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Methodologies for analysis of patterning in the mouse RPE sheet.

Jeffrey H Boatright1, Nupur Dalal1, Micah A Chrenek1

  • 1Department of Ophthalmology, Emory University, Atlanta, GA.

Molecular Vision
|January 17, 2015
PubMed
Summary

This study optimized mouse retinal pigment epithelium (RPE) flatmount preparation and developed open-access software for rapid, large-scale analysis of RPE cell metrics and interactions. The new method is faster and easier than manual analysis, enabling high-throughput studies in vision science.

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Area of Science:

  • Ophthalmology
  • Cell Biology
  • Image Analysis

Background:

  • Retinal pigment epithelium (RPE) cell morphology and interactions are crucial for retinal health.
  • Quantitative analysis of RPE cells in large image datasets is challenging with traditional methods.

Purpose of the Study:

  • To optimize procedures for assessing quantitative metrics of RPE cells and their interactions.
  • To develop a rapid, high-throughput analysis method for flatmount RPE images.

Main Methods:

  • Optimized mouse RPE flatmount preparation involving eye dissection and RPE sheet isolation.
  • Developed open-access software using Photoshop, Java, Perl, Matlab, and CellProfiler for image analysis.
  • Validated software by comparing automated results with manual measurements.

Main Results:

  • A simplified dissection yielded consistent images for computer processing.
  • Software successfully merged images and quantified RPE cell shape, neighbors, and interactions.
  • Automated analysis closely agreed with manual scoring and identified subtle age-related RPE changes and differences in disease models (IRBP(-/-), Rd8).

Conclusions:

  • Optimized dissection and software enable rapid, hands-off analysis of RPE sheets with high throughput.
  • The method is faster, easier, and as accurate as human scorers for analyzing tens to hundreds of thousands of cells.
  • This approach is applicable to various fields studying cellular patterns in sheets or surfaces.