Three-dimensional organoid culture using the CellRaft microwell technology

项目摘要 有机化合物是一种3D微型组织结构，正在给体外研究带来革命性的变化。它们可以派生出来 使用干细胞或诱导多能干细胞(IPSCs)从各种物种中分离出来 或病变组织。在疾病建模中使用有机化合物已成为复制的有力方法 采用相对标准的细胞培养方法进行病理生理学研究。几乎每种组织类型现在都有一个体外培养的 有机物质相互关联。顾名思义，有机体是组织层(通常是上皮)的代表。 在生物体中具有特定功能的生物。它们通常是干细胞来源的，使它们有可能 产生在特定组织中发现的所有分化细胞类型。虽然这种灵活性允许重述 活体多细胞结构，它还需要使用具有挑战性的和手动的细胞生物学方案来 建立和维护各种类型的器官。快速建立有机培养物的障碍是 这在很大程度上是由于从单个细胞启动克隆克隆的效率较低，难以跟踪克隆生长 随着时间的推移和低效的诱导分化过程。此外，支持有机化合物的系统 培养必须允许基于时间进程的生理表型分析。细胞微系统公司拥有 开发了CellRaft技术，这是一个基于微孔阵列的平台，可以在小范围内种植单细胞 培养室，成长为克隆克隆，并使用几乎任何成像方式随着时间的推移进行跟踪。 在我们的第一阶段项目中，我们与北卡罗来纳大学的博士Scott Magness合作 教堂山利用CellRaft技术开发有机培养、分选和亚克隆方法。 细胞排序阵列以数千个用于细胞培养的微孔为特征，被用于建立干细胞- 衍生的有机培养物。在阵列上使用Matrigel允许有机化合物的三维支撑 结构，因为它们形成单个细胞。Magness博士的实验室还尝试了有机亚克隆，方法是分离出一种 从CytoSort阵列中分离出有机物，解离后重新电镀细胞形成第二代细胞 有机化合物。在第二阶段，我们将在CytoSort阵列上利用这一强大的方法来传播多个 一代又一代的有机化合物的创始人和进行分子分析，以确定谱系属性，细胞 导致包括癌症在内的各种疾病的突变类型和潜在累积。为了支持这些 经过努力，细胞微系统公司开发了3D细胞排序阵列，其特点是具有更大的微孔，以实现三个- 用于分子分析的单个有机化合物的立体培养和分离。在第二阶段，我们将开发 适用于其他有机物类型(包括神经、胰腺和肝脏)的协议，通过 3D细胞排序阵列，以及对多代有机化合物的RNA-Seq分析进行评估。这些方法 广泛适用于许多细胞和组织类型的有机化合物研究，并填补了自动化的未满足需求 在有机类工作流程中使用，同时保持与当代分子分析方法的广泛兼容性。

Project Summary Organoids are 3D mini‐tissue structures that are revolutionizing in vitro studies. They can be derived from a variety of species, using stem cells or induced pluripotent stem cells (iPSCs) isolated from either normal or diseased tissues. The use of organoids in disease modeling has become a powerful method to replicate pathophysiology using relatively standard cell culture methods. Virtually every tissue type now has an in vitro organoid correlate. As the name implies, organoids are representations of tissue layers (typically epithelium) that have a specific function in an organism. They are often stem cell derived, giving them the potential to produce all the differentiated cell types found in a given tissue. While this flexibility allows recapitulation of in vivo multicellular structures, it also necessitates the use of challenging and manual cell biology protocols to establish and maintain various types of organoid. Roadblocks to rapidly establishing organoid cultures are largely due to the low efficiency of initiating a clonal colony from a single cell, difficulty tracking colony growth over time and inefficient induction of differentiation processes. In addition, systems supporting organoid culture must allow for time‐course based analysis of physiological phenotypes. Cell Microsystems has developed the CellRaft Technology, a microwell array‐based platform where single cells can be seeded in small culture chambers, grown into clonal colonies and tracked over time using virtually any imaging modality. During our Phase I program, we collaborated with Scott Magness, PhD of the University of North Carolina at Chapel Hill to develop organoid culture, sorting and subcloning methods using the CellRaft Technology. CytoSort Arrays, which feature thousands of microwells for cell culture, were employed to establish stem cell‐ derived organoid cultures. The use of Matrigel on the arrays allowed for three‐dimensional support of organoid structures as they form single cells. Dr. Magness' lab also attempted organoid subcloning by isolating a single organoid from the CytoSort Array and re‐plating the cells after dissociation to form second‐generation organoids. In Phase II, we will leverage this powerful method on CytoSort Arrays to propagate multiple generations of organoids from a founder and undertake molecular analysis to identify lineage properties, cell types and potential accumulation of mutations leading to various disease, including cancer. To support these efforts, Cell Microsystems has developed the 3D CytoSort Array, featuring larger microwells to enable three‐ dimensional culture and isolation of individual organoids for molecular analysis. In Phase II we will develop protocols for other organoid types including neural, pancreatic and hepatic, optimize the overall workflow with the 3D CytoSort Array, as well as evaluate RNA‐Seq analysis of multiple organoid generations. These methods are broadly applicable to organoid research in many cell and tissue types and fill an unmet need for automation in organoid workflows while retaining broad compatibility with contemporary molecular analysis methods.