- Email: [email protected]
Sleep: Helicon Cells Charge the Circuit
Current Biology
Dispatches of the female reproductive tract, including follicular maturation, as suggested for budgerigars already in the 1960s [16], and induce certain behaviors like approach, nest-building or calling. Conversely, these female behaviors might further stimulate testicular development and male behaviors like calling, singing and courting. ‘Good’ synchrony of mates, such as coordinated exchanges of thousands of short soft calls, correlates with reproductive success [17]. Thus, the sexual valence of the decoded femaledirected song depends on the connectivity of the NCC with circuits that control various pair-maintenance and courtship behaviors such as the hypothalamus and/or the dopaminergic reward system, which in turn might modify behavioral control circuits or the hypothalamus–pituitary– gonadal axis controlling the gonadal status and hormonal milieu. Since females’ behavioral responses to male-directed songs increase with estrogens, NCC might respond to female-directed songs only in females with elevated estrogens. Estrogens are known to modify auditory properties of female birds’ forebrain neurons [18]. Alternatively, elevated estrogen levels might be important to amplify the input of NCC to its target areas. The identification of the NCC by Van Ruijssevelt et al. in their recent study opens up the possibility to work out the circuit that links females’ song perception to their reproductive success. In relation to this, it shall be interesting to verify if these neurons decode ‘sexually motivated male’ or ‘sexy’ in other species. A particularly good candidate for study is the canary since females respond behaviorally with a copulation-soliciting display to the hearing of the speedy presentation of particular syllables of a male [19]. Thus, the endogenous properties of the NCC might determine the structure of the males’ sexual signal, the song [20]. REFERENCES 1. Searcy, W.A., and Andersson, M. (1986). Sexual selection and the evolution of song. Annu. Rev. Ecol. Syst. 17, 507–533. 2. Catchpole, C.K., and Slater, P.J.B. (2008). Bird Song: Biological Themes and Variations, 2nd Edition (Cambridge: Cambridge University Press). 3. Van Ruijssevelt, L., Chen, Y., von Eugen, K., Hamaide, J., De Groof, G., Verhoye, M., Gu¨ntu¨rku¨n, O., Woolley, S.C., and Van der
Linden, A. (2018). fMRI reveals a novel region for evaluating acoustic information for mate choice in a female songbird. Curr. Biol. 28, 711–721. 4. Sossinka, R., and Bohner, J. (1980). Song types in the zebra finch Poephila Guttata Castanotis. Z. Tierpsychol. 53, 123–132. 5. Kao, M.H., Doupe, A.J., and Brainard, M.S. (2005). Contributions of an avian basal gangliaforebrain circuit to real-time modulation of song. Nature 433, 638–643. 6. Stepanek, L., and Doupe, A.J. (2010). Activity in a cortical-basal ganglia circuit for song is required for social context-dependent vocal variability. J. Neurophysiol. 104, 2474–2486. 7. Pro¨ve, E. (1974). Der Einfluß von Kastration und Testosteronsubstitution auf das €nnlicher Zebrafinken Sexualverhalten ma (Taeniopygia guttata castanotis Gould). J. Ornithol. 115, 338–347. 8. Bolhuis, J.J., and Gahr, M. (2006). Neural mechanisms of birdsong memory. Nat. Rev. Neurosci. 7, 347–357. 9. Mello, C.V., Velho, T.A., and Pinaud, R. (2004). Song-induced gene expression: a window on song auditory processing and perception. Ann. N.Y. Acad. Sci. 1016, 263–281. 10. Chen, Y.N., Clarke, O., and Woolley, S.C. (2017). Courtship song preferences in female zebra finches are shaped by developmental auditory experience. Proc. Biol. Sci. 284, 2017.0054. 11. Bell, B.A., Phan, M.L., and Vicario, D.S. (2015). Neural responses in songbird forebrain reflect learning rates, acquired salience, and stimulus novelty after auditory discrimination training. J. Neurophysiol. 113, 1480–1492.
