The Interactive Fly
Genes involved in tissue and organ development
During embryogenesis in insects, the axon-scaffold of the brain is built around the embryonic foregut which separates the anlagen of the brain hemispheres. An investigation of this process was carried out in Drosophila and it appears that the major longitudinal and horizontal tracts of the embryonic brain form superficially near the interface between the foregut and embryonic brain hemispheres. Three types of cellular structures are identified that might be involved in tract formation: rows of glial cells at the medial brain margin, cellular bridges composed of neuronal somata and the epithelial surface of the foregut itself.
Courtship is the best-studied behavior in Drosophila melanogaster, and work on its anatomical basis has concentrated mainly on the functional identification of sexually dimorphic sites in the brain. Much less is known of the more expansive, nondimorphic, but nonetheless essential, neural elements subserving male courtship behavior. Sites in the CNS mediating initiation and early steps of male courtship in Drosophila melanogaster were identified by analyzing the behavior of mosaic flies expressing transgenes designed either to suppress neurotransmission or enhance neuronal excitability. Suppression of neurotransmission was accomplished by means of the dominantly acting, temperature-sensitive dynamin mutation shibirets1, whereas enhanced neuronal excitability was produced by means of a novel, dominantly acting, truncated eag potassium channel. By using a new, landmark-based procedure for aligning diverse expression patterns among the various mosaic strains, a comparison of courtship performance and affected brain sites in strains expressing the transgenes identified a cluster of cells in the posterior lateral protocerebrum that exerts reciprocal effects on the initiation of courtship, suppressing it when they are inactivated and enhancing it when they are hyperactivated, indicative of cells that normally play an excitatory, triggering role. A separate group of nearby cells, slightly more anterior in the lateral protocerebrum, was found to inhibit courtship when its activity is enhanced, indicative of an inhibitory role in courtship. It is concluded that a cluster of cells, some excitatory and some inhibitory, in the lateral protocerebrum regulates courtship initiation in Drosophila. These cells are likely to be an integration center for the multiple sensory inputs that trigger male courtship (Broughton, 2004).
Male courtship is elicited by visual and chemosensory cues, either of which is sufficient to initiate courtship behavior in the presence of a virgin female. Projections from the antennal lobes to the lateral protocerebrum, independent of the mushroom bodies, are essential for courtship initiation. These data, which are consistent with the normal initiation of courtship in mushroom body-ablated and mushroom-body impaired males, suggest that courtship is initiated via a mushroom body-independent mechanism (Broughton, 2004).
In the current study, only those GAL4 lines expressed in a common region of the lateral, posterior protocerebrum had a specific effect on courtship initiation. Of particular significance is the reciprocal effect on initation seen in MJ286 and MJ146 when expressing a transgene suppressing neuronal activity as compared with an enhancing transgene. The implication is that these cells exert an activating effect on courtship initiation. This region has previously been implicated sex specifically in male courtship, physiologically in male courtship, and in mediating the plasticity associated with courtship conditioning. As the recipient of many different kinds of sensory projections, it is likely to carry out a variety of integrative functions, as already suggested by a study of its olfactory inputs (Broughton, 2004).
These lateral protocerebral cells in enhancer trap lines MJ286 and MJ146 lie just ventral to the anatomical neighborhood previously identified as the sex-specific focus for courtship initiation: the dorsal posterior brain. In fact, the marking technique used in the earlier studies detected cell bodies whose neuronal processes may well project into the region identified in the current study. The presence in MJ286 of sexually dimorphic function suggests that its dorsal, lateral, and protocerebral cells may even be part of the sex-specific focus for initiation, as well as being required for its physiological realization. The lack of FRUM expression in these cells may reflect the incomplete overlap in expression patterns between FRUM and the male-specific product of another gene in the sex determination cascade, doublesex (DSXM), each of which distinctively influences male courtship behavior. MJ146 does not show sex-specific function, despite its overlap, albeit limited, with FRUM expression (Broughton, 2004).
