Acylglycines are an important class of metabolites that have been used in the diagnosis of several inborn errors of metabolism (IEM). However, current analytical methods detect only a few acylglycines. There is a need to profile these metabolites in a comprehensive manner for studying their functions and improving their diagnostic values for different IEM and potentially other diseases. We describe a sensitive method that combines the chromatographic resolving power of ultra-performance liquid chromatography (UPLC) to separate closely related metabolites including isomers with tandem mass spectrometry (MS/MS). Acylglycines were extracted from urine using an anion exchange solid-phase extraction (SPE) cartridge. After UPLC separation, the acylglycines were detected on a hybrid triple quadrupole linear ion trap mass spectrometer. A set of standards were used for the development of an optimal MS acquisition method. Several acquisition modes using information derived from collisioninduced dissociation breakdown curves were used to detect acylglycines. Using this method, 18 acylglycines were detected in the urine of healthy individuals and confirmed using standards, while 47 additional acylglycines were detected and tentatively identified, based on their retention and fragmentation pattern. Among the 65 acylglycines detected, only 18 of them have been previously reported in biofluids of healthy individuals. These results will be deposited in a public human metabolome database. This example illustrates that by developing a method tailored to the analysis of a class of metabolites sharing similar structural moieties, we can potentially identify many more new metabolites, thereby expanding the overall metabolome coverage. (J Am Soc Mass Spectrom 2010, 21, 2105-2116) © 2010 American Society for Mass Spectrometry M etabolomics is an emerging field that is poised to play a significant role in many disciplines of biosciences. One of the current challenges in metabolomics is to profile the metabolome in a very comprehensive manner, ideally covering the entire set of metabolites present in a biological system. However, due to technical limitations, only a small portion of the metabolome is analyzed. There is a great need to expand the metabolome coverage to reveal subtle changes of the metabolome in biological studies or disease biomarker discovery. Liquid chromatography mass spectrometry (LC/MS) is a sensitive technique that can detect many metabolites in a metabolome sample [1]. However, metabolite identification from the mass spectral data alone is often difficult [2][3][4][5][6]. There are only a limited number of metabolite standards available for spectral comparison to identify unknowns. For example, in the Human Metabolome Database (HMDB), product ion spectra of about 900 known standards obtained by tandem mass spectrometry (MS/MS) are included. To create this MS/MS spectral library, we went through almost all the possible commercial sources to acquire the available metabolite standards [7]. This number is still quite ...