Chemical Senses Vol. 29 No. 8 © Oxford University Press
2004; all rights reserved
Monosodium Glutamate and Sweet Taste: Discrimination between the Tastes of Sweet Stimuli and Glutamate in Rats
Neuroscience Program, Department of Psychology, Regis University, Denver, CO 80221, USA
Correspondence to be sent to: Eugene R. Delay, Neuroscience Program, Department of Psychology, Regis University, 3333 Regis Blvd, Denver, CO 80221, USA. e-mail: edelay{at}regis.edu
 |
Abstract |
|---|
 Top Abstract IntroductionMaterial and methodsResultsDiscussionAcknowledgementsReferences |
|---|
Generalization of a conditioned taste aversion (CTA) is based on similarities in taste qualities shared by the aversive substance and another taste substance. CTA experiments with rats have found that an aversion to a variety of sweet stimuli will cross-generalize with monosodium glutamate (MSG) when amiloride, a sodium channel blocker, is added to all solutions to reduce the taste of sodium. These findings suggest that the glutamate anion elicits a sweet taste sensation in rats. CTA experiments, however, generally do not indicate whether two substances have different taste qualities. In this study, discrimination methods in which rats focused on perceptual differences were used to determine if they could distinguish between the tastes of MSG and four sweet substances. As expected, rats readily discriminated between two natural sugars (sucrose, glucose) and two artificial sweeteners (saccharin, SC45647). Rats also easily discriminated between MSG and glucose, saccharin and, to a lesser extent, SC45647 when the taste of the sodium ion of MSG was reduced by the addition of amiloride to all solutions, or the addition of amiloride to all solutions and NaCl to each sweet stimulus to match the concentration of Na+ in the MSG solutions. In contrast, reducing the cue function of the Na+ ion significantly decreased their ability to discriminate between sucrose and MSG. These results suggest that the sweet qualities of glutamate taste is not as dominate a component of glutamate taste as CTA experiments suggest and these qualities are most closely related to the taste qualities of sucrose. The findings of this study, in conjunction with other research, suggest that sweet and umami afferent signaling may converge through a taste receptor with a high affinity for glutamate and sucrose or a downstream transduction mechanism. These data also suggest that rats do not necessarily perceive the tastes of these sweet stimuli as similar and that these sweet stimuli are detected by multiple sweet receptors.
Key words: glucose, MSG, saccharin, SC45647, SC45647 threshold, sucrose
|
Introduction |
|---|
|
TopAbstractIntroductionMaterial and methodsResultsDiscussionAcknowledgementsReferences |
|---|
Glutamate is a naturally occurring amino acid that is found in many protein-rich foods such as meats, fish, cheese and some vegetables. The taste of glutamate is believed to have a unique quality called ‘umami’ that is distinct from the other primary tastes of sweet, sour, salty and bitter (Yamaguchi, 1967
). Monosodium glutamate (MSG) is considered
to be the prototypical umami substance and has long been incorporated into Asian cuisine
to enhance flavor (Maga, 1983). The
ability of an organism to detect glutamate is important because its taste signals the
presence of dietary protein and it can increase the palatability of food, thereby
increasing food intake (Bellisle,
1999). Even though glutamate is an important food additive and a substance
naturally present in many foods, the peripheral mechanisms responsible for the taste
sensation of MSG are not yet well understood.
Although humans perceive the taste of MSG as umami, under certain conditions rats
perceive the taste of MSG as similar to that of sucrose. If a taste aversion is
conditioned (CTA) to MSG mixed with amiloride (an Na+ channel blocker
that reduces the Na+ component of MSG taste), this CTA will also cause
rats to avoid sucrose, suggesting that MSG and sucrose share perceptual qualities
(Yamamoto et al., 1991;
Chaudhari et al., 1996;
Stapleton et al., 1999;
Heyer et al., 2003). These
findings have piqued the interest of researchers and spawned a surge of research activity
in umami taste transduction. Behavioral and molecular evidence indicate that, in rats,
glutamate activates a novel taste variant of a G-protein coupled class III metabotropic
glutamate receptor (mGluR4).
Chaudhari et al. (2000)
cloned a taste-mGluR4 receptor that is identical to the brain mGluR4 except the
n-terminus of the taste-mGluR4 receptor is truncated and has a lower affinity for
glutamate. Behavioral studies have also supported the role of this receptor in umami
taste (Chaudhari et al.,
1996;
Delay et al., 2000, 2004).
Another taste specific G-protein coupled receptor, a heterodimer formed from the
combination of T1R1 and T1R3 subunits, has also been implicated in umami taste
(Nelson et al., 2002;
Damak et al., 2003;
Zhao et al., 2003).
Behavioral and molecular studies have shown that this T1R1 + T1R3 heterodimer is
responsive to MSG and other substances that elicit an umami taste and appears to be able
to detect certain other L-amino acids as well. In contrast, stimuli that
elicit a sweet sensation in humans activate a different heterodimeric receptor (T1R2
+ T1R3) that is not activated by umami substances (Nelson et al., 2002;
Zhao et al., 2003). In
short, a combination of behavioral and molecular data support the notion that MSG and
sweet stimuli activate different afferent pathways.
