Key Points
-
The context and role of individual proteins in complexes, pathways and networks can be experimentally examined using neuroproteomics, thus, providing a logical framework for physiological properties from these sets of proteins.
-
Expression neuroproteomics, a field initiated in the early 1980s, has profiled the nervous system at different levels, from synaptic protein complexes to the entire brain.
-
Quantitative methods for mass spectrometry have opened the door to comparative neuroproteomics in many fields of neurobiology: synaptic plasticity, sleep, development, ageing, stem cell research and in the molecular pathology of brain diseases.
-
Functional neuroproteomics has characterized the spatial organization of proteins in the nervous system, particularly inside the synapse, and how proteins interact together to form functional networks. Functional neuroproteomics has also profiled post-translational modifications, such phosphorylation events, to show the complexity of the signalling pathways associated with neural function.
-
Clinical neuroproteomics has focused on studying the molecular basis of neural diseases, characterizing the cerebrospinal fluid proteome to identify disease markers and the molecular events underlying addiction.
-
The analysis of protein information from different proteomic databases with the aid of bioinformatic and statistical tools is a very powerful approach to obtain new biological information partly contributing to the understanding of physiological events however also contributing to our understanding of disease and disorders and aiding in clinical diagnosis and drug discovery.
Abstract
Advances in technology have equipped the field of neuroproteomics with refined tools for the study of the expression, interaction and function of proteins in the nervous system. In combination with bioinformatics, neuroproteomics can address the organization of dynamic, functional protein networks and macromolecular structures that underlie physiological, anatomical and behavioural processes. Furthermore, neuroproteomics is contributing to the elucidation of disease mechanisms and is a powerful tool for the identification of biomarkers.
This is a preview of subscription content, access via your institution
Relevant articles
Open Access articles citing this article.
-
Proteomic analysis of human frontal and temporal cortex using iTRAQ-based 2D LC-MS/MS
Chinese Neurosurgical Journal Open Access 05 May 2021
-
Proteomic insights into synaptic signaling in the brain: the past, present and future
Molecular Brain Open Access 17 February 2021
-
Protein signature of human skin fibroblasts allows the study of the molecular etiology of rare neurological diseases
Orphanet Journal of Rare Diseases Open Access 09 February 2021
Access options
Subscribe to this journal
Receive 12 print issues and online access
$189.00 per year
only $15.75 per issue
Rent or buy this article
Get just this article for as long as you need it
$39.95
Prices may be subject to local taxes which are calculated during checkout


References
Wasinger, V. C. et al. Progress with gene-product mapping of the Mollicutes: Mycoplasma genitalium. Electrophoresis 16, 1090–1094 (1995).
de Hoog, C. L. & Mann, M. Proteomics. Annu. Rev. Genomics Hum. Genet. 5, 267–293 (2004).
Gauss, C., Kalkum, M., Lowe, M., Lehrach, H. & Klose, J. Analysis of the mouse proteome. (I) Brain proteins: separation by two-dimensional electrophoresis and identification by mass spectrometry and genetic variation. Electrophoresis 20, 575–600 (1999).
Gygi, S. P., Rochon, Y., Franza, B. R. & Aebersold, R. Correlation between protein and mRNA abundance in yeast. Mol. Cell Biol. 19, 1720–1730 (1999).
de Godoy, L. M. et al. Comprehensive mass-spectrometry-based proteome quantification of haploid versus diploid yeast. Nature 455, 1251–1254 (2008).
Tannu, N. S. & Hemby, S. E. Methods for proteomics in neuroscience. Prog. Brain Res. 158, 41–82 (2006).
Liao, L., McClatchy, D. B. & Yates, J. R. Shotgun proteomics in neuroscience. Neuron 63, 12–26 (2009).
Ong, S. E. & Mann, M. Mass spectrometry-based proteomics turns quantitative. Nature Chem. Biol. 1, 252–262 (2005).
Focking, M. et al. 2-D DIGE as a quantitative tool for investigating the HUPO Brain Proteome Project mouse series. Proteomics 6, 4914–4931 (2006).
Fossard, C., Dale, G. & Latner, A. L. Separation of the proteins of cerebrospinal fluid using gel electrofocusing followed by electrophoresis. J. Clin. Pathol. 23, 586–589 (1970).
Delmotte, P. Gel isoelectric focusing of cerebrospinal fluid proteins: a potential diagnostic tool. Z. Klin. Chem. Klin. Biochem. 9, 334–336 (1971).
Kjellin, K. G. & Stibler, H. Protein patterns of cerebrospinal fluid in hereditary ataxias and hereditary spastic paraplegia. J. Neurol. Sci. 25, 65–74 (1975).
Latner, A. L. Some clinical biochemical aspects of isoelectric focusing. Ann. NY Acad. Sci. 209, 281–298 (1973).
O'Farrell, P. H. High resolution two-dimensional electrophoresis of proteins. J. Biol. Chem. 250, 4007–4021 (1975).
Klose, J. & von Wallenberg-Pachaly, H. Changes of soluble protein populations during organogenesis of mouse embryos as revealed by protein mapping. Dev. Biol. 51, 324–331 (1976).
Goldman, D., Merril, C. R. & Ebert, M. H. Two-dimensional gel electrophoresis of cerebrospinal fluid proteins. Clin. Chem. 26, 1317–1322 (1980).
Yun, M., Wu, W., Hood, L. & Harrington, M. Human cerebrospinal fluid protein database: edition 1992. Electrophoresis 13, 1002–1013 (1992).
Yates, J. R. 3rd., et al. Future prospects for the analysis of complex biological systems using micro-column liquid chromatography-electrospray tandem mass spectrometry. Analyst 121, 65R–76R (1996). The development of LC/MS-MS allowed for a less biased and more straightforward system to analyse very complex protein samples.
Pan, S. et al. A combined dataset of human cerebrospinal fluid proteins identified by multi-dimensional chromatography and tandem mass spectrometry. Proteomics 7, 469–473 (2007). Study reporting the largest catalogue of the human CSF proteome, an important source of biomarkers.
Klose, J. & Feller, M. Genetic variability of proteins from plasma membranes and cytosols of mouse organs. Biochem. Genet. 19, 859–870 (1981). This paper marks the beginning of the systematical classification of the brain proteome.
Jungblut, P. & Klose, J. Genetic variability of proteins from mitochondria and mitochondrial fractions of mouse organs. Biochem. Genet. 23, 227–245 (1985).
Wang, H. et al. Characterization of the mouse brain proteome using global proteomic analysis complemented with cysteinyl-peptide enrichment. J. Proteome Res. 5, 361–369 (2006). The largest profiling of a brain proteome to date retrieved 7,792 proteins, 34% of the total predicted mouse proteome.
Lein, E. S. et al. Genome-wide atlas of gene expression in the adult mouse brain. Nature 445, 168–176 (2007).
Mayford, M., Barzilai, A., Keller, F., Schacher, S. & Kandel, E. R. Modulation of an NCAM-related adhesion molecule with long-term synaptic plasticity in Aplysia. Science 256, 638–644 (1992).
Schoofs, L., Holman, G. M., Hayes, T. K., Nachman, R. J. & De Loof, A. Locustatachykinin I and II, two novel insect neuropeptides with homology to peptides of the vertebrate tachykinin family. FEBS Lett. 261, 397–401 (1990).
Svensson, M. et al. Neuropeptidomics: expanding proteomics downwards. Biochem. Soc. Trans. 35, 588–593 (2007).
Brockmann, A. et al. Quantitative peptidomics reveal brain peptide signatures of behavior. Proc. Natl Acad. Sci. USA 106, 2383–2388 (2009).
Cheng, D. et al. Relative and absolute quantification of postsynaptic density proteome isolated from rat forebrain and cerebellum. Mol. Cell Proteomics 5, 1158–1170 (2006).
McClatchy, D. B., Liao, L., Park, S. K., Venable, J. D. & Yates, J. R. Quantification of the synaptosomal proteome of the rat cerebellum during post-natal development. Genome Res. 17, 1378–1388 (2007).
