Skip to main content
Download PDF
  • Research article
  • Open access
  • Published:

Global analysis of neuropeptide receptor conservation across phylum Nematoda

BMC Biology volume 22, Article number: 223 (2024) Cite this article

Abstract

Background

The phylum Nematoda is incredibly diverse and includes many parasites of humans, livestock, and plants. Peptide-activated G protein-coupled receptors (GPCRs) are central to the regulation of physiology and numerous behaviors, and they represent appealing pharmacological targets for parasite control. Efforts are ongoing to characterize the functions and define the ligands of nematode GPCRs, with already most peptide GPCRs known or predicted in Caenorhabditis elegans. However, comparative analyses of peptide GPCR conservation between C. elegans and other nematode species are limited, and many nematode GPCRs remain orphan. A phylum-wide perspective on peptide GPCR profiles will benefit functional and applied studies of nematode peptide GPCRs.

Results

We constructed a pan-phylum resource of C. elegans peptide GPCR orthologs in 125 nematode species using a semi-automated pipeline for analysis of predicted proteome datasets. The peptide GPCR profile varies between nematode species of different phylogenetic clades and multiple C. elegans peptide GPCRs have orthologs across the phylum Nematoda. We identified peptide ligands for two highly conserved orphan receptors, NPR-9 and NPR-16, that belong to the bilaterian galanin/allatostatin A (Gal/AstA) and somatostatin/allatostatin C (SST/AstC) receptor families. The AstA-like NLP-1 peptides activate NPR-9 in cultured cells and are cognate ligands of this receptor in vivo. In addition, we discovered an AstC-type peptide, NLP-99, that activates the AstC-type receptor NPR-16. In our pan-phylum resource, the phylum-wide representation of NPR-9 and NPR-16 resembles that of their cognate ligands more than those of allatostatin-like peptides that do not activate these receptors.

Conclusions

The repertoire of C. elegans peptide GPCR orthologs varies across phylogenetic clades and several peptide GPCRs show broad conservation in the phylum Nematoda. Our work functionally characterizes the conserved receptors NPR-9 and NPR-16 as the respective GPCRs for the AstA-like NLP-1 peptides and the AstC-related peptide NLP-99. NLP-1 and NLP-99 are widely conserved in nematodes and their representation matches that of their receptor in most species. These findings demonstrate the conservation of a functional Gal/AstA and SST/AstC signaling system in nematodes. Our dataset of C. elegans peptide GPCR orthologs also lays a foundation for further functional studies of peptide GPCRs in the widely diverse nematode phylum.

Background

Bioactive peptides, including neuropeptides, are ancient and conserved signaling molecules that regulate physiology and brain functions in all animals [1,2,3,4]. Peptide messengers are usually cleaved enzymatically from larger preproproteins and mainly bind to G protein-coupled receptors (GPCRs) [1, 5, 6]. Among the five main GPCR classes (rhodopsin, secretin, adhesion, glutamate, and Frizzled type receptors), most peptide GPCRs belong to the rhodopsin and secretin families [1, 2, 7], and their activation elicits downstream signaling cascades that modulate cellular physiology in different tissues [8,9,10]. Peptidergic signaling has been implicated in a broad range of biological processes such as reproduction, development, growth, metabolism, and the regulation of behavior [11,12,13,14,15]. As their activity is crucial for animal survival, peptide GPCRs have become promising therapeutic targets for human diseases [16,17,18]. Indeed, GPCRs comprise one of the most successful classes of drug targets in humans, representing > 34% of the targets for prescribed drugs [16,17,18].

The nematode phylum comprises a rich diversity of species, including both parasitic and free-living roundworms that inhabit a broad range of environments [19, 20]. Different nematode parasites can infect humans, livestock, and crops, and thus have a significant impact on human health and agricultural productivity [21,22,23]. Increasing resistance to anthelmintic drugs drives the need for identifying new targets for the development of anthelmintics [24,25,26]. Peptide GPCRs are considered among the most druggable candidates and represent attractive, potential novel anthelmintic targets [27]. These include antagonistic drug targets, such as those associated with lethality in reverse genetic studies [19]. In addition, nematode peptide GPCRs represent attractive agonistic drug targets based on the established impact of neuropeptides on nematode parasite muscle and nerve tissues, and the detrimental phenotypes (e.g. paralysis) observed following peptide injections [19, 28, 29].

To date, most nematode peptide GPCRs have been functionally characterized in the model organism Caenorhabditis elegans [7, 30]. Out of more than 1600 GPCRs encoded in the genome of C. elegans, approximately 160 are peptide GPCR candidates [31], of which 60 peptide-activated GPCRs have known ligands [7]. These receptors subdivide into distinct classes based on their type of ligand interaction, ranging from specific receptors that interact with one type of peptides to promiscuous receptors that bind many peptides from different peptide precursors [7]. Many C. elegans receptors are orthologous to peptide GPCRs in other animals [1, 7, 32,33,34,35]. These include orthologs of peptidergic systems that are conserved across bilaterian animals, such as oxytocin/vasopressin and neuropeptide Y signaling, as well as peptide GPCRs belonging to protostomian receptor families [7, 36, 37]. Some of these families expanded in nematodes, while other C. elegans peptide GPCRs do not appear to belong to a known family and may represent nematode-specific receptor groups [7].

Comparative analyses have revealed strong conservation of peptide GPCRs between C. elegans and other nematode species [7, 19, 38]. However, these comparisons are restricted to a small subset of GPCRs or a limited cohort of therapeutically and phylogenetically relevant species, leaving a gap in our understanding of the peptide GPCR repertoire across the phylum Nematoda. Many putative peptide receptors in nematode parasites and free-living species, including C. elegans, also remain orphan or uncharacterized [7]. Thanks to the increasing number of available nematode omics datasets [39], peptide GPCR orthologs can be identified across the phylum in species that are phylogenetically distinct and representative of different lifestyles. Such pan-phylum analyses may reveal nematode-conserved peptide GPCR families, facilitate the identification of receptor ligands, and help prioritize candidates for functional studies in nematode parasites and free-living models.

Here, we investigate the conservation of peptide GPCR sequences in 125 nematode species by building a semi-automated pipeline for predicted proteome analysis. We use this in silico resource to determine patterns in the peptide GPCR repertoire of different species and define receptors that are widely conserved in nematodes as these may play crucial roles in regulating nematode physiology. We identify peptide ligands for two conserved orphan receptors, NPR-9 and NPR-16, and show that these ligand-receptor interactions broadly match our comparative analyses of peptide and GPCR conservation. Our work identifies a functional galanin/allatostatin A and somatostatin/allatostatin C-related signaling system in C. elegans and reveals broad conservation of these ancestral peptidergic systems in nematodes.

Results

Pan-phylum analysis of peptide GPCR conservation in nematodes

Comparative sequence analyses for all known and predicted (neuro)peptide GPCRs (NP-GPCRs) of C. elegans identified homologs in 37 nematode species [7, 19]. To investigate the complete repertoire of NP-GPCRs across the phylum Nematoda, we constructed an in silico pipeline to mine predicted proteome datasets of 125 nematode species (Fig. 1). We first upscaled a bioinformatics pipeline for the identification and phylogenetics of nematode NP-GPCRs based on Hidden Markov Models (HMM) derived from multiple sequence alignments [19, 40]. To identify putative NP-GPCR sequences in nematodes, we collected the protein sequences of 161 known and predicted C. elegans NP-GPCRs [7, 19] (Additional file 1: Table S1) and used them as entry queries to search for homologs in 152 predicted proteome datasets from 125 nematode species (Additional file 2: Table S1 [41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110]). All predicted proteomes, irrespective of genome annotation quality, were included (BUSCO scores available in Additional file 2: Table S1). Datasets were available for species belonging to 22 superfamilies (Fig. 2), including fresh water, marine, and terrestrial species [39]. These include all species present in the WormBase ParaSite database (Version 16.0) [39], which span 7 out of 12 phylogenetically dispersed nematode clades (Fig. 2) [111, 112]. Nematode species were classified as either free-living or parasitic, with the latter further subdivided into animal, plant, or insect (entomopathogenic) parasites (Fig. 2) [19, 39]. The initial HMM search yielded 17,345 sequences, which were filtered to remove sequences with < 4 transmembrane domains, the minimum number of predicted transmembrane domains in the C. elegans NP-GPCR dataset. This resulted in 15,929 putative C. elegans NP-GPCR homologs from the predicted protein datasets of 125 nematode species (Fig. 1).

Fig. 1
figure 1

In silico pipeline for identifying C. elegans NP-GPCR orthologs in the nematode phylum. A resource of 161 known and predicted C. elegans NP-GPCRs was used to search for homologs in predicted proteomes of 125 nematode species using a Hidden Markov Model (hhmbuild, hmmsearch and hmmtop), yielding 15,929 protein sequences. The predicted NP-GPCRs were used in clustering and phylogenetic analyses to identify orthologs of C. elegans NP-GPCR candidates. Orphan NP-GPCR candidates of C. elegans that show broad conservation in the nematode phylum (C50H11.13, F13H6.5, F59D12.1, FRPR-5, NPR-9, NPR-16, and NPR-19) are prioritized for functional studies. MSA, Multiple Sequence Alignment; TM, TransMembrane; CLANS, CLuster ANalysis of Sequences

Full size image
Fig. 2
figure 2

Cladogram of nematode species used in this study. To construct a pan-phylum resource of putative nematode NP-GPCRs, we used predicted proteomes of 125 nematode species, covering 7 out of 12 nematode clades (2, 6, 8, 9, 10, 11, 12 according to Holterman et al. [38]). Clade 9 is the most represented clade with 50 species, whereas for clades 6 and 11 only one species was found for which a predicted protein dataset was available. Boxed numbers indicate superfamilies within each clade [19, 20, 111]. Nematode lifestyles are classified as animal parasitic, entomopathogenic, plant parasitic, and free-living and indicated by colored dots. Outer skyline shows the overall percentage of C. elegans NP-GPCRs with orthologs found in a given species. Full names of species, historical clade distribution according to Blaxter et al. [112], % values of C. elegans orthologs, and genome quality scores (BUSCO) can be found in Additional file 2: Table S2

Full size image

Representation of NP-GPCR families in nematodes

To gain insight into the representation of NP-GPCR families in our pan-phylum dataset, we first clustered the identified homologs using a linkage clustering algorithm based on sequence similarity [113]. We obtained 39 clusters, 24 of which included known or predicted C. elegans NP-GPCRs from one or multiple peptide receptor families (Fig. 3, C. elegans NP-GPCRs and receptor families for each cluster can be found in Additional file 3: Table S1). Species distribution within each cluster follows their predicted evolutionary distance; clades 9 and 10 were represented in most of the 39 identified clusters (respectively in 35 and 33 clusters), whereas we could identify species of clade 2 only in 21 clusters (Additional file 4: Fig. S1). To further determine the conservation of NP-GPCR families and identify orthologs of C. elegans NP-GPCRs in other nematodes, we used the output sequences of each cluster with C. elegans representatives and constructed phylogenetic trees employing a maximum likelihood algorithm [114, 115]. We then annotated each tree and transformed the output into a binary table indicating the absence or presence of orthologs for each C. elegans NP-GPCR in our dataset (Additional file 3: Table S1). We found orthologs for every NP-GPCR family reported in C. elegans, even outside the order Rhabditida [7, 19]. Regardless of substantial family-level conservation, not every C. elegans NP-GPCR is represented in another nematode species (Additional file 3: Table S1). For example, some members of the myosuppressin-like receptor family, such as DMSR-2 and DMSR-8, have orthologs in over 70% of the species, whereas other DMSRs are found in only a few species (e.g., DMSR-15 in 10 Caenorhabditis species), or are only present in the C. elegans proteome and not in other nematodes (e.g., DMSR-9 to -14, and DMSR-16).

Fig. 3
figure 3

Clustering of 15,929 putative C. elegans NP-GPCR homologs based on sequence similarity. Each dot represents a nematode sequence; edges between dots represent BLAST connections with P value > 1e − 30. Only clusters with more than 5 sequences are color-coded according to the number (zero, one, or multiple) of C. elegans NP-GPCR families represented in each cluster. See also Additional files 3 and 5 for an overview of C. elegans NP-GPCRs and homologs in each cluster

Full size image

Our clustering analysis also identified 15 clusters that do not include C. elegans receptors (clusters #25–39 in Fig. 3). These clusters comprise multiple sequences from phylogenetically distinct nematode species (Additional file 5: Table S1 and Additional file 6), suggesting that they may represent putative NP-GPCR families which have not yet been annotated or have been lost in C. elegans. Several clusters contain putative NP-GPCRs derived from nematodes spanning clades 8 to 12 (clusters #25, #26, #27, #35, #36, #37), whereas others have sequences from species that are restricted to a limited number of clades (e.g., cluster #30 includes species from clades 2 and 6). To reveal whether some of these clusters might have unannotated representatives in C. elegans, we performed a BLAST search using their sequences as queries against the C. elegans proteome (Bioproject reference Additional file 2: Table S1) [116]. For 5 out of 15 clusters, this yielded multiple unannotated C. elegans proteins with sequence similarity to the query receptor sequences (Additional file 5: Table S2). Among them, five C. elegans sequences are predicted with high fidelity as rhodopsin class A receptors by InterPro-based protein family prediction (Additional file 5: Table S2) [117]. These C. elegans sequences may represent putative, unannotated, NP-GPCRs based on their sequence similarity to NP-GPCR homologs in other nematodes. Only nematode species were returned as output when a BLAST search was performed against the entire NCBI databank, giving confidence for these newly identified clusters to be nematode-specific.

