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The Journal of Neuroscience, January 1, 2003, 23(1):34-42
Quantitative Single-Cell Differences in µ-Opioid Receptor
mRNA Distinguish Myelinated and Unmyelinated Nociceptors
Seth C.
Silbert,
Daniel W.
Beacham, and
Edwin W.
McCleskey
Vollum Institute, Oregon Health and Science University, Portland,
Oregon 97239
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ABSTRACT |
A remarkable feature of opioids is that they inhibit pain that
persists from previous injuries without eliminating either the initial
pain of a new injury or the protective reflexes triggered by it. Here
we ask whether selective expression of the µ-opioid receptor (MOR)
gene in primary nociceptors (pain-sensing neurons) might contribute to
this aspect of opioid specificity. We quantified single-cell levels of
MOR mRNA and measured opioid inhibition of Ca channels on identified
nociceptors and low-threshold mechanosensors (non-nociceptors) isolated
from rats. Negligibly few non-nociceptors express MOR mRNA, thereby
rendering nonpain sensations insensitive to opioids. Nearly half of
nociceptors of all size classes also fail to express MOR mRNA or to
respond to opioids. Among the opioid-responsive nociceptors, a gene
dose-response relationship exists such that maximal opioid inhibition
occurs when the MOR mRNA concentration of a cell is >15
pM. Almost all large, myelinated nociceptors express MOR
mRNA below this level, whereas small, unmyelinated nociceptors are
likely to express above it. Because myelinated nociceptors mediate
anti-nociceptive reflexes, the data suggest that fine control of the
MOR mRNA level contributes to a complex neural trait: the ability of
opioids to suppress persistent pain without preventing response to a
new injury.
Key words:
opioid receptors; opiates; nociceptors; sensory
neurons; pain; analgesia; calcium channels; single-cell PCR
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Introduction |
At analgesic doses, morphine binds
only to the µ-opioid receptor (MOR) (Goldstein and Naidu, 1989 ;
Raynor et al., 1994 ), one of three cloned receptors activated by
opioids (Li et al., 1996 ; Kieffer, 2000 ; Williams et al., 2001 ). The
transgenic knock-out of MOR in mice completely eliminates morphine
analgesia, and partial knock-down fractionally suppresses it (Matthes
et al., 1996 ; Sora et al., 1997 ). Thus, the MOR is considered the
receptor responsible for opiate analgesia.
Opioids distinguish different kinds of pain, powerfully suppressing
second pain and having much less effect on first pain (Price et al.,
1985 ; Cooper et al., 1986 ; Yeomans et al., 1996 ). Second pain develops
slowly, over several seconds, and persists well after a noxious
stimulus; first pain is the earliest sensation of injury, is transient,
and is accompanied by reflexes that cause rapid withdrawal from the
noxious stimulus (Lewis and Pochin, 1937 ; Torebjork and Hallin, 1973 ;
Fields, 1987 ). Through specific targeting of second pain, opioids can
relieve pain that persists from a previous injury without interrupting
the pain or protective responses elicited by new injuries.
Action potentials for first pain are conducted from the periphery to
the spinal cord over rapidly conducting, myelinated axons, whereas
signals for second pain travel over unmyelinated axons (C fibers) that
conduct too slowly (1 m/sec) to mediate rapid antinociceptive reflexes
(Lewis and Pochin, 1937 ; Campbell and LaMotte, 1983 ). The synapse
formed by nociceptive axons in the spinal cord is a major target of
opioids (Arvidsson et al., 1995 ; Kohno et al., 1999 ). Spinal opioid
selectivity arises because opioids target only synapses formed by
nociceptors and opioids suppress synaptic activity caused by
unmyelinated nociceptors more than that of myelinated nociceptors
(Jurna and Heinz, 1979 ; Light and Willcockson, 1999 ). We sought a
molecular explanation for this specificity by asking whether the
selective expression of MOR mRNA explains differences in opioid
sensitivity between nociceptors and non-nociceptors and nociceptors
that differ in myelination.
We used the perforated patch-clamp technique to measure Ca-channel
inhibition by a saturating dose of
D-Ala2-N-Me-Phe4-Gly-ol5-enkephalin
(DAMGO) (a MOR-selective agonist). The expression of MOR mRNA was
quantitatively assayed in the same cells using competitive reverse
transcription (RT)-PCR (Gilliland et al., 1990 ; Chehadeh et al.,
1995 ), modified so it could be used on single cells. These methods were
applied to dissociated sensory neurons that were identified either as
nociceptors or as low-threshold (non-nociceptive) mechanosensors using
the anatomical strategies illustrated in
Figure 1. The relationship between myelination and opioid sensitivity
was studied by comparing populations of nociceptors that differ in
cell-body size, because most of the smallest sensory neurons have
unmyelinated axons and most of the largest have myelinated axons
(Harper and Lawson, 1985 ; Lee et al., 1986 ).

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Figure 1.
Strategy to distinguish nociceptors from
mechanosensors. Low-threshold (non-nociceptive) mechanosensors were
isolated from the mesencephalic nucleus of the fifth nerve, which
contains only muscle spindle and fine-touch receptor afferents (Cody et
al., 1972 ) (muscle spindle shown). Tooth pulp, an organ from which pain
is the only conscious sensation (Ahlquist et al., 1984 ; Narhi et al.,
1994 ), was used to obtain nociceptors. A dye (DiI), placed in small
cavities drilled in rat molars ~1 week before harvesting the
trigeminal ganglia, is transported to the cell body, where its
fluorescence distinguishes tooth-pulp afferents from other dissociated
trigeminal sensory neurons (Fig. 2).
