A day sleep promoting role of phototransduction in Drosophila melanogaster

Circadian (∼24 h) timekeeping is essential for the lives of many organisms. To understand the biochemical mechanisms of this timekeeping, we have developed a detailed mathematical model of the mammalian circadian clock. Our model can accurately predict diverse experimental data including the phenotypes of mutations or knockdown of clock genes as well as the time courses and relative expression of clock transcripts and proteins. Using this model, we show how a universal motif of circadian timekeeping, where repressors tightly bind activators rather than directly binding to DNA, can generate oscillations when activators and repressors are in stoichiometric balance. Furthermore, we find that an additional slow negative feedback loop preserves this stoichiometric balance and maintains timekeeping with a fixed period. The role of this mechanism in generating robust rhythms is validated by analysis of a simple and general model and a previous model of the Drosophila circadian clock. We propose a double-negative feedback loop design for biological clocks whose period needs to be tightly regulated even with large changes in gene dosage.

The rotation of the Earth around its axis generates 24 h cycles of environmental change, such as daily rhythms of light and temperature. Circadian clocks, cellular biological oscillators that generate 24 h rhythms of gene expression and metabolism, are thought to synchronize the functioning of organisms with these daily environmental changes. Circadian regulation enables organisms to anticipate environmental changes such as dawn and dusk and co-ordinate their metabolism, physiology and behaviour with daily changes in the environment. This is particularly important for plants, which cannot move to escape environmental challenges. In the experimental model Arabidopsis thaliana (Arabidopsis), correct circadian regulation increases photosynthesis, biomass accumulation, survival, seed number and viability (Green, Tingay, Wang, & Tobin 2002; Dodd et al. 2005). It is estimated that almost 90% of Arabidopsis transcripts can oscillate in abundance over the 24 h cycle, with about 30% of transcripts being circadian-regulated (Michael et al. 2008). This multitude of genes under circadian control highlights the pervasiveness of circadian regulation in co-ordinating the functioning of plants with their rhythmic environment. Because photosynthetic light harvesting can only occur during the day and stored carbohydrate reserves require mobilization at night to supply respiration and growth, plant metabolism is intimately associated with cycles of day and night. Building upon extensive underpinning research into the molecular genetics of circadian oscillators, the interactions between metabolism, signalling and circadian regulation have become an important growth area in plant circadian biology. For example, breakthroughs have demonstrated that the rate of nocturnal starch breakdown is intricately timed so that plants do not starve at night (Graf, Schlereth, Stitt, & Smith 2010), sugars produced by photosynthesis can entrain the circadian clock (Haydon, Mielczarek, Robertson, Hubbard, & Webb 2013) and the concentrations of ions such as Ca2+ and Mg2+ are regulated by, and can regulate, the circadian oscillator (Dodd et al. 2007; Feeney et al. 2016). In this issue of Plant, Cell & Environment, Shin et al. 2017 identified another potential connection between metabolism and circadian regulation. The authors established that an energy-sensing protein complex can influence circadian rhythms. AKIN10 (known also as KIN10 or SnRK1.1) is a catalytic α-subunit of Snf1 (sucrose non-fermenting1)-related kinase 1 (SnRK1), which is an evolutionarily conserved energy sensor. SnRK1 controls metabolic enzymes through protein phosphorylation (Sugden, Donaghy, Halford, & Hardie 1999) and also regulates >1000 transcripts in response to starvation by controlling transcription factor activity (Baena-González, Rolland, Thevelein, & Sheen 2007; Mair et al. 2015). SnRK1 plays such a fundamental role in energy metabolism that AKIN10 knockouts are lethal (Baena-González et al. 2007). By overexpressing AKIN10 with a chemically inducible promoter, the authors explored the role of AKIN10 in circadian regulation. They found that inducing very high levels of AKIN10 expression caused the circadian clock to assume a long period, of up to 5 h longer than controls, when plants were under conditions of continuous light. Interestingly, the long circadian period caused by AKIN10 overexpression disappeared in experiments performed under continuous darkness, such that AKIN10 overexpressing plants had the same circadian period as the controls. When AKIN10 overexpressors were in constant darkness, supplementing the growth media with sugars did not restore the long circadian period that occurred in the light. The authors interpret this to indicate that starvation does not cause the insensitivity of circadian period to AKIN10 overexpression in darkness. Instead, Shin et al. (2017) propose that the influence of AKIN10 upon circadian period forms a response to the light environment. The study also found that under both light/dark cycles and constant light, AKIN10 overexpression caused a delay in the peak of expression of transcripts encoding the evening-expressed circadian oscillator component GIGANTEA (GI). This is interesting because gi-11 mutants are insensitive to a long-term effect of sucrose upon the circadian oscillator (Dalchau et al. 2011). Additionally, the authors found that the period of plants harbouring the tic-2 mutation in the circadian oscillator gene TIME FOR COFFEE (TIC) had reduced sensitivity to the effects of AKIN10 overexpression, suggesting a role for TIC in the regulation of circadian period by AKIN10. It is intriguing that AKIN10, a key player in the regulation of energy metabolism of Arabidopsis, can influence circadian rhythms. The work of Shin et al. (2017) builds on studies demonstrating bidirectional regulatory interactions between circadian regulation and metabolism (Fig. 1). For example, the environmental cycles of day and night dictate when photosynthesis can occur, and photosynthesis is also regulated extensively by the circadian oscillator (Dodd, Kusakina, Hall, Gould, & Hanaoka 2014). Importantly, the products of photosynthesis can, in turn, entrain the circadian oscillator (Haydon et al. 2013). Each morning, the up-regulation of photosynthesis causes an accumulation of sugars, which alters circadian oscillator gene expression and can adjust the circadian phase (Haydon et al. 2013). Similarly, the circadian oscillator controls the rate of nocturnal starch consumption (Graf et al. 2010), with one mathematical model for the regulation of nocturnal starch degradation assuming the presence of a sugar sensing mechanism (Feugier & Satake 2013). In this way, the environment affects metabolism, metabolism regulates the circadian oscillator and the circadian oscillator regulates metabolism (Fig. 1). By demonstrating that a subunit of the central energy sensor SnRK1 affects the functioning of the circadian oscillator, Shin et al. (2017) have identified a mechanism that has the potential to couple metabolism with circadian regulation. This adds to the evidence that reciprocal regulation between the circadian oscillator and energy metabolism exists across several Kingdoms of life. For example, in mammals, there are circadian rhythms of NAD+ and ATP synthesis and feeding can reset the circadian oscillator, and in both plants and cyanobacteria, the availability of energy can regulate circadian rhythms (Rust, Golden, & O'Shea 2011; Bass 2012; Haydon et al. 2013). Therefore, the long circadian period caused by AKIN10 overexpression (Shin et al. 2017) could point to a role for AKIN10 in interfacing the circadian oscillator with both metabolism and environment, given the extensive influence of environmental conditions upon the metabolic state of plants. In future, it will be informative to determine the function and position of SnRK1 within the circadian system, to understand how a sensor of cellular energy status contributes to the responses of plants to the daily changes that occur in the environment.

