The Drosophila SIFamide Receptor Regulates Sleep and Feeding in a Time‐Of‐Day Specific Manner

ABSTRACT

To optimize health, organisms must coordinate energy intake and expenditure and apportion related behaviors to appropriate times of day. In the fruit fly, Drosophila melanogaster , the SIFamide (SIFa) neuropeptide impacts multiple behavioral outputs important for energy regulation, including reproductive activity, sleep, and feeding. SIFa‐expressing neurons receive convergent inputs from circadian and homeostatic brain regions and extend elaborate projections throughout the central nervous system. Consistent with this distribution pattern, the SIFa receptor (SIFaR) is widely expressed in the brain and ventral nerve cord, providing the anatomical substrate for SIFa signaling to influence a broad range of neuronal functions. To further explore the pleiotropic role of SIFa signaling in behavioral control, we have assessed survival, locomotor activity, sleep, and feeding in SIFaR mutant flies, as well as in flies with RNA interference‐induced reduction of SIFaR expression. We find that loss of SIFaR has a complex effect on fly survival that is background‐ and allele‐specific. However, outcrossed SIFaR mutant flies are viable, enabling monitoring of adult behavior. These flies exhibit elevated locomotor activity, reduced sleep, and increased feeding at specific times of day. We also find that SIFaR mutations drastically decrease starvation resistance. These results suggest a prominent role for SIFaR in integrating homeostatic and circadian information to coordinate the magnitude and timing of energy balance‐related behaviors.

We found that mutations in the Drosophila SIFa receptor gene cause increases in locomotor activity and feeding behavior at specific times of day. This suggests that SIFa signaling exerts behavioral control to contribute to optimal energy balance.

1. Introduction

The nervous system maintains energy balance by monitoring peripheral and central cues of energy supply and engaging appropriate behavioral and metabolic responses in the face of energy depletion. These homeostatic mechanisms ensure the stability of energy stores. At the same time, circadian mechanisms partition energy intake, storage, and usage across the day [1, 2]. During the active period, energy is expended to forage for food and to engage in reproductive activity. During the inactive period, energy is conserved through sleep and usage is shifted towards internal metabolic processes [3]. This is partly achieved through circadian modulation of homeostatic drive across the day, which aligns behavioral choice with energetic demands and maximizes energy efficiency [1, 4].

In mammals, the integration of circadian and homeostatic mechanisms to optimize energy use and storage relies on neuronal circuits that converge in the hypothalamus, which houses the central circadian clock and contains additional nuclei that regulate hunger, feeding, reproductive behavior, and sleep. For example, agouti‐related peptide (AgRP)‐expressing neurons in the hypothalamic arcuate nucleus acutely drive feeding behavior, regulate metabolic responses to feeding in a circadian clock‐dependent manner, and suppress sleep during times of homeostatic need [5, 6, 7]. In flies, these functions are served in part by neurons in the pars intercerebralis (PI), which has structural and developmental similarities to the mammalian hypothalamus [8].

The PI has multiple groups of peptidergic neurons that regulate diverse behaviors [9]. This includes a set of four neurons that are marked by the neuropeptide SIFa, which acts on cells expressing SIFaR, a 7‐transmembrane G protein‐coupled receptor with homology to vertebrate gonadotropin inhibitory hormone receptor (GnIHR) [10, 11]. SIFa signaling has been tied to multiple behavioral outputs. Initial studies demonstrated that the ablation of SIFa‐expressing neurons, or RNA interference (RNAi)‐mediated downregulation of SIFa, increased reproductive behavior and resulted in promiscuous courtship [12]. Similar results were observed upon ablation of SIFaR‐expressing cells or RNAi knockdown of SIFaR [13]. This demonstrates that SIFa signaling normally acts to suppress sexual activity, consistent with the function of its vertebrate homolog, GnIHR [10]. SIFa signaling has also been found to regulate the impact of sexual history on mating duration. Sexually inexperienced male flies normally prolong mating duration following prior exposure to competing males, while sexually experienced males decrease mating duration. Notably, these changes in mating duration are eliminated in flies with reduced expression of either SIFa or SIFaR [14, 15]. In addition to regulating reproductive behavior, SIFa signaling has been shown to promote sleep. Targeted ablation of SIFa‐expressing cells, or RNAi knockdown of SIFa or its receptor, drastically decreases sleep duration [16, 17]. Conversely, optogenetic activation of SIFa‐expressing cells acutely promotes sleep [18]. Finally, SIFa signaling has been shown to regulate the amount and timing of feeding. Loss of SIFa or ablation of SIFa‐expressing cells results in increased food consumption and a reduction in the strength of circadian feeding rhythms [19]. The impact of these manipulations on feeding may stem from a role of SIFa in modulating the processing of gustatory and olfactory information to control appetitive drive to feed [20].

SIFa‐expressing neurons receive convergent inputs from the circadian clock network and neuropeptidergic centers conveying hunger and satiety information, and in turn extend elaborate neuronal processes throughout the central brain and ventral nerve cord [12, 17, 20, 21, 22]. Trans‐tango analysis revealed that SIFa‐expressing neurons form extensive synaptic connections across many brain regions, including areas involved in visual processing (the optic lobes), olfactory processing (the antennal lobes and mushroom bodies), and gustatory processing (the subesophageal zone) [19]. As a neuropeptide, SIFa may also diffuse longer distances to act extrasynaptically, which would expand its zone of influence into regions not directly innervated by SIFa‐containing axons. Consistent with this, SIFaR is broadly distributed in neurons throughout the nervous system [13, 15, 19, 23]. Thus, SIFaR is positioned to regulate sensory function in response to circadian and homeostatic cues.

Here we have investigated the effect of loss of Drosophila SIFaR on survival, locomotor activity, sleep, and feeding behavior. Flies with ubiquitous or panneuronal RNAi‐mediated knockdown of SIFaR expression did not survive to adulthood. We also observed developmental lethality in multiple lines of SIFaR null mutants in their original genetic backgrounds. Surprisingly, however, homozygous SIFaR mutants were viable upon outcrossing. These flies showed drastic changes in the amount and timing of multiple behaviors. This included hyperactivity and sleep suppression over most of the 24‐h day, and an increase in feeding that was most prominent around the time of the night–day transition. In addition to these behavioral phenotypes, SIFaR mutants were highly sensitive to starvation, exhibiting decreased survival time when deprived of food. Together, these results suggest that SIFaR functions at the interface of multiple regulatory systems and may be important for coordinating energy intake and expenditure across the day.

