This protocol describes real-time iontophoresis, a method that measures physical parameters of the extracellular space (ECS) of living brains. The diffusion of an inert molecule released into the ECS is used to calculate the ECS volume fraction and tortuosity. It is ideal for studying acute reversible changes to brain ECS.
This review describes the basic concepts and protocol to perform the real-time iontophoresis (RTI) method, the gold-standard to explore and quantify the extracellular space (ECS) of the living brain. The ECS surrounds all brain cells and contains both interstitial fluid and extracellular matrix. The transport of many substances required for brain activity, including neurotransmitters, hormones, and nutrients, occurs by diffusion through the ECS. Changes in the volume and geometry of this space occur during normal brain processes, like sleep, and pathological conditions, like ischemia. However, the structure and regulation of brain ECS, particularly in diseased states, remains largely unexplored. The RTI method measures two physical parameters of living brain: volume fraction and tortuosity. Volume fraction is the proportion of tissue volume occupied by ECS. Tortuosity is a measure of the relative hindrance a substance encounters when diffusing through a brain region as compared to a medium with no obstructions. In RTI, an inert molecule is pulsed from a source microelectrode into the brain ECS. As molecules diffuse away from this source, the changing concentration of the ion is measured over time using an ion-selective microelectrode positioned roughly 100 µm away. From the resulting diffusion curve, both volume fraction and tortuosity can be calculated. This technique has been used in brain slices from multiple species (including humans) and in vivo to study acute and chronic changes to ECS. Unlike other methods, RTI can be used to examine both reversible and irreversible changes to the brain ECS in real time.
The extracellular space (ECS) is the network of interconnected channels exterior to all brain cells and contains both interstitial fluid and extracellular matrix (Figure 1a and Figure 1b). The distribution of many substances required for brain cell function, including nutrients, hormones, and neurotransmitters, occurs by diffusion through the ECS. Changes in the physical parameters of this space, including volume, geometry, and extracellular matrix, can drastically affect diffusion through the ECS and the local ion concentrations bathing brain cells, which have a profound impact on brain cell function1,2.
Real-time iontophoresis (RTI) is used to determine two structural characteristics of a brain region: volume fraction and tortuosity3,4,5. Volume fraction (α) is the proportion of tissue volume occupied by the ECS (VECS) relative to the total tissue volume (Vtissue) in a representative elementary volume;
Tortuosity (λ) is the relative hindrance that a substance encounters when diffusing through a brain region as compared to a medium with no obstructions;
where D* (cm2 s-1) is the effective diffusion coefficient of the substance in brain and D (cm2s-1) is the free diffusion coefficient of the substance in a free medium, such as dilute agarose gel.
Today, the most commonly used probe substance for the RTI method is the small cation tetramethylammonium (TMA). TMA has a molecular weight of 74 g/mol, completely dissociates in solution, and has one positive charge. RTI studies with this ion have demonstrated that α 0.2 and λ 1.61,2. This means that the ECS is roughly 20% of the total brain volume and that the diffusion of a small, inert molecule occurs roughly 2.5 times slower in the ECS than in a medium with no obstructions3. However, both α and λ vary with brain age, region, and state and in pathological conditions1. Alterations of these parameters have been linked to brain development, aging, sleep, epilepsy, and many other fundamental processes and diseases of the brain1,6. While other techniques measure α and λ, RTI can measure both in localized regions of living tissue in real time. For this reason, RTI has become an indispensable tool for investigating changes in α and λ during acute and reversible challenges.
The theory supporting RTI was originally validated by Nicholson and Phillips, and the technique has been used extensively since that time4,7. Experiments employing RTI begin with the release of a pulse of TMA from a source microelectrode by iontophoresis into a dilute agarose gel. Once ejected, the ions freely diffuse away from the point source, choosing from a potentially infinite number of random paths (Figure 1d). The changing concentration of the ion is measured over time using an ion-selective microelectrode (ISM) positioned roughly 100 µm away (Figure 1c). The changes in TMA concentration are graphed and fitted to a curve that allows for the calculation of both D and the transport number of the iontophoresis microelectrode (parameters discussed in the Protocol). With these values, the procedure is repeated in a brain region of interest to obtain D* and to calculate both α and λ. Control of the iontophoresis microelectrode, data collection, graphing and fitting of the TMA concentration curve, and calculation of the experimental parameters are all typically done by the programs Wanda and Walter, which have been specifically designed for this purpose (the software and their manuals are freely available from the authors upon request).
The Protocol section of this review describes the basic procedures needed to design and perform RTI in rodent brain slices. The technique has also been used in non-rodent models, including human brain slices and in vivo brain preparations1,4,6,8,9. The Representative Results section provides both ideal and non-ideal results to highlight nuances in data interpretation. Finally, the Discussion section briefly covers troubleshooting techniques, limitations of RTI, alternative techniques used to study the ECS, and future applications of RTI.