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Our results indicate that non-nociceptive neurons and myelinated
nociceptors use different molecular strategies to limit their opioid
sensitivity: MOR mRNA is simply absent from the non-nociceptors, whereas it is quantitatively diminished in most large nociceptors compared with smaller ones. This suggests that fine control of the MOR
transcript level, as opposed to simple on/off control of transcription,
explains the high opioid sensitivity of unmyelinated nociceptors
compared with myelinated ones. We also find that many nociceptors,
including some small ones, express MOR mRNA at levels that give
submaximal opioid responses; this suggests that increasing MOR mRNA
production could increase opioid efficacy.
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Materials and Methods |
Cell preparation. Sensory neurons were used within 24 hr of dissociation from adult Sprague Dawley rats and were stored at room temperature in L15 media plus nerve growth factor (50 ng/ml). Only
cells with Ca-channel current amplitudes of >1 nA were used for
analysis. We observed no differences in Ca-channel current, opioid
responses, or mRNA expression between freshly dissociated cells and
those studied 1 d later. For example, in a random selection of
tooth-pulp afferents studied immediately after dissociation versus
those studied 24 hr later, MOR mRNA was detectable in 51% of fresh
(n = 33) and 57% of 24 hr (n = 120)
cells; those that expressed MOR mRNA had mean concentrations of
13.8 ± 3.2 and 17.3 ± 2.6 pM in fresh
and 24 hr cells, respectively.
All methods for surgeries, dissections, dissociations, and cell storage
are as described previously (Eckert et al., 1997 ), except for small
adjustments of incubation times. The two surgeries used were shallow
dental drilling to deposit crystals of DiI into the dentin and exposure
of masseter muscle to inject with DiI dissolved in DMSO. The two
dissections were of the trigeminal ganglion and the mesencephalic
nucleus. Tissue dissociations used papain alone (mesencephalic nuclei)
or papain, collagenase, and dispase (trigeminal ganglia). Any large,
round neurons from the mesencephalic nucleus were used regardless of
whether they were fluorescently labeled muscle spindle afferents.
Electrophysiology and cell harvest. In three ways, the
procedures minimized RNA degradation that might occur during
patch-clamp recording before PCR: (1) Solutions and surfaces were
treated to eliminate RNase activity. (2) The perforated-patch method
[using gramicidin, as described by Kyrozis and Reichling (1995) ] was used because it minimally disrupts the intracellular environment. (3)
Recording times were minimized by using voltage ramps to measure peak
Ca-channel currents rapidly and to detect whether series resistance
artifacts distort the current-voltage curve. All required voltage
protocols and recordings were completed within ~5 min, after which
cells were promptly harvested.
Voltage ramps (420 msec from 80 mV to +20 mV) were delivered at 20 sec intervals, and opioid action was measured 20 sec after the
application of 1 µM DAMGO, a time sufficient to complete
opioid inhibition (Wilding et al., 1995 ) and a concentration sufficient for a maximal response (Seward et al., 1991 ). Preliminary experiments confirmed that stimulating with voltage ramps or with voltage pulses
gave the same fractional Ca-channel inhibition. Nifedipine was included
in a bath solution to block opioid-insensitive L-type Ca channels
(Rusin and Moises, 1995 ) at a concentration (10 µM) reported not to affect other Ca channels (Triggle, 1999 ). Because L-channel expression varied from 20 to 50% of the total
Ca2+ current in different cells, we
blocked L channels so that their variable expression did not cause
artifactual variation in opioid efficacy. Series resistance
compensation, initially set at ~50%, was increased if the Ca-channel
current-voltage curve had a negative slope region that was
artifactually sharp. Currents through Ca channels were blocked by 1 mM Cd2+ at the end of each
run; the resulting record was subtracted from others to isolate
Ca-channel currents. Calculation of the percentage of inhibition
included correction for a constant fractional rundown rate using the
following algorithm: X = 100(1 ac/b2), where
X is the percentage of inhibition, a and
b are current amplitudes 20 sec apart before drug
application, and c is the amplitude 20 sec after drug application.
All solutions were prepared using nuclease-free reagents and
diethylpyrocarbonate-treated, deionized, distilled water,
and stored in RNase-free plastics or baked (200°C overnight) glass. The perforated-patch recording pipette contained 35 µg/ml
gramicidin in a solution of (in mM): 150 CsCl, 1 EGTA, and
10 HEPES, pH 7.3-7.4, adjusted with CsOH, 300-310 mOsm. In cases in
which cells were not harvested for PCR, standard whole-cell recording
was used, and the pipette contained (in mM): 100 Cs-methanesulfonate, 20 CsCl, 10 Na2
phosphocreatine, 4 Na2ATP, 0.5 Na3GTP, 5 Cs5[1,2-bis(2-aminophenoxy)ethane-N,N,N',N'- tetraacetic
acid], and 10 HEPES, pH 7.3-7.4, adjusted with
CsOH, 300-310 mOsm. When recording Ca-channel activity, the
extracellular solution contained (in mM): 1 BaCl2, 140 tetraethylammonium-Cl, 10 HEPES, and 0.01 nifedipine, pH 7.3-7.4. At all other times, cells were
exposed to physiological saline (in mM):
135 NaCl, 5 KCl, 2 CaCl2, 1 MgCl2, 10 glucose, and 10 HEPES, pH 7.3-7.4, 300-310 mOsm.
The entire cell was harvested for RT-PCR so that all mRNA was counted.
