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Human Immunomics & Trained Immunity in Persistent Candidemia

人类免疫组学

基本信息

批准号：
10551710
负责人：
ELAINE F REED
金额：
$ 43.61万
依托单位：
LUNDQUIST INSTITUTE FOR BIOMEDICAL INNOVATION AT HARBOR-UCLA MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-08-10 至 2028-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10551710
关键词：
ATAC-seq Address Affect Anti-Infective Agents Antibiotic Therapy Antibiotics Antifungal Therapy Antigen Presentation Attenuated Automobile Driving Big Data Biological Assay Biometry Blood specimen Candida albicans Candidiasis ChIP-seq Chromatin Clinical Clinical Research Coculture Techniques Communicable Diseases Computer Analysis Computer Models DNA Methylation Data Disease Outcome Disseminated candidiasis Enhancers Enzymes Epigenetic Process Experimental Models Genetic Genetic Transcription Goals Hematogenous Hematology Histone Acetylation Hospitals Human Immune Immune Response Genes Immune response Immune system Immunity Immunology In Vitro Infection Innate Immune Response Integration Host Factors Interferon Type II Interferon alpha Intervention Life Link Macrophage Maps Mediating Methicillin Resistance Modification Molecular Multi-Drug Resistance Mus Myeloid Cells Natural Immunity Nitrous Oxide Outcome Oxygen Pathologic Pathway interactions Patients Peripheral Phagocytosis Plasma Prophylactic treatment Proteomics Research Role Sepsis Shapes Signal Pathway Signal Transduction Specificity Staphylococcus aureus Staphylococcus aureus infection Stimulus Sulfides Surface System Systems Biology T cell response T-Cell Activation T-Lymphocyte TNF gene Training Vaccines Validation adaptive immune response adaptive immunity beta-Glucans candidemia cathelicidin antimicrobial peptide chemokine chronic infection cytokine diagnostic tool epigenome epigenomic profiling epigenomics histone methylation immune function in vivo infection rate inhibitor innate immune function innovation insight machine learning model methylation pattern mortality multiple omics mutant network models novel pathogen peripheral blood pharmacologic predictive modeling predictive signature programs promoter prophylactic resistant strain response statistical learning survival outcome targeted treatment therapeutic development therapeutic target transcription factor transcriptome transcriptome sequencing transcriptomics whole genome

项目摘要

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.

项目总结血液播散性念珠菌病(HDC)是医院最常见的侵袭性真菌种类全世界。尽管接受了抗真菌治疗，但这些感染的死亡率很高(40%)。同样，耐甲氧西林金黄色葡萄球菌(MRSA)可导致侵袭性和危及生命尽管接受了标准的抗感染治疗，但仍受到感染。因此，持久性反映了宿主-病原体在体内抗生素治疗的背景下发生的独特的相互作用。然而，宿主因素和机制涉及持续性MRSA和HDC的情况仍不清楚。本研究将使用基于系统的高吞吐量多组学平台和新颖的统计和计算方法提供全面的宿主对HDC和MRSA感染的体内外先天和适应性反应的纵向评估使用患者外周血、刺激特异性PAMP和患者来源的HDC血浆PAMP和分离物。创新成果包括：i)构建HDC和MRSA免疫图谱的深度免疫图谱；二)了解巨噬细胞新生增强子形成的刺激特异性及其如何影响转录景观和功能III)生成详细的分子图谱 HDC和MRSA感染期间的先天和获得性免疫反应；iv)结合使用用于解释和预测细胞和分子网络的生物统计学和计算模型免疫和持久的、可分辨的和存活的结果；以及v)可用药物的鉴定和验证重编程的表观基因组调控因子。对HDC和MRSA与宿主的互动的详细见解免疫系统将从根本上产生新的机械性假说和诊断工具来指导制定治疗策略。