Decoding the Sleep Homeostat Architecture

Sleep is an ancient behavior that is observed in nearly all organisms. Animals typically spend a significant part of their life sleeping, and prolonged sleep deprivation leads to serious physiological changes, signifying the importance of sleep. However, little is known about the regulation of sleep. Sleep is thought to be controlled by two mechanisms: the circadian clock, a biological oscillator that controls daily activity, and the sleep homeostat that tracks organism’s sleep need and controls the duration of sleep. While the circuit of the circadian clock is well studied, almost nothing is known about the structure of the sleep homeostat. Since sleep in flies is very similar to mammalian sleep, we use the fruit fly Drosophila melanogaster as a model organism to understand the homeostat. Since activity and sleep are tightly connected, the first part of this dissertation focuses on activity rhythms. In fruit flies, daily locomotor activity recordings are widely used to study the circadian clock, an endogenous biochemical oscillator with a period of 24 hours that helps to synchronize an organism’s internal processes and behavioral outputs with daily cycles in the environment. Drosophila is a crepuscular animal, meaning it is most active during dusk and dawn. Typical fly locomotor recordings in light/dark conditions show two peaks of activity: a morning peak (M) that happens when the light turns on, and an evening peak (E) that happens when the light turns off. Despite decades of study, a quantitative understanding of the temporal shape of Drosophila locomotor rhythms is missing. Locomotor recordings have been used mostly to extract the period of the circadian clock, leaving these data-rich time series largely underutilized. We propose a mathematical model with four exponential terms and a single period of oscillation that closely reproduces the shape of the locomotor data in both time and frequency domains. In frequency space, our model produces multiple spectral peaks that account for nearly all periodicities seen in fly locomotion power spectra. We show that the proposed single-period waveform is sufficient to explain the position and height of >88 % of spectral peaks in the locomotion of wild-type and circadian mutants of Drosophila. Our results indicate that multiple spectral peaks from fly locomotion are simply harmonics of the circadian period rather than independent ultradian oscillators as previously reported. In the time domain, our model provides a quantitative description of M and E peaks of activity. From timescales of the exponentials, we hypothesize that model rates reflect the activity of neuropeptides that likely transduce signals of the circadian clock and the sleep-wake homeostat to shape behavioral outputs. Next, we focus on the structure of the sleep homeostat in flies. In Drosophila, sleep is typically studied using behavioral metrics, such as average daily sleep amount or average sleep bout duration. The homeostatic sleep regulation is investigated using deprivation experiments, where flies ability to recoup sleep loss is analyzed. These measures have helped to identify multiple substrates and distinct groups of neurons that regulate sleep or wakefulness. Although these findings provide important information about sleep regulation, the functional structure of the homeostat remains largely unknown. Here we propose a new approach to study sleep homeostat in fruit flies. To access the structure of the homeostat, we investigate fly sleep architecture at the level of individual bouts. We find that the distribution of sleep bout lengths in wild type flies is best described by a sum of 4 exponential terms. Analysis of bout distributions in sleep and homeostat mutants show that while flies with altered sleep duration still retain the 4 exponential functional form, ablation of the homeostat leads to the collapse of the multiexponential distribution. These results suggest that the sleep homeostat regulates durations of sleep episodes through 4 independent regulatory pathways. Investigation of sleep bout distribution in clock mutants reveals a link between the circadian clock and the homeostat, giving rise to the possibility that the output of the clock regulates one of the pathways. We further demonstrate that another pathway might be regulated by light and that this interaction is mediated through the blue-sensing photo-pigment CRYPTOCHROME.</p

