Of the many metabolites involved in any clinical condition, only a narrow range of biomarkers is currently being used in the clinical setting. A key to personalized medicine would be to extend this range. Metabolic fingerprinting provides a more comprehensive insight, but many methods used for metabolomics analysis are too complex and time-consuming to be diagnostically useful. Here, a rapid evaporative ionization mass spectrometry (REIMS) system for direct ex vivo real-time analysis of biofluids with minor sample pretreatment is detailed. The REIMS can be linked to various laser wavelength systems (such as optical parametric oscillator or CO₂ laser) and with automation for high-throughput analysis. Laser-induced sample evaporation occurs within seconds through radiative heating with the plume guided to the MS instrument. The presented procedure includes (i) laser setup with automation, (ii) analysis of biofluids (blood/urine/stool/saliva/sputum/breast milk) and (iii) data analysis. We provide the optimal settings for biofluid analysis and quality control, enabling sensitive, precise and robust analysis. Using the automated setup, 96 samples can be analyzed in ~35–40 min per ionization mode, with no intervention required. Metabolic fingerprints are made up of 2,000–4,000 features, for which relative quantification can be achieved at high repeatability when total ion current normalization is applied. With saliva and feces as example matrices, >70% of features had a coefficient of variance ≤30%. However, to achieve acceptable long-term reproducibility, additional normalizations by, e.g., LOESS are recommended, especially for positive ionization.

在涉及任何临床病症的许多代谢物中，目前只有一小部分生物标志物用于临床环境。个性化医疗的一个关键是扩大这一范围。代谢指纹图谱提供了更全面的见解，但用于代谢组学分析的许多方法过于复杂和耗时，无法用于诊断。在这里，详细介绍了一种快速蒸发电离质谱 (REIMS) 系统，用于通过少量样品预处理直接离体实时分析生物流体。REIMS 可以连接到各种激光波长系统（例如光学参量振荡器或 CO ₂激光）和自动化进行高通量分析。激光诱导的样品蒸发通过辐射加热在几秒钟内发生，羽流引导至 MS 仪器。所提出的程序包括 (i) 自动化激光设置，(ii) 生物流体分析（血液/尿液/粪便/唾液/痰/母乳）和 (iii) 数据分析。我们为生物流体分析和质量控制提供最佳设置，从而实现灵敏、精确和稳健的分析。使用自动设置，每个电离模式可在约 35–40 分钟内分析 96 个样品，无需干预。代谢指纹由 2,000–4,000 个特征组成，当应用总离子流归一化时，可以以高重复性实现相对量化。以唾液和粪便作为示例矩阵，> 70% 的特征的方差系数≤30%。然而，为了实现可接受的长期重现性，建议通过例如 LOESS 进行额外的标准化，特别是对于正离子化。