The Howard Florey Institute, University of Melbourne, 1 The Department of Optometry and Vision Sciences, The University of Melbourne, Parkville, 3010, Victoria, Australia
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Abstract |
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Introduction |
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We have addressed this issue by combining postembedding silver-intensified immunogold labelling with digital image analysis. The sensitivity of this technique enables detection of cellular amino acid concentrations across a wide range, and has been used to detect glutamate levels as low as 50 µM in individual neurons (Marc et al., 1990, 1995
). In addition, the technique enables direct comparisons with known amino acid concentrations in goldfish retina (Marc et al., 1995
). Given the general importance of glutamate in cortical tissue, we have used this quantitative technique to assess whether the presence of glutamate accounts for all cellular space in the cortex. We were also interested in distinguishing cortical cellular subpopulations based upon varying levels of glutamate content.
Glutamate is known to be closely associated with other amino acids such as GABA, aspartate and glutamine via a complex biochemical web (Ereciñska and Silver, 1990; Kalloniatis and Tomisich, 1999
). Accordingly, it is of interest to identify colocalization patterns for aspartate, glutamine or GABA immunoreactivity with glutamate, and to further identify neuronal subpopulations based upon immunocytochemical overlap. For example, glutamate might coexist with another amino acid in a neuron, but two neurons containing a pair of amino acids may be further subclassified by quantitative variations for one or both molecules.
The cortex has been reported to be modular in composition, containing iterative columns of neurons with uniform cell densities across different cortical areas and species (Rockel et al., 1980). In many areas of the cortex, this uniformity appears to be reflected in neurons that contain GABA (Hendry et al., 1987
). If GABAergic neurons can be further partitioned into chemical subsets on the basis of neurotransmitter level or colocalization patterns with glutamate, it will be of interest to see if phenotypic uniformity is maintained between different cortical areas.
We have therefore compared amino acid immunoreactivity in two cortical regions: primary somatosensory (area 3) and secondary motor (area 6) areas. These two cortical regions were chosen because they have contrasting functions, different connectivity patterns and therefore possible metabolic differences. The secondary motor cortex is located on the superior and medial aspects of the hemisphere and is involved in the execution of complex movements. The laterally positioned primary somatosensory region (area 3 or SI in mouse) is a region sensitive to external stimuli, which in rodents contains the barrel cortex, a point-to-point mapping of individual vibrissae (Woolsey et al., 1975; Bear et al., 1996
).
Our results showed that virtually every cortical cell examined possessed some level of glutamate. The distribution of neurons immunoreactive (IR) for glutamate, aspartate, glutamine or GABA was without exception univariate and statistically followed a Gaussian pattern. Surprisingly, glutamate can coexist at high or low levels within GABAergic neurons, raising the prospect of dual transmitter usage within individual neurons. Alternatively, inhibitory neurons can contain high metabolic levels of glutamate. Although the level of immunoreactivity did not appear to differ significantly between cortical areas 3 and 6, there were significant differences in the number of glutamate and GABA-IR cells between cortical layers.
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Materials and Methods |
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Brains were collected from a total of 20 mice (C57BL/6) of 4270 days of age. From this group, four samples were selected for study. All animals were anaesthetized by i.p. injection of Avertin (0.015 ml/g body wt) and fixed for 10 min by intracardial perfusion with 4% paraformaldehyde, 2% glutaraldehyde in 0.1 M Sorensen's phosphate buffer (pH 7.4) containing 2 mM MgCl2 and 5 mM EGTA. Cortices were removed and coronal sections (200 µm thick) obtained using a custom-made grid slicer and post-fixed by immersion for 72 h. From the cortical slices, blocks of tissue (0.5 x 0.9 mm) were dissected from cortical areas 6 and area 3 for plastic embedding (Fig. 1).
