(346b) Single-Molecule Conductance Measurements with Conformational Smear Characterization for Nucleotide Recognition | AIChE

(346b) Single-Molecule Conductance Measurements with Conformational Smear Characterization for Nucleotide Recognition

Authors 

Korshoj, L. - Presenter, University of Colorado Boulder
Afsari, S., University of Colorado Boulder
Chatterjee, A., University of Colorado Boulder
Nagpal, P., University of Colorado Boulder
Next-generation single-molecule nucleic acid sequencing will require unambiguous identification of DNA nucleotides in an enzyme-free, low-cost, and accurate method that does not involve synthetic amplification or complex sample preparation. Several nanoscale electronic methods have been proposed for high-throughput single-molecule nucleic acid sequence identification. While many studies display a large ensemble of measurements as electronic fingerprints with some promise for distinguishing the nucleobases (adenine A, guanine G, cytosine C, thymine T), important metrics like accuracy of base calling fall well below the current genomic methods. Issues such as unreliable metal-molecule junction formation, variation of nucleotide conformations, insufficient differences between the molecular orbitals responsible for charge conduction, and lack of rigorous base calling algorithms lead to overlapping nanoelectronic measurements and poor nucleotide discrimination, especially at low coverage on single molecules. We have demonstrated a single-molecule conductance method for achieving highly accurate nucleotide discrimination with promising applications for next-generation sequencing.

Our quantum point contact single-nucleotide conductance sequencing (QPICS) method enables reproducible conductance measurements of conformationally constrained single nucleotides within electrostatically bound DNA molecules on a self-assembled cysteamine monolayer [1]. From these measurements, we quantify conformational variation, or smear, from the distance over which molecular junctions are maintained during each conductance measurement [2]. Advanced algorithmic approaches rooted in machine learning were designed for accurate nucleotide identification from single-molecule conductance measurements and the unique conductance signatures for each nucleotide. We observed 93.9% accuracy for recognition of DNA nucleotides at 20× coverage (repeat measurements).

These results represent a significant improvement over contemporary sequencing methods and demonstrate the potential for using simple surface modifications and existing biochemical moieties in nucleobases for reliable single-molecule, nanoelectronic nucleotide identification.

[1] Afsari, Korshoj, Abel, Jr., Khan, Chatterjee, Nagpal, ACS Nano 11 (11), 11169-11181 (2017).

[2] Korshoj, Afsari, Chatterjee, Nagpal, J. Am. Chem. Soc. 139 (43), 15420-15428 (2017).