Study Population
The UKB is a prospective cohort study that has collected extensive phenotypic and genetic data from approximately 500,000 participants across the United Kingdom21,45. All of the participants provided written informed consent.
Phenotype description and assessment
Phenotypes were defined using the ‘Experience of Pain’ UKB self-assessment questionnaire data under project ID 49572. This is part of the online UKB follow-up and was sent in May 2019 to all UKB participants with an active email address who had consented to further electronic contact (n = 335,587) (further details are provided in the Supplementary Methods). Definitions and characteristics of the phenotypic end points were described in detail previously22. Participants who have withdrawn (153 as of 15 September 2023) were excluded from the analysis. Chronic pain was defined by considering a screening question asking whether participants are “troubled by pain or discomfort present for more than 3 months” (item f120019). The question “area most bothered by pain in the last three months” (item f120037) was used to define the location of most bothersome pain and the intensity of the most bothersome pain was defined from items 120023–120035 asking for the “rating of pain” in the most bothersome pain location. People with no chronic pain had their intensity values imputed to 0. People who self-reported fibromyalgia (f120009), chronic fatigue syndrome/myalgic-encephalomyelitis (f120010) or chronic pain all over the body (f120021) were excluded from the analysis (11,951 with chronic pain and 821 with no chronic pain). We had valid most bothersome pain ratings for 139,167 (71,904 and 67,263 meeting criteria for no chronic pain and chronic pain, respectively).
Genotyping, imputation and quality control
In this study, we used genotype datasets from the UKB to investigate genetic factors related to chronic pain. We used two specific releases: version 2 for directly genotyped variants and version 3 for imputed genotypes. Initially, approximately 50,000 UKB participants were genotyped using the Applied Biosystems UK BiLEVE Axiom Array by Affymetrix. Subsequently, around 440,000 participants were genotyped using the Applied Biosystems UKB Axiom Array.
Quality-control and imputation procedures were performed as detailed previously45 and resulted in the released dataset of 488,377 samples and 805,426 directly typed markers from both arrays. This dataset was subjected to further quality control before phasing and imputation were performed using a combined Haplotype Reference Consortium (HRC) and UK10K reference panel. The imputed dataset has over 90 million autosomal SNVs, short indels and large structural variants for 487,442 individuals.
To assess genetic ancestry, we used the KING software (v.2.3.2)46, using the 1000 Genomes Project as a reference panel. The directly genotyped dataset was used with additional quality control filters using PLINK (v.1.90b6.21, https://www.cog-genomics.org/plink/1.9/)47 that included: autosomes, minor allele frequency ≥ 5%, not present in high linkage disequilibrium (LD) regions and LD pruning using a R2 threshold of 0.2 with a window size of 50 markers and a step size of 5 markers. This analysis enabled us to identify five distinct subpopulations within the UKB: African (9,059 samples), admixed American (605 samples), East Asian (2,572 samples), European (464,586 samples) and South Asian (9,604 samples). Moreover, there were 1,951 samples for which the ancestry could not be determined and the ancestries were therefore categorized as missing.
Genotyping data, encompassing both directly genotyped and imputed variants, and excluding individuals who had withdrawn their consent from the UKB study were available for 487,071 samples. Additional quality-control measures were applied that further excluded 367 samples where the reported sex did not match the inferred sex from their genetic data, 651 samples with suspected sex chromosome aneuploidy and 188 samples with more than ten putative third-degree relatives. In total, 1,024 samples were excluded, with some samples falling into multiple exclusion categories.
Samples of European ancestry were selected, resulting in 462,402 samples available for analyses. The imputed dataset (chromosomes 1–22) was restricted to common and low-frequency variants (minor allele frequency ≥ 1%) that were imputed with high confidence (imputation accuracy info score ≥ 0.8) leaving 9,572,556 variants in the dataset.
Association analyses and candidate SNV identification
We conducted association analyses using REGENIE (v.3.4.1)48. REGENIE uses a two-step whole-genome regression method that effectively accounts for population stratification and sample relatedness. For the continuous outcome, we applied rank-based inverse normal transformation to improve the distribution and meet the assumptions of the regression model. The model included the following covariates: age at the time of completing the questionnaire, sex, genotyping array and the top ten principal components provided by the UKB. REGENIE step 1 was run on a set of the directly genotyped variants, filtered using PLINK2 (v.2.00a5; https://www.cog-genomics.org/plink/2.0/)47 that included sample genotyping rate ≥ 90%, autosomes, minor allele frequency ≥ 1%, Hardy–Weinberg equilibrium test not exceeding P = 1 × 10−15, variant genotyping rate ≥ 99%, not present in high LD regions and LD pruning using a R2 threshold of 0.9 with a window size of 1,000 markers and a step size of 100 markers. REGENIE step 2 was run on the imputed dataset.
To identify risk loci and their lead variants, we performed LD clumping using the Functional Mapping and Annotation of Genome-Wide Association Studies (FUMA)49. We set a range of 250 kb and an r2 threshold of >0.6 to define independent significant SNVs. For lead SNVs, we used an r2 threshold of >0.1. The analysis was based on the respective ancestry from the 1000 Genomes Phase 3 EUR reference panel50. After clumping, we combined genomic risk loci within 1 Mb of each other into a single locus. Moreover, we leveraged resources from Open Targets Genetics, which integrate data from human GWAS and functional genomics, including gene expression, protein levels, and chromatin interactions across various cell types and tissues51. This comprehensive approach enabled us to confirm the connections between GWAS-associated loci, variants and their probable causal genes.
pheWAS
To determine potential associations between the lead SNV associations and their corresponding genes from our study and additional traits, we conducted a pheWAS. This analysis involved generating pheWAS plots from a comprehensive dataset comprising 4,756 GWAS summary statistics, acquired from the GWAS ATLAS. We incorporated all relevant GWAS and associated genes into our selection criteria. For the pheWAS SNV plots, SNVs were deemed to be significant with P values of less than 0.05 and applied the Bonferroni correction method to adjust for multiple comparisons.
Gene-based tests, pathway exploration and enrichment analyses
In our study, we used the FUMA software for gene-based tests, pathway exploration and enrichment analyses. FUMA leverages GWAS summary statistics to prioritize genes, assess gene expression and enrich pathway processes. To address the issue of multiple testing, FUMA applied the Bonferroni correction with a threshold of Pbon < 0.05. Moreover, FUMA incorporates multimarker analysis of genomic annotation (MAGMA) for both gene-based and gene-set analysis.
Ethics
Data for this study were obtained from the UKB for project “Risk factors for chronic pain”, application ID: 49572. UKB has approval from the North West Multicentre Research Ethics Committee (MREC) as a Research Tissue Bank (RTB) approval, REC reference: 21/NW/0157, IRAS project ID: 299116. This approval means that researchers do not require separate ethical clearance and can operate under the RTB approval.
Metabolome correlation analysis
Correlation analysis to identify potential substrates was performed as described previously28. In brief, RNA-seq raw counts data for cell lines in the CCLE were downloaded and processed using median of ratios normalization. Metabolomics data were downloaded from the CCLE website (https://sites.broadinstitute.org/ccle/datasets). Cell lines were matched, and Spearman’s rank correlation coefficients were calculated between each SLC protein and each metabolite. The significance of the correlation coefficients was adjusted using the Benjamani–Hochberg multiple-testing method and plotted as a volcano plot with the value of the correlation coefficient on the x axis and the log10 of the significance on the y axis.
