Spatial Models of Intrahepatic Hepatitis C Virus Propagation in Humans

 描述(申请人提供)：丙型肝炎病毒(丙型肝炎病毒)感染全球1.7亿人。虽然慢性丙型肝炎是可以治疗的，但它是美国慢性病毒感染的主要死亡原因，导致肝纤维化、肝硬变和肝细胞癌(HCC)，这些疾病无法通过治疗完全逆转。丙型肝炎病毒的研究具有挑战性：感染的器官(肝脏)不易获得，血液是感染动力学的一个小窗口；没有代表性的组织培养模型；动物模型缺乏代表性的免疫力。尽管存在这些挑战，但慢性丙型肝炎病毒感染是研究病毒通过实体组织传播的理想模型，因为i)丙型肝炎病毒感染主要限于一种细胞类型(肝细胞)，ii)丙型肝炎病毒复制在慢性感染中基本上处于稳定状态，以及iii)体内丙型肝炎病毒的多样性是巨大的，形成了一个准种，允许对局部病毒传播进行系统发育推断。我们组建了一个来自约翰霍普金斯大学(JHU)、洛斯阿拉莫斯国家实验室(LANL)和英国兰卡斯特大学的多学科团队，他们结合了翻译病毒学、动态病毒建模和空间统计方面的互补技能。JHU团队已经开发出独特的能力，可以通过单细胞激光捕获显微切割(ScLCM)测量单个肝细胞中的丙型肝炎病毒感染和序列变异，并可以访问宝贵的丙型肝炎病毒感染者肝脏活检存储库。LANL的研究人员已经开发了多个尺度(例如，细胞内到全身)的丙型肝炎病毒感染模型，兰开斯特大学的研究人员是空间统计学的世界领先者。我们的假设是，丙型肝炎病毒在局部传播，并受到感染肝细胞繁殖和先天免疫控制之间的平衡的限制。我们将使用来自丙型肝炎病毒感染者的数千个细胞的scLCM来绘制丙型肝炎病毒复制、多样化和局部免疫反应的空间图谱；我们将使用这些数据来开发丙型肝炎病毒通过组织传播的机制模型。我们将利用这些工具来实现以下具体目标。目的1.详细描述感染细胞团、肝内丙型肝炎病毒核糖核酸分布及其与血清丙型肝炎病毒核糖核酸水平的关系。目的2.确定丙型肝炎病毒肝内传播是否是由于局部感染而非全身性传播。目的3.确定局部先天免疫反应是否抑制了丙型肝炎病毒在肝内的传播。我们的目标是整合和创新的，但也是可行的。我们的策略不仅对了解丙型肝炎病毒的传播很重要，而且可以广泛应用于其他慢性感染：事实上，我们的系统是此类研究的理想模型。此外，我们的方法开辟了新的途径，为未来的调查提供了新的工具。

 DESCRIPTION (provided by applicant): Hepatitis C virus (HCV) infects >170 million people worldwide. Although chronic HCV can be treated, it is the leading cause of death in the US among chronic viral infections, resulting in liver fibrosis, cirrhosis, and hepatocellular carcinom (HCC), that are not fully reversed by therapy. HCV is challenging to study: the infected organ (the liver) is not easily accessible, and blood is a small window on infection dynamics; there is no representative tissue culture model; and animal models lack representative immunity. Despite the challenges, chronic HCV infection is an ideal model to study the spread of viruses through solid tissues because i) HCV infection is predominantly constrained to one cell type (hepatocyte), ii) HCV replication is largely at steady state in chronic infection, and iii) within-ost HCV diversity is immense, forming a quasispecies that permits phylogenetic inference of local viral spread. We assembled a multidisciplinary team from Johns Hopkins University (JHU), Los Alamos National Laboratory (LANL) and Lancaster University, UK, that combines complementary skills in translational virology, dynamic viral modeling and spatial statistics. The JHU team has developed unique capabilities to measure HCV infection and sequence variation in single hepatocytes by single-cell laser capture microdissection (scLCM) and has access to a precious repository of liver biopsies from HCV-infected persons. The researchers at LANL have developed models of HCV infection at multiple scales (e.g., intracellular to whole body), and the investigators at Lancaster University are world leaders in spatial statistics. Our hypothesis is that HCV spreads and is constrained locally by a balance between propagation from infected hepatocytes and innate immune control. We will employ scLCM for thousands of cells from HCV-infected people to spatially map HCV replication, diversification, and local immune responses; we will use this data to develop mechanistic models of HCV spread through tissues. We will employ these tools to address the following specific aims. Aim 1. To characterize in detail infected cell clusters, the intrahepatic HCV RNA landscape, and their relation to serum HCV RNA levels. Aim 2. To determine if intrahepatic HCV spread occurs due to localized infection rather than due to systemic spread. Aim 3. To determine if local innate immune responses constrain intrahepatic HCV spread. Our aims are integrated and innovative, yet feasible. Not only is our strategy important in understanding HCV spread, but can be broadly applied to other chronic infections: indeed our system is an ideal model for such studies. In addition, our approaches open new avenues and provide new tools for future investigations.