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Neuroproteomics pp 229–242Cite as

Neuropeptidomics of the Mammalian Brain

Part of the Neuromethods book series (NM,volume 57)

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.

Key words

  • Neuropeptidome
  • Hormone
  • Neuropeptide
  • Bioinformatics
  • Liquid chromatography
  • Mass spectrometry

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  • DOI: 10.1007/978-1-61779-111-6_17
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References

  1. Li, L., Sweedler, J. V. (2008) Peptides in the brain: mass spectrometry-based measurement approaches and challenges. Ann. Rev. Anal. Chem. 1, 451–483.

    CrossRef  CAS  Google Scholar 

  2. 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.

    PubMed  CrossRef  CAS  Google Scholar 

  3. 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.

    PubMed  CrossRef  CAS  Google Scholar 

  4. Schrader, M., Schulz-Knappe, P. (2001) Peptidomics technologies for human body fluids. Trends Biotechnol. 19, S55–60.

    PubMed  CrossRef  CAS  Google Scholar 

  5. 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.

    PubMed  CrossRef  CAS  Google Scholar 

  6. 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.

    PubMed  CrossRef  CAS  Google Scholar 

  7. 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.

    PubMed  CrossRef  CAS  Google Scholar 

  8. 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.

    PubMed  CrossRef  CAS  Google Scholar 

  9. 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.

    PubMed  CrossRef  CAS  Google Scholar 

  10. 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.

    PubMed  CrossRef  CAS  Google Scholar 

  11. 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.

    PubMed  CrossRef  CAS  Google Scholar 

  12. 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.

    PubMed  CrossRef  CAS  Google Scholar 

  13. Altschul, S. F., Lipman, D. J. (1990) Protein database searches for multiple alignments. Proc. Natl. Acad. Sci. USA. 87, 5509–5513.

    PubMed  CrossRef  CAS  Google Scholar 

  14. 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.

    PubMed  CrossRef  CAS  Google Scholar 

  15. 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.

    PubMed  CrossRef  CAS  Google Scholar 

  16. 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.

    PubMed  CrossRef  CAS  Google Scholar 

  17. 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.

    CrossRef  CAS  Google Scholar 

  18. Craig, R., Beavis, R. C. (2004) TANDEM: matching proteins with tandem mass spectra. Bioinformatics 20, 1466–1467.

    PubMed  CrossRef  CAS  Google Scholar 

  19. 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.

    PubMed  CrossRef  CAS  Google Scholar 

  20. 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.

    PubMed  CrossRef  CAS  Google Scholar 

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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.

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Authors and Affiliations

  1. Department of Chemistry and the Beckman Institute, University of Illinois, Urbana, IL, USA

    Jonathan V. Sweedler

Authors
  1. Fang Xie
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  2. Elena V. Romanova
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  3. Jonathan V. Sweedler
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Corresponding author

Correspondence to Jonathan V. Sweedler .

Editor information

Editors and Affiliations

  1. Ctr Neurogenomics/Cognitive Research, Dept Molecular & Cellular Neurobiology, VU University, De Boelelaan 1085, Amsterdam, 1081 HV, Netherlands

    Ka Wan Li

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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

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  • DOI: https://doi.org/10.1007/978-1-61779-111-6_17

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  • Publisher Name: Humana Press, Totowa, NJ

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