Nematode NP-GPCR profiles vary between phylogenetic clades and lifestyles

Previous work analyzed the predicted protein datasets of 10 nematode species to reveal broad conservation of C. elegans NP-GPCR orthologs in species from clades 9 and 10 [19]. Conversely, the lowest number of NP-GPCR orthologs was found in clade 2 species, representing the most basal clade in the phylum Nematoda [7, 19]. To evaluate whether these patterns remain consistent across 125 nematode species, we calculated the percentage of orthologs for every C. elegans NP-GPCR family in each species and averaged this value per clade (Fig. 4a). As expected, species in clades 9 and 10 display the highest complement of C. elegans NP-GPCR orthologs (Fig. 4a and b), regardless of differences in lifestyle or genome annotation quality (Additional file 4: Fig. S2). Species in clade 2 display the most reduced NP-GPCR complement in comparison to C. elegans, irrespective of BUSCO scores (Fig. 4a and b, and Additional file 4: Fig. S2 and S3). This could reflect their distant evolutionary relationship to C. elegans (Fig. 2) as well as the predominance of animals with a parasitic lifestyle in this clade, which generally show a reduced NP-GPCR repertoire compared to C. elegans (Fig. 4c) [7, 19].

Fig. 4
figure 4

The complement of C. elegans NP-GPCR orthologs varies for different nematode clades and lifestyles. a Heatmap representing the percentage of orthologs for each C. elegans NP-GPCR family in a given species, averaged per clade. See also Additional file 3: Table S1 for corresponding cluster numbers, and for names and C. elegans representatives of NP-GPCR families. b Percentage of C. elegans NP-GPCR orthologs identified in each species per clade. c Percentage of C. elegans NP-GPCRs orthologs in animal parasitic nematodes (APN) is lower than in entomopathogenic (EPN), plant pathogenic (PPN), and free-living (FLN) nematodes. Horizontal red lines in b and c represent the mean value. Intensity of data points in these two panels refers to BUSCO scores (genome quality) of each species (see Additional file 2: Table S2). d Percentage of nematode species with orthologs of C. elegans NP-GPCRs having specific (one-to-one) or more promiscuous (one-to-multiple, multiple-to-multiple) ligand interactions. Mean values are displayed as black vertical lines. See Additional file 7: Table S1 for classification of receptors according to their ligand interaction profile. Gray circles represent individual C. elegans GPCRs, and red circles highlight the three most promiscuous ones (DMSR-1, DMSR-7, FRPR-8). Individual values are available in Additional file 3: Table S1

Full size image

Since nematodes can be free-living or parasitic, we compared the NP-GPCR complement between species with different lifestyles. Animal parasitic nematodes show a lower percentage of C. elegans NP-GPCR orthologs in comparison to free-living species (Fig. 4c). However, most free-living species in our dataset belong to the same clade as C. elegans (Fig. 2). In accordance with previous work [19], nematode species closely related to C. elegans, or with a similar lifestyle, show the highest complement of C. elegans NP-GPCR orthologs, whereas fewer orthologs are found in species from more distantly related clades that often have parasitic lifestyles (Fig. 2, Fig. 4b and c). This observation is unlikely biased by overrepresentation of certain clades or lifestyles, as we observed a similar trend when retaining only one representative per genus and removing species with low quality of genome annotation (Additional file 4: Fig. S2).

Finally, we examined the conservation of C. elegans NP-GPCRs based on the arrangement of their putative ligand interactions. In a large-scale reverse pharmacology screen, we found that C. elegans NP-GPCRs and their ligands subdivide into three groups based on whether they have one-to-one, one-to-many, or many-to-many ligand-receptor interactions [7]. Receptors interacting with peptides from one peptide-encoding gene have orthologs in 10% more nematode species than GPCRs with more promiscuous interactions (Fig. 4d, Additional file 4: Fig. S2. Classification of receptor binding profiles is available in Additional file 7: Table S1). However, even highly promiscuous receptors, such as DMSR-1, DMSR-7, and FRPR-8, have orthologs in > 50% of the species in our dataset (Fig. 4d, Additional file 4: Fig. S2). Therefore, receptors with specific and promiscuous interactions appear to be similarly conserved across nematodes.

Identification of NP-GPCRs with pan-phylum proteome representation in nematodes

While all C. elegans NP-GPCR families have orthologs in other nematodes, this is not necessarily the case when looking at individual C. elegans NP-GPCRs. For 13 of the 161 C. elegans NP-GPCRs in our dataset, no orthologous sequences were identified in the predicted proteome of any other nematode species (Additional file 3: Table S2). These include several members of the myosuppressin (DMSR-9 to DMSR-14, DMSR-16) and RFamide (FRPR-11, FRPR-12) receptor families that expanded in C. elegans [7]. Thirteen additional C. elegans receptors (AEXR-2, C04C3.6, DMSR-15, F56A12.2, FRPR-4, FRPR-6, FRPR-13, FRPR-16, SRSX-24, SRSX-25, SRSX-35, T21H3.5, ZK863.1) appear to be conserved only in Caenorhabditis species (Additional file 3: Table S2). The majority of C. elegans NP-GPCRs, however, have orthologs in phylogenetically diverse nematodes. Among the 20% most broadly conserved C. elegans NP-GPCRs, which corresponds to 32 receptors in our dataset, 22 NP-GPCRs have orthologs in at least every clade (with the exception of clades 6 and 11 that are represented by only one species). These include nine receptors related to bilaterian-conserved NP-GPCR families (FSHR-1, GNRR-1, NPR-9, NPR-16, NPR-22, PDFR-1, SEB-3, SPRR-1, TRHR-1), seven receptors related to protostomian NP-GPCR families (DMSR-2, DMSR-8, FRPR-5, FRPR-7, FPRP-9, FRPR-19, NPR-5), and six receptors belonging to nematode-specific NP-GPCR families (C50H11.13, F13H6.5, F59D12.1, NPR-19, NPR-30, NPR-42) (Fig. 5a, and Additional file 3: Table S2). Because of their broad conservation, it is conceivable that these receptors have important biological functions in nematodes.

Fig. 5
figure 5

C. elegans NP-GPCRs with pan-phylum representation in nematodes. a Among the top 20% of the conserved C. elegans NP-GPCRs that have at least one ortholog in most species, seven (NPR-9, FRPR-5, NPR-16, C50H11.13, F13H6.5, F59D12.1, and NPR-19) are still orphan receptors. b Amino acid sequence alignment of AstA/buccalin-like peptides. Amino acids highlighted in green are conserved in all peptide sequences; amino acids in red match the C-terminal sequence motif [F/Y]XXG[L/I/V]G, characteristic of the AstA/buccalin peptide family [1]. Amino acids highlighted in gray are buccalin-specific. c Amino acid sequence alignment of AstC/somatostatin-like peptides. Amino acids in green are identical in all peptides; amino acids in orange are conserved in 60% of all peptide sequences. Aplysia californica (Aca), Acyrthosiphon pisum (Api), Caenorhabditis elegans (Cel), Crassostrea gigas (Cgi), Capitella teleta (Cte), Drosophila melanogaster (Dme), Daphnia pulex (Dpu), Helobdella robusta (Hro), Lottia gigantea (Lgi), and Tribolium castaneum (Tca)

Full size image

Discovery of galanin/allatostatin A and somatostatin/allatostatin C signaling systems in nematodes

Despite sizeable efforts, the functions of many broadly conserved NP-GPCRs remain elusive, in part because their ligand(s) have not yet been characterized. Among the 22 NP-GPCRs that we found to be widely conserved in nematodes, 15 NP-GPCRs have known peptide ligands, whereas the ligands of seven remain unknown (Fig. 5a) [7]. To identify their putative ligands, we aimed to predict possible ligand interactions based on phylogenetic relationships of the orphan GPCRs. Indeed, phylogenetic analyses have proven to be effective in predicting ligands of NP-GPCRs that are conserved in widely divergent animal phyla [1, 3, 7]. Two orphan receptors that are broadly conserved in nematodes, NPR-9 and NPR-16, are related to bilaterian NP-GPCR families. NPR-9 is orthologous to the protostomian allatostatin A (AstA) and vertebrate galanin receptors, while NPR-16 is related to the protostomian allatostatin C (AstC) and vertebrate somatostatin (SST) receptors [1, 3, 7]. A third receptor, FRPR-5, belongs to the family of FMRFamide-like NP-GPCRs that expanded in nematodes [1, 3, 7]. The remaining four orphan receptors (C50H11.13, F13H6.5, F59D12.1, and NPR-19) do not appear to have obvious orthologs outside the phylum Nematoda [7]. Therefore, based on their relatedness to widely conserved NP-GPCR families, we focused on identifying ligands for NPR-9, NPR-16, and FRPR-5.

Caenorhabditis elegans has three genes encoding neuropeptides orthologous to insect AstA and the related buccalin peptides in mollusks [1, 118, 119]. These include C. elegans NLP-1, NLP-5, and NLP-6 peptides, which have a carboxyterminal sequence that resembles the terminal sequence motif of the AstA/buccalin family (Fig. 5b). In addition, several SST/AstC-like peptide precursors have been identified in C. elegans, including NLP-55, NLP-62, NLP-64, NLP-66, NLP-67, NLP-71, NLP-79, NLP-88, NLP-89, NLP-90, and NLP-91 [1, 20, 120]. Through BLAST searches and sequence comparisons, we identified two additional AstC-like peptide precursors in the C. elegans genome, encoded by the genes nlp-99 (previously identified in Steinernema carpocapsae [121]) and nlp-119. Like vertebrate SST and protostomian AstC peptides, C. elegans AstC-type peptides contain two cysteine residues that form a disulfide bridge (Fig. 5c). Furthermore, most of them have the sequence motif F-X-P (in which X is variable) in common with arthropod AstC-type peptides (Fig. 5c) [1, 120].

Based on these phylogenetic relationships, we hypothesized that NPR-9 might be activated by NLP-1, NLP-5 and/or NLP-6 peptides, whereas NPR-16 might be a cognate receptor for one or multiple of the 13 AstC-like peptides. FRPR-5, a member of the RFamide receptor family, most likely binds peptides of the RFamide (FLP) family, which encompasses 31 flp genes in C. elegans [122,123,124]. To test these hypotheses, we expressed C. elegans NPR-9, NPR-16, and FRPR-5 using a heterologous expression approach in Chinese hamster ovary (CHO) cells. We then used a cell-based calcium mobilization assay to measure receptor activation in response to their predicted ligands (Fig. 6a) [7, 125, 126]. The NPR-9 receptor was specifically activated by NLP-1 peptides of the AstA/buccalin-like peptide family (Fig. 6b). Three peptides derived from the NLP-1 precursor (NLP-1–1 to NLP-1–3) activate NPR-9 in a concentration-dependent manner with EC50 values ranging between 240 and 610 nM (Fig. 6b). A fourth peptide, NLP-1–4, differs from the other NLP-1 peptides in its C-terminal sequence (Fig. 5b) and is much less potent in activating NPR-9 (Additional file 4: Fig. S4a). None of the other AstA/buccalin-like peptides, derived from NLP-5 and NLP-6 precursors, activated NPR-9 in a concentration-dependent manner (Additional file 4: Fig. S4b and S4c). An increased calcium signal was recorded only at the highest concentration for NLP-6–3 and NLP-6–4 (10 µM), but not at any other lower concentration (Additional file 4: Fig. S4c). For NPR-16, we found that two receptor isoforms encoded by the npr-16 gene are activated by the AstC-like peptide NLP-99, with EC50 values of 65 and 89 nM (Fig. 6c). Two other AstC-type peptides, NLP-88–3 and NLP-119–1, evoked calcium responses in receptor-transfected cells but only when tested at 10 µM, which is likely above relevant physiological concentrations (Additional file 4: Fig. S4d and S4e). NPR-9 and NPR-16 were not activated by any peptide other than NLP-1 or NLP-99 in a synthetic library of 344 C. elegans peptides [7]. NLP-1 and NLP-99 peptides also did not induce calcium responses in CHO cells transfected with an empty control vector (Additional file 4: Fig. S4f). Together, these results show that NLP-1 is a cognate ligand of NPR-9, and NLP-99 is the cognate ligand of NPR-16, as predicted by phylogenetic analyses. We did not observe activation of FRPR-5 with any C. elegans RFamide peptide or with any other peptide in our C. elegans peptide library. This may be because this receptor is not functionally expressed in CHO cells, or is activated by another, unidentified, peptide not included in the library.

