bioRxiv · 10.1101/2023.12.22.572975
Genomic analysis of Staphylococcus aureus isolates from bacteremia reveals genetic features associated with the COVID-19 pandemic
Abstract
Genomic analyses of bacterial isolates are necessary to monitor the prevalence of antibiotic resistance genes and virulence determinants. Herein, we provide a comprehensive genomic description of a collection of 339 Staphylococcus aureus strains isolated from patients with bacteremia between 2014 and 2022. Nosocomial acquisition accounted for 56.6% of episodes, with vascular catheters being the predominant source of infection (31.8%). Cases of fatality (27.4%), persistent bacteremia (19.5%) and diagnosis of septic emboli (24.2%) were documented. During the COVID-19 pandemic, we observed a 140% increase of the episodes of S. aureus bacteremia per year, with a concomitant increase of the cases from nosocomial origin. This prompted us to investigate the existence of genetic features associated with S. aureus isolates from the COVID-19 pandemic. While genes conferring resistance to {beta}-lactams (blaI-blaR-blaZ), macrolides (ermA, ermC, ermT, mphC, msrA) and aminoglycosides (ant(4)-Ia, ant(9)-Ia, aph(3)-IIIa, aph(2)-Ih) were prevalent in our collection, detection of the msrA and mphC genes increased significantly in pandemic S. aureus isolates. Similarly, we observed a higher prevalence of isolates carrying the genes encoding the Clumping Factors A and B, involved in fibrinogen binding. Of note, macrolides were extensively used as accessory therapy for COVID-19 and fibrinogen levels were usually elevated upon SARS-CoV-2 infection. Therefore, our results reveal a remarkable adaptation of the S. aureus isolates to the COVID-19 pandemic context and demonstrates the potential of whole-genome sequencing to conduct molecular epidemiology studies.
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Sanchez-Osuna, M., Pedrosa, M., Bierge, P., Gomez-Sanchez, I., Alguacil-Guillen, M., Espasa, M., Erill, I., Gasch, O., Pich, O. Q.. 2023-12-22. Genomic analysis of Staphylococcus aureus isolates from bacteremia reveals genetic features associated with the COVID-19 pandemic. https://doi.org/10.1101/2023.12.22.572975
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