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Nanomechanoelectrical approach to highly sensitive and specific label-free DNA detection.
Zhang, Xiaoyu; Fan, Xiao; Bao, Huilu; Ping, Jinglei.
Afiliação
  • Zhang X; Department of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA 01003.
  • Fan X; Department of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA 01003.
  • Bao H; Department of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA 01003.
  • Ping J; Department of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA 01003.
Proc Natl Acad Sci U S A ; 120(33): e2306130120, 2023 08 15.
Article em En | MEDLINE | ID: mdl-37549255
Electronic detection of DNA oligomers offers the promise of rapid, miniaturized DNA analysis across various biotechnological applications. However, known all-electrical methods, which solely rely on measuring electrical signals in transducers during probe-target DNA hybridization, are prone to nonspecific electrostatic and electrochemical interactions, subsequently limiting their specificity and detection limit. Here, we demonstrate a nanomechanoelectrical approach that delivers ultra-robust specificity and a 100-fold improvement in detection limit. We drive nanostructural DNA strands tethered to a graphene transistor to oscillate in an alternating electric field and show that the transistor-current spectra are characteristic and indicative of DNA hybridization. We find that the inherent difference in pliability between unpaired and paired DNA strands leads to the spectral characteristics with minimal influence from nonspecific electrostatic and electrochemical interactions, resulting in high selectivity and sensitivity. Our results highlight the potential of high-performance DNA analysis based on miniaturized all-electronic settings.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Técnicas Biossensoriais / Grafite Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Técnicas Biossensoriais / Grafite Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article