In contrast, the one case in which the transgene that enhances neuronal activity exerted a suppressing effect on courtship, MJ63, is suggestive of an inhibitory circuit, though it is not associated with the GABA-ergic marker GAD-dsRED. In this instance, the effect was unidirectional: blocking neuronal activity in the same cells had no effect. One interpretation of this result is that this region normally acts in a modulatory fashion and does not act to continuously inhibit courtship behavior. When MJ63 is used to drive expression of a CaMKII inhibitory peptide during the courtship conditioning assay, memory is disrupted and regions defined by this line have been suggested to be involved in enabling memory of the inhibition by the mated female. These data raise the possibility that the inhibitory regions identified by MJ63 may normally act to mediate experience-dependent inhibition of male courtship behavior and the inappropriate activation of them suppresses courtship, thus mimicking the conditioning paradigm (Broughton, 2004).
The opposing effects of c747/UAS-shits1 and c309/UAS-shits1 on wing extension and vibration, are likely to be due to the fact that the broader expression pattern in c747 disrupts inhibitory sites that are intact in c309 and that c309 affects excitatory sites. If this excitation were due to the mushroom body expression in c309, which would then be couteracted by additional expression in c747, it would be consistent with the previous finding of a sex-specific effect of this structure on the performance of wing extension and vibration. The song itself is controlled in the mesothoracic ganglion. Although the mushroom bodies have been suggested to be involved in mate discrimination, a recent finding that expression of UAS-shits1 in the mushroom bodies did not induce male-male courtship behavior shows that mushroom body activity is not required for the recognition of sex-specific pheromones that inhibit male-male courtship. Mushroom bodies have been implicated, however, in modulating other kinds of motor output (Broughton, 2004).
Mapping the neural elements of male courtship is an essential step in understanding the functional circuitry and neural basis for this evolutionarily critical behavior. The fact that courtship consists of a series of stereotypical steps offers great advantages for assigning roles to particular circuits and will facilitate the merging of findings from studies of the sexual dimorphisms underlying courtship with those of genetic perturbations of physiology (Broughton, 2004).
An animal's state of arousal is fundamental to all of its behavior. Arousal is generally ascertained by measures of movement complemented by brain activity recordings, which can provide signatures independently of movement activity. The relationships were examined among movement, arousal state, and local field potential (LFP) activity in the Drosophila brain. This study measured the correlation between local field potentials (LFPs) in the brain and overt movements of the fruit fly during different states of arousal, such as spontaneous daytime waking movement, visual arousal, spontaneous night-time movement, and stimulus-induced movement. The correlation strength between brain LFP activity and movement was found to be dependent on behavioral state and, to some extent, on LFP frequency range. Brain activity and movement are uncoupled during the presentation of visual stimuli and also in the course of overnight experiments in the dark. Epochs of low correlation or uncoupling are predictive of increased arousal thresholds even in moving flies and thus define a distinct state of arousal intermediate between sleep and waking in the fruit fly. These experiments indicate that the relationship between brain LFPs and movement in the fruit fly is dynamic and that the degree of coupling between these two measures of activity defines distinct states of arousal (van Swinderen, 2004).
Sleep in fruit flies shares key characteristics with sleep in all other animals. In Drosophila, sleep is homeostatically regulated and is defined by increased arousal thresholds, and molecular changes correlated with sleep mirror similar changes occurring in mammals. Sleep measures, which include rest/activity data, arousal thresholds, and sleep rebound following deprivation, are most often quantified behaviorally by locomotor activity; an awake fly shows a high probability of walking within a 5 min period. Sleep in Drosophila is accompanied by decreased brain activity (10-100 Hz), as measured by local field potentials (LFPs) in the medial protocerebrum (mpc). In the preparation developed for these studies, sleep is defined by lack of fly movement for periods of more than 5 min and an increased arousal threshold. In this study movement was not monitored in freely moving flies. Instead, flies were tethered by their head and thorax, and movement was monitored by an infrared beam directed across their legs. Alternatively, a wire implanted into their thorax served as a movement detector. By these techniques, gross movements from the fly's wings, legs, and abdomen were monitored continuously to determine sleep states and arousal thresholds, and these were correlated with simultaneous brain activity recordings. A central finding (Nitz, 2002) is that that sleep in Drosophila is correlated with significantly decreased brain LFP activity, and by the same token, that waking is correlated with increased brain LFP activity in the medial protocerebrum (mpc). However, waking LFP activity is not well correlated with fly movement on a short time scale; moment-to-moment correlation between brain activity and movement potentials is insignificant and increases only moderately for longer (5 s) correlation bins. This observation is important because it uncouples the waking levels of brain activity from every movement and suggests that increased brain activity is truly a correlate of waking rather than a correlate of just the movement that accompanies most waking states. Similarly, van Swinderen (2003) showed that 20-30 Hz brain activity in response to visual salience (noticable visual stimulation) can be uncoupled from flight or movement behavior in the fruit fly. Increased arousal, as measured by increased responsiveness to a visual or mechanical stimulus, can therefore be manifested in the fly brain without necessarily being accompanied by gross behavioral changes. Behavior is usually correlated with states of arousal, especially over circadian time scales, but changes in arousal, as evidenced by neural signatures in the brain, can occur without changes in behavior. In the current study, the dynamic relationship between brain activity, movement, and arousal has been explore more closely in Drosophila. This study seeks to define how arousal is manifested over short time scales by examining the ongoing correlation between two parameters central to describing arousal: brain activity and movement (van Swinderen, 2004).
