A combined computational and experimental approach to the evolution and role of the DNA sequence environment in targeting mutations to antibody V regions

项目总结 在我们对突变如何优先针对变量的理解上存在一个根本的差距 (V)体细胞超突变(SHM)期间免疫球蛋白(Ig)基因座的区域。这种差距的持续存在 限制了我们对涉及激活诱导脱氨酶(AID)的突变机制的了解 在免疫反应中以及AID在导致B细胞淋巴瘤和 其他癌症。这项拟议研究的长期目标是了解 保护我们免受感染所需的免疫突变。作为来自人类的高通量数据 抗体免疫反应的出现，为我们提供了新的机会来产生 解释SHM潜在机制的假说。我们现在建议生成进一步的假设 使用应用于其他数据库的计算模型，并使用CELICAL验证这些假设 和动物实验。我们的目标是了解是什么引导SHM穿过许多人类Ig Heavy 链V面域。我们的中心假设是V区SHM过程高度依赖于DNA 序列签名(S)，在很大程度上以确定性的方式驱动突变。这一假设得到了支持 根据我们利用人体活体数据得出的一些人类V区基因的初步结果，已经开始 使用独立的数据库和人类B细胞系的实验进行了验证。理由是 基于生物学机制的计算数据的评估，以及适当的生物学 实验，将揭示IGHV区域(IGHV 3-23、4-34、1-18、1-02等)之间的关键差异。那 导致这些V区中的每一个在对医学上重要的抗原的反应中占据主导地位。我们的 假说将通过追求两个具体目标来检验：1)确定DNA签名的程度 确定四个单独的人类IGHV基因的突变过程，这四个基因在疾病中很重要 回答；2)检查艾滋病热点和POLη热点之间的关系 V区基因，从而严格定义突变靶向签名。这两个目标也都需要学习 人V区基因及其在人细胞系和表达人V区小鼠中的修饰 区域，以进一步确认签名和确定分子机制在体内。我们的方法是 创新是因为我们提出的计算模型将是机械驱动的聚焦 关于艾滋病和POLη热点之间的相互作用，从而测试分子机制而不是 经典的统计模型使用完整的V区序列，忽略了潜在的生物学。此外， 关注我们将利用来自人类V区的新的高通量数据的机制，这些数据尚未 接受了抗原选择。我们的结果将与人类免疫球蛋白谱分析高度相关 目前难以解释的免疫反应，将有助于未来的疫苗和治疗性抗体 发展，以及帮助了解人类恶性肿瘤的突变，而艾滋病在其中发挥关键作用。

Project summary There is a fundamental gap in our understanding of how mutations are preferentially targeted to the variable (V) regions of the Immunoglobulin (Ig) loci during somatic hypermutation (SHM). The persistence of this gap has limited our understanding of the mutagenic mechanisms involving activation-induced deaminase (AID) in the immune response and in the role of AID in mis-targeting mutations leading to B-cell lymphomas and other cancers. The long-term goal of the proposed research is to understand the global targeting of mutations in immunity that are required to protect us from infections. As high-throughput data from human antibody immune responses became available, it provided us with new opportunities to generate hypotheses to explain the underlying mechanisms of SHM. We now propose to generate further hypotheses using computational models applied to additional databases and to validate these hypotheses using cellular and animal experiments. Our objective is to understand what directs SHM across the many human Ig heavy chain V-regions. Our central hypothesis is that the V-region SHM process is highly dependent on a DNA sequence signature(s) that drives mutations in a largely deterministic fashion. This hypothesis is supported by our preliminary results using human in vivo data from a few human V region genes and has begun to be validated using independent databases and experiments in human B cell lines. The rationale is that evaluations of computational data based upon biological mechanisms, together with appropriate biological experiments, will reveal the key differences between IGHV regions (IGHV 3-23, 4-34, 1-18, 1-02, etc.) that lead to the dominance of each of those V regions in the responses to medically important antigens. Our hypothesis will be tested by pursuing two specific aims: 1) identify the extent to which a DNA signature determines the mutation process in four individual human IGHV genes that are important in disease responses; 2) examine the relationship between AID hotspots and Polη hotspots across all the other human V region genes, thus rigorously defining a mutation targeting signature. Both aims will also entail studying human V region genes and modifications of them in human cell lines and in mice expressing a human V region to further confirm the signature and identify molecular mechanisms in vivo. Our approach is innovative because the computational models we are proposing will be mechanistically motivated focusing on the interaction between AID and Polη hotspots, thus testing molecular mechanisms as opposed to classic statistical models using whole V region sequences that ignore the underlying biology. In addition, to focus on mechanisms we will leverage new high-throughput data from human V regions that have not undergone antigen selection. Our results will be highly relevant to human IgV repertoire analyses from immune responses that are currently hard to interpret and will help future vaccine and therapeutic antibody development, as well as help to understand mutations in human malignancies where AID plays a key role.