The antimicrobial resistome in relation to antimicrobial use and biosecurity in pig farming, a metagenome-wide association study in nine European countries.
Van Gompel L, Luiken REC, Sarrazin S, Munk P, Knudsen BE, Hansen RB, Bossers A, Aarestrup FM, Dewulf J, Wagenaar JA, Mevius DJ, Schmitt H, Heederik DJJ, Dorado-García A, Smit LAM
J Antimicrob Chemother. Jan 2019. doi: 10.1093/jac/dky518
COMMENT: Antimicrobial resistance is a global public health problem. It is known that veterinary antimicrobial use (AMU) promotes antimicrobial resistance (AMR) in animals, and AMR can be transmitted from animals to humans. The resistome is the term proposed to designate the compendium of antiobiotic resistence genes in microorganisms and microbial populations, the mobile resistome refers to those genes transferred horizontally (ARGs). This study of the mobile resistome improve the knowledge of the AMR epidemiology.
Previous studies found positive associations between country-level antimicrobial use (AMU) in pigs and the pig resistome. This study is build upon a previous study, now including detailed farm-level data, using a shotgun metagenomic approach to investigate associations between the pig resistome and farm-level risk factors.
The univariate meta-analysis showed a positive association between total AMU during the fattening phase and total ARG (AMR class clustering) in pigs.
Among the main determinants for AMR, we found positive corresponding AMU-ARG associations for macrolides and tetracyclines.
We also found positive associations between non-corresponding AMU-ARG classes such as β-lactam use (penicillins, aminopenicillins and cephalosporins) and amphenicol resistance.
An overview of the top 10 ARG clusters (90% identity level) within the main ARG classes identified in the meta-analysis is presented.
Our study is (as far as we are aware) unique in combining a large resistome dataset with risk factors. We established associations between ARGs and farming practices, which provides more insight into the biological pathways of resistance.
Our approach enabled the evaluation of a large set of antimicrobial classes in parallel while checking for cross- and co-resistances (~2000 associations within nine countries).