Established models of surveillance for AMR in livestock typically have a low sampling intensity, which creates a tremendous barrier to understanding the variation of resistance among animal and food enterprises. However, developments in laboratory robotics now make it possible to rapidly and affordably process large volumes of samples.
Success in the global fight against antimicrobial resistance (AMR) is likely to improve if surveillance can be performed more rapidly, affordably and on a larger scale. An approach based on robotics and agars incorporated with antimicrobials has enormous potential to achieve this. However, there is a need to identify the combinations of selective agars and key antimicrobials yielding the most accurate counts of susceptible and resistant organisms. A series of designed experiments involving 1,202 plates identified the best candidate-combinations from six commercially available agars and five antimicrobials using 18 Escherichia coli strains as either pure cultures or inoculums within faeces. The effect of various design factors on colony counts were analysed in generalised linear models. Without antimicrobials, Brilliance™ E. coli (Brilliance) and CHROMagar™ ECC (CHROMagar) agars yielded 28.9% and 23.5% more colonies than MacConkey agar. The order of superiority of agars remained unchanged when faecal samples with and without spiking of resistant E. coli were inoculated onto agars with or without specific antimicrobials. When incorporating antimicrobials at varying concentrations, it was revealed that ampicillin, tetracycline and ciprofloxacin are suitable for incorporation into Brilliance and CHROMagar agars at all defined concentrations. Gentamicin was only suitable for incorporation at 8 and 16 µg/mL while ceftiofur was only suitable at 1 µg/mL. CHROMagar™ ESBL agar supported growth of a wider diversity of extended-spectrum cephalosporin-resistant E. coli. The findings demonstrate the potential for combining robotics with agars to deliver AMR surveillance on a vast scale with greater sensitivity of detection and strategic relevance.
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