Shani, Noam; Oberhaensli, Simone; Berthoud, Hélène; Schmidt, Remo S.; Bachmann, Hans-Peter (2021). Antimicrobial Susceptibility of Lactobacillus delbrueckii subsp. lactis from Milk Products and Other Habitats. Foods, 10(12) MDPI 10.3390/foods10123145
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As components of many cheese starter cultures, strains of Lactobacillus delbrueckii subsp. lactis (LDL) must be tested for their antimicrobial susceptibility to avoid the potential horizontal transfer of antibiotic resistance (ABR) determinants in the human body or in the environment. To this end, a phenotypic test, as well as a screening for antibiotic resistance genes (ARGs) in genome sequences, is commonly performed. Historically, microbiological cutoffs (MCs), which are used to classify strains as either ‘sensitive’ or ‘resistant’ based on the minimal inhibitory concentrations (MICs) of a range of clinically-relevant antibiotics, have been defined for the whole group of the obligate homofermentative lactobacilli, which includes LDL among many other species. This often leads to inaccuracies in the appreciation of the ABR status of tested LDL strains and to false positive results. To define more accurate MCs for LDL, we analyzed the MIC profiles of strains originating from various habitats by using the broth microdilution method. These strains’ genomes were sequenced and used to complement our analysis involving a search for ARGs, as well as to assess the phylogenetic proximity between strains. Of LDL strains, 52.1% displayed MICs that were higher than the defined MCs for kanamycin, 9.9% for chloramphenicol, and 5.6% for tetracycline, but no ARG was conclusively detected. On the other hand, all strains displayed MICs below the defined MCs for ampicillin, gentamycin, erythromycin, and clindamycin. Considering our results, we propose the adaptation of the MCs for six of the tested clinically-relevant antibiotics to improve the accuracy of phenotypic antibiotic testing.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
08 Faculty of Science > Department of Biology > Bioinformatics and Computational Biology > Bioinformatics 08 Faculty of Science > Department of Biology > Bioinformatics and Computational Biology > Computational Biology 08 Faculty of Science > Department of Biology > Bioinformatics and Computational Biology |
UniBE Contributor: |
Oberhänsli, Simone |
Subjects: |
500 Science > 570 Life sciences; biology |
ISSN: |
2304-8158 |
Publisher: |
MDPI |
Language: |
English |
Submitter: |
Jolanda Paganoni Zurbrügg |
Date Deposited: |
11 May 2023 14:04 |
Last Modified: |
11 May 2023 14:14 |
Publisher DOI: |
10.3390/foods10123145 |
PubMed ID: |
34945696 |
BORIS DOI: |
10.48350/182471 |
URI: |
https://boris.unibe.ch/id/eprint/182471 |
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