12. Beckers, G.J.L., and Gahr, M. (2012). Largescale synchronized activity during vocal deviance detection in the zebra finch auditory forebrain. J. Neurosci. 32, 10594–10608. 13. Elie, J.E., and Theunissen, F.E. (2015). Meaning in the avian auditory cortex: neural representation of communication calls. Eur. J. Neurosci. 41, 546–567. 14. Van Ruijssevelt, L., Van der Kant, A., De Groof, G., and Van der Linden, A. (2013). Current stateof-the-art of auditory functional MRI (fMRI) on zebra finches: Technique and scientific achievements. J. Physiol. 107, 156–169. 15. Riebel, K. (2009). Song and female mate choice in zebra finches: a review. Adv. Stud. Behav. 40, 197–238. 16. Brockway, B.F. (1965). Stimulation of ovarian development and egg-laying by male courtship vocalization in budgerigars (Melopsittacus undulatus). Anim. Behav. 13, 575–578. 17. Gill, L.F., Goymann, W., Ter Maat, A., and Gahr, M. (2015). Patterns of call communication between group-housed zebra finches change during the breeding cycle. eLife 4, e07770. 18. Yoder, K.M., Phan, M.L., Lu, L., and Vicario, D.S. (2015). He hears, she hears: are there sex differences in auditory processing? Dev. Neurobiol. 75, 302–314. 19. Kreutzer, M., and Vallet, E. (1991). Differences in the response of captive female canaries to variation in conspecific and heterospecific songs. Behaviour 117, 106–116. 20. Ryan, M.J., Fox, J.H., Wilczynski, W., and Rand, A.S. (1990). Sexual selection for sensory exploitation in the frog Physalaemus pustulosus. Nature 343, 66–67.
Sleep: Helicon Cells Charge the Circuit Maria E. Yurgel and Alex C. Keene* Department of Biological Sciences, Florida Atlantic University, Jupiter, FL 33458, USA *Correspondence: [email protected] https://doi.org/10.1016/j.cub.2018.02.035
A new study in the fruit fly, Drosophila melanogaster, has identified a neural circuitry that connects regions that control sleep with those that encode sleep pressure. These novel cells, termed helicon cells for their unique morphology, are modulated by sleep control centers and integrate sensory information, providing a novel mechanism for gating of sleep. Sleep is regulated by diverse environmental and physiological processes including sensory stimuli, circadian cues, and metabolic states [1].
While sleep control centers in the brain have been identified in diverse species ranging from nematodes to mammals, our understanding of how sleep gates
Current Biology 28, R306–R327, April 2, 2018 ª 2018 Elsevier Ltd. R317
Current Biology
Dispatches
dFB neurons
Helicon cells Visual inputs
EB neurons Locomotion Current Biology
Figure 1. A neural circuit connecting sleep centers in the fly brain. During wakefulness, the dorsal fan-shaped body (dFB) neurons (red) are inactive, which lifts the inhibition from helicon cells (green), becoming responsive to visual inputs. Helicon cells have excitatory connections to the ellipsoid body (EB, blue) which generates sleep pressure and promotes locomotor activity. The sleep pressure is possibly, then, communicated to dFB neurons either directly or indirectly. Conversely, activation of dFB neurons during sleep inhibits helicon cells by the release of AstA neuropeptide, increasing the threshold for visual stimuli and EB-dependent locomotor activity.