Spontaneous fly movement was monitored in 5 s bins with an electrode implanted into the thorax and brain activity was simultaneously recorded from electrodes inserted 75-100 μm into the medial protocerebrum with a reference electrode in the eye. Dye released from the mpc electrode tip showed that this brain-recording position in adult CS females is level with the base of the mushroom bodies, above the esophagus and in the vicinity of the central complex. The simultaneous recordings of spontaneous movement from the thoracic electrode and brain activity from the mpc revealed a correlation profile for this recording position. The correlation level is not equal for all frequencies (1-100 Hz) of brain activity. The higher frequencies (60-100 Hz) are more strongly correlated to movement than the lower frequencies in the 10-50 Hz range. The very lowest frequency range examined, 1-10 Hz, also shows a stronger correlation to movement than the 10-50 Hz bracket does. Among the lower frequencies, the 20-30 Hz bracket shows the lowest correlation to movement during spontaneous, daytime waking activity at this recording position (van Swinderen, 2004).
In a study of Drosophila LFP responses to visual stimuli, it has been shown that 20-30 Hz brain activity is associated with salience effects evoked by novelty, conditioning, and selective discrimination of visual stimuli (van Swinderen, 2003). In that study, the 20-30 Hz effects were found to be independent of spontaneous, gross movement. Such movement-independent changes in 20-30 Hz activity may account for some of the 10-50 Hz trough in the profile correlating brain activity and movement. Therefore two distinct frequency ranges emerge from these results: the lower range centered around 20-30 Hz (this is less correlated with unstimulated, waking movement but is associated with salience-related arousal), and the higher frequencies, which are more strongly correlated with unstimulated, waking movement but less associated with salience effects (van Swinderen, 2004).
Both visual and movement paradigms were combined in order to test the effect of visually induced arousal (van Swinderen, 2003) on the correlation profile coupling brain activity and ongoing movement. Introducing a visual stimulus (a rotating dark bar layered onto an unchanged lit background) to the fly uncouples brain activity from movement. That this uncoupling was most significant in the higher frequency range is surprising because these higher frequencies are not coupled to the visual response either. Neither low (10-50 Hz) nor high (60-100 Hz) frequencies by themselves change significantly in average power for the duration of the experiment in comparison to the imageless control, and average movement was unchanged as well. Rather, it appears that visual salience (which has a characteristic 20-30 Hz response (van Swinderen, 2003) uncouples most brain LFP activity (at this medial recording position) from ongoing movement activity. The correlation level between movement and brain LFP activity appears to depend on the fly's arousal state as well as on the frequency bracket examined. In the following experiments the relationship between the correlation phenotype and arousal was examined more closely by focusing on movement activity and two LFP frequency ranges: 20-30 Hz because of its association to salience effects and 80-90 Hz as a contrasting range that is more correlated to movement (van Swinderen, 2004).
