Combining biological components, such as cells and tissues, with soft robotics can enable the fabrication of biological machines with the ability to sense, process signals, and produce force. An intuitive demonstration of a biological machine is one that can produce motion in response to controllable external signaling. Whereas cardiac cell-driven biological actuators have been demonstrated, the requirements of these machines to respond to stimuli and exhibit controlled movement merit the use of skeletal muscle, the primary generator of actuation in animals, as a contractile power source. Here, we report the development of 3D printed hydrogel "bio-bots" with an asymmetric physical design and powered by the actuation of an engineered mammalian skeletal muscle strip to result in net locomotion of the bio-bot. Geometric design and material properties of the hydrogel bio-bots were optimized using stereolithographic 3D printing, and the effect of collagen I and fibrin extracellular matrix proteins and insulin-like growth factor 1 on the force production of engineered skeletal muscle was characterized. Electrical stimulation triggered contraction of cells in the muscle strip and net locomotion of the bio-bot with a maximum velocity of ∼156 μm s −1 , which is over 1.5 body lengths per min. Modeling and simulation were used to understand both the effect of different design parameters on the bio-bot and the mechanism of motion. This demonstration advances the goal of realizing forward-engineered integrated cellular machines and systems, which can have a myriad array of applications in drug screening, programmable tissue engineering, drug delivery, and biomimetic machine design.bioactuator | stereolithography
Densely arrayed skeletal myotubes are activated individually and as a group using precise optical stimulation with high spatiotemporal resolution. Skeletal muscle myoblasts are genetically encoded to express light-activated cation channel, Channelrhodopsin-2, which allows for spatiotemporal coordination of the multitude of skeletal myotubes that contract in response to pulsed blue light. Furthermore, ensembles of mature functional 3D muscle microtissues have been formed from the optogenetically encoded myoblasts using a high-throughput device. The device, called “skeletal muscle on a chip”, not only provides the myoblasts with controlled stress and constraints necessary for muscle alignment, fusion and maturation, but also facilitates to measure forces and characterize the muscle tissue. We measured the specific static and dynamic stresses generated by the microtissues, and characterized the morphology and alignment of the myotubes within the constructs. The device allows for testing the effect of a wide range of parameters (cell source, matrix composition, microtissue geometry, auxotonic load, growth factors, and exercise) on the maturation, structure, and function of the engineered muscle tissues in a combinatorial manner. Our studies integrate tools from optogenetics and microelectromechanical systems (MEMS) technology with skeletal muscle tissue engineering to open up opportunities to generate soft robots actuated by multitude of spatiotemporally coordinated 3D skeletal muscle microtissues.
We introduce a novel representation of two-dimensional shape that we call smoothed local symmetries (SLS). Smoothed local symmetries represent both the bounding contour of a shape fragment and the region that it occupies. In this paper we develop the main features of the SLS representation and describe an implemented algorithm that computes it. The performance of the algorithm is illustrated for a set of tools. We conclude by sketching a method for determining the articulation of a shape into subshapes.
Filopodia have a key role in sensing both chemical and mechanical cues in surrounding extracellular matrix (ECM). However, quantitative understanding is still missing in the filopodial mechanosensing of local ECM stiffness, resulting from dynamic interactions between filopodia and the surrounding 3D ECM fibers. Here we present a method for characterizing the stiffness of ECM that is sensed by filopodia based on the theory of elasticity and discrete ECM fiber. We have applied this method to a filopodial mechanosensing model for predicting directed cell migration toward stiffer ECM. This model provides us with a distribution of force and displacement as well as their time rate of changes near the tip of a filopodium when it is bound to the surrounding ECM fibers. Aggregating these effects in each local region of 3D ECM, we express the local ECM stiffness sensed by the cell and explain polarity in the cellular durotaxis mechanism.
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