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10.1093/genetics/iyad047
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Distinct clusters of human pain gene orthologs in Caenorhabditis elegans regulate thermo-nociceptive sensitivity and plasticity
Jordan Aurore Department of Biology, University of Fribourg, 1700 Fribourg, Switzerland

Glauser Dominique A Department of Biology, University of Fribourg, 1700 Fribourg, Switzerland

Barrios A Editor
Corresponding author: Department of Biology, University of Fribourg, Chemin du Musée 10, 1700 Fribourg, Switzerland. Email: dominique.glauser@unifr.ch
Conflicts of interest The author(s) declare no conflict of interest.

5 2023
22 3 2023
22 3 2023
224 1 iyad04713 5 2022
07 3 2023
04 4 2023
© The Author(s) 2023. Published by Oxford University Press on behalf of the Genetics Society of America.
2023
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

Abstract

The detection and avoidance of harmful stimuli are essential animal capabilities. The molecular and cellular mechanisms controlling nociception and its plasticity are conserved, genetically controlled processes of broad biomedical interest given their relevance to understand and treat pain conditions that represent a major health burden. Recent genome-wide association studies (GWAS) have identified a rich set of polymorphisms related to different pain conditions and pointed to many human pain gene candidates, whose connection to the pain pathways is however often poorly understood. Here, we used a computer-assisted Caenorhabditis elegans thermal avoidance analysis pipeline to screen for behavioral defects in a set of 109 mutants for genes orthologous to human pain-related genes. We measured heat-evoked reversal thermosensitivity profiles, as well as spontaneous reversal rate, and compared naïve animals with adapted animals submitted to a series of repeated noxious heat stimuli, which in wild type causes a progressive habituation. Mutations affecting 28 genes displayed defects in at least one of the considered parameters and could be clustered based on specific phenotypic footprints, such as high-sensitivity mutants, nonadapting mutants, or mutants combining multiple defects. Collectively, our data reveal the functional architecture of a network of conserved pain-related genes in C. elegans and offer novel entry points for the characterization of poorly understood human pain genes in this genetic model.

Jordan and Glauser report the result of a mutant screen addressing thermal nociception and its plasticity in C. elegans. Their data reveal the functional architecture of a network of conserved pain-related genes and offer novel entry points for the characterization of poorly-understood human pain genes in this genetic model.

thermal nociception
pain genes
worm
invertebrate
neurogenetics
behavioral plasticity
habituation
sensory adaptation
aversive behavior
heat avoidance
NIH 10.13039/100000002 P40 OD010440 Swiss National Science Foundation 10.13039/501100001711 310030_197607 PP00P3_150681 BSSGI0_155764
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pmcIntroduction

Avoiding harmful situations is essential for animal survival. Nociception, the ability to detect damaging or potentially damaging stimuli, is a well-conserved physiological process, underlying avoidance behaviors across phyla (Burrell 2017; Walters 2018). Normal or abnormal activation of nociceptive pathways is also a primary trigger for the conscious experience of pain, which significantly decrease human well-being in a variety of clinical or subclinical contexts. The cellular and molecular mechanisms underpinning nociception and its regulation are also largely conserved from invertebrates to human. Characterizing conserved nociception processes in animal models may thus provide new insights into the mechanisms underlying pathological pain conditions in human and provide new treatment avenues (Williams 2016).

Chronic pain conditions in various forms affect up to 30% of the population (Breivik et al. 2006; Goldberg and McGee 2011; Zorina-Lichtenwalter et al. 2016). Unfortunately, available therapies are still often unsatisfactory, which has motivated intensive research on pain, including on its genetic basis (Mogil 2009; Burrell 2017). Pain genetics may not only provide information on pain etiology in specific populations, but also bring insights into the molecular network regulating pain more generally, and suggest new therapeutic approaches. Numerous genetic risk factors have been identified for migraines, musculoskeletal conditions, visceral pain disorders (due to diabetes or cancer), or neuropathic pain disorders (Zorina-Lichtenwalter et al. 2016). Screening for pain-related gene mutations/variants is either done via linkage analysis or via genome-wide association studies (GWAS) (Young et al. 2012). The first method is used to identify rare familial mutations. The second method is mainly used for the identification of common functional polymorphisms, usually on large populations of unrelated subjects with the pathology of interest. Hence, in the recent years, GWAS identified hundreds of genetic variations pointing to some known pain genes, but also to a very large number of genes, whose functional connections to pain pathways are not entirely clear (Young et al. 2012; Zorina-Lichtenwalter et al. 2016; Veluchamy et al. 2018; Sutherland et al. 2019; van den Maagdenberg et al. 2019). Therefore, a large set of candidate human pain-associated genes needs to be characterized.

Because of the complexity of human nociception, the limitation in available methodologies, and ethically concerns, animal models are widely used for pain research (Mogil 2009; Burrell 2017). Even if they cannot speak for themselves and report their level of pain, animal avoidance response to noxious stimuli can be reliably and objectively scored (Mogil 2009; Gregory et al. 2013). For this task, rodents are widely used. However, research with these models often involves invasive procedures or requires the use of anesthetics, which may introduce biases by directly or indirectly altering the physiological processes into play (Magalhães-Sant’Ana et al. 2009). The development of mammalian genetic models for specific pain genes is furthermore time-consuming and costly. Invertebrates represent useful alternative models, overcoming many of these limitations (Burrell 2017; Walters 2018).

With a fully mapped nervous system and potent genetic tools, the nematode Caenorhabditis elegans is particularly attractive for neurobiological studies (Corsi et al. 2015). Genetic studies with C. elegans have been extensively used to dissect the molecular and cellular functions in the nervous system, notably those involved in sensory-behavior connections (Bargmann 1993; Hobert 2003; Schafer 2005; Iliff and Xu 2020; Xiao and Xu 2021) and to model human diseases, including neurological conditions (Markaki and Tavernarakis 2010; Calahorro and Ruiz-Rubio 2011; Sin et al. 2014; Cooper and Van Raamsdonk 2018). The molecular factors controlling nociception are remarkably well-conserved from worms to humans, as evidenced, for example, by the involvement of transient receptor potential (TRP) channels (Chatzigeorgiou et al. 2010; Glauser et al. 2011; Liu et al. 2012; Nkambeu et al. 2020), the existence of a cannabinoid signaling system (Oakes et al. 2017; Oakes et al. 2019), or the sensitivity to many known painkiller drugs (e.g. nonsteroidal anti-inflammatory drugs and opiates) (Nieto-Fernandez et al. 2009; Leung et al. 2016). Like humans, worms are innervated by nociceptor neurons and are able to detect a variety of noxious or potentially noxious stimuli to produce avoidance responses, including noxious heat avoidance (Culotti and Russell 1978; Kaplan and Horvitz 1993; Wittenburg and Baumeister 1999; Hilliard et al. 2005; Li et al. 2011; Liu et al. 2012). Worms cannot grow and reproduce at temperatures above 26°C and transient exposure to higher temperatures may produce irreversible damage causing infertility or death. Therefore, worms developed a series of behavioral strategies to avoid noxious heat (Glauser 2013; Schild and Glauser 2013), including acute withdrawal responses. When stimulated with a fast-rising heating stimulus, worms produce a reversal response, which involves a period of backward locomotion facultatively followed by sharp reorientation maneuvers (Wittenburg and Baumeister 1999). Heat-evoked reversal represents a convenient readout of the animal ability to detect and respond to noxious temperature. The reversal response probability depends on a variety of factors, including the intensity and localization of the heating stimuli, but also the past animal experience (Mohammadi et al. 2013; Byrne Rodgers and Ryu 2020). Repeated whole-animal noxious heat stimulations (delivered every 20 s) cause the worm responsiveness to progressively decline over a 1-hour period (Lia and Glauser 2020). This habituation-like adaptation phenomenon represents a simple nociceptive plasticity experimental paradigm.