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Tissue blocks containing cortical sections were dehydrated in graded alcohols, cleared in acetone and embedded in EPON resin (Pelco, Redding, CA). To enable a single cortical neuron to be simultaneously interrogated by antibodies directed against different amino acid antigens, serial sections (0.25 µm) were cut (ReichertJung Ultracut S) and each section incubated with a different antibody. In order to estimate glutamate concentration in cortical neurons, goldfish retinal ganglion cells were used as our standard (Marc et al., 1995). Archival tissue blocks (containing goldfish retina) were sectioned and amino acid immunocytochemistry was carried out simultaneously with cortical samples.
Sections were incubated on Teflon-coated slides (Cel-line, NJ) for postembedding immunocytochemistry (Kalloniatis and Fletcher, 1993; Kalloniatis et al., 1994
; Marc et al., 1995
). Briefly, sections were etched in a 1:5 solution of sodium ethoxide/ethanol and rinsed through graded methanol concentrations followed by 10 min in a solution of 1% sodium borohydride in 0.1 M phosphate buffer. Non-specific binding was blocked with 5% goat serum, 0.8% BSA in buffered saline for 3060 min. Sections were incubated with the primary antibody for 6 h. Rabbit polyclonal antibodies (Marc et al., 1990
, 1995
) (kindly donated by Dr Robert Marc, University of Utah) were diluted in 1% goat serum in buffered saline at the following working concentrations: anti-glutamate (1:4500), anti-GABA (1:4500), anti-glutamine (1:800) and anti-aspartate (1:100). Sections were rinsed in 1% buffered saline for 30 min before addition of goat anti-rabbit secondary antibody (coated with 1 nm gold; Immunodiagnostics, Australia) at 1:100 dilution. For all sections, silver intensification was carried out using a solution of 200 mM silver nitrate containing 38 mM hydroquinone in 200 mM citrate buffer for ~8 min (Moeremans et al., 1984
).
Image Analysis
Cellular intensity profiles were viewed on a Zeiss Axiophot light microscope and captured using a Kodak Megaplus 1.4 camera equipped with NIH Image software (Bethesda, MD). To obtain relative estimates of cellular amino acid content, data were collected in a single immunocytochemical run with constant light settings and fixed camera gain. Images were captured in sequence from the pial surface to the white matter with no overlap; on average, a single section provided 36 images. Single low-power images for laminar analysis (Fig. 6) and colocalization scatterplots (Fig. 5
) were captured via a Zeiss Axioplan microscope attached to a SPOT Cooled Color Digital camera, using SPOT software (version 2.1).
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Amino acid labelling patterns can be assessed qualitatively by viewing the registered images in an RGB format (ie. an image where the labelling patterns of three amino acids are shown in red, green and blue). In the present study the paired amino acid data is depicted as doublet images (e.g. glutamate: red; GABA: green). Cells in these images that contain predominantly glutamate have a red hue, those that contain higher levels of GABA a green hue, and those that contain similar levels of both glutamate and GABA, a yellow hue. These data were analysed quantitatively and bivariate scatterplots representing paired amino acid patterns of glutamate/GABA, glutamate/aspartate and glutamate/glutamine were generated using EASI/PACE software. Regression analysis (Microsoft Excel) was conducted to establish the correlation pattern for each pair of amino acids.
Cellular Intensity Profiles
Our objective was to determine the immunoreactivity patterns for glutamate, GABA, glutamine and aspartate within two different cortical regions. All neurons immunoreactive for a specified antigen from cortical area 3 (primary somatosensory, n = 4) and area 6 (secondary motor, n = 4) were sampled and assigned a PV using Scion Image software. Following individual assessment, these datasets were pooled. In the case of GABA, very few cells were immunopositive and therefore only those with labeling intensities clearly above background were selected for quantification. To obtain cellular PV intensities, cell perimeters were traced and pixel values within the enclosed area were averaged. In certain cases (e.g. low intracellular glutamate), the soma PV was lower than the surrounding neuropil (although still above background value) due to increased immunoreactivity of surrounding neuronal processes. The background PV was determined by sampling cellular signals from a parallel batch of sections in the immunocytochemical run for which the primary antibodies had been omitted. For each amino acid, an equivalent area of cortical tissue from areas 3 and 6 was analysed. The PV analysis yielded two kinds of information: (i) the relative levels of amino acid present in different cells (expressed as PV), and (ii) the numerical distribution of cells with different amino acid contents.
