Neuropeptide signaling network of Caenorhabditis elegans: from structure to behavior

Abstract

Neuropeptides are abundant signaling molecules that control neuronal activity and behavior in all animals. Owing in part to its well-defined and compact nervous system, Caenorhabditis elegans has been one of the primary model organisms used to investigate how neuropeptide signaling networks are organized and how these neurochemicals regulate behavior. We here review recent work that has expanded our understanding of the neuropeptidergic signaling network in C. elegans by mapping the evolutionary conservation, the molecular expression, the receptor-ligand interactions, and the system-wide organization of neuropeptide pathways in the C. elegans nervous system. We also describe general insights into neuropeptidergic circuit motifs and the spatiotemporal range of peptidergic transmission that have emerged from in vivo studies on neuropeptide signaling. With efforts ongoing to chart peptide signaling networks in other organisms, the C. elegans neuropeptidergic connectome can serve as a prototype to further understand the organization and the signaling dynamics of these networks at organismal level.

Keywords: Caenorhabditis elegans; behavior; neuromodulation; neuropeptide signaling network; peptide GPCRs.

Fig. 1.

The neuropeptide network of the C. elegans nervous system forms a dense signaling network that structurally differs from synaptic and monoamine networks. a) Graphical and connection matrix representations of the signaling networks mediated by chemical synapses (left), monoamines (middle), and neuropeptides (right) in the C. elegans nervous system. Individual neurons in the graph representations are depicted as nodes that are connected by gray edges, indicating neuron-to-neuron interactions either through chemical synapses (left) or through neuromodulator to receptor pathways inferred from receptor–ligand pairing and gene expression data (middle and right). Neuronal nodes are colored based on their anatomical classification, and their size is defined by their relative degree (total sum of number of incoming and outgoing connections). The neuropeptide network is much denser and has a more decentralized topology, as there are many more high-degree neurons that are highly connected in comparison to the synaptic and monoamine networks. The monoamine network has only a limited number of sending neurons, while in the neuropeptide network nearly all neurons both send and receive peptide signals. Raw data from Varshney et al. (2011), Bentley et al. (2016), and Ripoll-Sánchez et al. (2023); visualized using Flourish Studios. b) t-SNE dimensionality reduction shows a mesoscale structure in the neuropeptide network, with neurons of the core network clustering into 3 groups that receive similar peptidergic input connections: One mainly containing sensory neurons, a second containing most of the peptidergic hub neurons, and a third containing many motor neurons. Figure adapted from Ripoll-Sánchez et al. (2023). c) Examples of 4 different topologies identified for individual peptide–receptor networks. Top left: Local network with only a few neurons expressing the neuropeptide capa-1 or its cognate receptor nmur-1. Top right: Pervasive network with many neurons expressing flp-18 and its receptor npr-5. Bottom left: Broadcasting network from a small number of neurons expressing the neuropeptide nlp-49 to many downstream putative partners expressing seb-3, a cognate receptor of NLP-49. Bottom right: Integrative network in which peptide signals from many neurons expressing flp-9 may converge onto a small number of neurons expressing the receptor egl-6. Figure adapted from Ripoll-Sánchez et al. (2023).

Fig. 2.

Hub neurons in the C. elegans neuropeptide signaling network. a) Synaptic and neuropeptide degrees, defined as the respective number of synaptic and peptidergic connections that are incoming and outgoing in each neuron, are positively correlated (r = 0.54, p = 3.1e⁻¹⁴). Synaptic hub neurons with very high synaptic degrees are also highly connected hubs in the neuropeptide network. By contrast, some neurons seem to be specialized peptidergic hubs (e.g. AVKL/R, PVQL/R, PVR, and PVT), as they are highly connected in the neuropeptide network but have relatively few synaptic connections (figure adapted from Ripoll-Sánchez et al. 2023). Dots represent neurons and color codes indicate the relative composition of neuron vesicles (small clear vesicles and DCVs) as determined on electron micrographs of the head's neuropil (data from Witvliet et al. 2021). Neurons that are highly connected in the peptide network tend to have a high prevalence of DCVs. b) Many C. elegans neurons that display a relative excess of DCVs over small clear vesicles extend long processes throughout the body. Anatomical model adapted from the Virtual Worm Project (Sternberg Lab, OpenWorm Project) and visualized with Blender (Blender Foundation).

Fig. 3.

