Autor: |
Mariane Pivard, Sylvère Bastien, Iulia Macavei, Nicolas Mouton, Jean-Philippe Rasigade, Florence Couzon, Benjamin Youenou, Anne Tristan, Romain Carrière, Karen Moreau, Jérôme Lemoine, François Vandenesch |
Jazyk: |
angličtina |
Rok vydání: |
2023 |
Předmět: |
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Zdroj: |
Frontiers in Cellular and Infection Microbiology, Vol 13 (2023) |
Druh dokumentu: |
article |
ISSN: |
2235-2988 |
DOI: |
10.3389/fcimb.2023.1162617 |
Popis: |
IntroductionThe bacterial pathogen Staphylococcus aureus harbors numerous virulence factors that impact infection severity. Beyond virulence gene presence or absence, the expression level of virulence proteins is known to vary across S. aureus lineages and isolates. However, the impact of expression level on severity is poorly understood due to the lack of high-throughput quantification methods of virulence proteins.MethodsWe present a targeted proteomic approach able to monitor 42 staphylococcal proteins in a single experiment. Using this approach, we compared the quantitative virulomes of 136 S. aureus isolates from a nationwide cohort of French patients with severe community-acquired staphylococcal pneumonia, all requiring intensive care. We used multivariable regression models adjusted for patient baseline health (Charlson comorbidity score) to identify the virulence factors whose in vitro expression level predicted pneumonia severity markers, namely leukopenia and hemoptysis, as well as patient survival.ResultsWe found that leukopenia was predicted by higher expression of HlgB, Nuc, and Tsst-1 and lower expression of BlaI and HlgC, while hemoptysis was predicted by higher expression of BlaZ and HlgB and lower expression of HlgC. Strikingly, mortality was independently predicted in a dose-dependent fashion by a single phage-encoded virulence factor, the Panton-Valentine leucocidin (PVL), both in logistic (OR 1.28; 95%CI[1.02;1.60]) and survival (HR 1.15; 95%CI[1.02;1.30]) regression models.DiscussionThese findings demonstrate that the in vitro expression level of virulence factors can be correlated with infection severity using targeted proteomics, a method that may be adapted to other bacterial pathogens. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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