Decoding the Sleep Homeostat Architecture

Sleep is an ancient behavior that is observed in nearly all organisms. Animals typically spend a significant part of their life sleeping, and prolonged sleep deprivation leads to serious physiological changes, signifying the importance of sleep. However, little is known about the regulation of sleep. Sleep is thought to be controlled by two mechanisms: the circadian clock, a biological oscillator that controls daily activity, and the sleep homeostat that tracks organism’s sleep need and controls the duration of sleep. While the circuit of the circadian clock is well studied, almost nothing is known about the structure of the sleep homeostat. Since sleep in flies is very similar to mammalian sleep, we use the fruit fly Drosophila melanogaster as a model organism to understand the homeostat. Since activity and sleep are tightly connected, the first part of this dissertation focuses on activity rhythms. In fruit flies, daily locomotor activity recordings are widely used to study the circadian clock, an endogenous biochemical oscillator with a period of 24 hours that helps to synchronize an organism’s internal processes and behavioral outputs with daily cycles in the environment. Drosophila is a crepuscular animal, meaning it is most active during dusk and dawn. Typical fly locomotor recordings in light/dark conditions show two peaks of activity: a morning peak (M) that happens when the light turns on, and an evening peak (E) that happens when the light turns off. Despite decades of study, a quantitative understanding of the temporal shape of Drosophila locomotor rhythms is missing. Locomotor recordings have been used mostly to extract the period of the circadian clock, leaving these data-rich time series largely underutilized. We propose a mathematical model with four exponential terms and a single period of oscillation that closely reproduces the shape of the locomotor data in both time and frequency domains. In frequency space, our model produces multiple spectral peaks that account for nearly all periodicities seen in fly locomotion power spectra. We show that the proposed single-period waveform is sufficient to explain the position and height of \u3e88 % of spectral peaks in the locomotion of wild-type and circadian mutants of Drosophila. Our results indicate that multiple spectral peaks from fly locomotion are simply harmonics of the circadian period rather than independent ultradian oscillators as previously reported. In the time domain, our model provides a quantitative description of M and E peaks of activity. From timescales of the exponentials, we hypothesize that model rates reflect the activity of neuropeptides that likely transduce signals of the circadian clock and the sleep-wake homeostat to shape behavioral outputs. Next, we focus on the structure of the sleep homeostat in flies. In Drosophila, sleep is typically studied using behavioral metrics, such as average daily sleep amount or average sleep bout duration. The homeostatic sleep regulation is investigated using deprivation experiments, where flies ability to recoup sleep loss is analyzed. These measures have helped to identify multiple substrates and distinct groups of neurons that regulate sleep or wakefulness. Although these findings provide important information about sleep regulation, the functional structure of the homeostat remains largely unknown. Here we propose a new approach to study sleep homeostat in fruit flies. To access the structure of the homeostat, we investigate fly sleep architecture at the level of individual bouts. We find that the distribution of sleep bout lengths in wild type flies is best described by a sum of 4 exponential terms. Analysis of bout distributions in sleep and homeostat mutants show that while flies with altered sleep duration still retain the 4 exponential functional form, ablation of the homeostat leads to the collapse of the multiexponential distribution. These results suggest that the sleep homeostat regulates durations of sleep episodes through 4 independent regulatory pathways. Investigation of sleep bout distribution in clock mutants reveals a link between the circadian clock and the homeostat, giving rise to the possibility that the output of the clock regulates one of the pathways. We further demonstrate that another pathway might be regulated by light and that this interaction is mediated through the blue-sensing photo-pigment CRYPTOCHROME

A Computational Method to Quantify Fly Circadian Activity

In most animals and plants, circadian clocks orchestrate behavioral and molecular processes and synchronize them to the daily light-dark cycle. Fundamental mechanisms that underlie this temporal control are widely studied using the fruit fly Drosophila melanogaster as a model organism. In flies, the clock is typically studied by analyzing multiday locomotor recording. Such a recording shows a complex bimodal pattern with two peaks of activity: a morning peak that happens around dawn, and an evening peak that happens around dusk. These two peaks together form a waveform that is very different from sinusoidal oscillations observed in clock genes, suggesting that mechanisms in addition to the clock have profound effects in producing the observed patterns in behavioral data. Here we provide instructions on using a recently developed computational method that mathematically describes temporal patterns in fly activity. The method fits activity data with a model waveform that consists of four exponential terms and nine independent parameters that fully describe the shape and size of the morning and evening peaks of activity. The extracted parameters can help elucidate the kinetic mechanisms of substrates that underlie the commonly observed bimodal activity patterns in fly locomotor rhythms

