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The Journal of Neuroscience, March 15, 2000, 20(6):2383-2390
Peripheral Odor Coding in the Rat and Frog: Quality and Intensity
Specification
Patricia
Duchamp-Viret,
André
Duchamp, and
Michel A.
Chaput
Laboratoire de Neurosciences et Systèmes Sensoriels,
Unité Mixte de Recherche, Centre National de la Recherche
Scientifique-Université Claude Bernard Lyon 1, 69622 Villeurbanne cedex, France
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ABSTRACT |
In mammals, two recent studies have shown recently that one odor
molecule can be recognized by several molecular olfactory receptors
(ORs), and a single OR can recognize multiple odor molecules. In
addition, one olfactory receptor neuron (ORN) may respond to different
stimuli chosen as representative of distinct odor qualities. The aim of
the present study was to analyze quality and intensity coding abilities
of rat single ORNs, comparing them with previous extensive data
gathered in the frog to get insight into the generality of olfactory
coding mechanisms over vertebrates.
Response properties of 90 rat ORNs to different odors or to one odor at
different concentrations were analyzed. In the rat and the frog, odor
quality appears to be specified through the identity of activated ORNs.
However, rat ORNs have higher response thresholds. This lower
sensitivity may be interpreted as an increase in selectivity of rat
ORNs for low or medium odor intensities. In these conditions, the lower
proportion of activated ORNs could be counterbalanced by their number,
as well as by their higher glomerular convergence ratio in the
olfactory bulb. From amphibians to mammals, the olfactory system
appears to use universal mechanisms based on a combinatorial-coding mode that may allow quasi-infinite possibilities of adaptation to various olfactory environments.
Key words:
olfaction; odor; rat olfactory receptor neurons; odor
coding; in vivo single-unit extracellular recordings; comparison between amphibian and mammalian olfactory receptor response
properties
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INTRODUCTION |
The identification of a novel
multigene family that appears to encode proteins with seven
transmembrane domains that may bind odor molecules and transduce odor
reception signal through interactions with G-proteins (Buck and Axel,
1991 ; Buck, 1993; Raming et al., 1993) constitutes a major contribution
of molecular biology to odor transduction issue. It shed new light on
the question of odor coding and gave rise to a way of thinking that
places the interaction between odor molecules and their olfactory
molecular receptors (ORs) at the center of transduction mechanisms.
In mammals, our knowledge of the degree of specificity of
odor-receptor interaction mechanisms has been enriched recently by two
functional studies that differ by their methodology but are
complementary in the information they provide. The first one is the
calcium-imaging study coupled with reverse transcription-PCR of
rat olfactory receptor neurons (ORNs) in vitro (Malnic et al., 1999) in which the authors conclude that ORNs express only one OR each
but suggest that odor-receptor interactions can be realized through
multiple combinations. Thus, one odor molecule will be recognized by
several ORs, while one OR will be able to bind multiple odor molecules.
The second one is our electrophysiological study performed in the rat
in vivo (Duchamp-Viret et al., 1999) that shows that one ORN
may respond to different stimuli chosen as representative of distinct
odor qualities. Based on the hypothesis that one ORN would be endowed
with one OR, this study argues in favor of a broad odor-quality tuning
of ORs.
In light of these observations, the concept of combinatorial peripheral
coding, initially named "across fiber pattern" (Erickson, 1963),
becomes topical again. This type of coding, which involves numerous ORs
and ORNs to specify one odor quality, would produce a very enriched
code. As a matter of fact, a code based on a quasi-infinity of cell
combinations can both allow specification of pure chemicals with close
molecular structures through a continuum of variation of cell responses
and generate highly distinct patterns for complex odor mixtures.
