Loop-recognition dual-hairpin competitive probes enabling a dual-ratiometric electrochemical platform for specific SNP discrimination and logic gate construction
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题目 |
Loop-recognition dual-hairpin competitive probes enabling a dual-ratiometric electrochemical platform for specific SNP discrimination and logic gate construction |
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作者 |
Zhang W, Tang X, Chen Y, Guo R, Wang M, Yang X, Deng W, Zhang Y, Feng X, Ye J*, Zhang D* |
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发表年度 |
2026 |
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刊物名称 |
Biosens Bioelectron |
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摘要 |
Accurate discrimination of single nucleotide polymorphisms (SNPs) remains a fundamental challenge in nucleic acid biosensing due to the minimal thermodynamic differences between perfectly matched and single-base mismatched sequences. This intrinsic limitation often compromises recognition fidelity at the initial hybridization stage, regardless of subsequent signal amplification strategies. Herein, we propose a electrochemical biosensing strategy based on a competitive loop-recognition dual-hairpin probe for highly specific SNP identification. This paradigm utilizes a wild-type (WT) sequestering probe to form an inhibiting complex (HW/WT) that actively suppresses background interference, while a target-specific probe binds with the SNP to form a triggering complex (HS/SNP) to initiate signal transduction. By positioning the recognition domains within the loop regions, the formation of the triggering complex is subjected to pronounced structural confinement, thereby significantly amplifying the thermodynamic penalty associated with single-base mismatches. On the basis of this enhanced competitive recognition fidelity, a dual-ratiometric electrochemical biosensor with high robustness and specificity was constructed for reliable SNP detection. Furthermore, benefiting from the exceptional single-base resolution of the inhibiting-triggering mechanism, SNP and WT sequences were directly utilized as molecular logic inputs to implement Exclusive OR (XOR), AND, and OR logic operations. This work demonstrates how structural regulation and competitive molecular sorting, prior to signal amplification, can convert subtle genetic variations into reliable analytical and computational signals, providing a versatile biointerface for precise nucleic acid analysis and intelligent biocomputing. |
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