Almost all life forms on earth have adapted to the most impactful and most predictable recurring change in environmental condition, the cycle of day and night, caused by the axial rotation of the planet. As a result many animals have evolved intricate endogenous clocks, which adapt and synchronize the organisms’ physiology, metabolism and behaviour to the daily change in environmental conditions. The scientific field researching these endogenous clocks is called chronobiology and has steadily grown in size, scope and relevance since the works of the earliest pioneers in the 1960s. The number one model organism for the research of circadian clocks is the fruit fly, Drosophila melanogaster, whose clock serves as the entry point to understanding the basic inner workings of such an intricately constructed endogenous timekeeping system. In this thesis it was attempted to combine the research on the circadian clock with the techniques of optogenetics, a fairly new scientific field, launched by the discovery of Channelrhodopsin 2 just over 15 years ago. Channelrhodopsin 2 is a light-gated ion channel found in the green alga Chlamydomonas reinhardtii. In optogenetics, researches use these light-gated ion channels like Channelrhodopsin 2 by heterologously expressing them in cells and tissues of other organisms, which can then be stimulated by the application of light. This is most useful when studying neurons, as these channels provide an almost non-invasive tool to depolarize the neuronal plasma membranes at will. The goal of this thesis was to develop an optogenetic tool, which would be able to influence and phase shift the circadian clock of Drosophila melanogaster upon illumination. A phase shift is the adaptive response of the circadian clock to an outside stimulus that signals a change in the environmental light cycle. An optogenetic tool, able to influence and phase shift the circadian clock predictably and reliably, would open up many new ways and methods of researching the neuronal network of the clock and which neurons communicate to what extent, ultimately synchronizing the network. The first optogenetic tool to be tested in the circadian clock of Drosophila melanogaster was ChR2-XXL, a channelrhodopsin variant with dramatically increased expression levels and photocurrents combined with a prolonged open state. The specific expression of ChR2-XXL and of later constructs was facilitated by deploying the three different clock-specific GAL4-driver lines, clk856-gal4, pdf-gal4 and mai179-gal4. Although ChR2-XXL was shown to be highly effective at depolarizing neurons, these stimulations proved to be unable to significantly phase shift the circadian clock of Drosophila. The second series of experiments was conducted with the conceptually novel optogenetic tools Olf-bPAC and SthK-bPAC, which respectively combine a cyclic nucleotide-gated ion channel (Olf and SthK) with the light-activated adenylyl-cyclase bPAC. These tools proved to be quite useful when expressed in the motor neurons of instar-3 larvae of Drosophila, paralyzing the larvae upon illumination, as well as affecting body length. This way, these new tools could be precisely characterized, spawning a successfully published research paper, centered around their electrophysiological characterization and their applicability in model organisms like Drosophila. In the circadian clock however, these tools caused substantial damage, producing severe arrhythmicity and anomalies in neuronal development. Using a temperature-sensitive GAL80-line to delay the expression until after the flies had eclosed, yielded no positive results either. The last series of experiments saw the use of another new series of optogenetic tools, modelled after the Olf-bPAC, with bPAC swapped out for CyclOp, a membrane-bound guanylyl-cyclase, coupled with less potent versions of the Olf. This final attempt however also ended up being unsuccessful. While these tools could efficiently depolarize neuronal membranes upon illumination, they were ultimately unable to stimulate the circadian clock in way that would cause it to phase shift. Taken together, these mostly negative results indicate that an optogenetic manipulation of the circadian clock of Drosophila melanogaster is an extremely challenging subject. As light already constitutes the most impactful environmental factor on the circadian clock, the combination of chronobiology with optogenetics demands the parameters of the conducted experiments to be tuned with an extremely high degree of precision, if one hopes to receive positive results from these types of experiments at all.