This report sought to further document the rules governing
odor-receptor interactions at the level of single ORNs. Because the
qualitative and quantitative coding abilities of ORNs have been
extensively analyzed in the frog (Duchamp et al., 1974; Revial et al.,
1978a,b, 1982, 1983; Sicard and Holley, 1984), comparing these previous
studies with data gathered in the rat should provide insight into the
generality of olfactory coding mechanisms. To analyze the olfactory
coding abilities of ORNs, series of responses of ORNs to different
odors or to one odor at different concentrations were obtained. This
paper opens the useful opportunity to discuss our data with respect to
those obtained recently by Malnic et al. (1999) through molecular and
calcium imaging and attempts to get insight on some rules governing the
interactions between molecular odor receptors and multiple odorants.
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MATERIALS AND METHODS |
Surgical methods. Experiments were performed in
accordance with the European Communities Council Directive for the care
and use of laboratory animals. Adult Wistar rats (n = 35; weight, 250-300 gm) were anesthetized by an intraperitoneal
injection of Equithesine (mixture of pentobarbital sodium and chloral
hydrate) at the initial dose of 3 ml/kg and were secured in a
stereotaxic apparatus for surgical preparation. Anesthetic was then
supplemented as necessary to maintain a deep level of anesthesia.
Rectal temperature was maintained at 37 ± 0.5°C by a
homeothermic blanket (Harvard Apparatus, Holliston, MA), and
surgical wounds of the animals were regularly infiltrated with 2% Procaine.
Odor stimuli. Sixteen pure odor compounds were used as
stimuli in this study: acetophenone (ACE), anisole (ANI), camphor
(CAM), cineole (CIN), cyclodecanone (CDN), cyclohexanone (HEX),
p-cymene (CYM), heptanol (HEP), limonene (LIM), iso-amyl
acetate (ISO), methyl-amyl ketone (MAK), vanillin (VAN), and two pairs
of enantiomers, l- and d-carvone (l-
and d-CAR) and l- and d-citronellol
(l- and d-CIT). They were selected for their
effectiveness, their molecular structure, and their previous use in the
frog (Duchamp-Viret and Duchamp, 1997). Some of them were clearly
established as members of qualitative groups through studies of
Duchamp, Revial, and collaborators (Duchamp et al., 1974; Revial et
al., 1978a,b, 1982, 1983; Sicard and Holley, 1984). CAM and CIN belong
to the camphor group, LIM and CYM belong to the terpene group, ACE and
ANI belong to the aromatic group, MAK and ISO are linear ketones, and
CDN and HEX are cyclic ketones. Only VAN had never been tested in the
frog in vivo. It was chosen to get information on the
IP3 transduction pathway (Sklar et al.,
1986).
Stimuli consisted of odor pulses of 2 sec duration delivered at 200 ml/min. They were applied directly near the surface of the turbinate
using a dynamic multistage olfactometer as described previously
(Vigouroux et al., 1988), which ensured a precise control of the
concentration range and allowed the delivery of 12 discrete concentrations. Depending on their saturated vapor pressure (SV), compounds were delivered at concentrations ranging from 2.5 × 10 8/5.2 × 107
M/l (SV/562) to 1.4 × 105/2.9 × 104 M/l (SV). Stimuli were
delivered from the lowest to the highest concentration, and a delay of
at least 2 min elapsed between successive odor presentations.
Electrophysiological recordings and experimental paradigm.
Access to the olfactory mucosa was gained by removing the nasal bones
and then by gently slipping aside the dorsal recess underlying them.
Recordings were performed in the Endoturbinate at 0-400 µm depth.
Single-unit action potentials were recorded using metal-filled glass
micropipettes (2 µm diameter, 3-7 M impedance at 1000 Hz) and
electro-olfactograms (EOGs) with glass micropipettes of 50 µm
diameter filled with saline solution gelled with agar. These signals
were led through conventional amplifiers to a data tape recorder
(Biologic, Claix, France) for off-line analysis.
Spike signals were filtered between 300 and 3000 Hz. During
experiments, the single-unit nature of the spikes was controlled by
triggering the recorded cell on a memory oscilloscope. This allowed us
to control the characteristics of the polyphasic spike of the recorded
cell to ensure that the same cell was recorded during the entire
experimental procedure.
