Antibiotic resistance has become a major human health concern due to widespread use, misuse and overuse of antibiotics. In addition to antibiotics, antibacterial biocides and metals can contribute to the development and maintenance of antibiotic resistance in bacterial communities through co-selection. Information on metal and biocide resistance genes, including their sequences and molecular functions, is, however, scattered. Here, we introduce BacMet (http://bacmet.biomedicine.gu.se)—a manually curated database of antibacterial biocide- and metal-resistance genes based on an in-depth review of the scientific literature. The BacMet database contains 470 experimentally verified resistance genes. In addition, the database also contains 25 477 potential resistance genes collected from public sequence repositories. All resistance genes in the BacMet database have been organized according to their molecular function and induced resistance phenotype.

BackgroundAntibacterial biocides and metals can co-select for antibiotic resistance when bacteria harbour resistance or tolerance genes towards both types of compounds. Despite numerous case studies, systematic and quantitative data on co-occurrence of such genes on plasmids and chromosomes is lacking, as is knowledge on environments and bacterial taxa that tend to carry resistance genes to such compounds. This effectively prevents identification of risk scenarios. Therefore, we aimed to identify general patterns for which biocide/metal resistance genes (BMRGs) and antibiotic resistance genes (ARGs) that tend to occur together. We also aimed to quantify co-occurrence of resistance genes in different environments and taxa, and investigate to what extent plasmids carrying both types of genes are conjugative and/or are carrying toxin-antitoxin systems.ResultsCo-occurrence patterns of resistance genes were derived from publicly available, fully sequenced bacterial genomes (n = 2522) and plasmids (n = 4582). The only BMRGs commonly co-occurring with ARGs on plasmids were mercury resistance genes and the qacE∆1 gene that provides low-level resistance to quaternary ammonium compounds. Novel connections between cadmium/zinc and macrolide/aminoglycoside resistance genes were also uncovered. Several clinically important bacterial taxa were particularly prone to carry both BMRGs and ARGs. Bacteria carrying BMRGs more often carried ARGs compared to bacteria without (p < 0.0001). BMRGs were found in 86 % of bacterial genomes, and co-occurred with ARGs in 17 % of the cases. In contrast, co-occurrences of BMRGs and ARGs were rare on plasmids from all external environments (<0.7 %) but more common on those of human and domestic animal origin (5 % and 7 %, respectively). Finally, plasmids with both BMRGs and ARGs were more likely to be conjugative (p < 0.0001) and carry toxin-antitoxin systems (p < 0.0001) than plasmids without resistance genes.ConclusionsThis is the first large-scale identification of compounds, taxa and environments of particular concern for co-selection of resistance against antibiotics, biocides and metals. Genetic co-occurrences suggest that plasmids provide limited opportunities for biocides and metals to promote horizontal transfer of antibiotic resistance through co-selection, whereas ample possibilities exist for indirect selection via chromosomal BMRGs. Taken together, the derived patterns improve our understanding of co-selection potential between biocides, metals and antibiotics, and thereby provide guidance for risk-reducing actions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2153-5) contains supplementary material, which is available to authorized users.

The ribosomal rRNA genes are widely used as genetic markers for taxonomic identification of microbes. Particularly the small subunit (SSU; 16S/18S) rRNA gene is frequently used for species- or genus-level identification, but also the large subunit (LSU; 23S/28S) rRNA gene is employed in taxonomic assignment. The METAXA software tool is a popular utility for extracting partial rRNA sequences from large sequencing data sets and assigning them to an archaeal, bacterial, nuclear eukaryote, mitochondrial or chloroplast origin. This study describes a comprehensive update to METAXA - METAXA2 - that extends the capabilities of the tool, introducing support for the LSU rRNA gene, a greatly improved classifier allowing classification down to genus or species level, as well as enhanced support for short-read (100 bp) and paired-end sequences, among other changes. The performance of METAXA2 was compared to other commonly used taxonomic classifiers, showing that METAXA2 often outperforms previous methods in terms of making correct predictions while maintaining a low misclassification rate. METAXA2 is freely available from http://microbiology.se/software/metaxa2/.