These correlation studies were all performed for short time periods (200 s, or 40 five-second bins) during the day. In the absence of salient, rotating, visual stimuli, the correlation between brain LFP activity and movement was consistent for these daytime experiments. Whether such consistency persists throughout much longer recording sessions (12 hr) extending through the animal's night time, when characteristic changes in arousal state are endogenously generated, was examined. Epochs without movement more than 5 min long are associated with decreased power for all frequencies in the brain. However, such immobile epochs do not constitute the majority of a tethered fly's night time behavior, in contrast to the behavior of a freely walking fly. In fact, tethered flies move most of the time, even at night, and will be rendered immobile by sleep for only about 20% of the night, not necessarily contiguously. Whether the correlation profile (between movement and brain LFP activity) changed during spontaneous night time movement was investigated (van Swinderen, 2004).
The correlation was analyzed for six flies kept in sealed and humidified chambers during overnight (12 hr) experiments performed in complete darkness. All animals were still alive and moving in the morning after lights were turned back on. Average movement activity during the first daylight hour after the experiments was not significantly different from pre-experiment levels. For each hour of the night, the correlation coefficient between brain activity (20-30 Hz, 80-90 Hz) and movement was calculated from averages of 5 s activity data. In all six flies, the correlation between brain activity and movement decreased during several consecutive hours of the night compared to the first two hours of the night. Both frequency ranges showed a proportionally similar decrease in correlation to movement. These decreases did not necessarily occur during the same contiguous hours in all animals. This 'correlation trough' was maximal in hours 6-7 after dark for four flies and hours 3-4 for two flies. Average correlation levels increased later in the night) to pre-trough levels, before the lights were turned back on (van Swinderen, 2004).
Average hourly movement and average LFP amplitude at both 20-30 and 80-90 Hz also decrease during the night, but the decrease of either is not significant during the respective 'correlation trough' hours compared to the first two hours of the experiments. Thus, the loss of correlation between brain activity and movement cannot be accounted for by any significant changes in the hourly averages of either brain activity or movement. The epoch in which both average hourly movement and LFP power do attenuate significantly, during the last hours of the night, exhibits a correlation between the two statistics that is as high as pre-trough levels (van Swinderen, 2004).
Closer inspection of hourly averages through the night reveals that average movement can increase while average brain activity does not. Indeed, combined data from all six flies show that the variance in 20-30 Hz activity decreases significantly during the respective trough hours compared to the first hours of the night. Variance in 80-90 Hz brain activity was also significantly decreased during the 'correlation trough' hour. In comparison, the variance of movement activity was not significantly decreased during the trough hours compared to hours 1-2. Such unmatched changes in variance may partially explain why a decreased correlation with brain activity is seen during consecutive hours of the night (van Swinderen, 2004).
Because the records also show evidence of sleep, the relationship between the LFP/movement correlation dynamics and epochs of extended immobility embedded throughout the overnight records was investigated. Long bouts of quiescence (>5 min) were immediately preceded by significantly lower levels of correlation to movement (for both 20-30 Hz and 80-90 Hz), compared to the correlation levels seen immediately after the resumption of movement. Brain activity and movement are thus more uncoupled immediately before quiescence as well as during contiguous hours of the night (van Swinderen, 2004).
Sleep is typically associated with immobility, but determining sleep in an animal is also contingent on testing arousal thresholds by measuring behavioral responsiveness to a stimulus. Because the average correlation between movement and brain activity is dynamic during the night and because sleep is preceded by uncoupling, it was questioned whether the loss of correlation between brain and body was similarly associated with altered behavioral responsiveness to a test stimulus, as was shown for sleep (van Swinderen, 2004).
Six additional flies were prepared for testing arousal thresholds throughout the night. Responsiveness to arousing stimuli (measured by increased movement following mechanical taps or light flashes) was analyzed in terms of the preceding level of correlation between movement and brain activity. Using an automated online paradigm, the thoracic channel was periodically scanned for brief epochs (5 s) of immobility before delivering a stimulus, so that all subsequent behavioral responses were compared with this baseline immobility. Responsive animals displayed, on average, a greater correlation between movement and 20-30 Hz brain activity during the 3 min preceding the test stimulus. The level of correlation between 80-90 Hz brain activity and movement was also predictive of responsiveness to the test stimulus. By the same token, unresponsive flies displayed a significantly decreased correlation between brain activity at both frequencies and ongoing movement in the 3 min preceding the test stimulus (van Swinderen, 2004).