Because recording a single ORN for a period long enough to test the 16 odorants used in this study was rather difficult, the presentation of
the whole odor set was subdivided into three subsets. First, ACE, ANI,
CAM, LIM, ISO, and MAK were systematically delivered. Then CDN, CIN,
CYM, HEP, HEX, and VAN were presented. Last, l-CAR, d-CAR, l-CIT, and d-CIT were delivered
when possible. Stimuli were delivered at random within each subset.
Data acquisition and response measurement. The single-unit
activity and EOG signal were sampled off-line at 15 kHz and 200 Hz,
respectively, using a CED-1401 data acquisition system (Cambridge Electronic Design, Cambridge, UK) connected to a computer. Spikes were
first detected using their waveform as a criterion and then by
verifying visually the consistency of the shapes of the sorted spikes
on the computer screen. The stability and the unitary characteristics of the recordings were checked by following the form of the multiphase spikes and by selecting single-unit activities with a high
signal-to-noise ratio.
EOG analysis consisted of measuring the latency and the peak amplitude
of the signal with respect to the spontaneous baseline. The single-unit
activity was processed to calculate the mean spontaneous firing
frequency of the cell over a period of 3 min systematically sampled at
the beginning of each recording and to determine its response type to
each stimulus. Mean instantaneous frequencies of cells during their
initial burst of response were calculated, and latencies of the first
spike of this initial burst with respect to stimulation onset were measured.
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RESULTS |
The present analysis is based on the recordings of 90 ORNs that
were performed in 19 freely breathing and 16 tracheotomized rats
(Duchamp-Viret et al., 1999). Comparison was done with previous data
gathered in the frog (Rana ridubunda) in our laboratory
(Revial et al., 1982; Duchamp-Viret et al., 1989; 1990a,b;
Duchamp-Viret and Duchamp, 1997).
Spontaneous activity
As shown in Figure 1, rat individual
ORNs were generally more spontaneously active than frog ORNs. Indeed,
only 2 of 124 cells recorded by Revial et al. (1982) in the frog had a
spontaneous firing frequency between 100 and 200 spikes/min, and none
fired at more than 200 spikes/min. In contrast, in the rat, ~40% of the ORNs fired at more than 100 spikes/min. Nineteen cells fired at
more than 200 spikes/min, and seven of them had a spontaneous firing
frequency between 300 and 500 spikes/min.
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Figure 1.
Distribution of spontaneous ORN firing frequencies
in the rat (n = 90) and the frog
(n = 99) (Revial et al., 1982).
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General odor responsiveness
Figure 2 shows the single-unit
activity of a rat ORN that was excited by 5 of the 10 odors tested and
displayed different temporal response patterns and latencies. Such
differences were similar to those described previously in the frog
(Revial et al., 1982). Tonic long latency patterns were induced by ACE
and LIM, whereas decremental and more frequency-sustained bursts were
observed with ISO, ANI, and MAK.
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Figure 2.
Spontaneous activity (top trace)
and response profile (bottom traces) of ORN13 (raw
data). This ORN was tested with all odors except CIT. It did not
respond to CAM, CIN, VAN, d-CAR, and
l-CAR, and to CYM, CDN, HEP, and HEX (data not shown).
All its thresholds corresponded to SV/5.62, i.e., 3.5 × 106 M/l for ACE, 1.9 × 105 M/l for LIM, 3.5 × 105 M/l for ANI and MAC, and 5.2 × 105 M/l for ISO.
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In Figure 3, the percentages of
excitatory and suppressive responses of rat ORNs to the six most
frequently tested odors are compared with those elicited by the same
odor series in the frog (Revial et al., 1982). The comparison between
the two species was performed on responses to similar and high
concentrations of each compound so that potential differences of
sensitivity cannot interfere with results. Percentages of ORNs excited
by the six stimuli were both high and very close in the two species. Percentages of suppressed ORNs were very low in the rat and nearly zero
in the frog. Indeed, 1.8-10.7% of suppression was observed in the rat
according to the odors, whereas only MAK and ACE induced 5.5 and 1.4%
of suppressive responses, respectively, in the frog.
