Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID platform
Abstract Background Antimicrobial resistant (AMR) pathogens represent urgent threats to human health, and their surveillance is of paramount importance. Metagenomic next-generation sequencing (mNGS) has revolutionized such efforts, but remains challenging due to the lack of open-access bioinformatic...
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2025-05-01
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| Online Access: | https://doi.org/10.1186/s13073-025-01480-2 |
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| author | Dan Lu Katrina L. Kalantar Abigail L. Glascock Victoria T. Chu Estella S. Guerrero Nina Bernick Xochitl Butcher Kirsty Ewing Elizabeth Fahsbender Olivia Holmes Erin Hoops Ann E. Jones Ryan Lim Suzette McCanny Lucia Reynoso Karyna Rosario Jennifer Tang Omar Valenzuela Peter M. Mourani Amy J. Pickering Amogelang R. Raphenya Brian P. Alcock Andrew G. McArthur Charles R. Langelier |
| author_facet | Dan Lu Katrina L. Kalantar Abigail L. Glascock Victoria T. Chu Estella S. Guerrero Nina Bernick Xochitl Butcher Kirsty Ewing Elizabeth Fahsbender Olivia Holmes Erin Hoops Ann E. Jones Ryan Lim Suzette McCanny Lucia Reynoso Karyna Rosario Jennifer Tang Omar Valenzuela Peter M. Mourani Amy J. Pickering Amogelang R. Raphenya Brian P. Alcock Andrew G. McArthur Charles R. Langelier |
| author_sort | Dan Lu |
| collection | DOAJ |
| description | Abstract Background Antimicrobial resistant (AMR) pathogens represent urgent threats to human health, and their surveillance is of paramount importance. Metagenomic next-generation sequencing (mNGS) has revolutionized such efforts, but remains challenging due to the lack of open-access bioinformatics tools capable of simultaneously analyzing both microbial and AMR gene sequences. Results To address this need, we developed the Chan Zuckerberg ID (CZ ID) AMR module, an open-access, cloud-based workflow designed to integrate detection of both microbes and AMR genes in mNGS and single-isolate whole-genome sequencing (WGS) data. It leverages the Comprehensive Antibiotic Resistance Database and associated Resistance Gene Identifier software, and works synergistically with the CZ ID short-read mNGS module to enable broad detection of both microbes and AMR genes from Illumina data. We highlight diverse applications of the AMR module through analysis of both publicly available and newly generated mNGS and single-isolate WGS data from four clinical cohort studies and an environmental surveillance project. Through genomic investigations of bacterial sepsis and pneumonia cases, hospital outbreaks, and wastewater surveillance data, we gain a deeper understanding of infectious agents and their resistomes, highlighting the value of integrating microbial identification and AMR profiling for both research and public health. We leverage additional functionalities of the CZ ID mNGS platform to couple resistome profiling with the assessment of phylogenetic relationships between nosocomial pathogens, and further demonstrate the potential to capture the longitudinal dynamics of pathogen and AMR genes in hospital acquired bacterial infections. Conclusions In sum, the new AMR module advances the capabilities of the open-access CZ ID microbial bioinformatics platform by integrating pathogen detection and AMR profiling from mNGS and single-isolate WGS data. Its development represents an important step toward democratizing pathogen genomic analysis and supporting collaborative efforts to combat the growing threat of AMR. |
| format | Article |
| id | doaj-art-db75da9b8fa14a97976b8626946c76bc |
| institution | Kabale University |
| issn | 1756-994X |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMC |
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| series | Genome Medicine |
