Feeding decision-making by a single neuron via disparate neurotransmitters

Domain: neuroscience
Published: 2026-02-13
Editorial outcome: minor_revision

Abstract
Animals use gustatory information to decide whether to ingest nutritious substances or avoid toxic ones. Although certain neurons in the gustatory circuits respond to both aversive and appetitive signals, how these neurons resolve inputs with opposing valences is unknown. Here, we examine how the Drosophila melanogaster neuropeptide leucokinin (LK) affects gustatory information processing to elicit the appropriate feeding behaviors. We identify the subesophageal LK neurons (SELKs) as downstream synaptic partners of gustatory receptor neurons and show that these two groups are functionally connected. We then show that SELKs affect bitter avoidance through LK release and food intake in an acetylcholine-dependent manner. Our study uncovers a mechanism whereby strong activation of SELKs results in LK release, leading to feeding suppression, while weak activation results in acetylcholine-dependent feeding promotion. Thus, our results reveal that a single pair of neurons, SELKs, differentially controls opposing feeding behaviors via distinct neurotransmitters.

Introduction
To survive, animals must make feeding-related decisions based on the quality of the available food and their internal states. In these decisions, they use the sense of taste to discern nutritious, palatable substances, which are ingested, from potentially toxic ones, which are rejected1. In Drosophila melanogaster, gustatory receptor neurons (GRNs) are found in the peripheral taste organs, such as proboscis labella, leg tarsi, and pharynx. GRNs express gustatory receptors that sense non-volatile chemicals in the environment and send information about the quality of a potential food source to the central nervous system (CNS)2-4. Sweet and bitter tastants are sensed by distinct gustatory receptors that are expressed by functionally segregated GRNs that drive opposing feeding behaviors5: while activation of sweet-sensing GRNs promotes feeding6,7, activation of bitter-sensing GRNs leads to food aversion8-11. GRNs primarily relay taste information to the subesophageal zone (SEZ), the primary gustatory processing center in the brain that harbors sensorimotor circuits for feeding12.

The control of feeding requires complex sensorimotor processing that, even in its simplest form, involves multiple layers of interneurons between the sensory and motor neuron populations13. Further, although sweet and bitter GRNs exhibit non-overlapping arborizations in the SEZ14,15, the anatomical organization of the SEZ is considerably less structured than the highly structured glomerular arrangement of the olfactory system or the layered architecture of the visual system.

Given the more diffuse organization of the SEZ, it is conceivable that some interneurons would receive overlapping inputs from circuits encoding disparate taste modalities. Indeed, electrophysiological and calcium imaging experiments in both mammals and insects reveal that taste representation in the second-order gustatory neurons is complex, as some of these neurons respond to taste modalities with opposing valences (i.e., sweet and bitter)16-20.

One mechanism by which the complex representation of taste information in the SEZ can be resolved to instruct proper feeding behaviors is through neuromodulation. Indeed, various neuromodulatory systems integrate the metabolic needs and internal state of the animal with external stimuli, such as taste, to regulate feeding21. Some neuromodulatory systems involve the use of neuropeptides that bind their cognate receptors on target neurons and thereby alter their intrinsic properties22,23. Neuropeptides regulate a wide range of physiological states, such as hunger, thirst, and sleep24-28. Seminal studies in the crustacean stomatogastric ganglion revealed how an intricate network of neuromodulatory systems affects the sensory-motor transformation to alter circuit dynamics and behavioral output22,29. Notably, these studies showed that neurons in the ganglion employ cotransmission of neurotransmitters and neuropeptides22.

Cotransmission is a process by which neurons use more than one neurotransmitter, or neuropeptide, to communicate with their downstream targets. In this manner, a single neuron can generate diverse functional outputs that are superimposed on its synaptic connections22,23,30. The differential release of these neurotransmitters can be ensured through spatial segregation of the vesicles, stimulus intensity, or differential Ca++ sensitivity31. The capacity of a single neuron to release two orthogonal chemical signals could endow it with the ability to govern two separate behaviors in a context-dependent manner. While such neurons have been reported in various models30,32, how they produce the appropriate behavioral outcomes in response to various inputs remains elusive.

Hence, we sought to characterize the neuromodulators in the SEZ to understand how they shape the sensorimotor transformations that underlie feeding behaviors.

Results
SELKs are postsynaptic to both sweet and bitter GRNs

The SEZ circuits for taste processing, which compute feeding decisions based on the quality of food, are complex and highly interconnected. Lessons learned from studying the stomatogastric ganglion in crabs and lobsters indicate that a single ensemble of a few neurons can regulate diverse functions through the coordinated release of various neuromodulators22,23. Thus, we wished to examine whether neuropeptidergic neurons receiving input from the SEZ shape feeding decisions based on taste information from the GRNs in flies. To identify a candidate neuropeptide that could serve this function, we conducted an anatomical screen in which we initiated trans-Tango, a genetically encoded anterograde transsynaptic labeling technique33, from bitter or sweet GRNs and co-stained the brains for the postsynaptic marker and various neuropeptides (Supplementary information table). To facilitate the identification of the postsynaptic neurons, we used a configuration of trans-Tango with a nuclear red fluorescent protein (RFP) as its output34.

Our anatomical screen revealed a pair of postsynaptic partners of GRNs residing in ventral SEZ and marked by the antibody against the neuropeptide LK (Fig. 1a & b). The invertebrate neuropeptide LK has emerged as a key regulator of diverse metabolic processes including feeding35, as flies in which Lk expression is perturbed demonstrate feeding deficiencies36-38. Four groups of LK neurons in Drosophila are classified based upon their anatomical location39, and each group has distinct functions ranging from regulation of feeding and sleep24,25,28 to water homeostasis36,40,41. The pair of SEZ LK neurons identified in our screen is termed SELKs. They elaborate extensive arborizations in the SEZ where they run along the midline and branch laterally. The SELKs also project to the ventral nerve cord (VNIC)39. Due to their extensive innervation in the SEZ, SELKs are thought to affect gustatory information processing42. However, the role of SELKs in feeding is unknown.

Notably, our anatomical analysis indicates that SELKs receive input from both bitter-sensing Gr66a+ GRNs (Fig. 1a) and sweet-sensing Gr64f+ GRNs (Fig. 1b). Further, our analysis revealed that SELKs receive input from GRNs residing in anatomically distinct taste organs: the proboscis labella, leg tarsi, and pharynx (Supplementary Fig. 1a-c). We found that no other LK neuron was postsynaptic to GRNs from either modality except for a few abdominal ganglion LK neurons (Supplementary Fig. 1d-g). We did not observe any colocalization of the postsynaptic marker and LK antibodies in the absence of a genetic driver (Supplementary Fig.1h). These results indicate that SELKs are the only LK neurons in the central brain that are postsynaptic to both bitter- and sweet-sensing GRNs.

To corroborate these findings, we compared them to the electron microscopy (EM) reconstruction of a fly brain connectome43. To this end, we used the mosaic labeling approach SPARC44 to visualize a single SELK. This analysis revealed that SELKs predominantly project to the contralateral brain hemisphere and arborize in the dorsal SEZ (Supplementary Fig. 2a). Using this image as a guide, we identified both SELKs (Supplementary Fig. 2b) in the connectome (Cell type: DNg68; Body IDs: 720575940629543409 and 720575940630808827). Notably, the connectome annotation predicts that SELKs use acetylcholine (ACh) as a fast-acting neurotransmitter, with prediction scores of 0.59 and 0.66.

We next queried the presynaptic partners of SELKs in a fly connectome43,45-47. Our connectome analysis revealed that SELKs receive the majority of their synaptic inputs from ascending and central neurons (42% and 41% of all their inputs, respectively; Supplementary Fig. 2c). Only 2% of all their synaptic inputs are from 46 sensory neurons (Supplementary Fig. 2c). The majority of these sensory neurons are GRNs (37 neurons); 13 of which are bitter GRNs, additional 13 are sweet/water GRNs, and 11 are pharyngeal GRNs. Among the gustatory neurons, the pharyngeal GRNs make the largest number of synapses with SELKs (Supplementary Fig. 2d-f).

We then sought to investigate the functional connectivity between GRNs and SELKs. To this end, we expressed the optogenetic activator CsChrimson48 in bitter or sweet GRNs, and the calcium indicator GCaMP6s49 in LK neurons. We measured the activity of SELKs while artificially activating either GRN population (Fig. 1c & f). We observed a sustained elevation of calcium levels in SELKs upon stimulation of bitter GRNs by light (Fig. 1d, e). Similarly, we observed an increase in calcium levels in SELKs upon activation of sweet GRNs by light (Fig. 1g), albeit to a smaller degree than when the bitter GRNs were activated (Fig. 1h). We did not observe such an increase in calcium levels in control animals not fed with all-trans retinal (ATR), the necessary co-factor for CsChrimson (Supplementary Fig. 3a & b). Next, we sought to measure the SELK activity in response to the introduction of either bitter (Fig. 1i) or sweet (Fig. 1l) tastants to the proboscis. In fed animals, we observed an increase in GCaMP fluorescence levels in SELKs upon bitter stimulation of the proboscis (Fig. 1j), while sweet stimulation had no significant effect (Fig. 1m). Since starvation increases the sensitivity of sweet GRNs to sweet substances10,11,50,51, we sought to examine whether it would also lead to an increase in SELK response. Remarkably, we observed that in starved animals both bitter and sweet stimulation led to significant increases in GCaMP fluorescence levels in SELKs (Fig. 1k, n). These observations indicate that both bitter and sweet GRNs are presynaptic to SELKs and that the activation of either GRN population can lead to the activation of SELKs, depending on the feeding state of the animal.

Our observation that SELKs are both anatomically and functionally connected to taste modalities that elicit opposing behavioral outcomes poses an intriguing question: Could SELKs be regulating both opposing behavioral outcomes, and, if yes, how? To address this question, we characterized the contributions of SELKs to feeding behaviors, starting with their involvement in bitter taste avoidance.

To this end, we sought to inhibit the SELKs and assess the behavioral consequences. Since the other LK neurons are implicated in various aspects of feeding behavior36-38,52, we generated two driver lines, SELK1 and SELK2, with selective expression in SELKs and a few other neurons (Supplementary text, Supplementary Fig. 4). Importantly, SELKs are the only shared neurons between these two split Gal4 drivers. Therefore, we used both drivers in all subsequent experiments to examine the specific roles of SELKs in feeding behavior.

SELKs mediate bitter avoidance in an LK-dependent manner

To examine defects in bitter avoidance associated with SELKs, we used a modified optoPAD assay53 while optogenetically inhibiting SELKs via GtACR154. In this paradigm, the flies could choose between two equally sweet solutions, one of which was mixed with a low concentration of lobeline, a bitter compound (bittersweet), and the numbers of sips were scored. Control flies carrying either the driver or the effector alone as well as controls carrying both alleles but not exposed to light, exhibited bitter avoidance, taking significantly fewer sips from the bittersweet solution. By contrast, experimental flies in which SELKs were inhibited took similar numbers of sips from both solutions (Fig. 2a). These results indicate that SELK activity is necessary for bitter avoidance.

We next sought to address the involvement of LK in bitter avoidance. To this end, we tested both a published Lk mutant (LkCC9)26 and a new null mutant, termed Lk13, which we generated using CRISPR-Cas9-mediated genome editing (see Supplementary Notes, Supplementary Fig. 5a & b). To eliminate the confounding effects of the feeding deficits exhibited by LkCC9 26, we chose 1 M sucrose, a concentration at which Lk mutants exhibit comparable amount of feeding to controls (see Supplementary Notes and Supplementary Fig. 5c). We subjected the flies to a two-choice feeding assay on flyPAD, where they could choose between sweet and bittersweet, as described above. While control flies fed significantly less from the bittersweet food than from the sweet option, flies from both mutant lines took similar numbers of sips from either food option, indicating a deficiency in bitter avoidance (Fig. 2b). Remarkably, total feeding (i.e. number of sips taken from sweet + number of sips taken from bittersweet mixture) was not significantly different between the control group and either of the mutant groups (Supplementary Fig. 5d). Next, we asked whether this effect can be generalized to other bitter compounds. To this end, we replaced lobeline with either quinine or denatonium and subjected the control and mutant flies to two-choice feeding assays. While controls effectively avoided the bittersweet mixture, flies from both Lk mutant groups took similar numbers of sips from either food option, further affirming the deficiencies in bitter avoidance in the absence of LK signaling (Supplementary Fig. 5e & f). We confirmed these results in existing26 and newly generated mutants of the Lk receptor (see Supplementary Notes, Supplementary Fig. 6a-b). We observed that total feeding was also reduced in the receptor mutants (Supplementary Fig. 6c), an effect we speculate to stem from LK-independent activity of the receptor. Together, these results indicate that LK signaling is necessary for proper bitter avoidance.

