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A conserved neuropeptide system links head and body motor circuits to enable adaptive behavior

  1. Shankar Ramachandran
  2. Navonil Banerjee
  3. Raja Bhattacharya
  4. Michele L Lemons
  5. Jeremy Florman
  6. Christopher M Lambert
  7. Denis Touroutine
  8. Kellianne Alexander
  9. Liliane Schoofs
  10. Mark J Alkema
  11. Isabel Beets
  12. Michael M Francis  Is a corresponding author
  1. Department of Neurobiology, University of Massachusetts Chan Medical School, United States
  2. Department of Biological and Physical Sciences, Assumption University, United States
  3. Department of Biology, University of Leuven (KU Leuven), Belgium
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Cite this article as: eLife 2021;10:e71747 doi: 10.7554/eLife.71747

Abstract

Neuromodulators promote adaptive behaviors that are often complex and involve concerted activity changes across circuits that are often not physically connected. It is not well understood how neuromodulatory systems accomplish these tasks. Here, we show that the Caenorhabditis elegans NLP-12 neuropeptide system shapes responses to food availability by modulating the activity of head and body wall motor neurons through alternate G-protein coupled receptor (GPCR) targets, CKR-1 and CKR-2. We show ckr-2 deletion reduces body bend depth during movement under basal conditions. We demonstrate CKR-1 is a functional NLP-12 receptor and define its expression in the nervous system. In contrast to basal locomotion, biased CKR-1 GPCR stimulation of head motor neurons promotes turning during local searching. Deletion of ckr-1 reduces head neuron activity and diminishes turning while specific ckr-1 overexpression or head neuron activation promote turning. Thus, our studies suggest locomotor responses to changing food availability are regulated through conditional NLP-12 stimulation of head or body wall motor circuits.

Editor's evaluation

In this work, Ramachandran and colleagues investigate how the C. elegans cholecystokinin-like neuropeptide (NLP-12) signaling pathway modulates animal posture during locomotion. They show that control over head- versus body-bending diverges at the level of two different NLP-12 receptors and that this fine-tuning enables the animal to reach different behavioral goals i.e., local exploration versus long-distance traveling during food search.

https://doi.org/10.7554/eLife.71747.sa0

Introduction

Neuromodulators serve critical roles in altering the functions of neurons to elicit alternate behavior. Disruptions in neuromodulatory transmitter systems are associated with a variety of behavioral and neuropsychiatric conditions, including eating disorders, anxiety, stress and mood disorders, depression, and schizophrenia (Bailer and Kaye, 2003; Kormos and Gaszner, 2013; Pomrenze et al., 2019). To achieve their effects, neuromodulatory systems may act broadly through projections across many brain regions or have circuit-specific actions, based on the GPCRs involved and their cellular expression. A single neuromodulator may therefore perform vastly different signaling functions across the circuits where it is released. For example, Neuropeptide Y (NPY) coordinates a variety of energy and feeding-related behaviors in mammals through circuit-specific mechanisms. NPY signaling may increase or decrease food intake depending upon the circuit and GPCR targets involved (West and Roseberry, 2017; Zhang et al., 2019). Due to the varied actions of neuromodulators across cell types and neural circuits, it has remained challenging to define how specific neuromodulatory systems act in vivo to elicit alternate behaviors. Addressing this question in the mammalian brain is further complicated by the often widespread and complex projection patterns of neuromodulatory transmitter systems, and our still growing knowledge of brain connectivity.

The compact neural organization and robust genetics of invertebrate systems such as Caenorhabditis elegans are attractive features for studies of neuromodulatory function. Prior work has shown that C. elegans NLP-12 neuropeptides are key modulatory signals in the control of behavioral adaptations to changing environmental conditions, such as food availability or oxygen abundance (Bhattacharya et al., 2014; Hums et al., 2016; Oranth et al., 2018). The NLP-12 system is the closest relative of the mammalian Cholecystokinin (CCK) neuropeptide system and is highly conserved across flies, worms, and mammals (Janssen et al., 2009; Janssen et al., 2008; Peeters et al., 2012). CCK is abundantly expressed in the mammalian brain; however, a clear understanding of the regulatory actions of CCK on the circuits where it is expressed is only now beginning to emerge (Ballaz, 2017; Lee and Soltesz, 2011; Nishimura et al., 2015; Saito et al., 1980). Like mammals, the C. elegans genome encodes two putative CCK-responsive G protein-coupled receptors (GPCRs) (CKR-1 and CKR-2), though, prior to the present study, direct activation by NLP-12 peptides had only been demonstrated for the CKR-2 GPCR (Frooninckx et al., 2012; Janssen et al., 2009; Janssen et al., 2008; Peeters et al., 2012). The experimental tractability of C. elegans, combined with the highly conserved nature of the NLP-12/CCK system, offers a complementary approach for uncovering circuit-level actions underlying neuropeptide modulation, in particular, NLP-12/CCK neuropeptide signaling.

Sudden decreases in food availability or environmental oxygen levels each evoke a characteristic behavioral response in C. elegans where animals limit their movement to a restricted area by increasing the frequency of trajectory changes (reorientations), a behavior known as local or area-restricted searching (ARS) (Bhattacharya et al., 2014; Gray et al., 2005; Hills et al., 2004; Hums et al., 2016; Oranth et al., 2018). ARS is a highly conserved adaptive behavior and is evident across diverse animal species (Bailey et al., 2019; Bell, 1990; Marques et al., 2020; Paiva et al., 2010; Sommerfeld et al., 2013; Weimerskirch et al., 2007). ARS responses during food searching in particular are rapid and transient. Trajectory changes increase within a few minutes after food removal, and decrease with prolonged removal from food (>15–20 min) as animals transition to global searching (dispersal) (Bhattacharya et al., 2014; Calhoun et al., 2014; Gray et al., 2005; Hills et al., 2004; Hums et al., 2016; Oranth et al., 2018; Wakabayashi et al., 2004). The clearly discernible behavioral states during food searching present a highly tractable model for understanding the contributions of specific neuromodulatory systems. NLP-12 neuropeptide signaling promotes increases in body bending amplitude and turning during movement (Bhattacharya et al., 2014; Hums et al., 2016), motor adaptations that are particularly relevant for ARS. Notably, nlp-12 is strongly expressed in only a single neuron, the interneuron DVA that has synaptic targets in the motor circuit and elsewhere (Bhattacharya et al., 2014; White et al., 1997). Despite the restricted expression of nlp-12, there remains considerable uncertainty about the cellular targets of NLP-12 peptides and the circuit-level mechanisms by which NLP-12 modulation promotes its behavioral effects.

Here, we explore the GPCR and cellular targets involved in NLP-12 neuromodulation of local food searching. Our findings reveal a primary requirement for NLP-12 signaling onto SMD head motor neurons, mediated through the CKR-1 GPCR, for trajectory changes during local searching. In contrast, NLP-12 signaling through both CKR-1 and CKR-2 GPCRs contribute to NLP-12 regulation of basal locomotion, likely through signaling onto head and body wall motor neurons. Our results suggest a model where NLP-12 signaling acts through CKR-1 and CKR-2 to coordinate activity changes across head and body wall motor circuits during transitions between basal and adaptive motor states.

Results

NLP-12/CCK induced locomotor responses require functional CKR-1 signaling

To decipher mechanisms underlying NLP-12 regulation of local food searching, we sought to identify genes required for NLP-12-mediated locomotor changes, in particular, the G protein-coupled receptors (GPCRs) responsible for NLP-12 signaling. The C. elegans genome encodes closely related CKR-1 and CKR-2 (Cholecystokinin-like Receptors 1 and 2) GPCRs with sequence homology to the mammalian Cholecystokinin receptors CCK-1 and CCK-2 (Figure 1—figure supplement 1A-B; Janssen et al., 2009; Janssen et al., 2008; Peeters et al., 2012). Prior work demonstrated that NLP-12 activates CKR-2 in vitro (Janssen et al., 2008). Further, genetic studies provided evidence that NLP-12 signaling mediates functional plasticity at cholinergic neuromuscular synapses through CKR-2 modulation of acetylcholine release from motor neurons (Bhattacharya et al., 2014; Hu et al., 2015; Hu et al., 2011). Surprisingly, however, deletion of ckr-2 does not strongly affect local search behavior (Bhattacharya et al., 2014). As functional roles for the CKR-1 GPCR have not been previously described, we sought to determine whether CKR-1 may be acting either alone or in combination with CKR-2 to direct NLP-12 regulation of local searching. We first isolated a full-length ckr-1 cDNA identical to the predicted ckr-1 sequence. As expected, we found the ckr-1 locus encodes a predicted protein containing seven transmembrane domains and sharing strong similarity to the CCK-like GPCR family (Figure 1—figure supplement 1).

To define potential roles for CKR-1 and CKR-2 in local searching, we took advantage of a strain we had previously generated that stably expresses high levels of the NLP-12 precursor [nlp-12(OE)] (Bhattacharya et al., 2014). Overexpression of nlp-12 in this manner elicits exaggerated loopy movement, increased trajectory changes, and enhanced body bend amplitude (Figure 1A, Figure 6C, Video 1). The average amplitude of bending is increased approximately threefold in comparison to wild type (Figure 1B), and body bends are more broadly distributed over steeper angles (Figure 1C–D). These overexpression effects are constitutive, offering experimental advantages for pursuing genetic strategies to identify signaling mechanisms. We investigated the requirement for CKR-1 and CKR-2 in the locomotor changes elicited by nlp-12 overexpression using available strains carrying independent deletions in each of these genes. The ckr-2 deletion (tm3082) has been characterized previously and likely represents a null allele (Hu et al., 2011; Janssen et al., 2008; Peeters et al., 2012). The ckr-1 deletion (ok2502) removes 1289 base pairs, including exons 3–7 that encode predicted transmembrane domains 2–5 (Figure 1—figure supplement 1B-C) and therefore also likely represents a null allele. ckr-1 and ckr-2 single gene deletions each partially reversed the effects of nlp-12 overexpression (Figure 1A,B,D, 6C), indicating that both CKR-1 and CKR-2 GPCRs are active under conditions when NLP-12 peptides are present at high levels. Notably, ckr-1 deletion showed slightly greater suppression of nlp-12(OE) phenotypes compared with ckr-2 deletion (Figure 1B,D, 6C). Combined deletion of ckr-1 and ckr-2 largely reversed the locomotor changes produced by NLP-12 overexpression (Figure 1A,B,D, 6C), indicating that the GPCRs act in a partially redundant manner. Our genetic analysis of nlp-12 overexpression confirms a role for the CKR-2 GPCR in NLP-12-elicited motor adaptations, and importantly, provides first evidence implicating the previously uncharacterized CKR-1 GPCR in NLP-12 modulation of motor activity.

Figure 1 with 2 supplements see all
NLP-12/CCK induced locomotor responses require functional ckr-1 signaling.

(A) Representative movement trajectories of wild-type (black), nlp-12(OE) (red), nlp-12(OE);ckr-1(lf) (blue), nlp-12(OE);ckr-2(lf) (orange), and nlp-12(OE);ckr-1(lf);ckr-2(lf) (green) animals during forward runs (30 s) on NGM agar plates seeded with OP50 bacteria. nlp-12(OE) refers to the transgenic strain (ufIs104) stably expressing high levels of wild-type nlp-12 genomic sequence. Note the convoluted nlp-12(OE) movement tracks are restored to wild type by combined ckr-1 and ckr-2 deletion. Scale bar, 1 mm. Asterisks (*) indicate position of worm at start of recording. (B) Average body bend amplitude (indicated in schematic by blue arrow between orange lines, midbody centroid [green] of worm) for the genotypes as indicated. Bars represent mean ± SEM. In this and subsequent figures. ****p<0.0001, ***p<0.001, ANOVA with Holms-Sidak post hoc test. wild-type n=19, nlp-12(OE): n=14, nlp-12(OE);ckr-1(lf): n=27, nlp-12(OE);ckr-2(lf): n=25, nlp-12(OE);ckr-1(lf);ckr-2(lf): n=20. (C) Schematic representation of measured body bending angle, for shallow (top) and deep (bottom) body bends. Solid orange circles indicate the vertices (head, midbody, and tail) of the body bending angle (blue) measured. (D) Frequency distribution of body bending angle (indicated in blue in (C)) for the genotypes indicated. Kolmogorov-Smirnov test: wild-type versus nlp-12(OE)**, wild-type versus nlp-12(OE);ckr-2(lf)**, nlp-12(OE) versus nlp-12(OE);ckr-1(lf);ckr-2(lf)**, **p<0.01. wild-type: n=12, nlp-12(OE): n=10, nlp-12(OE);ckr-1(lf): n=10, nlp-12(OE);ckr-2(lf): n=12, nlp-12(OE);ckr-1(lf);ckr-2(lf): n=12. (E, F) Concentration-response curves of the mean calcium responses (% activation ± SEM) in CHO cells expressing either CKR-1 (E) or CKR-2 (F) for different concentrations of synthetic peptides NLP-12–1 (solid blue circles) or NLP-12–2 (solid black squares). Solid lines indicate curve fits to the data (n=6). 95% confidence intervals (nM), CKR-1: NLP-12–1, 1.79–7.07; NLP-12–2, 0.93–3.77 and CKR-2: NLP-12–1, 5.16–12.51; NLP-12–2, 6.43–16.73. NGM, nematode growth media.

Video 1
Representative 20-s video showing locomotion on food of animal overexpressing nlp-12.

Video has been sped up 4×.

