High-throughput Kinetics using Capillary Electrophoresis and Robotics (HiKER) platform used to Study T7, T3, and Sp6 RNA Polymerase Misincorporation

Abstract

T7 RNA Polymerase (RNAP) is a well-studied and widely used enzyme with recent applications in the production of RNA vaccines. For over 50 years denaturing sequencing gels have been used as a key analysis tool for probing the kinetic mechanism of T7 RNAP nucleotide addition. However, sequencing gels are both slow and low throughput limiting their utility for comprehensive enzyme analysis. Here, we report the development of HiKER; (High-throughput Kinetics using Capillary Electrophoresis and Robotics) a high-throughput pipeline to quantitatively measure enzyme kinetics. We adapted a traditional polymerase misincorporation assay for fluorescent detection at scale allowing rapid estimates of RNAP misincorporation in different experimental conditions. In addition, high-throughput kinetics reactions were automated using an open-source OT-2 liquid handling robot. The platform allows multiple weeks worth of data to be collected in mere days. Using this platform, [~]1500 time points were collected in a single workday. T7 RNAP exhibited dramatic differences in both observed rate constant and amplitude depending on the mismatch examined. An average misincorporation frequency of [~]45 misincorporations per million bases was estimated using HiKER and is consistent with previous observations from next generation sequencing studies. Misincorporation time courses for T3 RNAP and Sp6 RNAP were similar to T7 RNAP suggesting conserved kinetic mechanisms. Interestingly, dramatic changes in the extent of misincorporation were observed in the three RNAPs depending on the mismatch. Extension from base mismatch experiments showed differences between T7, T3, and Sp6 RNAP. Sp6 RNAP was the slowest to extend from a mismatch followed by T7 RNAP and then T3 RNAP. Taken together the results presented here demonstrate the capabilities of HiKER to carry out high-throughput enzymology studies. Importantly, this pipeline and the corresponding analysis strategies are affordable, open-source, and broadly applicable to many enzymes.