2. Materials and Methods

2.1. Fly Stocks

SIFaR mutant flies: y¹w*; Mi{MIC}SIFaR^MI08811 CG17298^MI08811/TM3, Sb¹ Ser¹ (referred to as SIFaR ^MI08811; RRID:BDSC_50489) and w[*]; TI{RFP[3xP3.cUa] = TI}SIFaR[attP]/TM6B, Tb [1] (referred to as SIFaR ^attP; RRID:BDSC_84573) were obtained from the Bloomington Drosophila Stock Center (BDSC) and outcrossed 7× into the iso31 background [24]. RNAi lines targeting SIFaR were obtained from the BDSC: UAS‐SIFaR RNAi^HMS02785 (RRID:BDSC_44068); UAS‐SIFaR RNAi^JF01849 (RRID:BDSC_25831), UAS‐SIFaR RNAi^HMS00299 (RRID:BDSC_34947) and the Vienna Drosophila Resource Center (VDRC): UAS‐SIFaR RNAi^v1783 (RRID: Flybase_FBst0452884). tub‐GAL4 (RRID:BDSC_5138), a second chromosome neuronal Synaptobrevin‐GAL4 (nSyb‐GAL4), UAS‐TrpA1 (RRID:BDSC_26263) and UAS‐Kir2.1::eGFP (RRID:BDSC_6596) were provided by Amita Sehgal. SIFaR‐2A‐GAL4 (RRID:BDSC_84689), UAS‐GFP.nls (RRID:BDSC_4775), UAS‐mCD8::GFP (RRID:BDSC_5137), tub‐GAL80^ts (RRID:BDSC_710) and UAS‐Dicer2 (RRID:BDSC_24650) were obtained from the BDSC. Flies were maintained in narrow polystyrene vials (Fisher Scientific) and provided a cornmeal‐molasses food consisting of (per L): 1.0 L deionized water, 64.7 g yellow cornmeal, 27.1 g dry active granular yeast, 8.0 g 80–100 mesh agar, 90.0 g unsulfured molasses, with 4.4 mL propionic acid and 2.03 g Tegosept to prevent contamination.

2.2. Locomotor Activity Monitoring and Analysis of SIFaR Mutant Flies

Flies were collected at eclosion and entrained to a 12:12 light–dark (LD) cycle at 25°C prior to behavioral testing. Locomotor activity monitoring was performed on ~7 day old male flies with the Drosophila Activity Monitoring (DAM) system [25]. Individual flies were housed in glass tubes containing a 5% sucrose and 2% agar food source and loaded into DAM2 monitors (Trikinetics Inc., Waltham, MA). Monitoring was conducted for 7 days at 25°C in constant dark (DD) conditions, and DAM beam break data were acquired every min. To allow for acclimation, we omitted the first monitoring day from behavioral analyses. We also removed data from flies that did not survive through the entire recording period, as determined by visual inspection of DAM activity records.

We created average day locomotor activity eduction plots with 30‐min binned DAM beam break data. We used DAMfilescan (Trikinetics Inc.) to sum DAM beam break data into 30‐min bins. We averaged each 30‐min bin across the 6 days of DAM recording following the acclimation day for individual flies, then averaged these values across all flies of a given genotype. We used the same 30‐min binned beam break data to calculate circadian locomotor activity rhythm strength with Lomb‐Scargle periodogram analysis using ClockLab software (Actimetrics, Wilmette IL). The Lomb‐Scargle “Amplitude” value at the dominant period is reported as a measure of rhythm strength (power). We used the oamean function of the sleep and circadian analysis MATLAB program (SCAMP) [26] to calculate activity index and the atcounts function to calculate the total number of beam breaks during subjective daytime and subjective nighttime.

2.3. Sleep Analysis

We calculated sleep, defined as ≥ 5 consecutive minutes of inactivity, from DAM beam break data. We used the S30 function of SCAMP to create average day sleep eduction plots for 30‐min binned sleep data, the stdur function to quantify subjective daytime and nighttime sleep duration, the sfreq and smeandur functions to calculate the number of sleep bouts and average sleep bout lengths during the subjective daytime and nighttime, and the Pdoze30 and Pwake30 functions to calculate p(Doze) and p(Wake) across an average day. p(Doze) measures the probability that an active fly will stop moving, while p(Wake) measures the probability that an inactive fly will start moving [27].

2.4. Feeding Monitoring and Analysis

Following entrainment (as described for locomotor activity monitoring), ~7 day old male flies were aspirated into individual wells of a fly liquid–food interaction counter (FLIC) monitor (Sable Systems, North Las Vegas, NV) that was fitted with reservoirs to maintain adequate food levels throughout the monitoring period. To allow for acclimation, recording of feeding behavior began 12 h after flies were initially loaded into FLIC monitors. Feeding monitoring was then conducted over 6 days at 25°C in DD. Liquid food consisted of a 10% sugar solution with 45 mg/L MgCl₂ for increased circuit conductance. Raw data from FLIC experiments were processed using R code [28] to extract feeding events, which we defined as times when the FLIC signal amplitude: (1) exceeded the baseline readings by 5 mV for a minimum of 4 consecutive 200 ms recording periods, and (2) at some point during the event, achieved a 15 mV feeding threshold above baseline readings. Feeding events therefore have a minimum duration of 800 ms and are made up of multiple individual 200 ms feeding interactions, termed “licks”. For subsequent analysis, we summed lick data for individual flies into 30‐min bins. Data from dead flies or flies with poor signal, as determined by visual inspection of data, were removed from analysis.

To create average day feeding eduction plots, we averaged each 30‐min bin across the 6 days of FLIC recording for individual flies, then averaged these values across all flies of a given genotype. To determine total feeding, we calculated the summed duration of all feeding events over the 6 days of recording for each individual fly. To calculate feeding rhythm power, we used Lomb‐Scargle periodogram analysis with ClockLab analysis software as described for locomotor activity rhythms.