Recording pipettes gave inconsistent harvests, so a second, larger
pipette was used. These were fire-polished to an inner diameter of 6-8
µm (for cells of <40 µm diameter) or 8-12 µm (for larger
cells), and filled with <1 µl of harvest solution (in
mM: 135 KCl, 1 EGTA, and 5 Tris, pH 8.2). The contents of the pipette were expelled into the bottom of a thin-walled 200 µl PCR
tube (PerkinElmer Life Sciences, Boston, MA), containing 10 µl of frozen primer annealing buffer (see below). The tubes were
kept frozen in an ethanol/dry ice bath, and RT was performed at the end
of the day. Sham harvests were performed by dipping a pipette into the
culture dish, manipulating the tip to within a few micrometers of the
culture surface, applying gentle suction, and carrying the contents
through RT-PCR. Shams were assembled each day of recording; in >100
sessions, no MOR mRNA contamination was found, and
glyceraldehyde-3-phosphate dehydrogenase (GPD) mRNA (50 molecules)
was found only once.
Quantitative PCR. We used a variation of competitive PCR
(Gilliland et al., 1990 ) rather than real-time PCR, because real-time PCR is reported to be less able to detect small numbers of DNA molecules (Tkatch et al., 2000 ). The essential PCR controls are: (1)
measurement on each cell for a constitutively expressed
"housekeeping" gene (GPD, a metabolic enzyme); (2) addition into
each PCR tube of a known amount of competitor sequence that is
amplified by the same PCR primers as the wild-type (w.t.) DNA; (3) a
calibration ladder made for each PCR run by performing the reaction on
known amounts of the competitor and wild-type DNAs; and (4) addition of
a known amount of a mutant GPD RNA to quantify the RT reaction for each
cell (see below). We analyzed the ratios of the densities of wild-type
and competitor PCR products. We picked up the entire cell, rather than
harvesting a variable amount of cytoplasm, so that total mRNA
levels were measured (Sucher and Deitcher, 1995 ). The method
does not assume that wild-type and mutant DNA sequences are amplified
identically in the PCR. Rather, it assumes only that whatever
wild-type-to-mutant amplification efficiency occurred in the
calibration tubes used in any particular PCR run also occurred in the
cell tubes for that run.
RT reactions had, in a 20 µl volume, 1× Superscript II buffer
(Invitrogen, Carlsbad, CA), 5 µM random hexamers
(Roche Applied Science, Indianapolis, IN), 0.5 U/µl RNasin (Amersham
Biosciences, Arlington Heights, IL, or Invitrogen), 0.5 mM of each deoxyNTP (dNTP) (Roche Applied Science), 5 U/µl Superscript II reverse transcriptase (Invitrogen), and
104 molecules of a mutant GPD mRNA. The
reaction was assembled and performed in two stages: one for cell
disruption and primer annealing at low ionic strength and one for RT.
RT reaction was 60 min at 42°C, followed by 15 min at 75°C;
products were then stored at 20°C. Sham RTs lacking the mutant mRNA
and cell harvests were assembled with each reaction set and were
subsequently used to assemble calibration tubes for the PCR sets.
Two rounds of PCR using nested primers generated visible
ethidium-stained products. The first round was a multiplex reaction using PCR primers for both MOR and GPD sequences; 50 µl PCRs were assembled using one-half of the contents (10 µl) of each RT reaction. Mutant competitor DNA of MOR (12 copies) or GPD (500 copies) was added
to the first-round reaction by the serial dilution of DNA stocks
quantified spectrophotometrically; 1 µl aliquots of the first-round
reaction product were the starting material for the second-round PCRs,
which used primers for either MOR or GPD that were complementary to
sequences internal to those used for the first round. All reaction
tubes in the set contained 50 µl. The first, multiplexed PCR round
had 25 cycles; the second round for MOR had 24 cycles; the second round
for GPD had 17 cycles. Denaturation, annealing, and extension steps
were 98°C for 5 sec, 54.4°C for 30 sec, and 70°C for 2 min,
except for the first five cycles, during which the extension time was
lengthened to 5 min. For the first round, primer concentrations were
200 nM, nucleotides were 150 µM (substituting
dUTP for dTTP). For the second round, the primers were 500 nM and the nucleotides were 250 µM. Other
reaction components were: 50 mM Tris-HCl, pH 8.7 at 23°C;
16 mM
(NH4)2SO4; 150 µg/ml BSA; 10-15 mM KCl; 3-5 mM
MgCl2; 100 µM tetramethylammonium chloride; 6-8% DMSO; and 4 mU/µl KlenTaq I (Barnes,
1992 ).
Primers, selected using Oligo version 5.0 (National
Biosciences, Plymouth, MA) and purchased from Oligos Etc (Wilsonville, OR), spanned the splice site between exons 2 and 3 for MOR and those
between exons 5 and 8 for GPD. The following primers were used: MOR
outer primers, 5'-GCGACTGCTCAGACCCCTTAGCTC-3' and
5'-TCTGGAATCGTGATCAGCGCTTTG-3', corresponding to MOR 215-238(+) and
1112-1089( ), respectively; MOR inner primers,
5'-GGAACATGGCCCTTCGGAACCATC-3' and 5'-TACCAGGTTGGGTGGGAGAACGTG-3', corresponding to MOR 574-597(+) and 863-840( ), respectively; GPD
outer primers, 5'-TGGTGCTGAGTATGTCGTGGAGTC-3' and
5'-AGAATGGGAGTTGCTGTTGAAGTC-3', corresponding to GPD 335-358(+) and
941-918( ), respectively; GPD inner primers,
5'-GGGTGTGAACCACGAGAAATATGA-3' and 5'-AGCACCAGTGGATGCAGGGATGAT-3', corresponding to GPD 464-487(+) and 704-681( ), respectively.
PCR products were electrophoresed through a 1.0-1.3% agarose gel and
stained with ethidium bromide. All single-cell PCR analyses used ratios
of the band intensities of wild-type and mutant DNA.
Quantifying RT. To convert the number of DNA molecules
counted in the PCR into the number of mRNA molecules that were in the cell, we quantified the RT reaction for a housekeeping gene in each
cell and assumed that this same RT efficiency applied to the MOR gene.