In spite of apparent differences in afferent mechanisms activated by MSG and sweet
stimuli, strong cross-generalization of CTA between MSG mixed with amiloride and the
natural sugars sucrose and glucose (and, to a lesser extent, maltose) and the artificial
sweeteners saccharin and SC45647 has been reported for rats (Heyer et al., 2003). These data suggest that the
taste of glutamate mimics the taste qualities of sucrose and other natural sugars and
artificial sweeteners. In addition,
Stapleton et al. (2002)
found that rats had difficulty discriminating between sucrose and MSG when the cue
function of the Na+ ion was reduced by either adding amiloride to test
solutions or by matching the Na+ content of sucrose to that of MSG.
Collectively, these findings suggest that to rats glutamate has a strong, maybe even
dominating ‘sweet’ component and raise the question of whether rats can
discriminate between any of these sweet substances and MSG. It is possible that rats may
not be able to differentiate between substances identified as ‘sweet’ and
‘umami’ by humans. To address this issue, behavioral discrimination
experiments were conducted with rats to determine the degree to which rats could
discriminate between the tastes of MSG and several natural sugars (sucrose and glucose)
and artificial sweeteners (sodium saccharin and SC45647) that previously were reported to
show strong bi-directional generalization of CTA. If glutamate primarily elicits a sweet
taste in rats, then they should have difficulty discriminating between MSG and these
sweet substances, especially when the role of Na+ taste is reduced.
|
Material and methods |
|---|
|
TopAbstractIntroductionMaterial and methodsResultsDiscussionAcknowledgementsReferences |
|---|
Subjects
Twenty-nine male albino Sprague–Dawley rats were obtained from Harlan Sprague–Dawley (Indianapolis, IN). At the beginning of the experiment all animals were 90–120 days old, weighed between 300 and 450 g and were housed individually. Two weeks prior to testing, the rats were placed on a 21 h water deprivation schedule that was maintained throughout the experiment. Purina Lab chow was available ad libitum. The colony lighting was regulated according to a 12 h light/dark cycle with the lights turned on at 7:00 a.m. All testing took place during the light portion of the cycle and each rat was tested at the same time each day.
Apparatus
Each test station contained a computer controlled Knosys Ltd gustometer (Brosvic and Slotnick, 1986) housed in individual
benchtop stations. Each test apparatus consisted of a Plexiglas operant chamber (25.4
x 15.9 x 20.6 cm) with a small circular opening (2.2 cm diameter) in one
wall, centered 11.4 cm from the floor of the chamber, that permitted access to a drinking
spout positioned 3 mm behind the portal. A fan, mounted in the ceiling of the chamber,
forced air out of the chamber through the opening for the spout to reduce olfactory cues.
Each taste solution was stored in one of ten 10 ml unpressurized syringe barrels that
were located at least 15 cm above the drinking spout. The flow of solution from each
syringe barrel was regulated by solenoids, located at least 20 cm from the chamber. All
syringe barrels were connected to capillary tubing through which each solution flowed to
individual 24 gauge stainless steel tubes within the drinking spout. The tips of these
tubes were recessed 2 mm from the end of the spout. Each taste stimulus was presented as
a 55 µl aliquot delivered over 0.6 s. Licks were counted when the
animal’s tongue made contact with the drinking spout and completed a 64 nA contact
current through a stainless steel plate on the floor of the chamber. All testing was
conducted under 30 ± 5 lx illumination from a white incandescent bulb inside the
station. To reduce auditory cues, an independent solenoid was activated simultaneously
with the solenoid delivering the stimulus. In addition, a Radio Shack Sleep Machine
generated masking noise (SPL A scale: 75 ± 5 dB) throughout the test period.
Procedures
Training procedures
Training and discrimination methods were similar to those used in previous experiments
(Stapleton et al., 2002;
Delay et al., 2004). Six
rats were randomly assigned to four test groups. Each group was trained to discriminate
between one of four sweet taste substances—sucrose, glucose, sodium saccharin
(Sigma, St Louis, MO) and SC45647 (Nofre et
al., 1990)—and MSG (Sigma). Initially, half of the rats in each
group were randomly assigned to discriminate MSG from deionized water and the other half
of the animals were assigned to discriminate easily detectable concentrations of the
sweet substance from deionized water. To initiate a trial, the rats licked on a variable
ratio 20 schedule that resulted in a 35 µl water rinse. Three seconds later, the
rat could begin a second variable ratio 20 schedule which, when completed, resulted in
the delivery of the 55 µl stimulus aliquot. Once the stimulus was delivered, the
rat had 2 s (decision interval) to determine if the stimulus was an S+ or an
S–. After the delivery of an S+ solution, the rat had to lick the spout during
the last 0.4 s of the decision interval to receive a 70 µl water reinforcer (i.e.
correct detection of the S+). Upon delivery of an S– solution, a correct
detection was registered if the rat did not lick during the last 0.4 s of the decision
interval. If the animal failed to correctly respond to the S– taste stimulus, a
weak shock (30–35 mV) was delivered through the lick spout to the animal’s
tongue. The shock intensity was adjusted for each animal by increasing the intensity
until the rat briefly stopped licking when the shock was applied. Shock was always
presented to the lick spout for 2 s following the end of the decision interval of
S– trials. However, the animal only experienced shock if it licked the spout during
the shock presentation. A 10 s intertrial interval occurred before the start of the next
variable ratio 20. A session was completed after the animal completed 160 trials or an
hour had elapsed, whichever came first. During each training session, seven of the
stimulus barrels contained different concentrations of the taste stimulus (S–) and
three contained deionized water (S+). An equal number of S+ and S– trials
were presented within each session and the order of the S+/S– presentations
followed a random sequence established with a Latin square design. A different
concentration sequence was tested each day and each concentration was stored in a
different syringe barrel each day to minimize the possibility that the rat could identify
a taste stimulus using the location of the stimulus delivery in the spout. When the
detection rate of a concentration was 80% in three consecutive sessions, the range
of concentrations was decreased in the next session until the test concentrations were
reached. Following the end of a session, the rat was returned to its home cage and 15 min
later the rat received an additional hour of access to water.