As in the overnight 'correlation troughs', correlation level in these arousal experiments was not dependent on the amount of movement displayed by the animal. Different levels of movement showed similar levels of correlation to brain activity when considered irrespective of responsiveness to stimuli. Unresponsiveness to a test stimulus is therefore predicted by a decreased correlation between brain LFPs and movement as well as by prolonged immobility in these tethered preparations. These predictors of arousal level are distinct but complementary. As in Nitz (2002), unresponsiveness was also associated with less average movement in the minutes preceding a test stimulus because these cases included instances of extended (> 5 min) immobility. The predictive value for arousal level of the correlation between movement and LFPs was significant, however, even when these few cases were removed from the analysis (van Swinderen, 2004).
In summary, the correspondence between movement and brain LFP activity in the mpc decreases significantly during overnight recordings, and such uncoupling is characterized by increased arousal thresholds. These results demonstrate that ongoing changes in arousal levels in the fly do not necessarily parallel spontaneous movement activity. Rather, changes in arousal are marked by changes in the coupling dynamics between brain activity and movement (van Swinderen, 2004).
These studies demonstrate, by simultaneously monitoring brain LFPs and gross movement in a tethered Drosophila preparation, that brain activity can be uncoupled from the body activity typically used as the measure of arousal state in nonhuman animals. It was thus possible to examine arousal in terms of the correlation between two relevant yet distinct measures of fly activity. The results suggest that ongoing changes in arousal in the fly can be effectively studied as a function of the degree of coupling between brain LFP activity and movement (van Swinderen, 2004).
In humans and other mammals, most states of heightened arousal (waking, attention), as well as 'paradoxical' (REM) sleep, are accompanied by increased high-frequency (40-80 Hz) field activity in the brain, whereas deep sleep is associated with slow activity. Such brain signatures can be uncorrelated to bodily movement, as in paradoxical sleep and in sleep disorders such as narcolepsy/catalepsy or somnambulism, although most sleep is indeed accompanied by quiescence. In fruit flies, extended immobility also correlates with sleep and associated changes in brain activity. Yet, changes in fly brain LFP activity are not always associated with movement on shorter time scales. Because behavioral changes, evidenced by movement of some kind, are the primary way of ascertaining arousal states in nonhuman animals, the relationship between arousal and movement can be difficult to disentangle. Brain activity may be closer to reflecting ongoing changes in arousal in the fruit fly, and the uncoupling between brain activity and movement appears to be a useful indicator of a change in arousal state (van Swinderen, 2004).
20-30 Hz brain activity plays a crucial role in visually directed arousal (van Swinderen, 2003). In the current study, 20-30 Hz brain activity is less coupled to spontaneous, waking movement than are other frequencies, including the 80-90 Hz range contrasted throughout this study. The higher frequencies (of which 80-90 Hz is just representative) may represent a variety of stimuli coming from the body, whereas the 20-30 Hz signature might represent the fly's version of a 'spotlight.' In support of this idea, the level of correlation between movement and 20-30 Hz brain activity increases up to 80-90 Hz correlation levels during the initial hours of the overnight experiments, immediately after epochs of extended quiescence, and also throughout overnight arousal-testing experiments. This contrasts with the lower correlation (approximately 0.2) found during the day for the 20-30 Hz range in spontaneously moving flies. 20-30 Hz activity can be selectively correlated with visual stimuli (van Swinderen, 2003). For an awake fly in complete darkness at night, when visual (as well as auditory and vibrational) stimuli are lacking, this signal may associate with a different set of stimuli, such as those engendered by the fly's own movement (van Swinderen, 2004).
