Project 2 - Host-virus networks regulating flu replication and host responses ex vivo

项目 2 - 调节流感复制和宿主离体反应的宿主病毒网络

基本信息

批准号：
10080715
负责人：
SUMIT K CHANDA
金额：
$ 56.88万
依托单位：
ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-01-20 至 2022-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10080715
关键词：
Affect Antiviral Therapy Biochemical Biological Biological Models Cells Cessation of life Clinical Clinical Data Clustered Regularly Interspaced Short Palindromic Repeats Data Development Disease Disease Outcome Disease Progression Epidemic Epigenetic Process Epithelial Cells Evaluation Genes Genetic Genetic Polymorphism Genetic Screening Genetic Transcription Human Immune Immune response Infection Inflammatory Response Influenza Influenza A virus Investigation Life Cycle Stages Link Lung diseases Machine Learning Maps Measurement Medical Metabolic Modeling Molecular Molecular Profiling Network-based Outcome Pathogenicity Pathway interactions Pneumonia Post-Translational Protein Processing Proteins Proteome Proteomics Public Health Research Personnel Role Sampling Severities Severity of illness Systems Biology Therapeutic Tracheobronchial Validation Viral Viral Pathogenesis Virus Virus Diseases Virus Replication base biomarker identification biomarker signature cell type clinical biomarkers clinical phenotype data integration data modeling flu in vivo in vivo Model influenza infection insight loss of function machine learning algorithm macrophage metabolic profile metabolome molecular modeling monocyte next generation novel novel therapeutics pathogen predictive marker predictive modeling predictive signature prevent programs resilience response single-cell RNA sequencing therapeutic target tool transcriptome

项目摘要

PROJECT 2: Host-virus networks regulating flu replication and host responses ex vivo. Sumit Chanda, Project Leader; Megan Shaw, Co-Investigator; Ivan Marazzi, Co-Investigator, Nevan Krogan , Co-Investigator. In this proposal, we hypothesize that multiple, discrete molecular pathways determine influenza disease severity, and that these pathways elicit biomarker signatures that can be identified through network-based modeling of system-level measurements. In Project 2, we propose to utilize leading edge OMICS approaches to identify ex vivo molecular signatures that correlate with clinical disease outcomes. The elucidation and characterization of factors that govern outcome-related biomarker signatures offer the potential for the development of novel antiviral therapies. In Aim 1, we will use a systems biology approach to elucidate network signatures associated with clinical influenza severity. Here, we will profile changes to the host transcriptome, proteome and metabolome, in response to infection using viruses of different pathogenicity, as well as additional host perturbations linked to clinical outcome. Ex vivo molecular signatures correlated with disease severity will be integrated and modeled with in vivo and clinical data generated in Project 1. In Aim 2, we propose to use genetic tools to identify nodes within outcome-related molecular signatures that are critical regulators of host response pathways and viral replication (`driver genes'). Both Aims 1 and 2 will rely on a paradigm of reiterative experimentation and modeling to link ex vivo signatures to clinical phenotypes, and identify the host proteins and pathways that govern them. In Aim 3, those genes found to regulate pathways and signatures associated with disease outcome (driver genes) will be further characterized. We propose to employ CRISPR-based analysis of transcriptional, epigenetic, proteomic, and metabolic profiles to provide insight into the role of these factors in regulating responses linked to disease outcomes (CRISPR-OMICs). Additional molecular, cellular, biochemical and in vivo studies will be conducted to further characterize those nodes that determine disease outcomes as potential therapeutic targets.

项目 2：宿主病毒网络调节流感复制和离体宿主反应。 Sumit Chanda，项目负责人；梅根·肖（Megan Shaw），联合研究员； Ivan Marazzi，联合研究员，Nevan Krogan，共同研究员。在这个提议中，我们假设多种、离散的分子途径决定流感疾病严重性，并且这些途径引发可以通过基于网络来识别的生物标志物特征系统级测量的建模。在项目 2 中，我们建议利用领先的 OMICS 方法识别与临床疾病结果相关的离体分子特征。澄清和控制结果相关生物标志物特征的因素的表征为开发新型抗病毒疗法。在目标 1 中，我们将使用系统生物学方法来阐明与临床流感严重程度相关的网络特征。在这里，我们将分析主机的更改转录组、蛋白质组和代谢组，响应不同致病性病毒的感染，如以及与临床结果相关的其他宿主扰动。离体分子特征与相关疾病严重程度将与项目 1 中生成的体内和临床数据进行整合和建模。在目标 2 中，我们建议使用遗传工具来识别与结果相关的分子特征中至关重要的节点宿主反应途径和病毒复制的调节因子（“驱动基因”）。目标 1 和 2 都将依赖于将离体特征与临床表型联系起来的重复实验和建模范例，以及识别宿主蛋白质和控制它们的途径。在目标 3 中，那些被发现调节通路的基因与疾病结果相关的特征（驱动基因）将得到进一步表征。我们建议采用基于 CRISPR 的转录、表观遗传、蛋白质组和代谢图谱分析来提供深入了解这些因素在调节与疾病结果相关的反应中的作用 (CRISPR-OMIC)。将进行额外的分子、细胞、生化和体内研究，以进一步表征这些确定疾病结果作为潜在治疗目标的节点。