Olsen, J. V., Nielsen, P. A., Andersen, J. R., Mann, M. & Wisniewski, J. R. Quantitative proteomic profiling of membrane proteins from the mouse brain cortex, hippocampus, and cerebellum using the HysTag reagent: mapping of neurotransmitter receptors and ion channels. Brain Res. 1134, 95–106 (2007).
Trinidad, J. C. et al. Quantitative analysis of synaptic phosphorylation and protein expression. Mol. Cell Proteomics 7, 684–696 (2008).
Chin, M. H. et al. Mitochondrial dysfunction, oxidative stress, and apoptosis revealed by proteomic and transcriptomic analyses of the striata in two mouse models of Parkinson's disease. J. Proteome Res. 7, 666–677 (2008).
Lovell, M. A., Xiong, S., Markesbery, W. R. & Lynn, B. C. Quantitative proteomic analysis of mitochondria from primary neuron cultures treated with amyloid beta peptide. Neurochem. Res. 30, 113–122 (2005).
Lovestone, S. et al. Proteomics of Alzheimer's disease: understanding mechanisms and seeking biomarkers. Expert Rev. Proteomics 4, 227–238 (2007).
Martins-de-Souza, D. et al. Prefrontal cortex shotgun proteome analysis reveals altered calcium homeostasis and immune system imbalance in schizophrenia. Eur. Arch. Psychiatry Clin. Neurosci. (2009).
Ogata, Y. et al. Differential protein expression in male and female human lumbar cerebrospinal fluid using iTRAQ reagents after abundant protein depletion. Proteomics 7, 3726–3734 (2007).
Prokai, L., Zharikova, A. D. & Stevens, S. M. Jr. Effect of chronic morphine exposure on the synaptic plasma-membrane subproteome of rats: a quantitative protein profiling study based on isotope-coded affinity tags and liquid chromatography/mass spectrometry. J. Mass Spectrom. 40, 169–175 (2005).
Roth, C. L., McCormack, A. L., Lomniczi, A., Mungenast, A. E. & Ojeda, S. R. Quantitative proteomics identifies a change in glial glutamate metabolism at the time of female puberty. Mol. Cell Endocrinol. 254–255, 51–59 (2006).
Salim, K. et al. Identification of proteomic changes during differentiation of adult mouse subventricular zone progenitor cells. Stem Cells Dev. 16, 143–165 (2007).
Schrimpf, S. P. et al. Proteomic analysis of synaptosomes using isotope-coded affinity tags and mass spectrometry. Proteomics 5, 2531–2541 (2005).
Gevaert, K. et al. Stable isotopic labeling in proteomics. Proteomics 8, 4873–4885 (2008).
Becker, M., Nothwang, H. G. & Friauf, E. Different protein profiles in inferior colliculus and cerebellum: a comparative proteomic study. Neuroscience 154, 233–244 (2008).
Alexander-Kaufman, K., Dedova, I., Harper, C. & Matsumoto, I. Proteome analysis of the dorsolateral prefrontal region from healthy individuals. Neurochem. Int. 51, 433–439 (2007).
Petyuk, V. A. et al. Spatial mapping of protein abundances in the mouse brain by voxelation integrated with high-throughput liquid chromatography-mass spectrometry. Genome Res. 17, 328–336 (2007).
Crecelius, A. C. et al. Three-dimensional visualization of protein expression in mouse brain structures using imaging mass spectrometry. J. Am. Soc. Mass Spectrom. 16, 1093–1099 (2005).
Le Bihan, T. et al. Differential analysis of membrane proteins in mouse fore- and hindbrain using a label-free approach. J. Proteome Res. 5, 2701–2710 (2006).
Hamacher, M. et al. Inside SMP proteomics: six years German Human Brain Proteome Project (HBPP) — a summary. Proteomics 8, 1118–1128 (2008).
Fountoulakis, M., Hardmaier, R., Schuller, E. & Lubec, G. Differences in protein level between neonatal and adult brain. Electrophoresis 21, 673–678 (2000).
Fountoulakis, M., Juranville, J. F., Dierssen, M. & Lubec, G. Proteomic analysis of the fetal brain. Proteomics 2, 1547–1576 (2002).
