FB2024_03 , released June 25, 2024
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Citation
Madabattula, S.T., Strautman, J.C., Bysice, A.M., O'Sullivan, J.A., Androschuk, A., Rosenfelt, C., Doucet, K., Rouleau, G., Bolduc, F. (2015). Quantitative Analysis of Climbing Defects in a Drosophila Model of Neurodegenerative Disorders.  J. Vis. Exp. (100): e52741.
FlyBase ID
FBrf0228890
Publication Type
Research paper
Abstract
Locomotive defects resulting from neurodegenerative disorders can be a late onset symptom of disease, following years of subclinical degeneration, and thus current therapeutic treatment strategies are not curative. Through the use of whole exome sequencing, an increasing number of genes have been identified to play a role in human locomotion. Despite identifying these genes, it is not known how these genes are crucial to normal locomotive functioning. Therefore, a reliable assay, which utilizes model organisms to elucidate the role of these genes in order to identify novel targets of therapeutic interest, is needed more than ever. We have designed a sensitized version of the negative geotaxis assay that allows for the detection of milder defects earlier and has the ability to evaluate these defects over time. The assay is performed in a glass graduated cylinder, which is sealed with a wax barrier film. By increasing the threshold distance to be climbed to 17.5 cm and increasing the experiment duration to 2 min we have observed a greater sensitivity in detecting mild mobility dysfunctions. The assay is cost effective and does not require extensive training to obtain highly reproducible results. This makes it an excellent technique for screening candidate drugs in Drosophila mutants with locomotion defects.
PubMed ID
PubMed Central ID
PMC4544889 (PMC) (EuropePMC)
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Secondary IDs
    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    J. Vis. Exp.
    Title
    Journal of visualized experiments : JoVE
    ISBN/ISSN
    1940-087X
    Data From Reference
    Alleles (4)
    Genes (2)
    Human Disease Models (1)
    Transgenic Constructs (2)