Before the discrimination experiments with SC45647 were conducted, five additional rats were trained with the above procedures with concentrations as low as 0.001 mM to establish the detection threshold, defined as the concentration detected 50% of the time. Each concentration was tested in at least three sessions. A second set of tests was conducted with 30 µM amiloride added to all solutions. The range of detection thresholds for SC45647 for these rats was between 0.0012–0.0045 mM without amiloride and 0.0022–0.0047 mM with amiloride.
Discrimination procedures
Once the rats reached a stable rate of performance with water as the S+ and the
test concentrations of one of the taste substances as the S–, discrimination
procedures were initiated by changing the S+ condition from water to the opposite
taste substance. For example, of the six rats assigned to the sucrose/MSG discrimination,
three were tested with sucrose as the S+ and MSG as the S– and three were
tested with MSG as the S+ and sucrose as the S–. During each test session, 5
of 10 stimulus tubes contained different concentrations of the S+ and 5 contained
different concentrations of the S–. The stimulus tubes and the stimulus
presentation order were randomized each day with a Latin square.
To minimize the possibility that stimulus intensity rather than stimulus quality
could serve as a discriminative cue, five concentrations of each substance were tested
each day. The concentrations of each substance used in the discrimination experiments
were based on a combination of detection threshold values, pilot data and previous CTA
studies in which strong cross-generalization between the sweet substance and MSG was
reported (Stapleton et al.,
1999;
Heyer et al., 2003). The
test concentrations of MSG were 10, 25, 50, 100 and 150 mM in all experiments. The range
of glucose concentrations was 100, 200, 300, 400 and 500 mM. Because of apparently
steeper psychophysical functions, the stimulus concentrations of sodium saccharin and
SC45647 were divided into high and low ranges. For saccharin, the low range of
concentrations included 0.5, 0.625, 0.75, 1.0 and 1.25 mM and the high range included
1.25, 1.5, 2.0, 2.5 and 3.0 mM. For SC45647, the low range included 0.005, 0.0075, 0.01,
0.015 and 0.02 mM and the high range included 0.02, 0.025, 0.03, 0.035 and 0.04 mM. The
pH of all stimuli was between 6.75–7.0.
Because the Na+ ion of MSG could serve as a cue to differentiate MSG
from the other substances, these experiments were conducted under three separate
conditions to control for sodium taste: (1) no amiloride, (2) amiloride (30 µM) in
all solutions and (3) amiloride (30 µM) in all solutions and NaCl added to the
sweet solutions. The last condition was conducted because amiloride, although tasteless
at 30 µM (Markison and Spector,
1995), does not fully block Na+ taste at the higher
concentrations (Geran and Spector,
2000). Thus, to further minimize the cue function of sodium taste, NaCl was
added to each solution of the sweet substance to match the Na+ content of
each concentration of MSG. When testing glucose, for example, 10 mM of NaCl was added to
the 100 mM concentration of glucose, 25 mM of NaCl was added to the 200 mM concentration
of glucose and so on.
Discrimination training began with at least 14 days of the no amiloride condition to ensure stable performance. The rats were then run an additional 4 days for data collection. This was followed by 6 days of training with the amiloride condition and then 4 days of testing. Another 6 days of training followed and then 4 days of testing with the amiloride and NaCl matching condition. Finally, the amiloride condition was repeated for an additional 6 days to control for experience and the data from the last 4 days were averaged with the first set of scores. After completion of each sodium cue condition, an additional test session was conducted to determine if any of the rats were able to discriminate between stimulus tubes on the basis of spout location or some equipment generated cue. All experimental parameters were maintained during this session except each tube was filled with water and randomly assigned as an S+ or S–. For the rats in the saccharin and SC45647 experiments, discrimination began with the low range of concentrations and then the procedures were repeated for the high range of concentrations.
|
Results |
|---|
|
TopAbstractIntroductionMaterial and methodsResultsDiscussionAcknowledgementsReferences |
|---|
Even though the substances treated as the S+ and S– were counterbalanced in each experiment, the data were examined to see if there were any differences in performance related to the specific substance being tested as the S+ and S–. No significant differences were detected for this factor and thus to simplify the analyses, scores for the two substances were pooled for the S+ and S– conditions in each experiment. The primary analysis of the data for each experiment examined the number of correct detections for each stimulus. This within subject analysis of variance examined the effects of sodium cue condition (3) and concentrations matched by ordinal ranking (5) on correct detections.
