Methicillin-resistant Staphylococcus aureus (MRSA) is highly prevalent in U.S. cystic fibrosis (CF) patients and is associated with worse clinical outcomes in CF. These infections often become chronic despite repeated antibiotic therapy. Here, we assessed whether bacterial phenotypes, including antibiotic tolerance, can predict the clinical outcomes of MRSA infections. MRSA isolates ( = 90) collected at the incident (i.e., acute) and early infection states from 57 patients were characterized for growth rates, biofilm formation, hemolysis, pigmentation, and vancomycin tolerance. The resistance profiles were consistent with those in prior studies. Isolates from the early stage of infection were found to produce biofilms, and 70% of the isolates exhibited delta-hemolysis, an indicator of activity. Strong vancomycin tolerance was present in 24% of the isolates but was not associated with intermediate vancomycin susceptibility. There were no associations between these phenotypic measures, antibiotic tolerance, and MRSA clearance. Our research suggests that additional factors may be relevant for predicting the clearance of MRSA. Chronic MRSA infections remain challenging to treat in patients with cystic fibrosis (CF). The ability of the bacterial population to survive high concentrations of bactericidal antibiotics, including vancomycin, despite lacking resistance is considered one of the main reasons for treatment failures. The connection between antibiotic tolerance and treatment outcomes remains unexplored and can be crucial for prognosis and regimen design toward eradication. In this study, we measured the capacity of 90 MRSA isolates from CF patients to form vancomycin-tolerant persister cells and evaluated their correlation with the clinical outcomes. Additionally, various traits that could reflect the metabolism and/or virulence of those MRSA isolates were systematically phenotyped and included for their predictive power. Our research highlights that despite the importance of antibiotic tolerance, additional factors need to be considered for predicting the clearance of MRSA.

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http://dx.doi.org/10.1128/spectrum.04061-22DOI Listing

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