Cortical Laminar Analysis
To ascertain whether cellular amino acid content (for glutamate and GABA) has layer-specific variation, all immunoreactive cells found within a 500 x 900 µm area spanning layers IVI were analysed. Following low-power image capture, a background signal corresponding to the PV of the neuropil was obtained using Image-Pro Plus software. From this value, a threshold was set in order to detect cells with immunoreactivity higher than neuropil throughout the section. The entire cortical depth was divided into 10% bins (100% being equal to the maximum cortical depth) using a grid overlay. The number of immunoreactive cells found in each cortical layer was scored for both areas 3 and 6. To ascertain whether antigen content varied with cortical depth, the mean PVs for all glutamate-IR cells analysed were plotted against percent cortical depth. Because the distribution of the small population of GABA-IR cells with high PVs (i.e. >140 PV for this data set) was of interest, the median PV and raw data for the GABA-IR population was also plotted against cortical depth. This laminar analysis allows characterization of immunoreactive cells in terms of their prevalence and amino acid content across different cortical layers.
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Results |
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The specificity of the antibodies for the amino acids has been characterized using dot immunoassays (Marc et al., 1990, 1995
). These studies have demonstrated, using the postembedding technique, that the PV is proportional to the log of cellular antigen concentration effectively just over a two log unit range. The postembedding technique on semithin specimens is highly suited to providing continuous data across a large useable range (Marc et al., 1990
, 1995
, 1998
; Kalloniatis et al., 1996
). This has implications for extending the power of immunocytochemical analysis from the qualitative to the quantitative realm of assessment.
Qualitative Analysis
There were no overt differences in staining intensity or overall distribution of immunoreactive cells for all four amino acids in area 3 and area 6. This was true for each of the animals examined, with both areas separately considered. For brevity, the patterns of immunoreactivity for both areas were considered together.
Glutamate-IR somata were found in all cortical layers, although not uniformly distributed (Fig. 2A). Labelled cells in layers V and VI had larger cell diameters compared to cells in layers II and III. Every cell showed immunoreactivity at a signal level above the background of control sections (see below). Strongly immunoreactive cells in the upper layers tended to be small. In deeper layers, immunoreactive cells were pyramidal in shape with a large-diameter process emerging from the apex (Fig. 2B
). This process, perhaps the apical dendrite of pyramidal neurons, showed lower levels of immunoreactivity compared to darker- staining regions of the perikaryon. The increased nuclear staining for antigen, perhaps a feature of semithin immunocytochemistry, has also been reported by others (Ottersen and Storm-Mathisen, 1984
; Marc et al., 1995
). Other large cells but with lower immunoreactivity levels were also seen, although many of these did not have associated processes (Fig. 2B
, asterisk). Significant glutamate labelling was also seen in the neuropil which was infiltrated by a fine mesh of immunoreactive processes. Some ascending dendrites branching at the layer I/II interface showed punctate staining for glutamate (Fig. 2C
). This dendritic network gave layer I a strong overall staining for glutamate, although the cells in this layer had low levels of the antigen.
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The general pattern of glutamine immunoreactivity was quite similar to aspartate in layer distribution and frequency (Fig. 2G). Both large and small diameter cells were labelled with no upper versus lower layer differences. In addition, cells in lower layers often showed associated staining of apical dendrites (Fig. 2H
). Unlike aspartate labelling, the distribution of glutamine in large pyramidal cells was non-uniform, with stronger staining over the nuclear region and reduced labelling in the cytoplasm (Fig. 2H
). The neuropil showed punctate staining, although not as intense as aspartate. At layer I, glutamine-positive cell processes were also seen to branch into terminal processes (Fig. 2I
).