Figure 1: Diagrams of Diffusion through ECS. (a) Diagram of ECS: Demonstrates the size and location of the ECS in a typical brain section. Yellow marks the ECS between the gray brain cell processes. The volume of the ECS is roughly 20% of the total tissue volume (i.e., volume fraction = 0.2) under physiological conditions. (b) Magnified diagram of the ECS: Highlights physical parameters contributing to tortuosity, including brain cell geometry (gray) and extracellular matrix (diagramed as a mesh of multicolored glycosaminoglycans and proteoglycans). (c) 3D diagram of diffusion from a point source: Demonstrates the net movement of inert molecules from an iontophoretic source to an ISM. Excluding diffusion barriers and cellular uptake, molecules diffuse outwards in all directions, producing a spherical concentration front. The ISM quantifies the local concentration of the inert molecules released from the iontophoretic source. (d) Computer simulation of diffusion in ECS of brain: [Far left] Setup for Monte Carlo simulation; green spheres represent brain cell processes and the red cross represents a point source. This setup models the brain tissue diagrammed in Figure 1a. [Middle images] 3 and 6 molecules performing random movements as they diffuse through the extracellular space of the brain, shown in 2 dimensions. [Far right] Random walks of many molecules released from the point source. The net movement of all molecules from the point source is outwards as depicted in Figure 1c. The cumulative random walks outline the spaces between the cells (i.e., the ECS; see reference5 for further explanation). Please click here to view a larger version of this figure.
All animal procedures, used to obtain tissue samples, were approval by the animal ethics committee at SUNY Downstate Medical Center.
1. Preparation of Solutions and Equipment
2. Electronic Setup
Figure 2: Porous Experimental Cup and Electronic Setup. (a) Porous experimental cup: A porous mesh is used to create an experimental cup that allows for electrical continuity between the agarose (inside) and the experimental bathing fluid (outside). A metal ring is attached to the bottom of the cup to prevent the cup from floating in the bathing solution. (b) Block diagram of the RTI setup (steps 2.1 and 2.2): An ISM is connected to an amplifier (amp.). The ISM has two barrels. One contains liquid ion exchanger (LIX) in the tip and generates a voltage proportional to the logarithm of the TMA concentration at the tip together with the local ambient voltage; the signal path is represented by a red line. The other barrel of the ISM is known as the reference barrel and measures the ambient voltage at the tip of the ISM; it is connected by a blue signal path. The amplifier has two so-called head stages that connect to the ISM; these units have a gain of 1 (x1) and match the high impedance of the microelectrode to the low impedance of the rest of the amplifier circuitry. The head stage connected to the ion-selective barrel must be able to match an incoming resistance of about 1,000 MΩ, whereas the resistance of the reference barrel is typically about 10 MΩ. After leaving the head stage, the voltage from the reference barrel is inverted and subtracted from the voltage on the ion-selective barrel using a summing amplifier (Σ) to obtain the pure ion signal voltage. The outputs of the amplifier pass to a signal conditioning unit that provides additional amplification and a multipole low-pass filter (≤10 Hz; typically a Bessel filter), which removes noise and prevents signal aliasing at the analog-to-digital converter (A/D). The outputs of the filter are also displayed on a strip chart recorder. The A/D converter digitizes the signals and sends them to a personal computer (PC). The PC also generates a digital signal that is converted by a digital-to-analog converter (D/A) to an analog voltage pulse that is fed to the iontophoresis unit, which converts the voltage to a current pulse of constant amplitude and sends it to the iontophoresis microelectrode. The iontophoresis signal path is represented by a green line. The data acquisition and iontophoresis signal are under the control of the Wanda program, which generates an output file for each diffusion record in the form of a voltage versus time recording, along with all the parameters that define the experiment. A second program, Walter, reads the output file and uses ISM calibration data to convert the digitized voltages to concentrations. The concentration versus time curves are then fitted in Walter to the appropriate solution to the diffusion equation. D and nt are extracted if the medium is agarose, and λ and α extracted if the medium is brain. Analog signals are solid lines; digital signals are dotted lines. There is also an indifferent ground electrode (not shown) in the bath containing the slice. Red lines = ion signal, Blue lines = reference signal, Green lines = iontophoresis command, Solid lines = analog, Dotted lines = digital. Please click here to view a larger version of this figure.
3. Preparation and Calibration of Ion-selective Microelectrodes
Figure 3: Preparation of an Ion-Selective Microelectrode. (a) ISM after chipping back the ends of a capillary and pulling (steps 3.2-3.6): A single barrel at both ends of a glass capillary is chipped. An ISM is generated by pulling one double-barreled glass capillary to generate two micropipettes with fine tips. (b) ISM after backfilling both barrels (steps 3.7-3.9): The tip of a single ISM is chipped to a diameter of 2-5 µm. The ion-selective barrel is backfilled with TMA-Cl, and the reference barrel is backfilled with NaCl. (c) ISM prior to coating with chlorotrimethylsilane (steps 3.11-3.13): A chloridized silver wire is inserted into the reference barrel. Polytetrafluoroethylene (PTFE) tubing is connected to a 25 G needle and inserted into the ion-selective barrel. An air-tight seal on top of both barrels is created using dental wax. (d) Coating a micropipette with chlorotrimethylsilane (steps 3.15-3.26): [Low magnification] An ISM suspended in chlorotrimethylsilane in line with a horizontally mounted stereomicroscope. [High magnification] The view through a horizontally mounted stereomicroscope of an ISM tip in chlorotrimethylsilane solution. After visualization of the tip through a microscope, small amount of TMA-Cl solution is expelled from the ion-selective barrel (enough to generate a small bubble of TMA-Cl solution). The ISM holder is tapped to release a TMA-Cl solution bubble and then chlorotrimethylsilane is drawn up into the tip. This cycle is repeated several times. After all chlorotrimethylsilane is ejected from the ISM, the ISM is placed into the liquid ion exchanger (LIX) for TMA and LIX is drawn into the tip of the ion-selective barrel. Please click here to view a larger version of this figure.