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Figure 3.
Percentages of excitatory (hatched
and dotted bars) and suppressive (black
bars) responses elicited by six odors commonly tested in the
rat and frog.
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Figure 4 gives the probability of
observing any combination of response types across the series of
individual rat ORNs for the whole odor set or for the initial set of
six odors. In this figure, the major response type was excitation
(E and E/N bars). Excitation and suppression were
observed in the same ORN in ~10% of the cells (E/S and
E/S/N bars).
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Figure 4.
Distribution of response types in single ORNs
response profiles. Black bars represent ORNs that were
simulated with the six odors of the first subset (ACE, ANI, CAM, LIM,
ISO, and MAC). Hatched bars represent ORNs that were
tested with 2 of the 16 odors of our set. Bars represent
response profiles of ORNs containing no response to all the tested
odors (N), excitatory responses only
(E), both excitatory and suppressive responses
(E/S), both excitatory and no responses
(E/N), both suppressive and no responses
(S/N), and excitatory, suppressive, and no
responses (E/S/N).
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Selectivity and qualitative discrimination
Four odors were commonly used at the same concentrations in this
study and in a previous one in the frog (Duchamp-Viret, 1988). ORNs of
the two species displayed different degrees of selectivity toward the
four odors (Fig. 5). In the frog, most of
the cells responded to one odor. Then, the proportion of excited cells
decreased when the number of stimuli was increased (Duchamp-Viret et
al., 1989). In contrast, in the rat, ~32% of ORNs were found
to be poorly selective because they responded to the four tested
odors.
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Figure 5.
Selectivity of ORNs for ISO, LIM, ANI, and CAM.
Distribution of the percentages of cells as a function of the number of
odors to which they responded by excitation. Hatched
bar, Rat (n = 51); line with
symbols, frog (n = 60).
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In the rat, the percentage of successful discrimination by odor pairs
was determined for the whole odor set. We calculated the proportion of
cells that responded to one odor with a response type and to another
odor with a different response type or failed to respond, among the
cells that responded at least to one of the two odors of the pair.
Results are given in Figure 6 in which odor pairs were ranked according to their score of successful discrimination. Percentages of successful discrimination varied from 29 to 78%. The least discriminated pair of odors was MAK-ISO, two linear
ketones. The most well discriminated pairs were ISO-CYM and ISO-CIN,
i.e., a linear molecule (ISO) compared with a terpene (CYM) or with a
small round camphoraceous molecule (CIN). The less well discriminated
odor pairs corresponded to those linked by the
 2 computation. A principal component
analysis was applied to the responses to the six most frequently tested
odors (data not shown). It grouped the two linear molecules (ISO and
MAK) on the one hand and the two aromatic compounds (ACE and ANI) on
the other hand. These two groups were separated from the terpene (LIM)
and the camphoraceous compound (CAM). These results are similar to
those described in the frog (Sicard and Holley, 1984).
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Figure 6.
Percentages of successful discrimination of odor
pairs by rat ORNs. On the right are indicated the number
of pairs used for each comparison. Only pairs presented to at least 15 cells are shown.
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Based on the four odors commonly used in the frog and rat at the same
concentrations, it was possible to compare the percentages of
successful discrimination of odor pairs in the two species (rat,
n = 51; frog, n = 60). As seen in
Figure 7, the discrimination abilities of
ORNs were not statistically different in the rat and frog
(nonparametric Kruskal-Wallis test).
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Figure 7.
Percentages of successful discrimination of odor
pairs in the rat and frog for ANI, ISO, LIM, and MAK.
