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Amplification Bias-Free Sequence-Generic Exponential Amplification Reaction.

Xinrong Yan1, Qingyuan Wang2, Peiru Yang1

  • 1State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210093, P. R. China.

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This study introduces sequence-generic exponential amplification reaction (SG-EXPAR), a novel method for nucleic acid detection. SG-EXPAR overcomes amplification bias, achieving highly sensitive and consistent results for diverse targets.

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Area of Science:

  • Molecular Biology
  • Biotechnology
  • Nucleic Acid Amplification

Background:

  • Isothermal exponential amplification reaction (EXPAR) offers rapid nucleic acid detection but suffers from sequence-dependent amplification bias.
  • This bias, caused by template secondary structures at 55 °C, leads to variable limits of detection (LOD) from aM to nM.
  • Existing methods lack consistent performance across different target sequences.

Purpose of the Study:

  • To develop a sequence-generic exponential amplification reaction (SG-EXPAR) that eliminates amplification bias.
  • To achieve consistent and highly sensitive nucleic acid detection across various targets.
  • To enable reliable point-of-care nucleic acid assays.

Main Methods:

  • Employed a thermophilic nicking enzyme for SG-EXPAR to function at higher temperatures (60-70 °C), eliminating template secondary structures.
  • Optimized locked nucleic acids and template design to enhance trigger/template binding probability.
  • Developed an automated design platform for creating optimal SG-EXPAR templates for any sequence.

Main Results:

  • Achieved sequence-generic amplification with generally sub-fM LODs, eliminating sequence-dependent bias.
  • Demonstrated robust performance in quantifying microRNA, SARS-CoV-2, monkeypox virus, and HPV B19 at the 1 fM level without sequence screening.
  • Validated the method's efficiency and broad applicability across diverse nucleic acid targets.

Conclusions:

  • SG-EXPAR overcomes the limitations of traditional EXPAR by eliminating sequence-dependent amplification bias.
  • The developed method offers highly sensitive and consistent detection of various nucleic acids, including pathogens.
  • SG-EXPAR significantly expands EXPAR applications and supports the development of reliable point-of-care diagnostic tools.