The main goal of this study was to evaluate the potential of using C. elegans thermal nociception as an experimental system to study if and how recently identified human pain-associated genes control nociception and its plasticity in vivo. To that end, we identified worm orthologs for a set of candidate human pain genes and tested 109 available worm mutant lines by quantifying thermal avoidance using a recently established semi-automated, computer-assisted system (Lia and Glauser 2020). We focused on three main phenotypic aspects: (1) the spontaneous reversal rate, assessed in the absence of heat stimuli, (2) the thermal sensitivity of the worms, assessed with a series of heat stimuli of raising intensities, and (3) the nociceptive plasticity, assessed by comparing the responsiveness of naïve (unstimulated) animals and adapted animals (submitted to a train of repeated heat stimulation). Thirty mutants (out of 109) displayed defects on one or more aspects as compared to the wild type and could be clustered in distinct phenotypic classes, highlighting their distributed functions to regulate, spontaneous reversal rate, naïve thermosensitivity, and nociceptive plasticity. We conclude that thermal nociception in C. elegans represents a promising in vivo system to study the role of several human pain genes. Thanks to the many efficient tools available in this genetic model, our results set the ground for further studies in C. elegans to accelerate the research on these poorly understood pain-related genes before follow-up studies in vertebrate models.

Material and methods

Identification of C. elegans orthologs for human pain-related genes and mutant lines

Several review articles (Foulkes and Wood 2008; Young et al. 2012; Zorina-Lichtenwalter et al. 2016) and the Pain Research Forum platform (www.painresearchforum.org/resources/pain-gene-resource accessed July 2017) were used to determine a list of human pain-related genes. The resulting gene list was then submitted to Biomart (www.ensembl.org/info/data/biomart/index.html accessed July 2017) to recover the Ensembl Gene (ENSG) identifiers for 201 human pain genes. Those identifiers were then used in the Ortholist online tool (www.greenwaldlab.org/ortholist/ accessed July 2017) in order to recover C. elegans orthologs (Shaye and Greenwald 2011). Out of those 201 human pain genes, 89 did not have an ortholog in the C. elegans genome, 68 had a single ortholog and 44 had more than one ortholog, resulting in a list of 264 orthologs of human pain genes in C. elegans. 123 mutants were available from the Caenorhabditis Genetics Center (CGC), but only 109 were used in the behavioral screen after removing lines with severely uncoordinated locomotion or extremely slow growth. When possible, mutants already backcrossed were ordered. Supplementary File 1 presents the list of human genes considered, the worm orthologs identified and the mutants tested.

Overview of the system used for heat stimulations and reversal analysis during the screen

For the behavioral screen, we used a previously developed system for the delivery of heat stimuli, the video recording of animal behavior, and the computer-assisted analysis of reversal behavior, which has been described by Lia and Glauser in a detailed methodological article (Lia and Glauser 2020). Briefly, the system is composed of two separate platforms, which are used to analyze populations of worms (up to ∼150 animals) crawling on a 6-cm diameter nematode growth medium (NGM) petri dish, here-below referred to as worm plate. The first platform, named INFERNO (for infrared-evoked reversal analysis platform) was used to quantify spontaneous reversal rate (in the absence of acute heat stimuli) and heat-evoked reversals (determining thermal sensitivity). The INFERNO platform is composed of (1) a temperature-controlled aluminum support plate, on which one worm plate is deposited and which cools down the worm plate to return to baseline temperature in-between stimulations, (2) four infrared lamps able to deliver temporally controlled heat stimuli at 100, 200, 300, or 400 W over the whole worm plate area, (3) an oblique light emitting diode (LED)-based illumination system for dark-field illumination, and (4) a macrozoom linked camera for video recording of behavior at the worm population scale. Behavioral movies are analyzed using the Multi-Worm tracker (Swierczek et al. 2011) and a custom-written python script to flag reversal events (see details below). The second platform, named ThermINATOR (for thermal adaptation multiplexed induction platform) was used during habituation protocols, to deliver repeated acute heat stimulation on multiple worm populations in parallel (up to 18 worm plates). Worm plates are deposited on a large temperature-controlled aluminum plate and repeated heat stimuli are delivered by a rack of over-hanging infrared (IR) lamps. In both platforms, the heat delivery is controlled via a Raspberry Pie-based system and custom Python scripts.

Overview of phenotype measures during the screen

During the screen, a worm plate containing worms from the same genotype, which had never been stimulated with heat (corresponding to the naïve condition), was first placed in the INFERNO to quantify spontaneous reversals (during a baseline period in the absence of heat stimuli) and heat-evoked reversals during a short series of four heat stimuli of graded intensities. The worm plate was then placed in the ThermINATOR for 10 minutes of repeated heat stimulation and transferred in the INFERNO for a second recoding with the same measures (adaptation time t = 10 min). Then, the worm plate was returned to the ThermINATOR for another 30 min and transferred one last time in the INFERNO for the last set of measures (adaptation time t = 40 min). The screen unfolding is schematically summarized in Fig. 1a and described in more detail below.

