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Open-Source Miniature Fluorimeter to Monitor Real-Time Isothermal Nucleic Acid Amplification Reactions in Resource-Limited Settings
Published on: February 3, 2021
Real-time fluorescence ligase chain reaction for sensitive detection of single nucleotide polymorphism based on
Yueying Sun1, Xiaohui Lu1, Fengxia Su1
1Key Laboratory of Medicinal Chemistry and Molecular Diagnosis, Ministry of Education, College of Chemistry and Environmental Science, Hebei University, Baoding 071002, Hebei Province, PR China.
Abstract:
Most of practical methods for detection of single nucleotide polymorphism (SNP) need at least two steps: amplification (usually by PCR) and detection of SNP by using the amplification products. Ligase chain reaction (LCR) can integrate the amplification and allele discrimination in one step. However, the detection of LCR products still remains a great challenge for highly sensitive and quantitative SNP detection. Herein, a simple but robust strategy for real-time fluorescence LCR has been developed for highly sensitive and quantitative SNP detection. A pair of LCR probes are firstly labeled with a fluorophore and a quencher, respectively. When the pair of LCR probes are ligated in LCR, the fluorophore will be brought close to the quencher, and thus, the fluorescence will be specifically quenched by fluorescence resonance energy transfer (FRET). The decrease of fluorescence intensity resulted from FRET can be real-time monitored in the LCR process. With the proposed real-time fluorescence LCR assay, 10 aM DNA targets or 100 pg genomic DNA can be accurately determined and as low as 0.1% mutant DNA can be detected in the presence of a large excess of wild-type DNA, indicating the high sensitivity and specificity. The real-time measuring does not require the detection step after LCR and gives a wide dynamic range for detection of DNA targets (from 10 aM to 1 pM). As LCR has been widely used for detection of SNP, DNA methylation, mRNA and microRNA, the real-time fluorescence LCR assay shows great potential for various genetic analysis.

