Antimicrobial susceptibility testing and tentative epidemiological cut-off values for Lactobacillaceae family species...

In this work, 170 strains covering 13 species from the Lactobacillaceae family were analyzed to determine minimal inhibitory concentration (MIC) distributions to nine antimicrobial agents, and genes potentially conferring resistance. This allows a proposal of tentative Epidemiological Cut-Offs (ECOFFs) that follows the phylogeny for interpretation of resistance in the 13 species.

The 170 strains originated from different sources, geographical areas, and time periods. MICs for nine antibiotics were determined according to the ISO 10932 standard for lactobacillia and by a modified CLSI-method for Leuconostoc and Pediococcus which ensured sufficient growth. The strains were whole genome sequenced, subtyped by core genome analysis, and assessed for the presence of antibiotic resistance genes using the ResFinder and NCBI AMRFinder databases.

The data provide evidence that antimicrobial susceptibility follows phylogeny instead of fermentation pattern and accordingly, tentative ECOFFs were defined. For some species the tentative ECOFFs for specific antibiotics are above the cut-off values set by the European Food Safety Authority (EFSA) which are primarily defined according to fermentation pattern or at genus level. The increased tolerance for specific antibiotics observed for some species was evaluated to be innate, as only for one strain phenotypic resistance was found to be related to an acquired resistance gene. In general, more data are needed to define ECOFFs and since the number of isolates available for industrial relevant bacterial species are often limited compared to clinically relevant species, it is important; 1) that strains are unambiguously defined at species level and subtyped through core genome analysis, 2) MIC determination are performed by use of a standardized method to define species-specific MIC distributions and 3) that known antimicrobial resistance genes are determined in whole genome sequences to support the MIC determinations.