Evidence map›Paper›PMID 41561306›Full record

ArticleISME communications2026

Wastewater metaproteomics: tracking microbial and human protein biomarkers.

Claudia G Tugui, Filine Cordesius, Willem van Holthe, Mark C M van Loosdrecht, Martin Pabst

Abstract read
In one paragraph

Article in ISME communications, 2026. 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

5 authors.

Claudia G TuguiDepartment of Biotechnology, Delft University of Technology, Delft, HZ 2629, The Netherlands.
Filine CordesiusDepartment of Biotechnology, Delft University of Technology, Delft, HZ 2629, The Netherlands.
Willem van HoltheDepartment of Biotechnology, Delft University of Technology, Delft, HZ 2629, The Netherlands.
Mark C M van LoosdrechtDepartment of Biotechnology, Delft University of Technology, Delft, HZ 2629, The Netherlands.ORCID https://orcid.org/0000-0003-0658-4775
Martin PabstDepartment of Biotechnology, Delft University of Technology, Delft, HZ 2629, The Netherlands.ORCID https://orcid.org/0000-0001-9897-0723

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wastewater-based surveillance has become a powerful tool for monitoring the spread of pathogens, antibiotic resistance genes, and measuring population-level exposure to pharmaceuticals and chemicals. While surveillance methods commonly target small molecules, DNA, or RNA, wastewater also contains a vast spectrum of proteins. However, despite recent advances in environmental proteomics, large-scale monitoring of protein biomarkers in wastewater is still far from routine. Analyzing raw wastewater presents a challenge due to its heterogeneous mixture of organic and inorganic substances, microorganisms, cellular debris, and various chemical pollutants. To overcome these obstacles, we developed a wastewater metaproteomics approach including efficient protein extraction and an optimized data-processing pipeline. The pipeline utilizes de novo sequencing to customize large public sequence databases to enable comprehensive metaproteomic coverage. Using this approach, we analyzed wastewater samples collected over approximately three months from two urban locations. This revealed a core microbiome comprising a broad spectrum of microbes, gut bacteria and potential opportunistic pathogens. Additionally, we identified nearly 200 human proteins, including promising population-level health indicators, such as immunoglobulins, uromodulin, and cancer-associated proteins.

Indexed as

biomarkersgut microbesmetaproteomicswastewaterwastewater-based epidemiology

Identifiers

PMID41561306
PMCPMC12815272

What OpenQuestion holds

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LicenceCC BY
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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.