Evidence map›Paper›PMID 40681571›Full record

ArticleNature communications2025

Ultra-sensitive metaproteomics redefines the dark metaproteome, uncovering host-microbiome interactions and drug targets in intestinal diseases.

Feng Xian, Malena Brenek, Christoph Krisp, Elisabeth Urbauer, Ranjith Kumar Ravi Kumar, Doriane Aguanno, Tharan Srikumar, Qixin Liu, Allison M Barry, Bin Ma and 4 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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.

Feng XianCenter of Excellence for Metaproteomics and Systems Biology of Pain Laboratory, Division of Pharmacology & Toxicology, Department of Pharmaceutical Sciences, Faculty of Life Sciences, University of Vienna, Vienna, Austria.ORCID http://orcid.org/0000-0002-8345-0108
Malena BrenekCenter of Excellence for Metaproteomics and Systems Biology of Pain Laboratory, Division of Pharmacology & Toxicology, Department of Pharmaceutical Sciences, Faculty of Life Sciences, University of Vienna, Vienna, Austria.
Christoph KrispBruker Daltonics GmbH & Co. KG, Bremen, Germany.
Elisabeth UrbauerChair of Nutrition and Immunology, Technical University of Munich, Freising, Germany.
Ranjith Kumar Ravi KumarCenter of Excellence for Metaproteomics and Systems Biology of Pain Laboratory, Division of Pharmacology & Toxicology, Department of Pharmaceutical Sciences, Faculty of Life Sciences, University of Vienna, Vienna, Austria.ORCID http://orcid.org/0000-0003-2809-948X
Doriane AguannoChair of Nutrition and Immunology, Technical University of Munich, Freising, Germany.
Tharan SrikumarBruker Daltonics GmbH & Co. KG, Bremen, Germany.ORCID http://orcid.org/0000-0003-3359-0281
Qixin LiuRapid Novor, Kitchener, ON, Canada.
Allison M BarryCenter of Excellence for Metaproteomics and Systems Biology of Pain Laboratory, Division of Pharmacology & Toxicology, Department of Pharmaceutical Sciences, Faculty of Life Sciences, University of Vienna, Vienna, Austria.ORCID http://orcid.org/0000-0002-6787-6889
Bin MaRapid Novor, Kitchener, ON, Canada.ORCID http://orcid.org/0000-0001-6254-4087
Jonathan KriegerBruker Daltonics GmbH & Co. KG, Bremen, Germany.
Dirk HallerChair of Nutrition and Immunology, Technical University of Munich, Freising, Germany.ORCID http://orcid.org/0000-0002-6977-4085
Manuela Schmidt *Center of Excellence for Metaproteomics and Systems Biology of Pain Laboratory, Division of Pharmacology & Toxicology, Department of Pharmaceutical Sciences, Faculty of Life Sciences, University of Vienna, Vienna, Austria.ORCID http://orcid.org/0000-0003-1972-3519
David Gómez-Varela *Center of Excellence for Metaproteomics and Systems Biology of Pain Laboratory, Division of Pharmacology & Toxicology, Department of Pharmaceutical Sciences, Faculty of Life Sciences, University of Vienna, Vienna, Austria. david.gomez.varela@univie.ac.at.ORCID http://orcid.org/0000-0003-2502-9419

Funding

Austrian Science Fund (Fonds zur Förderung der Wissenschaftlichen Forschung) 10.55776/P35856Austrian Science Fund (Fonds zur Förderung der Wissenschaftlichen Forschung) 10.55776/P36554Deutsche Forschungsgemeinschaft (German Research Foundation) 469152594
6 · The paper itself

Abstract

The functional characterization of host-gut microbiome interactions remains limited by the sensitivity of current metaproteomic approaches. Here, we present uMetaP, an ultra-sensitive workflow combining advanced LC-MS technologies with an FDR-validated de novo sequencing strategy, novoMP. uMetaP markedly expands functional coverage and improves the taxonomic detection limit of the gut dark metaproteome by 5000-fold, enabling precise detection and quantification of low-abundance microbial and host proteins. Applied to a mouse model of intestinal injury, uMetaP revealed host-microbiome functional networks underlying tissue damage, beyond genomic findings. Orthogonal validation using transcriptomic data from Crohn's disease patients confirmed key host protein alterations. Furthermore, we introduce the concept of a druggable metaproteome, mapping functional targets within the host and microbiota. By redefining the sensitivity limits of metaproteomics, uMetaP provides a highly valuable framework for advancing microbiome research and developing therapeutic strategies for microbiome-related diseases.

Indexed as

Gastrointestinal MicrobiomeHost Microbial InteractionsIntestinal DiseasesProteomeProteomicsAnimalsChromatography, LiquidCrohn DiseaseDisease Models, AnimalHumansMiceMice, Inbred C57BLProteome

Identifiers

PMID40681571
PMCPMC12274446

What OpenQuestion holds

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LicenceCC BY
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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.