NIH: Spatial Models of Intrahepatic Hepatitis Virus Propagation in Humans

总结 意义：B型肝炎病毒（HBV）感染全球约2.6亿人，是肝脏疾病的主要原因。 疾病和肝细胞癌（HCC）。尽管有一种有效的预防感染的疫苗， 慢性B型肝炎病毒感染（CH B）一旦确立就难以治愈。病毒遗传物质进入 感染细胞的细胞核产生稳定的共价闭合环状DNA（cccDNA）分子或线性的共价闭合环状DNA（cccDNA）分子。 整合到宿主细胞染色体（iDNA）中的形式。现有的治疗方法对cccDNA影响不大 因此成功率很低。治疗中断经常导致HBV DNA反弹， 复发性肝炎此外，即使经过治疗，慢性乙型肝炎的肝脏疾病也经常进展为失代偿性， 肝硬化需要肝移植几种病毒合并感染加剧了这一过程，例如 HIV或丙型肝炎病毒（HCV）。因此，需要用于CHB治愈的改进的治疗剂。 创新：我们的建议在三个方面具有创新性。i）获取珍贵和独特的肝脏样本 组织; ii）使用最先进的实验技术进行单细胞分析和同期血液分析 生物标志物; iii）通过我们丰富的数据集开发新的HBV感染多尺度模型， 是为临床应用而设计的。 方法：HBV具有复杂的生命周期，包括细胞内和细胞外阶段。我们的团队已被 开发了在单个肝细胞水平上询问HBV细胞内相的工具。我们取得了 HBV在单细胞中的初步观察，但最近才开始将细胞内和细胞外的HBV结合起来。 HBV的细胞外阶段。因此，我们准备揭示血液和肝脏之间HBV生物学的关键联系。 使用一种综合的方法，我们建议开发HBV的模型，其特征是在细胞中复制。 有机体统一了我们对病毒细胞内和细胞外阶段的理解。我们的具体目标是： i）开发细胞内和细胞外HBV复制的综合模型，测量和 在血液中和肝脏中的单细胞水平上建立一套全面的HBV相关生物标志物模型， 未治疗的和治疗的CHB;和ii）开发HBV在肝脏中的空间传播和持久性的模型， 使用HBV的单细胞病毒测序，在基因相关的HBV变异体之间建立空间联系， 肝脏这些数据和模型将允许关于本地与非本地HBV传播的推断。具体地说， 我们将检测HBV感染肝细胞的克隆性增殖是否有助于HBV感染持续存在。 感染的细胞，这不仅对治疗研究，而且对HCC肿瘤发生具有重要意义。 影响：由于正在开发多种用于HBV治疗的新型化合物， 这一建议将填补我们对HBV复制和发病机制的理解的空白。我们以前的努力和 其他人在HCV和HIV建模中的作用对于开发成功的治疗方法非常重要， 感染.我们希望这里产生的新数据和模型在推进HBV方面具有相同的影响。 疗法

Summary Significance: Hepatitis B virus (HBV) infects ~260 million people worldwide and is the leading cause of liver disease and hepatocellular carcinoma (HCC) in the world. Despite an effective vaccine for infection prevention, chronic hepatitis B virus infection (CHB) is difficult to cure once established. The viral genetic material enters the infected cell's nucleus generating a stable covalently closed-circular DNA (cccDNA) molecule or a linear form that integrates into the host cell's chromosome (iDNA). Existing treatments have little effect on cccDNA and as a result have poor success rates. Treatment interruption often leads to rebound of HBV DNA and recurrent hepatitis. In addition, even with treatment, liver disease in CHB often progresses to decompensated cirrhosis requiring liver transplantation. This process is exacerbated by several viral co-infections, such as with HIV or hepatitis C virus (HCV). Thus, improved therapeutics for CHB cure are required. Innovation: Our proposal is innovative in three aspects. i) access to precious and unique samples of liver tissue; ii) using state-of-the-art experimental techniques for single cell analyses and contemporaneous blood biomarkers; iii) development of new multi-scale models of HBV infection informed by our rich data sets, which are designed for clinical usefulness. Approach: HBV has a complex lifecycle comprising intracellular and extracellular phases. Our team has developed tools to interrogate the intracellular phase of HBV at the single-hepatocyte level. We have made preliminary observations of HBV in single cells but have only recently begun to link the intracellular and extracellular phases of HBV. Thus, we are poised to uncover key links in HBV biology between blood and liver. Using an integrated approach, we propose developing models of HBV that characterize replication in the organism uniting our understanding of intracellular and extracellular phases of the virus. Our specific aims are: i) To develop integrated models of intracellular and extracellular HBV replication, measuring and modeling a comprehensive set of HBV-related biomarkers in the blood and at the single-cell level in the liver, in untreated and treated CHB; and ii) To develop models of HBV spatial spread and persistence in the liver, using single-cell viral sequencing of HBV to make spatial linkages between genetically related HBV variants in the liver. These data and models will allow inferences about local versus non-local HBV spread. Specifically, we will test if clonal proliferation of HBV infected hepatocytes may contribute to continued persistence of infected cells, which has important implications not only for cure research but also for HCC oncogenesis. Impact: As multiple novel compounds for HBV treatment are in development, the timely insights generated in this proposal will fill gaps in our understanding of HBV replication and pathogenesis. Previous efforts by us and others in modeling HCV and HIV were important in the development of successful therapies for those infections. We expect the new data and models generated here to have the same impact in advancing HBV therapy.