Divergent and convergent signaling in neuropeptidergic circuits. a, b) The neuropeptide FLP-18 has pleiotropic functions, mediated by different receptors, target cells, and source neurons. a) FLP-18 released from AIY interneurons controls olfaction and foraging through its receptor NPR-4 in RIV and AVA neurons. It also regulates fat accumulation by acting on NPR-4 in the intestine and on NPR-5 in ciliated sensory neurons. FLP-18 signaling to NPR-5 in ASJ sensory neurons controls dauer formation. Figure adapted from Cohen et al. (2009). b) FLP-18 secreted from AVA and RIM interneurons regulates locomotion through the activation of multiple receptors on body wall muscles, on ASE sensory neurons, and on AVA. FLP-18 signaling from AVA also regulates feeding through the activation of NPR-5 in ADF sensory neurons. c) The ALA neuron plays a central role in the control of stress-induced sleep by the release of multiple quiescence-promoting neuropeptides such as FLP-13, FLP-24, NLP-8, and NLP-14. These neuropeptides induce distinct components of sleep-like behavior, such as locomotion quiescence, feeding quiescence, defecation quiescence, and a reduction of avoidance responses to aversive stimuli. d) The peptidergic hub neuron HSN controls a suite of temporally distinct egg-laying related behaviors by the release of multiple neuropeptides and monoamines. HSN receives diverse peptidergic inputs that modulate egg-laying according to physiological and environmental context, such as the BAG-secreted neuropeptides FLP-10 and FLP-17 that inhibit HSN in response to aversive cues, and tyramine and neuropeptide signals that feed back to inhibit egg-laying upon mechanical activation of the uv1 neuroendocrine cells during egg release. Serotonin (5-HT) and the neuropeptide NLP-3 coordinately initiate egg-laying upon local release onto the egg-laying machinery. Axonal release of the neuropeptides FLP-2, FLP-26, and FLP-28 is required for locomotory changes associated with egg-laying.

Fig. 4.

Antagonistic and synergistic interactions between neuromodulatory pathways. a) AVK and DVA hub neurons release antagonistic neuropeptides to regulate transitions between dispersal and local searching when C. elegans is removed from food. AVK-derived FLP-1 and release of NLP-12 from DVA antagonistically regulate dispersal and local search through a distributed network of receptor-expressing cells. b, c) FLP-1 signaling from AVK antagonizes the actions of other neuromodulators to regulate locomotion speed and pathogen avoidance behavior. b) Autocrine signaling of FLP-1 in AVK neurons reduces locomotion speed by inhibiting the release of the forward-accelerating neuropeptide NLP-10, which increases speed via its receptor NPR-35 on AIY and AVB premotor interneurons. c) Prolonged exposure to pathogenic bacteria increases FLP-1 release from AVK to promote pathogen avoidance. FLP-1 signaling evokes avoidance by antagonizing tyraminergic/octopaminergic signaling from RIM and RIC neurons, through activation of its receptor DMSR-7 in these cells. FLP-1 mediates pathogen avoidance also by acting on other, yet unidentified neurons, through NPR-6 and DMSR-7. d) Locomotion arousal from the quiescence period associated with molts (developmentally timed sleep) is promoted by a synergistic interaction between PDF-1 and FLP-2 neuropeptides. Enhanced secretion of PDF-1 and FLP-2 arouses locomotion and is regulated by reciprocal positive feedback between the PDF-1 and FLP-2 signaling pathways. This may occur in the ASI sensory neurons, which express both peptides along with the FLP-2 receptor FRPR-18, suggesting that FLP-2 secretion is additionally regulated by autocrine feedback. PDF-1 release from sensory neurons, including ASK, mediates locomotory arousal by acting on its receptor PDFR-1 in touch sensory neurons and body wall muscles.

Fig. 5.

Neuropeptidergic signaling cascades and autocrine feedback. a) Aversive mechanical stimuli elicit a state of arousal, characterized by locomotory arousal and cross-modal sensitization of the nociceptive ASH neurons. Both effects are mediated by a peptidergic signaling cascade that requires FLP-20 neuropeptide signaling from the touch receptor neurons to its receptor FRPR-3 on the RID interneuron, which in turn evokes arousal through the release of yet unknown neuropeptides. Mechanosensory-induced locomotory arousal is also stimulated by FRPR-3 on the AIY interneurons and by neuropeptides from other cells, such as NLP-49 released from AVK and acting on its receptor SEB-3. b) The response of AWC olfactory neurons upon odor removal is dampened by a peptidergic cascade. NLP-1 released from AWC binds to its receptor NPR-11 in AIA interneurons, triggering the release of the insulin-like peptide INS-1. The insulin signal acts back onto AWC through a yet unknown receptor to dampen AWC olfactory responses. c) Autocrine peptidergic feedback in the RIM interneurons is important for threat-reward decision making between aversive stimuli (high osmolarity) and attractive cues (food odors). Both autocrine PDF-2 signaling and tyramine release from RIM neurons decrease threat tolerance in well-fed C. elegans, while food deprivation increases threat tolerance through suppression of these neuromodulatory pathways. Figure adapted from Li et al. (2016). d) An activity-dependent autocrine insulin signal, INS-1, represses the expression of the BAG neuron fate and its function in CO₂ avoidance, by acting on its receptor DAF-2 and inhibiting expression of the flp-17 neuropeptide gene in BAG.