We describe an analytical method to estimate the lifetime of glutamate at astrocytic membranes from electrophysiological recordings of glutamate transporter currents in astrocytes.
The highest density of glutamate transporters in the brain is found in astrocytes. Glutamate transporters couple the movement of glutamate across the membrane with the co-transport of 3 Na+ and 1 H+ and the counter-transport of 1 K+. The stoichiometric current generated by the transport process can be monitored with whole-cell patch-clamp recordings from astrocytes. The time course of the recorded current is shaped by the time course of the glutamate concentration profile to which astrocytes are exposed, the kinetics of glutamate transporters, and the passive electrotonic properties of astrocytic membranes. Here we describe the experimental and analytical methods that can be used to record glutamate transporter currents in astrocytes and isolate the time course of glutamate clearance from all other factors that shape the waveform of astrocytic transporter currents. The methods described here can be used to estimate the lifetime of flash-uncaged and synaptically-released glutamate at astrocytic membranes in any region of the central nervous system during health and disease.
Astrocytes are one of the most abundant cell types in the brain with star-shaped morphology and fine membrane protrusions that extend throughout the neuropil and reach neighboring synaptic contacts 1,2. The astrocytes’ cell membrane is densely packed with glutamate transporter molecules 3. Under physiological conditions, glutamate transporters rapidly bind glutamate at the extracellular side of the membrane and transfer it to the cell cytoplasm. By doing so, the transporters maintain low the basal concentration of glutamate in the extracellular space 4. Glutamate transporters in fine astrocytic processes adjacent to excitatory synapses are ideally positioned to bind glutamate released during synaptic events as it diffuses away from the synaptic cleft. By doing so, the transporters also limit glutamate spillover towards peri- and extra-synaptic regions and onto neighboring synapses, reducing the spatial spread of excitatory signals in the brain 5-7.
Glutamate transport is an electrogenic process stoichiometrically coupled to the movement of 3 Na+ and 1 H+ along their electrochemical gradient and to the counter-transport of 1 K+ 8. Glutamate transport is associated with (but not stoichiometrically coupled to) an anionic conductance permeable to SCN– (thiocyanate) > NO3– (nitrate) ≈ ClO4– (perchlorate) > I– > Br– > Cl– > F–, not to CH3SO3– (methane sulfonate) and C6H11O7– (gluconate) 9-11. Both currents (stoichiometric and non-stoichiometric) can be recorded by obtaining whole-cell patch-clamp recordings from astrocytes, visually identified under Dodt illumination or infra-red differential interference contrast (IR-DIC) in acute brain slices 12. The stoichiometric component of the current associated with glutamate transport across the membrane can be isolated by using CH3SO3–, or C6H11O7– based intracellular solutions and can be evoked by flash-uncaging glutamate on astrocytes 13,14, or by activating glutamate release from neighboring synapses, either electrically 12 or with a targeted optogenetic control.
The time course of the stoichiometric component of the transporter current is shaped by the lifetime of the glutamate concentration profile at astrocytic membranes (i.e. glutamate clearance), the kinetics of glutamate transporters, the passive membrane properties of astrocytes, and during synaptic stimulations, by the synchronicity of glutamate release across the activated synapses 13. Here we describe in full detail: (1) an experimental approach to isolate the stoichiometric component of glutamate transporter currents from whole-cell patch-clamp recordings from astrocytes using acute mouse hippocampal slices as an example experimental preparation; (2) an analytical approach to derive the time course of glutamate clearance from these recordings 13,14. These methods can be used to record and analyze glutamate transporter currents from astrocytes in any region of the central nervous system.
1. Slice Preparation
Note: speed and precision are paramount for the dissection steps described below.
2. Astrocyte Identification and Recordings
3. Pharmacological Isolation of the Sustained K+-current
4. Isolation of the Facilitated Portion of Synaptically-Activated Transporter Currents (fSTCs)
5. Subtraction of the Residual zdustained K+-current from fSTCs
6. Isolation of Flash-activated Transporter Currents (FTCs)
7. Deconvolution analysis
The success of the analytical approach described here critically depends on obtaining high-quality electrophysiological recordings of transporter currents from astrocytes in any region of the central nervous system. In acute mouse hippocampal slices, astrocytes can be readily identified under Dodt illumination or IR-DIC because of their small cell body (Ø = 10 μm) and prominent nucleus (Figure 1). Their distinctive star-shaped morphology can be appreciated with epifluorescence, confocal, or two-photon laser scanning microscopy, when adding a fluorophore like Alexa 594 (50 μM) to the intracellular solution, (Figure 1). At the electrophysiology level, astrocytes are characterized by low input resistance, hyperpolarized membrane potential (~-90 mV) and inability to generate action potentials. Astrocytes generate currents in response to electrical or optogenetic stimulation of neighboring neurons and UV photolysis of caged compounds like MNI-L-glutamate.
