Systems Epigenomics of Persistent Bloodstream Infection
Project Number1U19AI172713-01
Contact PI/Project LeaderYEAMAN, MICHAEL R
Awardee OrganizationLUNDQUIST INSTITUTE FOR BIOMEDICAL INNOVATION AT HARBOR-UCLA MEDICAL CENTER
Description
Abstract Text
PROJECT ABSTRACT
Persistent bloodstream infections are life-threatening infectious disease emergencies posing significant challenges
to effective treatment. Such infections occur when a pathogen is susceptible to an anti-infective agent in vitro but is not
cleared from the bloodstream in vivo when that anti-infective agent is used appropriately. As a result, anti-infective usage
increases, accelerating alarming increases in anti-infective resistance. This vicious cycle of persistence driving anti-
infective escalation driving resistance is an NIH high–priority concern. Bloodstream infections caused by
Staphylococcus aureus (SA) or Candida albicans (CA) are increasingly common. Of urgent concern, up to 35% of
patients with methicillin-resistant SA (MRSA) persistent bacteremia succumb even on gold-standard therapy. Likewise,
in patients with hematogenously disseminated candidiasis (HDC), mortality is 39% overall and 47% in those in the
intensive care unit, despite appropriate treatment. A disease mystery is central to such infections: the causative
pathogen is susceptible to antimicrobials in laboratory testing—but not in the human being. Importantly, persistence
reflects a unique type of treatment-refractory infections distinct from classical antibiotic resistance. Rather, persistent
MRSA or CA are elusive: they adapt to host immune responses and antibiotic stresses uniquely in vivo and then revert
quickly in vitro. Presently, there are few therapeutic options for persistent MRSA or CA bloodstream infections. Hence,
there is a critical, unmet need to understand the unique interactions of the human, pathogen and therapeutic factors
driving persistence outcomes.
Based on our extensive preliminary data, we believe that persistent infections caused by MRSA and CA result from
a three-way interaction of the pathogen, host immune response and antimicrobial agent in vivo. We hypothesize that
persistent isolates: 1) have specific epigenomes to enable persistence; 2) subvert innate immune programming
and memory for immune evasion; 3) evoke non-protective or maladaptive immune responses; and 4) exploit
contextual immunity as persistence reservoirs. We further posit that conventional approaches to study this clinically
urgent phenomenon are insufficient to understand it. We have developed three independent but synergistic research
Projects to overcome these limitations. Each Project brings proven strengths and innovative approaches to bear on
Specific Aims that synergize via a systems-based approach supported by outstanding technology, bioinformatics and
computational Cores. Here, we will use state-of-the-art technologies to comprehensively analyze the genetics and
epigenetics of pathogens and the host immune system in context of antimicrobial therapy in laboratory studies and
experimental models of infection. In turn, these data will be analyzed using powerful bioinformatics and computational
methods to detect hidden patterns within large complex datasets. By understanding these factors and their interactions,
new approaches to identify and treat high risk patients can be developed and applied to improve and save lives. These
goals are ideally aligned with priorities of the National Institutes of Health and Centers for Disease Control & Prevention.
Public Health Relevance Statement
PROJECT NARRATIVE
Persistent bloodstream infections are life-threatening emergencies that pose significant challenges to effective
treatment. A disease mystery is central to these infections: the causative pathogen is susceptible to antimicrobials in
laboratory testing—but not in the human being. Persistent bloodstream infections caused by Staphylococcus aureus
and Candida albicans are increasingly common, but there are few therapeutic options and patients frequently succumb.
In this U19 Center, we will use state-of-the-art technologies in synergistic research to understand the host-pathogen
interactions driving persistence. In turn, these data will be analyzed using powerful computational methods to detect
hidden patterns within large complex datasets. As a result, new approaches to identify and treat high risk patients can
be developed and applied to improve and save lives. These goals are ideally aligned with priorities of the National
Institutes of Health and Centers for Disease Control & Prevention.
NIH Spending Category
No NIH Spending Category available.
Project Terms
AccelerationAddressAlgorithmsAnti-Infective AgentsAntibiotic ResistanceAntibiotic TherapyAntibioticsAntifungal AgentsAntigensAutomobile DrivingBacteremiaBioinformaticsBloodBlood CirculationCandidaCandida albicansCenters for Disease Control and Prevention (U.S.)Chromosomal RearrangementClinicalCommunicable DiseasesComputer ModelsComputing MethodologiesDNA MethylationDataData SetDetectionDiagnosticDiseaseDisseminated candidiasisEmergency SituationEpigenetic ProcessEtiologyExperimental ModelsFungemiaGene ExpressionGene RearrangementGeneticGenotypeGoalsHealthcareHematogenousHospital MortalityHumanImmuneImmune EvasionImmune responseImmune systemImmunityImmunologic MemoryImmunotherapeutic agentIn VitroInfectionIntensive Care UnitsInterventionLaboratoriesLaboratory StudyLength of StayLibrariesLifeMacrophageMediatingMemoryMethodsMicrobial BiofilmsModelingMolecularMorbidity - disease rateNosocomial InfectionsOrganOutcomePathogenesisPatientsPatternPattern recognition receptorPhenotypePredispositionProcessProductivityReceptor SignalingRefractoryResearchResearch Project GrantsResistanceRiskSTAT proteinSTAT1 proteinSepsisSpecificityStaphylococcus aureusStressStudy modelsSystemSystems BiologyTechnologyTestingTherapeuticTissuesTrainingTranslatingUnited States National Institutes of HealthVariantVirulenceWorkantimicrobialantimicrobial drugantimicrobial tolerancebiobankcandidemiacell injurychronic infectioncomplex datacytokinedata managementeffective therapyepigenetic memoryepigenomeepigenomicshigh riskimprovedin vivoinnate immune mechanismsinnovationinsightmethicillin resistant Staphylococcus aureusmethylomicsmortalitymouse modelneutrophilnovelnovel strategiespathogenpharmacologicprediction algorithmpredictive modelingpreventprogramsprospectiveprototyperesponsescreeningsexsuccesssynergismtherapeutic candidatevaccine strategy
National Institute of Allergy and Infectious Diseases
CFDA Code
855
DUNS Number
069926962
UEI
LTJVF4QSFCP9
Project Start Date
10-August-2023
Project End Date
31-May-2028
Budget Start Date
10-August-2023
Budget End Date
31-May-2024
Project Funding Information for 2023
Total Funding
$2,304,639
Direct Costs
$1,916,683
Indirect Costs
$387,956
Year
Funding IC
FY Total Cost by IC
2023
National Institute of Allergy and Infectious Diseases
$2,304,639
Year
Funding IC
FY Total Cost by IC
Sub Projects
No Sub Projects information available for 1U19AI172713-01
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The Project Outcomes shown here are displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed are those of the PI and do not necessarily reflect the views of the National Institutes of Health. NIH has not endorsed the content below.
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