To further confirm that Lk mutants are deficient in bitter avoidance, we tested whether optogenetic activation of bitter GRNs would suppress feeding in Lk mutants. To this end, we expressed CsChrimson in bitter GRNs in either Lk13 mutant or control Lk+/+ background. We presented flies in an optoPAD assay with two identical food options of 1 M sucrose and paired one with a 2-second light pulse to activate the bitter GRNs. While Lk+/+ animals strongly avoided the option paired with activation of bitter GRNs (Preference index (PI), mean=0.68, median=0.93), Lk13 mutants exhibited no such avoidance (PI mean=0.17, median=0.40) (Fig. 2c and 2d). We observed similar results comparing animals in the Lk+/+ control and LkCC9 mutant backgrounds: while activation of bitter neurons led to a strong food aversion in the control background (PI mean=0.85, median=0.91), this avoidance was abolished in LkCC9 mutants (PI mean=0.1861, median=-0.083, Supplementary Fig. 5g-h). These observations further demonstrate the necessity of LK for bitter avoidance.

We next examined whether LK expression in SELKs is required for bitter avoidance. To selectively manipulate SELKs, we searched for driver lines that label SELKs but not the other LK neurons. We identified a candidate, the Homeobox gene Sex combs reduced (Scr), since the Scr driver labels neurons in the ventral SEZ55. Further, the single-cell transcriptomic analysis of the fly brain56 shows an overlap between Scr and a small subset of LK-producing cells (Supplementary Fig. 7a), likely the SELKs. Indeed, when we expressed green fluorescent protein (GFP) under the control of the Scr driver, we observed that it labels both SELKs and no other LK neuron (Supplementary Fig. 7b-d). We then used the Scr driver to selectively knockdown Lk expression28 in SELKs using RNA interference (RNAi). First, we confirmed the efficacy of the knockdown approach by LK immunostaining. We drove expression of the Lk RNAi with the Scr driver and observed a dramatic reduction in the LK signal in SELKs (Supplementary Fig. 7e). When tested on the two-choice feeding assay, flies expressing the Lk RNAi in SELKs did not exhibit bitter avoidance (Fig. 2e). Together, these results indicate that LK expression in SELKs is necessary for bitter avoidance.

Next, we tested whether bitter avoidance could be restored by selectively reintroducing LK to SELKs in the Lk mutant background using our SELK drivers. First, we used immunohistochemistry to validate the selective expression of LK in SELKs. We used the SELK1 or SELK2 drivers to express the Lk transgene in Lk13 mutant background and stained for LK. We observed LK staining only in SELKs and not in the other LK neurons (Supplementary Fig. 8a & b). Notably, with the SELK2 driver, we observed an ectopic pair of LK+ neurons in the pars intercerebralis (Supplementary Fig. 8b). When subjected to the bitter avoidance paradigm, Lk13 mutant flies carrying either the driver or effector alleles alone exhibited no significant difference in feeding between the two food options. Conversely, flies in which LK expression is restored in SELKs using either driver exhibited bitter avoidance to a similar degree as Lk+/+ flies (Fig. 2f). These results demonstrate that the expression of LK in SELKs is sufficient for proper bitter avoidance.

Activation of SELKs induces food aversion in an LK-dependent manner

Since LK expression in SELKs is necessary for bitter avoidance, we wished to examine whether activation of SELKs is sufficient to suppress feeding. First, we examined the effects of activation of all LK neurons on feeding. To this end, we expressed CsChrimson in all LK neurons and subjected the flies to a two-choice optoPAD paradigm where the flies are presented with two identical sweet food options and feeding on one of the options triggers a pulse of light. Activation of all LK neurons resulted in a strong aversion (Fig. 3a), with a much higher preference for the sweet-only option (PI mean=0.59, median=0.85) (Fig. 3b). Remarkably, this aversion requires LK since activation of all LK neurons in the Lk13 mutants did not result in aversion (Fig. 3a). The Lk-dependence of the aversion is also manifested as a lower preference for the sweet-only option in Lk mutants (PI mean=0.090, median=0.29) than in flies with intact LK expression (Fig. 3b). We next corroborated these results in the other Lk mutant background, LkCC9. Importantly, this mutant line was generated through a Gal4 insertion into the 5’-end of the coding sequence of Lk26, and it expresses in a few non-LK neurons (Supplementary Fig. 9a). Additionally, we failed to generate a line with CsChrimson in the LkCC9 mutant background. To circumvent these shortcomings, we generated a transgenic fly line expressing LexA under the Lk promoter. This line recapitulated the expression of the Lk-Gal4 line39 with expression in a few additional neurons in the optic lobes and the anterior ventrolateral protocerebrum (Supplementary Fig. 9b). Activation of LK neurons using the Lk-LexA driver leads to robust food aversion (Supplementary Fig. 9c) and a high preference for the sweet only option (PI mean=0.64, median=0.85) (Supplementary Fig. 9d). By contrast, activation of the LK neurons using the same driver in the LkCC9 mutant background did not result in an aversion to the food paired with light (PI mean=0.20, median=0.24) (Supplementary Fig. 9d). Thus, the experiments with the LkCC9 line corroborated the results obtained in the Lk13 mutant background. Taken together, our results with both mutants reveal that LK is necessary for the effects of LK neurons on food aversion. To assess the role of SELKs in the food aversion phenotype, we used the two SELK drivers to express CsChrimson and subjected the flies to the same experimental paradigm. We observed a similar food aversion phenotype upon activation of SELKs (Fig. 3c). These observations indicate that the activation of SELKs is sufficient to drive food aversion.

We next wished to examine whether the optogenetic activation of SELKs indeed leads to secretion of the neuropeptide. To test this, we optogenetically activated SELKs at the same light intensity used in the behavioral experiments (15.46 µW.mm-2), dissected the flies, and stained the brains with antibodies against LK. We compared the numbers of puncta in the neurites of SELKs in flies subjected to light and controls kept in the dark. We observed significantly fewer puncta when SELKs are optogenetically activated, indicating LK release (Fig. 3d). Next, we examined the release of LK from SELKs upon optogenetic activation of bitter GRNs. Strikingly, we observed a significant reduction in the number of puncta in SELKs upon light activation of bitter GRNs compared to flies kept in the dark (Fig. 3e). These results demonstrate that SELKs release LK upon activation of bitter GRNs and further confirm the functional connection between bitter GRNs and SELKs. Together, these observations indicate that SELKs release LK in response to aversive gustatory stimuli and that LK release is necessary to elicit food rejection.

SELKs promote feeding via acetylcholine

Given that SELKs are also postsynaptic to sweet-sensing Gr64f+ neurons, we wished to examine whether they have an additional, opposing role in promoting food intake. To test this, we drove GtACR1 by SELK1 or SELK2 to selectively inhibit SELKs. In this paradigm, we provided the same food in both wells of optoPAD and kept the light on throughout the experiment to constantly inhibit the neurons. We used 100 mM sucrose here rather than the 1 M used in the two-choice experiments to prevent the animals from reaching satiety and keep the responses to food within a dynamic range (Supplementary Fig. 5c). We observed that the inhibition of SELKs resulted in fewer sips compared to controls (Fig. 4a). These results were corroborated by expression of GtACR1 in all LK neurons using the Lk-Gal4 driver that also resulted in a decrease in the number of sips taken (Fig. 4a). Since SELKs are the only common neurons labeled by these three drivers (SELK1, SELK2 and Lk-Gal4), we concluded that inhibition of SELKs during feeding leads to a decrease in food intake, suggesting an additional role of SELKs in promoting feeding.

In view of these results and our earlier observation that Lk mutants exhibit a decrease in food intake (Supplementary Fig. 5c), we wished to examine whether the effect of SELKs on food intake requires Lk expression. To test this, we knocked down Lk expression in SELKs using the Scr driver to express RNAi for Lk and scored the number of sips taken from 100 mM sucrose. To our surprise, rather than a decrease in the number of sips, knocking down Lk in SELKs resulted in a slight increase (Supplementary Fig. 10a). To further assess the role of Lk expression in SELKs, we attempted to rescue the decrease in food intake exhibited by Lk mutants. To this end, we restored the expression of Lk in SELKs in the Lk13 mutant background. However, this manipulation did not rescue the decreased food intake either (Supplementary Fig. 10b). We next wished to examine whether activation of sweet GRNs induce LK release from SELKs. To achieve this, we optogenetically activated sweet GRNs and scored the number of LK puncta in SELKs. Unlike the activation of bitter GRNs, the activation of sweet GRNs did not result in a decrease in the number of LK puncta in SELKs (Supplementary Fig. 10c), indicating that sweet GRNs do not induce LK secretion from SELKs. We concluded that the effect of SELKs in promoting feeding is not mediated by LK and hypothesized that SELKs regulate food intake using another neurotransmitter.

To identify the putative neurotransmitter produced by SELKs, we decided to mine the single-cell transcriptomic atlas of the fly brain56. We examined every cell with high levels of LK reads and, through a process of elimination, identified the various LK neuron subtypes. We could reliably identify ALKs using the marker genes ion transport peptide (ITP), short Neuropeptide F (sNPF), tachykinin (TK), and LKR, known to be expressed by this population25,41,57 (Supplementary Fig. 7a). Similarly, we identified lateral horn LK neurons (LHLKs) by the expression of the transcription factor apterous (AP), known to be expressed only in LHLKs among LK neurons58. The three remaining LK neurons are all positive for Scr, the SEZ marker we used in our knockdown experiments. Notably, two of these are positive for choline acetyltransferase (ChAT) transcripts, a marker for cholinergic neurons59. We, therefore, hypothesized that SELKs use acetylcholine (ACh) as the neurotransmitter that carries out the antagonistic functions to those mediated by the LK peptide. To examine whether SELKs are indeed cholinergic, we performed immunostaining experiments with antibodies against LK and ChAT. We observed colocalization of the two signals in SELKs (Fig. 4b), but not in LHLKs (Supplementary Fig. 10d) or ABLKs (Supplementary Fig. 10e). To further confirm that SELKs are cholinergic, we expressed GFP in all cholinergic neurons and stained the brains with the antibody against LK. We observed colocalization of GFP and LK staining only in SELKs (Supplementary Fig. 10f’ and f’’). Notably, the observation that SELKs are cholinergic is also in line with the EM data predictions45. Taken together, these findings reveal that SELKs produce both LK and ACh and are the only cholinergic LK neurons.

To assess the role of ACh production by SELKs in regulating food intake, we knocked down ACh production by expressing an RNAi targeting the ChAT transcript60 using the Lk driver. Since SELKs are the only cholinergic LK neurons, this manipulation should only affect ACh production by SELKs. In the no-choice paradigm where flies are presented with 100 mM sucrose in both wells, knocking down ChAT in SELKs resulted in a decrease in the number of sips compared to controls (Fig. 4c). Notably, down-regulation of ACh production in SELKs did not affect the bitter avoidance behavior (Supplementary Fig. 10g). These findings provide further evidence that SELKs modulate food intake through ACh.

To further determine how the cholinergic output from SELKs affects food intake, we sought to examine if SELK activation would influence the proboscis extension response (PER), a feeding behavior exhibited towards appetitive tastants61. As a positive control, we optogenetically activated the sweet-sensing Gr64f+ GRNs14. Activation of these neurons was sufficient to drive all motor sub-programs of PER: rostrum lifting, as well as haustellum and labella extensions, collectively constituting a full PER (Fig. 4d). Surprisingly, optogenetic activation of SELKs using SELK1, SELK2 or LK driver lines induced PER (Fig. 4d). However, the PER observed upon SELK activation was not as robust as the PER induced by activation of Gr64f+ GRNs: it occurred at lower frequencies and the proboscis was not consistently fully extended. The partial extensions typically included rostrum lifting and labella extension, but not haustellum extension. These observations indicate that SELKs are involved in regulating PER, albeit to a lesser extent than the sweet-sensing GRNs.

We next wished to determine which of the neurotransmitters produced by SELKs affects PER: is it the neuropeptide LK or the fast-acting neurotransmitter ACh? To address this, we optogenetically activated LK neurons in Lk+/+ background or LkCC9 mutant background. In these experiments, we used the Lk-LexA driver to express CsChrimson. We observed no significant difference in the PER elicited by the optogenetic activation of LK neurons in the Lk+/+ background or LkCC9 mutant background (Fig. 4e). By contrast, optogenetic activation of the LK neurons while knocking down ChAT in SELKs did not induce PER (Fig. 4f). These results demonstrate that for SELK-induced PER, ACh production is necessary while LK secretion is dispensable.

Amulet neurons are postsynaptic to SELKs and their activation promotes feeding

While neuropeptides can act extrasynaptically on distant targets, fast-acting neurotransmitters typically act synaptically. We, therefore, reasoned that the ACh-dependent, feeding-promoting effects of SELKs should be exerted synaptically. To identify the postsynaptic targets of SELKs and examine their roles in regulating food intake, we again turned to an EM reconstruction of a fly brain connectome43,46,47. Our analysis of the connectome revealed that downstream targets with which the SELKs make the most synaptic connections are either central or descending neurons. Most of these synaptic targets of SELKs are presynaptic to motor neurons that control the proboscis, and hence feeding (Supplementary Fig. 11a & b). Next, we activated SELKs in silico using a leaky integrate-and-fire computational model62. This analysis revealed that increasing the frequency of activation of SELKs elevated the activity of some descending neurons, motor neurons, and bilateral clusters of central neurons (Body IDs 720575940635211768 and 720575940604470240) as the major postsynaptic partners of both SELKs (Fig. 5a and Supplementary Fig. 11c). These clusters had been identified as projection neurons from the SEZ and termed Amulet neurons12. Interestingly, each SELK neuron makes synaptic connections with the Amulet neurons on both hemispheres (ipsilaterally and contralaterally). We found that the Amulet neurons have extensive arborizations both in the SEZ and in the protocerebrum in both brain hemispheres (Fig. 5b). To confirm that the Amulet neurons are indeed postsynaptic to SELKs, we initiated retro-Tango63 from the Amulet neurons and revealed that SELKs are presynaptic to them (Fig. 5c).

We next sought to examine the effects of the Amulet neurons on feeding. To this end, we expressed CsChrimson in these neurons and subjected the flies to the two-choice optoPAD paradigm. Strikingly, unlike the controls, the experimental flies exhibited a high preference for the food paired with light (Fig. 5d). Thus, activation of the Amulet neurons recapitulates the feeding-promoting effects of activation of SELKs. Together, these results suggest that the Amulet neurons are postsynaptic to SELKs and mediate the feeding-promoting effects of SELKs.

SELKs elicit opposing feeding behaviors based on their level of activation

Collectively, the behavioral experiments indicate a dual role for SELKs in regulating feeding: they suppress it via LK release and induce it via ACh. Thus, SELKs act both as negative and positive regulators of feeding. What is the mechanism that enables SELKs to differentially modulate feeding in opposing ways using two types of neurotransmitters?

Neuropeptides are released from dense core vesicles, which require high levels of activation for secretion64,65. By contrast, fast-acting neurotransmitters, like ACh, are released from synaptic vesicles that are smaller and closer to the synapse, and, therefore, more readily available for synaptic release66. We hypothesized that the different types of vesicles in which LK and ACh are stored enable their differential release in response to various degrees of neuronal activation. We, therefore, predicted that optogenetic activation of SELKs at different light intensities would elicit different feeding behaviors. To test this prediction, we subjected flies expressing CsChrimson in SELKs to the two-choice optoPAD paradigm, where they were given two identical food options, one of which paired with a light pulse. As controls, we used flies bearing only the CsChrimson transgene, but not the driver. We observed that at light intensities of 108, 62.38, and 15.46 µW.mm-2, the experimental flies fed significantly less from the food paired with light (Fig. 6a), whereas controls did not exhibit any preference (Fig. 6b). Strikingly, when the food is paired with a low light intensity (0.15 µW.mm-2), the experimental flies behaved in the opposite way and preferred the food paired with light, while the controls still exhibited no preference (Fig. 6b). Moreover, we observed no significant difference in the number of LK puncta in SELKs between flies exposed to this lower light intensity and flies kept in the dark (Fig. 3d). These results demonstrate that the activation of SELKs to various degrees can elicit opposing behaviors through differential neurotransmitter release. Low levels of activation lead to ACh release and induce feeding, while high levels of activation lead to LK release and food avoidance.

Methods
Fly maintenance and husbandry

All flies used in this study were maintained at 25°C, 70% humidity chambers with a 12-hour light: 12-hour dark cycle unless otherwise stated. All the animals were kept in standard cornmeal-agar-molasses media. The detailed genotypes of the animals used in this study can be found in Table 1. To minimize genetic variability, all lines used in behavioral experiments were backcrossed to the isogenic w1118 background (BDSC#5905) obtained from Bloomington Drosophila Stock Center (BDSC).

For optogenetic experiments, flies were raised in the dark and provided with food supplemented with 0.4 mM ATR (Sigma). ATR was dissolved in absolute ethanol and mixed into the standard fly food. For ATR-negative controls, equivalent amounts of ethanol were mixed in the food.

Immunohistochemistry staining and confocal imaging

Immunostaining procedures were performed as previously described71, with minor modifications. Briefly, 4-5 day old adult flies were picked and dissected in cold phosphate-buffered saline (PBS). For trans-Tango experiments, flies were raised at 18°C for 15 days. For retro-Tango experiments, flies were raised at 25°C for 15 days. Tissues were then fixed in a 4% paraformaldehyde (PFA) in 0.5% PBS-Triton (PBS-T) solution at room temperature (RT) for 30 minutes. Samples were then washed in 0.5% PBS-T, four times for 15 minutes at RT. Next, the tissues were put in 5% heat-inactivated equine or donkey serum (HIES or HIDS) in 0.5% PBS-T for 30 mins to 1 hour at RT. Subsequently, the samples were transferred to the primary antibody solution in 5% HIES or HIDS in 0.5% PBS-T and stained for 2 overnights at 4°C. After the primary antibody staining, the samples were washed with 0.5% PBS-T, four times for 15 minutes at RT, which then were transferred to the secondary antibody solution in 5% HIES or HIDS in 0.5% PBS-T and stained for another 2 overnights at 4°C. The secondary antibody solution was washed off with 0.5% PBS-T, four times for 15 minutes at RT. All the fixing, washing, blocking, and staining steps were carried out on a nutator. The samples were then mounted on a slide (Fisherbrand Superfrost Plus) in Fluoromount-G mounting medium (SouthernBiotech).

After curing overnight, the samples were imaged using Zeiss, LSM800 confocal microscopy with ZEN software (Zeiss, version 2.1). The acquired images were then processed using the Fiji software (ImageJ, v.2.14.o/1.54f). The list of antibodies used can be found in Table 2.

A representative image out of 4-5 independent brains is shown in figure panels for the immunohistochemistry experiments.

Generation of mutant and transgenic lines

Lk13 and Lkrex3 mutants were generated using CRISPR/Cas9 technology to create double-stranded DNA breaks in the coding sequence. Previously generated gRNA lines targeting the respective genes were crossed with flies expressing Cas9 in the germ line (see Table 1). The progeny was screened for any deletion mutation in the respective genes using polymerase chain reaction (PCR) and subsequent gel electrophoresis and DNA sequencing. Lines carrying the mutations were selected and backcrossed for at least 6 generations to the isogenic w1118 background (BDSC#5905).

The vectors for transgenic flies were generated using Gibson Assembly. To clone the plasmids for the split Gal4s, the Lk promoter region (2.2 kbp region upstream of the start codon) was amplified from a Canton S fly genomic DNA using PCR. p65 activation domain and Gal4 DNA binding domain were amplified from commercially available pBPp65ADZpUw (addgene26234) and pBPZpGAL4DBDUw (addgene26233) plasmids, respectively. The ChAT promoter (7.3 kbp region upstream of the start codon) was amplified from the genomic DNA of a Canton S fly. These promoter amplicons were then ligated with split Gal4 coding sequences into the pUASTattB cloning vector using Gibson Assembly.

For the construction of the Lk-LexA plasmid, the LexA.p65 coding sequence was amplified from the pBPnlsLexA::p65Uw vector (addgene 219858). This coding sequence was ligated together with the Lk promoter amplicon mentioned above using Gibson Assembly in the pUASTattB cloning vector that was linearized via restriction digestion.

To clone UAS-Lk, the coding sequence for the Lk gene was amplified from a PiggyBack vector, DmCD00771608 (PACMAN Resources). The 20XUAS IVS CsChrimson tdtomato_tr (AddGene111544) plasmid was linearized with XhoI and XbaI restriction digestion enzymes to remove the CsChrimson-tdTomato sequence. The remaining vector backbone was purified with gel extraction which then was used as a template to insert the Lk coding sequence amplicon using Gibson Assembly.

All constructed plasmids were verified via sequencing and used to generate transgenic flies via the PhiC31 system for site-directed genomic integration72 (Rainbow Transgenic Flies, Inc.). Lk-p65.AD, ChAT-p65.AD and Lk-LexA.p65 constructs were inserted into the attp40 genomic location. Lk-Gal4.DBD and ChAT-Gal4.DBD constructs were inserted into the attp2 genomic location. UAS-Lk construct was inserted into the VK00018 genomic location. Primers used in the generation and confirmation of the fly lines are listed in Table 3.

flyPAD experiments

4-5 days old male flies were used. Flies were starved for 21-24 hours on a wet Kimwipe before each experiment. Individual flies were mouth-pipetted into each arena and were allowed to feed for an hour in a temperature and humidity-controlled chamber (25°C, 70% humidity) in the dark.

We used 1 M sucrose for the sweet option and 1 M sucrose mixed with 0.1 mM of lobeline as the bittersweet in two-choice feeding assays. The food substrate was loaded into the wells of the assay in a 1% agarose solution. The data was analyzed using the script provided by the manufacturer (Easy Behavior) in MATLAB. For no-choice experiments, the same food was loaded into both wells of the arena. At the end of the experiment, the number of sips taken from each well in an arena was summed together for each fly. The sip duration data from each well in an arena was averaged for each fly.

OptoPAD experiments

4-5 days old male flies were starved for 21-24 hours on a wet Kimwipe supplemented with 0.4mM ATR before each experiment. Experiment conditions were the same as the FlyPAD experiments.

For optogenetic activation experiments, one of the food sources was paired with a 2-second light activation. The intensity of light used for activation experiments was 15.46 µW.mm-2 unless otherwise stated. For the optogenetic inhibition experiments, the LEDs were kept on throughout the experiment at a light intensity of 62.38 µW.mm-2. For both types of optogenetic experiments, a green LED was used to minimize the aversion to light.

The Preference Index (PI) was calculated using the following formula:

PI = (Number of sips sweet - Number of sips sweet+light) / (Number of sips sweet + Number of sips sweet+light)

Optogenetic PER experiments

The experimental animals were handled as stated above. Starved flies were cold-anesthetized and mounted on a coverslip using nail polish. Flies were acclimated for at least 30 minutes in the dark. Green LEDs were at an intensity of 31.23 µW.mm-2 and used to introduce two light pulses, each lasting 5 seconds, with a 5-second interval between pulses. Flies’ behavior was recorded with a UV-filter camera and scored manually. The PER is scored 1 if the full repertoire of the behavior is observed, 0.5 for the animals that only lifted their rostra and labella, and 0 if the proboscis was not extended at all. The PER scores for the two pulses were averaged per animal and the average PER score was reported on the graphs.

