bioRxiv · 10.1101/2020.02.26.960336
Numerical optimization of microfluidic vortex shedding for genome editing human primary T cells using machine learning
Abstract
Microfluidic vortex shedding (VS) can rapidly deliver mRNA to T cells with high yield. The mechanistic underpinning of VS intracellular delivery remains undefined and VS-Cas9 genome editing requires further studies. Herein, we evaluated a series of VS devices containing splitter plates to attenuate vortex shedding and understand the contribution of computed force and frequency on efficiency and viability. We then selected a VS design to knockout the expression of the endogenous T cell receptor in primary human T cells via delivery of CRISPR-Cas9 ribonucleoprotein (RNP) with and without brief exposure to an electric field (eVS). VS alone resulted in an equivalent yield of genome-edited T cells relative to electroporation with improved cell quality. A 1.8-fold increase in editing efficiency was demonstrated with eVS with negligible impact on cell viability. Cumulatively, these results demonstrate the utility of VS and eVS for genome editing human primary T cells with Cas9 RNPs.
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Jarrell, J. A., Lievano, A. A., Pan, F. L., Lau, K. H. W. J., Kirby, G. T. S., Pawell, R. S.. 2020-02-27. Numerical optimization of microfluidic vortex shedding for genome editing human primary T cells using machine learning. https://doi.org/10.1101/2020.02.26.960336
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