Image-Seq: A high-density microfluidic trap array for single cell transcriptome analysis coupled with image based phenotyping

图像序列：用于单细胞转录组分析的高密度微流体陷阱阵列以及基于图像的表型分析

• 批准号: 9789363
• 负责人: Purushothama Rao Tata
• 金额: $ 19.85万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-20 至 2020-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9789363
• 关键词: Address; Architecture; Back; Basic Science; Biological; Biopsy; Bioreactors; Buffers; Cell Count; Cell Line; Cells; Cellular biology; Clinical; Complementary DNA; Coupled; Cytolysis; DNA; DNA Sequence; Data; Data Set; Diffuse; Drug resistance; Engineering; Enzymes; Exposure to; Gel; Gene Expression; Gene Expression Profiling; Genomics; Goals; Human; Hybrids; Hydrogels; Image; Injections; K-562; Letters; Messenger RNA; Methods; Microfluidic Microchips; Microfluidics; Microscopy; Molecular; Molecular Biology; Monitor; Mouse Cell Line; Mus; NIH 3T3 Cells; NIH Mouse; Pattern; Pharmaceutical Preparations; Phenotype; Population; Preparation; Printing; Process; Reporter; Resolution; Reverse Transcription; Sampling; Signal Pathway; Site; System; Techniques; Technology; Testing; Time; Tissue Sample; Tissues; Work; base; cDNA Library; cell growth; cellular imaging; clinical application; constriction; crosslink; density; design; drug sensitivity; experimental study; live cell imaging; next generation sequencing; phenotypic data; prevent; seal; single cell analysis; single-cell RNA sequencing; success; transcriptome; transcriptome sequencing; tumor

ABSTRACT The ability to combine single cell RNA sequencing and image-based phenotyping in a massively parallel format would enable direct correlations to be made between the function and gene expression of single cells. However, the fundamental limitations of existing technologies have prevented the realization of this goal in a high-throughput automated platform. Here we propose to solve this systems design challenge by creating a high-density trap array that contains unique DNA barcodes printed at known addresses in the trap array. The proposed technology, which we refer to as Image-Seq, will involve organizing single cells in a high-density array, imaging each cell/well at high resolution at multiple wavelengths, and finally preparing the single cells for RNA-seq using the locally printed DNA barcodes as cellular identifiers that can be traced in NGS datasets back to specific live cell images. To achieve this goal, the Duke team will partner with Applied Microarray, who will print an array of DNA barcodes at unique spatial addresses. Aim 1 will focus on demonstrating that DNA barcodes can be printed with high fidelity and used as templates for reverse transcription of cellular mRNA. Aim 2 will demonstrate the ability to achieve high throughput trapping of single cells, automated imaging, and lysis of single cells directly inside the microfluidic chips. Aim 3 will demonstrate the ability to obtain both a live cell image and a transcriptome profile of each single cell in mixed human and mouse cell lines and also in dissociated tissue samples. This project has many potential applications both in basic research and in follow- on clinical applications. One application is in making better use of limited samples where only hundreds to thousands of dissociated single cells can be obtained from a tissue, which is not currently possible by other single cell analysis workflows. Another potential application is in drug sensitivity testing, which involves time- lapse imaging to quantify single cell growth rates and compare these to the gene expression analysis of those same cells in order to implicate the signaling pathways invoked by drug resistant cells.

抽象的 以大规模并行格式将单细胞 RNA 测序和基于图像的表型分析相结合的能力 将使单细胞的功能和基因表达之间建立直接关联。 然而，现有技术的根本局限性阻碍了这一目标的实现。 高通量自动化平台。在这里，我们建议通过创建一个解决这个系统设计挑战 高密度陷阱阵列，包含在陷阱阵列中的已知地址打印的独特 DNA 条形码。这 所提出的技术，我们称之为图像序列，将涉及以高密度组织单个细胞 阵列，在多个波长下对每个细胞/孔进行高分辨率成像，最后准备单细胞 RNA-seq 使用本地打印的 DNA 条形码作为可在 NGS 数据集中追踪的细胞标识符 回到特定的活细胞图像。为了实现这一目标，杜克大学团队将与 Applied Microarray 合作，后者 将在唯一的空间地址打印一系列 DNA 条形码。目标 1 将侧重于证明 DNA 条形码可以高保真度打印并用作细胞 mRNA 逆转录的模板。 目标 2 将展示实现单细胞高通量捕获、自动成像和 直接在微流控芯片内裂解单细胞。目标 3 将展示获得现场直播的能力 人类和小鼠混合细胞系中每个单细胞的细胞图像和转录组图谱 分离的组织样本。该项目在基础研究和后续研究方面都有许多潜在的应用 关于临床应用。一种应用是更好地利用有限的样本，其中只有数百个样本 可以从组织中获得数千个分离的单细胞，这是目前其他方法无法实现的 单细胞分析工作流程。另一个潜在的应用是药物敏感性测试，其中涉及时间 延时成像以量化单细胞生长速率并将其与这些细胞的基因表达分析进行比较 相同的细胞，以暗示耐药细胞调用的信号通路。