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

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.

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

The Drosophila model has been invaluable for the study of neurological function and for understanding the molecular and cellular mechanisms that underlie neurodegeneration. While fly techniques for the manipulation and study of neuronal subsets have grown increasingly sophisticated, the richness of the resultant behavioral phenotypes has not been captured at a similar detail. To be able to study subtle fly leg movements for comparison amongst mutants requires the ability to automatically measure and quantify high-speed and rapid leg movements. Hence, we developed a machine-learning algorithm for automated leg claw tracking in freely walking flies, Feature Learning-based Limb segmentation and Tracking (FLLIT). Unlike most deep learning methods, FLLIT is fully automated and generates its own training sets without a need for user annotation, using morphological parameters built into the learning algorithm. This article describes an in depth protocol for carrying out gait analysis using FLLIT. It details the procedures for camera setup, arena construction, video recording, leg segmentation and leg claw tracking. It also gives an overview of the data produced by FLLIT, which includes raw tracked body and leg positions in every video frame, 20 gait parameters, 5 plots and a tracked video. To demonstrate the use of FLLIT, we quantify relevant diseased gait parameters in a fly model of Spinocerebellar ataxia 3.

A Glio-Protective Role of mir-263a by Tuning Sensitivity to Glutamate.

Glutamate is a ubiquitous neurotransmitter, mediating information flow between neurons. Defects in the regulation of glutamatergic transmission can result in glutamate toxicity, which is associated with neurodegeneration. Interestingly, glutamate receptors are expressed in glia, but little is known about their function, and the effects of their misregulation, in these non-neuronal cells. Here, we report a glio-protective role for Drosophila mir-263a mediated by its regulation of glutamate receptor levels in glia. mir-263a mutants exhibit a pronounced movement defect due to aberrant overexpression of CG5621/Grik, Nmdar1, and Nmdar2. mir-263a mutants exhibit excitotoxic death of a subset of astrocyte-like and ensheathing glia in the CNS. Glial-specific normalization of glutamate receptor levels restores cell numbers and suppresses the movement defect. Therefore, microRNA-mediated regulation of glutamate receptor levels protects glia from excitotoxicity, ensuring CNS health. Chronic low-level glutamate receptor overexpression due to mutations affecting microRNA (miRNA) regulation might contribute to glial dysfunction and CNS impairment.

The Brm-HDAC3-Erm repressor complex suppresses dedifferentiation in Drosophila type II neuroblast lineages.

The control of self-renewal and differentiation of neural stem and progenitor cells is a crucial issue in stem cell and cancer biology. Drosophila type II neuroblast lineages are prone to developing impaired neuroblast homeostasis if the limited self-renewing potential of intermediate neural progenitors (INPs) is unrestrained. Here, we demonstrate that Drosophila SWI/SNF chromatin remodeling Brahma (Brm) complex functions cooperatively with another chromatin remodeling factor, Histone deacetylase 3 (HDAC3) to suppress the formation of ectopic type II neuroblasts. We show that multiple components of the Brm complex and HDAC3 physically associate with Earmuff (Erm), a type II-specific transcription factor that prevents dedifferentiation of INPs into neuroblasts. Consistently, the predicted Erm-binding motif is present in most of known binding loci of Brm. Furthermore, brm and hdac3 genetically interact with erm to prevent type II neuroblast overgrowth. Thus, the Brm-HDAC3-Erm repressor complex suppresses dedifferentiation of INPs back into type II neuroblasts. DOI: http://dx.doi.org/10.7554/eLife.01906.001.