Legionella pneumophila causes human lung infections resulting in severe pneumonia. High-resolution genotyping of L. pneumophila isolates can be achieved by multiple-locus variable-number tandem-repeat analysis (MLVA-8). Legionella infections in humans occur as a result of inhalation of bacteria-containing aerosols, thus, our aim was to study the antimicrobial susceptibilities of different MLVA-8 genotypes to ten commonly used antimicrobial agents in legionellosis therapy. Epidemiological cut-off values were determined for all antibiotics. Significant differences were found between the antimicrobial agents’ susceptibilities of the three studied environmental genotypes (Gt4, Gt6, and Gt15). Each genotype exhibited a significantly different susceptibility profile, with Gt4 strains (Sequence Type 1) significantly more resistant towards most studied antimicrobial agents. In contrast, Gt6 strains (also Sequence Type 1) were more susceptible to six of the ten studied antimicrobial agents compared to the other genotypes. Our findings show that environmental strains isolated from adjacent points of the same water system, exhibit distinct antimicrobial resistance profiles. These differences highlight the importance of susceptibility testing of Legionella strains. In Israel, the most extensively used macrolide for pneumonia is azithromycin. Our results point at the fact that clarithromycin (another macrolide) and trimethoprim with sulfamethoxazole (SXT) were the most effective antimicrobial agents towards L. pneumophila strains. Moreover, legionellosis can be caused by multiple L. pneumophila genotypes, thus, the treatment approach should be the use of combined antibiotic therapy. Further studies are needed to evaluate specific antimicrobial combinations for legionellosis therapy.
|State||Published - 1 Dec 2019|
Bibliographical noteFunding Information:
This study was supported by a grant from the German Research Foundation (Deutsche Forschungsgemeinschaft DFG grant GZ: HO 930/5-2) and by the joint Indian University Grant Commission and Israel Science Foundation (UGC-ISF grant: 2728/17). Special thanks to Marina Pecellin and Leila Kahlisch for assistance and fruitful discussions regarding the MLVA analysis.
© 2019, The Author(s).
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