Related Experiment Video
Updated: Jul 25, 2026

Wild-type Blocking PCR Combined with Direct Sequencing as a Highly Sensitive Method for Detection of Low-Frequency Somatic Mutations
Published on: March 29, 2017
Ultra-specific discrimination of single-nucleotide mutations using sequestration-assisted molecular beacons
Shichao Hu1, Wei Tang2, Yan Zhao1
1Beijing National Laboratory for Molecular Sciences , Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education , College of Chemistry and Molecular Engineering , Peking University , Beijing 100871 , China .
A new sequestration-assisted molecular beacon (MB) strategy enhances single-nucleotide mutation (SNM) discrimination. This method improves accuracy for clinical diagnosis by reducing cross-reactivity with unintended sequences.
Area of Science:
- Biochemistry
- Molecular Biology
- Genetics
Background:
- Distinguishing low-abundance single-nucleotide mutations (SNMs) is crucial for clinical diagnosis.
- Current methods often lack specificity due to probe cross-reactivity with similar sequences.
Purpose of the Study:
- To develop a highly specific method for SNM discrimination using a novel molecular beacon (MB) strategy.
- To improve the accuracy and reliability of SNM detection in clinical settings.
Main Methods:
- Proposed a sequestration-assisted molecular beacon (MB) system.
- Utilized hairpin sequestering agents (SEQs) to bind unintended sequences.
- Combined MB-SEQ system with PCR amplification for mutation detection.
Main Results:
- Achieved high specificity with discrimination factors ranging from 12 to 1144 (median 117) against 20 model SNMs.
- Demonstrated robust performance across various conditions.
- Successfully detected low-abundance KRAS G12D and G12V mutations (as low as 0.5%) using the combined method.
Conclusions:
- The sequestration-assisted MB strategy significantly enhances SNM discrimination specificity.
- This method offers a rapid, robust, and sensitive approach for clinical mutation detection.
- The strategy expands design principles for hybridization-based SNM discrimination and shows clinical potential.

