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<p>Critical to the success of CRISPR-based diagnostic assays is the selection of a diagnostic target highly specific to the organism of interest, a process often requiring iterative cycles of manual selection, optimisation, and redesign. Here we present PathoGD, a bioinformatic pipeline for rapid and high-throughput design of RPA primers and gRNAs for CRISPR-Cas12a-based pathogen detection. PathoGD is fully automated, leverages publicly available sequences and is scalable to large datasets, allowing rapid continuous monitoring and validation of primer/gRNA sets to ensure ongoing assay relevance. We designed primers and gRNAs for five clinically relevant bacterial pathogens, and experimentally validated a subset of the designs for detecting <i>Streptococcus pyogenes</i> and/or <i>Neisseria gonorrhoeae</i> in assays with and without pre-amplification. We demonstrated high specificity of primers and gRNAs designed, with minimal off-target signal observed for all combinations. We anticipate PathoGD will be an important resource for assay design for current and emerging pathogens. PathoGD is available on GitHub at <a href="https://github.com/sjlow23/pathogd">https://github.com/sjlow23/pathogd</a>.</p>

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PathoGD: an integrative genomics approach to primer and guide RNA design for CRISPR-based diagnostics

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年1月30日

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  • Soo Jen Low,
  • Matthew O’Neill,
  • William J. Kerry,
  • Natasha Wild,
  • Marcelina Krysiak,
  • Yi Nong,
  • Francesca Azzato,
  • Eileen Hor,
  • Lewis Williams,
  • George Taiaroa,
  • Eike Steinig,
  • Shivani Pasricha,
  • Deborah A. Williamson

摘要

Critical to the success of CRISPR-based diagnostic assays is the selection of a diagnostic target highly specific to the organism of interest, a process often requiring iterative cycles of manual selection, optimisation, and redesign. Here we present PathoGD, a bioinformatic pipeline for rapid and high-throughput design of RPA primers and gRNAs for CRISPR-Cas12a-based pathogen detection. PathoGD is fully automated, leverages publicly available sequences and is scalable to large datasets, allowing rapid continuous monitoring and validation of primer/gRNA sets to ensure ongoing assay relevance. We designed primers and gRNAs for five clinically relevant bacterial pathogens, and experimentally validated a subset of the designs for detecting Streptococcus pyogenes and/or Neisseria gonorrhoeae in assays with and without pre-amplification. We demonstrated high specificity of primers and gRNAs designed, with minimal off-target signal observed for all combinations. We anticipate PathoGD will be an important resource for assay design for current and emerging pathogens. PathoGD is available on GitHub at https://github.com/sjlow23/pathogd.