SIFa neurons control internal states and energy balance in male fruit flies

To determine which NP is neuronally connected to both LMD and SMD (Fig 1A and 1B), we performed screening with pan-neuronal elav^c155 driver with NPs and neuropeptide receptors (NPRs)-RNAi lines (S1–S5 Files, S1 Table). We discovered that knocking down the neuronal expression of CCHa1, CCHa2, ETH, ilp4, and SIFa eliminates both LMD and SMD behaviors (S1 Table and Fig 1C and 1D). SIFa is selected from the NPs that affect both LMD and SMD because it is known to govern internal state-related activities such as sleep, hunger, and mating [40,42,44–46]. The expression pattern of SIFa in four neurons located in PI is validated by utilizing neuronal-expressing GAL80 line (S1A Fig), as well as anti-repo or anti-elav antibodies (S1B Fig). Using the GAL4^SIFa.PT driver and the elav^c155 driver, we observed a significant decrease in SIFa immunoreactivity following SIFa-RNAi treatment, thereby confirming the effective knockdown of SIFa in these cells. In contrast, when SIFa-RNAi was expressed under the control of the repo-GAL4 driver, no significant change in SIFa immunoreactivity was detected (S1C Fig). Notably, our custom-generated SIFa polyclonal antiserum, while exhibiting weaker overall signal intensity compared to previously reported antibodies [42], specifically labels SIFa neuronal cell bodies and is validated by SIFa-GAL4-mediated knockdown. This control experiment highlights the specificity of the SIFa-RNAi effect and supports the conclusion that the behavioral changes observed in SMD and LMD are likely attributable to the targeted reduction of SIFa in the intended neuronal populations.

Localized amplification of SIFa peptide level through the utilization of UAS-SIFa with GAL4^SIFa.PT influences both LMD and SMD behavior through either secretion (Fig 1E and 1F) or membrane-tethered formats (Fig 1G and 1H), suggesting that the level of SIFa peptide in SIFa neurons is important for controlling interval timing behaviors. In line with the effects of SIFa overexpression on LMD and SMD behaviors, both social isolation and sexual experience lead to an increase in SIFa transcript levels (S1D Fig). However, the SIFa peptide level remained consistent in the PI region despite variations in the social environment (S1F–S1H Fig). These findings with genetic control experiments (Fig 1I–1P) indicate that the neuronal function of the SIFa neuropeptide itself, plays a critical role in regulating interval timing behaviors.

In order to compare the distinctions between male and female SIFa-positive neurons in the central nervous system (CNS), we examined the distribution of SIFa-expressing cells in terms of their membrane and nuclear expression patterns, utilizing UAS-CD4-tdGFP and UAS-RedStinger. As previously described [43,44,42], a membrane marker expressing GAL4^SIFa.PT exhibits a broad arborization pattern in both the male and female central brain (CB) (Fig 1Q and 1R). We found no significant differences between male and female brain regions covered by the SIFa cell membrane (S1I and S1J Fig). While qualitative observations suggest more intense SIFa immunoreactivity in males and increased arborization patterns in female antennal lobes (AL), quantitative analysis showed no significant differences in regional coverage (S1I and S1J Fig). Precise morphological investigation would be necessary to discern potential sexual dimorphic differences in SIFa neuronal architecture. SIFa acts on fruitless-positive neurons via the SIFa receptor (SIFaR) and it has been reported that SIFa neurons do not express fruitless, which are responsible for the generation of male-specific neuronal circuitry [41]. Building on this foundation, we sought to determine if the sexual dimorphism in SIFa neurons contributes to the regulation of interval timing behaviors. We have validated that GAL4^SIFa.PT neurons do not label fru^FLP-positive neurons in the male brain (S1L Fig). Interval timing behaviors are unaffected by the expression of female form of doublesex, which drives female-specific splicing of downstream genes (UAS-dsx^F) (S2A and S2B Fig); transformer, a key player in female sex determination affecting dsx splicing (UAS-tra^F) (S2C and S2D Fig); or sex lethal (UAS-sxl) (S2E and S2F Fig) all of which have strong feminizing activity. According to these results and genetic control experiments (Fig 1I–1P), neurons that express SIFa are not implicated in sexual dimorphism by itself.

Four SIFa neurons located in the PI are likely the most extensively branching peptidergic neurons in Drosophila [49]. We used an interactive tool for neuron connectivity (Virtual Fly Brain) [50] to precisely determine the location of SIFa-positive neurons. We discovered that the cell bodies of SIFa neurons arborize from the posterior to the anterior region (S1K Fig). It was verified through 3D reconstruction that two dorsal cell bodies are situated further anteriorly than two ventral cell bodies (S1 Movie). Anterior-dorsal SIFa neurons (SIFa^DA) and posterior-ventral SIFa neurons (SIFa^VP) could potentially have distinct functions (S1E Fig).

The established connections and architecture of SIFa neurons have been described by Martelli and colleagues, which enhances our understanding of their functional roles within the neuronal circuitry [51]. To identify the dendritic and axonal components of SIFa-neuronal processes, we employed a similar approach to that reported by Martelli [51]. We co-expressed UAS-Denmark (a dendritic marker) with UAS-syt.eGFP (a presynaptic marker) to label postsynapses and presynapses of neurons labeled by GAL4 [52]. We discovered that dendrites of SIFa neurons span just the CB area, including the PI, AL, and posterior-ventral region of the protocerebrum (PRW), whereas presynaptic terminals cover nearly the whole brain region (magnified regions in S3A Fig). Colocalization analysis in the total brain (S3B–S3D Fig), the CB (S3E–S3G Fig), and the OL (S3H–S3J Fig) confirms the broader arborization of presynaptic terminals than dendrites.

Within the VNC, the majority of branching structures are found in the abdominal ganglion (AG) (S3K Fig). Additionally, most of these branching structures are presynaptic terminals, which are different from those found in the brain (S3L–S3N Fig). This suggests that the majority of SIFa⁺ neuronal structures in VNC are axons rather than dendrites. Compared to brain SIFa⁺ dendrites, which overlap presynaptic terminals by almost 80%, VNC SIFa⁺ dendrites only overlap presynaptic terminals by around 2%. (S3M and S3N Fig), suggesting that SIFa⁺ cells form extensive synapses each other within the brain but not in the VNC (S3O Fig). We noticed that the SIFa^2A-GAL4 strains, which were created through the knock-in (KI) lines using the site-specific integration system, exhibit robust expression exclusively in the brain region (S3P Fig). This indicates the potential existence of distinct arborization and functional differences between the dorsal and ventral SIFa neurons (S1E Fig), which may play a role in modulating physiology and behaviors.

It has been proposed that SIFa neurons might be able to utilize glutamate, a neurotransmitter, for controlling sleep [46]; however, no comprehensive analysis of neurotransmitter screening has been conducted yet. To determine which neurotransmitter (NT) was responsible for the LMD/SMD, we utilized RNAi-mediated knockdown of key genes which are necessary to produce each NT. We chose VGlut-RNAi (Vesicular glutamate transporter) to disrupt the glutamatergic (Fig 2A and 2B), ple-RNAi (pale) for the dopaminergic (DA) (Fig 2C and 2D), Gad1-RNAi (Glutamic acid decarboxylase 1) for the GABAergic (Fig 2E and 2F), Trhn-RNAi (Tryptophan hydroxylase neuronal) for the serotonergic (Fig 2G and 2H), ChAT-RNAi (Choline acetyltransferase) for the cholinergic (Fig 2I and 2J), and Hdc-RNAi (Histidine decarboxylase) for the histaminergic (Fig 2K and 2L).

By using RNAi-mediated knockdown experiments, we found that glutamatergic and dopaminergic transmission are crucial for generating SMD but not LMD behavior in SIFa-positive neurons (Fig 2A–2L). SIFa also modulates the courtship behavior of male flies [42]. Studies have shown that social isolation can reduce male courtship behavior in Drosophila melanogaster [53–55], however, courtship behavior does not change in response to sexual experience [34]. The knockdown of VGlut augmented the courtship activity of males reared in isolation, while diminishing it in males with prior sexual experience (S4A–S4D Fig). The removal of ple, on the other hand, enhances courtship behavior in both socially isolated and sexually experienced males (S4E and S4F Fig).

Notably, the sleep patterns and overall sleep duration of male flies were not influenced by the interruption of glutamatergic synaptic transmission from SIFa neurons (Fig 2M). The findings indicate that glutamatergic inputs specifically influence SMD behavior, but do not have an effect on sleep. On the other hand, dopaminergic inputs from SIFa neurons have an impact on both sleep and SMD behavior which is consistent with previous research (Fig 2M) [56,57]. To further substantiate the role of glutamate in SIFa-mediated behaviors. We targeted knockdown of VGlut receptors in SIFaR-expressing neurons. Strikingly, the knockdown of VGlut receptors in these neurons also disrupted SMD behavior, mirroring the phenotype observed upon direct suppression of glutamatergic signaling in SIFa neurons (S4G–S4L Fig). We also employed a conditional glutamatergic synaptic vesicle marker to confirm the presence of glutamatergic SIFa neurons (Figs 2P and S4M) [58]. This suggests that glutamate is an essential neurotransmitter for modulating interval timing in SIFa neurons.

Fly Scope single-cell RNA sequencing data suggest potential high-level co-expression of VGlut and ple in SIFa neurons (Fig 2N and 2O). To verify the presence of dopaminergic (DA) neurons within the SIFa neuron population, we utilized the Dop1R1-Tango system, which produces a GFP signal upon dopamine binding [59]. Our results confirm the existence of active dopamine receptors in SIFaR neurons and demonstrate that these neurons are responsive to dopamine (Fig 3A; genetic control shown in S5I Fig). Given that SIFaR^24F06 neurons have been identified as forming direct synaptic connections with SIFa neurons (Fig 3A), these findings substantiate that SIFa neurons employ DA signaling to modulate SIFaR-expressing neural circuits [60]. Additionally, we conducted RNAi experiments targeting Dop1R1, Dop1R2, DopEcR, and Dop2R receptors in SIFaR-expressing cells to elucidate the role of DA signaling in modulating interval timing mediated by SIFa neurons (S5A–S5H Fig). Our findings indicated that Dop1R1-RNAi selectively influenced SMD behavior. Conversely, the other dopamine receptors, when diminished, affected both SMD and LMD behaviors. These results indicate that diverse dopamine receptors have specific functions in modulating interval timing behaviors. We also employed a well-established genetic toolkit to analyze DA circuits and confirmed that a subset of SIFa neurons is dopaminergic (S5J and S5K Fig) [61]. This finding aligns with predictions from Flywire data, which indicate that SIFa neurons include dopaminergic neurons [62,63].

To further validate our hypothesis that SIFa neurons utilize the DA system for neurotransmission, we employed next-generation GRAB (GPCR-activation-based) sensors specifically developed for monitoring dopaminergic activity in vivo [64,65]. These sensors represent a significant advancement in neurotransmitter detection, offering high sensitivity, selectivity, and signal-to-noise properties with subsecond response kinetics and the ability to detect a wide range of dopamine concentrations [64,65]. We implemented a targeted experimental approach using the UAS-P2X2 system to achieve precise activation of SIFa neurons through ATP application [66,67]. This system enables specific neuronal activation while maintaining temporal precision, as P2X2 receptors are ATP-gated ion channels that generate rapid, nonspecific cation conductance upon ATP binding. Our experimental design involved expressing GRAB sensors in SIFaR neurons while simultaneously expressing P2X2 receptors in SIFa neurons. Upon ATP application to activate the P2X2-expressing SIFa neurons, we monitored the resulting DA signals through the GRAB sensor responses in downstream SIFaR neurons. As predicted by our previous experimental evidence supporting the presence of dopaminergic components within SIFa neurons, the GRAB sensors exhibited activation in SIFaR neurons following ATP-induced stimulation of SIFa neurons (Fig 3B–3D).

This response pattern provides compelling evidence for several key aspects of SIFa neurotransmission: First, it confirms functional dopamine release from SIFa neurons upon activation. Second, it demonstrates the existence of functional dopaminergic signaling pathways from SIFa to SIFaR neurons. Third, it validates the physiological relevance of dopaminergic co-transmission in SIFa neurons, complementing their known neuropeptidergic signaling. Our demonstration that SIFa neurons can release dopamine positions them as critical modulators in timing circuits, capable of transmitting internal state information that influences context-dependent interval timing behaviors. All these data indicate that the modulation of diverse behavioral repertoires can be achieved by the use of various combinations of neurotransmitter co-transmission in SIFa neurons.

