The diagnosis of Legionnaires' disease (LD) caused by Legionella non-pneumophila species is likely to increase with broader use of PCR targeting Legionella spp. In this context, accurate species identification in PCR-positive but culture-negative samples is essential to improve understanding of disease epidemiology and to support source attribution. Here, we presented a validated and user-friendly bioinformatic pipeline compatible with next-generation sequencing (NGS) for analyzing the hypervariable 23S-5S region, paired with a curated database encompassing all described Legionella species as of January 2026. Parameters were optimized for sensitivity and specificity using both strains and culture-positive clinical and environmental samples. We then applied the pipeline retrospectively to 92 culture-negative PCR-positive samples collected from 2023 to 2025. Legionella species were successfully assigned in 60% (55/92) of tested samples and revealed a high diversity. Co-infections were detected in clinical samples, including combinations of L. pneumophila with L. longbeachae or L. bozemanii, while environmental samples contained up to six different species. These results demonstrate that 23S-5S amplicon NGS enables species-level identification in the absence of cultured isolates, improving surveillance of non-pneumophila Legionella cases. The proposed pipeline, implemented in QIIME2 and accompanied by a publicly available database, provides a practical framework for routine molecular monitoring and outbreak investigation.
Jacqueline, C., Peticca, A., Lannes, J., Curtil-dit-Galin, M., Ibranosyan, M., Beraud, L., Descours, G., Jarraud, S., Ginevra, C.
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