grant

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

Organization UNIVERSITY OF MARYLAND BALTIMORELocation BALTIMORE, UNITED STATESPosted 1 Feb 2022Deadline 31 Jan 2027
NIHUS FederalResearch GrantFY20260-11 years old21+ years oldAb-mediated immunityAb-mediated protectionAdultAdult HumanAfrica South of the SaharaAnimal ModelAnimal Models and Related StudiesAntibiotic AgentsAntibiotic DrugsAntibioticsAntibodiesAntibody ResponseAntibody immunityAntibody protectionAntibody-mediated protectionAntiseraAreaAwardBacterial InfectionsBacterial ModelBacterial O AntigenBioinformaticsBiological MarkersBlood SerumChemicalsChildChild YouthChildhoodChildren (0-21)Clinical EvaluationClinical TestingCommunicable DiseasesComplementComplement ProteinsComputational BiologyComputer AnalysisComputer ModelsComputerized ModelsConjugate VaccinesDataData SetDevelopmentDiseaseDisorderDoctor of PhilosophyEarly identificationElementsEnsureFlagellinFutureGene ExpressionGene TranscriptionGenetic TranscriptionGlycansGlycoconjugatesGoalsGram-Negative BacteriaHumanHuman VolunteersImmune SeraImmune responseImmunityImmunizationImmunologyInfantInfectionInfectious DiseasesInfectious DisorderInvestigationInvestigatorsK01 AwardK01 MechanismK01 ProgramKnowledgeLinkMachine LearningMacrophageMeasuresMentored Research Scientist Development AwardMentored Training AwardMentorsMetabolicMiceMice MammalsMiscellaneous AntibioticModelingModern ManMolecularMolecular FingerprintingMolecular ProfilingMorbidityMultiomic DataMurineMusNatureO AntigensO-Specific PolysaccharidesPathogenicityPathway interactionsPh.D.PhDPhenotypePolysaccharidesPositionPositioning AttributeProcessProgram DevelopmentProteinsPublic HealthRNA ExpressionResearchResearch PersonnelResearch Scientist Development AwardResearchersResistanceS enterica serovar TyphimuriumS typhimuriumS. enterica TyphimuriumS. enterica serovar TyphimuriumS. typhimuriumSalmonella VaccinesSalmonella enterica TyphimuriumSalmonella enterica serovar TyphimuriumSalmonella infectionsSalmonella typhimuriumSalmonellosisSalmonellosis VaccinesSerologySerology testSerumSub-Saharan AfricaSubsaharan AfricaSurfaceSystemSystemic infectionTarget PopulationsTrainingTranscriptionVaccinatedVaccinationVaccination acquired immunityVaccination induced immunityVaccine Against SalmonellaVaccinesVirulentadulthoodanti-microbialantibody-mediated immunityantimicrobialbacteria infectionbacterial diseasebio-markersbiologic markerbiomarkercareercareer developmentclinical developmentclinical testcohortcomplementationcomplex datacomputational analysescomputational analysiscomputational modelingcomputational modelscomputer analysescomputer based modelscomputer based predictioncomputer biologycomputerized modelingdata integrationdesigndesigningdevelop a vaccinedevelop vaccinesdevelopment of a vaccinedevelopmentalefficacy trialhost responseimmune response to vaccinationimmune response to vaccinesimmune serumimmune system responseimmunogenicimmunoresponsein vivoinfancyinfantileinsightkidsmachine based learningmachine learned algorithmmachine learning algorithmmachine learning based algorithmmetabolism measurementmetabolomicsmetabonomicsmodel of animalmolecular profilemolecular signaturemonomermortalitymouse modelmultiple omic datamurine modelnon-typhoid Salmonellanon-typhoidal Salmonellanoveloutcome following vaccinationoutcome following vaccinepathwaypediatricpredictive modelingpredictive signaturerational designresearch clinical testingresistantresponseresult following vaccinationresult following vaccineseroconversionserology assayskillssuccesstooltranscriptomicsvaccination outcomevaccination resultvaccine acquired immunityvaccine antibodiesvaccine associated immune responsevaccine associated immunityvaccine candidatevaccine developmentvaccine immune responsevaccine immunogenicityvaccine induced antibodiesvaccine induced immune responsevaccine outcomevaccine responsevaccine responsivenessvaccine resultvaccine-induced antibodiesvaccine-induced immunityvaccine-induced protectionvaccine-induced responsevaccinologyyoungster
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Full Description

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.

Grant Number: 5K01AI168587-05
NIH Institute/Center: NIH

Principal Investigator: Scott Baliban

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