Published June 2021 | Version v1
Journal article

A comprehensive system for detecting rare single nucleotide variants based on competitive DNA probe and duplex-specific nuclease

  • 1. Key Laboratory of Clinical Laboratory Diagnostics (Chinese Ministry of Education), College of Laboratory Medicine, Chongqing Medical University, Chongqing, 400016 (China)
  • 2. Clinical Laboratory of Traditional Chinese Medicine Hospital Affiliated to Southwest Medical University, Luzhou, 646000 (China)
  • 3. Clinical Laboratory of Chongqing University Cancer Hospital, Chongqing, 400016 (China)

Description

Highlights: • Combination of competitive DNA probe system and duplex-specific nuclease enable two-layer identification of SNVs. • A theoretical model was established to optimize the performance of CAD System. • This non-equivalent tradeoff between sensitivity and specificity provides a new concept for nucleic acid analysis. • Accurate analysis of low variant allele frequency in human genomic DNA. Single nucleotide variants (SNVs) have emerged as increasingly important biomarkers, particularly in the diagnosis and prognosis of cancers. However, most SNVs are rarely detected in blood samples from cancer patients as they are surrounded by abundant concomitant wild-type nucleic acids. Herein, we design a system that features a combination of competitive DNA probe system (CDPS) and duplex-specific nuclease (DSN) that we referred to as CAD. A theoretical model was established for the CAD system based on reaction networks. Guided by the theoretical model, we found that a minor loss in sensitivity significantly improved the specificity of the system, thus creating a theoretical discrimination factor (DF) > 100 for most conditions. This non-equivalent tradeoff between sensitivity and specificity provides a new concept for the analysis of rare DNA-sequence variants. As a demonstration of practicality, we applied as-proposed CAD system to identify low variant allele frequency (VAF) in a synthetic template (0.1% VAF) and human genomic DNA (1% VAF). This work promises complete guidance for the design of enzyme-based nucleic acid analysis.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.aca.2021.338545

Additional details

Identifiers

DOI
10.1016/j.aca.2021.338545;
PII
S0003267021003718;

Publishing Information

Journal Title
Analytica Chimica Acta
Journal Volume
1166
Journal Page Range
vp.
ISSN
0003-2670
CODEN
ACACAM

INIS

Optional Information

Copyright
Copyright (c) 2021 Elsevier B.V. All rights reserved.