Novel Separation Methods for exRNA Carriers: Extracellular Vesicles, Lipoprotein Particles, and Protein Aggregates

exRNA 载体的新型分离方法：细胞外囊泡、脂蛋白颗粒和蛋白质聚集体

• 批准号: 9812105
• 负责人: Kenneth W Witwer
• 金额: $ 48.7万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9812105
• 关键词: Affinity; Age; Analytical Chemistry; Antibodies; Attention; Binding; Biochemical; Biological; Biological Factors; Biology; Catalogs; Cells; Centrifugation; Characteristics; Charge; Data Set; Detection; Development; Diet; Disease; Engineering; Ensure; Field Flow Fractionation; Gold; Health; High Density Lipoproteins; Higher Order Chromatin Structure; Immobilization; Intervention Studies; Libraries; Lipid Bilayers; Lipoproteins; Liquid substance; Location; Low-Density Lipoproteins; MLLT2 gene; Measures; Methodology; Methods; MicroRNAs; Modification; Molecular; Morphologic artifacts; Phase; Process; Proteomics; RNA; Resolution; Ribonucleases; Ribonucleoproteins; Sampling; Speed; Surface; Techniques; Technology; Testing; Therapeutic; Time; Tissues; Validation; base; biological sex; density; design; extracellular; extracellular vesicles; improved; inhibitor/antagonist; liquid biopsy; member; molecular carrier; novel; particle; preservation; protein aggregate; sample collection; screening; sensor; sex; validation studies

ABSTRACT Extracellular RNA (exRNA) is a particularly attractive molecular component of liquid biopsy because RNA species can be specifically amplified. Of the three major classes of exRNA vehicle—extracellular vesicles (EVs), lipoprotein particles (LPPs), and free ribonucleoproteins (RNPs)—EVs have so far received the most attention. Within each class, there is also tremendous diversity by physical characteristics of size, density, and surface charge. Indeed, to our knowledge, no study to date has profiled exRNA in multiple members of the three carrier classes that have been isolated rigorously from the same samples. There is a strong need to develop new strategies and controls to ensure that comparisons of exRNA carriers are not confounded by co- isolation (different classes of carriers present in the same fraction) or contamination (detection of uncomplexed and/or foreign RNAs introduced during sample collection and processing). To this end, we assemble a team of experts on EVs, LPPs, and RNPs, along with experts in cutting-edge separation and characterization methods. In an initial UG3 phase, we will first (Aim 1) use a combination of state-of-the-field physical and biochemical separation methods to separate a library of eight subtypes of EVs, LPPs, and RNPs from the same biological samples and with the best achievable purity. “Gold standard” proteomic, lipidomic, glycomic, and RNomic datasets will be generated. Carefully designed “process” controls will for the first time establish an across-the- board baseline of contaminants and other artifacts that may complicate interpretation. In Aim 2, we will test asymmetric field-flow fractionation (AF4) and affinity capture platforms including the ExoView platform and sensitive electrochemical sensors as superior alternatives to the most commonly used legacy method, differential centrifugation. We will seek gains in speed, resolution, and purity compared with legacy techniques. If go/no-go criteria are met by the end of the second year (UG3), we will proceed to a UH3 phase. This phase will include an Aim 3, validating results in multiple locations and with approximately 6 times the original sample numbers to account for influence of sex and age. The AF4 method will be further developed with additional modifications based on our engineering and analytical chemistry expertise, while ExoView technology will be harnessed to screen antibodies and other affinity materials for rapid isolations and to detect abundant RNA species directly in immobilized exRNA carriers. Finally, an Aim 4 will assess the biological factor of diet with valuable samples from intervention studies, along with the possible desirability of collecting samples in RNase inhibitors to preserve more fragile RNA species. Overall, we hypothesize that 1) AF4, on its own or with methodologic modifications, as well as 2) novel affinity separation approaches will improve substantially on ultracentrifuge-based methods in ease and purity and on current state-of-the-art but tedious and lengthy exRNA carrier separation methods.

抽象的 细胞外RNA（EXRNA）是液体活检的特别有吸引力的分子成分，因为RNA 物种可以特异性扩增。在三个主要类别的Exrna车辆中 （EVS），脂蛋白颗粒（LPP）和游离核糖核蛋白（RNP） - EVS到目前为止收到的最多 注意力。在每个班级中，大小，密度和 表面电荷。确实，据我们所知，迄今为止还没有研究在多个成员中介绍 与同一样品严格隔离的三个载体类别。有很大的需求 制定新的策略和控制，以确保Exrna载体的比较不会被共同混淆 隔离（相同分数中存在的不同类别的载体）或污染（检测未复杂的载体 和/或样本收集和处理过程中引入的外国RNA）。为此，我们组装了一个团队 电动汽车，LPP和RNP的专家，以及前沿分离和表征方法的专家。 在最初的UG3阶段，我们将首先（AIM 1）使用最先进的物理和生化的组合 分离方法将八个亚型的电动汽车，LPP和RNP的库与相同的生物学分开 样品和最好的纯度。 “黄金标准”蛋白质组学，脂质组，糖和RNOMIC 数据集将生成。精心设计的“过程”控件将首次建立 污染物和其他可能使解释复杂化的污染物的基线。在AIM 2中，我们将测试 不对称的场流分馏（AF4）和亲和力捕获平台，包括Exoview平台和 敏感的电化学传感器是最常用的遗产方法的优越选择， 差异离心。与传统技术相比，我们将寻求速度，分辨率和纯度的提高。 如果在第二年结束时满足GO/No-Go标准（UG3），我们将继续进行UH3阶段。这个阶段 将包括一个目标3，验证多个位置的结果，大约是原始样本的6倍 计算性别和年龄影响的数字。 AF4方法将进一步开发 基于我们的工程和分析化学专业知识的修改，而Exoview技术将是 利用筛选抗体和其他亲和力材料，用于快速隔离并检测丰富的RNA 直接在固定的ExRNA载体中的物种。最后，目标4将评估饮食的生物学因素 干预研究中的有价值的样本，以及在RNase中收集样品的可能性 抑制剂保存更脆弱的RNA物种。总体而言，我们假设1）AF4，本身或与 方法论修改以及2）新型亲和力分离方法将在很大程度上改善 宽松和纯度以及当前最新但乏味且冗长的基于超速离心的方法 EXRNA载体分离方法。