bioRxivBioengineeringPreprint
Self-Actuating 4D Cell-Strand Bioprinting
Aixiang DingiD, Ana Filipa CunhaiD, Mariana B. OliveiraiD, João Filipe ManoiD, Eben AlsbergiD
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Abstract
Engineering biomimetic tissues with dynamically evolving 3D architectures represents an important direction for next-generation tissue engineering, as it enables recapitulation of the continuous morphogenesis of native tissues during development and regeneration. Here, a self-actuating 4D cell-strand bioprinting platform is developed to engineer complex tissue architectures through autonomous cell contractile force (CCF)-driven morphing without requiring external stimuli. The platform integrates a mechanically compliant and self-softening base hydrogel with embedded high-density cell strands printed using a fast-degrading carrier bioink. During culture, the carrier bioink rapidly degrades while the encapsulated cells proliferate and establish connected cellular networks, generating localized contraction that drives programmable shape transformation. Through spatial patterning of embedded cell strands, constructs with diverse morphologies, including V-shaped, helical, folded, and tubular architectures, are generated via controllable self-actuated morphogenesis. The platform further enables engineering of cartilage-like and bone-like tissues with well-defined curvature configurations and mechanically robust tissue matrices. In addition, programmable multi-tissue engineering is demonstrated through fabrication of a muscle-tendon junction-mimicking construct containing spatially organized fibroblast and myoblast compartments. This self-actuating 4D bioprinting strategy enables highly programmable and directionally controlled morphogenesis using a simple construct design with low cell amount requirements, providing a versatile platform for engineering dynamic tissue architectures.
- assay: organoid / primary culture
- research focus: transcription & RNA processing
- research focus: cell type annotation
- research focus: clustering
- research focus: trajectory inference
- approach: experimental assay
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