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ABSTRACT Drosophila’s innate response to gravity, geotaxis, has been used to assess the impact of aging and disease on motor performance. Despite its rich history, fly geotaxis continues to be largely measured manually and assessed through simplistic metrics, limiting analytic insights into the behavior. Here, we have constructed a fully programmable apparatus and developed a multi-object tracking software capable of following sub-second movements of individual flies, thus allowing quantitative analysis of geotaxis. The apparatus monitors 10 fly cohorts simultaneously, with each cohort consisting of up to 7 flies. The software tracks single flies during the entire run with ∼97% accuracy, yielding detailed climbing curve, speed and movement direction with 1/30 s resolution. Our tracking permits the construction of multi-variable metrics and the detection of transitory movement phenotypes, such as slips and falls. The platform is therefore poised to advance Drosophila geotaxis assay into a comprehensive assessment of locomotor behavior. 

Sleep and circadian rhythm dysfunctions are common clinical features of Alzheimer’s disease (AD). Increasing evidence suggests that in addition to being a symptom, sleep disturbances can also drive the progression of neurodegeneration. Protein aggregation is a pathological hallmark of AD; however, the molecular pathways behind how sleep affects protein homeostasis remain elusive. Here we demonstrate that sleep modulation influences proteostasis and the progression of neurodegeneration inDrosophilamodels of tauopathy. We show that sleep deprivation enhanced Tau aggregational toxicity resulting in exacerbated synaptic degeneration. In contrast, sleep induction using gaboxadol led to reduced toxic Tau accumulation in neurons as a result of modulated autophagic flux and enhanced clearance of ubiquitinated Tau, suggesting altered protein processing and clearance that resulted in improved synaptic integrity and function. These findings highlight the complex relationship between sleep and regulation of protein homeostasis and the neuroprotective potential of sleep-enhancing therapeutics to slow the progression or delay the onset of neurodegeneration. 

Background and aimsSYNGAP1-related disorder (SYNGAP1-RD) is a prevalent genetic form of Autism Spectrum Disorder and Intellectual Disability (ASD/ID) and is caused byde novoor inherited mutations in one copy of theSYNGAP1gene. In addition to ASD/ID, SYNGAP1 disorder is associated with comorbid symptoms including treatment-resistant-epilepsy, sleep disturbances, and gastrointestinal distress. Mechanistic links between these diverse symptoms andSYNGAP1variants remain obscure, therefore, our goal was to generate a zebrafish model in which this range of symptoms can be studied. MethodsWe used CRISPR/Cas9 to introduce frameshift mutations in thesyngap1aandsyngap1bzebrafish duplicates (syngap1ab) and validated these stable models for Syngap1 loss-of-function. BecauseSYNGAP1is extensively spliced, we mapped splice variants to the two zebrafishsyngap1aandbgenes and identified mammalian-like isoforms. We then quantified locomotory behaviors in zebrafishsyngap1ablarvae under three conditions that normally evoke different arousal states in wild-type larvae: aversive, high-arousal acoustic, medium-arousal dark, and low-arousal light stimuli. ResultsWe show that CRISPR/Cas9 indels in zebrafishsyngap1aandsyngap1bproduced loss-of-function alleles at RNA and protein levels. Our analyses of zebrafish Syngap1 isoforms showed that, as in mammals, zebrafish Syngap1 N- and C-termini are extensively spliced. We identified a zebrafishsyngap1α1-like variant that maps exclusively to thesyngap1bgene. Quantifying locomotor behaviors showed thatsyngap1abmutant larvae are hyperactive compared to wild-type but to differing degrees depending on the stimulus. Hyperactivity was most pronounced in low arousal settings, and hyperactivity was proportional to the number of mutantsyngap1alleles. LimitationsSyngap1loss-of-function mutations produce relatively subtle phenotypes in zebrafish compared to mammals. For example, while mouseSyngap1homozygotes die at birth, zebrafishsyngap1ab−/−survive to adulthood and are fertile, thus some aspects of symptoms in people withSYNGAP1-Related Disorder are not likely to be reflected in zebrafish. ConclusionOur data support mutations in zebrafishsyngap1abas causal for hyperactivity associated with elevated arousal that is especially pronounced in low-arousal environments. 

Abstract Inhibitors of enzymes that inactivate amine neurotransmitters (dopamine, serotonin), such as catechol-O-methyltransferase (COMT) and monoamine oxidase (MAO), are thought to increase neurotransmitter levels and are widely used to treat Parkinson's disease and psychiatric disorders, yet the role of these enzymes in regulating behavior remains unclear. Here, we investigated the genetic loss of a similar enzyme in the model organismDrosophila melanogaster. Because the enzyme Ebony modifies and inactivates amine neurotransmitters, its loss is assumed to increase neurotransmitter levels, increasing behaviors such as aggression and courtship and decreasing sleep. Indeed,ebonymutants have been described since 1960 as aggressive mutants, though this behavior has not been quantified. Using automated machine learning-based analyses, we quantitatively confirmed thatebonymutants exhibited increased aggressive behaviors such as boxing but also decreased courtship behaviors and increased sleep. Through tissue-specific knockdown, we found thatebony’s role in these behaviors was specific to glia. Unexpectedly, direct measurement of amine neurotransmitters inebonybrains revealed that their levels were not increased but reduced. Thus, increased aggression is the anomalous behavior for this neurotransmitter profile. We further found thatebonymutants exhibited increased aggression only when fighting each other, not when fighting wild-type controls. Moreover, fights betweenebonymutants were less likely to end with a clear winner than fights between controls or fights betweenebonymutants and controls. Inebonyvs. control fights,ebonymutants were more likely to win. Together, these results suggest thatebonymutants exhibit prolonged aggressive behavior only in a specific context, with an equally dominant opponent. 

From birds that preen their feathers to dogs that lick their fur, many animals groom themselves. They do so to stay clean, but routine grooming also has a range of other uses, such as social communication or controlling body temperature. Despite its importance, grooming remains poorly understood; it is especially unclear how this behavior is regulated. Fruit flies could be a good model to study grooming because they are often used in laboratories to look into the genetic and brain mechanisms that control behavior. Flies clean themselves by sweeping their legs over their wings and body, but little is known about how the insects groom ‘naturally’ over long periods of time. This is partly because scientists have had to recognize and classify grooming behavior by eye, which is highly time-consuming. Here, Qiao, Li et al. have created a system to automatically detect grooming behavior in fruit flies over time. First, a camera records the movement of an individual insect. A computer then analyzes the images and picks out general features of the fly’s movement that can help work out what the insect is doing. For example, if a fly is moving its limbs, but not the main part of its body, it is probably grooming itself. Qiao, Li et al. then borrowed an algorithm from an area of computer science known as ‘machine learning’ to teach the computer how to classify each fly’s behavior automatically. The new system successfully recognized grooming behavior in over 90% of cases, and it revealed that fruit flies spend about 13% of their waking life grooming. It also showed that grooming seems to be controlled by two potentially independent internal programs. One program is tied to the internal body clock of the fly, and regulates when the insect grooms during the day. The other commands how long the fly cleans itself, and balances the amount of time spent on grooming with other behaviors. Cleaning oneself is not just important for animals to stay disease-free: it also reflects the general health state of an individual. For example, a loss of grooming is associated with sickness, old age, and, in humans, with mental illness. If scientists can understand how grooming is controlled at the brain and molecular levels, this may give an insight into how these mechanisms relate to diseases. The system created by Qiao, Li et al. could help to make such studies possible.