Sucrose versus MSG
In general, the discrimination between sucrose and MSG was easy for these rats but, as
seen in Figure
1, it became much more difficult when
the cue function of Na+ was reduced. The analysis of these data indicate
that detection rates decreased systematically as the concentrations of the two substances
decreased [F(4,20) = 58.91, P < 0.001]. This ANOVA
also revealed a significant main effect for the sodium cue condition
[F(2,10) = 11.44, P < 0.005]. Further analysis of
this variable using simple effects tests and Bonferroni t-tests (Howell, 1997) indicated that detection rates were
significantly higher in the no amiloride condition than in either the amiloride or the
amiloride plus NaCl conditions and that these differences were seen primarily at 10, 25
and 50 mM (all Ps 
0.05). Detection rates in the no amiloride condition were
between 86 and 98%, whereas detection rates for the other two sodium cue
conditions were between 72 and 94%. These results indicate that the discrimination
between sucrose and MSG is rather easy for these rats, but when the cue function of
Na+ is reduced, this discrimination is much more difficult.
|
Glucose versus MSG
Rats easily discriminated between glucose and MSG, regardless of the sodium cue condition (Figure 2). Mean detection rates ranged between 93.1 and 98.7%. The ANOVA detected a significant effect of concentration on detection rates [F(4,20) = 9.63, P < 0.001] which was due to a small but significantly lower detection rate for the 100 mM glucose/10 mM MSG pair of concentrations than for the other concentrations. The analysis did not find any effect related to the sodium cue condition.
|
Saccharin versus MSG
The rats also found the saccharin/MSG discrimination task easy to perform at all concentrations. The analysis of the data for the low range of saccharin concentrations (0.5–1.25 mM) revealed a significant effect related to concentrations [F(4,20) = 14.03, P < 0.001] and to the interaction between the sodium cue condition and concentration [F(4,20) = 2.23, P < 0.05]. Simple effects and Bonferroni t-tests indicated that detection rates at the lowest concentrations of MSG and saccharin were significantly higher in the no amiloride condition than in either of the other two sodium cue conditions (P < 0.01). The sodium cue conditions did not affect performance at any of the higher concentrations (Figure 3).
|
The analyses of the correct detection data for the high range of saccharin concentrations (1.25–3.0 mM) revealed only a significant effect of concentration [F(4,20) = 21.36, P < 0.001]. Although detection rates (Mean = 91.8 ± 0.7%) were significantly lower at the lowest concentrations of saccharin (1.25 mM) and MSG (10 mM) than at the other concentrations, this effect was small (Figure 3). No effect related to the sodium condition was found. Thus, these rats easily distinguished between saccharin and MSG at all concentrations of the solutions tested.
SC45647 versus MSG
Importantly, a paired comparison t-test indicated that the threshold estimates for
SC45647 were unaffected by amiloride (P > 0.10) (without amiloride, mean
threshold estimate = 0.0037 mM; with amiloride, mean threshold estimate =
0.0041 mM). In the discrimination experiments, the rats generally found this
discrimination task easy to perform. The mean correct detections ranged between 81.8 and
98.8% for the low range of concentrations of SC45647 (0.005–0.02 mM) and MSG
(left panel, Figure
4). Although these detection rates
indicate that this was a relatively easy discrimination for rats, the ANOVA procedures
revealed significant effects for the sodium cue condition [F(2,10) =
14.80, P < 0.005], concentration [F(4,20) = 16.12,
P < 0.001] and their interaction [F(8,40) = 3.74,
P < 0.001]. Simple effects tests indicated significant differences
between sodium cue conditions at the three lowest concentrations of MSG and SC45647
[all Fs(2,10) 
6.43, P < 0.001]. Bonferroni t
comparisons of the two lowest stimulus concentrations showed that detection rates were
significantly lower when amiloride or amiloride and NaCl were added to neutralize the cue
function of the Na+ ion (P < 0.01). At 50 mM MSG and 0.01 mM
SC45647, detection rates in the amiloride condition were significantly lower than in the
other two conditions (P < 0.01). Thus, even though these are relatively high
detection rates, reducing the importance of the sodium ion for detecting MSG produced a
small but significant decrease in discrimination accuracy at the lowest concentrations of
each substance.
|
Detection rates of the higher range of SC45647 and MSG were very high, ranging from 88.9 to 98.4% accuracy, indicating this discrimination was also very easy for rats to perform (right panel, Figure 4). The ANOVA analysis comparing discrimination performance of the higher range of SC45647 and MSG uncovered a significant increase in detection rates related to increases in stimulus concentrations [F(4,20) = 10.34, P < 0.001]. Significant effects for the sodium cue condition [F(2,10) = 7.28, P < 0.025] and the interaction between concentration and sodium cue condition [F(8,40) = 4.38, P < 0.001] were found. Simple effects and Bonferroni t-tests indicated that at the lowest concentration of SC45647 and MSG, detection in the amiloride and the amiloride plus NaCl conditions were slightly but significantly lower than the no amiloride condition (P < 0.05).
