The coordinated action of multiple leg joints and muscles is required even for the simplest movements. Understanding the neuronal circuits and mechanisms that generate precise movements is essential for comprehending the neuronal basis of the locomotion and to infer the neuronal mechanisms underlying several locomotor-related diseases. Drosophila melanogaster provides an excellent model system for investigating the neuronal circuits underlying motor behaviors due to its simple nervous system and genetic accessibility. This review discusses current genetic methods for studying locomotor circuits and their function in adult Drosophila. We highlight recently identified neuronal pathways that modulate distinct forward and backward locomotion and describe the underlying neuronal control of leg swing and stance phases in freely moving flies. We also report various automated leg tracking methods to measure leg motion parameters and define inter-leg coordination, gait and locomotor speed of freely moving adult flies. Finally, we emphasize the role of leg proprioceptive signals to central motor circuits in leg coordination. Together, this review highlights the utility of adult Drosophila as a model to uncover underlying motor circuitry and the functional organization of the leg motor system that governs correct movement.
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http://dx.doi.org/10.1002/jnr.25332 | DOI Listing |
J Chem Ecol
January 2025
Centre des Sciences du Goût et de l'Alimentation, UMR-CNRS 6265, INRAe, Université de Bourgogne, Dijon, France.
Geographical, ethological, temporal and ecological barriers can affect interbreeding between populations deriving from an ancestral population, this progressively leading to speciation. A rare case of incipient speciation currently occurs between Drosophila melanogaster populations sampled in Zimbabwe (Z) and all other populations (M). This phenomenon was initially characterized by Z females refusing to mate with M males.
View Article and Find Full Text PDFEnviron Sci Pollut Res Int
January 2025
University of Rennes, CNRS, ECOBIO [(Ecosystèmes, biodiversité, évolution)] - UMR 6553, 263 Avenue du Gal Leclerc, CS 74205, 35042, Rennes Cedex, France.
Surfactants are used for a variety of applications such as emulsifiers, solubilizers, or foaming agents. Their intensive production and use in pharmaceutical, cosmetic and agricultural products have resulted in their continuous discharge in the environment, especially via wastewaters. Surfactants have become a threat to living organisms as they interact with, and disrupt, cell membranes and macromolecules.
View Article and Find Full Text PDFSci Signal
January 2025
Department of Environmental Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA.
Chronic exposure to manganese (Mn) induces manganism and has been widely implicated as a contributing environmental factor to Parkinson's disease (PD), featuring notable overlaps between the two in motor symptoms and clinical hallmarks. Here, we developed an adult model of Mn toxicity that recapitulated key parkinsonian features, spanning behavioral deficits, neuronal loss, and dysfunctions in lysosomes and mitochondria. Metabolomics analysis of the brain and body tissues of these flies at an early stage of toxicity identified systemic changes in the metabolism of biotin (also known as vitamin B) in Mn-treated groups.
View Article and Find Full Text PDFArch Insect Biochem Physiol
January 2025
College of Marine Life Sciences, Ocean University of China, Qingdao, China.
Zinc homeostasis contributes significantly to numerous physiological processes. Drosophila ZnT35C protein, a zinc transporter encoded by CG3994, is chiefly located on the cell membrane and facilitates the transport of zinc from the cytoplasm to the extracellular space to sustain zinc homeostasis within the organism. Previous studies about ZnT35C have involved diverse structures such as the Malpighian tubules, adult brain, and sensory nervous system.
View Article and Find Full Text PDFBiol Methods Protoc
January 2025
Division of Biological Sciences, University of Montana, Missoula, MT 59812, United States.
A longstanding challenge in biology is accurately analyzing images acquired using microscopy. Recently, machine learning (ML) approaches have facilitated detailed quantification of images that were refractile to traditional computation methods. Here, we detail a method for measuring pigments in the complex-mosaic adult eye using high-resolution photographs and the pixel classifier [1].
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