NLP-12 activates CKR-1 with high potency

To obtain direct evidence for NLP-12 activation of CKR-1, we used an in vitro bioluminescence-based approach. CKR-1 was expressed in Chinese hamster ovarian (CHO) cells stably expressing the promiscuous G-protein alpha subunit Gα16 and a bioluminescent calcium indicator, aequorin (Caers et al., 2014). The NLP-12 precursor gives rise to two distinct mature peptides, NLP-12–1 and NLP-12–2. Application of either NLP-12–1 or NLP-12–2 synthetic peptides produced robust calcium responses in cells expressing CKR-1. These responses were concentration-dependent with EC50 values of 3.5 and 1.9 nM for NLP-12–1 and NLP-12–2 peptides, respectively (Figure 1E). These EC50 values are comparable to those measured for NLP-12 activation of CKR-2 (8.0 nM and 10.2 nM) (Figure 1F; Janssen et al., 2008), suggesting NLP-12 peptides act with similar potency across CKR-1 and CKR-2 GPCRs. Importantly, no other peptides from a library of over 350 synthetic C. elegans peptides elicited CKR-1 activation, nor did the NLP-12 peptides evoke calcium responses in cells transfected with empty vector (Figure 1—figure supplement 2), indicating that CKR-1, like CKR-2, is a highly specific receptor for NLP-12.

CKR-1 is a key signaling component for local search behavior

To more deeply investigate roles for CKR-1 and CKR-2 in NLP-12 regulation of movement, we quantified body and head bending during basal locomotion (in the presence of food) using single worm tracking analysis. nlp-12 deletion significantly reduced both body bending and head bending angles in comparison to wild type (Figure 2A–B). Similarly, single deletions in ckr-1 and ckr-2 each produced significant reductions in body bending, and combined deletion produced effects similar to nlp-12 deletion (Figure 2A). In contrast, head bending was strikingly affected by ckr-1 deletion, while ckr-2 deletion did not produce a significant reduction (Figure 2B). The preferential involvement of CKR-1 in head bending suggested the interesting possibility that CKR-1 and CKR-2 GPCRs differentially regulate specific features of locomotion.

CKR-1 and CKR-2 differentially regulate head and body bending during basal locomotion.

Schematics showing body bending (A) and head bending (B) angles (solid orange circles indicate the vertices and measured angle in blue) quantified during single worm track analyses of movement (5 min) in the presence of food. Each data point in the scatterplots represents the average body or head bend angle for a single animal from analysis of 5 min of locomotion. Horizontal red bar indicates mean, shading indicates SEM for wild-type (blue) and mutants (orange). ****p<0.0001, ***p<0.001, *p<0.05, ns, not significant. ANOVA with Holms-Sidak post hoc test. wild-type: n=19, nlp-12(ok335): n=16, ckr-1(ok2502): n=16, ckr-2(tm3082): n=16, ckr-1(ok2502);ckr-2(tm3082): n=8.

Figure 2—source data 1

Source data for body bending measurements during single worm tracking of basal locomotion (Figure 2A).

https://cdn.elifesciences.org/articles/71747/elife-71747-fig2-data1-v2.xlsx
Figure 2—source data 2

Source data for head bending measurements during single worm tracking of basal locomotion (Figure 2B).

https://cdn.elifesciences.org/articles/71747/elife-71747-fig2-data2-v2.xlsx

To explore this possibility further, we investigated the involvement of CKR-1 and CKR-2 GPCRs in local search responses following removal from food. Specifically, we monitored worm movement during a 35-min period immediately after removal from food and quantified turning behavior during the first (0–5, local searching, Video 2) and last (30–35, dispersal, Video 3) five minutes (Figure 3A). Post hoc video analysis proved most reliable for measuring turning behavior during local searching. We quantified changes in trajectory (reorientations), that resulted in a change of >50° in the direction of movement, executed either through forward turns or reversal-coupled omega turns (Figure 3B, Figure 3—figure supplement 1). For wild type, we noted an increase in reorientations immediately following removal from food compared to animals maintained on food (Figure 3—figure supplement 2A). Consistent with our previous findings (Bhattacharya et al., 2014), we found that deletion of nlp-12 significantly decreased reorientations immediately following removal from food (Figure 3C–D). In particular, we noted a significant reduction in the forward reorientations of nlp-12 mutants, but no appreciable effect on reversal-coupled omega turns (Figure 3—figure supplement 2B). Deletion of ckr-2 produced no appreciable effect on reorientations (Figure 3C–D; Bhattacharya et al., 2014); however, single deletion of ckr-1 decreased reorientations to a similar level as observed for nlp-12 deletion (Figure 3C–D). Similar to nlp-12(lf), we found that ckr-1(lf) significantly impacted forward reorientations, but did not affect reversal-coupled omega turns (Figure 3—figure supplement 2B). Combined deletion of ckr-1 and ckr-2 provided no additional decrease beyond that observed for single ckr-1 deletion (Figure 3C–D). In addition, combined deletion of nlp-12 and ckr-1 did not further decrease reorientations compared with either of the single mutants (Figure 3C–D). Expression of wild-type ckr-1, but not ckr-2, rescued reorientations in ckr-1(lf);ckr-2(lf) double mutants (Figure 3—figure supplement 3A). Expression of wild-type ckr-1 also restored normal reorientation behavior in ckr-1(lf) animals when expressed under the control of native ckr-1 promoter elements (3.5 kb) (Figure 3C), but not when expressed under the ckr-2 promoter (Figure 3—figure supplement 3B). These findings show that nlp-12 and ckr-1 act in the same genetic pathway and point to a selective requirement for NLP-12 signaling through CKR-1 in regulating trajectory changes during local searching. Deletion of nlp-12 did not produce significant changes in dispersal behavior, but we noted a modest decrease in reorientations during dispersal in ckr-1 mutants (Figure 3E). This may indicate additional roles for CKR-1 during dispersal. Taken together, our genetic and behavioral studies implicate CKR-1 and CKR-2 GPCRs as targets of NLP-12 signaling under conditions of overexpression and during basal locomotion. In contrast, we find that NLP-12 modulation of local searching is primarily achieved through CKR-1 activation.

Figure 3 with 3 supplements see all
NLP-12/CCK food search responses are mediated through the GPCR CKR-1.

(A) Schematic of the food search assay indicating the time intervals when reorientations were scored. Wild-type animals increase reorientations during the first 5 min (0–5 min) after removal from food (local search) and reduce reorientations during dispersal (30–35 min). Asterisks (*) indicate the position of worm at the start of recording. (B) Frame grabs showing worm position and posture prior to, during and after reorientation. Angle (blue) between the black (original trajectory) and white (new trajectory) dashed lines indicates the change in trajectory. Frame numbers and time points indicated are relative to the first image in each sequence, which represents the start point (frame 0, time 0 s) when the reorientation event began, and the last frame was when the reorientation was completed. Trajectory changes were scored as reorientations if changes in trajectory were greater than 50°. (C) Quantification of reorientations during 0–5 min following removal from food for the genotypes indicated. Rescue refers to transgenic expression of wild-type ckr-1 in ckr-1 mutants. Bars represent mean ± SEM. ****p<0.0001, **p<0.01, ns, not significant, ANOVA with Holms-Sidak post hoc test. wild-type: n=25, nlp-12(ok335): n=27, ckr-1(ok2502): n=24, nlp-12(ok335);ckr-1(ok2502): n=10, ckr-1 rescue: n=18, ckr-2(tm3082): n=10, ckr-1(ok2502);ckr-2(tm3082): n=25. (D) Representative body curvature kymographs for worm locomotion during basal locomotion and area restricted searching (ARS). Head to tail orientation along the horizontal axis in each kymograph is left to right as indicated for wild type. Time is indicated along the vertical axis from 0 min to 1 min. (E) Total number of reorientations during an interval of 30–35 min following removal from food for the genotypes as shown. Each bar represents mean ± SEM. *p<0.05, ANOVA with Holms-Sidak post hoc test. wild-type: n=10, nlp-12(ok335): n=10, ckr-1(ok2502): n=10, ckr-2(tm3082): n=10, ckr-1(ok2502);ckr-2(tm3082): n=11. (F) Trajectory changes (reorientations) scored in response to photostimulation of DVA. Percent change in the number of high angle turns elicited during 1 min of blue light exposure compared to prestimulus (no blue light). Bars represent mean ± SEM. ***p<0.001, **p<0.01, ns, not significant, compared to +ATR control, ANOVA with Holms-Sidak post hoc test. ATR, all-trans retinal.

Figure 3—source data 1

Source data for reorientations quantified during area restricted search (0–5 min off food, Figure 3C).

https://cdn.elifesciences.org/articles/71747/elife-71747-fig3-data1-v2.xlsx
Figure 3—source data 2

Source data for reorientations quantified during dispersal (30–35 min off food, Figure 3E).

https://cdn.elifesciences.org/articles/71747/elife-71747-fig3-data2-v2.xlsx
Figure 3—source data 3

Source data for % change in reorientations from mean quantified for DVA photostimulation (Figure 3F).

https://cdn.elifesciences.org/articles/71747/elife-71747-fig3-data3-v2.xlsx
Video 2
Representative 20-s video showing locomotion of wild-type animal during area restricted search (0–5 min off food).

Video has been sped up 4×.

Video 3
Representative 20-s video showing locomotion of wild-type animal during dispersal (30–35 mi off food).

Video has been sped up 4×.

Acute stimulation of DVA promotes reorientation behavior and requires NLP-12 and CKR-1

We next addressed the question of how neuronal release of NLP-12 promotes area restricted searching. We measured trajectory changes elicited by acute depolarization of the DVA neuron. We used the nlp-12 promoter to drive cell-specific expression of Channelrhodopsin-2 (ChR2) (Nagel et al., 2003) in DVA and tracked worm movement during a 1-min period of blue light (470 nm) photostimulation. We found that animals reorient more frequently with depolarization of DVA compared to pre-stimulus control (Figure 3F). Importantly, light exposure did not increase reorientations in the absence of retinal (–ATR) (Figure 3F). Depolarization of the DVA neuron in nlp-12 mutants failed to produce a similar enhancement (Figure 3F), offering support for the idea that reorientations primarily arise due to the release of NLP-12 peptides. Single ckr-1 deletion or combined ckr-1 and ckr-2 deletion also abrogated DVA-elicited increases in reorientation behavior, while single ckr-2 deletion produced more variable responses that were not clearly distinguishable from control (Figure 3F). Our photostimulation experiments provide direct evidence that NLP-12 release from the DVA neuron promotes reorientation behavior, and, in addition, provide evidence for central involvement of NLP-12 signaling through the CKR-1 GPCR in directing reorientations. While NLP-12 expression has also been recently reported in PVD neurons (Tao et al., 2019), expression of nlp-12 under a PVD specific promoter (ser-2prom3) did not restore reorientations in nlp-12(lf) animals (Figure 3—figure supplement 3C), pointing toward DVA as the primary source of NLP-12 in promoting reorientations.

Elevated CKR-1 signaling enhances turning and body bending in an Nlp-12 dependent manner

To further define the role of CKR-1, we next asked whether increased CKR-1 signaling would be sufficient to induce local search-like behavior. To address this question, we pursued an overexpression strategy similar to our above approach for nlp-12. We generated transgenic lines where the ckr-1 genomic sequence including native ckr-1 promoter elements was injected into wild-type animals at high concentration.

We found that ckr-1 overexpression produced striking increases in turning and large head to tail body bends (Figure 4A, 6C, Video 4), qualitatively similar to the effects of nlp-12 overexpression (Figure 1A, Video 1). ckr-1(OE) animals made steep bends during runs of forward movement, with angles approaching 200°, whereas bending angles in wild type rarely exceeded 75° (Figure 4B). Notably, these high angle bends often produced spontaneous reorientations during forward movement and sometimes elicited sustained coiling. The amplitude of body bends during movement also increased by approximately threefold in ckr-1(OE) animals compared to wild type (Figure 4C). These increases in bending angles and body bend depth were returned to wild-type levels by nlp-12 deletion (Figure 4A–C), offering support that NLP-12 peptides are the major CKR-1 ligands required to elicit these characteristic changes in movement. Taken together, our genetic studies define NLP-12/CKR-1 as a novel ligand-GPCR pathway that controls trajectory changes and body bending to produce adaptive behavior.

Elevated CKR-1 signaling enhances bending angle and amplitude in an nlp-12 dependent manner.

(A) Representative movement trajectories of wild-type (black), ckr-1(OE) (blue) and ckr-1(OE); nlp-12(lf) (green) animals for 30 s on NGM agar plates seeded with OP50 bacteria. ckr-1(OE) refers to high copy expression of the wild-type ckr-1 genomic locus (ufEx802). Note the increased frequency of high angle turns and convoluted track for ckr-1(OE). These movement phenotypes are reversed by nlp-12 deletion. Scale bar, 1 mm. (B) Frequency distribution of body bending angles (mean ± SEM) during forward runs (30 s) on plates thinly seeded with OP50 bacteria. Kolmogorov-Smirnov test: wild-type versus ckr-1(OE)**, ckr-1(OE) versus ckr-1(OE); nlp-12(ok335)**, wild-type versus ckr-1(OE); nlp-12(ok335) ns. **p<0.01, ns, not significant. wild-type: n=8, ckr-1(OE): n=10, and ckr-1(OE);nlp-12(lf): n=10. (C) Comparison of the average body bend amplitude for the indicated genotypes. Bars represent mean ± SEM. ****p<0.0001, ns, not significant, ANOVA with Holms-Sidak post hoc test. wild-type: n=12, ckr-1(OE): n=15, ckr-1(OE);nlp-12(ok335): n=16. NGM, nematode growth media.

Video 4
Representative 20-s video showing locomotion on food of animal overexpressing ckr-1.

