Rembotte Leon, Beneyton Thomas, Buisson Lionel, Badon Amaury, Boyreau Adeline, Douillet Camille, Hermant Loic, Jana Anirban, Nassoy Pierre, Baret Jean-Christophe
CNRS, Univ. Bordeaux, CRPP, UMR 5031, Pessac, F-33600, France.
LP2N, Univ. Bordeaux, Talence, F-33400, France.
Adv Sci (Weinh). 2025 Mar;12(9):e2410677. doi: 10.1002/advs.202410677. Epub 2025 Jan 10.
Three-dimensional multicellular aggregates (MCAs) like organoids and spheroids have become essential tools to study the biological mechanisms involved in the progression of diseases. In cancer research, they are now widely used as in vitro models for drug testing. However, their analysis still relies on tedious manual procedures, which hinders their routine use in large-scale biological assays. Here, a novel drop millifluidic approach is introduced to screen and sort large populations containing over one thousand MCAs: ImOCAS (Image-based Organoid Cytometry and Acoustic Sorting). This system utilizes real-time image processing to detect pheno-morphological traits in MCAs. They are then encapsulated in millimetric drops, actuated on-demand using the acoustic radiation force. The performance of ImOCAS is demonstrated by sorting spheroids with uniform sizes from a heterogeneous population, and by isolating organoids from spheroids with different phenotypes. This approach lays the groundwork for high-throughput screening and high-content analysis of MCAs with controlled morphological and phenotypical properties, which promises accelerated progress in biomedical research.
类器官和球体等三维多细胞聚集体(MCAs)已成为研究疾病进展所涉及生物学机制的重要工具。在癌症研究中,它们如今被广泛用作药物测试的体外模型。然而,对它们的分析仍依赖于繁琐的手工操作,这阻碍了它们在大规模生物学检测中的常规应用。在此,引入了一种新型的液滴微流控方法来筛选和分选包含一千多个MCAs的大群体:ImOCAS(基于图像的类器官细胞计数与声学分选)。该系统利用实时图像处理来检测MCAs中的表型形态特征。然后将它们封装在毫米级液滴中,利用声辐射力按需驱动。通过从异质群体中分选大小均匀的球体,以及从具有不同表型的球体中分离类器官,证明了ImOCAS的性能。这种方法为具有可控形态和表型特性的MCAs的高通量筛选和高内涵分析奠定了基础,有望推动生物医学研究加速发展。