Cloning, expression and purification of HsSLC45A4
The gene encoding full-length human SLC45A4 (UniProt: Q5BKX6) was inserted into pDDGFP-Leu2D52, containing a C-terminal tobacco etch virus (TEV) protease cleavable eGFP–His8 tag, for expression in Saccharomyces cerevisiae strain BJ5460 (ATCC-208285). Transformed yeast were cultivated in synthetic complete medium without leucine (−Leu), supplemented with 2% (w/v) glucose, at 30 °C to an optical density at 600 nm (OD600) of 5.0–6.0 and diluted ninefold into −Leu with 2% (v/v) lactate pH 5.1. Once the OD600 reached 1.8–2.2, expression was induced by addition of 1.5% galactose and expression was maintained for 20–24 h. Cells were collected, lysed through high pressure cell disruption (40 kpsi) and membranes were isolated through ultracentrifugation at 200,000g for 90 min. Membranes were washed in wash buffer, 20 mM HEPES pH 7.4, 1 M KAc, and isolated again at 200,000g for 90 min before being resuspended in 1× PBS and stored at −80 °C.
For expression in tissue culture, SLC45A4 was inserted into the pLexM vector53 with a C-terminal Avi tag (GLNDIFEAQKIEWHE), followed by TEV-cleavable eGFP–His6 fusions. HEK293F cells (Thermo Fisher Scientific), which tested negative for mycoplasma, were cultured in FreeStyle 293 Expression Medium (Thermo Fisher Scientific) at 37 °C under 8% CO2 and 24 h before transfection, were passaged to 0.7 × 106 cells per ml to give a density of 1.3–1.4 × 106 cells per ml after transfection. Transfection was carried out with 1.1 mg plasmid and 2.2 mg linear polyethyleneimine (PEI) MAX (Mw 40,000; Polysciences) per l culture. After transfection, sodium butyrate was added to 10 mM to increase protein expression. Cells were collected 40 h after transfection. Membranes were prepared by lysing the cells by sonication and unbroken cells and cell debris were pelleted at 10,000g for 10 min at 4 °C and membranes were collected through centrifugation at 200,000g for 1 h and washed once with 20 mM HEPES pH 7.5, 20 mM KCl. After washing, the membranes were resuspended in PBS and snap-frozen for storage at −80 °C until required. For purification, thawed membranes were solubilized in buffer containing 1× PBS pH 7.4, 150 mM NaCl, 10% (v/v) glycerol and 2% (w/v) n-dodecyl-β-d-maltopyranoside (DDM, Anatrace) with 0.4% (w/v) cholesteryl hemisuccinate (CHS) for nanodisc reconstitution or 1% lauryl maltoside neopentyl glycol with (LMNG, Anatrace) 0.1% (w/v) CHS for 90 min at 4 °C under gentle agitation using a magnetic stir plate. Insoluble material was removed through centrifugation for 1 h at 200,000g. SLC45A4 was purified to homogeneity using standard immobilized metal-ion affinity chromatography protocols in either DDM:CHS (5:1 ratio) or LMNG:CHS (10:1 ratio). In brief, 4 ml of nickel NTA resin (Thermo Fisher Scientific) was added with 25 mM imidazole (Sigma-Aldrich) for 3 h at 4 °C under gentle agitation using a magnetic stir plate. The resin was loaded onto a gravity flow column (Bio-Rad) and washed with ten column volumes (CVs) of buffer containing either 0.15% DDM:CHS (5:1 ratio) or 0.15% LMNG:CHS (5:1 ratio) and 25 mM imidazole, followed by 20 CVs of buffer with 30 mM imidazole and 300 mM NaCl. The protein was eluted in four CVs of buffer containing 250 mM imidazole and dialysed overnight with TEV protease (1:0.5 M ratio) against 20 mM Tris pH 7.5, 150 mM NaCl with 0.03% DDM:CHS (5:1 ratio) or 0.003% LMNG:CHS (10:1 ratio) at 4 °C under gentle agitation using a magnetic stir plate. After TEV cleavage, the protease and cleaved His-tagged GFP were removed through nickel affinity chromatography on a 1 ml HisTrap column (Sigma-Aldrich). Unbound material was then concentrated to 500 μl using a 50 kDa molecular-weight cut-off spin concentrator (Sartorius) at 4 °C and subjected to size-exclusion chromatography (Superdex 200) in the same buffer as above.
Cell-based 14C-SPD transport assays
The transport activity of overexpressed SLC45A4 was assayed in Neuro-2A cells (ATCC CCL-131), which tested negative for mycoplasma, using 14C-radiolabelled SPD (American Radiolabeled Chemical, ARC3138, 100 mCi mmol−1). Cells were maintained in Gibco DMEM (high glucose, GlutaMAX Supplement, pyruvate, 31966021) at 37 °C under 5% CO2. For transport assays, 1.0–1.7 × 105 cells were seeded per well in 12-well plates and transfected 48–52 h later (once confluency had reached about 60–80%) using FuGENE HD (Promega, E2311) transfection reagent, with 1 µg plasmid (WT SLC45A4 or mutants in pLexM, with a C-terminal Flag tag) and 2.5 µl FuGENE per well. Fresh medium was placed onto the cells 12–15 h thereafter and assays were carried out 40–46 h after transfection.
Before measuring transport activity, cells were washed twice in assay buffer (25 mM HEPES pH 7.5, 135 mM NaCl, 5 mM KCl, 1.2 mM MgCl2, 28 mM glucose) and incubated for 3 min at 37 °C after the second wash. Immediately after the incubation, 240 µl of the assay buffer supplemented with 1 µM 14C-SPD and 9 µM cold SPD was pipetted onto the cells and incubated for 1.5, 5 and 10 min (time-course assays) or 8 min (single-timepoint assays for mutants) at 37 °C. Uptake was then quenched by washing cells twice in 500 µl ice-cold assay buffer and the cells were lysed in 20 mM Tris pH 7.5, 0.2% Triton X-100. The amount of transported 14C-SPD was measured by scintillation counting in Ultima Gold scintillation liquid (PerkinElmer), and the amount of transported SPD was calculated using a standard curve for the substrate using the specific activity of the SPD. For competition assays and IC50 measurements, only 1 µM of 14C-SPD was used in the substrate mixture along with the desired concentration of the competing compound. Experiments were performed at least six times to generate an overall mean and s.d. Owing to variability and high background in the assay, originating from endogenous SLC45A4 and possibly to some extent endocytosis/binding to plasma membrane proteins, each experiment was performed with both WT (cells that were transfected with a plasmid containing WT SLC45A4) and cells transfected with an empty plasmid. If the WT uptake did not exceed 2.5-fold that of the empty plasmid control, the results from that plate were discarded.
Expression of WT SLC45A4 and mutants were assessed using western blotting on membrane fractions with an anti-Flag antibody (Merck, F1804) at 5,000× dilution, using an anti-β-actin antibody as a loading control at 10,000× dilution (Merck, A2228) (Extended Data Fig. 1f). Plasma membrane localization was measured using immunofluorescence (Extended Data Fig. 1h). Cells were seeded on glass coverslips, transfected as described above with Flag-tagged SLC45A4 and 36 h after transfection, cells were washed in PBS pH 7.4 and fixed in 4% PFA for 7 min. After quenching in 50 mM ammonium chloride and further washing, the cells were permeabilized in 100 µM digitonin and the coverslips blocked in 1% bovine serum albumin (BSA) for 30 min. Cells were stained with mouse anti-Flag (1:200 dilution) and rabbit anti-Na+/K+ ATPase (1:50 dilution) primary antibodies for 1 h, washed and further stained with goat anti-mouse IgG AF488 (1:200) and anti-rabbit IgG AF647 (1:200) secondary antibody–fluorophore conjugates for imaging. Imaging was performed on the LSM-980 confocal microscope (Zeiss) and images were processed in ZenBlue (v.3.9, Zeiss) and ImageJ54.
Thermal stability measurements
For assessment of thermal stability in the absence or presence of compounds, nano-differential scanning fluorimetry measurements were carried out on the Prometheus NT.28 instrument (NanoTemper Technologies). Purified SLC45A4 was diluted to a final concentration of 0.2–0.4 mg ml−1 in buffer (20 mM Tris pH 7.5/20 mM MES pH 7.5, 150 mM NaCl, DDM:CHS (0.03:0.003%) with 2.5–50 mM metabolite. Unfolding was monitored as the ratio of Trp fluorescence emission at 330 nm and 350 nm between 20–90 °C using a ramp rate of 1 °C min−1. The apparent Tm was determined as the maximum of the first derivative of the emission ratio.
Nanodisc reconstitution
SLC45A4, purified from HEK293F in DDM:CHS, was reconstituted into MSP1D1 lipid nanodiscs with EBC lipid (85% (mol/mol) E. coli polar lipid extract, 10% bovine brain polar lipid extract, 5% cholesterol) using the BioBead method55. Then, 100 µg SLC45A4 was mixed with MSP1D1 and EBC lipid solubilized in 0.5 M sodium cholate, at a molar ratio of 1:5:75, respectively, the mixture incubated on ice for 1 h and excess detergent removed through stepwise addition of BioBeads and overnight incubation under gentle agitation. Insoluble material was removed through ultracentrifugation and reconstituted SLC45A4 separated from empty nanodiscs and excess lipid on a Superdex200 Increase 10/300 GL column in 20 mM HEPES pH 7.5, 150 mM NaCl and concentrated to 2 mg ml−1 for cryo-EM analysis.
Cryo-EM sample preparation and data acquisition
For the LMNG:CHS sample, purified SLC45A4 was subjected to a further round of SEC polishing on the Superdex 200 Increase 10/300 GL column in 20 mM Tris pH 7.5, 150 mM NaCl, 0.001% LMNG:CHS (10:1), to separate from empty detergent micelles, and the unconcentrated peak fraction (0.31 mg ml−1) used for grid preparation. The sample was adsorbed to glow-discharged holey carbon-coated grids (Quantifoil 300 mesh, Au R1.2/1.3) for 10 s. The grids were then blotted for 2 s at 100% humidity at 10 °C and frozen in liquid ethane using the Vitrobot Mark IV (Thermo Fisher Scientific). Data were collected in counting mode in electron event representation (EER) format on the CFEG-equipped Titan Krios G4 (Thermo Fisher Scientific) system operating at 300 kV with a Selectris X imaging filter (Thermo Fisher Scientific) with slit width of 10 eV at ×165,000 magnification on a Falcon 4i direct detection camera (Thermo Fisher Scientific) corresponding to a calibrated pixel size of 0.732 Å. Videos were collected at a total dose of 57.6 e− Å−2 fractionated to about 1 e− Å2 per fraction. SLC45A4 reconstituted into EBC:MSP1D1 nanodiscs, as described above, was concentrated to 2 mg ml−1 and directly used for preparation of grids. Then, 3 µl of sample was applied onto a glow-discharged holey carbon grid (Quantifoil Cu R1.2/1.3 300 mesh), blotted for 5 s at 100% humidity and 4 °C and plunge-frozen in liquid ethane using a Vitrobot Mark IV. Data were collected in counted super-resolution bin2 mode on the Titan Krios G3 (FEI) system with a K3 camera (Gatan) and BioQuantum imaging filter at 300 kV, with a pixel size of 0.832 Å. A total of 20,184 micrographs was collected using a dose of 15.89 e− Å−2 s−1 and an exposure time of 2.5 s, giving a total dose of 39.71 e− Å−2.
Cryo-EM data processing
Patched (20 × 20) motion correction, CTF parameter estimation, particle picking, extraction and initial 2D classification were performed in SIMPLE (v.3.0)56. All further processing was performed in cryoSPARC (v.3.3.1)57 and RELION (v.3.1)58, using the csparc2star.py script within UCSF pyem59 to convert between formats. The global resolution was estimated from gold-standard Fourier shell correlations (FSCs) using the 0.143 criterion and local resolution estimation was calculated within cryoSPARC.
The cryo-EM processing workflow for SLC45A4 in LMNG:CHS is outlined in Extended Data Fig. 2. In brief, particles were subjected to two rounds of reference-free 2D classification (k = 300 each) using a 140 Å soft circular mask within cryoSPARC. Four volumes were generated from a 479,080 particle subset of the 2D-cleaned particles after multiclass ab initio reconstruction using a maximum resolution cut-off of 6 Å. Particles from the most populated and structured class were selected, and another multiclass ab initio reconstruction (k = 4) was performed. Output volumes were lowpass-filtered to 7 Å and used as references for a four-class heterogeneous refinement against the full 2D-cleaned particle set (2,815,141 particles). Particles (964,648) from the most populated and structured class were selected and non-uniform refined against their corresponding volume lowpass-filtered to 15 Å, generating a 3.3 Å map. A multiclass ab initio reconstruction (k = 4) using a maximum-resolution cut-off of 6 Å was performed on these particles, generating four volumes that were lowpass-filtered to 7 Å and used as references for heterogeneous refinement against the same particle set. Particles (700,436) belonging to the two most populated and structured volumes (which were in opposite hands) were combined and subjected to non-uniform refinement against one of the corresponding volumes, lowpass-filtered to 15 Å, generating a 3.3 Å map with slightly improved density over the previously refined volume. Bayesian polishing followed by non-uniform refinement (15 Å lowpass-filtered reference) further improved the map quality to 3.0 Å. Per-particle defocus refinement followed by non-uniform refinement (15 Å lowpass-filtered reference) resulted in a 2.8 Å map that was used for model building.
For the SLC45A4 nanodisc structure (Extended Data Fig. 3), the 20,196,090 extracted particles (box size of 240 px) were subjected to three rounds of conservative 2D classification to give 1,473,487 particles, which were further classified into four classes in ab initio reconstruction. Three rounds of less conservative 2D classification of the initial particle set gave 5,812,766 particles, which were classified by two rounds of heterogeneous refinement, using the best ab initio map from the earlier reconstruction. After further sorting particles using ab initio reconstruction, Bayesian polishing was performed and particles were re-extracted with a box size of 320 px. After 2D classification, two further rounds of ab initio reconstruction, non-uniform and local refinement gave a final map of 3.25 Å (where FSC = 0.143) from 227,752 particles.
Model building was performed in Coot (v.0.9.8.1 EL)60 and ISOLDE61, refinement in PHENIX (v.1.20.1-4487) real-space refinement62 and validation in MolProbity63. Images were generated using PyMol64 and ChimeraX65.
Animals
Animals were group-housed in temperature-controlled (21.5 ± 0.5 °C) and humidity-controlled (55 ± 10%), specific-pathogen-free facilities in individually ventilated cages. Mice were housed under 12 h–12 h light–dark cycle with food and water provided ad libitum. All experiments were carried out using male and female C57BL/6J mice. Behavioural studies were carried out on age and sex matched littermates. All transgenic mice were backcrossed onto the C57BL/6J background. All procedures complied with the UK Animals (Scientific Procedures) Act (1986) and were performed under a UK Home Office Project Licence in accordance with University of Oxford Policy on the Use of Animals in Scientific Research. This study conforms to the NC3Rs policy on reduction, refinement and replacement of animal research, and to the ARRIVE guidelines66.
Generation of the Slc45a4-KO mouse
Design and development of the Slc45a4-KO mouse was carried out in partnership with Taconic Biosciences and Cyagen Biosciences. In brief, CRISPR–Cas9 technology was used to delete exons 3–8 of the mouse Slc45a4 gene on chromosome 15. This 13.3 kb deletion accounts for 89.64% of the Slc45a4 coding region. Guide RNAs were designed to target only the Slc45a4 locus and injected together with Cas9 into mouse zygotes. Chimeric F0 offspring mice were bred with WT mice to generate heterozygous founders F1 which were screened for successful Slc45a4 editing. The targeted region of Slc45a4 was sequenced to confirm deletion of exons 3–8. Mice were genotyped using primers in Supplementary Table 7 using a standard Taq polymerase-based protocol. WT band, 652 bp; KO band, 468 bp.
Mouse histology
Tissue collection
For histology studies, mice received an overdose of pentobarbital, then vascular perfused with saline and 4% paraformaldehyde (PFA). DRG, EDL muscle and skin tissue was collected and post-fixed in 4% PFA for 1–2 h, and spinal cord for 24 h. DRG, skin and spinal cord were cryoprotected in 30% sucrose and stored for at least 48 h before embedding in OCT. DRG tissue was cryosectioned at 12 μm, skin at 30 µm and spinal cord at 20 µm. Fixed EDL muscle was teased into small fibre bundles of about 1 mm diameter per bundle. For histology on neural cultures, live CellTracker dye CMTMR was added along with IB4-conjugated AF488, or cells were washed and fixed in 4% PFA for 15 min room temperature.
IHC
Standard immunohistochemistry (IHC) techniques were used. Antigen retrieval in a citric acid buffer was performed on skin sections before IHC (citrate buffer, sodium citrate dihydrate, EDTA, distilled H2O, pH 6.1, 65 °C, 1 h). In brief, the sectioned or teased samples were washed in PBS and blocked in a blocking solution (5% normal goat serum and 0.3% Triton X-100, PBS) for at least 30 min at room temperature. Primary antibodies (Supplementary Table 8) were diluted in the same blocking solution and were left to incubate on the tissue samples overnight at room temperature or 4 °C. The samples were washed in a washing buffer solution (0.3% Triton X-100, PBS). Secondary antibodies (Supplementary Table 8) were diluted in the washing buffer solution and left to incubate on the tissue for 1–2 h at room temperature in dark conditions. The samples were washed thoroughly in the washing buffer, DRG and skin sections were mounted using Vectorshield (with or without DAPI) and muscle fibres were mounted onto microscope slides (Avantor, 631-0108) using hard-set confocal matrix (Micro Tech Lab). Images were taken on confocal microscopes (Zeiss LSM-710, LSM-780 or Olympus FV3000).
ISH analysis
In situ hybridization (ISH) was performed according to the user instructions for the RNAscope 2.5 RED Chromogenic assay kit (Advanced Cell Diagnostics, Bio-techne). In brief, fixed DRG tissue underwent pretreatment with H2O2, protease III and 100% ethanol. The tissue was then incubated at 2 h at 40 °C with an Slc45a4 mRNA probe (522131). Probe amplification, washing steps and chromogenic development with fast red were carried out as described in the user kit. The tissue was then co-stained and imaged using the IHC protocol described above.
Image analysis
All image analysis was performed using ImageJ/Fuji (NIH). For IHC, at least, three sections per animal were used from three animals per group. Total cells and cells positive for each subpopulation marker were counted using the multipoint tool. For ISH, cells were defined and mRNA intensity calculated. The background intensity was calculated with tissue that underwent the ISH protocol with a standard negative control mRNA probe. A threshold for positive cells was defined as cells whose average intensity was more than mean + 3 s.d. of background intensity. Cell size classification was as follows: cell area < 490μm2 was classified as a small cell, cell area between 490–962 μm2 was classified as a medium cell and a large cell had an area greater than 962 μm2. For intraepidermal nerve fibre density analysis, nerve fibres crossing into the epidermis were counted live under the ocular lens of the Zeiss LSM-710 system. The distance of each section was calculated post hoc in Fuji and nerve fibres were quantified as fibres per mm. Spinal neurons were first segmented using Cellpose 2.0. Within Cellpose 2.0, we used a human-in-the-loop pipeline to train a custom model by annotating cells on the Cellpose graphical user interface. Cells were determined to be positive for target probe mRNA if signal intensity was 3 s.d. above the negative control readings. Superficial lamina (I + II) were defined by IB4 staining to mark lamina II. A reference template (Atlas of the Mouse Spinal Cord) was used analyse all other laminae. For assessment of neuromuscular junction (NMJ) size, fragmentation, area and nerve terminal registration, optimized settings for each image were used. Between three and five z stacks were obtained per muscle sample. Ten NMJs were analysed from each animal using ImageJ software. The ImageJ macro (BetterAreaGreyValues) was used to measure NMJ area and fragmentation (Supplementary Methods). Registration of different fluorescence signals was analysed using the JACoP plugin for ImageJ. All comparative image analysis was conducted with the experimenter blinded to genotype. Cartoon illustrations were made in-house or provided by Servier Medical Art (https://smart.servier.com/), licensed under a CC BY 4.0 license.
RT–qPCR
Tissue was collected from mice after overdose with pentobarbital and transcardiac perfusion with ice-cold saline. Tissues were rapidly dissected and flash-frozen in liquid nitrogen and stored at −80 °C. RNA was isolated from fresh-frozen mouse tissues using a combination of TriPure (Roche) and a RNeasy mini kit (Qiagen). In brief, tissue was homogenized in Tripure using a handheld homogenizer (Cole-Parmer), treated with chloroform and then column-purified and eluted in RNase-free water. Genomic DNA was removed with on-column DNase I digestion. cDNA synthesis was performed using the EvoScript Universal cDNA Master kit (Roche). Gene expression was quantified by detecting amplified material using the LightCycler SYBR Green Master Mix (Roche) on the LightCycler 480 II system (Roche). Three technical replicates were included for each sample. The results were normalized to three reference gene controls (mouse Actb, Gapdh and Hprt) using the ∆∆CT method. A list of the primers is provided in Supplementary Table 7.
DRG culture
DRG neurons were quickly and carefully dissected from the vertebral column67 and enzymatically digested for 75–90 min at 37 °C 5% CO2 (collagenase type II, 4 mg ml−1; dispase type II, 4.7 mg ml−1 in Hank’s balanced salt solution Mg2+ and Ca2+ free (HBSS-Gibco Thermo Fisher Scientific)). Cells were then mechanically dissociated using fire-polished glass pipettes plated into wells of a 24-well plate containing poly-d-lysine/laminin-coated glass coverslips. Cells were maintained in supplemented Neurobasal medium (Gibco, Thermo Fisher Scientific) (2% (v/v) B27, 1%(v/v) GlutaMAX, 1%(v/v) antibiotic–antimycotic, mouse nerve growth factor (50 ng ml−1; NGF, PeproTech) and 10 ng ml−1 glial-derived neurotrophic factor (GDNF, PeproTech). Cells were used/analysed 24–72 h later.
DRG electroporation
Electroporation was performed on dissociated cells before plating. Neurons were resuspended in 10 μl buffer R containing 1 μg of plasmid DNA. Neurons were immediately withdrawn with an electroporation pipette/tip, and inserted into a Neon transfection system (Thermo Fisher Scientific). Neurons were transfected using the following protocol: three 1,500 V pulses of 10 ms duration. Cells were used/analysed 24–72 h later.
Metabolomic analysis of polyamines and GABA
Chemicals and materials
Reagents used in this study were purchased from Sigma-Aldrich unless stated otherwise. 2-Amino-3-(2-chlorophenyl)propanoic acid was purchased from FluoroChem. Methanol was obtained from Merck. Putrescine dihydrochloride and spermidine trihydrochloride were from Insight Biotechnology. Spermine tetrahydrochloride and N-methyl-N-trimethylsilyltrifluoroacetamide (MSTFA) with 1% of chlorotrimethylsilane (TMCS) were purchased from Thermo Fisher Scientific. Deuterated polyamine standards: putrescine-D8 (PUTD8), spermidine-D8 (SPDD8) and spermine-D8 (SPMD8) were obtained from Cambridge Isotope Laboratories through CK Isotopes. GABA was obtained from MP Biomedicals.
Sample collection and preparation
Mouse tissues used for extraction were as follows. For brain tissue, half a hemisphere was used (average 230 mg). DRGs were dissected and collected across all regions (cervical to lumbar), with an average of 8 mg. Blood was collected during perfusion and plasma separated after centrifugation at 1,300 rpm for 10 min at room temperature. Spinal columns were removed and kept on HBSS. Each spinal column was transferred to a silicon-coated Petri dish containing HBSS and fixed in place with the dorsal side facing up using four needles. The whole spinal cord was collected (~51 mg) after exposure and removal of the overlying tissue, vertebrae and meninges. To delineate dorsal versus ventral horn, the dorsal fourth of the spinal cord (average 22 mg) was collected, and the remaining tissue was collected as ventral (average 31 mg).
Polyamines and GABA were extracted as previously described68,69. All tissues were suspended in 800 μl of lysis buffer (80% methanol diluted in H2O with 2% TFA). For plasma, 100 μl was diluted in 400 μl of 100% methanol with 2% TFA. For polyamine analysis, the samples were spiked with 5 μl of 1 mM deuterated polyamine samples and 10 μl of each polyamine standard (10 mM solution, 10 nmol per sample). For GABA analysis, 2-amino-3-(2-chlorophenyl)propanoic acid was used as an internal standard (10 mM solution, 20 nmol per sample). The suspensions were homogenized in a bead beater (Precellys 24, Bertin Technologies) for three cycles (6,500 rpm, 45 s) (5 cycles for DRG tissues) with 3 min incubation on dry ice between cycles. The samples were left on dry ice for 1 h and then centrifuged at 17,000g for 30 min at 4 °C. The supernatants were collected and transferred into a glass vial to dry under vacuum (SpeedVac) overnight.
Chemical derivatization
For GABA analysis, the dried samples were resuspended in a mixture of 50 μl MSTFA with 5% TMCS and 50 μl pyridine, followed by incubation for 1 h at 60 °C at a shaking speed of 1,200 rpm. The samples were cooled down to ambient temperature, centrifuged at 8,000g for 30 min at 4 °C and injected directly for two-dimensional gas chromatography mass spectrometry (GC×GC–MS) analysis (described below) with splits of 1/20 or 1/100, respectively.
For polyamine analysis, the dried samples were resuspended in 300 μl trifluoracetic anhydride. The vials were then sealed and incubated for 1 h at 60 °C. The samples were left to dry at ambient temperature for an hour and then evaporated to dryness under vacuum (SpeedVac). Derivatized samples were resuspended in 50 μl of 100% acetonitrile and vortexed until any solid was adequately mixed. Finally, the samples were centrifuged for 5 min at 8,000g at 4 °C and injected for GC×GC–MS analysis (described below) with splits of 1/2 or 1/10, respectively.
GC×GC–MS analysis
The samples were immediately analysed using a GC×GC–MS system comprising a gas chromatograph coupled to a quadrupole mass spectrometer (Shimadzu GCMS QP2010 Ultra) and a Shimadzu AOC-20i/s auto sampler. The first-dimension separation was carried out on a SHM5MS capillary column (30 m, 0.25 mm inner diameter, 0.25 μm film thickness, Shimadzu) while the second-dimension separation was on a BPX-50 capillary column (5 m, 0.15 mm inner diameter, 0.15 μm film thickness, SGE). Helium gas was used as a carrier gas at a 73 psi constant inlet head pressure. The modulation period was set as 4 s. The samples (1 μl) were injected at 280 °C. For GABA analysis, the oven temperature was programmed from 60 °C to 240 °C at 10 °C min−1, and then to 320 °C at 40 °C min−1, held at 320 °C for 6 min. For polyamine analysis, the oven temperature was programmed from 60 °C to 320 °C at 10 °C min−1 and held at 320 °C for 8 min. The interface temperature to the mass spectrometer was set at 300 °C and ion source was heated at 230 °C. The MS was operated at scan speeds of 20,000 amu, covering m/z 45–600. Electron ionization spectra were recorded at 70 eV. The standard curves were generated using mixtures of deuterated polyamines (10 nmol) and different ratios of endogenous polyamines. Phosphate-buffered saline (PBS pH 7.4) was used as the matrix to do the standard curves.
Data processing and analysis
Raw GC×GC MS data were processed using GCMSsolution software (v.2.72/4.50 Shimadzu) and Chromsquare software (v.2.1.6, Shimadzu) in combination with the NIST 11/s, OA_TMS, FA_ME and YUTDI in-house libraries that were used for data analysis. The annotation of metabolites was carried out by comparing them to the standards (IM spectra and retention times). The confidence of identification was further validated by manual inspection of matches between experimentally observed and standard EI spectra. The m/z values for identification and quantification (in bold) of the metabolites are shown in Supplementary Table 9.
Spinal cord slice recordings
Adult mice (5 WT and 6 KO) were anaesthetized with urethane (i.p. 2 g per kg), and perfused transcardially with ice-cold oxygenated (95% O2, 5% CO2) sucrose-based artificial cerebrospinal fluid (sACSF) containing 50 mM sucrose, 92 mM NaCl, 5 mM KCl, 7 mM MgSO4, 0.5 mM CaCl2, 1.25 mM NaH2PO4, 26 mM NaHCO3 and 15 mM glucose. The lumbar spinal column was removed and immersed in ice-cold sACSF and the spinal cord was quickly obtained by laminectomy. Parasagittal slices (300 μm) were cut on a vibratome (Leica VT 1200) in ice-cold sACSF. Slices were then transferred to a submerged chamber containing oxygenated NMDG-based recovery ACSF (rACSF) for 15 min at 34 °C, containing 93 mM NMDG, 2.5 mM KCl, 1.2 mM NaH2PO4, 30 mM NaHCO3, 20 mM HEPES, 25 mM glucose, 5 mM Na-ascorbate, 2 mM thiourea, 3 mM Na-pyruvate, 10 mM MgSO4 and 0.5 mM CaCl2, and adjusted to pH 7.4 with HCl. After recovery incubation, slices were maintained in oxygenated at room temperature until recording. ACSF was composed of 126 mM NaCl, 2.5 mM KCl, 2 mM MgCl2, 2 mM CaCl2, 1.25 mM NaH2PO4, 26 mM NaHCO3 and 10 mM glucose. Lamina II neurons were visually identified in an Olympus BX51 microscope equipped with infrared differential interference contrast (IR-DIC) and a ×40 water-immersion-objective. Patch pipettes (4–6 MΩ) were filled with 140 mM KCl, 2 mM MgCl2, 10 mM HEPES, 5 mM MgATPg, 0.4 mM NaGTP, 0.1% Lucifer-Yellow (LY, Sigma-Aldrich), pH 7.3 adjusted with KOH. Whole-cell patch clamp recordings were obtained using a Axopatch 200B amplifier (Molecular Devices), digitized with a Digidata 1440 (Molecular Devices), and recorded using pClamp 10 software (Molecular Devices). Data were filtered at 5 kHz and sampled at 10 kHz.
Neurons were recorded in current clamp to obtain measures of resting membrane potential (RMP), input resistance and rheobase. Thereafter, tetrodotoxin (TTX; 1 μM) and 6-cyano-7-nitroquinoxaline-2,3-dione disodium salt (CNQX; 10 μM) were superfused onto slices to record miniature inhibitory postsynaptic currents. Neurons were maintained at −70 mV (liquid junction potential = 5 mV). Only neurons with a resting potential more negative than −40 mV and stable access resistance (<25 MΩ) during the recording were included for subsequent analysis.
Whole-cell patch-clamp
Four independent patch-clamp experiments were conducted using 4 (2 male, 2 female) WT and 4 (2 male, 2 female) Slc45a4-KO mice. Before patch-clamp, an IB4-conjugated AF488 live dye was added to the cells for 30 min at 37 °C to distinguish IB4-binding/positive and IB4-non binding/negative neurons. Using this, we defined small (diameter < 25 µm) IB4+ neurons as predominantly non-peptidergic nociceptors and small IB4− neurons as predominantly peptidergic nociceptors. This definition is not clear cut—there will be some overlap and some cells that are negative for both markers (that is, C-LTMRs and CYSLTR2+ nociceptors70). To confirm that the majority of IB4− neurons are peptidergic nociceptors, we carried out an independent experiment and cultured CgrpcreERT2-tdTomato sensory neurons and live imaged them with IB4–AF488 and a blue live-cell dye. We counted 933 small-sized neurons. In total, 459 small cells bound to IB4–AF488, and 140 small cells (15%) were negative for both tdTomato and IB4–AF488. We determined that of the small neurons that were IB4−, 70% were tdTomato+, confirming our assumption that the majority of small-sized IB4− neurons are peptidergic nociceptors.
Experiments using the Axopatch 200B amplifier and Digidata 1550 acquisition system (Molecular Devices) were performed at room temperature. Data were sampled at 20 kHz and low-pass filtered at 5 kHz. Series resistance was compensated 80 to 85% to reduce voltage errors. AF488+ neurons were detected with an Olympus microscope with an inbuilt GFP filter set (470/40× excitation filter, dichroic LP 495 mirror, and 525/50 emission filter). Filamental borosilicate glass capillaries (1.5 mm outer diameter, 0.84 mm inner diameter; World Precision Instruments) were pulled to form patch pipettes of 2 to 5 MΩ tip resistance and filled with an internal solution containing 100 mM K+ gluconate, 28 mM KCl, 1 mM MgCl2, 5 mM MgATP, 10 mM HEPES and 0.5 mM EGTA; the pH was adjusted to 7.3 with KOH and the osmolarity was set at 305 mOsm (using glucose). Neurons were maintained in a chamber constantly perfused with a standard extracellular solution containing 140 mM NaCl, 4.7 mM KCl, 2.5 mM CaCl2, 1.2 mM MgCl2, 10 mM HEPES and 10 mM glucose; the pH was adjusted to 7.3 with NaOH and the osmolarity was set at 315 mOsm (using glucose). There was a calculated −13 mV junction potential when using these solutions; voltage values were adjusted to compensate for this.
The RMP was measured in bridge mode (I = 0). In current-clamp mode, neurons were held at −60 mV. The input resistance was derived by measuring the change in membrane voltage caused by a 80 pA hyperpolarizing current step. Rheobase was determined by applying 50 ms depolarizing current steps, (Δ10 pA), until action potential generation. Suprathreshold activity/repetitive firing was assed using two protocols. First, 500 ms depolarizing current steps (Δ50 pA) were used until a final step current of 950 pA. Second, we used a ramp protocol that gradually injects current from 0 to 1 nA, with the duration of the ramp increasing (Δ100 ms) each time until a final ramp stimulus of 1,000 ms. All data were collected using pClamp10 and analysed by Clampfit 10 software (Molecular Devices).
Ex vivo skin-nerve preparation
The hind paw glabrous skin and tibial nerve were dissected from adult WT (n = 8, 5 male and 3 female) and Slc45a4-KO (n = 8, 6 male, 2 female) mice. The skin was maintained in a perfusion chamber in the outside out configuration (epidermis facing up). The chamber was perfused with carbogen bubbled synthetic interstitial fluid (SIF: 2.0 mM CaCl2, 5.5 mM glucose, 3.5 mM KCL, 26.2 mM NaHCO3, 0.7 mM MgSO4, 108 mM NaCl, 1.5 mM NaH2PO4, 9.5 mM Na-gluconate, 7.5 mM sucrose) at 32 °C. The tibial nerve was isolated using mineral oil (Sigma-Aldrich) in an adjacent chamber, desheathed and the nerve fibres were teased apart and placed onto a silver recording electrode. Single-fibre receptive fields were located using a blunt probe and conduction velocity was measured (C-fibre, <1.2 m s−1; Aδ-fibre, 1.2–10 m s−1; Aβ-fibre, ≥10 m s−1) using pulsed suprathreshold electrical currents. Receptive fields were stimulated mechanically using a 0.8 mm diameter flat probe attached to a piezo electric stimulator (Physik Instrument) or a NanoMotor stimulator (Kleindiek), both in conjunction with force sensors (Kleindiek). Stimuli were as follows: consistent force with subsequent stimuli increasing in velocity; 20 Hz vibration with a steadily increasing force; and 7 s step-increasing forces were applied to characterize mechanical thresholds and stimulus–response profiles. Thermal responses were achieved by using a receptive field isolator (ring-isolator) containing an internal thermistor (Warner instruments), and placed on top of an identified receptive field. Then, 1 ml of 65 °C buffer was pipetted into the ring isolator (starting at 32 °C), creating a consistent temperature ramp from 32 to 50 °C in 1.21 s (±0.055). All stimuli evoked action potentials/spikes were recorded using a Powerlab v.4.0 system in conjunction with LabChart v8 software (ADInstruments).
Animal behaviour
A total of 15 (8 male, 7 female) WT mice, 14 (7 male, 7 female) heterozygous mice and 7 (3 male, 4 female) homozygous KO mice were used for behavioural studies. All mice were littermates, and age and sex matched where possible. All mice included in the behavioural pipelines underwent all behavioural tests. Mice were tested at a consistent time of day during the light phase, in the same environment by the same experimenter. Mice were habituated to their testing environments and equipment before testing days. The experimenter was blinded to animal genotype until post-behavioural analysis was complete. Mice were randomly assigned a test environment and test order, which was achieved by random selection from their home cages. Unless otherwise stated, each test was conducted three times on different days to obtain an average baseline score.
Open field
Each mouse was individually placed into an open black testing box (size) with a grid marked into the floor. Mice were allowed to freely explore the open field for 3 min while being video recorded and tracked using ANY maze software. The following parameters were measured: the number of rears, number of gridline crossing, total distance travelled and maximum speed when travelling.
Rotarod
Mice were placed onto a speed-controlled horizontal rod/beam (Ugo Basile). Once mice were placed onto the stationary rod, an increasing speed (ramp) protocol was applied (0.5 rpm s−1 for 20 s, 0.25 rpm s−1 for 160 s, 0.16 rpm s−1 for 120 s to reach a final speed of 80 rpm). Mice were monitored until they fell from the rotating rod. Latency to fall (s) and final speed (rpm) was recorded on two testing days and averaged.
Mechanical testing
Mice were placed into a testing box (5 × 5 × 10 cm) elevated on a wire mesh base and the mice allowed to acclimatize for 30–60 min. The plantar hind paws were tested using von Frey hairs (using the up-down method71) to calculate the 50% paw withdrawal threshold, or a pin prick attached to a 1 g von Frey hair to measure the latency to withdraw (using a high-frame-rate camera).
Thermal sensory testing
Mice were plated onto a Perspex enclosed hot plate that was set to 48 °C, 50 °C or 53 °C. The mice were observed and timed until their hind paws reacted to the hot plate (lifting, flicking, licking, cut off set to 20 s). The latency to respond to each hot plate was measured. For the Hargreaves test, the mice were placed into a test box (5 × 5 × 10 cm) on elevated glass and acclimatized for 30–60 min. The Hargreaves radiant heat source was applied to each paw three times and latency to withdraw was recorded. Noxious cold sensitivity was measured using the dry ice test. Mice were placed in test boxes, and elevated on a 5 mm thick glass platform. Dry-ice pieces were placed into a 2 ml syringe (top removed), which was placed against the glass under a visible hind paw. Latency to withdraw from the dry ice/glass was measured and three measurements were taken for each hind paw.
Thermal gradient test
Mice were allowed to freely explore a thermal gradient apparatus (BIOSEB), which consisted of a metal platform that was heated at one end and cooled at the other. This created a thermal gradient platform ranging from 54 °C to 6 °C. During the 60 min exploration mice were video tracked using a HD webcam and ANYMaze software, and the time in different temperature zones was analysed. This test was performed only once to avoid learning confounds. One heterozygous mouse (female) was excluded from this test owing to a camera fault during the 60 min run.
Tonic pain assay: formalin
Mice received a single subcutaneous injection of 20 μl of 2% formalin in the left hind paw. Mice were immediately placed into a test box (5 × 5 × 10 cm), elevated on a glass platform, surrounded by angled mirrors, all above a video camera. Mice were video recorded for 1 h while the experimenter left the room. The videos were analysed offline by two blinded experimenters, each measured the duration of nocifensive behaviours (lifting, licking, flinching, shaking) of the injected hind paw every 5 min for 1 h. The first formalin phase was defined as 0–15 min, and the second phase was defined as 15–60 min.
Statistical analysis and reproducibility
Biochemical assay
All biochemical assay data were derived from at least three independent experiments. Exact n values are as follows. Figure 2a: n indicates the number of thermal stability assays. Sucrose: n = 5; GABA: n = 4; l-ornithine: n = 4; l-lysine: n = 4; l-arginine: n = 4; Put: n = 3; Cad: n = 3; Spd: n = 3; Spm: n = 3. Figure 2i: n indicates the number of wells containing cells. Empty: n = 46; WT: n = 42; K450R/R453E: n = 6; E63A: n = 8; Y66A: n = 6; Y66F: n = 6; D169A: n = 10; D173A: n = 7; E176A: n = 12; W519A: n = 5; W519F: n = 5; Y672A: n = 5; Y672F: n = 4. Extended Data Figure 1c: n indicates the number of wells containing cells. No competitor: n = 18; 100 μM SPM: n = 7; 100 μM SPD: n = 10; 100 μM Put: n = 8; 100 μM Cad: n = 8; 1 mM l-Lys: n = 10; 1 mM l-Arg: n = 7; 1 mM l-Orn: n = 4; 1 mM GABA: n = 8. Extended Data Figure 1d: n indicates the number of wells containing cells. pH washes: all empty 2 wash cycles: n = 4; all empty 5 wash cycles: n = 5; all WT 2 pH 7.5 and 9.0: n = 10, pH 5.5: n = 9; WT 5 pH 7.5: n = 6, pH 9.0 and pH 5.5: n = 5; NaCl washes: all empty 2 wash cycles: n = 2; all empty 5 cycles: n = 4; all WT 2: n = 2; all WT 5: n = 4. Cold SPD wash cycles: all n = 5, except for WT 2: 0.1 mM SPD: n = 4. ‘Empty’ refers to empty plasmid. Extended Data Figure 1e: n values indicate the number of wells containing cells. WT: n = 5; D173A: n = 3; E176A: n = 5; D169A/E63A: n = 3; D173A/E176A: n = 3; Y66A: n = 4; Y66A/E176A: n = 3; Y66A/W519A: n = 3. Extended Data Figure 4e: n values indicate the number of wells containing cells. Empty: n = 16; WT: n = 15; N718D: n = 12; N718A: n = 8; N718R: n = 8; N718W: n = 8.
Animal work
Data were analysed using GraphPad Prism 10 and ImageJ/Fiji (NIH). The numbers of samples and the statistical tests used for each experiment are included in the figure legends. In cases in which n represents the number of animals, the number of cells has also been described. In all histology experiments, at least three sections containing cells were analysed per mouse. The number of animals used in behavioural experiments is described in the legends and the relevant Methods section. Sample sizes were calculated using power calculations and historic data.
Statistical analysis used were unpaired t-tests (two-tailed), Mann–Whitney U-tests (two-tailed), one-way ANOVA with Tukey multiple-comparison test, extra sum of squares F-test, Kruskal–Wallis test with Dunn’s multiple-comparison test, two-way ANOVA with Holm–Šidák multiple-comparison test, RM two-way ANOVA with Holm–Šidák multiple-comparison test. Exact n numbers and P values are reported in the figure legends. Full statistics for each test used in the study are shown below.
Figure 3f: brain: Put, t-test, WT versus KO, P = 0.828, t = 0.22, d.f. = 5. Spd, t-test, WT versus KO, P = 0.47, t = 0.79, d.f. = 4. Spm, t-test, WT versus KO, P = 0.66, t = 0.45, d.f. = 6. Spinal cord: Put, t-test, WT versus KO, P = 0.51, t = 0.69, d.f. = 6. Spd, t-test, WT versus KO, P = 0.019, t = 3.37, d.f. = 5. Spm, t-test, WT versus KO, P = 0.13, t = 1.74, d.f. = 6. DRG: Put, t-test, WT versus KO, P = 0.015, t = 2.84, d.f. = 12. Spd, t-test, WT versus KO, P = 0.99, t = 0.001, d.f. = 14. Spm, t-test, WT versus KO, P = 0.97, t = 0.03, d.f. = 14. Plasma: Put, t-test, WT versus KO, P = 0.656, t = 0.455, d.f. = 13. Spd, Mann–Whitney U-test, WT versus KO, P = 0.014, U = 7. Spm, Mann–Whitney U-test, WT versus KO, P = , U = 0.743. Figure 3h: two-way ANOVA, Holm–Šidák test, WT versus KO, CGRP: P = 0.4809, t = 1.492, d.f. = 20. IB4: P = 0.7123, t = 1.140, d.f. = 20. NF200: P = 0.6926, t = 1.171, d.f. = 20. TH: P = 0.8667, t = 0.0678, d.f. = 20. Figure 3j: glabrous PGP 9.5: t-test, P = 0.23, t = 1.31, d.f. = 7. Glabrous CGRP: Mann–Whitney U-test, P = 0.412, U = 6. Hairy PGP 9.5: t-test, P = 0.26, t = 1.22, d.f. = 7. Hairy CGRP: t-test, P = 0.877, t = 0.159. d.f. = 7. Figure 4a: latency to fall: one way-ANOVA, F = 4.581, P = 0.0176, d.f.n, d.f.d = 2, 33. WT versus KO, P = 0.0132, q = 4.267, d.f. = 33. Final speed: one-way ANOVA, F = 5.094, P = 0.0118, d.f.n, d.f.d = 2, 33. WT versus KO, P = 0.0085, q = 4.513, d.f. = 33. Figure 4b: one-way ANOVA, F = 0.1043, P = 0.9013, d.f.n, d.f.d = 2, 33. Figure 4c: one-way ANOVA, F = 7.824. P = 0.0017, d.f.n, d.f.d = 2, 33. WT versus KO, P = 0.002, q = 5.271, d.f. = 33. HET versus KO, P = 0.0039, q = 4.938, d.f. = 33. Figure 4d: one-way ANOVA, F = 3.703, P = 0.0354, d.f.n, d.f.d = 2, 33. WT versus KO, P = 0.0398, q = 3.615, d.f. = 33. HET versus KO, P = 0.0546, q = 3.413, d.f. = 33. Figure 4e: two-way ANOVA, Holm–Šidák test, WT versus HET at 29 °C, P = 0.0096, t = 2.959, d.f. = 544. WT versus KO at 29 °C, P = 0.0275, t = 2.469, d.f. = 544. Inset: extra sum of squares F-test, F = 2.44, P = 0.0242, d.f.n, d.f.d = 6, 586. Figure 4f: RM two-way ANOVA, Holm–Šidák test, WT versus KO at 5 min, P = 0.0113, t = 3.298, d.f. = 19.05. HET versus KO at 5 min, P = 0.0276, t = 2.734, d.f. = 17.41. HET versus KO at 10 min, P = 0.0182, t = 3.237, d.f. = 13.75. Figure 4g: phase 1: Kruskal–Wallis test, P = 0.0208, KW = 7.743. Dunn’s WT versus KO, P = 0.020, Z = 2.713. Phase 2: ANOVA, F = 0.4275, P = 0.6557, d.f.n, d.f.d = 2, 33. Figure 5c: RM two-way ANOVA, Holm–Šidák test, WT versus KO 50–950 pA, P > 0.95, t = 0.007–1.44, d.f. = 323. Figure 5d: RM two-way ANOVA, Holm–Šidák test, WT versus KO, 100–1,000 ms, P > 0.99, t = 0.011–0.655, d.f. = 150. Figure 5e: RM two-way ANOVA, Holm–Šidák test, WT versus KO at 100 pA, P = 0.039, t 3.038, d.f. = 418; at 150 pA, P = 0.0027, t = 3.807, d.f. = 418; at 200 pA, P = 0.0002, t = 4.507, d.f. = 418; at 250 pA, P = 0.0006, t = 4.212, d.f. = 418; at 300 pA, P = 0.047, t = 2.961, d.f. = 418. Figure 5f: RM two-way ANOVA, Holm–Šidák test, WT versus KO at 300 ms, P = 0.036, t = 2.623, d.f. = 220; at 400 ms, P = 0.021, t = 2.904, d.f. = 220; at 500 ms, P = 0.011, t = 3.314, d.f. = 220; at 600 ms, P = 0.013, t = 3.22, d.f. = 220; at 700 ms, P = 0.021, t = 2.998, d.f. = 220; at 800 ms, P = 0.015, t = 3.127, d.f. = 220; at 900 ms, P = 0.021, t = 2.951, d.f. = 220; at 1,000 ms, P = 0.037, t = 2.623, d.f. = 220. Figure 5h: CM: Mann–Whitney U-test, P = 0.39, U = 38. CMH: Mann–Whitney U-test, P = 0.93, U = 94. Figure 5i RM two-way ANOVA, Holm–Šidák test, WT versus KO, P > 0.2, t = 0.58–1.2, d.f. = 108. Figure 5k: RM two-way ANOVA, Holm–Šidák test, WT versus KO, 17–402 mN, P = 0.09, 0.002, 0.0004, <0.0001, <0.0001, 0.0002, respectively. t = 1.76, 3.11, 3.64, 5.99, 5.14, 3.76, respectively. d.f. = 156. Figure 5m: t-test, P = 0.044, t = 2.11, d.f. = 25. Figure 5n: t-test, P = 0.048, t = 2.07, d.f. = 25. Figure 5o: Mann–Whitney U-test, P = 0.0002, U = 18. Extended Data Figure 7d: DRG: one-way ANOVA, F = 305.7, P < 0.0001, d.f.n, d.f.d = 2, 10. WT versus heterozygous, P < 0.0001, q = 21.28, d.f. = 10. WT versus KO, P < 0.0001, q = 34.32, d.f. = 10. Heterozygous versus KO, P < 0.0001, q = 12.37, d.f. = 10. Spinal cord: one-way ANOVA, F = 34.51, P < 0.0001, d.f.n, d.f.d = 2, 9. WT versus heterozygous, P = 0.0262, q = 4.535, d.f. = 9. WT versus KO, P < 0.0001, q = 11.65, d.f. = 9. Heterozygous versus KO, P = 0.0018, q = 7.118, d.f. = 9. Brain: one-way ANOVA, F = 16.23, P = 0.001, d.f.n, d.f.d = 2, 9. WT versus heterozygous, P = 0.1206, q = 3.142, d.f. = 9. WT versus KO, P = 0.0008, q = 7.996, d.f. = 9. Heterozygous versus KO, P = 0.0185, q = 4.854, d.f. = 9. Extended Data Figure 7e: one-way ANOVA, F = 980.5, P < 0.0001, d.f.n, d.f.d = 2, 3,749. WT versus heterozygous, P < 0.0001, q = 38.58, d.f. = 3,749. WT versus KO, P < 0.0001, q = 61.59, d.f. = 3,749. Heterozygous versus KO, P < 0.0001, q = 27.54, d.f. = 3,749. Extended Data Figure 8b: one-way ANOVA, F = 0.2183, P = 0.8050, d.f.n, d.f.d = 2, 33. Extended Data Figure 8c: one-way ANOVA, F = 2.308, P = 0.1163, d.f.n, d.f.d = 2, 33. Extended Data Figure 8d: one-way ANOVA, F = 0.6064, P = 0.5513, d.f.n, d.f.d = 2, 33. Extended Data Figure 8e: one-way ANOVA, F = 0.3041, P = 0.7398, d.f.n, d.f.d = 2, 33. Extended Data Figure 8f: one-way ANOVA, F = 2.012, P = 0.1497, d.f.n, d.f.d = 2, 33. Extended Data Figure 8g: one-way ANOVA, F = 1.035, P = 0.3666, d.f.n, d.f.d = 2, 33. Extended Data Figure 8h: one-way ANOVA, F = 2.960, P = 0.0657, d.f.n, d.f.d = 2, 33. Extended Data Figure 8i: one-way ANOVA, F = 0.7461, P = 0.4820, d.f.n, d.f.d = 2, 33. Extended Data Figure 9b: number of fragments, one-way ANOVA, F = 0.700, P = 0.5283, d.f.n, d.f.d = 2, 7. NMJ area, one-way ANOVA, F = 0.4309, P = 0.666, d.f.n, d.f.d = 2, 7. α-BuTx/synapNF, one-way ANOVA, F = 1.197, P = 0.3572, d.f.n, d.f.d = 2, 7. synapNF/α-BuTx, one-way ANOVA, F = 1.587, P = 0.2703, d.f.n, d.f.d = 2, 7. Extended Data Figure 10a: brain, t-test, P = 0.32, t = 1.104, d.f. = 5. Spinal cord, t-test, P = 0.006, t = 4.56, d.f. = 5. Extended Data Figure 10b: RMP, t-test, P = 0.652, t = 0.453, d.f. = 41. Input resistance, t-test, P = 0.181, t = 1.36, d.f. = 40. Rheobase, Mann–Whitney U-test, P = 0.114, U = 144. Extended Data Figure 10c: amplitude, Mann–Whitney U-test, P = 0.511, U = 71. Frequency, Mann–Whitney U-test, P = 0.84, U = 80. Extended Data Figure 10d: dorsal horn, t-test, P = 0.854, t = 0.19, d.f. = 7. Ventral horn, t-test, P = 0.04, t = 2.50, d.f. = 7. Extended Data Figure 11a: C/V: CM, t-test, P = 0.67, t = 0.419, d.f. = 18. CMH, Mann–Whitney U-test, P = 0.589, U = 91. AM, Mann–Whitney U-test, P = 0.38, U = 30. D-hair, t-test, P = 0.192, t = 1.362, d.f. = 16. RA, Mann–Whitney U-test, P = 0.60, U = 38. SA, t-test, P = 0.141, t = 1.538, d.f. = 18. Extended Data Figure 11b: AM, t-test, P = 0.41, t = 0.847, d.f. = 16. D-hair, Mann–Whitney U-test, P = 0.712, U = 35.50. RA, t-test, P = 0.70, t = 0.38, d.f. = 17. SA, Mann–Whitney U-test, P > 0.99, U = 49.50. Extended Data Figure 11c: AM, RM two-way ANOVA, Holm–Šidák test, WT versus KO, P > 0.3, t = 1.0–0.008, d.f. = 96. D-hair, RM two-way ANOVA, Holm–Šidák test, WT versus KO, 75–450, P > 0.096, t = 0.29, 0.15, 0.4, respectively; 1,500 μm s−1, P = 0.094, t = 2.30, d.f. = 64. RA-LTMR, RM two-way ANOVA, Holm–Šidák test, WT versus KO, 75–1,500 μm s−1, P > 0.97, t = 0.16, 0.26, 0.004, 0.49, respectively, d.f. = 68. SA-LTMR, RM two-way ANOVA, Holm–Šidák test, WT versus KO, 75–1,500 μm s−1, P > 0.98, t = 0.25, 0.44, 0.25, 0.32, respectively, d.f. = 72.
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