Developing Antibody-Oligonucleotide Bridges to Simplify Single Cell Spatial Transcriptomics

项目摘要 单细胞rna测序(scrna-seq)使研究人员能够研究广泛的 生物过程以及组织异质性如何对功能做出贡献。这些技术已经导致了 开发程序，如NIH人类生物分子图谱计划，以了解细胞如何 在有机体中相互作用以驱动其功能。空间转录技术的发展已经 使研究人员能够研究细胞与细胞之间的相互作用如何影响组织内的细胞基因表达。 目前的方法通常依赖于基于原位RNA的方法或基于玻片的测序相结合 使用scRNA-seq(例如Slide-seq)来生成相互作用细胞的空间图谱。这些技术帮助了 展示结合组织结构数据和转录数据的能力，以更好地理解 细胞在组织中的行为以及未来改善这些技术之间的接口将是关键 揭示结构和细胞转录是如何驱动功能的。然而，多重障碍阻碍了 广泛采用目前进行空间转录的方法，包括显著的 财务成本、时间要求，以及缺乏足够的专业知识。在此，我们建议开发一种简单的 试剂与当前滴基和移液管scRNA-seq技术的方案兼容。这 试剂将能够在scRNA-seq实验的正常过程中产生空间数据，而不需要 显著增加成本或时间承诺。我们建议发明“抗体-寡核苷酸桥”和 构建能够以生物信息方式生成跨组织的细胞-细胞接触网络的软件 概括一个组织中细胞的空间关系。在这项提案中，我们将进行一项证明- 用于生成空间关系的AO桥scRNA-seq方法的主要实验 细胞。

Project Summary Single cell RNA-sequencing (scRNA-seq) has enabled researchers to investigate a wide array of biological processes and how tissue heterogeneity contributes to function. These technologies have led to the development of programs, such as the NIH Human Biomolecular Atlas Program, to understand how cells interact in an organism to drive its function. The development of spatial transcriptomic technologies has allowed researchers to investigate how cell-cell interactions affect cellular gene expression within a tissue. Current approaches generally rely in situ RNA based methodolgies or slide-based sequencing in combination with scRNA-seq (e.g. Slide-seq) to generate spatial maps of interacting cells. These technologies have helped demonstrate the power of combining the tissues structural data with transcriptional data to better understand cell behavior in a tissue and going forward improving the interface between these technologies will be key to uncovering how structure and cell transcription drives function. However, multiple barriers impede the widespread adoption of the current methods for performing spatial transcriptomics, including significant financial cost, time requirements, and a lack of sufficient expertise. Herein, we propose to develop a simple reagent compatible with current protocols for drop-based and pipette-based scRNA-seq technologies. This reagent will be able to generate spatial data in the normal course of scRNA-seq experiments without significantly increasing cost or time commitments. We propose to invent “antibody-oligonucleotide bridges” and build software capable of bioinformatically generating a network of cell-cell contacts across the tissue to recapitulate the spatial relationships of the cells in a tissue. In this proposal, we will carry out a proof-of- principal experiment for the AO bridge scRNA-seq approach for generating the spatial relationships between cells.