Evidence map›Paper›PMID 41031110›Full record

ArticleFrontiers in cellular and infection microbiology2025

Development and performance evaluation of a clinical metagenomics approach for identifying pathogens in the whole blood from patients with undifferentiated fever.

Jan Slunečko, Rok Kogoj, Samo Zakotnik, Alen Suljič, Nataša Knap, Martin Bosilj, Franc Strle, Tatjana Avšič-Županc, Petra Bogovič, Miša Korva

Abstract readEvaluation Study
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

10 authors.

Jan SlunečkoInstitute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Rok KogojInstitute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Samo ZakotnikInstitute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Alen SuljičInstitute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Nataša KnapInstitute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Martin BosiljInstitute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Franc StrleDepartment of Infectious Diseases, University Medical Center Ljubljana, Ljubljana, Slovenia.
Tatjana Avšič-ŽupancInstitute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Petra BogovičDepartment of Infectious Diseases, University Medical Center Ljubljana, Ljubljana, Slovenia.
Miša KorvaInstitute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Blood culture is the cornerstone of microbiological diagnostics for patients with acute undifferentiated fever and no obvious localization of infection; however, up to 50% of cases remain undiagnosed. Infections caused by arboviruses, fastidious or even uncultivable bacteria, or parasites often go undiagnosed without the use of target-specific molecular methods. These are typically performed in a stepwise manner, increasing cost and delaying results. Metagenomic next-generation sequencing (mNGS) has recently gained recognition as a potential universal pathogen detection tool for such cases. Our study aimed to develop a streamlined mNGS workflow for simultaneous detection of intracellular and cell-free pathogens within a single sequencing library. Methods: Total nucleic acid was isolated separately from 200 EDTA blood samples. The plasma isolate was processed with DNase, followed by the depletion of host ribosomal and messenger RNA, reverse transcription, and sequence-independent single primer amplification (SISPA). The whole blood isolate was only reverse transcribed, with no other pre-processing manipulation. Finally, the two fractions were combined prior to library preparation and sequencing using either Oxford Nanopore Technologies or Illumina. Following established bioinformatics analysis, we developed a mathematical ranking approach (ClinSeq score) that enabled quick identification of relevant pathogens in approximately one hour. Results: The mNGS workflow reached 79.5% (159/200) overall sensitivity. For bacteria the sensitivity was 88.6% (70/79), DNA viruses, 66.7% (10/15) and for RNA viruses 73.8% (76/103). Pathogen detections by individual sequencing methods showed overall sensitivity of Illumina and ONT to be 80.0% (76/95) and 79.1% (83/105) respectively. The ClinSeq score correctly highlighted the pathogen in 126/200 (63.0%) samples effectively with a Cohen's kappa ( Conclusion: Developed comprehensive mNGS workflow detects a wide range of pathogens in patients with acute undifferentiated fever. The unified workflow improves sensitivity for intracellular bacteria and RNA viruses, reduces time, cost and complexity by eliminating the need for separate library preparations, enabling faster turnaround suitable for clinical settings. The ClinSeq score effectively differentiates true pathogen signals from background noise, reducing false positives and manual interpretation time. Overall, the workflow demonstrates flexible, and efficient pathogen detection, supporting its potential for clinical diagnostics and improved patient management.

Indexed as

BacteriaBloodFeverMetagenomicsComputational BiologyFemaleHigh-Throughput Nucleotide SequencingHumansMaleMolecular Diagnostic TechniquesSensitivity and Specificityclinical metagenomicsenhanced RNA virus detectionmNGSmolecular diagnosticsuniversal pathogen detection

Identifiers

PMID41031110
PMCPMC12477237

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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.