RT efficiency is the number of cDNA molecules made in the RT reaction
per mRNA molecule present in the reaction. Referring to Figure
3A, the second GPD mRNA mutant, m2, enables the measurement
of GPD mRNA for each cell. w.t./m1 and w.t./m2 ratio calibrations are
plotted separately to measure the cDNA and mRNA, respectively. The
ratio of GPD cDNA/mRNA is taken as the RT efficiency for a given cell.
Dividing MOR cDNA by the RT efficiency gives the number of MOR mRNA
molecules. RT efficiency, which averaged 0.175, varied from ~0.2 to
0.1 in different cells. Data from cells A, J, and
K in Figure 3, A and B, illustrate
effects of this variation. For example, cells A and
J had the same number of MOR cDNA molecules (22), but,
because their RT efficiency differed, we conclude that cell
A had 175 mRNA MOR mRNA molecules and cell J had 215.
Statistics. Statistics calculations used Prism (GraphPad
Software Inc., San Diego, CA). Error bars on averaged data indicate SEM; error bars on fractional data indicate the 68% confidence interval. Averaged data were compared using one-way ANOVA
followed by Tukey's multiple comparison test or a post-test for linear trend. Ranked data were analyzed for correlation using the
nonparametric Spearman test. Confidence intervals and statistical
significance of fractional data are from the
2 test of contingency tables.
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Results |
Opioids spare Ca channels on non-nociceptive neurons and on
some nociceptors
Depolarizing ramps of voltage evoked Ba2+
current through voltage-gated Ca channels in fluorescently identified
tooth-pulp afferents (nociceptors) (Fig.
2A) or mesencephalic
nucleus sensory neurons (low-threshold mechanosensors) (Fig.
2B). DAMGO (1 µM, a saturating concentration for the MOR) reversibly inhibited peak
Ba2+ current in most nociceptors (Fig.
2Ac) but not in any mechanosensors (Fig.
2Bb, Table 1). Evidently,
opioids spare nonpainful sensations because they fail to
inhibit Ca channels and neurotransmitter release from non-nociceptive
sensory neurons.

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Figure 2.
Opioids inhibit Ca channels on nociceptive but not
on non-nociceptive sensory neurons. A, Bright-field
(a) and fluorescence (b)
photographs of sensory neurons dissociated from the trigeminal ganglion
1 week after DiI was placed in tooth pulp; the fluorescent cell would
be taken as a tooth-pulp nociceptor. A,
c, Nociceptor currents carried by 1 mM
Ba2+ through Ca channels activated by the indicated
ramp of voltage just before (control), 20 sec after the application of
1 µM DAMGO, and 40 sec after removal (recovery). A
control record in 1 mM Cd2+ (which
blocks all Ca channels) was subtracted from all test records. Opioid
receptor antagonists (10 µM naloxone or 200 nM CTAP) fully blocked DAMGO action (data not
shown). B, a, Bright-field photograph of
three neurons dissociated from the mesencephalic nucleus and placed on
a bed of glial cells; all three would be accepted as low-threshold
(non-nociceptive) mechanosensors. B, b,
Ca channels were not inhibited by DAMGO in this or any other
mesencephalic neuron. Scale bars, 30 µm.
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DAMGO inhibition of nociceptors varied widely (range, 0-49%), with
approximately one-third of them being clearly insensitive, as shown
previously in tooth-pulp afferents (Taddese et al., 1995 ) and in
nociceptors identified by long durations of action potential (Abdulla and Smith, 1998 ). To independently confirm that some nociceptors are insensitive to opioids, we used capsaicin, which activates a particular subset of nociceptors that senses noxious heat
(Kirschstein et al., 1999 ; Nagy and Rang, 1999 ). A third of the
capsaicin-sensitive sensory neurons had little or no response to DAMGO.
Thus, regardless of whether nociceptors are identified by the
innervation of tooth pulp, duration of action potential, or capsaicin
sensitivity, a significant fraction fail to respond to opioids, and
inhibition is submaximal in many others.
Nociceptors selectively transcribe the MOR gene
The MOR inhibits primarily N-type Ca channels in sensory neurons
(Rusin and Moises, 1995 ); it does so through a simple signaling path
involving direct mediation by a G-protein (Moises et al., 1994 ; Wilding
et al., 1995 ). The difference in opioid sensitivity of nociceptors and
mechanosensors is not attributable to differences in N-channel
expression, because -conotoxin GVIA, an N-channel-selective toxin, inhibited Ba2+ currents to the same
degree on mechanosensors and nociceptors (44 ± 4%,
n = 6, and 41 ± 3%, n = 12, respectively).
Single-cell PCR
We then asked whether opioid selectivity arises from selective
transcription of the MOR gene. We picked up individual neurons and
performed quantitative RT-PCR to detect and count the MOR mRNA in each
cell. Figure 3 illustrates our method,
which is a variation of competitive PCR (Gilliland et al., 1990 ), along
with a method to quantify the RT reaction so that the mRNA is counted. Competitive PCR was used instead of real-time PCR, because real-time PCR is reported to be weak at detecting low numbers of cDNA molecules (Tkatch et al., 2000 ). In addition to quantifying mRNA, our method tests for three kinds of false negatives: failure of the PCR, failure
of the RT, and failure of the cell harvest.

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Figure 3.
Use of competitive RT-PCR to quantify single-cell
MOR and GPD mRNAs. A, Ethidium-stained agarose gels of
PCR products for MOR (top) and GPD
(bottom) for 12 individual nociceptors (lanes
A-L) and seven calibration tubes (left lanes).
