Comprehensive screening of genomic and metagenomic data reveals a large diversity of tetracycline resistance genes
Journal article, 2020

Tetracyclines are broad-spectrum antibiotics used to prevent or treat a variety of bacterial infections. Resistance is often mediated through mobile resistance genes, which encode one of the three main mechanisms: active efflux, ribosomal target protection or enzymatic degradation. In the last few decades, a large number of new tetracycline-resistance genes have been discovered in clinical settings. These genes are hypothesized to originate from environmental and commensal bacteria, but the diversity of tetracycline-resistance determinants that have not yet been mobilized into pathogens is unknown. In this study, we aimed to characterize the potential tetracycline resistome by screening genomic and metagenomic data for novel resistance genes. By using probabilistic models, we predicted 1254 unique putative tetracycline resistance genes, representing 195 gene families (<70 % amino acid sequence identity), whereof 164 families had not been described previously. Out of 17 predicted genes selected for experimental verification, 7 induced a resistance phenotype in an Escherichia coli host. Several of the predicted genes were located on mobile genetic elements or in regions that indicated mobility, suggesting that they easily can be shared between bacteria. Furthermore, phylogenetic analysis indicated several events of horizontal gene transfer between bacterial phyla. Our results also suggested that acquired efflux pumps originate from proteobacterial species, while ribosomal protection genes have been mobilized from Firmicutes and Actinobacteria. This study significantly expands the knowledge of known and putatively novel tetracycline resistance genes, their mobility and evolutionary history. The study also provides insights into the unknown resistome and genes that may be encountered in clinical settings in the future.

antibiotic resistance

resistome

hidden Markov model

microbiome

tetracycline resistance

metagenomics

Author

Fanny Berglund

University of Gothenburg

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Maria Elisabeth Böhm

University of Gothenburg

Anton Martinsson

University of Gothenburg

Student at Chalmers

Stefan Ebmeyer

University of Gothenburg

Tobias Österlund

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

University of Gothenburg

Anna Johnning

Fraunhofer-Chalmers Centre

University of Gothenburg

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

D. G. Joakim Larsson

University of Gothenburg

Erik Kristiansson

University of Gothenburg

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Microbial Genomics

2057-5858 (eISSN)

Vol. 6 11

Subject Categories

Microbiology

Medical Genetics

Genetics

DOI

10.1099/mgen.0.000455

PubMed

33125315

More information

Latest update

12/15/2020