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      Metagenomic analysis of viral diversity in respiratory samples from patients with respiratory tract infections in Kuwait

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      https://www.riss.kr/link?id=O119686464

      • 저자
      • 발행기관
      • 학술지명
      • 권호사항
      • 발행연도

        2018년

      • 작성언어

        -

      • Print ISSN

        0146-6615

      • Online ISSN

        1096-9071

      • 등재정보

        SCI;SCIE;SCOPUS

      • 자료형태

        학술저널

      • 수록면

        412-420   [※수록면이 p5 이하이면, Review, Columns, Editor's Note, Abstract 등일 경우가 있습니다.]

      • 소장기관
      • 구독기관
        • 전북대학교 중앙도서관  
        • 성균관대학교 중앙학술정보관  
        • 부산대학교 중앙도서관  
        • 전남대학교 중앙도서관  
        • 제주대학교 중앙도서관  
        • 중앙대학교 서울캠퍼스 중앙도서관  
        • 인천대학교 학산도서관  
        • 숙명여자대학교 중앙도서관  
        • 서강대학교 로욜라중앙도서관  
        • 계명대학교 동산도서관  
        • 충남대학교 중앙도서관  
        • 한양대학교 백남학술정보관  
        • 이화여자대학교 중앙도서관  
        • 고려대학교 도서관  
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      다국어 초록 (Multilingual Abstract)

      A metagenomic approach based on target independent next‐generation sequencing has become a known method for the detection of both known and novel viruses in clinical samples. This study aimed to use the metagenomic sequencing approach to characteriz...

      A metagenomic approach based on target independent next‐generation sequencing has become a known method for the detection of both known and novel viruses in clinical samples. This study aimed to use the metagenomic sequencing approach to characterize the viral diversity in respiratory samples from patients with respiratory tract infections. We have investigated 86 respiratory samples received from various hospitals in Kuwait between 2015 and 2016 for the diagnosis of respiratory tract infections. A metagenomic approach using the next‐generation sequencer to characterize viruses was used. According to the metagenomic analysis, an average of 145, 019 reads were identified, and 2% of these reads were of viral origin. Also, metagenomic analysis of the viral sequences revealed many known respiratory viruses, which were detected in 30.2% of the clinical samples. Also, sequences of non‐respiratory viruses were detected in 14% of the clinical samples, while sequences of non‐human viruses were detected in 55.8% of the clinical samples. The average genome coverage of the viruses was 12% with the highest genome coverage of 99.2% for respiratory syncytial virus, and the lowest was 1% for torque teno midi virus 2. Our results showed 47.7% agreement between multiplex Real‐Time PCR and metagenomics sequencing in the detection of respiratory viruses in the clinical samples. Though there are some difficulties in using this method to clinical samples such as specimen quality, these observations are indicative of the promising utility of the metagenomic sequencing approach for the identification of respiratory viruses in patients with respiratory tract infections.

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