The most surprising outcome of overnight studies is the finding that fruit flies display a distinct behavioral state intermediate between sleep and waking; this state is defined by heightened arousal thresholds and is characterized by the loss of correlation between ongoing movement and LFP activity. In unperturbed flies during the course of overnight experiments, such loss of correlation is consolidated during several contiguous hours of the night. Additionally, periods of low correlation between brain activity and movement immediately precede epochs of extended quiescence. During sleep, already well characterized in this organism, animals become immobile, and all brain frequencies attenuate to equal extents (Nitz, 2002). The uncoupled state in moving animals may enable subsequent sleep or may itself accomplish certain key sleep functions. Beyond increased arousal thresholds, both behavioral states are also similar in the uniformity of their effects on the different frequency ranges. In the low-arousal, moving state, correlation to movement is decreased proportionally for both 20-30 Hz and 80-90 Hz frequency ranges, and during sleep, both frequency ranges decrease proportionally in terms of overall power. In contrast, in awake flies, frequencies between 1 and 100 Hz are partitioned by salience effects in the 20-30 Hz range (van Swinderen, 2003) and movement effects in the higher frequencies (e.g., 80-90 Hz). When flies are in either of the two states characterized by increased arousal threshold, there is a corresponding decrease in the variance or amount of information in the entire LFP signal (van Swinderen, 2004).
Experiments with visual stimuli show that a form of arousal directed to salient images (van Swinderen, 2003) also uncouples brain activity from movement, even at the higher frequencies not associated with visual salience. This brings up the possibility that during the uncoupled state at night flies may still be partially aroused (as suggested, after all, by their ongoing movement), despite their higher arousal thresholds. This paradox may be partially understood if one considers some common features between sleep and selective attention, both arousal states with behavioral and neural correlates in the fruit fly. Although humans perceive sleep and attention as clearly different states of arousal, both are defined to a certain extent by uncoupling. During sleep, most external stimuli are rendered less accessible, thereby uncoupling the brain from those sensory modalities. During selective attention, an animal may be seen as having partitioned its arousal between a high level directed at the salient stimulus and a low level directed at everything else. The current demonstration of uncoupling between brain activity and movement is consistent with Drosophila's ability to suppress brain responses to simultaneous unattended stimuli (van Swinderen, 2003). Similarly, responses to visual stimuli persist in the optic lobes during sleep, whereas the 20-30 Hz response in the medial brain is attenuated (van Swinderen, 2003). These ideas are extended, in this study, to propose that such uncoupling is a common feature of different arousal states and that fly brain activity might be uncorrelated from movement at night by a similar mechanism as that which suppresses visual stimuli. Altogether, these findings suggest that arousal states in the fly are a function of the degree of coupling within the nervous system and that changes in arousal can be defined more accurately by such criteria in the fly when considered in conjunction with the standard behavioral measures of responsiveness (van Swinderen, 2004).
Arousal in Drosophila, like consciousness in humans, is unlikely to be localized to a unique set of cells in the brain. Rather, arousal probably recruits dynamic networks extending throughout the brain, a phenomenon that may be accessible to a combined genetic and electrophysiological approach in Drosophila (van Swinderen, 2004).
Sleep is one of the few major whole-organ phenomena for which no function and no underlying mechanism have been conclusively demonstrated. Sleep could result from global changes in the brain during wakefulness or it could be regulated by specific loci that recruit the rest of the brain into the electrical and metabolic states characteristic of sleep. This study addresses this issue by exploiting the genetic tractability Drosophila, which exhibits the hallmarks of vertebrate sleep. Large changes in sleep are achieved by spatial and temporal enhancement of cyclic-AMP-dependent protein kinase (PKA) activity specifically in the adult mushroom bodies of Drosophila. Other manipulations of the mushroom bodies, such as electrical silencing, increasing excitation or ablation, also alter sleep. These results link sleep regulation to an anatomical locus known to be involved in learning and memory (Joiner, 2006).
To determine whether specific brain loci regulate sleep, the GAL4/UAS (upstream activating sequence) system was used to express a catalytic subunit of PKA in various regions of the fly brain. PKA was first expressed under the control of the RU486-inducible pan-neuronal driver elavGeneSwitch. Restricting the expression of PKA to adult neurons decreased daily sleep, supporting earlier studies with mutants such as dunce that increase PKA levels, and showing that PKA directly regulates sleep rather than a developmental process that might affect sleep. PKA was expressed under the control of different GAL4 drivers, and the changes in total daily sleep were examined in the different driver/transgene combinations relative to driver/background and background/transgene controls. When both controls were taken into account, the expression of PKA by only two drivers led to changes in sleep that exceeded 2 s.d. These were 201Y, which increased sleep by 75 +/- 3% and 93 +/- 4% respectively, and c309, which decreased sleep by 46 +/- 11% and 43 +/- 14% per day compared with the two sets of controls. Changes in sleep caused by all other GAL4 drivers remained within 1 s.d. of the mean (Joiner, 2006).
