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Split G-quadruplex based PfAgo sensing platform for nucleotide mutation discrimination and human genotyping.

Yan Zhang1, Bin Gong1, Yanan Lin1

  • 1School of Pharmacy, Nantong University, Nantong, Jiangsu 226001, China. sugaoxing@ntu.edu.cn.

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|January 17, 2024
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Summary

A novel DNA sensing platform uses G-quadruplexes for signal reporting, enabling accurate single nucleotide polymorphism discrimination. This method successfully genotyped the FUT2 gene in human samples.

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Area of Science:

  • Biotechnology
  • Molecular Biology
  • Genetics

Background:

  • G-quadruplex (G4) structures are unique DNA secondary structures with potential applications in biosensing.
  • Efficient and accurate discrimination of single nucleotide polymorphisms (SNPs) is crucial for genetic analysis and diagnostics.
  • The DNA-binding protein PfAgo has shown promise in nucleic acid detection but requires optimized strategies for SNP genotyping.

Purpose of the Study:

  • To develop and validate a novel sensing platform utilizing PfAgo and G4 structures for SNP detection.
  • To establish a universal nucleotide design rule for accurate SNP discrimination using the PfAgo-G4 system.
  • To demonstrate the platform's efficacy in genotyping a specific gene (FUT2) in human samples.

Main Methods:

  • A PfAgo-G4 sensing platform was designed, incorporating G4 structures as signal reporters.
  • Two mismatches were introduced in the Link strand to create a universal nucleotide design rule.
  • The optimized platform was applied to genotype the FUT2 gene using human buccal swab samples.

Main Results:

  • The PfAgo-G4 sensing platform was successfully developed, validated, and optimized.
  • A universal nucleotide design rule enabling accurate SNP discrimination was established.
  • The FUT2 gene was accurately genotyped in human buccal swab samples, demonstrating the platform's practical applicability.

Conclusions:

  • The proposed PfAgo-G4 sensing platform offers a robust method for accurate SNP genotyping.
  • The established nucleotide design rule provides a universal strategy for enhancing discrimination accuracy.
  • This technology holds potential for various genetic analysis applications, including disease diagnostics.