Dataset Information

Identification of genes associated with resilience/vulnerability to sleep deprivation and starvation in Drosophila.

ABSTRACT:

Background and study objectives

Flies mutant for the canonical clock protein cycle (cyc(01)) exhibit a sleep rebound that is ?10 times larger than wild-type flies and die after only 10 h of sleep deprivation. Surprisingly, when starved, cyc(01) mutants can remain awake for 28 h without demonstrating negative outcomes. Thus, we hypothesized that identifying transcripts that are differentially regulated between waking induced by sleep deprivation and waking induced by starvation would identify genes that underlie the deleterious effects of sleep deprivation and/or protect flies from the negative consequences of waking.

Design

We used partial complementary DNA microarrays to identify transcripts that are differentially expressed between cyc(01) mutants that had been sleep deprived or starved for 7 h. We then used genetics to determine whether disrupting genes involved in lipid metabolism would exhibit alterations in their response to sleep deprivation.

Setting

Laboratory.

Patients or participants

Drosophila melanogaster.

Interventions

Sleep deprivation and starvation.

Measurements and results

We identified 84 genes with transcript levels that were differentially modulated by 7 h of sleep deprivation and starvation in cyc(01) mutants and were confirmed in independent samples using quantitative polymerase chain reaction. Several of these genes were predicted to be lipid metabolism genes, including bubblegum, cueball, and CG4500, which based on our data we have renamed heimdall (hll). Using lipidomics we confirmed that knockdown of hll using RNA interference significantly decreased lipid stores. Importantly, genetically modifying bubblegum, cueball, or hll resulted in sleep rebound alterations following sleep deprivation compared to genetic background controls.

Conclusions

We have identified a set of genes that may confer resilience/vulnerability to sleep deprivation and demonstrate that genes involved in lipid metabolism modulate sleep homeostasis.

SUBMITTER: Thimgan MS

PROVIDER: S-EPMC4402663 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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Publications

Identification of genes associated with resilience/vulnerability to sleep deprivation and starvation in Drosophila.

Thimgan Matthew S MS Seugnet Laurent L Turk John J Shaw Paul J PJ

Sleep 20150501 5

<h4>Background and study objectives</h4>Flies mutant for the canonical clock protein cycle (cyc(01)) exhibit a sleep rebound that is ∼10 times larger than wild-type flies and die after only 10 h of sleep deprivation. Surprisingly, when starved, cyc(01) mutants can remain awake for 28 h without demonstrating negative outcomes. Thus, we hypothesized that identifying transcripts that are differentially regulated between waking induced by sleep deprivation and waking induced by starvation would iden ...[more]

PMID: 25409104

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Project description:To identify measures derived from baseline psychomotor vigilance task (PVT) performance that can reliably predict vulnerability to sleep deprivation.Subjects underwent total sleep deprivation and completed a 10-min PVT every 1-2 h in a controlled laboratory setting. Participants were categorized as vulnerable or resistant to sleep deprivation, based on a median split of lapses that occurred following sleep deprivation. Standard reaction time, drift diffusion model (DDM), and wavelet metrics were derived from PVT response times collected at baseline. A support vector machine model that incorporated maximum relevance and minimum redundancy feature selection and wrapper-based heuristics was used to classify subjects as vulnerable or resistant using rested data.Two academic sleep laboratories.Independent samples of 135 (69 women, age 18 to 25 y), and 45 (3 women, age 22 to 32 y) healthy adults.In both datasets, DDM measures, number of consecutive reaction times that differ by more than 250 ms, and two wavelet features were selected by the model as features predictive of vulnerability to sleep deprivation. Using the best set of features selected in each dataset, classification accuracy was 77% and 82% using fivefold stratified cross-validation, respectively.In both datasets, DDM measures, number of consecutive reaction times that differ by more than 250 ms, and two wavelet features were selected by the model as features predictive of vulnerability to sleep deprivation. Using the best set of features selected in each dataset, classification accuracy was 77% and 82% using fivefold stratified cross-validation, respectively.Despite differences in experimental conditions across studies, drift diffusion model parameters associated reliably with individual differences in performance during total sleep deprivation. These results demonstrate the utility of drift diffusion modeling of baseline performance in estimating vulnerability to psychomotor vigilance decline following sleep deprivation.

Project description:Study objectivesSleep rebound-the increase in sleep that follows sleep deprivation-is a hallmark of homeostatic sleep regulation that is conserved across the animal kingdom. However, both the mechanisms that underlie sleep rebound and its relationship to habitual daily sleep remain unclear. To address this, we developed an efficient thermogenetic method of inducing sleep deprivation in Drosophila that produces a substantial rebound, and applied the newly developed method to assess sleep rebound in a screen of 1,741 mutated lines. We used data generated by this screen to identify lines with reduced sleep rebound following thermogenetic sleep deprivation, and to probe the relationship between habitual sleep amount and sleep following thermogenetic sleep deprivation in Drosophila.MethodsTo develop a thermogenetic method of sleep deprivation suitable for screening, we thermogenetically stimulated different populations of wake-promoting neurons labeled by Gal4 drivers. Sleep rebound following thermogenetically-induced wakefulness varies across the different sets of wake-promoting neurons that were stimulated, from very little to quite substantial. Thermogenetic activation of neurons marked by the c584-Gal4 driver produces both strong sleep loss and a substantial rebound that is more consistent within genotypes than rebound following mechanical or caffeine-induced sleep deprivation. We therefore used this driver to induce sleep deprivation in a screen of 1,741 mutagenized lines generated by the Drosophila Gene Disruption Project. Flies were subjected to 9 h of sleep deprivation during the dark period and released from sleep deprivation 3 h before lights-on. Recovery was measured over the 15 h following sleep deprivation. Following identification of lines with reduced sleep rebound, we characterized baseline sleep and sleep depth before and after sleep deprivation for these hits.ResultsWe identified two lines that consistently exhibit a blunted increase in the duration and depth of sleep after thermogenetic sleep deprivation. Neither of the two genotypes has reduced total baseline sleep. Statistical analysis across all screened lines shows that genotype is a strong predictor of recovery sleep, independent from effects of genotype on baseline sleep.ConclusionsOur data show that rebound sleep following thermogenetic sleep deprivation can be genetically separated from sleep at baseline. This suggests that genetically controlled mechanisms of sleep regulation not manifest under undisturbed conditions contribute to sleep rebound following thermogenetic sleep deprivation.

Dataset Information

Identification of genes associated with resilience/vulnerability to sleep deprivation and starvation in Drosophila.

Background and study objectives

Design

Setting

Patients or participants

Interventions

Measurements and results

Conclusions

Publications

Identification of genes associated with resilience/vulnerability to sleep deprivation and starvation in Drosophila.

Similar Datasets

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