In addition, a second within subject analysis of variance was used to examine the
data of each experiment for stimulus valence (S+/S–) and concentration (5)
within each sodium cue condition to detect potential effects related to stimulus valence
such as shifts in response strategy or motivational factors. No effect of valence was
detected for SC45647, but a significant effect of valence was detected for both ranges of
saccharin and glucose. Simple effects tests showed that these were due to significantly
lower detection rates of the S– than the S+ only at the lowest concentration
of each substance [all Fs(1,5) 9.90, P < 0.05 ]. In
the sucrose/MSG discrimination experiments, the 10 and 25 mM S+ in all three
sodium cue conditions and the 50 mM S+ in the amiloride and amiloride plus NaCl
conditions was detected significantly more often than the corresponding S–
[all Fs(1,5) 8.94, P < 0.05; Figure
5]. In general, the rats in all
of these experiments tended to miss the S– more than the S+ as the difficulty
of the discrimination increased either because the concentration decreased or because of
the change in sodium cue effect.
|
|
Discussion |
|---|
|
TopAbstractIntroductionMaterial and methodsResultsDiscussionAcknowledgementsReferences |
|---|
Previous experiments with rodents using CTA methods showed strong bi-directional generalization of aversion between each of these sweet substances and MSG mixed with amiloride (Yamamoto et al., 1991
;
Chaudhari et al., 1996;
Stapleton et al., 1999;
Nakashima et al., 2001;
Heyer et al., 2003).
Generalization within a CTA experiment is based on the degree of similarity in taste
qualities shared by each stimulus and the results of these experiments suggest that
glutamate elicits a sweet taste with qualities shared by a range of artificial sweeteners
and natural sugars. However, the findings of the discrimination experiments reported here
suggest that may not be the case. As reported by
Stapleton et al. (2002),
rats found it difficult to distinguish between the tastes of sucrose and MSG when the
sodium taste associated with glutamate was reduced or minimized by amiloride and by NaCl
matching, especially at concentrations <100 mM. In contrast, the tastes of saccharin
and glucose were easily discriminated from MSG by these rats, regardless of the sodium
cue condition. Moreover, their ability to discriminate between the artificial sweetener
SC45647 and MSG was only slightly, although significantly, diminished when the sodium
taste of MSG was reduced. Thus, even though CTA experiments indicate that glutamate
elicits taste qualities that mimic qualities elicited by several sweet substances, the
taste of glutamate is most similar but not identical to the taste sensation elicited by
sucrose.
One might ask whether the ease with which rats distinguished glucose, saccharin and
SC45647 from MSG was due to differences in apparent intensity when the psychophysical
functions of the two substances are dissimilar or if the thresholds are quite different.
If a wide range of concentrations of one substance is tested while holding constant the
concentrations of the second substance, then the perceived intensities of both substances
should overlap at some point and the rat will then be forced to use only qualitative
taste features to make the discrimination. The concentrations of the sweet substances
tested in these experiments were the same as those eliciting strong stimulus
generalization in CTA experiments with MSG (Heyer
et al., 2003). For example, in this study glucose was tested at
concentrations between 100 and 500 mM.
Heyer et al. (2003) found
that cross-generalization of CTA between 100 mM MSG (with amiloride) and glucose was
apparent at 50 mM glucose and increased at higher concentrations of glucose. Similarly,
the concentrations selected for the low concentration range of saccharin readily showed
cross-generalization of CTA with 100 mM MSG. When the rats had little difficulty
discriminating the tastes of these substances and MSG, a higher concentration range was
tested to ensure a sufficient portion of the psychophysical function of each substance
was compared to MSG. Saccharin was not tested at concentrations >3 mM to avoid the
emergence of bitter taste qualities that occur at higher concentrations of saccharin
(Dess, 1993). The moderate difficulty
in discrimination that was seen for the lower range of SC45647 when the
Na+ taste of MSG was reduced may be at least partially related to the
proximity of detection thresholds for SC45647 and MSG. Still, these rats readily
discriminated between SC45647 and MSG in all sodium conditions at the higher
concentrations where CTA readily cross-generalizes (Heyer et al., 2003). Although it is possible that
intensity was the basis for the high degree of accuracy in these discrimination
experiments (except sucrose), the wide range of concentrations tested for each sweet
substance makes this unlikely. Finally, one must at least consider whether non-taste
cues, such as equipment-generated cues, might play some role in these experiments. This
seems unlikely since water-only test days did not reveal any systematic bias in
responding. Also, several steps were taken to minimize potential odor cues. First,
stimulus volumes were small and rats were required to emit a response within a short time
after stimulus delivery to minimize the possibility that retro-oral odor cues might
facilitate discrimination. In addition, fresh solutions were used daily and the delivery
system (e.g. lick spout) was designed to minimize odor cues (Brosvic and Slotnick, 1986). Although these procedures may
not have completely eliminated all non-taste cues, the saliency and reliability of any
residual non-taste cues should have been much less than those of the taste stimuli
serving as discriminative stimuli in these experiments.
Although there is evidence that umami and sweet signals may travel different afferent
pathways (cf.
Sako et al., 2000;
Nelson et al., 2002), it
seems unlikely that these pathways are completely separate. Several investigators have
suggested that glutamate and sweet afferent pathways may interact or converge at some
point (Yamamoto et al.,
1991, 2001;
Chaudhari and Kinnamon, 2001;
Sugimoto et al., 2001;
Heyer et al., 2003). For
example, studies of candidate taste receptors have identified two heterodimeric G-protein
coupled receptors, T1R2/T1R3 for detecting sweet stimuli and T1R1/T1R3 for detecting
umami stimuli and other L-amino acids (Li et al., 2002;
Nelson et al., 2002;
Damak et al., 2003;
Zhao et al., 2003).
Zhao et al. (2003) reported
that genetically eliminating the T1R1 and T1R3 subunits in mice abolished preferences for
umami and artificial sweeteners and most of the response to natural sugars.
