High-resolution spatial transcriptomics through light patterning

通过光图案化进行高分辨率空间转录组学

• 批准号: 10112854
• 负责人: Georg Seelig
• 金额: $ 18.17万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10112854
• 关键词: Adoption; Antibodies; Architecture; B-Cell Lymphomas; Back; Bar Codes; Biological Process; Cell Nucleus; Cell-Matrix Junction; Cells; Censuses; Characteristics; Chemistry; Cleaved cell; Clinical; Complementary DNA; Computing Methodologies; Cultured Cells; DNA; Disease; Dissociation; Drug resistance; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Genes; Heart; Heterogeneity; Hodgkin Disease; Immune Evasion; Immunohistochemistry; Immunomodulators; In Situ Hybridization; Individual; Knowledge; Label; Length; Ligation; Light; Lighting; Liquid substance; Location; Maps; Mature B-Lymphocyte; Measures; Methods; Molecular; Nuclear; Optics; Pattern; Pharmaceutical Preparations; Phenotype; Positioning Attribute; Procedures; Proteins; Protocols documentation; RNA; Reaction; Reproducibility; Research Personnel; Research Project Grants; Resistance; Resolution; Sampling; Series; Shapes; Split-Pool Ligation Transcriptome sequencing; Techniques; Technology; Time; Tissues; Transcript; Tumor Tissue; Work; anticancer research; base; cancer diagnosis; cell type; combinatorial; cost; detection sensitivity; experimental study; flexibility; genome-wide; immunomodulatory therapies; improved; indexing; innovation; instrument; interest; new therapeutic target; patient stratification; predicting response; preservation; prototype; response; single-cell RNA sequencing; spatial relationship; success; tool; transcriptome; transcriptomics; tumor; tumor heterogeneity; tumor microenvironment

PROJECT SUMMARY The cellular composition of a tumor as well as the spatial arrangement of cells within the tumor are major determinants of the response to therapy and the emergence of resistance. To improve our understanding of tumor heterogeneity, accelerate the discovery of new drug targets or enable better patient stratification it is thus necessary to develop tools that can resolve molecularly defined cell types within a tumor and capture their spatial relationships. Driven by progress in single-cell RNA sequencing (scRNA-seq) technologies, a complete census of molecularly defined cell types within a tumor is now within reach. However, because scRNA-seq requires dissociated cells and cannot preserve information about the spatial arrangement of cells in their original context, it gives an incomplete picture of the relationship between gene expression, cell type identity and tumor architecture. The need for technologies that measure gene expression in single cells while retaining position information has long been recognized, but existing solutions have insufficient cellular throughput, spatial resolution, or gene detection sensitivity. We propose to develop Combinatorial Light-Activated Spatial Sequencing (CLASSeq), a transformative approach to spatial transcriptomics that overcomes these limitations. CLASSeq uses patterned light illumination to attach DNA barcodes encoding location information to all cells of interest within a tissue section, with spatial resolution limited only by the wavelength of light. Spatial barcodes are sequenced together with cellular transcriptomes after dissociating the tissue into individual cells or nuclei, and tissue-wide gene expression patterns are computationally recreated. Because sequencing is performed after dissociation, any established scRNA-seq workflow can be used, enabling high sensitivity and cell throughput. To achieve high throughput and reproducibility, and facilitate wide adoption, we will work toward automating the labeling workflow by constructing a prototype instrument that integrates fluidics for barcode delivery with patterned illumination. To validate our approach and demonstrate its utility to cancer research, CLASSeq will be used to characterize cellular diversity and organization in Hodgkin lymphoma, a mature B-cell lymphoma in which the tumor microenvironment niche is critical to the tumor's success for host immune evasion and thus governs the response or lack thereof to clinical immune modulatory therapies.

项目总结 肿瘤的细胞组成以及肿瘤内细胞的空间排列是主要因素。 治疗反应和出现耐药性的决定因素。为了提高我们对 肿瘤异质性，加速发现新的药物靶点或使患者能够更好地分层 有必要开发工具来解析肿瘤内分子定义的细胞类型并捕捉它们的空间 两性关系。在单细胞RNA测序(scRNA-seq)技术进步的推动下，一项完整的人口普查 肿瘤内分子定义的细胞类型的研究现已触手可及。然而，因为scRNA-seq需要 并且不能在它们的原始上下文中保存关于单元的空间排列的信息， 它对基因表达、细胞类型识别和肿瘤之间的关系提供了一个不完整的图景 建筑。需要在保持位置的同时测量单个细胞中的基因表达的技术 信息早已被认识到，但现有的解决方案没有足够的蜂窝吞吐量、空间 分辨率，或基因检测灵敏度。我们建议发展组合式光激活空间 测序(CLASSeq)，一种克服这些限制的空间转录组学的变革性方法。 CLASSeq使用图案光照明将编码位置信息的DNA条形码附着到 感兴趣的组织切片，其空间分辨率仅受光的波长限制。空间条形码 在将组织分离成单独的细胞或核后与细胞转录本一起测序， 组织范围内的基因表达模式通过计算重新生成。因为排序是在以下时间之后执行的 解离后，可以使用任何已建立的scRNA-seq工作流程，从而实现高灵敏度和细胞吞吐量。至 实现高吞吐量和重复性，并促进广泛采用，我们将努力实现自动化 通过构建集成了用于条码交付的流体的原型仪器来标记工作流 图案照明。为了验证我们的方法并展示其对癌症研究的效用，CLASSeq将 用于描述霍奇金淋巴瘤的细胞多样性和组织，霍奇金淋巴瘤是一种成熟的B细胞淋巴瘤，在这种淋巴瘤中 肿瘤微环境是肿瘤成功逃避宿主免疫的关键，因此控制着 对临床免疫调节疗法的反应或缺乏。