Highly specific SNP detection using 2D graphene electronics and DNA strand displacement
Highly specific SNP detection using 2D graphene electronics and DNA strand displacement
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DOI：
10.1073/pnas.1603753113
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发表时间：
2016-06-28
影响因子：
11.1
通讯作者：
Lal, Ratnesh
中科院分区：
文献类型：
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作者：
Hwang, Michael T.;Landon, Preston B.;Lal, Ratnesh
基因序列中的单核苷酸多态性（SNP）是多种人类疾病的标记。具有高特异性和灵敏度的SNP检测对于个性化医疗的有效实际实施是必不可少的。目前的DNA测序，包括SNP检测，主要使用基于酶的方法或荧光团标记的测定，这些方法耗时，需要实验室规模的设置，并且昂贵。先前报道的基于电荷的SNP检测器具有不足的特异性和准确性，限制了它们的有效性。在这里，我们展示了使用石墨烯场效应晶体管（FET）上的DNA链置换为基础的探针的高特异性，单核苷酸错配检测。通过测量石墨烯FET中链位移诱导的电阻（以及因此电流）变化和狄拉克点位移来检测单个失配。大双螺旋DNA链中的SNP检测（例如，47 nt）最小化假阳性结果。我们的电传感器为基础的SNP检测技术，没有标记，没有明显的交叉杂交文物，将允许快速，灵敏，便携式SNP检测与单核苷酸分辨率。该技术将在数字和植入式生物传感器以及高通量DNA基因分型方面具有广泛的应用，对个性化医疗具有变革性的影响。
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.