external sensory stimuli and how sleep need is detected are poorly understood [1]. As reported in a recent issue of Neuron, Donlea et al. have identified a neural circuit that connects brain regions that initiate sleep with those that control the homeostatic response to sleep loss [2]. The molecular and neural circuit principles underlying sleep are highly conserved across phyla. The fruit fly, Drosophila melanogaster, provides a powerful model to investigate the mechanisms underlying sleep. With a relatively simple brain consisting of 100,000 neurons and genetic tools that allow for fine-scale manipulation of gene function and neural circuits, a multitude of sleep- and wake-promoting neurons have been identified [3]. In addition, highthroughput behavioral assays, as well as amenability to electrophysiological analysis and functional imaging, uniquely position Drosophila as a model for investigating the neural and genetic basis of sleep regulation. A central behavioral characteristic of sleep is a compensatory rebound following deprivation. This requires the integration of brain regions that control sleep and regions that detect sleep pressure. Previous studies in the fly have identified the dorsal fan-shaped body (dFB) as a sleep-control center. Activation of the dFB robustly induces sleep, while inputs from dopaminergic neurons inhibit dFB activity and promote wakefulness [4–6]. Additionally, a
number of ion channels and signaling molecules regulate sleep by modulating the activity of dFB neurons [7]. A separate region, the ellipsoid body, is critical for generating sleep pressure, and silencing this region blocks rebound following sleep deprivation [8]. However, the connectivity and functional interactions between sleep-promoting dFB neurons and the ellipsoid body remains unclear. To identify signaling mechanisms and downstream targets of dFB neurons, Donlea et al. examined the function of neuromodulators produced within identified sleep circuits. They investigated a subset of dFB neurons that produce the neuropeptide Allatostatin A (AstA). Genetic disruption of AstA or its receptor AstA-R1 reduces sleep duration, revealing a sleep-promoting role for AstA signaling [2]. The identification of AstA, a critical modulator of sleep, allowed for mapping of downstream neurons based on the phenotype and localization of their target receptor. Expression of AstA-R1 localizes to a described population of neurons called ‘helicon cells’, termed such for their shape. While measuring the activity of single neurons in freely moving animals has been a limitation in the sleep field, the authors leverage whole cell patch clamp in a fly mounted on a tracking ball to investigate the function of helicon cells. Donlea et al. found that these cells are responsive to both visual cues and directly regulate locomotion, suggesting
R318 Current Biology 28, R306–R327, April 2, 2018
they integrate sensory inputs with motor responses to regulate sleep. How do helicon cells integrate existing sleep circuits? These neurons are inhibited by AstA secretion from the dFB, and project axons in close proximity to the R2 neurons of the ellipsoid body that detect sleep debt. Indeed, optogenetic stimulation of helicon cells alone was sufficient to induce locomotor activity, resulting in subsequent rebound sleep. These findings reveal a central role for helicon cells in the integration of sleep induction and homeostasis, and provide a model for investigating how neuromodulators contribute to sleep regulation. In addition to sleep debt, sleep is modulated by sensory stimuli. In sleeping animals, a higher threshold of sensory stimulus is required to elicit a response. Conversely, sensory stimuli, including light and smell, inhibit sleep. Whole-cell patch clamp recording of helicon cells in a tethered fly reveal that they are responsive to visual cues, suggesting these neurons may be critical for sensory gating. The identification of this circuit and its modulation by sensory stimuli sets the groundwork for future studies investigating how central brain sleep circuits influence the processing of sensory inputs. Donlea et al. propose that the sleep homeostat functions similarly to a relaxation oscillator: a circuit that repeatedly alternates between two states with a duration that depends on the
Current Biology
