Production of Phenotypically Uniform Human Cerebral Organoids from Pluripotent Stem Cells
Bibliographic record
Abstract
Recent advances in stem cell technology have allowed researchers to generate 3D cerebral organoids (COs) from human pluripotent stem cells (hPSCs). Indeed, COs have provided an unprecedented opportunity to model the developing human brain in a 3D context, and in turn, are suitable for addressing complex neurological questions by leveraging advancements in genetic engineering, high resolution microscopy, and tissue transcriptomics. However, the use of this model is limited by substantial variations in the overall morphology and cellular composition of organoids derived from the same pluripotent cell line. To address these limitations, we established a robust, high-efficiency protocol for the production of consistent COs by optimizing the initial phase of embryoid body (EB) formation and neural induction. Using this protocol, COs can be reproducibly generated with a uniform size, shape, and cellular composition across multiple batches. Furthermore, organoids that developed over extended periods of time (3–6 months) showed the establishment of relatively mature features, including electrophysiologically active neurons, and the emergence of oligodendrocyte progenitors. Thus, this platform provides a robust experimental model that can be used to study human brain development and associated disorders.Graphic abstract:Overview of cerebral organoid development from pluripotent stem cells, [摘要]在干细胞技术的最新进展已经使研究人员能够产生3D脑类器官由人多能干细胞（（COS）hPSCs ）。事实上，COS提供了一个前所未有的机会，发展人的大脑在3D场景模型，并反过来，适用于通过利用在进步，基因工程，高分辨率显微镜处理复杂的神经系统的问题，并组织转录。然而，在U SE 该模型的模型受到源自同一多能细胞系的类器官的整体形态和细胞组成的实质性变化的限制。为了解决这些限制，我们建立了坚固的，高-通过优化的初始阶段用于生产相一致的COS效率协议胚状体（EB）形成和神经诱导。使用该协议，采购员可以重复地与产生一个均匀的尺寸，形状，以及跨多个批次的细胞组合物。˚F urthermore，类器官的是发展了延长的时间段（3 - 6个月）显示建立的相对成熟的功能，包括电生理学活性的神经元，少突胶质细胞和祖细胞的产生。因此，该平台提供了可用于研究人脑发育和相关疾病的强大实验模型。图形摘要：多能干细胞对脑类器官发育的概述[背景技术]在最新进展在体外从人多能干细胞（衍生3D脑类器官（COS）的发展hPSCs ）提供了一个前所未有的机会，在实验上易处理的系统中的显影人脑和相关的复杂疾病的模型。事实上，这种做法已经允许研究人员研究早期大脑发育和变化的各种人类神经系统疾病相关的后果，如阿尔茨海默氏症，失明，孤独症谱系障碍（ASD） ，和寨卡病毒感染（兰开斯特和Knoblich，2014B; Quadrato等等人，2016；Di和Kriegstein，2017； Huch等人，2017；Amin和Paşca ，2018；Rossi等人，2018 ；Chen等人，2019）。此外，几个研究小组已将CO应用于研究和建立人类脑癌的临床前模型，例如多形性胶质母细胞瘤（Drost和Clevers ，2018; Linkous等，2018）。在RECE NT年，许多协议都出现以促进开发区域特定的-通过控制下层的细胞信号与外源性生长因子和小分子抑制剂的途径，以指导细胞命运变化的类器官日趋成熟的CO （兰开斯特等人，2013; Mariani等人，2015; Jo等人，2016; Qian等人，2016; Birey等人，2017; Quadrato等人，2017; Watanabe等人，2017; Pollen等人，2019; Velasco等人，2019； Yoon等人，2019）。但是，由于人类全脑类器官大部分是由内在的自我模式产生的，并且不依赖于可控的外源因素，因此随机分化通常会导致细胞多样性，这种现象随着扩大的培养而得以扩大。不幸的是，使用全脑分化平台可以得到次单独的组织体之间的相当大的变异erefore限制这些狱警的实用程序，用于研究疾病机制或潜在疗法的发展。在这里，我们描述了可靠的协议，可有效且可重复地生成成熟，统一的人类CO（图1）。通过优化已建立的协议，用于创建的自图案化全脑类器官（兰开斯特和Knoblich，2014A;兰开斯特等人，2013） ，我们成功地产生具有可重现的细胞类型的组合物在表型均一前脑类器官。图1.从多能干细胞生成人CO的已开发方法的概述。
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".