A novel universal neuropeptide display approach in the mass range of 300-5000 Da was developed to complement two-dimensional gel electrophoresis in the analysis of peptides and small proteins from brain tissue samples. For the analysis of neuropeptides we utilized on-line nanoscale capillary reversed phase liquid chromatography and electrospray ionization quadrupole-time of flight mass spectrometry. The method was employed for the analysis of a large number of peptides from three specific rat brain regions. Approximately 1500 peptides from each brain region were detected in the same analysis. Several of these peptides were sequenced using collision-induced dissociation and identified by database search tools. In addition, a method for comparing peptide elution profiles between samples was developed, to provide two- and three-dimensional computer graphics of the profiles and to pinpoint differences for statistical measurements. Among the characterized peptides were fragments from proteins such as hemoglobin, alpha-synuclein, stathmin, cyclophilin, actin, NADH dehydrogenase, cytochrome c oxidase and prosomatostatin, as well as the bioactive neuropeptides W-hemorphin-4, and LW-hemorphin-7. The present study showed that the combination of nanoscale reversed phase liquid chromatography and high-resolution tandem mass spectrometry provides a novel and powerful approach to investigate a large number of peptides and protein fragments in the brain.

Differential quantification of proteins and peptides by LC-MS is a promising method to acquire knowledge about biological processes, and for finding drug targets and biomarkers. However, differential protein analysis using LC-MS has been held back by the lack of suitable software tools. Large amounts of experimental data are easily generated in protein and peptide profiling experiments, but data analysis is time-consuming and labor-intensive. Here, we present a fully automated method for scanning LC-MS/MS data for biologically significant peptides and proteins, including support for interactive confirmation and further profiling. By studying peptide mixtures of known composition, we demonstrate that peptides present in different amounts in different groups of samples can be automatically screened for using statistical tests. A linear response can be obtained over almost 3 orders of magnitude, facilitating further profiling of peptides and proteins of interest. Furthermore, we apply the method to study the changes of endogenous peptide levels in mouse brain striatum after administration of reserpine, a classical model drug for inducing Parkinson disease symptoms.