Laser particles-based spatiotemporal and dynamic single-cell multiomics

基于激光粒子的时空和动态单细胞多组学

• 批准号: 10723601
• 负责人: Yue Jane Wu
• 金额: $ 13.61万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10723601
• 关键词: 3-Dimensional; Area; Bar Codes; Behavioral; Bioinformatics; Cancer Biology; Cell Communication; Cell Separation; Cells; Cellular biology; Color; DNA; Data; Diagnosis; Dimensions; Effectiveness; Environment; General Hospitals; Genome; Growth; Harvest; Healthcare; Image; In Vitro; Individual; Interdisciplinary Study; Lasers; Life; Location; Lymphatic Metastasis; Massachusetts; Mentorship; Metastatic Neoplasm to Lymph Nodes; Methods; Microscope; Modality; Morphology; Multiomic Data; Mus; Optics; Phenotype; Physiological; Process; Proteome; RNA; Resolution; Semiconductors; Sentinel Lymph Node; Shapes; Slide; Speed; Systems Biology; Techniques; Technology; Time; Tissues; Training; biomaterial compatibility; cancer cell; cell behavior; cellular imaging; epigenome; experience; in vivo; in vivo imaging system; innovation; insight; malignant breast neoplasm; medical schools; multiple omics; next generation; novel; particle; protein profiling; response; sequencing platform; single cell analysis; single cell sequencing; single-cell RNA sequencing; spatiotemporal; transcriptome; transcriptomics

Project Summary/Abstract Cells are the basic unit of life. Cells are very dynamic: they change over time and locations, respond to different environments, and interact with other cells. Over the past decade, single-cell biology has witnessed enormous growth owing to massive technical advances, such as single-cell sequencing, multi-omics, and spatial omics. However, obtaining dynamic dimensions of live cells along with their multi-omic information at the single-cell resolution is currently difficult and certainly not possible on large scales. Here, we propose a novel cell barcoding technology that has the potential to enable us to collect live information of cells and connect the data to their detailed omics information. This technology makes use of laser particles (LPs) with unique optical barcodes for >100,000 channels, each containing a unique DNA barcode. The “dual-barcoding” will allow us to optically track live cells under a microscope while they are in their natural environment or in culture, acquire their live information, harvest the cells, acquire the omics information of the same cells by droplet-based next-generation single-cell sequencing, and then combine the live imaging and omics data at the single cell resolution. Furthermore, our technique can be upgraded to multi-omics modalities, combining multiple layers of information from the genome, epigenome, transcriptome, and proteome, together with morphological, locational, functional, and behavioral data. We will apply the method to study sentinel lymph node (SLN) metastasis of cancer cells in vivo. The acquired in vivo single-cell imaging and multi-omics data will provide an unprecedented picture of the cancer cell lymphatic metastasis process. This project has two specific aims. Aim 1 will develop an optical-and- DNA “dual” barcoding strategy for droplet-based single-cell sequencing. Aim 2 will apply the method to study breast cancer SLN metastasis in vivo. During the K99 period, the applicant will receive additional training to expand her experience and shape her independence in the following areas: (1) LPs and optical barcoding, (2) LP imaging and in vivo mouse imaging, and (3) single-cell sequencing and multi-omics. This proposal is under the combined mentorship of Dr. Andy Yun (LP technology, optics, and imaging) and Dr. Ralph Weissleder (cancer biology, in vivo imaging, and system biology), and a team of experts as advisors for single-cell sequencing and bioinformatics. The interdisciplinary research environment at Massachusetts General Hospital and Harvard Medical School will significantly facilitate the proposed study. If successful, the proposed study will offer a new paradigm for “dynamic” single-cell analysis, with unprecedented speed and throughput, enabling multi-omics modalities for the profiling of proteins, RNAs, and DNAs at the single-cell level, together with cells’ dynamic phenotype information, enable spatial-omics profiling at the 3D resolution without the need for cell segmentation. This will be a significant step beyond the current single-cell omics strategies that collect only snapshot data, in vitro or ex-vivo. This new method will transform the way we use imaging and single-cell analysis and will open enormous applications for scientific discovery, diagnosis, and treatment in healthcare.

项目概要/摘要 细胞是生命的基本单位，是非常动态的：它们随着时间和位置的变化而变化，对不同的情况做出反应。 在过去的十年里，单细胞生物学取得了巨大的进步。 增长得益于单细胞测序、多组学和空间组学等大规模技术进步。 然而，在单细胞上获得活细胞的动态尺寸及其多组学信息 目前分辨率很困难，而且在大规模上肯定是不可能的。在这里，我们提出了一种新颖的细胞条形码。 技术有潜力使我们能够收集细胞的实时信息并将数据连接到它们 该技术利用具有独特光学条形码的激光粒子 (LP)。 对于超过 100,000 个通道，每个通道都包含一个独特的 DNA 条形码，“双条形码”将使我们能够以光学方式进行识别。 在显微镜下追踪处于自然环境或培养物中的活细胞，获取它们的活细胞 信息，收获细胞，通过基于液滴的下一代技术获取相同细胞的组学信息 单细胞测序，然后以单细胞分辨率结合实时成像和组学数据。 此外，我们的技术可以升级到多组学模式，结合多层信息 来自基因组、表观基因组、转录组和蛋白质组，以及形态、位置、功能、 我们将应用该方法来研究癌细胞的前哨淋巴结（SLN）转移。 获得的体内单细胞成像和多组学数据将提供前所未有的图像。 该项目有两个具体目标：开发一种光学-和-。 基于液滴的单细胞测序的 DNA“双”条形码策略 Aim 2 将应用该方法进行研究。 乳腺癌SLN体内转移 在K99期间，申请人将接受额外的培训。 在以下领域拓展她的经验并塑造她的独立性：(1) LP 和光学条形码，(2) LP 成像和小鼠体内成像，以及 (3) 单细胞测序和多组学。 Andy Yun 博士（LP 技术、光学和成像）和 Ralph Weissleder 博士的联合指导 （癌症生物学、体内成像和系统生物学），以及作为单细胞顾问的专家团队 马萨诸塞州总医院的跨学科研究环境。 哈佛医学院将极大地促进拟议的研究如果成功，拟议的研究将。 为“动态”单细胞分析提供了新的范例，具有前所未有的速度和通量，使 用于在单细胞水平上分析蛋白质、RNA 和 DNA 以及细胞的多组学模式 动态表型信息，无需细胞即可以 3D 分辨率进行空间组学分析 这将是超越当前仅收集数据的单细胞组学策略的重要一步。 这种新方法将改变我们使用成像和单细胞分析的方式。 并将为医疗保健领域的科学发现、诊断和治疗开辟巨大的应用。