The short neuropeptide F (sNPF) is involved in executive signaling inside local neuroendocrine cells. It functions as a co-transmitter through its receptor, sNPF-R, in specific circuits. The sNPF governs the regulation of food intake and body size [68,69], is sleep-promoting inhibitory modulator [70–72], affects olfactory memory formation [73], and control interval timing behavior [33]. sNPF signaling plays a crucial role in regulating feeding behavior in Drosophila melanogaster, influencing food intake and body size [44,68,74,75]. However, there is currently no direct evidence reported linking sNPF signaling to SIFa neurons.

Knockdown of sNPF in SIFa-expressing neurons (Fig 4A and 4B) or SIFa in sNPF-expressing cells (Fig 4C and 4D) has no impact on both LMD and SMD behavior, implying that both neuropeptide-expressing cells are mutually exclusive. Knockdown of sNPF-R in SIFa-expressing cells (Fig 4E and 4F) or SIFa in sNPF-R-expressing cells (Fig 4G and 4H) disrupts only SMD behavior, implying that sNPF-R function in SIFa-positive cells and SIFa function in sNPF-R-positive cells are required to generate SMD. SIFa transmits information to adjacent cells through the SIFaR. Inhibition of SIFaR in cells expressing sNPF leads to the disruption of both LMD and SMD behaviors (Fig 4I and 4J). Similarly, the knockdown of sNPF in cells expressing SIFaR also disrupts both behaviors (Fig 4K and 4L). When the expression of SIFaR was suppressed in cells expressing sNPF-R using sNPF-R^64H09-GAL4 drivers, only the SMD behavior was affected (S6A and S6B Fig). However, when the expression of sNPF-R was suppressed in SIFaR-expressing cells, both LMD and SMD behaviors were disrupted (S6C and S6D Fig). These data with genetic control experiments (Fig 4M–4R) indicate that the signaling of SIFa-SIFaR is regulated by sNPF-sNPF-R signaling, and that SIFa and sNPF collaborate to regulate interval timing behaviors in a specific manner.

The coexpression of SIFa with sNPF-R was verified by genetic intersection approaches (Figs 4T, S6E–S6G) and fly SCope data (S6H Fig). The extensive coexpression patterns of sNPF with SIFaR were also validated using the same methodology (S6F and S6I Fig). Upon performing GRASP using SIFa^2A-lexA in conjunction with sNPF-R^64B11-GAL4, we observed the formation of robust synapses in the PI tract and the lateral accessory lobe (LAL) area connecting them. Interestingly, when males are exposed to social isolation or sexual experience, there is an increase in synaptic signals around the PI region where SIFa cells are located (S6J Fig). This indicates that the synapses between SIFa cells expressing sNPF-R become stronger (S6K–S6M Fig) since we have found that SIFa cells express sNPF-R (Figs 4T, S6E and S6G). In contrast, we found no synapses between SIFa^2A and sNPF-R^64H09 in VNC (S6J Fig). These findings demonstrate that the synaptic plasticity among SIFa cells in the brain plays a crucial role in regulating interval timing behaviors.

To investigate the response of SIFa neurons following the activation of sNPF neurons in the brain, we used the ATP/P2X2 system [76] in an ex vivo preparation to stimuli sNPF cells and simultaneously recorded Ca²⁺ influx in SIFa using GCaMP6 [77] (Fig 4U–4W). To selectively stimulate SIFa neurons, the adenosine triphosphate (ATP)-gated cation channel P2X2 was expressed in sNPF neurons to allow specific depolarization by ATP application, expressed using the sNPF^2A-GAL4 driver. The Ca²⁺ fluctuations were tracked in these neurons using fluorescent microscopy in conjunction with a genetically encoded calcium indicator, GCaMP6, which was expressed under the control of the LexA^SIFa.PT driver. Upon activation of sNPF cells via 1mM ATP perfusion, strong Ca²⁺ responses were elicited in SIFa cells (Fig 4U–4W). A similar timescale of Ca²⁺ responses has been observed in the temperature coding of central circadian circuits [78] but is different from the time scale of Ca²⁺ responses of glucose-sensing neurons in the brain [79]. Therefore, our GCaMP responses align with the neuronal signaling cascades occurring within brain interneuron circuits. In contrast, no change in GCaMP fluorescence was detected in the control group treated with artificial hemolymph (AHL) buffer. These findings demonstrate that sNPF neuronal activation strongly activates SIFa neurons.

The cells that express both sNPF and SIFaR are predominantly found in the AG (shown by yellow dotted lines labeled as “cell” in S6F Fig). This indicates that the sNPF-positive cells responsible for SIFa-SIFaR signaling to induce SMD are located in the VNC rather than the brain. The results suggest that SIFa signals originating from the brain and sNPF signals originating from the VNC create a feedback or feedforward loop to modulate the internal states of the CNS in male flies when they are exposed to varying social environments. The internal states created by the interaction of these two neuropeptides and their receptors, which signal through the brain to VNC, are crucial components of the circuit responsible for interval timing behaviors (Fig 4S).

The activity of SIFa neurons can be changed by a number of different stimuli [44,49]. However, the precise mechanisms by which they regulate SIFa neuronal activity remain unknown. To determine whether neuronal activities undergo alterations in SIFa neurons associated with interval timing, we utilized the TRIC (transcriptional reporters for sensing Ca²⁺) system [80]. TRIC serves as a valuable complement to functional Ca²⁺ imaging by integrating long-term changes in neuronal activity and providing genetic access to neurons based on their activity. Given that both LMD and SMD require at least 6–12 h of social isolation or sexual interaction [29,81], repeated sensory inputs could potentially lead to the accumulation of the modified transcription factor within the nucleus of activated neurons in vivo. Indeed, social isolation or sexual experiences affected the neural activity of GAL4^SIFa.PT-labeled neurons (Fig 5A). Male flies with social isolation or sexual experience exhibited robust TRIC fluorescence in the PI region (Fig 5B and 5C). In contrast, the TRIC fluorescence in the prow (PRW) region becomes weakened in males raised in isolation and stronger in males with sexual experience (Fig 5D and 5E). Considering the similarity of the control RFP signals across conditions, we conclude that social isolation and sexual experience alter Ca²⁺ levels in SIFa neurons in a comparable yet distinct manner (Fig 5J).

