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.

项目摘要血液传播念珠菌病（HDC）是医院环境中最常见的侵入性真菌物种全世界。尽管治疗了抗真菌疗法，但这些感染的死亡率较高（40％）。同样，金黄色葡萄球菌（MRSA）的耐甲氧西林菌株可能引起侵入性和威胁生命尽管治疗了标准抗感染疗法，但感染。因此，持久性反映了宿主病原体在体内抗生素疗法的情况下，相互作用发生。但是，宿主因素和机制参与持续的MRSA和HDC尚不清楚。这项研究将使用基于系统的高通量多媒体平台以及新颖的统计和计算方法，以提供全面的对HDC和MRSA感染的体外和体内和自适应反应的宿主的纵向评估使用患者外周血，刺激特定的PAMP和患者衍生的HDC血浆PAMP和分离株。创新的可交付成果包括：i）构建HDC和MRSA免疫概况的深入免疫轮廓； ii）了解巨噬细胞中从头增强子形成及其影响的刺激特异性转录景观和函数iii）生成了详细的分子图 HDC和MRSA感染期间先天和适应性免疫反应； iv）结合生物统计学和计算建模，以解释和预测受过训练的细胞和分子网络免疫和持久，解决和生存结果； v）识别和验证可药物重编程的表观基因组调节剂。详细的见解HDC和MRSA与主机的相互作用免疫系统立于产生根本的新机械假设和诊断工具来指导制定治疗策略。