Elucidating Effects of Fibrosis on Aged Stem Cells with Dynamic Biomaterials

项目总结 尽管纤维化在衰老和疾病引起的组织功能障碍中普遍存在，但没有 存在具有代表性的纤维化微环境体外模型。纤维化的特征是过度 细胞外基质(ECM)沉积，使细胞微环境变硬。因此，为了建立纤维化模型， 体外，允许对基质力学和成分进行定量、动态调整的细胞培养基质是 这是必要的。然而，现有的动态水凝胶培养平台通常依赖于可能是 对细胞有毒或同时改变多个参数，使得很难确定原因 改变的基质属性和细胞命运改变之间的关系。纤维性硬化的范围很广。 包括骨骼肌在内的组织。随着纤维化的增加，骨骼肌的再生功能 随着年龄的增长而减少。肌肉干细胞(MuSCs)负责维持和修复肌肉 在整个生命过程中，它们被认为是非常机械敏感的，当培养到 坚硬的衬底。因此，僵硬、纤维化的微环境可能是再生能力减弱的原因之一。 老年间充质干细胞的能力。本项目的目标是开发一种体外组织纤维化模型，该模型基于 动态水凝胶生物材料及其在分子生物学机制研究中的应用 与衰老中的MUSC功能障碍有关的机械感觉。本建议书的指导阶段将 提供衰老生物学、转基因小鼠模型、细胞牵引力等方面的高级技术培训 生物信息学的测量和机器学习方法。这项培训将使独立的 利用动态生物材料来解卷复杂的机械相互作用的研究计划 决定衰老和疾病进展的力量、基质生物化学和细胞-细胞信号。其他内容 科学写作、科研能力和研究管理方面的系统培训将促进向 独立，由斯坦福大学医学院和工程学院的教职员工委员会支持。 目标一号将优化一种合成水凝胶系统，该系统使用近红外光和生物正交反应来 动态地使凝胶变硬，模仿纤维化。这些水凝胶将被用来阐明 使用基于FRET的力传感器和转基因小鼠模型在MUSCs中进行机械传感。AIM 2将成为典范 肌肉在体外老化，使用具有老化特性的ECM成分修改的动态僵硬凝胶。 单细胞RNA测序和机器学习生物信息学方法将机械地识别独特的 调节细胞命运的驱动因素，在衰老过程中降低MUSC的再生潜力。目标3将开发小说 具有动态调节粘弹性特性的3D细胞培养材料，以建立第一个人类模型 肌肉“在盘子里老化。”该项目旨在确定新的治疗靶点，以改善肌肉功能 并开发工程平台来研究多种遗传性疾病和不同组织中的衰老。

PROJECT SUMMARY Despite the ubiquitous role of fibrosis in tissue dysfunction arising from aging and disease, no representative in vitro model of the fibrotic microenvironment exists. Fibrosis is characterized by excess extracellular matrix (ECM) deposition that stiffens the cellular microenvironment. Therefore, to model fibrosis in vitro, cell culture substrates that permit quantitative, dynamic tuning of matrix mechanics and composition are necessary. However, existing dynamic hydrogel culture platforms generally rely on chemistries that may be toxic to cells or that simultaneously change multiple parameters, making it difficult to assign causal relationships between altered matrix properties and cell fate changes. Fibrotic stiffening occurs in a wide range of tissues, including skeletal muscle. Along with increased fibrosis, the regenerative function of skeletal muscle decreases with aging. Muscle stem cells (MuSCs) are responsible for maintaining and repairing muscle throughout life and are known to be acutely mechanosensitive, losing their stem cell potential when cultured on stiff substrates. Thus, the stiffened, fibrotic microenvironment may contribute to the diminished regenerative capacity of aged MuSCs. The goal of this project is to develop an in vitro model of tissue fibrosis based on dynamic hydrogel biomaterials and to employ this model to identify molecular mechanisms of MuSC mechanosensing that are implicated in MuSC dysfunction in aging. The mentored phase of this proposal will provide advanced technical training in aging biology, transgenic mouse models, cellular traction force measurement, and machine learning approaches for bioinformatics. This training will enable an independent research program leveraging dynamic biomaterials to deconvolve the complex interactions of mechanical forces, matrix biochemistry, and cell-cell signaling that dictate the progression of aging and disease. Additional structured training in scientific writing, grantsmanship, and research management will facilitate the transition to independence, supported by a committee of faculty from the Stanford Schools of Medicine and Engineering. Aim 1 will optimize a synthetic hydrogel system that uses near-infrared light and bioorthogonal reactions to dynamically stiffen the gels, mimicking fibrosis. These hydrogels will be used to elucidate mechanisms of mechanosensing in MuSCs, using FRET-based force sensors and transgenic mouse models. Aim 2 will model muscle aging in vitro, using dynamically stiffening gels modified with ECM components characteristic of aging. Single cell RNA sequencing and machine learning bioinformatics approaches will identify unique mechanically regulated drivers of cell fate that reduce MuSC regenerative potential in aging. Aim 3 will develop novel materials for 3D cell culture with dynamic tuning of viscoelastic properties to establish the first human model of muscle “aging in a dish.” This project stands to identify new therapeutic targets to improve muscle function with aging and to develop engineered platforms to study numerous heritable diseases and aging in diverse tissues.