Evidence map›Paper›PMID 40764745›Full record

ArticleScientific reports2025

Rapid and reliable species-level identification from clinical samples using 16 S rRNA gene nanopore sequencing analysis.

Marco J R Ivens, Sergio Kamminga, Kawtar Benchamach, Chaimae Akile, Els Wessels, Eric C J Claas, Stefan A Boers

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. 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.

Marco J R IvensCenter of Infectious Diseases, Medical Microbiology and Infection Control, Leiden University Medical Centre, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands.
Sergio KammingaCenter of Infectious Diseases, Medical Microbiology and Infection Control, Leiden University Medical Centre, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands.
Kawtar BenchamachCenter of Infectious Diseases, Medical Microbiology and Infection Control, Leiden University Medical Centre, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands.
Chaimae AkileCenter of Infectious Diseases, Medical Microbiology and Infection Control, Leiden University Medical Centre, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands.
Els WesselsCenter of Infectious Diseases, Medical Microbiology and Infection Control, Leiden University Medical Centre, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands.
Eric C J ClaasCenter of Infectious Diseases, Medical Microbiology and Infection Control, Leiden University Medical Centre, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands.
Stefan A BoersCenter of Infectious Diseases, Medical Microbiology and Infection Control, Leiden University Medical Centre, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands. s.a.boers@lumc.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The detection and identification of bacterial species in clinical samples are crucial for patient management and antibiotic treatment. When culture-based identification methods fail, 16 S rRNA gene next-generation sequencing (NGS) serves as a valuable alternative. However, its clinical utility is often limited by prolonged time to results (TtR) and limited species-level resolution. This study aimed to develop and validate a faster, more discriminative 16 S rRNA gene NGS workflow. Our current 16 S rRNA gene NGS protocol uses micelle-based PCR (micPCR) targeting the V4 region, followed by Illumina sequencing. This method ensures accurate quantification of 16 S rRNA gene copies in (low biomass) clinical samples by reducing PCR artefacts and correcting for background DNA contamination. To shorten the TtR and improve species-level determination, the micPCR protocol was adapted to amplify full-length 16s rRNA genes, followed by nanopore sequencing using the Flongle Flow Cell with automated data analysis using the Genome Detective platform. Testing with a synthetic microbial community and six clinical samples showed that the 16 S rRNA gene micPCR/nanopore sequencing protocol maintains good accuracy and sensitivity, reducing TtR to 24 h and enhancing species-level resolution. This optimized workflow improves clinical diagnostics, making it a valuable tool for guiding patient treatment decisions.

Indexed as

BacteriaNanopore SequencingRNA, Ribosomal, 16SDNA, BacterialHigh-Throughput Nucleotide SequencingHumansPolymerase Chain ReactionDNA, BacterialRNA, Ribosomal, 16S

Identifiers

PMID40764745
PMCPMC12325908

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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 OpenQuestion graph.