Evidence map›Paper›PMID 42181278›Full record

ArticleiScience2026

Diversity of antibiotic resistance genes increases in urbanized lakes: A multi-tool screening.

Pau De Yebra, Luca Zoccarato, John A Galindo, Daniela Numberger, Nafi'u Abdulkadir, Hans-Peter Grossart, Alex D Greenwood

Abstract read
In one paragraph

Article in iScience, 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

7 authors.

Pau De YebraLeibniz Institute for Zoo and Wildlife Research, Alfred-Kowalke-Strasse 17, 10315 Berlin, Germany.
Luca ZoccaratoInstitute of Computational Biology, University of Natural Resources and Life Sciences (BOKU), Muthgasse 18, Vienna 1190, Austria.
John A GalindoLeibniz Institute for Zoo and Wildlife Research, Alfred-Kowalke-Strasse 17, 10315 Berlin, Germany.
Daniela NumbergerLeibniz Institute for Zoo and Wildlife Research, Alfred-Kowalke-Strasse 17, 10315 Berlin, Germany.
Nafi'u AbdulkadirLeibniz Institute of Freshwater Ecology and Inland Fisheries, Department, of Plankton and Microbial Ecology, Zur alten Fischerhütte 2, 16775 Stechlin, Germany.
Hans-Peter GrossartLeibniz Institute of Freshwater Ecology and Inland Fisheries, Department, of Plankton and Microbial Ecology, Zur alten Fischerhütte 2, 16775 Stechlin, Germany.
Alex D GreenwoodLeibniz Institute for Zoo and Wildlife Research, Alfred-Kowalke-Strasse 17, 10315 Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antimicrobial resistance (AMR) threatens to cause up to 10 million deaths annually by 2050 if no action is taken. Using shotgun sequencing, we examined the eco-evolutionary dynamics of AMR across urban-rural environment gradients in lake water and sediments, a farm pond and a wastewater treatment plant (WWTP). ARGs were identified using multiple databases and five bioinformatic tools, detecting up to 18 ARG classes-more than any single tool alone. ARG diversity was higher in urban lake sediments, urban waters, and wastewater compared to rural lake sediments and water. Among all environments, urban lake water showed the highest overall ARG abundance, second only to wastewater, and this pattern held across all ARG classes, except for aminoglycoside resistance, which was most prevalent in rural lake sediments. These findings highlight multi-tool ARG screening efficiency, WWTPs and urban sediments as major ARG reservoirs, and emphasize the need for enhanced urban-rural AMR surveillance.

Indexed as

Biological sciences toolsGenesMicrobial genetics

Identifiers

PMID42181278
PMCPMC13197638

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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.