Methodologies for analysis of patterning in the mouse RPE sheet

PURPOSE: Our goal was to optimize procedures for assessing shapes, sizes, and other quantitative metrics of retinal pigment epithelium (RPE) cells and contact- and noncontact-mediated cell-to-cell interactions across a large series of flatmount RPE images. METHODS: The two principal methodological advances of this study were optimization of a mouse RPE flatmount preparation and refinement of open-access software to rapidly analyze large numbers of flatmount images. Mouse eyes were harvested, and extra-orbital fat and muscles were removed. Eyes were fixed for 10 min, and dissected by puncturing the cornea with a sharp needle or a stab knife. Four radial cuts were made with iridectomy scissors from the puncture to near the optic nerve head. The lens, iris, and the neural retina were removed, leaving the RPE sheet exposed. The dissection and outcomes were monitored and evaluated by video recording. The RPE sheet was imaged under fluorescence confocal microscopy after staining for ZO-1 to identify RPE cell boundaries. Photoshop, Java, Perl, and Matlab scripts, as well as CellProfiler, were used to quantify selected parameters. Data were exported into Excel spreadsheets for further analysis. RESULTS: A simplified dissection procedure afforded a consistent source of images that could be processed by computer. The dissection and flatmounting techniques were illustrated in a video recording. Almost all of the sheet could be routinely imaged, and substantial fractions of the RPE sheet (usually 20–50% of the sheet) could be analyzed. Several common technical problems were noted and workarounds developed. The software-based analysis merged 25 to 36 images into one and adjusted settings to record an image suitable for large-scale identification of cell-to-cell boundaries, and then obtained quantitative descriptors of the shape of each cell, its neighbors, and interactions beyond direct cell–cell contact in the sheet. To validate the software, human- and computer-analyzed results were compared. Whether tallied manually or automatically with software, the resulting cell measurements were in close agreement. We compared normal with diseased RPE cells during aging with quantitative cell size and shape metrics. Subtle differences between the RPE sheet characteristics of young and old mice were identified. The IRBP(−/−) mouse RPE sheet did not differ from C57BL/6J (wild type, WT), suggesting that IRBP does not play a direct role in maintaining the health of the RPE cell, while the slow loss of photoreceptor (PhR) cells previously established in this knockout does support a role in the maintenance of PhR cells. Rd8 mice exhibited several measurable changes in patterns of RPE cells compared to WT, suggesting a slow degeneration of the RPE sheet that had not been previously noticed in rd8. CONCLUSIONS: An optimized dissection method and a series of programs were used to establish a rapid and hands-off analysis. The software-aided, high-sampling-size approach performed as well as trained human scorers, but was considerably faster and easier. This method allows tens to hundreds of thousands of cells to be analyzed, each with 23 metrics. With this combination of dissection and image analysis of the RPE sheet, we can now analyze cell-to-cell interactions of immediate neighbors. In the future, we may be able to observe interactions of second, third, or higher ring neighbors and analyze tension in sheets, which might be expected to deviate from normal near large bumps in the RPE sheet caused by druse or when large frank holes in the RPE sheet are observed in geographic atrophy. This method and software can be readily applied to other aspects of vision science, neuroscience, and epithelial biology where patterns may exist in a sheet or surface of cells.