Abstract
A suite of bioactive peptides orchestrates a variety of cellular interactions in the mammalian brain. A new bioanalytical strategy, neuropeptidomics, has evolved from the quest to characterize these important signaling peptides (SPs). The goal of a neuropeptidomics experiment is to characterize the peptides present in an intact brain, brain region, or individual neuron. To succeed, a neuropeptidomics measurement needs to deal with the large dynamic range and low abundance of some neuropeptides in a background of peptides from postmortem degradation of ubiquitous proteins. Core components of a successful neuropeptidomics study include effective tissue sampling, sensitive and robust peptide characterization, and comprehensive data analysis and interpretation. Mass spectrometry (MS) has become the central analytical approach for high-throughput, high-confidence characterization of the brain peptidome because of its capability to detect, identify, and quantify known and unknown peptides. Robust fractionation techniques, such as two-dimensional liquid chromatography, are commonly used in conjunction with MS to enhance investigation of the peptidome. Identification and characterization of peptides are more complex when neuropeptide prohormone genes have not been annotated. This chapter outlines techniques and describes protocols for three different experimental designs that combine MS with liquid chromatography, each aimed at high-throughput discovery of peptides in brain tissue. Further, we describe the currently available bioinformatics tools for automatic query of the experimental data against existing protein databases, as well as manual retrieval of structural information from raw MS data.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Li, L., Sweedler, J. V. (2008) Peptides in the brain: mass spectrometry-based measurement approaches and challenges. Ann. Rev. Anal. Chem. 1, 451–483.
Boonen, K., Landuyt, B., Baggerman, G., Husson, S. J., Huybrechts, J., Schoofs, L. (2008) Peptidomics: the integrated approach of MS, hyphenated techniques and bioinformatics for neuropeptide analysis. J. Sep. Sci. 31, 427–445.
Clynen, E., Baggerman, G., Veelaert, D., Cerstiaens, A., Van der Horst, D., Harthoorn, L., et al. (2001) Peptidomics of the pars intercerebralis-corpus cardiacum complex of the migratory locust, Locusta migratoria. Eur. J. Biochem. 268, 1929–1939.
Schrader, M., Schulz-Knappe, P. (2001) Peptidomics technologies for human body fluids. Trends Biotechnol. 19, S55–60.
Verhaert, P., Uttenweiler-Joseph, S., de Vries, M., Loboda, A., Ens, W., Standing, K. G. (2001) Matrix-assisted laser desorption/ionization quadrupole time-of-flight mass spectrometry: an elegant tool for peptidomics. Proteomics 1, 118–131.
Bora, A., Annangudi, S. P., Millet, L. J., Rubakhin, S. S., Forbes, A. J., Kelleher, N. L., et al. (2008) Neuropeptidomics of the supraoptic rat nucleus. J. Proteome Res. 7, 4992–5003.
Che, F. Y., Lim, J., Pan, H., Biswas, R., Fricker, L. D. (2005) Quantitative neuropeptidomics of microwave-irradiated mouse brain and pituitary. Mol. Cell Proteomics 4, 1391–1405.
Boonen, K., Baggerman, G., D’Hertog, W., Husson, S. J., Overbergh, L., Mathieu, C., et al. (2007) Neuropeptides of the islets of Langerhans: a peptidomics study. Gen. Comp. Endocrinol. 152, 231–241.
Dowell, J. A., Heyden, W. V., Li, L. (2006) Rat neuropeptidomics by LC-MS/MS and MALDI-FTMS: Enhanced dissection and extraction techniques coupled with 2D RP-RP HPLC. J. Proteome Res. 5, 3368–3375.
Zhang, X., Scalf, M., Berggren, T. W., Westphall, M. S., Smith, L. M. (2006) Identification of mammalian cell lines using MALDI-TOF and LC-ESI-MS/MS mass spectrometry. J. Am. Soc. Mass Spectrom. 17, 490–499.
Canas, B., Pineiro, C., Calvo, E., Lopez-Ferrer, D., Gallardo, J. M. (2007) Trends in sample preparation for classical and second generation proteomics. J. Chromatogr. A 1153, 235–258.
Garden, R. W., Shippy, S. A., Li, L., Moroz, T. P., Sweedler, J. V. (1998) Proteolytic processing of the Aplysia egg-laying hormone prohormone. Proc. Natl. Acad. Sci. USA. 95, 3972–3977.
Altschul, S. F., Lipman, D. J. (1990) Protein database searches for multiple alignments. Proc. Natl. Acad. Sci. USA. 87, 5509–5513.
Amare, A., Hummon, A. B., Southey, B. R., Zimmerman, T. A., Rodriguez-Zas, S. L., Sweedler, J. V. (2006) Bridging neuropeptidomics and genomics with bioinformatics: prediction of mammalian neuropeptide prohormone processing. J. Proteome Res. 5, 1162–1167.
Southey, B. R., Amare, A., Zimmerman, T. A., Rodriguez-Zas, S. L., Sweedler, J. V. (2006) NeuroPred: a tool to predict cleavage sites in neuropeptide precursors and provide the masses of the resulting peptides. Nucleic Acids Res. 34, W267–272.
Perkins, D. N., Pappin, D. J., Creasy, D. M., Cottrell, J. S. (1999) Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20, 3551–3567.
Eng, J. K., McCormack, A. L., Yates, J. R. (1994) An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spectrom. 5, 976–989.
Craig, R., Beavis, R. C. (2004) TANDEM: matching proteins with tandem mass spectra. Bioinformatics 20, 1466–1467.
Ma, B., Zhang, K., Hendrie, C., Liang, C., Li, M., Doherty-Kirby, A., et al. (2003) PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry. Rapid Commun. Mass Spectrom. 17, 2337–2342.
Colinge, J., Masselot, A., Cusin, I., Mahe, E., Niknejad, A., Argoud-Puy, G., et al. (2004) High-performance peptide identification by tandem mass spectrometry allows reliable automatic data processing in proteomics. Proteomics 4, 1977–1984.
Acknowledgments
The project described was supported by Award Number P30 DA018310 from the National Institute on Drug Abuse (NIDA), and by Award No. NS031609 from the National Institute of Neurological Disorders and Stroke (NINDS). The content is solely the responsibility of the authors and does not necessarily represent the official views of NIDA, NINDS, or the National Institutes of Health.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer Science+Business Media, LLC
About this protocol
Cite this protocol
Xie, F., Romanova, E.V., Sweedler, J.V. (2011). Neuropeptidomics of the Mammalian Brain. In: Li, K. (eds) Neuroproteomics. Neuromethods, vol 57. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-61779-111-6_17
Download citation
DOI: https://doi.org/10.1007/978-1-61779-111-6_17
Published:
Publisher Name: Humana Press, Totowa, NJ
Print ISBN: 978-1-61779-110-9
Online ISBN: 978-1-61779-111-6
eBook Packages: Springer Protocols