Recent work indicates a role for RING finger protein 11 (RNF11) in Parkinson disease (PD) pathology, which involves the loss of dopaminergic neurons. However, the role of RNF11 in regulating dopamine neurotransmission has not been studied. In this work, we tested the effect of RNF11 RNAi knockdown or overexpression on stimulated dopamine release in the larval Drosophila central nervous system. Dopamine release was stimulated using optogenetics and monitored in real-time using fast-scan cyclic voltammetry at an electrode implanted in an isolated ventral nerve cord. RNF11 knockdown doubled dopamine release, but there was no decrease in dopamine from RNF11 overexpression. RNF11 knockdown did not significantly increase stimulated serotonin or octopamine release, indicating the effect is dopamine specific. Dopamine clearance was also changed, as RNF11 RNAi flies had a higher Vmax and RNF11 overexpressing flies had a lower Vmax than control flies. RNF11 RNAi flies had increased mRNA levels of dopamine transporter (DAT) in RNF11, confirming changes in DAT. In RNF11 RNAi flies, release was maintained better for stimulations repeated at short intervals, indicating increases in the recycled releasable pool of dopamine. Nisoxetine, a DAT inhibitor, and flupenthixol, a D2 antagonist, did not affect RNF11 RNAi or overexpressing flies differently than control. Thus, RNF11 knockdown causes early changes in dopamine neurotransmission, and this is the first work to demonstrate that RNF11 affects both dopamine release and uptake. RNF11 expression decreases in human dopaminergic neurons during PD, and that decrease may be protective by increasing dopamine neurotransmission in the surviving dopaminergic neurons.

Sleep pressure and sleep depth are key regulators of wake and sleep. Current methods of measuring these parameters in Drosophila melanogaster have low temporal resolution and/or require disrupting sleep. Here we report analysis tools for high-resolution, noninvasive measurement of sleep pressure and depth from movement data. Probability of initiating activity, P(Wake), measures sleep depth while probability of ceasing activity, P(Doze), measures sleep pressure. In vivo and computational analyses show that P(Wake) and P(Doze) are largely independent and control the amount of total sleep. We also develop a Hidden Markov Model that allows visualization of distinct sleep/wake substates. These hidden states have a predictable relationship with P(Doze) and P(Wake), suggesting that the methods capture the same behaviors. Importantly, we demonstrate that both the Doze/Wake probabilities and the sleep/wake substates are tied to specific biological processes. These metrics provide greater mechanistic insight into behavior than measuring the amount of sleep alone.

Locomotion is an ancient and fundamental output of the nervous system required for animals to perform many other complex behaviors. Although the formation of motor circuits is known to be under developmental control of transcriptional mechanisms that define the fates and connectivity of the many neurons, glia and muscle constituents of these circuits, relatively little is known about the role of post-transcriptional regulation of locomotor behavior. MicroRNAs have emerged as a potentially rich source of modulators for neural development and function. In order to define the microRNAs required for normal locomotion in Drosophila melanogaster, we utilized a set of transgenic Gal4-dependent competitive inhibitors (microRNA sponges, or miR-SPs) to functionally assess ca. 140 high-confidence Drosophila microRNAs using automated quantitative movement tracking systems followed by multiparametric analysis. Using ubiquitous expression of miR-SP constructs, we identified a large number of microRNAs that modulate aspects of normal baseline adult locomotion. Addition of temperature-dependent Gal80 to identify microRNAs that act during adulthood revealed that the majority of these microRNAs play developmental roles. Comparison of ubiquitous and neural-specific miR-SP expression suggests that most of these microRNAs function within the nervous system. Parallel analyses of spontaneous locomotion in adults and in larvae also reveal that very few of the microRNAs required in the adult overlap with those that control the behavior of larval motor circuits. These screens suggest that a rich regulatory landscape underlies the formation and function of motor circuits and that many of these mechanisms are stage and/or parameter-specific.

ABSTRACT Sleep pressure and sleep depth are key regulators of wake and sleep. Current methods of measuring these parameters in Drosophila melanogaster have low temporal resolution and/or require disrupting sleep. Here we report a novel analysis tool for high-resolution, non-invasive measurement of sleep pressure and depth from movement data. Probability of transitioning to an active state, P(Wake), measures sleep depth while probability of transitioning to an inactive state, P(Doze), measures sleep pressure. In vivo and computational analyses show that P(Wake) and P(Doze) are independent and control the amount of total sleep. Importantly, we demonstrate that these probabilities are tied to specific biological processes. Genetic and environmental perturbations demonstrate that a given amount of sleep can be produced by many combinations of underlying P(Wake) and P(Doze). We show that measuring sleep pressure and depth continuously, without disturbing on-going behavior, provides greater mechanistic insight into behavior than measuring the amount of sleep alone.