Dispatches charging of a capacitor via a resistor. Following the same principles, helicon cells are responsive during wakefulness to visual inputs and have axonal projections to the R2 neurons of the ellipsoid body, which sense sleep pressure and modulate homeostatic sleep rebound following deprivation [2,8]. The circuit is ‘charged up’; sleep pressure is built through the increased ellipsoid body neural firing, which promotes locomotor activity and signals sleep pressure to the dFB neurons. During sleep, activation of dFB neurons inhibits helicon cells by the release of AstA neuropeptide, decreasing responsiveness to visual stimuli and locomotor activity, thus discharging the circuit, and inactivating the dFB (Figure 1). The authors propose that this circuit functions similarly to a water clock, allowing for filling or emptying of a reservoir as sleep debt accumulates or is relieved. While Donlea et al. measure sleep by quantifying periods of immobility, as has been standard for studies in fruit flies, a number of approaches also allow for measuring the physiological changes associated with sleep and wakefulness. For example, measurement of local field potentials reveals characteristic oscillations associated with sleep, and indirect calorimetry reveals that flies, like mammals, reduce metabolic rate while sleeping [9,10]. In addition, quantification of arousal threshold, a behavioral metric of sleep, supports the notion that flies possess forms of light and deep sleep [11]. Assessing the role of helicon cells in sleep-dependent changes in physiology and sleep depth will provide insight into whether independent circuits encode distinct stages of sleep. Constructing models of sleep circuitry in fruit flies and other model systems will allow for addressing whether mechanisms of sleep regulation are conserved throughout the animal kingdom. In mammals, the ventrolateral preoptic nucleus (VLPO) of the hypothalamus is activated during sleep, and forms reciprocal connections with wake-promoting centers [12]. Like the VLPO, dFB neurons are active during sleep, and modulated by sleep need, raising the possibility that these structures are functionally analogous [7,13]. Supporting this notion, the mammalian
ortholog of AstA, Galanin, is expressed in the VLPO and modulates sleep [14]. The findings that dFB and VLPO neurons signal through orthologous neuromodulators provides strong support for conservation of sleep-regulating neural mechanisms from flies to mammals. Neurons regulating sleep and wakefulness are widespread throughout the brain. The identification of connections between the two sleep centers allows for constructing models of sleep regulation, but the picture is far from complete. For example, the connectivity between R2 neurons of the ellipsoid body and the dFB neurons have yet to be identified. In addition, numerous wake-promoting neurons, including dopaminergic and octopaminergic populations, have been identified in the fly [1]. Further, sleep timing and duration are regulated by circadian pacemaker neuron [15]. A comprehensive model of sleep regulation will require the identification of EB–dFB connectivity and the understanding of how alternative sleep circuits are integrated within the R2–dFB– helicon circuit. While the R2–dFB–helicon circuit is likely to modulate the rebound sleep following deprivation, much less is known about other factors that regulate sleep. For example, sleep loss following sexual arousal does not result in a rebound, suggesting arousal overrides sleep loss [16]. In addition, sleep is modulated by many factors including diet, aging, and social experience [17–19]. Understanding how these factors modulate the function of the R2–dFB–helicon circuit will improve our understanding of context-dependent regulation of sleep. REFERENCES
regulates sleep and arousal in Drosophila. Nat. Neurosci. 15, 1516–1523. 5. Liu, Q., Liu, S., Kodama, L., Driscoll, M.R., and Wu, M.N. (2012). Two dopaminergic neurons signal to the dorsal fan-shaped body to promote wakefulness in Drosophila. Curr. Biol. 22, 2114–2123. 6. Donlea, J.M., Thimgan, M.S., Suzuki, Y., Gottschalk, L., and Shaw, P.J. (2011). Inducing sleep by remote control facilitates memory consolidation in Drosophila. Science 332, 1571–1576. 7. Pimentel, D., Donlea, J.M., Talbot, C.B., Song, S.M., Thurston, A.J.F., and Miesenbo¨ck, G. (2016). Operation of a homeostatic sleep switch. Nature 536, 333–337. 8. Liu, S., Liu, Q., Tabuchi, M., and Wu, M.N. (2016). Sleep drive is encoded by neural plastic changes in a dedicated circuit. Cell 165, 1347– 1360. 9. Yap, M.H.W., Grabowska, M.J., Rohrscheib, C., Jeans, R., Troup, M., Paulk, A.C., van Alphen, B., Shaw, P.J., and van Swinderen, B. (2017). Oscillatory brain activity in spontaneous and induced sleep stages in flies. Nat. Commun. 8, 1815. 10. Stahl, B., Slocumb, M., Chaitin, H., DiAngelo, J., and Keene, A. (2017). Sleep-dependent modulation of metabolic rate in Drosophila. Sleep 40, https://doi.org/10.1093/sleep/ zsx084. 11. van Alphen, B., Yap, M.H.W., Kirszenblat, L., Kottler, B., and van Swinderen, B. (2013). A dynamic deep sleep stage in Drosophila. J. Neurosci. 33, 6917–6927. 12. Saper, C.B., Fuller, P.M., Pedersen, N.P., Lu, J., and Scammell, T.E. (2010). Sleep state switching. Neuron 68, 1023–1042. 13. Donlea, J.M., Pimentel, D., and Miesenbo¨ck, G. (2014). Neuronal machinery of sleep homeostasis in Drosophila. Neuron 81, 860–872. 14. Gaus, S.E., Strecker, R.E., Tate, B.A., Parker, R.A., and Saper, C.B. (2002). Ventrolateral preoptic nucleus contains sleep-active, galaninergic neurons in multiple mammalian species. Neuroscience 115, 285–294. 15. Griffith, L.C. (2013). Neuromodulatory control of sleep in Drosophila melanogaster: Integration of competing and complementary behaviors. Curr. Opin. Neurobiol. 23, 819–823.
