Investigations of proteome turnover kinetics under cellular differentiation

项目摘要 细胞分化过程中蛋白质组更新动力学的研究：蛋白质处于恒定的流动中 持续的合成和降解，这两者都有助于调节细胞中的蛋白质水平。虽然 这一事实已经被知道了80年，目前大多数生物学研究仅限于静态快照， 整体转录和蛋白质水平，而知识的动态变化的蛋白质周转仍然 严重滞后。这ESI MIRA提案旨在推进目前对细胞如何 在细胞状态转换过程中，通过在关键位置引入蛋白质周转动力学信息， 人诱导多能干细胞（iPSC）分化为不同细胞谱系的各个阶段。使用 合作者，我们以前开发了氘稳定同位素标记，质谱，和动力学 建模方法来定量动物模型和人体中的蛋白质周转。在此过程中，我们发现许多 新的细胞状态和疾病标志物可以从整合正交蛋白质丰度中发现， 动力学信息在未来的五年里，我们建议：（1）应用这些方法，以获得高的时间 人iPSC三系分化为心肌细胞、肝细胞和神经祖细胞的密度图; (2)询问管理不同分化阶段的营业额流量的监管原则;以及（3） 评估蛋白质降解对终末细胞的成功和细胞成熟的功能后果 生产最后，当前技术的局限性在于蛋白质周转研究中使用的动力学模型 在稳定状态下主要假定蛋白质库大小不变，这不适用于分化细胞 或疾病进展。我们建议扩展现有的分析重水稳定同位素标记的模型 对具有可变蛋白质池大小的动态系统的实验。如果成功，拟议的研究 这将极大地扩展目前对人类iPSC中发生的分子事件的了解， 分化，以及生成公开可用的数据集和软件工具，以促进蛋白质周转 在不同领域的研究。

PROJECT SUMMARY Investigations of Proteome Turnover Kinetics Under Cellular Differentiation: Proteins are in a constant flux of continuous synthesis and degradation, both of which contribute to regulate protein levels in the cell. 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.