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MALDI-TOF MS biomarkers for methicillin-resistant Staphylococcus aureus detection: a systematic review
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Resumo(s)
Background/objectives: Methicillin-resistant Staphylococcus aureus (MRSA) infections remain a significant challenge in healthcare. Conventional and molecular techniques used for MRSA identification are either time-consuming or costly. Alternatively, Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) offers a rapid method for microbial identification and has the potential to detect biomarkers that distinguish methicillin resistance in S. aureus isolates. This study aimed to identify methicillin-resistant discriminative biomarkers for S. aureus obtained using MALDI-TOF MS. Methods: A systematic review was conducted by searching databases such as PubMed and Web of Science for studies that focused on MRSA detection with biomarkers by MALDI-TOF MS, including all relevant studies published up to July 2024. The review protocol was registered in the PROSPERO registry. Results: A total of 15 studies were selected for analysis. Data were extracted on study location, sample size, MALDI-TOF MS analyzer, sample preparation, methicillin resistance and sensitivity biomarkers, and the use of Artificial Intelligence (AI) models. Notably, PSM-mec and delta toxin were frequently reported as informative biomarkers, detectable at 2414 ± 2 Da and 3006 ± 2 Da, respectively. Additionally, eight studies used AI models to identify specific biomarkers differentiating methicillin-resistant and methicillin-sensitive strains, based on differences in peak intensities or the exclusive presence of certain peaks. Moreover, two studies employed the detection of MRSA in low concentrations from biological samples, and others employed an optimized matrix solution for improved analysis. Conclusions: Overall, MALDI-TOF MS is not only a powerful tool for the identification of bacterial isolates but also shows strong potential for rapid, cost-effective detection of methicillin resistance in S. aureus through biomarker analysis. Given that it is already implemented in several clinical laboratories, this approach could be adopted without a high additional cost.
Descrição
H&TRC authors gratefully acknowledge FCT/MCTES UIDP/05608/2020 and UIDB/05608/2020.
Palavras-chave
MALDI-TOF MS Staphylococcus aureus Artificial Intelligence Biomarkers Discrimination Methicillin-resistant Staphylococcus aureus FCT_UIDP/05608/2020 FCT_UIDB/05608/2020
Contexto Educativo
Citação
Santos P, Alho I, Ribeiro E. MALDI-TOF MS biomarkers for methicillin-resistant Staphylococcus aureus detection: a systematic review. Metabolites. 2025;15(8):540.
Editora
MDPI AG