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

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

doi:10.1038/s42003-025-07591-1

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

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

^*Corresponding author for this work

School of Medicine

Research output: Contribution to journal › Article › peer-review

Abstract

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 .

Original language	English
Article number	147
Pages (from-to)	1-13
Number of pages	13
Journal	Communications Biology
Volume	8
DOIs	https://doi.org/10.1038/s42003-025-07591-1
Publication status	Published - 30 Jan 2025

Keywords

Genomics/methods
Streptococcus pyogenes/genetics
CRISPR-Cas systems
RNA, Guide, CRISPR-Cas systems/genetics
Neisseria gonorrhoeae/genetics
Humans
DNA primers/genetics
Computational biology/methods
Clustered regularly interspaced short palindromic repeats

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

abstract = "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 .",

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author = "Low, \{Soo Jen\} and Matthew O'Neill and Kerry, \{William J\} and Natasha Wild and Marcelina Krysiak and Yi Nong and Francesca Azzato and Eileen Hor and Lewis Williams and George Taiaroa and Eike Steinig and Shivani Pasricha and Williamson, \{Deborah A\}",

note = "Funding: This study was funded by the Victorian Medical Research Accelerator Fund (GA-F3791196–5514) and the Australian Government Department of Health (PO4932). D.A.W. is supported by an NHMRC Investigator Grant (APP1174555). This work was also supported by an Australian Research Council Industrial Transformation Research Hub Grant (IH190100021). ",

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doi = "10.1038/s42003-025-07591-1",

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T2 - an integrative genomics approach to primer and guide RNA design for CRISPR-based diagnostics

AU - Low, Soo Jen

AU - O'Neill, Matthew

AU - Kerry, William J

AU - Wild, Natasha

AU - Krysiak, Marcelina

AU - Nong, Yi

AU - Azzato, Francesca

AU - Hor, Eileen

AU - Williams, Lewis

AU - Taiaroa, George

AU - Steinig, Eike

AU - Pasricha, Shivani

AU - Williamson, Deborah A

N1 - Funding: This study was funded by the Victorian Medical Research Accelerator Fund (GA-F3791196–5514) and the Australian Government Department of Health (PO4932). D.A.W. is supported by an NHMRC Investigator Grant (APP1174555). This work was also supported by an Australian Research Council Industrial Transformation Research Hub Grant (IH190100021).

PY - 2025/1/30

Y1 - 2025/1/30

N2 - 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 .

AB - 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 .

KW - Genomics/methods

KW - Streptococcus pyogenes/genetics

KW - CRISPR-Cas systems

KW - RNA, Guide, CRISPR-Cas systems/genetics

KW - Neisseria gonorrhoeae/genetics

KW - Humans

KW - DNA primers/genetics

KW - Computational biology/methods

KW - Clustered regularly interspaced short palindromic repeats

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DO - 10.1038/s42003-025-07591-1

M3 - Article

C2 - 39885339

SN - 2399-3642

VL - 8

SP - 1

EP - 13

JO - Communications Biology

JF - Communications Biology

M1 - 147

ER -

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

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Keywords

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