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This study developed and validated a method, based on the coupling of Fourier-transform infrared spectroscopy (FT-IR) and machine learning, for the automated serotyping of Legionella pneumophila serogroup 1, Legionella pneumophila serogroups 2-15 as well as their successful discrimination from Legionella non-pneumophila. As Legionella presents significant intra- and inter-species heterogeneities, careful data validation strategies were applied to minimize late-stage performance variations of the method across a large microbial population. A total of 244 isolates were analyzed. In details, the method was validated with a multi-centric approach with isolates from Italian thermal and drinking water (n = 82) as well as with samples from German, Italian, French, and British collections (n = 162). Specifically, robustness of the method was verified over the time-span of 1 year with multiple operators and two different FT-IR instruments located in Italy and Germany. Moreover, different production procedures for the solid culture medium (in-house or commercial) and different culture conditions (with and without 2.5% CO2) were tested. The method achieved an overall accuracy of 100, 98.5, and 93.9% on the Italian test set of Legionella, an independent batch of Legionella from multiple European culture collections, and an extra set of rare Legionella non-pneumophila, respectively.

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Understanding the actual distribution of different Legionella species in water networks would help prevent outbreaks. Culture investigations followed by serological agglutination tests, with poly/monovalent antisera, still represent the gold standard for isolation and identification of Legionella strains. However, also MALDI-TOF and mip-gene sequencing are currently used. This study was conducted to genetically correlate strains of Legionella non pneumophila (L-np) isolated during environmental surveillance comparing different molecular techniques. Overall, 346 water samples were collected from the water system of four pavilions located in a hospital of the Apulia Region of Italy. Strains isolated from the samples were then identified by serological tests, MALDI-TOF, and mip-gene sequencing. Overall, 24.9% of water samples were positive for Legionella, among which the majority were Legionella pneumophila (Lpn) 1 (52.3%), followed by Lpn2-15 (20.9%), L-np (17.4%), Lpn1 + Lpn2-15 (7.1%), and L-np + Lpn1 (2.3%). Initially, L-np strains were identified as L. bozemanii by monovalent antiserum, while MALDI-TOF and mip-gene sequencing assigned them to L. anisa. More cold water than hot water samples were contaminated by L. anisa (p < 0.001). PFGE, RAPD, Rep-PCR, and SAU-PCR were performed to correlate L. anisa strains. Eleven out of 14 strains identified in all four pavilions showed 100% of similarity upon PFGE analysis. RAPD, Rep-PCR, and SAU-PCR showed greater discriminative power than PFGE.

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BACKGROUND: Legionella spp. is recognized as a common cause of community acquired pneumonia, with Legionella pneumophila serogroup 1 being the most prevalent. At least 70 species are described so far but few are identified in pathogenic conditions. Data on extrapulmonary infections are scarce. CASE PRESENTATION: A 73-yar-old male with chronic lymphoid leukemia was hospitalized for an insidious wrist arthritis. Ultrasound of the wrist showed a carpal and radiocarpal fluid effusion with positive Doppler signal. While routine bacterial cultures remained sterile, 16S rRNA PCR identified Legionella anisa. Ciprofloxacin 500 mg twice a day for a period of six weeks improved arthritis with full recovery at the end of the treatment. CONCLUSION: Legionella non pneumophila are a rare cause of septic arthritis especially found in immunosuppressed patients and identification of species could help clinician to adapt antibiotherapy.

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The identification of Legionella non-pneumophila species (non-Lp) in clinical and environmental samples is based on the mip gene, although several studies suggest its limitations and the need to expand the classification scheme to include other genes. In this study, the development of a new classification scheme targeting the rpoB gene is proposed to obtain a more reliable identification of 135 Legionella environmental isolates. All isolates were sequenced for the mip and rpoB genes, and the results were compared to study the discriminatory power of the proposed rpoB scheme. Complete concordance between the mip and rpoB results based on genomic percent identity was found for 121/135 (89.6%) isolates; in contrast, discordance was found for 14/135 (10.4%) isolates. Additionally, due to the lack of reference values for the rpoB gene, inter- and intraspecies variation intervals were calculated based on a pairwise identity matrix that was built using the entire rpoB gene (∼4,107 bp) and a partial region (329 bp) to better evaluate the genomic identity obtained. The interspecies variation interval found here (4.9% to 26.7%) was then proposed as a useful sequence-based classification scheme for the identification of unknown non-Lp isolates. The results suggest that using both the mip and rpoB genes makes it possible to correctly discriminate between several species, allowing possible new species to be identified, as confirmed by preliminary whole-genome sequencing analyses performed on our isolates. Therefore, starting from a valid and reliable identification approach, the simultaneous use of mip and rpoB associated with other genes, as it occurs with the sequence-based typing (SBT) scheme developed for Legionella pneumophila, could support the development of multilocus sequence typing to improve the knowledge and discovery of Legionella species subtypes. IMPORTANCELegionella 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. Several studies focused on the mip gene classification scheme showed its limitations and the need to improve the classification scheme, including other genes. Our study provides significant advantages on Legionella identification, providing a reproducible new rpoB gene classification scheme that seems to be more accurate than mip gene sequencing, bringing out greater genetic variation on Legionella species. In addition, the combined use of both the mip and rpoB genes allowed us to identify presumed new Legionella species, improving epidemiological investigations and acquiring new understanding on Legionella fields.

