Spatial Models of Intrahepatic Hepatitis C Virus Propagation in Humans

丙型肝炎病毒在人体中传播的空间模型

基本信息

批准号：
9882937
负责人：
ASHWIN BALAGOPAL
金额：
$ 74.65万
依托单位：
TRIAD NATIONAL SECURITY, LLC
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-02-01 至 2022-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9882937
关键词：
Address Animal Model Antiviral Therapy Blood Cause of Death Cells Characteristics Chronic Chronic Hepatitis C Cirrhosis Complement Data Dendritic Cells Disease model Equilibrium Focal Infection Future Hepatic Hepatitis B Hepatitis C Hepatitis C virus Hepatocyte Human Immune Immune response Immune signaling Immunity In Situ Infection Innate Immune Response Interferon-alpha Investigation Kupffer Cells Laboratories Liver Liver Fibrosis Maps Mathematics Measures Minority Modeling Organ Pathology Patients Persons Phylogenetic Analysis Primary carcinoma of the liver cells Property Research Personnel Sampling Solid Spatial Distribution Statistical Models System Systemic infection Testing Tissues Universities Validation Variant Viral Virus Virus Diseases Virus Replication cell type chronic infection in vivo innovation insight intrahepatic laser capture microdissection liver biopsy liver transplantation macrophage mathematical methods model building multidisciplinary novel strategies public health relevance repository response simulation single cell analysis skills statistics tissue culture tool viral RNA virology

项目摘要

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.

描述（由适用提供）：乙型肝炎病毒（HCV）感染> 1.7亿人。尽管可以治疗慢性HCV，但在慢性病毒感染中，这是美国死亡的主要原因，导致肝纤维化，肝硬化和肝细胞癌（HCC）并未通过治疗完全反转。 HCV的研究具有挑战性：感染器官（肝脏）不容易获得，血液是感染动态的小窗口。没有代表性的组织培养模型。动物模型缺乏代表性的免疫组织化学。 Despite the challenges, chronic HCV infection is an ideal model to study the spread of viruses through solid timings because i) HCV infection is predominantly constrained to one cell type (hepatocyte), ii) HCV replication is large 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.我们组建了来自约翰·霍普金斯大学（JHU），洛斯阿拉莫斯国家实验室（LANL）和英国兰开斯特大学的多学科团队，该团队结合了翻译病毒学，动态病毒建模和空间统计的互补技能。 JHU团队通过单细胞激光捕获显微解剖（SCLCM）开发了独特的功能来测量单个肝细胞中HCV感染和序列变化，并可以从HCV感染者中访问珍贵的肝活检库。 LANL的研究人员已经开发了多个尺度（例如，细胞内到全身）的HCV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导者。我们的假设是HCV扩散并受到感染肝细胞的传播与先天免疫控制的繁殖之间的平衡来限制。我们将采用从HCV感染者的成千上万个细胞的SCLCM来空间绘制HCV复制，多样化和局部免疫反应；我们将使用这些数据来开发HCV通过组织扩散的机械模型。我们将采用这些工具来解决以下特定目标。目的1。为了详细表征感染的细胞簇，ePatitic HCV RNA景观及其与血清HCV RNA水平的关系。目的2。确定epatitic HCV扩散是否是由于局部感染而不是由于系统性扩散而发生的。目的3。确定局部先天免疫反应是否限制了epatitic HCV的扩散。我们的目标是整合，创新的，但可行。我们的策略不仅在理解HCV传播方面很重要，而且可以广泛地应用于其他慢性感染：的确，我们的系统是此类研究的理想模型。此外，我们的方法开放了新的途径，并为未来的调查提供了新的工具。