Maurer, M. H., Feldmann, R. E. Jr, Burgers, H. F. & Kuschinsky, W. Protein expression differs between neural progenitor cells from the adult rat brain subventricular zone and olfactory bulb. BMC Neurosci. 9, 7 (2008).
Skalnikova, H., Vodicka, P., Gadher, S. J. & Kovarova, H. Proteomics of neural stem cells. Expert Rev. Proteomics 5, 175–186 (2008).
McNair, K., Davies, C. H. & Cobb, S. R. Plasticity-related regulation of the hippocampal proteome. Eur. J. Neurosci. 23, 575–580 (2006).
Henninger, N. et al. Spatial learning induces predominant downregulation of cytosolic proteins in the rat hippocampus. Genes Brain Behav. 6, 128–140 (2007).
Piccoli, G. et al. Proteomic analysis of activity-dependent synaptic plasticity in hippocampal neurons. J. Proteome Res. 6, 3203–3215 (2007).
Pinaud, R., Osorio, C., Alzate, O. & Jarvis, E. D. Profiling of experience-regulated proteins in the songbird auditory forebrain using quantitative proteomics. Eur. J. Neurosci. 27, 1409–1422 (2008).
O'Hara, B. F., Ding, J., Bernat, R. L. & Franken, P. Genomic and proteomic approaches towards an understanding of sleep. CNS Neurol. Disord. Drug Targets. 6, 71–81 (2007).
Nilsen, J., Irwin, R. W., Gallaher, T. K. & Brinton, R. D. Estradiol in vivo regulation of brain mitochondrial proteome. J. Neurosci. 27, 14069–14077 (2007).
Moller, M., Sparre, T., Bache, N., Roepstorff, P. & Vorum, H. Proteomic analysis of day-night variations in protein levels in the rat pineal gland. Proteomics 7, 2009–2018 (2007).
Seo, H. S. et al. Effects of coffee bean aroma on the rat brain stressed by sleep deprivation: a selected transcript- and 2D gel-based proteome analysis. J. Agric. Food Chem. 56, 4665–4673 (2008).
Tsugita, A. et al. Proteome analysis of mouse brain: two-dimensional electrophoresis profiles of tissue proteins during the course of aging. Electrophoresis 21, 1853–1871 (2000).
Chen, W., Ji, J., Xu, X., He, S. & Ru, B. Proteomic comparison between human young and old brains by two-dimensional gel electrophoresis and identification of proteins. Int. J. Dev. Neurosci. 21, 209–216 (2003).
Sato, Y., Yamanaka, H., Toda, T., Shinohara, Y. & Endo, T. Comparison of hippocampal synaptosome proteins in young-adult and aged rats. Neurosci. Lett. 382, 22–26 (2005).
Poon, H. F., Vaishnav, R. A., Butterfield, D. A., Getchell, M. L. & Getchell, T. V. Proteomic identification of differentially expressed proteins in the aging murine olfactory system and transcriptional analysis of the associated genes. J. Neurochem. 94, 380–392 (2005).
Yang, S. et al. Comparative proteomic analysis of brains of naturally aging mice. Neuroscience 154, 1107–1120 (2008).
Dencher, N. A., Frenzel, M., Reifschneider, N. H., Sugawa, M. & Krause, F. Proteome alterations in rat mitochondria caused by aging. Ann. NY Acad. Sci. 1100, 291–298 (2007).
Emes, R. D. et al. Evolutionary expansion and anatomical specialization of synapse proteome complexity. Nature Neurosci. 11, 799–806 (2008). Comparative neuroproteomics on synapse evolution identifies a similar, although simplified, version of postsynaptic proteome in invertebrates.
Whittaker, V. P., Michaelson, I. A. & Kirkland, R. J. The separation of synaptic vesicles from nerve-ending particles ('synaptosomes'). Biochem. J. 90, 293–303 (1964).
Husi, H., Ward, M. A., Choudhary, J. S., Blackstock, W. P. & Grant, S. G. Proteomic analysis of NMDA receptor-adhesion protein signaling complexes. Nature Neurosci. 3, 661–669 (2000). First demonstration that large protein complexes are associated with neurotransmitter receptors.
