Relative Quantitation of Neuropeptides over a Thousand-fold Concentration Range

2012 
Neuropeptides are essential cell-to-cell signaling molecules that influence diverse regulatory and behavioral functions within biological systems. Differing in their amino acid sequences and post-translational modifications, hundreds of neuropeptides are produced via a series of enzymatic processing steps, and their levels vary with location, time, and physiological condition. Due to their wide range of endogenous concentrations and inherent chemical complexity, using mass spectrometry (MS) to accurately quantify changes in peptide levels can be challenging. Here we evaluate three different MS systems for their ability to accurately measure neuropeptide levels: capillary liquid chromatography-electrospray ionization-ion trap (CapLC-ESI-IT) MS, ultraperformance liquid chromatography-electrospray ionization-quadrupole-time-of-flight (UPLC-LC-ESI-Q-TOF) MS, and matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) MS. Specifically, eight sample mixtures composed of five neuropeptide standards, with four technical replicates of each, were labeled with H4/D4-succinic anhydride, followed by relative peptide quantitation using the three MS platforms. For these samples, the CapLC-ESI-IT MS platform offered the most robust ability to accurately quantify peptides over a concentration range of 1200-fold, although it required larger sample sizes than the other two platforms. Both the UPLC-ESI-Q-TOF MS and the MALDI-TOF MS systems had lower limits of quantification, with the MALDI-TOF having the lowest. By implementing several data acquisition schemes and optimizing the data analysis approaches, we were able to accurately quantify peptides over a three orders of magnitude concentration range using either the UPLC or MALDI-TOF platforms. Overall these results increase our understanding of both the capabilities and limits of using MS-based approaches to measure peptides.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    53
    References
    17
    Citations
    NaN
    KQI
    []