Fully automated leg tracking of Drosophila neurodegeneration models reveals distinct conserved movement signatures

Abstract

Some 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.

Extended Study of NUS1 Gene Variants in Parkinson's Disease

“…(iv) Mouse models with genetic deficiencies in transcription factor genes, such as the engrailed homeobox 1/2 gene (En1/2) and the paired like homeodomain 3 gene (Pitx3), exhibited features of PD, especially dopaminergic neuronal loss in the substantia nigra, but no definite pathogenic gene mutations were found in PD patients (34). Moreover, Drosophila with mutant spinocerebellar ataxia 3 (SCA3) selectively expressed in dopaminergic neurons, a non-PD causative gene deficiency, also presents PD-like phenotype (35). These challenge the persuasiveness of functional studies in Drosophila models (16).…”

Fully Automated Leg Tracking in Freely Moving Insects using Feature Learning Leg Segmentation and Tracking (FLLIT)

“…There are now a number of methods for leg movement tracking of Drosophila and other animals 1,2,3,4,14,15,16 , giving researchers a wide range of options depending on the goals of the experiment. Some of these are foot printing-based approaches, which are highly accurate but which report only claw contact points with the detection surface 4,14…”

“…On the other hand, recent deep learning approaches 2,3,16 are highly versatile, allowing analysis of behaviors that require tracking of leg joints and other body parts in any animal, with the caveat that the algorithms need to first be trained with user annotated datasets. A third type of approach uses morphology or image-contrast-based methods 1,15,17 to find the outline of each leg to identify claw positions. In general, these methods deal poorly with behaviors where the legs cross over (e.g.…”

“…Although our understanding of many neurodegenerative diseases has advanced at the molecular and cellular level, fundamental features of the affected neuronal circuitry underlying disease remain poorly understood. Recently developed behavioral tracking tools 1,2,3,4 now allow us to study movement abnormalities in animal disease models in order to identify molecular, cellular and circuit dysregulation underlying disease.…”

“…Molecular pathways involved in many neurodegenerative diseases are conserved in the fruit fly Drosophila melanogaster, and Drosophila disease models have helped to elucidate fundamental mechanisms underlying neurodegeneration 5,6 . We recently showed that fly models of Parkinson's Disease (PD) and Spinocerebellar ataxia 3 (SCA3) exhibit distinct, conserved gait signatures that resemble those of the respective human diseases 1 , demonstrating that the fly model can be used to understand circuit mechanisms underlying movement dysfunction in specific movement disorders. The rich and continually growing arsenal of tools in the fly model for targeted manipulation and visualization of neurons at the single gene and single cell level 7,8,9,10 makes the fly an ideal model one to probe the relationship between disease pathways, neuronal circuitry and behavioral phenotypic manifestation in vivo.…”