Showing papers by "Michael G. Pollack published in 2017"
TL;DR: The results suggest that dielectric shielding intrinsic to bead-bound cells significantly reduces electroporation field exposure efficiency, but high transformation frequency can be maintained in the presence of magnetic beads through the application of more intense Electroporation pulses.
Abstract: This paper reports on the use of a digital microfluidic platform to perform multiplex automated genetic engineering (MAGE) cycles on droplets containing Escherichia coli cells. Bioactivated magnetic beads were employed for cell binding, washing, and media exchange in the preparation of electrocompetent cells in the electrowetting-on-dieletric (EWoD) platform. On-cartridge electroporation was used to deliver oligonucleotides into the cells. In addition to the optimization of a magnetic bead-based benchtop protocol for generating and transforming electrocompetent E. coli cells, we report on the implementation of this protocol in a fully automated digital microfluidic platform. Bead-based media exchange and electroporation pulse conditions were optimized on benchtop for transformation frequency to provide initial parameters for microfluidic device trials. Benchtop experiments comparing electrotransformation of free and bead-bound cells are presented. Our results suggest that dielectric shielding intrinsic to bead-bound cells significantly reduces electroporation field exposure efficiency. However, high transformation frequency can be maintained in the presence of magnetic beads through the application of more intense electroporation pulses. As a proof of concept, MAGE cycles were successfully performed on a commercial EWoD cartridge using variations of the optimal magnetic bead-based preparation procedure and pulse conditions determined by the benchtop results. Transformation frequencies up to 22% were achieved on benchtop; this frequency was matched within 1% (21%) by MAGE cycles on the microfluidic device. However, typical frequencies on the device remain lower, averaging 9% with a standard deviation of 9%. The presented results demonstrate the potential of digital microfluidics to perform complex and automated genetic engineering protocols.
13 citations