Statistical Analysis

For the two-choice assays, a pairwise comparison of the total number of sips taken from sweet substance versus bittersweet substance at the last time point in the assay was performed and a t-test was done to test the significance of the difference in feeding from either food source. For no-choice experiments, the number of sips taken by the experimental group was compared to that of the controls in a one-way ANOVA test.

For the two-choice OptoPAD experiments, the data was analyzed in a similar way as the two-choice FlyPAD experiments. When comparing the PIs resulting from the activation of either LK neurons or Gr66a+ neurons in control and Lk mutant backgrounds in the two-choice OptoPAD paradigm, an unpaired t-test was performed. For the PER experiments, statistical significance was tested with one-way ANOVA when comparing the scores of the experimental groups to the controls’. An unpaired t-test was performed to compare the scores of LK activation in the control and mutant background.

Transcriptome analysis

We utilized a previously published dataset for the single-cell transcriptome of the adult fly brain56. Using a custom R-script, we pooled the cells that highly express Lk (CG13480) transcripts by setting a threshold based on the 99.9th percentile values of LK reads amongst the dataset. We then performed a base-2 logarithmic transformation on the raw read counts to report the relative levels of selected marker gene expression for each cell.

Connectome analyses and data visualization

SELKs (DNg68 cell type) were identified in the female adult fly brain (FAFB) FlyWire connectome43,46,47, following manual comparison with light-microscopy staining of a single SELK. We used the v783 snapshot of the FlyWire connectome and its annotations for all the analyses. Neuron reconstructions were visualized using FlyWire neuroglancer46. For in silico activation of SELKs, we used the computational brain model and analysis described previously62 and the Python code publicly provided by Philip Shiu (https://github.com/philshiu/Drosophila_brain_model). Default parameters used for the model include: -52 mV resting potential and reset potential after spike, -45 mV spiking threshold, 20 ms membrane time scale, 5 ms time constant, 2.2 ms refractory period, 1.8 ms time delay for changes in post-synaptic neuron, and 0.275 mV synaptic weight. SELKs were stimulated for 1 s and an average of 30 stimulation trials was used. Connectivity and in silico activation analyses were based on updated synapse predictions73. All data for figure visualizations were processed and analyzed in R-Studio (2024.04.2+764).

Calcium imaging

4-5 days old male flies were prepared as described previously16. Briefly, flies were anesthetized under CO2 and all legs were removed to minimize gustatory inputs from these organs. The proboscis was glued out using a UV glue (Loctite). Individual flies were then mounted on the bottom side of a petri dish with a small hole on, upside down. The opposite side of the dish was filled with a ribose artificial hemolymph-like (AHL) solution (108 mM NaCl, 5 mM KCl, 2 mM CaCl2, 8.2 mM MgCl2, 4 mM NaHCO3, 1 mM NaH2PO4, 15 mM ribose, 5 mM HEPES, pH adjusted to 7.2-7.5, osmolarity adjusted to ~275 mOsm). A window at the base of the proboscis was dissected to expose the SEZ.

A Scientifica multiphoton galvo system was used for two-photon imaging. An excitation wavelength of 920 nm was used. The preparations were imaged with a 16x Nikon objective and imaging was performed using the SciScan software (Scientifica). Imaging volumes were acquired on 4 planes at a 256x256 pixel resolution and at a 6.1 frame/second rate (volume rate ~1.5 Hz).

A Drummond Nanoject II microinjector mounted on a micromanipulator (Scientifica) was used to administer tastant solutions to the fly proboscis during imaging. In each imaging session, the tastant was manually delivered after collecting at least 10 baseline imaging volumes. A Point Grey Firefly camera equipped with an Infinistix lens and a shortpass IR filter (850nm OD 4.0 shortpass filter, Edmund Optics) was used to monitor the tastant delivery to the proboscis. We used 1 M sucrose for the sweet tastant and 10 mM lobeline as the bitter compound. Each tastant was delivered three times to each fly. The results from the three tastant deliveries were averaged.

For the optogenetic activation, a 635 nm laser that is integrated into the microscope was used at 1 pulse per frame, at an intensity of 7.69 µW.mm-2. Three experiments were conducted per animal. The results from the three different experiments were averaged per data point.

For the analysis, images were Z-projected at maximum intensity using the Fiji software. The region of interest (ROI) was drawn manually around the cell bodies and fluorescence levels were measured per frame. A background subtraction was applied. The background fluorescence was measured from the vicinity of the ROI where there is no apparent fluorescent signal. The area of the background reading was kept identical to that of the ROI and background fluorescence was subtracted from the actual fluorescence readings of the ROI per time frame. ΔF/F was calculated as (F-F0)/F0, where F0 is the mean value of the ten frames preceding the stimulus presentation.

Neuropeptide release experiments

Experimental flies were placed in the optoPAD arena. Every 5 minutes, a green light pulse of 30 seconds is activated for an hour. At the end of the experiment, flies were collected and dissected immediately. The intensity of light used for activation experiments was 108 µW.mm-2 unless otherwise stated.

Puncta counting

Puncta were counted as described before74. Briefly, images were opened using the Fiji software (ImageJ, v.2.14.o/1.54f). The images were then collapsed on a Z-stack at maximum intensity. Difference of Gaussians were applied using Gaussian radii of 1 and 2. Yielding two images were then subtracted from each other. Using default threshold settings, puncta were analyzed using the ‘Analyze Particles’ function. For the images obtained with the activation of bitter and sweet GRNs, no size thresholding was applied (Size (pixel2)= 0-infinity). For the experiments with the SELK2 driver, a size threshold of 0.35-infinity was applied since these images had to be imaged at a higher gain.

Corrected total cell fluorescence (CTCF) measurement

CTCF of SELKs is measured to test the efficacy of Lk knockdown as previously described75. Briefly, images were collapsed on a Z-stack at maximum intensity on the Fiji software (ImageJ, v.2.14.o/1.54f). An ROI was manually drawn around the cell bodies. The integrated density and area of the ROI were measured on the software. Next, a background was selected, and the mean fluorescence of the background was measured. Finally, CTCF was calculated for each cell using the following formula:

CTCF = Integrated density - (Area x mean fluorescence of the background)

Code Availability

Custom codes used for data analyses are available at: https://github.com/Zandawala-lab/Savas-et-al-2025-Drosophila-SELK