2.5. Capillary Feeder (CAFE) Assay

Following entrainment to a 12:12 LD cycle, groups of 4–6 adult male flies, 6–10 days old, were housed in a humidified vial (Drosophila narrow vial, VWR International) containing a single calibrated glass micropipette (5 μL, VWR International) suspended in a hole at the top of the vial. The micropipette was filled by capillary action with the same liquid food as used in the FLIC assays (10% sucrose with 45 mg/L MgCl2) plus blue dye for ease of visualization. Flies were loaded into a CAFE vial during the light period of their entrainment cycle and allowed a 24‐h acclimation period in LD before transfer to DD for a 24‐h monitoring period. Capillary tubes were replaced at the start of the DD period to accommodate evaporative loss. Loss of liquid food via evaporation was controlled for by subtracting measurements from identical CAFE vials with no flies present. Average per fly liquid food consumption was determined based on measurements of the meniscus of the food level in the capillary tube at the start and end of the 24‐h DD monitoring period divided by the number of flies alive at the end of monitoring.

2.6. Starvation Resistance Assay

Six to ten days old male flies were entrained for at least 5 days to a 12:12 LD cycle. At ZT11 (1 h prior to the end of the light phase of their entrainment conditions), flies were CO₂ anesthetized and loaded into DAM vials containing a 2% agar‐only food source. Locomotor activity was monitored under DD conditions, and the time of death was determined as the last 1‐min bin with beam‐break activity.

2.7. Reverse Transcription‐Quantitative PCR (RT‐qPCR) Analysis

Three independent samples, each consisting of 10–15 pooled male flies, were collected for each genotype. Total RNA was extracted with TRIreagent (TR 118; Molecular Research Center Inc., Cincinnati, OH) according to the manufacturer's instructions. Following phase separation, samples were additionally subjected to DNAse treatment and purification with the Direct‐zol RNA Microprep Kit (R2060; Zymo Research, Irvine CA). cDNA was synthesized from 1 μg of RNA with the High‐Capacity cDNA Reverse Transcription Kit (43‐688‐14; Applied Biosystems, Waltham, MA) and served as the template for qPCR reactions with PowerUp SYBR Green Master Mix (A25742; Applied Biosystems) using the following primers: rp49‐qF: 5′‐TACAGGCCCAAGATCGTGAA‐3′; rp49‐qR: 5′‐GCACTCTGTTGTCGATACCC‐3′; SIFaR‐qF: 5′‐ACATACAAGGTGTCTCCGTG‐3′; SIFaR‐qR: 5′‐GTCGCTTTGTCATCTGCTTC‐3′. qPCR reactions were performed in triplicate. For quantification, unknown samples were compared to standard curve dilutions, and SIFaR was normalized to rp49 levels for each sample.

2.8. Lethality, Locomotor Activity and Feeding Monitoring and Analysis of RNAi Knockdown Flies

For assessment of RNAi‐induced lethality, we crossed UAS‐Dicer2; tub‐GAL4/TM6C, Sb flies to each of 4 UAS‐SIFaR RNAi lines, with 3 biological replicates of each cross, and counted the number of Sb vs. non‐Sb offspring that eclosed from each cross. The absence of non‐Sb flies indicated complete lethality. For locomotor activity and feeding monitoring following inducible RNAi knockdown, we maintained crosses in 12:12 LD conditions at 19°C, then collected and transferred ~3 days old offspring to LD conditions at 29°C for 3 days prior to the start of DAM or FLIC monitoring for 6 days in DD conditions at 29°C. Because we noted a gradual reduction in activity in RNAi flies, we used multibeam DAM5H monitors (Trikinetics Inc.) to track locomotor activity, which detect even small movements occurring away from the center of the tube. To create locomotor and activity plots, we summed DAM or FLIC data into 30‐min bins and calculated an average value for each bin across all flies of a given genotype.

2.9. Statistical Analysis

Three or four experimental replicates were conducted for all behavioral experiments, and data were pooled for final analyses. To account for experimental variability, locomotor activity and feeding rhythm power data were normalized for each experimental replicate by dividing the power value for each fly by the mean power value of the experimental control group for that experiment. Data were then analyzed using GraphPad Prism 10 (GraphPad) software. For comparisons of mean values in experiments with three or more groups, Welch's ANOVA with Dunnett's T3 multiple comparisons test was used. For experiments consisting of two groups, Welch's t‐test was used. For comparison of eduction plot data, two‐way ANOVA (with genotype and time as factors) followed by Tukey's multiple comparisons test was used to compare genotype values at each time point. For comparison of starvation survival duration, Logrank test was used and p values were adjusted for multiple comparisons with a Bonferroni correction. For all tests, p values of < 0.05 compared to all controls were considered significant.

2.10. Single‐Cell RNA Expression Dataset Analysis

We accessed Fly Cell Atlas 10× Genomics stringent datasets through SCope [29, 30]. Cell types were determined based on SCope Annotation. We visually identified t‐SNE clusters enriched for SIFaR expression and used the lasso tool in SCope to obtain log‐transformed SIFaR expression and annotation data for cells within each enriched cluster.

2.11. Immunohistochemistry

Approximately seven day old adult male flies were anesthetized with CO₂ at lights‐on time (ZT0) and transferred to 100% ethanol for 1 min, then rinsed briefly in phosphate buffered saline with 0.1% Triton‐X (PBST). Abdomens and digestive tracts were dissected in PBST, fixed in 4% paraformaldehyde for 20–40 min, blocked for 60 min in 5% normal donkey serum in PBST (NDST), and incubated for 24 h in rabbit anti‐GFP 1:1000 (Invitrogen A11122) diluted in NDST. Tissues were then washed 3 × 15 min in PBST, incubated for 24 h in FITC donkey anti‐rabbit 1:1000 (Jackson 711‐095‐152) diluted in NDST, washed 3 × 15 min in PBST, cleared for 5 min in 50% glycerol in PBST, and mounted with Vectashield (Vector Labs). Immunolabeled tissues were visualized with a FLUOVIEW 1000 confocal microscope (Olympus).

