Integrative analysis of metabolomics, transcriptomics and proteomics to study mechanisms that regulate lentiviral vector hepatocyte transduction

代谢组学、转录组学和蛋白质组学的综合分析，研究慢病毒载体肝细胞转导的调节机制

• 批准号: 2891574
• 金额: --
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2891574
• 关键词: Integrative; analysis; metabolomics; transcriptomics; proteomics

Liver transplantation is the only cure for many congenital and acquired diseases. However, multiple liver diseases are thought to be single-gene disorders that may be amenable to gene therapy via targeting of liver hepatocytes. The liver, therefore, represents an important target organ for developing new gene therapy approaches. One challenge is that hepatocytes are generally quiescent; thus a recombinant lentiviral vector (LV) may have the advantage over other gene transfer vectors in being able to transduce non-dividing cells, and also to integrate in the cell genome permitting long-term transgene expression. Crucially, irrespective of the specific application, establishing efficient LV transduction will be imperative for successful liver gene therapy. The specific focus of this project will be to study potential effects of LV transduction on cellular metabolism and signalling pathways in liver cells. Whereas transcriptomics and proteomics measure changes in genes and proteins, respectively, metabolomics allows the concurrent measurement of large numbers of cellular metabolites. Machine learning can be used to integrate data generated from all three technologies, and will be used to determine large-scale changes induced by the virus aiming to identify novel targets, pathways and mechanisms that affect/regulate efficient gene transfer in hepatocytes.

肝移植是治疗许多先天性和后天性疾病的唯一方法。然而，多发性肝病被认为是单基因疾病，可以通过靶向肝细胞进行基因治疗。因此，肝脏是开发新基因治疗方法的重要靶器官。一个挑战是肝细胞通常是静止的;因此重组慢病毒载体（LV）可能具有优于其他基因转移载体的优势，能够使非分裂细胞增殖，并且还整合到细胞基因组中，允许长期转基因表达。至关重要的是，无论具体的应用，建立有效的LV转导将是成功的肝脏基因治疗的必要条件。该项目的具体重点将是研究LV转导对肝细胞中细胞代谢和信号传导途径的潜在影响。转录组学和蛋白质组学分别测量基因和蛋白质的变化，而代谢组学允许同时测量大量的细胞代谢产物。机器学习可用于整合所有三种技术生成的数据，并将用于确定病毒诱导的大规模变化，旨在确定影响/调节肝细胞中有效基因转移的新靶点、途径和机制。