Each gel shows the reaction products from a particular run of the PCR
machine. mut and m1, Mutants of MOR and
GPD DNA, respectively, having 78 and 88 bp insertions between primer
sites. Twelve molecules of mut and 500 molecules of m1 were seeded into
their PCR tubes. RT reactions were seeded with the indicated amount of
synthetic RNA for m2, which has a 268 bp insertion into the GPD
sequence. Calibration tubes, assembled and processed along with the
cell tubes, contain the indicated number of w.t. MOR or GPD DNA and
either 12 (MOR) or 500 (GPD) mutant molecules. MW,
Molecular weight. B, Positive MOR bands were
quantified (numbers below MOR gel in A)
by comparison with calibration ladders and correcting for RT efficiency
to obtain mRNA values. Ratios of w.t./mutant band intensities in each
calibration tube are plotted against the number of initial w.t.
molecules (open symbols). Polynomial equations
(curves) fitted to these data are used to interpolate
initial cellular w.t. content from the w.t./mutant product ratios from
each cell (solid symbols).
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Figure 3 is like most of our reactions in that two MOR cDNA molecules
were detectable. This corresponds to a resolution of four MOR cDNA
molecules per cell (because one-half of the RT reaction was used for
the MOR PCR) and 23 MOR mRNA molecules per cell (assuming our mean RT
efficiency of 5.7 mRNA/cDNA). Dividing by the volume of a
30-µm-diameter cell gives a cellular detection threshold of 2 pM MOR mRNA. Cells with robust expression had ~100 copies of MOR mRNA, 1000 copies of neurokinin peptide mRNA (data not shown),
and 10,000 copies of mRNA for the metabolic enzyme GPD.
The final lane, Sh, from a sham harvest, has no evident w.t.
MOR and no w.t. GPD; however, it has a mut band, which
confirms that PCR for MOR worked, and an m2 band, which
confirms that the RT worked. In contrast, cell I, which also has no
detectable w.t. MOR, has w.t. GPD, mut, and m2; this shows that the
cell harvest, PCR, and RT were all successful, indicating that the MOR
mRNA in cell I was truly below the detection threshold. Approximately 10% of apparent MOR-negative cells failed to exhibit w.t. GPD bands,
indicating that the cell harvest failed and requiring discarding of the
data; we never had failures of RT and PCR.
Nociceptors versus non-nociceptors
We successfully measured MOR mRNA levels in 191 tooth-pulp
afferents (Figs. 3, 4A)
and 72 mesencephalic mechanosensory neurons (Fig. 4B,
Table 1). A majority (60%) of the tooth-pulp nociceptors contained
detectable MOR mRNA, but only two mechanosensors tested positive. The
number of MOR mRNA molecules varied extensively in different
nociceptors: the mean (considering only those with detectable MOR mRNA)
was 227 molecules and the median was 160; 50% of the positives were
between 60 and 290 molecules. These small levels are in contrast to the
mean of 13,100 molecules of GPD mRNA in the same cells.

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Figure 4.
Most nociceptors, but only rare mechanosensors,
transcribe MOR mRNA. A, MOR and GPD mRNA amplified and
quantified from 15 single tooth-pulp afferents (lanes
A-O). MOR mRNA expression spans from below the detection
threshold to 460 molecules per cell (60 pM, assuming equal
distribution throughout the spherical cell); 60% of 191 nociceptors
tested had detectable MOR mRNA (Table 1). B, MOR and GPD
mRNA amplified and quantified from seven individual mesencephalic
neurons (lanes C-I) and three pooled samples of
either five (lanes A and B) or 10 (lane J) mesencephalic neurons. Cell I is one of
only two (of 72) individual mesencephalic neurons that had detectable
MOR mRNA. We used the pooled samples to determine whether most
mesencephalic neurons express at nonzero levels below our detection
threshold or whether rare ones express high levels of MOR mRNA. Six
pooled samples were prepared (4 with 5 cells in each and 2 with 10).
MOR mRNA was present in only three of these pools, at levels (50, 100, and 250 molecules) similar to those in single nociceptors and similar
to the two individual positive cells (lane A is a
positive pool; lanes B and J are negative
pools). This argues that rare cells in the mesencephalic preparation
have substantial MOR mRNA, because all pools should be positive if the
majority of cells express at levels just below our detection threshold.
MW, Molecular weight; GPD,
glycerol-3-phosphate dehydrogenase.
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One of the two positive mechanosensors is in Figure
4B (lane I). We asked whether these
two cells are rare expressers or whether all cells have MOR mRNA at low
levels that are usually below our limit of resolution. Using pooled
samples, we concluded that only rare cells from the mesencephalic
nucleus have MOR mRNA (Fig. 4B, legend). The absence
of MOR mRNA in the overwhelming fraction of non-nociceptive
sensory neurons indicates that only nociceptors effectively
transcribe the MOR gene.
Large nociceptors have low MOR response and low MOR mRNA
Might selective transcription also explain why opioids fail to
suppress antinociceptive reflexes? This could occur through selective
suppression of MOR mRNA in myelinated nociceptors, the cells that
trigger these reflexes. Tooth pulp is well suited for addressing this
question because it is rich in myelinated afferents, and the only
sensation these evoke is pain (Ahlquist et al., 1984 ; Narhi et al.,
1994 ). Moreover, the tooth has clear psychophysical correlates to first
(sharp, shooting) and second (dull) pain, mediated, as in the skin, by
myelinated and unmyelinated axons, respectively (Jyvasjarvi and
Kniffki, 1987 ). Myelination was studied by comparing populations of
tooth-pulp afferents that differ in cell-body diameter; the larger the
cell, the more likely it has a myelinated axon (Harper and Lawson,
1985 ; Lee et al., 1986 ). We asked whether the lower mean opioid
sensitivity of large nociceptors that we reported previously (Taddese
et al., 1995 ) correlates with low MOR mRNA expression (Fig.
5).

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Figure 5.
