New Insight regarding Legionella Non-Pneumophila Species Identification: Comparison between the Traditional mip Gene Classification Scheme and a Newly Proposed Scheme Targeting the rpoB Gene

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.

Evaluation of MALDI-TOF Mass Spectrometry in Diagnostic and Environmental Surveillance of Legionella Species: A Comparison With Culture and Mip-Gene Sequencing Technique

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.