Next, to determine if the temporal activation of SIFa neurons may generate distinct internal states for MD in the absence of social isolation of sexual experience, we expressed the heat-sensitive Drosophila cation channel TrpA1 in SIFa neurons and then transferred the experimental group to the activation temperature (29 °C). Surprisingly, flies expressing TrpA1 in SIFa neurons at the activation temperature exhibited a SMD than flies maintained at 22 °C (Fig 5F) compared to genetic control (Fig 5H and 5I). However, the temporal activation of SIFa neurons did not have an impact on courtship behavior (Fig 5G). This indicates that the MD and the level of courtship activity are controlled separately by the activity of SIFa neurons. Stimulation of SIFa neurons resulted in an elevation in food consumption, as assessed using the EX-Q (excreta quantification) method [82] (S7A and S7B Fig) and the colorimetric food intake assay [83] (S7C and S7D Fig). Notably, the temporary deactivation of SIFa neurons through the expression of shi^ts did not have any impact on the MD or the level of courtship activity (Fig 5L and 5N) within the temperature range of 22–29 °C. Nevertheless, the temporary deactivation of SIFa neurons leads to a decrease in food consumption in male flies (S7E–S7H Fig) as previously described by Martelli and colleagues’ report in female flies [44]. These findings indicate that activating SIFa-positive neurons is sufficient to generate specific internal states that lead to reduced MDs and increased food intake. However, it is not sufficient to alter courtship activities (Fig 5K). Moreover, the deactivation of SIFa neurons has the potential of generating internal states that decrease food consumption [51], but it does not have the ability to alter the MD or courtship behavior (Fig 5Q).

We then tried to alter the neuronal activity of SIFa-positive neurons during social isolation and sexual experiences by expressing various modifiers of neuronal activity with GAL4^SIFa.PT. By expressing TNT (tetanus toxin light chain) to block synaptic transmission in SIFa neurons, we observed that both LMD and SMD were impaired (S7I and S7J Fig). However, food intake was shown to be elevated under these circumstances (S7K–S7L Fig). In contrast to TNT expression, potassium channels KCNJ2/OrkΔC [84] or bacterial sodium channel NachBac expression in SIFa neurons only impaired either LMD or SMD (S7M–S7N; S7U–S7V; S7Q–S7R Fig). Notably, the food intake was partially increased by constitutive modulation of SIFa neuronal activities whether neuronal activity was activated or inhibited (S7O–S7P; S7S–S7T Fig). TNT has been used effectively in several studies to inhibit neurotransmitter and neuropeptide release, KCNJ2/OrkΔC prevents membrane depolarization, and NachBac induces sodium conductance, which causes cell depolarization [85]. Thus, in accordance with genetic control experiments (S8G–S8J Fig), our research suggests that the release of neurotransmitter and neuropeptide vesicles is necessary for the transition of internal states, leading to the production of both LMD and SMD, as well as regulating food intake (S7W Fig).

When TrpA1 artificially stimulated SIFa neurons while simultaneously knocking down SIFa, the MD remained the same (Fig 5O). However, there was a modest increase in courtship activity (Fig 5P). The data support our hypothesis that altering internal states for interval timing activities requires augmentation between SIFa synaptic transmission and SIFa release (S7W Fig).

Even though calcium activity successfully represents the internal states that determine the MD of male flies, it is still unknown why similar neuronal alteration affect LMD and SMD in different ways (S7M–S7N; S7Q–S7R; S7U–S7V Fig). Thus, we used DenMark and syt.eGFP to measure the synaptic plasticity of SIFa neurons in various conditions due to their capacity to detect broad changes in synaptic structure. DenMark signals in the brains of grouped (naïve), singly reared (single), and sexually experienced (exp.) males were comparable; however, syt.eGFP signals in the brains of group reared males were significantly stronger than those in the brains of both singly reared and sexually experienced males (Fig 6A–6E). Similar to the brain, the syt.eGFP signals in the VNC of singly reared and sexually experienced males were significantly weaker than in the VNC of grouped males (Fig 6F–6L). The findings indicate that significant alterations in the postsynaptic region, rather than the presynaptic region, occur in the CNS of males who are in groups, socially isolated, or undergo sexual experience (Fig 6M). These variations in extensive structural synaptic changes may explain why various neuronal activity alterations influence LMD and SMD in different ways.

Finally, we sought to identify circuits downstream of GAL4^SIFa.PT neurons. At first, we used a recently developed system for unbiased trans-synaptic labeling: trans-Tango, which induces both myrGFP and mtdTomato to be produced by certain presynaptic neurons and their post-synaptic partners through an engineered signaling pathway [86]. When trans-Tango was driven by GAL4^SIFa.PT, we observed a significant overlap of 40%–45% between SIFa neurons and SIFa trans-Tango signals in the PI and AG region (S8A–S8C Fig). These regions are critical for processing sensory inputs and controlling reproductive behaviors, respectively. We hypothesize that the SIFa neurons, through their extensive projections, form a circuitry that translates social experiences into changes in MD. This finding not only suggests that SIFa neurons establish synaptic connections with each other, which supports the results obtained from the DenMark and syt.eGFP experiments (S3O Fig) but also corroborates the synaptic connectivity patterns previously reported [45]

SIFa neurons project to the protocerebral bridge (PB), which demonstrates several fundamental wiring principles within the central complex (CX), indicating that PB performs crucial computational tasks in the fly brain, such as the transformation of sensory (e.g., visual) input into locomotor commands [87]. SIFa neurons also project to noduli (No) in the CX, which are involved in olfactory processing and memory formation [88,89], and the PRW region, where it is attached to the subesophageal ganglion (SOG), which contains the circuitry underlying feeding behavior and is involved in numerous other aspects of sensory processing and motor control [90]. Additionally, we discovered that SIFa neurons project to a small subset of OL neurons (Bottom panels in S8A Fig). The most prominent projection of SIFa neurons is the AG of the VNC, which regulates abdominal muscles, the gastric system, and reproductive organs [91]. These findings imply that SIFa neurons project to an important brain region for extremely complicated computation and to a crucial VNC region for control of reproductive behavior, all of which modulate interval timing behavior based on the social context (S8F Fig).