4. Preparation of Iontophoresis Microelectrodes
NOTE: Iontophoresis microelectrodes should be fabricated on the day of the experiment.
Figure 4: Preparation of an Iontophoresis Microelectrode. (a) Iontophoresis microelectrode after backfilling both barrels (steps 4.1-4.3): An iontophoresis microelectrode is pulled from a capillary tube. The tip of the microelectrode is chipped to a diameter of 2-5 µm. Both barrels of the iontophoresis microelectrode are filled with TMA-Cl solution. (b) Completed iontophoresis microelectrode (steps 4.5-4.6): An iontophoresis microelectrode with two chloridized silver wires inserted into the barrels. The barrels of the microelectrode are sealed with wax, and the silver wires are twisted together at the back of the microelectrode. Please click here to view a larger version of this figure.
5. Preparation of Artificial Cerebrospinal Fluid and Rodent Brain Tissue Slices
6. Real-time Iontophoresis in Agarose
Figure 5: Setup for Experiments in Agar. (a) Setup for experiment in dilute agar (steps 6.1-6.5): A small porous container filled with dilute agar placed in a running perfusion chamber. An iontophoresis microelectrode (left side) and an ISM (right side) are held by microelectrode holders; microelectrode holders are fitted into the arms of robotic micromanipulators. A temperature probe is placed in agar gel, and an indifferent ground electrode is placed within the submersion chamber. (b) Magnified view of microelectrodes in agar: An iontophoresis microelectrode (left side) and an ISM (right side) are visualized in agar using a 10X water immersion objective (objective immersed here in 150 mM NaCl). Microelectrodes are positioned using micromanipulators to a depth of 1,000 µm; the spacing between microelectrodes is 120 µm. Please click here to view a larger version of this figure.
Figure 6: Wanda Computer Software Interface. (a) Navigating Wanda graphical user interface (GUI): The screen that appears after opening the Wanda software. In box (1), the appropriate medium, iontophoresis molecule, and technique are selected. (2) "Calibrate" is clicked to open the Wanda Calibration box. After calibrating the ISM (see Figure 6b and Supplement B), the ISM is positioned in agar or brain, as described in steps 6 and 8 of the protocol. In box (6), all appropriate values for the experiment being performed are entered. (7) "Acquire" is clicked to take a recording; a graph of voltage versus time appears in the top-right portion of the Wanda GUI. (b) Calibrating ISM in Wanda: The window that opens after clicking on (2) "Calibrate" in the Wanda GUI. The values from step 3.29 are entered into box (3), and (4) "Fit Data" is selected. The calibration curve is confirmed to be linear. (5) "Accept" is clicked to return to the Wanda GUI. Please click here to view a larger version of this figure.
7. Agarose Data Analysis
Figure 7: Walter Computer Software Interface. (a) Choosing the data collection program in Walter: The "0. Records From:" menu opens after starting the Walter software. The option to load the records saved by Wanda is selected by clicking the "Wanda/Voltoro" button. (b) Choosing the data and data analysis output location in Walter: [Left] After the appropriate spreadsheet program is opened, "Sheets 1,3" is chosen to output all Walter data analysis to the previously opened spreadsheet program. [Right] After the data analysis output location is chosen, a pop-up window opens, allowing the user to choose the first and last recordings to be read by Walter. (c) Choosing the recording to analyze in Walter: [Right] After the files to read are chosen, a pop-up window will open with all chosen records displayed as a graph ("Figure 2"). [Left] In the "2.Options" menu, "select rec" is clicked, and the mouse is used to move the crosshairs to identify the first recording for analysis; either mouse button is pressed to choose the recording. (d) Exporting the data analysis from Walter to a spreadsheet: After fitting the data, a pop-up window and the "7. Results" menu appear. [Left] Graph of the selected recording (blue) with the fitted diffusion curve generated by Walter (red). [Right] The "7. Results" menu allows the user to write the data from the analysis to a spreadsheet program by clicking the "Excel" button. Please click here to view a larger version of this figure.
8. Real-time Iontophoresis in Brain Slices
9. Brain Data Analysis
10. Checking Transport Number and ISM Calibration
The utility of the RTI technique is demonstrated in an experiment designed to measure the changes in α and during a hypoosmolar challenge (Figure 8 and Figure 9). It has previously been shown that reducing the osmolarity of the ECS by washing on hypotonic ACSF will produce a decrease in α and an increase in λ13.
