Vesicle Epitope Transcript sequencing (VET-seq): Droplet-based Multiomic Profiling Platform for Single Vesicle Analysis

囊泡表位转录本测序 (VET-seq)：用于单囊泡分析的基于液滴的多组学分析平台

• 批准号: 10613257
• 负责人: Yue Lu
• 金额: $ 24.35万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10613257
• 关键词: Address; Antibodies; Back; Bar Codes; Benchmarking; Biological; Biology; Blood; Blood Cells; Cancer Hospital; Cancer cell line; Cell Culture Techniques; Cell model; Cells; Characteristics; Clinical; Clinical Oncology; Clinical Trials Design; Community Clinical Oncology Program; Computational Biology; Custom; Cytolysis; DNA; Data; Detection; Development; Diagnostic; Diameter; Disease; Drug resistance; Encapsulated; Epitopes; Genetic; Health Status; High-Throughput Nucleotide Sequencing; Human; In Situ; Individual; Investigation; Light; Malignant Neoplasms; Malignant neoplasm of lung; Medical Oncologist; Membrane; Messenger RNA; Methods; MicroRNAs; Microfluidic Microchips; Modeling; Modification; Molecular; Moloney Leukemia Virus; Monitor; Nanotechnology; Neoplasm Metastasis; Permeability; Plasma; Play; Poly A; Poly(A) Tail; Polyadenylation; Primary Lesion; Proteins; Proteome; Protocols documentation; RNA; RNA-Directed DNA Polymerase; Recurrent Malignant Neoplasm; Reporting; Resolution; Role; Sampling; Scientist; Screening for cancer; Serum; Signal Transduction; Site; Source; Specimen; Stains; Surface; Systems Biology; Technology; Therapeutic; Tissues; Transcript; Universities; Untranslated RNA; Utah; Vesicle; Work; antibody conjugate; assay development; cancer biomarkers; cancer cell; cancer drug resistance; cancer recurrence; combinatorial; cost effective; detection limit; ds-DNA; experimental study; extracellular vesicles; high dimensionality; indexing; innovation; insight; liquid biopsy; multidisciplinary; multiple omics; sample fixation; single cell analysis; statistics; trafficking; transcriptome; transcriptome sequencing; treatment response; tumor microenvironment

ABSTRACT Extracellular vesicles (EVs) are bilayer membrane structures of diameters 30 – 1000 nm released into the blood by cells throughout the body, at concentrations on the order of 1010 per ml. Their molecular content of proteins, dsDNA oligomers, microRNAs (miRNAs), mRNAs, and other analytes, may play multiple functional roles via EV trafficking, and may also provide a diagnostic report back on the disease site or tissue of origin. As such, EVs can serve as potential sources of cancer biomarkers, perhaps even providing insights into the genetic and functional characteristics of the tumor microenvironment. However, this potential remains largely untapped due to technical challenges. We propose to develop an ultra-high-throughput droplet-based multiomic profiling platform, Vesicle Epitope Transcript sequencing (VET-seq), that can simultaneously resolve the surface proteome, internal proteins, and broad RNA spectrum with single extracellular vesicle (sEV) resolution. In AIM 1, we manipulate EVs to permit access to encapsulated EV cargoes and allow in situ modifications of EV molecules. This will yield protocols for detecting a broad spectrum of EV molecules. Here, we also begin to generate and validate custom probes for VET-seq. In AIM 2, we propose an EV indexing approach to add vesicle-specific barcodes to EV molecules that enable the identification of their vesicle-source. This strategy will significantly increase the throughput for droplet-based EV profiling by overcoming the need for limiting dilution. To address the unmet need for a cost-effective multiomic sEV profiling method, in AIM 3, we integrate the in situ modification protocols and the EV indexing protocol to form the VET-seq workflow. We will benchmark the VET-seq protocol on EVs isolated from human cancer cell lines and drug resistance models. The EV detection limit of VET-seq will be determined for cancer-cell derived EVs in a background of EVs isolated from human plasma and serum. High- dimensional sEV profiling enabled by VET-seq will deepen our understanding of the molecular contents and biological implications of EVs in the context of cancer. This will potentially shed light into the utility of EVs as cancer biomarkers for early detection of cancer or recurrent cancer as well as for monitoring treatment response to cancer therapeutics. Our multidisciplinary team is comprised of scientists and clinicians with expertise in micro-nanotechnologies, multiomics analysis, EV biology, computational biology, clinical oncology, and assay development.

摘要 细胞外囊泡（EV）是释放到血液中的直径为30 - 1000 nm的双层膜结构 通过全身的细胞，浓度在每毫升1010的数量级。它们的蛋白质分子含量， dsDNA寡聚体、microRNA（miRNAs）、mRNAs和其他分析物可以通过EV发挥多种功能作用。 贩运，并且还可以提供关于疾病部位或来源组织的诊断报告。因此，EV 可以作为癌症生物标志物的潜在来源，甚至可能提供对遗传和 肿瘤微环境的功能特征。然而，这一潜力在很大程度上尚未开发， 技术挑战。 我们建议开发一个超高通量的基于液滴的多组学分析平台，囊泡表位 转录测序（VET-seq），可以同时解析表面蛋白质组，内部蛋白质， 和具有单个细胞外囊泡（sEV）分辨率的宽RNA谱。在AIM 1中，我们操纵电动汽车， 允许进入包封的EV货物并允许EV分子的原位修饰。这将产生 用于检测广谱EV分子的方案。在这里，我们还开始生成和验证自定义 用于VET-seq的探针在AIM 2中，我们提出了一种EV索引方法，将囊泡特异性条形码添加到EV中 这些分子能够识别它们的囊泡来源。这一战略将大大提高 通过克服对有限稀释的需要，提高了基于液滴的EV分析的通量。解决未得到满足的问题 需要一个具有成本效益的多组sEV分析方法，在AIM 3中，我们整合了原位修饰方案， 和EV索引协议以形成VET-seq工作流。我们将在电动汽车上对VET-seq协议进行基准测试 从人类癌细胞系和耐药模型中分离。VET-seq的EV检测限为 在从人血浆和血清分离的EV的背景下，测定癌细胞衍生的EV。高- 通过VET-seq实现的三维sEV分析将加深我们对分子内容的理解， EV在癌症背景下的生物学意义。这将潜在地揭示电动汽车的实用性， 用于癌症或复发性癌症的早期检测以及用于监测治疗反应的癌症生物标志物 to cancer癌症therapeutics治疗. 我们的多学科团队由具有微纳米技术专业知识的科学家和临床医生组成， 多组学分析、EV生物学、计算生物学、临床肿瘤学和分析开发。