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<p>We have developed a tailored next-generation sequencing (tNGS) panel, employing our innovative UMPlex™ primer design workflow, to enhance pathogen identification in clinical diagnostics. Through iterative experimentation and rigorous validation, we refined the primer design by excluding those with insufficient specificity or efficiency. To mitigate amplification challenges arising from pathogenic mutations, we implemented a strategy of using a minimum of two primer pairs per pathogen, ensuring redundancy and robust detection. Validation using clinical samples showcased high specificity and efficacy, with 11 cultured pathogens isolated exclusively. In a study involving 107 positive respiratory samples, tNGS outperformed the TaqMan Array, detecting a higher number of pathogens in patients with influenza-like symptoms of unknown etiology. Additionally, tNGS yielded higher read counts for potentially pathogenic microorganisms and produced results consistent with metagenomic NGS, despite generating a reduced data volume. This approach not only improves detection rates but also offers a flexible tool for both clinical diagnostics and surveillance, particularly in the context of influenza-like illnesses.</p>

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UMPlex™: a targeted next-generation sequencing primer design workflow

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月5日

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  • Dachuan Lin,
  • Xiaomin Zhang,
  • Dan Wang,
  • Tongyingzi Liu,
  • Tong Li,
  • Yingluan Zhang,
  • Lihua Li,
  • Yi Huang,
  • Yongchao Guo,
  • Renli Zhang,
  • Xinchun Chen,
  • Tiejian Feng

摘要

We have developed a tailored next-generation sequencing (tNGS) panel, employing our innovative UMPlex™ primer design workflow, to enhance pathogen identification in clinical diagnostics. Through iterative experimentation and rigorous validation, we refined the primer design by excluding those with insufficient specificity or efficiency. To mitigate amplification challenges arising from pathogenic mutations, we implemented a strategy of using a minimum of two primer pairs per pathogen, ensuring redundancy and robust detection. Validation using clinical samples showcased high specificity and efficacy, with 11 cultured pathogens isolated exclusively. In a study involving 107 positive respiratory samples, tNGS outperformed the TaqMan Array, detecting a higher number of pathogens in patients with influenza-like symptoms of unknown etiology. Additionally, tNGS yielded higher read counts for potentially pathogenic microorganisms and produced results consistent with metagenomic NGS, despite generating a reduced data volume. This approach not only improves detection rates but also offers a flexible tool for both clinical diagnostics and surveillance, particularly in the context of influenza-like illnesses.