In this experiment, RTI was performed on rat brain slices under both control conditions and during the wash-on of hypotonic ACSF. An ISM was fabricated, and its calibration parameters were input into Wanda for fitting to the Nicolsky equation, which calculated a slope (M) of 58.21 mV. The ISM and iontophoresis microelectrodes were placed in agar and positioned 120 µm apart from each other in order to measure the transport number. Three recordings were taken, and the curves were fitted and analyzed according to the procedure in step 6 of the protocol (Figure 8a). The fitted curve of each trial overlapped with the raw curve (Figure 8a). The measured diffusion coefficient (D x 1E5), the transport number (nt), and the difference between the apparent spacing of the microelectrodes (r_app) and their actual spacing (r) did not differ significantly between the three recordings (Figure 8b, recordings a1-3). Based on these criteria, this iontophoresis microelectrode was deemed acceptable to continue with the experiment.
Once the stable iontophoresis microelectrode was chosen, control values for α and λ in the rat brain slice were taken in order to establish a baseline for these parameters. Previous studies found control values for the rat neocortex to be α = 0.18-0.22 and λ = 1.54-1.651. To replicate these values in this experiment, the ISM and iontophoresis microelectrode were placed 200 µm deep in the rat neocortex and 120 µm apart from each other. The average nt, calculated from the data in Figure 8b, was entered into the Wanda program for use in the calculations of α and λ. A shift in baseline V from the placement of the two microelectrodes about 200 µm deep in the brain was recorded, and the voltage jump was entered into Wanda to correct the baseline TMA (i.e., the baseline C parameter) concentration. Three recordings were taken, and their curves were fitted (Figure 9a, Figure 9d, and Figure 9f). The fits revealed an average α = 0.192 and λ = 1.69 (Figure 9e). Spacing and shifts in baseline V were checked after the recordings were taken, and the corrected values were entered into Wanda to reanalyze the data (as detailed in step 8 of the protocol). The recalculated values did not differ significantly, and the values reported in Figure 9d were accepted.
The normal osmolarity of ACSF is 300 mOsm. To test the effect of hypotonic ACSF on α and λ in the rat somatosensory neocortex, ACSF with an osmolarity of 150 mOsm was made by reducing the NaCl concentration. It was hypothesized that this hypotonic ACSF would lead to swelling of brain cells, causing a lower α and a potentially higher λ13. The brain slice was superfused with hypotonic ACSF for approximately 30 min, allowing it to equilibrate with the brain. During this time, the microelectrodes remained in the same place in the neocortex as they were during previous measurements of control conditions. Five recordings were taken under hypotonic conditions (Figure 9b and f). This generated an average α = 0.13 and λ = 1.84 (Figure 9e). These values were consistent with the hypothesis that hypoosmolarity decreases α and increases λ. Spacing and changes in baseline V were measured and taken into account during the analysis and fitting procedure.
Recovery parameters were also measured by washing on regular ACSF (300 mOsm) and taking new recordings in the same place in the neocortex. Because swelling effects should be reversible, it was expected that α and λ would recover to control levels. The values averaged over four records taken after 30 min of regular ACSF wash-on were α = 0.37 and λ = 1.61 (Figure 9c, Figure 9e, and Figure 9f). This demonstrated that there was an unexpected overshoot during the recovery of α under these conditions (Figure 9e and Figure 9f). Afterwards, the microelectrodes were returned to agar to confirm that the transport number of the iontophoresis microelectrode was unchanged (Figure 8c). The ISM was then recalibrated, and the new fit to the Nicolsky equation revealed the slope to be 58.21 mV.
This experiment is a clear example of what RTI looks like under ideal conditions. The following elements of the experiment were the key to its success. First, experimental data collected in agarose and the brain demonstrated adequate overlap with the theoretical curves generated by Wanda (Figure 8a and Figure 9a and Figure 9c). The similarity in slope, peak, and return to a similar baseline are all important in determining the strength of the match. These portions of the curve are frequently problematic when recording in agarose, and it is common that multiple recordings must be taken before finding the conditions that produce well-matched curves (i.e., good microelectrodes). Second, the average transport numbers before and after the experiment were within 10% of each other (Figure 8b and Figure 8c). If this had not occurred, the values recorded in brain could not be trusted. This is by far the most common problem that occurs in RTI experiments. Third, the ISM calibrations in standardized TMA solutions before and after the experiment matched (data not shown). Typically, the calibrations of a working ISM are within 10%, making this an uncommon source of experiment failure.
Figure 8: Ideal Curve Fitting Data in Agar Before and After Experimentation in the Brain. (a) Representative data from a trial in agar: [Far left] Representative data from a single trial obtained in agar demonstrating the concentration curve of TMA. Prior to diffusion measurements, a constant bias current of +20 nA was applied through the iontophoresis microelectrode. At time = 10 s, TMA was pulsed from the iontophoresis microelectrode into the agar by applying a +60 nA main current for 50 s. A diffusion curve was generated by measuring [TMA] over time using an ISM positioned 120 µm from the source. [Middle] A fitted curve obtained from data processing in Walter. [Right] The overlap of the data and the fitted curve demonstrates that the curve fitting done by Walter accurately models diffusion in this trial. (b) Table of agar measurements before experimentation in the brain: Data obtained from three trials (a1, graphed above) prior to the hypotonic stress experiments (Figure 9). All trials were conducted with the iontophoresis microelectrode and ISM used for the hypoosmotic stress trials. The data fulfilled the criteria needed to proceed with the experiment in brain slices. These criteria include adequate overlap between the data and the fitted curve (as above) and less than 10% variation in transport number. Additional criteria are outlined in step 7.6. (c) Table of agar measurements after experimentation in the brain: Data obtained from three trials performed in agar after the hypoosmotic stress experiments (Figure 9). The consistency demonstrated between trials a1-3 and a4-6 strongly suggests that the ISM and iontophoresis microelectrodes were stable throughout the brain trials. Rec = recording or trial; r = distance between the ISM and iontophoresis microelectrode; Cb = baseline concentration; ref Dx1E5 = theoretical free diffusion coefficient x 105 (cm2s-1) based on a pre-calculated standard; nt = transport number (dimensionless); D(E5) = measured free diffusion coefficient x 105 (cm2s-1); r_app = apparent microelectrode spacing (cm) based on the measured and reference D(E5); nt apparent = apparent transport number based on r_app. Please click here to view a larger version of this figure.