3. Results

3.1. SIFaR Downregulation Induces Lethality

To determine the role of the SIFaR in the regulation of behavioral outputs, we sought to conduct long‐term locomotor activity and feeding monitoring in flies lacking functional SIFaR expression. We started by using the GAL4‐UAS system to drive the expression of RNAi constructs targeting SIFaR. We tested multiple UAS‐SIFaR RNAi constructs, first using a ubiquitously expressed tub‐GAL4 line to downregulate SIFaR expression in all tissues. We also included a UAS‐Dicer2 construct to maximize RNAi efficiency. We found that this resulted in complete developmental lethality in two of four RNAi lines tested (UAS‐SIFaR RNAi^v1783 and UAS‐SIFaR RNAi^JF01849), whereas flies from crosses with the other two lines (UAS‐SIFaR RNAi^HMS02785 and UAS‐SIFaR RNAi^HMS00299) eclosed with expected Mendelian ratios. Notably, we could not detect a significant reduction of SIFaR expression in the two surviving lines (Figure S1), suggesting that the lack of lethality in these flies was due to incomplete knockdown. Consistent with previous results, panneuronal expression of UAS‐SIFaR RNAi^v1783 with nSyb‐GAL4 also produced complete lethality, while nSyb‐GAL4‐driven SIFaR RNAi^JF01849 was without effect on survival [31]. Furthermore, UAS‐SIFaR RNAi^JF01849 required co‐expression of Dicer2 to induce lethality, while UAS‐SIFaR RNAi^v1783 did not. We interpret these results to indicate that SIFaR RNAⁱ¹⁷⁸³ produces the strongest SIFaR knockdown and that SIFaR is required in neurons for survival through larval and pupal stages in RNAi knockdown flies. Unfortunately, this precluded assessment of adult behavior in these flies.

To circumvent developmental issues, we restricted tub‐GAL4‐driven UAS‐SIFaR RNAi^v1783 to adult stages with the addition of a temperature‐sensitive tub‐GAL80 allele (tub‐GAL80^ts) [32]. When raised at low temperature (19°C), which permits the repressive effect of tub‐GAL80^ts on GAL4 activity, we found that flies survived into adulthood. However, they died within ~2 weeks of adult‐specific induction of SIFaR knockdown via exposure to 30°C, which inactivates GAL80 repression. This was associated with a progressive decline in the amount of feeding and locomotor activity (Figure 1A–F), demonstrating an ongoing requirement of SIFaR expression in adult stages for health and survival. Consistent with these results, we also observed pupal lethality when we used SIFaR‐GAL4 lines to drive expression of UAS‐Kir2.1, which induces constitutive electrical silencing [33]. In addition, flies died within a few hours of prolonged, adult‐specific activation of SIFaR‐expressing neurons with UAS‐TrpA1 [34].

FIGURE 1.

Adult‐specific RNAi‐mediated knockdown of SIFaR causes progressive decline in activity and feeding. (A) Representative individual fly activity plots show the number of DAM beam breaks/30‐min bin over 6 days in DD at 29°C for tub‐GAL4>SIFaR RNAi^v1783, +>SIFaR RNAi^ts and tub‐GAL4>+ flies. Data are double plotted such that each line shows 48 h of activity and the second day on each line is plotted again at the start of the next line. Light‐ and dark‐gray shading indicate subjective day and night, respectively. (B) Representative individual fly feeding plots show the number of “licks”/30‐min bin over 6 days in DD at 29°C, as described in (A). For (A) and (B), note the gradual reduction in activity or feeding over the course of the 6 days of recording in tub‐GAL4>SIFaR RNAi^ts flies. (C–F) Average activity (C) or feeding (E) is depicted for for tub‐GAL4>SIFaR RNAi^v1783 (red), +>SIFaR RNAi^ts (gray) and tub‐GAL4>+ (black) flies across 6 days of DD monitoring (C and E) or selectively for the 6th day of monitoring (D and F). Lines show means ±95% confidence intervals. n = 49–76 flies/genotype. tub‐GAL4>SIFaR RNAi^ts indicates that the expression of UAS‐SIFaR RNAi^v1783 is being driven by tub‐GAL4 under control of a temperature‐sensitive GAL80 construct.

3.2. SIFaR Mutant Flies

To supplement our RNAi studies, we obtained several lines of SIFaR mutant flies, including a line in which a MI(MIC) gene‐trap cassette has been inserted into the 4th intron of the SIFaR gene (SIFaR ^MI08811) [35, 36], and a line in which the last two coding exons have been excised and replaced with an attP‐containing cassette (SIFaR ^attP) [37] (Figure 2A). Both are expected to produce null alleles. Consistent with our RNAi results, we found that the mutant lines exhibited homozygous lethality in the larval or pupal stages. Surprisingly, heteroallelic combinations were viable, but in their original genetic backgrounds, these flies showed aberrant locomotor activity behavior, even for heterozygous control flies that contained just a single mutant allele. This indicates the potential for background genetic effects that compromised motor control. To address this, we outcrossed both mutant lines into the iso31 background. After outcrossing, one of the two mutant lines (SIFaR ^attP) was homozygous viable, while the other (SIFaR ^MI08811) remained homozygous lethal but was viable in trans‐heterozygous combination with the SIFaR ^attP allele. Using RT‐qPCR analysis, we confirmed a complete loss of SIFaR expression in both homozygous SIFaR ^attP/attP and trans‐heterozygous SIFaR ^attP/MI08811 flies (Figure 2B). Because mutant lethality was affected by genetic background, we also tested the viability of RNAi knockdown flies after outcrossing both the tub‐GAL4 and UAS‐SIFaR RNAi^v1783 lines; however, this manipulation remained lethal in the iso31 background. We conclude that the requirement for SIFaR for fly survival is genetic background‐ and allele‐dependent.

FIGURE 2.

SIFaR null mutants. (A) Schematic depiction of SIFaR mutant lines. The SIFaR gene has two known variants (SIFaR‐RA and SIFaR‐RC; < indicates direction of transcription). Exons are shown in thick rectangles and coding regions are shown in red. The SIFaR ^MI08811 line has a MI(MIC) cassette (indicated by the black triangle) inserted in the 4th intron of SIFaR. For SIFaR ^attP, CRISPR targeting was used to excise the last two coding exons. (B) RT‐qPCR analysis shows a complete lack of SIFaR mRNA expression in both homozygous SIFaR ^attP/attP and trans‐heterozygous SIFaR ^attP/MI08811 flies compared to wildtype controls. Dots show SIFaR expression, normalized to Rp49, for each biological replicate. Lines show means ±95% confidence intervals.

