Robotic Antimicrobial Susceptibility Platform (RASP): a next-generation approach to One Health surveillance of antimicrobial resistance

Abstract

Abstract Background Surveillance of antimicrobial resistance (AMR) is critical to reducing its wide-reaching impact. Its reliance on sample size invites solutions to longstanding constraints regarding scalability. A robotic platform (RASP) was developed for high-throughput AMR surveillance in accordance with internationally recognized standards (CLSI and ISO 20776-1:2019) and validated through a series of experiments. Methods Experiment A compared RASP’s ability to achieve consistent MICs with that of a human technician across eight replicates for four Escherichia coli isolates. Experiment B assessed RASP’s agreement with human-performed MICs across 91 E. coli isolates with a diverse range of AMR profiles. Additionally, to demonstrate its real-world applicability, the RASP workflow was then applied to five faecal samples where a minimum of 47 E. coli per animal (239 total) were evaluated using an AMR indexing framework. Results For each drug–rater–isolate combination in Experiment A, there was a clear consensus of the MIC and deviation from the consensus remained within one doubling dilution (the exception being gentamicin at two dilutions). Experiment B revealed a concordance correlation coefficient of 0.9670 (95% CI: 0.9670–0.9670) between the robot- and human-performed MICs. RASP’s application to the five faecal samples highlighted the intra-animal diversity of gut commensal E. coli, identifying between five and nine unique isolate AMR phenotypes per sample. Conclusions While adhering to internationally accepted guidelines, RASP was superior in throughput, cost and data resolution when compared with an experienced human technician. Integration of robotics platforms in the microbiology laboratory is a necessary advancement for future One Health AMR endeavours.