1. Joiner, W.J. (2016). Unraveling the evolutionary determinants of sleep. Curr. Biol. 26, R1073–R1087.
16. Beckwith, E., Geissmann, Q., French, A., and Gilestro, G. (2017). Regulation of sleep homeostasis by sexual arousal. eLife 6, e27445.
2. Donlea, J.M., Pimentel, D., Talbot, C.B., Kempf, A., Omoto, J.J., Hartenstein, V., and Miesenbo¨ck, G. (2018). Recurrent circuitry for balancing sleep need and sleep. Neuron 97, 378–389.
17. Murakami, K., Yurgel, M.E., Stahl, B.A., Masek, P., Mehta, A., Heidker, R., Bollinger, W., Gingras, R.M., Kim, Y.J., Ja, W.W., et al. (2016). Translin is required for metabolic regulation of sleep. Curr. Biol. 26, 972–980.
3. Venken, K.J.T., Simpson, J.H., and Bellen, H.J. (2011). Genetic manipulation of genes and cells in the nervous system of the fruit fly. Neuron 72, 202–230.
18. Koh, K., Evans, J.M., Hendricks, J.C., and Sehgal, A. (2006). A Drosophila model for ageassociated changes in sleep:wake cycles. Proc. Natl. Acad. Sci. USA 103, 13843–13847.
4. Ueno, T., Tomita, J., Tanimoto, H., Endo, K., Ito, K., Kume, S., and Kume, K. (2012). Identification of a dopamine pathway that
19. Ganguly-Fitzgerald, I. (2006). Waking experience affects sleep need in Drosophila. Science 313, 1775–1781.
Current Biology 28, R306–R327, April 2, 2018 R319
Dispatches of the female reproductive tract, including follicular maturation, as suggested for budgerigars already in the 1960s [16], and induce certain behaviors like approach, nest-building or calling. Conversely, these female behaviors might further stimulate testicular development and male behaviors like calling, singing and courting. ‘Good’ synchrony of mates, such as coordinated exchanges of thousands of short soft calls, correlates with reproductive success [17]. Thus, the sexual valence of the decoded femaledirected song depends on the connectivity of the NCC with circuits that control various pair-maintenance and courtship behaviors such as the hypothalamus and/or the dopaminergic reward system, which in turn might modify behavioral control circuits or the hypothalamus–pituitary– gonadal axis controlling the gonadal status and hormonal milieu. Since females’ behavioral responses to male-directed songs increase with estrogens, NCC might respond to female-directed songs only in females with elevated estrogens. Estrogens are known to modify auditory properties of female birds’ forebrain neurons [18]. Alternatively, elevated estrogen levels might be important to amplify the input of NCC to its target areas. The identification of the NCC by Van Ruijssevelt et al. in their recent study opens up the possibility to work out the circuit that links females’ song perception to their reproductive success. In relation to this, it shall be interesting to verify if these neurons decode ‘sexually motivated male’ or ‘sexy’ in other species. A particularly good candidate for study is the canary since females respond behaviorally with a copulation-soliciting display to the hearing of the speedy presentation of particular syllables of a male [19]. Thus, the endogenous properties of the NCC might determine the structure of the males’ sexual signal, the song [20]. REFERENCES 1. Searcy, W.A., and Andersson, M. (1986). Sexual selection and the evolution of song. Annu. Rev. Ecol. Syst. 17, 507–533. 2. Catchpole, C.K., and Slater, P.J.B. (2008). Bird Song: Biological Themes and Variations, 2nd Edition (Cambridge: Cambridge University Press). 3. Van Ruijssevelt, L., Chen, Y., von Eugen, K., Hamaide, J., De Groof, G., Verhoye, M., Gu¨ntu¨rku¨n, O., Woolley, S.C., and Van der
