Abstract

Accurate species-level identification of Legionella during routine environmental surveillance remains challenging, as standard proteomic screening methods like MALDI-TOF MS often lack the resolution to distinguish closely related taxa. This study introduces a novel, cost-effective, and stepwise taxonomic framework that bridges routine environmental monitoring with multi-layered, genome-resolved analysis. We expanded upon our previous screening of four novel candidate lineages by focusing on the three remaining, uncharacterized environmental isolates, while using the recently validly described Legionella sheltonii (strain PATHC038) as a reference framework control. By applying nucleotide- and protein-based overall genomic relatedness indices (ANI, dDDH, AAI, and POCP) alongside core-genome phylogenomics, our framework independently confirmed the genomic distinctiveness of the three isolates, which exhibited AAI values of 94.3–96.6% and POCP values of 86.5–91.0%, with POCP values lying close to the proposed species delineation threshold. By defining clear criteria for escalating isolates from culture to targeted sequencing, this workflow prevents diagnostic misidentification during epidemiological outbreak investigations and provides public health agencies with a scalable tool to monitor hidden Legionella diversity, ultimately enhancing proactive water safety and risk assessment.

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