DOI: 10.5061/dryad.g79cnp602
title: A selective small-molecule agonist of G protein-gated inwardly-rectifying potassium channels reduces epileptiform activity in a mouse model of tumor associated epilepsy - Part 2: WT Non-Tumor MEA Data

description: Tumor associated epilepsy is a common and debilitating co-morbidity of
 brain tumors, for which inadequate treatments are available. Additionally,
 animal models suggest a potential link between seizures and tumor
 progression. Our group has previously described a mouse model of diffusely
 infiltrating glioma and associated chronic epilepsy. G protein-gated
 inwardly rectifying potassium (GIRK) channels are important regulators of
 neuronal excitability, but their development as a target of antiseizure
 medications has been hampered by cross-reactivity with GIRK channels in
 the heart. Recently GiGA1, a novel GIRK agonist that is highly selective
 for brain tissue, was developed and shown to have antiseizure properties
 in an acute chemoconvulsant model. Here, we test GiGA1 ex vivo in
 our established mouse model of tumor associated epilepsy, demonstrating
 that a highly selective, small-molecule GIRK agonist can reduce
 seizure-like activity in the peritumoral region, where neurons and glioma
 cells interact and from which focal seizures arise.
description: <em>Mouse Glioma Model</em> A
 retroviral vector containing PDGFA-IRES-Cre was injected into the
 subcortical white matter of transgenic C57BL/6 mice containing floxed p53,
 STOP-floxed RPL22<sup>HA</sup>, and STOP-floxed
 mCherry-luciferase, resulting in conditional expression of these genes.
 Glioma cells were then isolated from these tumors and sustained in
 culture. Wild-type C57BL/6 or transgenic Thy1-GCaMP6f
 mice, of both sexes, were used for experiments. In some experiments, mice
 aged 1-4 months were injected with 50,000 glioma cells in a volume of 1 μl
 at 0.2 μl/min. The cells were injected into right frontal cortex
 (coordinates relative to the bregma: 2 mm anterior, 2 mm right, and 2 mm
 deep). <em>In vivo</em> luciferase imaging was performed
 weekly to track tumor growth, and tumor-bearing mice were sacrificed 28-35
 days post injection (dpi) to prepare acute slices for
 electrophysiology.
 <em>Electrophysiology</em> Mice
 were sacrificed by cervical dislocation and the whole brain was
 immediately placed in ice-cold Cutting Solution (sucrose 210 mM, potassium
 chloride 2.5 mM, sodium bicarbonate 26 mM, sodium phosphate monobasic 1.25
 mM, dextrose 10 mM, calcium chloride 0.5 mM, magnesium chloride 7 mM).
 While submerged in ice-cold, aerated (95% O<sub>2</sub> and 5%
 CO<sub>2</sub>) cutting solution, 400 µm coronal slices
 through frontal cortex were prepared using a Leica VT 1000S Vibratome
 (Nussloch, Germany). Slices were placed in aerated Recovery Solution
 (sodium chloride 125 mM, potassium chloride 2.5 mM, sodium bicarbonate 26
 mM, sodium phosphate monobasic 1.25 mM, dextrose 10 mM, calcium chloride 2
 mM, magnesium chloride 1.5 mM) at 35° C for 18 minutes, then at least 42
 minutes (for a total of 1 hour) in the same aerated solution at room
 temperature. Baseline recordings were performed in
 artificial cerebrospinal fluid (ACSF) comprising sodium chloride 125 mM,
 potassium chloride 5 mM, sodium bicarbonate 26 mM, sodium phosphate
 monobasic 1.25 mM, dextrose 10 mM, calcium chloride 2 mM, magnesium
 chloride 1.5 mM. To generate spontaneous seizure-like events while
 preserving inhibitory function, slices were recorded in Zero-Magnesium
 ACSF (sodium chloride 125 mM, potassium chloride 5 mM, sodium bicarbonate
 26 mM, sodium phosphate monobasic 1.25 mM, dextrose 10 mM, calcium
 chloride 2 mM) containing either 0.1% DMSO (vehicle control), or 0.1% DMSO
 and 100 µM GiGA1. Recordings were performed at 32° C.
 Each slice was placed on a 4 x 4 mm, orthogonal array of 96
 penetrating microelectrodes (10 x 10 arrangement, with 4 corner reference
 electrodes), each 1 mm in length (Blackrock Neurotech Inc., Salt Lake
 City, UT). The slices were positioned such that electrodes covered cortex
 (including tumor, if present) as well as subcortical regions. Signals were
 continuously acquired on a CerePlex Direct acquisition system with digital
 preamplifier (Blackrock Neurotech Inc., Salt Lake City, UT) at 30 kHz,
 with 16-bit precision and a range of +/− 8 mV.
