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Hybrid Capture-Based Sequencing Enables Highly Sensitive Zoonotic Virus Detection Within the One Health Framework.

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A new hybrid capture sequencing method significantly enhances viral detection sensitivity, lowering the limit of detection to 10 copies. This advancement improves pathogen surveillance and genomic characterization for emerging infectious diseases.

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capture probesone healthviral diagnosticsviral metagenomics

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Area of Science:

  • Molecular Biology
  • Genomics
  • Infectious Disease Research

Background:

  • Hybrid capture sequencing improves detection sensitivity for genetic targets.
  • Pathogen detection is crucial for One Health initiatives, monitoring both human and animal diseases.
  • Metagenomic next-generation sequencing (mNGS) has limitations in sensitivity and comprehensive characterization of pathogens in complex samples.

Purpose of the Study:

  • To develop and validate a hybrid capture-based sequencing method for sensitive and comprehensive viral detection in human and animal samples.
  • To improve upon the limitations of standard mNGS for pathogen surveillance.
  • To bridge the gap between diagnostic detection and genomic surveillance for emerging infectious diseases.

Main Methods:

  • Designed an optimized probe set (149,990 probes) targeting 663 human and animal viruses.
  • Assessed performance using viral reference materials spiked into human nucleic acids.
  • Validated the method with infectious samples from animals (bovine rectal swabs) and humans (SARS-CoV-2 positive throat swabs).

Main Results:

  • Achieved 143- to 1126-fold read enrichment compared to standard mNGS.
  • Lowered the limit of detection (LoD) from 10^3-10^4 copies to as few as 10 copies.
  • Demonstrated heightened sensitivity, increased viral genome coverage (>99%), and comprehensive characterization in real-world samples.

Conclusions:

  • The developed hybrid capture sequencing method significantly enhances viral detection sensitivity and genome coverage.
  • This method effectively addresses limitations of mNGS for pathogen surveillance in complex samples.
  • The approach is impactful for early detection and genomic characterization of emerging pathogens like SARS-CoV-2.