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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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | STAR Protocols |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666166724007585 |
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| author | Mattijs Bulcaen Ronald B. Liu Kasper Gryspeert Sam Thierie Anabela S. Ramalho François Vermeulen Xavier Casadevall I Solvas Marianne S. Carlon |
| author_facet | Mattijs Bulcaen Ronald B. Liu Kasper Gryspeert Sam Thierie Anabela S. Ramalho François Vermeulen Xavier Casadevall I Solvas Marianne S. Carlon |
| author_sort | Mattijs Bulcaen |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-2b2d918e0a9043b29aa7532c70991044 |
| institution | Kabale University |
| issn | 2666-1667 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | STAR Protocols |
| spelling | doaj-art-2b2d918e0a9043b29aa7532c709910442025-02-02T05:29:20ZengElsevierSTAR Protocols2666-16672025-03-0161103593Protocol for functional screening of CFTR-targeted genetic therapies in patient-derived organoids using DETECTOR deep-learning-based analysisMattijs Bulcaen0Ronald B. Liu1Kasper Gryspeert2Sam Thierie3Anabela S. Ramalho4François Vermeulen5Xavier Casadevall I Solvas6Marianne S. Carlon7Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium; Department of Chronic Diseases and Metabolism, KU Leuven, 3000 Leuven, Belgium; Corresponding authorDepartment of Biosystems, KU Leuven, 3001 Leuven, Belgium; Institute for Imaging, Data and Communication, University of Edinburgh, Edinburgh EH93JL, UK; Corresponding authorDepartment of Chronic Diseases and Metabolism, KU Leuven, 3000 Leuven, Belgium; Corresponding authorDepartment of Chronic Diseases and Metabolism, KU Leuven, 3000 Leuven, BelgiumDepartment of Development and Regeneration, KU Leuven, 3000 Leuven, BelgiumDepartment of Development and Regeneration, KU Leuven, 3000 Leuven, Belgium; Department of Pediatrics, UZ Leuven, 3000 Leuven, BelgiumDepartment of Biosystems, KU Leuven, 3001 Leuven, BelgiumDepartment of Chronic Diseases and Metabolism, KU Leuven, 3000 Leuven, Belgium; Corresponding authorSummary: 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.http://www.sciencedirect.com/science/article/pii/S2666166724007585CRISPRorganoidscomputer sciences |
| spellingShingle | Mattijs Bulcaen Ronald B. Liu Kasper Gryspeert Sam Thierie Anabela S. Ramalho François Vermeulen Xavier Casadevall I Solvas Marianne S. Carlon Protocol for functional screening of CFTR-targeted genetic therapies in patient-derived organoids using DETECTOR deep-learning-based analysis STAR Protocols CRISPR organoids computer sciences |
| title | Protocol for functional screening of CFTR-targeted genetic therapies in patient-derived organoids using DETECTOR deep-learning-based analysis |
| title_full | Protocol for functional screening of CFTR-targeted genetic therapies in patient-derived organoids using DETECTOR deep-learning-based analysis |
| title_fullStr | Protocol for functional screening of CFTR-targeted genetic therapies in patient-derived organoids using DETECTOR deep-learning-based analysis |
| title_full_unstemmed | Protocol for functional screening of CFTR-targeted genetic therapies in patient-derived organoids using DETECTOR deep-learning-based analysis |
| title_short | Protocol for functional screening of CFTR-targeted genetic therapies in patient-derived organoids using DETECTOR deep-learning-based analysis |
| title_sort | protocol for functional screening of cftr targeted genetic therapies in patient derived organoids using detector deep learning based analysis |
| topic | CRISPR organoids computer sciences |
| url | http://www.sciencedirect.com/science/article/pii/S2666166724007585 |
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