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

1263701(丹尼尔)。技术部分：拟议研究的总体目标是开发一个基于包膜病毒进入动力学的单颗粒实验平台，用于鉴定和表征包膜病毒。该平台将整合两项关键技术：1)单个病毒粒子的病毒结合和病毒-宿主膜融合的单颗粒成像到一个支持的双层平台；2)对这些单个事件进行统计分析，根据进入动力学参数的变化来区分群体。在这个项目中，病毒将作为模型病毒，因为它是研究最多的病毒之一，因此进入机制已经很好地理解；它的表面蛋白很容易发生突变，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，并且这些差异与传染性相关。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，可以用来确定人（或组织样本）感染了哪种表型。就流感而言，这种快速检测对于在大流行爆发或故意释放期间迅速追踪病毒的传播可能至关重要。在流感中，病毒的进入过程是由相同的蛋白控制的，血凝素（HA），这使得整个进入动力学中的解耦结合和融合变得复杂。以目前的技术，只能单独评估，而不能在同一病毒粒子内评估结合和融合动力学。该平台在单个病毒粒子中区分这些过程，提供两个过程的定量动力学信息，然后可用于识别表型。无PCR的表型检测是目前病毒检测的一大挑战。因此，这是一项潜在的变革性技术，将有助于在混合样本中快速区分病毒表型。非技术部分：该建议将更好地了解流感病毒亚型如何在感染期间进入细胞。这一认识是重要的，作者假设它可以用来区分危害较大的流感类型和危害较小的流感类型。因此，通过帮助开发更好的流感诊断工具，该项目将在未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.