Background Rapid identification of bacteria is critical to prevent antimicrobial resistance and ensure positive patient outcomes. We have developed the MasSpec Pen, a handheld mass spectrometry-based device that enables rapid analysis of biological samples. Here, we evaluated the MasSpec Pen for identification of bacteria from culture and clinical samples. Methods A total of 247 molecular profiles were obtained from 43 well-characterized strains of 8 bacteria species that are clinically relevant to osteoarticular infections, including Staphylococcus aureus, Group A and B Streptococcus, and Kingella kingae, using the MasSpec Pen coupled to a high-resolution mass spectrometer. The molecular profiles were used to generate statistical classifiers based on metabolites that were predictive of Gram stain category, genus, and species. Then, we directly analyzed samples from 4 patients, including surgical specimens and clinical isolates, and used the classifiers to predict the etiologic agent. Results High accuracies were achieved for all levels of classification with a mean accuracy of 93.3% considering training and validation sets. Several biomolecules were detected at varied abundances between classes, many of which were selected as predictive features in the classifiers including glycerophospholipids and quorum-sensing molecules. The classifiers also enabled correct identification of Gram stain type and genus of the etiologic agent from 3 surgical specimens and all classification levels for clinical specimen isolates. Conclusions The MasSpec Pen enables identification of several bacteria at different taxonomic levels in seconds from cultured samples and has potential for culture-independent identification of bacteria directly from clinical samples based on the detection of metabolic species.

中文翻译：

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使用手持式质谱探针直接从培养物和临床样本中鉴定临床相关细菌

背景 细菌的快速鉴定对于防止抗菌素耐药性和确保积极的患者治疗效果至关重要。我们开发了 MasSpec Pen，这是一种基于质谱的手持式设备，可以快速分析生物样本。在这里，我们评估了 MasSpec Pen 从培养物和临床样本中鉴定细菌的能力。方法 使用与高-分辨率质谱仪。分子图谱用于生成基于代谢物的统计分类器，这些代谢物可预测革兰氏染色的类别、属和种。然后，我们直接分析了 4 名患者的样本，包括手术标本和临床分离株，并使用分类器来预测病原体。结果 考虑到训练集和验证集，所有级别的分类都实现了高精度，平均准确率为 93.3%。在类别之间检测到不同丰度的几种生物分子，其中许多被选为分类器中的预测特征，包括甘油磷脂和群体感应分子。分类器还能够正确识别来自 3 个手术标本的革兰氏染色类型和病原体属以及临床标本分离株的所有分类水平。