Data Availability

The behavioral and functional imaging data generated in this study have been deposited in the Figshare database under accession code 10.6084/m9.figshare.31049989. Source data are provided as a Source Data file.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript reports a potentially exciting and novel mechanism by which a single pair of neurons—SELKs—\nin Drosophila can bidirectionally regulate feeding behavior via the dual release of two neurotransmitters: leucokinin (LK) and\nacetylcholine (ACh). The authors employ an impressive combination of anatomical mapping, optogenetics, calcium imaging,\nand behavioral assays to demonstrate that SELKs receive convergent input from both sweet- and bitter-sensing gustatory\nreceptor neurons and modulate feeding through neurotransmitter-specific outputs. High SELK activation triggers LK release\nand suppresses feeding, while low activation promotes feeding through ACh signaling. While the overall framework of dual-\ntransmitter coding for opposing behaviors is compelling, several inconsistencies within the behavioral data and mechanistic\ninterpretations warrant clarification. I listed my specific concerns below.\n1. The claim in line 65—that it is unclear whether a single neuron can release two neurotransmitters to govern separate\nbehaviors—is inaccurate. For example, prior work in C. elegans (PMID: 37769660) has demonstrated that a single neuron\ncan orchestrate multiple motor outputs via parallel modes of transmission. While the authors do reference this study in the\nDiscussion, they should still revise the statement in the Introduction to more accurately reflect existing evidence and avoid\noverstating the novelty of their findings.\n2. Figure 1d and 1g require clarification. The legend does not clearly explain the meaning of the dashed versus solid lines,\nmaking it difficult to interpret the data. Additionally, the calcium signals shown in Fig. 1g are extremely small (in the range of\n0.0005–0.001), which appears inconsistent with the data in Fig. 1h. The authors may wish to present a more representative\ntrace. Finally, the weak and noisy response of SELKs to sweet GRN activation raises questions about its physiological\nrelevance. Including SELK responses to actual sugar and bitter compounds would substantially strengthen the conclusion.\n3. The data presented in Fig. 2 raise several concerns and require clarification:\na. The optogenetic inhibition experiments in Fig. 2a lack a no-light control. Without it, it is difficult to interpret the behavioral\neffects as being due specifically to neuronal inhibition or genetic background effects.\nb. Although the authors note that 1 M sucrose was chosen to minimize baseline feeding deficits in LK mutants (line 157), the\ndata still indicate reduced feeding in these flies. As such, the observed reduction in preference for the sweet-only option\ncould result from an overall decrease in feeding (a potential floor effect), rather than a specific deficit in bitter avoidance.\nc. Given that the LK13 mutant appears to feed normally on sweet-only food, it is unclear why the authors chose to use the\nLKCC9 line for the GR66a activation experiments. Using LK13 would avoid potential confounds.\nd. Despite being in an LK mutant background, flies still show a reduction in sipping from the GR66a-activated food,\nsuggesting bitter avoidance (Fig. 2c, the final group). This result conflicts with the claim that LK is required for this behavior\nand should be explained.\ne. Fig. 2e: The reduced feeding observed when LK is knocked down in SELKs appears to stem mainly from a decrease in\nsips on the sweet-only food. This contradicts the conclusion that LK from SELKs is specifically required for bitter avoidance.\nf. Fig. 2f: In the rescue experiments, the SELK2 driver appears to fail in rescuing the phenotype—or the statistical annotation\nmay be missing for that group? This needs clarification. Moreover, the apparent rescue seen with the SELK1 driver seems to\narise primarily from increased feeding on sweet-only food, again complicating the claim that LK specifically regulates bitter\navoidance without affecting sweet feeding.\nTogether, these inconsistencies weaken the central conclusion that LK from SELKs specifically mediates bitter avoidance\nwithout affecting sweet feeding. Additional controls, clearer annotations, and more careful interpretation of the data are\nneeded to resolve these issues.\n4. The interpretation of SELK activation promoting feeding based on the PER experiments in Fig. 4d is not consistent with\nthe behavioral data shown in Fig. 6a. In the PER assay, SELK neurons were activated using a green LED at 31.23 μW/mm²,\nwhich elicited partial proboscis extension and was interpreted as evidence of feeding promotion. However, in Fig. 6a, SELK\nactivation at 15.46 μW/mm² failed to promote feeding and instead induced food avoidance. Notably, feeding promotion was\nonly observed at the much lower intensity of 0.15 μW/mm². The authors should clarify this apparent inconsistency.\n5. It is difficult to assess colocalization in Fig. 5c, Extended Data Fig. 4, and Extended Data Fig. 7b due to poor image quality\nand low magnification.\n6. In Extended Data Fig. 6b, the LKr receptor mutant exhibits a reduced number of sips from the sweet solution, without a\ncorresponding change in sips from the bittersweet option. This result is not consistent with the authors’ conclusion that LK\nsignaling specifically mediates bitter avoidance but does not affect sweet feeding. The authors should clarify this\ninconsistency and explain how these results fit with their overall model.\n7. Extended Data Fig. 9 does not convincingly support the conclusions it is intended to reinforce. First, the staining shown in\nFig. 9b does not appear to include SELK cell bodies, making it unclear whether this line reliably labels SELKs. Second,\ndespite the use of this driver in an LK mutant background, flies still display strong food avoidance upon optogenetic\nactivation (Fig. 9c–d), which is inconsistent with the idea of LK-dependent feeding suppression via SELKs.\n8. The authors state that a green LED was used in the OptoPAD experiments to minimize light aversion during optogenetic\nactivation and inhibition. However, flies are generally considered to be largely insensitive to red light. Is the aversion to red\nlight specific to the OptoPAD setup?\n9. The authors should describe how the preference index was calculated in experiments such as those presented in Fig. 2d.", "reviewer_2": "This manuscript by Savaş et al. presents a conceptually innovative study showing that a single pair of leucokinin neurons in the subesophageal zone (SELKs) can drive opposing feeding behaviors in Drosophila by releasing distinct\nneurotransmitters. The authors demonstrate that SELK neurons receive direct input from both sweet- and bitter-sensing\ngustatory receptor neurons and, depending on the strength of activation, release either acetylcholine (ACh) to promote\nfeeding or leucokinin (LK) to suppress it. This dual-transmitter mechanism enables SELKs to flexibly encode both positive\nand negative valences in response to gustatory input, allowing for adaptive decision-making under sensory conflict.\nThe strength of this work lies in the integration of new genetic tools, functional imaging, behavioral assays, and connectomic\ndata to dissect a complete circuit from sensory input to motor output. The identification of Amulet neurons as downstream\ncholinergic targets further clarifies how SELK activity drives feeding. The finding that weak SELK activation promotes\nfeeding while strong activation suppresses it offers a clear, testable model for how behavioral decisions can be regulated by\ndifferential neurotransmitter release within a single neuron type.\nWhile the manuscript is well executed, a few points would benefit from further development. The downstream pathways\nmediating LK-dependent feeding suppression are less well-defined than the ACh circuit and warrant further exploration. The\nidea that transmitter release is modulated by activation strength is compelling; however, direct physiological evidence, such\nas SELK responses to the ingestion of bitter or sweet substances, would further support this claim. Finally, incorporating the\nresults of this paper into the previous computational model of gustatory processing in flies (Shiu et al, 2024) would help\nposition this work in a larger neurobiological context.\nOverall, this is a compelling and well-executed manuscript that uncovers a novel mechanism for behavioral flexibility\nthrough dual neurotransmission. The clarity of the circuit dissection, the elegance of the experimental design, and the depth\nof mechanistic insight make this work a valuable contribution to the fields of sensory neuroscience and decision-making.\nAddressing a few key questions and clarifications, as outlined below, will further strengthen the manuscript and enhance its\nimpact. Please find my detailed comments below:\nMajor comments\n1. The manuscript lacks detailed information about the initial screen that led to the identification of the SELK neurons.\nProviding a more comprehensive description of this primary screen would be valuable for the field. Specifically, it would be\nhelpful to clarify how many other neuropeptidergic neurons were identified as connected to sweet and bitter GRNs. This\ncontext would allow readers to assess whether the connectivity of SELK neurons is unique or part of a broader pattern. Are\nSELKs outliers in being connected to both sweet- and bitter-sensing GRNs, or do other peptidergic neurons exhibit similar\ndual connectivity? Including these details would strengthen the rationale for focusing on SELKs and clarify their relevance\nwithin the broader gustatory circuit architecture.\n2. The connectome analysis of SELK neurons, as presented, is insufficient. To fully support the conclusions drawn from this\nwork, the authors should include an expanded figure that visualizes the synaptic strengths and classifications of the top\ncandidate input and output partners of SELKs. This would greatly help in interpreting the circuit logic. Additionally, since\nboth bitter and sweet GRNs are annotated in FlyWire, the authors should report whether SELKs receive direct input from\neither or both classes of GRNs. At present, this critical information is lacking. More broadly, the connectivity analysis needs\nto be expanded to provide a comprehensive view of SELK connectivity. For instance, if SELKs receive input from tarsal or\npharyngeal GRNs, it would be important to demonstrate that the amputation of these organs affects the Trans-Tango\nlabeling. Addressing these points would clarify the connectivity analysis of SELK neurons.\n3. Previous studies have demonstrated that gustatory responses to both sugar and bitter compounds are modulated by the\nmetabolic state of the fly, particularly under conditions of food deprivation. Given this, it would be important to assess\nwhether the GRN-SELK functional connectivity is influenced by internal nutritional state. Do SELK responses vary\ndepending on whether flies are fed or food-deprived? If so, does the mode of neurotransmitter release (e.g., ACh vs. Lk) shift\nwith metabolic status? Addressing this question would add valuable insight into how internal state modulates circuit function\nand behavioral output and would clarify whether SELKs serve as a convergence point for both external gustatory cues and\ninternal energy needs. Could it be possible that Lk release from SELKs is involved in metabolic control of sugar intake\nand bitter avoidance?\n4. In Figure 2, the authors show that manipulating SELK neuron activity or Lk signaling alters behavioral avoidance of sugar\nmixed with lobeline. However, it is unclear whether this effect is specific to lobeline or can be generalized to other bitter\ncompounds. To strengthen the conclusion that SELK neurons broadly regulate aversive responses to bitter-sweet mixtures,\nit would be important to test additional bitter tastants, such as caffeine, denatonium, or quinine, in similar assays. If the\nobserved modulation is specific to lobeline, it may suggest compound-specific tuning within the circuit. Including additional\ndata or discussion on the generality of this effect, particularly whether SELK neuron modulation extends to other bitter\ncompounds, would provide a more comprehensive understanding of their role in gustatory processing.\n5. It is unclear whether the ingestion of sugar or bitter compounds directly triggers Lk release or activates SELK neurons.\nClarifying whether SELK activity is modulated by actual intake would help establish the physiological conditions under\nwhich SELKs are engaged. Additionally, the manuscript would benefit from a more detailed explanation of the specific\ncontexts in which SELKs regulate sugar ingestion versus bitter avoidance. Are SELKs differentially activated depending on\nstimulus valence, concentration, or internal state of the animal (e.g., hunger or satiety)? Do they function primarily in conflict\nscenarios, such as when appetitive and aversive cues are simultaneously present, or do they also play a role in more\nstraightforward gustatory decisions? Addressing these questions would clarify the computational role of SELKs within the\nbroader gustatory circuit and provide deeper insight into how they integrate competing sensory inputs to shape fly feeding\nbehavior.\n6. Please explain your findings in the context of recent work by Shiu P. et al. (Nature, 2024), “A Drosophila computational\nbrain model reveals sensorimotor processing.” This study presents a comprehensive model of gustatory and sensorimotor\nintegration in the fly brain and may offer a useful framework for interpreting your results. What is the connectivity of SELKs to\nthe rest of the PER circuit neurons that are identified in the connectome? If activation of SELKs promotes sugar ingestion via\namulet neurons, are these neurons also involved in bitter avoidance? If they are not, what neurons that are postsynaptic to\nSELKs promote bitter avoidance based on connectome data? Relating the current manuscript’s findings to this broader\ncomputational model could help contextualize the role of SELK neurons within established sensorimotor pathways and\nstrengthen the theoretical impact of the manuscript.\nMinor comments:\n7. The following sentence is misleading (lines 39-42): “Further, although sweet and bitter GRNs exhibit non-overlapping\narborizations in the SEZ14, the SEZ lacks a clear anatomical organization, unlike those found in the olfactory system (i.e.,\nglomerular organization) or the visual system (i.e., layered organization)”. The SEZ exhibits an anatomical organization that\nreflects the projection patterns of gustatory neurons, which originate from distinct chemosensory organs or convey different\nvalences. Please correct accordingly with proper citations such as Kendroud S, Bohra AA et al. Structure and development\nof the subesophageal zone of the Drosophila brain. II. Sensory compartments. J Comp Neurol. 2018 Jan 1;526(1):33-58.