Potential of ESBL-producing Escherichia coli selection in bovine feces after intramammary administration of first generation cephalosporins using in vitro experiments

Abstract

Selection and spread of Extended Spectrum Beta-Lactamase (ESBL) -producing Enterobacteriaceae within animal production systems and potential spillover to humans is a major concern. Intramammary treatment of dairy cows with first-generation cephalosporins is a common practice and potentially selects for ESBL-producing Enterobacteriaceae, although it is unknown whether this really occurs in the bovine fecal environment. We aimed to study the potential effects of intramammary application of cephapirin (CP) and cefalonium (CL) to select for ESBL-producing Escherichia coli in the intestinal content of treated dairy cows and in manure slurry, using in vitro competition experiments with ESBL and non-ESBL E. coli isolates. No selection of ESBL-producing E. coli was observed at or below concentrations of 0.8 µg/ml and 4.0 µg/ml in bovine feces for CP and CL, respectively, and at or below 8.0 µg/ml and 4.0 µg/ml, respectively, in manure slurry. We calculated that the maximum concentration of CP and CL after intramammary treatment with commercial products will not exceed 0.29 µg/ml in feces and 0.03 µg/ml in manure slurry. Therefore, the results of this study did not find evidence supporting the selection of ESBL-producing E. coli in bovine feces or in manure slurry after intramammary use of commercial CP or CL-containing products.

Towards facilitated interpretation of shotgun metagenomics long-read sequencing data analyzed with KMA for the detection of bacterial pathogens and their antimicrobial resistance genes

“…The open-source bioinformatics tool k -mer alignment (KMA) is a fast read mapper using k -mer alignment and has been proven to be more performant in accuracy and speed in comparison with other classifiers ( Clausen et al, 2018 ; Marcelino et al, 2020 ). Notably, it has been widely used in studies for metataxonomics (16S/18S rRNA) and AMR gene identification from metagenomics samples sequenced with short-read technologies ( Sturød et al, 2020 ; Horie et al, 2021 ; Speksnijder et al, 2022 ; Stege et al, 2022 ). Using a scoring scheme named ConClave, KMA is able to overcome the difficulties encountered when using a redundant database, such as SILVA for metataxonomics and ResFinder for AMR detection ( Clausen et al, 2018 ).…”