Drosophila Ebony Activity Is Required in Glia for the Circadian Regulation of Locomotor Activity

Flowering of Arabidopsis is promoted by long days and delayed by short days. Mutations in the GIGANTEA (GI) gene delay flowering under long days but have little or no effect under short days. We have now isolated the GI gene and show that it encodes a novel, putative membrane protein. By comparing the sequence of the Arabidopsis gene with that of a likely rice orthologue and by sequencing mutant alleles, we identify regions of the GI protein that are likely to be important for its function. We show that GI expression is regulated by the circadian clock with a peak in transcript levels 8-10 h after dawn. The timing, height and duration of this peak are influenced by daylength. We analysed the interactions between GI and the LHY, CCA1 and ELF3 genes, previously shown to affect daylength responses; we show that the rhythmic pattern of GI expression is altered in the elf3, CCA1-OX and lhy genotypes, and that CCA1 and LHY expression are reduced by gi mutations. Our results are consistent with the idea that GI plays an important role in regulating the expression of flowering time genes during the promotion of flowering by photoperiod.

Every fall, Northeastern America monarch butterflies ( Danaus plexippus ) undergo an extraordinary migration to their overwintering site in Central Mexico. During their long migration, monarch migrants use sun compass to navigate. To maintain a southward flying direction, monarch migrants compensate for the continuously changing position of the sun by providing timing information to the compass using their circadian clock. Animal circadian clocks depend primarily on a negative transcriptional feedback loop to track time. I started my work to re-construct the monarch butterfly circadian clock negative feedback loop in cell culture, focusing on homologs of Drosophila clock genes. It turned out that in addition to a Drosophila -like cryptochrome (cry1) gene, a second mammalian-like cry2 gene exists in monarch butterflies and many other insects, except in Drosophila . The two CRYs showed distinct functions in our initial assays in cultured Drosophila Schneider 2 (S2) cells. CRY2 functions as a potent transcriptional repressor, while CRY1 is light sensitive but shows no obvious transcriptional activity. The existence of two cry genes in insects changed the Drosophila -centric view of insect circadian clock. During the course of my study, our lab obtained a monarch cell line called DpN1 cells. These cells possess a light-driven clock and contributed tremendously to the research on monarch circadian clock. Using this cell line, I provided strong evidence supporting monarch CRY2’s role as a major circadian clock repressor and identified a protein-protein protective interaction cascade underlying the CRY1-mediated resetting of the molecular oscillator in DpN1 cells. I continued my work trying to understand how insect CRY2 inhibits transcription. I provided evidence suggesting the involvement of monarch PER in promoting CRY2 nuclear entry in both S2 cells and DpN1 cells. Finally, I mapped CRY2’s transcriptional inhibitory activity onto its N-terminal domain. Collectively, my research helped to change our view of insect clocks from a Drosophila -centric standpoint to a much more diverse picture. My studies also advanced the understanding of monarch circadian clock mechanism, and provides a foundation for further studies.

The marine bristle worm Platynereis dumerilii is a useful functional model system for the study of the circadian clock and its interplay with others, e.g., circalunar clocks. The focus has so far been on the worm’s head. However, behavioral and physiological cycles in other animals typically arise from the coordination of circadian clocks located in the brain and in peripheral tissues. Here, we focus on peripheral circadian rhythms and clocks, revisit and expand classical circadian work on the worm’s chromatophores, investigate locomotion as read-out and include molecular analyses. We establish that different pieces of the trunk exhibit synchronized, robust oscillations of core circadian clock genes. These circadian core clock transcripts are under strong control of the light-dark cycle, quickly losing synchronized oscillation under constant darkness, irrespective of the absence or presence of heads. Different wavelengths are differently effective in controlling the peripheral molecular synchronization. We have previously shown that locomotor activity is under circadian clock control. Here, we show that upon decapitation worms exhibit strongly reduced activity levels. While still following the light-dark cycle, locomotor rhythmicity under constant darkness is less clear. We also observe the rhythmicity of pigments in the worm’s individual chromatophores, confirming their circadian pattern. These size changes continue under constant darkness, but cannot be re-entrained by light upon decapitation. Our works thus provides the first basic characterization of the peripheral circadian clock of P. dumerilii. In the absence of the head, light is essential as a major synchronization cue for peripheral molecular and locomotor circadian rhythms, while circadian changes in chromatophore size can continue for several days in the absence of light/dark changes and the head. Thus, in Platynereis the dependence on the head depends on the type of peripheral rhythm studied. These data show that peripheral circadian rhythms and clocks should also be considered in “non-conventional” molecular model systems, i.e., outside Drosophila melanogaster, Danio rerio, and Mus musculus, and build a basic foundation for future investigations of interactions of clocks with different period lengths in marine organisms.