In humans and flies, sleep is a highly organized behavior, occurring in discrete episodes that are consolidated at night but have a more fragmented structure during the day. Longer episodes correlate with transitions to deeper sleep states for both species, and sleep fragmentation has been shown to have deleterious outcomes for a large number of physiological processes. In mammals and birds, EEG provides an excellent measure of sleep structure and state. In invertebrates, assessment of sleep structure has relied on measures of episode duration, which can fail to capture important aspects of sleep architecture. Here we model Drosophila sleep as a probabilistic behavior and develop analytical tools to measure transition probabilities and the organization of sleep episodes within a defined analysis window. We show that these tools provide insight into the underlying mechanisms of normal sleep and into how they are altered in pathological conditions. The probability of transition to the wake state, P(Wake), is a major driver of normal sleep quantity and is responsive to dopaminergic tone, suggesting it is a measure of arousal. The probability of transition to the sleep state, P(Doze), is regulated by sleep deprivation and contributes significantly to regulating sleep fragmentation, suggesting it is a measure of sleep drive. Our method for assessing sleep fragmentation adds important information about the organization of sleep bouts that is missing in measures of episode duration alone. Importantly, the ability to measure behavioral drives provides a way to compare the effects of neural circuits and perturbations that play a role in more than one sleep-relevant process.

In humans and flies, sleep is a highly organized behavior, occurring in discrete bouts that are consolidated at night but have a more fragmented structure during the day. Longer episodes correlate with transitions to deeper sleep states for both species, and sleep fragmentation has been shown to have deleterious outcomes for a large number of physiological processes. In mammals and birds, EEG provides an excellent measure of sleep structure and state. In invertebrates, assessment of sleep structure has relied on measures of episode duration, which can fail to capture important aspects of sleep architecture. Here we model Drosophila sleep as a probabilistic behavior and develop analytical tools to measure transition probabilities and the organization of sleep episodes within a defined analysis window. We show that these tools provide insight into the underlying mechanisms of normal sleep and into how they are altered in pathological conditions. The probability of transition to the wake state, P(Wake) is a major driver of normal sleep and responsive to dopaminergic tone, suggesting it is a measure of arousal. Our method for assessing sleep fragmentation adds important information about the organization of sleep bouts that is missing in measures of episode duration alone. Importantly, the ability to obtain a measure of the probability structure underlying sleep in a particular condition or genotype provides a way to compare the state of brain sleep circuits across conditions that utilizes information from all of the many processes that influence sleep.

Increasing ambient temperature reorganizes the Drosophila sleep pattern in a way similar to the human response to heat, increasing daytime sleep while decreasing nighttime sleep. Mutation of core circadian genes blocks the immediate increase in daytime sleep, but not the heat-stimulated decrease in nighttime sleep, when animals are in a light:dark cycle. The ability of per(01) flies to increase daytime sleep in light:dark can be rescued by expression of PER in either LNv or DN1p clock cells and does not require rescue of locomotor rhythms. Prolonged heat exposure engages the homeostat to maintain daytime sleep in the face of nighttime sleep loss. In constant darkness, all genotypes show an immediate decrease in sleep in response to temperature shift during the subjective day, implying that the absence of light input uncovers a clock-independent pro-arousal effect of increased temperature. Interestingly, the effects of temperature on nighttime sleep are blunted in constant darkness and in cry(OUT) mutants in light:dark, suggesting that they are dependent on the presence of light the previous day. In contrast, flies of all genotypes kept in constant light sleep more at all times of day in response to high temperature, indicating that the presence of light can invert the normal nighttime response to increased temperature. The effect of temperature on sleep thus reflects coordinated regulation by light, the homeostat, and components of the clock, allowing animals to reorganize sleep patterns in response to high temperature with rough preservation of the total amount of sleep.

Restless legs syndrome (RLS) is a complex disorder that involves sensory and motor systems. The major pathophysiology of RLS is low iron concentration in the substantia nigra containing the cell bodies of dopamine neurons that project to the striatum, an area that is crucial for modulating movement. People who have RLS often present with normal iron values outside the brain; recent studies implicate several genes are involved in the syndrome. Like most complex diseases, animal models usually do not faithfully capture the full phenotypic spectrum of “disease,” which is a uniquely human construct. Nonetheless, animal models have proven useful in helping to unravel the complex pathophysiology of diseases such as RLS and suggesting novel treatment paradigms. For example, hypothesis-independent genome-wide association studies (GWAS) have identified several genes as increasing the risk for RLS, including BTBD9. Independently, the murine homolog Btbd9 was identified as a candidate gene for iron regulation in the midbrain in mice. The relevance of the phenotype of another of the GWAS identified genes, MEIS1, has also been explored. The role of Btbd9 in iron regulation and RLS-like behaviors has been further evaluated in mice carrying a null mutation of the gene and in fruit flies when the BTBD9 protein is degraded. The BTBD9 and MEIS1 stories originate from human GWAS research, supported by work in a genetic reference population of mice (forward genetics) and further verified in mice, fish flies, and worms. Finally, the role of genetics is further supported by an inbred mouse strain that displays many of the phenotypic characteristics of RLS. The role of animal models of RLS phenotypes is also extended to include periodic limb movements.

