Single molecule sequencing of full-length RNA will provide a technology platform for analysis of transcripts with low copy numbers in a single cell. Two methods for doing this have been demonstrated: In the first one (Pacific Biosciences), full-length RNA is first converted to complementary DNA and then sequenced via single molecule, real-time (SMRT) sequencing, in which single-molecule optics is used to monitor the addition of nucleotides during DNA synthesis. The second approach is ion-current sensing of translocation in a protein nanopore (the MinION from Oxford Nanopore Technologies). SMRT sequencing has high capital and reagent costs, factors that have limited its deployment. Ion-current based nanopore sensing is low-cost and convenient but limited to sensing five bases at a time. This complicates reads of modified bases and homopolymer tracts. Electron tunneling has the ability to read one base at a time, but the required electrode gaps are too small to pass an RNA molecule. We have developed Recognition Tunneling (RT) using small recognition molecules (RMs) that are chemically attached to electrodes. RT extends the tunneling range, so that larger (2.5 nm) electrode gaps can be used, and specific interactions with the RMs improve the readout accuracy. Using RT we are able to read through homopolymer tracts and recognize modified bases directly, offering a path to a substantial advance beyond existing approaches. Solid-state RT chips have been demonstrated and the first signals from translocating oligomers have been obtained (using devices with fairly large pores). A better control of translocation and unwinding of folded RNA molecules are now the key requirements for successful implementation of RT sequencing (as was the case with ion-current protein pores prior to 2012). Here, we propose to implement a hybrid pore comprised of a poliovirus RNA polymerase trapped in a solid-state pore.
In Aim 1 we will develop a scalable process to make solid-state devices with smaller pores (< 5nm). We are partnering with Norcada, a manufacturer of MEMs devices, for production engineering.
In Aim 2 we will develop protocols to trap the polymerase-RNA complex, and pull the RNA through the solid-state pore, using the polymerase tunnel to linearize the RNA and pass a single strand into the solid-state pore one base at a time.
In Aim 3 we will develop the device and on-chip electronics so as to lay the groundwork for large-scale manufacture of arrays of devices that operate in parallel and at high speed. Our team has unique strengths and consists of Stuart Lindsay and Peiming Zhang (Arizona State University) who will build devices and integrate the work of the team; Meni Wanunu (North Eastern University) and Ya-Ming Hou (Thomas Jefferson University) who will build and characterize hybrid solid-state-protein pores; Adam Hall (Wake Forest University) who will develop reliable (and scalable) methods of fabricating small pores and Jacob Rosenstein (Brown) who will design RT chips with enhanced performance, including on-chip signal processing.

Public Health Relevance

/Relevance The ability to read RNA sequences directly, including modified ribonucleosides and homopolymer tracts, will improve our understanding of the human transcriptome and its role in human health and disease. Recognition tunneling offers a substantial advancement over other single molecule sequencing technologies, using low-cost and convenient solid-state devices.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
1R01HG009180-01
Application #
9171847
Study Section
Special Emphasis Panel (ZHG1-HGR-N (M1))
Program Officer
Smith, Michael
Project Start
2016-09-28
Project End
2019-06-30
Budget Start
2016-09-28
Budget End
2017-06-30
Support Year
1
Fiscal Year
2016
Total Cost
$512,738
Indirect Cost
$150,570
Name
Arizona State University-Tempe Campus
Department
Physiology
Type
Organized Research Units
DUNS #
943360412
City
Tempe
State
AZ
Country
United States
Zip Code
85287
Zhang, Bintian; Song, Weisi; Pang, Pei et al. (2017) Observation of Giant Conductance Fluctuations in a Protein. Nano Futures 1: