NanoCore: core-genome-based bacterial genomic surveillance and outbreak detection in healthcare facilities from Nanopore and Illumina data
ABSTRACT Genomic surveillance enables the early detection of pathogen transmission in healthcare facilities and contributes to the reduction of substantial patient harm. Fast turnaround times, flexible multiplexing, and low capital requirements make Nanopore sequencing well suited for genomic survei...
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American Society for Microbiology
2024-11-01
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| Series: | mSystems |
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| Online Access: | https://journals.asm.org/doi/10.1128/msystems.01080-24 |
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| author | Sebastian A. Fuchs Lisanna Hülse Teresa Tamayo Susanne Kolbe-Busch Klaus Pfeffer Alexander T. Dilthey |
| author_facet | Sebastian A. Fuchs Lisanna Hülse Teresa Tamayo Susanne Kolbe-Busch Klaus Pfeffer Alexander T. Dilthey |
| author_sort | Sebastian A. Fuchs |
| collection | DOAJ |
| description | ABSTRACT Genomic surveillance enables the early detection of pathogen transmission in healthcare facilities and contributes to the reduction of substantial patient harm. Fast turnaround times, flexible multiplexing, and low capital requirements make Nanopore sequencing well suited for genomic surveillance purposes; the analysis of Nanopore data, however, can be challenging. We present NanoCore, a user-friendly method for Nanopore-based genomic surveillance in healthcare facilities, enabling the calculation and visualization of cgMLST-like (core-genome multilocus sequence typing) sample distances directly from unassembled Nanopore reads. NanoCore implements a mapping, variant calling, and multilevel filtering strategy and also supports the analysis of Illumina data. We validated NanoCore on two 24-isolate data sets of methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus faecium (VRE). In the Nanopore-only mode, NanoCore-based pairwise distances between closely related isolates were near-identical to Illumina-based SeqSphere+ distances, a gold standard commercial method (average differences of 0.75 and 0.81 alleles for MRSA and VRE; sd = 0.98 and 1.00), and gave an identical clustering into closely related and non-closely related isolates. In the “hybrid” mode, in which only Nanopore data are used for some isolates and only Illumina data for others, increased average pairwise isolate distance differences were observed (average differences of 3.44 and 1.95 for MRSA and VRE, respectively; sd = 2.76 and 1.34), while clustering results remained identical. NanoCore is computationally efficient (<15 hours of wall time for the analysis of a 24-isolate data set on a workstation), available as free software, and supports installation via conda. In conclusion, NanoCore enables the effective use of the Nanopore technology for bacterial pathogen surveillance in healthcare facilities.IMPORTANCEGenomic surveillance involves sequencing the genomes and measuring the relatedness of bacteria from different patients or locations in the same healthcare facility, enabling an improved understanding of pathogen transmission pathways and the detection of “silent” outbreaks that would otherwise go undetected. It has become an indispensable tool for the detection and prevention of healthcare-associated infections and is routinely applied by many healthcare institutions. The earlier an outbreak or transmission chain is detected, the better; in this context, the Oxford Nanopore sequencing technology has important potential advantages over traditionally used short-read sequencing technologies, because it supports “real-time” data generation and the cost-effective “on demand” sequencing of small numbers of bacterial isolates. The analysis of Nanopore sequencing data, however, can be challenging. We present NanoCore, a user-friendly software for genomic surveillance that works directly based on Nanopore sequencing reads in FASTQ format, and demonstrate that its accuracy is equivalent to traditional gold standard short read-based analyses. |
| format | Article |
| id | doaj-art-4f958f28a1de4ecca2b94725eae96dbd |
| institution | DOAJ |
| issn | 2379-5077 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | American Society for Microbiology |
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| series | mSystems |
