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Excitatory neurotransmission activates compartmentalized calcium transients in Müller glia without affecting lateral process motility

Citation

Tworig, Joshua; Coate, Chandler; Feller, Marla (2022), Excitatory neurotransmission activates compartmentalized calcium transients in Müller glia without affecting lateral process motility, Dryad, Dataset, https://doi.org/10.6078/D12D9F

Abstract

Neural activity has been implicated in the motility and outgrowth of glial cell processes throughout the central nervous system. Here we explore this phenomenon in Müller glia, which are specialized radial astroglia that are the predominant glial type of the vertebrate retina. Müller glia extend fine filopodia-like processes into retinal synaptic layers, in similar fashion to brain astrocytes and radial glia which exhibit perisynaptic processes. Using two-photon volumetric imaging, we found that during the second postnatal week, Müller glial processes were highly dynamic, with rapid extensions and retractions that were mediated by cytoskeletal rearrangements. During this same stage of development, retinal waves led to increases in cytosolic calcium within Müller glial lateral processes and stalks. These comprised distinct calcium compartments, distinguished by variable participation in waves, timing, and sensitivity to an M1 muscarinic acetylcholine receptor antagonist. However, we found that motility of lateral processes was unaffected by the presence of pharmacological agents that enhanced or blocked wave-associated calcium transients. Finally, we found that mice lacking normal cholinergic waves in the first postnatal week also exhibited normal Müller glial process morphology. Hence, outgrowth of Müller glial lateral processes into synaptic layers is determined by factors that are independent of neuronal activity.

Methods

This dataset includes Müller glial calcium imaging and morphological data underlying all figures for the referenced manuscript, in which details about data acquisition and processing can be found in the 'Materials and Methods' section.

For Figures 1 and 5, morphological measurements were obtained from two-photon volumetric images of membrane-tagged Müller glial processes in live flat mount retina. All morphological images were band pass filtered in XY space to reduce noise, corrected for 3D drift and photobleaching, and time course movies were collapsed into a single temporally color-coded image stack for subsequent quantification. For each field of view (FOV), processes were counted and grouped into one of 7 categories depending on whether motility occurred. Process counts and their associated Z-planes were then imported into MATLAB, where Z-planes for all counts within each FOV were normalized from 0 to 1 to enable comparison across cells and experiments. This morphological dataset is found in "motilityDataWithZ.mat". 

For Figures 2-4, two-photon calcium imaging was performed on live flat mount retina in which Müller glia were labeled with a genetically encoded or organic calcium indicator. Following motion correction, regions of interest (ROIs) were semiautomatically placed over glial stalks and lateral processes using a segmentation algorithm. Average fluorescence intensity within these ROIs was normalized and smoothed using a median filter. Traces were Z scored, and a threshold Z score of 3 was used to define calcium transients, which were then further defined as wave-associated if they occurred within 3 seconds of the peak of a wave-associated EPSC. Using MATLAB scripts, measurements including proportion of ROIs participating in retinal waves, calcium transient amplitudes, and calcium transient latencies between stalks and lateral processes were obtained and can be found in "caImagingData.mat". This dataset also contains data from simultaneous electrophysiological recording of retinal waves, including EPSC amplitude and inter-wave interval.

For Figure 6, Müller glial morphology was visualized by filling individual cells with fluorescent dye and obtaining volumetric two-photon images of dye-filled cells. Cells were traced using FIJI's Simple Neurite Tracer plugin, and measurements including number of tips, total process length, total branch points, and primary branches from stalk were derived from traced paths. Paths were converted into binarized skeletons and registered to correct for XY displacement of the stalk between the GCL and INL. Sholl analysis was performed using concentric rings spaced 1 µm apart, in the XY, XZ, and YZ planes. For the XZ and YZ planes, the center of each Sholl radius was placed on the end of the stalk closest to the INL in orthogonal projections of traced cells. Sholl radii were normalized to the total IPL thickness. Convex hull area was defined as the area of the smallest convex polygon enclosing the entire skeleton in an XY maximum projection image. These measurements and Sholl analysis data are in the MATLAB structures 'fillData.mat', 'sholl_xy.mat', 'sholl_xz.mat', and sholl_yz.mat'.

MATLAB scripts were used to extract data points of interest from these datasets for subsequent computation of summary statistics. There is a separate script associated with each figure. For each figure, the underlying data to be included was compiled into a source data file (eg. "Figure 1-source data 1.csv"). R scripts referencing these source data files were used to apply statistical testing. 

Usage Notes

See README.txt for more information about datasets provided. These should be loaded into MATLAB, and then to extract relevant data, run the MATLAB script(s) associated with each figure.

Statistical analyses may be run using the enclosed R scripts. These R scripts reference the source data which was extracted from the main .mat morphology or calcium imaging datasets. This source data is also included.

Funding

National Science Foundation, Award: DGE 1752814

National Institutes of Health, Award: R01EY019498

National Institutes of Health, Award: R01EY013528

National Institutes of Health, Award: P30EY003176