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: 9975112
• 负责人: Kenneth W Witwer
• 金额: $ 45.35万
• 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/9975112
• 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 aggregation; 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) 是液体活检中特别有吸引力的分子成分，因为 RNA 物种可以被特异性扩增。 exRNA 载体的三大类——细胞外囊泡 （EV）、脂蛋白颗粒（LPP）和游离核糖核蛋白（RNP）——迄今为止，EV 受到最多的关注。 注意力。在每个类别中，尺寸、密度和物理特性方面也存在巨大的多样性。 表面电荷。事实上，据我们所知，迄今为止还没有研究对多个成员的 exRNA 进行了分析。 从相同样本中严格分离出三种载体类别。有强烈的需要 制定新的策略和控制措施，以确保 exRNA 载体的比较不会因共同因素而混淆 分离（同一级分中存在不同类别的载体）或污染（检测未复合的载体） 和/或在样品收集和处理过程中引入的外源RNA）。为此，我们组建了一个团队 EV、LPP 和 RNP 方面的专家，以及尖端分离和表征方法方面的专家。 在最初的 UG3 阶段，我们将首先（目标 1）结合使用最新的物理和生化方法 分离方法从相同的生物体中分离出包含 EV、LPP 和 RNP 八种亚型的文库 样品并具有可达到的最佳纯度。 “黄金标准”蛋白质组学、脂质组学、糖组学和 RNomic 将生成数据集。精心设计的“流程”控制将首次建立一个跨部门的 板污染物和其他可能使解释复杂化的伪影的基线。在目标 2 中，我们将测试 不对称场流分离 (AF4) 和亲和捕获平台，包括 ExoView 平台和 灵敏的电化学传感器作为最常用的传统方法的优质替代品， 差速离心。与传统技术相比，我们将寻求速度、分辨率和纯度方面的提升。 如果到第二年 (UG3) 年底满足通过/不通过标准，我们将进入 UH3 阶段。这一阶段 将包括目标 3，在多个地点验证结果，样本数量约为原始样本的 6 倍 数字来解释性别和年龄的影响。 AF4 方法将进一步发展，并增加额外的 基于我们的工程和分析化学专业知识进行修改，而 ExoView 技术将 用于筛选抗体和其他亲和材料以进行快速分离并检测丰富的 RNA 直接在固定化的 exRNA 载体中进行物种鉴定。最后，目标 4 将评估饮食的生物因素 来自干预研究的有价值的样本，以及在 RNase 中收集样本的可能需求 抑制剂以保护更脆弱的RNA种类。总的来说，我们假设 1) AF4，单独或与 方法学的修改以及 2) 新颖的亲和分离方法将大大改善 基于超速离心的方法简单、纯净，符合当前最先进的技术，但繁琐且冗长 exRNA载体分离方法。