RNA dynamics and co-translational decay in aging and aging-related disease

衰老和衰老相关疾病中的 RNA 动力学和共翻译衰减

• 批准号: 10471685
• 负责人: Emmanouil Maragkakis
• 金额: $ 266.59万
• 依托单位: NATIONAL INSTITUTE ON AGING
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10471685
• 关键词: Aging; Alzheimer' s Disease; Biological; Biological Process; Brain; Cell physiology; Cells; Complex; Computer Analysis; Development; Disease; Encapsulated; Gene Expression Regulation; Genetic Transcription; Genome; Goals; Homeostasis; Label; Lead; Machine Learning; Malignant Neoplasms; Mediating; Messenger RNA; Metabolic; Modeling; Mus; Nerve Degeneration; Oxidative Stress; Pathway interactions; Phase; Physiology; Post-Transcriptional RNA Processing; Post-Transcriptional Regulation; Process; Property; Protocols documentation; RNA; RNA Probes; Regulator Genes; Ribosomes; Signal Transduction; Tissues; Work; experimental study; high dimensionality; mRNA Decay; nanopore; programs; tool

While genomes encapsulate the information for the development and function of cells most of the biological complexity lies on high-order interactions and gene regulatory programs. Dissecting these regulatory mechanisms is critical for understanding complex, polygenic processes such as aging. In previous works we described a co-translational pathway of mRNA decay that is mediated by ribosome-phased cleavage of the mRNA (Ibrahim et al., 2018). There we developed a new experimental protocol to capture the native ends of mRNAs. However, the available protocols are limited as they cannot capture both the 5' and 3' ends simultaneously on the same molecule. This limited our ability to probe mRNA properties. Over the past year we developed, experimental/computational approaches to capture the native ends of mRNA molecules using direct RNA, nanopore sequencing. We have applied these protocols to analyze RNA dynamics (transcriptional and decay rates) in oxidative stress in cells, and in the aging, wild-type and Alzheimer's disease (App/PS1), mouse brain. We also employ machine learning to extract information about post-transcriptional RNA modifications from raw nanopore electrical signal which we plan to use to more accurately probe RNA dynamics in metabolic labelling experiments.

虽然基因组封装了细胞发育和功能的信息，但大多数生物复杂性取决于高阶相互作用和基因调控程序。剖析这些调节机制对于理解衰老等复杂的多基因过程至关重要。在之前的工作中，我们描述了 mRNA 降解的共翻译途径，该途径是由 mRNA 的核糖体定相切割介导的（Ibrahim et al., 2018）。在那里，我们开发了一种新的实验方案来捕获 mRNA 的天然末端。然而，可用的协议是有限的，因为它们不能同时捕获同一分子上的 5' 和 3' 末端。这限制了我们探测 mRNA 特性的能力。在过去的一年里，我们开发了实验/计算方法，使用直接 RNA、纳米孔测序捕获 mRNA 分子的天然末端。我们应用这些协议来分析细胞氧化应激以及衰老、野生型和阿尔茨海默病 (App/PS1) 小鼠大脑中的 RNA 动态（转录和衰变率）。我们还利用机器学习从原始纳米孔电信号中提取有关转录后 RNA 修饰的信息，我们计划使用这些信息来更准确地探测代谢标记实验中的 RNA 动力学。