Fig. 6
figure 6

Deorphanization of C. elegans Gal/AstA-type and SST/AstC-type receptors. a Cell-based reverse pharmacology approach for receptor deorphanization. Each receptor is transiently expressed in CHO cells together with the promiscuous Gα16 protein, which couples to many GPCRs and directs intracellular signaling to phospholipase Cβ (PLCβ) activity [36, 125, 126, 135]. This results in the release of calcium from intracellular storage sites, eliciting a luminescent signal from the calcium indicator aequorin. b NPR-9 is activated by three peptides encoded by the nlp-1 gene (NLP-1–1 = MDANAFRMSFamide, NLP-1–2 = MDPNAFRMSFamide, NLP-1–3 = VNLDPNAFRMSFamide) with similar potencies. EC50 for NLP-1–1 = 243.6 nM (logEC50 (M) = − 6.613, with 95% confidence interval (CI) = − 6.709 to − 6.519), for NLP-1–2 = 618.0 nM (logEC50 (M) = − 6.209, with 95% CI = − 6.266 to − 6.153), and for NLP-1–3 = 475.0 nM (logEC50 (M) = − 6.319, with 95% CI = − 6.383 to − 6.256). c Both receptor isoforms of NPR-16 are activated by the AstC-like peptide NLP-99 (GDGYGWNDCEFSPLSCLL, disulfide bridge C9-C16). EC50 for isoform a = 89.9 nM (logEC50 (M) = − 7.046, with 95% CI = − 7.113 to -6.979), and for isoform b = 65.4 nM (logEC50 (M) = − 7.184, with 95% CI = − 7.244 to − 7.125). b, c concentration-dependent activation curves are plotted as percentage of the highest peptide-evoked response (100% activation) using a nonlinear regression model. Error bars indicate Standard Error of Mean (SEM) with n ≥ 6. d Evolutionary conservation of the Gal/AstA-like receptor NPR-9 and the SST/AstC-like receptors NPR-16, NPR-24, and NPR-32, with peptides belonging to the same family. Black bars represent the number of species with mismatches in precursor-receptor conservation, meaning either only the peptide or the receptor is found. Gray and white bars indicate the number of species in which both peptide and receptor orthologs have been identified (gray), or in which none of the two were found (white). Confirmed peptide ligands of receptors are indicated in red and rank among the best scoring peptide precursors (with the lowest number of mismatches between peptide and receptor representation in nematode predicted proteomes). e Schematic representation of local search behavior assay. f Both nlp-1 and npr-9 mutants show increased turning behavior compared to wild-type animals upon removal from food. Double mutants of nlp-1 and npr-9 do not significantly differ in turning compared to the single mutants. Data are presented as mean + / − SEM including n > 6 assays with 10–15 animals tested for each strain per replicate. Statistical significance between different conditions was calculated using one-way ANOVA with Dunnett multiple comparisons test correction. * p < 0.05, ** p < 0.01. Individual data available in Additional file 9: Tables S1-S4

Full size image

Because receptors often co-evolve with their ligand(s), it is conceivable that the presence or absence of a given receptor matches that of its ligand more frequently than a peptide and receptor that do not form an interacting pair. We assessed this for NPR-9 and NPR-16 by first determining the complement of C. elegans AstA- and AstC-type peptides in all 125 nematode species in our resource (Additional file 8: Table S1 and S2). We then compared the conservation of each peptide precursor with that of NPR-9 and NPR-16 across all species. For each precursor-receptor combination, we determined the number of species in which the presence or absence of the receptor matches that of the peptide precursor, along with the number of species where only one of the two was present. For NPR-9 and NPR-16, we observed that the best-scoring peptide precursors (having the lowest discrepancy between the phylogenetic profiles of precursor and receptor) encoded peptides that we identified as receptor ligands in our in vitro assay (Fig. 6d). We performed a similar analysis for two AstC-type GPCRs that were deorphanized previously, NPR-24 and NPR-32 [7], and found that the representation of these receptors in nematode predicted protein datasets resembled that of their interacting ligands more than those of AstC-type peptides that do not activate these receptors. For NPR-24, the cognate ligand (NLP-62) shows the lowest number of mismatches in ligand-receptor representation among all SST/AstC-like peptide precursors, while the ligand of NPR-32 (NLP-64) ranks at the third position (Fig. 6d); the two peptides preceding NLP-64 (NLP-55 and NLP-71) still lack a cognate receptor. These findings suggest that phylum-wide studies of peptide and receptor conservation may help to identify putative ligands for orphan receptors.

Functional validation of NLP-1/NPR-9 interaction in vivo

Finally, to provide further evidence for the identified ligand-receptor pairs, we validated interactions in vivo. To date, there are no known phenotypes associated with NLP-99 or NPR-16 signaling. Therefore, we focused on NLP-1, for which several functions associated with C. elegans locomotion have been reported, including a role in local search behavior [118, 127]. This behavior is characterized by an increase in omega turns when worms are removed from food and is regulated by NLP-1 [118, 128]. To test whether NPR-9 is involved in local search behavior, we generated a deletion allele for npr-9 using CRISPR/Cas9 and measured C. elegans’ locomotion responses shortly (5 min) after removal from a food source (Fig. 6e). As expected, wild-type worms temporarily increase their turning behavior to generate an undirected local search, and nlp-1 mutants show increased turning behavior in comparison to wild-type animals (Fig. 6f). Likewise, null mutants of npr-9 display an increased turning (Fig. 6f). Local search behavior of nlp-1 npr-9 double mutants did not significantly differ from that of the single mutants, indicating that nlp-1 and npr-9 are involved in the same signaling pathway (Fig. 6f). Collectively, our results show that NLP-1 acts as cognate ligand of NPR-9 both in vitro and in vivo.

Discussion

The phylum Nematoda is species-rich and genetically diverse [129]. However, insight into the complement of NP-GPCRs, a class of receptors with promising pharmacological potential, across the phylum is limited [7, 19, 38]. Here, we provide a semi-automated bioinformatics pipeline to generate a pan-phylum resource of nematode NP-GPCR candidates from the predicted protein datasets of 125 nematode species. These data provide insight into the evolutionary conservation of nematode NP-GPCRs and lay a foundation for functional and pharmacological studies of putative peptide GPCRs in diverse nematode species.

We find that C. elegans NP-GPCRs are conserved broadly across the nematode phylum. Overall, we identified fewer NP-GPCR orthologs in those nematode species that are more distantly related to C. elegans, especially in the most basal clade 2. This observation is in accordance with previous studies comparing NP-GPCR sequences in a smaller set of 10 and 34 species [7, 19], or examining a reduced subset of receptors across the phylum [38]. We find a higher percentage of C. elegans NP-GPCR orthologs in free-living species compared to most parasitic nematodes, suggesting that the NP-GPCR signaling network may have undergone adaptive changes in nematode parasites compared to C. elegans. However, this finding is inconclusive because lifestyle is largely nested with clade in our dataset. Both specific and promiscuous NP-GPCRs have orthologs in over half of the species included in this resource, suggesting that different types of receptors are evolutionarily well conserved. Whether the ligand interactions of these receptors are conserved between C. elegans and other nematodes remains to be determined.

Our results show that at the family level, every NP-GPCR family defined in C. elegans has at least one ortholog that is conserved in other nematode clades. This broad conservation is, however, not generally true for each individual member of a receptor family. Such patterns reflect gene multiplications and losses throughout history [130,131,132]. For example, myosuppressin-like GPCRs are present in all clades, with some members highly conserved among nematodes, but several others represented in only a few or single Caenorhabditis species. One explanation might be that NP-GPCR families, like the DMSR family, expanded throughout nematode evolution [1, 7]. This is corroborated by the reduced complement of NP-GPCRs found in species from clade 2, the most basal nematode clade [19, 38, 111]. While receptors identified in only one or a few closely related species may have evolved more recently, it cannot be ruled out that these genes might represent pseudogenes in C. elegans, or that orthologs in other nematodes were not identified by our pipeline. To construct our resource, we exploited WormBase ParaSite predicted proteome datasets, some of which are constructed from manually curated genomes. Consequently, our approach may have overlooked NP-GPCR candidates not (yet) included in predicted proteome data. Validation of the accuracy of NP-GPCR profiles derived from predicted protein datasets requires a high level of manual curation, such as through tBLASTn approaches, which represents a bottleneck for more comprehensive NP-GPCR analyses. From a practical perspective, our semi-automated pipeline can be readily deployed to update nematode NP-GPCR profiles when additional and/or more complete predicted proteomes become available.

We used a comprehensive dataset of known and predicted C. elegans NP-GPCR sequences to identify orthologs in other nematode species, as available NP-GPCR functional data have mostly been derived from this model organism [7]. One limitation of this approach may be that our pan-phylum dataset does not include NP-GPCR candidates which are present in other nematodes but not conserved in C. elegans. However, through our analyses, we identified several protein sequence clusters from phylogenetically diverse nematode species, which did not include any representatives of known C. elegans NP-GPCR families. Protein sequences in some of these clusters show sequence similarity to C. elegans proteins, including several predicted rhodopsin class A GPCRs. These clusters may represent additional novel families of putative NP-GPCRs, which have not yet been annotated as peptide GPCR candidates in nematodes. As none of the GPCRs in these clusters have been deorphanized, we cannot rule out the possibility that they exert different functions or interact with ligands other than peptides.

We focused functional characterization of NP-GPCR candidates on receptors that are most highly conserved across the phylum Nematoda, based on the rationale that these broadly conserved GPCRs likely have crucial roles in regulating nematode physiology and may represent attractive targets for broad spectrum nematode parasite control [19]. Indeed, several of these highly conserved NP-GPCRs have been shown to regulate central aspects of physiology and behavior in C. elegans [133]. For example, mutants of trhr-1 and fshr-1, orthologs of vertebrate thyrotropin-releasing hormone and glycoprotein hormone receptors, are defective in growth [134, 135]. PDFR-1 activity was shown to be involved in mating behavior, the receptor NPR-22 regulates feeding and reproductive behavior, and SEB-3 has been linked to locomotory arousal in C. elegans [33, 136,137,138]. Interestingly, many of these receptors belong to NP-GPCR families that are ancestral to bilaterian animals, which might have evolved under higher evolutionary pressure across the phylum.

In this study, we discovered two additional bilaterian peptidergic systems that are evolutionarily conserved in nematodes. By combining phylogenetic analyses and reverse pharmacology, we identified a functional Gal/AstA-like peptide-receptor system NLP-1/NPR-9 and an additional SST/AstC-like system NLP-99/NPR-16 in C. elegans. We find that NLP-1 peptides of the AstA/buccalin peptide family potently activate the AstA receptor ortholog NPR-9. Likewise, the AstC-like peptide NLP-99 is a cognate ligand of the AstC receptor ortholog NPR-16. These findings confirm conservation of these ancestral bilaterian peptide systems, as predicted from phylogenetic analyses [1, 3, 7]. The representation of AstA- and AstC-like receptors in predicted protein datasets resembled that of their interacting ligands more than those of non-interacting peptides from the same family. One exciting prospect would be to integrate our pan-phylum NP-GPCR dataset with phylum-wide resources of putative NP-GPCR ligands to guide future receptor deorphanization efforts. Building such resources for putative NP-GPCR ligands would require significant analyses and manual curation, due to the complexity of neuropeptide gene structure and diversity of neuropeptide families [20]. Although it remains to be determined whether our in silico datasets can derive accurate prediction of NP-GPCR-ligand interactions, they do encourage the construction of pan-phylum resources to investigate this prospect.

Our results show that the Gal/AstA-related system, NLP-1/NPR-9, is widely conserved in nematodes. Gal/AstA-like peptides have a multitude of functions in mammals, ranging from the control of nociception to cognition, and feeding [139]. In Drosophila melanogaster, peptides of the AstA family are well-known for their juvenile hormone-inhibitory functions [140]. In addition, type-A allatostatins have broadly conserved myomodulatory functions [141]. For example, the AstA-like peptide buccalin was shown to decrease myoactivity in the mollusk Aplysia californica, whereas type-A allatostatins induce contractions in flatworm muscle preparations [142, 143]. In C. elegans, the AstA/buccalin-like peptide NLP-1 is released from olfactory AWC neurons and limits turning during local search behavior through activation of a neuropeptide Y/F (NPY/F) receptor ortholog, NPR-11 [118]. The AstA receptor ortholog NPR-9 is specifically expressed in the AIB interneurons, which control backward locomotion and turning [128, 144, 145]. Previous reports suggested that npr-9 overexpression abolishes turning, whereas loss-of-function mutants of npr-9 show increased reorientations during local search [145, 146]. We find that a full gene knockout mutant of npr-9, like the nlp-1 mutant, displays increased turning during local food search. In addition, we show that npr-9 and nlp-1 act in the same genetic pathway to regulate this behavior. NPR-9 has also been implicated in innate immune responses and processing of sensory cues, such as food and nose touch [32, 128, 145]. Whether any of these effects are mediated by NLP-1 signaling has not yet been studied.

