Selective Enrichment of Low-Abundance DNA Variants Based on Programmable Peptide Nucleic Acid Probes

Abstract

Single-nucleotide variants (SNVs) are crucial in disease development, but their accurate detection is challenging due to their low abundance and interference from wild-type targets. Although nucleic acid analogs like peptide nucleic acids (PNAs) have been used for SNV detection, they often lack programmable sensitivity and specificity due to poorly calculated thermodynamics and kinetics. Here, we present a computational method for calculating the stacking energy of PNA and DNA hybrids, leveraging nearest neighbor parameters. Validation against experimental data from 16 sequences under varied hybridization conditions yielded good agreement using Bland-Altman analysis, with all data points falling within the confidence interval. Our findings indicate that PNA-DNA hybridization is thermodynamically more stable and exhibits kinetics 140-fold faster than DNA-DNA hybridization for identical sequences. Utilizing this computational framework, we designed PNA toehold probes, which were screened via simulations and experiments. This combined approach facilitated the identification of highly sensitive and specific PNA toehold probes for single point mutation detection via strand displacement reaction. Our results demonstrate the successful application of PNA toehold probes for detecting point mutations with high sensitivity and specificity, achieving a selective amplification of approximately 200-fold for variants with a variant allele frequency (VAF) of 0.5% using quantitative polymerase chain reaction.

Keywords

Peptide nucleic acids / Thermodynamics / Strand displacement reaction / SNVs detection / Biosensors / Nucleic Acids / Kinetics

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2024 SIOC, CAS, Shanghai, & WILEY-VCH GmbH