An open-source high-content analysis workflow for CFTR function measurements using the forskolin-induced swelling assay
Abstract Motivation The forskolin-induced swelling (FIS) assay has become the preferential assay to predict the efficacy of approved and investigational CFTR-modulating drugs for individuals with cystic fibrosis (CF). Currently, no standardized quantification method of FIS data exists thereby hamper...
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Published in | Bioinformatics Vol. 36; no. 24; pp. 5686 - 5694 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Oxford University Press
05.04.2021
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Online Access | Get full text |
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Summary: | Abstract
Motivation
The forskolin-induced swelling (FIS) assay has become the preferential assay to predict the efficacy of approved and investigational CFTR-modulating drugs for individuals with cystic fibrosis (CF). Currently, no standardized quantification method of FIS data exists thereby hampering inter-laboratory reproducibility.
Results
We developed a complete open-source workflow for standardized high-content analysis of CFTR function measurements in intestinal organoids using raw microscopy images as input. The workflow includes tools for (i) file and metadata handling; (ii) image quantification and (iii) statistical analysis. Our workflow reproduced results generated by published proprietary analysis protocols and enables standardized CFTR function measurements in CF organoids.
Availability and implementation
All workflow components are open-source and freely available: the htmrenamer R package for file handling https://github.com/hmbotelho/htmrenamer; CellProfiler and ImageJ analysis scripts/pipelines https://github.com/hmbotelho/FIS_image_analysis; the Organoid Analyst application for statistical analysis https://github.com/hmbotelho/organoid_analyst; detailed usage instructions and a demonstration dataset https://github.com/hmbotelho/FIS_analysis. Distributed under GPL v3.0.
Supplementary information
Supplementary data are available at Bioinformatics online. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 USDOE Office of Nuclear Energy (NE), Nuclear Fuel Cycle and Supply Chain |
ISSN: | 1367-4803 1460-2059 1367-4811 |
DOI: | 10.1093/bioinformatics/btaa1073 |