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You are researching: Methacrylated Collagen (CollMA)
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AUTHOR Oliveira, Hugo and Médina, Chantal and Stachowicz, Marie-Laure and Paiva dos Santos, Bruno and Chagot, Lise and Dusserre, Nathalie and Fricain, Jean-Christophe
Title Extracellular matrix (ECM)-derived bioinks designed to foster vasculogenesis and neurite outgrowth: Characterization and bioprinting [Abstract]
Year 2021
Journal/Proceedings Bioprinting
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DOI/URL URL DOI
Abstract
The field of bioprinting has shown a tremendous development in recent years, focusing on the development of advanced in vitro models and on regeneration approaches. In this scope, the lack of suitable biomaterials that can be efficiently formulated as printable bioinks, while supporting specific cellular events, is currently considered as one of the main limitations in the field. Indeed, extracellular matrix (ECM)-derived biomaterials formulated to enable printability and support cellular response, for instance via integrin binding, are eagerly awaited in the field of bioprinting. Several bioactive laminin sequences, including peptides such as YIGSR and IKVAV, have been identified to promote endothelial cell attachment and/or neurite outgrowth and guidance, respectively. Here, we show the development of two distinct bioinks, designed to foster vasculogenesis or neurogenesis, based on methacrylated collagen and hyaluronic acid (CollMA and HAMA, respectively), both relevant ECM-derived polymers, and on their combination with cysteine-flanked laminin-derived peptides. Using this strategy, it was possible to optimize the bioink printability, by tuning CollMA and HAMA concentration and ratio, and modulate their bioactivity, through adjustments in the cell-active peptide sequence spatial density, without compromising cell viability. We demonstrated that cell-specific bioinks could be customized for the bioprinting of both human umbilical vein cord endothelial cells (HUVECs) or adult rat sensory neurons from the dorsal root ganglia, and could stimulate both vasculogenesis and neurite outgrowth, respectively. This approach holds great potential as it can be tailored to other cellular models, due to its inherent capacity to accommodate different peptide compositions and to generate complex peptide mixtures and/or gradients.