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Myokines and exosomes, originating from skeletal muscle, are shown to play a significant role in maintaining brain homeostasis. While exercise has been reported to promote muscle secretion, little is known about the effects of neuronal innervation and activity on the yield and molecular composition of biologically active molecules from muscle. As neuromuscular diseases and disabilities associated with denervation impact muscle metabolism, we hypothesize that neuronal innervation and firing may play a pivotal role in regulating secretion activities of skeletal muscles. We examined this hypothesis using an engineered neuromuscular tissue model consisting of skeletal muscles innervated by motor neurons. The innervated muscles displayed elevated expression of mRNAs encoding neurotrophic myokines, such as interleukin-6, brain-derived neurotrophic factor, and FDNC5, as well as the mRNA of peroxisome-proliferator-activated receptor γ coactivator 1α, a key regulator of muscle metabolism. Upon glutamate stimulation, the innervated muscles secreted higher levels of irisin and exosomes containing more diverse neurotrophic microRNAs than neuron-free muscles. Consequently, biological factors secreted by innervated muscles enhanced branching, axonal transport, and, ultimately, spontaneous network activities of primary hippocampal neurons in vitro. Overall, these results reveal the importance of neuronal innervation in modulating muscle-derived factors that promote neuronal function and suggest that the engineered neuromuscular tissue model holds significant promise as a platform for producing neurotrophic molecules. 

The integration of muscle cells with soft robotics in recent years has led to the development of biohybrid machines capable of untethered locomotion. A major frontier that currently remains unexplored is neuronal actuation and control of such muscle-powered biohybrid machines. As a step toward this goal, we present here a biohybrid swimmer driven by on-board neuromuscular units. The body of the swimmer consists of a free-standing soft scaffold, skeletal muscle tissue, and optogenetic stem cell-derived neural cluster containing motor neurons. Myoblasts embedded in extracellular matrix self-organize into a muscle tissue guided by the geometry of the scaffold, and the resulting muscle tissue is cocultured in situ with a neural cluster. Motor neurons then extend neurites selectively toward the muscle and innervate it, developing functional neuromuscular units. Based on this initial construct, we computationally designed, optimized, and implemented light-sensitive flagellar swimmers actuated by these neuromuscular units. Cyclic muscle contractions, induced by neural stimulation, drive time-irreversible flagellar dynamics, thereby providing thrust for untethered forward locomotion of the swimmer. Overall, this work demonstrates an example of a biohybrid robot implementing neuromuscular actuation and illustrates a path toward the forward design and control of neuron-enabled biohybrid machines. 

Formation of tissue models in 3 dimensions is more effective in recapitulating structure and function compared to their 2-dimensional (2D) counterparts. Formation of 3D engineered tissue to control shape and size can have important implications in biomedical research and in engineering applications such as biological soft robotics. While neural spheroids routinely are created during differentiation processes, further geometric control of in vitro neural models has not been demonstrated. Here, we present an approach to form functional in vitro neural tissue mimic (NTM) of different shapes using stem cells, a fibrin matrix, and 3D printed molds. We used murine-derived embryonic stem cells for optimizing cell-seeding protocols, characterization of the resulting internal structure of the construct, and remodeling of the extracellular matrix, as well as validation of electrophysiological activity. Then, we used these findings to biofabricate these constructs using neurons derived from human embryonic stem cells. This method can provide a large degree of design flexibility for development of in vitro functional neural tissue models of varying forms for therapeutic biomedical research, drug discovery, and disease modeling, and engineering applications. 

Tissue-on-chip systems represent promising platforms for monitoring and controlling tissue functions in vitro for various purposes in biomedical research. The two-dimensional (2D) layouts of these constructs constrain the types of interactions that can be studied and limit their relevance to three-dimensional (3D) tissues. The development of 3D electronic scaffolds and microphysiological devices with geometries and functions tailored to realistic 3D tissues has the potential to create important possibilities in advanced sensing and control. This study presents classes of compliant 3D frameworks that incorporate microscale strain sensors for high-sensitivity measurements of contractile forces of engineered optogenetic muscle tissue rings, supported by quantitative simulations. Compared with traditional approaches based on optical microscopy, these 3D mechanical frameworks and sensing systems can measure not only motions but also contractile forces with high accuracy and high temporal resolution. Results of active tension force measurements of engineered muscle rings under different stimulation conditions in long-term monitoring settings for over 5 wk and in response to various chemical and drug doses demonstrate the utility of such platforms in sensing and modulation of muscle and other tissues. Possibilities for applications range from drug screening and disease modeling to biohybrid robotic engineering. 

Abstract Integration of conductive electrodes with 3D tissue models can have great potential for applications in bioelectronics, drug screening, and implantable devices. As conventional electrodes cannot be easily integrated on 3D, polymeric, and biocompatible substrates, alternatives are highly desirable. Graphene offers significant advantages over conventional electrodes due to its mechanical flexibility and robustness, biocompatibility, and electrical properties. However, the transfer of chemical vapor deposition graphene onto millimeter scale 3D structures is challenging using conventional wet graphene transfer methods with a rigid poly (methyl methacrylate) (PMMA) supportive layer. Here, a biocompatible 3D graphene transfer method onto 3D printed structure using a soft poly ethylene glycol diacrylate (PEGDA) supportive layer to integrate the graphene layer with a 3D engineered ring of skeletal muscle tissue is reported. The use of softer PEGDA supportive layer, with a 10⁵times lower Young's modulus compared to PMMA, results in conformal integration of the graphene with 3D printed pillars and allows electrical stimulation and actuation of the muscle ring with various applied voltages and frequencies. The graphene integration method can be applied to many 3D tissue models and be used as a platform for electrical interfaces to 3D biological tissue system.