Seq-Scope: Microscopic Examination of Spatial Single Cell Transcriptome in Cell and Tissue Senescence

Seq-Scope：细胞和组织衰老中空间单细胞转录组的显微镜检查

• 批准号: 10375628
• 负责人: Jun Hee Lee
• 金额: $ 54.6万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-20 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10375628
• 关键词: Age; Aging; Architecture; Area; Atlases; Bar Codes; Cell Aging; Cell Nucleus; Cell Separation; Cells; Colon; Complement; Cytoplasm; Data; Detection; Dissociation; Eye; Fibrosis; Freezing; Genes; Genome; Genomics; Hepatic; Hepatocyte; Heterogeneity; Histologic; Human; In Situ Hybridization; Inferior; Inflammation; Libraries; Lipids; Literature; Liver; Liver diseases; Location; Methodology; Methods; Microscope; Microscopic; Mitochondria; Molecular Target; Monitor; Mus; Names; Oligonucleotide Microarrays; Optics; Output; Performance; Phase; Population; Procedures; Process; Proteins; RNA; RNA Sequences; Research Personnel; Resolution; Resources; Sampling; Slide; Solid; Surface; System; Techniques; Technology; Time; Tissues; Transcript; Vulnerable Populations; Work; cell type; droplet sequencing; histological slides; human tissue; improved; in situ sequencing; liver injury; protein biomarkers; response; senescence; single-cell RNA sequencing; technology development; transcriptome; transcriptomics

SUMMARY Standard immunostaining or RNA in situ hybridization can examine only one or a handful of target molecular species at a time; therefore, the amount of information obtained from a single experimental session is limited. To overcome this, emerging Spatial Transcriptomics (ST) techniques aim to examine all genes expressed from the genome from a single histological slide. There are three major methodologies of experimentally implementing ST: the sequential in situ hybridization method, in situ sequencing method and spatial barcoding method. Among these, the spatial barcoding method is the most straightforward, comprehensive and so far the only method scalable for large amount of samples. The spatial barcoding method reveals both the RNA sequence and their spatial locations by capturing tissue RNA using a spatially-barcoded oligonucleotide array. The current spatial barcoding method, however, are intrinsically limited by their low resolution and low RNA capture efficiencies; correspondingly, all currently available technologies failed to reveal the microscopic details of the spatial transcriptome. We recently developed a technology named Seq-Scope, which overcomes all these limitations. Seq-Scope has an effective resolution of 0.5-1 μm, and reveals over 20 transcripts per μm2 area (~50 transcripts/μm2 estimated at library saturation). Both resolution and transcriptome capture output of Seq-Scope are the best among all available technologies described in the literature so far. With this unprecedented performance, Seq-Scope visualized spatial transcriptome heterogeneity at multiple histological scales, including tissue zonation according to the portal-central (liver), crypt-surface (colon) and inflammation- fibrosis (injured liver) axes, cellular components including single cell types and subtypes, and subcellular architectures of nucleus, cytoplasm and mitochondria. Seq-Scope also has a potential to improve and complement current scRNA-seq approaches. In response to the SenNet announcement, we propose to adapt and utilize Seq-Scope to provide atlases of cellular senescence in multiple tissues during normal human aging, focusing on the following three aims: (1) Identify and Characterize Hepatic Senescent Cell Population during Liver Disease. (2) Characterize Age-Associated Changes of Hepatic Spatial Transcriptome. (3) Combine Seq- Scope with Detection of Senescence Protein and Cell-type Marker Proteins. For all aims, we will begin with analyzing mouse tissue to establish the feasibility of monitoring cell and tissue senescence (UG3), and then expand the work in human tissues using the tissue obtained from diverse resources including the SenNet tissue mapping center (TMC) (UH3). Seq-Scope is a versatile technology, which is quick, straightforward, scalable and adaptable. Once optimized, a single researcher can process 5-10 frozen tissue blocks every week to generate a high-quality spatial single cell transcriptome data. Therefore, our team is confident that we will be able to adapt our technology to any of the tissue systems that are provided by the SenNet TMC in the UH3 phase.

摘要 标准免疫染色或rna原位杂交只能检测一个或少数靶分子。 因此，从一次实验中获得的信息量是有限的。 为了克服这一点，新兴的空间转录学(ST)技术旨在检测从 一张组织切片上的基因组。有三种主要的实验方法 实施ST：顺序原位杂交法、原位测序法和空间条码 方法。其中，空间条码方法是最直接、最全面的，到目前为止 只有方法可扩展的大量样本。空间条形码方法显示了RNA 通过使用空间条形码寡核苷酸阵列捕获组织RNA来获得序列及其空间位置。 然而，目前的空间条码方法存在分辨率低、信噪比低等固有的局限性 捕获效率；相应地，目前所有可用的技术都未能揭示微观 空间转录组的细节。我们最近开发了一种名为Seq-Scope的技术，它克服了 所有这些限制。SEQ-SCOPE的有效分辨率为0.5-1μm，并显示每个 μm2面积(在文库饱和时估计为~50个转录本/μm2)。分辨率和转录组捕获 到目前为止，Seq-Scope的输出是文献中描述的所有可用技术中最好的。有了这个 史无前例的表现，Seq-Scope可视化多组织学空间转录组的异质性 鳞片，包括根据门脉中央(肝脏)、隐窝表面(结肠)和炎症- 纤维化(肝损伤)轴、细胞成分，包括单细胞类型和亚型，以及亚细胞 细胞核、细胞质和线粒体的构筑。SEQ-Scope也有改进和改进的潜力 补充目前的scRNA-seq方法。为了回应Sennet的声明，我们建议将 并利用序列显微镜提供人体正常衰老过程中多个组织的细胞衰老图谱， 主要针对以下三个目标：(1)鉴定和鉴定肝衰老细胞群 肝病。(2)肝脏空间转录组的增龄变化特征。(3)合并序列- 检测衰老蛋白和细胞型标志蛋白的范围。 出于所有目的，我们将从分析小鼠组织开始，以确定监测细胞和组织的可行性 衰老(UG3)，然后利用从不同组织中获得的组织扩大在人体组织中的工作 资源包括Sennet组织测绘中心(TMC)(UH3)。SEQ-Scope是一种多功能技术， 它具有快速、直观、可扩展和适应性强的特点。一旦得到优化，一个研究人员就可以处理5-10个 冰冻组织块每周生成高质量的空间单细胞转录组数据。因此，我们的 团队相信，我们将能够使我们的技术适用于由 处于UH3阶段的Sennet TMC。