Developing metagenomic methods for legionella detection

Abstract

Legionella is a Gram-negative bacterium naturally present in freshwater and soil. The bacteria can enter, colonise and multiply in man-made water systems. Infection through inhalation of aerosols containing the bacteria can cause Legionnaires' disease (LD) an atypical, severe pneumonia in individuals with underlying risk factors.Legionella pneumophila serogroup 1, the most widely studied species, is reported to account for more than 90 % of all clinical isolates related to LD in England. L. pneumophila is isolated routinely at Public Health England however Legionella is a slow growing bacterium, typically taking from three to five days to grow. Additionally, it has been reported that L. pneumophila is isolated in only 60 % of urinary antigen-positive cases. Here, the application of metagenomic sequencing was investigated in Legionella positive clinical and environmental samples, the hypothesis being that metagenomic sequencing may provide a more time efficient result and may reveal previously undetected heterogeneity in clinical and environmental cases. The results demonstrate that L. pneumophila genomes can be captured and sequenced from patients with LD and from environmental source samples without prior culture using a targeted capture approach. The data generated also demonstrate that Legionella diversity within environmental sources as well as a clinical case could be captured. Importantly, the work has demonstrated the first successful application of in silico 7-loci sequence-based typing and 50 core gene MLST to Legionella data generated by a metagenomic method. Overall, this thesis demonstrates the proof of concept of targeted metagenomic sequencing of L. pneumophila directly from multiple patients and environmental sources as well as the ability to capture a variety of sequence types. Furthermore, the challenges of implementing metagenomic sequencing for routine diagnostic use and future avenues for technical optimisation of the targeted capture approach are outlined.