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Cell-mediated sculptable living platforms as highly efficient hybrid units to bioengineer human microtissues
Summary
Original abstract (not yet simplified)Geometrical, mechanical, and biochemical signals are master regulators of differentiation and other cellular processes. Biomaterials have been used to create artificial 3D niches recapitulating such favourable cues, traditionally optimized through progressive and laborious design-build-test-learn cycles. In native environments, however, cells dynamically interact and modify their surroundings, engaging in feedback loops that alter their phenotype and trigger collective effects. Based on...
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Geometrical, mechanical, and biochemical signals are master regulators of differentiation and other cellular processes. Biomaterials have been used to create artificial 3D niches recapitulating such favourable cues, traditionally optimized through progressive and laborious design-build-test-learn cycles. In native environments, however, cells dynamically interact and modify their surroundings, engaging in feedback loops that alter their phenotype and trigger collective effects. Based on such principles, and leveraged by a unique synergy between biomaterials, synthetic biology, and computer modelling, RODIN proposes a transformative approach by engineering biomaterial units based on flexible, micro-sized films that allow stem cells to autonomously sculpt their environments. These hybrid structures (pockets), formed through crumpling or origami-like folding, will create diverse internal milieus for cells to freely explore. We hypothesise that the microenvironment in the pockets can be moulded for a targeted cell phenotype based on local material properties and biochemical differentiation factors. To test this, films will be made from bioactive human-derived proteins or nanocellulose. In the latter, engineered microbes programmed to secrete specific factors will be embedded within the films to create a living platform able to guide stem cells toward osteogenic differentiation. Cell behaviour will be correlated with local structural data from the pockets and analysed using deep learning to identify favourable geometrical and structural descriptors that could help to engineer bioactive improbable synthetic niches. Computer modelling will identify optimal conditions for producing high-quality microtissues, with applications in regenerative medicine and pre-clinical disease modelling. These insights will also assist in scaling tissue engineering through assembly-based biofabrication techniques to generate hierarchical living constructs with unprecedent biological features.
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