Evidence map›Paper›PMID 27717408›Full record

ArticleMicrobiome2016

The structure and diversity of human, animal and environmental resistomes.

Chandan Pal, Johan Bengtsson-Palme, Erik Kristiansson, D G Joakim Larsson

Abstract read
In one paragraph

Article in Microbiome, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 178 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
178citing 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

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

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

118 more citing papers are in PubMed but not listed here.

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

4 authors.

Chandan PalDepartment of Infectious Diseases, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, SE-413 46, Gothenburg, Sweden.
Johan Bengtsson-PalmeDepartment of Infectious Diseases, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, SE-413 46, Gothenburg, Sweden.
Erik KristianssonCentre for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden.
D G Joakim LarssonDepartment of Infectious Diseases, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, SE-413 46, Gothenburg, Sweden. joakim.larsson@fysiologi.gu.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAntibiotic resistance genes (ARGs) are widespread but cause problems only when present in pathogens. Environments where selection and transmission of antibiotic resistance frequently take place are likely to be characterized by high abundance and diversity of horizontally transferable ARGs. Large-scale quantitative data on ARGs is, however, lacking for most types of environments, including humans and animals, as is data on resistance genes to potential co-selective agents, such as biocides and metals. This paucity prevents efficient identification of risk environments.

resultsWe provide a comprehensive characterization of resistance genes, mobile genetic elements (MGEs) and bacterial taxonomic compositions for 864 metagenomes from humans (n = 350), animals (n = 145) and external environments (n = 369), all deeply sequenced using Illumina technology. Environment types showed clear differences in both resistance profiles and bacterial community compositions. Human and animal microbial communities were characterized by limited taxonomic diversity and low abundance and diversity of biocide/metal resistance genes and MGEs but a relatively high abundance of ARGs. In contrast, external environments showed consistently high taxonomic diversity which in turn was linked to high diversity of both biocide/metal resistance genes and MGEs. Water, sediment and soil generally carried low relative abundance and few varieties of known ARGs, whereas wastewater/sludge was on par with the human gut. The environments with the largest relative abundance and/or diversity of ARGs, including genes encoding resistance to last resort antibiotics, were those subjected to industrial antibiotic pollution and a limited set of deeply sequenced air samples from a Beijing smog event.

conclusionsOur study identifies air and antibiotic-polluted environments as under-investigated transmission routes and reservoirs for antibiotic resistance. The high taxonomic and genetic diversity of external environments supports the hypothesis that these also form vast sources of unknown resistance genes, with potential to be transferred to pathogens in the future.

Indexed as

AnimalsAnti-Bacterial AgentsBacteriaDrug Resistance, Multiple, BacterialGastrointestinal MicrobiomeGenes, BacterialGene Transfer, HorizontalHigh-Throughput Nucleotide SequencingHumansInterspersed Repetitive SequencesMetalsSelection, GeneticSewageSmogSoil MicrobiologyTetracycline ResistanceAnti-Bacterial AgentsMetalsSewageSmogAntibiotic resistanceBiocide resistanceEnvironmental microbiomeHuman microbiomeMetagenomicsMetal resistanceResistome

Identifiers

PMID27717408
PMCPMC5055678

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.