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