Large nociceptors have a low opioid response and
have low MOR mRNA levels. A, Mean ± SEM percentage
of Ca-channel inhibition by 1 µM DAMGO (black
columns, left axis) and the fraction (±68%
confidence interval) of cells inhibited by >10% (hatched
columns, right axis) in tooth-pulp afferents of
different cell-body diameters. The medians were 12, 17, and 5.5% for
the small (<30 µm), medium (30-40 µm), and large (>40 µm)
cells, respectively. There were nonresponders and very large responders
(>40% inhibition) in each bin. B,
Inset, The mean number of GPD (open
circles, right axis) and MOR
(filled circles, left axis) mRNA
molecules for small, medium, and large nociceptors. GPD mRNA
systematically increases with cell size, as expected when an increasing
amount of cytoplasm is harvested. In contrast, MOR mRNA drops in the
largest cells after increasing with cell size between the smaller
cells. B, Mean concentration (moles per volume, assuming
a spherical cell) of MOR mRNA (black columns,
left axis) is lowest in the largest nociceptors.
Asterisks indicate a significant difference from the
other two means (p < 0.05).
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Electrophysiology
Ca-channel inhibition by DAMGO was measured in 182 tooth-pulp
nociceptors. Ranking them by size confirmed that opioid sensitivity decreases as the cell-body diameter increases (Spearman rank-order correlation coefficient, rs = 0.19;
p = 0.011 that this could occur by chance). The reason
is evident from binning the data (Fig. 5A): the mean DAMGO
inhibition of Ca channels is less in the largest cells (diameters of
40 µm), the population most enriched in myelinated axons. The
results qualitatively agree with previous reports (Taddese et al.,
1995 ; Borgland et al., 2001 ), which suggested that unmyelinated
nociceptors have greater opioid responses than the myelinated ones. Our
previous report demonstrated larger opioid differences between small
and large neurons than we show here. This is explained by the nature of
data acquisition. Previously, we chose the largest and smallest labeled
cells possible in a culture dish, because this is the most certain
way to compare myelinated and unmyelinated cells (Harper and Lawson,
1985 ). Here, we investigated all labeled cells, a method that allows
use of the Spearman rank analysis and, thus, an independent test of the previous conclusion.
MOR and GPD mRNA expression
MOR and GPD mRNA levels were measured in 191 tooth-pulp
nociceptors that ranged from 20 to 50 µm in diameter. The number of GPD mRNA molecules increased almost perfectly as the cell diameter increased (Spearman rs = 0.49;
p < 0.0001). Figure 5B, inset, shows the mean number of GPD mRNA molecules (open circles,
right axis) in the three different bins of cell-body
diameter. The systematic increase in GPD mRNA levels is consistent with
the increasing metabolic demands of larger cells and confirms GPD as a
useful housekeeping gene.
In clear contrast to GPD, the number of MOR mRNA molecules fails to
correlate statistically with nociceptor cell diameter (Spearman
rs = 0.085; p = 0.24). The reason is evident when data are binned by diameter. Like
GPD, the mean number of MOR mRNA molecules (Fig. 5B,
inset, solid circles, left axis)
increases with cell size between the small- and medium-cell-size bins.
However, the mean in the largest cells drops dramatically from the
expected trend. Normalizing expression to cell-body size, dividing
either by cell volume (Fig. 5B) or by surface area (data not
shown), emphasizes the similar trends for MOR mRNA expression and
opioid response: both drop in the largest population of tooth-pulp afferents.
Relationship between MOR mRNA concentration and Ca-channel
inhibition in single nociceptors
Gene dose-response relationship
Hoping to gain insight into the mechanism for the apparent
relationships between nociceptor size, opioid response, and MOR mRNA,
we obtained a single-cell MOR mRNA dose-response relationship. Each
point in Figure 6A
expresses, for a particular labeled tooth-pulp afferent, the percentage
of inhibition by DAMGO (y-axis) and the concentration
of MOR mRNA (x-axis). We used concentration (moles of MOR
mRNA per cell spherical volume), because it controls for the 15-fold
span of cell volumes between the different-sized cells (see
Discussion).

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Figure 6.
Opioid sensitivity is limited when the MOR mRNA is
<15 pM. A, Percentage of inhibition of Ca
channels by DAMGO versus the cellular MOR mRNA concentration for 120 tooth-pulp afferents (each point from a single cell). The origin
(0*), which has 51 points, denotes cells with no
detectable MOR mRNA. The dashed curve is the best fit
(R2 = 0.51) of a single site
isotherm (K1/2 = 5.4 pM;
Bmax = 35%). B, The
same data expressed as means ± SEM for bins of MOR mRNA
concentrations. The mean opioid response systematically rises with MOR
mRNA concentration until it saturates at 15 pM. The
number of cells in each bin is indicated. Except for the
10-15 pM versus >25 pM bins, values for
non-neighboring bins differed significantly
(p < 0.05).
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As expected of single-cell data, there is considerable scatter, yet
several clear conclusions arise. Of the 120 cells successfully studied,
51 had no MOR mRNA above our detection threshold (points at the
origin); only four of the 51 had opioid inhibition of >10%. In
contrast, most cells that had detectable MOR mRNA had obvious responses
to DAMGO. Thus, the fraction of nociceptors reported to be
opioid-insensitive (Taddese et al., 1995 ; Abdulla and Smith, 1998 )
exhibits little or no expression of the MOR gene.
Most importantly, a saturable dose-response relationship appears when
data are binned and averaged (Fig. 6B). Ca-channel
inhibition increases with MOR mRNA concentrations up to ~15
pM but gets no greater at higher concentrations.
More than half of the nociceptor population express at <15
pM. Therefore, most nociceptors express MOR mRNA
at levels that result in submaximal inhibition by opioids.
