Mass spectrometry-based neuropeptidomics is one of the most powerful approaches for identification of endogenous neuropeptides in the brain. Until now, however, the identification rate of neuropeptides in neuropeptidomics is relatively low and this severely restricts insights into their biological function. In the present study, we developed a high accuracy mass spectrometry-based approach to enhance the identification rates of neuropeptides from brain tissue. Our integrated approach used mixing on column for loading aqueous and organic extracts to reduce the loss of peptides during sample treatment and used charge state-directed tandem mass spectrometry to increase the number of peptides subjected to high mass accuracy fragmentation. This approach allowed 206 peptides on average to be identified from a single mouse brain sample that was prepared using 15 μL of solutions per 1 mg of tissue. In total, we identified more than 500 endogenous peptides from mouse hypothalamus and whole brain samples. Our identification rate is about two to four times higher compared to previously reported studies conducted on mice or other species. The hydrophobic peptides, such as neuropeptide Y and galanin, could be presented and detected with hydrophilic peptides in the same LC−MS run, allowing a high coverage of peptide characterization over an organism. This will advance our understanding of the roles of diverse peptides and their links in the brain functions.

Neuropeptidomics is used to characterize endogenous peptides in the brain of tree shrews (Tupaia belangeri). Tree shrews are small animals similar to rodents in size but close relatives of primates, and are excellent models for brain research. Currently, tree shrews have no complete proteome information available on which direct database search can be allowed for neuropeptide identification. To increase the capability in the identification of neuropeptides in tree shrews, we developed an integrated mass spectrometry (MS)-based approach that combines methods including data-dependent, directed, and targeted liquid chromatography (LC)-Fourier transform (FT)-tandem MS (MS/MS) analysis, database construction, de novo sequencing, precursor protein search, and homology analysis. Using this integrated approach, we identified 107 endogenous peptides that have sequences identical or similar to those from other mammalian species. High accuracy MS and tandem MS information, with BLAST analysis and chromatographic characteristics were used to confirm the sequences of all the identified peptides. Interestingly, further sequence homology analysis demonstrated that tree shrew peptides have a significantly higher degree of homology to equivalent sequences in humans than those in mice or rats, consistent with the close phylogenetic relationship between tree shrews and primates. Our results provide the first extensive characterization of the peptidome in tree shrews, which now permits characterization of their function in nervous and endocrine system. As the approach developed fully used the conservative properties of neuropeptides in evolution and the advantage of high accuracy MS, it can be portable for identification of neuropeptides in other species for which the fully sequenced genomes or proteomes are not available.

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Neuropeptides are critical signaling molecules, involved in the regulation of diverse physiological processes including energy metabolism, pain perception and brain cognitive state. Prolonged general anesthesia has an impact on many of these processes, but the regulation of peptides by general anesthetics is poorly understood. In this study, we present an in-depth characterization of the hypothalamic neuropeptides of the tree shrew during volatile isoflurane/nitrous oxide anesthesia administered accompanying a neurosurgical procedure. Using a predicted-peptide database and hybrid spectral analysis, we first identified 85 peptides from the tree shrew hypothalamus. Differential analysis was then performed between control and experimental group animals. The levels of 12 hypothalamic peptides were up-regulated following prolonged general anesthesia. Our study revealed for the first time that several neuropeptides, including alpha-neoendorphin and somatostatin-14, were altered during general anesthesia. Our study broadens the scope for the involvement of neuropeptides in volatile anesthesia regulation, opening the possibility for investigating the associated regulatory mechanisms.

The chronic use of nicotine, the main psychoactive ingredient of tobacco smoking, alters diverse physiological processes and consequently generates physical dependence. To understand the impact of chronic nicotine on neuropeptides, which are potential molecules associated with dependence, we conducted qualitative and quantitative neuropeptidomics on the rat dorsal striatum, an important brain region implicated in the preoccupation/ craving phase of drug dependence. We used extensive LC-FT-MS/MS analyses for neuropeptide identification and LC-FT-MS in conjunction with stable isotope addition for relative quantification. The treatment with chronic nicotine for 3 months led to moderate changes in the levels of endogenous dorsal striatum peptides. Five enkephalin opioid peptides were up-regulated, although no change was observed for dynorphin peptides. Specially, nicotine altered levels of nine non-opioid peptides derived from precursors, including somatostatin and cerebellin, which potentially modulate neurotransmitter release and energy metabolism. This broad but selective impact on the multiple peptidergic systems suggests that apart from the opioid peptides, several other peptidergic systems are involved in the preoccupation/craving phase of drug dependence. Our finding permits future evaluation of the neurochemical circuits modulated by chronic nicotine exposure and provides a number of novel molecules that could serve as potential therapeutic targets for treating drug dependence. Molecular & Cellular