Evidence map›Paper›PMID 26142410›Full record

ArticleThe Journal of antimicrobial chemotherapy2015

WGS accurately predicts antimicrobial resistance in Escherichia coli.

Gregory H Tyson, Patrick F McDermott, Cong Li, Yuansha Chen, Daniel A Tadesse, Sampa Mukherjee, Sonya Bodeis-Jones, Claudine Kabera, Stuart A Gaines, Guy H Loneragan and 4 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Journal of antimicrobial chemotherapy, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 132 papers.

0numbers the graph read from it
0cells of the map it votes in
132citing papers in PubMed
7.7field-weighted citation impact, top 1% 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

132 citing papers in PubMed, 241 citations in OpenAlex.

  1. Article
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  6. Genomic profiling of ESBL/AmpC-producingFrontiers in microbiology · 2026
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  7. Review
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  14. Article
  15. Comparison of genotypic and phenotypic antimicrobial resistance profiles ofJournal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc · 2024
    Article
  16. Article
  17. Article
  18. Article
  19. Multistate nontyphoidalEpidemiology and infection · 2024
    Article
  20. Article

72 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

14 authors at 5 institutions in 1 country.

Gregory H TysonDivision of Animal and Food Microbiology, Office of Research, Center for Veterinary Medicine, US Food and Drug Administration, Laurel, MD, USA.
Patrick F McDermottDivision of Animal and Food Microbiology, Office of Research, Center for Veterinary Medicine, US Food and Drug Administration, Laurel, MD, USA.
Cong LiDivision of Animal and Food Microbiology, Office of Research, Center for Veterinary Medicine, US Food and Drug Administration, Laurel, MD, USA.
Yuansha ChenDivision of Animal and Food Microbiology, Office of Research, Center for Veterinary Medicine, US Food and Drug Administration, Laurel, MD, USA.
Daniel A TadesseDivision of Animal and Food Microbiology, Office of Research, Center for Veterinary Medicine, US Food and Drug Administration, Laurel, MD, USA.
Sampa MukherjeeDivision of Animal and Food Microbiology, Office of Research, Center for Veterinary Medicine, US Food and Drug Administration, Laurel, MD, USA.
Sonya Bodeis-JonesDivision of Animal and Food Microbiology, Office of Research, Center for Veterinary Medicine, US Food and Drug Administration, Laurel, MD, USA.
Claudine KaberaDivision of Animal and Food Microbiology, Office of Research, Center for Veterinary Medicine, US Food and Drug Administration, Laurel, MD, USA.
Stuart A GainesDivision of Animal and Food Microbiology, Office of Research, Center for Veterinary Medicine, US Food and Drug Administration, Laurel, MD, USA.
Guy H LoneraganInternational Center for Food Industry Excellence, Department of Animal and Food Sciences, Texas Tech University, Lubbock, TX, USA.
Tom S EdringtonFood and Feed Safety Research Unit, Agricultural Research Service, US Department of Agriculture, College Station, TX, USA.
Mary TorrenceCenter for Food Safety and Applied Nutrition, US Food and Drug Administration, College Park, MD, USA.
Dayna M HarhayUS Meat Animal Research Center, Agricultural Research Service, US Department of Agriculture, Clay Center, NE, USA.
Shaohua ZhaoDivision of Animal and Food Microbiology, Office of Research, Center for Veterinary Medicine, US Food and Drug Administration, Laurel, MD, USA shaohua.zhao@fda.hhs.gov.
Center for Veterinary Medicine · USUnited States Food and Drug Administration · USAgricultural Research Service · USCenter for Food Safety and Applied Nutrition · USTexas Tech University · US

Funding

Intramural FDA HHS FD999999
6 · The paper itself

Abstract

objectivesThe objective of this study was to determine the effectiveness of WGS in identifying resistance genotypes of MDR Escherichia coli and whether these correlate with observed phenotypes.

methodsSeventy-six E. coli strains were isolated from farm cattle and measured for phenotypic resistance to 15 antimicrobials with the Sensititre(®) system. Isolates with resistance to at least four antimicrobials in three classes were selected for WGS using an Illumina MiSeq. Genotypic analysis was conducted with in-house Perl scripts using BLAST analysis to identify known genes and mutations associated with clinical resistance.

resultsOver 30 resistance genes and a number of resistance mutations were identified among the E. coli isolates. Resistance genotypes correlated with 97.8% specificity and 99.6% sensitivity to the identified phenotypes. The majority of discordant results were attributable to the aminoglycoside streptomycin, whereas there was a perfect genotype-phenotype correlation for most antibiotic classes such as tetracyclines, quinolones and phenicols. WGS also revealed information about rare resistance mechanisms, such as structural mutations in chromosomal copies of ampC conferring third-generation cephalosporin resistance.

conclusionsWGS can provide comprehensive resistance genotypes and is capable of accurately predicting resistance phenotypes, making it a valuable tool for surveillance. Moreover, the data presented here showing the ability to accurately predict resistance suggest that WGS may be used as a screening tool in selecting anti-infective therapy, especially as costs drop and methods improve.

Indexed as

Drug Resistance, BacterialAnimalsAnti-Bacterial AgentsCattleCattle DiseasesEscherichia coliEscherichia coli InfectionsEscherichia coli ProteinsGene OrderGenetic Association StudiesGenome, BacterialGenotypeMicrobial Sensitivity TestsSequence Analysis, DNAAnti-Bacterial AgentsEscherichia coli Proteins

Identifiers

PMID26142410
PMCPMC11606221
OpenAlexW1957445342

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.