The SST/AstC-like peptidergic system expanded in the nematode phylum, both at the receptor [7], and neuropeptide level [120]. Within this expanded family, NPR-16 represents the most conserved NP-GPCR in our pan-phylum dataset, and we show that NPR-16 is activated by the broadly conserved AstC-type peptide NLP-99. In insects, the AstC system has well-established endocrine functions, such as the control of juvenile hormone biosynthesis, and acts as central regulator, for example, in the circadian control of oogenesis [147, 148]. More generally in Bilateria, these highly conserved peptides play a fundamental role in myoregulation [120, 149]. In C. elegans, however, a function for AstC-type signaling has not yet been described. Based on the conserved activity of the SST/AstC system across different species and expression of npr-16 in inter- and motoneurons, NLP-99/NPR-16 might also exert context-dependent myoregulatory functions in C. elegans [150, 151].

Conclusions

In this study, we used a semi-automated pipeline to build a phylum-spanning NP-GPCR resource comprising 125 nematode species. NP-GPCR conservation across the phylum is variable, and generally maps according to the evolutionary distance from C. elegans. Our resource identifies highly conserved NP-GPCRs, with orthologs across the phylum Nematoda, that might play key roles in the regulation of nematode physiology. We focused on conserved orphan NP-GPCRs and used a combination of phylogenetic and biochemical approaches to identify a functional AstA/buccalin (NPR-9/NLP-1) and AstC/somatostatin-like (NPR-16/NLP-99) signaling system in C. elegans. Our findings and resource provide a basis for further functional studies of these ancestral bilaterian peptidergic systems and other conserved NP-GPCR candidates within Nematoda.

Methods

Nematode predicted proteome and NP-GPCR datasets

All available predicted proteome datasets from the WormBase ParaSite database (version 16.0) were searched for C. elegans NP-GPCR homologs [39, 152]. In total, 152 predicted proteomes for 125 species were collected, multiple datasets of a single species were merged, and duplicate sequences were removed using a custom Python script (software version 3.8.5). Reference Bioprojects for each species can be found in Additional file 2: Table S1. In addition, we generated a curated fasta file containing all known and predicted C. elegans NP-GPCR sequences [7, 19, 153], containing 161 protein sequences (Additional file 1: Table S1).

Identification of C. elegans NP-GPCR homologs

To identify homologs of C. elegans NP-GPCRs, we scaled up a previously published pipeline [19], based on a profile Hidden Markov Model (HMM) [154, 155]. Briefly, HMMs were constructed using predicted protein alignments of all known and predicted C. elegans NP-GPCRs (Additional file S1). Multiple sequence alignments of C. elegans NP-GPCRs were generated using an open-source Python script for ClustalOmega (Version 1.2.0), included in the provided pipeline [156]. This multiple sequence alignment file was transformed into a matrix containing scores that represent the initial position of each amino acid, using default hmmbuild parameters (Version 2.0). The resulting HMM profile was then fed into an hmmsearch script (HMMER3, Biopython module) to run similarity-based searches against the provided nematode proteome datasets, using an e-value threshold of 1e − 10. The other parameters were kept at default settings. Putative NP-GPCR sequences were then filtered based on the number of transmembrane regions, using HMMTOP (Version 2.1) [157]. As all protein sequences in the C. elegans NP-GPCR dataset had 4 to 7 predicted transmembrane regions, sequences with less than 4 transmembrane domains were excluded from our dataset, which is in accordance with previous analyses [19]. A value closer to 7 would filter out every truncated or not fully annotated protein sequence, whereas setting this parameter to 0 would increase the number of false positives. To validate our pipeline, we initially used the generated output to build a hmm profile and fed it into the hmmsearch algorithm against the C. elegans proteome. This was done to check for the correct identification of all the entry sequences. These duplicated sequences were later removed to avoid redundancy in the dataset.

Clustering analysis

Putative NP-GPCR sequences from C. elegans and other nematodes were further analyzed for sequence similarity using the CLANS algorithm (Version 2.0.1) [158]. An e-value limit of 1e − 5 was set for 20,000 iterations to perform a series of all-against all pairwise comparisons resulting in a 3D distribution of NP-GPCR sequences according to their sequence similarity.

To identify potential clusters, we used a linkage clustering script (set with minimum 5 links at e-value 1e − 30) [113]. Clusters were manually inspected, numbered (1 to 39), and color coded based on the presence of homologs for a single, multiple, or no C. elegans receptor families.

Sequences in clusters without C. elegans NP-GPCRs were used as queries in BLASTp searches of C. elegans predicted protein datasets, using standard parameters (BLOSUM62, expected threshold 0.05), to identify putative homologs in C. elegans. The same sequences and parameters were used to search against the entire NCBI databank to identify possible homologs in other phyla. Protein families of the identified hits were predicted using InterPro (version 97.0) [117].

Phylogenetic trees and annotation

Individual clusters identified by similarity features (using CLANS) were used to infer phylogenetic relationships among the sequences. First, we collected and merged all sequences from individual clusters into fasta files. To root the trees, a selection of 16 C. elegans bioamine receptor sequences was added to each fasta file [19]. Then, sequences extracted from each cluster were aligned using ClustalOmega (Version 1.2.0), with default settings. Alignments were further analyzed using a python script for FastTree 2, to generate rooted maximum likelihood phylogenetic trees [114, 115]. We added variables “spr 4,” “mlacc 2,” and “slownni” to increase the number of iterations and make the maximum-likelihood nearest-neighbor interchanges more exhaustive, the other parameters remained at default.

Each tree was annotated with a custom-made script that identifies all leaves with C. elegans NP-GPCR sequences, using a depth-first algorithm approach [159]. Next, all adjacent leaves were visited using a bottom-up approach until collision with other groups, and subclusters representing C. elegans NP-GPCR orthologs were colored. Clusters with a C. elegans NP-GPCR having a bootstrap value ≥ 60% were considered orthologs. Output was manually checked for correct clustering, to verify proper bootstrap values for each cluster and correct root of the trees.

Finally, the annotated trees were used to create a summary table indicating the presence of at least 1 ortholog for known C. elegans receptors (Additional file 3: Table S1). Values were normalized to 1 when more sequences from the same species were annotated as ortholog for a given receptor. This avoids ambiguity between different isoforms, gene duplication, or artifacts due to poor quality of a specific dataset.

Analysis of peptide representation in nematode predicted proteomes

The protein sequences for NLP-1, NLP-5, NLP-6, NLP-55, NLP-62, NLP-64, NLP-66, NLP-67, NLP-71, NLP-79, NLP-88, NLP-89, NLP-90, NLP-99, and NLP-119 were collected from WormBase [160]. Sequences for buccalin, AstA, and AstC peptides from A. californica, A. pisum, C. gigas, C. teleta, D. melanogaster, D. pulex, H. robusta, L. gigantea, and T. castaneum were collected from previous analyses [1, 120]. Sequences were aligned using MAFFT (Version 7), using standard BLOSUM62 parameters and L-INS-i as iterative refinement method. Outputs were manually checked and color-coded if amino acid patterns were recurrent in more than 60% of the sequences.

Putative nematode nlp genes were identified using HMMER v3.3.2 (www.hmmer.org). Individual HMM profiles were built for each nlp gene using nematode nlp sequence alignments generated previously [20]. HMM hits up to an e-value of 10 were used as reciprocal BLASTp queries against the C. elegans proteome using command line NCBI-blast-2.13.0 [116]. Where the reciprocal BLAST did not return the expected nlp gene as the top result, the hit was discarded. Hits were subsequently confirmed based on the presence of at least one key NLP sequence motif based on previously described alignments [20].

The conservation of receptor and peptide orthologs in each species was compared, where presence of only receptor or peptide was assigned as mismatch, whereas the presence or absence of both receptor and peptide was counted as a match.

Receptor activation assay

In vitro receptor activation assays were performed using an aequorin-based luminescence test as previously described [7, 36, 37, 135]. Briefly, CHO cells expressing the promiscuous Gα16 protein and aequorin calcium indicator (ES-000-A24, PerkinElmer) were transfected with pcDNA3.1/npr-9, pcDNA3.1/npr-16, or pcDNA3.1 empty vector at 40–50% confluency using Lipofectamine LTX and Plus Reagent (Invitrogen). Cells were maintained for 24 h at 37 °C, and then transferred to 28 °C overnight. Next, cells were collected at a density of 5 × 106 cells/ml in DMEM/F12 medium without phenol red (Invitrogen) and supplemented with 0.1% BSA and coelenterazine H (Invitrogen). Candidate peptide ligands were resuspended in DMEM/BSA at a final concentration of 10 μM to identify putative ligands, or in a serial dilution (10 μM to 1 fM) to construct concentration–response curves. Cells were added to the compound plates at a density of 25,000 cells/well and luminescence was measured at 469 nm for 30 s on a MicroBeta2 LumiJET (PerkinElmer). To normalize the luminescence signal based on the total Ca2+ response in each well, cells were lysed with 0.2% Triton X-100 (Merck), and luminescence was measured again for 30 s. To construct concentration–response curves, Ca2+ responses were calculated as percentage of the highest peptide-evoked response after subtraction of the negative control values (BSA) and normalized to the total Ca2+ response. A nonlinear regression analysis was used to create concentration–response curves, and EC50 values were calculated using GraphPad Prism (Version 8.0).

Besides candidate peptide ligands, receptors were also screened with a library of 344 synthetic replicates of C. elegans peptides [7]. Cells transfected with pcDNA3.1/frpr-5, pcDNA3.1/npr-9 and pcDNA3.1/npr-16 were tested with the complete library at a final concentration of 10 μM on a FLIPR Tetra High-Throughput Cellular Screening System (Molecular Devices) as described previously [7].

C. elegans maintenance

Using standard methods, C. elegans was cultured at 20 °C on nematode growth medium (NGM) and fed E. coli OP50. The wild-type N2 Bristol strain was obtained from the Caenorhabditis Genetics Center (University of Minnesota) [161]. A list of strains used in this study can be found in Table 1.

Table 1 Strains used in this study. CGC: Caenorhabditis Genetics Center (Minnesota, USA). Alleles ibt27 and lst1702 are theoretically identical but generated through independent CIRSPR-Cas9 editing
Full size table

CRISPR/Cas9-mediated npr-9 knockout

A deletion allele of npr-9 was generated using a dpy-10-based co-CRISPR strategy [162]. CRISPR RNAs (crRNAs) were chosen using CRISPOR [163] whereby two crRNAs were selected that generated a deletion covering 94.5% of the npr-9 open reading frame, including the start codon.

Young N2 adults were injected with a mix of 0.25 µL Cas9 enzyme (15 mg/µL, Thermo Fisher), 0.26 µL tracrRNA (0.17 mol/l, Integrated DNA Technologies [IDT]), 0.24 µL dpy-10 crRNA (0.6 nmol/μL, IDT), 0.20 µL npr-9 crRNA1 (0.6 nmol/μL, IDT), 0.20 µL npr-9 crRNA2 (0.6 nmol/μL, IDT), 2.2 µL dpy-10 repair template (0.5 mg/ml, Merck), and 1.1 µL npr-9 repair template (1 mg/ml, IDT). Progeny of the injected worms were screened by PCR for the desired gene edit. The genotype of the obtained npr-9 mutant was verified through sequencing. The crRNAs and repair templates used to edit npr-9 can be found in Table 2. A nlp-1 npr-9 double mutant was generated by injecting the same CRISPR mix into an nlp-1(ok1469) mutant animal.

Table 2 Oligonucleotides used in this study
Full size table

Local search assay

The assay was performed as previously reported [118]. Briefly, the day prior to the assay, L4 larvae were picked onto NGM plates seeded with E. coli OP50. At the time of recording, 10–15 young adults were transferred to an unseeded NGM plate and left to acclimate for 5 min. Afterwards, worms were recorded using a Pixelink PL-D734MU-T monochrome camera for 8 min at 15 fps using the manufacturer software (Pixelink Capture). Omega turns per minute were manually counted whereby the videos were blinded. Data were plotted and statistical analysis was performed using GraphPad Prism (version 8). One-way ANOVAs with post hoc Dunnett’s tests were performed when comparing different strains. Significance is indicated in the figures as follows: * p < 0.05, ** p < 0.01, *** p < 0.001. Bar graphs show mean ± SEM.

Availability of data and materials

All data generated or analyzed during this study are included in this published article and its supplementary information files. The CHO-K1 cell lines stably expressing mitochondrial-targeted apo-aequorin are under MTA and cannot be freely distributed. The complete code and datasets can be found in the public GitHub repository, [https://github.com/TemmermanLab/pipeline-phylum-NP-GPCR-analysis]. Phylogenetic trees and a list of orthologs for each C. elegans NP-GPCR are available in Additional file 6. Individual data values for in vitro and in vivo analyses are available in Additional file 9.

