Complete mapping of immune selection from antibodies to HIV

从抗体到 HIV 的免疫选择的完整图谱

• 批准号: 10593442
• 负责人: Jesse D Bloom
• 金额: $ 39.6万
• 依托单位: FRED HUTCHINSON CANCER CENTER
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-12-07 至 2023-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10593442
• 关键词: Academy; Address; Affect; Algorithmic Software; Amino Acids; Animals; Antibodies; Bar Codes; Big Data; Biological Assay; Communities; Computer software; Critiques; Data; Data Set; Enzyme-Linked Immunosorbent Assay; Escape Mutant; Evolution; Goals; HIV; HIV Antibodies; HIV envelope protein; HIV vaccine; Human; Immune; Immunity; Intuition; Libraries; Maps; Medical; Medicine; Membrane Proteins; Methods; Modernization; Monoclonal Antibodies; Mutation; Plasma; Rabies Vaccines; Research; Research Personnel; Resolution; Serum; Site; Structure; Techniques; Therapeutic; Vaccinated; Vaccine Design; Vaccines; Viral; Viral Proteins; Virus; Visualization; Work; base; computerized tools; cost; deep sequencing; design; env Gene Products; experimental study; improved; mutant; neutralizing antibody; open source; pressure; programs; prophylactic; response; tool; vaccine development; vaccine evaluation; vaccine strategy; vaccine-induced antibodies; vaccinology; web platform

PROJECT SUMMARY This isolation of exceptionally broad anti-HIV antibodies has revealed sites of vulnerability on the virus’s surface protein, Env. Major efforts are now underway to elicit such antibodies with vaccines, or to use the antibodies directly as therapeutics. The design of such vaccines and therapies requires carefully characterizing how monoclonal antibodies and polyclonal sera recognize Env. We have recently developed a new deep-sequencing based approach to functionally characterize antibody-Env interactions on a large scale. Here we will greatly extend the utility of this approach by making it possible to easily and completely map the effects of all amino-acid mutations on viral recognition by both neutralizing and non- neutralizing antibodies or sera. Specifically, we will: 1) Create libraries of viruses carrying all single amino-acid mutations to Env, as well as many combinations of mutations. These libraries will be designed in a way that enables them to be easily and cheaply characterized by deep sequencing. 2) Develop methods to use the libraries to efficiently map how mutations to Env affect virus recognition by neutralizing and non-neutralizing antibodies and sera. 3) Create algorithms and software to analyze and visualize the “Big Data” sets generated by the mappings. We will use these tools to completely map how Env mutations affect recognition by important monoclonal antibodies, as well as natural and vaccine-induced plasma responses. We will also distribute the experimental and computational tools so that they can be easily used by the entire HIV research community. Overall, this work will develop powerful methods to functionally map the antigenic effects of mutations to HIV. Such maps will aid in the basic study of HIV and inform the design of vaccines and therapeutics.

项目摘要 这种分离出的异常广泛的抗艾滋病毒抗体揭示了易受感染的部位 病毒表面蛋白Env.目前正在进行重大努力，以诱发这种抗体 或者直接使用抗体作为治疗剂。这种疫苗的设计 和治疗需要仔细表征如何单克隆抗体和多克隆抗体， 血清识别Env.我们最近开发了一种新的基于深度测序的方法， 在大规模上功能性地表征抗体-Env相互作用。在这里，我们将大大 扩展这种方法的实用性，使其能够轻松和完整地映射 所有氨基酸突变对中和和非中和病毒识别的影响 中和抗体或血清。具体而言，我们将： 1)创建携带Env的所有单个氨基酸突变的病毒库，以及 许多突变的组合。这些图书馆的设计方式 使它们能够通过深度测序容易且便宜地表征。 2)开发使用文库的方法，以有效地映射Env突变如何影响 通过中和和非中和抗体和血清识别病毒。 3)创建算法和软件来分析和可视化“大数据”集 由映射生成。 我们将使用这些工具来完全绘制Env突变如何影响识别， 重要的单克隆抗体，以及天然和疫苗诱导的血浆反应。 我们还将分发实验和计算工具，以便他们可以很容易地 被整个艾滋病研究界使用。总的来说，这项工作将发展强大的 功能性地绘制突变对HIV的抗原效应的方法。这些地图将有助于 艾滋病毒的基础研究，并为疫苗和治疗方法的设计提供信息。