\n8. Please clarify the concept of co-transmission more clearly in the introduction. It remains unclear whether single synapses\ncan release multiple neurotransmitters or whether different synapses of the same neuron release distinct transmitters. While\nDale’s principle originally proposed that a neuron releases only one type of neurotransmitter, this idea has been revised in\nlight of evidence from various systems demonstrating co-release or co-transmission. However, it is still unclear\nwhether individual synapses can simultaneously release multiple neurotransmitters or if transmitter release is spatially segregated\nacross synapses within the same neuron. A more precise framing of these distinctions would help readers better understand\nthe significance of the manuscript’s findings in relation to current models of neurotransmission.\n9. The y-axis in Figures 1d and 1g is not clearly labeled—please clarify whether it represents percent ΔF/F, a fractional\nchange, or another metric. This information is critical for understanding the magnitude and biological significance of the\nneural responses. Furthermore, the scale of responses in Figures 1e and 1h is significantly different from that in Figures 1d\nand 1g. How is the % ΔF/F max calculated? This requires an explanation in the text.\n10. For consistency and clarity, please indicate the fly genotypes directly on the plots in Figures 3d and 3e, as was done for\nthe other figures. This will make it easier for readers to interpret the data without needing to cross-reference the figure\nlegend.\n11. Please provide more details on how proboscis extension behavior was scored, particularly in\ndistinguishing between full and partial responses."}, "author_response": "Response to the Reviewers’ Comments\nReviewer #1 (Remarks to the Author):\nThis manuscript reports a potentially exciting and novel mechanism by which a single pair of\nneurons—SELKs—in Drosophila can bidirectionally regulate feeding behavior via the dual\nrelease of two neurotransmitters: leucokinin (LK) and acetylcholine (ACh). The authors employ\nan impressive combination of anatomical mapping, optogenetics, calcium imaging, and\nbehavioral assays to demonstrate that SELKs receive convergent input from both sweet- and\nbitter-sensing gustatory receptor neurons and modulate feeding through neurotransmitter-specific\noutputs. High SELK activation triggers LK release and suppresses feeding, while low activation\npromotes feeding through ACh signaling. While the overall framework of dual-transmitter coding\nfor opposing behaviors is compelling, several inconsistencies within the behavioral data and\nmechanistic interpretations warrant clarification. I listed my specific concerns below.\nWe thank the reviewer for their positive feedback and thoughtful comments about our manuscript.\nWe especially appreciate their excitement about our discovery that SELKs bidirectionally regulate\nfeeding via dual neurotransmitter release and their recognition of the strength of our multipronged\napproach. We have addressed the specific points raised by the reviewer, and we feel that\nconsequently our manuscript has become clearer and more rigorous. For this, we sincerely thank\nthe reviewer. Our point-by-point responses to the reviewer’s comments are included below.\n1. The claim in line 65—that it is unclear whether a single neuron can release two\nneurotransmitters to govern separate behaviors—is inaccurate. For example, prior work in C.\nelegans (PMID: 37769660) has demonstrated that a single neuron can orchestrate multiple motor\noutputs via parallel modes of transmission. While the authors do reference this study in the\nDiscussion, they should still revise the statement in the Introduction to more accurately reflect\nexisting evidence and avoid overstating the novelty of their findings.\nWe thank the reviewer for their comment. We have edited the text in the Introduction as follows:\n“While such neurons have been reported (Huang et al. 2023), how they produce the appropriate\nbehavioral outcomes in response to various inputs remains elusive” (please see lines 71-72).\n2. Figure 1d and 1g require clarification. The legend does not clearly explain the meaning of the\ndashed versus solid lines, making it difficult to interpret the data. Additionally, the calcium signals\nshown in Fig. 1g are extremely small (in the range of 0.0005–0.001), which appears inconsistent\nwith the data in Fig. 1h. The authors may wish to present a more representative trace. Finally, the\nweak and noisy response of SELKs to sweet GRN activation raises questions about its\nphysiological relevance. Including SELK responses to actual sugar and bitter compounds would\nsubstantially strengthen the conclusion.\nIn response to this comment, we have now added a sentence in the figure legend stating: “Dotted\nlines indicate the actual data points, and the solid lines indicate the smoothened curve”.\nThe scales in panels d and g in figure 1 were different from those in panels e and h because in\npanels d and g, we reported the dF/F ratio, while in panels e and h we reported the percent dF/F.\nIn response to the reviewer’s comment, we are now reporting all the results as percent dF/F. In\naddition, we replaced the trace in panel 1d with a more representative one. Further, we changed\nthe scales in all panels such that all graphs within Figure 1 are consistent.\nThe reviewer’s comment regarding the extent of the change in our observed calcium signal led\nus to realize that, unlike what is commonly used in the literature, our calcium imaging analysis\npipeline lacked background subtraction. Thus, the changes in the fluorescence readings produced\nby our pipeline were indeed small. We now modified the analysis pipeline to include a background\nsubtraction step and analyzed the same ROIs. We added text to the Methods section describing\nthe background subtraction and replaced panels d-h to include the results produced by the new\nanalysis (please see lines 693-697). We performed the same analysis for ATR- controls and\nedited the figure and legend accordingly.\nFinally, as the reviewer suggested, we performed additional calcium imaging experiments in\nSELKs while delivering sweet and bitter substances to the fly’s proboscis. In fed flies,\nadministration of bitter but not sweet substances led to increased calcium signals in SELKs.\nIntriguingly, upon starvation, we observed a meaningful increase in GCamP fluorescence in\nSELKs while administering either bitter or sweet substances. We added text describing this\nexperiment in the Results (please see lines 136-146) and Methods sections (please see lines\n679-686) and discussed the interpretation of the data in the Discussion section (please see lines\n469-475). We thank the reviewer for suggesting these experiments and agree that they have\nstrengthened our study.\n3. The data presented in Fig. 2 raise several concerns and require clarification:\na. The optogenetic inhibition experiments in Fig. 2a lacks no-light control. Without it, it is difficult\nto interpret the behavioral effects as being due specifically to neuronal inhibition or genetic\nbackground effects.\nWe thank the reviewer for this comment. In response to it, we have added this control to Fig. 2a\nand edited the text accordingly (please see lines 164-165). We have also added no light controls\nto the experiment reported in Fig. 4a.\nTo ensure that including data from experiments conducted on different days had no confounding\neffects, we compared the total feeding of control flies bearing only the UAS-GtACR1 allele on two\ndifferent days. Indeed, we observed no differences (Response to reviewers fig.1, p-value=0.24).\nResponse to reviewers fig. 1: Comparison of total feeding of control animals on two\nexperimental days\nb. Although the authors note that 1 M sucrose was chosen to minimize baseline feeding deficits\nin LK mutants (line 157), the data still indicate reduced feeding in these flies. As such, the\nobserved reduction in preference for the sweet-only option could result from an overall decrease\nin feeding (a potential floor effect), rather than a specific deficit in bitter avoidance.\nWe thank the reviewer for this comment and for suggesting examining total feeding in these flies.\nIndeed, examination of total feeding by the control and mutant groups has helped us clarify the\ninterpretation of the data, as we discuss in our responses to the points below. We calculated the\ntotal feeding value (i.e., the sum of the numbers of sips taken from sweet only and from the\nbittersweet mixture) for each group in Figure 2b. We did not observe any significant differences\nin total feeding between groups (ANOVA, p-value = 0.76). We have now added the results of this\nanalysis as Extended Data Fig. 5d and added a sentence describing it in the Results section\n(please see lines 179-182). Finally, there are no statistically significant differences in the numbers\nof sips taken from the sweet-only option between the control group and either of the mutants\n(ANOVA, p-value=0.27).\nc. Given that the LK13 mutant appears to feed normally on sweet-only food, it is unclear why the\nauthors chose to use the LKCC9 line for the GR66a activation experiments. Using LK13 would\navoid potential confounds.\nPer the reviewer’s suggestion, we have now performed this experiment using Gr66a-Gal4 and\nUAS-CsChrimson in either w1118 background or Lk13 mutant background. As expected, while light\nactivation of bitter GRNs robustly suppressed feeding in the w1118 background, this suppression\nwas abolished in the Lk13 mutant background. We have now replaced Figures 2c and 2d with the\nresults from this new experiment, added text to the Results section to reflect this (please see lines\n193-200), and moved the results from the previous experiments to Extended Data 6f-g.\nImportantly, with the exception of the ATR- control, there is no statistically significant difference\nin total feeding between the experimental group in the mutant background and the various groups\nin the w1118 background (Response to reviewers fig. 2).\nResponse to reviewers fig. 2: Total feeding of the various groups in the experiment presented\nin Fig. 2c.\nd. Despite being in an LK mutant background, flies still show a reduction in sipping from the\nGR66a-activated food, suggesting bitter avoidance (Fig. 2c, the final group). This result conflicts\nwith the claim that LK is required for this behavior and should be explained.\nWhile attempting to address this comment of the reviewer, we noticed that regrettably we had\nmade a mistake in Figure 2c of the initial submission. Instead of showing the results of activation\nof Gr66a neurons in the LKCC9 background, we showed the results of activation of Lk neurons in\nthe LkCC9 background using the Lk-LexA driver as reported in Extended Data Fig. 9c. We have\nnow corrected this panel and moved the corrected panel to Extended Data Fig. 5g of the revised\nmanuscript. As seen in the new corrected panel in Extended Data Fig. 5g, there is no significant\ndifference in the numbers of sips taken from the sweet-only and the sweet paired with light\noptions, and a significant decrease in the preference index (Extended Data Fig. 5h). We truly\napologize for this mishap. Importantly, the results of our experiments with both mutants (Lk13 in\nFigure 2c-b and LkCC9 in Extended Data Fig. 5g-h) are consistent.\nAs the reviewer noted, LkCC9 mutants exhibit a decrease in overall feeding in this experiment. We\nreasoned that this could have been due to the combination of the number of alleles carried by\nthese flies (i.e., Gr66a-LexA and/or LexAop-CsChrimson) and the disruption of the Lk locus by\nthe introduction of Gal4 into it. Consequently, the overall health of these flies is decreased.\nConsistent with this reasoning, this decrease is observed in both control and experimental groups.\nAs the reviewer suggested, we repeated this experiment with the Lk13 mutant flies, and\nimportantly, these animals exhibited minimal decrease in food intake (Response to reviewers\nfig.2) and no aversion to the food source paired with light (Fig. 2c).\nResponse to reviewers fig. 3: Total feeding of the various groups in the experiment presented\nin Fig. 2e.\ne. Fig. 2e: The reduced feeding observed when LK is knocked down in SELKs appears to stem\nmainly from a decrease in sips on the sweet-only food. This contradicts the conclusion that LK\nfrom SELKs is specifically required for bitter avoidance.\nComparing the total feeding across groups in Fig. 2e, we observed no statistical difference\nbetween the experimental group and the Gal4 driver-only control (p-value= 0.3645). However, the\nexperimental group fed significantly less than the UAS RNAi-only control group (p-value=0.0067,\nResponse to reviewers fig. 3). We speculate that this is due to the difference in the genetic\nbackgrounds of the driver and the RNAi lines (white-rescue and vermillion-rescue, respectively).\nIn addition, we argue that had this been merely a decrease in feeding from the sweet substances,\nthe number of sips taken from the bittersweet mixture would have also decreased since it includes\nthe same concentration of sucrose.\nf. Fig. 2f: In the rescue experiments, the SELK2 driver appears to fail in rescuing the phenotype—\nor the statistical annotation may be missing for that group? This needs clarification. Moreover, the\napparent rescue seen with the SELK1 driver seems to arise primarily from increased feeding on\nsweet-only food, again complicating the claim that LK specifically regulates bitter avoidance\nwithout affecting sweet feeding.\nIn our initial evaluation, SELK2 rescue showed a trend of rescuing the deficiency in bitter\navoidance (p value=0.0765). We reasoned that the lack of statistical significance was due to the\nlow sample size (n=12). We decided to repeat this experiment for all the groups in which the\nsample size was lower than 16, namely SELK1- and SELK2-driver-only controls in the Lk13\nbackground, and SELK2 rescue in the Lk13 background. We have now updated this figure\naccordingly. Importantly, this new analysis reveals that the reintroduction of Lk in SELKs using\neither SELK1 or SELK2 drivers in the Lk13 background rescues the deficiencies in bitter\navoidance. We also compared the total feeding for this figure. Total feeding is not significantly\ndifferent across Lk13 controls and the rescue group (Response to reviewers fig. 4).\nResponse to reviewers fig. 4: Total feeding of the various groups in the experiment presented\nin Fig. 2f.\nTogether, these inconsistencies weaken the central conclusion that LK from SELKs specifically\nmediates bitter avoidance without affecting sweet feeding. Additional controls, clearer\nannotations, and more careful interpretation of the data are needed to resolve these issues.\nWe believe that in totality, the additional controls, new experiment, and new analysis that we have\nperformed according to the reviewer’s suggestions clarify our statements and interpretations of\nthe data and strengthen our conclusions. For this, we are grateful to the reviewer.\n4. The interpretation of SELK activation promoting feeding based on the PER experiments in Fig.\n4d is not consistent with the behavioral data shown in Fig. 6a. In the PER assay, SELK neurons\nwere activated using a green LED at 31.23 μW/mm², which elicited partial proboscis extension\nand was interpreted as evidence of feeding promotion. However, in Fig. 6a, SELK activation at\n15.46 μW/mm² failed to promote feeding and instead induced food avoidance. Notably, feeding\npromotion was only observed at the much lower intensity of 0.15 μW/mm². The authors should\nclarify this apparent inconsistency.