ABSTRACT
Legionella pneumophila is ubiquitous and sporadically infects humans causing Legionnaire's disease (LD). Globally, reported cases of LD have risen fourfold from 2000 to 2014. In 2016, Sydney, Australia was the epicenter of an outbreak caused by L. pneumophila serogroup 1 (Lpsg1). Whole-genome sequencing was instrumental in identifying the causal clone which was found in multiple locations across the city. This study examined the epidemiology of Lpsg1 in an urban environment, assessed typing schemes to classify resident clones, and investigated the association between local climate variables and LD outbreaks. Of 223 local Lpsg1 isolates, we identified dominant clones with one clone isolated from patients in high frequency during outbreak investigations. The core genome multi-locus sequence typing scheme was the most reliable in identifying this Lpsg1 clone. While an increase in humidity and rainfall was found to coincide with a rise in LD cases, the incidence of the major L. pneumophila outbreak clone did not link to weather phenomena. These findings demonstrated the role of high-resolution typing and weather context assessment in determining source attribution for LD outbreaks in urban settings, particularly when clinical isolates remain scarce.IMPORTANCEWe investigated the genomic and meteorological influences of infections caused by Legionella pneumophila in Sydney, Australia. Our study contributes to a knowledge gap of factors that drive outbreaks of legionellosis compared to sporadic infections in urban settings. In such cases, clinical isolates can be rare, and thus, other data are needed to inform decision-making around control measures. The study revealed that core genome multi-locus sequence typing is a reliable and adaptable technique when investigating Lpsg1 outbreaks. In Sydney, the genomic profile of Lpsg1 was dominated by a single clone, which was linked to numerous community cases over a period of 40 years. Interestingly, the peak in legionellosis cases during Autumn was not associated with this prevalent outbreak clone. Incorporating meteorological data with Lpsg1 genomics can support risk assessment strategies for legionellosis in urban environments, and this approach may be relevant for other densely populated regions globally.
ABSTRACT
BACKGROUND: The emergence of macrolide resistance in Bordetella pertussis, the causative agent of pertussis, due to mutations in the 23S rRNA gene has been recently recognized. However, resistance mechanisms to macrolides in Bordetella parapertussis and Bordetella holmesii remain unknown. OBJECTIVES: This study investigated genomic changes induced by in vitro exposure to erythromycin in these three main pathogens responsible for pertussis-like disease. METHODS: A set of 10 clinical and reference strains of B. pertussis, B. parapertussis and B. holmesii was exposed to erythromycin for 15â weeks or 30 subculture passages. Antibiotic pressure was achieved by growth on the selective media with erythromycin Etest strips or impregnated discs. Genome polymorphisms and transcriptomic profiles were examined by short- and long-read sequencing of passaged isolates. RESULTS: B. parapertussis and B. holmesii isolates developed significant in vitro resistance to erythromycin (MIC >256â mg/L) within 2 to 7â weeks and at 5 to 12â weeks, respectively. B. pertussis remained phenotypically susceptible to the antibiotic following 15â weeks of exposure, with the MIC between 0.032 to 0.38â mg/L. Genomic analysis revealed that B. holmesii developed resistance due to mutations in the 23S rRNA gene. The resistance mechanism in B. parapertussis was hypothesized as being due to upregulation of an efflux pump mechanism. CONCLUSIONS: These findings indicate that both B. holmesii and B. parapertussis can be more prone to induced resistance following exposure to treatment with erythromycin than B. pertussis. The surveillance of macrolide resistance in Bordetella isolates recovered from patients with pertussis, especially persistent disease, is warranted.