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用于耐甲氧西林检测的基质辅助激光解吸电离飞行时间质谱生物标志物:一项系统评价。

MALDI-TOF MS Biomarkers for Methicillin-Resistant Detection: A Systematic Review.

作者信息

Santos Pedro, Alho Irina, Ribeiro Edna

机构信息

Escola Superior de Tecnologia da Saúde, Instituto Politécnico de Lisboa (ESTeSL-IPL), Av. D. João II, Lote 4.69.01, Parque das Nações, 1990-096 Lisboa, Portugal.

Serviço de Patologia Clínica-Unidade Local de Saúde do Alentejo Central, Largo Senhor da Pobreza, 7000-811 Évora, Portugal.

出版信息

Metabolites. 2025 Aug 8;15(8):540. doi: 10.3390/metabo15080540.

Abstract

BACKGROUND/OBJECTIVES: Methicillin-resistant (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 isolates. The aim of this study was to identify methicillin-resistant discriminative biomarkers for 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 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 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 through biomarker analysis. Given that it is already implemented in several clinical laboratories, this approach could be adopted without significant additional cost.

摘要

背景/目的:耐甲氧西林金黄色葡萄球菌(MRSA)感染仍是医疗保健领域的一项重大挑战。用于MRSA鉴定的传统技术和分子技术要么耗时,要么成本高昂。相比之下,基质辅助激光解吸/电离飞行时间质谱(MALDI-TOF MS)提供了一种快速的微生物鉴定方法,并且有潜力检测出区分分离株中甲氧西林耐药性的生物标志物。本研究的目的是使用MALDI-TOF MS鉴定获得的耐甲氧西林鉴别生物标志物。

方法

通过检索PubMed和Web of Science等数据库,对聚焦于用MALDI-TOF MS通过生物标志物检测MRSA的研究进行系统综述,包括截至2024年7月发表的所有相关研究。该综述方案已在PROSPERO登记处注册。

结果

共选择15项研究进行分析。提取了有关研究地点、样本量、MALDI-TOF MS分析仪、样本制备、甲氧西林耐药性和敏感性生物标志物以及人工智能(AI)模型使用情况的数据。值得注意的是,PSM-mec和δ毒素经常被报告为信息丰富的生物标志物,分别在2414±2 Da和3006±2 Da处可检测到。此外,八项研究使用AI模型根据峰强度差异或某些峰的独有存在来识别区分耐甲氧西林和甲氧西林敏感菌株的特定生物标志物。此外,两项研究对生物样本中低浓度的MRSA进行检测,其他研究采用优化的基质溶液以改进分析。

结论

总体而言,MALDI-TOF MS不仅是鉴定细菌分离株的有力工具,而且通过生物标志物分析在快速、经济高效地检测MRSA耐药性方面也显示出强大潜力。鉴于它已在多个临床实验室实施,这种方法可以在不产生重大额外成本的情况下采用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbda/12388497/98629a33abf4/metabolites-15-00540-g0A1.jpg

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