Figure 9: Hypoosmotic Stress Decreases Alpha and Increases Lambda
a-c. Representative data from trials in the brain under (a) control, (b) hypoosmotic, and (c) recovery conditions: Solid lines represent data and dashed black lines are fitted curves. The three conditions demonstrate markedly different diffusion curves, including different slopes, amplitudes, and widths. (d) Data table from control trials: Data table of three control trials (b1, graphed above); α and λ are similar in all trials and consistent with published data for the rat neocortex. For all trials in the brain, the average nt from pre- and post-experiment agar measurements (Figure 8b and 8c) was used for the brain nt. The brain Dref was set to 1.25 × 10-5 cm2 s-1, based on a database of diffusion coefficients (in Walter) that was obtained in the rat brain when T = 34.5 [°C]. The parameter k' [s-1] accounts for the small amount of TMA lost from the ECS during the diffusion measurements. Although k' is typically very small, including the parameter in curve fitting improves the accuracy of the RTI method. The loss parameter k' probably represents cellular uptake or the loss of TMA to the ACSF. (e) Comparison of control, hypoosmotic, and recovery conditions: Averages from all trials in the brain under control, hypoosmotic, and recovery conditions. The data demonstrate that hypoosmotic stress decreases α and increases λ. During a recovery period following hypoosmotic conditions, α overshoots baseline (control), while λ returns to baseline. The results suggest that changes in ECS during hypoosmotic challenges are partially reversible. The RTI method is ideal for studying this type of acute reversible effect. (f) Graph demonstrating data clustering: The volume fraction (x-axis) and tortuosity (y-axis) from each trial are plotted as a single point. The graph demonstrates the clustering of data within each group (i.e., control, hypoosmolar, and recovery), suggesting that RTI has the sensitivity to detect the reproducible effects of a hypoosmolar challenge in the brain ECS. Rec = recording or trial; r = distance between ISM and iontophoresis microelectrode; Cb = baseline concentration; alpha = volume fraction; lambda = tortuosity; k' = non-specific clearance of probe. Please click here to view a larger version of this figure.
Supplemental Files: Please click here to download the files.
Figure 10: Non-ideal Data Demonstrating Common Technical Issues. (a) Diagrams of common technical issues with iontophoresis microelectrodes: Comparison of the normal release of TMA from a functioning iontophoresis microelectrode with three sources demonstrating technical issues. [High magnification, a1] The current in an ideal iontophoretic source is carried equally by TMA release and chloride uptake. [High magnification, a2] An iontophoresis microelectrode with low nt releases less TMA and takes up more chloride than normal. [High magnification, a3] An iontophoresis microelectrode displaying electroosmosis releases TMA, chloride, and solvent. [High magnification, a4] An iontophoresis microelectrode displaying growing release over time (i.e., "warming up"). (b) Graph of non-ideal data obtained in agar: The data is not adequately modeled by the curve fitted by Walter and therefore cannot be accurately interpreted; the exact cause of the discrepancy is unclear. (c) Table of non-ideal data obtained in agar: Normal or expected results in agar are displayed in the top row (graphed in Figure 8a) for comparison to the non-ideal data in the second row (graphed in Figure 10b). The poor overlap between the data and the fitted curve in Figure 10b means that the fitted curve does not accurately model the diffusion data; therefore, the calculated values (marked with *) cannot be interpreted. This could have been caused by issues with the iontophoresis microelectrode (e.g., warming up) or the ISM (e.g., slow response). Troubleshooting: exchange microelectrodes one at a time, starting with the iontophoresis microelectrode. Rec = recording or trial; r = distance between ISM and iontophoresis microelectrode; Cb = baseline concentration; ref Dx1E5 = theoretical free diffusion coefficient x 105 (cm2s-1) based on a pre-calculated standard; nt = transport number (dimensionless); D(E5) = measured free diffusion coefficient x 105 (cm2s-1); r_app = apparent microelectrode spacing (cm) based on the measured and reference D(E5); nt apparent = apparent transport number based on r_app. Please click here to view a larger version of this figure.
While the experiment shown in Figure 8 and Figure 9 had a stable and working iontophoresis microelectrode and ISM, there are many experiments in which either or both microelectrodes are compromised and do not yield ideal results. A "normal" TMA iontophoresis microelectrode has a value of nt 0.3. Figure 10a demonstrates three common issues with the iontophoresis microelectrode that can be encountered during RTI experiments.