 <em>Calcium Imaging</em> Images
 were acquired using an upright Leica DM LFS microscope, with a 2.5x/0.07NA
 Leica objective and an I3 fluorescence filter cube (Leica Microsystems,
 Wetzlar, Germany). Tumor-bearing slices from Thy1-GCaMP6f transgenic mice
 were excited at 450-490 nm. Images were recorded using an Andor Zyla Plus
 sCMOS 4.2 MP camera (Oxford Instruments, Abingdon, UK), at 50 frames per
 second and a resolution of 1024 x 1024 pixels.
 <em>Experimental Drugs</em> GiGA1
 was provided courtesy of the National Center for Advancing Translational
 Sciences (NCATS), National Institutes of Health (NIH). GiGA1 powder was
 reconstituted in DMSO at 100 mM, aliquoted, and stored at -20° C. Prior to
 each experiment an aliquot was diluted 1:1000 in ACSF, for a final
 concentration of 100 µM GiGA1 and 0.1% DMSO.
 <em>Data Analysis</em> All
 analyses were performed in MATLAB versions R2019a, R2022a or R2024a using
 published libraries including NSxFile
 (https://github.com/edmerix/NSxFile), NeuroClass
 (https://github.com/edmerix/NeuroClass); and custom scripts
 (https://github.com/rrifkin/RAR_MEA_GECI).
 <em>Local Field Potentials (LFP)</em>
 Raw multi-electrode array data was symmetrically band-pass
 filtered (2-50 Hz, 1024<sup>th</sup> order, window-based FIR1
 filter using MATLAB) and down-sampled to 2000 Hz. LFP data were visually
 analyzed to remove time periods and channels with excessive artifact.
 Channels for which the electrode was not contacting the slice were also
 removed. Additionally, for paired, ‘per-channel’ analyses, inactive
 channels (those with zero definite epileptiform discharges) were excluded.
 ‘Line-length’ was calculated from the 2-50 Hz LFP. ‘Peak Amplitude’ was
 determined by finding local maxima and minima with an absolute value ≥ 4
 standard deviations from the mean. ‘Peritumoral’ electrodes were defined
 as those located within the tumor, or within a margin of two electrodes
 (i.e. 800 µm) of the tumor, based on light microscopy.    
 <em>Multi-Unit Activity (MUA)</em>
 Raw multi-electrode array data was symmetrically band-pass
 filtered (500-5000 Hz, 1024<sup>th</sup> order, window-based
 FIR1 filter using MATLAB). Spikes within each channel were detected using
 a voltage threshold of 4.5 σ, where σ = median(|x|/0.6745) and x is the
 MUA of that channel. These putative spikes were subjected to several
 quality control measures. Spikes with no calculable full-width at
 half-maximum (FWHM), spikes with a Mahalanobis distance in principal
 component space greater than would be expected less than 1% of the time,
 and spikes with voltages not within 3 standard deviations of any unit in a
 library of 4,772 manually sorted single units, were deleted. For those
 remaining, the FWHM was compared to a Gaussian mixture model fitted to the
 FWHM of action potentials from human microelectrode array recordings. From
 this, each spike was assigned a probability of belonging to the
 fast-spiking interneuron or pyramidal cell populations, and these values
 were used to calculate a probabilistic instantaneous firing rate for each
 population. Spike-triggered averaging was performed
 using spikes across all electrodes categorized as either fast-spiking
 interneuron (IN) or pyramidal cell (PC) by the above method. In addition
 to filtering for false-positives as described above, spikes occurring at
 the same time point were deleted, as they likely represented electrical
 noise. PC spikes occurring within +/- 20 ms of an IN spike were counted in
 2 ms bins. PC spikes were normalized to mean PC firing rate and total
 number of IN spikes, to account for the effect of GiGA1 on overall firing
 as well as intrinsic differences between slices. Within each 2 ms bin,
 DMSO vs. GiGA1 were compared using Wilcoxon Signed-Rank test, and these p
 values were corrected using the Bonferroni-Holm method.
 <em>Calcium Imaging</em> Circular
 Regions of Interest (ROI) with a radius of 140 µm were created around each
 electrode, with the exception of electrodes not in contact with the slice,
 which were excluded. The average fluorescence within each of these ROIs
 was calculated for each frame of the recording. This fluorescence was
 divided by the mean of a sliding window of 125 frames before and after.