Next, whether activity levels during wake periods were affected by the 201Y and c309 drivers was examined. Many GAL4 driver/UAS–PKA lines were hypoactive, but line 201Y had normal waking activity. Similarly, activity normalized to waking time in c309 was not significantly higher in PKA-driven animals than in either control, indicating that c309 was not hyperactive. It is concluded that the sleep phenotypes of animals expressing PKA under control of the 201Y and c309 drivers are not associated with abnormal waking activity. Interestingly, both these drivers are known to be expressed in the mushroom bodies (MBs), a brain region implicated in associative learning (Joiner, 2006).
Given the strong, yet opposite, effects that 201Y and c309 had on sleep, their expression patterns in the fly brain were further characterized by crossing them into animals bearing a UAS transgene for green fluorescent protein (GFP). It was found that 201Y is expressed largely in the γ lobes and the core region of the α/β lobes of the MBs, whereas c309 is expressed in the α/β and γ lobes but not in the core region of the α/β; lobes. This differential expression pattern within the MBs indicates that PKA might affect the regulation of sleep by the MBs in both a positive and a negative fashion by using anatomically distinct classes of neurons. Consistent with this notion of heterogeneous cell types within the MBs, some MB drivers, such as 30Y and 238Y, promoted sleep during the day but inhibited sleep during the night, leading to only marginal overall changes in daily sleep. This effect was not observed with any driver that was expressed exclusively outside the MBs. A small increase in daytime sleep was also frequently produced by the pan-neuronal elavGeneSwitch driver, which decreased overall sleep. The expression patterns of 238Y and 30Y overlap those of 201Y and c309, supporting the idea that 238Y and 30Y are expressed in both sleep-promoting and sleep-inhibiting areas (Joiner, 2006).
To test the hypothesis that PKA expression in MBs regulates adult sleep, the PKA transgene was expressed under the control of an RU486-activatable MB GAL4 driver, P{MB-Switch}. It was confirmed selective expression of this driver in the MBs by coupling it to a GFP reporter, and inducible expression was found in the MBs. Sleep was significantly reduced in response to RU486 in MB-Switch/PKA animals but was unaffected by the drug in control animals harbouring either the driver or the transgene alone. Thus, PKA overexpressed preferentially in specific neurons of adult MBs is sufficient to reduce sleep (Joiner, 2006).
Next sleep structure in the hyposomnolent animals was compared with that of controls. In both MB-Switch/PKA animals and c309/PKA animals, loss of sleep was caused by a shortened sleep bout duration without a concomitant increase in the sleep bout number. The underlying cause of reduced sleep in both sets of animals therefore seems to be impaired sleep need, because the alternative—normal sleep need, but an inability to maintain the sleep state—would be expected to produce an increase in sleep bout number. In contrast, in 201Y sleep bout duration remained unchanged (Joiner, 2006).
It was then asked whether the reduction of sleep in MB-Switch/PKA animals was due to an impaired accrual of a sleep-inducing signal. If this were so, then a hallmark of sleep, homeostatic rebound—sleep that exceeds baseline to compensate for lost sleep—should not occur on relief of induced PKA expression. However, when RU486 was withdrawn after about three days of sleep deprivation, an average rebound of 156 +/- 38 min was observed. This is a robust rebound, comparable to that produced when genetically identical but uninduced flies were submitted to a standard 12 h of mechanical deprivation (137 +/- 26 min). Behavioural rebound was also observed in animals expressing elavGeneSwitch-driven PKA, after withdrawal of RU486, and was accompanied by a decrease in PKA activity in fly heads. Rebound after withdrawal of RU486 indicates that PKA might not prevent the accrual of sleep-promoting signals but might suppress homeostatic output (Joiner, 2006).
