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MALDI-TOF MS biomarkers for methicillin-resistant Staphylococcus aureus detection: a systematic review

2025-08Artigo científico Acesso aberto
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datacite.subject.sdg03:Saúde de Qualidade
dc.contributor.authorSantos, Pedro
dc.contributor.authorAlho, Irina
dc.contributor.authorRibeiro, Edna
dc.date.accessioned2025-12-17T13:40:16Z
dc.date.available2025-12-17T13:40:16Z
dc.date.issued2025-08
dc.descriptionH&TRC authors gratefully acknowledge FCT/MCTES UIDP/05608/2020 and UIDB/05608/2020.
dc.description.abstractBackground/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.eng
dc.identifier.citationSantos P, Alho I, Ribeiro E. MALDI-TOF MS biomarkers for methicillin-resistant Staphylococcus aureus detection: a systematic review. Metabolites. 2025;15(8):540.
dc.identifier.doi10.3390/metabo15080540
dc.identifier.issn2218-1989
dc.identifier.urihttp://hdl.handle.net/10400.21/22349
dc.language.isoeng
dc.peerreviewedyes
dc.publisherMDPI AG
dc.relation.hasversionhttps://www.mdpi.com/2218-1989/15/8/540
dc.relation.ispartofMetabolites
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectMALDI-TOF MS
dc.subjectStaphylococcus aureus
dc.subjectArtificial Intelligence
dc.subjectBiomarkers
dc.subjectDiscrimination
dc.subjectMethicillin-resistant Staphylococcus aureus
dc.subjectFCT_UIDP/05608/2020
dc.subjectFCT_UIDB/05608/2020
dc.titleMALDI-TOF MS biomarkers for methicillin-resistant Staphylococcus aureus detection: a systematic revieweng
dc.typejournal article
dspace.entity.typePublication
oaire.citation.issue8
oaire.citation.startPage540
oaire.citation.titleMetabolites
oaire.citation.volume15
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameRibeiro
person.givenNameEdna
person.identifier.ciencia-idC414-CDF2-D35A
person.identifier.orcid0000-0003-1316-7750
relation.isAuthorOfPublicationa571bf34-bcda-49ca-b5cb-4cdecbb3d9c7
relation.isAuthorOfPublication.latestForDiscoverya571bf34-bcda-49ca-b5cb-4cdecbb3d9c7

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