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Intensity coding
In the rat, 21 cells were studied with concentration series. Over
these cells, the evolution of excitatory responses with concentrations
was rather similar. Stimulus strength was obviously transduced into
firing increases. Near thresholds, ORNs gave tonic response patterns.
When increasing concentrations, frequency generally increased, and
burst duration and latency decreased. However, even at high
concentrations, some cells that responded with high-frequency bursts
still discharged with a long latency (Fig. 2). Actually, latencies of
rat ORNs ranged from 200 msec to several seconds as described
previously in the frog (Revial et al., 1982; Duchamp-Viret et al.,
1990b). Concentration-response series are illustrated through
responses of ORN50 in Figure 8, and the
high-frequency bursts constituting the initial sustained excitatory
responses of this cell are shown in Figure
9. For high concentrations, this cell
gave early regular and rhythmic decremental bursts. Discharge frequencies were very high, and the size of the spikes were assumed to
be reduced proportionally to the amplitude of the odor-evoked depolarization as described previously through intracellular recordings in the salamander (Trotier and Mac Leod, 1983) and extracellular recordings in the frog (Revial et al., 1982). When repolarizing, ORNs
gave incremental discharges that constituted "off" effects of the
initial responses. By pooling the discharges of the population of ORNs,
such delayed off discharges were shown previously not to prevail
in the overall output activity flow rate of the mucosa (Duchamp-Viret
et al., 1990).
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Figure 8.
Spontaneous (top trace) and
odor-evoked single-unit responses and EOGs (pairs of
bottom traces) of rat ORN50 (raw data) to increasing
concentrations of ANI. Recordings obtained for two presentations at
1.98 × 105 M/l (SV/10)
illustrate the reproducibility of the response. Firing frequencies in
the initial response burst and amplitudes of the EOG are given between
the respective recordings. Concentrations (molar) are on the
left and right, respectively.
Asterisks below single-unit recordings indicate the
artifact at the beginning of the stimulation. This ORN had a mean
spontaneous firing frequency of ~1 spike/sec.
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Figure 9.
Detail of Figure 8. Initial decremental response
bursts of ORN50 (indicated by arrowheads in Fig. 8)
elicited at high concentrations.
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Using such temporal response series, concentration-discharge frequency
curves and corresponding concentration-latency curves were
established. Although the aspect of frequency curves directly depends
on the method of quantification, they give a synthetic view of spike
frequency odor coding. As with frog ORNs, rat ORNs never adapted in our
experimental conditions. Moreover, they showed reproducible responses
to repeated presentations of the same stimulus, as exemplified by the
two traces at the bottom of Fig. 9.
Concentration-response curves established for rat ORN50 (whose
response patterns were shown in Fig. 8) and ORN55 are given in Figures
10 and
11, respectively. These examples well
illustrate how the frequency of the spike discharge and the amplitude
of the EOG recorded simultaneously increased with concentration.
Moreover, the insets in Figures 10 and 11 show how the
latencies of the spike bursts and EOG responses decreased with
concentrations. More precisely, Figure 10 shows that ORN50 responded
from the lowest concentration but with a latency of 500 msec. Thus, at
low concentrations, this cell did not participate to the genesis of the
early phase of EOG. When concentrations increased, response latency
decreased to the EOG latency. This would result in a synchronization of
the population of ORNs at high concentration as described previously in
the frog (Duchamp-Viret et al., 1990b). ORN55 (Fig. 11) reached its
threshold, whereas the EOG response was detectable at lower
concentrations. Moreover, its latency was high (>1 sec). At higher
concentrations, the beginning of the cell discharge and EOG were
simultaneous. Very similar types of concentration-response
relationships were observed in the frog (Duchamp-Viret, 1988).
Nevertheless, rat ORNs were able to fire at very high frequencies, up
to 142 spikes/sec, compared with frog ORNs, which reached a maximum
rate of ~60 spikes/sec.
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Figure 10.
Concentration-response curves of ORN50 spike
frequency and EOG amplitude, and their corresponding latency curves
(inset).
