Friedrich Miescher Institute for Biomedical Research (FMI), Maulbeerstrasse 66, 4058, Basel, Switzerland.
University of Basel, Petersplatz 1, 4001, Basel, Switzerland.
Exp Mol Med. 2021 Oct;53(10):1495-1502. doi: 10.1038/s12276-021-00641-8. Epub 2021 Oct 18.
Image-based phenotypic screening relies on the extraction of multivariate information from cells cultured under a large variety of conditions. Technical advances in high-throughput microscopy enable screening in increasingly complex and biologically relevant model systems. To this end, organoids hold great potential for high-content screening because they recapitulate many aspects of parent tissues and can be derived from patient material. However, screening is substantially more difficult in organoids than in classical cell lines from both technical and analytical standpoints. In this review, we present an overview of studies employing organoids for screening applications. We discuss the promises and challenges of small-molecule treatments in organoids and give practical advice on designing, running, and analyzing high-content organoid-based phenotypic screens.
基于图像的表型筛选依赖于从在大量不同条件下培养的细胞中提取多变量信息。高通量显微镜技术的进步使在越来越复杂和具有生物学相关性的模型系统中进行筛选成为可能。为此,类器官在高内涵筛选中具有很大的潜力,因为它们可以再现母体组织的许多方面,并且可以从患者材料中获得。然而,从技术和分析的角度来看,与经典的细胞系相比,在类器官中进行筛选要困难得多。在这篇综述中,我们介绍了利用类器官进行筛选应用的研究概述。我们讨论了小分子处理在类器官中的应用前景和挑战,并就设计、运行和分析基于高内涵类器官的表型筛选提供了实用建议。