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Detection of respiratory viruses directly from clinical samples using next-generation sequencing: A literature review of recent advances and potential for routine clinical use.
Wang, Xinye; Stelzer-Braid, Sacha; Scotch, Matthew; Rawlinson, William D.
  • Wang X; Virology Research Laboratory, Serology and Virology Division (SAViD), NSW Health Pathology, Prince of Wales Hospital, University of New South Wales, Sydney, New South Wales, Australia.
  • Stelzer-Braid S; School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia.
  • Scotch M; Virology Research Laboratory, Serology and Virology Division (SAViD), NSW Health Pathology, Prince of Wales Hospital, University of New South Wales, Sydney, New South Wales, Australia.
  • Rawlinson WD; School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia.
Rev Med Virol ; 32(5): e2375, 2022 09.
Article in English | MEDLINE | ID: covidwho-1913892
ABSTRACT
Acute respiratory infection is the third most frequent cause of mortality worldwide, causing over 4.25 million deaths annually. Although most diagnosed acute respiratory infections are thought to be of viral origin, the aetiology often remains unclear. The advent of next-generation sequencing (NGS) has revolutionised the field of virus discovery and identification, particularly in the detection of unknown respiratory viruses. We systematically reviewed the application of NGS technologies for detecting respiratory viruses from clinical samples and outline potential barriers to the routine clinical introduction of NGS. The five databases searched for studies published in English from 01 January 2010 to 01 February 2021, which led to the inclusion of 52 studies. A total of 14 different models of NGS platforms were summarised from included studies. Among these models, second-generation sequencing platforms (e.g., Illumina sequencers) were used in the majority of studies (41/52, 79%). Moreover, NGS platforms have proven successful in detecting a variety of respiratory viruses, including influenza A/B viruses (9/52, 17%), SARS-CoV-2 (21/52, 40%), parainfluenza virus (3/52, 6%), respiratory syncytial virus (1/52, 2%), human metapneumovirus (2/52, 4%), or a viral panel including other respiratory viruses (16/52, 31%). The review of NGS technologies used in previous studies indicates the advantages of NGS technologies in novel virus detection, virus typing, mutation identification, and infection cluster assessment. Although there remain some technical and ethical challenges associated with NGS use in clinical laboratories, NGS is a promising future tool to improve understanding of respiratory viruses and provide a more accurate diagnosis with simultaneous virus characterisation.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Influenza A virus / Respiratory Tract Infections / COVID-19 Type of study: Diagnostic study / Etiology study / Prognostic study / Reviews Limits: Humans Language: English Journal: Rev Med Virol Journal subject: Virology Year: 2022 Document Type: Article Affiliation country: Rmv.2375

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Influenza A virus / Respiratory Tract Infections / COVID-19 Type of study: Diagnostic study / Etiology study / Prognostic study / Reviews Limits: Humans Language: English Journal: Rev Med Virol Journal subject: Virology Year: 2022 Document Type: Article Affiliation country: Rmv.2375