Damak et al. (2003)
independently developed a T1R3 knockout mouse and similarly found a loss of response for
artificial sweeteners, but only a moderate loss of response for umami substances and
natural sugars. The findings reported in the present study suggest there may be another
sweet receptor that also responds to glutamate. One possibility is another candidate
G-protein coupled glutamate receptor, a taste-mGluR4 receptor, that mimics the cellular
effects and umami taste perception of MSG (Chaudhari et al., 1996, 2000). Within taste
receptor cells, sucrose increases cAMP while artificial sweeteners increase
IP3, downstream second messengers also affected by MSG stimulation (Lindemann, 1996;
Chaudhari et al., 2000;
Sugimoto et al., 2001;
Abaffy et al., 2003).
Convergence of these signals within the same cell could account for the difficulty in the
sucrose-MSG discrimination.
Nerve recording studies also point to convergence of umami and sweet signaling. For
instance,
Yamamoto et al. (2001) found
that mixtures of MSG and IMP and of L-AP4 (a potent mGluR4 agonist) and IMP elicited
activity in chorda tympani nerve recordings that are suppressed by gurmarin, a sweet
inhibitor. Moreover, mixtures of L-AP4 and several sweet substances produced a synergism
that was not seen with mixtures of MSG and sweet substances. Curiously,
Sako et al. (2003) detected
synergy between L-AP4 and sweet substances (e.g. sucrose, glucose) that was blocked by
gurmarin in fibers that respond only weakly to sucrose. These data, along with the data
reported here, strengthen the possibility that the taste-mGluR4 receptor may have played
a role in these discrimination experiments. Gustatory neurons within the nucleus of the
solitary tract, like fibers of the afferent nerves, respond better to selected taste
stimuli than to others. Some of the NTS neurons that respond best when the rat’s
tongue is bathed with sucrose also respond to MSG and show synergy to mixtures of MSG and
IMP (Adachi and Aoyama, 1991;
Nakamura and Norgren, 1993). Thus,
while afferent signaling of umami stimuli may travel in pathways separate from sweet,
molecular and nerve recording data, along with CTA data, suggest that there is at least
some convergence of afferent signals for sweet and umami taste early in the afferent
system. The discrimination data reported in this study also support this hypothesis.
Although these experiments do not directly address the manner of convergence, the
difficulty these rats had discriminating between sucrose and MSG and the ease with which
these rats discriminated between all other sweet substances and MSG, suggest that the
interaction between sweet and umami may be through a receptor with a high affinity for
glutamate and sucrose, or a point further downstream such as a shared transduction
process within taste receptor cells, or possibly cellular interactions within a taste
bud. Further study with other glutamate agonists, L-amino acids and sweet
stimuli may help elucidate the nature of this convergence.
Although this study was designed to explore the sweet qualities of MSG, the results
may provide some insights into sweet transduction as well. Recent behavioral and
electrophysiological studies with knockout mouse studies support the hypothesis that the
T1R2/T1R3 receptor may be the primary receptor for many artificial sweeteners and an
important but almost certainly not the only receptor for natural sugars (Li et al., 2002;
Damak et al., 2003;
Zhao et al., 2003). In this
study the taste of sucrose was not easily discriminated from MSG by rats yet glucose, in
sharp contrast, was quite readily discriminated from MSG. These results suggest that rats
do not perceive the tastes of these four sweet substances as identical and that at least
two different sweet receptors may be involved in the detection of natural sugars by rats.
Additionally, a previous CTA study found that while sucrose and glucose showed strong
stimulus generalization with MSG, maltose showed only weak cross-generalization to MSG
(Heyer et al., 2003) or
sucrose (Spector and Grill, 1988;
Heyer et al., 2003). These
results indicate that rats perceive maltose as only weakly similar to either MSG or
sucrose at the concentrations used in these studies and suggests that maltose may also
activate receptors different from those that respond to sucrose or MSG. The apparent
differences in taste qualities of these natural sugars relative to MSG, when considered
together with numerous other studies, suggest that rats have at least one sweet receptor
that can detect some artificial sweeteners and multiple receptors capable of detecting
carbohydrates (e.g.
Lawless and Stevens, 1983;
Dubois, 1997;
Ninomiya et al., 1999). One
possibility, suggested by Sclafani and others (Nissenbaum and Sclafani, 1987;
Sclafani et al., 1987;
Sako et al., 1994), is that
in addition to a receptor for sucrose, there are ‘polysaccharide’ receptors.
Another possibility, suggested by the differential effects of gurmarin on synergistic
responses induced by glutamate agonists and either IMP or natural sugars in the chorda
tympani nerve, is that there may be ‘gurmarin-sensitive’ and
‘gurmarin-insensitive’ sweet receptors (Ninomiya et al., 1999;
Sako and Yamamoto, 1999;
Sako et al., 2003). Although
the results of the present study do not elucidate the number or the specific nature of
sweet receptors in the rat, they clearly support the notion that there are multiple
receptors for detecting sweet stimuli.
