Evidence map›Paper›PMID 34403881›Full record

ArticleEnvironment international2021

A multi-omics study on quantifying antimicrobial resistance in European freshwater lakes.

Sebastian Spänig, Lisa Eick, Julia K Nuy, Daniela Beisser, Margaret Ip, Dominik Heider, Jens Boenigk

Abstract read
In one paragraph

Article in Environment international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. 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

7 authors.

Sebastian SpänigDepartment of Bioinformatics, Faculty of Mathematics and Computer Science, Philipps-University of Marburg, Marburg, Germany.
Lisa EickDepartment of Bioinformatics, Faculty of Mathematics and Computer Science, Philipps-University of Marburg, Marburg, Germany.
Julia K NuyDepartment of Biodiversity, University of Duisburg-Essen, Universitätsstr. 5, Essen 45141, Germany.
Daniela BeisserDepartment of Biodiversity, University of Duisburg-Essen, Universitätsstr. 5, Essen 45141, Germany.
Margaret IpDepartment of Microbiology, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
Dominik HeiderDepartment of Bioinformatics, Faculty of Mathematics and Computer Science, Philipps-University of Marburg, Marburg, Germany. Electronic address: dominik.heider@uni-marburg.de.
Jens BoenigkDepartment of Biodiversity, University of Duisburg-Essen, Universitätsstr. 5, Essen 45141, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The surveillance of wastewater for the Covid-19 virus during this unprecedented pandemic and mapped to the distribution and magnitude of the infected in the population near real-time exemplifies the importance of tracking rapidly changing trends of pathogens or public health problems at a large scale. The rising trends of antimicrobial resistance (AMR) with multidrug-resistant pathogens from the environmental water have similarly gained much attention in recent years. Wastewater-based epidemiology from water samples has shown that a wide range of AMR-related genes is frequently detected. Albeit sewage is treated before release and thus, the abundance of pathogens should be significantly reduced or even pathogen-free, several studies indicated the contrary. Pathogens are still measurable in the released water, ultimately entering freshwaters, such as rivers and lakes. Furthermore, socio-economic and environmental factors, such as chemical industries and animal farming nearby, impact the presence of AMR. Many bacterial species from the environment are intrinsically resistant and also contribute to the resistome of freshwater lakes. This study collected the most extensive standardized freshwater data set from hundreds of European lakes and conducted a comprehensive multi-omics analysis on antimicrobial resistance from these freshwater lakes. Our research shows that genes encoding for AMR against tetracyclines, cephalosporins, and quinolones were commonly identified, while for some, such as sulfonamides, resistance was less frequently present. We provide an estimation of the characteristic resistance of AMR in European lakes, which can be used as a comprehensive resistome dataset to facilitate and monitor temporal changes in the development of AMR in European freshwater lakes.

Indexed as

Anti-Bacterial AgentsCOVID-19AnimalsDrug Resistance, BacterialHumansLakesSARS-CoV-2Anti-Bacterial AgentsAntimicrobial ResistanceEuropean Freshwater LakesMulti-OmicsPathogens

Identifiers

PMID34403881
PMCPMC8364379

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.