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Sleep-Dependent Modulation of Metabolic Rate in Drosophila.

ABSTRACT: Study Objectives:Dysregulation of sleep is associated with metabolic diseases, and metabolic rate (MR) is acutely regulated by sleep-wake behavior. In humans and rodent models, sleep loss is associated with obesity, reduced metabolic rate, and negative energy balance, yet little is known about the neural mechanisms governing interactions between sleep and metabolism. Methods:We have developed a system to simultaneously measure sleep and MR in individual Drosophila, allowing for interrogation of neural systems governing interactions between sleep and metabolic rate. Results:Like mammals, MR in flies is reduced during sleep and increased during sleep deprivation suggesting sleep-dependent regulation of MR is conserved across phyla. The reduction of MR during sleep is not simply a consequence of inactivity because MR is reduced ~30 minutes following the onset of sleep, raising the possibility that CO2 production provides a metric to distinguish different sleep states in the fruit fly. To examine the relationship between sleep and metabolism, we determined basal and sleep-dependent changes in MR is reduced in starved flies, suggesting that starvation inhibits normal sleep-associated effects on metabolic rate. Further, translin mutant flies that fail to suppress sleep during starvation demonstrate a lower basal metabolic rate, but this rate was further reduced in response to starvation, revealing that regulation of starvation-induced changes in MR and sleep duration are genetically distinct. Conclusions:Therefore, this system provides the unique ability to simultaneously measure sleep and oxidative metabolism, providing novel insight into the physiological changes associated with sleep and wakefulness in the fruit fly.

SUBMITTER: Stahl BA

PROVIDER: S-EPMC6074949 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Objective: Measurements of heart rate variability (HRV) during sleep have become increasingly popular as sleep could provide an optimal state for HRV assessments. While sleep stages have been reported to affect HRV, the effect of sleep stages on the variance of HRV parameters were hardly investigated. We aimed to assess the variance of HRV parameters during the different sleep stages. Further, we tested the accuracy of an algorithm using HRV to identify a 5-min segment within an episode of slow wave sleep (SWS, deep sleep). Methods: Polysomnographic (PSG) sleep recordings of 3 nights of 15 healthy young males were analyzed. Sleep was scored according to conventional criteria. HRV parameters of consecutive 5-min segments were analyzed within the different sleep stages. The total variance of HRV parameters was partitioned into between-subjects variance, between-nights variance, and between-segments variance and compared between the different sleep stages. Intra-class correlation coefficients of all HRV parameters were calculated for all sleep stages. To identify an SWS segment based on HRV, Pearson correlation coefficients of consecutive R-R intervals (rRR) of moving 5-min windows (20-s steps). The linear trend was removed from the rRR time series and the first segment with rRR values 0.1 units below the mean rRR for at least 10 min was identified. A 5-min segment was placed in the middle of such an identified segment and the corresponding sleep stage was used to assess the accuracy of the algorithm. Results: Good reproducibility within and across nights was found for heart rate in all sleep stages and for high frequency (HF) power in SWS. Reproducibility of low frequency (LF) power and of LF/HF was poor in all sleep stages. Of all the 5-min segments selected based on HRV data, 87% were accurately located within SWS. Conclusions: SWS, a stable state that, in contrast to waking, is unaffected by internal and external factors, is a reproducible state that allows reliable determination of heart rate, and HF power, and can satisfactorily be detected based on R-R intervals, without the need of full PSG. Sleep may not be an optimal condition to assess LF power and LF/HF power ratio.

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Sleep-Dependent Modulation of Metabolic Rate in Drosophila.

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