Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pbio.3000346
DC FieldValue
dc.titleFully automated leg tracking of drosophila neurodegeneration models reveals distinct conserved movement signatures
dc.contributor.authorWu, S.
dc.contributor.authorTan, K.J.
dc.contributor.authorGovindarajan, L.N.
dc.contributor.authorStewart, J.C.
dc.contributor.authorGu, L.
dc.contributor.authorHo, J.W.H.
dc.contributor.authorKatarya, M.
dc.contributor.authorWong, B.H.
dc.contributor.authorTan, E.-K.
dc.contributor.authorLi, D.
dc.contributor.authorClaridge-Chang, A.
dc.contributor.authorLibedinsky, C.
dc.contributor.authorCheng, L.
dc.contributor.authorAw, S.S.
dc.date.accessioned2021-12-09T03:04:09Z
dc.date.available2021-12-09T03:04:09Z
dc.date.issued2019
dc.identifier.citationWu, S., Tan, K.J., Govindarajan, L.N., Stewart, J.C., Gu, L., Ho, J.W.H., Katarya, M., Wong, B.H., Tan, E.-K., Li, D., Claridge-Chang, A., Libedinsky, C., Cheng, L., Aw, S.S. (2019). Fully automated leg tracking of drosophila neurodegeneration models reveals distinct conserved movement signatures. PLoS Biology 17 (6) : e3000346. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pbio.3000346
dc.identifier.issn1544-9173
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/209969
dc.description.abstractSome neurodegenerative diseases, like Parkinsons Disease (PD) and Spinocerebellar ataxia 3 (SCA3), are associated with distinct, altered gait and tremor movements that are reflective of the underlying disease etiology. Drosophila melanogaster models of neurodegeneration have illuminated our understanding of the molecular mechanisms of disease.However, it is unknown whether specific gait and tremor dysfunctions also occur in fly disease mutants. To answer this question, we developed a machine-learning image-analysis program, Feature Learning-based LImb segmentation and Tracking (FLLIT), that automatically tracks leg claw positions of freely moving flies recorded on high-speed video, producing a series of gait measurements. Notably, unlike other machine-learning methods, FLLIT generates its own training sets and does not require user-annotated images for learning. Using FLLIT, we carried out high-throughput and high-resolution analysis of gait and tremor features in Drosophila neurodegeneration mutants for the first time. We found that fly models of PD and SCA3 exhibited markedly different walking gait and tremor signatures, which recapitulated characteristics of the respective human diseases. Selective expression of mutant SCA3 in dopaminergic neurons led to a gait signature that more closely resembled those of PD flies. This suggests that the behavioral phenotype depends on the neurons affected rather than the specific nature of the mutation. Different mutations produced tremors in distinct leg pairs, indicating that different motor circuits were affected. Using this approach,fly models can be used to dissect the neurogenetic mechanisms that underlie movement disorders. © 2019 Wu et al.
dc.publisherPublic Library of Science
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceScopus OA2019
dc.typeArticle
dc.contributor.departmentDEPT OF BIOLOGICAL SCIENCES
dc.contributor.departmentDEPT OF PSYCHOLOGY
dc.description.doi10.1371/journal.pbio.3000346
dc.description.sourcetitlePLoS Biology
dc.description.volume17
dc.description.issue6
dc.description.pagee3000346
Appears in Collections:Elements
Staff Publications

Show simple item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
10_1371_journal_pbio_3000346.pdf2.45 MBAdobe PDF

OPEN

NoneView/Download

SCOPUSTM   
Citations

10
checked on Feb 2, 2023

Page view(s)

105
checked on Feb 2, 2023

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons