2024.01.11.575033v1.full-html.html

Analgesic targets identified in mouse sensory neuron
somata and terminal pain translatomes.

M. Ali Bangash

, Cankut Cubuk

, Federico Iseppon

, Rayan Haroun

, Ana P. Luiz

Manuel Arcangeletti

, Samuel J. Gossage

, Sonia Santana-Varela

, James J. Cox

Myles J. Lewis

, John N. Wood

and Jing Zhao

Molecular Nociception Group, Wolfson Institute for Biomedical Research, University

College London WC1E 6BT, UK

Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute,

Barts and The London School of Medicine and Dentistry, Queen Mary University of London,
London, EC1M 6BQ, UK

*Corresponding Authors

Drs Bangash, Cubuk, and Iseppon are equal first authors.

Correspondence to

j.wood@ucl.ac.uk

or jing02.zhao@ucl.ac.uk

Abstract

The relationship between transcription and protein expression is complex. We

identified polysome-associated RNA transcripts in the somata and central terminals of

mouse sensory neurons in control, painful (+ Nerve Growth Factor (NGF)) and pain-

free conditions (Nav1.7 null mice). The majority (98%) of translated transcripts are

shared between male and female mice in both the somata and terminals. Some

transcripts are highly enriched in the somata or terminals. Changes in the translatome

in painful and pain-free conditions include novel and known regulators of pain

pathways. Antisense knockdown of selected somatic and terminal polysome-

associated transcripts that correlate with pain states diminished pain behaviour.

Terminal-enriched transcripts encoding synaptic proteins (e.g. Synaptotagmin), non-

coding RNAs, transcription factors (e.g. Znf431), proteins associated with trans-

synaptic trafficking (HoxC9), GABA generating enzymes (Gad1 and Gad2) and

neuropeptides (Penk). Thus, central terminal translation may well be a significant

regulatory locus for peripheral input from sensory neurons.

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Introduction

Sensory neurons are essential to drive almost all pain conditions and so their

biology is of keen interest for analgesic drug development. Sensory neuron-specific

transcripts,

mRNA transcriptional profiles

2,3

and proteomic studies

4,5

have been used

to examine sensory neurons in control and pain states. Distinct rather than common

sets of transcriptional responses are hallmarks of different pain stimuli

suggesting

that a number of mechanisms drive pain from the periphery. RNA-Sequencing (RNA-

seq) is often used to characterise sensory neurons but may miss low abundance

RNAs.

In addition, transcription is not necessarily coupled to protein translation and

mRNA levels are not sufficient to predict protein concentrations.

In cells as large as

sensory neurons, with processes of up to a meter in length in humans, protein

synthesis does not only occur in somata. Axonal protein synthesis has been observed

whilst presynaptic protein synthesis in CNS neurons has been causally related to

neurotransmitter release.

The control of mRNA transport from soma to terminals is

complex and incompletely understood.

The central terminals of sensory neurons are a key regulatory site in pain

pathways, as exemplified by Nav1.7 null mutant mice, where deficits in the central

terminals leads to loss of neurotransmitter release resulting in a pain-free

phenotype.

11,12

Thus defining which proteins are selectively translated in sensory

neuron terminals is potentially important and provides information that is not revealed

by transcriptional analysis. In this study, we have used the technique of

immunoprecipitating polysomes that are actively engaged in protein synthesis, so that

we can identify ribosome-associated mRNAs in dorsal root ganglion (DRG) sensory

neurons. Translating ribosome affinity purification (TRAP) exploits an epitope tagged

(eGFP-L10) ribosomal protein as a target for antibodies that enable translating

polysomes to be isolated.

13,14

This approach has been used to examine somatic

translatomes in sensory neurons in neuronal injury

and neuropathic pain.

These

studies have also shown potential sexual dimorphism in prostaglandin signalling from

somatic sensory translatomes.

We modified the somatic-TRAP method (see methods) to enable specific enrichment

and isolation of ribosome-bound actively translating mRNAs from both the somata and

the central terminals of sensory neurons. We coupled the TRAP method with a DRG-

specific Cre recombinase, using Advillin-Cre to enable DRG neuron-specific eGFP

tagging of sensory neuron ribosomes. This enables isolation of actively translating

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mRNAs from both sensory neuronal somata and central terminals. We asked whether

the translatome was gender specific, and if it changed in painful or pain free conditions.

We used Nerve Growth Factor (NGF) to lower pain thresholds and the Nav1.7

knockout mouse as a pain-free mouse model to examine pain related alterations in

translated proteins. We examined some identified pain-related transcripts using

antisense oligonucleotides to block translation to test any significant role in pain

behaviour. Here we describe the somatic and terminal translatome of mice and define

known and novel analgesic targets involved in pain pathways identified with TRAP

technology.

Results

The technology employed to define ribosome-associated transcripts in the somata and

terminals of sensory neurons is described in Figure 1. In order to isolate mRNAs

translated in soma and central terminals of DRG neurons, we used the eGFP-L10

line,

in which Cre-mediated recombination activated expression of the 60S ribosomal

subunit, L10a (RPL10a) tagged to eGFP. We crossed the eGFP-L10a line with the

Advillin-Cre line which expresses Cre in all DRG sensory neurons (Fig 1A),

permanently labelling the ribosomes in both somata and central terminals with GFP.

We sought to visualise tagged ribosomes using immunocytochemistry with GFP

antibodies, detecting GFP in both the DRG soma and central terminals in the spinal

cord (Fig 1B), confirming TRAP can label ribosomes in central DRG synapses. We

confirmed the somatic ribosomal labelling with GFP using RT-PCR (Fig 1Ci) and

immunoblotting using GFP antibodies (Fig 1Cii). The mRNA bound to ribosomes

represents a very small fraction of total mRNA especially so in the central terminals

and GFP-L10a levels from spinal cord were thus below the detection level of

immunoblotting (Fig 1Cii), whilst the lack of a RT-PCR signal in terminal samples

suggests that the ribosomal subunits are not themselves translated in the terminals

but originate in the soma.

In order to assess the level of background mRNA non-specifically binding to

immunoglobulins, beads or protein L, we examined the signal from eGFP-L10a lines

without Cre, detecting no GFP signal (Fig1B, Ci, and Cii) and detecting negligible

amounts of total mRNA immunoprecipitated from these Cre-negative samples.

Therefore, the immunoprecipitation of GFP-tagged ribosomal-mRNA complexes from

dissected DRG and spinal cord seems to reflect polysome-associated mRNA in these

samples.

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Figure 1: TRAP Strategy for polysomes isolation and sequencing

Generation of Adv-Cre-eGFPL10 mice. eGFP L10 mice with an upstream floxed

stop sequence were mated with Adv-Cre mice to generate DRG specific GFP-tagging

of ribosomes.

Somatic and Central Terminal TRAP Strategy: Immunocytochemistry of DRG and

Spinal Cord slices showing GFP-tagged ribosomal expression using polyclonal anti-

GFP antibody. Scale Bar: 50μm. Tagged ribosomes were affinity purified using

monoclonal anti-GFP antibodies before DGE analysis.

RT-PCR detection (

) and immunoblotting (

) of GFP-tagged ribosomes from

somatic and central terminal lysates.

NGF-

evoked increased pain sensitivity was measured using the Hargreaves’ test in

both male and female mice.

The acute pain-free status of Advillin-Cre Nav1.7 null mice was confirmed with

measurements of thermal (

) and mechanical (

) thresholds.

Mean latencies and withdrawal thresholds in

and

were compared using unpaired

t-test. * = p<0.05; **** = p<0.0001.

Sex-specific translatomes?

We analysed somatic ribosome bound mRNAs (the translatome) from dissected DRGs

from Adv-Cre-GFPL10a mice using RNA-seq. We compared male Adv-Cre;

eGFPL10a samples directly with female samples (Fig 2A). The alternative method of

normalizing the TRAP IP (translatome) to the unbound

supernatant (“transcriptome”)

is likely to dilute the sensory neuron translatome because the unbound fraction from

a heterogenous tissue such as the spinal cord or DRG will contain many non-neuronal

mRNAs.

The potential problem of low-level contamination of RNA transcripts in our TRAP

samples is to some extent obviated by the fact that concentrating on high read number

altered transcripts in different protocols is likely to reflect specific immunoprecipitation

profiles. We sequenced 20,480 genes from somatic male and female Adv-Cre;

eGFPL10a DRGs, out of which 460 were differentially expressed (Fig 2A, B, and

Tables S1, S2).

Since TRAP isolates ribosome-bound mRNAs in a cell-type specific manner, we tested

the specificity of our TRAP IP by examining the expression of non-neuronal DRG

genes (e.g.

GFAP

) and found them to be completely absent from IP samples (Fig 2E).

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This confirms the specificity of the TRAP pull down. We have listed all sequenced

genes with read counts, fold changes, log2 fold changes and p-values in a series of

supplementary tables that link to each of the Volcano Figures (Figure S1 and Tables

S1-S9).

Advillin-Cre; eGFPL10a somatic and terminal translatomes are shared by male

and female mice

Despite the low abundance of ribosome-bound mRNA in central terminals of DRGs,

we were able to successfully isolate and sequence the terminal translatome from

pooled dissected spinal cords from Advillin-Cre; eGFPL10a mice (Fig. 2B). Although

we sequenced a higher number of low-read number genes in the terminal compared

to the somatic TRAP, this likely represented a higher background from the greater

mass of spinal cord tissue.

Comparing male and female DRG sensory neuron total translatomes directly, we

identified a small fraction of sex specific transcripts (116 of 20480 genes), indicating

predominantly shared pain pathways including key pain genes (Fig 2C, D). We tested

the specificity of our terminal IP by examining the expression of non-neuronal DRG

genes (for example GFAP) and postsynaptic dorsal horn neuronal genes (for example

PDYN absent in normal DRG neurons

) which were found to be entirely absent in our

transcriptome data sets (Fig 2E).

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Figure 2: Sex differences in male and female translatomes

Volcano plot showing differentially expressed translated genes in the soma between

male (n=6) and female (n=6) samples. Statistical analysis by Wald test using DESeq2.

Genes on the left side of the plot are upregulated in females and upregulated male

genes are shown on the right side. Non-significant genes are shown in grey, significant

genes (p<0.05) with log

fold change < 1 with blue and significant genes with log

fold

change > 1 are represented with red colour. X-axis and y-axis show, log

fold change

and -log

p-value, respectively. Complete data comprising read numbers and fold

increase (log

) with p-values are presented in excel format in table S1.

Same as in

, but the volcano plot shows the genes expressed in the terminals.

Complete data comprising read numbers and fold increase (log

) with p-values are

presented in excel format in table S2. A volcano plot showing pooled data from somata

and terminals is detailed in figure S1.

Bar plot comparing the expression levels of known pain genes in male (in blue) and

female (in red) somata.

Bar plot comparing the expression levels of known pain genes in male (in blue) and

female (in red) terminals.

Heatmap showing the Log read counts of different non neuronal genes. The

expression of these genes is very low when compared to control genes (Nefl and

Nefm) expressed at similar levels in soma and terminals translatomes.

Normalized read counts in

and

were compared using unpaired t-test.

The vast majority (>98%) of the translatome was shared between male and female

mice suggesting predominantly shared pain mechanisms, including key pain genes

(e.g.

Scn9a

Scn10a

) (Fig 2C, Tables S1, S2). These numbers are consistent with

recent TRAP-seq studies

22,23

, including a study of sex differences from TRAP samples

in Nav1.8+ neurons

. In total DRG neuronal samples we found a small increase in

Ptgds

mRNA in female mouse somata with low-read numbers (See Table S1)

consistent with the data in Tavares-Ferreira

et al.

When comparing somatic male and female translatome data we found that

Piezo1

, a

mechanosensitive channel, was upregulated in females although transcript levels

were low. In female terminals,

Kcnq1ot1

is 8-fold enriched

– this is a long ncRNA that

is known to interact with chromatin.

Intriguingly

Xist

, which is totally absent from

somatic translatomes, is found in central terminals and enriched in female mice.

This

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gene, crucial for X-inactivation, may associate with polysomes like other ncRNAs but

its mechanisms of action remain uncertain.

Nhsl2

is a cytoplasmic calcium-binding

protein 20-fold upregulated in females that is linked to Nance-Horan syndrome.

In male somata, the gene

Chchd2

implicated in stress responses to low oxygen was

upregulated 20-fold with high read numbers

whilst

Jpot1

, which encodes a nuclear

envelope protein, was 50-fold upregulated. Very interestingly, the mRNA encoding the

isoform of ribosomal protein RPS4X is 30-fold enriched in the male translatome,

suggesting that there is a potential for gender specific differences in ribosomal

composition at the terminals.

The top genes differentially upregulated in male terminals include the translational

control gene

Eif2s3y

which is 30-fold upregulated in males, and is known to enhance

synaptic efficacy in male but not female mice. Its overexpression is linked to autism.

Scarna2

is an ncRNA that has multiple functions in DNA repair and is 30-fold

upregulated in males, whilst

Amigo2

has been implicated in synaptic function and cell-

cell interactions, and is 20-fold upregulated in males.

Taken together the results support the claim that terminal translatome transcripts

accurately reflect transcripts present in sensory neurons but generally absent from

other cell types (Table S2). The fact that major pain related genes are shared by male

and female mice led us to focus on male mice to minimise animal usage.

Distinct translatomes in somata and terminals

Although 90% of transcripts were common to terminal and soma translatomes, and

those present at very low read levels potentially included some contaminating material,

about 5% of transcripts were enriched either in the soma or in the terminals, (1704

genes from a total of 20,480 examined) some more than 30-fold (Figure 3 and S2, and

Table S3). There were some interesting findings. For example,

Penk

mRNA encoding

the enkephalins, was substantially enriched in the terminals and absent from the

soma, a finding consistent with recent insights into opioid signalling within the spinal

cord and regulation of pain pathways.

In contrast, Calcitonin Gene Related Peptide

(CGRP) genes were principally translated in the soma, perhaps because these

peptides play an important role at the peripheral terminal in regulating blood flow.

Voltage-gated sodium channels are a topic of interest for pain studies, and Nav1.1

was enriched in the terminals of sensory neurons, whilst Nav1.7, Nav1.8 and the key

regulator of Nav1.8 expression p11 (S100A10) were substantially enriched in somatic

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Figure 3: Somatic versus terminal translatomes

Volcano plot showing differentially expressed translated genes between somata

(n=6) and terminal (n=6) samples. Genes on the left side of the plot are upregulated

in somata and upregulated terminal genes are shown on the right side. Non-significant

transcripts are grey, significant genes (p<0.05) with log2 fold change < 1 with blue and

significant genes with log

fold change > 1 are represented with a red colour. x-axis

and y-axis show, log

fold change and -log

p-value, respectively. Complete data

comprising read numbers and fold increase (log

) with p-values are presented in table

S3. Futher comparisons between somata and terminal genes, as well as gene

enrichment pathways in both conditions, are detailed in figure S2.

Antisense oligonucleotide (ASO) inhibition of terminal translatome transcripts

Nos1ap lowers heat and mechanical pain thresholds. Mice (n=10) were tested with

the von Frey (

), Hargreaves’ (

) and Randall Selitto (

iii

) tests before (baseline) and

after ASO intrathecal injection (treated).

Antisense oligonucleotide (ASO) inhibition of terminal translatome transcripts

Nos1ap lowers heat and mechanical pain thresholds. Mice (n=10) were tested with

the von Frey (

), Hargreaves’ (

) and Randall Selitto (

iii

) tests before (baseline) and

after ASO intrathecal injection (treated). Substantially diminished pain behaviour was

apparent in both

and

. Experiments using control ASOs are shown in figure S3.

Cancer induced bone pain is attenuated by ASO knockdown of Gnas. Limb use and

weight bearing were improved with ASO knockdown.

ASO knockdown targeting combined lncRNAs Malat1, Kcnq1ot1, and Snhg11 leads

to lowered heat pain behaviour as measured with a Hargreaves’ apparatus.

Experiments silencing individual lncRNAs are shown in figure S4.

Motor impairment tests for

, and

are shown in figure S5.

Mean latencies and withdrawal thresholds in

, and

were compared using paired

t-test. Limb scores and weight-bearing fractions in

were compared using restricted

maximum likelihood analysis (REML). * = p<0.05; *** = p<0.001.

We investigated the role of some peripherally enriched transcripts using antisense

knock-down.

Nos1ap

has been linked to neuropathic pain in global knock-out

studies.

It is also implicated in neuropathic pain in mice and some progress has been

made in developing blockers of interactions with NOS. Our data suggest that terminal

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Nos1ap

plays a role in pain induction.

Gnas

is an interesting and complex imprinted

gene that encodes the alpha subunit of the adenyl cyclase activating complex Gs.

Gain-of-function mutations in

GNAS

are associated with painful conditions in

humans.

We found a clear inhibition of thermal and mechanical acute pain with

antisense oligonucleotides (ASO) directed against

Gnas

delivered intrathecally, whilst

control scrambled ASOs were inactive (Figures 3B, C, and Figure S3A, B). Given the

role of adenyl cyclases in inflammatory pain, this is an interesting potential target for

localised pain therapies. To further check this hypothesis, we tested the translation

knockdown of

Gnas

in a mouse model of cancer-induced bone pain using three

intrathecal injections of ASOs against

Gnas

(Figure 3D). The knockdown of this gene

resulted in a modest reduction of pain-like behaviour associated with this model, as

assessed by limb-use scoring and weight-bearing. Statistical analyses indicated that

the knockdown of

Gnas

expression slowed down the reduction of the limb-use

significantly compared to control mice (Figure 3Di) (REstricted Maximum Likelihood

(REML) analysis, p-value=0.0486). While the improvement of weight-bearing following

Gnas

knockdown was apparent, it failed to reach an 0.05 level of statistical

significance (REML, p-value= 0.0537, Figure 3Dii). It is likely that our antisense

protocols will diminish both transcript levels as well as the translation of candidate

target genes. Nevertheless, if there is less mRNA to translate, this approach still

relates to the role of the translatome in regulating pain pathways.

The TRAP RNA-seq data not only identified protein-coding mRNAs but also a

significant number of non-coding RNAs that were associated with the sensory neuron

ribosomes

. This is consistent with previous polysome profiling data where it was

found that the majority (70%) of cytoplasmic-expressed long non-coding (lnc) RNAs

have more than half of their cytoplasmic copies associated with polysomal fractions

We focused on three high read number ncRNAs associated with sensory neuron

polysomes.

Malat1

Kcnq1ot1

and

Snhg11

and found that antisense knockdown

could lower heat pain thresholds when all three ncRNAS were targeted, without any

effect shown from the scrambled control ASOs (Figure 3E, Figure S3C). However,

individually targeted ASOs did not have any statistically significant effect (Figure S4),

suggesting a minor contribution to heat thresholds of the tested ncRNAs. Whether the

sensory neuron polysome-associated lncRNAs identified here actively participate in

regulating translation, or have other ribosomal functions, in different pain states merits

further investigation.

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NGF-induced pain states alter translatome activity

In order to address potential alterations in the translatome int pain states, we used the

well characterised inflammatory mediator NGF to sensitise mouse tissues globally

(Figure 1D). We then used TRAP technology to compare the polysome-associated

transcripts in an NGF-evoked pain state with normal mice (Tables S4, S5). A number

of studies have examined translational alterations in NGF-evoked pain states in mice,

but these events do not seem to be mirrored in the polysome-associated transcripts

that we identified

Nerve growth factor acting through TrkA is known to sensitise pain pathways at the

level of sensory neuron activation. We examined the alterations in the soma and

terminals comparing NGF-treated samples with control samples. We found 268 genes

of 20,480 examined were dysregulated in the soma, whilst more changes (369

transcripts) were altered in the terminal from the 20,480 examined (Figure 4).

Figure 4: NGF-induced transcripts in somatic and terminal translatomes

Volcano plots showing differentially expressed translated genes between NGF

enriched (n=6) and control (n=6) samples in the somata (

) and terminals (

DESeq2 was used for statistical analysis. Genes on the left side of the plot are down

regulated by NGF and NGF upregulated genes are shown on the right side. Non-

significant genes are in grey, significant genes (p<0.05) with log

fold change < 1 with

blue and significant genes with log

fold change > 1 are represented with red colour.

x-axis and y-axis show, log

fold change and -log

p-value, respectively. Complete

data comprising read numbers and fold increase (with log

) with p-values are

presented in excel format in tables S4 and S5. Histograms detailing the gene

enrichment pathways in both conditions are shown in figure S6.

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A range of mRNAs were upregulated in the somatic translatome on NGF treatment

(Figure 4A). These included mitochondrial proteins that could be involved in increased

metabolic activity in activated sensory neurons,

Unc79

which encodes the mouse

homologue of UNC79,

which is a subunit of the sodium ion leak channel NALCN,

and

Dok4

, a transmembrane tyrosine kinase receptor involved in regulating neurite

outgrowth during nervous system development

In terminals (Figure 4B) we found that

Gcn1

, whose encoded protein enhances

translation by removing stalled ribosomes and is associated with polysomes, was

strongly upregulated consistent with increased protein synthesis.

Other enhanced

transcripts included phenol sulfotransferase

Sult1a1,

whose human homologue is

highly inducible by dopamine and is part of a family of proteins thought to protect

neurons from neurotoxicity,

as well as

Tmem252

thought to play a possible role in

kidney function.

Bioinformatic analysis links enhanced glutamatergic synapse

activity as well as PI3 Kinase Akt signalling activity with the terminals to NGF -induced

enhanced pain states

– in agreement with such enhanced activity found in the spinal

cord in chronic pain (Figure S6)

Pain-free Nav1.7 null mouse translatomes

We examined the alteration in translatomes in the pain free Nav1.7 null mouse (Figure

5, Tables S6, S7). Amongst genes downregulated in the somatic translatome are

several that were not detected in microarray analysis of Nav1.7 null DRG

. Genes

shown in Figure 5 could be potential mediators in pain pathways. 132 genes were

down regulated in soma and 557 were lower in terminals of pan-DRG pain-free Nav1.7

null mice.

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Figure 5: Altered translatomes in Nav1.7 null, pain-free mice soma and

terminals.

Volcano plots showing differentially expressed translated genes between Nav1.7 null

(n=6) and control (n=6) samples in the somata (

) and terminals (

). Genes on the

left side of the plot are down regulated in Nav1.7 nulls and upregulated genes are

shown on the right side. Non-significant genes are in grey, significant genes (p<0.05)

with log

fold change < 1 with blue and significant genes with log

fold change > 1 are

represented with red colour. X-axis and y-axis show, log

fold change and -log

value, respectively. Complete data comprising read numbers and fold increase (log

)

with p-values are presented in excel format in tables S6 and S7. Histograms detailing

the gene enrichment pathways in both conditions are shown in figure S7.

Amongst the genes downregulated in Nav1.7 null somata (Figure 5A), the

Clock

gene

is a bHLH transcription factor that controls the expression of the Per genes that in

DRG regulates neuronal excitability with a circadian rhythm.

Mrgprd

is a GPCR that

is activated by enkephalins and other ligands.

Protein kinase C theta (

Prkcq

) is a

calcium-independent serine-threonine kinase involved in neurotransmitter release.

Tyrosine hydroxylase (

) generates dopamine from tyrosine that then gives rise to

catecholamines all of which are implicated in pain regulation. Casein kinase 1 gamma

1 (

Csnk1g1

) phosphorylates acidic proteins on serine and threonine and has been

linked to epilepsy

Within the terminals (Figure 5B), transcripts reduced in the Nav1.7 null mice

translatome include

Ppp6r1

, a phosphatase that may be involved in NF-kappa B

signalling.

Mepce

is involved in RNA methylation and enhances Pol2 dependent

transcription.

Tssc4

is a tumour suppressor implicated in a large range of pathologies.

Chp1

is a

key component of the Na/H exchanger and is a calcium binding EF hand protein.

Inflammatory pain as well as intracellular pH control are linked to these proteins.

Hhipl1

is a hedgehog interacting protein linked to morphogenesis and differentiation.

Bioinformatic analysis shows diminished glutamatergic and dopaminergic synapse

activity in Nav1.7 nulls, and oxidative phosphorylation genes are also downregulated

in both somata and terminals in the pain free state. This fits with less sensory neuron

activity in the absence of nociceptive input.

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Identifying translated proteins that correlate with pain states

Now that we had the repertoires of translated genes in pain-free and painful states

from somata and terminals of DRG sensory neurons, we were able to focus on

translated genes that correlate strongly with enhanced pain and examine their

potential significance using antisense knock-down behavioural assays (Figure 6).

Figure 6: Differences in gene expression between NGF-treated and NaV1.7 null

mice soma and terminals.

Scatter plots showing differentially expressed translated genes between Nav1.7 null

(n=6) and NGF treated (n=6) samples in the somata (

) and terminals (

). Non-

significant genes are not showed; significant genes (p<0.05) in the NGF vs WT

comparison are shown in green, whereas significant genes (p<0.05) in the 1.7 null vs

WT comparison are shown in blue. X-axis and y-axis show log

fold change for the

two comparisons. Complete data comprising read numbers and fold increase (log

)

with p-values are presented in excel format in tables S8 and S9. Histograms detailing

the gene enrichment pathways in both conditions are shown in figure S8.

We examined the relative expression of promising candidate genes in pain states, in

the pain free mouse and the wild type controls to select potential targets for antisense

experiments. Volcano plots are shown in Figure 4, 5, and 6, where a number of

potential targets are identified.

We compared expression of some of the most promising candidate genes in the

somata of mice as shown in Figure 7A, where the relative expression is colour coded.

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Figure 7: Pain-related somatic transcripts and effects of transcript ASO

knockdown on acute pain behaviour.

Color-coded levels of expression in individual mice (abscissa) for transcripts that

show a level of ribosome association with enhanced pain levels

Relative levels of expression of transcripts shown in (

) derived from supplementary

tables 4,6, and 8, together with Pearson’s correlation coefficient and the respective p

value of the correlation.

ASO knockdown targeting combined Sdcbp, Ttyh3, and Wdr91 genes show a mild

effect on mechanical sensation.

ASO knockdown targeting Necab2 leads to lowered acute mechanical pain

behaviour.

= von Frey test,

= Hargreaves’ heat test,

iii

= Randall Selitto test in both

and

Motor impairment tests for

and

are shown in figure S5.

Mean latencies and withdrawal thresholds in

and

were compared using paired t-

test. * = p<0.05.

We found some transcripts were present at very low levels in both pain free and normal

mice but highly expressed with NGF (e.g.

Wdr91

Cav2

), whilst others showed a

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gradation of increased expression that correlated with enhanced pain states (e.g.

Sdcbp

Rgs4

) (Figure 7B).

Sdcbp

or syntenin is associated with kainate receptor

expression whilst the

Necab

family of genes are neuronal specific

and

Necab2

associated with mGlu receptors linked to autism and neurodegeneration

62,63

. Sensory

neuron glutamate receptors have been implicated in altered pain states.

Ttyh3

, a

chloride channel, has been implicated in epilepsy, chronic pain, and viral infections.

Related channels have been reported to form Ca

- and cell volume-regulated anion

channels structurally distinct from any characterized protein family with potential roles

in cell adhesion, migration, and developmental signalling.

Wdr91

is implicated in

neurodegeneration and lysosome function.

Psme3

activates the proteosome,

whilst

Cav2

is a caveolin-like molecule of unknown function.

Mtmr3

or Myotubularin-

related protein regulates the cell cycle.

Ncaph2

is implicated in cognitive decline and

AD,

whilst

Rgs4

is linked to schizophrenia and G protein function.

Rac1

is a small

GTPase linked to the inflammasome

and

Uhrf1bp11

is a lipid transfer bridge.

We decided to test an individual transcript

Necab2

, and in addition mix three sets of

antisense oligonucleotides for a further experiment because we have a large number

of potential targets, in order to minimise animal use. We selected

Sdcbp

, a syndecan-

binding protein that shows excellent translational correlation with enriched expression

after NGF treatment and lower expression in NaV1.7 null mice;

Ttyh3

a large

conductance calcium-activated chloride channel that presents high expression in

NGF-treated mice and is absent in Na

1.7 nulls, and

Wdr91

, a negative regulator of

the PI3 kinase activity which is selectively translated only after NGF-dependent pain

induction. This mix showed a minor effect on mechanical thresholds using the Von

Frey apparatus and Randall Selitto apparatus, and little to no effect on heat sensation

(Figure 7C).

We also examined the effect of antisense oligonucleotides delivered intrathecally

directed against the single target

Necab2

, which is NGF-induced and absent in pain-

free samples (Figure 7D). This protein is a neuronal calcium-binding protein that binds

to and modulates the function of two or more receptors, including adenosine A(2A)

receptors and metabotropic glutamate receptor type 5 that are implicated in pain

pathways. The inhibition of

Necab2

expression resulted in a diminution in noxious

mechanosensation as measured with the Randall-Selitto apparatus, with little effect

on heat sensing.

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Changes in TRAP data from cell bodies contrasts with changes in central terminals,

where proteins synthesised may be expected to play some role in interactions with

spinal cord neurons and central pain pathways (Tables S8, S9). Once again, we

exploited colour coded tables to summarise interesting transcripts that show pain-

related expression. Two uncharacterised transcripts,

Gm4202

and

Gm10033

, showed

an inverse correlation to pain and were not further investigated.

Zfp105

(ZNF35) is a

retinoic acid regulated transcription factor.

Rps6ka3

is a member of the ribosomal 6

kinase family that play a wide-ranging role in signal transduction.

BCR is a GTPase

activating protein that also acts on tyrosine kinases.

Thoc7

has an important role in

RNA translocation from the nucleus as well as viral release.

We examined antisense knockdown of transcripts like

Thoc7

that show a pain

correlation in terms of local protein synthesis (Figure 8).

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Figure 8: Pain-related central terminal transcripts and effects of transcript ASO

knockdown on acute pain behaviour.

Color-coded levels of expression in individual mice (abscissa) for transcripts that

show a level of ribosome association with enhanced pain levels

Relative levels of expression of transcripts shown in (

) derived from supplementary

tables 5, 7, and 9, together with Pearson’s correlation coefficient and the respective p

value of the correlation.

ASO knockdown targeting Ube2f leads to lowered acute mechanical and thermal

pain behaviour.

ASO knockdown targeting PP1r15b leads to lowered acute mechanical and thermal

pain behaviour.

ASO knockdown targeting Zfp362 shows no significant change in acute pain

behaviour.

ASO knockdown targeting Thoc7 leads to lowered acute mechanical pain behaviour.

= von Frey test,

= Hargreaves’ heat test,

iii

= Randall Selitto test in

and

Motor impairment tests for

, and

are shown in figure S5.

Mean latencies and withdrawal thresholds in

and

were compared using

paired t-test. * = p<0.05; ** = p<0.01.

Other terminally translated proteins further investigated include

Ube2f

, a ubiquitin

conjugating enzyme involved in neddylation that is known to play a role in pain

pathways, and to stabilise voltage gated sodium channel activity.

Ppp1r15b

is a

fascinating molecule that is regulated by glutamate receptor activity that controls its

kinase or phosphatase inhibitory activity.

Intriguingly, this protein can control the

activity of

Eif2

, a key control for local translation. Thus, both proteins show a clear link

to pain pathways. Lastly,

Zfp362

is assumed to be a transcription factor.

Pafah1b3

removes an acetyl group from PAF: its function is uncertain, but it seems to have a

key role in brain development.

Knockdown of both

Ube2f

and

Ppp1r15b

showed a significant reduction of both

mechanical and thermal sensitivity across all the battery of tests used, highlighting

even more their potential role in pain pathways (Figure 8C, D).

Thoc7

showed a

significant increase in mechanical thresholds when using the Randall-Selitto

apparatus, whereas knockdown of

Zfp362

did not show any effect on any of the pain

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tests performed (Figure 8E, F). For all antisense experiments, motor coordination was

measured with a rotarod apparatus, and no impairment was observed (Figure S5).

Discussion

Pain pathways depend on sensory neuron neurotransmitter input into the central

nervous system evoked by damaging stimuli. The molecular organisation of the first

synapse is incompletely understood and mainly rely on immunocytochemical studies.

Protein synthesis is finely regulated at several stages, from transcription to translation

and trafficking. Single cell RNA-seq has given helpful insights into cellular diversity

and function, but there are limitations including the inability to detect low level

transcripts, altered transcripts during circadian changes, and further changes caused

by isolation of single cells from their normal milieu. Unfortunately, proteomic analysis

is relatively insensitive, making single cell proteomic analysis at present problematic.

There are thus significant gaps in our knowledge of the structure of the central

terminals of sensory neurons, and potential changes that may occur in acute or chronic

pain states. One interesting element in the physiology of sensory neurons is the

existence of local protein synthesis at axon terminals. We have adapted the TRAP

technology developed by Liu et al

to examine proteins synthesised both in cell bodies

and at the central terminals that may have a role in synaptic function. By comparing

polysome-associated transcripts in pain states with those in normal or pain-free states,

we have identified several mRNAs that could play a role in pain pathways.

Interestingly, there is no obvious link between the translatome and the transcriptome

in the somata of sensory neurons.

Similarly, the mechanism and signals that result in

mRNA translocation are poorly understood.

There are no obvious consensus

5’ or

3’ UTR sequences linked to central terminal polysome-associated transcripts. We

have used bioinformatic tools to classify genes that are co-ordinately regulated in

response to altered pain states. These data are presented in Figure S6-S8.

A broad range of transcripts have been identified in this TRAP analysis, including data

that suggest the vast majority of translatome transcripts are common to male and

female mice. ncRNAs are present. These polysome-associated lncRNAs frequently

have long ‘pseudo’ 5’UTRs and are 5’ capped, features that are important for

ribosomal engagement and also nonsense-mediated decay.

37,77,78

For the majority of

known ribosome-associated lncRNAs, it is still unclear whether they are engaged by

the ribosomes for translation (e.g. producing short/micro peptides),

79-81

help to

regulate protein translation,

82-85

inertly reside in ribosomes or are degraded by the

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ribosome as a mechanism to control the cellular lncRNA population.

However, for

some specific lncRNAs their translation regulation function is known. For example,

lincRNA-p21 associates with polysomes and suppresses the translation of JUNB and

CTNNB1 mRNAs.

In contrast, the natural antisense transcript to ubiquitin carboxy-

terminal hydrolase L1 (AS-Uchl1), promotes the translation of Uchl1 by base pairing

with its sense gene at a SINEB2 element and helps associate the sense mRNA with

the active translating polysome.

Genes that seem to play a role in pain pathways include a range of functional proteins.

Mitochondrial genes that may play a role in the increased activity found in active

sensory neurons signalling pain states have been identified (e.g.COX, see Figure S6).

Other interesting transcripts that are clearly involved in pain pathways (e.g.

Penk

)

show no altered levels of translatome association.

The rate of translation of

polysome associated genes may be regulated by kinase and phosphatases acting on

eukaryotic initiation factors like EIF2, and such enzymes (e.g.

Ppp1r15b

are also

present in the central translatome, and so relative read counts may not give a complete

picture of effective translation.

Bioinformatic analysis (Figure S8) shows that enhanced pain leads to more activity of

genes involved in oxidative phosphorylation, synaptic vesicle activity, as one would

suspect if sensory neurons were more actively signalling in pain states.

One striking observation is the presence of transcription factors in the central terminal

translatome.

HoxC9

has been proposed to shuttle across membranes

and other

terminal Hox genes (for example

Hoxc8

) are implicated in motor neuron specification.

It is an intriguing possibility that Hox proteins translated at sensory neuron terminals

could exert functional effects on motor neurons.

We have used antisense oligonucleotides to examine a role for some of the

translatome mRNAs in acute pain and provide evidence that some do indeed

contribute to pain states. These reagents may diminish mRNA levels in general rather

than those associated with polysomes, but the net effect of diminishing protein

production should be the same. We first checked two terminally enriched candidates,

the G-protein regulatory protein

Gnas

and the Nitric Oxide synthase regulatory protein

Nos1ap

, both of which seem to play a role in acute pain. The novel genes that have

so far not been linked to pain pathways were identified by correlating expression with

enhanced pain states. Within the soma we found regulators of kainate receptor

expression (

Sdcbp

) as well as metabotropic glutamate receptors (

Necab2

50,51

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novel unique anion channel potentially activated by calcium (

Ttyh3

) was also identified

as well as

Cav2

, a caveolin

–like protein of unknown function. Both

Wdr91

and

Ncaph2

are implicated in neurodegeneration, whilst

Uhrf1bp1l

is a lipid transfer bridge and

Psme3

activates the proteosome.

Rgs4

regulates G-protein signalling and is a

schizophrenia risk factor gene.

Rac1

is linked to innate immunity and the

inflammasome whilst

Zfp362

is a potential transcription factor without activity in acute

pain. Tables S4-S9 contain complete rank ordered lists of altered genes with P values

and read counts.

Our functional studies demonstrate a clear role in acute pain for the terminally enriched

transcripts

Gnas

and

Nos1Ap

, as well as

Ppp1r15b

that regulates translational activity

via Eif proteins,

Thoc7

that regulates RNA transport and

Ube2f

a regulator of

neddylation are also linked to pain. Neither scrambled ASO controls nor

Zfp362

ASOs

showed any effect on pain behaviour (Figure 8E, Figure S3). Within the soma,

Necab2

was a strong candidate that showed a major effect on mechanical pain. With the

current availability of targeted delivery systems and advances in gene therapy, these

targets are worthy of further study in other models of human chronic pain. In the future

it would be helpful to appraise more complex pain states like chronic inflammatory and

neuropathic pain with the substantial number of candidate genes identified, but in the

interest of minimising animal suffering, candidates that have some genetic links to

human pain (e.g.

Ttyh3

) should be prioritised.

Acknowledgements

We acknowledge with gratitude the following sources of funding: Versus Arthritis UK

(21950), Medical Research Council (MR/V012509/1; 571476), and Cancer Research

UK (185341). This work acknowledges the support of the National Institute for Health

Research Barts Biomedical Research Centre (NIHR 203330). The views expressed

are those of the authors and do not represent those of the NHS, NIHR or funding

bodies.

Author Contributions

Conceptualization, M.A.B., J.Z., and J.N.W.; Formal Analysis, C.C., M.J.L.;

Investigation, M.A.B., F.I., A.P.L., M.A., R.H., S.J.G., S.S-V.; Resources, F.I., R.H.,

S.J.G., S.S-V; Data Curation, C.C.; Visualization, F.I., C.C., M.A.B.; Writing

– Original

Draft, J.N.W., J.Z., C.C., F.I.; Writing

– Review and Editing, F.I., R.H., J.J.C., M.J.L.,

J.Z., J.N.W.; Supervision, J.N.W., J.Z., M.J.L.; Funding Acquisition, J.N.W., M.J.L.;

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Declarations of Interest

The authors declare no competing interests.

STAR METHODS

KEY RESOURCES TABLE

REAGENT or RESOURCE

SOURCE

IDENTIFIER

Antibodies

19C8 anti-EGFP

Heintz Lab;
Rockefeller University

AB_2716737; Htz-GFP-
19C8

19F7 anti-EGFP

Heintz Lab;
Rockefeller University

AB_2716736; Htz-GFP-19F7

Alexa 488

‐

conjugated goat anti

‐

mouse

Invitrogen

Cat. # A32723

goat anti

‐

rabbit IgG

‐

HRP

Jackson
Immunoresearch Labs

AB_2313567;
Cat. # 111-035-003

goat anti

‐

mouse IgG

‐

HRP

Jackson
Immunoresearch Labs

AB_2338511;
Cat. #

115-035-116

Chemicals, peptides, and recombinant proteins

rRNasin

Promega

Cat. # N2511

Superasin

Applied Biosystems

Cat. # AM2696

TRIzol

Invitrogen

Cat. # 15596026

iScript Reverse Transcription Supermix

Bio-Rad

Cat. # 1708840

SsoAdvanced Universal SYBR Green
Supermix

Bio-Rad

Cat. # 1725270

Critical commercial assays

MyOne T1 Dynabeads

Invitrogen

Cat. # 65601

RNA Nanoprep kit

Agilent

Cat. # 400753

Quant-it Ribogreen kit

Invitrogen

Cat. # R11490

Pierce BCA protein assay kit

Sigma-Aldrich

Cat. # 71285-3

Super Signal West Dura

Thermo Scientific

Cat. # 34075

SMART-Seq v4 ultra-low Input RNA Kit

Takara Bio

Cat. # 634891

Deposited data

RNA-Seq source data

See Tables S1-9

N/A

Read counts and sample annotation files

Figshare

https://figshare.com/s/3e706
e13702a2fc40885

Behavioural assays data

Figshare

https://figshare.com/s/7bf8e1
bac93abfc51d98

Experimental models: Cell lines

Lewis lung carcinoma (LL/2) cells

ATCC

CRL-1642

Experimental models: Organisms/strains

Mouse: Na

1.7 flox

Nassar et al., 2004

N/A

Mouse: Advillin Cre

Zhou et al., 2010

N/A

Mouse: NaV1.8 Cre

Nassar et al., 2004

RRID:IMSR_JAX:036564

Mouse: eGFP-L10a

Liu J et al., 2014

RRID:IMSR_JAX:024750

Oligonucleotides

Primers for mouse genotyping

See Table 2

N/A

Software and algorithms

BBMap software v.38.94

JGI

https://jgi.doe.gov/data-and-
tools/software-tools/bbtools/

R studio

https://rstudio.com

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perpetuity. It is made available under a

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HiPathia v.2.10

Hipatia

http://hipathia.babelomics.or
g/

Prism

Graphpad

https://www.graphpad.com/

RESOURCE AVAILABILITY

Lead contact

Further information and requests for resources and reagents should be directed to and

will be fulfilled by the lead contact, John N. Wood (

j.wood@ucl.ac.uk

Materials availability

This study did not generate any new unique reagents.

Data and code availability

Data is available from the lead contact on reasonable request.

Complete data comprising read numbers, fold increase (log

) and p-values are

presented in tables S1-S9.

TRAP gene expression counts and sample annotation files, as well as behavioural

assays

data

files,

are

deposited

Mendeley

data

https://data.mendeley.com/preview/ppj2ptnpgz?a=0b4c72a3-e21c-4bf3-a8e4-

1d0e5b7abcc9

EXPERIMENTAL MODEL DETAILS

Animals

All experiments were performed in compliance with the UK Animals (Scientific

Procedures) Act 1986, under a Home Office project licence (PPL 413329A2). Mice

were housed in a 12-h light/dark cycle with

ad libitum

provision of food and water. All

mice were acclimatized for 1 week to the facility before the start of experiments. Mice

were housed in individually ventilated cages (Techniplast GM500 Mouse IVC Green

line) containing Lignocel bedding with a maximum of 5 adult mice per cage. All

experiments were carried out using adult male and female mice. Mice were euthanized

by CO

asphyxiation followed by cervical dislocation.

Mice in pain free and painful conditions were tested, using Nav1.7 null mutant mice

generated by crossing floxed Nav1.7 with Advillin-Cre. Mice in pain were generated

by systemic injection of NGF.

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Generation of eGFP-L10a mice:

eGFP-L10a mice were obtained from the Jackson laboratory. Homozygous or

Heterozygous eGFP-L10a were then crossed with either Nav1.8-cre or Adv-cre mice

to obtain Cre; eGFP-L10a heterozygote mice. All experiments were performed in 8-12

weeks old male and female mice. Details of primers used for genotyping are available

in table 1.

Table 1: Primers used for genotyping.

Sequences are listed as 5’-3’.

Target

FORWARD PRIMER

REVERSE PRIMER

NaV1.7 flox

NaV1.7 WT (382 b.p.)

CAGAGATTTCTGCATTAGAA
TTTGTTC

GCAAATCATAATTAATTCATG
ACACAG

NaV1.7 flox (527 b.p.)

CAGAGATTTCTGCATTAGAA
TTTGTTC

GCAAATCATAATTAATTCATG
ACACAG

AGTCTTTGTGGCACACGTTAC
CTC

NaV1.7 KO (395 b.p.)

CAGAGATTTCTGCATTAGAA
TTTGTTC

GTTCCTCTCTTTGAATGCTGG
GCA

Advillin Cre

Advillin WT (480 b.p.)

CCCTGTTCACTGTGAGTAG
G

AGTATCTGGTAGGTGCTTCCA
G

Cre (180 b.p.)

CCCTGTTCACTGTGAGTAG
G

GCGATCCCTGAACATGTCCA
TC

NaV1.8 Cre

NaV1.8 WT (258 b.p.)

CAGTGGTCAGGCTGTCACC
A

ACAGGCCTTGAAGTCCAACT
G

Cre (346 b.p.)

CAGTGGTCAGGCTGTCACC
A

AAATGTTGCTGGATAGTTTTT
ACTGCC

eGFP-L10a

eGFP-L10a (300 b.p.)

CAAAGGGAGCTGCAGTGGA
GTA

CCGAAAATCTGTGGGAAGTC

eGFP-L10a WT (297 b.p.)

ATTGCATCGCATTGTCTGAG CCGAAAATCTGTGGGAAGTC

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METHOD DETAILS

Translating Ribosome Affinity Purification (TRAP):

TRAP assay was performed as described

with slight modifications. Briefly, affinity

matrix was prepared by incubating MyOne T1 Dynabeads (Life Technology) with

biotinylated protein L and monoclonal 19C8 and 19F7 eGFP antibodies

. All the

bilateral DRGs or Spinal Cords from 3 male or female mice were dissected on ice,

pooled and homogenized in low salt buffer, followed by extraction of post-nuclear

fraction at 1000

spin. This fraction was then homogenized in non-denaturing 1% NP-

40 buffer followed by isolation of post-mitochondrial fraction at 12000

spin. GFP

tagged ribosomes were then isolated by mixing the post-mitochondrial fraction with

the pre-prepared affinity matrix of eGFP antibodies and beads overnight at 4

C. After

washing the beads in high-salt buffer, the ribosome bound RNA was eluted and

purified using RNA Nanoprep kit (Agilent). Finally, the isolated ribosomal bound RNA

was quantified using Quant-it Ribogreen kit (Invitrogen). All buffers had 100 ug/ml

cycloheximide (Sigma) with 10ul/ml rRNasin (Promega) and Superasin (Applied

Biosystems) to inhibit RNAases, while all reactions were carried out in RNAse-free

tubes (Ambion).

Reverse Transcriptase (RT)- qPCR:

DRGs from all the segments or spinal cords were dissected from three mice and

pooled. RNA was extracted using TRIzol Reagent (Invitrogen) according to the

manufacturer's instructions. Reverse transcription was performed using iScript

Reverse Transcription Supermix for reverse transcriptase

–qPCR following the

supplied protocol by Invitrogen. Complementary DNA amplification was performed in

triplicate, using SsoAdvanced Universal SYBR Green Supermix (Bio-Rad).

Immunohistochemistry:

Following anaesthesia, mice were trans-cardially perfused with PBS, followed by 4%

paraformaldehyde in PBS. DRGs and spinal cord were dissected and incubated in

fixative for 4h at 4°C, followed by 30% sucrose in PBS overnight at 4°C. Tissue was

embedded in O.C.T. (Tissue

‐

Tek) and snap

‐

frozen in a dry ice/2

‐

methylbutane bath.

DRG and spinal cord cross cryosections (20μm) were collected on glass slides

(Superfrost Plus, Polyscience) and stored at −80°C until further processing. For GFP

‐

tag immunohistochemistry in DRGs and spinal cord, sections were incubated in

blocking solution (4% horse serum, 0.3% Triton X

‐

100 in PBS) for 1h at room

temperature, followed by incubation in mouse anti

‐

GFP antibody (C7 or F8) diluted

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1:200 in blocking solution overnight at 4°C. Following three washes in PBS, bound

antibody was visualised using an Alexa 488

‐

conjugated goat anti

‐

mouse secondary

antibody (1:1000, Invitrogen). Fluorescence images were acquired on confocal laser

scanning microscope (LSM 780, Zeiss).

Immunoblotting:

Proteins for immunoblots were isolated from freshly excised DRG or spinal cord

followed by homogenization in RIPA lysis buffer as described previously

. The nuclear

fraction and cell debris were removed by centrifugation at

∼

20,000

for 15 min at 4°C.

Protein concentrations were determined with Pierce BCA protein assay kit, and then

samples of 40

μg were separated on SDS–PAGE gel in Bio

‐

Rad Mini

‐

PROTEAN

Vertical Electrophoresis Cell System and blotted to the Immobilin

‐

P membrane

(IPVH00010, Millipore) in transfer buffer (25 mM Tris

–HCl, pH 8.3, 192 mM glycine,

0.1% SDS and 20% methanol) for 1 h at 100 V with a Bio

‐

Rad transfer cell

system. The membrane was blocked in blocking buffer [5% nonfat milk in PBS

–Tween

buffer (0.1% Tween 20 in 1× PBS)] for 1 h at room temperature and then incubated

with primary antibody, anti-GFP (C7, 1:1000) in blocking buffer overnight at 4°C. The

membrane was washed three times with TBS

–Tween (20 mM Tris, 150 mM NaCl,

0.1% Tween 20, pH 7.5) and then incubated with secondary antibody goat anti

‐

mouse

or goat anti

‐

rabbit IgG

‐

HRP (1:4,000; Jackson ImmunoResearch Laboratories) in

TBS

–Tween at room temperature for 2 h. Detection was performed using a Western

Lightning Chemiluminescence Reagent (Super Signal Western Dura, Thermo

Scientific) and exposed to BioMax film (Kodak).

RNA-Seq Analysis:

RNA integrity of ribosome-bound mRNA samples from three replicates was assessed

using RIN and DV200 scores. SMART-Seq v4 ultra-low RNA (Takara Bio) library

preparation protocol was used to generate cDNA libraries and sequencing was

performed on an Illumina HiSeq 2 instrument with 150 bp reads according to the

manufacturer’s instructions. Samples with 50M reads were sequenced using a 2×150-

base-pair (BP) paired-end configuration. After demultiplexing, Illumina adapters and

nucleotides with poor quality were trimmed using bbduk from the BBMap software

v.38.94. The mouse reference genome, Gencode release v28 (GRCm39), was edited

concatenation

the

eGFP

sequence

retrieved

from

https://www.ncbi.nlm.nih.gov/nuccore/EU056363.1

. The reference genome indexing,

read mapping and counting mapped reads were performed using the STAR aligner

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v.2.7.3a in the 2-pass mapping mode that allows for unbiased exon splice junction

detection.

After extracting uniquely mapped read counts, the genes that showed low expression

across all samples, less than 20 total counts, were discarded from our dataset and the

remaining genes were used for data quality control and downstream analysis. The

remaining counts were subjected to variance-stabilizing transformation (VST) and

then differential expression analysis was performed between different conditions using

the DESeq2 v.1.25.9 package. A Principal Component Analysis (PCA) for

unsupervised projection of RNA-Seq data was performed with prcomp function in R

using normalized data and PCA plots were generated using ggplot2 v.3.3.6. All the

sample clusters shown in PCA plots were highly associated with biological conditions

rather than technical ones. Therefore, no batch effect correction was applied. Partition

of samples based on the proportion of neuronal mRNA content was assessed using

32 genes recently published by Pradipta R Ray et al.

. The median value of these

genes was used as neuronal module score and then samples were categorized into

three groups (enriched, moderate and de-enriched) using the 30th and 70th

percentiles of module scores. DESeq2 was used to calculate p-values (statistical

analysis by negative binomial general linear model with Wald test) and log

fold

changes that were used to generate volcano plots using easylabel package v.0.2.4.

Linear relationships between genes and three genotypes (1.7KO, WT, NGF / -1, 0, 1)

were

identified by means of Pearson’s correlation using the cor.test function of the R

Stats package. Results are shown for only the genes with absolute correlation

coefficient > 0.75 and p-value < 0.05. Heatmaps were generated using

ComplexHeatmap v.2.12.1.

Pathway Analysis:

Geneset Enrichment Analysis

Differentially expressed genes were used for gene set enrichment analysis. This

analysis was performed with an R interface to the Enrichr database v.3.0. The

hypergeometric model was used to assess whether the number of selected genes

associated with a KEGG pathway was larger than expected. Pathway terms with p-

value < 0.05 were considered significant.

Differentially Active Pathways

The expression levels of the genes corresponding to the proteins involved in the

pathways are used by the mechanistic pathway models to infer the activities of the

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pathways. Activities of signaling and metabolic sub-pathways were estimated using

Hipathia v.2.10 and Metabolizer v.1.7.0 tools, respectively. A two-sided Wilcoxon

signed-rank test was used for the statistical assessment when comparing different

conditions.

Antisense Oligonucleotides

Antisense Oligonucleotides (ASOs) directed against sequences encompassing

initiator methionines and polyadenylation sites of candidate mRNAs were purchased

from Sigma-Aldrich. All ASOs were 20mers, HPLC purified with phosphorothioate

nucleotides at the 5′ and 3′ end (see Table 2)

Table 2: Sequence of each pair of targeted and control ASO used.

Asterisk denotes phosphorothioate residues; target species is mouse.