Fig. 1. Scoring procedure for heat-evoked reversal sensitivity/adaptation and wild type animal responses. a) Schematic of the reversal behavior scoring procedure. Each plate containing a worm population was scored for spontaneous reversals (heat stimuli = 0 W) and thermal sensitivity (heat stimuli from 100 to 400 W) at 3 different time points: t = 0 (naïve animals), t = 10 min (early adaptation), and t = 40 (late adaptation). b–f) Behavioral response of wild type animals (N2) prior to (t = 0), after 10 min (t = 10), and after 40 min (t = 40) of repeated heat stimulations. n = 138 assays, each scoring at least 50 animals. b) Spontaneous reversal rate (in the absence of heat stimulus) before and during adaptation. A one-way ANOVA followed by Bonferroni post hoc tests showed a significant, progressive decrease during the adaptation period. *P < 0.01 vs the other two time points. c) Heat dose-response before and during adaptation. Data as means ± s.e.m. (error bars are smaller than the data marks). A two-way ANOVA revealed significant main effects of the heat level and of the adaptation time, as well as a significant heat level × adaptation time interaction effect. *P < 0.01 vs 0 W; ##P < 0.001, and #P < 0.01 vs same condition at t = 0 by Bonferroni post hoc tests. d). Thermal sensitivity in naïve wild type animals (measured at t = 0). Data are fractions of animals producing heat-evoked reversals normalized to the spontaneous reversal rate in the absence of heat stimuli (see Method section). *P < 0.01 vs 0 by 1 sample t-test (with Bonferroni correction for multiple comparisons). e and f) Heat-evoked response adaptation effects after 10 min (e) and 40 min (f), respectively, of repeated stimulations. The adaptation effect calculation includes a normalization to the spontaneous reversal rate immediately before the stimulation train (see Material and Methods section). An Adaptation effect of 0 indicates no change in responsiveness, negative values indicate a decrease (“desensitization”), and positive values an increase in responsiveness (“hypersensitization”). *P < 0.01 vs 0 by 1 sample t-test (with Bonferroni correction for multiple comparisons).

Worm preparation

Adult worms were treated with hypochlorite according to standard protocols and eggs were rinsed twice with M9 buffer, resuspended in M9 buffer, and left for 18 h on a rotator to obtain synchronized L1 larvae. 200–300 L1 larvae were plated onto individual NGM plates seeded with OP50 E. coli. Plates were incubated at 23°C until the worms started laying eggs (44–54 h depending on the strains). After incubation, worms were washed off the plates with distilled water and transferred into 1.5 ml microcentrifuge tubes. They were then washed twice to remove bacterial food. 100–150 worms were transferred onto unseeded NGM plates and left to acclimate in the experiment room for 60 min. The lid was open 3 min before the start of behavioral assays.

Stimulation and video recording with the INFERNO

Each worm plate was gently placed in the INFERNO system and after 20 s, the video recording and the stimulation program were simultaneously started. The stimulation program consisted of a baseline period of 40 s without any heat stimulation (later used to determine spontaneous reversal rate), 4 s with 100 W heating (1 IR lamp turned on), 20 s of interstimulus interval (ISI), 4 s with 200 W heating (2 lamps turned on), 20 s of ISI, 4 s with 300 W heating (3 lamps turned on), 20 s of ISI and 4 s with 400 W heating (4 lamps turned on) as previously described (Lia and Glauser 2020). The evoked thermal changes at the surface of the plate were ∼0.3, ∼0.6, ∼1, and ∼1.4°C/s for each of the four heating powers, respectively. In previous experiments with wild type worm (N2), “dose-response” profiles obtained with this train of 4 stimuli were indistinguishable from profiles in which single heat stimuli were used in separate worm populations (Lia and Glauser 2020). Therefore, short-term adaptation effect taking place during a single 4-stimuli series is negligible and this protocol can provide an estimation of the thermal sensitivity of the worm population. During the stimulation program, worm plates were filmed using a DMK 33U×250 camera and movies acquired with the IC capture software (The Imaging Source), at a 1600×1800 pixel resolution, at 8 frames per second, and the resulting .AVI file was encoded as Y800 8-bit monochrome.

Adaptation protocol

The INFERNO stimulation program described above was applied 3 times: at t = 0 min (naïve animals), t = 10 min (early adaptation), and t = 40 min (late adaptation). Between t = 0 min and t = 10 min and between t = 10 min and t = 40 min, the plate was put under the ThermINATOR system for 10 and 30 min, respectively. The ThermINATOR system was run to trigger an infinitely looping temperature program consisting of 4 s of stimulation, with the IR lamps on, followed by 20 s ISI with the lamps turned off. The thermal change at the surface of the worm plate during each stimulus was ∼1°C/s.

Number of replicates

At least 3 replicates were done per strain, on three different days, always alongside a replicate of N2 (wild-type) as control. For each replicate, between 50 and 100 worms were recorded.

Movie analyses

Movies were analyzed using the Multi-Worm Tracker 1.3.0 (MWT) (Swierczek et al. 2011). The configuration settings were the same as previously described (Lia and Glauser 2020), besides the maximum object size and minimum object size, which were manually set up between 150 and 240 pixels and between 50 and 160 pixels, respectively, to accommodate plate-to-plate variations in object size that were mostly due to the subtle differences in illumination. A custom Python script was used to flag reversal events and report the frame during which they occurred. The movie time course was separated into 4-s bins and the fraction of animals reversing in each bin was extracted as the primary output for subsequent analyses.

Data processing and variable definition

Spontaneous reversal

Spontaneous reversal rate was calculated by averaging the fraction of animals reversing over the 10 bins corresponding to the 40 s baseline period of each movie. Spontaneous reversal rate thus reflects the probability that any worm has to reverse within a 4-s time interval.

Heat-evoked reversals

For each heating power, the reversal rate during stimulation was computed over the 4 s bin corresponding to the stimulation. We reasoned that any reversal measured during the stimulation period could either be a spontaneous reversal or a heat-evoked reversal. We calculated the heat-evoked reversal rate as a normalized value compensating for the contribution of spontaneous reversal events that would occur during the stimulation period independently of the stimulation:

heat-evoked reversal rate = (reversal rate during stimulation − spontaneous reversal rate)/(1−spontaneous reversal rate)

This normalization can compensate for day-to-day, plate-to-plate and genotype-to-genotype variability in the spontaneous reversal rate, in order for the normalized metrics to best reflect the impact of the heat stimuli. We nevertheless considered that this normalization cannot compensate for extremely high spontaneous reversal rates and genotypes with a spontaneous reversal rate >50% were excluded from the heat-evoked response analyses.

Adaptation effect

The magnitude of the adaptation effect was assessed for each of the four heating levels by comparing the normalized heat-evoked response at t = 10 and t = 40, respectively, with the naïve response level at t = 0. Hence, the adaptation effects at t = 10 and t = 40, respectively, were calculated as follows:

Early adaptation effect = (heat-evoked reversal rate at t = 10) − (heat-evoked reversal rate at t = 0)

Late adaptation effect = (heat-evoked reversal rate at t = 40) − (heat-evoked reversal rate at t = 0)

An adaptation effect of 0 indicates no change in responsiveness, negative values indicate a decrease (“desensitization”), and positive values an increase (“hypersensitization”) in responsiveness.

