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Rapid methicillin resistance detection and subspecies discrimination in Staphylococcus hominis clinical isolates by MALDI-TOF MS

Authors :
Verónica Villarreal-Salazar
Soraya Mendoza-Olazarán
Samantha Flores-Treviño
Elvira Garza-González
Paola Bocanegra-Ibarias
Rayo Morfín-Otero
Adrián Camacho-Ortiz
Eduardo Rodríguez-Noriega
Licet Villarreal-Treviño
Source :
Indian journal of medical microbiology.
Publication Year :
2021

Abstract

Staphylococcus hominis is a coagulase-negative opportunistic pathogen responsible for implanted medical device infections. Rapid identification and virulence factors detection are crucial for appropriate antimicrobial therapy. We aimed to search protein biomarker peaks for rapid classification of antibiotic resistance and subspecies of S. hominis using MALDI-TOF MS.S. hominis clinical isolates (n = 148) were screened for subspecies differentiation by novobiocin resistance. Biofilm composition and formation were determined by detachment assay and crystal violet staining, respectively. Antibiotic susceptibility was performed by the broth microdilution method. The search for potential biomarkers peaks was enabled by ClinProTools 3.0, flexAnalysis 3.4, and Biotools 3.2 for statistical analysis, peak visualization, and protein/peptide alignment, respectively.Of 148 isolates, 12.16% were classified as S. hominis subsp. novobiosepticus, 77.77% were biofilm producers, and ˃ 50% were multidrug-resistant. Two potential biomarker peaks, 8975 m/z and 9035 m/z were detected for the discrimination of methicillin resistance with a sensitivity of 96.72%. The following peaks were detected for subspecies differentiation: 2582 m/z, 2823 m/z, and 2619 m/z with 88.89-98.28% of sensitivity.We found potential biomarker peaks to predict methicillin resistance and discriminate S. hominis subspecies during routine MALDI-TOF MS identification in a clinical setting to enable better antibiotic treatment.

Details

ISSN :
19983646
Database :
OpenAIRE
Journal :
Indian journal of medical microbiology
Accession number :
edsair.doi.dedup.....f48d7ad787936f87177c094c2d1dcda3