Low release. The iontophoresis microelectrode releases very little TMA when bias current or main current is applied, resulting in nt <0.1. Current is still passing through the tip, but most of it is carried by the Cl anion entering the tip and very little by the TMA cation leaving the tip. If nt is stable in several consecutive trials, these iontophoresis microelectrodes can be used. However, this is not recommended, as they are not functioning optimally, meaning that further issues may develop. An even bigger extreme occurs when the tip of the iontophoretic microelectrode is blocked and no ions leave or enter the tip. In this case, no curve will be produced. In such instances, after checking that all electrical connections are proper and secure, the iontophoresis microelectrode should be discarded.
High release (electroosmosis). In addition to TMA, the iontophoresis microelectrode also releases water, resulting in nt > 0.5. If the nt is stable over several trials, these iontophoresis microelectrodes can be used, but this is not recommended, as further issues may develop. The only troubleshooting step to take is to reduce the main current. This sometimes eliminates water release and causes the nt to decrease below 0.5.
Growing release ("warming up"). In this case, the TMA release increases over time. When the "warming up" is rapid, the diffusion curve has a shape similar to that shown in Figure 10b, and it cannot be reliably fitted. In this case, the diffusion curve demonstrates a slow rise in TMA concentration during the initial phase of the main current, and the TMA concentration does not plateau. An unreliable fit creates an inaccurate measured D, which affects the consistency of the measured transport number and the r_app values. When the "warming up" is more gradual, it does not have a significant impact on the shape of individual diffusion curves, but it manifests in an nt that increases over successive trials. A "warming up" condition can sometimes be remedied by "pulsing" the iontophoresis microelectrode for a period of time (about 30 min). This is done by alternating between a bias current and a high main current (+200 nA) for a few seconds at a time. If an iontophoresis microelectrode still does not give a stable transport number, it is best to simply test a new one.
Precise measurement of the transport number and stability during the entire experiment are essential to ensure an accurate value for α. Maintaining the spacing between microelectrodes is critical to the determination of both α and λ. If the spacing does change after a measurement, either in agarose or in the brain, the straight-line distance between the tips of the microelectrodes can be entered into the output spreadsheet and reanalyzed by Walter. If the values differ too much, the measurement must be discarded. Temperature fluctuation can also be a contributing factor to inaccuracy, so using an accurate temperature probe and a reliable chamber heating element is important.
The iontophoresis microelectrode is the most frequent source of problems in the RTI technique; making and using a stable ISM is crucial to obtaining good data. One possible problem with the ISM can be a sluggish response, which can be caused by very high impedance in the tip. With a slow-responding ISM, all the iontophoresis microelectrodes will appear to have a "warming up" effect (Figure 10b), but the curve is simply caused by the inability of the ISM to detect the changing TMA concentrations fast enough. Increasing the distance between the microelectrodes (up to 150 µm) can allow more time for the ISM to respond and can improve curve fitting. A sluggish response may indicate that the ion exchanger has retreated up inside the tip. This can be seen under a compound microscope and, if present, means the silanization was poor and that the ISM must be discarded. In addition, drifts in the ISM signal can cause inaccurate fits of the data. It is up to the experimenter to determine if the drift is affecting the data beyond tolerance.
Limitations of RTI
There are several limitations to the RTI method because of assumptions underlying the data analysis. These assumptions include a requirement for tissue homogeneity and tissue isotropy in both the brain region of interest and a spherical volume surrounding this region. In the context of RTI, tissue homogeneity requires that the diffusion parameters are constant within the region of interest. Tissue isotropy means that a single value of D* applies to all three spatial axes. Each molecule released from a source microelectrode takes a random path before arriving at the position of the recording ISM. The voltage on the ISM, representing the number of molecules (i.e., concentration) recorded at a single time, includes molecules that have traveled in all three spatial axes, as well as some molecules that have traveled beyond the ISM and have returned to the measuring point (Figure 1c). During RTI data analysis, the Walter program generates average α and λ, which include the diffusion of all molecules traveling in all axes from a point source to the ISM. If the rate of diffusion is significantly different in any one of the three spatial axes (anisotropy) or if the tissue is non-homogeneous, additional data collection and data analysis are required to calculate α and λ8,14.
In addition to the above tissue prerequisites, the RTI method requires that the spacing between a point source and ISM, which is referred to as r, is roughly 80 – 130 µm. When r is decreased below 50 µm, the ISM response may not be fast enough to record diffusion-dependent changes in concentration of the probe molecule. This might be remedied in the future using concentric ISMs with faster response times10,15. Larger r distances also minimize brain region-independent differences in the ECS milieu, ISM tip size, and brain tissue damage during ISM placement. Conversely, when r is increased beyond 150 µm, the diffusion of molecules from the iontophoretic point source is more susceptible to influence by non-isotropic, inhomogeneous elements surrounding the brain region of interest or the tissue-perfusate boundary14.