Daytime Colour Preference in Drosophila Depends on the Circadian Clock and TRP Channels

By guiding animals towards food and shelter and repelling them from potentially harmful situations, light discrimination according to colour can confer survival advantages 1,2 . Such colour-dependent behaviour may be experiential or innate. Data on innate colour preference remain controversial in mammals 3 and limited in simpler organisms 4–7 . Here we show that when given a choice among blue, green and dim light, fruit flies exhibit an unexpectedly complex pattern of colour preference that changes with the time of day. Flies show a strong preference for green in the early morning and late afternoon, a reduced green preference at midday and a robust avoidance of blue throughout the day. Genetic manipulations reveal that the peaks in green preference require rhodopsin-based photoreceptors, and are controlled by the circadian clock. The midday reduction in green preference in favour of dim light depends on the Transient Receptor Potential (TRP) channels dTRPA1 and Pyrexia (Pyx), and is also timed by the clock. In contrast, blue avoidance is primarily mediated by class IV multidendritic neurons, requires the TRP channel Painless (Pain) and is independent of the clock. With unexpected roles for several TRP channels in Drosophila colour-specific phototransduction, our results reveal distinct pathways of innate colour preference that coordinate the fly’s behavioural dynamics in ambient light

A mathematical model provides mechanistic links to temporal patterns in Drosophila daily activity

BACKGROUND: Circadian clocks are endogenous biochemical oscillators that control daily behavioral rhythms in all living organisms. In fruit fly, the circadian rhythms are typically studied using power spectra of multiday behavioral recordings. Despite decades of study, a quantitative understanding of the temporal shape of Drosophila locomotor rhythms is missing. Locomotor recordings have been used mostly to extract the period of the circadian clock, leaving these data-rich time series largely underutilized. The power spectra of Drosophila and mouse locomotion often show multiple peaks in addition to the expected at T ~ 24 h. Several theoretical and experimental studies have previously used these data to examine interactions between the circadian and other endogenous rhythms, in some cases, attributing peaks in the T < 24 h regime to ultradian oscillators. However, the analysis of fly locomotion was typically performed without considering the shape of time series, while the shape of the signal plays important role in its power spectrum. To account for locomotion patterns in circadian studies we construct a mathematical model of fly activity. Our model allows careful analysis of the temporal shape of behavioral recordings and can provide important information about biochemical mechanisms that control fly activity. RESULTS: Here we propose a mathematical model with four exponential terms and a single period of oscillation that closely reproduces the shape of the locomotor data in both time and frequency domains. Using our model, we reexamine interactions between the circadian and other endogenous rhythms and show that the proposed single-period waveform is sufficient to explain the position and height of >88 % of spectral peaks in the locomotion of wild-type and circadian mutants of Drosophila. In the time domain, we find the timescales of the exponentials in our model to be ~1.5 h(−1) on average. CONCLUSIONS: Our results indicate that multiple spectral peaks from fly locomotion are simply harmonics of the circadian period rather than independent ultradian oscillators as previously reported. From timescales of the exponentials we hypothesize that model rates reflect activity of the neuropeptides that likely transduce signals of the circadian clock and the sleep–wake homeostat to shape behavioral outputs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12868-016-0248-9) contains supplementary material, which is available to authorized users

MOESM1 of A mathematical model provides mechanistic links to temporal patterns in Drosophila daily activity

Additional file 1. Supplementary material for the main manuscript. The file contains additional data that support our findings, detailed mathematical derivation of the model power spectrum, and mathematical analysis of effects of the Dirichlet kernel and Butterworth filter on power spectra