To examine the SIFa projections in further detail, we utilized SIFaR^24F06-GAL4, which we recently identified as a key GAL4 strain, which labels the essential VNC neurons expressing SIFaR for both LMD and SMD in AG [60]. The majority of SIFaR^24F06 neurons in the brain project to the PI, SOG, and OL regions (GFP panels of Brain in S8D Fig). In VNC, the majority of SIFaR^24F06 neurons project to the AG region RFP signals J (S8D Fig). We discovered that the projection of SIFa neurons in AG parallels the myrGFP signals of SIFaR^24F06 neurons, indicating that these AG neurons are the direct synaptic target of SIFa neurons from the brain to the VNC to modulate interval timing. (S8E Fig). Our results suggest that SIFa neurons in the PI of the brain and SIFaR neurons in the AG of the VNC are functionally linked for SIFa-SIFaR signaling (S8F Fig).

Drosophila Melanogaster were raised on cornmeal-yeast medium at similar densities to yield adults with similar body sizes. Flies were kept in 12 h light: 12 h dark cycles (LD) at 25 °C (ZT 0 is the beginning of the light phase, ZT12 beginning of the dark phase) except for some experimental manipulation. For temperature-controlled experiments, the flies were initially crossed and maintained at a constant temperature of 22 °C within an incubator. The temperature shift was initiated post-eclosion. Once the flies had emerged, they were transferred to an incubator set at an elevated temperature of 29 °C for a defined period, after which the experimental protocols were carried out. Wild-type flies were Canton-S(CS).

Following lines used in this study, Canton-S (#64349), w1118 (#3605), Df(1)Exel6234 (#7708), SIFa^2A-GAL4 (#84690), ple-RNAi (#25796), Trhn-RNAi (#25842), ChAT-RNAi (#25856), Gad1-RNAi (#28079), VGlut-RNAi (#27538), hdc-RNAi (#30489), SIFa-RNAi (#60484), sNPF-RNAi (#25867), sNPF-R-RNAi (#27507), SIFaR-RNAi (#34947), SIFaR^24F06-GAL4 (#49087), sNPF-R^64B11-GAL4 (#41288), sNPF-R^64H09-GAL4 (#46547), CCKLR17D1-RNAi (#27494), CCKLR17D3-RNAi (#28333), Dimm-RANi (#38530), UAS>stop>mCD8GFP (#30125), fru^FLP (#66870), UAS-KCNJ2 (#6596), UAS-TNT (#28838), UAS-NaChBac-EGFP (#9466), SIFa[1] (#80696), SIFa[2] (#80697), UAS-myr-GFP (#32197), UAS-CD4tdGFP (#35839), UAS-Redstinger (#32222), UAS-mCD8RFP, lexAop-mCD8GFP (#32229), lexAop-nSyb-spGFP1-10, UAS-CD4-spGFP11 (#64315), UAS-mCD8-RFP (#61679), UAS-myrGFP.QUAS-mtdTomato-3xHA, trans-Tango (#77124), elav^c155; UAS-Dicer (#25750), UAS-Denmark, UAS-syt.eGFP (#33065), UAS-mCD8RFP, lexAop-mCD8GFP (#32229), UAS-Dop1R1-Tango (#68234), UAS-Dop2R-RNAi (#26001), UAS-Dop1R2-RNAi (#51423), UAS-DopEcR-RNAi (#93710) were obtained from the Bloomington Drosophila Stock Center at Indiana University. The following lines, CrzR-RNAi (#108506), PK2-R2-RNAi (#44871), and CCHa1-R-RNAi (#103055). InR-RNAi (#991), UAS-TrpA1 (#61504), UAS-ShiBirets (#66600), UAS-dsx^F (#44223), UAS-tra^F (#4590), and UAS-sxl (#55769) were obtained from the Vienna Drosophila Resource Center. The following lines, SIFa^2A-lexA (#FBA00106), SIFaR^2A-GAL4 (#FBA00102), UAS-t-SIFa-SEC, UAS-t-SIFa-ML, SIFa^PT-lexA (see Materials and methods: Generation of transgenic flies and SIFa t-Peptide (t-SIFa) generation). The GAL4^SIFa.PT was a gift from Jan A. Veenstra. UAS-OrkΔC were obtained from Nitabach MN.

To reduce the variation from genetic background, all flies were backcrossed for at least 3 generations to CS strain. For the generation of outcrosses, all GAL4, UAS, and RNAi lines employed as the virgin female stock were backcrossed to the CS genetic background for a minimum of ten generations. Notably, the majority of these lines, which were utilized for LMD assays, have been maintained in a CS backcrossed state for long-term generations subsequent to the initial outcrossing process, exceeding ten backcrosses. Based on our experimental observations, the genetic background of primary significance is that of the X chromosome inherited from the female parent. Consequently, we consistently utilized these fully outcrossed females as virgins for the execution of experiments pertaining to LMD and SMD behaviors. Contrary to the influence on LMD behaviors, we have previously demonstrated that the genetic background exerts negligible influence on SMD behaviors, as reported in our prior publication [34]. The mutants and transgenic lines utilized in this study have been previously characterized, with the exception of the novel transgenic strains that we generated and describe herein.