3.3. SIFaR Mutants Have Increased Activity During the Subjective Night

As outcrossed mutant lines survived into adulthood, we undertook behavioral monitoring to determine the consequences of loss of SIFaR function. We first used the DAM system to assess locomotor activity over 6 days in DD conditions. We observed that both SIFaR ^attP/attP and SIFaR ^attP/MI08811 flies exhibited increased activity during a substantial portion of the 24‐h day (Figure 3A). When quantified, the mean number of DAM beam breaks for mutant flies was nearly double that of heterozygous or wild‐type controls during the subjective night (Figure 3C). Subjective day activity also trended slightly higher in SIFaR mutants, but this did not reach statistical significance compared to all control groups (Figure 3B). The time‐of‐day specificity suggests that SIFaR signaling normally acts to suppress activity during the nighttime, especially in the hours following the day‐night transition. Despite the increase in overall locomotor activity, the activity index, defined as beam breaks per minute awake, was unchanged in the SIFaR mutants, indicating that these flies spend more time awake but are not hyperactive during wake time (Figure 3D).

FIGURE 3.

SIFaR mutants have increased locomotor activity during the subjective night. (A) Average day eduction plot shows mean activity (DAM beam breaks/30‐min bin) ± 95% confidence intervals for SIFaR ^attP/attP (green), SIFaR ^attP/MI08811 (magenta), SIFaR ^attP/+ (dark gray), SIFaR ^MI08811/+ (light gray) and SIFaR ^+/+ (black) flies. A two‐way ANOVA showed a significant effect of genotype (F(4, 14,016) = 457.66, p < 0.0001, ηp ² = 0.12), time of day (F(47, 14,016) = 403.73, p < 0.0001, ηp ² = 0.58), and a significant genotype × time of day interaction (F(188, 14,016) = 3.31, p < 0.0001, ηp ² = 0.043). *p < 0.05 for the experimental line (color‐coded by genotype) compared to all heterozygous and wildtype controls at that time point, Tukey's multiple comparisons test. (B, C) Plots depict average DAM beam breaks during the subjective day (B) or subjective night (C). Both mutant lines had significantly elevated subjective nighttime activity. (D) Average activity index (beam breaks/min awake) is shown for the indicated genotypes. (E) Normalized circadian rhythm power (Lomb‐Scargle amplitude value) is unchanged in SIFaR mutants. For (B–E), dots depict values for individual flies and lines show means ±95% confidence intervals. Different letters above each plot indicate significant differences (at p < 0.05), Dunnett's T3 multiple comparisons test following ANOVA. (F) Representative individual fly activity records are shown for the indicated genotypes, as described for Figure 1. Note the increased subjective nighttime activity in SIFaR mutant lines. For all graphs, n = 57–62 per genotype.

In addition to monitoring for changes in the overall amount of activity, we determined whether SIFaR mutations altered circadian locomotor activity rhythms. Somewhat surprisingly, we did not detect a reduction in the strength of locomotor activity rhythms, as determined by Lomb‐Scargle periodogram analysis (Figure 3E). Nevertheless, mutant flies clearly exhibited elevated activity during the subjective nighttime (Figure 3F). Thus, although SIFaR mutants retained daily rhythmic oscillation in their rest–activity behavior, the temporal distribution of activity was altered such that they were more active during times when control flies are normally sleeping.

3.4. SIFaR Mutants Reduce Sleep Duration

Concomitant with the increased locomotor activity, we observed that SIFaR ^attP/attP and SIFaR ^attP/MI08811 flies significantly reduced sleep duration across most of the 24‐h day compared to control lines (Figure 4A). This constituted a ~300 and ~200 min reduction in daily sleep for SIFaR ^attP/attP and SIFaR ^attP/MI08811 flies, respectively. This reduction was statistically significant for both mutant lines during subjective daytime (Figure 4B) as well as subjective nighttime (Figure 4C), although the subjective daytime effect was relatively greater in homozygous SIFaR ^attP/attP mutants. The decreased sleep in mutants was associated with changes in sleep architecture, especially during the subjective nighttime. Both mutant lines showed evidence of a loss of nighttime sleep consolidation, with an increased number of subjective nighttime sleep bouts (Figure 4F) that were of substantially shorter duration than controls (Figure 4G). Subjective daytime sleep bout length was also reduced in SIFaR ^attP/attP mutants, but this was not recapitulated in trans‐heterozygous SIFaR ^attP/MI08811 flies, and the number of subjective daytime sleep bouts was unchanged in both mutant groups (Figure 4D,E).

FIGURE 4.

SIFaR mutants have drastically decreased sleep duration. (A) Average day eduction plot shows mean sleep (min sleep/30‐min bin) ± 95% confidence intervals for SIFaR ^attP/attP (green), SIFaR ^attP/MI08811 (magenta), SIFaR ^attP/+ (dark gray), SIFaR ^MI08811/+ (light gray) and SIFaR ^+/+ (black) flies. A two‐way ANOVA showed a significant effect of genotype (F(4, 14,304) = 1065.83, p < 0.0001, ηp ² = 0.23), time of day (F(47, 14,304) = 523.99, p < 0.0001, ηp ²  = 0.63), and a significant genotype × time of day interaction (F(188, 14,304) = 3.84, p < 0.0001, ηp ² = 0.048). *p < 0.05 for the experimental line (color‐coded by genotype) compared to all heterozygous and wildtype controls at that time point, Tukey's multiple comparisons test. (B–G) Average subjective day sleep duration (min) (B), subjective night sleep duration (min) (C), subjective day sleep bout number (D), subjective day sleep bout length (min) (E), subjective night sleep bout number (F), and subjective night sleep bout length (min) (G). For (B–G), dots depict values for individual flies and lines show means ±95% confidence intervals. Different letters above each plot indicate significant differences (at p < 0.05), Dunnett's T3 multiple comparisons test following ANOVA. SIFaR mutant flies have more, shorter nighttime sleep bouts. (H–I) Mean p(Wake) (H) and p(Doze) (I) across an average DD day are plotted for the indicated genotypes as described in A. Points are means ±95% confidence intervals. For (H), a two‐way ANOVA showed a significant effect of genotype (F(4, 14,297) = 753.34, p < 0.0001, ηp ² = 0.17), time of day (F(47, 14,297) = 271.40, p < 0.0001, ηp ² = 0.47), and a significant genotype × time of day interaction (F(188, 14,297) = 3.78, p < 0.0001, ηp ² = 0.047). For (I), a two‐way ANOVA showed a significant effect of genotype (F(4, 13,328) = 258.26, p < 0.0001, ηp ² = 0.072), time of day (F(47, 13,328) = 179.25, p < 0.0001, ηp ² = 0.39), and a significant genotype × time of day interaction (F(188, 13,328) = 3.36, p < 0.0001, ηp ² = 0.045). *p < 0.05 for the experimental line (color‐coded by genotype) compared to all heterozygous and wildtype controls at that time point, Tukey's multiple comparisons test. Note the increase in p(Wake) across most of the subjective day, and reduction in p(Doze) during the subjective night. For all graphs, n = 57–62 per genotype.

