Mathematical Modeling and Quantification of Viral Entry Assays

病毒进入检测的数学建模和定量

• 批准号: 1516675
• 负责人: Tom Chou
• 金额: $ 31.29万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-15 至 2019-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1516675&HistoricalAwards=false
• 关键词: Mathematical; Modeling; Quantification; Viral; Entry

The ability to quantitatively define and measure how infective different strains of viruses are towards live cells is critical for the development of antivirals. Surprisingly, there exists no standardized way to measure and compare infectivities across viral strains and under different experimental conditions. This research will develop the quantitative framework needed and quantify existing experimental measurements of infectivity. Most importantly, the models and analysis tool will allow quantitative comparison of existing infectivity data. Such comparisons will facilitate the development of antivirals that block viral entry, or complex antibodies that neutralize virus particles. The research is independent of the particular virus under consideration and may be feasibly extended to bacterial pathogens.The first component of the research will be to model, under typical experimental conditions, the physical process of viral entry into cells. Specifically, the investigators aim to understand the effects of (i) protocols such as centrifugation that bring virus particles close to their target cells, (ii) the reporter system used to count the number of cells infected, and (iii) the different parameters, such as temperature, duration of exposure, and antiviral concentrations under which the assays were performed. A model for how these variables affect the measured infectivities will allow different experiments, performed in different laboratories under different conditions, to be compared with each other. The second component of the proposed research involves implementing the models for viral entry into a web-based data analysis tool that will be constructed. It is anticipated that this tool will aid virologists in their interpretation of large scale infectivity data in terms of biological and mechanistic attributes of the viruses.

定量定义和测量不同病毒株对活细胞的感染性的能力对于抗病毒药物的开发至关重要。 令人惊讶的是，没有标准化的方法来测量和比较不同病毒株和不同实验条件下的感染性。 这项研究将开发所需的定量框架，并量化现有的感染性实验测量。 最重要的是，模型和分析工具将允许对现有的传染性数据进行定量比较。 这种比较将有助于开发阻断病毒进入的抗病毒药物，或中和病毒颗粒的复合抗体。 这项研究与所考虑的特定病毒无关，并可能扩大到细菌病原体，研究的第一个组成部分将是在典型的实验条件下模拟病毒进入细胞的物理过程。 具体来说，研究人员的目标是了解（i）方案的影响，如离心使病毒颗粒接近其靶细胞，（ii）用于计数感染细胞数量的报告系统，以及（iii）不同的参数，如温度，暴露持续时间和进行测定的抗病毒浓度。 这些变量如何影响测量的感染性的模型将允许在不同实验室在不同条件下进行的不同实验相互比较。 拟议研究的第二个组成部分涉及将病毒进入一个基于网络的数据分析工具，将被构建的模型。 预计该工具将有助于病毒学家根据病毒的生物学和机制属性解释大规模感染性数据。