How do we know we are tired and that it is time to sleep, and why can we go without sleep when we are excited? Usually, after a sleepless night, we make up for it the following day by taking a nap (if possible) or by going to bed earlier – a process referred to as rebound sleep. According to a long-standing model, this need to catch up on our sleep is modulated by two distinct mechanisms: the sleep homeostat, which controls how much we sleep, and the circadian clock, which dictates when we sleep (Borbély, 1982). While this model lays the foundation for understanding how sleep is regulated, it neglects a variety of other social, emotional and environmental factors that impact on sleep.
Sleep is highly conserved throughout the animal kingdom at both the genetic and the functional level. Some species are also known to skip sleep in favor of migration, mating or other social interactions. Flies, for example, can forgo sleep when they are exposed to mechanical stimulation or social interactions, which makes them a popular model for studying the regulation of sleep (Gilestro et al., 2009). Now, in eLife, Giorgio Gilestro of Imperial College and co-workers – Esteban Beckwith as first author, Quentin Geissmann and Alice French – report new insights into how sexual arousal in flies affects their need for sleep (Beckwith et al., 2017).
To examine how 'social sleep deprivation' affects rebound sleep, Beckwith et al. exposed the flies to different social scenarios. First, they placed a male fly into an arena that already contained a male resident. The presence of another male caused the resident to lose sleep, but he caught up via rebound sleep once the male intruder had been removed (Figure 1). The resident also lost sleep when a receptive female fly was introduced, but he did not catch up via rebound sleep once the female was removed. This suggests that the sexual arousal induced by the female fly was sufficient to override any need for the male to catch up after a sleepless night.
What allows sexual arousal to overcome rebound sleep? Fly courtship is a multisensory experience that involves visual, tactile, acoustic and pheromonal cues. Beckwith et al. found that exposing male flies to female pheromones, or transferring them into tubes that previously contained a female fly, was sufficient to suppress rebound sleep.
To get to the bottom of why sexually aroused males did not catch up on lost sleep, Beckwith et al. looked deeper into the fly brain. Previous research has shown that male flies sense certain pheromones through neurons (and their receptor proteins) on their forelegs – this is why male flies repeatedly tap female flies with their legs during courtship. Beckwith et al. discovered that when males lacked the pheromone receptor pickpocket 23 on these leg neurons, they did not notice the pheromones and rebound sleep occurred.
Moreover, the results showed that a specific cluster of neurons, called P1 neurons, are critical for courtship-suppressed sleep. When these neurons were stimulated, rebound sleep was inhibited. Taken together, these findings suggest that pickpocket 23 neurons detect pheromones and then activate P1 neurons which, in turn, suppress sleep and prevent rebound sleep.
To better understand the mechanisms underlying the sexual arousal vs. sleep trade-off, we need to identify how pheromone circuits interface with sleep centers in the brain to modulate behavior. Two other recent papers shed light on this issue. In males, P1 neurons are activated by contact with females, and Chen et al. have shown that these neurons are connected with a set of wake-promoting neurons (Chen et al., 2017). In a separate study, Machado et al. discovered another pair of wake-promoting neurons that directly modulate courtship circuits (Machado et al., 2017).
Despite this progress, two central questions persist: how is the need for sleep sensed, and is sleep loss centrally integrated within the brain? So far, researchers have discovered many different neuronal circuits for sleep homeostasis within the fly brain, which could be directly or indirectly affected by sexual arousal and result in suppressed rebound sleep (Liu et al., 2016; Pimentel et al., 2016; Seidner et al., 2015). Identifying the neural circuits that regulate sleep and courtship will serve as a framework for determining the molecular sensors that know when we need to sleep.
Together, these findings highlight the integrated nature of sleep, and the way it is affected by the internal clock, the need for sleep and external factors, such as arousal. However, there is much that we do not know: for example, how do other external influences, such as stress, excitement or caffeine consumption, affect sleep loss and rebound sleep? Answering these questions will shed light on the basic functions of sleep.
Kinase inhibitors are successful therapeutics in the treatment of cancers and autoimmune diseases and are useful tools in biomedical research. However, the high sequence and structural conservation of the catalytic kinase domain complicates the development of selective kinase inhibitors. Inhibition of off-target kinases makes it difficult to study the mechanism of inhibitors in biological systems. Current efforts focus on the development of inhibitors with improved selectivity. Here, we present an alternative solution to this problem by combining inhibitors with divergent off-target effects. We develop a multicompound-multitarget scoring (MMS) method that combines inhibitors to maximize target inhibition and to minimize off-target inhibition. Additionally, this framework enables optimization of inhibitor combinations for multiple on-targets. Using MMS with published kinase inhibitor datasets we determine potent inhibitor combinations for target kinases with better selectivity than the most selective single inhibitor and validate the predicted effect and selectivity of inhibitor combinations using in vitro and in cellulo techniques. MMS greatly enhances selectivity in rational multitargeting applications. The MMS framework is generalizable to other non-kinase biological targets where compound selectivity is a challenge and diverse compound libraries are available.
Diabetes is caused by the inability of electrically coupled, functionally heterogeneous -cells within the pancreatic islet to provide adequate insulin secretion. Functional networks have been used to represent synchronized oscillatory [Ca2+] dynamics and to study -cell subpopulations, which play an important role in driving islet function. The mechanism by which highly synchronized -cell subpopulations drive islet function is unclear. We used experimental and computational techniques to investigate the relationship between functional networks, structural (gap-junction) networks, and intrinsic -cell dynamics in slow and fast oscillating islets. Highly synchronized subpopulations in the functional network were differentiated by intrinsic dynamics, including metabolic activity and KATP channel conductance, more than structural coupling. Consistent with this, intrinsic dynamics were more predictive of high synchronization in the islet functional network as compared to high levels of structural coupling. Finally, dysfunction of gap junctions, which can occur in diabetes, caused decreases in the efficiency and clustering of the functional network. These results indicate that intrinsic dynamics rather than structure drive connections in the functional network and highly synchronized subpopulations, but gap junctions are still essential for overall network efficiency. These findings deepen our interpretation of functional networks and the formation of functional sub-populations in dynamic tissues such as the islet.