| spelling | doaj-art-4f958f28a1de4ecca2b94725eae96dbd2025-08-20T02:39:33ZengAmerican Society for MicrobiologymSystems2379-50772024-11-0191110.1128/msystems.01080-24NanoCore: core-genome-based bacterial genomic surveillance and outbreak detection in healthcare facilities from Nanopore and Illumina dataSebastian A. Fuchs0Lisanna Hülse1Teresa Tamayo2Susanne Kolbe-Busch3Klaus Pfeffer4Alexander T. Dilthey5Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University, Düsseldorf, GermanyInstitute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University, Düsseldorf, GermanyInstitute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University, Düsseldorf, GermanyInstitute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University, Düsseldorf, GermanyInstitute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University, Düsseldorf, GermanyInstitute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University, Düsseldorf, GermanyABSTRACT Genomic surveillance enables the early detection of pathogen transmission in healthcare facilities and contributes to the reduction of substantial patient harm. Fast turnaround times, flexible multiplexing, and low capital requirements make Nanopore sequencing well suited for genomic surveillance purposes; the analysis of Nanopore data, however, can be challenging. We present NanoCore, a user-friendly method for Nanopore-based genomic surveillance in healthcare facilities, enabling the calculation and visualization of cgMLST-like (core-genome multilocus sequence typing) sample distances directly from unassembled Nanopore reads. NanoCore implements a mapping, variant calling, and multilevel filtering strategy and also supports the analysis of Illumina data. We validated NanoCore on two 24-isolate data sets of methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus faecium (VRE). In the Nanopore-only mode, NanoCore-based pairwise distances between closely related isolates were near-identical to Illumina-based SeqSphere+ distances, a gold standard commercial method (average differences of 0.75 and 0.81 alleles for MRSA and VRE; sd = 0.98 and 1.00), and gave an identical clustering into closely related and non-closely related isolates. In the “hybrid” mode, in which only Nanopore data are used for some isolates and only Illumina data for others, increased average pairwise isolate distance differences were observed (average differences of 3.44 and 1.95 for MRSA and VRE, respectively; sd = 2.76 and 1.34), while clustering results remained identical. NanoCore is computationally efficient (<15 hours of wall time for the analysis of a 24-isolate data set on a workstation), available as free software, and supports installation via conda. In conclusion, NanoCore enables the effective use of the Nanopore technology for bacterial pathogen surveillance in healthcare facilities.IMPORTANCEGenomic surveillance involves sequencing the genomes and measuring the relatedness of bacteria from different patients or locations in the same healthcare facility, enabling an improved understanding of pathogen transmission pathways and the detection of “silent” outbreaks that would otherwise go undetected. It has become an indispensable tool for the detection and prevention of healthcare-associated infections and is routinely applied by many healthcare institutions. The earlier an outbreak or transmission chain is detected, the better; in this context, the Oxford Nanopore sequencing technology has important potential advantages over traditionally used short-read sequencing technologies, because it supports “real-time” data generation and the cost-effective “on demand” sequencing of small numbers of bacterial isolates. The analysis of Nanopore sequencing data, however, can be challenging. We present NanoCore, a user-friendly software for genomic surveillance that works directly based on Nanopore sequencing reads in FASTQ format, and demonstrate that its accuracy is equivalent to traditional gold standard short read-based analyses.https://journals.asm.org/doi/10.1128/msystems.01080-24microbial genomicsbacterial outbreak analysisNanopore sequencinghybrid approachesMLSThealthcare pathogen surveillance |
| spellingShingle | Sebastian A. Fuchs Lisanna Hülse Teresa Tamayo Susanne Kolbe-Busch Klaus Pfeffer Alexander T. Dilthey NanoCore: core-genome-based bacterial genomic surveillance and outbreak detection in healthcare facilities from Nanopore and Illumina data mSystems microbial genomics bacterial outbreak analysis Nanopore sequencing hybrid approaches MLST healthcare pathogen surveillance |
| title | NanoCore: core-genome-based bacterial genomic surveillance and outbreak detection in healthcare facilities from Nanopore and Illumina data |
| title_full | NanoCore: core-genome-based bacterial genomic surveillance and outbreak detection in healthcare facilities from Nanopore and Illumina data |
| title_fullStr | NanoCore: core-genome-based bacterial genomic surveillance and outbreak detection in healthcare facilities from Nanopore and Illumina data |
| title_full_unstemmed | NanoCore: core-genome-based bacterial genomic surveillance and outbreak detection in healthcare facilities from Nanopore and Illumina data |
| title_short | NanoCore: core-genome-based bacterial genomic surveillance and outbreak detection in healthcare facilities from Nanopore and Illumina data |
| title_sort | nanocore core genome based bacterial genomic surveillance and outbreak detection in healthcare facilities from nanopore and illumina data |
| topic | microbial genomics bacterial outbreak analysis Nanopore sequencing hybrid approaches MLST healthcare pathogen surveillance |
| url | https://journals.asm.org/doi/10.1128/msystems.01080-24 |
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