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. 2011:789:223-36.
doi: 10.1007/978-1-61779-310-3_14.

Neuropeptidomics: mass spectrometry-based qualitative and quantitative analysis

Affiliations

Neuropeptidomics: mass spectrometry-based qualitative and quantitative analysis

Ping Yin et al. Methods Mol Biol. 2011.

Abstract

Neuropeptidomics refers to a global characterization approach for the investigation of neuropeptides, often under specific physiological conditions. Neuropeptides comprise a complex set of signaling molecules that are involved in regulatory functions and behavioral control in the nervous system. Neuropeptidomics is inherently challenging because neuropeptides are spatially, temporally, and chemically heterogeneous, making them difficult to predict in silico from genomic information. Mature neuropeptides are produced from intricate enzymatic processing of precursor proteins/prohormones via a range of posttranslational modifications, resulting in multiple final peptide products from each prohormone gene. Although there are several methods for targeted peptide studies, mass spectrometry (MS), with its qualitative and quantitative capabilities, is ideally suited to the task. MS provides fast, sensitive, accurate, and high-throughput peptidomic analysis of neuropeptides without requiring prior knowledge of the peptide sequences. Aided by liquid chromatography (LC) separations and bioinformatics, MS is quickly becoming a leading technique in neuropeptidomics. This chapter describes several LC-MS analytical methods to identify, characterize, and quantify neuropeptides while emphasizing the sample preparation steps so integral to experimental success.

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Figures

Fig. 1
Fig. 1
Workflow of sample processing (A) prior to LC-MS data analysis in a typical MS-based neuropeptidomics approach for peptide identification, and (B) sample processing and succinic anhydride labeling prior to LC-MS data analysis for MS-based neuropeptide quantitation.
Fig. 2
Fig. 2
Typical LC-ESI-IT MS results using the animal model Aplysia californica. Left: a peptide was identified from the existing prohormone database via MS/MS. Right: de novo sequencing of unassigned MS/MS spectra facilitate the refinement of the existing prohormone database. The sequences in italics indicate the signal peptide of the prohormone.
Fig. 3
Fig. 3
LC-ESI-Q-TOF MS spectra of bradykinin standards labeled with isotopic succinic anhydride tags (molecular weight, 1059.55; masses after labeling 1159.62(H)/1163.66(D); charge state +2). (A). Forward labeling is within 4% of the expected ratio, 2:1. (B). Reverse labeling is within 18% of the expected ratio, 1:2.

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