Evidence map›Paper›PMID 40397179›Full record

ArticleFunctional & integrative genomics2025

mlstverse-web: advancing real-time identification of mycobacteria from sputum using targeted sequencing NALC-Seq.

Yuki Matsumoto, Kiyoharu Fukushima, Shunran Zhang, Yuzy Fauzyah, Daisuke Motooka, Haruko Saito, June Yamauchi, Tadayoshi Nitta, Takuro Nii, Takanori Matsuki and 4 more

Abstract read
In one paragraph

Article in Functional & integrative genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

14 authors.

Yuki MatsumotoDepartment of Infection Metagenomics, Bioinformatics Center, Research Institute for Microbial Diseases (RIMD), Osaka University, Suita, Osaka, Japan.
Kiyoharu FukushimaDepartment of Infection Metagenomics, Bioinformatics Center, Research Institute for Microbial Diseases (RIMD), Osaka University, Suita, Osaka, Japan. fukushima@imed3.med.osaka-u.ac.jp.
Shunran ZhangDepartment of Infection Metagenomics, Bioinformatics Center, Research Institute for Microbial Diseases (RIMD), Osaka University, Suita, Osaka, Japan.
Yuzy FauzyahDepartment of Infection Metagenomics, Bioinformatics Center, Research Institute for Microbial Diseases (RIMD), Osaka University, Suita, Osaka, Japan.
Daisuke MotookaDepartment of Infection Metagenomics, Bioinformatics Center, Research Institute for Microbial Diseases (RIMD), Osaka University, Suita, Osaka, Japan.
Haruko SaitoDepartment of Clinical Laboratory, National Hospital Organization, Osaka Toneyama Medical Center, Toyonaka, Osaka, Japan.
June YamauchiDepartment of Clinical Laboratory, National Hospital Organization, Osaka Toneyama Medical Center, Toyonaka, Osaka, Japan.
Tadayoshi NittaDepartment of Clinical Laboratory, National Hospital Organization, Osaka Toneyama Medical Center, Toyonaka, Osaka, Japan.
Takuro NiiDepartment of Respiratory Medicine, National Hospital Organization, Osaka Toneyama Medical Center, Toyonaka, Osaka, Japan.
Takanori MatsukiDepartment of Respiratory Medicine, National Hospital Organization, Osaka Toneyama Medical Center, Toyonaka, Osaka, Japan.
Kazuyuki TsujinoDepartment of Respiratory Medicine, National Hospital Organization, Osaka Toneyama Medical Center, Toyonaka, Osaka, Japan.
Keisuke MikiDepartment of Respiratory Medicine, National Hospital Organization, Osaka Toneyama Medical Center, Toyonaka, Osaka, Japan.
Hiroshi KidaDepartment of Clinical Laboratory, National Hospital Organization, Osaka Toneyama Medical Center, Toyonaka, Osaka, Japan.
Shota NakamuraDepartment of Infection Metagenomics, Bioinformatics Center, Research Institute for Microbial Diseases (RIMD), Osaka University, Suita, Osaka, Japan. nshota@gen-info.osaka-u.ac.jp.

Funding

Japan Agency for Medical Research and Development JP22ym0126809j0001Japan Society for the Promotion of Science JP19K16643Japan Society for the Promotion of Science JP20KK0179Japan Society for the Promotion of Science JP21K08194
6 · The paper itself

Abstract

The identification of mycobacteria, including Mycobacterium tuberculosis (MTB) and non-tuberculous mycobacteria (NTM), remains a critical challenge in clinical and public health settings due to their pathogenicity and increasing drug resistance. Traditional diagnostic methods, such as PCR and mass spectrometry, are limited by species detectability and prolonged culture requirements. To address these limitations, this study introduces a novel approach, named NALC-Seq, which integrates next-generation sequencing (NGS) and target capture sequencing for the direct and comprehensive identification of mycobacteria from sputum samples. A total of 54 patients were prospectively or retrospectively enrolled between April 6, 2021, and November 8, 2022, and sputum samples were subjected to next generation sequencing. The NALC-Seq methodology utilizes custom-designed RNA probes for targeted enrichment of mycobacterial DNA, coupled with species identification via the mlstverse-web system. This system integrates web, upload, head, and cloud nodes to streamline data management and analysis. Our evaluation demonstrated that NALC-Seq achieved high sensitivity (98.1%) and accuracy (83.3%) in detecting diverse mycobacterial species, including rare and drug-resistant subspecies. There were discrepancies with MGIT-Seq in nine samples. These samples exhibited low smear positivity rates, and the detection of environmental mycobacteria suggested potential contamination. Furthermore, real-time identification using the MinION device significantly reduced the turnaround time from 686 to 19 h.These findings highlight the potential of NALC-Seq and mlstverse-web as an integrated diagnostic solution for overcoming the limitations of current methods. The proposed approach offers a rapid, accurate, and comprehensive strategy for mycobacterial identification, with significant implications for clinical diagnostics and public health surveillance.

Indexed as

High-Throughput Nucleotide SequencingMultilocus Sequence TypingMycobacterium tuberculosisSputumHumansMaleDrug resistance predictionMycobacteriaReal-time diagnosticsSpecies identificationTargeted capture sequencing

Identifiers

PMID40397179
PMCPMC12095390

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.