Data aggregation for low and high heat stimuli

A total of 15 primary variables were thus defined and analyzed: 3 variables measuring the spontaneous reversal rate and its evolution during habituation (spontaneous reversal rate at t = 0, 10, and 40 min, respectively), 4 variables measuring naïve animal thermal sensitivity (heat-evoked reversal rate at t = 0 for 100, 200, 300, and 400 W heating power, respectively), 4 variables measuring the early adaptation (early adaptation effect for 100, 200, 300, and 400 W heating power, respectively) and 4 variables measuring the late adaptation (late adaptation effect for 100, 200, 300, and 400 W heating power, respectively). Results of principal component analyses (PCA) and hierarchical cluster analyses (see Results section) a posteriori led us to present the data aggregated for low heat (100 and 200 W) and high heat (300 and 400 W), respectively. The aggregation was performed by averaging the values between the two heat levels on a plate-by-plate basis, resulting in 6 secondary variables (heat-evoked reversal rate at low heat, heat-evoked reversal rate at high heat, early adaptation effect at low heat, early adaptation effect at high heat, late adaptation effect at low heat, late adaptation effect at high heat).

Statistical analyses

ANOVAs were conducted for each of the 15 primary variables to test for the impact of genotypes. Post hoc tests were used to compare each of the 109 mutants with wild type (N2) using Bonferroni–Holm correction for multiple testing. We did not perform all the possible comparisons between all the mutants. Raw data from the screen and uncorrected P-values are reported in Supplementary File 1. Thirty mutants showing at least one test with a corrected P < 0.05 were retained for further analyses, including PCA and hierarchical cluster analyses performed with the ClustVis online tool (Metsalu and Vilo 2015). We used the same statistical approach when comparing the secondary variables aggregating low and high heat levels, respectively. Genetic interactions were assessed using two-way ANOVAs with each mutation as a factor (2 levels: wild type or mutant) and followed by Holm–Bonferroni post hoc tests; P-values are reported directly in the corresponding figures.

Fig. 2. Clustering of behavioral parameters that are under similar genetic control. a) PCA of the screen data for 30 mutants displaying at least one parameter significantly different from wild type. Projections in the space of the first 3 principal components (PC1, PC2 and PC3), with % of variance, explained indicated on the axis labels. b) Hierarchical clustering analysis (Euclidean distance) using the same dataset. Five groups of behavioral parameters that coherently varied across the mutants are highlighted with the same color code and labeled within the figure (a and b).

Fig. 3. Spontaneous reversal rate and its adaptation in mutants for C. elegans orthologs of human pain genes. Evolution of the mean spontaneous reversal rate in the indicated genotypes before any heat stimulation, and after 10 and 40 min, respectively, of repeated heat stimulation (as depicted in Fig. 1a). Wild type (N2) data correspond to data in Fig. 1b. Of 18 mutants significantly different from wild type, 2 had reduced spontaneous reversal rate (a), 7 had an increased spontaneous reversal rate but a maintained plasticity (b), 4 had increased spontaneous reversal rate with blunted adaptation (c) and 5 displayed an abnormal adaptation without a significant increase at t = 0 (d). Note the different vertical axis scales across panels.

Results

Spontaneous reversal, thermal sensitivity, and adaptation assessment in wild type animals

In order to screen for thermal avoidance sensitivity/adaptation abnormalities in C. elegans mutants, we set up a scoring procedure using previously established semi-automated platforms enabling the high throughput analysis of synchronized adult worm populations (Lia and Glauser 2020). The scoring procedure is schematically described in Fig. 1a. The spontaneous reversal rate and thermal sensitivity of worm populations were assessed at the beginning of the procedure (naïve animal, t = 0), as well as after 10 minutes (t = 10), and 40 minutes (t = 40) of exposure to repeated heat stimulations. Figure 1b–f presents the wild type (N2) animal responses scored during the present study (n = 138 wild type worm populations). This dataset recapitulated all previously published observations (Lia and Glauser 2020), notably regarding the thermal sensitivity of naïve animals (Fig. 1d), as well as the decreased spontaneous reversal rate (Fig. 1b) and the thermal responsiveness adaptation effect caused by repeated stimulations (Fig. 1c, e and f).

Overview of the phenotypic spectrum over 109 mutants for human pain gene orthologs

A set of 201 human genes associated with various pain conditions was retrieved from a variety of published genetic studies (see Supplementary Methods and File 1) (Young et al. 2012; Zorina-Lichtenwalter et al. 2016; Veluchamy et al. 2018; Sutherland et al. 2019; van den Maagdenberg et al. 2019). These candidates included some well-studied pain condition-causing genes, but also a large number of candidate genes whose connection to pain regulation is less understood. We retrieved 109 pre-existing mutants from the Caenorhabditis Genetic Center (CGC, Supplementary File 1). Most mutants are predicted loss-of-functions. In addition, the tested mutant set included mutant lines for the N-methyl-D-aspartate (NMDA)-type glutamatergic receptor-1 and -2 (nmr-1 and 2) genes, previously shown to control experience-evoked behavioral plasticity in C. elegans (Kano et al. 2008) and, as positive controls, three alleles of the calcium/calmodulin-dependent protein kinase-1 gene, cmk-1, previously characterized for its role in noxious heat avoidance plasticity (Schild et al. 2014; Lia and Glauser 2020; Ippolito et al. 2021). cmk-1(ok287) and cmk-1(oy21) are loss-of-function alleles (Satterlee et al. 2004), whereas cmk-1(pg58) is a gain-of-function allele causing CMK-1 subcellular mislocalization and presumably preventing a full inactivation of the kinase in the absence of Ca2+/CaM binding (Schild et al. 2014).

These 109 mutant lines were scored using the protocol described in Fig. 1a and their responses were compared to those of wild type animals. We focused on a set of 15 parameters: three parameters defining spontaneous behavioral rates (at t = 0, 10, and 40 min of adaptation, respectively); four parameters related to naïve thermal sensitivity (heat-evoked reversal rate increase at t = 0 for 100, 200, 300, and 400 W stimuli); four parameters reflecting the early adaptation effect at t = 10 (for the response to 100, 200, 300, and 400 W, respectively); and four parameters reflecting the late adaptation effect at t = 40 (for the response to 100, 200, 300, and 400 W, respectively). ANOVAs, followed by post hoc tests comparing every mutant with wild type and including a Holm–Bonferroni correction for multiple comparisons, revealed a set of 30 mutants (with a mutation in 28 different genes) showing a significant difference for at least one of the 15 analyzed parameters. These 30 mutants include nmr-2, the 3 cmk-1 alleles used as positive controls, as well as 26 additional mutants. The remaining 79 mutants, for which no significant difference with wild type was detected, were not further analyzed in this study. However, it is important to keep in mind that we cannot rule out more subtle phenotypes in these mutants and that it is possible that the affected genes are implicated in other types of nociceptive sensitivity/adaptation phenomenon in C. elegans.

Next, a PCA was conducted to analyze the overall impact of these 30 relevant mutations and the potential interrelationships between the 15 behavioral parameters. Figure 2a presents a plot of the 15 behavioral parameters in the space of the three first principal components (PC1, 2, and 3, explaining 30, 20, and 12% of the total variance, respectively). The parameter distribution formed five clusters, which were similarly highlighted with a hierarchical clustering analysis (Fig. 2b). These clusters are related to (1) spontaneous reversals, (2) low heat response in naïve animals, (3) high heat response in naïve animals, (4) late adaptation effect on high heat response, and (5) other adaptation effects (forming a less compact cluster). Taken together, these analyses point to several discernable groups of related parameters, which are co-regulated across the set of 30 nociception gene candidates. Of note, low-heat stimuli (100 and 200 W) and high heat stimuli (300 and 400 W) formed respective clusters, which prompted us to pool them in subsequent analyses. Furthermore, these results suggest that our dataset could be used to decipher the task distributions among these genes. The next subsections will present in more details how specific behavioral components are impacted in this set of 30 mutants.

Fig. 4. Thermal sensitivity in mutants for C. elegans orthologs of human pain genes. Reversal response in animal populations of the indicated genotype that were stimulated with a train of four stimuli of graded heating power at 100, 200, 300, and 400 W. Data were grouped as low heat (100 and 200 W, a) and high heat stimuli (300 W and 400 W, b). Heat-evoked reversal rate was calculated after normalization with baseline reversal rate in the pre-stimulus period (see Methods section). n ≥ 3 plates, each containing more than 50 animals. *P < 0.01 vs N2 by Holm–Bonferroni post hoc tests performed on the entire strain set used in the screen (n = 109 strains).

Mutations affecting the spontaneous reversal rate

Before analyzing the response directly triggered by acute noxious stimuli in human pain-gene orthologs, we first evaluated how these mutations affect spontaneous reversals. The rate of spontaneous reversals in wild type animals is affected by the exposure to repeated heat stimulations, progressively decreasing from about 22% of animals reversing in any 4-s time windows before adaptation at t = 0, to values below 10% at t = 40 (Fig. 1b). In total, 18 mutants presented some alterations in spontaneous reversal rates at one or more adaptation timepoints (Fig. 3).

Fig. 5. Habituation to repeated heat stimuli in mutants for C. elegans orthologs of human pain genes. Animal populations of the indicated genotype were exposed to repeated noxious heat stimuli, and their heat-evoked reversal responses were scored after 10 min (early adaptation, a and b) and 40 min (late adaptation, c and d) as described in Fig. 1e and f. Data were grouped as low heat (100 and 200 W, a, c) and high heat stimuli (300 W and 400 W, b, d). n ≥ 3 plates, each containing more than 50 animals. *P < 0.01 vs N2 by Holm–Bonferroni post hoc tests performed on the entire strain set used in the screen (n = 109 strains).

Two mutants (lgc-11 and twk-7) displayed significantly decreased reversal rates as compared to wild type, already before any stimulation (Fig. 3a). However, the adaptation treatment was still able to produce a significant decrease (Supplementary Fig. 1a). These data suggest that these two mutants display a constitutively lower spontaneous reversal rate, but retain the ability to produce a relative decrease in response to repeated heat stimulations over 10–40 minutes.

Eleven mutants displayed significantly increased spontaneous reversal rates before any stimulation, the magnitude of this effect varying broadly across them (Fig. 3b and c). For 7 mutant lines, repeated stimulations could still produce a relative reduction in spontaneous reversal rate at t = 40 min (ckr-1, unc-2, wnk-1, fut-3, sptl-1, sma-2, and nmr-2; Fig. 3b and Supplementary Fig. 1b). The adaptation effect was not always significant at t = 10 min (Supplementary Fig. 1b). In contrast, for the remaining four mutants (unc-64, cyp-33E1, unc-43, and sup-9), we could not detect a significant decrease in spontaneous reversal rate after repeated heat stimulations (Fig. 3c), suggesting a constitutively increased, nonadaptable spontaneous reversal rate in these mutants.

Finally, 5 mutants with a normal spontaneous reversal rate at t = 0, either failed to adapt in response to repeated heat stimulations (cmk-1(ok287), cmk-1(oy21), cmk-1(pg58), and sptl-2) or produced the opposite response with a dramatic increase in spontaneous reversal rate (twk-18, Figs. 3d and Supplementary Fig. 1c).

Collectively, these data indicate that the spontaneous reversal rate and its adaptability are controlled by genetically separable molecular pathways.

Mutations altering heat-evoked reversals in naïve animals

Next, we examined how mutations impact the thermal sensitivity of the heat-evoked reversal response in naïve animals (t = 0). We used the same 4-heat level stimulation protocol, which in wild type produces a graded response from 100 to 400 W (Fig. 1d). Mutants with markedly elevated spontaneous reversal rate were excluded from the analysis, as heat-evoked reversal could not be reliably compared to that in wild type. Seven out of the remaining 23 mutants displayed alterations as compared to wild type in response to either low-heat stimuli (100 and 200 W, Fig. 4a) or high heat stimuli (300 and 400 W, Fig. 4b).

Four mutations (the three alleles of cmk-1, and the fut-4 mutation) caused increased responsiveness. This effect was only significant for low-heat stimuli (Fig. 4a), but not for high heat stimuli (Fig. 4b), which suggests a shifted thermal sensitivity in these mutants. On the opposite, three mutations decreased the responsiveness of naïve animals. For two mutants (fut-6, twk-7), the decrease was only apparent at high heat levels (Fig. 4b), while for the last one (cat-4), the effect was observed at all heat levels (Fig. 4a and b).

Overall, the analysis of the thermal avoidance response in naïve worms carrying mutations for human pain gene orthologs suggests that several of them control either positively or negatively the responsiveness to noxious stimuli in previously unstimulated, naïve animals.

Mutations altering the adaptation to repeated heat stimulations

Our next goal was to address the nociceptive plasticity in mutants for human pain gene orthologs. We, therefore, analyzed the impact of repeated heat stimulations on the responsiveness to heat stimuli, which in wild type causes a progressive adaptation (Fig. 1c). The two adaptation timepoints at t = 10 (early adaptation, no significant effect in wild type, Fig. 1e) and t = 40 (late adaptation, significant effect in wild type, Fig. 1f), were chosen in order to be able to highlight both enhanced and dampened adaptation phenotypes. Overall, we identified 17 mutant lines showing an adaptation alteration as compared to wild type. Data are presented in Fig. 5, showing the early and late adaptation effects for low heat and high heat responsiveness, respectively.

An enhanced adaptation phenotype was observed in eight mutants (Fig. 5, more negative values). In 4 of these mutants, the adaptation was faster (significantly different already at t = 10) and stronger (still significant at t = 40). The most pervasive phenotype was observed in the cmk-1(pg58) gain-of-function mutants, which produced a faster and stronger adaptation for both low and high heat stimuli (Fig. 5a–d). These effects were observed only for high heat stimuli in dat-1 and pgq-8 mutants (Fig. 5b and d) and for low-heat stimuli in fut-4 mutants (Fig. 5a and c). In the four remaining mutants, an enhanced adaptation was seen only at t = 10 for low heat (nmr-2, Fig. 5a) or for high heat stimuli (tbh-1, glr-1, npr-24, Fig. 5b), respectively. The magnitude of the adaptation effect in these mutants was not further decreasing at t = 40, and was not different from that in wild type anymore. These observations suggest that nmr-2, tbh-1, glr-1, and npr-24 mutations selectively accelerate the response decrease during the early phase of adaptation.

A down-regulated adaptation phenotype was observed in 9 mutants (kcnl-1, dao-3, dbl-1, fut-3, fut-6, nmr-2, ocr-2, twk-7, and wnk-1). These mutants all failed to decrease their responsiveness to high heat stimuli in response to repeated stimuli, which is the hallmark of the thermal nociceptive plasticity in wild type (purple shade in Fig. 5).

Finally, a reverted adaptation phenotype was observed in one mutant, cat-4. Indeed, in contrast to the “desensitization” effect observed in wild type, cat-4 mutants developed a slightly increased responsiveness upon repeated noxious heat stimulations. This effect was only observed for low-heat stimuli, which suggests an enhanced thermal sensitivity triggered by repeated stimulations.

Overall, our data show that genetic alterations among human pain gene orthologs can produce a broad spectrum of nociceptive adaptation abnormalities in C. elegans, with several genes modulating specific aspects of the nociceptive plasticity phenomenon.

Screen validation with additional alleles

Whereas most mutants tested in our screen had been outcrossed several times with wild type, specific phenotypes might be caused by uncharacterized side mutations. In order to validate the screen results, we recovered 10 additional alleles available from the CGC for 8 hit genes (1 allele for dbl-1, fut-3, sup-9, tbh-1, unc-43, unc-64 and 2 alleles for ocr-2 and unc-2). We could recapitulate most phenotypes: the spontaneous reversal rate phenotypes for fut-3, sup-9, unc-2, unc-43, and unc-64 (Supplementary Fig. 2) and the adaptation phenotypes for dbl-1, tbh-1, and fut-3 (Supplementary Fig. 3). The only one exception was the adaptation defect of ocr-2(ak47), which was not present in ocr-2(ok1711) and ocr-2(yz5) animals. A similar discrepancy was recently reported between animals carrying these alleles (Davis et al. 2023), and further evidence indicated that the phenotype in ocr-2(ak47)-containing animals was due to an unknown side mutation. In summary, our validation experiments could confirm the phenotypes for the majority of the genes tested, but the ocr-2 example highlights the importance of such validation experiments.

Genetic interactions between cmk-1, fut-4, and cat-4

In order to start characterizing potential genetic interactions within the network of genes controlling thermal nociception and its plasticity, we carried out epistasis analyses with double mutants. We first focused on the interaction between cat-4 and cmk-1, as an opportunity to test the potential connections between intracellular CaM kinase signaling (altered in cmk-1 mutants) and extracellular communication via three key monoamines (dopamine, octopamine, and serotonin, whose production is defective in cat-4 mutants) (Chase and Koelle). These mutations were also interesting as they combine opposite impacts on different behavioral parameters and allele-specific effects caused by cmk-1(ok287) loss-of-function and cmk-1(pg58) gain-of-function, respectively. On the one hand, animal naïve sensitivity was reduced by the loss of cat-4, but enhanced by both gain and loss of cmk-1 function (Fig. 4). On the other hand, adaptation was impaired by the loss of cat-4 (in particular for low-heat stimuli, Fig. 5a and c), left unchanged by the loss of cmk-1, but enhanced by the gain of cmk-1 function (for both low and high heat stimuli, Fig. 5).

Regarding the thermal sensitivity of naïve animals and the adaptation of the response to low-heat stimuli, we found no genetic interaction between cat-4 and cmk-1(pg58) (Fig. 6a and b), but that cmk-1(ok287) was epistatic to cat-4 (Fig. 6d, right and Fig. 6e). These results suggest (1) that an aberrant activity of CMK-1 (in cmk-1(pg58)) can increase naïve sensitivity and favor adaptation independently of dopamine/octopamine/serotonin production, (2) that the lack of dopamine/octopamine/serotonin production can increase naïve sensitivity and prevent the adaptation effect even when CMK-1 is aberrantly activated, but (3) that the lack of dopamine/octopamine/serotonin production cannot increase naïve sensitivity or prevent adaptation when CMK-1 is defective. These elements suggest that cat-4 might act upstream of cmk-1 in the genetic pathway controlling the sensitivity of naïve animals and the adaptation of the response to low-heat stimuli.

Fig. 6. Genetic interaction between cmk-1 and cat-4. Heat-evoked reversal response in naïve animals (a) and habituation to repeated heat stimuli (b) quantified and reported as in Figs. 2 and 3, respectively. Low-heat stimuli (100–200 W); high heat stimuli (300–400 W); early adaptation (t = 10 min); late adaptation (t = 40 min). Some wild type and cat-4 single mutant data are reused across plots. n < 6 plates, each with more than 50 animals. For each comparison, we performed a two-way ANOVA with each mutation as a factor (2 levels: wt or mutant) and reported the P-values for the main effects and the interaction effect at the top of each plot. For comparisons showing significant or nearly significant interaction effects, we performed Holm–Bonferroni post hoc tests and indicated relevant significance levels on each plot.

Regarding the adaptation of the response to high heat stimuli, neither cat-4 nor cmk-1(ok287) alone or in combination had an effect (Fig. 6f). However, the strong adaptation effect caused by cmk-1(pg58) was blocked in a cat-4 null background (Fig. 6c). These data suggest that neither CMK-1 signaling, nor dopamine/octopamine/serotonin signaling pathways are required for the adaptation of the response to high heat stimuli, but that the aberrant CMK-1 signaling in cmk-1(pg58) works via dopamine, octopamine, and/or serotonin signaling. It is possible that the cmk-1(pg58) allele might favor adaptation of the high heat response by activating a monoamine-dependent pathway, which is normally only engaged to promote the adaptation of the response to low-heat stimuli.

Finally, we evaluated the genetic interaction between fut-4 and cat-4 loss-of-function mutations. In single mutants, the loss of cat-4 reduced the reversal response to low-heat stimuli in naïve animals, whereas the loss of fut-4 increased it. We found that the double mutant had an intermediate response level (Supplementary Fig. 4a), suggesting that the two mutations act independently of each other to control this phenotype. Regarding the adaptation to repeated stimuli, the loss of cat-4 enhanced adaptation, whereas the loss of fut-4 impeded adaptation (Fig. 5). We found that the cat-4; fut-4 double mutant behaved like fut-4 (Supplementary Fig. 4b), suggesting that cat-4 might act upstream of fut-4 in the genetic pathway controlling adaptation.

Taken together, the results of epistasis analyses between, cat-4, cmk-1, and fut-4, indicate that these genes are part of partially connected genetic pathways controlling specific aspects of the thermal nociceptive response and its plasticity.

Discussion

The recent discovery of numerous pain-associated genes in human calls for fundamental research on their biological function in the nociceptive pathway. The value of invertebrate models to address the molecular mechanisms controlling nociception and associated plasticity mechanisms is now well-established (Komuniecki et al. 2012; Mills et al. 2012; Burrell 2017). Leveraging a high-throughput thermal avoidance behavior quantification pipeline in C. elegans, we screened here for defects in mutants for human pain-associated gene orthologs. We successfully identified dozens of mutants, which supports the notion that these genes have a conserved function in regulating nociception and which provides experimental entry points for further studies in C. elegans. Furthermore, because of the relatively large number of mutants and the distributed phenotypes, our study provides insight into the underlying genetic network.

A network of conserved pain-related genes

Overall, the distribution of phenotypes across the different human pain-related gene mutants tested in our screen indicates that distinct phenotypic traits are controlled by genetically separable pathways. Indeed, even when considering only four general phenotypes (spontaneous reversal before adaptation, spontaneous reversal adaptation effect, heat-evoked reversal before adaptation, heat-evoked reversal adaptation effect), we could highlight 15 different effect combinations (Supplementary Fig. 5). These can be further categorized in seven main mutation groups: (1) mutations selectively affecting spontaneous reversal in naïve animals, (2) mutations affecting spontaneous reversals in naïve animals and heat-evoked reversal adaptation, (3) mutations affecting spontaneous reversals in naïve animals as well as heat-evoked reversals prior and after adaptation, (4) mutations selectively affecting spontaneous reversal adaptation, (5) mutations affecting spontaneous reversal adaptation and heat-evoked reversals, (6) mutations affecting naïve heat-evoked reversals and adaptation, and (7) mutations selectively affecting heat-evoked reversal adaptation (Supplementary Fig. 5). The existence of mutations selectively affecting spontaneous reversals in naïve animals, the adaptation of spontaneous rate and the adaptation of heat-evoked reversals, respectively, suggests that the underlying processes are controlled by genetically separable molecular pathways. We have not identified at this stage any mutant selectively affecting the thermal sensitivity of the heat-evoked response in naïve animals, without also affecting the adaptation processes. fut-4 or cmk-1(pg58) mutations, which increased the naïve thermal sensitivity, also caused a corollary increased “desensitization” adaptation effect. Conversely, mutations reducing the naïve thermal sensitivity (cat-4, fut-6, and twk-7) also reduced the heat-evoked response adaptation. These observations are in line with a simple model in which the thermal sensitivity state in naïve animals will contribute to determine the magnitude of the adaptation effect upon repeat acute stimulations. We also note that the adaptation of the stochastic spontaneous reversal response and of the deterministic heat-evoked reversal responses is controlled by largely nonoverlapping sets of genes. Only cmk-1(pg58) affected both adaptation processes, but this mutation had an opposite impact on each of them. Hence, these two adaptation processes are largely uncoupled. Considering these observations, we proposed a working model of the architecture of the genetic network controlling spontaneous and heat-evoked reversal responses and their plasticity (Fig. 7).

Fig. 7. Schematic of the genetic network controlling spontaneous and heat-evoked reversal and their adaptation to repeated stimuli. Dark gray boxes and arrows: biological processes. Pale blue boxes: gene clusters. Arrows connecting genes to phenotypes: proposed effects on the different biological processes, including both positive and negative effects.

Separable genetic pathways control specific phenotypic aspects of the reversal response

Our results are in line with those of a previous multiparameter behavioral profiling analysis in C. elegans, which characterized the heat-evoked response of wild type and 47 mutant or transgenic strains (Ghosh et al. 2012). This previous study highlighted that thermal nociception is controlled by a rich set of molecular players, that some mutations have a pleiotropic impact, and also showed that the response to different heating levels was controlled by distinct genetic pathways. Our study with a different setting and a different set of mutants expands on these previous findings to integrate plasticity aspects and highlight the suitability of the worm model to study conserved human pain genes. Furthermore, our small-scale epistasis analysis with three double mutants demonstrates the feasibility of using our experimental setup to further characterize genetic interactions within these conserved human pain genes in C. elegans.

Reversal behavior is known to reflect the integration of information from numerous modalities reflecting the internal state of the organism and external cues (Zhao et al. 2003; Summers et al. 2015). Interestingly, we found that spontaneous reversals and heat-evoked reversals are regulated by largely nonoverlapping sets of genes, and it is particularly the case during habituation to repeated heat-evoked stimuli. This could potentially be explained by the involvement of different neuronal (sub-)circuits for the elicitation of spontaneous vs heat-evoked reversals, or by the existence of distinct plasticity loci within the neuronal circuit. Multiple parallel interneuron pathways can control the occurrence of spontaneous reversal induction (Piggott et al. 2011). Interestingly, all of them are postsynaptic to the known worm thermosensory neurons responsible for heat-evoked reversals (White et al. 1986; Liu et al. 2012; Schild and Glauser 2015; Kotera et al. 2016). Additional studies will be needed to decipher how the genetic pathways revealed in our screen affect the function of this circuit.

Thermal nociception gene product molecular/cellular functions

The products of many genes identified in our screen can be gathered according to their molecular/cellular functions. A first group includes several genes coding for transmembrane proteins important for synaptic and/or extra-synaptic communication: the presynaptic voltage-gated ion channel UNC-2, the SNARE protein UNC-64/syntaxin controlling exocytosis, the ionotropic glutamate receptors GLR-1, and NMR-2, the cholecystokinin receptor-1 (CKR-1), which was recently shown to bind the NLP-18 neuropeptide in order to qualitatively modulate worm escape response, the somatostatin receptor NPR-24 and the uncharacterized ligand-gated ion channel LGC-11, potentially acting as neuropeptide/neurotransmitter receptors (Ogawa et al. 1998; Brockie and Maricq 2006; Gracheva et al. 2008; Kim et al. 2018; Chen et al. 2022).

A second group includes proteins controlling neuron excitability: the WNK-1 kinase known to orchestrate Na+, K+, and Cl− homeostasis by acting on multiple transporters and channels (Goldsmith and Rodan 2023), as well as 4 K+ channels SUP-9, TWK-7, TWK-18, and KCNL-1, which might contribute to hyperpolarize neuronal membranes. Potassium channels are considered as promising future targets for the pharmacological treatment of pain (Tsantoulas and McMahon 2014). Because mutations in these potassium channels produce very different phenotypes in our study, it is possible that they work in a different part of the neuronal circuits controlling spontaneous reversal, heat-evoked reversal, and their adaptation in C. elegans.