We also used DAM records to calculate conditional wake probability, p(Wake), which is a measure of sleep depth, and conditional doze probability, p(Doze), which is a measure of sleep pressure (see Section 2) [27]. We found that p(Wake) was increased compared to controls in both mutant groups. For SIFaR ^attP/attP flies, p(Wake) was increased across nearly the entire 24‐h day, while for SIFaR ^attP/MI08811 flies, this increase was restricted to the subjective daytime and the first few hours of subjective nighttime (Figure 4H). This indicates that SIFaR mutants have decreased sleep depth, which is consistent with reduced sleep bout length. Both mutant lines additionally exhibited decreases in p(Doze), but this was restricted to the subjective nighttime (Figure 4I). This suggests that nighttime sleep drive is lower in flies lacking SIFaR function, which could explain the drastic reduction in nighttime sleep in these flies.

3.5. SIFaR Mutants Increase Feeding Around the Day–Night Transition

We used the FLIC system to track feeding behavior over 6 days in DD conditions. On a group level, we found that SIFaR mutant flies increased food interaction time during the late subjective night and into the early subjective day (Figure 5A). This translated into a ~50% increase in feeding time across the 24‐h day (Figure 5B). SIFaR mutants also demonstrated an increase in the median feeding event duration, although for the transheterozygous SIFaR ^attP/MI08811 line, this was only statistically different compared to two of the three control groups (Figure 5C). FLIC feeding event duration has previously been found to correlate with hunger state, with starved flies exhibiting longer duration feeding events [38, 39]. Our data showing increased feeding event duration therefore suggests that SIFaR mutants have an elevated feeding drive. The FLIC system measures food interaction time but does not directly quantify consumption. Therefore, to supplement our FLIC assay data, we used the CAFE assay [40] to determine 24‐h food intake. Consistent with our results from the FLIC assay, SIFaR mutants showed a trend towards elevated food intake (Brown‐Forsythe ANOVA revealed a significant main effect of genotype on food consumption (F _4,49.59 = 3.907, p = 0.0078), although individual pairwise comparisons did not maintain significance after multiple test correction; Figure 5D).

FIGURE 5.

SIFaR mutants have increased feeding around the night‐day transition. (A) Average day eduction plot shows mean feeding (“licks”/30‐min bin) ± 95% confidence intervals for SIFaR ^attP/attP (green), SIFaR ^attP/MI08811 (magenta), SIFaR ^attP/+ (dark gray), SIFaR ^MI08811/+ (light gray) and SIFaR ^+/+ (black) flies. A two‐way ANOVA showed a significant effect of genotype (F(4, 12,576) = 202.62, p < 0.0001, ηp ² = 0.061), time of day (F(47, 12,576) = 444.77, p < 0.0001, ηp ² = 0.62), and a significant genotype × time of day interaction (F(4, 12,576) = 202.62, p < 0.0001, ηp ² = 0.055). *p < 0.05 for the experimental line (color‐coded by genotype) compared to all heterozygous and wildtype controls at that time point, Tukey's multiple comparisons test. (B–D) Plots depict total daily feeding time (min/day) (B), median feeding event duration (s) (C), 24‐h food consumption (μL/fly, determined with the CAFE Assay) (D), and normalized Lomb‐Scargle feeding rhythm power (E). Mutant lines show increases in total feeding time and median event duration, but no consistent change in feeding rhythm power. For (B–E), dots depict values for individual flies and lines show means ±95% confidence intervals. Different letters above each plot indicate significant differences (at p < 0.05), Dunnett's T3 multiple comparisons test following ANOVA. (F) Representative individual fly feeding records show the number of “licks”/30‐min bin over 6 days in DD at 25°C for the indicated genotypes. Data are double plotted such that each line shows 48 h of feeding data and the second day on each line is plotted again at the start of the next line. Light‐ and dark‐gray shading indicate subjective day and night, respectively. For A–C and E–F, n = 49–59 flies per genotype. For D, n = 12–13 biological replicates, each consisting of 4–5 flies.

Despite the time‐of‐day specific change in feeding duration, we did not observe consistent changes in the strength of circadian feeding–fasting rhythms, as determined by Lomb‐Scargle periodogram analysis. Thus, the feeding–fasting rhythm strength of SIFaR ^attP/attP flies was equivalent to controls, while SIFaR ^attP/MI08811 flies showed a moderate (~15%) reduction in this parameter (Figure 5E). The maintenance of feeding–fasting rhythms was evident in individual fly feeding records, which show that the overall increase in feeding duration did not eliminate rhythmic feeding patterns (Figure 5F).

3.6. SIFaR Mutations Decrease Starvation Resistance

The behavioral phenotypes associated with SIFaR mutations, including increased activity and feeding, suggest a potential dysregulation of energy homeostasis. Consistent with this possibility, we found that SIFaR mutants have drastically decreased starvation resistance. The median duration of survival was decreased to ~23 h in mutant flies, compared to ~30 h in controls (Figure 6). The decreased survival time could reflect an inability to effectively store or utilize energy reserves.

FIGURE 6.

Decreased starvation resistance in SIFaR mutants. Kaplan–Meier plot of starvation resistance. Median survival duration was 23.02 h for SIFaR ^attP/attP (green), 22.76 h for SIFaR ^attP/MI08811 (magenta), 31.98 h for SIFaR ^attP/+ (dark gray), 29.40 h for SIFaR ^MI08811/+ (light gray), and 32.80 h for SIFaR ^+/+ (black). ****p < 0.0001 for the experimental line (color‐coded by genotype) compared to all heterozygous and wildtype controls, Bonferroni‐corrected Logrank test.