Fernandez, E. et al. Targeted tandem affinity purification of PSD-95 recovers core postsynaptic complexes and schizophrenia susceptibility proteins. Mol. Syst. Biol. 5, 269 (2009). First example of genetically modified mice using gene targeting to isolate in vivo protein complexes using tandem affinity purification tags.
Grant, S. G., Marshall, M. C., Page, K. L., Cumiskey, M. A. & Armstrong, J. D. Synapse proteomics of multiprotein complexes: en route from genes to nervous system diseases. Hum. Mol. Genet. 14, R225–R234 (2005).
Farr, C. D. et al. Proteomic analysis of native metabotropic glutamate receptor 5 protein complexes reveals novel molecular constituents. J. Neurochem. 91, 438–450 (2004).
Becamel, C. et al. The serotonin 5-HT2A and 5-HT2C receptors interact with specific sets of PDZ proteins. J. Biol. Chem. 279, 20257–20266 (2004).
Kabbani, N., Woll, M. P., Levenson, R., Lindstrom, J. M. & Changeux, J. P. Intracellular complexes of the β2 subunit of the nicotinic acetylcholine receptor in brain identified by proteomics. Proc. Natl Acad. Sci. USA 104, 20570–20575 (2007).
Leonoudakis, D., Conti, L. R., Radeke, C. M., McGuire, L. M. & Vandenberg, C. A. A multiprotein trafficking complex composed of SAP97, CASK, Veli, and Mint1 is associated with inward rectifier Kir2 potassium channels. J. Biol. Chem. 279, 19051–19063 (2004).
Klemmer, P., Smit, A. B. & Li, K. W. Proteomics analysis of immuno-precipitated synaptic protein complexes. J. Proteomics 72, 82–90 (2009).
Collins, M. O. et al. Molecular characterization and comparison of the components and multiprotein complexes in the postsynaptic proteome. J. Neurochem. 97 (Suppl. 1), 16–23 (2006).
Selimi, F., Cristea, I. M., Heller, E., Chait, B. T. & Heintz, N. Proteomic studies of a single CNS synapse type: the parallel fiber/purkinje cell synapse. PLoS Biol. 7, e83 (2009).
Grant, S. G. Toward a molecular catalogue of synapses. Brain Res. Rev. 55, 445–449 (2007).
Takamori, S. et al. Molecular anatomy of a trafficking organelle. Cell 127, 831–846 (2006). Use of proteomics with structural biology to propose a three-dimensional model of synaptic vesicles.
Burre, J. & Volknandt, W. The synaptic vesicle proteome. J. Neurochem. 101, 1448–1462 (2007).
Phillips, G. R. et al. The presynaptic particle web: ultrastructure, composition, dissolution, and reconstitution. Neuron 32, 63–77 (2001).
Phillips, G. R. et al. Proteomic comparison of two fractions derived from the transsynaptic scaffold. J. Neurosci. Res. 81, 762–775 (2005).
Fields, S. & Song, O. A novel genetic system to detect protein-protein interactions. Nature 340, 245–246 (1989).
Giot, L. et al. A protein interaction map of Drosophila melanogaster. Science 302, 1727–1736 (2003).
Cusick, M. E., Klitgord, N., Vidal, M. & Hill, D. E. Interactome: gateway into systems biology. Hum. Mol. Genet. 14, R171–R181 (2005).
Goehler, H. et al. A protein interaction network links GIT1, an enhancer of huntingtin aggregation, to Huntington's disease. Mol. Cell 15, 853–865 (2004).
Lim, J. et al. A protein-protein interaction network for human inherited ataxias and disorders of Purkinje cell degeneration. Cell 125, 801–814 (2006). References 86 and 87 report pioneering work using bioinformatics analysis of neuroproteomics data to gain insight into human disease.
Munton, R. P. et al. Qualitative and quantitative analyses of protein phosphorylation in naive and stimulated mouse synaptosomal preparations. Mol. Cell Proteomics 6, 283–293 (2007).
Coba, M. P. et al. Neurotransmitters drive combinatorial multistate postsynaptic density networks. Sci. Signal 2, ra19 (2009). Synapse phosphoproteomics reveals a high degree of complexity and combination of methods to generate the first site-specific phosphorylation map of a proteome.