The MD assay in this study has been reported [34,29,28]. To enhance the efficiency of the MD assay, we utilized the Df (1) Exel6234 (DF hereafter) genetic modified fly line in this study, which harbors a deletion of a specific genomic region that includes the sex peptide receptor (SPR) [99,100]. Previous studies have demonstrated that virgin females of this line exhibit increased receptivity to males [100]. We conducted a comparative analysis between the virgin females of this line and the CS virgin females and found that both groups induced SMD. Consequently, we have elected to employ virgin females from this modified line in all subsequent studies. For naïve males, 40 males from the same strain were placed into a vial with food for 5 days. For single-reared males, males of the same strain were collected individually and placed into vials with food for 5 days. For experienced males, 40 males from the same strain were placed into a vial with food for 4 days then 80 DF virgin females were introduced into vials for last 1 day before assay. Forty DF virgin females were collected from bottles and placed into a vial for 5 days. These females provide both sexually experienced partners and mating partners for MD assays. On the fifth day after eclosion, males of the appropriate strain and DF virgin females were mildly anaesthetized by CO₂. After placing a single female into the mating chamber, we inserted a transparent film and then placed a single male on the other side of the film in each chamber. After allowing for 1 h of recovery in the mating chamber in 25 °C incubators, we removed the transparent film and recorded the mating activities. Only those males that succeeded to mate within 1 h were included for analyses. Initiation and completion of copulation were recorded with an accuracy of 10 s, and total MD was calculated for each couple. All assays were performed from noon to 4 pm. Part of genetic controls with GAL4/+ or UAS/+ lines were omitted from supplementary figures, as prior data confirm their consistent exhibition of normal LMD and SMD behaviors [34,29,28,101,102]. Hence, genetic controls for LMD and SMD behaviors were incorporated exclusively when assessing novel fly strains that had not previously been examined. In essence, internal controls were predominantly employed in the experiments, as LMD and SMD behaviors exhibit enhanced statistical significance when internally controlled. Within the LMD assay, both group and single conditions function reciprocally as internal controls. A significant distinction between the naïve and single conditions implies that the experimental manipulation does not affect LMD. Conversely, the lack of a significant discrepancy suggests that the manipulation does influence LMD. In the context of SMD experiments, the naïve condition (equivalent to the group condition in the LMD assay) and sexually experienced males act as mutual internal controls for one another. A statistically significant divergence between naïve and experienced males indicates that the experimental procedure does not alter SMD. Conversely, the absence of a statistically significant difference suggests that the manipulation does impact SMD. Hence, we incorporated supplementary genetic control experiments solely if they deemed indispensable for testing. All assays were performed from noon to 4 PM. We conducted blinded studies for every test [103,104].

To ascertain calcium levels and synaptic intensity from microscopic images, we dissected and imaged five-day-old flies of various social conditions and genotypes under uniform conditions. For group-reared (naïve) flies, the flies were reared in group condition and dissect right after 5 days of rearing without any further action. For single-reared flies, the flies were reared in single condition and dissect at the same time as group-reared flies right after 5 days of rearing without any further action. For sexual experienced flies, the flies were reared in group condition after 4 days of rearing and will be given virgins to give them sexual experience for 1 day, those flies will also be dissected at the same time as group and single-reared flies after one day. The GFP signal in the brains and VNCs was amplified through immunostaining with chicken anti-GFP, rabbit anti-DsRed, and mouse anti-nc82 primary antibodies. Image analysis was conducted using ImageJ software. For the quantification of fluorescence intensities, an investigator, blinded to the fly’s genotype, thresholded the sum of all pixel intensities within a sub-stack to optimize the signal-to-noise ratio, following established methods [105]. The total fluorescent area or region of interest (ROI) was then quantified using ImageJ, as previously reported. For CaLexA or TRIC signal quantification, we adhered to protocols detailed by Kayser and colleagues [106], which involve measuring the ROI’s GFP-labeled area by summing pixel values across the image stack. This method assumes that changes in the GFP-labeled area and intensity are indicative of alterations in the CaLexA and TRIC signal, reflecting synaptic activity. ROI intensities were background-corrected by measuring and subtracting the fluorescent intensity from a nonspecific adjacent area, as per Kayser and colleagues [106]. For normalization, nc82 fluorescence is utilized for CaLexA, while RFP signal is employed for TRIC experiments, as the RFP signal from the TRIC reporter is independent of calcium signaling [80]. For the analysis of GRASP or tGRASP signals, a sub-stack encompassing all synaptic puncta was thresholded by a genotype-blinded investigator to achieve the optimal signal-to-noise ratio. The fluorescence area or ROI for each region was quantified using ImageJ, employing a similar approach to that used for CaLexA or TRIC quantification [105]. ‘Norm. GFP Int.’ refers to the normalized GFP intensity relative to the RFP signal.

To prepare representative images for figures, grayscale channels were used for single fluorophore display to improve clarity and avoid color-based misinterpretation. For overlays involving multiple reporters (e.g., GFP, RFP, and nc82), distinct non-overlapping pseudocolors were applied, with channel identities labeled below each panel. Thresholding for all displayed images was performed conservatively and consistently across genotypes and conditions, with the primary goal of preserving visible biological signals while avoiding oversaturation. For quantified data, identical threshold settings were applied across conditions. All brightness and contrast adjustments were applied uniformly to the entire image and were restricted to linear modifications for visual clarity only. No nonlinear enhancements or selective adjustments were applied. These standardized procedures ensured both accurate visualization and reproducible quantification. Raw image data are available upon request.

To generate the SIFa^PT-lexA driver, the putative promotor sequence of the gene was amplified by PCR using wild-type genomic DNA as a template with the following primers GCCAATTGGCTGAATCTCCTGACCCTCA and GCAGATCTCTTGCAGTTTTCGGTGAGC as mentioned before [107]. The amplified DNA fragment (1482 base pairs located immediately upstream of the SIFa coding sequence) was inserted into the E2 Enhancer-lexA vector. This vector, supplied by Qidong Fungene Biotechnology Co., (http://www.fungene.tech/↗), is a derivative of the pBPLexA::p65Uw vector (available at https://www.addgene.org/26231↗). The insertion was achieved by digesting the fragment and the vector with EcoRI and XbaI restriction enzymes to create compatible sticky ends. The genetic construct was inserted into the attp2 site on chromosome III to generate transgenic flies using established techniques, a service conducted by Qidong Fungene Biotechnology Co., Ltd.

To generate the UAS-t-SIFa-ML and UAS-t-SIFa-SEC driver in Fig 1E–1H, t-peptide cDNAs were chemically synthesized with optimal Drosophila codon usage and with an optimal Drosophila Kozak translation initiation site upstream of the start methionine (CAAA) [108]. Encoded t-peptide is as follows: t-SIFa-ML, MSALLILALVGAAVAAYRKPPFNGSIFGNEQKLISEEDLGNGAGFATPVTLALVPALLATFWSLL. These cDNAs were cloned into the pUAS-attB vector. For generation of transgenic Drosophila, vectors were injected into the embryos of flies. The genetic construct was inserted into the attp40 site on chromosome II to generate transgenic flies using established techniques, a service conducted by Qidong Fungene Biotechnology Co., Ltd. (http://www.fungene.tech/↗).

