Association of farm-related factors with characteristics profiles of extended-spectrum β-lactamase- / plasmid-mediated AmpC β-lactamase-producing Escherichia coli isolates from German livestock farms

Abstract

Resistance to β-lactam antibiotics, including third-generation cephalosporins, is of major concern for animal and human health. In this study, extended-spectrum β-lactamase (ESBL) / plasmid-mediated AmpC (pAmpC) β-lactamase -producing Escherichia coli isolates from German livestock farms were characterised and associations of these isolate characteristics with farm-related factors were investigated across different types of livestock.A total of 469 isolates originating from 150 farms (34 broiler farms, 38 fattening pig farms, 43 dairy cattle farms, 35 beef cattle farms) was included in the analyses. ESBL-gene family, phylogroup and phenotypic antimicrobial susceptibility for several antimicrobial agents were determined. This data was used to define different profiles characterising the isolates. Multivariate analyses using a distance-based non-parametric approach were performed to investigate associations between the profiles of the isolates and farm-related factors (e.g. management, husbandry, and environment of the farms).Co-occurrence of ESBL-gene families were not found in any of the isolates analysed. Sixty-eight percent of the isolates carried blaCTX-M variant genes. The frequency of phylogroups was as follows: A (55%), B1 (35%), D (17%) and B2 (3%). The most frequent phenotypic non-wildtype profile was non-wildtype status of solely cefepime (27%). Profiles of isolates from broilers differed substantially from those of other isolates. Associations between farm-related factors and characteristics profiles differed, depending on the isolate characteristics included in the analyses. Some factors describing the farm environment, like waterfowl in the surrounding of the farm, were associated with all tested profiles.The epidemiological method applied defines distances between isolates on basis of isolate characteristics data and is capable of analysing associations between isolate characteristics and epidemiological factors. As additional data, such as plasmid characteristics, gene type, or sequence information could be included in future studies, the method is suitable to identify points of action to reduce the occurrence of antimicrobial resistant bacteria.