Astrocytic transporter currents can be recorded using Cs+ or K+ based internal solutions. Note that Cs+, a popular K+ substitute, supports glutamate transport but slows the glutamate transporter cycling rate 16,17 (because glutamate transporters bind and/or translocate Cs+ across the membrane more slowly than K+). If Cs+ reduces significantly the number of transporters available for binding glutamate, it also leads to smaller/slower transporter currents than the ones recorded with K+ based internal solutions 16,17.
When using CH3SO3– or C6H11O7– as the main intracellular anion, the current generated by glutamate transporters in astrocytes is due to the stoichiometrically-coupled movement of 1 glutamate, 3 Na+, 1 H+ and 1 K+ across the membrane. This stoichiometric current is the only one recorded from astrocytes in photolysis experiments and we refer to it as the FTC. When performing photolysis experiments, it is recommended to alternate UV stimulations obtained with the light path open and blocked. The traces obtained with the light path blocked are useful to isolate the stimulus artifact generated by the flash lamp and can be subtracted from the ones obtained with the light path open to perfectly isolate the FTC.
The current recorded in astrocytes when evoking synaptic release of glutamate has a more complex waveform. It is composed of a fast-rising, transient inward component due to the stoichiometrically-coupled glutamate transporter current described above. In addition, it comprises a slow-rising, sustained inward K+-current due to influx of K+ accumulated in the extracellular space after action potential propagation along neighboring axons. A pharmacological approach can be used to isolate the transporter current from the sustained K+-current and requires the use of high concentrations of the broad-spectrum glutamate transporter antagonist TBOA (100 μM) at the end of the experiment 12. The method described here uses a purely analytical approach to isolate the glutamate transporter current from the sustained K+-current and therefore allows for shorter experiments (Figure 2).
As a first step, we interleave single and paired-pulse synaptic stimulations (100 msec apart), every 10 – 20 sec, and average an equal number of the sweeps obtained with single and paired-pulse stimuli. The amplitude of the first current evoked by the paired stimuli should match the amplitude of the current evoked by the single stimulus. We begin this analysis by subtracting the current evoked by the single stimulus from that evoked by the paired stimuli. This subtraction allows isolating the response to the second stimulus, which is also composed of a fast-rising, transient glutamate transporter current and a slow-rising, sustained K+-current (Figure 2a right). Next, we shift the response to the single stimulus by a time interval corresponding to the inter-pulse interval of the paired stimuli, so that the time of onset of the single response matches the time of onset of the second response isolated above (Figure 2b). By subtracting these two currents, we isolate the facilitated portion of the transporter current, which here we call fSTC (Figure 2c). The kinetics of the fSTC are similar to the kinetics of the synaptically-activated transporter current (STCs) isolated pharmacologically with high concentrations of the glutamate transporter antagonist TBOA (100 μM) 13. For this reason and for simplicity, in previous work, we referred to the fSTC as STC 13,14. Despite being currents with similar properties, fSTCs and STCs are not the same current. For this reason and for accuracy, in this work, we will refer to them explicitly as fSTCs and STCs. The subtraction method described here allows for accurate isolation of fSTCs in most recordings. However, in some cases, a residual sustained K+-current is still present. In this case, it is necessary to isolate the sustained K+-current in separate experiments using high concentrations of TBOA (50 – 100 μM). The time course of the pharmacologically-isolated sustained K+-current can be described by a mono-exponential function in the form:
By recording astrocytic currents in different cells, we estimate the average value of Τrise. We next create a mono-exponential function like the one described above, in which Τrise corresponds to the average value of Τrise measured experimentally in different astrocytes and A corresponds to the amplitude of the residual sustained K+-current that we want to remove (Figure 2d).
The method we just described to isolate fSTCs works nicely when evoking glutamate release from facilitating synapses and can also be used to study glutamate release from synapses that undergo paired-pulse depression. However, it is of little use when the glutamatergic synapses under study do not show any clear form of short-term facilitation or depression. In this case, the pharmacological isolation of transporter currents with high concentrations of TBOA (100 μM) remains the most feasible solution to isolate the stoichiometrically-coupled, synaptically-evoked glutamate transporter current.
