Computational and Experimental Modeling of Cardiomyocyte Proliferation

心肌细胞增殖的计算和实验模型

基本信息

批准号：
10337761
负责人：
Jeffrey J. Saucerman
金额：
$ 70.91万
依托单位：
UNIVERSITY OF VIRGINIA
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-01-01 至 2025-12-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10337761
关键词：
Adult Algorithms American Biological Assay Biological Models Candidate Disease Gene Cardiac Cardiac Myocytes Cardiology Cell Cycle Cell Differentiation process Cells Computer Models DNA biosynthesis Data Development Experimental Models Future Genes Heart Heart failure Hematopoietic Human Image In Vitro Injury Literature Logic Mammals Measures Methodology Methods Modeling Molecular Molecular Biology Mus Myocardium Natural regeneration Neonatal Network-based Organ Outcome Pathway interactions Phenotype Prevalence Proteins Regulation Reproducibility Signal Transduction System Testing Therapeutic Transforming Growth Factor alpha Transforming Growth Factor beta Validation Work base cardiac regeneration cell regeneration experience experimental study gene discovery genome-wide in vivo in vivo regeneration induced pluripotent stem cell derived cardiomyocytes innovation insight knock-down live cell microscopy molecular modeling mouse model network models novel organ regeneration postnatal development predictive modeling prenatal regeneration potential regenerative regenerative therapy screening skeletal stem cell differentiation stem cells therapeutic candidate therapeutic target

项目摘要

Summary Heart failure arises in large part due to the very limited ability of cardiomyocytes to regenerate following injury. Recent studies have identified some molecular regulators of cardiomyocyte proliferation in mammals, but the field lacks an understanding of how these and yet-to-be identified components work as a system to regulate cardiomyocyte proliferation. A better understanding of the pathways that control CM proliferation and cell cycle exit is needed in order to develop strategies that stimulate CM proliferation as a regenerative therapy. Here, we integrate innovative computational and experimental methods to develop a systems-level understanding of cardiomyocyte proliferation. First, we develop a literature-based computational model of the molecular network, comprising known regulators of cardiomyocyte proliferation. This network model is expanded mechanistically to include novel regulators of cardiomyocyte proliferation that we have discovered through a genome-wide phenotypic screen, including several in a TGF-beta module. Model-predicted regulators within this TGF-beta module are validated experimentally in mouse cardiomyocytes, human induced pluripotent stem-cell derived cardiomyocytes, and an in vivo mouse model of cardiac regeneration. Overall, this study will provide novel candidate therapeutic targets for cardiomyocyte proliferation, the first mechanistic model integrating these candidates and known regulators of cardiomyocyte proliferation, and experimental validation that the model can predict network perturbations that enhance cardiomyocyte proliferation in vitro and in vivo.

概括心力衰竭的发生很大程度上是由于心肌细胞受伤后再生的能力非常有限。最近的研究已经确定了哺乳动物心肌细胞增殖的一些分子调节因子，但该领域缺乏对这些和尚未确定的组成部分如何作为一个系统进行调节的理解心肌细胞增殖。更好地了解控制 CM 增殖和细胞周期的途径为了制定刺激 CM 增殖作为再生疗法的策略，需要退出。在这里，我们整合创新的计算和实验方法，以形成系统级的理解心肌细胞增殖。首先，我们开发了一个基于文献的分子网络计算模型，包含已知的心肌细胞增殖调节剂。该网络模型是机械扩展的包括我们通过全基因组发现的新型心肌细胞增殖调节因子表型筛选，包括 TGF-β 模块中的几个。 TGF-β 内的模型预测调节因子模块在小鼠心肌细胞、人类诱导多能干细胞中进行了实验验证心肌细胞和心脏再生的体内小鼠模型。总的来说，这项研究将提供新颖的心肌细胞增殖的候选治疗靶点，第一个整合这些的机制模型心肌细胞增殖的候选者和已知调节者，以及该模型的实验验证可以预测增强体外和体内心肌细胞增殖的网络扰动。