ArticleMicrobiome2018
The diversity of uncharacterized antibiotic resistance genes can be predicted from known gene variants-but not always.
Article in Microbiome, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Farming practices exert selection pressures on the resistome of natural populations of house mice.Nature communications · 2026Article
- Resistance Gene Dynamics, Biogeochemical Coupling, and Ecological Risks in Sediments of Anthropogenically Impacted Lake Wetlands in China.Environment & health (Washington, D.C.) · 2026Article
- UPGG: expanding the taxonomic and functional diversity of the pig gut microbiome with an enhanced genome catalog.NPJ biofilms and microbiomes · 2025Article
- Article
- Sustainable application of biocides to promote hygiene and minimize antimicrobial resistance.Sustainable microbiology · 2024Review
- Metagenomic analysis reveals the dissemination mechanisms and risks of resistance genes in plateau lakes.iScience · 2023Article
- Antibiotic Resistance Genes in Aerosols: Baseline from Kuwait.International journal of molecular sciences · 2023Article
- Latent antibiotic resistance genes are abundant, diverse, and mobile in human, animal, and environmental microbiomes.Microbiome · 2023Article
- Antibiotic resistance genes are differentially mobilized according to resistance mechanism.GigaScience · 2022Article
- Extensive metagenomic analysis of the porcine gut resistome to identify indicators reflecting antimicrobial resistance.Microbiome · 2022Article
- Microbiomes of air dust collected during the ground-based closed bioregenerative life support experiment "Lunar Palace 365".Environmental microbiome · 2022Article
- Metagenomic-based surveillance systems for antibiotic resistance in non-clinical settings.Frontiers in microbiology · 2022Review
- KAUST Metagenomic Analysis Platform (KMAP), enabling access to massive analytics of re-annotated metagenomic data.Scientific reports · 2021Article
- ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data.NAR genomics and bioinformatics · 2021Article
- Microbial retention and resistances in stormwater quality improvement devices treating road runoff.FEMS microbes · 2021Article
- Abundance and diversity of resistomes differ between healthy human oral cavities and gut.Nature communications · 2020Article
- MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data.Nucleic acids research · 2020Article
- Metagenomic Analysis Reveals the Distribution of Antibiotic Resistance Genes in a Large-Scale Population of Healthy Individuals and Patients With Varied Diseases.Frontiers in molecular biosciences · 2020Article
- Effects of Dairy Manure-Based Amendments and Soil Texture on Lettuce- and Radish-Associated Microbiota and Resistomes.mSphere · 2019Article
- Antibiotic resistomes of healthy pig faecal metagenomes.Microbial genomics · 2019Article
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1 author.
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Abstract
backgroundAntibiotic resistance is considered one of the most urgent threats to modern healthcare, and the role of the environment in resistance development is increasingly recognized. It is often assumed that the abundance and diversity of known resistance genes are representative also for the non-characterized fraction of the resistome in a given environment, but this assumption has not been verified. In this study, this hypothesis is tested, using the resistance gene profiles of 1109 metagenomes from various environments.
resultsThis study shows that the diversity and abundance of known antibiotic resistance genes can generally predict the diversity and abundance of undescribed resistance genes. However, the extent of this predictability is dependent on the type of environment investigated. Furthermore, it is shown that carefully selected small sets of resistance genes can describe total resistance gene diversity remarkably well.
conclusionsThe results of this study suggest that knowledge gained from large-scale quantifications of known resistance genes can be utilized as a proxy for unknown resistance factors. This is important for current and proposed monitoring efforts for environmental antibiotic resistance and has implications for the design of risk ranking strategies and the choices of measures and methods for describing resistance gene abundance and diversity in the environment.
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