Abbreviations

ACP:

Adipokinetic hormone-Corazonin-like Peptide

AKH:

Adipokinetic Hormone

AstA:

Allatostatin A

AstB:

Allatostatin B

AstC:

Allatostatin C

AT:

Allatotropin

BLAST:

Basic Local Alignment Search Tool

Calc:

Calcitonin

CAPA:

Capability

CCK:

Cholecystokinin

SK:

Sulfakinin

Cer:

Cerebellin

CLANS:

Cluster ANalysis of Sequences

DH31:

Diuretic Hormone 31

DMSR:

DroMyoSuppressin Receptor

FRPR:

FMRFamide Peptide Receptor

FSHR:

Follicle Stimulating Hormone Receptor

Ful:

Fulicin

Gal:

Galanin

GnRH:

Gonadotropin-Releasing Hormone

HHM:

Hidden Markov Model

L11:

Elevenin

LK:

Leucokinin

Luq:

Luqin

MIP:

Myo Inhibiting Peptide

MSA:

Multiple Sequence Alignment

NLP:

Neuropeptide Like Protein

NMU:

Neuromedin U

NP-GPCR:

Neuropeptide G Protein-Coupled Receptor

NPF:

Neuropeptide F

NPFF:

Neuropeptide FF

NPR:

NeuroPeptide Receptor

NPY:

Neuropeptide Y

OP:

Opioid

OT:

Oxytocin

Ox:

Orexin

PBAN:

Pheromone Biosynthesis Activating Neuropeptide

PDF:

Pigment Dispersing Factor

PDFR:

Pigment Dispersing Factor Receptor

PK:

Pyrokinin

Prct:

Proctolin

RWa:

RWamide

RYa:

RYamide

SIFa:

SIFamide

sNPF:

Short Neuropeptide F

SST:

Somatostatin

TK:

Tachykinin

TRH:

Thyrotropin-Releasing Hormone

VP:

Vasopressin

References

  1. Mirabeau O, Joly JS. Molecular evolution of peptidergic signaling systems in bilaterians. PNAS. 2013;110:E2028–37. https://doiorg.publicaciones.saludcastillayleon.es/10.1073/pnas.1219956110.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Elphick MR, Mirabeau O, Larhammar D. Evolution of neuropeptide signalling systems. J Exp Biol. 2018;221. https://doiorg.publicaciones.saludcastillayleon.es/10.1242/jeb.151092

  3. Jékely G. Global view of the evolution and diversity of metazoan neuropeptide signaling. PNAS. 2013;110:8702–7. https://doiorg.publicaciones.saludcastillayleon.es/10.1073/pnas.1221833110.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Jékely G. The chemical brain hypothesis for the origin of nervous systems. Phil Trans R Soc B. 2021;376. https://doiorg.publicaciones.saludcastillayleon.es/10.1098/rstb.2019.0761

  5. Seidah NG, Chretien M. Proprotein and prohormone convertases: A family of subtilases generating diverse bioactive polypeptides. Brain Res. 1999;848:45–62. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/S0006-8993(99)01909-5.

    Article  CAS  PubMed  Google Scholar 

  6. van den Pol AN. Neuropeptide transmission in brain circuits. Neuron. 2012;76:98–115. hhtps://doi.org/https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.neuron.2012.09.014

  7. Beets I, Zels S, Vandewyer E, Demeulemeester J, Caers J, Baytemur E, et al. System-wide mapping of peptide-GPCR interactions in C. elegans. Cell Rep. 2023;42. hhtps://doi.org/https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.celrep.2023.113058

  8. Rashid AJ, O’Dowd BF, George SR. Minireview: Diversity and complexity of signaling through peptidergic G protein-coupled receptors. Endocrinology. 2004;145:2645–52. https://doiorg.publicaciones.saludcastillayleon.es/10.1210/en.2004-0052.

    Article  CAS  PubMed  Google Scholar 

  9. Tuteja N. Signaling through G protein coupled receptors. Plant Signal Behav. 2009;4:942–7. https://doiorg.publicaciones.saludcastillayleon.es/10.4161/psb.4.10.9530.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Naor Z, Benard O, Seger R. Activation of MAPK cascades by G-protein-coupled receptors: The case of gonadotropin-releasing hormone receptor. Trends Endocrinol Metab. 2000;11:91–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/S1043-2760(99)00232-5.

    Article  CAS  PubMed  Google Scholar 

  11. Tzameli I. GPCRs – Pivotal players in metabolism. Trends Endocrinol Metab. 2016;27:597–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.tem.2016.07.003.

    Article  CAS  PubMed  Google Scholar 

  12. Oliveira de Souza C, Sun X, Oh D. Metabolic functions of G protein-coupled receptors and β-arrestin-mediated signaling pathways in the pathophysiology of type 2 diabetes and obesity. Front Endocrinol. 2021;12. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fendo.2021.715877

  13. Latronico AC, Hochberg Z. G protein-coupled receptors in child development, growth, and maturation. Sci Signal. 2010;3. https://doiorg.publicaciones.saludcastillayleon.es/10.1126/scisignal.3143re7

  14. Cardoso JCR, Félix RC, Fonseca VG, Power DM. Feeding and the rhodopsin family G-protein coupled receptors in nematodes and arthropods. Front Endocrinol. 2012;3. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fendo.2012.00157

  15. Syrovatkina V, Alegre KO, Dey R, Huang XY. Regulation, signaling, and physiological functions of G-proteins. J Mol Biol. 2016;428:3850–68. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jmb.2016.08.002.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Azam S, Haque ME, Jakaria M, Jo SH, Kim IS, Choi DK. G-protein-coupled receptors in CNS: A potential therapeutic target for intervention in neurodegenerative disorders and associated cognitive deficits. Cells. 2020;9:506. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/cells9020506.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Hauser AS, Attwood MM, Rask-Andersen M, Schiöth HB, Gloriam DE. Trends in GPCR drug discovery: New agents, targets and indications. Nat Rev Drug Discov. 2017;16:829–42. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/nrd.2017.178.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Sriram K, Insel PA. G protein-coupled receptors as targets for approved drugs: How many targets and how many drugs?. Mol Pharmacol. 2018. p. 251–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1124/mol.117.111062

  19. Atkinson LE, McCoy CJ, Crooks BA, McKay FM, McVeigh P, McKenzie D, et al. Phylum-spanning Neuropeptide GPCR identification and prioritization: Shaping drug target discovery pipelines for nematode parasite control. Front Endocrinol. 2021;12:951. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fendo.2021.718363.

    Article  Google Scholar 

  20. McKay FM, McCoy CJ, Crooks B, Marks NJ, Maule AG, Atkinson LE, et al. In silico analyses of neuropeptide-like protein (NLP) profiles in parasitic nematodes. Int J Parasitol. 2022;52:77–85. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ijpara.2021.07.002.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Charlier J, Rinaldi L, Musella V, Ploeger HW, Chartier C, Vineer HR, et al. Initial assessment of the economic burden of major parasitic helminth infections to the ruminant livestock industry in Europe. Prev Vet Med. 2020;182. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.prevetmed.2020.105103[LG1]

  22. Abad P, Gouzy J, Aury JM, Castagnone-Sereno P, Danchin EGJ, Deleury E, et al. Genome sequence of the metazoan plant-parasitic nematode Meloidogyne incognita. Nat Biotechnol. 2008;26:909–15. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/nbt.1482.

    Article  CAS  PubMed  Google Scholar 

  23. Agrios GN. Plant diseases caused by nematodes. Plant Pathol. 2005;:838–42. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/B978-0-08-047378-9.50021-X

  24. Waller PJ. Anthelmintic resistance. Vet Parasitol. 1997;72:405–12. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/s0304-4017(97)00107-6.

    Article  Google Scholar 

  25. Wolstenholme AJ, Fairweather I, Prichard R, Von Samson-Himmelstjerna G, Sangster NC. Drug resistance in veterinary helminths. Trends Parasitol. 2004;20:469–76. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.pt.2004.07.010.

    Article  CAS  PubMed  Google Scholar 

  26. Wondimu A, Bayu Y. Anthelmintic Drug resistance of gastrointestinal nematodes of naturally infected goats in Haramaya, Ethiopia. J Parasitol Res. 2022;2022. https://doiorg.publicaciones.saludcastillayleon.es/10.1155/2022/4025902

  27. McVeigh P, Atkinson L, Marks NJ, Mousley A, Dalzell JJ, Sluder A, et al. Parasite neuropeptide biology: Seeding rational drug target selection? Int J Parasitol Drugs Drug Resist. 2012;2:76–91. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ijpddr.2011.10.004.

    Article  CAS  PubMed  Google Scholar 

  28. Davis RE, Stretton AOW. Structure-activity relationships of 18 endogenous neuropeptides on the motornervous system of the nematode Ascaris suum. Peptides. 2001;22:7–23. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/S0196-9781(00)00351-X.

    Article  CAS  PubMed  Google Scholar 

  29. Reinitz CA, Herfel HG, Messinger LA, Stretton AOW. Changes in locomotory behavior and cAMP produced in Ascaris suum by neuropeptides from Ascaris suum or Caenorhabditis elegans. Mol Biochem Parasitol. 2000;111:185–97. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/S0166-6851(00)00317-0.

    Article  CAS  PubMed  Google Scholar 

  30. Frooninckx L, Van Rompay L, Temmerman L, Sinay E Van, Beets I, Janssen T, et al. Neuropeptide GPCRs in C. elegans. Front Endocrinol. 2012;3:167. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fendo.2012.00167

  31. Pu L, Wang J, Lu Q, Nilsson L, Philbrook A, Pandey A, et al. Dissecting the genetic landscape of GPCR signaling through phenotypic profiling in C. elegans. Nat Commun. 2023 14:1. 2023;14:1–16. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41467-023-44177-z

  32. Yu Y, Zhi L, Wu Q, Jing L, Wang D. NPR-9 regulates the innate immune response in Caenorhabditis elegans by antagonizing the activity of AIB interneurons. Cell Mol Immunol. 2018;15:27–37. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/cmi.2016.8.

    Article  CAS  PubMed  Google Scholar 

  33. Barrios A, Ghosh R, Fang C, Emmons SW, Barr MM. PDF-1 neuropeptide signaling modulates a neural circuit for mate-searching behavior in C. elegans. Nat Neurosci. 2012;15:1675–82. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/nn.3253

  34. Van der Auwera P, Frooninckx L, Buscemi K, Vance RT, Watteyne J, Mirabeau O, et al. RPamide neuropeptides NLP-22 and NLP-2 act through GnRH-like receptors to promote sleep and wakefulness in C. elegans. Sci Rep. 2020;10. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41598-020-66536-2

  35. Watteyne J, Peymen K, Van der Auwera P, Borghgraef C, Vandewyer E, Van Damme S, et al. Neuromedin U signaling regulates retrieval of learned salt avoidance in a C. elegans gustatory circuit. Nat Commun. 2020;11. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41467-020-15964-9

  36. Beets I, Janssen T, Meelkop E, Temmerman L, Suetens N, Rademakers S, et al. Vasopressin/oxytocin-related signaling regulates gustatory associative learning in C. elegans. Science. 2012;338:543–5. https://doiorg.publicaciones.saludcastillayleon.es/10.1126/science.1226860

  37. Fadda M, De Fruyt N, Borghgraef C, Watteyne J, Peymen K, Vandewyer E, et al. NPY/NPF-related neuropeptide FLP-34 signals from serotonergic neurons to modulate aversive olfactory learning in Caenorhabditis elegans. J Neurosci. 2020;40. https://doiorg.publicaciones.saludcastillayleon.es/10.1523/JNEUROSCI.2674-19.2020

  38. Reinhardt F, Kaiser A, Prömel S, Stadler PF. Evolution of neuropeptide Y/RFamide-like receptors in nematodes. Heliyon. 2024;10. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.heliyon.2024.e34473

  39. Howe KL, Bolt BJ, Shafie M, Kersey P, Berriman M. WormBase ParaSite − a comprehensive resource for helminth genomics. Mol Biochem Parasitol. 2017;215:2–10. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.molbiopara.2016.11.005.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Johnson LS, Eddy SR, Portugaly E. Hidden Markov model speed heuristic and iterative HMM search procedure. BMC Bioinformatics. 2010;11:1–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/1471-2105-11-431.

    Article  CAS  Google Scholar 

  41. Bai X, Adams BJ, Ciche TA, Clifton S, Gaugler R, Kim K suk, et al. A Lover and a Fighter: The Genome Sequence of an Entomopathogenic Nematode Heterorhabditis bacteriophora. PLoS One. 2013;8. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal-pone.0069618

  42. Besnard F, Koutsovoulos G, Dieudonné S, Blaxter M, Félix MA. Toward universal forward genetics: Using a draft genome sequence of the nematode Oscheius tipulae to identify mutations affecting vulva development. Genetics. 2017;206:1747–61. https://doiorg.publicaciones.saludcastillayleon.es/10.1534/genetics.117.203521.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Blanc C, Saclier N, Le Faou E, Marie-Orleach L, Wenger E, Diblasi C, et al. Cosegregation of recombinant chromatids maintains genome-wide heterozygosity in an asexual nematode. Sci Adv. 2023;9. https://doiorg.publicaciones.saludcastillayleon.es/10.1126/sciadv.adi2804

  44. Blanc-Mathieu R, Perfus-Barbeoch L, Aury JM, Da Rocha M, Gouzy J, Sallet E, et al. Hybridization and polyploidy enable genomic plasticity without sex in the most devastating plant-parasitic nematodes. PLoS Genet. 2017;13: e1006777. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pgen.1006777.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Genome sequence of the nematode C. elegans: A platform for investigating biology. Science. 1998;282:2012–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1126/science.282.5396.2012

  46. Cotton JA, Bennuru S, Grote A, Harsha B, Tracey A, Beech R, et al. The genome of Onchocerca volvulus, agent of river blindness. Nat Microbiol. 2016 2:2. 2016;2:1–12. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/nmicrobiol.2016.216

  47. Cotton JA, Lilley CJ, Jones LM, Kikuchi T, Reid AJ, Thorpe P, et al. The genome and life-stage specific transcriptomes of Globodera pallida elucidate key aspects of plant parasitism by a cyst nematode. Genome Biol. 2014;15:1–17. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/gb-2014-15-3-r43.