Small and large nociceptors differ quantitatively
Figure 5 showed that large nociceptors, on average, have lower MOR
mRNA and respond weakly to opioids compared with small nociceptors. Is
this because more large nociceptors simply fail to express MOR mRNA, or
do they express it at quantitatively lower levels? We found that the
likelihood that a nociceptor had detectable MOR mRNA did not depend on
cell size (p = 0.1084;
2 test; <30 µm, 27 expressors per 46 tested cells; 30-40 µm, 52 expressors per 81 tested cells; >40
µm, 30 expressors per 64 tested cells). This agrees with in
situ hybridization results showing that equal fractions of small
and large sensory neurons express MOR antigen (Wang and Wessendorf,
2001 ).
A difference between large and small nociceptors is seen when we
consider the amount of MOR mRNA in cells that have it. The largest
cells that have MOR mRNA clearly have a lower mean concentration than
smaller cells (Fig. 7A,
solid bars) and also a lower mRNA number (Fig.
5B, inset). Only 20% of the largest nociceptors
that have MOR mRNA express it at concentrations of >15
pM, the value that correlates with maximal opioid
sensitivity; in contrast, 60% of the smallest nociceptors express at
>15 pM (Fig. 7A, hatched columns). We interpret Figures 6 and 7 to indicate that the opioid response of a nociceptor can be limited by its cellular concentration of MOR mRNA, and that this mechanism diminishes the opioid sensitivity of large, myelinated nociceptors.

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Figure 7.
Opioid sensitivity of most large nociceptors is
RNA limited. A, The mean concentration ± SEM of
MOR mRNA for different-sized tooth-pulp afferents in which it was
detectable (black columns, left axis) and
the fraction (±68% confidence interval) of tooth-pulp afferents with
detectable MOR mRNA that expressed it at >15 pM
(hatched columns, right axis)
decrease with increasing cell body size. Only a small fraction of large
nociceptors express MOR mRNA at levels that lead to maximal opioid
response. B, Hypothesis for selective opioid suppression
of second pain. If protein densities at presynaptic terminals
correspond to mRNA concentrations at the cell body, MOR is absent from
virtually all non-nociceptive mechanosensor terminals and is present at
low levels at terminals of most myelinated nociceptors.
C, In this way, second pain, which is mediated by the
unmyelinated terminals rich in MOR, can be selectively suppressed by
opioids.
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Discussion |
Our experiments demonstrate that: (1) non-nociceptive
mechanosensors primarily fail to express MOR mRNA and are therefore opioid-insensitive; (2) if its MOR mRNA is <15 pM, a
nociceptor generally has submaximal opioid sensitivity; (3) a majority
of nociceptors express MOR mRNA at <15 pM and therefore
respond submaximally to opioids; (4) almost all large nociceptors,
those likely to be myelinated and to mediate antinociceptive reflexes
and the initial sensation of pain, express MOR mRNA at <15
pM and therefore have lower opioid sensitivity; and (5)
small nociceptors, those likely to be unmyelinated and to mediate
persisting pain, are much more likely to express MOR mRNA at levels
that yield maximal opioid sensitivity.
We suggest (Fig. 7B,C) that this quantitative difference in
the expression of MOR mRNA between myelinated and unmyelinated nociceptors contributes to the ability of opioids to suppress second
pain while sparing first pain and antinociceptive reflexes (Price et
al., 1985 ; Cooper et al., 1986 ; Yeomans et al., 1996 ). What other
factors might contribute to the ability of opioids to distinguish
different kinds of pain? At a cellular level, there might be
differences in the expression of the several other relevant genes,
those for G-proteins and those for Ca channels. Given the array of
different genes involved, we were surprised that a single one, the MOR
gene, could so clearly limit cellular response. Another factor could be
protein turnover and trafficking, which would determine what delay
occurs between a change in MOR mRNA level and the opioid response. Our
experiments were performed at the cell body and, presumably, at a
steady-state mRNA level. There might be very significant delays between
nerve terminals and mRNA expression at the cell body.
At a systems level, opioids suppress the unpleasantness of pain while
allowing its perception. This cannot be explained solely by spinal and
peripheral actions of opioids. During noxious stimulation, endogenous
opioids bind to receptors in the human thalamus and in select cortical
regions, likely sites for distinguishing the affective and sensory
actions of opioids (Zubieta et al., 2001 ). Unlike perception,
antinociceptive withdrawal reflexes are spinal, but here, too, there
can be players other than the presynaptic opioid receptors. Opioids act
on both the presynaptic Ca channels that we have studied and on
postsynaptic K channels of nociceptive synapses (Grudt and Williams,
1994 ; Kohno et al., 1999 ). Postsynaptic projection neurons receive
input from both myelinated and unmyelinated fibers, yet opioids inhibit
only the signals arising from unmyelinated input (Jurna and Heinz,
1979 ; Woolf and Wall, 1986 ; Light and Willcockson, 1999 ). The most
obvious mechanism would be presynaptic inhibition. However, if
unmyelinated input is more likely to use interneurons, postsynaptic
actions on interneurons would be selective for second pain.
Fine control of gene expression and quantitative PCR
MOR mRNA expression appears to be controlled in two different
ways. One functions like a simple on-off switch: turned on only in
nociceptors, it causes opioids to inhibit pain while sparing other
sensations. The other functions like a dimmer switch that can set the
MOR mRNA concentration to different levels in nociceptors that differ
in myelination.
Fine control of gene expression might be caused by selective RNA
stabilization (Wymore et al., 1996 ) or by control of transcription. A
mechanism for precise transcriptional control has been deduced for the
Endo 16 gene in sea urchins (Yuh et al., 1998 ), which provide great experimental advantages over neural tissue. The Endo 16 regulatory system consists of dozens of DNA binding proteins acting at
a handful of upstream promoting or repressing DNA sequences. Most of
this machinery is devoted to fine control of the transcription rate,
and only a small fraction is devoted to determining the site at which
transcription occurs in the animal (Yuh and Davidson, 1996 ). The
methods generally used in neurobiology to detect gene transcription in
individual cells, in situ hybridization and
immunocytochemistry, can identify the anatomic location of gene
expression but do not quantify it; thus, they would fail to detect
action of the bulk of the control machinery for Endo 16.
