Quantitative analysis of zebrafish retinal morphology following chronic low-light injury using CellProfiler.

Abstract

Zebrafish possess a unique ability to regenerate their retina following injury, making them an ideal model organism for studying the cellular and molecular mechanisms underlying endogenous vision restoration. To present, researchers in the field have primarily used qualitative methods to assess retinal morphology. However, to gain a more nuanced understanding of the morphological changes over time, it is crucial to employ multifaceted analytical approaches. This study aimed to develop an unbiased, standardized method to quantitatively analyze 2D images of retinal structures using CellProfiler - a versatile, free, and open-source image analysis software. In the context of a chronic low-light model used to investigate zebrafish photoreceptor degeneration and regeneration, a pipeline module was integrated to measure various regions of the retina. Once the primary objects of interest - namely rods, cones, and cell debris - are identified using thresholding metrics, a wide variety of parameters may be measured. The data obtained provides nuanced insights into photoreceptor degeneration. Our data demonstrates the potential of CellProfiler to be a powerful open-source tool to extract valuable information from image data.