GABA-IR cells were diffusely distributed throughout the cortical depth. Unlike the other amino acids, there was no predominance of larger cells in the deeper layers (Fig. 2J). In addition, they did not possess pyramidal morphologies and were not associated with thick cell processes (Fig. 2K
). Instead, GABA-positive cells presented in a variety of soma shapes; some were round while others were bipolar or possessed horizontal processes (Fig. 2L
). While strongly immunoreactive cells clearly stood out, other neighbouring cells were also immunoreactive for GABA, although only weakly (Fig. 2K
, see also Fig. 3
). These weakly immunoreactive cells include many different cell shapes and sizes. Still other cells were clearly non-immunoreactive. Round immunoreactive cells displayed multipolar processes radiating at many points from their somas (Fig. 2L
). Compared with other amino acids, GABA-IR somas appeared to be smaller in size. Occasionally, processes with punctate staining were found to encircle cells that clearly lacked GABA (Fig. 2L
). In layer I, few GABA-IR cells were found.
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By combining the silver-intensified immunogold procedure with image analysis, we assigned a quantitative value for every cell in the section. For this exercise, the data was mathematically inverted using a logical NOT operation so that increasing immunoreactivity was scaled with increasing PV (scale 0255 representing low to high levels of immunoreactivity). Figure 3 demonstrates the range of PV obtained for GABA. The majority of cells in the section had a PV of 50 or less; these represent negative GABA staining and their cellular profiles were virtually indistinguishable from the adjacent neuropil. Other GABA-IR cells displayed varying levels of PV intensity, ranging from 70 to 170 (about one log unit range of antigen concentration), and their somas were clearly defined by the high level of immunoreactivity. There appeared to be a graded but inverse relationship between GABA levels and cellular frequency, with lower numbers of strongly GABA-IR cells (PV ~ 170) compared with a larger cellular population containing low GABA immunoreactivity.
Distribution Profiles
So far, almost every cell (98.9%) analysed appeared to contain some level of glutamate that was above the background of control sections (without primary antibody). We sought to ascertain the distribution profile of cells with different glutamate levels. For both cortical areas, the distribution of glutamate-IR cells appeared to fall within a Gaussian distribution (average r2 = 0.97, n = 8 brain samples; Fig. 4A). There was no statistical difference (t-test: paired two sample for means; F-test: two- sample for variances) in the distribution profiles for glutamate positive cells in area 3 compared to area 6. For both areas, the mean ± SD PV of the neuropil was 83 ± 16 (arrow in Fig. 4A
), whereas the signal intensity of intracellular glutamate ranged from 40 to 180 with a peak at 90. From the above data we calculated that 49.9% of cells in both areas of cortex have higher intracellular levels of glutamate compared to the neuropil. However, many cells have low levels of glutamate (i.e. below the PV seen in the neuropil), which are still above the background level of the control. The PV of control cells was 40 ± 3 (n = 24), indicating that half (50.1%) of the glutamate-IR cell population has a PV lower than that of the neuropil. For example, a glutamate-IR cell with low staining intensity (but with a PV above background) is illustrated in Figure 2B
(marked with an asterisk).
The distribution profiles for aspartate showed no significant differences (t-test: paired two sample for means; F-test: two-sample for variances) when comparing area 3 with area 6 although there was a greater number of cells with higher aspartate levels in the area 3 pool (Fig. 4B). The range of PV for aspartate was 40160, with the peak at ~90 for both cortical areas. The Gaussian distribution for aspartate in both cortical areas had an average r2 value of 0.98. Similarly, glutamine immunoreactivity appeared to be comparable for cells in both area 3 and area 6, with no statistical differences detected in the distribution profiles (Fig. 4C
). Overall, the level of immunoreactivity for both areas was lower compared to aspartate, with a range of 30130, with a peak at ~61. Again, there was a subpopulation of cells in area 3 that appeared to have higher levels of glutamine. The average r2 value for glutamine Gaussian distribution was 0.98. Despite the perceptible shift of the area 6 profile to the left, there were no statistically detectable differences between the two cortical areas.
