Background: A multidrug-resistant lineage of Staphylococcus epidermidis named ST215 is a common cause of prosthetic joint infections and other deep surgical site infections in Northern Europe, but is not present elsewhere. The increasing resistance among S. epidermidis strains is a global concern. We used whole-genome sequencing to characterize ST215 from healthcare settings. Results: We completed the genome of a ST215 isolate from a Swedish hospital using short and long reads, resulting in a circular 2,676,787 bp chromosome and a 2,326 bp plasmid. The new ST215 genome was placed in phylogenetic context using 1,361 finished public S. epidermidis reference genomes. We generated 10 additional short-read ST215 genomes and 11 short-read genomes of ST2, which is another common multidrug-resistant lineage at the same hospital. We studied recombination’s role in the evolution of ST2 and ST215, and found multiple recombination events averaging 30–50 kb. By comparing the results of antimicrobial susceptibility testing for 31 antimicrobial drugs with the genome content encoding antimicrobial resistance in the ST215 and ST2 isolates, we found highly similar resistance traits between the isolates, with 22 resistance genes being shared between all the ST215 and ST2 genomes. The ST215 genome contained 29 genes that were historically identified as virulence genes of S. epidermidis ST2. We established that in the nucleotide sequence stretches identified as recombination events, virulence genes were overrepresented in ST215, while antibiotic resistance genes were overrepresented in ST2. Conclusions: This study features the extensive antibiotic resistance and virulence gene content in ST215 genomes. ST215 and ST2 lineages have similarly evolved, acquiring resistance and virulence through genomic recombination. The results highlight the threat of new multidrug-resistant S. epidermidis lineages emerging in healthcare settings.

Summary: The Flexible Taxonomy Database framework provides a method for modification and merging official and custom taxonomic databases to create improved databases. Using such databases will increase accuracy and precision of existing methods to classify sequence reads. Availability and implementation: Source code is freely available at https://github.com/FOI-Bioinformatics/flextaxd and installable through Bioconda.

Summary: Nanometa Live presents a user-friendly interface designed for real-time metagenomic data analysis and pathogen identification utilizing Oxford Nanopore Technologies’ MinION and Flongle flow cells. It offers an efficient workflow and graphical interface for the visualization and interpretation of metagenomic data as it is being generated. Key features include automated BLAST validation, streamlined handling of custom Kraken2 databases, and a simplified graphical user interface for enhanced user experience. Nanometa Live is particularly notable for its capability to run without constant internet or server access once installed, setting it apart from similar tools. It provides a comprehensive view of taxonomic composition and facilitates the detection of user-defined pathogens or other species of interest, catering to both researchers and clinicians. Availability and implementation: Nanometa Live has been implemented as a local web application using the Dash framework with Snakemake handling the data processing. The source code is freely accessible on the GitHub repository at https://github.com/FOI-Bioinformatics/nanometa_live and it is easily installable using Bioconda. It includes containerization support via Docker and Singularity, ensuring ease of use, reproducibility, and portability.