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      High-Resolution Positional Tracking for Long-Term Analysis of Drosophila Sleep and Locomotion Using the “Tracker” Program

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          Abstract

          Drosophila melanogaster has been used for decades in the study of circadian behavior, and more recently has become a popular model for the study of sleep. The classic method for monitoring fly activity involves counting the number of infrared beam crosses in individual small glass tubes. Incident recording methods such as this can measure gross locomotor activity, but they are unable to provide details about where the fly is located in space and do not detect small movements (i.e. anything less than half the enclosure size), which could lead to an overestimation of sleep and an inaccurate report of the behavior of the fly. This is especially problematic if the fly is awake, but is not moving distances that span the enclosure. Similarly, locomotor deficiencies could be incorrectly classified as sleep phenotypes. To address these issues, we have developed a locomotor tracking technique (the “Tracker” program) that records the exact location of a fly in real time. This allows for the detection of very small movements at any location within the tube. In addition to circadian locomotor activity, we are able to collect other information, such as distance, speed, food proximity, place preference, and multiple additional parameters that relate to sleep structure. Direct comparisons of incident recording and our motion tracking application using wild type and locomotor-deficient ( CASK-β null ) flies show that the increased temporal resolution in the data from the Tracker program can greatly affect the interpretation of the state of the fly. This is especially evident when a particular condition or genotype has strong effects on the behavior, and can provide a wealth of information previously unavailable to the investigator. The interaction of sleep with other behaviors can also be assessed directly in many cases with this method.

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          Most cited references 23

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          High-throughput Ethomics in Large Groups of Drosophila

          We present a camera-based method for automatically quantifying the individual and social behaviors of fruit flies, Drosophila melanogaster, interacting within a planar arena. Our system includes machine vision algorithms that accurately track many individuals without swapping identities and classification algorithms that detect behaviors. The data may be represented as an ethogram that plots the time course of behaviors exhibited by each fly, or as a vector that concisely captures the statistical properties of all behaviors displayed within a given period. We found that behavioral differences between individuals are consistent over time and are sufficient to accurately predict gender and genotype. In addition, we show that the relative positions of flies during social interactions vary according to gender, genotype, and social environment. We expect that our software, which permits high-throughput screening, will complement existing molecular methods available in Drosophila, facilitating new investigations into the genetic and cellular basis of behavior.
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            The ubiquitin proteasome system in neurodegenerative diseases: sometimes the chicken, sometimes the egg.

            The ubiquitin-proteasome system targets numerous cellular proteins for degradation. In addition, modifications by ubiquitin-like proteins as well as proteins containing ubiquitin-interacting and -associated motifs modulate many others. This tightly controlled process involves multiple specific and general enzymes of the system as well as many modifying and ancillary proteins. Thus, it is not surprising that ubiquitin-mediated degradation/processing/modification regulates a broad array of basic cellular processes. Moreover, aberrations in the system have been implicated, either as a primary cause or secondary consequence, in the pathogenesis of both inherited and acquired neurodegenerative diseases. Recent findings indicate that the system is involved in the pathogenesis of Parkinson's, Alzheimer's, Huntington's, and Prion diseases as well as amyotrophic lateral sclerosis. This raises hopes for a better understanding of the pathogenetic mechanisms involved in these diseases and for the development of novel, mechanism-based therapeutic modalities.
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              Identification of SLEEPLESS, a sleep-promoting factor.

              Sleep is an essential process conserved from flies to humans. The importance of sleep is underscored by its tight homeostatic control. Through a forward genetic screen, we identified a gene, sleepless, required for sleep in Drosophila. The sleepless gene encodes a brain-enriched, glycosylphosphatidylinositol-anchored protein. Loss of SLEEPLESS protein caused an extreme (>80%) reduction in sleep; a moderate reduction in SLEEPLESS had minimal effects on baseline sleep but markedly reduced the amount of recovery sleep after sleep deprivation. Genetic and molecular analyses revealed that quiver, a mutation that impairs Shaker-dependent potassium current, is an allele of sleepless. Consistent with this finding, Shaker protein levels were reduced in sleepless mutants. We propose that SLEEPLESS is a signaling molecule that connects sleep drive to lowered membrane excitability.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                15 May 2012
                : 7
                : 5
                Affiliations
                [1 ]Department of Biology, National Center for Behavioral Genomics and Volen Center for Complex Systems, Brandeis University, Waltham, Massachusetts, United States of America
                [2 ]Department of Biological Sciences, JP Scott Center for Neuroscience, Mind, & Behavior, Bowling Green State University, Bowling Green, Ohio, United States of America
                Queensland Brain Institute, Australia
                Author notes

                Conceived and designed the experiments: NCD LCG. Performed the experiments: NCD. Analyzed the data: NCD. Contributed reagents/materials/analysis tools: NCD EZK JBS CGV RH. Wrote the paper: NCD CGV LCG. Designed tracking application: RH. Designed analysis scripts: EZK. Designed sleep analysis scripts: CGV. Provided fly lines: JBS.

                Article
                PONE-D-12-01779
                10.1371/journal.pone.0037250
                3352887
                22615954
                Donelson et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                Page count
                Pages: 12
                Categories
                Research Article
                Biology
                Anatomy and Physiology
                Physiological Processes
                Chronobiology
                Sleep
                Evolutionary Biology
                Animal Behavior
                Behavioral Ecology
                Genetics
                Animal Genetics
                Gene Function
                Genetics of Disease
                Model Organisms
                Animal Models
                Drosophila Melanogaster
                Neuroscience
                Behavioral Neuroscience
                Neuroethology
                Computer Science
                Software Engineering
                Software Tools
                Medicine
                Anatomy and Physiology
                Physiological Processes
                Chronobiology

                Uncategorized

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