Incorporating RTI and alternative techniques to explore ECS
The RTI method belongs to a larger group of techniques that utilize a molecular probe to study the ECS; each method has its own advantages and shortcomings. While RTI allows for an accurate calculation of both α and λ in real time, the method requires a charged molecular probe that can be detected by an ion exchanger. In experiments where iontophoresis is not suitable, such as the study of an uncharged probe, iontophoresis may be replaced by pressure ejection. Unfortunately, current techniques do not allow for the calculation of α with pressure ejection, because the volume released depends on the properties of the injected medium16. To use a probe for which no exchanger exists, the probe may be fluorescently tagged and its diffusion through ECS measured by epifluorescent microscopy. This technique, known as integrative optical imaging (IOI), is limited by the size and availability of fluorescently labeled molecules and the potential for cellular uptake17,18. The IOI technique has the advantage that macromolecules can be used as probes, and this has revealed that λ increases with molecular size. Finally, an important class of diffusion methods has employed radiotracers, but they are no longer in common use2.
Future Applications of RTI
The RTI method can be difficult to implement, and it demands persistence, but it is a powerful tool for quantifying changes that occur in the parameters that describe the brain ECS. This protocol describes the RTI method as applied to slices, but it is also possible to reliably implement this technique in vivo, expanding its potential1,4,6. It can also be used to test the effects of a wide variety of changes in brain physiology, such as those induced by alterations to the chemical environment, pharmacology, trauma, or genetic knockout1. As long as the change induced in the ECS lasts for a period of about 2 min or more, RTI can provide a precise quantification of ECS volume fraction and tortuosity.
While significant insights into the structure and function of brain ECS have been generated in the last 50 years, there remain many unanswered questions. For example, it is still unclear if and how homeostatic mechanisms regulate α and how changes in α affect brain function. Computer models have helped to estimate the relative contributions of cell geometry and other factors that influence λ, but more work is needed1. Finally, the role of the ECS in the pathogenesis of neurological disease (and vice versa) is largely unexplored. In the near future, RTI measurements might improve targeted drug delivery to specific brain regions19.
The authors have nothing to disclose.
The work was supported by NIH NINDS grant R01 NS047557.
A/D and D/A converter | National Instruments Corporation | NI USB-6221 DAQ | The NI USB-6221 is still sold as a 'Legacy' device by NI. They recommend using NI USB-6341 X Series DAQs for new installations, however we have not tested the newer units. We describe the use of the NI USB-6221 with MATLAB and Windows 7 (32-bit). Alternatives: the much older PCI-MIO-16E-4 A/D converter (Used under Windows XP or older OS only) with BNC-2090 BNC connector panel and SH68-68-EP cable. As noted in the Wanda Manual, an experimental MATLAB program to use Axon Binary Files is available. |
agarose | Lonza | NuSieve GTG Agarose #50081 | to prepare dilute agarose gel for RTI measurements |
amplifier for ISM | Dagan | Model IX2-700 Dual Intracellular Preamplifier | ion and reference voltage amplifier with N=0.1 (for reference barrel) and N=0.001 (for ion barrel) headstages |
biological compound miscroscope (with 4x and 10x objective) | for chipping the microelectrode tips and inspecting microelectrodes; various suppliers, e.g. AmScope | ||
borosilicate theta capillary glass tubing | Harvard Apparatus | Warner Instruments model TG200-4; order #64-0811 | double-barreled glass tubing for ion-selective microelectrodes and iontophoretic microelectrodes; O.D. 2.0 mm, I.D. 1.4 mm, septum 0.2 mm, length 10 cm |
brush | Winsor & Newton | University Series 233, size 0 | round shoft handle brush, available from Amazon |
bunsen burner | Fisher | ||
camera for visualizing micropipettes | Olympus | OLY-150 | requires monitor, IR filter on substage illuminator is optional |
chart recorder | to record continuously voltages on ion-selective microelectrode during calibration in tetramethylammonium standards and during RTI experiment; e.g. Kipp & Zonen type BD112 dual-cannel chart recorded, available refurbished | ||
chlorotrimethylsilane, puriss., > 99% | Sigma-Aldrich | catalog # 92360 | for silanization; CAUTION: flammable, acute toxicity (oral, dermal, inhalation), skin corrosion, eye damage, reacts violently with water, see Sigma-Aldrich Safety Information for full description |
Commercial Software | The MathWorks | MATLAB, Data acquisition toolbox | for data acquisition and analysis using Wanda and Walter programs. Note that an academic license is available. |
eye protective goggles | Fisher | ||
fixed-stage compound microscope | Olympus | BX51WI | can use other compound microscopes with fixed stages |
forceps | Fine Science Tools | #11251-10 | to chip glass capillary; Dumond #5, preferably used and no longer needed for fine work |
fume hood | for silanization and filling the tip of ion-selective barrel with liquid ion exchanger; various supliers, e.g. Captair with approriate filter sold by Erlab | ||
glass microscope slide | Fisher | #12-550A | to chip microelectrode tips |