Article Figures and data Abstract Editor's evaluation eLife digest Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Circadian clocks are highly conserved transcriptional regulators that control ~24 hr oscillations in gene expression, physiological function, and behavior. Circadian clocks exist in almost every tissue and are thought to control tissue-specific gene expression and function, synchronized by the brain clock. Many disease states are associated with loss of circadian regulation. How and when circadian clocks fail during pathogenesis remains largely unknown because it is currently difficult to monitor tissue-specific clock function in intact organisms. Here, we developed a method to directly measure the transcriptional oscillation of distinct neuronal and peripheral clocks in live, intact Drosophila, which we term Locally Activatable BioLuminescence, or LABL. Using this method, we observed that specific neuronal and peripheral clocks exhibit distinct transcriptional properties. Loss of the receptor for PDF, a circadian neurotransmitter critical for the function of the brain clock, disrupts circadian locomotor activity but not all tissue-specific circadian clocks. We found that, while peripheral clocks in non-neuronal tissues were less stable after the loss of PDF signaling, they continued to oscillate. We also demonstrate that distinct clocks exhibit differences in their loss of oscillatory amplitude or their change in period, depending on their anatomical location, mutation, or fly age. Our results demonstrate that LABL is an effective tool that allows rapid, affordable, and direct real-time monitoring of individual clocks in vivo. Editor's evaluation This manuscript will be of broad interest primarily to readers in the field of Chronobiology, but more in general, also Physiology. The reporter construct generated in this study provides a great tool to dissect with cell and tissue specificity the rhythmic transcriptional oscillations orchestrated by circadian clocks in vivo. Here, the authors take full advantage of such a tool showing how neuronal and peripheral clocks might be differentially regulated and possess distinct properties. https://doi.org/10.7554/eLife.77029.sa0 Decision letter Reviews on Sciety eLife's review process eLife digest The daily rhythms in our lives are driven by biological mechanisms called circadian clocks. These biological clocks are protein machines found in almost every cell and organ of the body, in nearly all living things, from fungi and plants to fruit flies and humans. These clocks control 24-hour cycles of gene activity and behaviour, and are kept in-time by so-called ‘master clocks’ in the brain. Ideally, scientists would be able to observe how circadian clocks work in different parts of the brain in a living animal and track changes throughout the day, as the animal performs different behaviours. However, the tools that are currently available to study circadian clocks do not allow this. To overcome this difficulty, Johnstone et al. used fruit flies to develop a new method that allows scientists to measure the oscillations of the circadian clocks in the brain in real time. Circadian clocks are composed of proteins called ‘transcription factors’ that activate different genes throughout the day, producing different proteins at different times. Transcription factors control the activity of genes by binding to DNA sequences called ‘promoters’ and switching the genes regulated by these promoters on or off. Knowing this, Johnstone et al. engineered fruit flies to carry the gene that codes for a protein called luciferase, which emits light, and placed it under the control of the promoter for the period gene, a gene that is regulated by the circadian clock. To prevent all of the cells in the fly from producing luciferase any time the period promoter was active, Johnstone et al. placed a second gene between the promoter and the luciferase gene. This second gene contains ‘stop’ sequences that prevent luciferase from being produced as long as the second gene is present. Importantly, this gene can be genetically removed from specific cells in live flies, so only these cells will produce luciferase. When Johnstone et al. removed the second gene from specific cells in the fly brain that are involved in controlling behaviours related to the circadian clocks, these cells started emitting light in cycles that reproduced the activity of the circadian clocks. Thus, by monitoring how the brightness of luciferase changed throughout the day in these flies, Johnstone et al. were able to reveal how the circadian clocks work in different parts of the fly brain. They found that each clock had slightly different cycling lengths, suggesting that the clocks work differently in different parts of the brain to control behaviour. Interestingly, Johnstone et al. found that if a key gene responsible for communication between cells was mutated, the effects of the mutation also varied in different parts of the brain. This suggests that different clocks respond differently to communication cues. Additionally, the results showed that circadian clock activity also changed with age: older flies had weaker circadian behaviours – fewer changes in both behavioural and genetic activity levels between the day and night – than younger animals. Johnstone et al.’s approach makes it possible to track a living animal’s circadian clocks in different parts of the brain and in different organs in real time without the need to dissect the animal. In the future, this method will help scientists understand the links between different circadian clocks, the genes associated with them, and the behaviours they control. Introduction ‘Circadian rhythms’ collectively refer to ~24 hr oscillations in an animal’s behavior and physiological responses to daily environmental changes. These rhythms are regulated by the circadian clock, a transcription/translation negative feedback loop that controls the ~24 hr oscillations in expression of hundreds of genes in every tissue. Circadian clocks are highly evolutionarily conserved time-keeping machines, from flies to humans. In both organisms, specialized neurons that express circadian clock components are considered the ‘central clock’; circadian clock components in non-neuronal tissue (hereafter, ‘peripheral clocks’) are widely assumed to respond to the central clock (Brown et al., 2019; Franco et al., 2018; Ito and Tomioka, 2016; Patke et al., 2020; Pilorz et al., 2018), likely through secreted factors (Handler and Konopka, 1979). In humans, disruption of the circadian clock is associated with a wide range of pathologies, including neurological, cardiovascular, and metabolic disorders, as well as cancer and aging (Acosta-Rodríguez et al., 2021; Bae et al., 2019; Hood and Amir, 2017a; Hood and Amir, 2017b; Leng et al., 2019; Logan and McClung, 2019; Rana et al., 2020; Shimizu et al., 2016; Sulli et al., 2019; Thosar et al., 2018; Tsuchiya et al., 2020; Zhang et al., 2021). Such a broad variety of pathologies associated with compromised circadian rhythms suggests a need for cheap and effective ways to measure tissue-specific circadian clocks directly in model organisms. In animals, locomotion is the simplest and most rapid way to measure circadian clock output, but this output embodies the cumulative activity of many clocks and does not necessarily represent all clocks equally. Moreover, while ablation of neuronal clocks in flies, mice, and humans leads to loss of sleep/activity rhythms and is thought to cause loss of circadian clock function in many tissues, the hierarchy of dysfunction of tissue-specific clocks during specific disease pathogenesis remains unclear. Currently, individual peripheral clocks can be measured in flies by removing the organ and extracting RNA to assess transcriptional oscillations (Erion et al., 2016; Gill et al., 2015; Litovchenko et al., 2021; Wang et al., 2004; Xu et al., 2011). Such terminal qRT-PCR outputs from explanted organs measure clock function only for that time point in the lifespan of the organism and can be time-, cost-, and labor-intensive. Given that circadian clocks appear to be linked to a wide range of physiologies, including metabolism as well as various behavioral disorders, there is a need to monitor distinct cell- and tissue-specific circadian clocks directly, in vivo, and in real time in Drosophila, similar to reporters developed in mouse models (Sinturel et al., 2021; Smith et al., 2022). We developed a genetically encoded reporter to monitor distinct clocks in Drosophila that we call Locally Activatable BioLuminescence (LABL), offering both high spatial and temporal resolution of clock oscillations in vivo. Our data reveal that tissue-specific clocks have similar but distinct properties of oscillation. To determine if tissue-specific clocks are differentially affected by whole-body mutations, we tested flies lacking a functional PDF (pigment dispersing factor) receptor (han5304, also known as pdfr5304) (Hyun et al., 2005) to demonstrate the properties of clock oscillations LABL can help uncover. PDF is a neuropeptide that elicits a cAMP response from most circadian neurons in the brain and is required to maintain robust rhythmic behaviour in constant dark conditions (Helfrich-Förster, 1995; Helfrich-Förster et al., 2000; Park et al., 2000; Renn et al., 1999; Shafer et al., 2008). While tim01 flies (lacking a functional clock) become completely behaviourally arrythmic and han5304 flies become mostly behaviourally arrhythmic in constant dark conditions, quantification of han5304 fly neuronal clocks reveals infradian oscillations over a narrower range with a mean of ~60 hr, suggesting that loss of different circadian components can disrupt circadian locomotor activity in different ways. When peripheral clocks of a han5304 mutant fly are investigated, they continue to oscillate, but with decreased stability. Here, we demonstrate that LABL reporter flies can be used to measure distinct circadian clocks in different neuronal subpopulations and peripheral tissues in real time and in vivo. The differential changes to distinct clocks caused by the han5304 mutation underscores the assertion that tissue-specific circadian clocks are differentially regulated. We believe that this technology will be critical in the interrogation of distinct circadian clocks in future studies, particularly in monitoring peripheral clock function during disease progression in Drosophila. Results Construction of LABL To monitor distinct clock oscillations in real time, in vivo, we designed a genetically encoded reporter that we call LABL. LABL was constructed into an attB cloning vector for Drosophila embryo injection and PhiC31-mediated genome integration (Bischof et al., 2007; Figure 1—figure supplement 1). LABL is comprised of a per promoter fused to mCherry flanked by FRT sequences, which was subsequently fused to Luc2 (pGL4.10) (Figure 1A). Three stop codons placed 3’ of mCherry are designed to block Luciferase expression. The employed per promoter (~6.7 kb) responds to clock regulation through the CLK/CYC transcription activator complex (Bargiello et al., 1984; Darlington et al., 1998). Tissue-specific expression of Flipase (FLP) triggers recombination at the FRT sites, excising mCherry from the genome and leaving Luciferase under per promoter control. To test the functionality of LABL in vitro, we monitored FLP-driven LABL activity in cultured S2 cells (Figure 1B and C). Since S2 cells do not express CLK, which is required to activate the per promoter, we co-transfected LABL plasmid with Clk-CFP, with and without FLP. These cells were subsequently imaged for CFP and mCherry expression and monitored for luminescence. Cells expressing FLP exhibited increased luminescence and a loss of mCherry fluorescence. Cells lacking FLP exhibited no luminescence but increased mCherry fluorescence. Thus, these data demonstrate that the LABL reporter is functional as designed and can be activated by FLP expression. Figure 1 with 1 supplement see all Download asset Open asset Design and activity of LABL reporter. (A) The Locally Activatable Bioluminescence (LABL) reporter construct. In architecture, the per promoter (pPer) is fused to mCherry followed by luciferase (Luc). The mCherry gene and three stop codons are flanked by FRT recombination sequences. Expression of Flipase (FLP) excises out mCherry (dashed lines), leaving luciferase under period promoter regulation. (B) Fluorescence image of LABL-expressing S2 cells. Expression of LABL reporter with actin promoter-driven Clk (pAc-Clk-CFP), FLP (pAc-FLP), or both reveals CLK-dependent expression of mCherry in the absence of FLP. Scale bar represents 5 μm. (C) LABL can be activated in cultured S2 cells. Lysed S2 cells emit measurable luminescence in a luciferase assay when expressing LABL reporter in a FLP-dependent manner. ****: p < 0.0001. Luminescence oscillations of transcription activity reflect behavioural rhythms Having established its functionality in cultured cells, we proceeded to assess LABL in adult flies. The LABL reporter plasmid was used to generate reporter flies which were then monitored in a luminometer using arenas