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.

项目摘要 该建议是为斯科特·巴利班（Scott Baliban）博士的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，重点是定义 支持对小儿细菌感染的保护性免疫反应并使用这些知识的元素 预测感染和疫​​苗接种结果。我目前的研究专业知识涉及开发鼠标模型 细菌传染病以及探索疫苗诱导抗体的功能和保护性方面 回答。该申请提出了一项五年的职业发展计划，旨在扩大我的疫苗。 具有生物信息学和计算生物学专业知识的新领域工具包。具体来说，我将接受培训 在使用多摩斯数据集成和机器学习分析丰富而复杂的数据集时。我的指导 咨询团队是我拟议研究的所有领域的专家，我设计了严格的培训 计划将确保我在整个奖励中取得成功。研究：小儿感染的全球增加引起 通过侵入性非细沙门氏菌（INTS）血清鼠伤寒和肠肠typhimurium和Enteritidis创建了紧急的公众 健康危机。我们已经开发了由INTS表面多糖组成的新型糖缀合物疫苗 （Core-O-Polysaccharide [COPS]）与鞭毛单体蛋白（FLIC）相关。 COPS：烟熏夫人 动物模型中的免疫原性和保护性；但是，对支持的机制知之甚少 保护性疫苗诱导的抗体的成功免疫以及体内效应子功能。我的 初步数据表明，婴儿小鼠对警察的反应：与COP的反应：FLIC免疫相比 对于成年疫苗接受者和COPS：FLIC诱导的抗体足以保护 致命的INT挑战。在AIM 1中，使用S. Enteritidis Cops：FLIC作为一种示例性结合疫苗，我将建造一个 基于基因表达和代谢产物扰动的疫苗反应的预测模型 疫苗接种。在AIM 2中，我将破译人类抗COPS的体内功能：使用婴儿的FLIC抗体 鼠标致命的INT挑战模型。展望：这项研究将确定疫苗诱导的分子途径 与COPS相关：FLIC疫苗接种结果。它还将确定特定抗体的体内重要性 效应子功能可在婴儿小鼠中进行保护。这些发现将支持R01应用程序 通过评估的时间动力学来得出COPS的更准确的预测模型：FLIC响应质量 代谢组和转录组对小鼠疫苗接种的反应。这种方法将扩展到S。 鼠伤寒警察：氟结合物，最终将在接种人类中验证预测模型 婴儿。我还将研究婴儿小鼠模型中保护的机理抗体与 开发血清学测定以测量抗微生物功能的目标。 K01完成时，我将 在独立职业中独特地定位，我将采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型概念框架。