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Human Immunomics & Trained Immunity in Persistent Candidemia

Human Immunomics & Trained Immunity in Persistent Candidemia
人类免疫组学
批准号:
10551710
负责人:
ELAINE F REED
金额:
$43.61万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-08-10 至 2028-05-31
关键词:
ATAC-seqAddressAffectAnti-Infective AgentsAntibiotic TherapyAntibioticsAntifungal TherapyAntigen PresentationAttenuatedAutomobile DrivingBig DataBiological AssayBiometryBlood specimenCandida albicansCandidiasisChIP-seqChromatinClinicalClinical ResearchCoculture TechniquesCommunicable DiseasesComputer AnalysisComputer ModelsDNA MethylationDataDisease OutcomeDisseminated candidiasisEnhancersEnzymesEpigenetic ProcessExperimental ModelsGeneticGenetic TranscriptionGoalsHematogenousHematologyHistone AcetylationHospitalsHumanImmuneImmune Response GenesImmune responseImmune systemImmunityImmunologyIn VitroInfectionInnate Immune ResponseIntegration Host FactorsInterferon Type IIInterferon alphaInterventionLifeLinkMacrophageMapsMediatingMethicillin ResistanceModificationMolecularMulti-Drug ResistanceMusMyeloid CellsNatural ImmunityNitrous OxideOutcomeOxygenPathologicPathway interactionsPatientsPeripheralPhagocytosisPlasmaProphylactic treatmentProteomicsResearchRoleSepsisShapesSignal PathwaySignal TransductionSpecificityStaphylococcus aureusStaphylococcus aureus infectionStimulusSulfidesSurfaceSystemSystems BiologyT cell responseT-Cell ActivationT-LymphocyteTNF geneTrainingVaccinesValidationadaptive immune responseadaptive immunitybeta-Glucanscandidemiacathelicidin antimicrobial peptidechemokinechronic infectioncytokinediagnostic toolepigenomeepigenomic profilingepigenomicshistone methylationimmune functionin vivoinfection rateinhibitorinnate immune functioninnovationinsightmachine learning modelmethylation patternmortalitymultiple omicsmutantnetwork modelsnovelpathogenperipheral bloodpharmacologicpredictive modelingpredictive signatureprogramspromoterprophylacticresistant strainresponsestatistical learningsurvival outcometargeted treatmenttherapeutic developmenttherapeutic targettranscription factortranscriptometranscriptome sequencingtranscriptomicswhole genome

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PROJECT SUMMARY Hematologic disseminated candidiasis (HDC) is the most common invasive fungal species in hospital settings worldwide. The mortality rate is high (40%) for these infections despite treatment with antifungal therapies. Similarly, methicillin-resistant strains of Staphylococcus aureus (MRSA) can cause invasive and life-threatening infections despite treatment with standard anti-infective therapies. Thus, persistence reflects host-pathogen interactions occurring uniquely in context of antibiotic therapy in vivo. However, host factors and mechanisms involved in persistent MRSA and HDC remain unclear. This study will use systems-based, high-throughput multi-omics platforms and novel statistical and computational approaches to provide a comprehensive longitudinal assessment of host in vitro and in vivo innate and adaptive responses to HDC and MRSA infection using patient peripheral blood, stimulus specific PAMPs and patient-derived HDC plasma PAMPs and isolates. Innovative deliverables include: i) Constructing an in-depth immune profile of HDC and MRSA immune profiles; ii) understand the stimulus-specificity of de novo enhancer formation in macrophages and how they affect transcriptional landscapes and functions iii) generate a detailed molecular map of the cross-talk between the innate and adaptive immune response during HDC and MRSA infection; iv) using the combination of biostatistics and computational modeling to explain and predict cellular and molecular networks driving trained immunity and persistent, resolving, and survival outcomes; and v) identification and validation of druggable epigenomic regulators of reprogramming. Detailed insights into the interaction of HDC and MRSA with the host immune system stand to generate fundamentally new mechanistic hypotheses and diagnostic tools to guide development of therapeutic strategies.
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