designed to hold 15 flies on top of fly food supplemented with luciferin (Figure 2A). LABL flies carrying the tim-UAS-Gal4 (TUG) pan-circadian tissue driver were crossed to flies carrying UAS-FLP, and the progeny monitored for luminescence activity in constant darkness (Figure 2B). The raw luminescence data exhibited an oscillating rhythm and a gradual decay, as expected (Brandes et al., 1996; Stanewsky et al., 1997). Figure 2 with 1 supplement see all Download asset Open asset Measurement, quantification, and analysis of luminescence from LABL flies. (A) LABL activation strategy in Drosophila brain. Fly brain schematic illustrates how LABL can be activated using tissue-specific Gal4 drivers which express UAS-FLP2 to excise mCherry out of the genome in some neurons to permit Luciferase expression (yellow circles) under the regulation of the period promoter, leaving other neurons untouched (red circles). Fifteen LABL flies are placed in custom-made plates containing luciferin mixed with standard fly food. Plates are loaded into a luminometer and luminescence from each cohort is recorded for analysis. (B) Raw luminescence measurements of live flies. Photons were detected from four replicates of 15 flies expressing LABL reporter, UAS-FLP2 and tim-UAS-Gal4 over 9 days at 4-min temporal resolution. (C) Comparison between luminescence signal (upper graph) and locomotor activity (lower graph) of wild-type flies. Luminescence signal from flies described in panel B is normalized to exponential decay of signal, the values are averaged into 30 min bins, and the mean of the four experiments presented, +/-SEM (thickness of curve). Light grey and dark grey backgrounds represent subjective day and subjective night, respectively. Vertical solid black lines divide days. The peaks and troughs of the presented curves are represented by dots, and are the mean of four experiments, +/-SEM. Lines connecting the dots of peaks or troughs are best-fit S-curves. The vertical dashed lines define the point of inflection of each S-curve, which is used to define the A50. Locomotion activity is measured in beam breaks (counts) per 30-min bouts. Curve in lower graph represents rhythmic locomotor activity of 25 flies, +/-SEM (thickness of curve). White background indicates lights on. Vertical solid lines divide days. Light grey and dark grey backgrounds represent subjective day and subjective night, respectively. Blue and yellow dots represent peaks of “morning anticipatory” and “evening anticipatory” locomotion activity, respectively. The vertical dashed lines define the point of inflection of each S-curve, fitted to peaks of activity, which is used to define the decay of amplitude of peaks of behavior. (D) Calculation of oscillation peaks and troughs. A representative single replicate from experiment in panels B and C is plotted. Dots represent averaged luminescence signal in 30-min bins. A sinusoidal curve spanning 2 days is fitted to the data in 1 day increments (distinct colored curves). The peaks and troughs of each curve are calculated (triangles), averaged for both x- and y-values and recorded. This process is repeated for all four replicates and the resulting average is reported as shown in panel C. (E) Changes in oscillation period over time determined by Morlet wavelet fitting. Wavelets of different periods were fitted to luminescence signal from a single representative replicate from experiment in panel B and C, and assigned a confidence interval, across time (upper graph). Periods with highest confidence intervals at a time point (i.e. across the x-axis) were plotted as white dots. Confidence intervals of 25% or less were omitted. These values were replotted along with the other replicates (below), with varying shades of grey representing each of the four experiments. The dotted horizontal line denotes 24 hr as a point of reference. Right panel: All data points without the time dimension are plotted. Bar represents the mean, +/-SD. We next compared pan-circadian tissue luminescence oscillations with behavioural rhythms. The recorded luminescence activity was normalized to the gradual decay in signal and plotted as an average of four experiments (Figure 2C, top panel). Control flies lacking a driver exhibited no discernable oscillation (white line). To characterize the luminescence oscillations, we first quantified the decay in amplitude (the difference in y-value, between peaks and troughs) of signal. Data points were binned into 30-min time intervals and a 48-hr sinusoidal curve was fitted to the data at 24-hr intervals (Figure 2D). The coordinates of the local minima and maxima were recorded, averaged, and plotted over the decay-normalized luminescence signal to reveal the amplitude of oscillation across time (black circles) (Figure 2C). An S-curve fitted to the changing local minima and maxima (black line) revealed points of inflection coinciding with Day 6 of constant darkness (vertical dashed lines). We used this point of inflection, which is the time at which the amplitude falls to 50% between maximum and minimum (A50), as a measure of clock stability because decay of oscillations into arrhythmic transcription may exceed the timeline of this assay. Genotypically identical flies were measured for locomotor activity and their behavioral rhythms plotted (Figure 2C, bottom panel). We found that the peaks of morning anticipation (yellow circles) decayed rapidly, allowing the evening anticipation peaks (blue circles) to dominate behavioral oscillations in constant dark conditions. Focusing on the change in evening anticipation peaks, we found that a fitted S-curve revealed a point of inflection (A50) at ~day 6, coincident to the A50 observed in luminescence oscillations. We conclude that the decay of amplitude of oscillation of the ubiquitously expressed molecular clock and behavioural rhythms are consistent with each other. We next characterized the change of period of luminescence oscillation across time. A Morlet wavelet was fitted onto the measured luminescence oscillations (Figure 2E). Period values with highest confidence intervals revealed a steady ~23.5 hr period of oscillation across time; specifically, oscillations occurred with an average period of 23.57 hr over nine days in constant darkness. This oscillation period also mirrored the behavioural period, with luminescence oscillation and behavioural period statistically the same, at ~23.5 hr. Thus, luminescence be detected in flies in which LABL was activated using and the pan-circadian Gal4 driver and revealed between transcription oscillations and behavioral rhythms of the LABL signal is to ubiquitously expressed luciferase reporters and is clock To determine the of LABL as a reporter, we compared LABL oscillations to ubiquitously expressed luciferase To this we compared our data to data from promoter fused to (Brandes et al., and promoter and of the per gene fused to et al., flies, other reporter (Figure Since Gal4 expression in all clock cells, we expected LABL luminescence signal to be to luminescence signal. the oscillation of luminescence signal was in period, and (Figure The on the other a of the and there is a between per transcription and per and Stanewsky et al., we expected a difference between LABL luminescence signal and signal. luminescence signal was compared to both LABL and flies et al., 1997). Thus, LABL is to both and flies. Figure with 1 supplement see all Download asset Open asset LABL oscillations are to other luminescence reporters and respond to circadian clock (A) Comparison of luminescence LABL activated by tim-UAS-Gal4 (black is plotted per promoter fused to luciferase and curve). (B) LABL is activated by tim-UAS-Gal4 in a tim01 genetic graph represents locomotor Locomotion activity is measured in beam breaks (counts) per 30-min bouts. Curve represents rhythmic locomotor activity of 25 flies, +/-SEM (thickness of curve). White background indicates lights on. Vertical solid lines divide days. Light grey and dark grey backgrounds represent subjective day and subjective night, respectively. graph illustrates luminescence signal over time. Luminescence signal is normalized to exponential decay of signal, values averaged into 30-min bins, as the mean of four experiments presented, +/-SEM (thickness of curve). Light grey and dark grey backgrounds represent subjective day and subjective night, respectively. Vertical solid black lines divide days. graph illustrates changes in oscillation period over time determined by Morlet wavelet fitting. are as described in Figure represents an replicate of wavelet period in the tim01 genetic is a of period of each of the four plotted. replicates are background represents range of of the han5304 genetic (C) LABL is activated by tim-UAS-Gal4 in a han5304 genetic are as described in panel of period in the infradian oscillation range – is different in han5304 flies when compared to tim01 flies, determined by the test p < the clock behavioural and loss of transcriptional oscillation. To that the transcription oscillations we observed using LABL were we monitored LABL luminescence oscillations in a genetic background lacking functional expression (Figure both locomotor activity and transcription oscillation of tim01 flies were arrhythmic and panel). Importantly, our to Morlet to the luminescence data revealed periods from hr to hr, consistent with circadian panel). of PDF using han5304 mutant flies PDF receptor lacking its and rhythmic behavior in the first days of constant but results in arrhythmic behavior in a of flies (Hyun et al., When we characterized LABL oscillations in a han5304 background (Figure we found that the of flies arrhythmic in their locomotor activity in the second day of constant as While there was also a rapid decay in transcription measured by revealed that ~24 hr oscillations decayed into a infradian oscillations with a narrower range of Such a decay from an ~24 hr oscillation and confidence wavelet infradian oscillation of luminescence was not in flies lacking a functional clock (i.e. tim01 A test reveals that the period the hr range of the han5304 mutant flies was different than that of tim01 flies (Figure and C, of the of infradian rhythms in we to determine if we observe these oscillations using other by locomotion assay or We first measured locomotion rhythms of wild-type and tim01 flies, then a analysis for behavioural period (Figure supplement 1A). In the hr wild-type flies robust ~24 hr rhythms with high of han5304 flies behavioural periods that 24 hr with a wide and a of and tim01 flies no discernable of behavioural period and a of We repeated the analysis for the hr range and found of behavioural periods at hr and hr for both and han5304 flies. tim01 flies showed no All flies had an of to the hr and hr we observed in wild-type and han5304 flies be considered infradian to the of that was to that of tim01 flies, we do not these data of infradian oscillations. We next protein from han5304 fly then for and by to determine if we observe infradian oscillations (Figure supplement We used protein from because protein from flies not oscillating protein signal by (Figure supplement to protein in in flies We observed and oscillations from from both wild-type and the first day of han5304 flies in constant darkness. However, the and not represent oscillations to a hr period in these We conclude that the amplitude of luminescence oscillation may be to observe by locomotion or Circadian drivers used to activate LABL reveal oscillating luminescence Since the driver can be used to activate LABL in flies to oscillating luminescence signal, we to demonstrate that other used circadian drivers can also be used as We FLP expression using and (Figure and Figure supplement 1). We found that the oscillation with the signal from flies in which LABL was activated by and and this well with the of neurons that were for LABL activation when compared with LABL (Figure and drivers oscillations with than would be expected in to their neurons (Figure supplement suggesting that neurons or tissues may be periods were at ~24 hr. We conclude that LABL can also be used in with more tissue-specific Figure with 2 see all Download asset Open asset Luminescence oscillations of distinct clocks measured in and flies. Luminescence signal using different Gal4 drivers to activate LABL compared in day and day flies. used to activate LABL are or in wild-type flies. Luminescence values are normalized and averaged into 30 bins, and the mean of four experiments presented, +/-SEM (thickness of curve). Light grey and dark grey backgrounds represent subjective day and subjective night, respectively. Vertical solid black lines divide days. The peaks and troughs of the presented curves are represented by dots, which are the mean of four experiments, +/-SEM. dots are no be Lines connecting peaks or troughs are best-fit S-curves. The vertical dashed lines define the point of inflection of each S-curve, which is used to define the A50. a vertical dashed line is no S-curve be or no decay be flies exhibit rapid loss of amplitude of luminescence oscillation and of infradian oscillations Since luminescence oscillations in han5304 exhibited differences in