A third group of mutants affects monoamine signaling: cat-4, lacking a cofactor needed for the biosynthesis of octopamine, dopamine, and serotonin, dat-1, deficient for dopamine transmission, and tbh-1, which is required for octopamine biosynthesis (Chase and Koelle). We found that dat-1 and tbh-1 mutants display a faster heat-evoked adaptation, which suggests that dopamine and octopamine signaling normally acts to slow down adaptation. In contrast, cat-4 mutants instead show a transient sensitization, which was dependent on CMK-1 signaling. A possible explanation would be that serotonin might have an opposite effect (accelerating the adaptation process), and that the lack of serotonin might predominate in the cat-4 mutants, in a situation where all three monoamines are lacking. These monoamines were all previously reported to modulate C. elegans aversive response to other type of nociceptive stimuli (Wragg et al. 2007; Harris et al. 2011; Ardiel et al. 2016; Ezcurra et al. 2016). Future studies with additional mutants in the monoamine synthesis/signaling pathways should be clarifying the role played by these different communication pathways in the context of thermal nociception.

Finally, the molecular functions of several gene products present no obvious direct connection to the regulation of thermal nociception by the nervous system and their potential mode of action remains very open. This is notably the case for two transforming growth factor beta signaling pathway components, the DBL-1 ligand and the SMA-2 transcription factor, for the cytochrome P450 family predicted oxidoreductase CYP-33E1, the predicted ATP-binding cassette transporter PGP-8, the predicted methenyltetrahydrofolate cyclohydrolase DAO-3, the sphingolipid biosynthetic enzymes SPTL-1 and SPTL-2, as well as the FUT-3, -4, and -6 fucosyl transferases, which are further discussed in a section below.

Screen limitations

One of the main limitations of our screen is that we only tested one strain for the majority of the candidates. When performing validation experiments with additional alleles for 8 genes, we could validate 7 of them, leaving one case (ocr-2) where one or more unidentified side mutations most likely caused the phenotype observed in the screen. This illustrates the need for additional validation on a case-by-case basis, before deeper follow-up analyses. Another limitation of our screen is that we had to set aside some uncoordinated mutants and some mutants with a high spontaneous reversal rate whose scoring was impractical. The outcome of the screen could have been different with different growth conditions (temperature, age), or different treatment before and/or during recordings (e.g. food availability, worm handling procedure, worm density) since these parameters are susceptible to alter worm behavior. Also, it is important to keep in mind that the negative hits on the screen could still present more subtle phenotypes related to thermal nociception not covered by the set of measured parameters or present defects in the response to other types of noxious stimuli.

Perspectives on the modeling of human pain-related genes

While keeping these different caveats in mind, we think the outcome of our screen is interesting, as it points to specific mutants that can serve as entry points to model nociceptive defects caused by genetic alterations in conserved pain-related genes, whose role in the etiology of pain conditions is poorly understood. For example, how a polymorphism in the FUT9 gene, coding for a fucosyl transferase-9, can predict chronic migraine conditions is an enigma (Anttila et al. 2013). FUT9 is a α-3-fucosyl transferase that participates in the process of protein glycosylation and, in human, is abundantly expressed in tissues of the digestive tract as well as in the brain. In the nervous system, protein glycosylation plays a role in neuron migration, neurite outgrowth, and fasciculation, as well as synapse formation and plasticity (Kleene and Schachner 2004). Considering the wide spectrum of glycosylated proteins, the complex pathophysiology of migraine conditions, and the plethora of candidate pathways, deciphering the underlying FUT9-dependent mechanisms is not a trivial task, which would clearly benefit from a simple animal model. Nematode glycosaminoglycans show strong similarities with those in human, and there is a large conservation of the proteins involved in the assembly, processing, and modification of a variety of glycan structures, including fucosyltransferases that catalyze the final step in the synthesis of fucosylated glycoconjugates (Berninsone). Five homologs of the human FUT9 gene were delineated in C. elegans, fut-1, -3, -4, -5, and -6. We detected different thermal nociception phenotypes in the mutants for three of them: fut-3, -4, and -6. The substrate specificity of FUT-6 was previously inferred by comparing the glycan profiles of fut-6 mutants with that in wild type and in fut-1 and fut-8 mutant (Yan et al. 2015), as well as via in vitro studies (Yan et al. 2013). In contrast, the substrate specificity of FUT-3 and -4 is unknown to date. To our knowledge, we report here the first behavioral phenotypes for fut-3, -4, and -6 mutants. Interestingly, while the fut-3, -4, and -6 strains tested here carry deletions predicted to cause loss-of-functions, their phenotypic profiles are different, sometime opposite. For example, the thermal sensitivity of naïve animals is enhanced in fut-4, reduced in fut-6, and unchanged in fut-3 mutants as compared to wild type. In addition, fut-3 and fut-6 mutations prevent the habituation of heat-evoked responses, while fut-4 accelerates and enhances the habituation effect. Hence, the 3 genes might work differently or even antagonistically in regulating specific aspects of the thermonociceptive response. Several nonmutually exclusive explanations could be proposed. The different enzymes could modify a similar set of target glycoproteins and produce a distinct set of fucosylation patterns differentially affecting the target protein properties. Alternatively, these enzymes could produce a similar fucosylation pattern, but work on a distinct set of target glycoproteins. Interestingly, recent single-cell RNA-seq analyses suggest very different expression patterns (Cao et al. 2017; Taylor et al. 2021). fut-3 is broadly expressed in multiple tissues, including the nervous system, where transcripts were detected in a majority of neuron types. In contrast, fut-4 is less abundantly expressed and found only in a few tissues such as the spermatheca, excretory, and glial cells, while its expression in the nervous system is limited to a few neurons. fut-6 has an intermediate expression span, including in head mesodermal cells, glandular tissues, glial cells, and a small neuron subset, which overlaps with fut-3-expressing neurons, but not with fut-4-expressing neurons. C. elegans could hence represent an interesting model to further study the role of glycoprotein fucosylation in specific tissues and their potential role in controlling nociceptive processes. Follow-up analyses for these genes and others revealed in our screen, might include (1) tissue-specific and neuron type-specific rescue or knock-down in order to identify the relevant locus of action of these genes, (2) heterologous human gene expression to test for biochemical conservation, and (3) deeper phenotypic characterization with other types of noxious stimuli. All these approaches can be readily implemented in the worm models at reasonable financial and ethical costs.

Given the high conservation of the molecular pathways controlling nociception and its plasticity, we anticipate that future studies with human pain-related gene models in C. elegans might give us new insights into their function and ultimately potential biomedically relevant intervention targets in pain management.

Supplementary Material

iyad047_Supplementary_Data

Acknowledgements

The authors are grateful to Andrei-Stefan Lia for help and advices with the INFERNO and ThermINATOR platforms, as well as to Laurence Bulliard and Lisa Schild for expert technical support.

Data availability

The authors affirm that all data necessary for confirming the conclusions of the article are present within the article, figures, and Supplementary File 1. All the strains used are available at the CGC or, in the case of double mutants generated in this study, upon request.

Supplemental material available at GENETICS online.

Funding

Some strains were provided by the CGC, which is funded by NIH Office of Research Infrastructure Programs (P40 OD010440). The work was supported by the Swiss National Science Foundation grants 310030_197607, PP00P3_150681, and BSSGI0_155764 to DAG.
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