MULTIseq: multiplexing massively parallel single cell transcriptional analysis across time, space, and conditions

MULTIseq：跨时间、空间和条件的多重大规模并行单细胞转录分析

• 批准号: 10439633
• 负责人: Zev Jordan Gartner
• 金额: $ 31.9万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-20 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10439633
• 关键词: 3-Dimensional; Affect; Aging; Autoimmunity; Bar Codes; Behavior; Biological Process; Breast Cancer Model; Buffers; Cell Count; Cell Culture Techniques; Cell Nucleus; Cell physiology; Cells; Chemicals; Collection; Communication; Communities; Complex; Coupled; Coupling; Data; Decision Making; Disease; Freezing; Genes; Genetic; Genetic Transcription; Goals; Immune; Immune response; Individual; Label; Link; Liquid substance; Logic; Lung; Malignant Neoplasms; Measures; Mechanics; Metastatic Neoplasm to the Lung; Methodology; Methods; Modeling; Molecular; Morphologic artifacts; Neoplasm Metastasis; Organ; Organoids; Paracrine Communication; Peripheral Blood Mononuclear Cell; Physiological; Preparation; Process; Protocols documentation; Reagent; Research Personnel; Resected; Resolution; Sampling; Series; Signal Pathway; Signal Transduction; Suspensions; System; T-Cell Activation; Techniques; Testing; Time; Tissue Model; Tissues; Transcript; Tumor Burden; Work; cell type; cost; diagnostic strategy; experimental study; high dimensionality; high-throughput drug screening; human disease; improved; mouse model; novel diagnostics; patient derived xenograft model; phenotypic data; preservation; response; single cell analysis; single-cell RNA sequencing; spatial relationship; temporal measurement; tool; transcriptome sequencing; treatment strategy

Abstract Many human diseases – including autoimmunity, cancer, and aging – are linked to a breakdown in the ability of different cell types to coordinate their behaviors and decisions across a tissue. Coordination occurs through a variety of mechanisms, including molecular, mechanical, and electrical signals that are exchanged among cells. These signals are integrated through signaling pathways, and ultimately, impact the transcription of numerous genes. The multicellular regulatory networks that coordinate transcription among each cell type of a tissue can be deduced by perturbing the transcriptional state of individual genes or cell types, then measuring how each cell type relaxes to a new steady state, both dynamically and spatially. However, the systematic application of this approach will require new experimental tools. We will therefore build on a new method developed in our lab – MULTIseq – that allows the simultaneous transcriptional analysis of numerous samples using existing single cell RNAseq pipelines (e.g. DropSeq, 10X, SeqWell, etc.). MULTIseq enables the implementation of entirely new classes of single cell experiments. The method has the additional benefits of dramatically increasing throughput and decreasing artifacts such as doublets and batch effects. As a consequence, MULTIseq allows researchers to gather richer single cell information at a 5- to 100-fold reduction in sample preparation costs. We present three aims that will enable application of MULTIseq to analyze dynamic biological processes in time; heterogeneous biological processes in space; and the response of complex tissues to hundreds or thousands of genetic, chemical, or microenvironmental perturbations. Finally, we propose to combine MULTIseq with methods to reduce sequencing costs by 10-fold while simultaneously increasing the information content from low-abundance transcripts. Completion of our goals will provide a powerful new tool to the scientific community that can be applied to any cell type using a simple and economical protocol.

摘要 许多人类疾病--包括自身免疫、癌症和衰老--都与 不同的细胞类型来协调它们在组织中的行为和决定。协调通过一个 多种机制，包括在细胞之间交换的分子、机械和电信号。 这些信号通过信号通路整合，最终影响许多基因的转录 基因。在组织的每种细胞类型之间协调转录的多细胞调控网络可以 通过扰乱单个基因或细胞类型的转录状态，然后测量每个基因或细胞类型如何 细胞类型在动态和空间上都松弛到一个新的稳定状态。然而，系统地应用 这种方法将需要新的实验工具。因此，我们将建立在我们实验室开发的新方法的基础上 -MULTISEQ-允许使用现有的单个 单元RNAseq管道(例如DropSeq、10X、SeqWell等)。MULTIseq支持实施全新的 单细胞实验课。该方法还具有显著提高吞吐量的额外好处 以及减少诸如二元组和批处理效果之类的伪影。因此，MULTIseq允许研究人员 收集更丰富的单细胞信息，样品制备成本降低5%至100%。我们为您呈现三个 旨在使应用MULTISEQ能够及时分析动态的生物过程；异质的 太空中的生物过程；以及复杂组织对成百上千种基因的反应， 化学或微环境扰动。最后，我们提出了将MULTISEQ与方法相结合的方法 将测序成本降低10倍，同时增加低丰度的信息含量 成绩单。完成我们的目标将为科学界提供一个强大的新工具，可以 适用于任何类型的电池，使用简单且经济的协议。