Engineering Highly-functional, Self-regenerative Skeletal Muscle Tissues with Enhanced Vascularization and Survival in Vivo

Tissue engineering of biomimetic skeletal muscle may lead to development of new therapies for myogenic repair and generation of improved in vitro models for studies of muscle function, regeneration, and disease. For the optimal therapeutic and in vitro results, engineered muscle should recreate the force-generating and regenerative capacities of native muscle, enabled respectively by its two main cellular constituents, the mature myofibers and satellite cells (SCs). Still, after 20 years of research, engineered muscle tissues fall short of mimicking contractile function and self-repair capacity of native skeletal muscle. To overcome this limitation, we set the thesis goals to: 1) generate a highly functional, self-regenerative engineered skeletal muscle and 2) explore mechanisms governing its formation and regeneration in vitro and survival and vascularization in vivo.

By studying myogenic progenitors isolated from neonatal rats, we first discovered advantages of using an adherent cell fraction for engineering of skeletal muscles with robust structure and function and the formation of a SC pool. Specifically, when synergized with dynamic culture conditions, the use of adherent cells yielded muscle constructs capable of replicating the contractile output of native neonatal muscle, generating >40 mN/mm2 of specific force. Moreover, tissue structure and cellular heterogeneity of engineered muscle constructs closely resembled those of native muscle, consisting of aligned, striated myofibers embedded in a matrix of basal lamina proteins and SCs that resided in native-like niches. Importantly, we identified rapid formation of myofibers early during engineered muscle culture as a critical condition leading to SC homing and conversion to a quiescent, non-proliferative state. The SCs retained natural regenerative capacity and activated, proliferated, and differentiated to rebuild damaged myofibers and recover contractile function within 10 days after the muscle was injured by cardiotoxin (CTX). The resulting regenerative response was directly dependent on the abundance of SCs in the engineered muscle that we varied by expanding starting cell population under different levels of basic fibroblast growth factor (bFGF), an inhibitor of myogenic differentiation. Using a dorsal skinfold window chamber model in nude mice, we further demonstrated that within 2 weeks after implantation, initially avascular engineered muscle underwent robust vascularization and perfusion and exhibited improved structure and contractile function beyond what was achievable in vitro.

To enhance translational value of our approach, we transitioned to use of adult rat myogenic cells, but found that despite similar function to that of neonatal constructs, adult-derived muscle lacked regenerative capacity. Using a novel platform for live monitoring of calcium transients during construct culture, we rapidly screened for potential enhancers of regeneration to establish that many known pro-regenerative soluble factors were ineffective in stimulating in vitro engineered muscle recovery from CTX injury. This led us to introduce bone marrow-derived macrophages (BMDMs), an established non-myogenic contributor to muscle repair, to the adult-derived constructs and to demonstrate remarkable recovery of force generation (>80%) and muscle mass (>70%) following CTX injury. Mechanistically, while similar patterns of early SC activation and proliferation upon injury were observed in engineered muscles with and without BMDMs, a significant decrease in injury-induced apoptosis occurred only in the presence of BMDMs. The importance of preventing apoptosis was further demonstrated by showing that application of caspase inhibitor (Q-VD-OPh) yielded myofiber regrowth and functional recovery post-injury. Gene expression analysis suggested muscle-secreted tumor necrosis factor-α (TNFα) as a potential inducer of apoptosis as common for muscle degeneration in diseases and aging in vivo. Finally, we showed that BMDM incorporation in engineered muscle enhanced its growth, angiogenesis, and function following implantation in the dorsal window chambers in nude mice.

In summary, this thesis describes novel strategies to engineer highly contractile and regenerative skeletal muscle tissues starting from neonatal or adult rat myogenic cells. We find that age-dependent differences of myogenic cells distinctly affect the self-repair capacity but not contractile function of engineered muscle. Adult, but not neonatal, myogenic progenitors appear to require co-culture with other cells, such as bone marrow-derived macrophages, to allow robust muscle regeneration in vitro and rapid vascularization in vivo. Regarding the established roles of immune system cells in the repair of various muscle and non-muscle tissues, we expect that our work will stimulate the future applications of immune cells as pro-regenerative or anti-inflammatory constituents of engineered tissue grafts. Furthermore, we expect that rodent studies in this thesis will inspire successful engineering of biomimetic human muscle tissues for use in regenerative therapy and drug discovery applications.

Biologically Inspired Design of Protein-Silica Hybrid Nanoparticles for Drug Delivery Applications

The design and application of effective drug carriers is a fundamental concern in the delivery of therapeutics for the treatment of cancer and other vexing health problems. Traditionally utilized chemotherapeutics are limited in efficacy due to poor bioavailability as a result of their size and solubility as well as significant deleterious effects to healthy tissue through their inability to preferentially target pathological cells and tissues, especially in treatment of cancer. Thus, a major effort in the development of nanoscopic drug delivery vehicles for cancer treatment has focused on exploiting the inherent differences in tumor physiology and limiting the exposure of drugs to non-tumorous tissue, which is commonly achieved by encapsulation of chemotherapeutics within macromolecular or supramolecular carriers that incorporate targeting ligands and that enable controlled release. The overall aim of this work is to engineer a hybrid nanomaterial system comprised of protein and silica and to characterize its potential as an encapsulating drug carrier. The synthesis of silica, an attractive nanomaterial component because it is both biocompatible as well as structurally and chemically stable, within this system is catalyzed by self-assembled elastin-like polypeptide (ELP) micelles that incorporate of a class of biologically-inspired, silica-promoting peptides, silaffins. Furthermore, this methodology produces near-monodisperse, hybrid inorganic/micellar materials under mild reaction conditions such as temperature, pH and solvent. This work studies this material system along three avenues: 1) proof-of-concept silicification (i.e. the formation and deposition of silica upon organic materials) of ELP micellar templates, 2) encapsulation and pH-triggered release of small, hydrophobic chemotherapeutics, and 3) selective silicification of templates to potentiate retention of peptide targeting ability.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.