Establishing Genotypic Cutoff Values To Measure Antimicrobial Resistance in Salmonella.

Area of Science:

• Microbiology
• Genomics
• Antimicrobial Resistance

Background:

• Whole-genome sequencing (WGS) aids in identifying antimicrobial resistance (AMR) mechanisms.
• Previous research shows strong links between phenotypic resistance and known resistance genes.
• A large-scale correlation between resistance genotypes and specific minimum inhibitory concentrations (MICs) has been lacking.

Purpose of the Study:

• To assess the correlation between resistance genotypes and specific MICs in Salmonella.
• To establish genotypic cutoff values (GCVs) for 13 antimicrobials against Salmonella.
• To explore the potential of WGS data for predicting MICs.

Main Methods:

• Antimicrobial susceptibility testing and WGS were performed on 1,738 nontyphoidal Salmonella strains.
• Over 20,000 MICs were correlated with identified resistance determinants.
• Genotypic cutoff values (GCVs) were defined as the highest MIC in isolates lacking known acquired resistance mechanisms.

Main Results:

• Established GCVs for 13 antimicrobials against Salmonella, distinct from epidemiological cutoff values (ECVs).
• Observed distinct MIC distributions for different resistance gene alleles, even for drugs like ciprofloxacin and tetracycline.
• Demonstrated a strong correlation between genotypic information and phenotypic resistance levels.

Conclusions:

• GCVs provide a genetically informed standard for antimicrobial resistance assessment in Salmonella.
• WGS data holds significant potential for predicting specific MIC values, advancing AMR surveillance.
• This approach refines the understanding of genotype-phenotype relationships in antimicrobial resistance.