Evidence map›Paper›PMID 33084388›Full record

ArticleEnvironmental health perspectives2020

The 'SELection End points in Communities of bacTeria' (SELECT) Method: A Novel Experimental Assay to Facilitate Risk Assessment of Selection for Antimicrobial Resistance in the Environment.

Aimee K Murray, Isobel C Stanton, Jessica Wright, Lihong Zhang, Jason Snape, William H Gaze

Abstract read
In one paragraph

Article in Environmental health perspectives, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
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  9. Environmental surveillance of antimicrobial resistance (AMR), perspectives from a national environmental regulator in 2023.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2023
    Article
  10. Article
  11. Article
  12. Article
  13. Antibiotic resistance in the environment.Nature reviews. Microbiology · 2022
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Microbial model communities: To understand complexity, harness the power of simplicity.Computational and structural biotechnology journal · 2020
    Review
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.

Aimee K MurrayEuropean Centre for Environment and Human Health, University of Exeter Medical School, Cornwall, UK.
Isobel C StantonEuropean Centre for Environment and Human Health, University of Exeter Medical School, Cornwall, UK.
Jessica WrightEuropean Centre for Environment and Human Health, University of Exeter Medical School, Cornwall, UK.
Lihong ZhangEuropean Centre for Environment and Human Health, University of Exeter Medical School, Cornwall, UK.
Jason SnapeAstraZeneca Global Environment, Macclesfield, UK.
William H GazeEuropean Centre for Environment and Human Health, University of Exeter Medical School, Cornwall, UK.

Funding

Biotechnology and Biological Sciences Research Council BB/L502509/1Biotechnology and Biological Sciences Research Council BB/N504026/1
6 · The paper itself

Abstract

backgroundAntimicrobial resistance (AMR) is one of the most significant health threats to society. A growing body of research demonstrates selection for AMR likely occurs at environmental concentrations of antibiotics. However, no standardized experimental approaches for determining selective concentrations of antimicrobials currently exist, preventing appropriate environmental and human health risk assessment of AMR.

objectivesWe aimed to design a rapid, simple, and cost-effective novel experimental assay to determine selective effect concentrations of antibiotics and to generate the largest experimental data set of selective effect concentrations of antibiotics to date.

methodsPreviously published methods and data were used to validate the assay, which determines the effect concentration based on reduction of bacterial community (wastewater) growth. Risk quotients for test antibiotics were generated to quantify risk.

resultsThe assay (SELection End points in Communities of bacTeria, or the SELECT method) was used to rapidly determine selective effect concentrations of antibiotics. These were in good agreement with quantitative polymerase chain reaction effect concentrations determined within the same experimental system. The SELECT method predicted no effect concentrations were minimally affected by changes in the assay temperature, growth media, or microbial community used as the inoculum. The predicted no effect concentrations for antibiotics tested ranged from DISCUSSION: The lack of evidence demonstrating environmental selection for AMR, and of associated human health risks, is a primary reason for the lack of action in the mitigation of release of antibiotics into the aquatic environment. We present a novel method that can reliably and rapidly fill this data gap to enable regulation and subsequent mitigation (where required) to lower the risk of selection for, and human exposure to, AMR in aquatic environments. In particular, ciprofloxacin and, to a lesser extent, azithromycin, cefotaxime, and trimethoprim all pose a significant risk for selection of AMR in the environment. https://doi.org/10.1289/EHP6635.

Indexed as

Biological AssayAnti-Bacterial AgentsAnti-Infective AgentsBacteriaDrug Resistance, BacterialEnvironmental MonitoringHumansRisk AssessmentWastewaterAnti-Bacterial AgentsAnti-Infective AgentsWastewater

Identifiers

PMID33084388
PMCPMC7577113

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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.