KREAP

An automated Galaxy platform to quantify in vitro re-epithelialization kinetics

Marcela M. Fernandez-Gutierrez, David B.H. van Zessen, Peter van Baarlen, Michiel Kleerebezem, Andrew P. Stubbs*

*Corresponding author for this work

Research output: Contribution to journalLetterAcademicpeer-review

Abstract

Background: In vitro scratch assays have been widely used to study the influence of bioactive substances on the processes of cell migration and proliferation that are involved in re-epithelialization. The development of high-throughput microscopy and image analysis has enabled scratch assays to become compatible with high-throughput research. However, effective processing and in-depth analysis of such high-throughput image datasets are far from trivial and require integration of multiple image processing and data extraction software tools. Findings: We developed and implemented a kinetic re-epithelialization analysis pipeline (KREAP) in Galaxy. The KREAP toolbox incorporates freely available image analysis tools and automatically performs image segmentation and feature extraction of each image series, followed by automatic quantification of cells inside and outside the scratched area over time. The enumeration of infiltrating cells over time is modeled to extract three biologically relevant parameters that describe re-epithelialization kinetics. The output of the tools is organized, displayed, and saved in the Galaxy environment for future reference. Conclusions: The KREAP toolbox in Galaxy provides an open-source, easy-to-use, web-based platform for reproducible image processing and data analysis of high-throughput scratch assays. The KREAP toolbox could assist a broad scientific community in the discovery of compounds that are able to modulate re-epithelialization kinetics.

Original languageEnglish
Article numbergiy078
JournalGigaScience
Volume7
Issue number7
DOIs
Publication statusPublished - 1 Jul 2018

Fingerprint

Galaxies
Re-Epithelialization
Pipelines
Kinetics
Throughput
Assays
Image analysis
Image processing
Image segmentation
In Vitro Techniques
Feature extraction
Microscopic examination
Cell Movement
Microscopy
Software
Cell Proliferation
Processing

Keywords

  • Cell migration
  • Galaxy
  • High-throughput
  • Image analysis
  • Modeling
  • Re-epithelialization
  • Scratch assay
  • Workflow
  • Wound healing

Cite this

@article{82ff0f4e2a2b4cb5920369142e528597,
title = "KREAP: An automated Galaxy platform to quantify in vitro re-epithelialization kinetics",
abstract = "Background: In vitro scratch assays have been widely used to study the influence of bioactive substances on the processes of cell migration and proliferation that are involved in re-epithelialization. The development of high-throughput microscopy and image analysis has enabled scratch assays to become compatible with high-throughput research. However, effective processing and in-depth analysis of such high-throughput image datasets are far from trivial and require integration of multiple image processing and data extraction software tools. Findings: We developed and implemented a kinetic re-epithelialization analysis pipeline (KREAP) in Galaxy. The KREAP toolbox incorporates freely available image analysis tools and automatically performs image segmentation and feature extraction of each image series, followed by automatic quantification of cells inside and outside the scratched area over time. The enumeration of infiltrating cells over time is modeled to extract three biologically relevant parameters that describe re-epithelialization kinetics. The output of the tools is organized, displayed, and saved in the Galaxy environment for future reference. Conclusions: The KREAP toolbox in Galaxy provides an open-source, easy-to-use, web-based platform for reproducible image processing and data analysis of high-throughput scratch assays. The KREAP toolbox could assist a broad scientific community in the discovery of compounds that are able to modulate re-epithelialization kinetics.",
keywords = "Cell migration, Galaxy, High-throughput, Image analysis, Modeling, Re-epithelialization, Scratch assay, Workflow, Wound healing",
author = "Fernandez-Gutierrez, {Marcela M.} and {van Zessen}, {David B.H.} and {van Baarlen}, Peter and Michiel Kleerebezem and Stubbs, {Andrew P.}",
year = "2018",
month = "7",
day = "1",
doi = "10.1093/gigascience/giy078",
language = "English",
volume = "7",
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KREAP : An automated Galaxy platform to quantify in vitro re-epithelialization kinetics. / Fernandez-Gutierrez, Marcela M.; van Zessen, David B.H.; van Baarlen, Peter; Kleerebezem, Michiel; Stubbs, Andrew P.

In: GigaScience, Vol. 7, No. 7, giy078, 01.07.2018.

Research output: Contribution to journalLetterAcademicpeer-review

TY - JOUR

T1 - KREAP

T2 - An automated Galaxy platform to quantify in vitro re-epithelialization kinetics

AU - Fernandez-Gutierrez, Marcela M.

AU - van Zessen, David B.H.

AU - van Baarlen, Peter

AU - Kleerebezem, Michiel

AU - Stubbs, Andrew P.

PY - 2018/7/1

Y1 - 2018/7/1

N2 - Background: In vitro scratch assays have been widely used to study the influence of bioactive substances on the processes of cell migration and proliferation that are involved in re-epithelialization. The development of high-throughput microscopy and image analysis has enabled scratch assays to become compatible with high-throughput research. However, effective processing and in-depth analysis of such high-throughput image datasets are far from trivial and require integration of multiple image processing and data extraction software tools. Findings: We developed and implemented a kinetic re-epithelialization analysis pipeline (KREAP) in Galaxy. The KREAP toolbox incorporates freely available image analysis tools and automatically performs image segmentation and feature extraction of each image series, followed by automatic quantification of cells inside and outside the scratched area over time. The enumeration of infiltrating cells over time is modeled to extract three biologically relevant parameters that describe re-epithelialization kinetics. The output of the tools is organized, displayed, and saved in the Galaxy environment for future reference. Conclusions: The KREAP toolbox in Galaxy provides an open-source, easy-to-use, web-based platform for reproducible image processing and data analysis of high-throughput scratch assays. The KREAP toolbox could assist a broad scientific community in the discovery of compounds that are able to modulate re-epithelialization kinetics.

AB - Background: In vitro scratch assays have been widely used to study the influence of bioactive substances on the processes of cell migration and proliferation that are involved in re-epithelialization. The development of high-throughput microscopy and image analysis has enabled scratch assays to become compatible with high-throughput research. However, effective processing and in-depth analysis of such high-throughput image datasets are far from trivial and require integration of multiple image processing and data extraction software tools. Findings: We developed and implemented a kinetic re-epithelialization analysis pipeline (KREAP) in Galaxy. The KREAP toolbox incorporates freely available image analysis tools and automatically performs image segmentation and feature extraction of each image series, followed by automatic quantification of cells inside and outside the scratched area over time. The enumeration of infiltrating cells over time is modeled to extract three biologically relevant parameters that describe re-epithelialization kinetics. The output of the tools is organized, displayed, and saved in the Galaxy environment for future reference. Conclusions: The KREAP toolbox in Galaxy provides an open-source, easy-to-use, web-based platform for reproducible image processing and data analysis of high-throughput scratch assays. The KREAP toolbox could assist a broad scientific community in the discovery of compounds that are able to modulate re-epithelialization kinetics.

KW - Cell migration

KW - Galaxy

KW - High-throughput

KW - Image analysis

KW - Modeling

KW - Re-epithelialization

KW - Scratch assay

KW - Workflow

KW - Wound healing

U2 - 10.1093/gigascience/giy078

DO - 10.1093/gigascience/giy078

M3 - Letter

VL - 7

JO - GigaScience

JF - GigaScience

SN - 2047-217X

IS - 7

M1 - giy078

ER -