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.

Legionella species distribution in the Emilia-Romagna region, involving hospital (H) and community (C) environments, was conducted. Legionella culture, agglutination test, and mip-gene sequencing were applied on 240 isolates. The analysis showed a higher prevalence of non-Legionellapneumophila (n-Lp) species (84.1%) compared with L. pneumophila (Lp) (15.9%), with a higher frequency of n-Lp with respect to Lp species in both environments (77.6% and 96.4%, in H and C, respectively). The Shannon index showed a significant difference in Legionella distribution (p = 0.00017), with a significant abundance of Lp in the H compared with C environment (p = 0.00028). The continuous disinfection treatment in H could contribute to adaptive survival of the Lp species. Phylogenetic analysis revealed a conservative clade distribution between H and C: L. feeleii clade with three subclades in C and the Lp clade with five subclades in H and two in C, respectively. Our findings suggest the importance of Legionella surveillance both in H and C, with a focus on n-Lp species less connected to human disease. The Legionella prevalence and diversity found here indicate that geographical and temporal isolate evolution should be considered during surveillance, particularly in the light of global warming and changes in population risk factors.

Legionella spp. are a widely spread bacteria that cause a fatal form of pneumonia. While traditional laboratory techniques have provided valuable systems for Legionella pneumophila identification, the amplification of the mip gene has been recognized as the only useful tool for Legionella non- pneumophila species identification both in clinical and environmental samples.

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In this study, we aimed to associate the molecular typing of Legionella isolates with a culture technique during routine Legionella hospital environmental surveillance in hot water distribution systems (HWDSs) to develop a risk map able to be used to prevent nosocomial infections and formulate appropriate preventive measures. Hot water samples were cultured according to ISO 11731:2017. The isolates were serotyped using an agglutination test and genotyped by sequence-based typing (SBT) for Legionella pneumophila or macrophage infectivity potentiator (mip) gene sequencing for non-pneumophila Legionella species. The isolates’ relationship was phylogenetically analyzed. The Legionella distribution and level of contamination were studied in relation to temperature and disinfectant residues. The culture technique detected 62.21% of Legionella positive samples, characterized by L. pneumophila serogroup 1, Legionella non-pneumophila, or both simultaneously. The SBT assigned two sequence types (STs): ST1, the most prevalent in Italy, and ST104, which had never been isolated before. The mip gene sequencing detected L. anisa and L. rubrilucens. The phylogenetic analysis showed distinct clusters for each species. The distribution of Legionella isolates showed significant differences between buildings, with a negative correlation between the measured level of contamination, disinfectant, and temperature. The Legionella molecular approach introduced in HWDSs environmental surveillance permits (i) a risk map to be outlined that can help formulate appropriate disinfection strategies and (ii) rapid epidemiological investigations to quickly identify the source of Legionella infections.