Discriminating protein tags on a dsDNA construct using a Dual Nanopore Device

Abstract

We report Brownian dynamics simulation results with the specific goal to identify key parameters controlling the experimentally measurable characteristics of protein tags on a dsDNA construct translocating through a double nanopore setup. First, we validate the simulation scheme in silico by reproducing and explaining the physical origin of the asymmetric experimental dwell time distributions of the oligonucleotide flap markers on a 48 kbp long dsDNA at the left and the right pore. We study the effect of the electric field inside and beyond the pores, critical to discriminate the protein tags based on their effective charges and masses revealed through a generic power-law dependence of the average dwell time at each pore. The simulation protocols monitor piecewise dynamics at a sub-nanometer length scale and explain the disparate velocity using the concepts of nonequilibrium tension propagation theory. We further justify the model and the chosen simulation parameters by calculating the Péclet number which is in close agreement with the experiment. We demonstrate that our carefully chosen simulation strategies can serve as a powerful tool to discriminate different types of neutral and charged tags of different origins on a dsDNA construct in terms of their physical characteristics and can provide insights to increase both the efficiency and accuracy of an experimental dual-nanopore setup.

Electronic Mapping of a Bacterial Genome with Dual Solid-State Nanopores and Active Single-Molecule Control

“…Therefore, the 2× higher observed velocity going R–L is likely a consequence of the 2× larger net force: 300 mV R–L (600–300 mV) vs 150 mV L–R (300–150 mV). A detailed analysis of how tag peak widths change as a function of the speed differences in the two directions is explored in another article in preparation …”

“…A detailed analysis of how tag peak widths change as a function of the speed differences in the two directions is explored in another article in preparation. 49 Once linear distance estimates between tags are computed for a given scan, the second conversion requires converting the spatial distance estimates (nm) into a genomic distance estimates (bp). The core of our alignment method is a probability distribution modeling the stretching of DNA under forces exerted by the dual-pore system.…”