To perform the deconvolution analysis and measure the lifetime of glutamate at astrocytic membranes it is necessary to isolate FTCs or fSTCs in control conditions and in the presence of a sub-saturating concentration of TBOA (10 μM), to reduce the transporter current amplitude to at least 30% of its value in control conditions (i.e. without blocking it entirely). The goal here is to slow down significantly the time course of the transporter current without losing the ability to distinguish it from the noise of the recordings. The underlying assumption is that in the presence of a small concentration of TBOA, when the uptake capacity of astrocytes is diminished, the main factor shaping the decay of the transporter current is the gradual decline of the glutamate concentration at the astrocytic membrane 12,18. We fit the transporter current in control conditions and in TBOA (10 μM) with the multi-exponential function:
(Figure 3a). We approximate the glutamate clearance in TBOA (10 μM) with an instantaneously-rising function with mono-exponential decay (Figure 3b) and we deconvolve it from the multi-exponential function describing the transporter current in TBOA (10 μM; Figure 3c). The resulting waveform is the “filter”, and represents the combination of factors that distort (i.e. filter) the glutamate concentration profile into the transporter current (Figure 3c). Deconvolving the filter from the multi-exponential fit of the transporter current in control conditions allows estimating the time course of the glutamate concentration profile at the recorded astrocyte in control conditions (Figure 3d). For this deconvolution analysis, we assume that the kinetics of the filter remain unaltered in the absence and in the presence of TBOA (10 μM). This is a reasonable assumption because all factors that contribute to the filter (i.e. transporter kinetics, electrotonic filtering, and during synaptic stimulations, asynchronous release of glutamate across synapses) are unlikely to be influenced by the presence of TBOA, a compound that reduces the number of transporters available for binding glutamate.
We use the centroid (<t>) as a measure of the glutamate lifetime at astrocytic membranes in different cells. <t> represents the “center of mass” of the clearance waveform, and is sensitive to changes in both rise time and decay of the glutamate clearance waveform. The centroid is expressed as:
There are two ways to decide the time interval over which we can calculate the integrals at the numerator and denominator of this expression. Because the clearance waveform rises from and decays back to zero, when the method was first established, there was no specification made on how to set the integration window, and in fact this was done rather loosely 13. One way around this issue is to limit the integration window to the time it takes to reach an arbitrary proportion of the FTC/fSTC peak, for example 10% 14. This simple criterion allows being consistent when performing this analysis in different cells, improves the accuracy in the estimates of <t> when the clearance waveform does not decay perfectly to zero, and improves the sensitivity of the analysis to small differences in clearance waveforms that might occur in different groups of cells.
Figure 1. Identification of astrocytes in acute hippocampal slices. (a-b) Dodt images of hippocampal astrocytes in CA1 stratum radiatum. Under Dodt illumination and IR-DIC, astrocytes can be identified by their small cell body and prominent nucleus. The red arrows point to multiple astrocytes that can be identified in the slices preparation. The yellow arrow shows the astrocyte that was patched and filled with a fluorescent dye (see below). (c-d) Overlaid Dodt image of the hippocampal slices and two-photon of the patched astrocytes, highlighted with a yellow arrow in (a-b). For this experiment, astrocytes were patched and filled with a KCH3SO3 – based internal solution added with Alexa 594 (50 μM). The astrocytic processes extend a few tens of μm away from the cell body. The annotations of the left identify the three main cellular layers of the hippocampal CA1 formation that can be recognized in the slices.
Figure 2. Isolation of fSTCs from synaptically-activated transporter currents recorded in astrocytes. (a-c) Scheme of the analytical steps required to isolate the fSTCs from synaptically-activated transporter currents recorded in astrocytes. (d) Analytical approach used to remove the residual sustained K+-current from the fSTCs (see section 5). Click here to view larger figure.
Figure 3. Deconvolution analysis used to derive the time course of glutamate clearance from astrocytes. (a) Mono-exponential fit of the fSTC/FTC isolated in control conditions (left) and in the presence of TBOA (10 μM; right). (b) The time course of glutamate clearance in TBOA (10 μM) is approximated by an instantaneously-rising function with mono-exponential decay. (c) Deconvolving the time course of glutamate clearance in TBOA (10 μM) from the multi-exponential fit of the transporter current in TBOA (10 μM) allows estimating the filter. (d) Deconvolving the filter from the multi-exponential fit of the transporter current in control conditions allows estimating the time course of glutamate clearance from astrocytes in control conditions. Click here to view larger figure.