GABA-IR cells also conformed to a normal distribution following regression analysis (average r2 = 0.93) with a peak level of 108 and range 60170 (Fig. 4D). There was no statistically detectable difference (t-test: paired two sample for means; F-test: two-sample for variances) when comparing the distribution profiles of GABA cells in the two cortical areas.
Colocalization Patterns
Qualitative observations clearly indicated that almost every cell examined expressed some level of glutamate, although there was a range in the level of the immunoreactivity reflecting cellular diversity at the biochemical level. Bivariate image analysis was conducted to unmask the correlation patterns between amino acid pairs and determine whether glutamate-IR cells fell into subpopulations that are distinguishable by colocalizing levels of aspartate, glutamine or GABA. The qualitative amino acid RG mapping (RHS panels in Fig. 5
) illustrates the hue shifts for different cells with different colocalization patterns. Cells immunoreactive for both glutamate and aspartate mostly possessed yellow hues, reflecting overlap of similar PV (Fig. 5B
). In contrast, glutamate-IR cells were seen to express glutamine at comparatively lower levels (Fig. 5C
), suggesting that this subpopulation was fairly uniform for glutamine levels across a wide range of glutamate. Cellular depiction of this correlation indicated predominantly red hues, which reflected higher glutamate levels (red channel) on a fairly constant background of low glutamine (green channel; Fig. 5D
). Finally, most glutamate positive cells did not appear to contain GABA (predominantly red hues), except for a minority population where colocalization patterns indicated cells with yellow hues (containing both glutamate and GABA) and some predominantly green hues (containing GABA with little glutamate; Fig. 5F
). In other words, strong GABA presence was associated with either weak (arrow on green cell, Fig. 5F
) or strong (arrow on yellow cell, Fig. 5F
) glutamate levels. This qualitative analysis indicates a wide range of possibilities when each amino acid is registered over glutamate. For example, co-registration for glutamate and aspartate indicated that two cells (encircled cells 1 and 2, Fig. 5B
) could have similar quantitative overlap for these two amino acids. However, the same two cells were found to differ significantly when GABA was registered over glutamate (cells 1 and 2, Fig. 5F
), with higher GABA content in cell 2 (green for GABA) compared to cell 1 (red for glutamate).
The bivariate scatterplots provide a quantitative assessment of the amino acid correlation patterns (Fig. 5). A scatterplot of cells immunoreactive for both glutamate and aspartate appeared to fall into a linear pattern, suggesting that this subpopulation of cortical cells expressed both amino acids at essentially similar levels. Regression analysis showed a significant correlation between cellular glutamate and aspartate content (P < 0.001, r2 value = 0.14). The correlation between these two amino acids identified a biochemical link translatable into a simple rule: cortical cells generally express similar levels of glutamate and aspartate. The correlation was weaker for glutamate and glutamine (Fig. 5C
), with the scatterplot and subsequent regression analysis indicating that, on average, cells contain higher levels of glutamate when compared to glutamine (regression analysis showed no significant correlation between glutamate and glutamine; P > 0.05, r2 value = 0.002). Finally, the majority of glutamate-IR cells did not show GABA signals above background (Fig. 5E
). However, in the few cases where this occurred, the double-immunoreactive cells showed colocalizing signals across a wide range of intensities (high to low levels of glutamate and GABA; Fig. 5E
). For strongly GABA-IR cells (PV > 95), the concentration of glutamate within these GABAergic cells varied by ~1.2 log units (i.e. a factor of ~x16). Regression analysis showed no significant correlation between glutamate and GABA content when a subpopulation of GABA-positive cells (PV > 95 for GABA immunoreactivity) was examined. However, when all glutamate versus GABA-IR cells were analysed, there was a negative correlation (slope = 0.22, P = 0.015). This correlation implied that cells with low GABA levels generally have high glutamate content although there is a large variance in the data (demonstrated by a poor r2 value; r2 = 0.04).
