Elucidating Effects of Fibrosis on Aged Stem Cells with Dynamic Biomaterials

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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.