4. Discussion

SIFa‐expressing neurons are positioned to integrate circadian and homeostatic signals and regulate behavioral outputs through widespread projections across much of the brain. Though a role for SIFa has been reported in the regulation of reproductive activity, sleep, and feeding, SIFaR mutants have not previously been studied in these contexts, presumably because developmental lethality has precluded monitoring of adult SIFaR mutant lines. Our finding that SIFaR mutants are adult viable upon outcrossing to the iso31 background offered the opportunity to determine the consequences of SIFaR null mutations. The behavioral changes present in these flies, such as decreased sleep, increased activity, and increased feeding, largely align with results from previous experiments that altered SIFa signaling, thereby confirming the crucial role of SIFa signaling in these processes and offering important additional insight into the mechanisms through which SIFa modulates behavior. In addition, our demonstration that SIFaR mutants exhibit profound deficits in starvation resistance further highlights the important contribution of SIFa signaling to energy storage and balance.

We observed lethality with multiple RNAi lines targeting SIFaR, as well as in SIFaR mutant stocks. However, the lethality was inconsistent across RNAi lines, specific to certain mutant allele combinations, and dependent upon genetic background. For RNAi experiments, lethality appeared to correlate with the extent of knockdown, which is dictated by the effectiveness of the specific RNAi construct and the strength of the GAL4 line used to drive expression. This may explain why lethality has previously been observed in some SIFaR RNAi experiments and not others [13, 15, 16, 31]. Lethality may also vary depending on the cellular location of knockdown. Notably, Zhang et al. recently demonstrated that SIFaR mutant lethality could be rescued by GAL4‐mediated restoration of SIFaR in neuronal subsets that most prominently included the optic lobe and subesophageal ganglion in the central brain and multiple ganglia of the ventral nerve cord [15]. These findings are consistent with the lethality we observed following nervous‐system specific SIFaR knockdown and furthermore highlight populations of cells in which SIFaR expression is sufficient to avoid lethality. Experiments targeting UAS‐SIFaR RNAi^v1783 to subsets of SIFaR‐expressing neurons would further help to identify important loci for SIFaR contributions to survival.

It is not clear whether the lethality associated with SIFaR manipulations derives from changes in SIFaR‐regulated behaviors, or from disruption of essential internal processes. However, our inducible RNAi experiments demonstrate a continued necessity for SIFaR expression in adult stages in addition to during development. We previously observed that adult‐specific electrical silencing of SIFa‐expressing neurons also led to high levels of lethality [19], consistent with an ongoing contribution of SIFa signaling to adult survival. Interestingly, SIFa mutant flies survive to adulthood, as do flies in which SIFa‐expressing neurons are constitutively ablated, indicating a complex and variable role for SIFa signaling in fly survival. In line with these results, here we found that though SIFaR mutants are viable, both constitutive silencing and adult‐specific activation of SIFaR‐expressing neurons resulted in fly death.

Our observation of decreased sleep in SIFaR mutants adds to a growing literature implicating SIFa signaling in promoting sleep. Ablation of SIFa‐expressing neurons and loss of SIFa expression due to genetic mutations or RNAi knockdown causes a severe decrease in sleep duration [16, 17, 19]. In line with these results, Park et al. reported that expression of SIFaR‐targeting RNAi molecules with panneuronal or PI‐enriched GAL4 lines reduced total sleep amount. While these manipulations are constitutive and therefore could result in developmental effects, adult‐specific optogenetic activation of SIFa‐expressing neurons induced sleep with short latency, demonstrating that SIFa is acutely sleep‐promoting in adults [18].

Although SIFaR has not previously been tested for a role in feeding regulation, the overall increase in feeding time we recorded in SIFaR mutants is of similar magnitude to that which we previously observed for SIFa mutants [19]. These results suggest that SIFa signaling normally limits feeding time. In contrast with this idea, however, Martelli et al. provided multiple lines of evidence indicating a feeding‐promoting role of SIFa‐expressing neurons [20]. They found that thermogenetic activation of SIFa‐expressing neurons increased food intake in an SIFa‐dependent manner, a result that we have independently verified. SIFa neuron activation also enhanced the behavioral approach of satiated flies to ethyl acetate (EA), a food‐related odorant, and this was associated with an increase in the response of olfactory glomerulus DM3 neurons to EA. Based on these results, they proposed a model wherein SIFa increases the appetitive drive to feed through modulation of sensitivity to food‐related stimuli. Our observation of increased feeding in both SIFa and SIFaR mutant flies is hard to square with this model, but the magnitude and direction of the effect of manipulations of SIFa signaling on feeding behavior may differ according to the nature of the manipulation. For example, chronic manipulations, such as genetic mutations, could differentially impact feeding compared to acute manipulations like thermogenetic activation. The effects may also depend on specific conditions, including the time of day and the hunger state of the flies at the time of testing. In support of such a nuanced contribution of SIFa to feeding regulation, Song et al. found that food intake was similarly increased by manipulations that are expected to oppositely affect SIFa signaling. They saw that feeding was elevated by acute and constitutive neuronal activation (via expression of TrpA1 and NaChBac, respectively), genetic silencing (via expression of a hyperpolarizing potassium channel), or prevention of neurotransmitter release (via expression of tetanus toxin) in SIFa‐expressing neurons [14].

Somewhat surprisingly, we did not see a change in the strength of locomotor activity or feeding rhythms in SIFaR mutant flies. In contrast, loss of SIFa or SIFa‐expressing neurons decreased feeding and locomotor activity rhythm strength to ~50% of control values [19]. It is unclear what accounts for these differences, although we note that the reduction in locomotor activity rhythm strength in SIFa mutants has not been consistently observed [41]. Nevertheless, despite the maintenance of normal strength rhythms, the effects of loss of SIFaR on feeding and activity were time‐of‐day specific. This was especially apparent for feeding behavior, which was most prominently increased around the time of the night‐to‐day transition. This may indicate circadian modulation of SIFaR function. Assessing the consequences of a combined loss of SIFaR and core clock genes would help to determine whether the contribution of SIFa to sleep and feeding is gated by the circadian clock, which could occur at the neuronal circuit level, through the convergence of circadian output and SIFa signaling pathways [19].

We note that our activity and feeding monitoring were carried out using a minimal, sucrose‐only food source. Though a sucrose‐only diet is standard for the behavioral paradigms that we used, it is possible that the effects of SIFaR mutations could depend on diet composition. It would therefore be of interest to conduct additional studies to determine whether the increased activity and feeding that we observed are consistent across varying diets.