Laminar Analysis
As for cellular intensity profiles, laminar analyses for glutamate and GABA immunocytochemistry in areas 3 and 6 were carried out using four different brain samples. Glutamate-positive cells with labelling intensities above neuropil PV were more numerous with increasing cortical depth (Fig. 6A). The number of glutamate-positive cells increased from the low level in layer I to a plateau in mid-cortical layers before rising in layers V and VI. As expected, the number of glutamate-IR cells in layer I (5% cortical depth) was found to be significantly lower than at 15, 55, 75, 85 and 95% cortical depth (±2 SEM). However, this increase in cell number with cortical depth may partly reflect sampling bias for cell size (i.e. larger cells are included in thin cortical slices at a higher incidence compared to smaller cells) and therefore awaits clarification using stereological tools. Nonetheless, a comparison (multiple paired t-tests) of area 3 and 6 showed a common distribution trend except for a possible higher number of cells found in area 6 at the 25% cortical depth (i.e. in the region of layer II/III). To compare PV variation across different cortical layers, the mean ± SEM was obtained from the above cell populations. This analysis revealed virtually no difference in cellular glutamate content with increasing cortical depth, for both area 3 and area 6 (Fig. 6B
). Comparison of cellular glutamate levels between the two cortical areas also did not yield statistically different trends (multiple paired t-tests).
A similar analysis of GABA-labelled tissue revealed a different trend compared to glutamate-IR cells (Fig. 6C). There was a decrease in GABA-IR cells at ~25% cortical depth (i.e. in the region of layer II/III). The number of cells appeared to increase between 35 and 45% depth before dropping to the lowest value at 5575% cortical depth (i.e. in the region of layer V). However, statistical analysis showed no significant difference in cell number throughout the cortical depth (±2 SEM). Both areas 3 and 6 showed similar trends, and comparison of the two cortical areas (multiple paired t-tests) showed no significant difference except at 95% cortical depth where GABA-IR cells were more numerous in area 6 compared with area 3 (Fig. 6C
). When PV data for GABA-IR cells (mean ± SEM) was examined, no significant difference between cortical areas or layers was encountered (data not shown). Neurons labelled for GABA in each layer displayed an almost similar range, with the majority of neurons in the mid to low GABA level, while a small number of neurons showed intense GABA labelling (Fig. 6D,E
). In other words, even though individual GABA content was seen to be highly variable among neurons present within a particular laminar location, there was a high degree of uniformity in the pattern distribution between areas 3 and 6, with a near linear median value across cortical layers in both regions (Fig. 6D,E
).
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Discussion |
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Glutamate immunoreactivity was present in almost all cortical cells (98.9%) examined. A wide range of glutamate content was indicated by PV; however, even cells with low PV (i.e. PV ~ 40) were shown to have glutamate signal above background. Parallel immunocytochemical runs using goldfish retina (results not shown), where PV has previously been scaled to known glutamate concentrations (Marc et al., 1995), indicate that the lowest PV exceeded 2 mM of glutamate. Strong glutamate immunoreactivity was observed in larger neurons of layers V and VI (Fig. 2A,B
). As these cortical layers are known to contain the cell bodies of excitatory projection neurons, these results may suggest a correlation between cells displaying high glutamate levels and those expected to use glutamate as a neurotransmitter. However, statistical analysis (±2 SEM) showed the number of layer I cells (at 5% cortical depth) to be significantly lower compared with 15, 55, 75, 85 and 95% cortical depth (Fig. 6A
), notwithstanding a possible sampling bias without stereological data. In addition, there appeared to be no difference when comparing different cortical regions (area 3 versus area 6) in either the overall cellular distribution pattern or intracellular glutamate variation. This may suggest similar patterns of glutamate usage for both metabolic and neurotransmitter needs despite cytoarchitectonic variation.