High fat diet induced abnormalities in metabolism, growth, behavior, and circadian clock in Drosophila melanogaster

The functions of the heat shock protein 70 (Hsp70) genes were studied using a line of Drosophila melanogaster with a knockout of 6 of these genes out of 13. Namely, the effect of knockout of Hsp70 genes on negative geotaxis climbing (locomotor) speed and the ability to adapt to climbing training (0.5-1.5 h/day, 7 days/wk, 19 days) were examined. Seven- and 23-day-old Hsp70- flies demonstrated a comparable reduction (twofold) in locomotor speed and widespread changes in leg skeletal muscle transcriptome (RNA sequencing) compared with w1118 flies. To identify the functions of genes related to decreased locomotor speed, the overlapped differentially expressed genes at both time points were analyzed: the upregulated genes encoded extracellular proteins, regulators of drug metabolism, and the antioxidant response, whereas downregulated genes encoded regulators of carbohydrate metabolism and transmembrane proteins. In addition, in Hsp70- flies, activation of transcription factors related to disruption of the fibril structure and heat shock response (Hsf) was predicted, using the position weight matrix approach. In control flies, adaptation to chronic exercise training was associated mainly with gene response to a single exercise bout, whereas the predicted transcription factors were related to stress/immune (Hsf, NF-κB, etc.) and early gene response. In contrast, Hsp70- flies demonstrated no adaptation to training as well as a significantly impaired gene response to a single exercise bout. In conclusion, the knockout of Hsp70 genes not only reduced physical performance but also disrupted adaptation to chronic physical training, which is associated with changes in the leg skeletal muscle transcriptome and impaired gene response to a single exercise bout.NEW & NOTEWORTHY Knockout of six heat shock protein 70 (Hsp70) genes in Drosophila melanogaster reduced locomotion (climbing) speed that is associated with genotype-specific differences in leg skeletal muscle gene expression. Disrupted adaptation of Hsp70- flies to chronic exercise training is associated with impaired gene response to a single exercise bout.

