Bacteria and pathogen characterizations using outer membrane vesicles

项目摘要 越来越多的人认识到，细胞外囊泡（EV）-微米或纳米尺寸的脂质 含有蛋白质和核酸货物的颗粒-被生命的所有领域所抛弃。无处不在的 原核EV表明，生物流体中细菌EV的存在可以用于新的 诊断学/药理学甚至治疗多种病原菌。然而，有一个未得到满足的需要， 对于能够解决混淆生物学中EV信息开发的基本问题的方法， 药物-EV是天然高度异质的颗粒，因此感兴趣的那些可能仅存在于 在其他EV的混合物中丰度非常低。在这个第一阶段的项目中，我们的总体实验目标是 通过关注一类重要的 称为外膜囊泡（OMV）的细菌纳米颗粒。具体来说，我们的新技术平台是 旨在解决在单个OMV水平上解决OMV亚群的问题， 将分散的OMV的表面蛋白质和核酸货物（这里是小RNA或sRNA）相关联， 高度多路复用的荧光成像分析与两种货物的放大读出相结合。我们的最终 目标是开发一种独特的成像平台，用于蛋白质的高含量，高通量分析， 从任何生物样品获得的单个OMV（和其它EV）的核酸货物。我们的平台可以 通过提供一种最小侵入性的方法，能够对细菌感染进行新的诊断/预后"液体活检"测试， 和更多的信息替代（或补充）传统的方法，往往依赖于冗长的 从临床样品或标本培养目标生物体。 我们的创新平台可以一次性同时分析多达10种潜在的OMV生物标志物， 从诸如血液、唾液或粪便的生物流体获得的多达106个分散的OMV。不同于常规 方法，我们的平台可以快速：1）分析不同的EV; 2）同时读取多个OMV表面 标记，从而检测亚群; 3）读取单个OMV货物，大大提高了信息产量。 使用产生合并货物数据的典型方法;以及4）基于独特的 来自点1 - 3的生物标志物的组合。因此，我们提出三个逐步实现的目标。第一，优化 由革兰氏阴性和革兰氏阴性的代表性实例脱落的OMV的组合蛋白质/核酸分析， 革兰氏阳性菌（E.大肠杆菌和金黄色葡萄球菌）。第二，为了测试我们平台的能力， 使用代表这些主要组分类的分散的单个OMV原位分析sRNA货物。 第三，联合收割机结合我们的表面分子和sRNA分析方法，进行相关的原位直接检测， 分散的单个OMV中的蛋白质和核酸货物代表两个主要组。我们 预计我们的平台可以成为管理病理的新研究/诊断/预后工具 其中OMV分析是临床信息，并用于监测正常或异常的微生物组状态。

PROJECT SUMMARY There is growing recognition that extracellular vesicles (EVs)–micrometer- or nanometer-sized lipid particles containing protein and nucleic acid cargoes–are shed by all domains of life. The ubiquity of prokaryotic EVs suggests that the presence of bacterial EVs in biofluids could be exploited for new diagnostics/prognostics and even therapies for diverse pathogenic bacteria. There is, however, an unmet need for methods able to solve a fundamental problem confounding the exploitation of EV information in biology and medicine--EVs are naturally highly heterogeneous particles and thus those of interest may be present only at very low abundance in a mixture of other EVs. In this Phase I project, our overall experimental goal is to address the need for analyzing EV heterogeneity (subpopulations) by focusing on an important class of bacterial nanoparticles called outer membrane vesicles (OMVs). Specifically, our novel technology platform is designed to address the problem of resolving OMV subpopulations at the single OMV level by directly correlating surface protein and nucleic acid cargoes (here small RNAs or sRNAs) of dispersed OMVs, through highly multiplexed fluorescence imaging analysis coupled with amplified readouts of both cargoes. Our ultimate goal is to develop a unique imaging platform for the high-content, high-throughput analysis of the protein and nucleic acid cargoes of single OMVs (and other EVs) obtained from any biological sample. Our platform could enable novel diagnostic/prognostic “liquid biopsy” tests for bacterial infections by providing a minimally invasive and more informative alternative (or supplement) to conventional methods, which often rely on lengthy culturing of target organisms from clinical samples or specimens. Our innovative platform simultaneously analyzes, in one pass, up to 10 potential OMV biomarkers in as many as 106 dispersed OMVs obtained from a biofluid such as blood, saliva, or stool. Unlike conventional methods, our platform can rapidly: 1) analyze diverse EVs; 2) simultaneously read multiple OMV surface markers and thus detect subpopulations; 3) read single OMV cargoes, greatly raising information yield com- pared to typical methods producing pooled cargo data; and 4) identify OMV subpopulations based on unique combinations of biomarkers from points 1-3. We therefore propose three stepwise objectives. First, to optimize the combined protein/nucleic acid analyses of OMVs shed by representative examples of Gram-negative and Gram-positive bacteria (E. coli and S.aureus, respectively). Second, to test the capability of our platform for the analysis in situ of sRNA cargo using dispersed single OMVs representing these major group classifications. Third, combine our surface molecule and sRNA analysis methods for the correlated direct detection in situ of both protein and nucleic acid cargoes in dispersed single OMVs representing the two major groups. We anticipate that our platform could become a new research/diagnostic/prognostic tool for managing pathologies in which OMV analysis is clinically informative, and for monitoring normal or aberrant microbiome status.