BacMet is an easy-to-use bioinformatics resource of antibacterial biocide- and metal-resistance genes. BacMet consists of two databases:

Database Statistics (version 2.0)
Last updated: 11 March 2018

Predicted Resistance Genes: 155,512          

Exp. Confirmed Resistance Genes: 753
        Chromosomal-borne: 550
        Plasmid/transposon-borne: 203

        Biocide resistance genes: 268
        Metal resistance genes: 420
        Genes with both biocide- and metal-           resistance potential: 65

Total Compounds: 111
        Chemical classes: 43
        Antibacterial biocides: 58
        Metals: 23
        'Other compounds' : 30

BacMet provides a high quality, manually curated database of bacterial genes that are experimentally confirmed to confer resistance to metals and/or antibacterial biocides, fully referenced to the scientific literature. BacMet also includes a database of predicted resistance genes, as the resistance genes may differ between species and/or occur in different forms that are not (yet) experimentally investigated. The database of predicted genes is generated by sequence similarity searches in public databases, using an uniform cut-off for genes found on plasmids, and individually set cut-offs for chromosomal genes.

BacMet provides tools for identification of biocide and metal-resistance genes in proteins and DNA sequences including full genomes. The genes in the databases can be accessed either through the browsing option, where one can browse genes by the compounds they confer resistance to or by their name. Alternatively one may use the search function to search for any term in the database, including for example gene name, name of biocide or metal and chemical class. Using the advanced search option, one may search specifically for e.g. plasmid-borne or chromosomal-borne genes. The entire database can also be downloaded for off-line analysis of larger datasets.

Citation: Pal, C., Bengtsson-Palme, J., Rensing, C., Kristiansson, E., Larsson, DGJ. (2014) BacMet: antibacterial biocide and metal resistance genes database, Nucleic Acids Res., 42, D737-D743. doi: 10.1093/nar/gkt1252

BacMet database/website was developed and designed by Chandan Pal and currently maintained by Joakim Larsson's team

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