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

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.

Assessment of integrated health of human, animal and environment: a holistic and stratified analysis based on global One Health index

“…The speci city of Niger's performance in GOH-IDI deserves more research analysis and discussion. ( 2 [22][23][24]. ( 4)Norway has the best GOH-IDI performance in HICs.…”

Validation of Selective Agars for Detection and Quantification of Escherichia coli Strains Resistant to Critically Important Antimicrobials

“…In contrast to the established approach of AMR surveillance, this enhanced approach is both qualitative and quantitative in nature and is built on the capacity to rapidly identify E. coli colonies on agars for colony enumeration. When combined with robotics, it provides exciting opportunities for up-scaling based on programming and machine learning pathways to allow the identification of E. coli colonies based on colony color for enumeration, with reduced human input and potentially greater accuracy (10). The practical ramifications of this are that more accurate information can be obtained from a greater number of samples, which increases the sensitivity of detecting a given phenotype across a population of animals and herds.…”

“…One way to achieve the scale described above is through large-scale enumeration of resistant E. coli strains from food or fecal samples using a process akin to the agar dilution technique for antimicrobial susceptibility testing (AST). Here, plating of diluted samples onto agars with incorporated antimicrobials is the foundation, which can be further automated using laboratory-based robotics (10). However, conventional solid agars used for AST, such as Mueller-Hinton agar (MHA), or traditional selective agars, such as MacConkey (MAC) agar, are unsuitable because they make it impossible to identify the target bacteria based solely on colony morphology and, especially in the case of MHA, the growth of nontarget bacteria is not adequately suppressed.…”

Antimicrobial Resistance, Genomic, and Public Health Insights into Enterococcus spp. from Australian Cattle

“…The vanB (60.6%) operon was more common than the vanA (38.8%) operon and a small proportion harboring both the vanA and vanB operons (0.6%) (Lee, Pang et al 2020, Coombs, Daley et al 2022. Surveillance of critical resistance in Australian food animals has not yet identified vancomycin resistance in enterococci due to vanA or vanB operons (Lee, Jordan et al 2021). Although a study of cattle six years ago did not find any resistance to highly important antimicrobials (Barlow, McMillan et al 2017) It is prudent to repeat this assessment to ensure emergence of critical resistance is detected promptly.…”