PUBLICATION
Neurological Disease Modelling for Spinocerebellar Ataxia Using Zebrafish
- Authors
- Namikawa, K., Dorigo, A., Köster, R.W.
- ID
- ZDB-PUB-191102-3
- Date
- 2019
- Source
- Journal of experimental neuroscience 13: 1179069519880515 (Other)
- Registered Authors
- Köster, Reinhard W., Namikawa, Kazuhiko
- Keywords
- Purkinje neurons, Zebrafish, disease modelling, neurodegeneration, spinocerebellar degeneration
- MeSH Terms
- none
- PubMed
- 31666796 Full text @ J. Exp. Neurosci.
Citation
Namikawa, K., Dorigo, A., Köster, R.W. (2019) Neurological Disease Modelling for Spinocerebellar Ataxia Using Zebrafish. Journal of experimental neuroscience. 13:1179069519880515.
Abstract
The cerebellum integrates sensory information and motor actions. Increasing experimental evidence has revealed that these functions as well as the cerebellar cytoarchitecture are highly conserved in zebrafish compared with mammals. However, the potential of zebrafish for modelling human cerebellar diseases remains to be addressed. Spinocerebellar ataxias (SCAs) represent a group of genetically inherited cerebellar diseases leading to motor discoordination that is most often caused by affected cerebellar Purkinje cells (PCs). Towards modelling SCAs in zebrafish we identified a small-sized PC-specific regulatory element that was used to develop coexpression vectors with tunable expression strength. These vectors allow for in vivo imaging of SCA-affected PCs by high-resolution fluorescence imaging. Next, zebrafish with SCA type 13 (SCA13) transgene expression were established, revealing that SCA13-induced cell-autonomous PC degeneration results in eye movement deficits. Thus, SCA13 zebrafish mimic the neuropathology of an SCA-affected brain as well as the involved loss of motor control and hence provide a powerful approach to unravel SCA13-induced cell biological pathogenic and cytotoxic mechanisms.
Genes / Markers
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Orthology
Engineered Foreign Genes
Mapping