Abstract

Sequencing Single RNA Molecules using a Nanofluidic Device with Dual In-Plane Nanopore Sensors and Immobilized Exoribonuclease Enzymes

Steve Soper, Foundation Distinguished Professor; Director, Center of BioModular Multi-scale System for Precision Medicine, Adjunct Professor, Ulsan National Institute of Science & Technology, The University of Kansas

With the development of next generation sequencing (NGS), the field of transcriptomics has seen tremendous advancements opening up opportunities for improved diagnostics of diseases such as cancers and infectious diseases. RNA sequencing enables measurement of single nucleotide variants (SNVs), insertions and deletions, detection of different transcript isoforms, splice variants, and chimeric gene fusions. Although NGS has been useful for unraveling RNA structure and function, several technical difficulties remain including the need for reverse transcription and PCR amplification, which can mask epitranscriptomic modifications. To address NGS issues, we are developing an exciting new sequencing technology called Exonuclease Time-of-Flight (X-ToF) for the label-free detection and identification of single molecules. The hypothesis behind X-ToF is, “individual molecules moving electrokinetically through a 2D nanotube will experience a time-of-flight (ToF) that is dependent upon its molecular identity.”  X-ToF is a nanofluidic device comprised of input/output channels, a nanoscale solid-phase enzymatic bioreactor, and a flight tube equipped with a pair of in-plane nanopores to measure the ToF of a single ribonucleotide monophosphate (rNMP). Each rNMP is produced from an unamplified RNA molecule being clipped with a processive exoribonuclease, XRN1. In this presentation we will discuss the high rate manufacturing of the X-ToF chip with sub-5 nm in-plane nanopores using nano-injection molding from a cyclic olefin polymer (COP) plastic. The in-plane pores are situated at either end of a nanochannel (50 x 50 nm; 10 µm long) that generates current transient signals to detect and deduce the identity of rNMPs. The ToF is dependent on the apparent electrophoretic mobility of the molecule. The identity is determined from the ToF, the current transient amplitudes, and dwell times using multi-parameter Principle Component Analysis (PCA) or machine learning. We will show the ability to detect (detection efficiency ~100%) single rNMPs with identification accuracies >99% in a single read. Finally, we will discuss the generation of solid-phase nano-bioreactors using XRN1, which can cleave ssRNA in the 5' to 3’ direction releasing single rNMPs that are detected and identified using the in-plane nanopore sensor. Unique properties of the immobilized enzyme will be presented in terms of its processivity and kinetic rate of cleaving single RNA molecules.