Evidence map›Paper›PMID 40679848›Full record

ArticleJournal of clinical microbiology2025

An open-source nanopore-only sequencing workflow for analysis of clonal outbreaks delivers short-read level accuracy.

Nick Vereecke, Thomas B Yoon, Ting L Luo, Brendan W Corey, Francois Lebreton, Patrick T Mc Gann, John P Dekker

Abstract read
In one paragraph

Article in Journal of clinical microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Nanopore Sequencing for Chikungunya Virus: Principles and Application.Methods in molecular biology (Clifton, N.J.) · 2027
    Article
  2. Draft genomes of 53Microbiology resource announcements · 2026
    Article
  3. Article
  4. Article
  5. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Nick VereeckeBacterial Pathogenesis and Antimicrobial Resistance Section (BPARS), Laboratory of Clinical Immunology & Microbiology (LCIM), National Institute for Allergy and Infectious Disease (NIAID), National Institutes of Health (NIH), Bethesda, Maryland, USA.ORCID 0000-0001-5367-9756
Thomas B YoonBacterial Pathogenesis and Antimicrobial Resistance Section (BPARS), Laboratory of Clinical Immunology & Microbiology (LCIM), National Institute for Allergy and Infectious Disease (NIAID), National Institutes of Health (NIH), Bethesda, Maryland, USA.ORCID 0000-0002-5427-8230
Ting L LuoMultidrug-Resistant Organism Repository and Surveillance Network (MRSN), Diagnostics and Countermeasures Branch, Center for Infectious Disease Research (CIDR), Walter Reed Army Institute of Research (WRAIR), Silver Spring, Maryland, USA.
Brendan W CoreyMultidrug-Resistant Organism Repository and Surveillance Network (MRSN), Diagnostics and Countermeasures Branch, Center for Infectious Disease Research (CIDR), Walter Reed Army Institute of Research (WRAIR), Silver Spring, Maryland, USA.
Francois LebretonMultidrug-Resistant Organism Repository and Surveillance Network (MRSN), Diagnostics and Countermeasures Branch, Center for Infectious Disease Research (CIDR), Walter Reed Army Institute of Research (WRAIR), Silver Spring, Maryland, USA.ORCID 0000-0002-7157-5026
Patrick T Mc GannMultidrug-Resistant Organism Repository and Surveillance Network (MRSN), Diagnostics and Countermeasures Branch, Center for Infectious Disease Research (CIDR), Walter Reed Army Institute of Research (WRAIR), Silver Spring, Maryland, USA.
John P DekkerBacterial Pathogenesis and Antimicrobial Resistance Section (BPARS), Laboratory of Clinical Immunology & Microbiology (LCIM), National Institute for Allergy and Infectious Disease (NIAID), National Institutes of Health (NIH), Bethesda, Maryland, USA.ORCID 0000-0002-3701-5228

Funding

Division of Intramural Research, National Institute of Allergy and Infectious DiseasesU.S. Department of Defense
6 · The paper itself

Abstract

In this work, we present an optimized nanopore long-read only sequencing workflow for epidemiologic analysis of clonal outbreaks built with open-source tools. A set of unrelated clinical IMPORTANCE: For the past decade, bacterial whole-genome sequencing has been performed using high-accuracy short-read sequencing. More recently, long-read sequencing with Oxford Nanopore Technologies (ONT) instruments has emerged as a potential alternative based on multiple advantages, including lower costs, portability, and speed. However, this platform has suffered from basecall error rates that were too high for many applications in clinical microbiology, including outbreak tracing. With the release of new flow cell chemistries and basecall algorithms, the accuracy has improved dramatically, making this approach feasible for outbreak investigations. In this work, we optimize a streamlined nanopore-only workflow for epidemiologic analysis of bacterial pathogens. The workflow was validated with isolates from four previously identified clinical outbreaks with varying GC content and demonstrated fully concordant cgMLST clustering as compared to short-read references. This workflow will facilitate the broader implementation of ONT-only genomes and cgMLST analysis to assist in hospital outbreaks worldwide.

Indexed as

Disease OutbreaksNanopore SequencingGenome, BacterialHigh-Throughput Nucleotide SequencingHumansKlebsiella pneumoniaeMolecular EpidemiologyMultilocus Sequence TypingNanoporesPseudomonas aeruginosaPseudomonas InfectionsRetrospective StudiesSequence Analysis, DNAWorkflowbacteriologybioinformaticscgMLSTclinical microbiologyepidemiologyerror correctiongenome sequencinglong-read nanopore sequencingminimum spanning treeopen-sourceoutbreak detectionpublic health microbiology

Identifiers

PMID40679848
PMCPMC12345217

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.