A Single Particle Imaging Approach for the Detection of Virus Phenotypes in a Mixture

1263701（丹尼尔）。技术部分：拟议的研究的总体目标是开发一个单粒子实验平台，用于基于其进入动力学来识别和表征包膜病毒。该平台将整合两项关键技术：1）病毒结合的单颗粒成像和单个病毒粒子与支持的双层平台的病毒-宿主膜融合，以及2）这些单个事件的统计分析，以基于进入动力学参数的变化来区分群体。在本项目中，病毒将作为模型病毒，因为它是研究最多的病毒之一，因此其进入机制已被充分理解;其表面蛋白易于突变并适应不同的细胞类型;众所周知，病毒株之间的结合和融合可能不同，例如H5（禽）与H3（人）毒株，并且这些变异与感染性相关。我们建议，通过我们在这里采用的方法，可以快速表征来自感染者的病毒样本的进入动力学，可以用于确定该人（或组织样本）感染了哪些表型。在流感的情况下，这种快速检测对于在大流行爆发或故意释放期间及时跟踪病毒传播至关重要。在流感中，病毒进入过程由相同的蛋白质血凝素（HA）控制，这使得在总体进入动力学中从融合的解耦结合复杂化。利用目前的技术，仅可能单独评估结合和融合动力学，但不能在相同的病毒体内。该平台可以区分单个病毒体中的这些过程，提供有关这两个过程的定量动力学信息，然后可以用于鉴定表型。非PCR的表型检测是目前病毒检测中的一个巨大挑战。因此，这是一项潜在的变革性技术，将有助于快速区分混合样本中的病毒表型。非技术部分：该提案将更好地了解流感病毒亚型如何在感染过程中进入细胞。 这种理解是重要的，作者假设，它可以用来区分更多的有害类型的infleunza。 因此，该项目将通过帮助开发更好的influenaza诊断工具来产生重大的社会效益。

1263701(Daniel). Technical part: The overall goal of the proposed research is to develop a single particle experimental platform for the identification and characterization of enveloped viruses based on their entry kinetics. This platform will integrate two key technologies: 1) single particle imaging of virus binding and viral-host membrane fusion of individual virion particles to a supported bilayer platform, and 2) statistical analysis of these individual events to discriminate populations based on variations in entry kinetic parameters. In this project, virus will serve as a model virus because it is one of the most studied viruses and thus the entry mechanism is well understood; its surface proteins are easily mutated and adapted to different cell types; it is well known that binding and fusion can vary among viral strains, e.g. H5 (avian) versus H3 (human) strains, and that these variations are correlated to infectivity. We propose that the rapid characterization of entry kinetics of virus samples from an infected person, made possible by the methods we employ here, can be used to determine which phenotypes the person (or a tissue sample) is infected with. In the case of influenza, this kind of rapid detection may be critical to promptly tracking the spread of virus during a pandemic outbreak or intentional release. In influenza, viral entry processes are controlled by the same protein, hemagglutinin (HA), which complicates decoupling binding from fusion in the overall entry kinetics. With current technology, it is only possible to assess separately, but not within the same virion, binding and fusion kinetics. This proposed platform discriminates between these processes within an individual virion, providing quantitative kinetic information on both processes that can then be used to identify phenotypes. Phenotype detection without PCR is currently a grand challenge in virus detection. Thus this is a potentially transformative technology that will aid in quickly discriminating among virus phenotypes in a mixed sample.Non-technical part: This proposal will develop better understanding of how influenza virus subtypes enter the cell during infection. This understanding is important and authors postulate that it may be used to discriminate more harmful from less harmful types of infleunza. This project will therefore have significant societal benefit down the road by helping develop better influenaza diagnostic tools.