The daily timing of sleep is controlled by a circadian clock, the disruption of which is physiologically and psychologically detrimental. While an identified network of circadian clock neurons controls the timing of sleep, a comprehensive understanding of how each of the components of the molecular clock affect sleep architecture is lacking. Though the loss of the circadian clock does not prevent sleep, it results in drastic changes in the quality of sleep. To better understand the ways in which the circadian clock governs sleep, we sought to systematically characterize the impact of loss of function mutations in Clock, cycle, period, and timeless on the sleep rhythm and sleep architecture in Drosophila under both entrained and free-running conditions and to investigate the role light plays in in the regulation of sleep in wild-type and mutant flies. Using the Drosophila activity monitoring system, we measured sleep in flies bearing loss of function mutations in the Clock (Clkjrk), cycle (cyc01), period (per01), and timeless (tim01) genes. Sleep was measured in under a 12:12h Light/Dark cycle, constant darkness, and constant light. To assess the impact of light on sleep, sleep was measured under various wavelengths and intensities. Our analysis of sleep in these lines reveals that all four mutations caused fragmented sleep. Loss of function mutations within the negative limb of the clock (i.e., per01 and tim01) resulted in altered daytime sleep architecture but no changes in total sleep time for over the diurnal or circadian cycle. Loss of function mutations in the positive limb of the circadian clock (i.e., Clkjrk and cyc01) result not only in significantly decreased sleep but also reveal a sleep promoting effect of light. We found that loss of function mutations in circadian clock genes resulted in significant effects on sleep quality with mutations in the negative and positive limb genes producing remarkably different phenotypes. none.

