Bioinformatics and Statistics

生物信息学和统计学

• 批准号: 10370982
• 负责人: Kshitij Wagh
• 金额: $ 36.17万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-03-07 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10370982
• 关键词: Affinity; Antibodies; Antibody Response; Antigens; B cell repertoire; B-Lymphocytes; Bioinformatics; Biological; Biological Models; Biological Phenomena; Biology; Chronic; Collaborations; Complement; Complex; Data; Development; Epitopes; Evolution; Foundations; Glycoproteins; Goals; HIV Infections; HIV-1; Helper-Inducer T-Lymphocyte; Human; Immunogenetics; Immunoglobulin Somatic Hypermutation; Individual; Infection; Lead; Macaca mulatta; Modeling; Molecular; Pathway Analysis; Pathway interactions; Pattern; Polysaccharides; Prevalence; Publishing; Reproducibility; Resistance; Rhesus; Series; Statistical Models; Structure of germinal center of lymph node; System; T-Lymphocyte; Testing; Vaccinated; Vaccination; Vaccine Design; Vaccines; Variant; Viral; computational pipelines; design; in vivo; in vivo Model; iterative design; longitudinal analysis; man; neutralizing antibody; novel; pressure; prevent; protective efficacy; simian human immunodeficiency virus; statistics; transcriptomics; vaccine efficacy; vaccine evaluation

PROJECT SUMMARY Vaccines that can induce broadly neutralizing antibodies (bNAbs) will be needed to protect against the global diversity of HIV-1 strains, however they do not currently exist (1,2). Vaccine induction of bNAbs will require two critical steps. First, priming of the appropriate bNAb precursors that, due to unusual features, are rare in the naïve human B-cell repertoire (3–5). Second, such precursors will need to be guided to acquire critical somatic hypermutations that confer heterologous neutralization potency and breadth (6). While it is clear that bNAbs evolve in natural HIV-1 infections through years of Env-antibody (Ab) coevolution, it is not clear how to trans- late these findings to design immunogens that can reproducibly prime and mature bNAbs across multiple hosts (1,5,7). In our last HIVRAD project, we developed a novel rhesus macaque (RM) SHIV infection model that re- capitulated several key features of Env-bNAb coevolution (8,9). We also showed that prior vaccination and in- fection with SHIVs bearing particular germline-targeting Envs could accelerate bNAb development. Thus, our rhesus model system thus provides a unique setting where reproducible induction of bNAbs in (S)HIV infec- tions can be studied. In this renewal, we will leverage this system to develop a vaccination and SHIV infection strategy that will lead to development of V3 glycan bNAbs in an accelerated and reproducible manner across multiple rhesus hosts. Our scientific premise is that a better understanding of the common Env-Ab coevolu- tionary patterns leading to V3 glycan bNAb development will allow design of immunogens that can prime and mature multiple V3 glycan bNAb lineages. Our Bioinformatics and Statistics Core (Core C) will provide bioin- formatic and statistical modeling analyses to facilitate these overall HIVRAD goals. We will analyze Env evolu- tion in SHIV-infected RMs from Project 1 by applying our novel computational pipeline to longitudinal se- quence data generated by Core B. We will identify the similarities and differences between the neutralization profiles of newly identified rhesus V3 glycan bNAbs (Project 1) and previously known V3 glycan bNAbs (Aim 2). Using the above two studies, we will iteratively design immunogens that are capable of engaging precur- sors of multiple V3 glycan bNAb lineages and of maturing them towards neutralization breadth in collaboration with Core B and Project 3 (Aim 3). Finally, we will provide statistical modeling of in vivo vaccine efficacy (Pro- ject 1) and other complex biological problems across all Projects.

项目摘要 将需要能够诱导广泛中和抗体（bNAb）的疫苗来预防全球性流感。 HIV-1病毒株的多样性，但它们目前并不存在（1，2）。bNAb的疫苗诱导将需要两个 关键步骤。首先，引发适当的bNAb前体，由于不寻常的特征，在 幼稚人B细胞库（3-5）。第二，这些前体需要被引导以获得关键的体细胞， 赋予异源中和效力和宽度的超突变（6）。虽然很明显bNAb 通过多年的Env-抗体（Ab）共同进化，在自然的HIV-1感染中进化，目前尚不清楚如何反式 将这些发现用于设计能够在多个宿主中重复引发和成熟bNAb的免疫原 （1、5、7）。在我们上一个HIVRAD项目中，我们开发了一种新的恒河猴（RM）SHIV感染模型， 放弃了Env-bNAb共同进化的几个关键特征（8，9）。我们还发现，之前的疫苗接种和- 用携带特定生殖系靶向Env的SHIV转染可加速bNAb发育。所以我们 因此，恒河猴模型系统提供了一种独特的环境，其中在（S）HIV感染中可再现地诱导bNAb， 可以研究。在这次更新中，我们将利用这一系统开发疫苗和SHIV感染 该策略将导致V3聚糖bNAb以加速和可重现的方式开发， 多个恒河猴宿主我们的科学前提是，更好地了解共同的Env-Ab coevolu- 导致V3聚糖bNAb形成的模式将允许设计可以引发和 成熟的多个V3聚糖bNAb谱系。我们的生物信息学和统计学核心（核心C）将提供生物信息学， 形式和统计建模分析，以促进这些整体HIVRAD目标。我们将分析环境演变- 通过将我们的新型计算管道应用于纵向选择， 由核心B生成的序列数据。我们将确定中和之间的异同 新鉴定的恒河猴V3聚糖bNAb（项目1）和先前已知的V3聚糖bNAb（目的 2）。利用上述两项研究，我们将反复设计能够参与前趋化的免疫原。 多种V3聚糖bNAb谱系的突变体，并使它们协同向中和宽度成熟 核心B和项目3（目标3）。最后，我们将提供体内疫苗效力的统计建模（Pro-100）。 项目1）和所有项目中的其他复杂生物问题。