Video has been sped up 4×.

ckr-1 is expressed in many neurons that do not receive direct synaptic inputs from DVA

To identify cells where CKR-1 may act to promote local searching, we generated strains expressing a ckr-1 reporter transgene that included the complete ckr-1 genomic locus and ~3.5 kb of upstream regulatory sequence SL2 trans-spliced to sequence encoding GFP (green fluorescent protein) or mCherry. We found that ckr-1 is broadly expressed in the nervous system, showing expression in a subset of ventral nerve cord motor neurons, amphid and phasmid sensory neurons, premotor interneurons, and motor neurons in the nerve ring (Figure 5A–B). We identified many of these neurons, largely from analysis of ckr-1 co-expression with previously characterized reporters (Supplementary file 2). In the ventral nerve cord, we found that ckr-1 is expressed in cholinergic, but not GABAergic, ventral cord motor neurons (Figure 5—figure supplement 1A-B, Supplementary file 2). Amongst head neurons, the ckr-1 reporter is expressed in GABAergic RMEV, RMED, AVL and RIS neurons, cholinergic SMDV, SMDD, and RIV head motor neurons, the interneuron RIG, the serotonergic NSM neuron, and in the interneurons AIA and AIB (Figure 5B, Supplementary file 2). Additional studies using DiI uptake indicated that ckr-1 is also expressed in the amphid sensory neurons ASK and ASI and the phasmid sensory neurons PHA and PHB (Supplementary file 2). With the exception of the ventral cord cholinergic neurons, the ckr-1 reporter almost exclusively labeled neurons that do not receive direct synaptic input from DVA, suggesting that NLP-12 acts at least partially through extrasynaptic mechanisms. Notably, ckr-1 and ckr-2 expression showed little overlap (Figure 5—figure supplement 2).

Figure 5 with 2 supplements see all
ckr-1 functions in the SMD head motor neurons to modulate body bending.

(A) Confocal maximum intensity projection of adult expressing the Pckr-1::ckr-1::SL2::GFP reporter. Note that the expression in multiple head neurons (white box) and a subset of ventral nerve cord motor neurons (white arrowheads). (B) Confocal maximum intensity projection of the head region of adult expressing the Pckr-1::ckr-1::SL2::GFP reporter. Scale bar, 10 μm. See Figure 5—figure supplement 1 and Supplementary file 2 for additional expression information. (C) Quantification of average body bend amplitudes (mean ± SEM) for ckr-1 overexpression in the indicated cell types. Promoters used for listed cell types: pan-neuronal Prgef-1, muscle Pmyo-3, GABA motor neurons Punc-47, cholinergic ventral cord motor neurons Punc-17β. See Supplementary file 3 for details about cellular expression of promoters used for head neurons. ****p<0.0001, ***p<0.001, ANOVA with Holms-Sidak’s post hoc test. Numbers within bars indicate n for each genotype. (D) Confocal maximum intensity projection of the nerve ring region of a transgenic animal expressing Pnlp-12::NLP-12::Venus. Note the high levels of NLP-12::Venus in the nerve ring. White box indicates approximate nerve ring region where close localization of NLP-12 clusters to SMD processes has been shown in panel (E). Scale bar, 5 µm. (E) Confocal maximum intensity projection of the nerve ring region of a transgenic animal expressing Pnlp-12::NLP-12::Venus (DVA) and Pflp-22∆4::mCherry (SMD). Note the close localization of NLP-12::Venus dense core vesicle clusters to the SMD process. Scale bar, 1 µm.

CKR-1 functions in the SMD head motor neurons to modulate body bending

We next pursued cell-specific ckr-1 overexpression to gain insight into which ckr-1-expressing neurons defined above may be primary targets for modulation during local searching (Supplementary files 3-4). We focused our analysis on body bending amplitude because this was the most easily quantifiable aspect of movement to be modified by ckr-1 overexpression. Transgenic strains where pan-neuronally expressed ckr-1 (rgef-1 promoter) was injected at high concentration displayed increased body bending amplitude, similar to overexpression using the native promoter (Figure 5C). In contrast, ectopic ckr-1 expression in muscles produced no appreciable change, consistent with a primary site of CKR-1 action in neurons (Figure 5C). Surprisingly, ckr-1 overexpression in cholinergic (unc-17β promoter) or GABAergic (unc-47 promoter) ventral nerve cord motor neurons did not elicit an appreciable change in body bend depth (Figure 5C). We therefore next targeted the head neurons identified by our ckr-1 reporter, using several different promoters for ckr-1 overexpression in subsets of head neurons (Figure 5C, Supplementary files 3-4). ckr-1 overexpression using either the odr-2(16) or lgc-55 promoters produced a striking (2.5-fold) increase in body bend depth, comparable with ckr-1 overexpressed under its endogenous promoter. In contrast, ckr-1 overexpression in GABAergic neurons, including RMED and RMEV (unc-47 promoter), did not produce an appreciable effect. Likewise, ckr-1 overexpression in RIV, RIG, NSM, AIA, AIB, or amphid neurons failed to significantly enhance body bend depth. The lgc-55 promoter drives expression in AVB, RMD, SMD, and IL1 neurons, as well as neck muscles and a few other head neurons (Pirri et al., 2009), while the odr-2(16) promoter primarily labels the RME and SMD head neurons (Chou et al., 2001; Supplementary files 2-3). The overlapping expression of the odr-2(16) and lgc-55 promoters in SMD neurons suggested that these neurons may be centrally involved. SMD co-labeling by ckr-1::SL2::mCherry and Plad-2::GFP (Wang et al., 2008) provided additional evidence for ckr-1 expression in these neurons (Figure 5—figure supplement 1C). In contrast to ckr-1, ckr-2 was either absent or more variably expressed in a subset of the SMD neurons, the SMDDs (Figure 5—figure supplement 1D). Intriguingly, we noted that NLP-12::Venus clusters in the nerve ring region of the DVA process (Figure 5D) are concentrated in the vicinity of SMD processes (Figure 5E).

The four SMDs (dorsal-projecting SMDDL and SMDDR and ventral-projecting SMDVL and SMDVR) are bilateral motor neuron pairs that innervate dorsal and ventral head/neck musculature, and also form reciprocal connections with one another (White et al., 1997). They have been previously implicated in directional head bending and steering (Gray et al., 2005; Hendricks et al., 2012; Kaplan et al., 2020; Kocabas et al., 2012; Shen et al., 2016; Yeon et al., 2018). To better define the behavioral effects of SMD modulation, we more closely examined body bending in animals overexpressing ckr-1 under control of the odr-2(16) promoter, and also using a second promoter, flp-22∆4, that was recently shown to drive selective expression in the SMD neurons (Yeon et al., 2018). For both overexpression strains, we observed significant increases in body bending amplitude and bending angle compared to wild type (Figures 5C and 6A–C, Video 5). These increases were dependent on NLP-12 signaling (Figure 6, Figure 6—figure supplement 1A-B) and were similar to those observed for native ckr-1 (Figures 4 and 6C, Video 4) and nlp-12 overexpression (Figures 1 and 6C, Video 1). Thus, the actions of CKR-1 in the SMD motor neurons recapitulate many of the behavioral effects of NLP-12 overexpression.

Figure 6 with 1 supplement see all
Ablation of SMD motor neurons abolishes the effects of ckr-1 overexpression.

(A) Representative tracks (1 min) for indicated genotypes. Asterisks indicate the position of animal at the beginning of recordings. Note that the increased reorientations and body bending depth in the tracks with cell-specific ckr-1 overexpression. Scale bar, 1 mm. (B) Average body bending angle distribution (mean ± SEM) for the indicated genotypes. High level expression of ckr-1 in SMDs using the odr-2(16) or flp-22∆4 promoters increases bending angle. Kolmogorov-Smirnov test: wild-type versus Podr-2(16)::ckr-1(OE)**, wild-type versus Pflp-22∆4::ckr-1(OE)*, **p<0.01, *p<0.05. wild-type n=9 (black circles), Podr-2(16)::ckr-1(OE): n=9 (blue squares), Pflp-22∆4::ckr-1(OE): n=11 (orange triangles). (C) Representative body curvature kymographs for worm locomotion during basal locomotion for indicated genotypes. Head to tail orientation along the horizontal axis in each kymograph is left to right as indicated for wild-type. Time is indicated along the vertical axis from 0 min to 1 min. (D) Top, representative fluorescent images of SMD motor neuron in ckr-1(OE) animals without (left) or with (right) miniSOG expression 16 hr following photoactivation. Bottom, representative 30 s track for control ckr-1(OE) (−miniSOG, left) animal or SMD ablated ckr-1(OE) (+miniSOG, right) animal 16 hr after photostimulation. Scale bar, 1 µm. (E) Average body bending angle distribution (mean ± SEM) for control ckr-1(OE) (green circles, n=11) and SMD ablated ckr-1(OE) (brown squares, n=11) animals. SMD ablation reduces the frequency of large bending angles produced by ckr-1(OE). Kolmogorov-Smirnov test: *p<0.05. (F) Comparison of average body bending amplitude for control ckr-1(OE) (n=11) and SMD ablated ckr-1(OE) (n=11). SMD ablation significantly reduces the enhanced body bending amplitude observed by ckr-1(OE). Bars represent mean ± SEM. ***p<0.001, Student’s t-test.

Video 5
Representative 20-s video showing locomotion on food of animal overexpressing ckr-1 in the SMD motor neurons.

Video has been sped up 4×.

To ask if the SMD neurons are required for the locomotor changes produced by ckr-1 overexpression, we expressed the photoactivatable cell ablation agent PH-miniSOG in the SMD neurons (Pflp-22∆4) of animals overexpressing ckr-1 (native promoter). When activated by blue light (470 nm) PH-miniSOG produces reactive oxygen species and disrupts cellular function (Xu and Chisholm, 2016). Following photoactivation of miniSOG in animals overexpressing ckr-1, we observed striking decreases in bending angles (Figure 6D–E) and amplitude (Figure 6F) during movement. We confirmed successful SMD ablation by examining morphological changes in GFP-labeled SMD neurons following photoactivation of miniSOG (Figure 6D). Expression of miniSOG did not have appreciable effects on the body bending of ckr-1(OE) animals under control conditions (without light exposure) (Figure 6—figure supplement 1C). In addition, stimulation of control animals without the miniSOG transgene did not appreciably alter body bending (Figure 6E) or SMD neuron morphology (Figure 6—figure supplement 1D). These results indicate that SMD motor neurons are required for the locomotor effects of ckr-1 overexpression, and, importantly, raise the possibility that the SMD neurons are key targets for NLP-12 neuromodulation during local searching in wild type.

NLP-12/CKR-1 excitation of the SMD neurons promotes local searching

To further investigate the site of CKR-1 function, we examined rescue of area restricted searching in ckr-1 mutants by generating additional transgenic lines providing for SMD-specific expression of wild-type ckr-1 (injected at fivefold lower concentration than used for overexpression above). Injection of wild-type animals with the SMD::ckr-1 transgene at this lower concentration did not appreciably increase bending depth or angle (Figure 7—figure supplement 1A). However, expression in ckr-1 mutants restored reorientations during food searching to roughly wild-type levels (Figure 7A), indicating that CKR-1 function in the SMD neurons is sufficient to support NLP-12 modulation of local searching.

Figure 7 with 1 supplement see all
NLP-12/CKR-1 excitation of the SMD neurons promotes reorientations.

Total reorientations measured during 0–5 min following removal from food for the genotypes indicated. ckr-1 rescue refers to expression of wild-type ckr-1 (5 ng/µl) in ckr-1(ok2502) animals using the indicated promoters. Bars represent mean ± SEM. ****p<0.0001, ***p<0.001 ANOVA with Holms-Sidak post hoc test. wild-type: n=38, ckr-1(lf): n=32, Podr-2(16)::ckr-1 rescue: n=12, Plgc-55::ckr-1 rescue: n=12, Pflp-22(∆4)::ckr-1 rescue: n=9. (B) Representative tracks (1 min) on thinly seeded NGM agar plates prior to (left) and during photostimulation (right) for transgenic animals expressing Podr-2(16)::Chrimson. Scale bar, 1 mm. Asterisks (*) indicate the position of worm at the start of recording. (C) Left, quantification of reorientations for individual animals over 1 min durations prior to (prestimulus) and during photostimulation (+ATR). Right, quantification of reorientations for individual animals prior to and during photostimulation in control animals (−ATR). Black circles, reorientations during prestimulus. Orange circles, reorientations during photostimulation. Numbers adjacent to circles indicate number of overlapping data points. **p<0.01, ns, not significant. Paired t-test. ATR, all-trans retinal. (D) Quantification of reorientations for wild-type and transgenic animals, (Pflp-22∆4::His-Cl1::SL2::GFP), in the presence and absence of histamine. Note reduced reorientations with SMD silencing in transgenics (+histamine). **p<0.01, *p<0.05, ANOVA with Holms-Sidak post hoc test. wild-type: −Histamine: n=8, +Histamine: n=7, pSMD::HisCl1::SL2::GFP: −Histamine: n=8, +Histamine: n=8. NGM, nematode growth media.

Figure 7—source data 1

Source data for reorientations quantified during area restricted search (0–5 min off food, Figure 7A).

https://cdn.elifesciences.org/articles/71747/elife-71747-fig7-data1-v2.xlsx
Figure 7—source data 2

Source data for reorientations quantified during SMD photostimulation (Figure 7C).

https://cdn.elifesciences.org/articles/71747/elife-71747-fig7-data2-v2.xlsx
Figure 7—source data 3

Source data for reorientations quantified during area restricted search upon SMD silencing (0–5 min off food, Figure 7D).

https://cdn.elifesciences.org/articles/71747/elife-71747-fig7-data3-v2.xlsx

To investigate how increased SMD activity may impact movement, we photostimulated the SMDs in animals expressing Podr-2(16)::Chrimson (Klapoetke et al., 2014). Prior to photostimulation, animals demonstrated long forward runs with relatively few changes in trajectory (Figure 7B). Following the onset of photostimulation, Chrimson-expressing animals rapidly increased reorientations (Figure 7B–C, Video 6), while control animals (-Retinal) did not increase trajectory changes during the light stimulation period (Figure 7C). SMD photostimulation also elicited a modest increase in body bending (Figure 7—figure supplement 1B). Conversely, transient and inducible silencing of the SMDs by histamine-gated chloride channel expression significantly reduced reorientations during food searching (Figure 7D). Thus, direct activation or inhibition of SMD neurons alter turning and reorientations, consistent with a potential mechanism for NLP-12/CKR-1 modulation of local searching through signaling onto the SMD neurons.