Gene duplication and complex circadian clocks in mammals

Life could not exist without organisms’ engineered ability to keep track of time on a 24-hour day-night cycle called a circadian rhythm. Insects display an impressive variety of daily rhythms, which are most evident in their behaviour. Circadian timekeeping systems that generate these daily rhythms of physiology and behaviour all involve three interacting elements: the timekeeper itself (i.e. the clock), inputs to the clock through which it entrains and otherwise responds to environmental cues such as light and temperature, and outputs from the clock through which it imposes daily rhythms on various physiological and behavioural parameters. The clocks control various behaviours, physiological functions, and developmental events, enabling adaptation to periodic environmental changes. Circadian clocks also function in time-compensation for celestial navigation and in the measurement of day or night length for photoperiodism. Molecular and physiological mechanisms are best understood for the optic-lobe and mid-brain circadian clocks, although there is no direct evidence that these clocks are involved in rhythmic phenomena other than circadian rhythms in daily events. Circadian clocks have also been localized in peripheral tissues. Circadian clocks are most well studied in Drosophila melanogaster. Drosophila flies spend their entire lives in small areas near the ground, and use their circadian brain clock to regulate daily rhythms of rest and activity, so as to organize their behaviour appropriately to the daily rhythms of their local environment. Migratory locusts and butterflies, on the other hand, spend substantial portions of their lives high up in the air migrating long distances and use their circadian brain clocks to provide time-compensation to their sun-compass navigational systems.

BackgroundSleep and temperature regulation are fundamental biological processes critical for health and survival across species. Despite their significance, the interplay between these systems remains poorly understood. Recent findings suggest overlapping neural circuits regulate both, indicating an interdependence with broad neurobiological implications. Neurodegenerative diseases, including Alzheimer's disease (AD), which are associated with impaired thermoregulation and sleep disruption, underscore the importance of understanding these mechanisms. Identifying these connections is vital for uncovering molecular pathways underlying AD symptoms and developing interventions for temperature and sleep dysregulation.MethodOur research used Drosophila melanogaster (fruit flies) as a model to better elucidate the relationship between sleep and thermoregulation. Two complementary strategies were implemented. First, a minimally invasive sleep‐fragmentation protocol briefly woke flies every 15 minutes, disrupting deep sleep without impairing memory or activating compensatory sleep homeostasis mechanisms. Second, genetic tools were used, including RNAi knockdown of the pigment dispersing factor receptor (Pdfr) in specific neural circuits and targeted expression of Alzheimer's‐related genes, such as Aβ‐Arctic, to explore neuronal contributions to sleep and temperature regulation. Behavioral assays assessed temperature preference under various sleep disruption protocols, including sleep deprivation, social jet lag, and sleep fragmentation, to better understand AD‐related pathology.ResultDrosophila subjected to sleep deprivation or fragmentation exhibited a significant increase in thermal preferences towards warmer temperatures, suggesting disrupted sleep alters thermoregulatory behaviors. Sleep fragmentation effectively disrupted deep sleep stages without impairing memory, reinforcing its utility for studying sleep regulation and providing a model for AD‐related dysfunction. RNAi‐mediated knockdown of Pdfr in clock neurons prevented the temperature preference shifts caused by sleep fragmentation, implicating these neural circuits in the behavior. Social jet lag induced persistent changes in temperature preference, highlighting the sensitivity of thermoregulation to AD‐related disruptions in circadian systems.ConclusionOur findings highlight that the neural circuits governing temperature preference and sleep overlap significantly, revealing their functional interdependence. Introducing Alzheimer's genes broadens our understanding of the underlying molecular mechanisms of impaired thermoregulation and sleep in neurodegenerative diseases. By leveraging behavioral assays and Drosophila genetics, this research provides key insights into conserved mechanisms and potential therapies for addressing sleep disorders and thermoregulatory dysfunctions in AD.

Neurobiologic Mechanisms of Sleep and Wakefulness