Comprehensive screening of genomic and metagenomic data reveals a large diversity of tetracycline resistance genes
Artikel i vetenskaplig tidskrift, 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

Författare

Fanny Berglund

Göteborgs universitet

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Maria Elisabeth Böhm

Göteborgs universitet

Anton Martinsson

Göteborgs universitet

Student vid Chalmers

Stefan Ebmeyer

Göteborgs universitet

Tobias Österlund

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Göteborgs universitet

Anna Johnning

Stiftelsen Fraunhofer-Chalmers Centrum för Industrimatematik

Göteborgs universitet

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

D. G. Joakim Larsson

Göteborgs universitet

Erik Kristiansson

Göteborgs universitet

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Microbial Genomics

2057-5858 (eISSN)

Vol. 6 11

Ämneskategorier

Mikrobiologi

Medicinsk genetik

Genetik

DOI

10.1099/mgen.0.000455

PubMed

33125315

Mer information

Senast uppdaterat

2020-12-15