In summary, the behavioral data obtained in this study suggest that sweet and umami afferent signaling may converge through a common taste receptor with a high affinity for glutamate and sucrose, a downstream transduction mechanism, or cell–cell interactions. These data also support the hypothesis that artificial sweeteners and natural sugars are detected by multiple sweet receptors.
|
Acknowledgements |
|---|
|
TopAbstractIntroductionMaterial and methodsResultsDiscussionAcknowledgementsReferences |
|---|
This work was supported by an NSF grant (9982913) awarded to E.R.D. Some of these data were presented at the Society for Neuroscience meetings in New Orleans, LA, in 2003 and at the Association for Chemoreception Sciences meetings in Sarasota, FL, in 2003.
|
References |
|---|
|
TopAbstractIntroductionMaterial and methodsResultsDiscussionAcknowledgementsReferences |
|---|
Abaffy, T., Trubey, K.R. and Chaudhari, N. (2003) Adenylyl cyclase expression and modulation of cAMP in rat taste cells. Am. J. Physiol. Cell Physiol., 284, C1420–C1428.
Adachi, A. and Aoyama, M. (1991) Neuronal responses of the nucleus tractus solitarius to oral stimulation with umami substances. Physiol. Behav., 49, 935–941.[CrossRef][Medline]
Bellisle, F. (1999) Glutamate and the UMAMI taste: sensory, metabolic, nutritional and behavioural considerations. A review of the literature published in the last 10 years. Appetite, 26, 267–276.[CrossRef]
Brosvic, G.M. and Slotnick, B.M. (1986) Absolute and intensity-difference taste thresholds in the rat: evaluation of an automated multi-channel gustometer. Physiol. Behav., 38, 711–717.[CrossRef][Medline]
Chaudhari, N. and Kinnamon, S.C. (2001) Molecular basis of the sweet tooth? Lancet, 358, 2101–2102.[CrossRef][ISI][Medline]
Chaudhari, N., Yang, H., Lamp, C., Delay, E., Cartford, C., Than, T. and Roper, S. (1996) The taste of monosodium glutamate: membrane receptors in taste buds. J. Neurosci., 16, 3817–3826.
Chaudhari, N., Landin, A.M. and Roper, S.D. (2000) A metabotropic glutamate receptor variant functions as a taste receptor. Nat. Neurosci., 3, 113–119.[CrossRef][ISI][Medline]
Damak, S., Rong, M., Yasumatsu, K., Kokrashvili, Z., Varadarajan, V., Zou, S., Jiang, P., Ninomiya, Y. and Margolskee, R.F. (2003) Detection of sweet and umami taste in the absence of taste receptor T1r3. Science, 301,. 850–853.
Delay, E.R., Beaver, A.J., Wagner, K.A., Stapleton, J.R., Harbaugh, J.O., Catron, K.D. and Roper, S.D. (2000) Taste preference synergy between glutamate receptor agonists and inosine monophosphate in rats. Chem. Senses, 25, 507–515.
Delay, E.R., Sewczak, G.M., Stapleton, J.R. and Roper, S.D. (2004) Glutamate taste: discrimination between the tastes of glutamate agonists and monosodium glutamate in rats. Chem. Senses, 29, 291–299.
Dess, N.K. (1993) Saccharin’s aversive taste in rats: evidence and implications. Neurosci. Biobehav. Rev., 17, 359–372.[CrossRef][ISI][Medline]
Dubois, G.E. (1997) New insights on the coding of the sweet taste message in chemical structure. In Salvadori, G. (ed.), Olfaction and Taste: A Century for the Senses. Allured, Carol Stream, IL, pp. 32–95.
Geran, L.C. and Spector, A.C. (2000) Amiloride increases sodium chloride taste detection threshold in rats. Behav. Neurosci., 114, 623–634.[CrossRef][ISI][Medline]
Heyer, B.R., Taylor-Burds, C.C., Tran, L.H. and Delay, E.R. (2003) Monosodium glutamate and sweet taste: generalization of conditioned taste aversion between glutamate and sweet stimuli in rats. Chem. Senses, 28, 631–641.
Howell, D. (1997) Statistical Methods for Psychology, 4th edn. Belmont, CA: Duxbury Press.
Lawless, H.T. and Stevens, D.A. (1983) Cross adaptation of sucrose and intensive sweeteners. Chem. Senses, 7, 309–315.
Li, X., Staszewski, L., Xu, H., Durick, K., Zoller, M. and Adler, E. (2002) Human receptors for sweet and umami taste. Proc. Natl Acad. Sci. USA, 99, 4692–4696.
Lindemann, B. (1996) Taste reception. Physiol. Rev., 76, 719–766.
Maga, J.A. (1983) Flavor potentiators. CRC Crit. Rev. Food Sci. Nutr., 18, 231–312.
Markison, S. and Spector, A.C. (1995) Amiloride is an ineffective conditioned stimulus in taste aversion learning. Chem. Senses, 20, 559–563.
Nakamura, K. and Norgren, R. (1993) Taste responses of neurons in the nucleus of the solitary tract of awake rats: an extended stimulus array. J. Neurophysiol., 70, 879–891.
Nakashima, K., Katsukawa, H., Sasamoto, K. and Ninomiya, Y. (2001) Behavioral taste similarities and differences among monosodium L-glutamate and glutamate receptor agonists in C57BL mice. J. Nutr. Sci. Vitamin., 47, 161–166.
Nelson, G., Chandrashekar, J., Hoon, M.A., Feng, L., Zhao, G., Ryba, N.J.P. and Zuker, C.S. (2002) An amino-acid taste receptor. Nature, 416, 199–202.[CrossRef][Medline]
Ninomiya, Y., Imoto, T. and Sugimura, T. (1999) Sweet taste responses of mouse chorda tympani neurons: existence of gurmarin-sensitive and -insensitive receptor components. J. Neurophysiol., 81, 3087–3091.