Mann, M. & Jensen, O. N. Proteomic analysis of post-translational modifications. Nature Biotechnol. 21, 255–261 (2003).
Witze, E. S., Old, W. M., Resing, K. A. & Ahn, N. G. Mapping protein post-translational modifications with mass spectrometry. Nature Methods 4, 798–806 (2007).
Thompson, S. J., Loftus, L. T., Ashley, M. D. & Meller, R. Ubiquitin-proteasome system as a modulator of cell fate. Curr. Opin. Pharmacol. 8, 90–95 (2008).
Khidekel, N. et al. Probing the dynamics of O-GlcNAc glycosylation in the brain using quantitative proteomics. Nature Chem. Biol. 3, 339–348 (2007).
Kang, R. et al. Neural palmitoyl-proteomics reveals dynamic synaptic palmitoylation. Nature 456, 904–909 (2008).
Schoneich, C. Protein modification in aging: an update. Exp. Gerontol 41, 807–812 (2006).
Hekimi, S. & Guarente, L. Genetics and the specificity of the aging process. Science 299, 1351–1354 (2003).
Sacksteder, C. A. et al. Endogenously nitrated proteins in mouse brain: links to neurodegenerative disease. Biochemistry 45, 8009–8022 (2006).
Gokulrangan, G., Zaidi, A., Michaelis, M. L. & Schoneich, C. Proteomic analysis of protein nitration in rat cerebellum: effect of biological aging. J. Neurochem. 100, 1494–1504 (2007).
Poon, H. F., Vaishnav, R. A., Getchell, T. V., Getchell, M. L. & Butterfield, D. A. Quantitative proteomics analysis of differential protein expression and oxidative modification of specific proteins in the brains of old mice. Neurobiol. Aging 27, 1010–1019 (2006).
Kaindl, A. M. et al. Acute and long-term proteome changes induced by oxidative stress in the developing brain. Cell Death Differ. 13, 1097–1109 (2006).
Wulfkuhle, J. D., Liotta, L. A. & Petricoin, E. F. Proteomic applications for the early detection of cancer. Nature Rev. Cancer 3, 267–275 (2003).
Lv, L. L. & Liu, B. C. High-throughput antibody microarrays for quantitative proteomic analysis. Expert Rev. Proteomics 4, 505–513 (2007).
Rohner, T. C., Staab, D. & Stoeckli, M. MALDI mass spectrometric imaging of biological tissue sections. Mech. Ageing Dev. 126, 177–185 (2005).
Mustafa, D., Kros, J. M. & Luider, T. Combining laser capture microdissection and proteomics techniques. Methods Mol. Biol. 428, 159–178 (2008). A methods paper that shows the potential of laser capture microdissection coupled with proteomics to study the brain molecular complexity.
Whittle, I. R. et al. Proteomic analysis of gliomas. Br. J. Neurosurg. 21, 576–582 (2007).
Chumbalkar, V., Sawaya, R. & Bogler, O. Proteomics: the new frontier also for brain tumor research. Curr. Probl. Cancer 32, 143–154 (2008).
Yang, J. W., Czech, T., Felizardo, M., Baumgartner, C. & Lubec, G. Aberrant expression of cytoskeleton proteins in hippocampus from patients with mesial temporal lobe epilepsy. Amino Acids 30, 477–493 (2006).
Jiang, W. et al. Preliminary explorations of the role of mitochondrial proteins in refractory epilepsy: some findings from comparative proteomics. J. Neurosci. Res. 85, 3160–3170 (2007).
Rubinsztein, D. C. Protein-protein interaction networks in the spinocerebellar ataxias. Genome Biol. 7, 229 (2006).
Fountoulakis, M., Gulesserian, T. & Lubec, G. Overexpression of C1-tetrahydrofolate synthase in fetal Down syndrome brain. J. Neural Transm. Suppl. 67 85–93 (2003).
Ottens, A. K. et al. Novel neuroproteomic approaches to studying traumatic brain injury. Prog. Brain Res. 161, 401–418 (2007).
Steinman, L. New targets for treatment of multiple sclerosis. J. Neurol. Sci. 274, 1–4 (2008).
