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Legionella surveillance plays a significant role not only to prevent the risk of infection but also to study the ecology of isolates, their characteristics, and how their prevalence changes in the environment. The difficulty in Legionella isolation, identification, and typing results in a low notification rate; therefore, human infection is still underestimated. In addition, during Legionella surveillance, the special attention given to Legionella pneumophila leads to an underestimation of the prevalence and risk of infection for other species. This study describes the workflow performed during environmental Legionella surveillance that resulted in the isolation of two strains, named 8cVS16 and 9fVS26, associated with the genus Legionella. Traditional and novel approaches such as standard culture technique, MALDI-TOF MS, gene sequencing, and whole-genome sequencing (WGS) analysis were combined to demonstrate that isolates belong to a novel species. The strain characteristics, the differences between macrophage infectivity potential (mip), RNA polymerase β subunit (rpoB), and reference gene sequences, the average nucleotide identity (ANI) of 90.4%, and the DNA–DNA digital hybridization (dDDH) analysis of 43% demonstrate that these isolates belong to a new Legionella species. The finding suggests that, during the culture technique, special attention should be paid to the characteristics of the isolates that are less associated with the Legionella genus in order to investigate the differences found using more sensitive methods. The characterization of the two newly discovered isolates based on morphological, biochemical, and microscopic characteristics is currently underway and will be described in another future study.

A very rare case of pulmonary Klebsiella pneumoniae-Legionella pneumophila coinfection in a double kidney transplanted man affected by the chronic renal disease is described. Cases of Legionnaires' disease with an incubation period of 14 days have rarely been documented. Despite the long period of hospitalization, typing of clinical and environmental L. pneumophila strains demonstrated that the patient's home water distribution system was the source of infection, highlighting that Legionella house contamination can be a hidden risk, especially for immune-compromised people.

Legionella spp. are Gram-negative bacteria that inhabit freshwater environments representing a serious risk for human health. Legionella pneumophila (Lp) is the species most frequently responsible for a severe pneumonia known as Legionnaires' disease. Lp consists of 15 serogroups (Sgs), usually identified by monoclonal or polyclonal antibodies. With regard to Lp serogrouping, it is well known that phenotyping methods do not have a sufficiently high discriminating power, while genotypic methods although very effective, are expensive and laborious. Recently, mass spectrometry and infrared spectroscopy have proved to be rapid and successful approaches for the microbial identification and typing. Different biomolecules (e.g., lipopolysaccharides) adsorb infrared radiation originating from a specific microbial fingerprint. The development of a classification system based on the intra-species identification features allows a rapid and reliable typing of strains for diagnostic and epidemiological purposes. The aim of the study was the evaluation of Fourier Transform Infrared Spectroscopy using the IR Biotyper® system (Bruker Daltonik, Germany) for the identification of Lp at the serogroup (Sg) level for diagnostic purposes as well as in outbreak events. A large dataset of Lp isolates (n = 133) and ATCC reference strains representing the 15 Lp serogroups were included. The discriminatory power of the instrument's classifier, was tested by Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). All isolates were classified as follows: 12/133 (9.0%) as Lp Sg1 and 115/133 (86.5%) as Lp Sg 2–15 (including both ATCC and environmental Lp serogroup). Moreover, a mis-classification for 2/133 (1.5%) isolates of Lp Sg 2–15 that returned as Lp Sg1 was observed, and 4/133 (3.0%) isolates were not classified. An accuracy of 95.49% and an error rate of 4.51% were calculated. IR Biotyper® is able provide a quick and cost-effective reliable Lp classification with advantages compared with agglutination tests that show ambiguous and unspecific results. Further studies including a larger number of isolates could be useful to implement the classifier obtaining a robust and reliable tool for the routine Lp serogrouping. IR Biotyper® could be a powerful and easy-to-use tool to identify Lp Sgs, especially during cluster/outbreak investigations, to trace the source of the infection and promptly adopt preventive and control strategies.

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.