The finding that glutamate was present in almost every cortical cell contrasts with previous studies employing immunostaining for either glutamate or PAG, an enzyme involved in glutamate synthesis. In many areas of the mammalian cortex, glutamate has been reported in all pyramidal neurons found across all layers (Ottersen and Storm-Mathisen, 1984; Conti et al., 1987b
; Dori et al., 1992
; Carder and Hendry, 1994
). In those studies, however, not all cells were immunoreactive for glutamate. One explanation is that at metabolic levels (as opposed to neurotransmitter levels), glutamate pools are too low to be revealed by conventional immunostaining. In the present work, the sensitivity of the quantitative immunogold technique enables detection of low glutamate levels (i.e. in the 50 µM range), which are less than the lowest levels of glutamate encountered in our cortical cells.
Using the goldfish ganglion cells as our standard, we calculated a range of 2.317.7 mM glutamate concentration in cortical cells with a mean cellular concentration of 8.1 mM and mean neuropil concentration of 8.9 mM. These concentrations are comparable to values established from previous cortical glutamate analysis using high-performance liquid chromatography in rat cortex, where mean cortical glutamate concentration is estimated to be ~12 mM (Balcom et al., 1976; Ereciñska et al., 1984
; Ereciñska and Silver, 1990
). Since cellular electrophysiological properties were not examined in this study we cannot assume excitatory activity from any particular subset of these neurons. However, retinal ganglion cells, which are known to use glutamate as their excitatory neurotransmitter, contain ~10 mM when assessed via similar methods (Marc et al., 1995
).
The distribution profile of aspartate-positive cells closely resembles glutamate. Quantitative analysis showed a similar distribution pattern in both areas 3 and 6, suggesting the absence of area-specific features for aspartate utilization. Colocalization analysis with glutamate suggests there are no neurons purely immunoreactive for aspartate, raising the possibility that aspartate and glutamate function as metabolic precursors for one another. This is consistent with the predominant role of AAT in brain, where activity is known to be as much as 10-fold higher than other glutamate-metabolizing enzymes (Hertz, 1979; Ereciñska and Silver, 1990
; Ross et al., 1995
). Perhaps the role of aspartate in these neurons is less related to neurotransmission than energy-related functions (such as the malateaspartate shuttle in cytosolic-mitochondrial transport).
Our finding that all aspartate-positive neurons also contain glutamate demonstrates the strength of semithin quantitative immunocytochemistry where each and every cell can be interrogated for both amino acid antigens. A comparable approach, using stereological alignment, also found that virtually 100% of aspartate-positive cells in the amygdala contain glutamate (McDonald, 1996). In contrast, others have reported distinct populations of aspartate- or glutamate-IR neurons in the cortex, although such studies were conducted on consecutive paraffin sections or even different tissue samples, rendering it difficult to study the issue of amino acid coexistence (Conti et al., 1987a
; Giuffrida and Rustioni, 1989
; Dori et al., 1992
).
A neurotransmitter role for aspartate has previously been hypothesized on the basis that many neurons in the CNS are immunoreactive for this amino acid alone (Conti et al., 1987a; Wiklund et al., 1982
). In numerical terms, it has been reported that there are as many aspartate-only neurons compared with glutamate-positive neurons in the cortex (Giuffrida and Rustioni, 1989
). However, neurons containing both amino acids have been reported by others (Conti et al., 1987a
), although our data go further to suggest that there are no purely aspartate- containing neurons. It has also been reported that aspartate is not taken up by brain synaptic vesicles (Maycox et al., 1988
). In this context, a neurotransmitter role of aspartate in the cortex remains uncertain. Coexistence ratios of aspartate with glutamate were linear; in other words, neurons possessing high levels of aspartate also had high levels of glutamate.
