Novel robotic tools used for the detection of faecal shedding of Escherichia coli resistant to critically important antimicrobials in healthy dogs

Escherichia coli recovered from dogs with clinical conditions such as urinary tract infections are often used to assess populations for resistance to critically important antimicrobials (CIAs). Despite the potential importance of such strains, the number of organisms scrutinised is very small and no information is obtained from the preponderance of normal, healthy dogs. Commensal E. coli are a valuable alternative, but little is gained if the number of isolates also remains small. In this work we demonstrate novel technology reliant on laboratory robots to examine the CIA resistance status of millions of commensal E. coli in the faeces of 86 healthy companion dogs. Fluoroquinolone-resistant isolates also underwent phenotypic resistance testing to detect multi-class resistant strains, and multi-locus sequence types and antimicrobial resistance genes identified with whole genome sequencing. Ciprofloxacin resistance was detected in isolates from five (5.8 %) of the healthy dogs, with a high ratio of ciprofloxacin-resistant E. coli to total E. coli being found in three of these animals. Antimicrobial susceptibility testing of the five isolates identified four resistance profiles, with all isolates having multi-class phenotypic resistance to between three and six antimicrobial classes. Genomic analysis confirmed the presence of genes encoding multi-class resistance, with four isolates being resistant to multiple classes. The five isolates belonged to sequence types ST1193 (n = 3) and ST354 (n = 2). All five isolates possessed multiple mutations within the quinolone resistance-determining regions. The predominant sequence type ST1193 is an emerging multidrug resistant E. coli strain harbouring fluoroquinolone resistance, which previously primarily has been detected in clinical samples from dogs. The current study demonstrates the power of robotics for delivering a multi-staged approach based on mass screening to achieve sensitivity and specificity achieved with detailed phenotypic and genotypic characterisation. Based on this experience, future studies can be expanded to yield a much richer understanding of antimicrobial resistance in canines.

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Publication Details

Journal
Veterinary Microbiology
Published
2025-05-16
DOI
https://doi.org/10.1016/j.vetmic.2025.110566
Citations
1
Primary Topic
Bacterial Identification and Susceptibility Testing
Type
article
Field-Weighted Citation Impact
1.32
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article

Novel robotic tools used for the detection of faecal shedding of Escherichia coli resistant to critically important antimicrobials in healthy dogs

D.J. Hampson, David Jordan, Amanda L. Ash, Sam Abraham et al.
1 citations
Veterinary Microbiology
Bacterial Identification and Susceptibility Testing
1.32
article

Novel robotic tools used for the detection of faecal shedding of Escherichia coli resistant to critically important antimicrobials in healthy dogs

D.J. Hampson, David Jordan, Amanda L. Ash, Sam Abraham, Breanna Knight, Alec Truswell
article en
1 citations

Abstract

Escherichia coli recovered from dogs with clinical conditions such as urinary tract infections are often used to assess populations for resistance to critically important antimicrobials (CIAs). Despite the potential importance of such strains, the number of organisms scrutinised is very small and no information is obtained from the preponderance of normal, healthy dogs. Commensal E. coli are a valuable alternative, but little is gained if the number of isolates also remains small. In this work we demonstrate novel technology reliant on laboratory robots to examine the CIA resistance status of millions of commensal E. coli in the faeces of 86 healthy companion dogs. Fluoroquinolone-resistant isolates also underwent phenotypic resistance testing to detect multi-class resistant strains, and multi-locus sequence types and antimicrobial resistance genes identified with whole genome sequencing. Ciprofloxacin resistance was detected in isolates from five (5.8 %) of the healthy dogs, with a high ratio of ciprofloxacin-resistant E. coli to total E. coli being found in three of these animals. Antimicrobial susceptibility testing of the five isolates identified four resistance profiles, with all isolates having multi-class phenotypic resistance to between three and six antimicrobial classes. Genomic analysis confirmed the presence of genes encoding multi-class resistance, with four isolates being resistant to multiple classes. The five isolates belonged to sequence types ST1193 (n = 3) and ST354 (n = 2). All five isolates possessed multiple mutations within the quinolone resistance-determining regions. The predominant sequence type ST1193 is an emerging multidrug resistant E. coli strain harbouring fluoroquinolone resistance, which previously primarily has been detected in clinical samples from dogs. The current study demonstrates the power of robotics for delivering a multi-staged approach based on mass screening to achieve sensitivity and specificity achieved with detailed phenotypic and genotypic characterisation. Based on this experience, future studies can be expanded to yield a much richer understanding of antimicrobial resistance in canines.

Veterinary MicrobiologyVol. 306
Murdoch University (AU)
Zero hunger
Openalex Percentile: Top 20%
Bacterial Identification and Susceptibility Testing
1.32
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