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Updated: Jun 4, 2026
High-throughput Detection of Respiratory Pathogens in Animal Specimens by Nanoscale PCR
Published on: November 28, 2016
A sensitive assay for virus discovery in respiratory clinical samples
Michel de Vries1, Martin Deijs, Marta Canuti
1Laboratory of Experimental Virology, Department of Medical Microbiology, Center for Infection and Immunity Amsterdam, Academic Medical Center of the University of Amsterdam, Amsterdam, The Netherlands.
Optimized Virus Discovery by Amplified Fragment Length Polymorphism (VIDISCA) method significantly reduces ribosomal RNA (rRNA) interference. This enhanced technique, coupled with high-throughput sequencing, improves sensitivity for identifying unknown respiratory viruses in patient samples.
Area of Science:
- Virology
- Molecular Biology
- Infectious Diseases
Background:
- Undiagnosed respiratory infections in children suggest the presence of unknown pathogens.
- Current diagnostic methods are insufficient for detecting novel viruses.
- Ribosomal RNA (rRNA) in nasopharyngeal swabs hinders virus discovery methods like VIDISCA.
Purpose of the Study:
- To optimize the Virus Discovery by Amplified Fragment Length Polymorphism (VIDISCA) method for direct pathogen detection in patient samples.
- To reduce the interference of ribosomal RNA (rRNA) during the virus discovery process.
- To enhance the sensitivity of VIDISCA for identifying unknown respiratory viruses.
Main Methods:
- Modified reverse transcription enzymes and specific oligonucleotides to minimize rRNA amplification during VIDISCA.
- Utilized 3'-dideoxy-C6-modified oligonucleotides to further reduce rRNA cDNA synthesis.
- Integrated high-throughput sequencing (VIDISCA-454) for improved sensitivity and data analysis.
Main Results:
- Achieved over 90% reduction in rRNA amplification through optimized VIDISCA protocols.
- Successfully identified known respiratory viruses in 11 out of 18 nasopharyngeal swab samples using VIDISCA-454.
- Detected viral loads ranging from 1.4 E3 to 7.7 E6 viral genome copies/ml, with a median of 7.2 E5 copies/ml.
Conclusions:
- Optimized VIDISCA combined with high-throughput sequencing dramatically enhances sensitivity for virus discovery.
- This improved method enables direct detection and identification of viruses, including potentially unknown pathogens, in clinical specimens.
- The study demonstrates a powerful approach for advancing respiratory virus diagnostics and pathogen discovery.
