A real-time PCR for specific detection of the Legionella pneumophila serogroup 1 ST1 complex.

OBJECTIVE: Legionella pneumophila serogroup 1 (Lp1) sequence type (ST) 1 is globally widespread in the environment and accounts for a significant proportion of Legionella infections, including nosocomial Legionnaires' disease (LD). This study aimed to design a sensitive and specific detection method for Lp ST1 that will underpin epidemiological investigations and risk assessment. METHODS: A total of 628 Lp genomes (126 ST1s) were analyzed by comparative genomics. Interrogation of more than 900 accessory genes revealed seven candidate targets for specific ST1 detection and specific primers and hydrolysis probes were designed and evaluated. The analytical sensitivity and specificity of the seven primer and probe sets were evaluated on serially diluted DNA extracted from the reference strain CIP107629 and via qPCR applied on 200 characterized isolates. The diagnostic performance of the assay was evaluated on 142 culture-proven clinical samples from LD cases and a real-life investigation of a case cluster. RESULTS: Of seven qPCR assays that underwent analytical validation, one PCR target (lpp1868) showed higher sensitivity and specificity for ST1 and ST1-like strains. The diagnostic performance of the assay using respiratory samples corresponded to a sensitivity of 95% (19/20) (95% CI (75.1-99.9)) and specificity of 100% (122/122) (95% CI (97-100)). The ST1 PCR assay could link two out of three culture-negative hospitalized LD cases to ST1 during a real-time investigation. CONCLUSION: Using whole genome sequencing (WGS) data, we developed and validated a sensitive and specific qPCR assay for the detection of Lp1 belonging to the ST1 clonal complex by amplification of the lpp1868 gene. The ST1 qPCR is expected to deliver an added value for Lp control and prevention, in conjunction with other recently developed molecular assays.

A bioinformatics tool for ensuring the backwards compatibility of Legionella pneumophila typing in the genomic era.

OBJECTIVES: Whole genome sequencing (WGS) has revolutionized the subtyping of Legionella pneumophila but calling the traditional sequence-based type from genomic data is hampered by multiple copies of the mompS locus. We propose a novel bioinformatics solution for rectifying that limitation, ensuring the feasibility of WGS for cluster investigation. METHODS: We designed a novel approach based on the alignment of raw reads with a reference sequence. With WGS, reads originating from either of the two mompS copies cannot be differentiated. Therefore, when non-identical copies were present, we applied a read-filtering strategy based on read alignment to a reference sequence via unique 'anchors'. If minimal read coverage was achieved after filtration (≥3X), a consensus sequence was built based on mapped reads followed by calling the sequence-based typing allele. The entire procedure was implemented using a Perl script. RESULTS: The method was validated using a diverse sample of 265 L. pneumophila genomes, consisting of 59 different sequence types (STs) and 23 mompS variants; 57 of the 265 (22%) had non-identical mompS copies. In 237 of the 265 samples (89.4%), mompS calling was successful and no erroneous calling occurred. A 98.1% success was recorded among 109 samples meeting quality requirements. The method was superior to alternative approaches. CONCLUSIONS: As WGS becomes more accessible, technical difficulties in routine clinical and surveillance work will arise. The case of mompS in L. pneumophila serves as an example for such limitations that necessitate the development of novel computational solutions that meet end-user demands.

Design and application of a core genome multilocus sequence typing scheme for investigation of Legionnaires' disease incidents.

Sequence-based typing (SBT) for Legionella pneumophila (Lp) has dramatically improved Legionnaires' disease (LD) cluster investigation. Microbial whole genome sequencing (WGS) is a promising modality for investigation but sequence analysis methods are neither standardised, nor agreed. We sought to develop a WGS-based typing scheme for Lp using de novo assembly and a genome-wide gene-by-gene approach (core genome multilocus sequence typing, cgMLST). We analysed 17 publicly available Lp genomes covering the whole species variation to define a core genome (1,521 gene targets) which was validated using 21 additional published genomes. The genomes of 12 Lp strains implicated in three independent cases of paediatric humidifier-associated LD were subject to cgMLST together with three 'outgroup' strains. cgMLST was able to resolve clustered strains and clearly identify related and unrelated strains. Thus, a cgMLST scheme was readily achievable and provided high-resolution analysis of Lp strains. cgMLST appears to have satisfactory discriminatory power for LD cluster analysis and is advantageous over mapping followed by single nucleotide polymorphism (SNP) calling as it is portable and easier to standardise. cgMLST thus has the potential for becoming a gold standard tool for LD investigation. Humidifiers pose an ongoing risk as vehicles for LD and should be considered in cluster investigation and control efforts.