Evidence map›Paper›PMID 31100356›Full record

ArticleGenomics, proteomics & bioinformatics2019

Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates.

Valentina Galata, Cédric C Laczny, Christina Backes, Georg Hemmrich-Stanisak, Susanne Schmolke, Andre Franke, Eckart Meese, Mathias Herrmann, Lutz von Müller, Achim Plum and 4 more

Abstract read
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Antimicrobial Peptides: From Design to Clinical Application.Antibiotics (Basel, Switzerland) · 2022
    Review
  5. Article
  6. Article
  7. Review
  8. Clinical Resistome Screening of 1,110Frontiers in microbiology · 2019
    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

14 authors.

Valentina GalataChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.
Cédric C LacznyChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.
Christina BackesChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.
Georg Hemmrich-StanisakInstitute of Clinical Molecular Biology, Christian-Albrechts University of Kiel, 24105 Kiel, Germany.
Susanne SchmolkeSiemens Healthcare GmbH, Strategy and Innovation, 91052 Erlangen, Germany.
Andre FrankeInstitute of Clinical Molecular Biology, Christian-Albrechts University of Kiel, 24105 Kiel, Germany.
Eckart MeeseDepartment of Human Genetics, Saarland University, 66421 Homburg, Germany.
Mathias HerrmannInstitute of Medical Microbiology and Hygiene, Saarland University, 66421 Homburg, Germany.
Lutz von MüllerInstitute of Medical Microbiology and Hygiene, Saarland University, 66421 Homburg, Germany.
Achim PlumAres Genetics GmbH, 1030 Vienna, Austria; Curetis GmbH, 71088 Holzgerlingen, Germany.
Rolf MüllerDepartment of Pharmacy, Pharmaceutical Biotechnology, Saarland University, 66123 Saarbrücken, Germany; Department of Microbial Natural Products, Helmholtz-Institute for Pharmaceutical Research Saarland (HIPS), Saarland University, 66123 Saarbrücken, Germany; Helmholtz Center for Infection Research and Pharmaceutical Biotechnology (HZI), Saarland University, 66123 Saarbrücken, Germany.
Cord StählerChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany.
Andreas E PoschChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany; Ares Genetics GmbH, 1030 Vienna, Austria; Curetis GmbH, 71088 Holzgerlingen, Germany. Electronic address: andreas.posch@ares-genetics.com.
Andreas KellerChair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany. Electronic address: andreas.keller@uni-saarland.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emerging antibiotic resistance is a major global health threat. The analysis of nucleic acid sequences linked to susceptibility phenotypes facilitates the study of genetic antibiotic resistance determinants to inform molecular diagnostics and drug development. We collected genetic data (11,087 newly-sequenced whole genomes) and culture-based resistance profiles (10,991 out of the 11,087 isolates comprehensively tested against 22 antibiotics in total) of clinical isolates including 18 main species spanning a time period of 30 years. Species and drug specific resistance patterns were observed including increased resistance rates for Acinetobacter baumannii to carbapenems and for Escherichia coli to fluoroquinolones. Species-level pan-genomes were constructed to reflect the genetic repertoire of the respective species, including conserved essential genes and known resistance factors. Integrating phenotypes and genotypes through species-level pan-genomes allowed to infer gene-drug resistance associations using statistical testing. The isolate collection and the analysis results have been integrated into GEAR-base, a resource available for academic research use free of charge at https://gear-base.com.

Indexed as

Whole Genome SequencingAcinetobacter baumanniiBacteriaCell Culture TechniquesDrug Resistance, MicrobialEscherichia coliGenome, BacterialGenotypeHumansInternetMicrobial Sensitivity TestsPhenotypeAntibiotic resistanceBacteriaPan-genomeWhole-genome sequencing

Identifiers

PMID31100356
PMCPMC6624217

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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.