Evolutionary dynamics of antibody affinity maturation

抗体亲和力成熟的进化动力学

• 批准号: 10318110
• 负责人: William S. DeWitt
• 金额: $ 0.66万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH CENTER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-01 至 2022-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10318110
• 关键词: Adaptive Immune System; Affinity; Alleles; Animal Model; Antibodies; Antibody Affinity; Antibody Repertoire; Antigen Targeting; Antigens; Autoimmunity; B cell repertoire; B-Cell Antigen Receptor; B-Lymphocytes; Back; Biological; Biological Models; Biology; Cells; Computational Biology; Computing Methodologies; Cre lox recombination system; Data; Dependence; Disabled Persons; Disease; Disease susceptibility; Equilibrium; Evolution; Experimental Designs; Experimental Models; Exposure to; Feedback; Future; Gene Combinations; Gene Frequency; Genes; Genetic Epistasis; Genetic Models; Genetic Recombination; Immune; Immune system; Immunization; Immunoglobulin-Secreting Cells; Immunologic Memory; Immunologic Receptors; Immunologics; Immunologist; Immunology; Individual; Interdisciplinary Study; Jaw; Knock-in; Knock-out; Lead; Learning; Life; Literature; Lymphocyte; Malignant Neoplasms; Mathematical Biology; Measurement; Measures; Mechanics; Memory B-Lymphocyte; Methods; Modeling; Monoclonal Antibodies; Mus; Mutate; Plasma Cells; Population; Population Genetics; Population Process; Process; Proliferating; Reaction; Recording of previous events; Research; Research Personnel; Resources; Role; Running; Secondary Immunization; Shapes; Specificity; Structure; Structure of germinal center of lymph node; System; Technology; Testing; Training; Transgenic Mice; Transgenic Organisms; Vertebrates; Work; adaptive immune response; antibody engineering; antigen antibody binding; antigen binding; computerized tools; cost; design; experimental study; fitness; model development; mouse development; mouse model; neutralizing antibody; pathogen; preservation; receptor; response; skills; statistics; theories; translational impact; translational potential; vaccination strategy

Project summary To defend against rapidly evolving pathogens, jawed vertebrates have specialized cells—lymphocytes—that evolve during an individual's lifetime to mount adaptive immune responses. Massive somatic diversity is maintained in loci that encode receptors on lymphocytes that can detect foreign antigen. B cells—lymphocytes that make antibodies—bind antigen with the B cell receptor (BCR), and diversify in microanatomical structures called germinal centers (GCs) where they proliferate while mutating the BCR. This process of affinity matura- tion is classically understood to impose selection for increased antigen binding affinity: surviving cells mature to become high-affinity memory B cells or plasma cells that secrete antibodies (the soluble form of the BCR). There is great potential for productive dialog between experiment, theory, and computation to learn new immunology and new evolutionary dynamics from these systems. Indeed, recent studies reveal a literature conflicted regarding GC evolution as adaptive toward high affinity. The hypothesis of this application is that GC evolutionary dynamics balance adaptation towards antigen specificity with neutral diversification that fortifies against antigenic drift. The research strategy is to develop quantitative models of GC evolution in a tight feedback loop with model organism experimental design of increasing complexity. Using mouse models, control can be exerted over B cell repertoire diversity, receptor affinity, and antigen targeting. Evolution in GCs can be tracked using both receptor sequencing and lineage tracing technology. Aim 1 will analyze GC BCR evolution in a mouse model with a monoclonal BCR and a model antigen exposure, such that all GC reactions constitute replicated evolution from the same ancestral state. Aim 2 will develop theoretical and computational tools to infer fitness, convergence, and contingency from the (quasi-)replicated evolutionary dynamics that characterize both our experimental models and natural repertoires. Aim 3 will design and analyze two mouse models of increasing repertoire complexity, and investigate recall responses to modified antigens. The training plan is designed to synthesize expertise in theoretical and computational evolutionary biology with immunology, and advance both hard and soft skills necessary for a future as a independent investigator. Co-sponsors Dr. Frederick Matsen and Dr. Kelley Harris combine expertise in mathematical and computa- tional biology and immunology, and population genetics. B cell immunologist Dr. Gabriel Victora will be a close collaborator; his lab will lead experimental development of the mouse models. I will also collaborate with theoretical physicist Dr. Armita Nourmohammad, who has expertise in rapid evolutionary dynamics. My thesis committee adds Dr. Phil Green and Dr. Joe Felsenstein as computational and theoretical resources. This interdisciplinary research team is matched to the proposed aims as a synthesis of distinct fields.

项目摘要 为了抵御快速进化的病原体，有颌脊椎动物有专门的细胞-淋巴细胞， 在个体的一生中进化以产生适应性免疫反应。巨大的躯体多样性 维持在编码淋巴细胞上的受体的基因座中，该受体可以检测外来抗原。B细胞淋巴细胞 使抗体与B细胞受体（BCR）结合，并在显微解剖结构上多样化 称为生发中心（GC），它们在BCR突变的同时增殖。这一成熟的过程-- 经典地理解为对增加的抗原结合亲和力施加选择：存活细胞成熟 成为高亲和力记忆B细胞或浆细胞，分泌抗体（BCR的可溶形式）。 在实验、理论和计算之间进行富有成效的对话，以学习新的知识， 免疫学和新的进化动力学从这些系统。事实上，最近的研究表明， 认为GC进化是适应高亲和力的。本申请的假设是GC 进化动力学平衡了对抗原特异性的适应与中性多样性， 抗原漂移 研究策略是在一个紧密的反馈回路中开发GC演变的定量模型， 模式生物实验设计的复杂性不断增加。使用鼠标模型，可以施加控制 超过B细胞库多样性、受体亲和力和抗原靶向。GC的演变可以使用 受体测序和谱系追踪技术。目的1将分析GC BCR在小鼠中的进化 具有单克隆BCR和模型抗原暴露的模型，使得所有GC反应构成重复 从同一个祖先进化而来。目标2将开发理论和计算工具来推断适合性， 收敛，和偶然性从（准）复制进化动力学的特点，我们都 实验模型和自然剧目。目的3将设计和分析两种小鼠模型， 库的复杂性，并研究对修饰的艾德抗原的回忆反应。 该培训计划旨在综合理论和计算进化生物学方面的专业知识 与免疫学，并推进未来作为一个独立的调查员所需的硬和软技能。 共同赞助者弗雷德里克·马特森博士和凯利·哈里斯博士联合收割机结合了数学和计算方面的专业知识， 功能生物学和免疫学以及群体遗传学。B细胞免疫学家Gabriel Victora博士将成为 密切合作者;他的实验室将领导小鼠模型的实验开发。我也会合作 理论物理学家阿米塔·努尔穆罕默德博士，他在快速进化动力学方面有专长。 我的论文委员会增加了Phil绿色博士和Joe Felsenstein博士作为计算和理论资源。 这个跨学科的研究团队与提出的目标相匹配，作为不同领域的综合。