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Development of multiplex nanopore sequencing method for the detection of multiple respiratory viruses in cases with severe acute respiratory infections
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  • Arqavan Zebardast ,
  • Kaveh Sadeghi,
  • Ahmad Nejati,
  • sevrin zadheidar,
  • Mohammad Hossein Najmi,
  • Adel Abedi,
  • Vahid Salimi,
  • Mehdi Shabani,
  • Jila Yavarian,
  • Nazanin Zahra Shafiei-Jandaghi,
  • Talat Mokhtari-Azad
Arqavan Zebardast
Tehran University of Medical Sciences
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Kaveh Sadeghi
Tehran University of Medical Sciences
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Ahmad Nejati
Tehran University of Medical Sciences
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sevrin zadheidar
Tehran University of Medical Sciences
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Mohammad Hossein Najmi
Faculty of Biological Sciences Department of Bioinformatics
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Adel Abedi
Shahid Beheshti University
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Vahid Salimi
Tehran University of Medical Sciences
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Mehdi Shabani
Tehran University of Medical Sciences
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Jila Yavarian
Tehran University of Medical Sciences

Corresponding Author:[email protected]

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Nazanin Zahra Shafiei-Jandaghi
Tehran University of Medical Sciences
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Talat Mokhtari-Azad
Tehran University of Medical Sciences
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Abstract

Background: Severe acute respiratory infection (SARI) remains one of the leading causes of morbidity and mortality worldwide. Multiple respiratory viral pathogens can cause this infection. Sequencing technologies hold great promise for detecting viral pathogens. This study aimed to develop and validate a method for the multiplex detection of SARI-related viruses (SARS-CoV-2, Influenza A (H1N1, H3N2), Influenza B, human respiratory syncytial virus, human adenoviruses, human enteroviruses, and human parainfluenza viruses) using a nanopore next-generation sequencing method. Methods: Following genome extraction from oropharyngeal swab samples and conventional RT-PCR assays, the libraries were barcoded and sequenced by the MinION flow cell. The sensitivity and specificity were assessed using various serial dilutions of samples and different primer pools, respectively. NGS data analysis, including adaptor trimming, assembly, mapping, and the generation of consensus sequences, was carried out using bioinformatic tools. Finally, the protocol was validated by evaluating with known positive samples. Results: During 12 hours of MinION sequencing, 711,000 reads passed the quality filters (Q-score>7). 11 out of 12 target genes were successfully identified in clinical samples, with more than 90% coverage for most viruses. All the viruses detected by Q30 value of more than 1%. The detection limit was measured for SARS-CoV-2, Influenza A (H1N1, H3N2), Influenza B, and human respiratory syncytial virus. The platform showed 99.9% specificity in detection and was validated by 20 clinical samples. Conclusion: This study developed and validated a novel multiplex detection method that made it possible to identify SARI-related respiratory viruses in a clinical laboratory setting.