Systems Vaccinology Approaches to Define and Predict Immunity in Response to Nontyphoidal Salmonella Conjugate Vaccines

定义和预测非伤寒沙门氏菌结合疫苗免疫反应的系统疫苗学方法

• 批准号: 10428968
• 负责人: Scott M. Baliban
• 金额: $ 12.92万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-01 至 2027-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10428968
• 关键词: Adult; Africa South of the Sahara; Animal Model; Antibiotics; Antibodies; Antibody Response; Antibody-mediated protection; Area; Award; Bacterial Infections; Bacterial Model; Bioinformatics; Biological Markers; Chemicals; Child; Childhood; Communicable Diseases; Complement; Computational Biology; Computer Analysis; Computer Models; Conjugate Vaccines; Data; Data Set; Development; Disease; Doctor of Philosophy; Early identification; Elements; Ensure; Flagellin; Future; Gene Expression; Genetic Transcription; Glycoconjugates; Goals; Gram-Negative Bacteria; Human; Human Volunteers; Immune Sera; Immune response; Immunity; Immunization; Immunology; Infant; Infection; Investigation; Knowledge; Light; Link; Machine Learning; Measures; Mentored Research Scientist Development Award; Mentors; Metabolic; Modeling; Molecular; Molecular Profiling; Morbidity - disease rate; Multiomic Data; Mus; Nature; O Antigens; Pathogenicity; Pathway interactions; Phenotype; Polysaccharides; Positioning Attribute; Process; Program Development; Proteins; Public Health; Research; Research Personnel; Resistance; Salmonella; Salmonella Vaccines; Salmonella infections; Salmonella typhimurium; Serology; Serology test; Serum; Surface; System; Systemic infection; Target Populations; Training; Vaccinated; Vaccination; Vaccines; Virulent; antimicrobial; base; career; career development; clinical development; cohort; complex data; data integration; design; efficacy trial; immunogenic; in vivo; infancy; insight; machine learning algorithm; macrophage; metabolomics; monomer; mortality; mouse model; non-typhoidal Salmonella; novel; predictive modeling; predictive signature; rational design; research clinical testing; response; seroconversion; success; transcriptomics; vaccination outcome; vaccine candidate; vaccine development; vaccine immunogenicity; vaccine response; vaccine-induced antibodies; vaccine-induced immunity; vaccinology

PROJECT SUMMARY This proposal is for a Mentored Research Scientist Development Award (K01) for Scott Baliban, Ph.D. Training: My long-term career goal is to become an independent investigator in systems vaccinology, focusing on defining the elements that support protective immune responses to pediatric bacterial infections and using this knowledge to predict infection and vaccination outcomes. My current research expertise involves developing mouse models of bacterial infectious disease and exploring functional and protective aspects of vaccine-induced antibody responses. This application presents a five-year career development program meant to expand my vaccinology toolkit with new areas of expertise in bioinformatics and computational biology. Specifically, I will receive training in analyzing rich and complex data sets using multi-omics data integration and machine learning. My mentoring and advising team are experts in all areas of my proposed research, and I have designed a rigorous training plan that will ensure my success throughout the award. Research: The global rise in pediatric infections caused by invasive nontyphoidal Salmonella (iNTS) serovars Typhimurium and Enteritidis has created an urgent public health crisis. We have developed novel glycoconjugate vaccines consisting of the iNTS surface polysaccharide (core-O-polysaccharide [COPS]) linked to the flagellar monomer protein (FliC). COPS:FliC conjugates are immunogenic and protective in animal models; however, less is known about the mechanisms that support successful immunization as well as the in vivo effector function of protective vaccine-induced antibodies. My preliminary data demonstrate that infant mice respond sub-optimally to COPS:FliC immunization as compared to adult vaccine recipients and that COPS:FliC-induced antibodies are sufficient for robust protection against lethal iNTS challenge. In Aim 1, using S. Enteritidis COPS:FliC as an exemplar conjugate vaccine, I will build a predictive model of vaccine responsiveness based on both gene expression and metabolite perturbations after vaccination. In Aim 2, I will decipher the in vivo functionality of human anti-COPS:FliC antibodies using the infant mouse model of fatal iNTS challenge. Outlook: This study will identify vaccine-induced molecular pathways that correlate with COPS:FliC vaccination outcomes. It will also establish the in vivo importance of specific antibody effector functions for protection against in infant mice. These findings will support an R01 application where I will derive more accurate predictive models of COPS:FliC response quality by assessing the temporal dynamics of metabolomic and transcriptomic responses to vaccination in mice. This approach will be extended to S. Typhimurium COPS:FliC conjugates, and ultimately the predictive models will be verified in vaccinated human infants. I will also investigate mechanistic antibody correlates of protection in the infant mouse model with the goal of developing serological assays to measure anti-microbial functions. At the completion of the K01, I will be uniquely positioned for an independent career where I will apply systems vaccinology approaches to develop novel conceptual frameworks for infant immunology and the vaccination process.

