Evidence map›Paper›PMID 31248462›Full record

ArticleMicrobiome2019

Sewage effluent from an Indian hospital harbors novel carbapenemases and integron-borne antibiotic resistance genes.

Nachiket P Marathe, Fanny Berglund, Mohammad Razavi, Chandan Pal, Johannes Dröge, Sharvari Samant, Erik Kristiansson, D G Joakim Larsson

Open access · goldAbstract read
In one paragraph

Article in Microbiome, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 5% of its field
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

39 citing papers in PubMed, 1 synthesis or guideline pooled it, 116 citations in OpenAlex.

  1. Pooled it
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  3. Review
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  7. Article
  8. Routine immunization againstThe Lancet regional health. Southeast Asia · 2024
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  9. Article
  10. Article
  11. Article
  12. Detection and Characterization of Carbapenemase-ProducingAntibiotics (Basel, Switzerland) · 2023
    Article
  13. Article
  14. Article
  15. Article
  16. A new class A beta-lactamase gene blaScientific reports · 2023
    Article
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  18. Review
  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 at 4 institutions in 3 countries.

Nachiket P MaratheCentre for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden.
Fanny BerglundCentre for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden.
Mohammad RazaviCentre for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden.
Chandan PalCentre for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden.
Johannes DrögeDepartment of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.
Sharvari SamantMahatma Gandhi Mission medical college, Navi Mumbai, Maharashtra, India.
Erik KristianssonCentre for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden.
D G Joakim LarssonCentre for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, Sweden. joakim.larsson@fysiologi.gu.se.
University of Gothenburg · SEChalmers University of Technology · SEMinistry for Primary Industries · NZNorwegian Institute of Marine Research · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHospital wastewaters contain fecal material from a large number of individuals, of which many are undergoing antibiotic therapy. It is, thus, plausible that hospital wastewaters could provide opportunities to find novel carbapenemases and other resistance genes not yet described in clinical strains. Our aim was therefore to investigate the microbiota and antibiotic resistome of hospital effluent collected from the city of Mumbai, India, with a special focus on identifying novel carbapenemases.

resultsShotgun metagenomics revealed a total of 112 different mobile antibiotic resistance gene types, conferring resistance against almost all classes of antibiotics. Beta-lactamase genes, including encoding clinically important carbapenemases, such as NDM, VIM, IMP, KPC, and OXA-48, were abundant. NDM (0.9% relative abundance to 16S rRNA genes) was the most common carbapenemase gene, followed by OXA-58 (0.84% relative abundance to 16S rRNA genes). Among the investigated mobile genetic elements, class 1 integrons (11% relative abundance to 16S rRNA genes) were the most abundant. The genus Acinetobacter accounted for as many as 30% of the total 16S rRNA reads, with A. baumannii accounting for an estimated 2.5%. High throughput sequencing of amplified integron gene cassettes identified a novel functional variant of an IMP-type (proposed IMP-81) carbapenemase gene (eight aa substitutions) along with recently described novel resistance genes like sul4 and bla

conclusionBy exploring hospital wastewater from India, our understanding of the diversity of carbapenemases has been extended. The study also demonstrates that the microbiota of hospital wastewater can serve as a reservoir of novel resistance genes, including previously uncharacterized carbapenemases with the potential to spread further.

Indexed as

Genes, BacterialHospitalsAnti-Bacterial AgentsBacteriaBacterial Proteinsbeta-LactamasesDrug Resistance, MicrobialHumansIndiaIntegronsMetagenomicsMicrobial Sensitivity TestsMicrobiotaRNA, Ribosomal, 16SSequence Analysis, DNASewageAnti-Bacterial AgentsBacterial Proteinsbeta-LactamasescarbapenemaseRNA, Ribosomal, 16SSewageAntibiotic resistanceCarbapenemaseHidden Markov modelHospital effluentIndiaPathogens

Identifiers

PMID31248462
PMCPMC6598227
OpenAlexW2955692928

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.