Dataset Information

Quantitative Profiling of Long-Chain Bases by Mass Tagging and Parallel Reaction Monitoring.

ABSTRACT: Long-chain bases (LCBs) are both intermediates in sphingolipid metabolism and potent signaling molecules that control cellular processes. To understand how regulation of sphingolipid metabolism and levels of individual LCB species impinge upon physiological and pathophysiological processes requires sensitive and specific assays for monitoring these molecules. Here we describe a shotgun lipidomics method for quantitative profiling of LCB molecules. The method employs a "mass-tag" strategy where LCBs are chemically derivatized with deuterated methyliodide (CD3I) to produce trimethylated derivatives having a positively charged quaternary amine group. This chemical derivatization minimizes unwanted in-source fragmentation of LCB analytes and prompts a characteristic trimethylaminium fragment ion that enables sensitive and quantitative profiling of LCB molecules by parallel reaction monitoring on a hybrid quadrupole time-of-flight mass spectrometer. Notably, the strategy provides, for the first time, a routine for monitoring endogenous 3-ketosphinganine molecules and distinguishing them from more abundant isomeric sphingosine molecules. To demonstrate the efficacy of the methodology we report an in-depth characterization of the LCB composition of yeast mutants with defective sphingolipid metabolism and the absolute levels of LCBs in mammalian cells. The strategy is generic, applicable to other types of mass spectrometers and can readily be applied as an additional routine in workflows for global lipidome quantification and for functional studies of sphingolipid metabolism.

SUBMITTER: Ejsing CS

PROVIDER: S-EPMC4684364 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Quantitative Profiling of Long-Chain Bases by Mass Tagging and Parallel Reaction Monitoring.

Ejsing Christer S CS Bilgin Mesut M Fabregat Andreu A

PloS one 20151211 12

Long-chain bases (LCBs) are both intermediates in sphingolipid metabolism and potent signaling molecules that control cellular processes. To understand how regulation of sphingolipid metabolism and levels of individual LCB species impinge upon physiological and pathophysiological processes requires sensitive and specific assays for monitoring these molecules. Here we describe a shotgun lipidomics method for quantitative profiling of LCB molecules. The method employs a "mass-tag" strategy where L ...[more]

PMID: 26660097

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Project description:High-density lipoprotein (HDL), a lipid nanoparticle containing many different low abundance proteins, is an attractive target for clinical proteomics because its compositional heterogeneity is linked to its cardioprotective effects. Selected reaction monitoring (SRM) is currently the method of choice for targeted quantification of proteins in such a complex biological matrix. However, model system studies suggest that parallel reaction monitoring (PRM) is more specific than SRM because many product ions can be used to confirm the identity of a peptide. We therefore compared PRM and SRM for their abilities to quantify proteins in HDL, using (15)N-labeled apolipoprotein A-I (HDL's most abundant protein) as the internal standard. PRM and SRM exhibited comparable linearity, dynamic range, precision, and repeatability for protein quantification of HDL. Moreover, the single internal standard protein performed as well as protein-specific peptide internal standards when quantifying 3 different proteins. Importantly, PRM and SRM yielded virtually identical quantitative results for 26 proteins in HDL isolated from 44 subjects. Because PRM requires less method development than SRM and is potentially more specific, our observations indicate that PRM in concert with a single isotope-labeled protein is a promising new strategy for quantifying HDL proteins in translational studies.Biological significanceHDL, a complex matrix composed of lipids and proteins, is implicated in cardioprotection. Its cholesterol content correlates inversely with cardiovascular disease and it is the current metric to assess cardiovascular risk. However, the cholesterol content does not capture HDL's complexity and heterogeneity. Devising metrics that better capture HDL's cardioprotective effects, we developed an optimized method for quantification of HDL proteome, using PRM in concert with a single labeled protein as internal standard. The availability of a method that increases sample throughput without compromising the reproducibility, sensitivity, and accuracy could therefore point to better risk assessment for CVD or other diseases.

Dataset Information

Quantitative Profiling of Long-Chain Bases by Mass Tagging and Parallel Reaction Monitoring.

Publications

Quantitative Profiling of Long-Chain Bases by Mass Tagging and Parallel Reaction Monitoring.

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