4.8 Article

Ultraspecific and Amplification-Free Quantification of Mutant DNA by Single-Molecule Kinetic Fingerprinting

期刊

JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
卷 140, 期 37, 页码 11755-11762

出版社

AMER CHEMICAL SOC
DOI: 10.1021/jacs.8b06685

关键词

-

资金

  1. Michigan Economic Development Corporation MTRAC for Life Sciences
  2. University of Michigan MCubed 2.0 program
  3. James Selleck Bower Permanently Endowed Innovative Promise Funds for Cancer Research of the University of Michigan Rogel Cancer Center
  4. Fast Forward GI Innovation Fund
  5. NIH [R21 CA204560]
  6. NSF MRI-R2-ID [DBI-0959823]
  7. NATIONAL CANCER INSTITUTE [R21CA204560] Funding Source: NIH RePORTER

向作者/读者索取更多资源

Conventional techniques for detecting rare DNA sequences require many cycles of PCR amplification for high sensitivity and specificity, potentially introducing significant biases and errors. While amplification-free methods exist, they rarely achieve the ability to detect single molecules, and their ability to discriminate between single-nucleotide variants is often dictated by the specificity limits of hybridization thermodynamics. Here we show that a direct detection approach using single-molecule kinetic fingerprinting can surpass the thermodynamic discrimination limit by 3 orders of magnitude, with a dynamic range of up to S orders of magnitude with optional super-resolution analysis. This approach detects mutations as subtle as the drug-resistance conferring cancer mutation EGFR T790M (a single C -> T substitution) with an estimated specificity of 99.99999%, surpassing even the leading PCR-based methods and enabling detection of 1 mutant molecule in a background of at least 1 million wild type molecules. This level of specificity revealed rare, heat-induced cytosine deamination events that introduce false positives in PCR-based detection, but which can be overcome in our approach through milder thermal denaturation and enzymatic removal of damaged nucleobases.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据