An investigation of the transmission of Actinobacillus pleuropneumoniae within vertically integrated systems using whole genome sequencing.

Actinobacillus pleuropneumoniae (APP) causes significant economic losses to the swine industry. Antibiotic treatment can be challenging due to its clinical urgency and the turnover of antimicrobial susceptibility results from the diagnostic laboratory. The aim of this study was to evaluate the vertical transmission of APP within integrated systems as a criterion for optimising antimicrobial treatment in the field, using whole genome sequencing (WGS). Additionally, the genetic variability of Spanish APP isolates has been assessed to decipher antimicrobial resistance (AMR) determinants, toxin presence, serotype, and phenotype/genotype concordance of AMR. A total of 169 isolates from clinical cases of porcine pleuropneumonia with known antimicrobial susceptibility profiles were sequenced. Additionally, 48 NCBI assemblies were included to perform a phylogenetic analysis. Phylogenetic analysis revealed high association between phylogenetic clusters, serotypes, and presence of toxins that are associated within vertically integrated systems by its epidemiological link. Concordance between presence of AMR determinants (genotype) vs in-vitro antimicrobial susceptibility pattern (phenotype) was acceptable for amoxicillin, florfenicol, oxytetracycline, and enrofloxacin using epidemiological cut-off values (ECOFFs), but low concordance was observed for doxycycline and trimethoprim-sulfamethoxazole (T/S). On the other hand, using CLSI clinical breakpoints (CBPs), concordance was acceptable for florfenicol and enrofloxacin and not evaluated for doxycycline, oxytetracycline, trimethoprim-sulfamethoxazole (T/S), and amoxicillin because no CBP are available for them. Finally, WGS has demonstrated the clonality between isolates that shared a common origin (grandmother's farm) and resistance phenotype, suggesting vertical transmission of this pathogen and supporting the use of the epidemiological approach as a good criterion to optimise the antimicrobial use.

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