Quantitative single-cell PCR proved sufficient to detect the presence
of fine control of MOR mRNA level and, along with electrophysiological recordings, to suggest its physiological significance. Other
quantitative single-cell PCR studies demonstrated that the levels of
particular mRNAs determine glutamate receptor kinetics (Jonas et al.,
1994 ), K+ current amplitude (Baro et al.,
1997 ), and K+ current kinetics (Tkatch et
al., 2000 ). It might be hoped that real-time PCR (Heid et al., 1996 ),
which is easier to implement than the competitive PCR we used, might
make such quantitative studies more common. However, a side-by-side
comparison of different methods found that real-time PCR was inferior
at detecting small numbers of cDNA molecules (Tkatch et al., 2000 );
this can be a disadvantage given the low copy number of some
transcripts in single cells.
Concentration versus copy number
Some of our mRNA data are presented in the traditional way (copy
number per cell) (Fig. 5B, inset) and some as
cell-body concentration (Fig. 6). In most preparations, cells are all
approximately the same size, so concentration and copy number are
proportional. But cell volume varied 15-fold in our population, so the
difference needed to be confronted; moreover, the strong dependence on
cell size for mRNA copy number of a housekeeping gene (Fig.
5B, inset) clearly demonstrates the need for
normalization. Because mRNA freely diffuses from its site of
manufacture to its site of reaction, we presume that concentration, not
copy number, determines the probability of mRNA reaction and thereby
provides the better predictor of the number of protein molecules generated.
Relationship to other studies
MOR is the sole receptor responsible for morphine analgesia: it is
the only opioid receptor that binds morphine (Goldstein and Naidu,
1989 ; Raynor et al., 1994 ); its genetic knock-out eliminates the action
of morphine in mice (Matthes et al., 1996 ; Sora et al., 1997 ).
Our results extend this previous work by showing that fine control of
MOR mRNA gives distinct µ-opioid sensitivity to nociceptors that
mediate different kinds of pain. The quantitative differences in MOR
mRNA expression can explain why, in in situ hybridization,
MOR mRNA is seen in the same fraction of large and small cells (Wang
and Wessendorf, 2001 ), yet differences exist in opioid sensitivity
between large and small cells (Taddese et al., 1995 ; Borgland et al.,
2001 ). In agreement with hybridization, our quantitative RT-PCR found
that large and small nociceptors are equally likely to express MOR mRNA
above the detection threshold; however, when they express it, most
small nociceptors express MOR mRNA at quantitatively higher levels than
do most large nociceptors.
Our experiments do not address several important aspects of opioid
action on sensory neurons. We have not studied here the other opioid
receptors, and , both of which are detected in sensory ganglia
(Ji et al., 1995 ; Zhu et al., 1998 ). These receptors do not bind
exogenous opiates, but they do bind endogenous opioid peptides, and
thereby function in the endogenous pain-control system. There may also
be multiple splice variants of MOR (Pasternak, 2001 ); our PCR primers
were not targeted to distinguish these. We also do not address
long-term changes in opioid sensitivity, such as occurs in either
tolerance (Williams et al., 2001 ) or neurogenic pain (Iadarola and
Caudle, 1997 ).
Significance
Our experiments suggest that fine control of MOR mRNA
concentration in individual nociceptors controls their individual
opioid sensitivity, and that this may contribute to the ability of
opioids to suppress pain from a previous injury without blocking pain from a new injury or inhibiting reflex withdrawal from noxious stimuli.
We found that many nociceptors (including small ones) fail to express
MOR mRNA at levels that cause maximal opioid sensitivity; this suggests
that upregulating MOR gene transcription in nociceptors might be a
means of increasing the efficacy of opiate analgesia.
 |
FOOTNOTES |
Received March 28, 2002; revised Sept. 19, 2002; accepted Sept. 30, 2002.
The work was supported by grants from the National Institute on Drug
Abuse (NIDA) and the National Institute of Neurological Disorders and
Stroke (E.W.M.), by the Medical Scientist Training Program at
Washington University (S.C.S.), and by a predoctoral training grant
from NIDA (D.W.B.). We thank David Grandy for providing the MOR cDNA;
John Scott and Susan Amara for sharing molecular biology equipment;
Susan Brust for making the drawing in Figure 1; Sean Cook, MacDonald
Christie, Christina Lessov, and John Williams for giving helpful
comments on this manuscript; and Lori Vaskalis for providing help with
all illustrations.
Correspondence should be addressed to Dr. Ed McCleskey, Vollum
Institute, Oregon Health and Science University, L-474, Portland, OR
97239. E-mail: mccleske{at}ohsu.edu.
 |
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G. Dussor, M. J. Zylka, D. J. Anderson, and E. W. McCleskey
Cutaneous Sensory Neurons Expressing the Mrgprd Receptor Sense Extracellular ATP and Are Putative Nociceptors
J Neurophysiol,
April 1, 2008;
99(4):
1581 - 1589.
[Abstract]
[Full Text]
[PDF]
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Z. Fang, C.-K. Park, H. Y. Li, H. Y. Kim, S.-H. Park, S. J. Jung, J. S. Kim, A. Monteil, S. B. Oh, and R. J. Miller
Molecular Basis of Cav2.3 Calcium Channels in Rat Nociceptive Neurons
J. Biol. Chem.,
February 16, 2007;
282(7):
4757 - 4764.
[Abstract]
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