\nWhen we set out to address the reviewer’s comment, we initially hypothesized that the\noptogenetic activation of SELKs at lower light intensities would elicit higher frequencies of PER.\nHowever, we observed that the optogenetic activation of SELKs at 0.15 μW/mm² led to the same\nPER score as the activation at 31.23 μW/mm² (Response to reviewers fig. 5). Therefore, we\nconclude that the feeding suppression observed with the optogenetic activation of SELKs at high\nlight intensities (Figure 6a) is independent of the expression of the PER motor programs (Figure\n4d). A possible explanation is that the suppression of feeding via Lk release from SELKs occurs\nthrough higher-order brain areas, by assigning a negative valence to the food substrate. We\ndiscuss this in the revised Discussion section.\nResponse to reviewers fig. 5: Activation of SELKs at low or high intensities of light elicits similar\nPER scores\n5. It is difficult to assess colocalization in Fig. 5c, Extended Data Fig. 4, and Extended Data Fig.\n7b due to poor image quality and low magnification.\nWe repeated the staining and changed the zoomed-in images in Extended Data Fig. 4 to images\nwith even a higher magnification. We also repeated the staining experiment for Fig. 5c and\nincluded fewer planes in the Z-stacks to increase clarity.\nRegarding Extended Data Fig. 7b, working with the Scr-Gal4 line has been challenging: the flies\nare very unhealthy and often do not produce progeny when crossed to reporter lines. The current\nimage might be difficult to interpret because of the dense labeling in the SEZ with a cytosolic GFP\nreporter. To address this, we tried to cross the Scr-Gal4 driver to several nuclear-localized\nreporters, but these crosses yielded no progeny. Thus, to confirm the effectiveness of the\nknockdown through driving RNAi by this driver, we resorted to quantifying the levels of LK in\nSELKs. To this end, we dissected brains and stained them with the Lk antibody and measured\nthe fluorescent intensity in SELKs. We found a significant decrease in LK signal in knockdown\nanimals compared to the controls. We added this graph to Extended Fig. 7 and added text to the\nResults and Methods sections (please see lines 215-217 and lines 713-720).\n6. In Extended Data Fig. 6b, the LKr receptor mutant exhibits a reduced number of sips from the\nsweet solution, without a corresponding change in sips from the bittersweet option. This result is\nnot consistent with the authors’ conclusion that LK signaling specifically mediates bitter avoidance\nbut does not affect sweet feeding. The authors should clarify this inconsistency and explain how\nthese results fit with their overall model.\nTotal feeding, in fact, was reduced in LkR mutants compared to the control group. We added a\ngraph showing these results in Extended Data Fig. 6c. We added text in the Results section\ndescribing that this reduced feeding might stem from Lk independent functions of the Lk receptor\n(please see lines 189-191).\n7. Extended Data Fig. 9 does not convincingly support the conclusions it is intended to reinforce.\nFirst, the staining shown in Fig. 9b does not appear to include SELK cell bodies, making it unclear\nwhether this line reliably labels SELKs. Second, despite the use of this driver in an LK mutant\nbackground, flies still display strong food avoidance upon optogenetic activation (Fig. 9c–d),\nwhich is inconsistent with the idea of LK-dependent feeding suppression via SELKs.\nWe repeated these staining experiments and added higher magnification images that reveal\ncolocalization of SELKs with the GFP staining. We marked the cell bodies in the merge image.\nWhile indeed mutant flies displayed some food avoidance upon optogenetic activation in the\nmutant background, it is important to note that the variability in the responses has increased and\nimportantly, resulted in a significant decrease in the preference index, as revealed by panel d.\nThese observations are in line with the results shown in Figure 3a and b.\n8. The authors state that a green LED was used in the OptoPAD experiments to minimize light\naversion during optogenetic activation and inhibition. However, flies are generally considered to\nbe largely insensitive to red light. Is the aversion to red light specific to the OptoPAD setup?\nWe observed that even the control flies were avoiding feeding from food paired with red light and\nthat this aversion was minimized or abolished with the use of green light instead.\n9. The authors should describe how the preference index was calculated in experiments such as\nthose presented in Fig. 2d.\nWe have added text in the Methods section describing how the preference index was calculated\n(please see lines 623-624).\nReviewer #2 (Remarks to the Author):\nThis manuscript by Savaş et al. presents a conceptually innovative study showing that a single\npair of leucokinin neurons in the subesophageal zone (SELKs) can drive opposing feeding\nbehaviors in Drosophila by releasing distinct neurotransmitters. The authors demonstrate that\nSELK neurons receive direct input from both sweet- and bitter-sensing gustatory receptor neurons\nand, depending on the strength of activation, release either acetylcholine (ACh) to promote\nfeeding or leucokinin (LK) to suppress it. This dual-transmitter mechanism enables SELKs to\nflexibly encode both positive and negative valences in response to gustatory input, allowing for\nadaptive decision-making under sensory conflict.\nThe strength of this work lies in the integration of new genetic tools, functional imaging, behavioral\nassays, and connectomic data to dissect a complete circuit from sensory input to motor output.\nThe identification of Amulet neurons as downstream cholinergic targets further clarifies how SELK\nactivity drives feeding. The finding that weak SELK activation promotes feeding while strong\nactivation suppresses it offers a clear, testable model for how behavioral decisions can be\nregulated by differential neurotransmitter release within a single neuron type.\nWhile the manuscript is well executed, a few points would benefit from further development. The\ndownstream pathways mediating LK-dependent feeding suppression are less well-defined than\nthe ACh circuit and warrant further exploration. The idea that transmitter release is modulated by\nactivation strength is compelling; however, direct physiological evidence, such as SELK\nresponses to the ingestion of bitter or sweet substances, would further support this claim. Finally,\nincorporating the results of this paper into the previous computational model of gustatory\nprocessing in flies (Shiu et al, 2024) would help position this work in a larger neurobiological\ncontext.\nOverall, this is a compelling and well-executed manuscript that uncovers a novel mechanism for\nbehavioral flexibility through dual neurotransmission. The clarity of the circuit dissection, the\nelegance of the experimental design, and the depth of mechanistic insight make this work a\nvaluable contribution to the fields of sensory neuroscience and decision-making. Addressing a\nfew key questions and clarifications, as outlined below, will further strengthen the manuscript and\nenhance its impact. Please find my detailed comments below:\nWe thank the reviewer for their kind words regarding the impact of our new observations, the\nelegance of the experimental design, and clarity of the manuscript. We have addressed the\nspecific points raised by the reviewer, and we feel that consequently our manuscript has\nimproved, and for this we sincerely thank the reviewer. Our point-by-point responses to the\nreviewer’s comments are included below.\nMajor comments\n1. The manuscript lacks detailed information about the initial screen that led to the identification\nof the SELK neurons. Providing a more comprehensive description of this primary screen would\nbe valuable for the field. Specifically, it would be helpful to clarify how many other neuropeptidergic\nneurons were identified as connected to sweet and bitter GRNs. This context would allow readers\nto assess whether the connectivity of SELK neurons is unique or part of a broader pattern. Are\nSELKs outliers in being connected to both sweet- and bitter-sensing GRNs, or do other\npeptidergic neurons exhibit similar dual connectivity? Including these details would strengthen the\nrationale for focusing on SELKs and clarify their relevance within the broader gustatory circuit\narchitecture.\nWe thank the reviewer for this comment and suggestion. In response to this comment, we have\nadded Supplementary Information Table 1 where we report the number of neurons we identified\nin central brain using antibodies against the various neuropeptides. We included the number of\nneurons identified by trans-Tango as postsynaptic to sweet GRNs and bitter GRNs. Our screen\nrevealed that some neuropeptidergic neurons, such as those producing LK, DH44, CRZ and DSK,\nare postsynaptic to both sweet and bitter GRNs. By contrast, neurons expressing other\nneuropeptides, such as all the SIFa neurons in central brain, are postsynaptic to sweet but not to\nbitter GRNs. We also observed instances where more neurons are postsynaptic to one modality\nthan the other (e.g., CAPA neurons).\n2. The connectome analysis of SELK neurons, as presented, is insufficient. To fully support the\nconclusions drawn from this work, the authors should include an expanded figure that visualizes\nthe synaptic strengths and classifications of the top candidate input and output partners of SELKs.\nThis would greatly help in interpreting the circuit logic. Additionally, since both bitter and sweet\nGRNs are annotated in FlyWire, the authors should report whether SELKs receive direct input\nfrom either or both classes of GRNs (Fig. 1G-J). At present, this critical information is lacking.\nMore broadly, the connectivity analysis needs to be expanded to provide a comprehensive view\nof SELK connectivity. For instance, if SELKs receive input from tarsal or pharyngeal GRNs, it\nwould be important to demonstrate that the amputation of these organs affects the Trans-Tango\nlabeling. Addressing these points would clarify the connectivity analysis of SELK neurons.\nWe thank the reviewer for this comment. To address it, we modified the Extended Data Fig. 2c-f\nand added Extended Data Fig. 11 as well as added relevant text to the Results section (please\nsee lines 119-126 & 364-373).\nThe new Extended Data Fig.2c shows the classifications of all presynaptic inputs to SELKs with\nthe numbers of synapses indicated. To achieve a more comprehensive analysis, we lowered the\nsynaptic threshold to one synapse. This analysis revealed the various bitter, sweet, and\npharyngeal GRNs that are presynaptic to SELKs. Panels d-f in Extended Data Fig. 2 show the\nEM reconstructions of the projections of these input neurons and the numbers of their synapses\nonto SELKs. We added text in the Results section to describe this analysis (please see lines 119-\n126).\nTo identify the top postsynaptic targets of SELKs, we queried the connectome and added a new\nfigure (Extended Data Fig. 11) as well as text describing the results of this analysis (please see\nlines 364-373). We discuss this analysis in more detail in response to point 6 in the reviewer’s\ncomments (please see below).\nWhile we have been working on these revisions, the connectome of the central nervous system\nof a male fly became available (Berg et al. 2025). Analysis of the male connectome revealed that,\nas we observed in the female connectome, SELKs receive synaptic inputs from diverse classes\nof neurons (Response to reviewers fig. 6a). Importantly, the analysis of the male connectome also\nrevealed that most of the sensory inputs onto SELKs are from GRNs of different modalities (i.e.,\nsweet and bitter, Response to reviewers fig. 6b-d). These observations support the notion that\nSELKs integrate information about sweet and bitter tastes in both male and female flies.\nTo examine from which taste organs SELKs receive inputs, we initiated trans-Tango with Gal4\nlines labeling GRNs exclusively from labella, legs, or pharynx (Kwon et al. 2015). In all three lines\ntested, we found colocalization of the postsynaptic trans-Tango signal and the LK antibody\nlabeling in the SELKs, indicating that SELKs receive synaptic inputs from GRNs in these three\ntaste organs. We present these data in panels a-c of the new Extended Data Fig. 1 and added\ntext in the Results section (please see lines 102-104).\nResponse to reviewers fig. 6: Analysis of the connectome dataset of a male fly reveals that\nSELKs receive synaptic inputs from GRNs\n3. Previous studies have demonstrated that gustatory responses to both sugar and bitter\ncompounds are modulated by the metabolic state of the fly, particularly under conditions of food\ndeprivation. Given this, it would be important to assess whether the GRN-SELK functional\nconnectivity is influenced by internal nutritional state. Do SELK responses vary depending on\nwhether flies are fed or food-deprived? If so, does the mode of neurotransmitter release (e.g.,\nACh vs. Lk) shift with metabolic status? Addressing this question would add valuable insight into\nhow internal state modulates circuit function and behavioral output and would clarify whether\nSELKs serve as a convergence point for both external gustatory cues and internal energy needs.\nCould it be possible that Lk release from SELKs is involved in metabolic control of sugar intake\nand bitter avoidance?\nTo address this comment, we have conducted a series of Ca++ imaging experiments on SELKs\nwhile administering bitter or sweet substances to fed or starved animals. Overall, these\nexperiments revealed that SELKs are not directly affected by starvation or satiety, and the effects\nthat we observe are most likely due to hunger-dependent modulation of sweet GRNs. We present\nthe results of these experiments below.\nThe first set of experiments revealed that SELKs respond to exposure of the fly to 10 mM lobeline\n(a bitter compound) in both starved and fed conditions, whereas they only respond to exposure\nof the fly to the sweet compound sucrose (1 M) in a food deprived (starved) fly. We added panels\ni-n to Figure 1 depicting the results of these experiments, as well as text to the Results and\nDiscussion sections (please see lines 136-144, 469-475 & 679-686).\nIn the second set of experiments, we wished to examine whether the activity of SELKs changes\ndepending on the internal state (hunger or satiety). To this end, we measured the baseline Ca++\nlevels in SELKs in starved and fed animals. We expressed GCamP6s and RFP in SELKs,\nperformed in vivo Ca++ imaging, and calculated the ratio of green to red fluorescence. As reported\n(Senapati et al. 2019, Yurgel et al. 2019), starvation does not change the baseline activity of\nSELKs (Response to reviewers fig. 7).\nTo address the question regarding neurotransmitter release, we used PER elicited by the\noptogenetic activation of SELKs as a proxy for ACh release since we had observed that this\nbehavior solely depended on ACh release from SELKs (Figure 4f). We observed that starvation\ndid not change the frequency of PER elicited by the optogenetic activation of SELKs (Response\nto reviewers fig. 8).