Objectives Antimicrobial resistance (AMR) to critically important antimicrobials (CIAs) amongst Gram-negative bacteria can feasibly be transferred amongst wildlife, humans and domestic animals. This study investigated the ecology, epidemiology and origins of CIA-resistant Escherichia coli carried by Australian silver gulls (Chroicocephalus novaehollandiae), a gregarious avian wildlife species that is a common inhabitant of coastal areas with high levels of human contact. Methods Sampling locations were widely dispersed around the perimeter of the Australian continent, with sites separated by up to 3500 km. WGS was used to study the diversity and molecular characteristics of resistant isolates to ascertain their epidemiological origin. Results Investigation of 562 faecal samples revealed widespread occurrence of extended-spectrum cephalosporin-resistant (21.7%) and fluoroquinolone-resistant (23.8%) E. coli. Genome sequencing revealed that CIA-resistant E. coli isolates (n = 284) from gulls predominantly belonged to human-associated extra-intestinal pathogenic E. coli (ExPEC) clones, including ST131 (17%), ST10 (8%), ST1193 (6%), ST69 (5%) and ST38 (4%). Genomic analysis revealed that gulls carry pandemic ExPEC-ST131 clades (O25:H4 H30-R and H30-Rx) and globally emerging fluoroquinolone-resistant ST1193 identified among humans worldwide. Comparative analysis revealed that ST131 and ST1193 isolates from gulls overlapped extensively with human clinical isolates from Australia and overseas. The present study also detected single isolates of carbapenem-resistant E. coli (ST410-blaOXA-48) and colistin-resistant E. coli (ST345-mcr-1). Conclusions The carriage of diverse CIA-resistant E. coli clones that strongly resemble pathogenic clones from humans suggests that gulls can act as ecological sponges indiscriminately accumulating and disseminating CIA-resistant bacteria over vast distances.

In a structured survey of all major chicken-meat producers in Australia, we investigated the antimicrobial resistance (AMR) and genomic characteristics of Campylobacter jejuni (n = 108) and C. coli (n = 96) from cecal samples of chickens at slaughter (n = 200). The majority of the C. jejuni (63%) and C. coli (86.5%) samples were susceptible to all antimicrobials. Fluoroquinolone resistance was detected among both C. jejuni (14.8%) and C. coli (5.2%), although this only included three sequence types (STs) and one ST, respectively. Multidrug resistance among strains of C. jejuni (0.9%) and C. coli (4.1%) was rare, and fluoroquinolone resistance, when present, was never accompanied by resistance to any other agent. Comparative genome analysis demonstrated that Australian isolates were found dispersed on different branches/clusters within the international collection. The major fluoroquinolone-resistant STs of C. jejuni (ST7323, ST2083, and ST2343) and C. coli (ST860) present in Australian chickens were similar to those of international isolates and have been reported previously in humans and animals overseas. The detection of a subpopulation of Campylobacter isolates exclusively resistant to fluoroquinolone was unexpected since most critically important antimicrobials such as fluoroquinolones are excluded from use in Australian livestock. A number of factors, including the low level of resistance to other antimicrobials, the absence of fluoroquinolone use, the adoption of measures for preventing spread of contagion between flocks, and particularly the genomic identities of isolates, all point to humans, pest species, or wild birds as being the most plausible source of organisms. This study also demonstrates the need for vigilance in the form of surveillance for AMR based on robust sampling to manage AMR risks in the food chain. IMPORTANCE Campylobacter is one of the most common causes of gastroenteritis in humans, with infections frequently resulting from exposure to undercooked poultry products. Although human illness is typically self-limiting, a minority of cases do require antimicrobial therapy. Ensuring that Campylobacter originating from meat chickens does not acquire resistance to fluoroquinolones is therefore a valuable outcome for public health. Australia has never legalized the use of fluoroquinolones in commercial chickens and until now fluoroquinolone-resistant Campylobacter has not been detected in the Australian poultry. This structured survey of meat chickens derived from all major Australian producers describes the unexpected emergence of fluoroquinolone resistance in Campylobacter jejuni and C. coli. Genetic characterization suggests that these isolates may have evolved outside the Australian poultry sector and were introduced into poultry by humans, pest species, or wild birds. The findings dramatically underline the critical role of biosecurity in the overall fight against antimicrobial resistance.

Highlights: 3 addition, we show that ST1 clones carry a constellation of putative virulence genes not present in other Australian STs.

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.

Background A key component to control of antimicrobial resistance (AMR) is the surveillance of food animals. Currently, national programmes test only limited isolates per animal species per year, an approach tacitly assuming that heterogeneity of AMR across animal populations is negligible. If the latter assumption is incorrect then the risk to humans from AMR in the food chain is underestimated. Objectives To demonstrate the extent of phenotypic and genetic heterogeneity of Escherichia coli in swine to assess the need for improved protocols for AMR surveillance in food animals. Methods Eight E. coli isolates were obtained from each of 10 pigs on each of 10 farms. For these 800 isolates, AMR profiles (MIC estimates for six drugs) and PCR-based fingerprinting analysis were performed and used to select a subset (n = 151) for WGS. Results Heterogeneity in the phenotypic AMR traits of E. coli was observed in 89% of pigs, with 58% of pigs harbouring three or more distinct phenotypes. Similarly, 94% of pigs harboured two or more distinct PCR-fingerprinting profiles. Farm-level heterogeneity was detected, with ciprofloxacin resistance detected in only 60% of pigs from a single farm. Furthermore, 58 STs were identified, with the dominant STs being ST10, ST101, ST542 and ST641. Conclusions Phenotypic and genotypic heterogeneity of AMR traits in bacteria from animal populations are real phenomena posing a barrier to correct interpretation of data from AMR surveillance. Evolution towards a more in-depth sampling model is needed to account for heterogeneity and increase the reliability of inferences.