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: 10059172
• 负责人: Jesse D Bloom
• 金额: $ 48.88万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH 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/10059172
• 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 evaluation; 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 这种非常广泛的抗HIV抗体的隔离揭示了脆弱性的位置 在病毒的表面蛋白上，env。现在正在进行重大努力以引发此类抗体 用疫苗或直接使用抗体作为治疗。这种疫苗的设计 疗法需要仔细表征单克隆抗体和多克隆 血清认可的环境。我们最近开发了一种新的基于深层的方法 在功能上表征大规模的抗体-ENV相互作用。在这里，我们会很大 通过使您可以轻松，完全绘制该方法来扩展这种方法的实用性 所有氨基酸突变对中和的影响对病毒识别的影响 中和抗体或血清。具体来说，我们将： 1）创建带有所有单个氨基酸突变的病毒库，以及 突变的许多组合。这些图书馆将以一种方式设计 使它们能够轻松，廉价地以深度测序为特征。 2）开发使用库有效映射突变如何影响的方法 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映射环境突变如何影响识别 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，以便它们可以轻松 由整个艾滋病毒研究界使用。总体而言，这项工作将发展强大 在功能上绘制突变与HIV的抗原作用的方法。这样的地图将有助于 艾滋病毒的基本研究并告知疫苗和治疗的设计。