控制蛋白质沉淀和芯片纳喷雾质谱法用于血浆代谢组学分析

Liquid chromatography-mass spectrometry (LC-MS) is a common method for profiling biological samples in metabolomics. However, LC-MS data of metabolomic studies are often affected by high noise levels, retention time shifts, and high variability in signal intensities. With a new chip-based nanoelectrospray source it becomes possible to directly infuse complex biological samples such as plasma without any chromatographic separation beforehand. In combination with highly diluted samples and long data acquisition times, the parallel analysis of hundreds of compounds is now possible. In a proof-of-concept study, 10 human plasma samples from females and males were analyzed with the intention to separate the two groups by their different metabolomes. The reproducibility was so high that statistical analysis of the data could be performed without prior normalization. Two groups of female and male samples were separated by a supervised machine learning algorithm, principal component analysis, and hierarchical clustering. Peaks contributing to the group separation were characterized by accurate mass measurement and MS-MS fragmentation and by spiking experiments. The feasibility of direct sample infusion using the new chip-based nanoelectrospray device opens a new dimension for the rapid parallel analysis of complex biological mixtures.