Target

Sequence 5’-3’

Malat1 (A)

G*G*G*T*CAGCTGCCAATG*C*T*A*G

Malat1 (B)

C*G*G*T*GCAAGGCTTAGG*A*A*T*T

Kcnq1ot1 (A)

T*G*T*T*TTATTGTGGTTT*A*A*A*T

Kcnq1ot1 (B)

C*T*A*T*TGACATGGTCTT*T*A*C*T

Snhg11 (A)

A*G*C*A*CAAAGTTCGCCA*G*G*A*T

Snhg11 (B)

A*G*G*C*TCTGACATGGTC*T*T*G*G

Scrambled (Malat1) (A)

C*C*T*T*CCCTGAAGGTTC*C*T*C*C

Scrambled (Malat1) (B)

T*A*G*T*GCGGACCTACCC*A*C*G*A

Gnas (A)

C*A*T*T*CTCTTAGGTGCT*C*A*C*C

Gnas (B)

C*C*A*A*CTGCTTGTACAA*T*T*A*C

Nos1ap (A)

G*C*A*T*GGTGACCCGCGG*C*G*G*A

Nos1ap (B)

A*C*T*G*CCAAAGCTTAGG*C*A*G*G

Scrambled (Gnas) (A)

G*T*G*C*ACTCCTACTATC*T*C*T*G

Scrambled (Gnas) (B)

A*T*T*C*TCTTAACGGACC*A*T*C*A

Scrambled (Nos1ap) (A)

G*G*C*C*AAGCGGTGAGGC*G*T*C*C

Scrambled (Nos1ap) (B)

G*A*C*C*AGGCTAGACGAT*T*G*C*A

PP1R15B (A)

G*C*G*T*TCCTGTCTCCATCT*C*C*T*T

PP1R15B (B)

C*T*C*A*AAGGCCAAGCAG*T*A*G*C

UBE2F (A)

C*A*G*C*GTTAGCATTCCT*G*C*C*A

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UBE2F (B)

G*G*C*A*TAGCGTTTGATG*T*A*T*T

THOC7 (A)

A*G*A*G*TGCTCAGCATGC*G*T*T*G

THOC7 (B)

C*T*A*T*GGCTTAGGGTCT*G*C*T*T

ZFP362 (A)

G*C*T*T*CTACTCATCCTT*C*A*A*G

ZFP362 (B)

C*A*G*A*GAGATTCGCACC*G*G*G*A

ASOs Injections

Adult C57BL/6J mice between 8-10 weeks were anaesthetised using 2-3% Isoflurane

and injected with 6 µl of two or more targeted of control antisense oligonucleotides

resuspended in PBS for a total amount of 15 µg/mouse/injection via the intrathecal

route using a Hamilton syringe connected to a 30G needle cannula. A pair of ASOs

designed for the extremities of the mRNA were designed for each target: their

sequences can be found in Table 2. The ASOs were injected on 3 days (every other

day), and mice were prepared for behavioural testing immediately after the last

injection.

Behavioural Testing

All animal experiments were performed in accordance with Home Office Regulations.

Observers were blinded to treatment. Animals were acclimatized to handling by the

investigator and every effort was made to minimize stress during the testing. Male

animals were used for experiments apart from gender comparison studies. All

experiments were filmed, and carried out by two independent researchers

. Cancer

pain studies were carried out exactly as described in

Randall Selitto

The threshold for mechanonociception was assessed using the Randall Selitto test

Animals were restrained in a clear plastic tube. A 3 mm

blunt probe was applied to

the tail of the animal with increasing pressure until the mouse exhibited a nocifensive

response, such as tail withdrawal. The pressure required to elicit the nocifensive

behavior was averaged across three trials. The cut-off was set to 500 g.

Von Frey

Punctate mechanical sensitivity was measured using the up-down method of Chaplan

to obtain a 50% withdrawal threshold

. Mice were habituated for one hour in darkened

enclosures with a wire mesh floor. A 0.4 g von Frey filament was applied to the plantar

surface of the paw for 3 s. A positive response resulted in application of a filament of

lesser strength on the following trial, and no response in application of a stronger

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filament. To calculate the 50% withdrawal threshold, five responses surrounding the

50% threshold were obtained after the first change in response. The pattern of

responses was used to calculate the 50% threshold = (10[χ+κδ])/10,000), where χ is

the log of

the final von Frey filament used, κ = tabular value for the pattern of responses

and δ the mean difference between filaments used in log units. The log of the 50%

threshold was used to calculate summary and test statistics, in accordance with

Weber’s Law.

Hargreaves’ Test

Spinal reflex responses to noxious heat stimulation were assessed using the

Hargreaves’ test

. Mice were habituated for an hour in plexiglass enclosures with a

glass base. Before testing, the enclosures were cleaned of faeces and urine. Radiant

heat was then locally applied to the plantar surface of the hindpaw until the animal

exhibited a nocifensive withdrawal response. Average latencies were obtained from

three trials per animal, with inter-trial interval of 15 mins. Cut-off time was set to 30 s.

Cancer-Induced Bone Pain

Cell culture

Lewis lung carcinoma (LL/2) cells (from American Type Culture Collection (ATCC))

were cultured in a medium containing 90% Dulbecco's Modified Eagle Medium

(DMEM) and 10% fetal bovine serum (FBS) and 0.1% Penicillin/Streptomycin for 14

days before the surgery. DMEM was supplemented with L-glutamine (1%) and glucose

(4.5 g/l). The cells were sub-cultured whenever ~80% confluency was reached, which

was done a day before the surgery. On the surgery day, LL/2 cells were harvested by

scraping and were centrifuged at a speed of 1500 rpm for two mins. The supernatant

was removed, and the cells were resuspended in a culture medium that contained

DMEM to attain a final concentration of ~2x10

cells/ml. The cell counting and viability

check were done using the Countess automated cell counter (Thermo Fisher

Scientific).

Surgery

Surgery was carried out on anaesthetized C57BL/6 mice. Anesthesia was achieved

using 2-3% isoflurane. The legs and the thighs of the mice were shaved, and the

shaved area was cleaned using hibiscrub solution. A sterile lacri-lube was applied to

the eyes and lidocaine was applied at the site of the surgery. The reflexes of the mice

to pinches were checked to ensure successful anaesthesia. An incision was made in

the skin above and lateral to the patella on the left leg. The patella and the lateral

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retinaculum tendons were loosened to move the patella to the side and expose the

distal femoral epiphysis. A 30G needle was used to drill a hole through the femur to

permit access to the intramedullary space of the femur. The 30G needle was removed,

and a 0.3ml insulin syringe was used to inoculate ~2x10

LL/2 cells suspended in

DMEM. The hole in the distal femur was sealed using bone wax (Johnson & Johnson).

To ensure that there was no bleeding, the wound was washed with sterile normal

saline. Following that, the patella was placed back into its original location, and the

skin was sutured using 6

–0 absorbable vicryl rapid (Ethicon). Lidocaine was applied

at the surgery site, and the animals were placed in the recovery chamber and

monitored until they recovered.

Limb-use score

The mice housed in the same cage were placed together in a glass box (30 × 45 cm)

for at least five minutes. Then each mouse was left in the glass box on its own and

was observed for ~4 minutes, and the use of the ipsilateral limb was estimated using

the standard limb use scoring system in which: 4 indicates a normal use of the affected

limb; 3 denotes slight limping (slight preferential use of the contralateral limb when

rearing); 2 indicates clear limping; 1 clear limping, and with a tendency of not using

the affected limb; and 0 means there is no use of the affected limb. Reaching a limb-

use score of zero was used as an endpoint for the experiment.

Static weight-bearing

The scale used for this behavioural test was the Incapacitance Metre (Linton

Instrumentation), which has two scales to assess the weight put on each limb. The

weight placed on each limb is measured for 3 seconds. The readings for the weight

put on the limbs were recorded three times for each mouse, and between the readings,

mice were allowed to re-place themselves into the tube. The fraction of the weight put

on the ipsilateral paw was determined by the summation of all three readings of the

weight put on the ipsilateral paw divided by the summation of all the weight

measurements on both paws.

QUANTIFICATION AND STATISTICAL ANALYSIS

For behavioural experiments,

refers to the number of animals.

Details about the statistical and correlation analyses of RNA-Seq data are detailed in

the appropriate methods sections.

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Datasets are presented using appropriate summary statistics as indicated in the figure

legends. Error bars in all graphs denote mean ± SEM. Tests of statistical comparison

for each dataset are described in detail in the figure legends. For grouped data, we

made the appropriate correction for multiple comparisons. We set an α-value of p=0.05

for significance testing and report all p values resulting from planned hypothesis

testing.

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