Organism-specific interpretation of antimicrobial susceptibility testing (AST) data is standard in clinical microbiology, with rules regularly reviewed by expert committees of CLSI and EUCAST. EUCAST also maintains lists of expert rules for some species, including expected (intrinsic) resistance and expected susceptibility phenotypes, to guide clinical labs in deciding which drugs to test and whether/how to report them.
We believe there is a similar need for systematic rules for the organism-specific interpretation of antimicrobial resistance (AMR) genotypes derived from pathogen whole genome sequence (WGS) data.
Current solutions focus on bespoke solutions for specific organisms (e.g. our Kleborate tool for Klebsiella pneumoniae; Pathogenwatch AMR libraries for Salmonella Typhi, Neisseria gonorrhoeae and others; Resfinder 4.0 for E. coli and others; Mykrobe and TBProfiler tools for Mycobacterium tuberculosis), but this complicates bioinformatics analyses and promotes fragmentation rather than consolidation of expertise. AbritAMR offers a potential solution for multiple organisms, but organism-specific interpretation rules are hard-coded in Python and separated from supporting evidence, making the logic difficult for others to curate and update.
This repo outlines a proposal for a simple data structure to store organism-specific rules for the interpretation of AMR genotype data, that could be used to enrich the outputs of standard AMR genotyping tools (such as AMRfinderplus and other tools, with or without hAMRonization) and generate informative genome reports that capture expert knowledge about how core genes contribute to antimicrobial susceptibility.
Example file: organism_specific_rules.tsv
Example file: annotated_gene_report.tsv
This file can be generated by annotating AMRfinder plus output with the above organism-specific rules for Klebsiella pneumoniae, using parse_amrfinder.py:
./parse_amrfinder.py --reports example_data_kleb/*_amrFinderPlusOutput.tsv
--species 'Klebsiella pneumoniae'
--organism_rules organism_specific_rules.tsv
--drug_dictionary example_dict_kleb/Kleb_local_dict.tsv
--output example_annotatedAMRreport.tsv
Example file (PDF): genome_report.pdf
Example file (RTF): genome_report.rtf
This concept was workshopped by members of the Holt lab at London School of Hygiene and Tropical Medicine and further developed in collaboration with Jane Hawkey at Monash University.