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.

项目摘要 该本科夏季研究的行政补充申请已提交给PA-20-272 根据非GM-22-009。父项目的范围保持不变。父母的摘要 R35-GM146815项目：蛋白质处于连续合成和降解的恒定通量中。两个都 蛋白质周期周期的成分有助于蛋白质丰度。虽然这一事实已知 80年来，目前大多数生物查询仅限于整体成绩单和蛋白质的静态快照 水平，而对蛋白质周转的动态变化的知识仍然严重落后。这个Esi Mira提案旨在提高人们对细胞蛋白质组如何在细胞状态中重塑的理解 过渡，通过在人类诱导多能的关键阶段合并蛋白质周转动力学信息 干细胞（IPSC）分化为不同的细胞谱系。与合作者合作，我们以前开发了 氘稳定的同位素标记，质谱和动力学建模方法来定量蛋白质 动物模型和人的营业额。这样，我们发现许多新颖的细胞状态和疾病标记可能 可以从整合正交蛋白丰度和动力学信息中发现。在接下来的五年中，我们 建议：（1）应用这些方法来获取人IPSC Trilineage的高时间密度图 分化为心肌细胞，肝细胞和神经元基因细胞； （2）审问监管原则 控制不同差异阶段的失误通量； （3）评估功能后果 蛋白质降解对末端细胞产生的成功和细胞成熟度的降解。最后，电流的限制 技术是在蛋白质周转研究中使用的动力学模型在很大程度上假设一种非变化蛋白 稳态的池大小不适用于区分细胞或进展疾病。我们建议 扩展当前分析重水稳定同位素标签实验的模型 具有可变的蛋白质池尺寸。如果成功，拟议的研究将大大扩展当前的知识 人类IPSC差异化期间发生的分子事件，并产生公开可用 数据集和软件工具可以推进各个领域的蛋白质转换研究。