Linden, A. (2018). fMRI reveals a novel region for evaluating acoustic information for mate choice in a female songbird. Curr. Biol. 28, 711–721. 4. Sossinka, R., and Bohner, J. (1980). Song types in the zebra finch Poephila Guttata Castanotis. Z. Tierpsychol. 53, 123–132. 5. Kao, M.H., Doupe, A.J., and Brainard, M.S. (2005). Contributions of an avian basal gangliaforebrain circuit to real-time modulation of song. Nature 433, 638–643. 6. Stepanek, L., and Doupe, A.J. (2010). Activity in a cortical-basal ganglia circuit for song is required for social context-dependent vocal variability. J. Neurophysiol. 104, 2474–2486. 7. Pro¨ve, E. (1974). Der Einfluß von Kastration und Testosteronsubstitution auf das €nnlicher Zebrafinken Sexualverhalten ma (Taeniopygia guttata castanotis Gould). J. Ornithol. 115, 338–347. 8. Bolhuis, J.J., and Gahr, M. (2006). Neural mechanisms of birdsong memory. Nat. Rev. Neurosci. 7, 347–357. 9. Mello, C.V., Velho, T.A., and Pinaud, R. (2004). Song-induced gene expression: a window on song auditory processing and perception. Ann. N.Y. Acad. Sci. 1016, 263–281. 10. Chen, Y.N., Clarke, O., and Woolley, S.C. (2017). Courtship song preferences in female zebra finches are shaped by developmental auditory experience. Proc. Biol. Sci. 284, 2017.0054. 11. Bell, B.A., Phan, M.L., and Vicario, D.S. (2015). Neural responses in songbird forebrain reflect learning rates, acquired salience, and stimulus novelty after auditory discrimination training. J. Neurophysiol. 113, 1480–1492.
12. Beckers, G.J.L., and Gahr, M. (2012). Largescale synchronized activity during vocal deviance detection in the zebra finch auditory forebrain. J. Neurosci. 32, 10594–10608. 13. Elie, J.E., and Theunissen, F.E. (2015). Meaning in the avian auditory cortex: neural representation of communication calls. Eur. J. Neurosci. 41, 546–567. 14. Van Ruijssevelt, L., Van der Kant, A., De Groof, G., and Van der Linden, A. (2013). Current stateof-the-art of auditory functional MRI (fMRI) on zebra finches: Technique and scientific achievements. J. Physiol. 107, 156–169. 15. Riebel, K. (2009). Song and female mate choice in zebra finches: a review. Adv. Stud. Behav. 40, 197–238. 16. Brockway, B.F. (1965). Stimulation of ovarian development and egg-laying by male courtship vocalization in budgerigars (Melopsittacus undulatus). Anim. Behav. 13, 575–578. 17. Gill, L.F., Goymann, W., Ter Maat, A., and Gahr, M. (2015). Patterns of call communication between group-housed zebra finches change during the breeding cycle. eLife 4, e07770. 18. Yoder, K.M., Phan, M.L., Lu, L., and Vicario, D.S. (2015). He hears, she hears: are there sex differences in auditory processing? Dev. Neurobiol. 75, 302–314. 19. Kreutzer, M., and Vallet, E. (1991). Differences in the response of captive female canaries to variation in conspecific and heterospecific songs. Behaviour 117, 106–116. 20. Ryan, M.J., Fox, J.H., Wilczynski, W., and Rand, A.S. (1990). Sexual selection for sensory exploitation in the frog Physalaemus pustulosus. Nature 343, 66–67.
Sleep: Helicon Cells Charge the Circuit Maria E. Yurgel and Alex C. Keene* Department of Biological Sciences, Florida Atlantic University, Jupiter, FL 33458, USA *Correspondence: [email protected] https://doi.org/10.1016/j.cub.2018.02.035
A new study in the fruit fly, Drosophila melanogaster, has identified a neural circuitry that connects regions that control sleep with those that encode sleep pressure. These novel cells, termed helicon cells for their unique morphology, are modulated by sleep control centers and integrate sensory information, providing a novel mechanism for gating of sleep. Sleep is regulated by diverse environmental and physiological processes including sensory stimuli, circadian cues, and metabolic states [1].
