OPTICAL, FLUIDIC, AND MOLECULAR TECHNOLOGIES FOR SINGLE-CELL OMICS

摘要 干细胞分化发生在由中间细胞状态的连续体定义的复杂环境中， 分支轨迹和高度协调的监管动态。这种复杂性通常被隐藏在 总体测量，通常仅限于测量种群中标记的平均值 细胞。最近迅速出现的高通量单细胞RNA测序提供了强大的 通过测量数千个基因在细胞状态之间的表达来解决细胞状态之间的转换 大量的细胞。互补的统计工具可以处理这些大型数据集并识别 不同的细胞群基于它们的转录图谱。然而，RNA转录物的丰度不会 总是与蛋白质组成有关，有许多重要的细胞内分子，如脂质和 代谢物，不是在基因组中特定编码的。细胞的正交分子测量 国家可以为转录组分析提供强大的补充，以调查调控动态 在干细胞分化过程中。这项研究计划侧重于技术的发展，以促进 在单个细胞中进行“多染色体”测量。我们利用三种核心技术来测量单元状态 表型。我们使用DAMID来探测基因组组织和蛋白质-DNA相互作用，单细胞RNAseq 提供全转录组基因表达谱和相干拉曼成像来表征 活细胞的化学成分。微流控技术促进了这些技术和 支持对单个单元进行多模式测量。这一平台将为解剖提供一种新的方法 干细胞分化过程中的协调调控网络。我们的最终目标是开发一种工具，使所有 为了保留单细胞的空间信息和细胞背景 发育中的组织或整个有机体。

SUMMARY Stem cell differentiation takes place on a complex landscape defined by a continuum of intermediate cell states, branching trajectories, and highly coordinated regulatory dynamics. This complexity is often hidden to ensemble measurements, which are typically limited to measuring average values of markers in populations of cells. The recent and rapid emergence of high-throughput single-cell RNA sequencing has provided a powerful solution for dissecting transitions between cell states by measuring the expression of thousands of genes in large populations of cells. Complementary statistical tools can process these large data sets and identify distinct groups of cells base on their transcriptional profile. However, RNA transcript abundance does not always correlate with protein composition and there are many important intracellular molecules, like lipids and metabolites, which are not specifically encoded in the genome. Orthogonal molecular measurements of cell state could provide a powerful complement to transcriptome analysis for investigating regulatory dynamics during stem cell differentiation. This research program focuses on the development of technology to facilitate “multi-omic” measurements in single cells. We take advantage of three core technologies to measure cell state phenotypes. We use DamID to probe genome organization and protein-DNA interactions, single-cell RNAseq to provide whole-transcriptome gene expression profiling, and coherent Raman imaging to characterize the chemical composition of live cells. Microfluidic technology facilitates the integration of these techniques and enables multimodal measurement of single cells. This platform will provide a new approach for dissecting coordinated regulatory networks in differentiating stem cells. Our ultimate goal is to develop a tool to make all of these measurements in situ, in order to retain single-cell spatial information and cellular context in a developing tissue or whole organism.