Here we describe an experimental approach to obtain electrophysiological recordings from astrocytes, an analytical protocol to isolate glutamate transporter currents in astrocytes and a mathematical method to derive the time course of glutamate clearance from astrocytic transporter currents.
The success of the analysis relies on the ability to obtain high-quality patch clamp recordings from astrocytes and on the accuracy of the fitting algorithms used to describe the transporter currents. The deconvolution analysis relies on the following two assumptions. (1) The multiple processes that distort the time course of glutamate clearance into the experimentally-recorded transporter current can be represented as a linear system. Although in absolute terms many of the factors that shape transporter currents are non-linear systems (in principle glutamate binding and transport can both undergo saturation), experimental evidence indicates that their linear regime is broad. Accordingly, the time course of transporter currents and of glutamate clearance remains the same over a broad range of stimulus strength, release probability, and glutamate concentrations 13,14,18. Although this approximation seems to be legitimate for our experimental conditions, it should be validated before repeating this analysis in different experimental preparations. (2) The characteristics of the filter are unaffected by the presence of TBOA (10 μM). This assumption seems reasonable because all factors that contribute to the filter (i.e. transporter kinetics, electrotonic filtering, and during synaptic stimulations, asynchronous release of glutamate across synapses) are unlikely to be influenced by the presence of TBOA.
By deriving the glutamate clearance waveform from fSTCs and FTCs, we obtain two different types of information. By analyzing fSTCs, we measure the time that astrocytic membranes are exposed to glutamate released from synapses. By evoking FTCs with full field UV illumination (i.e. by uncaging glutamate over the whole astrocytic surface), we measure the time that astrocytic membranes are exposed to uncaged glutamate. In these uncaging experiments all glutamate molecules are released (i.e. uncaged) at the same time and all transporters are activated at the same time, by the same glutamate concentration. Therefore, by analyzing FTCs, we can obtain an indirect readout of the astrocytic glutamate uptake capacity.
It is important to note that the methods described here allow estimating the time course of glutamate clearance, not the actual value of the glutamate concentration evoking the transporter currents. The estimated time course is an average measure of the time course of glutamate clearance at all areas of the astrocytic membrane to which we have electrophysiological access: it is not sensitive to heterogeneities in glutamate uptake at different sites within the astrocytic membrane 19. This information is more likely to be obtained with high-resolution microscopy of glutamate-sensitive fluorescent reporters 20. However, the currently available glutamate-sensitive reporters exhibit relatively narrow dynamic ranges. This can introduce non-linear distortions between the glutamate concentration profile and the fluorescent signal, limiting the use of these probes to extract temporal information on the glutamate concentration transient. Therefore, it is probably by combining all these different approaches that one can get the most comprehensive understanding of the dynamics of glutamatergic signals at astrocytic membranes.
In summary, the methods presented here can be used to estimate the clearance time course of synaptically-released or flash-uncaged glutamate at astrocytic membranes. They provide valuable tools that can be used to estimate the lifetime of glutamate in the extracellular space at different stages of development 13 in a variety of animal species 14 and brain regions under physiological and pathological conditions 21.
The authors have nothing to disclose.
This work was supported by the National Institute of Neurological Disorders and Stroke Intramural Research Program (NS002986). AS wrote the manuscript and implemented the deconvolution analysis. JSD developed the initial version of the deconvolution analysis and commented on the text.
Material Name | Company | Catalogue Number | Comments |
CGP52432 | Tocris | 1246 | |
(R,S)-CPP | Tocris | 173 | |
DPCPX | Tocris | 439 | |
LY341495 disodium salt | Tocris | 4062 | |
MSOP | Tocris | 803 | |
NBQX disodium salt | Tocris | 1044 | |
D,L-TBOA | Tocis | 1223 | |
Picrotoxin | Sigma | P1675 | |
MNI-L-glutamate | Tocris | 1490 | |
Alexa 594 | Life Technologies | A10438 | Optional |
Matrix electrodes | Frederick Haer Company | MX21AES(JD3) | |
Borosilicate glass capillaries | World Precision Instruments | PG10165-4 | |
Dual-stage glass micro-pipette puller | Narishige | PC-10 | |
Loctite 404 instant adhesive | Ted Pella | 46551 | |
Xe lamp | Rapp OptoElectronic | FlashMic | |
Igor Pro 6 | Wavemetrics |