Evidence map›Paper›PMID 37328565›Full record

ArticleScientific reports2023

Using nanopore sequencing to identify fungi from clinical samples with high phylogenetic resolution.

Atsufumi Ohta, Kenichiro Nishi, Kiichi Hirota, Yoshiyuki Matsuo

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Biocontrol Microbial Inoculants SuppressPlants (Basel, Switzerland) · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Pike: OTU-Level Analysis for Oxford Nanopore Amplicon Metagenomics.International journal of molecular sciences · 2025
    Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Predictive phage therapy forProceedings of the National Academy of Sciences of the United States of America · 2024
    Article
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

4 authors.

Atsufumi OhtaDepartment of Human Stress Response Science, Institute of Biomedical Science, Kansai Medical University, 2-5-1 Shin-machi, Hirakata, Osaka, 573-1010, Japan.
Kenichiro NishiDepartment of Human Stress Response Science, Institute of Biomedical Science, Kansai Medical University, 2-5-1 Shin-machi, Hirakata, Osaka, 573-1010, Japan.
Kiichi HirotaDepartment of Human Stress Response Science, Institute of Biomedical Science, Kansai Medical University, 2-5-1 Shin-machi, Hirakata, Osaka, 573-1010, Japan.
Yoshiyuki MatsuoDepartment of Human Stress Response Science, Institute of Biomedical Science, Kansai Medical University, 2-5-1 Shin-machi, Hirakata, Osaka, 573-1010, Japan. ysmatsuo-kyt@umin.ac.jp.ORCID 0000-0002-3183-4871

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study of microbiota has been revolutionized by the development of DNA metabarcoding. This sequence-based approach enables the direct detection of microorganisms without the need for culture and isolation, which significantly reduces analysis time and offers more comprehensive taxonomic profiles across broad phylogenetic lineages. While there has been an accumulating number of researches on bacteria, molecular phylogenetic analysis of fungi still remains challenging due to the lack of standardized tools and the incompleteness of reference databases limiting the accurate and precise identification of fungal taxa. Here, we present a DNA metabarcoding workflow for characterizing fungal microbiota with high taxonomic resolution. This method involves amplifying longer stretches of ribosomal RNA operons and sequencing them using nanopore long-read sequencing technology. The resulting reads were error-polished to generate consensus sequences with 99.5-100% accuracy, which were then aligned against reference genome assemblies. The efficacy of this method was explored using a polymicrobial mock community and patient-derived specimens, demonstrating the marked potential of long-read sequencing combined with consensus calling for accurate taxonomic classification. Our approach offers a powerful tool for the rapid identification of pathogenic fungi and has the promise to significantly improve our understanding of the role of fungi in health and disease.

Indexed as

MicrobiotaNanopore SequencingFungiHigh-Throughput Nucleotide SequencingHumansPhylogenySequence Analysis, DNA

Identifiers

PMID37328565
PMCPMC10275880

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Registered trials

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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.