State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai 200237, China.
Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.
J Zhejiang Univ Sci B. 2022 Jul 15;23(7):564-577. doi: 10.1631/jzus.B2100701.
Organoid models are used to study kidney physiology, such as the assessment of nephrotoxicity and underlying disease processes. Personalized human pluripotent stem cell-derived kidney organoids are ideal models for compound toxicity studies, but there is a need to accelerate basic and translational research in the field. Here, we developed an automated continuous imaging setup with the "read-on-ski" law of control to maximize temporal resolution with minimum culture plate vibration. High-accuracy performance was achieved: organoid screening and imaging were performed at a spatial resolution of 1.1 μm for the entire multi-well plate under 3 min. We used the in-house developed multi-well spinning device and cisplatin-induced nephrotoxicity model to evaluate the toxicity in kidney organoids using this system. The acquired images were processed via machine learning-based classification and segmentation algorithms, and the toxicity in kidney organoids was determined with 95% accuracy. The results obtained by the automated "read-on-ski" imaging device, combined with label-free and non-invasive algorithms for detection, were verified using conventional biological procedures. Taking advantage of the close-to-in vivo-kidney organoid model, this new development opens the door for further application of scaled-up screening using organoids in basic research and drug discovery.
类器官模型用于研究肾脏生理学,例如评估肾毒性和潜在疾病过程。个性化的人多能干细胞衍生的肾脏类器官是化合物毒性研究的理想模型,但需要加速该领域的基础和转化研究。在这里,我们开发了一种自动化连续成像设置,采用“随动滑雪”控制定律,以最小的培养板振动实现最大的时间分辨率。高精度性能得以实现:在 3 分钟内,以 1.1μm 的空间分辨率对整个多孔板进行类器官筛选和成像。我们使用内部开发的多井旋转装置和顺铂诱导的肾毒性模型,使用该系统评估肾脏类器官的毒性。通过基于机器学习的分类和分割算法处理采集到的图像,并以 95%的准确率确定肾脏类器官的毒性。通过自动化的“随动滑雪”成像设备获得的结果,结合用于检测的无标记和非侵入性算法,使用传统的生物学程序进行了验证。利用接近体内的肾脏类器官模型,这一新的发展为使用类器官在基础研究和药物发现中进行规模化筛选开辟了道路。