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: 10559619
• 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/10559619
• 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; Link; Machine Learning; Macrophage; 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 Vaccines; Salmonella infections; Salmonella typhimurium; Serology; Serology test; Serum; Surface; System; Systemic infection; Target Populations; Training; Vaccinated; Vaccination; Vaccines; Virulent; antimicrobial; career; career development; clinical development; cohort; complex data; data integration; design; efficacy trial; immunogenic; in vivo; infancy; insight; machine learning algorithm; metabolomics; monomer; mortality; mouse model; non-typhoidal Salmonella; novel; predictive modeling; predictive signature; rational design; research clinical testing; response; seroconversion; skills; 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.

项目总结 本提案旨在为Scott Baliban博士培训颁发导师研究科学家发展奖(K01)： 我的长期职业目标是成为一名系统疫苗学的独立研究员，专注于定义 支持对儿科细菌感染的保护性免疫反应的要素以及利用这一知识 以预测感染和疫苗接种结果。我目前的研究专长是开发老鼠模型 细菌感染性疾病和疫苗诱导抗体的功能和保护方面的探索 回应。这份申请提供了一个为期五年的职业发展计划，旨在扩大我的疫苗接种 工具包具有生物信息学和计算生物学领域的新专业知识。具体地说，我将接受培训 使用多组学数据集成和机器学习分析丰富和复杂的数据集。我的导师 和顾问团队都是我建议研究的各个领域的专家，我设计了一个严格的培训 这一计划将确保我在整个颁奖过程中取得成功。研究：全球儿科感染人数上升导致 由侵袭性非伤寒沙门氏菌(INTS)血清型鼠伤寒沙门氏菌和肠炎杆菌造成的紧急公众 健康危机。我们已经开发了由INTS表面多糖组成的新型糖结合疫苗 (核心-O-多糖[COPS])连接到鞭毛单体蛋白(Flic)。COPS：FLIC共轭是 在动物模型中具有免疫原性和保护性；然而，对支持 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 初步数据显示，幼鼠对COPS：FL IC免疫的反应是次优的 对于成人疫苗接受者和COPS：Flc诱导的抗体足以强大地预防 致命的INTS挑战。在目标1中，使用S.Enteritidis COPS：FLIC作为范例结合疫苗，我将建立一个 基于基因表达和代谢产物扰动的疫苗免疫应答预测模型 接种疫苗。在目标2中，我将破译人类抗COPS的体内功能：使用婴儿的Flc抗体 小鼠模型对INTS的致命挑战。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在体内的重要性。 效应器的功能是保护幼鼠免受感染。这些发现将支持R01应用程序，我将 通过评估COPS的时间动态获得更准确的COPS预测模型：FLIC响应质量 小鼠接种疫苗后的代谢学和转录反应。这一方法将扩展到S。 鼠伤寒杆菌COPS：flic结合物，最终预测模型将在接种疫苗的人身上得到验证 婴儿。我还将研究在幼鼠模型中保护作用的机制抗体与 发展血清学检测以测量抗微生物功能的目标。在K01竣工时，我将 在独立的职业生涯中处于独特的地位，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。