| spelling | doaj-art-db75da9b8fa14a97976b8626946c76bc2025-08-20T03:52:55ZengBMCGenome Medicine1756-994X2025-05-0117111710.1186/s13073-025-01480-2Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID platformDan Lu0Katrina L. Kalantar1Abigail L. Glascock2Victoria T. Chu3Estella S. Guerrero4Nina Bernick5Xochitl Butcher6Kirsty Ewing7Elizabeth Fahsbender8Olivia Holmes9Erin Hoops10Ann E. Jones11Ryan Lim12Suzette McCanny13Lucia Reynoso14Karyna Rosario15Jennifer Tang16Omar Valenzuela17Peter M. Mourani18Amy J. Pickering19Amogelang R. Raphenya20Brian P. Alcock21Andrew G. McArthur22Charles R. Langelier23Chan Zuckerberg InitiativeChan Zuckerberg InitiativeChan Zuckerberg BiohubChan Zuckerberg BiohubNova Southeastern UniversityChan Zuckerberg InitiativeChan Zuckerberg InitiativeChan Zuckerberg InitiativeChan Zuckerberg InitiativeChan Zuckerberg InitiativeChan Zuckerberg InitiativeChan Zuckerberg InitiativeChan Zuckerberg InitiativeChan Zuckerberg InitiativeChan Zuckerberg InitiativeChan Zuckerberg InitiativeChan Zuckerberg InitiativeChan Zuckerberg InitiativeDepartment of Pediatrics, University of Arkansas for Medical SciencesChan Zuckerberg BiohubDepartment of Biochemistry & Biomedical Sciences, McMaster UniversityDepartment of Biochemistry & Biomedical Sciences, McMaster UniversityDepartment of Biochemistry & Biomedical Sciences, McMaster UniversityChan Zuckerberg BiohubAbstract Background Antimicrobial resistant (AMR) pathogens represent urgent threats to human health, and their surveillance is of paramount importance. Metagenomic next-generation sequencing (mNGS) has revolutionized such efforts, but remains challenging due to the lack of open-access bioinformatics tools capable of simultaneously analyzing both microbial and AMR gene sequences. Results To address this need, we developed the Chan Zuckerberg ID (CZ ID) AMR module, an open-access, cloud-based workflow designed to integrate detection of both microbes and AMR genes in mNGS and single-isolate whole-genome sequencing (WGS) data. It leverages the Comprehensive Antibiotic Resistance Database and associated Resistance Gene Identifier software, and works synergistically with the CZ ID short-read mNGS module to enable broad detection of both microbes and AMR genes from Illumina data. We highlight diverse applications of the AMR module through analysis of both publicly available and newly generated mNGS and single-isolate WGS data from four clinical cohort studies and an environmental surveillance project. Through genomic investigations of bacterial sepsis and pneumonia cases, hospital outbreaks, and wastewater surveillance data, we gain a deeper understanding of infectious agents and their resistomes, highlighting the value of integrating microbial identification and AMR profiling for both research and public health. We leverage additional functionalities of the CZ ID mNGS platform to couple resistome profiling with the assessment of phylogenetic relationships between nosocomial pathogens, and further demonstrate the potential to capture the longitudinal dynamics of pathogen and AMR genes in hospital acquired bacterial infections. Conclusions In sum, the new AMR module advances the capabilities of the open-access CZ ID microbial bioinformatics platform by integrating pathogen detection and AMR profiling from mNGS and single-isolate WGS data. Its development represents an important step toward democratizing pathogen genomic analysis and supporting collaborative efforts to combat the growing threat of AMR.https://doi.org/10.1186/s13073-025-01480-2Antimicrobial resistanceMetagenomicsWhole-genome sequencingChan Zuckerberg IDCZ ID |
| spellingShingle | Dan Lu Katrina L. Kalantar Abigail L. Glascock Victoria T. Chu Estella S. Guerrero Nina Bernick Xochitl Butcher Kirsty Ewing Elizabeth Fahsbender Olivia Holmes Erin Hoops Ann E. Jones Ryan Lim Suzette McCanny Lucia Reynoso Karyna Rosario Jennifer Tang Omar Valenzuela Peter M. Mourani Amy J. Pickering Amogelang R. Raphenya Brian P. Alcock Andrew G. McArthur Charles R. Langelier Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID platform Genome Medicine Antimicrobial resistance Metagenomics Whole-genome sequencing Chan Zuckerberg ID CZ ID |
| title | Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID platform |
| title_full | Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID platform |
| title_fullStr | Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID platform |
| title_full_unstemmed | Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID platform |
| title_short | Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID platform |
| title_sort | simultaneous detection of pathogens and antimicrobial resistance genes with the open source cloud based cz id platform |
| topic | Antimicrobial resistance Metagenomics Whole-genome sequencing Chan Zuckerberg ID CZ ID |
| url | https://doi.org/10.1186/s13073-025-01480-2 |
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