Nissenbaum, J.W. and Sclafani, A. (1987) Qualitative differences in polysaccharide and sugar tastes in the rat: a two-carbohydrate taste model. Neurosci. Biobehav. Rev., 11, 187–196.[CrossRef][ISI][Medline]
Nofre, C., Tinti, J.-M. and Chatzopoulos, F.O. (1990) US Patent 4,921,939 (1 May).
Sako, N. and Yamamoto, T. (1999) Analyses of taste nerve responses with special reference to possible receptor mechanisms of umami taste in the rat. Neurosci. Lett., 261, 109–112.[CrossRef][ISI][Medline]
Sako, N., Shimura, T., Komure, M., Mochizuki, R., Matsuo, R. and Yamamoto, T. (1994) Differences in taste responses to polycose and common sugars in the rat as revealed by behavioral and electrophysiological studies. Physiol. Behav., 56, 741–745.[CrossRef][Medline]
Sako, N., Harada, S. and Yamamoto, T. (2000) Gustatory information of umami substances in three major taste nerves. Physiol. Behav., 71, 193–198.[CrossRef][Medline]
Sako, N., Tokita, K., Sugimura, T. and Yamamoto, T. (2003) Synergistic responses of the chorda tympani to mixtures of umami and sweet substances in rats. Chem. Senses, 28, 261–266.
Sclafani, A., Hertwig, H., Vigorito, M., Sloan, H. and Kerzner, B. (1987) influence of saccharide length on polysaccharide appetite in the rat. Neurosci. Biobehav. Rev., 11, 197–200.[CrossRef][ISI][Medline]
Spector, A.C. and Grill, H.J. (1988) Differences in the taste quality of maltose and sucrose in rats: issues involving the generalization of conditioned taste aversions. Chem. Senses, 13, 95–113.
Stapleton, J.R., Roper, S.D. and Delay, E.R. (1999) The taste of monosodium glutamate (MSG), L-aspartic acid and N-methyl-D aspartate (NMDA) in rats: are NMDA receptors involved in MSG taste? Chem. Senses, 24, 449–457.
Stapleton, J.R., Luellig, M., Roper, S.D. and Delay, E.R. (2002) Discrimination between the tastes of sucrose and monosodium glutamate in rats. Chem. Senses, 27, 375–382.
Sugimoto, K., Nakashima, K., Yasumatsu, K., Sasamoto, K. and Ninomiya, Y. (2001) Glutamate transduction mechanism in mouse taste cells. Sensory Neuron, 3, 139–154.[CrossRef]
Yamaguchi, S. (1967) The synergistic taste effect of monosodium glutamate and disodium 5' inosinate. J. Food Sci., 32, 473–478.[CrossRef]
Yamamoto, T., Matsuo, R., Fujimoto, Y., Fukunaga, I., Miyasaka, A. and Imoto, T. (1991) Electrophysiological and behavioral studies on the taste of umami substances in the rat. Physiol. Behav., 49, 919–925.[CrossRef][Medline]
Yamamoto, T., Sako, N. and Tokita, K. (2001) Characteristics of umami responses in rats. Sensory Neuron, 3, 185–204.[CrossRef]
Zhao, G.Q., Zhang, Y., Hoon, M.A., Chandrashekar, J., Erienbach, I., Ryba, N.J.P. and Zuker, C.S. (2003) The receptors for mammalian sweet and umami taste. Cell, 115, 255–266.[CrossRef][ISI][Medline]
Accepted September 1, 2004
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  J. M. Breza, K. S. Curtis, and R. J. Contreras Monosodium Glutamate but not Linoleic Acid Differentially Activates Gustatory Neurons in the Rat Geniculate Ganglion Chem Senses, November 1, 2007; 32(9): 833 - 846. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. D. Dotson and A. C. Spector Behavioral Discrimination between Sucrose and Other Natural Sweeteners in Mice: Implications for the Neural Coding of T1R Ligands J. Neurosci., October 17, 2007; 27(42): 11242 - 11253. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
L. M. Stone, J. Barrows, T. E. Finger, and S. C. Kinnamon Expression of T1Rs and Gustducin in Palatal Taste Buds of Mice Chem Senses, March 1, 2007; 32(3): 255 - 262. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
T. Wifall, T. Faes, C. Taylor-Burds, J. Mitzelfelt, and E. Delay An Analysis of 5'-Inosine and 5'-Guanosine Monophosphate Taste in Rats Chem Senses, February 1, 2007; 32(2): 161 - 172. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. H. Lemon and D. V. Smith Influence of response variability on the coding performance of central gustatory neurons. J. Neurosci., July 12, 2006; 26(28): 7433 - 7443. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
E.R. Delay, N.P. Hernandez, K. Bromley, and R.F. Margolskee Sucrose and Monosodium Glutamate Taste Thresholds and Discrimination Ability of T1R3 Knockout Mice Chem Senses, May 1, 2006; 31(4): 351 - 357. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. C. Taylor-Burds, A. M. Westburg, T. C. Wifall, and E. R. Delay Behavioral Comparisons of the Tastes of L-Alanine and Monosodium Glutamate in Rats Chem Senses, November 1, 2004; 29(9): 807 - 814. [Abstract] [Full Text] [PDF]
|
|
| |||||||||||||||||||||||||||||||||||||