Comprehensive pathogen identification and antimicrobial resistance prediction from positive blood cultures using nanopore sequencing technology
Abstract Background Blood cultures are essential for diagnosing bloodstream infections, but current phenotypic tests for antimicrobial resistance (AMR) provide limited information. Oxford Nanopore Technologies introduces nanopore sequencing with adaptive sampling, capable of real-time host genome de...
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BMC
2024-12-01
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| Series: | Genome Medicine |
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| Online Access: | https://doi.org/10.1186/s13073-024-01416-2 |
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| author | Po-Yu Liu Han-Chieh Wu Ying-Lan Li Hung-Wei Cheng Ci-Hong Liou Feng-Jui Chen Yu-Chieh Liao |
| author_facet | Po-Yu Liu Han-Chieh Wu Ying-Lan Li Hung-Wei Cheng Ci-Hong Liou Feng-Jui Chen Yu-Chieh Liao |
| author_sort | Po-Yu Liu |
| collection | DOAJ |
| description | Abstract Background Blood cultures are essential for diagnosing bloodstream infections, but current phenotypic tests for antimicrobial resistance (AMR) provide limited information. Oxford Nanopore Technologies introduces nanopore sequencing with adaptive sampling, capable of real-time host genome depletion, yet its application directly from blood cultures remains unexplored. This study aimed to identify pathogens and predict AMR using nanopore sequencing. Methods In this cross-sectional genomic study, 458 positive blood cultures from bloodstream infection patients in central Taiwan were analyzed. Parallel experiments involved routine microbiologic tests and nanopore sequencing with a 15-h run. A bioinformatic pipeline was proposed to analyze the real-time sequencing reads. Subsequently, a comparative analysis was performed to evaluate the performance of species identification and AMR prediction. Results The pipeline identified 76 species, with 88 Escherichia coli, 74 Klebsiella pneumoniae, 43 Staphylococcus aureus, and 9 Candida samples. Novel species were also discovered. Notably, precise species identification was achieved not only for monomicrobial infections but also for polymicrobial infections, which was detected in 23 samples and further confirmed by full-length 16S rRNA amplicon sequencing. Using a modified ResFinder database, AMR predictions showed a categorical agreement rate exceeding 90% (3799/4195) for monomicrobial infections, with minimal very major errors observed for K. pneumoniae (2/186, 1.1%) and S. aureus (1/90, 1.1%). Conclusions Nanopore sequencing with adaptive sampling can directly analyze positive blood cultures, facilitating pathogen detection, AMR prediction, and outbreak investigation. Integrating nanopore sequencing into clinical practices signifies a revolutionary advancement in managing bloodstream infections, offering an effective antimicrobial stewardship strategy, and improving patient outcomes. |
| format | Article |
| id | doaj-art-99d28f1ae86440d5bf8a29f40e2c58bf |
| institution | Kabale University |
| issn | 1756-994X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Medicine |
| spelling | doaj-art-99d28f1ae86440d5bf8a29f40e2c58bf2024-12-08T12:38:55ZengBMCGenome Medicine1756-994X2024-12-0116111110.1186/s13073-024-01416-2Comprehensive pathogen identification and antimicrobial resistance prediction from positive blood cultures using nanopore sequencing technologyPo-Yu Liu0Han-Chieh Wu1Ying-Lan Li2Hung-Wei Cheng3Ci-Hong Liou4Feng-Jui Chen5Yu-Chieh Liao6Division of Infectious Diseases, Department of Internal Medicine, Taichung Veterans General HospitalNational Institute of Infectious Diseases and Vaccinology, National Health Research Institutes, Miaoli CountyDivision of Infectious Diseases, Department of Internal Medicine, Taichung Veterans General HospitalInstitute of Population of Health Sciences, National Health Research Institutes, Miaoli CountyNational Institute of Infectious Diseases and Vaccinology, National Health Research Institutes, Miaoli CountyNational Institute of Infectious Diseases and Vaccinology, National Health Research Institutes, Miaoli CountyInstitute of Population of Health Sciences, National Health Research Institutes, Miaoli CountyAbstract Background Blood cultures are essential for diagnosing bloodstream infections, but current phenotypic tests for antimicrobial resistance (AMR) provide limited information. Oxford Nanopore Technologies introduces nanopore sequencing with adaptive sampling, capable of real-time host genome depletion, yet its application directly from blood cultures remains unexplored. This study aimed to identify pathogens and predict AMR using nanopore sequencing. Methods In this cross-sectional genomic study, 458 positive blood cultures from bloodstream infection patients in central Taiwan were analyzed. Parallel experiments involved routine microbiologic tests and nanopore sequencing with a 15-h run. A bioinformatic pipeline was proposed to analyze the real-time sequencing reads. Subsequently, a comparative analysis was performed to evaluate the performance of species identification and AMR prediction. Results The pipeline identified 76 species, with 88 Escherichia coli, 74 Klebsiella pneumoniae, 43 Staphylococcus aureus, and 9 Candida samples. Novel species were also discovered. Notably, precise species identification was achieved not only for monomicrobial infections but also for polymicrobial infections, which was detected in 23 samples and further confirmed by full-length 16S rRNA amplicon sequencing. Using a modified ResFinder database, AMR predictions showed a categorical agreement rate exceeding 90% (3799/4195) for monomicrobial infections, with minimal very major errors observed for K. pneumoniae (2/186, 1.1%) and S. aureus (1/90, 1.1%). Conclusions Nanopore sequencing with adaptive sampling can directly analyze positive blood cultures, facilitating pathogen detection, AMR prediction, and outbreak investigation. Integrating nanopore sequencing into clinical practices signifies a revolutionary advancement in managing bloodstream infections, offering an effective antimicrobial stewardship strategy, and improving patient outcomes.https://doi.org/10.1186/s13073-024-01416-2Pathogen identificationAntimicrobial resistance predictionPositive blood culturesReal-timeNanopore sequencingAdaptive sampling |
| spellingShingle | Po-Yu Liu Han-Chieh Wu Ying-Lan Li Hung-Wei Cheng Ci-Hong Liou Feng-Jui Chen Yu-Chieh Liao Comprehensive pathogen identification and antimicrobial resistance prediction from positive blood cultures using nanopore sequencing technology Genome Medicine Pathogen identification Antimicrobial resistance prediction Positive blood cultures Real-time Nanopore sequencing Adaptive sampling |
| title | Comprehensive pathogen identification and antimicrobial resistance prediction from positive blood cultures using nanopore sequencing technology |
| title_full | Comprehensive pathogen identification and antimicrobial resistance prediction from positive blood cultures using nanopore sequencing technology |
| title_fullStr | Comprehensive pathogen identification and antimicrobial resistance prediction from positive blood cultures using nanopore sequencing technology |
| title_full_unstemmed | Comprehensive pathogen identification and antimicrobial resistance prediction from positive blood cultures using nanopore sequencing technology |
| title_short | Comprehensive pathogen identification and antimicrobial resistance prediction from positive blood cultures using nanopore sequencing technology |
| title_sort | comprehensive pathogen identification and antimicrobial resistance prediction from positive blood cultures using nanopore sequencing technology |
| topic | Pathogen identification Antimicrobial resistance prediction Positive blood cultures Real-time Nanopore sequencing Adaptive sampling |
| url | https://doi.org/10.1186/s13073-024-01416-2 |
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