项目概要 该提案旨在为 Scott Baliban 博士授予指导研究科学家发展奖 (K01)。训练： 我的长期职业目标是成为系统疫苗学的独立研究者，专注于定义 支持对儿科细菌感染的保护性免疫反应的元素并利用这些知识 预测感染和疫​​苗接种结果。我目前的研究专长包括开发小鼠模型 细菌传染病的研究并探索疫苗诱导抗体的功能和保护作用 回应。该应用程序提供了一个为期五年的职业发展计划，旨在扩展我的疫苗学 具有生物信息学和计算生物学新专业领域的工具包。具体来说，我将接受培训 使用多组学数据集成和机器学习分析丰富而复杂的数据集。我的指导 和顾问团队都是我所提议研究的各个领域的专家，我设计了严格的培训 确保我在整个颁奖过程中取得成功的计划。研究：全球儿童感染率上升 侵袭性非伤寒沙门氏菌 (iNTS) 血清型鼠伤寒和肠炎引起了紧急公众的关注 健康危机。我们开发了由 iNTS 表面多糖组成的新型复合糖疫苗 （核心-O-多糖 [COPS]）与鞭毛单体蛋白 (FliC) 连接。 COPS：FliC 缀合物是 动物模型中的免疫原性和保护性；然而，人们对支持的机制知之甚少。 成功的免疫以及保护性疫苗诱导抗体的体内效应功能。我的 初步数据表明，与相比，幼年小鼠对 COPS:FliC 免疫的反应欠佳 成人疫苗接种者，COPS:FliC 诱导的抗体足以提供强有力的保护 致命的 iNTS 挑战。在目标 1 中，我将使用肠炎沙门氏菌 COPS:FliC 作为示例结合疫苗，构建一种 基于基因表达和代谢物扰动的疫苗反应预测模型 疫苗接种。在目标 2 中，我将使用婴儿破译人类抗 COPS:FliC 抗体的体内功能 致命性 iNTS 挑战的小鼠模型。展望：这项研究将确定疫苗诱导的分子途径 与 COPS:FliC 疫苗接种结果相关。它还将确定特异性抗体在体内的重要性 效应器功能对幼年小鼠具有保护作用。这些发现将支持 R01 应用程序，我将 通过评估 COPS:FliC 响应质量的时间动态，得出更准确的预测模型 小鼠对疫苗接种的代谢组学和转录组学反应。这种方法将被推广到S。 鼠伤寒 COPS：FliC 结合物，最终预测模型将在接种疫苗的人体中得到验证 婴儿。我还将研究婴儿小鼠模型中抗体与保护的机制相关性 开发血清学测定法来测量抗微生物功能的目标。完成 K01 后，我将 具有独特的独立职业定位，我将应用系统疫苗学方法来开发 婴儿免疫学和疫苗接种过程的新概念框架。