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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

基本信息

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
项目类别：
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

项目摘要

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