Methicillin‐resistant Staphylococcus aureus (MRSA) is one of major clinical pathogens responsible for both hospital‐ and community‐acquired infections worldwide. A delay in targeted antibiotic treatment contributes to longer hospitalization stay, higher costs, and increasing in‐hospital mortality. Matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (MALDI‐TOF MS) has been integrated into the routine workflow for microbial identification over the past decade, and it has also shown promising functions in the detection of bacterial resistance. Therefore, we describe a rapid MALDI‐TOF MS‐based methodology for MRSA screening with machine‐learning algorithms.

中文翻译：

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基质辅助激光解吸/电离飞行时间质谱法快速鉴定耐甲氧西林金黄色葡萄球菌

耐甲氧西林金黄色葡萄球菌(MRSA) 是导致全球医院和社区获得性感染的主要临床病原体之一。靶向抗生素治疗的延迟会导致住院时间延长、费用增加和院内死亡率增加。在过去的十年中，基质辅助激光解吸/电离飞行时间质谱 (MALDI-TOF MS) 已被整合到微生物鉴定的常规工作流程中，并且在检测细菌耐药性方面也显示出有前景的功能。因此，我们描述了一种基于 MALDI-TOF MS 的快速方法，用于使用机器学习算法进行 MRSA 筛查。