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Magnetic spatiotemporal control of SOS1 coupled nanoparticles for guided neurite growth in dopaminergic single cells
The axon regeneration of neurons in the brain can be enhanced by activating intracellular signaling pathways such as those triggered by the membrane-anchored Rat sarcoma (RAS) proto-oncogene. Here we demonstrate the induction of neurite growth by expressing tagged permanently active Harvey-RAS prote...
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Published in: | Scientific reports 2020-12, Vol.10 (1), p.22452-22452, Article 22452 |
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Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The axon regeneration of neurons in the brain can be enhanced by activating intracellular signaling pathways such as those triggered by the membrane-anchored Rat sarcoma (RAS) proto-oncogene. Here we demonstrate the induction of neurite growth by expressing tagged permanently active Harvey-RAS protein or the RAS-activating catalytic domain of the guanine nucleotide exchange factor (SOS1cat), in secondary dopaminergic cells. Due to the tag, the expressed fusion protein is captured by functionalized magnetic nanoparticles in the cytoplasm of the cell. We use magnetic tips for remote translocation of the SOS1cat-loaded magnetic nanoparticles from the cytoplasm towards the inner face of the plasma membrane where the endogenous Harvey-RAS protein is located. Furthermore, we show the magnetic transport of SOS1cat-bound nanoparticles from the cytoplasm into the neurite until they accumulate at its tip on a time scale of minutes. In order to scale-up from single cells, we show the cytoplasmic delivery of the magnetic nanoparticles into large numbers of cells without changing the cellular response to nerve growth factor. These results will serve as an initial step to develop tools for refining cell replacement therapies based on grafted human induced dopaminergic neurons loaded with functionalized magnetic nanoparticles in Parkinson model systems. |
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ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-020-80253-w |