Gelator Length Precisely Tunes Supramolecular Hydrogel Stiffness and Neuronal Phenotype in 3D Culture
| Autor: | Jacob A. Lewis, Ronit Freeman, Lena F. Burbulla, Dimitri Krainc, Jacqueline M. Godbe, Samuel I. Stupp |
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| Rok vydání: | 2020 |
| Předmět: |
Induced Pluripotent Stem Cells
0206 medical engineering Population Cell Culture Techniques Biomedical Engineering 02 engineering and technology Article Biomaterials Peptide amphiphile medicine education Induced pluripotent stem cell Neurons education.field_of_study technology industry and agriculture Hydrogels 021001 nanoscience & nanotechnology 020601 biomedical engineering Transplantation Phenotype medicine.anatomical_structure Cell culture Nanofiber Self-healing hydrogels Biophysics Neuron 0210 nano-technology |
| Zdroj: | ACS Biomater Sci Eng |
| ISSN: | 2373-9878 |
| DOI: | 10.1021/acsbiomaterials.9b01585 |
| Popis: | The brain is one of the softest tissues in the body with storage moduli (G') that range from hundreds to thousands of pascals (Pa) depending upon the anatomic region. Furthermore, pathological processes such as injury, aging and disease can cause subtle changes in the mechanical properties throughout the central nervous system. However, these changes in mechanical properties lie within an extremely narrow range of moduli and there is great interest in understanding their effect on neuron biology. We report here the design of supramolecular hydrogels based on anionic peptide amphiphile nanofibers using oligo-L-lysines of different molecular lengths to precisely tune gel stiffness over the range of interest and found that G' increases by 10.5 Pa for each additional lysine monomer in the oligo-L-lysine chain. We found that small changes in storage modulus on the order of 70 Pa significantly affect survival, neurite growth and tyrosine hydroxylase-positive population in dopaminergic neurons derived from induced pluripotent stem cells. The work reported here offers a strategy to tune mechanical stiffness of hydrogels for use in 3D neuronal cell cultures and transplantation matrices for neural regeneration. |
| Databáze: | OpenAIRE |
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