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Figure 11.
Concentration-response curves of ORN55 spike
frequency and EOG amplitude, and their corresponding latency curves
(inset).
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The sensitivity of the ORN
In the rat, 55 response thresholds were determined for 21 of 51 cells systematically stimulated with the six odorants. Figure 12 presents their distribution as a
function of the stimulus concentration expressed in terms of number of
odor molecules per liter. For each odorant, thresholds were distributed
on the whole concentration range used in the study but showed a
tendency to gather toward the lowest and highest concentrations.
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Figure 12.
Distribution of rat ORNs response thresholds
(n = 55) over the concentrations ranges for the six
odors of the first subset. For each odor, the diameters of the
filled circles are proportional to the number of
thresholds determined for a given concentration.
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Figure 13 shows the recruitment of the
rat ORNs for the four odors tested communally in the rat and frog
(Duchamp-Viret et al., 1989). It gives for the four odors
together the cumulated proportion of cells in which response thresholds
were reached or surpassed as a function of increasing concentration.
Both frog and rat recruitment curves have approximately the same shape, but in the frog, the curve is shifted toward the lower concentrations. Approximately 50% of the frog ORNs were recruited at  of
saturated vapor, whereas 50% of the rat ORNs were recruited at
 of saturated vapor. The lower number of active ORNs at low
concentration in the rat may be the sign of a lower sensitivity or a
higher selectivity of the cell population for these tested odors.
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Figure 13.
Dynamics of ORNs recruitment for ANI, CAM, ISO,
and LIM in the rat and frog. The cumulative number of excited cells is
represented as a function of concentration. One hundred percent of
excited cells correspond to 53.5 and 59% of the total number of
stimulation performed in the rat and frog, respectively. We had
observed in preliminary experiments the low sensitivity of rat ORNs
compared with the frog. This led us to shift the concentration range
available toward higher values. Thus, concentrations lower than
SV/1000 were not tested in the rat.
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DISCUSSION |
This comparison of response properties of ORNs in the rat and the
frog was not planed to focus on interspecies similarities or
differences per se but rather to draw general principles of the
functioning of the vertebrates' olfactory system using these two
animal species as a model. On the whole, rat and frog ORNs were found
to function similarly. The small differences observed are discussed below.
In the rat, the observation of suppressive responses was facilitated by
the relatively high rates of spontaneous firing of ORNs. However, the
number of suppressive responses was low but higher than in the frog in
which suppressive responses were rarely observed (Revial et al.,
1978a,b, 1982, 1983). In terrestrial vertebrates, the
IP3 transduction pathway was reported to be at the origin of suppressive responses, whereas the cAMP transduction pathway would generate excitatory responses, with these two
transduction pathways being the targets for distinct odor molecules
(Sklar et al., 1986; Raming et al., 1993). In agreement with the
literature, the few inhibitory responses observed in the present study
were assumed to be attributable to the fact that the used odor
stimuli were mainly devoted to set in motion the cAMP pathway.
Another explanation would be that suppressive responses could result
from interactions between several molecules composing a mixture at the
level of the two transduction pathways. Thus, the low number of
suppressive responses observed in the present experiment may result
from the use of pure chemicals. In contrast, when ORNs are stimulated
with an odor mixture, the probability of activating the two
transduction pathways (cAMP and IP3) would be
increased. This is all the more probable that the existence of these
two pathways has been evidenced in the two species (Sklar et al., 1986;
Breer et al., 1990) and that a single ORN would be endowed with the two
pathways (Dionne, 1992; Miyamoto et al., 1992; Ngai et al., 1993; Kang
and Caprio, 1995a,b; Cromarty and Derby, 1997; Sanhueza and Bacigalupo,
1999).
