Protocol for functional screening of CFTR-targeted genetic therapies in patient-derived organoids using DETECTOR deep-learning-based analysis

Protocol for functional screening of CFTR-targeted genetic therapies in patient-derived organoids using DETECTOR deep-learning-based analysis

Summary: Here, we present a protocol for the rapid functional screening of gene editing and addition strategies in patient-derived organoids using the deep-learning-based tool DETECTOR (detection of targeted editing of cystic fibrosis transmembrane conductance regulator [CFTR] in organoids). We desc...

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Bibliographic Details
Main Authors: Mattijs Bulcaen, Ronald B. Liu, Kasper Gryspeert, Sam Thierie, Anabela S. Ramalho, François Vermeulen, Xavier Casadevall I Solvas, Marianne S. Carlon
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:STAR Protocols
Subjects:
CRISPR
organoids
computer sciences
Online Access:http://www.sciencedirect.com/science/article/pii/S2666166724007585
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Summary:Summary: Here, we present a protocol for the rapid functional screening of gene editing and addition strategies in patient-derived organoids using the deep-learning-based tool DETECTOR (detection of targeted editing of cystic fibrosis transmembrane conductance regulator [CFTR] in organoids). We describe steps for wet-lab experiments, image acquisition, and CFTR function analysis by DETECTOR. We also detail procedures for applying pre-trained models and training custom models on new customized datasets.For complete details on the use and execution of this protocol, refer to Bulcaen et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.
ISSN:2666-1667

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