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.

项目摘要/摘要 细胞是生活的基本单位。细胞非常动态：它们会随着时间和位置而变化，对不同的响应 环境，并与其他细胞相互作用。在过去的十年中，单细胞生物学见证了巨大的 由于巨大的技术进步，例如单细胞测序，多词和空间上的幻象。 但是，在单细胞处获得活细胞的动态尺寸及其多摩变信息 目前的分辨率很困难，在大规模上当然不可能。在这里，我们提出了一种新型的细胞条形码 具有使我们能够收集细胞的实时信息并将数据连接到他们的技术的技术 详细的ODIC信息。该技术利用具有独特光学条形码的激光颗粒（LPS） 对于> 100,000个通道，每个通道都包含独特的DNA条形码。 “双重编码”将使我们能够光学地 在显微镜下在自然环境或文化中追踪活细胞，获取现场直播 信息，收获细胞，通过基于液滴的下一代获取同一单元的OMICS信息 单细胞测序，然后将实时成像和OMICS数据组合在单细胞分辨率下。 此外，我们的技术可以升级到多词的方式，结合了多层信息 来自基因组，表观基因组，转录组和蛋白质组，以及形态学，位置，功能， 和行为数据。我们将应用该方法研究癌细胞中癌细胞的前哨淋巴结（SLN）转移 体内。获取的体内单细胞成像和多摩学数据将提供前所未有的图片 癌细胞淋巴转移过程。该项目有两个具体的目标。 AIM 1将发展一个光学和 - 基于液滴的单细胞测序的DNA“双”条形码策略。 AIM 2将应用研究方法 体内乳腺癌SLN转移。在K99期间，申请人将接受额外的培训 扩大她的经验并在以下领域塑造她的独立性：（1）LPS和光学条形码，（2） LP成像和体内鼠标成像，以及（3）单细胞测序和多词。该提议未经 Andy Yun博士（LP技术，光学和成像）和Ralph Weissleder博士的结合心态 （癌症生物学，体内成像和系统生物学），以及由专家团队作为单细胞的顾问 测序和生物信息学。马萨诸塞州综合医院的跨学科研究环境 哈佛医学院将大力支持拟议的研究。如果成功，拟议的研究将 为“动态”单细胞分析提供新的范式，并以前所未有的速度和吞吐量 单细胞水平上蛋白质，RNA和DNA的多态模态，以及细胞 动态表型信息，在3D分辨率下启用空间词素分析而无需单元格 分割。这将超出当前仅收集的单细胞OMIC策略的重要一步 快照数据，体外或前体。这种新方法将改变我们使用成像和单细胞分析的方式 并将为医疗保健中的科学发现，诊断和治疗开放巨大的应用。