Investigations of proteome turnover kinetics under cellular differentiation

细胞分化下蛋白质组周转动力学的研究

• 批准号: 10808331
• 负责人: Edward Lau
• 金额: $ 1.13万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-17 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10808331
• 关键词: Administrative Supplement; Animal Model; Area; Biological; Cardiac Myocytes; Cell Differentiation process; Cells; Data Set; Deuterium; Deuterium Oxide; Disease Marker; Disease Progression; Disease model; Ensure; Event; Hepatocyte; Human; Investigation; Kinetics; Knowledge; Maps; Mass Spectrum Analysis; Methods; Modeling; Molecular; Physiological; Process; Production; Protein Biosynthesis; Proteins; Proteome; Research; Software Tools; Stable Isotope Labeling; Techniques; Tissue Engineering; Transcript; cell type; data tools; density; dynamic system; experimental study; induced pluripotent stem cell; kinetic model; knowledge of results; nerve stem cell; novel; parent project; protein degradation; stem cell differentiation; success; summer research; undergraduate student

PROJECT SUMMARY This administrative supplement application for undergraduate summer research is being submitted to PA-20-272 in accordance to NOT-GM-22-009. The scope of the parent project remains unchanged. Summary of Parent Project R35-GM146815: Proteins are in a constant flux of continuous synthesis and degradation. Both components of the protein turnover cycle contribute to protein abundance. Although this fact has been known for 80 years, currently most biological inquiries are limited to static snapshots of overall transcript and protein levels, whereas knowledge into the dynamic changes of protein turnover remains severely lagging. This ESI MIRA proposal seeks to advance the current understanding of how cellular proteomes remodel during cell state transitions, by incorporating protein turnover kinetics information at key stages of human induced pluripotent stem cell (iPSC) differentiation into distinct cellular lineages. Working with collaborators, we previously developed deuterium stable isotope labeling, mass spectrometry, and kinetic modeling methods to quantitate protein turnover in animal models and in human. In doing so, we found many novel cell states and disease markers may be discovered from integrating orthogonal protein abundance and kinetics information. In the next five years, we propose to: (1) apply these methods to acquire a high temporal density map of human iPSC trilineage differentiation into cardiomyocyte, hepatocyte, and neuroprogenitor cells; (2) interrogate the regulatory principles that govern turnover flux across different differentiation stages; and (3) assess the functional consequences of protein degradation on the success and cell maturity of terminal cell production. Finally, a limitation of current techniques is that the kinetic models used in protein turnover studies largely assume a non-changing protein pool size at steady state, which does not apply to differentiating cells or progressing diseases. We propose to expand current models of analyzing heavy water stable isotope label experiments toward dynamical systems with variable protein pool sizes. If successful, the proposed research would greatly expand the current knowledge of molecular events that take place during human iPSC differentiation, as well as generate publicly available data sets and software tools to advance protein turnover studies in diverse areas.

项目概要 本科生暑期研究行政补充申请将提交至 PA-20-272 根据 NOT-GM-22-009。父项目的范围保持不变。家长总结 项目 R35-GM146815：蛋白质处于持续合成和降解的恒定通量中。两个都 蛋白质周转周期的组成部分有助于蛋白质丰度。虽然这个事实已经众所周知 80 年来，目前大多数生物学查询仅限于整体转录本和蛋白质的静态快照 水平，而对蛋白质周转动态变化的了解仍然严重滞后。本次ESI MIRA 提案旨在增进目前对细胞状态下细胞蛋白质组如何重塑的理解 通过在人类诱导多能的关键阶段结合蛋白质周转动力学信息来实现转变 干细胞（iPSC）分化成不同的细胞谱系。我们之前与合作者合作开发了 用于定量蛋白质的氘稳定同位素标记、质谱分析和动力学建模方法 动物模型和人类的营业额。在此过程中，我们发现了许多新的细胞状态和疾病标志物可能 通过整合正交蛋白质丰度和动力学信息可以发现。未来五年，我们 提议：（1）应用这些方法来获取人类 iPSC 三系的高时间密度图 分化为心肌细胞、肝细胞和神经祖细胞； （二）质疑监管原则 控制不同分化阶段的营业额流量； (3) 评估功能后果 蛋白质降解对终末细胞生产的成功和细胞成熟度的影响。最后，电流的限制 技术的特点是蛋白质周转研究中使用的动力学模型很大程度上假设蛋白质不变 稳态池大小，不适用于分化细胞或进展性疾病。我们建议 将当前分析重水稳定同位素标记实验的模型扩展到动力系统 具有可变的蛋白质库大小。如果成功，拟议的研究将极大地扩展当前的知识 人类 iPSC 分化过程中发生的分子事件，并生成公开可用的 数据集和软件工具可推进不同领域的蛋白质周转研究。