The immunocytochemical localization of glutamine in mammalian cortex has so far, not been well studied. Glutamine biochemistry is intimately connected to that of glutamate; glutamine being the major source of glutamate in neurons, whereas glutamate is the direct precursor of glutamine in glia (Hertz, 1979; Ottersen et al., 1992
). It was therefore not surprising to observe glutamine in cells known to be enriched in glutamate. Glutamine was found in all cortical layers, both in cell bodies and neuropil, reflecting a precursor role for glutamate. The distribution profiles did not appear to vary between area 3 and area 6. However, colocalization with glutamate suggested a low glutaminehigh glutamate relationship. This distribution pattern may reflect the conversion of glutamine to glutamate in neurons. In contrast, CNS glial cells are known to demonstrate the inverse pattern of amino acid distribution (i.e. high glutaminelow glutamate), due to the deactivation and carbon skeleton recycling of glutamate that occurs within this cellular population. In this process, glutamate is actively taken up into glia, converted to glutamine and then exported to neurons (Hertz, 1979
; Kalloniatis and Tomisich, 1999
).
Except for layer IV spiny stellate cells, all non-pyramidal neurons are considered to use GABA as the main neurotransmitter. Contributing to ~1520% of all cortical neurons (Fitzpatrick et al., 1987; Hendry et al., 1987
; Beaulieu, 1993
), they are thought to be heterogeneous based on their physiological response and overlap with certain biochemical markers (Cauli et al., 1997
). Previous studies have shown that GABA- containing neurons are most abundantly packed in layers II, III and IV (Carder and Hendry, 1994
). This was generally supported by the present study in that layer IV contained more GABA-IR cells compared with layer V, although low numbers were observed in the region of layers II/III (Fig. 6C
). PV analysis indicated that although a small subpopulation had high signal intensity (PV 140160 range; Figs 3 and 4D
), the vast majority of GABA immunoreactivity was in the middle band (PV 80140; Figs 3 and 4D
). This spread in labelling intensities for GABA was consistent when GABA cell populations in different layers (including layer I) were compared, suggesting that heterogeneity (based on GABA content alone) is only local, i.e. within a layer. Even though the number of GABA-positive cells in a given layer was variable (Fig. 6C
), there was remarkable similarity in the spread of low to high expressing GABA cells in each layer (Fig. 6D,E
). This appeared to be the case for both areas 3 and 6 (Fig. 6D,E
).
A major finding of the present study, therefore, is that every GABA-containing neuron also contained glutamate. Surprisingly, colocalization of the two amino acids did not always fall into a high GABA/low glutamate relationship, which would be predicted by a metabolic role for glutamate in GABA-rich cells. Although GABA was found to coexist with low glutamate in some neurons, other neurons possessed high levels for both glutamate and GABA. This finding, also found in monkey somatosensory cortex (Conti et al., 1987a), calls for a reappraisal of the assumption that pools of glutamate serving as metabolic precursors in GABAergic neurons are necessarily low and therefore beyond the reach of immunocytochemical detection. Instead, it would support the view that some GABAergic neurons could have high steady-state levels of glutamate, perhaps due to slower glutamate clearance rates. Alternatively, simultaneously high levels of glutamate and GABA in the same neuron may indicate dual neurotransmitter usage within the same cell, as proposed in retinal amacrine cells (Ehinger, 1989
).
In conclusion, cortical cells are universal in possessing glutamate. That the level is not constant between different cells within a cortical area suggests biochemical variation at the population and individual level. When viewed against the background of other amino acids in the present study, the range of cellular diversity is clearly greater for glutamate. While the current analysis suffers from the disadvantage of providing only a biochemical snapshot of what must be a dynamic process, it nonetheless provides an indication of glutamate usage in relation to its metabolic and neurotransmitter roles. More importantly, this type of analysis opens up an avenue for further partitioning of cortical neurons based upon differential content of multiple amino acids in individual neurons the so called amino acid signature pattern already described for the retina (Marc et al., 1995). Such analysis can be expected to uncover further cellular heterogeneity in the cortex.
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Notes |
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Address correspondence to Seong-Seng Tan, Neurodevelopment Laboratory, The Howard Florey Institute, The University of Melbourne, Parkville, Victoria 3010, Australia. Email: stan{at}hfi.unimelb.edu.au.
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