Video 6
Representative 20-s video showing locomotion on food of animal in the absence (left) and during SMD photostimulation (right).

Video has been sped up 4×.

To explore the dynamics of SMD neuronal activity during searching, we next measured combined calcium responses from SMD neurons of behaving animals. We simultaneously recorded GCaMP6s and mCherry fluorescence (flp-22∆ promoter) during ARS (0–5 min off food) and dispersal (30–35 min off food) (Video 7). We observed a striking elevation of wild-type SMD activity during ARS compared with dispersal (Figure 8A, B, D and E, Figure 8—figure supplement 1). Though overall calcium levels during ARS were positively correlated with reorientation frequency (Figure 8D, Pearson’s correlation r=0.54), discrete events where the peak fluorescence ratio was elevated were not well correlated with specific episodes of behavior. This would be predicted for our measurements of combined fluorescence from SMDD and SMDV neurons that themselves have distinct patterns of activation (Kaplan et al., 2020). By comparison, SMD activity of ckr-1(lf) animals remained low throughout the ARS period (Figure 8C–E), supporting a model (Figure 9) where NLP-12/CKR-1 signaling promotes local searching by biasing SMD head motor neurons toward increased activation.

Figure 8 with 1 supplement see all
Elevated activity in SMD motor neurons during ARS promotes reorientations.

(A–C) Representative heat maps showing activity of SMD neurons in transgenic animals (Pflp-22∆4::GCaMP6s::SL2::mCherry) during ARS (A) and dispersal (B) for wild type, and ARS for ckr-1(ok2502) (C). Each row represents one animal over a duration of 1 min. Corresponding behaviors (forward, reversal, omega turn, forward reorientation) are annotated by color-coded (as indicated in legend) horizontal bar below each heat map. The SMD GCaMP6s/mCherry fluorescence ratio is elevated during wild-type ARS, compared with either ckr-1(lf) ARS, and wild-type dispersal. (D) Number of reorientations plotted against mean SMD GCaMP6s/mCherry ratio for the individuals in (A–C). Black line indicates linear fit for wild-type ARS values, with Pearson’s correlation coefficient (r), *p=0.02. (E) Quantification of mean SMD fluorescence ratio (GCaMP6s/mCherry) during ARS or dispersal for the genotypes indicated. ****p<0.0001, ANOVA with Holms-Sidak post hoc test. ARS wild-type: n=18, ARS ckr-1(ok2502): n=7, Dispersal wild-type: n=7. ARS, area-restricted searching.

Figure 8—source data 1

Source data for GCaMP6s/mCherry ratio during SMD calcium imaging (Figure 8A–D).

https://cdn.elifesciences.org/articles/71747/elife-71747-fig8-data1-v2.xlsx
Figure 8—source data 2

Source data for mean GCaMP6s/mCherry ratio during SMD calcium imaging (Figure 8E).

https://cdn.elifesciences.org/articles/71747/elife-71747-fig8-data2-v2.xlsx
Proposed model for NLP-12 action through CKR-1 and CKR-2.

During basal locomotion, NLP-12 activation of CKR-1 and CKR2 GPCRs in ventral nerve cord motor neurons regulates body bending. During local searching, NLP-12 acts primarily through CKR-1 in SMD motor neurons to promote increased turning, trajectory changes and enhance body bending. Solid arrows indicate known synaptic connections, dotted arrows indicate extrasynaptic. Sensory neurons (green), head interneurons (orange), and motor neurons (red). Olfactory sensory neurons: AWA, AWB, AWC, and ASE.

Video 7
Representative 20-s video showing simultaneous post hoc tracking of mCherry and GCaMP6s fluorescence for ratiometric calcium imaging analysis.

Video has been sped up 4×.

Discussion

Neuropeptidergic systems have crucial roles in modulating neuronal function to shape alternate behavioral responses, but we have limited knowledge of the circuit-level mechanisms by which these alternate responses are generated. Here, we show that the C. elegans NLP-12 neuropeptide system, closely related to the CCK system in mammals, shapes adaptive behavior through modulation of motor circuits dedicated to control of either head or body wall musculature. We demonstrate that NLP-12 modulation of these circuits occurs through distinct GPCRs, CKR-1 and CKR-2, that primarily act on either head or body wall motor neurons, respectively. Under basal conditions, we suggest that NLP-12 modulation of the body wall motor circuit predominates, influencing the depth of body bends during sinusoidal movement through CKR-1 and CKR-2 GPCRs located on body wall motor neurons. NLP-12 activation of head motor neurons through CKR-1 becomes predominant in the absence of food, promoting reorientations. We propose that changes in food availability reconfigure functional connectivity in the NLP-12 system by differentially engaging GPCRs across the head and body wall motor circuits. Intriguingly, the involvement of two GPCRs in nematode NLP-12 signaling is reminiscent of the organization of the CCK system in rodents, which relies on signaling through CCK1 and CCK2 GPCRs (Janssen et al., 2009). New details about central CCK signaling and the brain GPCRs involved are continuing to emerge (Ballaz, 2017; Chen et al., 2019; Crosby et al., 2018; Lee and Soltesz, 2011; Li et al., 2014; Miyasaka and Funakoshi, 2003; Nishimura et al., 2015; Saito et al., 1980). Our findings may point toward similar utilization of specific CCK-responsive GPCRs to coordinate activity across mammalian brain circuits.

NLP-12 neuropeptides act as key modulators in a range of C. elegans behaviors. Local search responses to varying oxygen levels and decreased food availability both involve NLP-12 signaling (Bhattacharya et al., 2014; Hums et al., 2016). Additionally, NLP-12 signaling has been implicated in various aspects of proprioceptive signaling and postural control (Hu et al., 2015; Hu et al., 2011). However, the mechanisms by which NLP-12 peptides exert their influence over these diverse behavioral responses have remained unclear. Our work addresses these mechanistic questions by defining roles for CKR-1 and CKR-2 GPCRs during basal locomotion and ARS. ARS is a complex motor behavior, involving rapid trajectory changes that serve to maintain the animal within a restricted area of their immediate environment (Bhattacharya et al., 2014; Calhoun et al., 2014; Gray et al., 2005; Hums et al., 2016). Reorientations during searching are produced through high angle forward turns (Bhattacharya et al., 2014; Broekmans et al., 2016; Pierce-Shimomura et al., 1999) and reversal-coupled omega turns (Bhattacharya et al., 2014; Gray et al., 2005). We previously demonstrated a requirement for NLP-12 in promoting reorientations during local searching. (Bhattacharya et al., 2014). Our analysis here shows that loss of nlp-12 also has modest effects on body posture during normal exploratory movement, indicating NLP-12 regulation of motor targets under basal conditions. Intriguingly, the behavioral requirement for NLP-12 is far more apparent during local searching compared with basal locomotion, suggesting enhanced involvement of NLP-12 signaling for performance of local searching. Similar observations about NLP-12 involvement in chemotactic responses to varying oxygen levels suggested a model for graded NLP-12 regulation of movement (Hums et al., 2016). Based on our observations, we speculate that increased engagement of head motor neurons through CKR-1 activation may be a generalizable mechanism for dynamic NLP-12 regulation of behavior over changing external conditions.

Prior studies had implicated the CKR-2 GPCR in NLP-12 function (Hu et al., 2015; Hu et al., 2011; Janssen et al., 2008), but roles for CKR-1 had not been previously described. Our genetic analyses and heterologous expression studies firmly establish CKR-1 as a functional target for NLP-12 signaling with an activation profile similar to CKR-2. CKR-2 shows slightly broader expression compared with CKR-1, but both GPCRs are expressed across a variety of neuron classes, including many that do not receive direct synaptic inputs from DVA. We noted very little overlap in CKR-1 and CKR-2 expression, consistent with the idea that the two GPCRs serve distinct roles in modulating behavior. NLP-12 activation of CKR-2 stimulates neurotransmission through coupling with egl-30 (Gαq) and egl-8 (PLCβ) likely by DAG interaction with the synaptic vesicle priming factor UNC-13 (Hu et al., 2015; Hu et al., 2011). Given the sequence homology between CKR-1 and CKR-2, it seems likely that CKR-1 also functions to positively regulate neuronal activity through egl-30. In support of this idea, we found that SMD-specific CKR-1 overexpression and SMD neuron photostimulation produced qualitatively similar behavioral effects. The DVA neuron makes a single synapse with SMDVL (Worm wiring). While it is possible that this single synapse accounts for NLP-12 elicited behavioral changes during local searching, it seems likely that extrasynaptic signaling to other SMD neurons also contributes.

Prior studies have indicated SMDs are cholinergic and their stimulation is sufficient to produce Ca2+ transients in head/neck muscles, consistent with proposed roles in head bending (Pereira et al., 2015; Shen et al., 2016). Prior studies of worms immobilized using microfluidic chips and freely moving animals noted anti-phasic activity between SMDD and SMDV neurons and opposing head/neck musculature during head bending (or head casting) (Hendricks et al., 2012; Kaplan et al., 2020; Shen et al., 2016; Yeon et al., 2018). Our Ca2+ imaging studies did not offer sufficient cellular resolution to directly address this point. However, combined with our silencing, photostimulation and CKR-1 overexpression experiments, our SMD Ca2+ imaging provides strong evidence that NLP-12 activation of CKR-1 modulates functional connectivity between SMD neurons and their partners. Physiological regulation of SMD activity is complex and involves reciprocal connections with RIA interneurons, reciprocal signaling with RME motor neurons, as well as proprioceptive feedback (Hendricks et al., 2012; Ouellette et al., 2018; Shen et al., 2016; White, 2018; White et al., 1997; Yeon et al., 2018). In particular, inhibitory signaling from the GABAergic RME neurons onto the SMDs is implicated in modulation of head bending amplitude to optimize head bends for forward movement. While the precise role of NLP-12 modulation of SMD activity remains unclear, one intriguing possibility is that NLP-12-elicited increases in SMD activity uncouple the SMDs from RME inhibitory regulation, perhaps promoting large amplitude head swings that couple to forward reorientations during searching. We propose that elevated SMD activity is permissive for reorientations to occur, perhaps acting in concert with SMD proprioceptive functions (Yeon et al., 2018) or other neurons implicated in the regulation of head movement and turning, such as SMB (Oranth et al., 2018).

Surprisingly, selective ckr-1 overexpression using the odr-2(16) or flp-22∆4 promoters increased body bend depth, raising the question of how altered SMD activity might translate into increased body bending. Recent work suggests an interesting functional coupling between the activity of SMD neurons and ventral cord B-type motor neurons (Kaplan et al., 2020). B-type motor neurons are suggested to act as a distributed central pattern generator for the propagation of body bends (Gao et al., 2018; Xu et al., 2018). CKR-1 activation of SMDs may therefore influence body depth directly by altering body wall motor neuron excitability through a gap junction connection between VB1 and SMDVR or through neuromuscular synapses located in the sub-lateral processes.

The similar potency of NLP-12 peptides for activating CKR-1 and CKR-2, suggests that differential contributions of these GPCRs during basal locomotion and search responses do not arise due to dramatic differences in NLP-12 potency to activate each receptor. This raises important questions about how a bias toward CKR-1 modulation of the head motor circuit during local searching may occur. We envision that NLP-12 regulation of the SMD neurons acts in parallel with other neural pathways previously shown to promote reversals during local searching. For example, olfactory information about food availability is conveyed by sensory neurons such as AWC and ASK to premotor interneurons (AIA, AIB, AIY) and ultimately transformed into patterns of motor neuron activity that drive reversals (Gray et al., 2005; Hills et al., 2004; Ouellette et al., 2018; Sawin et al., 2000). The SMD neurons also receive synaptic information from this circuit (e.g., through synaptic connections from the AIB and RIM neurons) (White et al., 1997), raising the possibility that a pathway activated by food removal may enhance SMD sensitivity to CKR-1 activation. In this case, SMD neurons may be a site for integration of information encoding reversals and forward reorientations during local searching. A shift to CKR-1 modulation of head neurons during searching could also be triggered by dopaminergic stimulation of DVA. Prior work implicated dopaminergic signaling from PDE neurons in the regulation of NLP-12 and motor responses (Bhattacharya et al., 2014; Oranth et al., 2018). In this case, elevated levels of NLP-12 secretion, perhaps from release sites in the nerve ring region, would be predicted to bias the system toward enhanced activation of the SMD neurons and elicit increased turning. Notably, PDE also regulates an antagonistic peptidergic circuit, mediated by FLP-1 neuropeptides, through inhibitory connections with AVK interneurons (Oranth et al., 2018), suggesting potentially more distributed behavioral regulation.

Our studies of the nematode NLP-12 system offer new mechanistic insights into neuropeptide modulation of behavior. Our findings provide a key first step in defining roles for two NLP-12-responsive GPCRs in coordinating motor control across changing conditions. We propose that the NLP-12 system conditionally engages GPCRs expressed in head or body motor neurons to modify specific features of locomotion, most notably reorientations during searching and body bend depth during basal locomotion. Brain CCK has been increasingly implicated as a key regulator in diverse aspects of behavior, including feeding, satiety, memory, nociception, and anxiety (Ballaz, 2017; Chandra and Liddle, 2007; Liddle, 1997; Miyasaka and Funakoshi, 2003; Lajtha and Lim, 2006; Rehfeld, 2017). Thus our studies elucidating mechanisms for NLP-12 regulation of circuit function in the compact nematode nervous system may have important and broadly applicable implications for neuromodulation in more complex systems.

Materials and methods

Strains

All nematode strains (Supplementary file 1) were maintained on OP50 seeded agar nematode growth media (NGM) at room temperature (22–24°C). N2 Bristol strain was used as wild type. Transgenic animals were generated by microinjection into the germ line and transformation was monitored by co-injection markers. Multiple independent extrachromosomal lines were obtained for each transgenic strain and data were presented from a single representative transgenic line. Stably integrated lines were generated by X-ray integration and outcrossed at least four times to wild type.

