Identification of Metabolite Interference Is Necessary for Accurate LC-MS Targeted Metabolomics Analysis.

Targeted metabolomics has been broadly used for metabolite measurement due to its good quantitative linearity and simple metabolite annotation workflow. However, metabolite interference, the phenomenon where one metabolite generates a peak in another metabolite's MRM setting (Q1/Q3) with a close retention time (RT), may lead to inaccurate metabolite annotation and quantification. Besides isomeric metabolites having the same precursor and product ions that may interfere with each other, we found other metabolite interferences as the result of inadequate mass resolution of triple-quadruple mass spectrometry and in-source fragmentation of metabolite ions. Characterizing the targeted metabolomics data using 334 metabolite standards revealed that about 75% of the metabolites generated measurable signals in at least one other metabolite's MRM setting. Different chromatography techniques can resolve 65-85% of these interfering signals among standards. Metabolite interference analysis combined with the manual inspection of cell lysate and serum data suggested that about 10% out of ∼180 annotated metabolites were mis-annotated or mis-quantified. These results highlight that a thorough investigation of metabolite interference is necessary for accurate metabolite measurement in targeted metabolomics.

A Simple and Efficient Method for the Substrate Identification of Amino Acid Decarboxylases.

Amino acid decarboxylases convert amino acids into different biogenic amines which regulate diverse biological processes. Therefore, identifying the substrates of amino acid decarboxylases is critical for investigating the function of the decarboxylases, especially for the new genes predicted to be amino acid decarboxylases. In the present work, we have established a simple and efficient method to identify the substrates and enzymatic activity of amino acid decarboxylases based on LC-MS methods. We chose GAD65 and AADC as models to validate our method. GAD65 and AADC were expressed in HEK 293T cells and purified through immunoprecipitation. The purified amino acid decarboxylases were subjected to enzymatic reaction with different substrate mixtures in vitro. LC-MS analysis of the reaction mixture identified depleted or accumulated metabolites, which corresponded to candidate enzyme substrates and products, respectively. Our method successfully identified the substrates and products of known amino acid decarboxylases. In summary, our method can efficiently identify the substrates and products of amino acid decarboxylases, which will facilitate future amino acid decarboxylase studies.

Allosteric Regulation of the Soluble Epoxide Hydrolase by Nitro Fatty Acids: a Combined Experimental and Computational Approach.

The human soluble epoxide hydrolase (hsEH) is a key regulator of epoxy fatty acid (EpFA) metabolism. Inhibition of sEH can maintain endogenous levels of beneficial EpFAs and reduce the levels of their corresponding diol products, thus ameliorating a variety of pathological conditions including cardiovascular, central nervous system and metabolic diseases. The quest for orthosteric drugs that bind directly to the catalytic crevice of hsEH has been prolonged and sustained over the past decades, but the disappointing outcome of clinical trials to date warrants alternative pharmacological approaches. Previously, we have shown that hsEH can be allosterically inhibited by the endogenous electrophilic lipid 15-deoxy-Δ12,14-Prostaglandin-J2, via covalent adduction to two cysteines, C423 and C522. In this study, we explore the properties and behaviour of three electrophilic lipids belonging to the class of the nitro fatty acids, namely 9- and 10-nitrooleate and 10-nitrolinoleate. Biochemical and biophysical investigations revealed that, in addition to C423 and C522, nitro fatty acids can covalently bind to additional nucleophilic residues in hsEH C-terminal domain (CTD), two of which predicted in this study to be latent allosteric sites. Systematic mapping of the protein mutational space and evaluation of possible propagation pathways delineated selected residues, both in the allosteric patches and in other regions of the enzyme, envisaged to play a role in allosteric signalling. The responses elicited by the ligands on the covalent adduction sites supports future fragment-based design studies of new allosteric effectors for hsEH with increased efficacy and selectivity.

Determination of 18 antibiotics in urine using LC-QqQ-MS/MS.

A determination method to identify and quantify 18 multi-class antibiotics in urine was developed using liquid chromatography triple quadrupole tandem mass spectrometry (LC-QqQ-MS/MS). Targeted antibiotics were extracted using preliminary dilution followed by d-SPE extraction. Specificity and selectivity, linearity, LOD and LOQ, accuracy, and precision were validated. LOQ of the majority of targeted compounds ranged from 0.3-7.5 µg/L. Excellent recovery in the range of 73-136% was achieved for most antibiotics, except macrolides whose recovery were of 52-78%. High precision was obtained with coefficients of variation (CV) less than 20%. All compounds were clearly separated and detected after a total run time of 15 min. Following development and validation, the method was applied to real urine samples where five out of 18 antibiotics were detected and high precision with CV less than 15% was obtained. The method was validated to be capable of quantifying antibiotics in urine for applications in supervision of antibiotics consumption or in pharmacokinetic studies.