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<p>The comprehensive identification of viruses using metagenomic next-generation sequencing (mNGS) has revolutionized the infectious disease diagnosis. Accurate detection of viruses on time is crucial to effectively control the outbreak. This review has meticulously analyzed the use of mNGS to identify viruses from respiratory samples, emphasizing how sample enrichment and amplification methods affect viral detection efficiency and genome coverage. A total of 66 studies were considered to evaluate sequencing workflows and their alignment with routine molecular techniques. Among these studies, the most frequently used method to enrich viruses was centrifugation (50%), followed by enzymatic treatment (45%). Sequence-independent single-primer amplification (SISPA) and switching mechanism at the 5’ end of RNA template (SMART) was most commonly used amplification methods, which produced better genome coverage for most of the viruses. While mNGS showed better detection capabilities, they showed variable agreement with routine diagnostic methods, with sensitivity varying from 62.5% to 95%. Rhinovirus was detected mainly in lower respiratory tract infections (68%) and respiratory syncytial viruses in upper respiratory tract infections (60%). Although mNGS has the potential, its routine use is hampered by various technical issues. Overcoming these limitations through optimized sequencing protocols and greater cost-effectiveness will be pivotal in integrating mNGS into clinical applications.</p>

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Metagenomic next-generation sequencing for the detection of viruses from respiratory samples: a systematized review on current methods and future directions

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年8月5日

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  • Pushpa Kumari,
  • Sudheesh N,
  • Krishna Kumar Ballamoole,
  • Babak Afrough,
  • Anitha Jagadesh

摘要

The comprehensive identification of viruses using metagenomic next-generation sequencing (mNGS) has revolutionized the infectious disease diagnosis. Accurate detection of viruses on time is crucial to effectively control the outbreak. This review has meticulously analyzed the use of mNGS to identify viruses from respiratory samples, emphasizing how sample enrichment and amplification methods affect viral detection efficiency and genome coverage. A total of 66 studies were considered to evaluate sequencing workflows and their alignment with routine molecular techniques. Among these studies, the most frequently used method to enrich viruses was centrifugation (50%), followed by enzymatic treatment (45%). Sequence-independent single-primer amplification (SISPA) and switching mechanism at the 5’ end of RNA template (SMART) was most commonly used amplification methods, which produced better genome coverage for most of the viruses. While mNGS showed better detection capabilities, they showed variable agreement with routine diagnostic methods, with sensitivity varying from 62.5% to 95%. Rhinovirus was detected mainly in lower respiratory tract infections (68%) and respiratory syncytial viruses in upper respiratory tract infections (60%). Although mNGS has the potential, its routine use is hampered by various technical issues. Overcoming these limitations through optimized sequencing protocols and greater cost-effectiveness will be pivotal in integrating mNGS into clinical applications.