Department of Pediatric Respiratory Medicine, Wilhelmina Children's Hospital, University Medical Center, Utrecht University, 3584 EA, Utrecht, The Netherlands.
Regenerative Medicine Utrecht, University Medical Center, Utrecht University, 3584 CT, Utrecht, The Netherlands.
Commun Biol. 2024 Mar 13;7(1):319. doi: 10.1038/s42003-024-05966-4.
Epithelial ion and fluid transport studies in patient-derived organoids (PDOs) are increasingly being used for preclinical studies, drug development and precision medicine applications. Epithelial fluid transport properties in PDOs can be measured through visual changes in organoid (lumen) size. Such organoid phenotypes have been highly instrumental for the studying of diseases, including cystic fibrosis (CF), which is characterized by genetic mutations of the CF transmembrane conductance regulator (CFTR) ion channel. Here we present OrgaSegment, a MASK-RCNN based deep-learning segmentation model allowing for the segmentation of individual intestinal PDO structures from bright-field images. OrgaSegment recognizes spherical structures in addition to the oddly-shaped organoids that are a hallmark of CF organoids and can be used in organoid swelling assays, including the new drug-induced swelling assay that we show here. OrgaSegment enabled easy quantification of organoid swelling and could discriminate between organoids with different CFTR mutations, as well as measure responses to CFTR modulating drugs. The easy-to-apply label-free segmentation tool can help to study CFTR-based fluid secretion and possibly other epithelial ion transport mechanisms in organoids.
越来越多的基于患者来源类器官（PDO）的上皮离子和液体转运研究被用于临床前研究、药物开发和精准医疗应用。可以通过类器官（腔室）大小的视觉变化来测量 PDO 中的上皮液体转运特性。这种类器官表型对于研究疾病非常有帮助，包括囊性纤维化（CF），其特征是 CF 跨膜电导调节剂（CFTR）离子通道的基因突变。在这里，我们介绍了基于 MASK-RCNN 的深度学习分割模型 OrgaSegment，它允许从明场图像中分割单个肠 PDO 结构。OrgaSegment 除了识别具有 CF 类器官特征的奇异形状的类器官外，还可以识别球形结构，并且可以用于类器官肿胀测定，包括我们在这里展示的新的药物诱导肿胀测定。OrgaSegment 能够轻松定量类器官肿胀，并能够区分具有不同 CFTR 突变的类器官，以及测量对 CFTR 调节药物的反应。这种易于应用的无标签分割工具可以帮助研究基于 CFTR 的液体分泌，以及可能在类器官中的其他上皮离子转运机制。