\nNext, we measured LK release upon optogenetic stimulation of bitter GRNs in fed and starved\nconditions. In both conditions, bitter GRN stimulation resulted in a decrease in the number of LK\npuncta in SELKs, indicating secretion of the neuropeptide, as we had previously demonstrated\n(Figure 3e and Response to reviewers fig. 9). Importantly, we observed no significant effect of the\nstarvation state of the animals on the number of puncta (Response to reviewers fig. 9).\nTogether this set of experiments revealed that food deprivation increases the response of SELKs\nto sweet tastants, probably due to the sensitization of sweet GRNs upon starvation (Inagaki et al.\n2012, Marella et al., 2012, Inagaki et al. 2014, Devineni et al. 2019). By contrast, we found that\nstarvation does not affect SELK responses to bitter tastants, nor does it affect the baseline activity\nof SELKs. Finally, the mode of neurotransmission of SELKs is not affected by starvation. Taken\ntogether, we conclude that SELKs are not directly modulated by food deprivation.\nResponse to reviewers fig. 7: Baseline activity level of SELKs in fed or starved conditions\n4. In Figure 2, the authors show that manipulating SELK neuron activity or Lk signaling alters\nbehavioral avoidance of sugar mixed with lobeline. However, it is unclear whether this effect is\nspecific to lobeline or can be generalized to other bitter compounds. To strengthen the conclusion\nthat SELK neurons broadly regulate aversive responses to bitter-sweet mixtures, it would be\nimportant to test additional bitter tastants, such as caffeine, denatonium, or quinine, in similar\nassays. If the observed modulation is specific to lobeline, it may suggest compound-specific\ntuning within the circuit. Including additional data or discussion on the generality of this effect,\nparticularly whether SELK neuron modulation extends to other bitter compounds, would provide\na more comprehensive understanding of their role in gustatory processing.\nWe have now conducted experiments replacing lobeline with either quinine or denatonium in the\nbittersweet mixture and subjected the mutant flies to two-choice feeding experiments. Lk mutants\nexhibited deficiencies in bitter avoidance towards all bitter compounds tested, indicating a general\nbitter avoidance rather than an avoidance to a specific molecule. We edited the text and included\nthe results in Extended Data Fig. 5 accordingly (please see lines 182-187).\nResponse to reviewers fig. 8: Optogenetic activation of SELKs in starved or fed conditions by\nhigh or low intensities of light does not affect the PER score.\n5. It is unclear whether the ingestion of sugar or bitter compounds directly triggers Lk release or\nactivates SELK neurons. Clarifying whether SELK activity is modulated by actual intake would\nhelp establish the physiological conditions under which SELKs are engaged. Additionally, the\nmanuscript would benefit from a more detailed explanation of the specific contexts in which\nSELKs regulate sugar ingestion versus bitter avoidance. Are SELKs differentially activated\ndepending on stimulus valence, concentration, or internal state of the animal (e.g., hunger or\nsatiety)? Do they function primarily in conflict scenarios, such as when appetitive and aversive\ncues are simultaneously present, or do they also play a role in more straightforward gustatory\ndecisions? Addressing these questions would clarify the computational role of SELKs within the\nbroader gustatory circuit and provide deeper insight into how they integrate competing sensory\ninputs to shape fly feeding behavior.\nIngestion is not necessary for triggering Lk release from SELKs or for their activation, as activation\nof the bitter GRNs or sweet GRNs without exposing the flies to actual compounds was sufficient\nto elicit Ca++ responses in SELKs. That said, ingestion is likely to also elicit these responses since\nanalysis of the EM reconstructed connectome reveals that SELKs make more synaptic\nconnections with pharyngeal GRNs than with labellar ones.\nRegarding the state-dependent effects, as we discussed in detail in our response to point 3 by\nthe reviewer, our analysis revealed that SELKs are not directly modulated by food deprivation.\nThus, we believe that the regulation of SELK is primarily input-dependent (i.e., it relies mainly on\nactivation of sweet GRNs versus bitter GRNs). Further, our interpretation of our data is that SELKs\ndo not code for sensory conflicts but rather the valence of the stimulus since they can be activated\nby sweet and bitter tastants alone.\nResponse to reviewers fig. 9: The internal state (starvation or satiety) does not affect LK release\nfrom SELKs upon optogenetic activation of bitter GRNs.\n6. Please explain your findings in the context of recent work by Shiu P. et al. (Nature, 2024), “A\nDrosophila computational brain model reveals sensorimotor processing.” This study presents a\ncomprehensive model of gustatory and sensorimotor integration in the fly brain and may offer a\nuseful framework for interpreting your results. What is the connectivity of SELKs to the rest of the\nPER circuit neurons that are identified in the connectome? If activation of SELKs promotes sugar\ningestion via amulet neurons, are these neurons also involved in bitter avoidance? If they are not,\nwhat neurons that are postsynaptic to SELKs promote bitter avoidance based on connectome\ndata? Relating the current manuscript’s findings to this broader computational model could help\ncontextualize the role of SELK neurons within established sensorimotor pathways and\nstrengthen the theoretical impact of the manuscript.\nWe thank the reviewer for this suggestion and agree that the analysis that we have now included,\nas the reviewer had suggested, strengthens our argument and enhances the manuscript. Analysis\nof the connectome dataset suggests that SELKs are presynaptic to descending neurons that are,\nin turn, presynaptic to motor neurons controlling the proboscis, including MN8. As the reviewer\nsuggested, we ran the leaky integrate-and-fire computational model, developed by Shiu et al.\n(2024), on the EM reconstruction of a fly brain and activated SELKs in silico. This simulation\nrevealed that activation of SELKs leads to activation of MN8 (CB0911) and another unclassified\nproboscis motor neuron (CB0762). To present these findings, we have added Extended Data Fig.\n11. Importantly, while these findings are in line with our observations that activation of SELKs\ninduces PER, they also indicate that Amulet neurons are not part of the PER circuitry, as\noptogenetic activation of Amulet neurons does not elicit PER. Thus, rather than being an integral\npart of the PER circuit, the role of the Amulet neurons might be to assign a positive valence to the\nfood being consumed.\nInhibition of amulet neurons via the optogenetic inhibitor GtAcR1 did not affect bitter avoidance\n(Response to reviewers fig. 10a). Furthermore, Amulet neurons do not express the Lk receptor\n(Response to reviewers fig. 10b). Therefore, we think that SELKs elicit food aversion through an\nextra-synaptic downstream target. In an attempt to identify this target, we carried out Lkr\nknockdown experiments using different drivers and testing animals for bitter avoidance. However,\nwe were unable to identify such a target. To identify the downstream targets of SELKs that are\ninvolved in bitter avoidance, a more exhaustive screen, which is outside the scope of this\nmanuscript, will be needed.\nA.\nb.\nResponse to reviewers fig. 10: Amulet neurons are not a part of the bitter taste circuit. a,\nInhibition of the Amulet neurons does not influence bitter avoidance. b, GFP expression driven\nby the SS32423 split Gal4 line (green) does not colocalize with tdTomato expression driven by\nthe LkR-LexA driver line (magenta). Blue shows the neuropil staining. Scale bars are 10 μm.\nMinor comments:\n7. The following sentence is misleading (lines 39-42): “Further, although sweet and bitter GRNs\nexhibit non-overlapping arborizations in the SEZ14, the SEZ lacks a clear anatomical\norganization, unlike those found in the olfactory system (i.e., glomerular organization) or the visual\nsystem (i.e., layered organization)”. The SEZ exhibits an anatomical organization that\nreflects the projection patterns of gustatory neurons, which originate from distinct chemosensory\norgans or convey different valences. Please correct accordingly with proper citations such as\nKendroud S, Bohra AA et al. Structure and development of the subesophageal zone of the Drosophila\nbrain. II. Sensory compartments. J Comp Neurol. 2018 Jan 1;526(1):33-58.\nWe have modified the text and included the reference (please see lines 43-47).\n8. Please clarify the concept of co-transmission more clearly in the introduction. It remains unclear\nwhether single synapses can release multiple neurotransmitters or whether different synapses of\nthe same neuron release distinct transmitters. While Dale’s principle originally proposed that a\nneuron releases only one type of neurotransmitter, this idea has been revised in light of evidence\nfrom various systems demonstrating co-release or co-transmission. However, it is still unclear\nwhether individual synapses can simultaneously release multiple neurotransmitters or if\ntransmitter release is spatially segregated across synapses within the same neuron. A more\nprecise framing of these distinctions would help readers better understand the significance of the\nmanuscript’s findings in relation to current models of neurotransmission.\nWhile the question of the reviewer regarding the precise nature of cotransmission is obviously\nvery interesting, our study offers no direct support for either of the possibilities put forth by the\nreviewer. Therefore, we chose to be concise and not to add additional text to the introduction.\n9. The y-axis in Figures 1d and 1g is not clearly labeled—please clarify whether it represents\npercent ΔF/F, a fractional change, or another metric. This information is critical for understanding\nthe magnitude and biological significance of the neural responses. Furthermore, the scale of\nresponses in Figures 1e and 1h is significantly different from that in Figures 1d and 1g. How is\nthe % ΔF/F max calculated? This requires an explanation in the text.\nA similar comment was raised by reviewer 1. Please refer to our response to point 2 of reviewer\n1.\n10. For consistency and clarity, please indicate the fly genotypes directly on the plots in Figures\n3d and 3e, as was done for the other figures. This will make it easier for readers to interpret the\ndata without needing to cross-reference the figure legend.\nWe have added the fly genotypes on the relevant panels.\n11. Please provide more details on how proboscis extension behavior was scored, particularly in\ndistinguishing between full and partial responses.\nWe included this information in the Methods section under “Optogenetic PER experiments”\n(please see lines 631-635)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have adequately addressed my concerns. I have not further questions and support the publication of this study.", "reviewer_2": "I thank the authors for carefully and thoroughly addressing all of my previous comments. They’ve conducted several\nadditional experiments and connectome analyses that significantly elucidate the function of SELK neurons in regulating\nfeeding behaviour in flies. These new results strengthen the manuscript and provide strong support for the author’s central\nconclusions. Moreover, the new supplementary tables and figures enhance the manuscript’s clarity and coherence.\nIn summary, the revisions provided have significantly increased the impact and clarity of the manuscript.\nIn its revised form, the manuscript represents a strong and significant contribution to the understanding of feeding circuits in\nflies, and I fully support its acceptance for publication once the minor issues mentioned below are resolved.\nMinor comments:\n1. In the text (line 124), the authors refer to the inputs of SELKs in the connectome. In this sentence, “sweet GRNs” should be\nchanged to “sweet/water GRNs,” as these neurons are not annotated separately in FlyWire. Extended Data Figure 2e uses\nthe correct labelling.\n2. Please correct the typo on Line 146 atate should be state: SELKs, depending on the feeding state of the animal.\n3. It needs to be noted in the manuscript that sugar and bitter neurons also respond to other taste modalities, such as salts\nand acids, which means these taste modalities might also activate SELK neurons. Therefore, the following sentence is\nmisleading (Line 147-148): “Our observation that SELKs are both anatomically and functionally connected to two taste\nmodalities that elicit opposing behavioural outcomes poses an intriguing question”."}, "author_response": "Response to reviewers\nReviewer #1 (Remarks to the Author):\nThe authors have adequately addressed my concerns. I have not further questions and\nsupport the publication of this study.\nReviewer #1 (Remarks on code availability):\nI did not run the code, but the GitHub repository appears to contain sufficient\ndocumentation to enable replication of the results.\nWe thank Reviewer #1 for their support in the publication of our manuscript.\nReviewer #2 (Remarks to the Author):\nI thank the authors for carefully and thoroughly addressing all of my previous\ncomments. They’ve conducted several additional experiments and connectome\nanalyses that significantly elucidate the function of SELK neurons in regulating\nfeeding behaviour in flies. These new results strengthen the manuscript and provide strong\nsupport for the author’s central conclusions. Moreover, the new supplementary tables\nand figures enhance the manuscript’s clarity and coherence.\nIn summary, the revisions provided have significantly increased the impact and clarity of\nthe manuscript.\nWe thank Reviewer #2 for their encouraging comments regarding the impact and clarity\nof our manuscript. Please find our point-by-point responses to the reviewer’s minor\ncomments below.\nIn its revised form, the manuscript represents a strong and significant contribution to the\nunderstanding of feeding circuits in flies, and I fully support its acceptance for\npublication once the minor issues mentioned below are resolved.\nMinor comments:\n1. In the text (line 124), the authors refer to the inputs of SELKs in the connectome. In\nthis sentence, “sweet GRNs” should be changed to “sweet/water GRNs,” as these\nneurons are not annotated separately in FlyWire. Extended Data Figure 2e uses the\ncorrect labelling.\nWe changed the text as requested.\n2. Please correct the typo on Line 146 atate should be state: SELKs, depending on the\nfeeding state of the animal.\nWe thank the reviewer for correcting this typo. We now fixed the typo.\n3. It needs to be noted in the manuscript that sugar and bitter neurons also respond to\nother taste modalities, such as salts and acids, which means these taste modalities\nmight also activate SELK neurons. Therefore, the following sentence is misleading (Line\n147-148): “Our observation that SELKs are both anatomically and functionally\nconnected to two taste modalities that elicit opposing behavioural outcomes poses an\nintriguing question”.\nWe removed the word “two” from this sentence to read: “Our observation that SELKs\nare both anatomically and functionally connected to taste modalities that elicit opposing\nbehavioural outcomes poses an intriguing question”."}]

Decision letter