To generate the SIFa-antibody in S1C Fig, the peptide sequence RDKKTLKIKMKLFI of SIFa was synthesized and conjugated to Keyhole Limpet Hemocyanin (KLH). The efficiency of the conjugation was confirmed by SDS-PAGE analysis. Healthy rabbits were immunized via multiple subcutaneous injections with the peptide-KLH conjugate mixed with Freund’s adjuvant. The immunization schedule included a primary immunization and two booster injections, each separated by 3 weeks. Two weeks after the final booster, serum was collected from the rabbits via cardiac puncture. The serum was purified using affinity chromatography, and the antibody titer and specificity were determined by ELISA. Antibody synthesis was performed by Wuhan Vapol Bioscience Company (http://www.vapolbio.com↗).

Courtship assay was performed as previously described [109], under normal light conditions in circular courtship arenas 11 mm in diameter, from noon to 4 PM Courtship latency is the time between female introduction and the first obvious male courtship behavior, such as orientation coupled with wing extensions. Once courtship began, courtship index was calculated as the fraction of time a male spent in any courtship-related activity during a 10 min period or until mating occurred.

The dissection and immunostaining protocols for the experiments are described elsewhere [28]. After 5 days of eclosion, the Drosophila brain was taken from adult flies and fixed in 4% formaldehyde at room temperature for 30 min. The sample was washed three times (5 min each) in 1% PBT and then blocked in 5% normal goat serum for 30 min. The sample next be incubated overnight at 4 °C with primary antibodies in 1% PBT, followed by the addition of fluorophore-conjugated secondary antibodies for one hour at room temperature. The brain was mounted on plates with an antifade mounting solution (Solarbio) for imaging purposes.

Samples were imaged with Zeiss LSM880. Antibodies were used at the following dilutions: Chicken anti-GFP (1:500, Invitrogen), mouse anti-nc82 (1:50, DSHB), rabbit anti-DsRed (1:500, Rockland Immunochemicals), Alexa-488 donkey anti-chicken (1:200, Jackson ImmunoResearch), Alexa-555 goat anti-rabbit (1:200, Invitrogen), Alexa-647 goat anti-mouse (1:200, Jackson ImmunoResearch).

RNA was extracted from 50 preparations of 5-day-old CS males using the RNA isolation kit (Vazyme), following the manufacturer’s protocol. And first-strand cDNA was synthesized from 1 μg of RNA template with random primers using SPARK script Ⅱ RT plus kit (SparkJade).

The expression levels of SIFa in naïve, exp, and single conditions were analyzed by quantitative real-time RT-PCR with SYBR Green qPCR MasterMix kit (Selleckchem). The primers of RT-PCR are F:5′-aagcaggagagcgagttcag-3′; R: 5′-ttcgccttgttttgtcacag-3′ [103]. qPCR reactions were performed in triplicate, and the specificity of each reaction was evaluated by dissociation curve analysis. Each experiment was replicated three times. PCR results were recorded as threshold cycle numbers (Ct). The fold change in the target gene expression, normalized to the expression of internal control gene (GAPDH) and relative to the expression at time point 0, was calculated using the 2 ^−ΔΔCT method as previously described [104]. The results are presented as the mean ± SD of three independent experiments.

Before the colocalization analysis, an investigator, blinded to the fly’s genotype, threshed the sum of all pixel intensities within a sub-stack to optimize the signal-to-noise ratio, following established methods [105]. To perform colocalization analysis of multi-color fluorescence microscopy images in this study, we employed ImageJ software [110]. In brief, we merged image channels to form a composite with accurate color representation and applied a threshold to isolate yellow pixels, signifying colocalization. The measured “area” values represented the colocalization zones between fluorophores. To determine the colocalization percentage relative to the total area of interest (e.g., GFP or RFP), we adjusted thresholds to capture the full fluorophore areas and remeasured to obtain total areas. The colocalization efficiency was calculated by dividing the colocalized area by the total fluorophore area. All samples were imaged uniformly.

To detect and quantify the activity of flies, we used the Fly Trajectory Dynamics Tracking (FlyTrDT) software. This is an open-source, custom-written Python program that utilizes the free OpenCV machine vision library and the Python Qt library. The FlyTrDT software simultaneously records the trajectory information of each fly and calculates various indicators of the group at a certain period. For each frame acquired, the moving fly is segmented using the binarization function from the OpenCV library. Subsequently, a Gaussian blur and morphological closing and opening operations were performed on the extracted foreground pixels to consolidate detected features and reducing false positives and negatives. Finally, the extraction of fly outlines was achieved using the contour detection algorithm in the OpenCV library.

Adult male flies (aged 3–7 days) were loaded into wells of white 96-well Microfluor 2 plates (Fishier) containing 300 µl food (5% sucrose and 1% agar). The fly boxes were placed in an incubator to control temperature precisely. A webcam tracked the locomotion of flies at 10 s intervals, and the data were used for sleep analysis [111]. All experiments were replicated at least three times.

To investigate Drosophila circadian rhythms, we utilized the DAM system [112], which records infrared beam breaks as flies move through glass tubes. Each DAM monitor tracked 32 individual flies, with experiments scaling to hundreds. Flies were housed in tubes with food for extended monitoring, and drugs were added to modulate behavior. Monitors were placed in incubators controlling temperature, humidity, and light to study environmental responses and transgene expression. We developed ShinyR-DAM, a free, open-source, cloud-based application for rapid data analysis, producing customizable plots and CSV files. ShinyR-DAM streamlines the analysis of LD and DD conditions, eliminating complex installations and manual dead fly detection. It leverages the R programming language’s Shiny framework, making it accessible and customizable for researchers.