Molecular biology

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All plasmids, unless specified, were generated by Gateway cloning (see Supplementary files 1–5). p-ENTR plasmids were generated for all promoters used (Supplementary file 5). The ckr-1 minigene construct (pRB12/pRB13) was generated by cloning the ckr-1 coding sequence (start to stop), with introns 1, 8, and 9. For cell-specific overexpression or rescue, the ckr-1 minigene was recombined with entry vectors containing the relevant cell-specific promoters (Supplementary files 3-4).

Behavioral assays and analyses

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All behavioral assays were carried out using staged 1 day adult animals on Bacto-agar NGM agar plates seeded with a thin lawn of OP50 bacteria (50 µl) unless otherwise noted. Video recordings for behavioral analyses were obtained using a Firewire camera (Imaging Source) and ICCapture2.2. Animals were allowed to acclimate for 30 s prior to video recording. Post hoc locomotor analysis was performed using WormLab (MBF Bioscience) (Video 8). Videos were thresholded to detect worms, and worm movement was tracked. Body bend amplitude was quantified as the average centroid displacement over the duration of a locomotion track (Figure 1B). Body bending angle was measured, at the midbody vertex, as the supplement of the angle between the head, mid-body, and tail vertices (Figure 1C). Bending angles were measured, continuously for each frame tracked, over 30 s (900 frames @30 fps). The measured bending angles were binned to generate a frequency distribution of body bending angles. Kymographs were generated from worm body curvature data (WormLab) in MATLAB (MathWorks, Natick, MA).

Video 8
Representative 20-s video showing tracking locomotion of animal overexpressing nlp-12 in WormLab to analyze body bending.

Video has been sped up 4×.

Area restricted search behavior

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For quantification of local search behavior, single well-fed animals were transferred to an intermediate unseeded plate. After 1 min, animals were repicked without bacteria and transferred to an unseeded behavior assay plate. Digital movies were captured over the first 5 min (local search) and after 30 min (dispersal) following removal from food. Reorientations were manually scored post hoc from monitoring movement direction, over sequential frames (~200 frames for forward reorientations, ~ 600 frames for reversal-coupled omega turns) from the start of the reorientation (original trajectory) to when the animal completed the reorientation (new trajectory) (Figure 3B, Figure 3—figure supplement 1). A forward reorientation was scored after animals moved a minimum of 3 s (~100 frames @30 fps) along a new trajectory. We scored forward trajectory changes >50° and reversal coupled omega turns as reorientations (examples of each in Figure 3B, Figure 3—figure supplement 1). Trajectory changes where animals initially performed head bends >50°, but then resumed the original path of movement or altered immediate trajectory <50° were not scored as reorientations. Trajectory changes were quantified (in degrees) using the angle tool (ImageJ, National Institutes of Health) to measure the angle between the original and new trajectory (Figure 3B, Figure 3—figure supplement 1). We excluded reversals and post reversal changes in trajectory that did not involve omega turns.

Single worm tracking

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Single worm tracking was carried out using Worm Tracker 2 (Yemini et al., 2011). Animals were allowed to acclimate for 30 s prior to tracking. Movement features were extracted from 5 min of continuous locomotion tracking (Video 9). Worm tracker software version 2.0.3.1, created by Eviatar Yemini and Tadas Jucikas (Schafer lab, MRC, Cambridge, UK), was used to analyze movement (Yemini et al., 2013). Worms were segmented into head, neck, midbody, hips, and tail. The body bend angle is angle measured at the midbody vertex, between the neck and hip skeleton vertices (Figure 2A). Head bend angles were measured as the largest bend angle prior to returning to a straight, unbent position (Figure 2B). Absolute midbody bending (Figure 2A) and head bending (Figure 2B) angles were quantified. Single worm tracking affords higher resolution and allows for rich quantification of relatively subtle postural changes. However, the continuous tracking of animals was difficult to achieve using this approach during the numerous steep turns performed during ARS, or with NLP-12 or CKR-1 overexpression. Post hoc analysis of videos to measure body bending (as described above) proved most reliable.

Video 9
Representative 20-s video showing single worm tracking of wild-type animal during basal locomotion on food to analyze body bending and head bending.

Video has been sped up 4×.

SMD ablation

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Conditions for cell ablation by miniSOG activation were adapted from Xu and Chisholm, 2016. MiniSOG activation was achieved by stimulation with repetitive 2 Hz 250 ms blue light pulses for 12 min (200 mW/cm2, 488 nm 50 W LED [Mightex Systems]). Experiments were performed on unseeded plates using larval stage four ckr-1(OE) animals expressing miniSOG and GFP transgenes under the flp-22∆4 promoter. Following stimulation, animals were allowed to recover in the dark on NGM OP50 plates for 16 hr prior to behavioral analysis or imaging.

Photostimulation experiments

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All-trans retinal (ATR) plates were prepared (100 mM stock in ethanol, final working 2.7 mM in OP50). Plates were stored at 4°C under dark conditions and used within 1 week. Animals were grown on +ATR OP50 plates in dark and L4 animals were transferred to a fresh +ATR plate prior to the day of experiment. Experiments were performed using 1-day adults. For ChR2 photostimulation, experiments were conducted using a fluorescent dissecting microscope (Zeiss stereo Discovery.V12) equipped with a GFP filter set. Behavior was recorded for a 1-min period prior to photostimulation and during a subsequent 1 min period during photostimulation. Data are expressed as % change in reorientations across these time intervals. Chrimson photostimulation (26 mW/cm2) experiments were conducted using a 625 nm 50 W LED (Mightex Systems). Animals were video recorded for 1 min in the absence of light stimulation (prestimulus) and subsequently for 1 min with light stimulation. Control experiments (−ATR) were performed in the same manner.

SMD silencing

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ARS assays were performed on unseeded Histamine (10 mM) and control Bacto-agar NGM plates using staged 1-day adults. For SMD silencing, transgenic animals were placed on Histamine plates, seeded with 100 µl OP-50, for 1 hr prior to experiment. ARS was quantified as described previously.

Imaging

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Fluorescent images were acquired using either BX51WI (Olympus) or Yokogawa (PerkinElmer) spinning disc confocal microscopes. Data acquisition was performed using Volocity software. Staged 1-day adult animals were immobilized using 0.3 M sodium azide on 2% agarose pads. Images were analyzed using ImageJ software.

SMD calcium imaging

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Calcium imaging was performed in behaving transgenic animals, expressing GCaMP6s::SL2::mCherry under flp-22∆4 promoter, on 5% agarose pads on a glass slide. Animals were treated as described for ARS and dispersal assays. Animals were tracked and videos captured, with continuous and simultaneous dual-channel (GCaMP6s and mCherry) fluorescence monitoring (Video 7), in the time windows of ARS (0–5 min) and dispersal (30–35 min off food). Imaging was carried out on an Axio Observer A1 inverted microscope (Zeiss) connected to a Sola SE Light Engine (Lumencor) with an Olympus 2.5× air objective, and a Hamamatsu Orca-Flash 4.0 sCMOS camera. Simultaneous GCaMP and mCherry acquisition were achieved using the optical splitter Optisplit-II (Cairn Research) with filters ET525/50M and ET632/60M, and dichroic T560Iprx-UF2 (Chroma). Image acquisition was performed using Micromanager, at 66 ms exposure (approximately 15 fps).

ROIs encompassing cell bodies in the nerve ring, labeled by mCherry, were tracked post hoc using MATLAB (Neuron Activity Analysis, Mei Zhen, Video 7). Frames where tracking issues were encountered due to stage movement were excluded from analysis. The background subtracted calcium signals were plotted as a ratio (GCaMP6s/mCherry). We encoded corresponding behavior into four categories: forward locomotion, reversals, forward reorientations, and omega turns. Wild-type animals that did not perform searching (<4 reorientations during ARS) were excluded from the analysis. Correlation analysis, including linear fits and calculation of Pearson’s coefficient, was performed in Graphpad Prism. For display, heat maps were plotted in Graphpad Prism (Figure 8) and representative traces (Figure 8—figure supplement 1) were interpolated with a smoothing spline in Igor Pro (Wavemetrics, Portland, OR).

in vitro GPCR characterization

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The GPCR activation assay was performed as previously described (Caers et al., 2014; Peymen et al., 2019; Van Sinay et al., 2017). Briefly, CHO-K1 cells stably expressing the luminescent Ca2+ indicator aequorin and the promiscuous Gα16 protein (ES-000-A24 cell line, PerkinElmer) were transiently transfected with ckr-1/pcDNA3.1, ckr-2/pcDNA3.1, or empty pcDNA3.1 vector. Cells were transfected with Lipofectamine LTX and Plus reagent (Invitrogen) at 60–80% confluency and grown overnight at 37°C. After 24 hr, they were shifted to 28°C overnight. On the day of the assay, transfected cells were collected in bovine serum albumin (BSA) medium (DMEM/F12 without phenol red with L-glutamine and 15 mM HEPES, Gibco, supplemented with 0.1% BSA), at a density of 5 million cells per ml, and loaded with 5 µM coelenterazine h (Invitrogen) for 4 hr at room temperature. Compound plates containing synthetic peptides in DMEM/BSA were placed in a MicroBeta LumiJet luminometer (PerkinElmer). After loading, the transfected cells were added at a density of 25,000 cells/well, and luminescence was measured for 30 s at a wavelength of 469 nm. After 30 s, 0.1% triton X-100 (Merck) was added to lyse the cells, resulting in a maximal Ca2+ response that was measured for 30 s. To constitute concentration-response curves of NLP-12 peptides, peptide concentrations ranging from 1 pM to 10 µM were tested in triplicate on 2 independent days.

Data availability

All data generated or analyzed during this study are included in the manuscript and supporting files.

References

    1. Chandra R
    2. Liddle RA
    (2007) Cholecystokinin
    Current Opinion in Endocrinology, Diabetes, and Obesity 14:63–67.
    https://doi.org/10.1097/MED.0b013e3280122850
  1. Book
    1. Lajtha A
    2. Lim R
    (2006) Handbook of Neurochemistry and Molecular Neurobiology
    In: Lajtha A, editors. Neuroactive Proteins and Peptides. Springer. pp. 545–571.
    https://doi.org/10.1007/978-0-387-30381-9
    1. White JG
    2. Southgate E
    3. Thomson JN
    4. Brenner S
    (1997) The structure of the ventral nerve cord of Caenorhabditis elegans
    Philosophical Transactions of the Royal Society of London. B, Biological Sciences 275:327–348.
    https://doi.org/10.1098/rstb.1976.0086
    1. White J
    (2018) Clues to basis of exploratory behaviour of the C. elegans snout from head somatotropy
    Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 373:20170367.
    https://doi.org/10.1098/rstb.2017.0367

Decision letter

  1. Manuel Zimmer
    Reviewing Editor; University of Vienna, Austria
  2. Ronald L Calabrese
    Senior Editor; Emory University, United States

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]

Thank you for submitting your work entitled "A conserved neuropeptide system links head and body motor circuits to enable adaptive behavior" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by a Senior Editor. The reviewers have opted to remain anonymous.

Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in eLife.

While the reviewers find your work very interesting and acknowledge its importance in understanding the role of cholecystokinin signaling in differentially controlling aspects of locomotion behavior in C. elegans, we think that in its current form it lacks further mechanistic insights into how ckr-1 signaling controls SMD activity.

Reviewer #1:

In this manuscript Ramachandran et al. provide a C. elegans behavioral genetics study focused on the worm cholecystokinin-like neuropeptide-receptor system. They show that nlp-12 neuropeptides released from the DVA neuron fulfil a dual role in controlling body posture as well as head-bending mediated area restricted search (ARS). Previous work showed that DVA controls body posture via nlp-12 signaling to ckr-2 receptor in ventral cord motor neurons. Moreover, nlp-12 signaling was implicated in ARS; but the exact circuit mechanisms and targets of nlp-12 remained elusive. The present work shows in a pretty straight forward way that ckr-1 in SMD head motor neurons is the missing link. In worms, ARS is composed of quiet complex body movements including high angle turns during the worm's forward crawling state. Nlp-12 and ckr-1 mutants show reduced head bending during ARS, while overexpression leads to a stark ectopic ARS like behavior. The authors convincingly show that SMDs are the site of action for ckr-1 and implicated in ARS. They show both requirement and sufficiency of SMDs for ARS like behaviors. The regulation of ARS vs. dispersive behaviors has been extensively studied at the levels of sensory and interneurons in the worm, but how the switch is implemented at motor circuits was largely unknown. Conceptually, this is one of only few studies investigating the selective control of head versus body movements and provides some interesting insights into the underlying mechanisms; therefore, the study is definitely important and timely. But it is unclear still how upper sensory circuits transmit the switch between ARS and dispersal to the DVA-SMD circuit. Moreover, the present study does not investigate the signaling pathway of ckr-1 in SMDs and its role in controlling neuronal activity, e.g. via Ca++ imaging. As a sole behavioral genetics study, however, I find the manuscript quite complete. The experiments logically built upon another, and the paper is well written. My only major critique is that parts of the behavioral analyses are described with insufficient detail so that it is unclear to the expert how and what exact movements were quantified. This should be addressed by providing more detailed figure captions, methods sections, more supplemental figures and movies.

1) The authors should exclude (or separate) reversal states and post-reversal turns in their analyses when measuring head bending, body bending and turn events, but it is unclear if they did so.

2) Figure 1C and methods: it is unclear what defines a singular bending event as marked on the y-axis. Did the authors measure the maximum angle during each half-oscillation? If yes, this should be explained and how maxima were calculated etc. Or do the histograms represent all values from all recording frames. In the latter case, the y-axis labelling is misleading, and I suggest use "fraction of frames".

3) Figure 1C: these are averaged histograms of n=10-12 worms, but what is the average number of events per worm and in total?