Genetic underpinnings for sleep disorders in humans remain poorly identified, investigated and understood. This is due to the inherent complexity of sleep and a disruption of normal sleep parameters in a number of neurological disorders. On the other hand, there have been steady and remarkable developments in the investigation of sleep using model organisms such as Drosophila. These studies have illuminated conserved genetic pathways, neural circuits and intra-cellular signaling modules in the regulation of sleep. Additionally, work in model systems is beginning to clarify the role of the circadian clock and basal sleep need in this process. There have also been initial efforts to directly model sleep disorders in flies in a few instances where a genetic basis has been suspected. Here, we discuss the opportunities and limitations of studying sleep disorders in Drosophila and propose that a greater convergence of basic sleep research in model organisms and human genetics should catalyze better understanding of sleep disorders and generate viable therapeutic options.

The fruit fly Drosophila melanogaster is a diurnal insect active during the day with consolidated sleep at night. Social interactions between pairs of flies have been shown to affect locomotor activity patterns, but effects on locomotion and sleep patterns have not been assessed for larger populations. Here, we use a commercially available locomotor activity monitor (LAM25H) system to record and analyze sleep behavior. Surprisingly, we find that same-sex populations of flies synchronize their sleep/wake activity, resulting in a population sleep pattern, which is similar but not identical to that of isolated individuals. Like individual flies, groups of flies show circadian and homeostatic regulation of sleep, as well as sexual dimorphism in sleep pattern and sensitivity to starvation and a known sleep-disrupting mutation (amnesiac). Populations of flies, however, exhibit distinct sleep characteristics from individuals. Differences in sleep appear to be due to olfaction-dependent social interactions and change with population size and sex ratio. These data support the idea that it is possible to investigate neural mechanisms underlying the effects of population behaviors on sleep by directly looking at a large number of animals in laboratory conditions.

CASK is an evolutionarily conserved scaffolding protein that has roles in many cell types. In Drosophila, loss of the entire CASK gene or just the CASK-β transcript causes a complex set of adult locomotor defects. In this study, we show that the motor initiation component of this phenotype is due to loss of CASK-β in dopaminergic neurons and can be specifically rescued by expression of CASK-β within this subset of neurons. Functional imaging demonstrates that mutation of CASK-β disrupts coupling of neuronal activity to vesicle fusion. Consistent with this, locomotor initiation can be rescued by artificially driving activity in dopaminergic neurons. The molecular mechanism underlying this role of CASK-β in dopaminergic neurons involves interaction with Hsc70-4, a molecular chaperone previously shown to regulate calcium-dependent vesicle fusion. These data suggest that there is a novel CASK-β-dependent regulatory complex in dopaminergic neurons that serves to link activity and neurotransmitter release.

To advance the understanding of sleep regulation, we screened for sleep-promoting cells and identified neurons expressing neuropeptide Y-like short neuropeptide F (sNPF). Sleep induction by sNPF meets all relevant criteria. Rebound sleep following sleep deprivation is reduced by activation of sNPF neurons, and flies experience negative sleep rebound upon cessation of sNPF neuronal stimulation, indicating that sNPF provides an important signal to the sleep homeostat. Only a subset of sNPF-expressing neurons, which includes the small ventrolateral clock neurons, is sleep promoting. Their release of sNPF increases sleep consolidation in part by suppressing the activity of wake-promoting large ventrolateral clock neurons, and suppression of neuronal firing may be the general response to sNPF receptor activation. sNPF acutely increases sleep without altering feeding behavior, which it affects only on a much longer time scale. The profound effect of sNPF on sleep indicates that it is an important sleep-promoting molecule.

Mate selection is critical to ensuring the survival of a species. In the fruit fly, Drosophila melanogaster, genetic and anatomical studies have focused on mate recognition and courtship initiation for decades. This model system has proven to be highly amenable for the study of neural systems controlling the decision making process. However, much less is known about how courtship quality is regulated in a temporally dynamic manner in males and how a female assesses male performance as she makes her decision of whether to accept copulation. Here, we report that the courting male dynamically adjusts the relative proportions of the song components, pulse song or sine song, by assessing female locomotion. Male flies deficient for olfaction failed to perform the locomotion-dependent song modulation, indicating that olfactory cues provide essential information regarding proximity to the target female. Olfactory mutant males also showed lower copulation success when paired with wild-type females, suggesting that the male's ability to temporally control song significantly affects female mating receptivity. These results depict the consecutive inter-sex behavioral decisions, in which a male smells the close proximity of a female as an indication of her increased receptivity and accordingly coordinates his song choice, which then enhances the probability of his successful copulation.

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.