Data-driven Computational Modeling of the Growth and Spread of Viruses

病毒生长和传播的数据驱动计算模型

• 批准号: 7900491
• 负责人: John Yin
• 金额: $ 34.73万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-15 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7900491
• 关键词: Accounting; Acquired Immunodeficiency Syndrome; Address; Adsorption; Affect; Animal Model; Bacteria; Bacteriophage T7; Bacteriophages; Binding; Biochemical; Biochemical Process; Biomedical Research; Buffers; Cell membrane; Cell model; Cell physiology; Cell surface; Cells; Chemicals; Code; Common Cold; Computer Simulation; Computer software; Coupled; Couples; Cytoplasm; Data; Development; Ebola virus; Educational process of instructing; Engineering; Environment; Equation; Equilibrium; Flow Cytometry; Gene Expression; Gene Order; Gene Structure; Generations; Genes; Genetic Transcription; Genome; Growth; Growth and Development function; HIV-1; Health; Human; Image; Infection; Influenza; Influenza A virus; Interferons; Laboratories; Life; Literature; Malignant Neoplasms; Measles virus; Measurement; Mediating; Methods; Modeling; Molecular; Molecular Models; Motivation; Mutation; Organism; Parasites; Phase; Positioning Attribute; Postdoctoral Fellow; Process; Production; Productivity; Protein Biosynthesis; Proteins; Publishing; RNA Viruses; Rabies; Reaction; Recombinants; Research; Research Project Grants; Resources; Role; Severe Acute Respiratory Syndrome; Simulate; Staging; System; Technology; Testing; Textbooks; Time; Transcriptional Regulation; Vaccines; Variant; Vesicular stomatitis Indiana virus; Viral; Viral Genome; Viral Proteins; Virion; Virus; Virus Diseases; anti-cancer therapeutic; base; chemical reaction; data modeling; design; experience; gene function; human disease; innovation; insight; intercellular communication; mathematical model; molecular modeling; open source; operation; protein expression; recombinant virus; research study; respiratory; software development; tool; tumor; web site

DESCRIPTION (provided by applicant): Our long-term objective is to understand how interactions between genomes and their environments influence the growth of simple organisms. We focus on the genomes of viruses because they carry a small number of genes, essential functions of these genes are often known, and the stages of the virus growth cycle have frequently been well characterized. Viruses also cause many human diseases including, for example, AIDS, influenza, cancer, SARS, and the common cold. Moreover, natural and engineered viruses have potential applications as vaccines and anti-cancer therapeutics. We propose in the first stage of this project to advance a quantitative and integrative understanding of vesicular stomatitis virus (VSV) by building a model of its growth. VSV ranks among the best-characterized viruses. Specific aims are to: (1) develop a data-driven intracellular computational model for the one-cycle growth of VSV, (2) evaluate the model using experimental data from a panel of recombinant VSV strains, and (3) employ the model to predict how gene order affects VSV growth. In natural host organisms viral infections span beyond one-cycle of growth, they spread spatially, and different infected cells produce different levels of virus. The second stage of the project will begin to address these realities by expanding our initial virus model to: (A) simulate the spatial spread of virus over many generations, and (B) examine how stochastic effects influence VSV one-cycle growth. Specifically, in project (A) we will develop a computational model that couples VSV growth with its spatial spread over many infection cycles. We will perform experiments to enable this model to incorporate and account for experimentally observed inhibitory effects of interferon-mediated cell-cell signaling on VSV growth and spread. In project (B) we will carry out single-cell experimental measurements of infection intermediates and production of virus progeny. At the same time, we will develop a stochastic model of VSV one-cycle growth to interpret these data and assess the role of stochastic effects on virus production by single infected cells. All computer simulations will be solved using the open-source numerical software GNU Octave (www.octave.org), an interactive system for numerical computations that has a growing worldwide user base. Data and software from this project, including a new method for parameter estimation for stochastic models, will be disseminated through a project-dedicated website.

描述（由申请人提供）：我们的长期目标是了解基因组及其环境之间的相互作用如何影响简单生物的生长。我们专注于病毒的基因组，因为它们具有少量基因，这些基因的基本功能通常是已知的，并且病毒生长周期的阶段经常被很好地表征。病毒还引起许多人类疾病，包括例如艾滋病，流感，癌症，SARS和普通感冒。此外，天然和工程病毒具有潜在的应用，作为疫苗和抗癌治疗剂。我们在该项目的第一阶段提出，通过构建其增长模型来提高对囊泡气孔病毒（VSV）的定量和综合理解。 VSV排名最佳的病毒。具体目的是：（1）为VSV的单周期生长开发数据驱动的细胞内计算模型，（2）使用来自重组VSV菌株的实验数据评估模型，（3）采用该模型来预测基因序列如何影响VSV的生长。在天然宿主生物体中，病毒感染超出了一个生长的一环，它们在空间上扩散，不同感染的细胞会产生不同水平的病毒。该项目的第二阶段将通过将我们的初始病毒模型扩展到以下几代人的初始病毒模型来解决这些现实，并模拟病毒在许多世代的空间扩散，（b）检查随机效应如何影响VSV一环生长。具体而言，在项目（a）中，我们将开发一个计算模型，该模型将VSV增长与其在许多感染周期中的空间扩散相结合。我们将执行实验，以使该模型能够合并并解释干扰素介导的细胞 - 细胞信号对VSV生长和扩散的抑制作用。在项目（b）中，我们将对感染中间体和病毒后代的产生进行单细胞实验测量。同时，我们将开发一个VSV一环生长的随机模型，以解释这些数据并评估单个感染细胞对病毒产生的随机作用的作用。所有计算机仿真将使用开源数值软件GNU八度（www.octave.org）来解决，这是一种用于数值计算的交互式系统，该系统在全球范围内增长。该项目的数据和软件，包括用于随机模型的参数估计方法的新方法，将通过项目划定的网站传播。