类有机物
微流控
表征(材料科学)
纳米技术
小学(天文学)
化学
材料科学
细胞生物学
生物
物理
天文
作者
Wanlong Wang,Yongde Cai,Xiaoyong Dai,Haowei Yang,Davit Khutsishvili,Jiawei Li,Yu Zhu,Jinmin Wang,Yan Xiu,Zitian Wang,Shaohua Ma
出处
期刊:
[Cold Spring Harbor Laboratory]
日期:2025-07-16
标识
DOI:10.1101/2025.07.10.664241
摘要
Abstract Organoid technology offers a powerful platform for modeling human tissues, studying disease mechanisms, and developing personalized therapies. However, widespread clinical application is hindered by challenges in scalability, reproducibility, and the handling of ultra-small tissue samples typical of clinical biopsies. Here, we present a comprehensive and automated protocol for the formulation and characterization of microfluidic droplet-engineered organoids (DEOs) derived from primary tissue samples. This protocol integrates 3 key stages: (1) Extraction and purification of viable primary cells from ultra-small tissue specimens using the small-Tissue Extraction Device (sTED); (2) High-throughput fabrication of uniform cell-laden microspheres using an integrated microfluidic bioprinter (OrgFab), capable of generating over 100 organoids from just 10 μL of bioink; and (3) Rapid organoid characterization using lamination-based processing for single-cell analysis while preserving spatial context. The automated workflow minimizes manual intervention, reducing variability and enhancing reproducibility, making it suitable for high-throughput applications such as drug screening and disease modeling. Our method allows for the generation of patient-derived organoids that closely mimic the native tissue microenvironment, including diverse cell types and structural features, within a significantly reduced timeframe. This 3 stage protocol enhances the use of organoids in personalized medicine by enabling the rapid assessment of drug efficacy in patient-specific models. Here, the integration of advanced techniques supports existing organoid protocols, providing a valuable resource for researchers and clinicians seeking to improve patient outcomes through more efficient and precise organoid-based applications.
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