Evidence map›Paper›PMID 41809988›Full record

ArticleFrontiers in cellular and infection microbiology2026

Metagenomics enables parallel detection of 176 clinically relevant targets from faecal samples.

Donovan H Parks, Rhys J P Newell, Andrew N Ginn, Kate L Bowerman, Areej Alsheikh-Hussain, Liang Fang, Sarah Shah, Samantha MacDonald, Tristan Wimpenny, Peter Evans and 10 more

Abstract readEvaluation Study
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

20 authors.

Donovan H ParksMicroba Life Sciences Limited, Brisbane, QLD, Australia.
Rhys J P NewellMicroba Life Sciences Limited, Brisbane, QLD, Australia.
Andrew N GinnDouglass Hanly Moir Pathology, a Sonic Healthcare practice, Sydney, NSW, Australia.
Kate L BowermanMicroba Life Sciences Limited, Brisbane, QLD, Australia.
Areej Alsheikh-HussainMicroba Life Sciences Limited, Brisbane, QLD, Australia.
Liang FangMicroba Life Sciences Limited, Brisbane, QLD, Australia.
Sarah ShahMicroba Life Sciences Limited, Brisbane, QLD, Australia.
Samantha MacDonaldMicroba Life Sciences Limited, Brisbane, QLD, Australia.
Tristan WimpennyMicroba Life Sciences Limited, Brisbane, QLD, Australia.
Peter EvansMicroba Life Sciences Limited, Brisbane, QLD, Australia.
Nadia E Arias GuzmanMicroba Life Sciences Limited, Brisbane, QLD, Australia.
Alena L PribylMicroba Life Sciences Limited, Brisbane, QLD, Australia.
Gene W TysonCentre for Microbiome Research, School of Biomedical Sciences, Queensland University of Technology (QUT), Translational Research Institute, Woolloongabba, QLD, Australia.
Philip HugenholtzAustralian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland, St. Lucia, QLD, Australia.
Lutz KrauseMicroba Life Sciences Limited, Brisbane, QLD, Australia.
Jim NewcombeDouglass Hanly Moir Pathology, a Sonic Healthcare practice, Sydney, NSW, Australia.
Paul GriffinMater Research, Raymond Terrace, Brisbane, QLD, Australia.
Michael C WehrhahnDouglass Hanly Moir Pathology, a Sonic Healthcare practice, Sydney, NSW, Australia.
Nicola Z AngelMicroba Life Sciences Limited, Brisbane, QLD, Australia.
David L A WoodMicroba Life Sciences Limited, Brisbane, QLD, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Robust identification of pathogens is essential for managing patients with symptomatic infection, yet conventional diagnostic methods focus on a subset of the most prevalent pathogens and genes. Metagenomic next-generation sequencing (mNGS) is a powerful technology that can comprehensively and simultaneously assess a broader range of pathogens and genes in a sample. This study evaluates the clinical (22 targets), analytical (19 targets), and Methods: Diagnostic performance was evaluated relative to conventional pathology testing using 510 clinical faecal samples from patients presenting with gastrointestinal symptoms. Contrived samples were used to assess analytical performance and establish the assay's limit of detection by adding cells to a faecal matrix. Results: Clinical specificity was ≥96% (≥99% for all but Adenovirus F), and median pathogen sensitivity was 91%. VF and AMR gene detection was less sensitive (median 58.7%). The assay was highly reproducible in biological triplicates (27,656/27,808 calls concordant; 99.5%). Importantly, broad mNGS coverage increased diagnostic yield, with 256/510 (50.2%) samples containing one or more additional targets not reported by standard care, and 181/510 (35.5%) containing AMR genes, including carbapenemases. Conclusions: The faecal mNGS assay performed competitively with existing diagnostic techniques while substantially expanding actionable detection in a single assay. These results support stool mNGS as a high-yield second-line or syndromic test for gastrointestinal infection, enabling improved recognition of rare pathogens, co-infections, and resistance determinants.

Indexed as

BacteriaFecesMetagenomicsMolecular Diagnostic TechniquesHigh-Throughput Nucleotide SequencingHumansReproducibility of ResultsSensitivity and SpecificityVirulence FactorsVirusesVirulence Factorsantimicrobial resistancediagnostic testenteropathogensfaecalgastrointestinalinfectionmetagenomicspathogen

Identifiers

PMID41809988
PMCPMC12968262

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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.