To determine whether PKA affects sleep by regulating synaptic output in MB neurons, either of two K+ channels, Kir2.1 or EKO, were inducibly expressed under the control of the MB-Switch driver. Such transgenic expression should suppress action-potential firing by hyperpolarizing neurons and decreasing membrane resistance, thus leading to reduced synaptic transmission. It was found that induction of either Kir2.1 or EKO caused a significant increase in sleep. Because the opposite was observed with PKA expression in the same neurons, it indicates that PKA might decrease sleep by increasing either excitability or synaptic transmission. To address this issue further, a sodium channel (NaChBac), which depolarizes neurons and increases excitability, was inducibly expressed. When expressed under the control of the MB-Switch driver, the sodium channel caused a decrease in sleep, similar to that produced by PKA, confirming that PKA increases the output of these neurons (Joiner, 2006).
The MB-Switch driver is expressed in a subpopulation of MB neurons similar to those labelled by c309, and both drivers had sleep-inhibiting effects. As noted above, this pattern of expression differed from that of other drivers, which had sleep-promoting or bidirectional effects on sleep, thus leading to a proposal that the MBs contain sleep-inhibiting and sleep-promoting neurons. To determine the overall effect of MBs on sleep, they were ablated with hydroxyurea, and sleep and activity were examined in adult flies. An overall increase in activity was observed. However, normalization of this activity to waking time indicates that the phenotype derives less from hyperactivity than from a reduction in sleep. Even so, the reduction in sleep was much less than that seen with other manipulations of the MBs or in short-sleep mutants such as minisleep. This supports the conclusion that MBs exert both positive and negative influences on sleep that are integrated to produce the overt behavioural state. A model takes into account these results; notably the integrator downstream of the MBs promotes activity in the default state. Thus, when MBs are ablated the overall effect is increased wakefulness (Joiner, 2006).
Opposing effects of the c309 and 201Y drivers are also observed in a different behavioural model. They parallel MB-dependent changes in brain activity during the sleep/wake cycle that are associated with salience, a behavioural trait that may correspond to arousal. Consistent with the data was the observation that reducing synaptic transmission using the c309 driver inhibited salience, whereas the 201Y driver in the same type of experiment yielded no change. Increased arousal wouldbe predicted with 201Y, but in those experiments the animals were already awake (Joiner, 2006).
Because MBs receive and transduce considerable sensory, particularly olfactory, input to the fly brain, it is speculate that they promote arousal or sleep by allowing or inhibiting the throughput of sensory information. In addition, given the major function that MBs have in regulating plasticity in the fly brain, it is likely that this is linked to their role in sleep. In mammals, sleep deprivation suppresses the performance of learned tasks, and sleep permits memory consolidation. Sleep and sleep deprivation also differentially affect cortical synaptic plasticity. In Drosophila, MBs participate in the consolidation or retrieval of memories involving olfactory cues, courtship conditioning and context-dependent visual cues by mechanisms that include cAMP signalling. Distinct anatomical regions of the MBs have been shown to be important for at least some forms of memory, as has now also been shown for sleep. Thus, memory and sleep may involve similar molecular pathways (cAMP signalling) and anatomical regulatory loci (MBs) (Joiner, 2006).
Broughton, S. J., Kitamoto, T. and Greenspan, R. J. (2004). Excitatory and inhibitory switches for courtship in the brain of Drosophila melanogaster. Curr. Biol. 14: 538-547. 15062094
Joiner, W. J., Crocker, A., White, B. H. and Sehgal, A. (2006). Sleep in Drosophila is regulated by adult mushroom bodies. Nature 441(7094): 757-60. Medline abstract: 16760980
Nitz, D. A., van Swinderen, B., Tononi, G., and Greenspan, R. J. (2002). Electrophysiological correlates of rest and activity in Drosophila melanogaster. Curr. Biol. 12: 1934-1940. 12445387
van Swinderen, B. and Greenspan, R.J. (2003). Salience modulates 20-30 Hz brain activity in Drosophila. Nat. Neurosci. 6: 579-586. 12717438
van Swinderen, B., Nitz, D. A. and Greenspan, R. J. (2004). Uncoupling of brain activity from movement defines arousal states in Drosophila. Curr. Biol. 14: 81-87. 14738728
Wildemann, B., Reichert, H. and Bicker, G. (1997). Embryonic brain tract formation in Drosophila melanogaster. Dev. Genes Evol. 206: 536-540
Separate sections of The Interactive Fly group genes according to their involvement in glia morphogenesis and axonogenesis.
genes expressed in brain morphogenesis
Genes involved in organ development
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