Optimizing mRNA transfection on a high-definition electroporation microelectrode array results in 98% efficiency and multiplexed gene delivery
Spatially resolved transfection, intracellular delivery of proteins and nucleic acids, has the potential to drastically speed up the discovery of biologically active cargos, for instance for the development of cell therapies or new genome engineering tools. We recently demonstrated the use of a high...
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Veröffentlicht in: | Biosensors & bioelectronics 2023-12, Vol.241, p.115634-115634, Article 115634 |
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Sprache: | eng |
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Zusammenfassung: | Spatially resolved transfection, intracellular delivery of proteins and nucleic acids, has the potential to drastically speed up the discovery of biologically active cargos, for instance for the development of cell therapies or new genome engineering tools. We recently demonstrated the use of a high-density microelectrode array for the targeted electrotransfection of cells grown on its surface, a process called High-Definition Electroporation (HD-EP). We also developed a framework based on Design of Experiments to quickly establish optimized electroporation conditions across five different electrical pulse parameters. Here, we used this framework to optimize the transfection efficiency of primary fibroblasts with a mCherry-encoding mRNA, resulting in 98% of the cells expressing the desired fluorescent protein without any sign of cell death. That transfection yield is the highest reported so far for electroporation. Moreover, varying the pulse number was shown to modulate the fluorescence intensity of cells, indicating the dosage-controlled delivery of mRNA and protein expression. Finally, exploiting the single-electrode addressability of the microelectrode array, we demonstrated spatially resolved, high efficiency, sequential transfection of cells with three distinct mRNAs. Since the chip can be easily redesigned to feature a much large number of electrodes, we anticipate that this methodology will enable the development of dedicated screening platforms for analysis of mRNA variants at scale. |
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ISSN: | 0956-5663 1873-4235 |
DOI: | 10.1016/j.bios.2023.115634 |