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Monitoring Intestinal Organoid-Derived Monolayer Barrier Functions with Electric Cell-Substrate Impedance Sensing (ECIS).
Ouahoud, Sarah; Giugliano, Francesca P; Muncan, Vanesa.
Afiliação
  • Ouahoud S; Tytgat Institute for Intestinal and Liver Research, Gastroenterology Endocrinology and Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
  • Giugliano FP; Tytgat Institute for Intestinal and Liver Research, Gastroenterology Endocrinology and Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
  • Muncan V; Tytgat Institute for Intestinal and Liver Research, Gastroenterology Endocrinology and Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
Bio Protoc ; 14(5): e4947, 2024 Mar 05.
Article em En | MEDLINE | ID: mdl-38464939
ABSTRACT
The measurement of transepithelial electrical resistance across confluent cell monolayer systems is the most commonly used technique to study intestinal barrier development and integrity. Electric cell substrate impedance sensing (ECIS) is a real-time, label-free, impedance-based method used to study various cell behaviors such as cell growth, viability, migration, and barrier function in vitro. So far, the ECIS technology has exclusively been performed on cell lines. Organoids, however, are cultured from tissue-specific stem cells, which better recapitulate cell functions and the heterogeneity of the parent tissue than cell lines and are therefore more physiologically relevant for research and modeling of human diseases. In this protocol paper, we demonstrate that ECIS technology can be successfully applied on 2D monolayers generated from patient-derived intestinal organoids. Key features • We present a protocol that allows the assessment of various cell functions, such as proliferation and barrier formation, with ECIS on organoid-derived monolayers. • The protocol facilitates intestinal barrier research on patient tissue-derived organoids, providing a valuable tool for disease modeling.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article