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Legionellosis, an often-lethal pneumonia, is generally associated with contamination by Legionella pneumophila. This bacterium can persist in the environment and resist chemical treatment when it is internalized by amoebae. In addition, there is increasing medical proof that other Legionella species can be causative agents of Legionellosis. The objective of this study was to evaluate whether Legionella non-pneumophila (Lnp) strains were able to use the machinery of amoeba to multiply, or whether amoebae were able to limit their proliferation. Seven strains belonging to the species L. longbeachae, L. anisa, L. bozemanae, L. taurinensis, and L. dumoffii were cocultured with three amoebae, Acanthamoeba castellanii, Willaertia magna T5(S)44, and Willaertia magna C2c Maky, at two temperatures, 22 and 37 °C. We found that at 22 °C, all amoebae were able to phagocytose the seven Lnp strains and to avoid intracellular development, except for L. longbeachae, which was able to multiply inside W. magna T5(S)44. At 37 °C, four Lnp strains were able to hijack the machinery of one or two amoebae and to use it to proliferate, but none were able to multiply inside W. magna C2c Maky.

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The present study analyzes at the national level, the presence of circulating Legionella in the artificial aquatic systems of different facilities of all of them state-owned centers throughout Spain for 12 months. 1754 water samples from various state-owned centers were collected from January to December 2014. Samples were collected from the cooling towers and evaporative condensers (CTC), and water distribution networks such as domestic hot water (DHW), cold water for human consumption (CW), sprinkler irrigation systems (SIS), fire sprinkler systems (FSS), and water from decorative fountains (DF). All these facilities are considered, according to current regulations, as potential amplifying systems for bacteria and possible sources of infection by the generation of droplets and aerosols. The isolation and counting of Legionella in water samples was carried out using microbiological culture following the international normative UNE-EN-ISO 11,731:2007 (ISO 11,731:1998) and UNE-EN ISO 8199:2008 (ISO 8199:2005).The quantification of Legionella colonization, the annual distribution, and the geographical distribution of the Legionella isolates recovered in the water were analyzed. Besides, molecular techniques were used for the characterization of the Legionella non-pneumophila isolates. Legionella was recovered from 15.79% of the analyzed water samples. High colonization was more frequently detected in water samples from CTC, DHW, CW, and DF. Regarding the geographic distribution, positive samples of Legionella were obtained in 14 of the 18 Spanish locations analyzed. Legionella non-pneumophila was the most prevalent and was isolated from water samples from 13 different geographical locations (72%). Legionella anisa and Legionella jordanis were the most frequently non-pneumophila species isolated. Legionella donaldsonii was isolated for the first time in the water distribution networks in Spain. Legionella pneumophila sg 2-14 was detected in 13 locations and Legionella pneumophila sg 1 in 11 locations. Therefore, our study concludes that the presence of Legionella pneumophila and Legionella non-pneumophila species in these systems can be a potential threat to public health and should be examined thoroughly with complementary techniques, such as molecular techniques as a screen for routine diagnosis.

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In early June 2018, an increase in non-travel-related cases of Legionella non-pneumophila Legionnaires' disease (LD) was observed in Sweden and a national outbreak investigation was started. Outbreak cases were defined as notified confirmed or probable cases of L. non-pneumophila LD, with symptom onset after 1 April 2018. From April to August 2018, 41 cases were reported, 30 of whom were identified as L. longbeachae. We conducted a case-control study with 27 cases and 182 matched controls. Results from the case-control study indicated that gardening and handling commercial bagged soil, especially dusty dry soil, were associated with disease. L. longbeachae was isolated in soils from cases' homes or gardens, but joint analysis of soil and human specimens did not identify any genetic clonality. Substantial polyclonality was noted between and within soil samples, which made finding a genetic match between soil and human specimens unlikely. Therefore, whole genome sequencing may be of limited use to confirm a specific soil as a vehicle of transmission for L. longbeachae. Handling soil for residential gardening was associated with disease and the isolation of L. longbeachae in different soils provided further evidence for Legionella non-pneumophila infection from soil.

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BACKGROUND: A rapid detection of Legionella bacteria in water samples is crucial to minimize the risk of acquiring infections, especially in health care facilities. Different detection methods and different decontamination procedures have been reported to affect the recovery of Legionella spp. Our goal was to test the recovery of Legionella pneumophila and Legionella non-pneumophila species using a kit based on non-specific and species-specific probes to treat water samples after two different decontamination procedures. METHODS: The study was conducted with samples collected in the teaching hospital "Le Scotte" of Siena (Italy). Waters samples were analyzed by: i) ScanVIT method after treatment with acids; ii) ScanVIT method after heating; and iii) cultural standard method after heating. The results of the decontamination procedures and the detection methods were evaluated by comparing the number of Legionella-positive and -negative samples, and the recovery rates (CFU l-1) obtained by ScanVIT and the standard method. RESULTS: We find that ScanVIT method is highly sensitive with both decontamination treatments, yielding a higher recovery of L. pneumophila compared to the standard method. Conversely, ScanVIT associated with the acid-treatment yielded the highest recovery of L. non-pneumophila. CONCLUSIONS: The acid-treatment combined to the ScanVIT method increases the recovery of L. non-pneumophila in water samples compared to both ScanVIT associated with heat-treatment and standard culture method. Thus, this method may represent the best choice to detect L. non-pneumophila in water samples and reduce the risk of infection due to underestimation of Legionella loads.

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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.