4) Figure 1B-C, 2A etc.: to perform the measurements as depicted in upper panels is not really trivial, and I have the impression that the authors used their software packages in a black-box manner. What are the exact image processing steps to implement these measurements, i.e. how was vertex and sides of the angles exactly positioned? The authors should provide time-series of individual examples alongside with movies demonstrating how accurately the pipeline performs during complex ARS postures.

5) Figure 2B: the angles and body segments describing the head and head-bending angels should be unambiguously defined. The cartoon in 2B looks like they just measured nose movements.

6) Figure 3B: reorientation events are not sufficiently defined here. During ARS, worms frequently switch between forward-backward movement, perform post-reversal turns and in a continuous manner exhibit curved trajectories. From a trajectory like the red one in 3A, it is again not trivial to identify and discretize individual turning events with a start and an end and distinguish them from reversals and post reversal turns.

– The procedure needs to be explained in greater details with justification of parameter choice.

– How did the authors validate that the procedure performed well, especially during the complex ARS behaviors?

– Again, example trajectories and movies should be shown.

7) All histogram panels lack statistics, e.g. KS test or appropriate alternatives.

Reviewer #2:

Ramachandran et al. report the discovery of a C. elegans GPCR – CKR-1 – that mediates some of the effects of the cholecystokinin-like neuropeptide NLP-12 on posture and foraging behavior. The discovery of this receptor permits further study of this neuropeptide signaling system, which is conserved from worms to vertebrates. Although CKR-1 is expressed in many neurons, the authors show that its function in SMD head-motorneurons is especially important for control of posture and foraging. The manuscript's strengths include: (1) rigorous characterization of receptor-ligand interactions in vitro, using a cell-based assay for GPCR activation, and in vivo, using genetic analysis, (2) compelling data in support of a model in which NLP-12 regulates SMD neurons to control foraging, and (3) high-resolution analysis of C. elegans posture during foraging, which illustrates the complexity and richness of this behavior, and (4) the circuit model, i.e. a role for SMDs, is tested using a number of independent methods and clearly indicated. The manuscript does have some weaknesses. In addition to specific technical points listed below, the manuscript discussed neuropeptides derived from a single source, the DVA pre-motor neuron, acting on distinct targets via distinct receptors in a conditional manner. This interesting model is suggested by the title and the abstract and comes up plainly in the introduction and discussion. However, the model is not clearly supported by the data, which primarily focus on the characterization of CKR-1 as a relevant receptor for NLP-12 peptides. Another weakness in the manuscript arises from the authors' switching between various assays for posture during locomotion, which makes it difficult for the reader to compare data between figures. Rich kymography data are relegated to supplementary figures, and data from only a subset of relevant genotypes are shown as kymographs. The manuscript would be strengthened by more uniform analysis of posture and foraging. Finally, while the data clearly show that effects of NLP-12 on posture and foraging require SMD neurons, the manuscript does not investigate how NLP-12 affects SMD activity. The manuscript would be strengthened by experiments showing a functional connection between DVA and SMD neurons, e.g. functional imaging of SMDs during optogenetic manipulation of DVAs.

1. One premise of the work is that DVA neurons are the sole source in vivo of NLP-12 peptides. A recent study (Tao et al. 2019, Dev. Cell) shows that there is an alternate source of NLP-12, the PVD nociceptors. The authors should address the possibility that their assays also detect a contribution of PVD neurons to posture/foraging.

2. The text associated with Figure 1B-C is tentative with respect to assigning redundant functions to CKR-1 and CKR-2. Why? The data are clear; these receptors function redundantly.

3. The very nice in vitro analysis of NLP-12 receptors should include negative controls. Ideally, the authors would use a scrambled neuropeptide or a related neuropeptide to demonstrate specificity of the interactions between NLP-12 and CKR-1/2.

4. The different 'bending angles' used in Figures 1 and 2 make it difficult to compare data between figures. Also, the schematics used to explain the bending angles have small fonts and are hard to read.

5. Figure 3E shows the results of a nice experiment in which optogenetic activation of NLP-12-expressing cells – presumably DVA – causes reorientations. The authors assert that this effect requires CKR-1 but not CKR-2. The data, however, suggest that CKR-2 might have an effect. The variance of the data does not allow the authors to reject a null hypothesis, but they err in then assuming that this means that CKR-2 plays no role in the phenomenon. This experiment should be repeated to determine whether there is indeed a specific or privileged role for CKR-1 in mediating NLP-12-dependent reorientations.

6. Also, Figure 3E should show raw data – don't show proportional changes – and all Figure 3 should be scatter plots allowing the reader to assess the variance of the data.

7. The authors show that effects of receptor overexpression are suppressed by loss of NLP-12 peptides. Is there precedent for this kind of genetic interaction in the literature?

8. Also, the authors, assert that suppression of effects of CKR-1 overexpression by loss of NLP-12 shows that NLP-12 peptides are the sole ligands for this receptor (page 9, line 17). It is not clear why the authors reach this conclusion.

9. There are some very nice data that are assigned to supplementary figures but might be better placed in main figures. Figure S3A-B shows data that are integral to the authors' model and could be presented in a main figure. Also, the localization of NLP-12::Venus in DVA axons near SMD processes would be appropriate to show in a main figure. It would be ideal to mark SMDs with a red fluor so that NLP-12::Venus colocalization with SMD processes could be assessed.

10. The kymography data are nice but incomplete. The authors should show kymographs from strains of all relevant genotypes. This would include: (1) ckr-1(oe); nlp-12, (2) nlp-12, ckr-1, and ckr-2 single mutants, and (3) ckr-1; ckr-2 double mutants.

11. Page 12, last paragraph indicates that 'low levels' of expression rescue ckr-1 phenotype – how has the expression level been determined? I guess that the authors refer to the amount of DNA used for transgenesis, not a direct measure of transgene expression – this should be reworded.

12. The manuscript would be strengthened by experiments that measured the effect of DVA activation on SMD physiology and what contribution NLP-12 signaling makes to any functional connection between these neurons. One potential impact of this work is that it establishes a nice paradigm for new molecular genetic analyses of neuropeptide signaling. Direct observation of the effects of NLP-12 peptides on SMD neuron physiology would further strengthen the authors' conclusions and suggest mechanisms by which CKR-1 regulates cell physiology.

Reviewer #3:

In this manuscript, Ramachandran and colleagues describe how cholecystokinin-related NLP-12 neuropeptide signalling in C. elegans can regulate two different behavioural programmes, area-restricted search (ARS) and basal locomotion, by conditionally engaging different specific receptors that are expressed in different neuronal targets. They thoroughly characterise the CKR-1 receptor which had not been described previously, and place its function in context with that of the previously known NLP-12 receptor CKR-2. The manuscript gives new insight into an interesting and likely conserved mechanisms of how neuromodulatory systems enable adaptive behaviour by coordinating the action of neural circuits even when they are not directly connected. The conclusions drawn appear solid and are justified by the data presented, and the experimental approaches and results are well documented.

The main problem with the work is a certain lack of clarity regarding the separation of the roles of the CKR-1 and CKR-2 receptors on basal locomotion/body bending and head bending/reorientations. Overexpression of NLP-12 places animals in a chronic ARS state, as described in a previous publication. Is the NLP-12 overexpression model representative of the increased reorientation in area restricted search, or of control of undulations in basal locomotion, or both? If it is primarily representative of area restricted search, this would mean that CKR-2, similarly to CKR-1, mediates the chronic ARS state induced by NLP-12 overexpression, because in Figure 1B and C its mutation causes a reduction in the phenotype, and deletion of both ckr-1 and ckr-2 causes a stronger reduction.

Also, it is unconvincing that SMD neurons do not express ckr-2 (see S3D); no comparison of ckr-1 and ckr-2 expression levels in SMD is provided and in fact the CeNGEN data of single cell RNAseq of C. elegans neurons shows similar expression of both receptors in SMDD (accessible at cengen.shinyapps.io/SCeNGEA). On the other hand, loss of ckr-2 on its own does not cause a significant reduction in ARS (Figure 3A).

To clarify this, the authors could measure the reorientation rate in the nlp-12OE ckr-2 mutant strain.

Given that ckr-1 overexpression as shown in Figures4-6 increases both body bending amplitude and ARS-like high reorientation rate, the authors offer the interesting possibility that SMD may also affect basal locomotion. I would suggest an experiment that clarifies whether SMD also controls body bending in basal locomotion using the single-worm tracking assay shown in Figure 2A with the SMD-specific ckr-1 rescue strains in a ckr-1 mutant background (as used in figure 7). Also they could measure body bending in the existing data on the SMD::Chrimson optogenetics.

Overall, the manuscript is of high quality and significant interest and warrants publication in eLife, once those points have been addressed.

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "A conserved neuropeptide system links head and body motor circuits to enable adaptive behavior" for further consideration by eLife. Your revised article has been evaluated by Ronald Calabrese (Senior Editor) and a Reviewing Editor.

The reviewers are very excited about your work and the improvements made in your revision. However, there are some remaining issues that need to be addressed. As outlined below, the major concern of reviewers #1-2 with respect to SMD Ca++ imaging and the minor points of reviewer #3 should be addressed. We assume that this would not require new experiments but further in-depth analysis of the recordings, which should be all feasible in a short time frame.

Reviewer #1:

The authors have fully addressed my review comments to the previous submission.

In the present manuscript, the authors provide SMD Ca++ imaging experiment, which require further clarifications:

1) SMD activity in crawling worms has been reported previously by several labs, and all studies found consistently activity related to head-bending (Hendricks et al., 2012; Kaplan et al., 2020; Yeon et al., 2018). From the activity profiles shown in Figure 5, it is not possible to evaluate whether these data can be reproduced by the authors. If movie S9 is representative for these recordings, then SMD activity profiles should relate to head-bending. The fluctuations in Figure 5E rather appear as noise to me. I find it essential that the authors annotate behaviour in these recordings (forward crawling, backward crawling, head bending) and analyse the relationship between SMD activity and locomotion. If any discrepancies to the literature remain, this and possible explanations should be discussed.

2) Despite the concerns above, I find it surprising and interesting that the authors observe different perhaps baseline ratio values in 0-5min vs 30-35min off-food conditions. How this relates to the different behavioral phenotypes, incorporating our knowledge about SMD physiology remains to be discussed in more detail.

Hendricks, M., Ha, H., Maffey, N., and Zhang, Y. (2012). Compartmentalized calcium dynamics in a C. elegans interneuron encode head movement. Nature 487, 99-103.

Kaplan, H.S., Salazar Thula, O., Khoss, N., and Zimmer, M. (2020). Nested Neuronal Dynamics Orchestrate a Behavioral Hierarchy across Timescales. Neuron 105, 562-576.e569.

Yeon, J., Kim, J., Kim, D.-Y., Kim, H., Kim, J., Du, E.J., Kang, K., Lim, H.-H., Moon, D., and Kim, K. (2018). A sensory-motor neuron type mediates proprioceptive coordination of steering in C. elegans via two TRPC channels. PLoS biology 16, e2004929.

Reviewer #2:

The revised manuscript of Ramachandran, Francis and colleagues addresses many of the questions raised during the initial round of review. I have only one comment. The authors include new data reporting SMD activity during area-restricted search and dispersal. This is an interesting experiment that shows clear evidence for CKR-1 in regulation of SMDs. It is not clear why the authors only show data from 3 individuals in panel E of Figure 7; panel F indicates that there are many more individuals that were assayed. I suggest that the authors show data from all the individuals in panel E.

Reviewer #3:

Using a variety of different approaches, Ramachandran and colleagues make a convincing case that CKR-1 acting in SMD primarily mediates the effect of the NLP-12 on local food searching. All relevant weaknesses of the first submission raised by reviewers have been addressed, in particular:

– The various behavioural measurements are now well defined.

– Additional functional data have been added for SMD which strengthen the hypothesis that ckr-1-mediated signalling in SMD is both necessary and sufficient for ARS.

– New data added describing the rescue of ckr-2 expression in a ckr-1; ckr-2 double mutant is convincing to answer the question of distinguishing the (lack of a) role of ckr-2 in ARS.

– New data on SMD now answer the question whether it affects only area-restricted search or also body bending in basal locomotion.

The manuscript still a variety of different behavioural analyses, but I think this is acceptable, because they are now better defined, and are also necessary to address the different effects of overexpression/loss of function and of the different behavioural programmes controlled by NLP-12.

In the first reviews the point was made that the paper was more or less only a behavioural genetics study; I believe that the evidence from ontogenetic, chemogenetic and functional neuronal imaging approaches used to support the hypothesis, the revised study is of sufficient standard for eLife.

https://doi.org/10.7554/eLife.71747.sa1

Author response

Reviewer #1:

In this manuscript Ramachandran et al. provide a C. elegans behavioral genetics study focused on the worm cholecystokinin-like neuropeptide-receptor system. They show that nlp-12 neuropeptides released from the DVA neuron fulfil a dual role in controlling body posture as well as head-bending mediated area restricted search (ARS). Previous work showed that DVA controls body posture via nlp-12 signaling to ckr-2 receptor in ventral cord motor neurons. Moreover, nlp-12 signaling was implicated in ARS; but the exact circuit mechanisms and targets of nlp-12 remained elusive. The present work shows in a pretty straight forward way that ckr-1 in SMD head motor neurons is the missing link. In worms, ARS is composed of quiet complex body movements including high angle turns during the worm's forward crawling state. Nlp-12 and ckr-1 mutants show reduced head bending during ARS, while overexpression leads to a stark ectopic ARS like behavior. The authors convincingly show that SMDs are the site of action for ckr-1 and implicated in ARS. They show both requirement and sufficiency of SMDs for ARS like behaviors. The regulation of ARS vs. dispersive behaviors has been extensively studied at the levels of sensory and interneurons in the worm, but how the switch is implemented at motor circuits was largely unknown. Conceptually, this is one of only few studies investigating the selective control of head versus body movements and provides some interesting insights into the underlying mechanisms; therefore, the study is definitely important and timely. But it is unclear still how upper sensory circuits transmit the switch between ARS and dispersal to the DVA-SMD circuit. Moreover, the present study does not investigate the signaling pathway of ckr-1 in SMDs and its role in controlling neuronal activity, e.g. via Ca++ imaging.

