Bottom-up and top-down computational modeling approaches to study CMV retinitis

研究 CMV 视网膜炎的自下而上和自上而下的计算模型方法

基本信息

批准号：
10748709
负责人：
Christopher E Monti
金额：
$ 5.27万
依托单位：
MEDICAL COLLEGE OF WISCONSIN
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-07-26 至 2027-07-25
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10748709
关键词：
Accounting Adult Antiviral Agents Behavior Biochemical Biological Models Biology Blindness Blood Tests Cells Characteristics Chemicals Clinical Data Complex Computer Models Cytolysis Cytomegalovirus Cytomegalovirus Infections Cytomegalovirus Retinitis DNA biosynthesis Data Dependence Diagnosis Diagnostic Fellowship Fibroblasts Ganciclovir Goals Grant Growth Human Human Characteristics Immunocompromised Host In Vitro Individual Infection Investigation Kinetics Knowledge Life Life Cycle Stages Lytic Methodology Modeling Nature Ophthalmologist Outcome Pathogenesis Pathologic Pathology Patients Pharmaceutical Preparations Population Production Proteins Recovery Regulation Research Retina Risk Sampling Scientist Sepsis Structure of retinal pigment epithelium Syndrome System Techniques Testing Time Training Variant Viral Genome Viral Proteins Viremia Virion Virus Virus Replication Vision Visual Western Blotting career cell type chronic infection computer studies cost detection limit effective intervention human model in vitro Model latent infection lytic replication models and simulation neural novel protein expression response skills therapeutically effective treatment duration viral DNA viral RNA

项目摘要

PROJECT SUMMARY Human cytomegalovirus (HCMV) is widespread and infection results in syndromes ranging from asymptomatic latency to life-threatening sepsis due to reactivation of a latent infection in immunocompromised individuals. One major, yet often overlooked, consequence of HCMV infection in immunosuppressed patients is CMV retinitis (CMVR). Given its ubiquitous nature, risk of visual complications including blindness, and cost associated with diagnosis and therapy, HCMV, the causative agent of CMVR, is a crucial target for investigation to advance knowledge and develop effective therapeutic strategies. The retinal pigment epithelium (RPE) has been impli- cated as a point of entry for viruses, including HCMV, into the neural layer of the retina. The single-step HCMV lytic replication cycle has an approximately 96 h duration in vitro in fibroblasts that culminates in production of infectious virions and destruction of the infected cell. It is known that HCMV infection of adult RPE (ARPE19) cells leads to a slower, less destructive persistent infection and multi-step replication. Computational modeling is a methodological advancement that has only been recently applied to the study of the dynamic profiling of some viral proteins in single-step replication, and there are very few multi-step replication models that exist, likely due to a lack of a readily testable in vitro persistence-like system, thus creating two related knowledge gaps. The objective of this fellowship is to provide training that integrates wet-lab and computational strategies to study complex visual pathologies using HCMV lytic replication kinetics and CMVR as a model system. The goals of this fellowship are to: (1) identify and computationally model the effects of varying multiplicity of infection (MOI) and cell type (i.e., fibroblast vs. ARPE19) on HCMV replication kinetics during single-step replication; (2) develop an in vitro model system similar to a persistent HCMV infection employing multi-step replication in ARPE19 cells; and (3) experimentally investigate and computationally simulate the effects of the anti-HCMV drug ganciclovir (GCV) on the novel persistence-like in vitro system using ARPE19 cells. In Aim 1, I will use a bottom-up, bio- chemically-based, MOI-dependent computational model to describe the protein interactions and regulation in single-step lytic HCMV replication. I will investigate cell type-dependent variability by comparing models param- eterized using MRC5 fibroblast-derived data and ARPE19 cell-derived data. In Aim 2, I will use a top-down approach to computationally model the effects of multi-step HCMV replication in ARPE19 cells at the cellular level using a novel, in vitro persistence-like system and a target-cell limited model. I will generate an in vitro persistence-like system using ARPE19 cells infected at a low MOI, allowing for multi-step replication, to achieve a steady-state level of viral DNA (vDNA). I will correlate this system’s response to the anti-HCMV drug GCV with the predictions from extant target-cell limited models that were parameterized using patient data. Finally, I will use the target-cell limited model to predict the optimal in vitro GCV treatment duration causing vDNA levels to decay below the qPCR limit of detection and then test this using the novel persistence-like system.

项目概要人类巨细胞病毒 (HCMV) 广泛传播，感染会导致从无症状到多种症状由于免疫功能低下个体的潜伏感染重新激活而导致危及生命的败血症的潜伏期。免疫抑制患者中 HCMV 感染的主要但经常被忽视的后果是 CMV 视网膜炎 (CMVR)。鉴于其普遍存在的性质，包括失明在内的视觉并发症的风险以及与此相关的费用。诊断和治疗方面，HCMV（CMVR 的病原体）是研究进展的重要目标视网膜色素上皮（RPE）的知识并制定有效的治疗策略。被认为是病毒（包括 HCMV）进入视网膜神经层的入口点。体外成纤维细胞的裂解复制周期持续约 96 小时，最终产生众所周知，HCMV 感染成人 RPE (ARPE19)。细胞导致更慢、破坏性更小的持续感染和多步骤复制。是一种方法上的进步，最近才应用于动态分析的研究一些病毒蛋白处于单步复制状态，并且存在很少的多步复制模型，可能由于缺乏易于测试的体外持久性系统，从而造成了两个相关的知识差距。该奖学金的目标是提供整合湿实验室和计算策略来研究的培训使用 HCMV 裂解复制动力学和 CMVR 作为模型系统来研究复杂的视觉病理学。该奖学金旨在：(1) 识别不同感染复数 (MOI) 的影响并对其进行计算建模和细胞类型（即成纤维细胞与 ARPE19）对单步复制过程中 HCMV 复制动力学的影响（2）；类似于持续性 HCMV 感染的体外模型系统，在 ARPE19 细胞中采用多步复制； (3) 实验研究并计算模拟抗 HCMV 药物更昔洛韦的作用。（GCV）关于使用 ARPE19 细胞的新型持久性体外系统。在目标 1 中，我将使用自下而上的生物- 基于化学、MOI 依赖的计算模型来描述蛋白质相互作用和调节我将通过比较模型参数来研究细胞类型依赖性变异性。在目标 2 中，我将使用自上而下的方法。计算模拟 ARPE19 细胞中多步 HCMV 复制效应的方法我将使用一种新颖的体外持久性系统和靶细胞有限模型来生成一个体外水平。使用低 MOI 感染的 ARPE19 细胞的持久性系统，允许多步复制，以实现我将把该系统对抗 HCMV 药物 GCV 的反应与病毒 DNA (vDNA) 的稳态水平相关联。使用患者数据参数化的现有靶细胞有限模型的预测。使用靶细胞有限模型来预测导致 vDNA 水平降低的最佳体外 GCV 治疗持续时间衰减低于 qPCR 检测限，然后使用新型持久性系统进行测试。