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KREAP: an automated Galaxy platform to quantify in vitro re-epithelialization kinetics
Marcela M Fernandez-Gutierrez1,2, David B H van Zessen3, Peter van Baarlen2
1TI Food and Nutrition, Nieuwe Kanaal 9-A, 6709 PA, Wageningen, The Netherlands.
We developed a new pipeline to analyze high-throughput scratch assays, enabling faster discovery of compounds that influence cell re-epithelialization. This tool simplifies complex image analysis for researchers.
Area of Science:
- Cell biology
- Bioimage analysis
- Computational biology
Background:
- In vitro scratch assays are crucial for studying re-epithelialization.
- High-throughput microscopy and image analysis have advanced scratch assay capabilities.
- Analyzing large scratch assay datasets is complex, requiring integrated software tools.
Purpose of the Study:
- To develop an automated pipeline for analyzing high-throughput scratch assay image data.
- To simplify and standardize the quantification of cell migration and proliferation in scratch assays.
- To extract biologically relevant parameters describing re-epithelialization kinetics.
Main Methods:
- Developed the kinetic re-epithelialization analysis pipeline (KREAP) within the Galaxy platform.
- Integrated freely available image analysis tools for automated segmentation and feature extraction.
- Quantified cell numbers inside and outside the scratch area over time and modeled cell infiltration kinetics.
Main Results:
- KREAP automates image processing and data extraction for high-throughput scratch assays.
- The pipeline extracts three key parameters characterizing re-epithelialization kinetics.
- Results are organized, displayed, and saved within the Galaxy environment for reproducibility.
Conclusions:
- KREAP offers an open-source, web-based solution for reproducible scratch assay analysis.
- This toolbox facilitates the discovery of compounds modulating re-epithelialization.
- KREAP supports the broader scientific community in advancing wound healing research.
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