An Effective Strategy to Characterize Acylglycines in Urine using UPLC MS/MS
Tue 4:00 PM - Track 3: Newborn Screening
Avalyn Lewis
University of Alberta
Avalyn Lewis, Liang Li

Chemistry Department, University of Alberta, Edmonton, T6G 2G2, Canada
Analysis of acylglycines in urine is important for the diagnosis of inherited metabolic disorders. Conjugation of free fatty acids with glycine is effective in balancing the ratio between free and esterified CoA in the mitochondria of liver cells. In inherited metabolic disorders, increased concentration of acylglycines in urine is directly related to the accumulation of acyl-CoA esters. In this work, we describe a sensitive method that uses the resolving power of UPLC to separate isomers and the selectivity of QTRAP scan modes to differentiate acylglycines. The aim of this study is to attempt to identify novel acylglycine metabolites in urine with an ultimate goal of studying the correlation of the acylglycine metabolite profiles and disease states.

A systematic approach, using breakdown curves and selective scan modes, was used to characterize acylglycines in human urine. To aid interpretation and identification, seventeen standards of the most common acylglycines were used to construct breakdown curves, which are plots of fragment ion intensities vs. collision energies. These breakdown curves were used to determine the optimal fragmentation conditions and to establish fragmentation trends of straight-chain, branched-chain, aromatic and di-carboxylic acylglycines. Precursor ion and constant neutral loss scans were used in the first step of the strategy, using fragment ions observed in the breakdown curves. Using trends observed and the molecular weights of expected and unexpected metabolites, multiple reaction monitoring (MRM) transitions were created for optimal detection of low-level acylglycines. Product ion spectra were acquired for the metabolite detected and compiled to create a library.

Urine samples were collected from six healthy volunteers, with no known diagnoses of metabolic disorders. Acylglycines were extracted from urine using mixed-mode anion-exchange (MAX) solid phase extraction (SPE) cartridges. The collected fractions were analyzed by UPLC-MS/MS using a Waters UPLC system coupled to a MDS SCIEX hybrid triple quadrupole linear ion trap mass spectrometer. The mass spectrometer was operated in the positive and negative electrospray ionization mode. Mass spectral scans were obtained using information-dependent data acquisition (IDA) experiments.

Using this analytical strategy, sixty five acylglycines were detected in the urine of healthy individuals. Using traditional methods, only fifteen acylglycines have been detected in healthy urine.

Quantification using a labeling strategy is currently underway.
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