Clinical considerations on antimicrobial resistance potential of complex microbiological samples

Area of Science:

• Microbiology
• Genomics
• Public Health

Background:

• Antimicrobial resistance (AMR) is a critical global health challenge.
• Effective treatment relies on understanding pathogen antibiotic susceptibility.
• Current methods analyze only a fraction of bacteria, potentially missing resistance mechanisms.

Purpose of the Study:

• To assess the concordance between genotypic antimicrobial resistance genes (ARGs) and phenotypic antimicrobial resistance (AMR).
• To evaluate the interpretability of antimicrobial resistance potential (AMRP) derived from metagenomic data.
• To determine the utility of metagenomic ARG analysis for guiding antibiotic selection in complex microbial samples.

Main Methods:

• Analysis of phenotypic AMR data and genotypic ARGs from 574 *Escherichia coli* strains across five studies.
• Investigated concordance rates for predicting resistance and susceptibility.
• Applied metagenomic ARG analysis to a canine external otitis sample to illustrate AMRP utility.

Main Results:

• Genotypic ARG detection predicted phenotypic resistance with 90% probability for 44% of antibiotics.
• Genotypic ARG detection predicted phenotypic susceptibility with 90% probability for 92% of antibiotics.
• Metagenomic ARG analysis achieved 90% confidence in phenotypic prediction for 67% of antibiotics.

Conclusions:

• Metagenomic ARG analysis provides a reliable method for assessing antimicrobial resistance potential (AMRP).
• AMRP data can guide the selection of effective antibiotics, especially in complex polymicrobial infections.
• This approach enhances targeted antimicrobial therapy and combats AMR spread.