The entire brain was dissected out in a plate filled with Drosophila Adult Hemolymph-Like Saline (AHL) buffer [108 mM NaCl, 5 mM KCl, 4 mM NaHCO₃, 1 mM NaH₂PO₄, 15 mM ribose, mM Hepes (pH 7.5); 300 mosM], CaCl₂ (2 mM), and MgCl₂ (8.2 mM) were added to the AHL before use to ensure the flies’ neurons remained in an active state throughout the experiment [113,114]. Calcium imaging was performed using an fluorescent microscope with a 10X objective. The Ca²⁺ indicator GCaMP6 was used to measure the Ca²⁺ signal. GCaMP6 was excited with 488 nm light and the fluorescent signals were collected at 5 Hz. ATP solution was added into the chamber to a final ATP concentration of 10 mM[119]. Regions of interest (ROIs) were manually selected from the cell body with ImageJ. Fluorescent change was calculated as (F_peak − F₀)/F₀, where F₀ was calculated from the average intensity of 50 frames of background-subtracted baseline fluorescence before optogenetic stimulation, and F_peak corresponds to the highest fluorescence after stimulation. To quantify neuronal activity in the brain region, the brains of male flies with the appropriate genotype were dissected and secured in a plastic dish. All subsequent steps were conducted as previously described.

The entire brain was dissected out in a plate filled with Drosophila Adult Hemolymph-Like Saline (AHL) buffer [108 mM NaCl, 5 mM KCl, 4 mM NaHCO₃, 1 mM NaH₂PO₄, 15 mM ribose, mM Hepes (pH 7.5); 300 mosM], CaCl₂ (2 mM), and MgCl₂ (8.2 mM) were added to the AHL before use to ensure the flies’ neurons remained in an active state throughout the experiment [113,114]. Fluorescence imaging was performed using an fluorescent microscope with a 20× objective. The Dopamine sensor rDA1m was used to measure the dopamine signal. rDA1m was excited with 555 nm light and the fluorescent signals were collected at 5 Hz. ATP solution was added into the chamber to a final ATP concentration of 10 mM [115]. Regions of interest (ROIs) were manually selected from the cell body with ImageJ. Fluorescent change was calculated as (F_peak − F₀)/F₀, where F₀ was calculated from the average intensity of 50 frames of background-subtracted baseline fluorescence before optogenetic stimulation, and F_peak corresponds to the highest fluorescence after stimulation.

For colorimetric food intake assay, flies were starved in PBS-containing vials for 2 h and fed for 15 min in vials containing 0.05% FD&C Blue dye, 7% sucrose and 5% yeast. The flies were frozen, homogenized in PBS, and centrifuged twice for 25 min each. The supernatant was measured at 625nm. Each experiment consisted of 20 flies and the assay was repeated three times [83].

Two flies were placed in a tube with 5% sucrose, 5% yeast, and 1% agar with 0.5% erioglaucine disodium blue dye. After 24 h, flies were homogenized in tubes with its excreta and centrifuged for 15 min in 13,000 rpm. The supernatant was measured at 630 nm. For TrpA1 and shi^ts thermogenetic experiments, flies were maintained and starved in 20 °C and transferred to 30 °C 30 min before testing.

The snRNAseq dataset analyzed in this paper is published in [116] and available at the Nextflow pipelines (VSN, https://github.com/vib-singlecell-nf↗), the availability of raw and processed datasets for users to explore, and the development of a crowd-annotation platform with voting, comments, and references through SCope (https://flycellatlas.org/scope↗), linked to an online analysis platform in ASAP (https://asap.epfl.ch/fca↗). For the generation of the tSNE plots, we utilized the Fly SCope website (https://scope.aertslab.org/#/FlyCellAtlas/*/welcome↗). Within the session interface, we selected the appropriate tissues and configured the parameters as follows: ‘Log transform’ enabled, ‘CPM normalize’ enabled, ‘Expression-based plotting’ enabled, ‘Show labels’ enabled, ‘Dissociate viewers’ enabled, and both ‘Point size’ and ‘Point alpha level’ set to maximum. For all tissues, we referred to the individual tissue sessions within the ‘10X Cross-tissue’ RNAseq dataset. Each tSNE visualization depicts the coexpression patterns of genes, with each color corresponding to the genes listed on the left, right, and bottom of the plot. The tissue name, as referenced on the Fly SCope website is indicated in the upper left corner of the tSNE plot. Dashed lines denote the significant overlap of cell populations annotated by the respective genes. Coexpression between genes or annotated tissues is visually represented by differentially colored cell populations. For instance, yellow cells indicate the coexpression of a gene (or annotated tissue) with red color and another gene (or annotated tissue) with green color. Cyan cells signify coexpression between green and blue, purple cells for red and blue, and white cells for the coexpression of all three colors (red, green, and blue). Consistency in the tSNE plot visualization is preserved across all figures.

Statistical analysis of MD assay was described previously [28,29,34]. More than 50 males (naïve, experienced, and single) were used for MD assay. Our experience suggests that the relative MD differences between naïve and experienced condition and singly reared are always consistent; however, both absolute values and the magnitude of the difference in each strain can vary. So, we always include internal controls for each treatment as suggested by previous studies. Therefore, statistical comparisons were made between groups that were naïvely reared, sexually experienced and singly reared within each experiment. As MD of males showed normal distribution (Kolmogorov–Smirnov tests, p > 0.05), we used two-sided Student t tests. The mean ± standard error (s.e.m) (**** = p < 0.0001, *** = p < 0.001, ** = p < 0.01, * = p < 0.05). All analysis was done in GraphPad (Prism). Individual tests and significance are detailed in Figure legends.

Besides traditional t test for statistical analysis, we added estimation statistics for all MD assays and two group comparing graphs. In short, ‘estimation statistics’ is a simple framework that—while avoiding the pitfalls of significance testing—uses familiar statistical concepts: means, mean differences, and error bars. More importantly, it focuses on the effect size of one’s experiment/intervention, as opposed to significance testing. In comparison to typical NHST plots, estimation graphics have the following five significant advantages such as (1) avoid false dichotomy, (2) display all observed values (3) visualize estimate precision (4) show mean difference distribution. And most importantly (5) by focusing attention on an effect size, the difference diagram encourages quantitative reasoning about the system under study. Thus, we conducted a reanalysis of all of our two group data sets using both standard t tests and estimate statistics. In 2019, the Society for Neuroscience journal eNeuro instituted a policy recommending the use of estimation graphics as the preferred method for data presentation.