Project 2 - Ex Vivo Analysis of Coronavirus Tropism, Adaptation, Replication, and Host Response

项目2：冠状病毒趋向性、适应、复制和宿主反应的体外活体分析 在这个提议中，我们假设多个和离散的病毒-宿主相互作用和宿主对 感染决定了SARS-CoV-2的致病结局和宿主嗜性。我们进一步假设这些 可以通过基于网络的系统级测量建模来剖析关键电路，从而提供 开发新的抗病毒疗法的潜力。在项目2中，我们建议利用前沿的组学- 基于定义病毒-宿主相互作用和控制病毒复制的网络的测量 蝙蝠冠状病毒、SARS-CoV-1和SARS-CoV-2变种的嗜性/适应和宿主反应。在……里面 目标1，我们将进行蛋白质组学(AP-MS，蛋白质丰度和翻译后修饰)， 转录组学(RNA-seq和scRNA-seq)、表观基因组学(atac-seq、Hi-C和ChIP-seq)以及遗传和 用体外原代上皮细胞和IPSC来源的肺泡细胞进行化合物筛选 取自人、蝙蝠和肺上皮细胞系(A549)。在目标2中，将对这些数据进行整合和建模 利用在项目1中使用基于网络的预测建模方法收集的体内和临床数据 确定与疾病严重程度和宿主适应相关的宿主蛋白质、网络和途径(驱动因素 基因)。将使用目标1和项目1中生成的数据的重复建模来改进这些数据 预测。在AIM 3中，将结合目标组学测量使用CRISPR编辑方法 (CRISPR-组学)，包括转录、表观遗传学、蛋白质组分析，以验证这些影响 疾病转归和宿主趋向性的“驱动基因”。额外的分子、细胞、生化和活体 将进行研究，以进一步确定决定疾病结果的潜在治疗结节的特征 目标。总体而言，这些研究将使我们能够将体内和临床预测新冠肺炎的生物标志物联系起来 严重程度(项目1)影响病毒感染、细胞宿主反应和 种间传播。

PROJECT 2: Ex Vivo Analysis of Coronavirus Tropism, Adaptation, Replication, and Host Response In this proposal, we hypothesize that multiple and discrete virus-host interactions and host responses to infection dictate the pathogenic outcome and host tropism of SARS-CoV-2. We further hypothesize that these critical circuits can be dissected through network-based modeling of system-level measurements offering the potential for the development of novel antiviral therapies. In Project 2, we propose to utilize leading edge OMICs- based measurements to define virus-host interactions and networks that control viral replication, viral tropism/adaptation and host responses across bat coronaviruses, SARS-CoV-1, and SARS-CoV-2 variants. In Aim 1, we will conduct proteomics (AP-MS, protein abundance and post-translational modifications), transcriptomics (RNA-seq and scRNA-seq), epigenomics (ATAC-seq, Hi-C and ChiP-seq) and genetic and chemical compound screens using ex vivo primary epithelial cells and iPSC-derived pneumocytes derived both from human and bats and a lung epithelial cell line (A549). In Aim 2, these data will be integrated and modeled with in vivo and clinical data collected in Project 1 using network-based predictive modeling approaches to identify host proteins, networks, and pathways that correlate with disease severity and host adaptation (‘driver genes’). Reiterative modeling of data generated in Aim 1 and Project 1 will be employed to refine these predictions. In Aim 3, CRISPR-editing approaches will be used in concert with targeted OMICs measurements (CRISPR-OMICs), including transcriptional, epigenetic, proteomic analyses, to validate the impact of these ‘driver genes’ on disease outcome and host tropism. Additional molecular, cellular, biochemical, and in vivo studies will be conducted to further characterize nodes that determine disease outcome as potential therapeutic targets. Overall, these studies will enable us to correlate in vivo and clinical biomarkers predictive of COVID-19 severity (Project 1) to specific genes and networks that impact viral infection, cellular host responses, and interspecies transmission.