As a sole behavioral genetics study, however, I find the manuscript quite complete. The experiments logically built upon another, and the paper is well written. My only major critique is that parts of the behavioral analyses are described with insufficient detail so that it is unclear to the expert how and what exact movements were quantified. This should be addressed by providing more detailed figure captions, methods sections, more supplemental figures and movies.

We thank the reviewer for pointing this out. We have now updated the methods and figures with additional details of the experiments and their analyses. In particular, Figure 3B has been revised to show how trajectory changes were measured and reorientations scored. We also now include in Figure S3 representative sequences of frames demonstrating examples of both forward reorientations and reversal coupled omega turns from our analyses.

1) The authors should exclude (or separate) reversal states and post-reversal turns in their analyses when measuring head bending, body bending and turn events, but it is unclear if they did so.

We scored forward reorientations greater than 50 degrees and reversal-coupled omega turns as reorientations (examples of each in Figure S3). We excluded post-reversal changes in trajectory that did not involve an omega turn. We have clarified this in the Methods. We agree that it is important to know which classes of reorientation may be affected by NLP-12 and CKR-1 signaling. We now include additional experiments showing that forward reorientations are significantly reduced by deletion of either nlp-12 or ckr-1, while reversal coupled omega turns are not, [Figure S4] consistent with our previously published findings for nlp-12 (Bhattacharya et al., 2015).

2) Figure 1C and methods: it is unclear what defines a singular bending event as marked on the y-axis. Did the authors measure the maximum angle during each half-oscillation? If yes, this should be explained and how maxima were calculated etc. Or do the histograms represent all values from all recording frames. In the latter case, the y-axis labelling is misleading, and I suggest use "fraction of frames".

We agree with the reviewer and clarify this in the revised version. We measured bending angles continuously (900 frames @ 30 fps) over the course of 30 s recordings. These were binned and represented as a frequency histogram. We changed the Y axis labels of the histograms to “frequency of bending angles (%)”.

3) Figure 1C: these are averaged histograms of n=10-12 worms, but what is the average number of events per worm and in total?

See above. Bending angles were measured continuously over 30 s (900 frames @ 30 fps).

4) Figure 1B-C, 2A etc.: to perform the measurements as depicted in upper panels is not really trivial, and I have the impression that the authors used their software packages in a black-box manner. What are the exact image processing steps to implement these measurements, i.e. how was vertex and sides of the angles exactly positioned? The authors should provide time-series of individual examples alongside with movies demonstrating how accurately the pipeline performs during complex ARS postures.

We now provide an illustrative time series as well as representative movies and additional details in the Methods.

5) Figure 2B: the angles and body segments describing the head and head-bending angels should be unambiguously defined. The cartoon in 2B looks like they just measured nose movements.

We have modified the figure to improve clarity and increased the size of schematics.

6) Figure 3B: reorientation events are not sufficiently defined here. During ARS, worms frequently switch between forward-backward movement, perform post-reversal turns and in a continuous manner exhibit curved trajectories. From a trajectory like the red one in 3A, it is again not trivial to identify and discretize individual turning events with a start and an end and distinguish them from reversals and post reversal turns.

– The procedure needs to be explained in greater details with justification of parameter choice.

We have modified the Methods to provide more experimental detail. Videos were scored manually. We measured changes in trajectory (degrees) using the angle measure tool in Fiji as shown in new Figure 3B. We scored forward trajectory changes greater than 50 degrees and reversal-coupled omega turns as reorientations (examples of each in Figure S3). We excluded post-reversal changes in trajectory that did not involve an omega turn. We have clarified this in the Methods. During post hoc analysis of acquired videos, original and new trajectories were set from monitoring movement direction, over sequential frames (~200 frames for forward reorientations and ~600 frames for reversal-coupled omega turns), from the start of the reorientation (original trajectory) to completion of the reorientation (new trajectory) (Figure 3B, S3). Reorientations were scored only in instances where the animal moved a minimum of 3 s (~100 frames @ 30 fps) along a new trajectory.

– How did the authors validate that the procedure performed well, especially during the complex ARS behaviors?

We have clarified the procedure we used for manual scoring by adding examples of sequential frames during reorientation with overlay of the angle measured (Figure 3B, S3) and added representative images showing forward reorientations and reversal coupled turns. We also note that our methods cleanly distinguished ARS (0-5 minutes after removal from food) and dispersal (30-35 minutes off food) behaviors in wild type, demonstrating its effectiveness.

– Again, example trajectories and movies should be shown.

These are now included.

7) All histogram panels lack statistics, e.g. KS test or appropriate alternatives.

We now include appropriate statistical comparisons by KS test.

Reviewer #2:

Ramachandran et al. report the discovery of a C. elegans GPCR – CKR-1 – that mediates some of the effects of the cholecystokinin-like neuropeptide NLP-12 on posture and foraging behavior. The discovery of this receptor permits further study of this neuropeptide signaling system, which is conserved from worms to vertebrates. Although CKR-1 is expressed in many neurons, the authors show that its function in SMD head-motorneurons is especially important for control of posture and foraging.

The manuscript's strengths include: (1) rigorous characterization of receptor-ligand interactions in vitro, using a cell-based assay for GPCR activation, and in vivo, using genetic analysis, (2) compelling data in support of a model in which NLP-12 regulates SMD neurons to control foraging, and (3) high-resolution analysis of C. elegans posture during foraging, which illustrates the complexity and richness of this behavior, and (4) the circuit model, i.e. a role for SMDs, is tested using a number of independent methods and clearly indicated.

We thank the reviewer for their positive assessment.

The manuscript does have some weaknesses. In addition to specific technical points listed below, the manuscript discussed neuropeptides derived from a single source, the DVA pre-motor neuron, acting on distinct targets via distinct receptors in a conditional manner. This interesting model is suggested by the title and the abstract and comes up plainly in the introduction and discussion. However, the model is not clearly supported by the data, which primarily focus on the characterization of CKR-1 as a relevant receptor for NLP-12 peptides.

We aim to understand how NLP-12 signaling regulates motor transitions that are characteristic features of both local food searching and oxygen chemotaxis. We demonstrate that NLP-12 can activate 2 GPCRs, CKR-1 and CKR-2. Roles for CKR-2 in regulation of body wall motor neuron activity have been demonstrated previously (Hu et al., 2011), but ckr-2 deletion has little effect on local searching behavior. We therefore focused our efforts on understanding whether CKR-1 may be a primary target of NLP-12 to promote local searching. Our deletion, rescue, overexpression, cell ablation, photostimulation, silencing and calcium imaging experiments support a model where NLP-12 activates CKR-1 expressed in the SMDs to promote searching. We show that CKR-1 and CKR-2 have largely nonoverlapping expression, suggesting they may be differentially utilized to promote alternate behavioral outcomes. Consistent with this, we are able to assign a functional role for CKR-2 solely during basal locomotion. As prior studies have demonstrated CKR-2 function in body wall motor neurons, we did not pursue this aspect further.

Another weakness in the manuscript arises from the authors' switching between various assays for posture during locomotion, which makes it difficult for the reader to compare data between figures. Rich kymography data are relegated to supplementary figures, and data from only a subset of relevant genotypes are shown as kymographs. The manuscript would be strengthened by more uniform analysis of posture and foraging.

We apologize for not making this more clear in the initial submission. The single worm tracking used for analysis of basal locomotion in Figure 2 affords higher resolution and allows for rich quantification of relatively subtle postural changes. However, we were not able to continuously track animals during the numerous steep turns performed during ARS or with NLP-12 or CKR1 overexpression using this approach (the head and tail were often misassigned during deep bends). Hence, we switched to recording videos of behaving animals, and performing post hoc analysis of bending angles with Wormlab (MBF Biosciences). This approach did not offer the same resolution but proved more robust for analyzing deeper body bends. We measure the body bending angle at the midbody vertex in both analyses. While we made every effort to keep these angle measurements consistent across platforms, we acknowledge the measured angles differ somewhat. We now include discussion of these points in both the Methods and Results. See also response to point 4 below.

Finally, while the data clearly show that effects of NLP-12 on posture and foraging require SMD neurons, the manuscript does not investigate how NLP-12 affects SMD activity. The manuscript would be strengthened by experiments showing a functional connection between DVA and SMD neurons, e.g. functional imaging of SMDs during optogenetic manipulation of DVAs.

We have now added calcium imaging (Figure 7E-F) and SMD silencing (Figure 7D) experiments to address the reviewer’s comments. Details below.

1. One premise of the work is that DVA neurons are the sole source in vivo of NLP-12 peptides. A recent study (Tao et al. 2019, Dev. Cell) shows that there is an alternate source of NLP-12, the PVD nociceptors. The authors should address the possibility that their assays also detect a contribution of PVD neurons to posture/foraging.

We thank the reviewer for this comment. We now include additional data showing that PVD-specific expression of nlp-12 does not rescue reorientations during ARS (0-5 minutes off food) [Figure S5C]. We also note that recent CeNGEN single cell RNAseq data show high levels of nlp-12 transcript in DVA and by comparison very low levels in PVD, consistent with our findings.

2. The text associated with Figure 1B-C is tentative with respect to assigning redundant functions to CKR-1 and CKR-2. Why? The data are clear; these receptors function redundantly.

We have modified the text as suggested.

3. The very nice in vitro analysis of NLP-12 receptors should include negative controls. Ideally, the authors would use a scrambled neuropeptide or a related neuropeptide to demonstrate specificity of the interactions between NLP-12 and CKR-1/2.

We now include empty vector negative controls [Figure S2]. Additionally, we note that no other peptides from the synthetic library of roughly 350 peptides significantly activated either CKR-1 or CKR-2.

4. The different 'bending angles' used in Figures 1 and 2 make it difficult to compare data between figures. Also, the schematics used to explain the bending angles have small fonts and are hard to read.

We have expanded the size of the schematics and increased the font size. The single worm tracking used in Figure 2 affords higher resolution and allows for rich quantification of postural changes during basal locomotion. However, we were unable to continuously track animals during the numerous steep turns performed during ARS or with NLP-12 or CKR-1 overexpression using this approach (the head and tail were often misassigned during deep bends). Conversely, we were unable to reliably detect and quantify the comparatively subtle effects of nlp-12, ckr-1 and ckr-2 deletion during basal locomotion using Wormlab. The major difference between the two analyses is that the single worm tracker divides the animal into 5 segments (head, neck, midbody, hip, tail). The body bend angle was measured at the midbody vertex, between the neck and hip skeleton vertices. The Wormlab bending angles were measured as the supplement of the angle between the head, midbody and tail vertices. We now include expanded discussion of these points in the Methods.

5. Figure 3E shows the results of a nice experiment in which optogenetic activation of NLP-12-expressing cells – presumably DVA – causes reorientations. The authors assert that this effect requires CKR-1 but not CKR-2. The data, however, suggest that CKR-2 might have an effect. The variance of the data does not allow the authors to reject a null hypothesis, but they err in then assuming that this means that CKR-2 plays no role in the phenomenon. This experiment should be repeated to determine whether there is indeed a specific or privileged role for CKR-1 in mediating NLP-12-dependent reorientations.

We modified Figure 3E to display to a scatterplot of the data and modified the text to more clearly describe the variability in ckr-2 mutant responses to DVA photostimulation. ckr-1 deletion led to a clear reduction in DVA-stimulated reorientations, leading us to primarily focus on the requirement for CKR-1. The critical importance of CKR-1 for generating reorientations is further supported by our additional behavioral, overexpression and calcium imaging results.

6. Also, Figure 3E should show raw data – don't show proportional changes – and all Figure 3 should be scatter plots allowing the reader to assess the variance of the data.

We modified Figure 3E to show scatter plot, all figures are now scatter plots.

7. The authors show that effects of receptor overexpression are suppressed by loss of NLP-12 peptides. Is there precedent for this kind of genetic interaction in the literature?

We have noted several previous examples in the literature where the effects of receptor overexpression are suppressed by loss of the ligand. For example, exaggerated body bend posture produced FRPR-4 overexpression is suppressed by flp-13(lf) (Nelson et al., 2015). Similarly, hyperactive egg-laying produced by overexpression of the SER-1 serotonin receptor is suppressed by loss of serotonin (tph-1 mutation) (Fernandez et al., 2020).

8. Also, the authors, assert that suppression of effects of CKR-1 overexpression by loss of NLP-12 shows that NLP-12 peptides are the sole ligands for this receptor (page 9, line 17). It is not clear why the authors reach this conclusion.

We have modified the text to indicate NLP-12 is likely to be the major ligand responsible for CKR-1 activation. nlp-12 deletion suppresses the behavioral effects of ckr-1 overexpression, indicating that other endogenous peptides cannot effectively substitute for NLP-12 in eliciting the behavioral changes. This conclusion is further supported by our in vitro studies showing that NLP-12 peptides are the only peptides in the library that significantly activate CKR-1.

9. There are some very nice data that are assigned to supplementary figures but might be better placed in main figures. Figure S3A-B shows data that are integral to the authors' model and could be presented in a main figure. Also, the localization of NLP-12::Venus in DVA axons near SMD processes would be appropriate to show in a main figure. It would be ideal to mark SMDs with a red fluor so that NLP-12::Venus colocalization with SMD processes could be assessed.

As requested, we added images to main Figure 5 showing NLP-12::Venus localization in proximity to SMD processes in the nerve ring. For space and clarity, we felt that S3A-B (Figure S6A-B in revised manuscript) should remain supplemental.

10. The kymography data are nice but incomplete. The authors should show kymographs from strains of all relevant genotypes. This would include: (1) ckr-1(oe); nlp-12, (2) nlp-12, ckr-1, and ckr-2 single mutants, and (3) ckr-1; ckr-2 double mutants.

We have added additional kymographs as requested, and moved the kymographs into main figures. Kymographs of movement during ARS are now shown in Figure 3. Kymographs of movement elicited by overexpression are now shown in Figure 6.