    Article  CAS  Google Scholar 

  48. Desjardins CA, Cerqueira GC, Goldberg JM, Dunning Hotopp JC, Haas BJ, Zucker J, et al. Genomics of Loa loa, a Wolbachia-free filarial parasite of humans. Nat Genet. 2013 45:5. 2013;45:495–500. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/ng.2585

  49. Dieterich C, Clifton SW, Schuster LN, Chinwalla A, Delehaunty K, Dinkelacker I, et al. The Pristionchus pacificus genome provides a unique perspective on nematode lifestyle and parasitism. Nat Genet. 2008 40:10. 2008;40:1193–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/ng.227

  50. Dillman AR, Macchietto M, Porter CF, Rogers A, Williams B, Antoshechkin I, et al. Comparative genomics of Steinernema reveals deeply conserved gene regulatory networks. Genome Biol. 2015;16:1–21. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13059-015-0746-6.

    Article  CAS  Google Scholar 

  51. Eves-van den Akker S, Laetsch DR, Thorpe P, Lilley CJ, Danchin EGJ, Da Rocha M, et al. The genome of the yellow potato cyst nematode, Globodera rostochiensis, reveals insights into the basis of parasitism and virulence. Genome Biol. 2016;17:1–23. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13059-016-0985-1

  52. Fierst JL, Willis JH, Thomas CG, Wang W, Reynolds RM, Ahearne TE, et al. Reproductive Mode and the Evolution of Genome Size and Structure in Caenorhabditis Nematodes. PLoS Genet. 2015;11:e1005323. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pgen.1005323.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Foth BJ, Tsai IJ, Reid AJ, Bancroft AJ, Nichol S, Tracey A, et al. Whipworm genome and dual-species transcriptome analyses provide molecular insights into an intimate host-parasite interaction. Nat Genet. 2014 46:7. 2014;46:693–700. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/ng.3010

  54. Fradin H, Kiontke K, Zegar C, Gutwein M, Lucas J, Kovtun M, et al. Genome Architecture and Evolution of a Unichromosomal Asexual Nematode. Curr Biol. 2017;27:2928–2939.e6. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.cub.2017.08.038.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Ghedin E, Wang S, Spiro D, Caler E, Zhao Q, Crabtree J, et al. Draft genome of the filarial nematode parasite Brugia malayi. Science. 2007;317:1756–60. https://doiorg.publicaciones.saludcastillayleon.es/10.1126/science.1145406.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Godel C, Kumar S, Koutsovoulos G, Ludin P, Nilsson D, Comandatore F, et al. The genome of the heartworm, Dirofilaria immitis, reveals drug and vaccine targets. FASEB J. 2012;26:4650–61. https://doiorg.publicaciones.saludcastillayleon.es/10.1096/fj.12-205096.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Grosmaire M, Launay C, Siegwald M, Brugière T, Estrada-Virrueta L, Berger D, et al. Males as somatic investment in a parthenogenetic nematode. Science. 2019;363:1210–3. https://doiorg.publicaciones.saludcastillayleon.es/10.1126/science.aau0099.

    Article  CAS  PubMed  Google Scholar 

  58. Harris TW, Arnaboldi V, Cain S, Chan J, Chen WJ, Cho J, et al. WormBase: a modern Model Organism Information Resource. Nucleic Acids Res. 2020;48:D762–7. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/nar/gkz920.

    Article  CAS  PubMed  Google Scholar 

  59. Hiraki H, Kagoshima H, Kraus C, Schiffer PH, Ueta Y, Kroiher M, et al. Genome analysis of Diploscapter coronatus: insights into molecular peculiarities of a nematode with parthenogenetic reproduction. BMC Genom. 2017 18:1. 2017;18:1–18. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12964-017-3860-x

  60. Hunt VL, Tsai IJ, Coghlan A, Reid AJ, Holroyd N, Foth BJ, et al. The genomic basis of parasitism in the Strongyloides clade of nematodes. Nat Genet. 2016 48:3. 2016;48:299–307. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/ng.3495

  61. Coghlan A, Tyagi R, Cotton JA, Holroyd N, Rosa BA, Tsai IJ, et al. Comparative genomics of the major parasitic worms. Nat Genet. 2018 51:1. 2018;51:163–74. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41588-018-0262-1

  62. Jex AR, Liu S, Li B, Young ND, Hall RS, Li Y, et al. Ascaris suum draft genome. Nature. 2011 479:7374. 2011;479:529–33. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/nature10553

  63. Jex AR, Nejsum P, Schwarz EM, Hu L, Young ND, Hall RS, et al. Genome and transcriptome of the porcine whipworm Trichuris suis. Nat Genet. 2014 46:7. 2014;46:701–6. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/ng.3012

  64. Kanzaki N, Tsai IJ, Tanaka R, Hunt VL, Liu D, Tsuyama K, et al. Biology and genome of a newly discovered sibling species of Caenorhabditis elegans. Nat Commun. 2018 9:1. 2018;9:1–12. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41467-018-05712-5

  65. Kikuchi T, Cotton JA, Dalzell JJ, Hasegawa K, Kanzaki N, McVeigh P, et al. Genomic Insights into the Origin of Parasitism in the Emerging Plant Pathogen Bursaphelenchus xylophilus. PLoS Pathog. 2011;7: e1002219. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal-ppat-1002219.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Korhonen PK, Pozio E, La Rosa G, Chang BCH, Koehler A V., Hoberg EP, et al. Phylogenomic and biogeographic reconstruction of the Trichinella complex. Nat Commun. 2016 7:1. 2016;7:1–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/ncomms10513

  67. Koutsovoulos G, Makepeace B, Tanya VN, Blaxter M. Palaeosymbiosis Revealed by Genomic Fossils of Wolbachia in a Strongyloidean Nematode. PLoS Genet. 2014;10:1004397. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pgen.1004397.

    Article  CAS  Google Scholar 

  68. Laing R, Kikuchi T, Martinelli A, Tsai IJ, Beech RN, Redman E, et al. The genome and transcriptome of Haemonchus contortus, a key model parasite for drug and vaccine discovery. Genome Biol. 2013;14:1–16. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/gb-2013-14-8-r88.

    Article  CAS  Google Scholar 

  69. Masonbrink R, Maier TR, Muppirala U, Seetharam AS, Lord E, Juvale PS, et al. The genome of the soybean cyst nematode (Heterodera glycines) reveals complex patterns of duplications involved in the evolution of parasitism genes. BMC Genom. 2019;20:1–14. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12864-019-5485-8.

    Article  Google Scholar 

  70. McNulty SN, Strübe C, Rosa BA, Martin JC, Tyagi R, Choi YJ, et al. Dictyocaulus viviparus genome, variome and transcriptome elucidate lungworm biology and support future intervention. Sci Rep. 2016 6:1. 2016;6:1–14. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/srep20316

  71. Mimee B, Lord E, Véronneau PY, Masonbrink R, Yu Q, den Akker SE van. The draft genome of Ditylenchus dipsaci. J Nematol. 2019;51:1–3. https://doiorg.publicaciones.saludcastillayleon.es/10.21307/jofnem-2019-027

  72. Mitreva M, Jasmer DP, Zarlenga DS, Wang Z, Abubucker S, Martin J, et al. The draft genome of the parasitic nematode Trichinella spiralis. Nat Genet. 2011 43:3. 2011;43:228–35. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/ng769

  73. Mortazavi A, Schwarz EM, Williams B, Schaeffer L, Antoshechkin I, Wold BJ, et al. Scaffolding a Caenorhabditis nematode genome with RNA-seq. Genome Res. 2010;20:1740–7. https://doiorg.publicaciones.saludcastillayleon.es/10.1101/gr.111021.110.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Opperman CH, Bird DM, Williamson VM, Rokhsar DS, Burke M, Cohn J, et al. Sequence and genetic map of Meloidogyne hapla: A compact nematode genome for plant parasitism. PNAS. 2008;105:14802–7. https://doiorg.publicaciones.saludcastillayleon.es/10.1073/pnas.0805946105.

    Article  PubMed  PubMed Central  Google Scholar 

  75. Prabh N, Roeseler W, Witte H, Eberhardt G, Sommer RJ, Rödelsperger C. Deep taxon sampling reveals the evolutionary dynamics of novel gene families in Pristionchus nematodes. Genome Res. 2018;28:1664–74. https://doiorg.publicaciones.saludcastillayleon.es/10.1101/gr.234971.118.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Rödelsperger C, Meyer JM, Prabh N, Lanz C, Bemm F, Sommer RJ. Single-Molecule Sequencing Reveals the Chromosome-Scale Genomic Architecture of the Nematode Model Organism Pristionchus pacificus. Cell Rep. 2017;21:834–44. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.celrep.2017.09.077.

    Article  CAS  PubMed  Google Scholar 

  77. Rödelsperger C, Neher RA, Weller AM, Eberhardt G, Witte H, Mayer WE, et al. Characterization of genetic diversity in the nematode Pristionchus pacificus from population-scale resequencing data. Genet. 2014;196:1153–65. https://doiorg.publicaciones.saludcastillayleon.es/10.1534/genetics.113.159855.

    Article  CAS  Google Scholar 

  78. Rošić S, Amouroux R, Requena CE, Gomes A, Emperle M, Beltran T, et al. Evolutionary analysis indicates that DNA alkylation damage is a byproduct of cytosine DNA methyltransferase activity. Nat Genet. 2018 50:3. 2018;50:452–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41588-018-0061-8

  79. Ross JA, Koboldt DC, Staisch JE, Chamberlin HM, Gupta BP, Miller RD, et al. Caenorhabditis briggsae Recombinant Inbred Line Genotypes Reveal Inter-Strain Incompatibility and the Evolution of Recombination. PLoS Genet. 2011;7: e1002174. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pgen.1002174.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Sato K, Kadota Y, Gan P, Bino T, Uehara T, Yamaguchi K, et al. High-Quality Genome Sequence of the Root-Knot Nematode Meloidogyne arenaria Genotype A2-O. Genome Announc. 2018;6. https://doiorg.publicaciones.saludcastillayleon.es/10.1128/genomea.00519-18

  81. Schiffer PH, Danchin EGJ, Burnell AM, Creevey CJ, Wong S, Dix I, et al. Signatures of the Evolution of Parthenogenesis and Cryptobiosis in the Genomes of Panagrolaimid Nematodes. iScience. 2019;21:587–602. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.isci.2019.10.039

  82. Schiffer PH, Kroiher M, Kraus C, Koutsovoulos GD, Kumar S, R Camps JI, et al. The genome of Romanomermis culicivorax: Revealing fundamental changes in the core developmental genetic toolkit in Nematoda. BMC Genom.. 2013;14:1–16. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/1471-2164-14-923

  83. Schiffer PH, Polsky AL, Cole AG, Camps JIR, Kroiher M, Silver DH, et al. The gene regulatory program of Acrobeloides nanus reveals conservation of phylum-specific expression. PNAS. 2018;115:4459–64. https://doiorg.publicaciones.saludcastillayleon.es/10.1073/pnas.1720817115.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Schwarz EM, Hu Y, Antoshechkin I, Miller MM, Sternberg PW, Aroian R V. The genome and transcriptome of the zoonotic hookworm Ancylostoma ceylanicum identify infection-specific gene families. Nat Genet. 2015 47:4. 2015;47:416–22. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/ng.3237

  85. Schwarz EM, Korhonen PK, Campbell BE, Young ND, Jex AR, Jabbar A, et al. The genome and developmental transcriptome of the strongylid nematode Haemonchus contortus. Genome Biol. 2013;14:1–18. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/gb-2013-14-8-r89.

    Article  CAS  Google Scholar 

  86. Serra L, Macchietto M, Macias-Muñoz A, McGill CJ, Rodriguez IM, Rodriguez B, et al. Hybrid Assembly of the Genome of the Entomopathogenic Nematode Steinernema carpocapsae Identifies the X-Chromosome. 2019;G3(9):2687–97. https://doiorg.publicaciones.saludcastillayleon.es/10.1534/g3.119.400180.