 ‘Peak Amplitude’ was determined by finding local maximal and minima with
 an absolute value ≥ 1% above the mean. To evaluate the hypersynchrony of
 adjacent regions of tissue, the normalized fluorescence data for each ROI
 was compared to each adjacent ROI via Pearson correlation, generating an
 r-value representing the degree of synchrony (duplicate comparisons were
 avoided). The means of these r-values were compared between
 groups. <em>Statistical
 Analysis</em> Non-paired data were analyzed using
 the Wilcoxon Rank-Sum (Mann-Whitney U) test. Paired data were analyzed
 using the Wilcoxon Signed-Rank test. For multiple comparisons, the
 Bonferroni-Holm correction method was used. For paired analyses in which
 the individual channels or ROIs were the data points, outliers ≥ 3 scaled
 median absolute deviations from the median were excluded (solely to allow
 every included data point to be plotted on a meaningful scale; inclusion
 or exclusion of outliers did not impact significance). Incalculable data
 points (‘NaN’) were excluded from analyses. (Adapted
 from methods of the linked manuscript)
description: # A selective small-molecule agonist of G protein-gated
 inwardly-rectifying potassium channels reduces epileptiform activity in a
 mouse model of tumor associated epilepsy - Part 2: WT Non-Tumor MEA Data
 [https://doi.org/10.5061/dryad.4qrfj6qk2(opens](https://doi.org/10.5061/dryad.4qrfj6qk2\(opens) in new window) ## Description of the data and file structure ### WT Non-Tumor Experiment Wild-type mice were sacrificed and 400 μm slices of frontal cortex were prepared. Slices were exposed to ACSF for 10 minutes, then either Zero-Magnesium ACSF containing vehicle control (0.1% DMSO) or study drug (GiGA1 at 100 μM in 0.1% DMSO) for 30 minutes. ### Thy1-GCaMP Tumor Experiment Thy1-GCaMP Tumor MEA-GECI GiGA1 vs. Vehicle: Thy1-GCaMP6f mice were injected in right frontal cortex with mouse glioma cells. 28-35 days later they were sacrificed and 400 μm slices of frontal cortex were prepared. Slices were exposed to ACSF for 10 minutes, then Zero-Magnesium ACSF containing vehicle control (0.1% DMSO) for 20 minutes, and then the study drug (GiGA1 at 100 μM in 0.1% DMSO) for 20 minutes. ### 2022.07.25_WT_Non-Tumor_MEA_GiGA1_vs._Vehicle.txt - 2022.08.05_WT_Non-Tumor_MEA_GiGA1_vs._Vehicle.txt The text files contain a header section that describes the experiment, and then “paragraphs” that describe each experiment. Each line contains the variable name, then a colon, then the value. So it can be parsed easily by reading each line and breaking the string at the colon. The header information is relatively self-explanatory, describing the date of the experiment, the mouse line used, the date of birth (DOB) of the mouse, and the genotype (either “WT” for wild type, or “Thy1-GCaMP” for transgenic mice). Each slice “paragraph” includes the condition of the slice (Vehicle or GiGA1) and then a triad of duration (in seconds), file name, and perfusion solution for each phase of the experiment. “Bad electrodes” are ones that clearly had artifact or noise; although for analysis, I used automated techniques to detect this rather than relying on these notes. ### Code/software The electrophysiology data are stored in NS5 files, a format created by BlackRock Neurotech. They can be read using the library noted below. Details of each day's experiments are recorded in a plain text file with that day's date. Analyses were performed in MATLAB using custom scripts ([https://github.com/rrifkin/RAR_MEA_GECI(opens](https://github.com/rrifkin/RAR_MEA_GECI\(opens) in new window)) as well as other freely available software packages. The NS5 files were imported and filtered using the NSxFile library ([https://github.com/edmerix/NSxFile(opens](https://github.com/edmerix/NSxFile\(opens) in new window)) and NeuroClass library ([https://github.com/edmerix/NeuroClass(opens](https://github.com/edmerix/NeuroClass\(opens) in new window)). Specifically, the function "RAR_process_directory (input_path, include_string, exclude_string)" can be used to automatically open and process the NS5 files in the included path meeting the inclusion and exclusion criteria. The imaging data are stored as TIFF files, but can also be processed using "RAR_calcium_washin_workflow()". The locations of the regions of interest must be specified in a CSV file. This is a linked dataset. Please see Part 1: [[https://doi.org/10.5061/dryad.4qrfj6qk2](https://doi.org/10.5061/dryad.4qrfj6qk2)] Part 3: [https://doi.org/10.5061/dryad.m0cfxppd0](https://doi.org/10.5061/dryad.m0cfxppd0)