Legionella spp. are widespread bacteria in aquatic environments with a growing impact on human health. Between the 61 species, Legionella pneumophila is the most prevalent in human diseases; on the contrary, Legionella non-pneumophila species are less detected in clinical diagnosis or during environmental surveillance due to their slow growth in culture and the absence of specific and rapid diagnostic/analytical tools. Reliable and rapid isolate identification is essential to estimate the source of infection, to undertake containment measures, and to determine clinical treatment. Matrix-assisted laser desorption ionization–time-of-flight mass spectrometry (MALDI–TOF MS), since its introduction into the routine diagnostics of laboratories, represents a widely accepted method for the identification of different bacteria species, described in a few studies on the Legionella clinical and environmental surveillance. The focus of this study was the improvement of MALDI–TOF MS on Legionella non-pneumophila species collected during Legionella nosocomial and community surveillance. Comparative analysis with cultural and mip-gene sequencing results was performed. Moreover, a phylogenetic analysis was carried out to estimate the correlations amongst isolates. MALDI–TOF MS achieved correct species-level identification for 45.0% of the isolates belonging to the Legionella anisa, Legionella rubrilucens, Legionella feeleii, and Legionella jordanis species, displaying a high concordance with the mip-gene sequencing results. In contrast, less reliable identification was found for the remaining 55.0% of the isolates, corresponding to the samples belonging to species not yet included in the database. The phylogenetic analysis showed relevant differences inside the species, regruped in three main clades; among the Legionella anisa clade, a subclade with a divergence of 3.3% from the main clade was observed. Moreover, one isolate, identified as Legionella quinlivanii, displayed a divergence of 3.8% from the corresponding reference strain. However, these findings require supplementary investigation. The results encourage the implementation of MALDI–TOF MS in routine diagnostics and environmental Legionella surveillance, as it displays a reliable and faster identification at the species level, as well as the potential to identify species that are not yet included in the database. Moreover, phylogenetic analysis is a relevant approach to correlate the isolates and to track their spread, especially in unconventional reservoirs, where Legionella prevention is still underestimated.
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