heater/stirrer | Fisher | Corning PC-420D | to prepare dilute agarose gel and stir solutions |
iontophoretic unit | Dagan | ION-100 and PS-100 | ION-100 is a single channel iontophoresis unit +/- 130 V compliance; PS-100 is an external power supply; alternatives: e.g. Axoprobe-1A made by Axon Instruments (now Molecular Devices), out of production, check for availability of refurbished units (eBay and other sites) |
liquid ion exchanger (LIX) for tetramethylammonium | World Precision Instruments | IE190 Potassium Ion Exchanger | Note: this is equivalent to the original Corning potassium exchanger 477317 based on tetraphenlyborate – do not confuse with neutral carrier potassium exchanger originating from the laboartory of Dr. Simon, ETH, Zurich, which does not sense tetramethylammonium, and is sold by Fluka. You can also make liquid ion exchanger for tetramethylammonium yourself: 3% by weight potassium tetrakis = (p-chlorophenyl) borate dissolved in 2,3-dimethylnitrobenzene. Buy chemicals from Fluka (now part of Sigma). See Oehme and Simon (1976) Anal. Chim. Acta 86: 21-25; CAUTION: The toxicological properties of this liquid ion exchanger have not been fully determined. Ingestion or contact with the human body may be harmful. Exercise due care! Liquid ion exchangers should be stored in a cool place out of direct sunlight. |
microelectrode holder | WPI | M3301EH | to hold ion-selective microeletrode prefabricate for silanization and filling the tip of ion-selective barrel with liquid ion exchanger; WPI sells two versions of this holder, clear M3301EH and black M3301EH. In our experience, the clear M3301EH appears to be sturdier then the black M3301EH. |
micromanipulator | Narishige | MM-3 | to position ion-selective microelectrode prefabricate during silanization and filling the tip of ion-selective barrel with liquid ion exchanger; can be substituted with any three-axis micromanipulator in good working condition |
micropipette puller | Sutter Instruments | Model P-97 | to pull double-barreled glass tubing; other pullers can be used as long as they can accommodate large diameter double-barreled glass tubing |
microprobe thermometer | Physiotemp | Model BAT-12R | fine probe of this thermometer is placed close to recording site |
needle | BD | Syringes and Needles # 305122 (25 gauge) | for silanization; BD PrecisionGlide needles 25 G x 5/8 in (0.5mm x 16mm) |
objective 5x dry | Olympus | MPlan N | |
objective 10x water immersion | Olympus | UMPlan FL N | 10x objective is water immersion, numerical aperture is 0.3, working distance is 3.3 mm |
plastic containers (with lids) | Fisher | #14-375-148 | to store tetramethylammonium standard solutions and microelectrodes |
platform and x-y translation stage for fixed-stage microscope | EXFO | Gibraltar Burleigh | platform holds slice chamber, micromanipulators and accesorries, x-y translational stage moves microscope without compromising recording stability |
porous minicup | for RTI measurements in a dilute agarose gel; homemade | ||
reusable adhesive | Bostik | Blu-Tack | for securing microelectrodes to holding vessel and other uses; various suppliers, available from Amazon |
robotic micromanipulator with precise x,y,z positioning | Sutter Instruments | MP-285 | two mircomanipulators are needed to hold separately ion-selective microelectrode and iontophoretic microelectrode. Also possible to glue micropipettes in a spaced array (see text). |
signal conditioning unit with low-pass filter | Axon Instruments | CyberAmp 320 or 380 | no longer available from the manufacturer but may be available from E-Bay; alternatives: e.g. FLA-01 Filter/Amplifier from Cygnus Technology. This is a single channel instrument with a minimum cutoff at 10 Hz using a multipole Bessel filter but the company may be willing to modify it for a lower cutoff frequency (2 Hz) if needed. |
silver wire | A-M Systems | #7830 | diameter 0.015", bare (no coating) |
slice chamber | Harvard Apparatus | Warner Model RC-27L | this is submersion slice chamber; do not use interface slice chamber |
stereomicroscope | for silanization and filling the tip of ion-selective barrel with liquid ion exchanger; horizontally mounted; various suppliers | ||
syringe, 10 mL | BD | Syringes and Needles #309604 | to backfill microelectrodes and for silanization; BD Luer-Lok tip |
syringe filter 0.22µm pore | Whatman | #6780-1302 | to filter backfill solutions; available from Fisher |
syringe needle, 28 gauge, 97mm | World Precision Instruments | MicroFil MF28G-5 | to backfill microelectrodes |
Teflon (=PTFE) tubing | Component Supply | STT-28 PTFE tube light wall (28 gauge) | for silanization of ion-selective barrel; fits on BD PrecisionGlide needles 25 G x 5/8 in. Note: Teflon is essential, PVC tubing would melt by hot wax. |
temperature control system | Harvard Apparatus | Warner Models TC-344B and SH-27A | TC-344B is a dual automatic temperature controller, SH-27A is an in-line heater; controller and heater work with Warner slice chambers |
tetramethyammonium (TMA) chloride | Sigma-Aldrich | T-3411 | 5 M solution; CAUTION: acute toxicity (oral, dermal, inhalation), carcinogenicity, hazardous to the aquatic environment, see Sigma-Aldrich Safety Information for full description |
vibrating blade microtome | Leica | VT1000S | to cut brain slices |
xylenes | Fisher | X5-1 | for silanization; CAUTION: flammable, acute toxicity (oral, dermal, inhalation), skin corrosion, eye damage, carcinogenicity, see Fisher Safety Information for full description |