Studying GABAA Receptors using AII Amacrine Cells in the Rat Retina
Not peer reviewed
MetadataShow full item record
The cell membrane consists of several membrane receptors, which based on the structure and functions, are typically divided in 3 classes: G protein-coupled receptors, enzyme-linked receptors and ion channel linked receptors, also commonly referred to as ligand-gate ion channels (LGICs) or ionotropic receptors. (Hucho & Weise, 2001; Purves et al., 2001; Yeagle, 2016). LGICs can be classified into three superfamilies, depending on the number of monomers composing an oligomer: the pentameric, tetrameric and trimeric LGIC: 1) The tetrameric superfamily of ionotropic glutamate receptors (iGluR). 2) The pentameric superfamily of receptors. 3. The trimeric superfamily ATP-gated purino receptors (P2X) (Hucho & Weise 2001; Nasiripourdori et al., 2011). In the pentameric superfamily we have: nicotinic acetylcholine receptors (nAChR), glycine receptors, GABAA receptors (GABAAR), and some serotonin receptors (5-hydroxytryptamine, 5-HT3R) (Casio, 2004; Jacob et al., 2008; Nasiripourdori et. al., 2011). GABAARs is a pentameric transmembrane receptor that consists of five subunits arranged around a central pore and are constituted from a family of over 20 different GABAAR subunit combinations called subtypes, constructed from a family of 19 homologous genes divided into eight classes according to sequence homology (GABAAR α1-6, β1-3, γ1-3, δ, ε, θ, π, ρ1-3) (Olsen & Sieghart, 2008). GABAAR are the binding sites for several drugs and compounds. Some major binding sites to mention include the GABA site, the benzodiazepine (BZ) site, the picrotoxin site, and the general anesthetic site (Olsen & Sieghart, 2008; Puthenkalam et al., 2016; Lorenz-Guertin & Jacob, 2017; Olsen, 2018), One of the main goals in this project was to study the properties of GABAA receptors by using the patch clamp technique and AII amacrine cells in the rat retina. I performed whole-cell and nucleated voltage clamp recording from AII amacrine cells in an acutely isolated slice preparation. GABA was applied to the cells using a puffer pipet and the current responses were recorded. Patch-clamp recording were made from 16 AII amacrine cell in slices cut from rat retina. During application of GABA; 8 cells died and were not further analysed. The remaining 12 cells all respond to application of GABA. Of these 12, five cells are further analyzed for reversal potential of the GABA-evoked currents. Data is presented as average ± standard error of mean (SEM). As described in section 3.8, 1 mM GABA was applied together with a series of voltage steps ranging from -80 mV to + 40 mV with 20 mV increments. A cesium-based intracellular solution called IC 6302 and a sodium-based extracellular solution called EC 1000 were used, and the reversal potential for chloride was calculated with Nernst equation to be Clrev ~ -0.6 mV. Results are presented as current-voltage (I-V) curves with the mean peak currentresponse evoked at each voltage plotted against the voltage steps (-80 mv to + 40 mV). The data was fit with a straight line in an attempt at finding a linear fit for the results. The point where the fitted line crosses the x-axis is an estimate of each cell’s reversal potential for GABA. The results from analyzing five AII cells gave a reversal potential for GABA-evoked currents = of – 2.9 mV ± 1.8 mV. This value is close to the calculated reversal potential for chloride with EC 1000 and IC 6302 (-0.6 mV), suggesting that GABA activates a chloride current. The slight difference between the calculated and experimentally obtained valued for the reversal potential can be explained by experimental error. Other reasons for variations in responses are desensitization and rundown and that can affect the response in peak amplitude of GABA application. In the pharmaceutical industry, ion channel assays are used frequently in basic research for investigating the ion-channel-related phenomena and in drug discovery for screening compounds directed to ion-channel related target (Xu et. al., 2001). Patch clamping provides high quality and physiologically relevant data of ion-channel function at the single cell or single channel level, and therefore is suited as a good method for this purpose. There are four major area of using patch clamping in drug discovery. They are: basic research, primary screening, secondary screening, and safety screening. Patch-clamping experiments are a complicated process that require highly trained and skillful personnel. It requires precision micromanipulation under high power visual magnification and vibration damping. Throughput of a veteran patch-clamper according to Xu et al. 2001 is, at best, 10–30 data points per day. Such low throughput and high labour-cost is not convenient for HTS purposes (Xu et al., 2001). Because of this, high-throughput studies required in proteomics and drug development have to rely on less informative methods such as fluorescence-based measurement of intracellular ion concentrations or membrane voltage (Denyer et al., 1998; Gonsalez et al., 1999; Xu et al., 2001). Suffering from low throughput and high cost, traditional patch clamp in drug discovery was used mainly in basic research, secondary screening, and safety screening, not so much in primary screening or drug screening. However, this is about to change, several studies with patch clamping recently were carried out using automated version of whole cell patch clamp. Automated patch clamping has showed vastly increased throughput, costs less than the traditional patch clamping and makes electrophysiological testing with its many advantages, the option of choice in early screening for ion channel active drugs (Dunlop et al., 2008; Jones et al., 2009; Martinez et al., 2010; Py et al., 2011; Kodandaramaiah et al., 2012; Billet et al., 2017).
PublisherThe University of Bergen
Copyright the Author. All rights reserved