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An advanced tool designed to identify antimicrobial resistance (AMR) genes, resistance-associated mutations, and ribosomal RNA (rRNA) gene mutations across approximately 18,000 bacterial species is available for free use online. The developers reported on the AmrProfiler web server in Nucleic Acids Research.

“By integrating and refining data from established databases, it provides a robust framework for AMR analysis,” wrote corresponding author Anargyros Skoulakis, MD, MSc, and colleagues.

AmrProfiler accepts genome assemblies in various formats and offers a trio of functions, the authors explained. The tool identifies AMR genes with thresholds specified by the user for identity, coverage, and protein start sites. It detects mutations in resistance-associated core genes and highlights mutations in nearby regions and related species. Moreover, it detects rRNA gene copies and signals corresponding mutations by comparing the reference genome.

“AmrProfiler is the first to systematically report mutations in rRNA genes, offering in-depth analysis of rRNA copy numbers and mutations—key for identifying potential rRNA-associated resistance mechanisms,” the authors wrote.

Genetically characterizing microbial strains is essential for a comprehensive view of AMR mechanisms. Clarifying the genetic basis of resistance and transmission helps with strategy development in surveillance, containment, and therapeutic intervention amid rapid AMR expansion.

The curated AmrProfiler encompasses 7600 unique AMR gene entries and more than 4300 resistance-associated mutations, according to the paper.

In validation testing with Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, and Staphylococcus epidermidis species, the tool correctly identified AMR genes and mutations reported by other tools. Moreover, it highlighted additional resistance markers and mutations not previously detected.

“Although not all reported mutations may be functionally relevant, AmrProfiler highlights those located near known resistance-associated sites—both within the selected species and across others—helping users distinguish between likely impactful and potentially non-informative mutations,” the authors wrote, “and enabling the discovery of novel resistance markers.”

The current version of AmrProfiler is specifically designed for AMR genes and will not detect genes associated with disinfectant resistance.

“In conclusion, AmrProfiler is an upgraded tool that detects all known genes and mutations associated with AMR, and is very friendly to non-familiar users of bioinformatics analysis,” the authors wrote.

AmrProfiler is available without registration or login at https://dianalab.e-ce.uth.gr/amrprofiler.