Although to date the question of the genesis of excitatory or
suppressive responses through cAMP and IP3
pathways has not been elucidated in vertebrates, some observations done
in the frog are in favor of the hypothesis that the expression of
inhibitory mechanisms in vertebrate ORNs could result from odor
molecular interactions (Revial et al., 1978). For example, a mixture of cineole and anethole has been shown to induce a weaker response than
the latter odorant alone, and an excitatory response to cineole has
been shown to become a suppressive response when the application of
this odorant was preceded by the delivery of anisole, bromobenzene, dichlorobenzene, or anethole, all molecules that belong to the aromatic
group (Duchamp-Viret and Duchamp, 1997). Moreover, some authors have
shown that ORNs for which one component of a binary mixture is
excitatory and the second is either neutral or inhibitory commonly can
show mixture suppression (Derby et al., 1989; Michel and Ache, 1992,
1994; Daniel et al., 1994, 1996; Kang and Caprio, 1997). Such phenomena
have been named mixture interactions (Laing et al., 1984). Given these
data, the present observation that only 10% of rat ORNs were excited
by a stimulus and inhibited by another (Fig. 4) could be explained by
the lack of molecular interactions when pure chemicals are used and by
the fact that our odor set was small compared with all potential odors.
We assume that the effectiveness of stimuli of inducing excitatory
responses was maximal in our experimental conditions, as well as in
frog studies, in which ORNs worked within a frame devoid of molecular interactions at the level of the ORs. This may also account for the
only 15-20% of ORNs that did not respond to any stimulus in the rat
and frog, respectively.
In contrast, the use of pure chemicals may have a detrimental effect on
the mechanisms of qualitative discrimination because it can be easily
imagined that the overlapping of arrays of excited ORNs that coded for
different stimuli ought to be greater without molecular competition
than in odor mixtures. However, despite this assumption, up to 80%
discrimination was observed for some odor pairs (Fig. 6). In the rat,
the possibility of a large overlap of arrays of ORNs, especially
represented by the 30% of neurons that responded to the six most
frequently tested odors, i.e., that were not selective (Duchamp-Viret
et al., 1999, their Table 1), implies that molecular receptors borne by
single ORNs would be capable of recognizing several distinct molecular
structures and conversely that a given molecule would bind with several
molecular receptors. This is in agreement with the recent results of
Malnic et al. (1999).
If the selectivity of ORNs directly mirrors the specificity of ORs, the
30% of ORNs that were not selective to the six most frequently tested
odors in the rat may signify that peripheral abilities to discriminate
the stimuli are reduced in the rat with respect to the frog. However,
the comparison of the percentages of discrimination of the odor pairs
used in both species did not show such a decrease (Fig. 7). Here, as in
previous studies (for review, see Duchamp-Viret and Duchamp,
1997), the ability of ORNs to discriminate odors was estimated
to be directly proportional to their selectivity. However, even
nonselective ORNs may be envisaged as discriminating two odors if these
odors elicit two distinct temporal response patterns. In the first
stage of the olfactory system, the "rate coding mode" is widely
accepted, and the high convergence of the projections of the ORNs on
bulbar glomeruli seems not favorable to the preservation of a "time
coding mode". Further studies would be necessary to precisely analyze
spike trains of ORNs and to shed light on this question more definitively.
To really compare the selectivity of and discrimination abilities of
ORNs in these two vertebrate species, the relevance of stimulus
concentration and its interaction with selectivity must be taken into
account. In the rat, we show that the number of responding ORNs
increases with concentration (Fig. 13). This is in agreement with the
literature on the rat (Sato et al., 1994; Malnic et al., 1999) and has
been shown previously in the frog (Duchamp-Viret et al., 1989).
Assuming that this fact mirrors, at least partly and indirectly the
specificity of ORs, this seems to signify that this specificity would
decrease when concentration increases. However, this result can be
interpreted differently, especially in the rat because response
thresholds of ORNs, although distributed over all the available
concentration range, tended to be more numerous at the two extremes of
this range. This may reveal two different functioning modes of the
olfactory system.