    Article  CAS  Google Scholar 

  87. Small ST, Reimer LJ, Tisch DJ, King CL, Christensen BM, Siba PM, et al. Population genomics of the filarial nematode parasite Wuchereria bancrofti from mosquitoes. Mol Ecol. 2016;25:1465–77. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/mec.13574.

    Article  PubMed  PubMed Central  Google Scholar 

  88. Somvanshi VS, Tathode M, Shukla RN, Rao U. Nematode genome announcement: A draft genome for rice root-knot nematode, Meloidogyne graminicola. J Nematol. 2018;50:111–6. https://doiorg.publicaciones.saludcastillayleon.es/10.21307/jofnem-2018-018

  89. Srinivasan J, Dillman AR, Macchietto MG, Heikkinen L, Lakso M, Fracchia KM, et al. The draft genome and transcriptome of Panagrellus redivivus are shaped by the harsh demands of a free-living lifestyle. Genet. 2013;193:1279–95. https://doiorg.publicaciones.saludcastillayleon.es/10.1534/genetics.112.148809.

    Article  CAS  Google Scholar 

  90. Stein LD, Bao Z, Blasiar D, Blumenthal T, Brent MR, Chen N, et al. The Genome Sequence of Caenorhabditis briggsae: A Platform for Comparative Genomics. PLoS Biol. 2003;1. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pbio.0000045

  91. Stevens L, Rooke S, Falzon LC, Machuka EM, Momanyi K, Murungi MK, et al. The Genome of Caenorhabditis bovis. Curr Biol. 2020;30:1023–1031.e4. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.cub.2020.01.074.

    Article  CAS  PubMed  Google Scholar 

  92. Stevens L, Félix MA, Beltran T, Braendle C, Caurcel C, Fausett S, et al. Comparative genomics of 10 new Caenorhabditis species. Evol Lett. 2019;3:217–36. https://doiorg.publicaciones.saludcastillayleon.es/10.1002/evl3.110.

    Article  PubMed  PubMed Central  Google Scholar 

  93. Sun S, Shinya R, Dayi M, Yoshida A, Sternberg PW, Kikuchi T. Telomere-to-Telomere Genome Assembly of Bursaphelenchus okinawaensis Strain SH1. Microbiol Resour Announc. 2020;9. https://doiorg.publicaciones.saludcastillayleon.es/10.1128/MRA.01000-20

  94. Szitenberg A, Salazar-Jaramillo L, Blok VC, Laetsch DR, Joseph S, Williamson VM, et al. Comparative Genomics of Apomictic Root-Knot Nematodes: Hybridization, Ploidy, and Dynamic Genome Change. Genome Biol Evol. 2017;9:2844–61. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/gbe/evx201.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Tallon LJ, Liu X, Bennuru S, Chibucos MC, Godinez A, Ott S, et al. Single molecule sequencing and genome assembly of a clinical specimen of Loa loa, the causative agent of loiasis. BMC Genom. 2014;15:1–14. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/1471-2164-15-788.

    Article  Google Scholar 

  96. Tang YT, Gao X, Rosa BA, Abubucker S, Hallsworth-Pepin K, Martin J, et al. Genome of the human hookworm Necator americanus. Nat Genet. 2013 46:3. 2014;46:261–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/ng.2875

  97. Thorne MAS, Kagoshima H, Clark MS, Marshall CJ, Wharton DA. Molecular Analysis of the Cold Tolerant Antarctic Nematode. Panagrolaimus davidi PLoS One. 2014;9: e104526. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pone.0104526.

    Article  CAS  PubMed  Google Scholar 

  98. Tyagi R, Joachim A, Ruttkowski B, Rosa BA, Martin JC, Hallsworth-Pepin K, et al. Cracking the nodule worm code advances knowledge of parasite biology and biotechnology to tackle major diseases of livestock. Biotechnol Adv. 2015;33 6 0 1:980. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.biotechadv.2015.05.004

  99. Wang J, Gao S, Mostovoy Y, Kang Y, Zagoskin M, Sun Y, et al. Comparative genome analysis of programmed DNA elimination in nematodes. Genome Res. 2017;27:2001–14. https://doiorg.publicaciones.saludcastillayleon.es/10.1101/gr.225730.117.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Wang J, Mitreva M, Berriman M, Thorne A, Magrini V, Koutsovoulos G, et al. Silencing of germline-expressed genes by DNA elimination in somatic cells. Dev Cell. 2012;23:1072–80. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.devcel.2012.09.020.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Weinstein DJ, Allen SE, Lau MCY, Erasmus M, Asalone KC, Walters-Conte K, et al. The genome of a subterrestrial nematode reveals adaptations to heat. Nat Commun. 2019 10:1. 2019;10:1–14. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/s41467-019.13245-8

  102. Yin D, Schwarz EM, Thomas CG, Felde RL, Korf IF, Cutter AD, et al. Rapid genome shrinkage in a self-fertile nematode reveals sperm competition proteins. Science. 2018;359:55–61. https://doiorg.publicaciones.saludcastillayleon.es/10.1126/science.aao0827.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Zheng J, Peng D, Chen L, Liu H, Chen F, Xu M, et al. The Ditylenchus destructor genome provides new insights into the evolution of plant parasitic nematodes. Proc R Soc B Biol Sci. 2016;283. https://doiorg.publicaciones.saludcastillayleon.es/10.1098/rspb.2016.0942

  104. Zhu XQ, Korhonen PK, Cai H, Young ND, Nejsum P, Von Samson-Himmelstjerna G, et al. Genetic blueprint of the zoonotic pathogen Toxocara canis. Nat Commun. 2015 6:1. 2015;6:1–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/ncomms7145

  105. Fu Z, Li Y, Elling AA, Snyder WE. A draft genome of a field-collected Steinernema feltiae strain NW. J Nematol. 2020;52. https://doiorg.publicaciones.saludcastillayleon.es/10.21307/jofnem-2020-003

  106. Dayi M, Sun S, Maeda Y, Tanaka R, Yoshida A, Tsai IJ, et al. Nearly Complete Genome Assembly of the Pinewood Nematode Bursaphelenchus xylophilus Strain Ka4C1. Microbiol Resour Announc. 2020;9. https://doiorg.publicaciones.saludcastillayleon.es/10.1128/mra.01002-20

  107. de la Rosa PMG, Thomson M, Trivedi U, Tracey A, Tandonnet S, Blaxter M. A telomere-to-telomere assembly of Oscheius tipulae and the evolution of rhabditid nematode chromosomes. 2021;G3:11. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/g3journal/jkaa020.

    Article  CAS  Google Scholar 

  108. Xu L, Xu M, Sun X, Xu J, Zeng X, Shan D, et al. The genetic basis of adaptive evolution in parasitic environment from the Angiostrongylus cantonensis genome. PLoS Negl Trop Dis. 2019;13. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pntd.0007846

  109. Abubucker S, McNulty SN, Rosa BA, Mitreva M. Identification and characterization of alternative splicing in parasitic nematode transcriptomes. Parasit Vectors. 2014;7:1–12. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/1756-3305-7-151.

    Article  CAS  Google Scholar 

  110. van Steenbrugge JJM, van den Elsen S, Holterman M, Sterken MG, Thorpe P, Goverse A, et al. Comparative genomics of two inbred lines of the potato cyst nematode Globodera rostochiensis reveals disparate effector family-specific diversification patterns. BMC Genom. 2021;22:1–19. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12864-021-07914-6.

    Article  CAS  Google Scholar 

  111. Holterman M, Van Der Wurff A, Van Den Elsen S, Van Megen H, Bongers T, Holovachov O, et al. Phylum-wide analysis of SSU rDNA reveals deep phylogenetic relationships among nematodes and accelerated evolution toward crown clades. Mol Biol Evol. 2006;23:1792–800. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/molbev/msl044.

    Article  CAS  PubMed  Google Scholar 

  112. Blaxter ML, De Ley P, Garey JR, Llu LX, Scheldeman P, Vierstraete A, et al. A molecular evolutionary framework for the phylum Nematoda. Nature 1998; 392:6671. 1998;392:71–5. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/32160

  113. Großwendt A, Röglin H. Improved analysis of complete-linkage clustering. Algorithmica. 2017;78:1131–50. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/s00453-017-0284-6.

    Article  Google Scholar 

  114. Price MN, Dehal PS, Arkin AP. FastTree 2--approximately maximum-likelihood trees for large alignments. PLoS One. 2010;5. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pone.0009490

  115. Price MN, Dehal PS, Arkin AP. FastTree: Computing large minimum evolution trees with profiles instead of a distance matrix. Mol Biol Evol. 2009;26:1641–50. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/molbev/msp077.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403–10. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/S0022-2836(05)80360-2.

    Article  CAS  PubMed  Google Scholar 

  117. Blum M, Chang HY, Chuguransky S, Grego T, Kandasaamy S, Mitchell A, et al. The InterPro protein families and domains database: 20 years on. Nucleic Acids Res. 2021;49:D344–54. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/nar/gkaa977.

    Article  CAS  PubMed  Google Scholar 

  118. Chalasani SH, Kato S, Albrecht DR, Nakagawa T, Abbott LF, Bargmann CI. Neuropeptide feedback modifies odor-evoked dynamics in Caenorhabditis elegans olfactory neurons. Nat Neurosci. 2010;13:615–21. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/nn.2526.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Nathoo AN, Moeller RA, Westlund BA, Hart AC. Identification of neuropeptide-like protein gene families in Caenorhabditis elegans and other species. PNAS. 2001;98:14000–5. https://doiorg.publicaciones.saludcastillayleon.es/10.1073/pnas.241231298.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Zhang Y, Yañez-Guerra LA, Tinoco AB, Castelán NE, Egertová M, Elphick MR. Somatostatin-type and allatostatin-C-type neuropeptides are paralogous and have opposing myoregulatory roles in an echinoderm. PNAS. 2022;119. https://doiorg.publicaciones.saludcastillayleon.es/10.1073/pnas.2113589119

  121. Cockx B, Van Bael S, Boelen R, Vandewyer E, Yang H, Le TA, et al. Mass spectrometry–driven discovery of neuropeptides mediating nictation behavior of nematodes. Mol Cell Proteomics. 2023;22: 100479. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.mcpro.2022.100479.

    Article  CAS  PubMed  Google Scholar 

  122. McCoy CJ, Atkinson LE, Zamanian M, McVeigh P, Day TA, Kimber MJ, et al. New insights into the FLPergic complements of parasitic nematodes: Informing deorphanisation approaches. EuPA Open Proteom. 2014;3:262–72. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.euprot.2014.04.002.

    Article  CAS  PubMed  Google Scholar 

  123. Li C, Kim K. Family of FLP peptides in Caenorhabditis elegans and related nematodes. Front Endocrinol. 2014;5. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fendo.2014.00150

  124. Peymen K, Watteyne J, Frooninckx L, Schoofs L, Beets I. The FMRFamide-like peptide family in nematodes. Front Endocrinol. 2014;5:90. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fendo.2014.00090.

    Article  Google Scholar 

  125. Stables J, Green A, Marshall F, Fraser N, Knight E, Sautel M, et al. A bioluminescent assay for agonist activity at potentially any G- protein-coupled receptor. Anal Biochem. 1997;252:115–26. https://doiorg.publicaciones.saludcastillayleon.es/10.1006/abio.1997.2308.

    Article  CAS  PubMed  Google Scholar 

  126. Bauknecht P, Jékely G. Large-scale combinatorial deorphanization of Platynereis neuropeptide GPCRs. Cell Rep. 2015;12:684–93. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.celrep.2015.06.052.

    Article  CAS  PubMed  Google Scholar 

  127. Yemini E, Jucikas T, Grundy LJ, Brown AEX, Schafer WR. A database of Caenorhabditis elegans behavioral phenotypes. Nat Methods. 2013;10:877–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/nmeth.2560.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  128. Bendena WG, Boudreau JR, Papanicolaou T, Maltby M, Tobe SS, Chin-Sang ID. A Caenorhabditis elegans allatostatin/galanin-like receptor NPR-9 inhibits local search behavior in response to feeding cues. PNAS. 2008;105:1339–42. https://doiorg.publicaciones.saludcastillayleon.es/10.1073/pnas.0709492105.

    Article  PubMed  PubMed Central  Google Scholar 

  129. Hodda M. Phylum Nematoda: trends in species descriptions, the documentation of diversity, systematics, and the species concept. Zootaxa. 2022;5114. https://doiorg.publicaciones.saludcastillayleon.es/10.11646/zootaxa.5114.1.2

  130. Zhang J. Evolution by gene duplication: An update. Trends Ecol Evol. 2003;18:292–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/S0169-5347(03)00033-8.

    Article  Google Scholar 

  131. Cotton JA, Page RDM. Rates and patterns of gene duplication and loss in the human genome. P Roy Soc B-Biol Sci. 2005;272. https://doiorg.publicaciones.saludcastillayleon.es/10.1098/rspb.2004.2969

  132. Birchler JA, Yang H. The multiple fates of gene duplications: Deletion, hypofunctionalization, subfunctionalization, neofunctionalization, dosage balance constraints, and neutral variation. Plant Cell. 2022;34:2466–74. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/plcell/koac076.

