Evidence map›Paper›PMID 39944596›Full record

ArticleFrontiers in genetics2025

Antimicrobial resistance in diverse urban microbiomes: uncovering patterns and predictive markers.

Rodolfo Brizola Toscan, Wojciech Lesiński, Piotr Stomma, Balakrishnan Subramanian, Paweł P Łabaj, Witold R Rudnicki

Abstract read
In one paragraph

Article in Frontiers in genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

6 authors.

Rodolfo Brizola ToscanMałopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland.
Wojciech LesińskiFaculty of Computer Science, University of Białystok, Białystok, Poland.
Piotr StommaFaculty of Computer Science, University of Białystok, Białystok, Poland.
Balakrishnan SubramanianComputational Center, University of Białystok, Białystok, Poland.
Paweł P ŁabajMałopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland.
Witold R RudnickiFaculty of Computer Science, University of Białystok, Białystok, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antimicrobial resistance (AMR) is a growing global health concern, driven by urbanization and anthropogenic activities. This study investigated AMR distribution and dynamics across microbiomes from six U.S. cities, focusing on resistomes, viromes, and mobile genetic elements (MGEs). Using metagenomic data from the CAMDA 2023 challenge, we applied tools such as AMR++, Bowtie, AMRFinderPlus, and RGI for resistome profiling, along with clustering, normalization, and machine learning techniques to identify predictive markers. AMR++ and Bowtie outperformed other tools in detecting diverse AMR markers, with binary normalization improving classification accuracy. MGEs were found to play a critical role in AMR dissemination, with 394 genes shared across all cities. Removal of MGE-associated AMR genes altered resistome profiles and reduced model performance. The findings reveal a heterogeneous AMR landscape in urban microbiomes, particularly in New York City, which showed the highest resistome diversity. These results underscore the importance of MGEs in AMR profiling and provide valuable insights for designing targeted strategies to address AMR in urban settings.

Indexed as

antimicrobial resistance (AMR)data sciencefeature selectionmicrobiomePCArandom forestresistome modelling

Identifiers

PMID39944596
PMCPMC11813901

What OpenQuestion holds

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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.