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基于激光捕获显微切割的 mRNA 表达微阵列和单细胞 RNA 测序在动脉粥样硬化研究中的应用。

Laser Capture Microdissection-Based mRNA Expression Microarrays and Single-Cell RNA Sequencing in Atherosclerosis Research.

机构信息

Institute for Cardiovascular Prevention (IPEK), Klinikum of the University of Munich (KUM), Ludwig-Maximilians-University (LMU), Munich, Germany.

German Center for Cardiovascular Research (DZHK), Partner site Munich Heart Alliance, Munich, Germany.

出版信息

Methods Mol Biol. 2022;2419:715-726. doi: 10.1007/978-1-0716-1924-7_43.

Abstract

A major goal of methodologies related to large scale gene expression analyses is to initiate comprehensive information on transcript signatures in single cells within the tissue's anatomy. Until now, this could be achieved in a stepwise experimental approach: (1) identify the majority of transcripts in a single cell (single cell transcriptome); (2) provide information on transcripts on multiple cell subtypes in a complex sample (cell heterogeneity); and (3) give information on each cell's spatial location within the tissue (zonation transcriptomics). Such genetic information will allow construction of functionally relevant gene expression maps of single cells of a given anatomically defined tissue compartment and thus pave the way for subsequent analyses, including their epigenetic modifications. Until today these aims have not been achieved in the area of cardiovascular disease research though steps toward these goals become apparent: laser capture microdissection (LCM)-based mRNA expression microarrays of atherosclerotic plaques were applied to gain information on local gene expression changes during disease progression, providing limited spatial resolution. Moreover, while LCM-derived tissue RNA extracts have been shown to be highly sensitive and covers a range of 10-16,000 genes per array/small amount of RNA, its original promise to isolate single cells from a tissue section turned out not to be practicable because of the inherent contamination of the cell's RNA of interest with RNA from neighboring cells. Many shortcomings of LCM-based analyses have been overcome using single-cell RNA sequencing (scRNA-seq) technologies though scRNA-seq also has several limitations including low numbers of transcripts/cell and the complete loss of spatial information. Here, we describe a protocol toward combining advantages of both techniques while avoiding their flaws.

摘要

大规模基因表达分析相关方法学的主要目标是在组织解剖学的单个细胞内启动对转录特征的全面信息研究。到目前为止,这可以通过逐步的实验方法来实现:(1)鉴定单个细胞中的大多数转录本(单细胞转录组);(2)在复杂样本中提供关于多个细胞亚型的转录本信息(细胞异质性);(3)提供组织内每个细胞的空间位置信息(分区转录组学)。这些遗传信息将允许构建给定解剖定义组织隔室的单个细胞的功能相关基因表达图谱,并为随后的分析铺平道路,包括它们的表观遗传修饰。尽管在心血管疾病研究领域尚未实现这些目标,但朝着这些目标迈进的步骤已经很明显:基于激光捕获显微解剖(LCM)的动脉粥样硬化斑块 mRNA 表达微阵列已被应用于获得疾病进展过程中局部基因表达变化的信息,提供有限的空间分辨率。此外,虽然已经证明 LCM 衍生的组织 RNA 提取物高度敏感,并且每个阵列/少量 RNA 可覆盖 10-16000 个基因的范围,但由于细胞 RNA 与相邻细胞 RNA 的固有污染,从组织切片中分离单个细胞的最初承诺未能实现。尽管单细胞 RNA 测序(scRNA-seq)技术克服了基于 LCM 的分析的许多缺点,但 scRNA-seq 也存在一些限制,包括转录本/细胞数量少和完全丧失空间信息。在这里,我们描述了一种结合两种技术优势的方案,同时避免了它们的缺陷。

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