期刊
ANALYTICAL CHEMISTRY
卷 88, 期 18, 页码 8989-8996出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.6b01186
关键词
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资金
- U.S. Army Research Office
- Defense Advanced Research Projects Agency [W911NF-14-2-0020]
- Division of Chemical Sciences, Geosciences, and Biosciences, Office of Basic Energy Sciences of the U.S. Department of Energy [DE-FG02-01ER15129]
The unique challenges presented by metabolomics have driven the development of new Mass spectrometry (MS) based techniques for small molecule analysis. We have. previously demonstrated silicon nanopost arrays (NAPA) to be an effective substrate for laser desorption ionization (LDI) of small molecules for MS. However, the utility of NAPA-LDI-MS for a wide-range of metabolite classes has not been investigated. Here we apply NAPA-LDI-MS to-the large,scale acquisition of high-resolution mass spectra and tandem mass spectra from a collection of metabolite standards,covering a, range of compound classes, including amino acids, nucleotides, carbohydrates, xenobiotics, lipids, and other classea. In untargeted analysis of metabolite standard mixtures, detection was, achieved for 374 compounds and, useful MS/MS spectra were. obtained for 287 compounds, without individual optimization of ionization or fragmentation conditions. Metabolite detection was evaluated in the context of 31 metabolic pathways, and NAPA-LDI-MS was found to provide detection for 63% of investigated pathway metabolites. Individual, targeted analysis of the 20 common amino acids provided detection of 100% of the investigated compounds, demonstrating that improved coverage is possible through optimization and targeting of individual analytes or analyte classes. In direct analysis of aqueous and organic extracts from human serum samples, spectral features were assigned to a total of 108 small metabolites and lipids. Glucose and amino acids were quantitated within their physiological concentration ranges. The broad coverage demonstrated by this large-scale screening experiment opens the door for use of NAPA-LDI-MS in numerous metabolite analysis applications.
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