Evidence map›Paper›PMID 33125315›Full record

ArticleMicrobial genomics2020

Comprehensive screening of genomic and metagenomic data reveals a large diversity of tetracycline resistance genes.

Fanny Berglund, Maria-Elisabeth Böhm, Anton Martinsson, Stefan Ebmeyer, Tobias Österlund, Anna Johnning, D G Joakim Larsson, Erik Kristiansson

Abstract read
In one paragraph

Article in Microbial genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
–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

31 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Evolution, Mechanisms, and Therapeutic Implications of Mobile Tetracycline Destructases.BioEssays : news and reviews in molecular, cellular and developmental biology · 2026
    Review
  5. Detection ofVeterinary sciences · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. 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

8 authors.

Fanny BerglundDepartment of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.
Maria-Elisabeth BöhmCentre for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden.
Anton MartinssonDepartment of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.
Stefan EbmeyerCentre for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden.
Tobias ÖsterlundDepartment of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.
Anna JohnningDepartment of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.
D G Joakim LarssonCentre for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden.
Erik KristianssonDepartment of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tetracyclines are broad-spectrum antibiotics used to prevent or treat a variety of bacterial infections. Resistance is often mediated through mobile resistance genes, which encode one of the three main mechanisms: active efflux, ribosomal target protection or enzymatic degradation. In the last few decades, a large number of new tetracycline-resistance genes have been discovered in clinical settings. These genes are hypothesized to originate from environmental and commensal bacteria, but the diversity of tetracycline-resistance determinants that have not yet been mobilized into pathogens is unknown. In this study, we aimed to characterize the potential tetracycline resistome by screening genomic and metagenomic data for novel resistance genes. By using probabilistic models, we predicted 1254 unique putative tetracycline resistance genes, representing 195 gene families (<70 % amino acid sequence identity), whereof 164 families had not been described previously. Out of 17 predicted genes selected for experimental verification, 7 induced a resistance phenotype in an

Indexed as

Anti-Bacterial AgentsEscherichia coliGene Transfer, HorizontalHumansInterspersed Repetitive SequencesMembrane Transport ProteinsMetagenomePhylogenyRibosomal ProteinsTetracyclineTetracycline ResistanceAnti-Bacterial AgentsMembrane Transport ProteinsRibosomal ProteinsTetracyclineantibiotic resistancehidden Markov modelmetagenomicsmicrobiomeresistometetracycline resistance

Identifiers

PMID33125315
PMCPMC7725328

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.