2024年12月9日，意大利米兰大学Giuseppe Testa课题组在《自然—方法学》杂志在线发表论文。该研究表明，多重化皮层大脑类器官可用于在单细胞分辨率下纵向剖析发育特征。

据悉，在高分辨率和机制精确性下剖析人类神经生物学，需要在可扩展性上取得重大突破，因为实验设计需要涵盖多个个体，并在未来涉及人口队列。

研究人员开发并基准测试了互补策略，通过在类器官生成过程中（马赛克模型）或在单细胞RNA测序（scRNA-seq）文库制备之前（下游多重化）将来自不同多能干细胞（PSC）系的细胞汇聚，进而实现大脑类器官的多重化。

研究人员还开发了一种新的计算方法SCanSNP和共识调用来解构细胞身份，克服了当前双重细胞和低质量细胞识别中的关键问题。

研究人员验证了这两种多重化方法，用于高分辨率绘制神经发育轨迹，从而将特定个体的轨迹与遗传变异联系起来。最后，研究人员对不同多重化组合的可扩展性进行了建模，显示马赛克类器官是高通量设置中的一种有效方法。

综上所述，这一实验和计算方法的多重化套件为大脑疾病和神经多样性建模提供了高度可扩展的资源。

附：英文原文

Title: Multiplexing cortical brain organoids for the longitudinal dissection of developmental traits at single-cell resolution

Author: Caporale, Nicol, Castaldi, Davide, Rigoli, Marco Tullio, Cheroni, Cristina, Valenti, Alessia, Stucchi, Sarah, Lessi, Manuel, Bulgheresi, Davide, Trattaro, Sebastiano, Pezzali, Martina, Vitriolo, Alessandro, Lopez-Tobon, Alejandro, Bonfanti, Matteo, Ricca, Dario, Schmid, Katharina T., Heinig, Matthias, Theis, Fabian J., Villa, Carlo Emanuele, Testa, Giuseppe

Issue&Volume: 2024-12-09

Abstract: Dissecting human neurobiology at high resolution and with mechanistic precision requires a major leap in scalability, given the need for experimental designs that include multiple individuals and, prospectively, population cohorts. To lay the foundation for this, we have developed and benchmarked complementary strategies to multiplex brain organoids by pooling cells from different pluripotent stem cell (PSC) lines either during organoid generation (mosaic models) or before single-cell RNA sequencing (scRNA-seq) library preparation (downstream multiplexing). We have also developed a new computational method, SCanSNP, and a consensus call to deconvolve cell identities, overcoming current criticalities in doublets and low-quality cell identification. We validated both multiplexing methods for charting neurodevelopmental trajectories at high resolution, thus linking specific individuals’ trajectories to genetic variation. Finally, we modeled their scalability across different multiplexing combinations and showed that mosaic organoids represent an enabling method for high-throughput settings. Together, this multiplexing suite of experimental and computational methods provides a highly scalable resource for brain disease and neurodiversity modeling.

DOI: 10.1038/s41592-024-02555-5

Source: https://www.nature.com/articles/s41592-024-02555-5