We and others have previously identified putative SIFaR‐expressing cells with promoter‐based and knock‐in SIFaR‐GAL4 lines [13, 19, 42]. These tools have indicated extremely widespread SIFaR expression throughout much of the brain and ventral nerve cord, with prominent expression in the optic lobes, in sleep‐regulatory regions such as the fan‐shaped body and the mushroom body, and in gustatory and olfactory centers such as the antennal lobe and the subesophageal zone. To further map SIFaR to genetically identified cell types throughout the body, we analyzed single‐cell gene expression data from the Fly Cell Atlas project [30]. This analysis showed that SIFaR mRNA is largely restricted to neurons, in addition to a limited number of non‐neuronal cells, including glial cells, spermatocytes, male accessory gland main cells, and secretory cells of the reproductive tract (Figures S2 and S3) [9]. It is possible that expression in the latter cells serves to coordinate mating and reproductive behaviors, in line with the demonstrated role of SIFaR in mediating mating frequency and choice [13]. SIFaR mRNA is largely absent from non‐neuronal cells in other regions cataloged by the Fly Cell Atlas, including the body wall, fat body, gut, heart, leg, Malpighian tubules, oenocytes, ovaries, and trachea. We note that G protein‐coupled receptors such as SIFaR are typically expressed at low levels, which might fall below the detection sensitivity of single‐cell analyses. However, consistent with the expression profile suggested by the single‐cell datasets, we failed to detect significant SIFaR‐GAL4 expression in peripheral tissues, with the exception of putative sensory neurons in the body wall and putative sensory axons innervating multiple peripheral organs, including components of the digestive tract (Figure S3). Further studies are required to confirm the neuronal identity of these cells and to pinpoint the source of these cellular processes. However, SIFaR expression in sensory neurons of the digestive tract could allow SIFa signaling to regulate hunger and feeding via modulation of gut‐brain communication.

Single‐cell data analysis also corroborated the extensive SIFaR expression in the central and peripheral nervous systems suggested by SIFaR‐GAL4 experiments. In particular, these approaches highlight enrichment in neurons involved in the processing of multiple sensory modalities (Figure S2) [9, 13, 15, 19, 23]. This includes extensive expression throughout the optic lobes, which mediate light responses, in several olfactory receptor neuron subtypes that transduce and process food‐related cues, and in mechanosensory neurons such as antennal Johnston organ neurons that mediate sound, wind, and gravity responses. This anatomical analysis indicates that SIFaR may control sleep and feeding both directly, through expression in sleep and feeding regulatory neurons, and indirectly, through modulation of sensory processing.

For example, prominent SIFaR expression in the fan‐shaped body and the mushroom body (Figure S2) [9, 19], which have both been implicated in sleep control [43], could confer a direct effect of SIFa signaling on sleep. This would be consistent with the short‐latency sleep induction produced by optogenetic stimulation of SIFa‐expressing cells and could explain the decreased sleep drive indicated by the reduction in p(Doze) in SIFaR mutant flies. Similarly, feeding behavior may be directly influenced by SIFaR expression in feeding‐related regions such as the subesophageal zone [2]. A direct role for SIFaR‐expressing neurons in sleep and feeding and identification of relevant SIFaR neuron subsets in the control of these behaviors could be tested with behavioral monitoring during activation or inhibition of subsets of SIFaR neuron populations.

SIFaR could also have indirect effects on sleep and feeding behavior secondary to modulation of sensory processing. In this way, SIFa could act to broadly regulate sensory processing to tune gustatory and olfactory responsiveness to food cues so that hunger and appetitive drive align with activity periods, and to filter out sensory signals during normal sleep times to maximize sleep consolidation. A loss of the latter function would explain the changes in sleep architecture that we observed in SIFaR mutant flies, such as more shorter nighttime sleep bouts. It would be of interest to conduct more direct tests of the impact of SIFa signaling on sensory processing, akin to those showing modulation of olfactory responses via SIFa neuron activation [20], to determine to what extent SIFa regulates behavior through alteration of sensory circuits. Such experiments would further clarify the role of Drosophila SIFa signaling in the orchestration of behavioral outputs to optimize energy usage, and would furthermore delineate general mechanisms through which peptidergic signaling can be used to integrate external and internal signals for brain‐wide coordination of basal state and behavioral choice [9].

Funding

This work was supported by the National Science Foundation (1942167).

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Figure S1: RT‐qPCR analysis of RNAi knockdown of SIFaR. (A,B) RT‐qPCR analysis shows equivalent SIFaR mRNA expression in experimental flies in which tub‐GAL4 was used to drive UAS‐SIFaR RNAi^HMS00299 (A) or UAS‐SIFaR RNAi^HMS02785 (B) compared to control flies lacking tub‐GAL4. Dots show SIFaR expression, normalized to Rp49, for each biological replicate. Lines show means ±95% confidence intervals. Controls had considerable variability in SIFaR levels, but there was no consistent change in expression in experimental lines

Figure S2: Fly Cell Atlas single cell RNA sequencing analysis of SIFaR expression in the head and related tissues. 10× Genomics Fly Cell Atlas stringent datasets were accessed with SCope [29,30]. Images are t‐SNE visualizations, and red indicates SIFaR expression. Clusters with significant SIFaR expression are labeled. Cell types were identified based on SCope Annotation. For each labeled cluster, the number of SIFaR‐expressing cells/the total number of cells in that cluster is listed

Figure S3: Fly Cell Atlas single cell RNA sequencing analysis of SIFaR expression in the body and related tissues. 10× Genomics Fly Cell Atlas stringent datasets were accessed with SCope [29,30]. Images are t‐SNE visualizations, and red indicates SIFaR expression. Clusters with significant SIFaR expression are labeled. Cell types were identified based on SCope Annotation. For each labeled cluster, the number of SIFaR‐expressing cells/the total number of cells in that cluster is listed. Inset images show SIFaR‐GAL4 driving green fluorescent protein. In the top image, nuclear GFP (GFPn) is visible in presumed multidendritic neurons of the body wall. The bottom image shows SIFaR‐GAL4‐driven CD8:GFP expression in putative sensory axons innervating the crop and proventriculus.

Velazquez A., Cusick M. R., De S., et al., “The Drosophila SIFamide Receptor Regulates Sleep and Feeding in a Time‐Of‐Day Specific Manner,” Genes, Brain and Behavior 24, no. 6 (2025): e70043, 10.1111/gbb.70043.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.