While sleep control centers in the brain have been identified in diverse species ranging from nematodes to mammals, our understanding of how sleep gates
Current Biology 28, R306–R327, April 2, 2018 ª 2018 Elsevier Ltd. R317
Current Biology
Dispatches
dFB neurons
Helicon cells Visual inputs
EB neurons Locomotion Current Biology
Figure 1. A neural circuit connecting sleep centers in the fly brain. During wakefulness, the dorsal fan-shaped body (dFB) neurons (red) are inactive, which lifts the inhibition from helicon cells (green), becoming responsive to visual inputs. Helicon cells have excitatory connections to the ellipsoid body (EB, blue) which generates sleep pressure and promotes locomotor activity. The sleep pressure is possibly, then, communicated to dFB neurons either directly or indirectly. Conversely, activation of dFB neurons during sleep inhibits helicon cells by the release of AstA neuropeptide, increasing the threshold for visual stimuli and EB-dependent locomotor activity.
external sensory stimuli and how sleep need is detected are poorly understood [1]. As reported in a recent issue of Neuron, Donlea et al. have identified a neural circuit that connects brain regions that initiate sleep with those that control the homeostatic response to sleep loss [2]. The molecular and neural circuit principles underlying sleep are highly conserved across phyla. The fruit fly, Drosophila melanogaster, provides a powerful model to investigate the mechanisms underlying sleep. With a relatively simple brain consisting of 100,000 neurons and genetic tools that allow for fine-scale manipulation of gene function and neural circuits, a multitude of sleep- and wake-promoting neurons have been identified [3]. In addition, highthroughput behavioral assays, as well as amenability to electrophysiological analysis and functional imaging, uniquely position Drosophila as a model for investigating the neural and genetic basis of sleep regulation. A central behavioral characteristic of sleep is a compensatory rebound following deprivation. This requires the integration of brain regions that control sleep and regions that detect sleep pressure. Previous studies in the fly have identified the dorsal fan-shaped body (dFB) as a sleep-control center. Activation of the dFB robustly induces sleep, while inputs from dopaminergic neurons inhibit dFB activity and promote wakefulness [4–6]. Additionally, a
number of ion channels and signaling molecules regulate sleep by modulating the activity of dFB neurons [7]. A separate region, the ellipsoid body, is critical for generating sleep pressure, and silencing this region blocks rebound following sleep deprivation [8]. However, the connectivity and functional interactions between sleep-promoting dFB neurons and the ellipsoid body remains unclear. To identify signaling mechanisms and downstream targets of dFB neurons, Donlea et al. examined the function of neuromodulators produced within identified sleep circuits. They investigated a subset of dFB neurons that produce the neuropeptide Allatostatin A (AstA). Genetic disruption of AstA or its receptor AstA-R1 reduces sleep duration, revealing a sleep-promoting role for AstA signaling [2]. The identification of AstA, a critical modulator of sleep, allowed for mapping of downstream neurons based on the phenotype and localization of their target receptor. Expression of AstA-R1 localizes to a described population of neurons called ‘helicon cells’, termed such for their shape. While measuring the activity of single neurons in freely moving animals has been a limitation in the sleep field, the authors leverage whole cell patch clamp in a fly mounted on a tracking ball to investigate the function of helicon cells. Donlea et al. found that these cells are responsive to both visual cues and directly regulate locomotion, suggesting
R318 Current Biology 28, R306–R327, April 2, 2018
they integrate sensory inputs with motor responses to regulate sleep. How do helicon cells integrate existing sleep circuits? These neurons are inhibited by AstA secretion from the dFB, and project axons in close proximity to the R2 neurons of the ellipsoid body that detect sleep debt. Indeed, optogenetic stimulation of helicon cells alone was sufficient to induce locomotor activity, resulting in subsequent rebound sleep. These findings reveal a central role for helicon cells in the integration of sleep induction and homeostasis, and provide a model for investigating how neuromodulators contribute to sleep regulation. In addition to sleep debt, sleep is modulated by sensory stimuli. In sleeping