11. Page 12, last paragraph indicates that 'low levels' of expression rescue ckr-1 phenotype – how has the expression level been determined? I guess that the authors refer to the amount of DNA used for transgenesis, not a direct measure of transgene expression – this should be reworded.

We have modified the text.

12. The manuscript would be strengthened by experiments that measured the effect of DVA activation on SMD physiology and what contribution NLP-12 signaling makes to any functional connection between these neurons. One potential impact of this work is that it establishes a nice paradigm for new molecular genetic analyses of neuropeptide signaling. Direct observation of the effects of NLP-12 peptides on SMD neuron physiology would further strengthen the authors' conclusions and suggest mechanisms by which CKR-1 regulates cell physiology.

We tried the experiment suggested by the reviewer. We stimulated DVA in hydrogel immobilized transgenic animals expressing DVA::Chrimson::SL2::BFP and SMD::GCaMP6s::SL2::mCherry, but were unable to detect clear SMD calcium transients that were timed with DVA stimulation. The failure to detect a synaptic response may be due to the immobilized preparation or may reflect limited synaptic connectivity between DVA and SMDs–a single synapse between DVA and SMDVL. We envision that NLP-12 activation of the SMDs occurs primarily through volume transmission which would act over a longer time scale and be quite difficult to measure with this approach. To address the reviewer’s comment, we also performed calcium imaging of SMD activity in behaving animals (Figure 7E-F) during ARS. We found that SMD activity is elevated in ARS compared with dispersal. Deletion of ckr-1 decreases SMD activity during ARS.

Reviewer #3:

In this manuscript, Ramachandran and colleagues describe how cholecystokinin-related NLP-12 neuropeptide signalling in C. elegans can regulate two different behavioural programmes, area-restricted search (ARS) and basal locomotion, by conditionally engaging different specific receptors that are expressed in different neuronal targets. They thoroughly characterise the CKR-1 receptor which had not been described previously, and place its function in context with that of the previously known NLP-12 receptor CKR-2. The manuscript gives new insight into an interesting and likely conserved mechanisms of how neuromodulatory systems enable adaptive behaviour by coordinating the action of neural circuits even when they are not directly connected. The conclusions drawn appear solid and are justified by the data presented, and the experimental approaches and results are well documented.

We thank the reviewer for their positive assessment.

The main problem with the work is a certain lack of clarity regarding the separation of the roles of the CKR-1 and CKR-2 receptors on basal locomotion/body bending and head bending/reorientations. Overexpression of NLP-12 places animals in a chronic ARS state, as described in a previous publication. Is the NLP-12 overexpression model representative of the increased reorientation in area restricted search, or of control of undulations in basal locomotion, or both? If it is primarily representative of area restricted search, this would mean that CKR-2, similarly to CKR-1, mediates the chronic ARS state induced by NLP-12 overexpression, because in Figure 1B and C its mutation causes a reduction in the phenotype, and deletion of both ckr-1 and ckr-2 causes a stronger reduction.

We used NLP-12 overexpression as a sensitive way to identify potential receptors. After implicating specific receptors through genetic suppression of peptide overexpression, we pursued behavioral studies of deletion mutants to assess specific contributions of CKR-1 versus CKR-2. NLP-12 overexpression produces behavioral effects that are qualitatively similar to ARS, but more severe. However, we are hesitant to assign further significance to interpretation of behaviors arising from peptide overexpression since they likely reflect high, non-physiological levels of NLP-12 peptides.

Also, it is unconvincing that SMD neurons do not express ckr-2 (see S3D); no comparison of ckr-1 and ckr-2 expression levels in SMD is provided and in fact the CeNGEN data of single cell RNAseq of C. elegans neurons shows similar expression of both receptors in SMDD (accessible at cengen.shinyapps.io/SCeNGEA). On the other hand, loss of ckr-2 on its own does not cause a significant reduction in ARS (Figure 3A).

To clarify this, the authors could measure the reorientation rate in the nlp-12OE ckr-2 mutant strain.

We apologize for not describing our findings more clearly. We noted weaker and more variable expression of ckr-2 in the SMD neurons. Variable ckr-2 expression was restricted to the SMDDs, and was not observed in the SMDVs. We noted more consistent expression of ckr-1 across both SMDDs and SMDVs. We have now clarified this in the revised manuscript. The CeNGEN data do not distinguish SMDV expression. To strengthen our conclusions, we attempted rescue of ckr-1(lf);ckr-2(lf) double mutants with wild type ckr-1 or ckr-2. We found that expression using the ckr-1, but not ckr-2, provided for rescue [Figure S5A]. Additionally, we show expression of wild type ckr-1 under control of ckr-1, but not ckr-2, promoter is sufficient for rescue of ckr-1(lf) mutants (Figure S5B). We also now show representative tracks for the nlp-12OE;ckr-1 and nlp-12OE;ckr-2 mutant strains (Figure 1A), demonstrating that turning remains elevated in these animals.

Given that ckr-1 overexpression as shown in Figures4-6 increases both body bending amplitude and ARS-like high reorientation rate, the authors offer the interesting possibility that SMD may also affect basal locomotion. I would suggest an experiment that clarifies whether SMD also controls body bending in basal locomotion using the single-worm tracking assay shown in Figure 2A with the SMD-specific ckr-1 rescue strains in a ckr-1 mutant background (as used in figure 7). Also they could measure body bending in the existing data on the SMD::Chrimson optogenetics.

To address this point, we measured body bending in response to SMD photostimulation and found that SMD depolarization leads to a modest increase in body bend amplitude [Figure S8E]. We also now include experiments showing that SMD silencing significantly reduces reorientations during ARS [Figure 7D].

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

The reviewers are very excited about your work and the improvements made in your revision. However, there are some remaining issues that need to be addressed. As outlined below, the concern of reviewers #1-2 with respect to SMD Ca++ imaging. We assume that this would not require new experiments but further in-depth analysis of the recordings, which should be all feasible in a short time frame.

Reviewer #1:

The authors have fully addressed my review comments to the previous submission.

In the present manuscript, the authors provide SMD Ca++ imaging experiment, which require further clarifications:

1) SMD activity in crawling worms has been reported previously by several labs, and all studies found consistently activity related to head-bending (Hendricks et al., 2012; Kaplan et al., 2020; Yeon et al., 2018). From the activity profiles shown in Figure 5, it is not possible to evaluate whether these data can be reproduced by the authors. If movie S9 is representative for these recordings, then SMD activity profiles should relate to head-bending. The fluctuations in Figure 5E rather appear as noise to me. I find it essential that the authors annotate behaviour in these recordings (forward crawling, backward crawling, head bending) and analyse the relationship between SMD activity and locomotion. If any discrepancies to the literature remain, this and possible explanations should be discussed.

We thank the reviewer for highlighting this point. We now show heat maps for all recordings and include behavioral annotations immediately below the heat map for each recording (Figure 8A-C). In addition, we now show that reorientation frequency is correlated with average GCaMP fluorescence intensity in the SMDs during local searching (Figure 8D). However, there was not a strong correlation between peak SMD fluorescence and episodes of forward or backward movement, or reorientations. This may be in part attributable to the way we performed our experiments. We measured combined fluorescence of SMDD and SMDV neurons that themselves have distinct patterns of activation. Notably, Kaplan et al. (2020) also found that SMDD and SMDV activity were not strictly correlated with either forward or reverse command states and instead varied according to locomotor state, consistent with our observations. Our work demonstrates that NLP-12 signaling through CKR-1 promotes a state of heightened SMD activity. Based on our observations, we propose that this state of elevated SMD activity is permissive for performing forward reorientations during ARS.

As noted by the reviewer, prior studies of worms immobilized using microfluidic chips (Hendricks 2012, Shen 2016) and freely moving animals (Yeon 2018, Kaplan 2020) have noted anti-phasic activity between SMDD and SMDV neurons and opposing head/neck musculature during head bending (or head casting). Our studies do not directly address this point. We monitored the combined fluorescence of SMD neurons over longer timescales at lower magnification, offering a view of the summed SMD neuronal activity during ARS and dispersal behaviors. The lower magnification used in our studies simplified measurements from animals freely moving over large areas but limited cellular resolution. Nonetheless, to address the reviewer’s question, we attempted to distinguish the fluorescence of SMDD and SMDV neurons in our recordings; however, we did not feel we could with confidence extract this information. We now include additional discussion of these points in the revised version of the manuscript.

2) Despite the concerns above, I find it surprising and interesting that the authors observe different perhaps baseline ratio values in 0-5min vs 30-35min off-food conditions. How this relates to the different behavioral phenotypes, incorporating our knowledge about SMD physiology remains to be discussed in more detail.

Hendricks, M., Ha, H., Maffey, N., and Zhang, Y. (2012). Compartmentalized calcium dynamics in a C. elegans interneuron encode head movement. Nature 487, 99-103.

Kaplan, H.S., Salazar Thula, O., Khoss, N., and Zimmer, M. (2020). Nested Neuronal Dynamics Orchestrate a Behavioral Hierarchy across Timescales. Neuron 105, 562-576.e569.

Yeon, J., Kim, J., Kim, D.-Y., Kim, H., Kim, J., Du, E.J., Kang, K., Lim, H.-H., Moon, D., and Kim, K. (2018). A sensory-motor neuron type mediates proprioceptive coordination of steering in C. elegans via two TRPC channels. PLoS biology 16, e2004929.

We now provide additional discussion of physiological regulation of SMD activity and how this is related to our findings. Prior studies have indicated the SMDs are cholinergic, and their stimulation is sufficient to produce ca2+ transients in head/neck muscles, consistent with proposed roles in head bending. However, physiological regulation of SMD activity is complex and involves reciprocal connections with RIA interneurons, reciprocal signaling with RME motor neurons, as well as proprioceptive feedback. In particular, inhibitory signaling from the GABAergic RME neurons onto the SMDs is implicated in modulation of head bending amplitude to optimize head bends for forward movement. While the precise role of NLP-12 modulation of SMD activity remains unclear, one intriguing possibility is that NLP12-elicited increases in SMD activity uncouple the SMDs from RME inhibitory regulation, perhaps promoting large amplitude head swings that couple to forward reorientations during searching.

Reviewer #2:

The revised manuscript of Ramachandran, Francis and colleagues addresses many of the questions raised during the initial round of review. I have only one comment. The authors include new data reporting SMD activity during area-restricted search and dispersal. This is an interesting experiment that shows clear evidence for CKR-1 in regulation of SMDs. It is not clear why the authors only show data from 3 individuals in panel E of Figure 7; panel F indicates that there are many more individuals that were assayed. I suggest that the authors show data from all the individuals in panel E.

We thank the reviewer for this suggestion. We now include heat maps for all individuals tested in our calcium imaging experiments (Figure 8A-C in revised manuscript).

https://doi.org/10.7554/eLife.71747.sa2

Article and author information

Author details

  1. Shankar Ramachandran

    Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing - original draft, Writing - review and editing
    Contributed equally with
    Navonil Banerjee and Raja Bhattacharya
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1299-4482
  2. Navonil Banerjee

    Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, United States
    Present address
    Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation
    Contributed equally with
    Shankar Ramachandran and Raja Bhattacharya
    Competing interests
    No competing interests declared
  3. Raja Bhattacharya

    Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, United States
    Present address
    Amity Institute of Biotechnology, Amity University Kolkata, West Bengal, India
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Methodology
    Contributed equally with
    Shankar Ramachandran and Navonil Banerjee
    Competing interests
    No competing interests declared
  4. Michele L Lemons

    Department of Biological and Physical Sciences, Assumption University, Worcester, United States
    Contribution
    Data curation, Resources
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8459-4130
  5. Jeremy Florman

    Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, United States
    Contribution
    Data curation, Formal analysis, Software
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7578-3511
  6. Christopher M Lambert

    Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, United States
    Contribution
    Resources
    Competing interests
    No competing interests declared
  7. Denis Touroutine

    Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, United States
    Contribution
    Resources
    Competing interests
    No competing interests declared
  8. Kellianne Alexander

    Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, United States
    Contribution
    Resources
    Competing interests
    No competing interests declared
  9. Liliane Schoofs

    Department of Biology, University of Leuven (KU Leuven), Leuven, Belgium
    Contribution
    Supervision
    Competing interests
    No competing interests declared
  10. Mark J Alkema

    Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, United States
    Contribution
    Resources
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1311-5179
  11. Isabel Beets

    Department of Biology, University of Leuven (KU Leuven), Leuven, Belgium
    Contribution
    Data curation, Formal analysis, Funding acquisition, Methodology
    Competing interests
    No competing interests declared
  12. Michael M Francis

    Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, United States
    Contribution
    Conceptualization, Funding acquisition, Project administration, Supervision, Writing - original draft, Writing - review and editing
    For correspondence
    michael.francis@umassmed.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8076-6668

Funding

National Institutes of Health (R21NS093492)

  • Michael M Francis

European Research Council (340318)

  • Isabel Beets

Research Foundation Flanders (G0C0618N)

  • Isabel Beets

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

The authors thank the Caenorhabditis Genetics Center, which is funded by the National Institutes of Health National Center for Research Resources, and the Mitani laboratory (National Bioresource Project) for providing Caenorhabditis elegans strains. The authors thank Mei Zhen lab for MATLAB script for calcium imaging analysis, Claire Bénard for strains, Michael Gorczyca and William Joyce for technical support. The author thank Francis lab members for helpful comments on the manuscript.

Senior Editor

  1. Ronald L Calabrese, Emory University, United States

Reviewing Editor

  1. Manuel Zimmer, University of Vienna, Austria

Publication history

  1. Preprint posted: April 28, 2020 (view preprint)
  2. Received: June 28, 2021
  3. Accepted: November 11, 2021
  4. Accepted Manuscript published: November 12, 2021 (version 1)
  5. Version of Record published: November 26, 2021 (version 2)

Copyright

© 2021, Ramachandran et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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