A first mode of functioning of the ORNs would be concerned with low and
medium concentrations and would involve only highly specific binding
mechanisms. Here, ORNs would be highly selective, thus implying that
the probability to find their specific ligand is very low by using a
small number of stimuli. In the rat, the especially low percentage of
involved ORNs in the coding of an odorant would be compensated first by
a higher number of ORNs, 32 × 106
ORNs per mucosa (Meisami, 1991) against 2-5 × 106 in the frog (Bronstein, 1977), and
second by a glomerular convergence ratio ~24-fold higher in the rat
(Meisami, 1991) than in the frog (Byrd and Burd, 1991). Thus, at low
concentration, the sensitivity of the system would be preserved in the
rat, despite a higher selectivity of ORNs. More generally in
vertebrates, odor quality would be encoded at low concentrations by
arrays of ORNs that have little overlap in response, with their overlap
increasing with concentration. The effectiveness of stimuli is assumed
to be maximal in our experimental conditions, and this overlap would be
limited with natural odor or mixtures, thanks to molecular interactions
between components or competition at binding site levels and to the
duality of the transduction pathways. Thus, a mixture would have its
own unique quality that may arise from these mechanisms (Derby
et al., 1989; Daniel et al., 1996).
A second mode of ORNs functioning would concern high concentrations in
which less specific mechanisms would occur involving olfactory
receptors with lower affinities. In the present experiment, this mode
of functioning was especially evident because the use of pure chemicals
avoided the interactions between different molecules, whereas such
interactions would favor high affinity binding. In contrast with
natural odors or experimental mixtures, our opinion is that this less
specific binding of odor molecules on receptor sites would be all the
more limited than mixtures are complex.
Our results show that intensity coding seems to be ensured through an
increase of the discharge frequency in initial bursts that occurs
earlier with concentration. Moreover, the number of recruited ORNs
increases with concentration. Such a cell recruitment process implies
that the combination of ORNs stimulated by an odorant will
progressively be enriched with intensity. Such a progressive change in
combinations of ORNs as a function of concentration may have a
consequence on the odor qualitative identity. As a matter of fact,
combinations of ORNs elicited by a low and a high concentration of the
same odorant might be analyzed as distinct qualities. However, we
propose that this does not imply that odor quality shifts
systematically with concentration because the recruitment process has
been described previously as useful to specify the odor quality feature
of the combinations of ORNs in the frog (Duchamp-Viret et al.,
1989, 1990a; Sato et al., 1994; Malnic et al., 1999). An
alternative hypothesis is that the identity of recruited ORNs with
concentration would specify not only the quality of an odor but also
its intensity (Duchamp-Viret, 1988; Derby et al., 1991).
In conclusion, airborne olfactory reception could be ensured over
terrestrial life vertebrates through very universal mechanisms. From
amphibians to mammals, phylogenetic evolution likely accounts for an
increase of specificity of ORs. Nevertheless, the combinatorial-coding mode remains valid because it is unrestrictive. From a perceptual and
behavioral point of view, this latter property appears all the more
useful because vertebrates were confronted with a larger number of odor
molecules when they acceded to a terrestrial life. During this kind of
adaptation, the olfactory system had to increase the specificity of ORs
while preserving the multiplicity of coding possibilities.
| |
FOOTNOTES |
Received Sept. 27, 1999; revised Dec. 28, 1999; accepted Dec. 28, 1999.
We are grateful to Dr. G. Sicard for the mathematical analyses of the
data and Dr. J. W. Scott for his comments on this manuscript.
Correspondence should be addressed to P. Duchamp-Viret, Laboratoire de
Neurosciences et Systèmes Sensoriels, Unité Mixte de
Recherche, Centre National de la Recherche
Scientifique-Université Claude Bernard Lyon 1, 43 boulevard du
11 novembre 1918, 69622 Villeurbanne cedex, France. E-mail:
pduchamp{at}olfac.univ-lyon1.fr.
| |
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ABSTRACT
INTRODUCTION
