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.

抽象的 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 由全身细胞产生，浓度约为每毫升 1010。它们的蛋白质分子含量， dsDNA 寡聚物、microRNA (miRNA)、mRNA 和其他分析物可能通过 EV 发挥多种功能作用 贩运，还可以提供有关疾病部位或起源组织的诊断报告。因此，电动汽车 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癌症的见解 肿瘤微环境的功能特征。然而，由于这种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，Vesicle Epitope 转录本测序（VET-seq），可同时解析表面蛋白质组、内部蛋白质、 以及具有单细胞外囊泡 (sEV) 分辨率的宽 RNA 谱。在 AIM 1 中，我们操纵 EV 来 允许接触封装的 EV 货物并允许对 EV 分子进行原位修饰。这将产生 用于检测广谱 EV 分子的协议。在这里，我们也开始生成并验证自定义 VET-seq 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 能够识别其囊泡来源的分子。这一战略将显着提高 通过克服有限稀释的需要，提高基于液滴的 EV 分析的吞吐量。解决未满足的问题 需要一种经济有效的多组学 sEV 分析方法，在 AIM 3 中，我们集成了原位修改协议 和 EV 索引协议形成 VET-seq 工作流程。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出来。 VET-seq 的 EV 检测限为 在从人血浆和血清中分离出的 EV 背景中测定癌细胞衍生的 EV。高的- VET-seq 实现的维度 sEV 分析将加深我们对分子内容和 EV 在癌症中的生物学意义。这可能会揭示电动汽车的实用性，因为 用于早期检测癌症或复发性癌症以及监测治疗反应的癌症生物标志物 到癌症治疗。 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、临床肿瘤学和检测开发。