    Article  PubMed  PubMed Central  Google Scholar 

  133. Istiban MN, De Fruyt N, Kenis S, Beets I. Evolutionary conserved peptide and glycoprotein hormone-like neuroendocrine systems in C. elegans. Mol Cell Endocrinol. 2024;584:112162. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.mce.2024.112162

  134. Kenis S, Istiban MN, Van Damme S, Vandewyer E, Watteyne J, Schoofs L, et al. Ancestral glycoprotein hormone-receptor pathway controls growth in C. elegans. Front Endocrinol. 2023;14:1200407. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fendo.2023.1200407

  135. Van Sinay E, Mirabeau O, Depuydt G, Van Hiel MB, Peymen K, Watteyne J, et al. Evolutionarily conserved TRH neuropeptide pathway regulates growth in Caenorhabditis elegans. PNAS. 2017;114:E4065–74. https://doiorg.publicaciones.saludcastillayleon.es/10.1073/pnas.1617392114.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  136. Ohno H, et al. Luqin-like RYamide peptides regulate food-evoked responses in C. elegans. eLife. 2017;6:299. https://doiorg.publicaciones.saludcastillayleon.es/10.7554/eLife.28877.

    Article  Google Scholar 

  137. Gadenne MJ, et al. Neuropeptide signalling shapes feeding and reproductive behaviours in male Caenorhabditis elegans. Life Sci Alliance. 2022;5:e202201420. https://doiorg.publicaciones.saludcastillayleon.es/10.26508/lsa.202201420.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Jee C, Lee J, Lim JP, Parry D, Messing RO, Mcintire SL. SEB-3, a CRF receptor-like GPCR, regulates locomotor activity states, stress responses and ethanol tolerance in Caenorhabditis elegans. Genes Brain Behav. 2013;12:250–62. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/j.1601-183X.2012.00829.x.

    Article  CAS  PubMed  Google Scholar 

  139. Vrontakis ME. Galanin: a biologically active peptide. CNS Neurol Disord Drug Targets. 2002;1:531–41. https://doiorg.publicaciones.saludcastillayleon.es/10.2174/1568007023338914.

    Article  CAS  Google Scholar 

  140. Deveci D, Martin FA, Leopold P, Romero NM. AstA signaling functions as an evolutionary conserved mechanism timing juvenile to adult transition. Curr Biol. 2019;29:813–22. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.cub.2019.01.053.

    Article  CAS  PubMed  Google Scholar 

  141. Bendena WG, Donly BC, Tobe SS. Allatostatins: A growing family of neuropeptides with structural and functional diversity. Ann N Y Acad Sci. 1999;897:311–29. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/j.1749-6632.1999.tb07902.x.

    Article  CAS  PubMed  Google Scholar 

  142. Cropper EC, Miller MW, Tenenbaum R, Kolks MA, Kupfermann I, Weiss KR. Structure and action of buccalin: a modulatory neuropeptide localized to an identified small cardioactive peptide-containing cholinergic motor neuron of Aplysia californica. PNAS. 1988;85:6177–81. http://www.jstor.org/stable/32322

  143. Mousley A, Moffett CL, Duve H, Thorpe A, Halton DW, Geary TG, et al. Expression and bioactivity of allatostatin-like neuropeptides in helminths. Int J Parasitol. 2005;35:1557–67. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ijpara.2005.08.002.

    Article  CAS  PubMed  Google Scholar 

  144. Wang L, Sato H, Satoh Y, Tomioka M, Kunitomo X, Iino Y. A gustatory neural circuit of Caenorhabditis elegans generates memory-dependent behaviors in Na+ chemotaxis. J Neurosc. 2017;37:2097. https://doiorg.publicaciones.saludcastillayleon.es/10.1523/JNEUROSCI.1774-16.2017.

    Article  CAS  Google Scholar 

  145. Campbell JC, Polan-Couillard LF, Chin-Sang ID, Bendena WG. NPR-9, a galanin-like G-protein coupled receptor, and GLR-1 regulate interneuronal circuitry underlying multisensory integration of environmental cues in Caenorhabditis elegans. PLoS Genet. 2016;12: e1006050. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pgen.1006050.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  146. López-Cruz A, Sordillo A, Pokala N, Liu Q, McGrath PT, Bargmann CI. Parallel multimodal circuits control an Iinnate foraging behavior. Neuron. 2019;102:407–19. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.neuron.2019.01.053.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  147. Kramer SJ, Toschi A, Miller CA, Kataoka H, Quistad GB, Li JP, et al. Identification of an allatostatin from the tobacco hornworm Manduca sexta. PNAS. 1991;88:9458–62. https://doiorg.publicaciones.saludcastillayleon.es/10.1073/pnas.88.21.9458.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Zhang C, Daubnerova I, Jang YH, Kondo S, Žitnan D, Kim YJ. The neuropeptide allatostatin C from clock-associated DN1p neurons generates the circadian rhythm for oogenesis. PNAS. 2021;118: e2016878118. https://doiorg.publicaciones.saludcastillayleon.es/10.1073/pnas.2016878118.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  149. Lubawy J, Marciniak P, Kuczer M, Rosiński G. Myotropic activity of allatostatins in tenebrionid beetles. Neuropeptides. 2018;70:26–36. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.npep.2018.05.003.

    Article  CAS  PubMed  Google Scholar 

  150. Taylor SR, Santpere G, Weinreb A, Barrett A, Reilly MB, Xu C, et al. Molecular topography of an entire nervous system. Cell. 2021;184:4329–4347.e23. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.cell.2021.06.023.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  151. Hammarlund M, Hobert O, Miller DM, Sestan N. The CeNGEN Project: The complete gene expression map of an entire nervous system. Neuron. 2018;99. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.neuron.2018.07.042

  152. Howe KL, Bolt BJ, Cain S, Chan J, Chen WJ, Davis P, et al. WormBase 2016: Expanding to enable helminth genomic research. Nucleic Acids Res. 2016;44:D774–80. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/nar/gkv1217.

    Article  CAS  PubMed  Google Scholar 

  153. Hobert O. Neurogenesis in the nematode Caenorhabditis elegans. WormBook. 2010;1–24.

  154. Eddy SR. A new generation of homology search tools based on probabilistic inference. Genome Inform. 2009;23:205–11. https://www.ncbi.nlm.nih.gov/books/NBK116086

  155. Eddy SR. What is a hidden Markov model? Nat Biotechnol. 2004;22:1315–6. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/nbt1004-1315.

    Article  CAS  PubMed  Google Scholar 

  156. Sievers F, Wilm A, Dineen D, Gibson TJ, Karplus K, Li W, et al. Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol Syst Biol. 2011;7:539. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/msb.2011.75.

    Article  PubMed  PubMed Central  Google Scholar 

  157. Tusnády E, Tusnády T, Istv´ I, Simon I. The HMMTOP transmembrane topology prediction server. Bioinformatics. 2001;17:849–50. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/bioinformatics/17.9.849

  158. Frickey T, Lupas A. CLANS: a Java application for visualizing protein families based on pairwise similarity. Bioinformatics. 2004;20:3702–4. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/bioinformatics/bth444.

    Article  CAS  PubMed  Google Scholar 

  159. Tarjan R. Depth- first search and linear graph algorithms. SICOMP. 1971. https://doiorg.publicaciones.saludcastillayleon.es/10.1137/0201010.

    Article  Google Scholar 

  160. Davis P, Zarowiecki M, Arnaboldi V, Becerra A, Cain S, Chan J, et al. WormBase in 2022-data, processes, and tools for analyzing Caenorhabditis elegans. Genetics. 2022;220:iyac003. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/genetics/iyac003

  161. Lewis JA, Fleming JT. Chapter 1 Basic culture methods. Methods Cell Biol. 1995;48:3–29. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/S0091-679X(08)61381-3

  162. Paix A, Folkmann A, Seydoux G. Precision genome editing using CRISPR-Cas9 and linear repair templates in C. elegans. Methods. 2017;121–122:86–93. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ymeth.2017.03.023

  163. Concordet JP, Haeussler M. CRISPOR: intuitive guide selection for CRISPR/Cas9 genome editing experiments and screens. Nucleic Acids Res. 2018;46:W242–5. https://doiorg.publicaciones.saludcastillayleon.es/10.1093/nar/gky354.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We are grateful to A. Kieswetter for technical assistance, and to M. Istiban, Dr. B. Cockx, Dr. J. Watteyne, and Dr. V. Cambareri for advice.

Funding

This work was supported by the KU Leuven Research Council (C16/19/003), the European Research Council (ERC FLEXPEPNET 950328), the Research Foundation Flanders (FWO G036524N and G085521N), Biotechnology and Biological Sciences Research Council grants (BB/H019472/1, BB/MO10392/1, BB/T016396/1). We thank the Caenorhabditis Genetics Center, funded by NIH Office of Research Infrastructure Programs Grant P40 OD010440, for providing the wild-type and nlp-1(ok1469) C. elegans strains.

Author information

Authors and Affiliations

  1. Animal Physiology and Neurobiology, Department of Biology, University of Leuven (KU Leuven), Naamsestraat 59, 3000, Leuven, Belgium

    Luca Golinelli, Ellen Geens, Elke Vandewyer, Liesbet Temmerman & Isabel Beets

  2. Microbes & Pathogen Biology, School of Biological Sciences, The Institute for Global Food Security, Queen’s University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL, UK

    Allister Irvine, Ciaran J. McCoy, Louise E. Atkinson & Angela Mousley

Authors
  1. Luca Golinelli
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Ellen Geens
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Allister Irvine
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Ciaran J. McCoy
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Elke Vandewyer
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Louise E. Atkinson
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Angela Mousley
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Liesbet Temmerman
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Isabel Beets
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

This study was conceived by LG, LA, AM, LT, and IB. Investigation, including experiments and analyses, were performed by LG, EG, AI, EV, and CMCC. The manuscript was written by LG, LT, and IB with contributions from EG, AI, CMCC, LA, and AM. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Liesbet Temmerman or Isabel Beets.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: Table S1 - Protein sequences of 161 C. elegans NP-GPCR candidates.

12915_2024_2017_MOESM2_ESM.xlsx

Additional file 2: Table S1 - Nematode species included in this study and related Bioprojects. Table 2 - BUSCO scores for each Bioproject included in this study.

12915_2024_2017_MOESM3_ESM.xlsx

Additional file 3: Table S1-S2 - Nematode orthologs of C. elegans NP-GPCRs. Black boxes indicate the presence of at least 1 orthologous sequence, white boxes represent the absence of an ortholog in our resource. Table S1 - Resource ordered by receptor family. Table S2 - Data ordered from least to most conserved receptor.

12915_2024_2017_MOESM4_ESM.pdf

Additional file 4: Figs. S1-24. Fig. S1 - Nematode species found within each cluster obtained from CLANS analysis. Fig. S2 - Analysis of C. elegans NP-GPCR orthologs using one high-quality annotated dataset per genus.Fig. S3 - Correlation between % of C. elegans NP-GPCR orthologs and BUSCO score for each species included in the study. Fig. S4 - Receptor activation assay for AstA- and AstC-like peptides and receptors.

12915_2024_2017_MOESM5_ESM.xlsx

Additional file 5: Table S1 - Nematodes in clusters with no known C. elegans NP-GPCR sequence. Black boxes indicate the presence of at least 1 sequence for a given nematode in that cluster, white boxes are assigned to nematode sequences missing in the cluster. Table S2 - Putative orthologs emerging from a BLASTp analysis [116] and predicted protein family based on InterPro [117].

12915_2024_2017_MOESM6_ESM.zip

Additional file 6: Phylogenetic trees and ortholog sequences. Compressed folder containing .json files for C. elegans NP-GPCRs, each listing the orthologs found in this analysis and .tree files corresponding to each generated phylogenetic tree. File extensions: .json (visualizable on every text editor software), and .tree (visualizable on iTOL itol.embl.de).

12915_2024_2017_MOESM7_ESM.xlsx

Additional file 7: Table S1 - Classification of C. elegans NP-GPCRs based on their interaction with cognate ligands [7]. One-to-one: the interaction is unique for both the peptide and the receptor. One-to-many: the receptor is activated by a single peptide that can also activate other receptors, or: the receptor interacts with multiple peptides that are unique for that receptor (one-to-many in both directions). Many-to-many: the receptor interacts with multiple peptides that can also interact with other receptors.

12915_2024_2017_MOESM8_ESM.xlsx

Additional file 8: Table S1 - Analysis of peptide representations of AstA- and AstC-like peptides in nematodes. Black boxes demonstrate the presence of at least 1 orthologous sequence, white boxes represent the absence of an ortholog. Table S2 - list of AstA- and AstC-like orthologs with peptide sequences.

Additional file 9: Tables S1-S12 - Individual data values.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Golinelli, L., Geens, E., Irvine, A. et al. Global analysis of neuropeptide receptor conservation across phylum Nematoda. BMC Biol 22, 223 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12915-024-02017-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12915-024-02017-6

Keywords

BMC Biology

ISSN: 1741-7007

Contact us