Highly specific SNP detection using 2D graphene electronics and DNA strand displacement
- Authors
- Hwang, Michael T.; Landon, Preston B.; Lee, Joon; Choi, Duyoung; Mo, Alexander H.; Glinsky, Gennadi; Lal, Ratnesh
- Issue Date
- Jun-2016
- Publisher
- NATL ACAD SCIENCES
- Keywords
- bioelectronics; graphene FET DNA sensor; electrical biosensor; DNA strand displacement; SNP detection
- Citation
- PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, v.113, no.26, pp.7088 - 7093
- Journal Title
- PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Volume
- 113
- Number
- 26
- Start Page
- 7088
- End Page
- 7093
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/81335
- DOI
- 10.1073/pnas.1603753113
- ISSN
- 0027-8424
- Abstract
- Single-nucleotide polymorphisms (SNPs) in a gene sequence are markers for a variety of human diseases. Detection of SNPs with high specificity and sensitivity is essential for effective practical implementation of personalized medicine. Current DNA sequencing, including SNP detection, primarily uses enzyme-based methods or fluorophore-labeled assays that are time-consuming, need laboratory-scale settings, and are expensive. Previously reported electrical charge-based SNP detectors have insufficient specificity and accuracy, limiting their effectiveness. Here, we demonstrate the use of a DNA strand displacement-based probe on a graphene field effect transistor (FET) for high-specificity, single-nucleotide mismatch detection. The single mismatch was detected by measuring strand displacement-induced resistance (and hence current) change and Dirac point shift in a graphene FET. SNP detection in large double-helix DNA strands (e.g., 47 nt) minimize false-positive results. Our electrical sensor-based SNP detection technology, without labeling and without apparent cross-hybridization artifacts, would allow fast, sensitive, and portable SNP detection with single-nucleotide resolution. The technology will have a wide range of applications in digital and implantable biosensors and high-throughput DNA genotyping, with transformative implications for personalized medicine.
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