Developing workflow tools for quantifying kidney regeneration post laser injury

This study introduces an automated analysis workflow to quantify kidney regeneration
over time in the developing zebrafish upon automated laser-induced injury on a screening
microscope equipped with a photomanipulation module. The screening dataset consists of
multiple time-lapse images of injured and fluorescently labelled distal pronephric tubules of
the transgenic Tg(cdh17:egfp) zebrafish line.
To overcome the lack of image analysis tools for whole-organism screening data and
to automate the quantification of kidney regeneration post photodamage, we developed a
workflow combining image-processing and data-analysis using the open-source software
tools FIJI, Ilastik and KNIME. Hence, the workflow enables the analysis
of regeneration dynamics and facilitates the identification of specimen with impaired or
enhanced regeneration.
Ultimately, we expect that workflow components can be directly applied for the
analysis of other complex timelapse datasets, and can be adapted for the quantification of
growth or migration of other fluorescently labelled tissues.