Farming Practice Influences Antimicrobial Resistance Burden of Non-Aureus Staphylococci in Pig Husbandries.
Manonmani SoundararajanGabriella MarincolaOlivia LiongTessa MarciniakFreya D R WenckerFranka HofmannHannah SchollenbruchIris KobuschSabrina LinnemannSilver A WolfMustafa HelalTorsten SemmlerBirgit WaltherChristoph SchoenJustin NyasingaGunturu RevathiMarc BoelhauveWilma ZiebuhrPublished in: Microorganisms (2022)
Non-aureus staphylococci (NAS) are ubiquitous bacteria in livestock-associated environments where they may act as reservoirs of antimicrobial resistance (AMR) genes for pathogens such as Staphylococcus aureus . Here, we tested whether housing conditions in pig farms could influence the overall AMR-NAS burden. Two hundred and forty porcine commensal and environmental NAS isolates from three different farm types (conventional, alternative, and organic) were tested for phenotypic antimicrobial susceptibility and subjected to whole genome sequencing. Genomic data were analysed regarding species identity and AMR gene carriage. Seventeen different NAS species were identified across all farm types. In contrast to conventional farms, no AMR genes were detectable towards methicillin, aminoglycosides, and phenicols in organic farms. Additionally, AMR genes to macrolides and tetracycline were rare among NAS in organic farms, while such genes were common in conventional husbandries. No differences in AMR detection existed between farm types regarding fosfomycin, lincosamides, fusidic acid, and heavy metal resistance gene presence. The combined data show that husbandry conditions influence the occurrence of resistant and multidrug-resistant bacteria in livestock, suggesting that changing husbandry practices may be an appropriate means of limiting the spread of AMR bacteria on farms.
Keyphrases
- antimicrobial resistance
- genome wide
- genome wide identification
- staphylococcus aureus
- multidrug resistant
- genome wide analysis
- copy number
- bioinformatics analysis
- heavy metals
- primary care
- healthcare
- dna methylation
- transcription factor
- electronic health record
- risk assessment
- big data
- water soluble
- computed tomography
- risk factors
- human health
- drug resistant
- gene expression
- pseudomonas aeruginosa
- quality improvement
- acinetobacter baumannii
- deep learning
- loop mediated isothermal amplification
- artificial intelligence
- contrast enhanced
- health risk
- klebsiella pneumoniae