateral sclerosis patients to study trafficking phenotypes of potential disease relevance. Our semi-automated pipeline of organelle tracking with FIJI and KNIME yields quantitative, multiparametric high content phenotypic signatures of organelle morphology and their trafficking in axons. We provide here the resultant large datasets to enable systemic signature interrogations for comprehensive and predictive disease modelling, mechanistic dissection and secondary hit validation (e.g. drug screens, genetic screens). Due to the nearly complete coverage of analysed motility events, our quantitative method yields a bias-free statistical power superior over common analyses of a handful of manual kymographs.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Transporte Axonal / Orgánulos / Enfermedades Neurodegenerativas / Ensayos Analíticos de Alto Rendimiento Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Sci Data Año: 2018 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Transporte Axonal / Orgánulos / Enfermedades Neurodegenerativas / Ensayos Analíticos de Alto Rendimiento Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Sci Data Año: 2018 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Reino Unido