Evidence map›Paper›PMID 40087699›Full record

ArticleJournal of translational medicine2025

Integrating DNA and RNA sequencing for enhanced pathogen detection in respiratory infections.

Dejian Gu, Jie Liu, Jiaping Wang, Yuting Yi, Yuxing Chu, Rui Gao, Hao Liu, Jun She, Binghuai Lu

Abstract read
In one paragraph

Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
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  5. Clinical features and prognostic factors ofFrontiers in medicine · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Article
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  11. Review
  12. Post-endoscopic neurosurgicalFrontiers in medicine · 2026
    Article
  13. Enrichment techniques for clinical metagenomics.Frontiers in cellular and infection microbiology · 2026
    Review
  14. Review
  15. Article
  16. Article
  17. Review
  18. Observational
  19. Article
  20. 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

9 authors.

Dejian Gu *Geneplus-Beijing Co., Ltd., Beijing, China.
Jie Liu *Shanghai Key Laboratory of Lung Inflammation and Injury, Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Jiaping Wang *Suzhou GenePlus Clinical Laboratory Co., Ltd, Beijing, China.
Yuting YiSuzhou GenePlus Clinical Laboratory Co., Ltd, Beijing, China.
Yuxing ChuSuzhou GenePlus Clinical Laboratory Co., Ltd, Beijing, China.
Rui GaoGeneplus-Beijing Co., Ltd., Beijing, China.
Hao LiuGeneplus-Beijing Co., Ltd., Beijing, China.
Jun She *Shanghai Key Laboratory of Lung Inflammation and Injury, Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China. she.jun@zs-hosptial.sh.cn.
Binghuai Lu *Laboratory of Clinical Microbiology and Infectious Diseases, Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, Beijing Key Laboratory of Surveillance, Early Warning and Pathogen Research on Emerging Infectious Diseases, National Center for Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China. zs25041@126.com.

Funding

Alpha Foundation for the Improvement of Mine Safety and Health CFH, 2024-1-4063Beijing Natural Science Foundation L222073Shanghai Municipal Science and Technology Major Project ZD2021CY001
6 · The paper itself

Abstract

backgroundThe clinical value of shotgun metagenomic next-generation sequencing (mNGS) in improving the detection rates of respiratory pathogens is well-established. However, mNGS is complex and expensive. This study designed and evaluated the performance of targeted NGS (tNGS) in diagnosing respiratory infections.

methodsWe retrospectively included samples from 281 patients with lower respiratory tract infections to establish thresholds of pathogens. Subsequently, target pathogens were selected and a probe hybridization system was established. The performance and clinical manifestations of tNGS for 306 pathogens were evaluated using clinical and simulated samples.

resultsThe tNGS method took 16 h with sequencing data sizes of 5 M reads. The limit-of-detection of tNGS was 100-200 CFU/mL, respectively. Bioinformatics simulation confirmed the method's high specificity and robustness. In 281 patients of clinical validation cohort, tNGS exhibited a sensitivity of 97.73% and specificity of 75.41% compared to the composite reference standard, which notably surpasses those of culture-based and conventional microbiological methods (CMT). In detecting bacterial and viral infection, tNGS demonstrated superior sensitivity relative to CMT. Notably, 61.40% of target viruses were subtype-resolved with the initial establishment of reliable typing cutoffs, with the subtyping results being completely consistent with the PCR results. tNGS allowed for concurrent identification of antimicrobial resistance (AMR) markers and viral subtyping. 80.56% of AMR markers identified by tNGS were consistent with antimicrobial susceptibility testing.

conclusionThis research established the robust performance of our tailored tNGS assay in the simultaneous detection of DNA and RNA pathogens, underscoring its prospective suitability for widespread use in clinical diagnostics.

Indexed as

Respiratory Tract InfectionsSequence Analysis, RNAAdultAgedFemaleHigh-Throughput Nucleotide SequencingHumansMaleMiddle AgedRetrospective StudiesCapture probe enrichmentDNA and RNA sequencingmNGSRespiratory tract infectionTarget NGS testtNGS

Identifiers

PMID40087699
PMCPMC11907987

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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.