animals, a higher threshold of sensory stimulus is required to elicit a response. Conversely, sensory stimuli, including light and smell, inhibit sleep. Whole-cell patch clamp recording of helicon cells in a tethered fly reveal that they are responsive to visual cues, suggesting these neurons may be critical for sensory gating. The identification of this circuit and its modulation by sensory stimuli sets the groundwork for future studies investigating how central brain sleep circuits influence the processing of sensory inputs. Donlea et al. propose that the sleep homeostat functions similarly to a relaxation oscillator: a circuit that repeatedly alternates between two states with a duration that depends on the
Current Biology
Dispatches charging of a capacitor via a resistor. Following the same principles, helicon cells are responsive during wakefulness to visual inputs and have axonal projections to the R2 neurons of the ellipsoid body, which sense sleep pressure and modulate homeostatic sleep rebound following deprivation [2,8]. The circuit is ‘charged up’; sleep pressure is built through the increased ellipsoid body neural firing, which promotes locomotor activity and signals sleep pressure to the dFB neurons. During sleep, activation of dFB neurons inhibits helicon cells by the release of AstA neuropeptide, decreasing responsiveness to visual stimuli and locomotor activity, thus discharging the circuit, and inactivating the dFB (Figure 1). The authors propose that this circuit functions similarly to a water clock, allowing for filling or emptying of a reservoir as sleep debt accumulates or is relieved. While Donlea et al. measure sleep by quantifying periods of immobility, as has been standard for studies in fruit flies, a number of approaches also allow for measuring the physiological changes associated with sleep and wakefulness. For example, measurement of local field potentials reveals characteristic oscillations associated with sleep, and indirect calorimetry reveals that flies, like mammals, reduce metabolic rate while sleeping [9,10]. In addition, quantification of arousal threshold, a behavioral metric of sleep, supports the notion that flies possess forms of light and deep sleep [11]. Assessing the role of helicon cells in sleep-dependent changes in physiology and sleep depth will provide insight into whether independent circuits encode distinct stages of sleep. Constructing models of sleep circuitry in fruit flies and other model systems will allow for addressing whether mechanisms of sleep regulation are conserved throughout the animal kingdom. In mammals, the ventrolateral preoptic nucleus (VLPO) of the hypothalamus is activated during sleep, and forms reciprocal connections with wake-promoting centers [12]. Like the VLPO, dFB neurons are active during sleep, and modulated by sleep need, raising the possibility that these structures are functionally analogous [7,13]. Supporting this notion, the mammalian
ortholog of AstA, Galanin, is expressed in the VLPO and modulates sleep [14]. The findings that dFB and VLPO neurons signal through orthologous neuromodulators provides strong support for conservation of sleep-regulating neural mechanisms from flies to mammals. Neurons regulating sleep and wakefulness are widespread throughout the brain. The identification of connections between the two sleep centers allows for constructing models of sleep regulation, but the picture is far from complete. For example, the connectivity between R2 neurons of the ellipsoid body and the dFB neurons have yet to be identified. In addition, numerous wake-promoting neurons, including dopaminergic and octopaminergic populations, have been identified in the fly [1]. Further, sleep timing and duration are regulated by circadian pacemaker neuron [15]. A comprehensive model of sleep regulation will require the identification of EB–dFB connectivity and the understanding of how alternative sleep circuits are integrated within the R2–dFB– helicon circuit. While the R2–dFB–helicon circuit is likely to modulate the rebound sleep following deprivation, much less is known about other factors that regulate sleep. For example, sleep loss following sexual arousal does not result in a rebound, suggesting arousal overrides sleep loss [16]. In addition, sleep is modulated by many factors including diet, aging, and social experience [17–19]. Understanding how these factors modulate the function of the R2–dFB–helicon circuit will improve our understanding of context-dependent regulation of sleep. REFERENCES
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