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Cited by 96Antibiotic Resistance in BacteriaPharmaceutical and Antibiotic Environmental ImpactsAntibiotic Use and Resistance

Review and Comparison of Antimicrobial Resistance Gene Databases

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Papp, Márton, Solymosi, Norbert·2022·Antibiotics
DOI 10.3390/antibiotics11030339PMC PMC8944830

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Abstract

As the prevalence of antimicrobial resistance genes is increasing in microbes, we are facing the return of the pre-antibiotic era. Consecutively, the number of studies concerning antibiotic resistance and its spread in the environment is rapidly growing. Next generation sequencing technologies are widespread used in many areas of biological research and antibiotic resistance is no exception. For the rapid annotation of whole genome sequencing and metagenomic results considering antibiotic resistance, several tools and data resources were developed. These databases, however, can differ fundamentally in the number and type of genes and resistance determinants they comprise. Furthermore, the annotation structure and metadata stored in these resources can also contribute to their differences. Several previous reviews were published on the tools and databases of resistance gene annotation; however, to our knowledge, no previous review focused solely and in depth on the differences in the databases. In this review, we compare the most well-known and widely used antibiotic resistance gene databases based on their structure and content. We believe that this knowledge is fundamental for selecting the most appropriate database for a research question and for the development of new tools and resources of resistance gene annotation.

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  • Identification of mobile antimicrobial resistance genes and their potential impact on intestinal resistance requires whole-genome sequencing and detailed characterization of antibiotic resistance genes.

    “The identification of mobile antimicrobial resistance genes and their potential impact on intestinal resistance also requires whole-genome sequencing and detailed characterization of antibiotic resistance genes [42,66,67,68].”

    From Current Concepts in Probiotic Safety and Efficacy (2026) · cites this paper as [67]

    The Introduction (page not supplied) says genome sequencing is commonly used in antimicrobial-resistance surveillance and that tools and databases analyze resistance genes in bacterial genomes and metagenomic samples. It also discusses genes with potential mobilization properties. It does not say whole-genome sequencing is required to identify mobile genes or assess their impact on intestinal resistance; the only intestinal-resistome match is a reference title. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • CARD and ResFinder use carefully curated databases to identify known antibiotic resistance genes, providing clear results but may fail to detect novel, unusual, or modulated resistance mechanisms.

    “In contrast, CARD and ResFinder use carefully curated databases to identify known antibiotic resistance genes, providing clear results but may fail to detect novel, unusual, or modulated resistance mechanisms [67,152,167,168].”

    From Current Concepts in Probiotic Safety and Efficacy (2026) · cites this paper as [67]

    Section 2.3 describes CARD as hand-curated, and Section 2.6 describes extensive expert curation of ResFinder; both are resources for identifying resistance determinants. The Conclusions (Section 4) say deep-learning approaches are generally considered better at detecting novel resistance-gene variants, which lends limited support to the caution about novelty. The paper does not establish that CARD and ResFinder provide clear results or that they may miss unusual or modulated resistance mechanisms. No page numbers are available in our copy. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • Computational approaches can result in false positives and false negatives due to annotation thresholds, database bias, fragmented assemblies, or model overfitting.

    “These approaches can result in false positives and false negatives due to factors such as annotation thresholds, database bias, fragmented assemblies, or model overfitting, highlighting the need for careful validation against phenotypic data and careful interpretation when assessing the safety and efficacy of probiotics [67,132,133].”

    From Current Concepts in Probiotic Safety and Efficacy (2026) · cites this paper as [67]

    Section 3.1 (page unavailable) discusses possible overestimation from duplicate database entries and false negatives in homology searches, while noting that CARD's gene-specific detection thresholds address the latter concern. The Introduction and Conclusions also say annotation-tool performance depends on the underlying database. The cited passages do not support fragmented assemblies or model overfitting as causes of errors, and they do not establish a need for validation against phenotypic data when assessing probiotics. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Papp, M., & Solymosi, N.
Affiliations
University of Veterinary Medicine (HU)
Corresponding author
Solymosi, Norbert
ORCID
Venue
Antibiotics
Publisher
MDPI AG
Published
2022-03-04
Volume
11
Issue
3
Pages
339
ISSN
2079-6382 (ISSN-L)
DOI
10.3390/antibiotics11030339
PMC
PMC8944830
OpenAlex
W4220922497
Cited by
96
References
1
Citations by year
2026: 29 · 2025: 19 · 2024: 18 · 2023: 22 · 2022: 8
FWCI
1.33
Type
journal article
Language
en
Update notices
correction (2022-03-04)
Open access
Licence
Locations
  • Antibiotics (publishedVersion, cc-by)
  • Preprints.org (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • European Union and co-financed by the European Social Fund (No. EFOP-3.6.3-VEKOP-16-2017-00005, No. 874735)
  • European Union’s Horizon 2020 research and innovation program under Grant Agreement (No. EFOP-3.6.3-VEKOP-16-2017-00005, No. 874735)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Medicine › Antibiotic Resistance in Bacteria
  • Physical Sciences › Environmental Science › Pollution › Pharmaceutical and Antibiotic Environmental Impacts
  • Life Sciences › Immunology and Microbiology › Applied Microbiology and Biotechnology › Antibiotic Use and Resistance
Keywords
antimicrobial resistance genes, metagenomics, whole genome sequencing, database comparison, resistance determinants, metadata

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