Van Elzen, R., Moens, L. & Dewilde, S. Expression profiling of the cerebral ischemic and hypoxic response. Expert Rev. Proteomics 5, 263–282 (2008).
Carboni, L. et al. Proteomic analysis of rat hippocampus and frontal cortex after chronic treatment with fluoxetine or putative novel antidepressants: CRF1 and NK1 receptor antagonists. Eur. Neuropsychopharmacol. 16, 521–537 (2006).
Khawaja, X., Xu, J., Liang, J. J. & Barrett, J. E. Proteomic analysis of protein changes developing in rat hippocampus after chronic antidepressant treatment: Implications for depressive disorders and future therapies. J. Neurosci. Res. 75, 451–460 (2004).
Corena-McLeod, M. D. et al. Paliperidone as a mood stabilizer: a pre-frontal cortex synaptoneurosomal proteomics comparison with lithium and valproic acid after chronic treatment reveals similarities in protein expression. Brain Res. 1233, 8–19 (2008).
O'Brien, E. et al. Effects of chronic risperidone treatment on the striatal protein profiles in rats. Brain Res. 1113, 24–32 (2006).
Matsumoto, I. Proteomics approach in the study of the pathophysiology of alcohol-related brain damage. Alcohol Alcohol. 44, 171–176 (2009).
Freeman, W. M. et al. Distinct proteomic profiles of amphetamine self-administration transitional states. Pharmacogenomics J. 5, 203–214 (2005).
Iwazaki, T., McGregor, I. S. & Matsumoto, I. Protein expression profile in the amygdala of rats with methamphetamine-induced behavioral sensitization. Neurosci. Lett. 435, 113–119 (2008).
Tannu, N. S., Howell, L. L. & Hemby, S. E. Integrative proteomic analysis of the nucleus accumbens in rhesus monkeys following cocaine self-administration. Mol. Psychiatry 27 May 2008 (doi: 10.1038/mp.2008.53).
Bierczynska-Krzysik, A. et al. Rat brain proteome in morphine dependence. Neurochem. Int. 49, 401–406 (2006).
Moron, J. A. et al. Morphine administration alters the profile of hippocampal postsynaptic density-associated proteins: a proteomics study focusing on endocytic proteins. Mol. Cell Proteomics 6, 29–42 (2007). A good example of how comparative proteomics can be used to study molecular changes caused by drug abuse.
Zhang, J., Keene, C. D., Pan, C., Montine, K. S. & Montine, T. J. Proteomics of Human Neurodegenerative Diseases. J. Neuropathol. Exp. Neurol. (2008).
Leverenz, J. B. et al. Proteomic identification of novel proteins in cortical lewy bodies. Brain Pathol. 17, 139–145 (2007).
Xia, Q. et al. Proteomic identification of novel proteins associated with Lewy bodies. Front. Biosci. 13, 3850–3856 (2008).
Fasano, M. & Lopiano, L. Alpha-synuclein and Parkinson's disease: a proteomic view. Expert Rev. Proteomics 5, 239–248 (2008). A neuroproteomics review proposing deregulation of cytoskeletal proteins as the origin for Parkinson's disease.
Lim, K. L. Ubiquitin-proteasome system dysfunction in Parkinson's disease: current evidence and controversies. Expert Rev. Proteomics 4, 769–781 (2007).
Butterfield, D. A. & Sultana, R. Redox proteomics: understanding oxidative stress in the progression of age-related neurodegenerative disorders. Expert Rev. Proteomics 5, 157–160 (2008).
Boyd-Kimball, D. et al. Proteomic identification of proteins specifically oxidized by intracerebral injection of amyloid beta-peptide (1–42) into rat brain: Implications for Alzheimer's disease. Neuroscience 132, 313–324 (2005).
Keller, J. N. et al. Evidence of increased oxidative damage in subjects with mild cognitive impairment. Neurology 64, 1152–1156 (2005).
Butterfield, D. A. et al. Redox proteomics identification of oxidatively modified hippocampal proteins in mild cognitive impairment: Insights into the development of Alzheimer's disease. Neurobiol. Dis. 22, 223–232 (2006).
Edgar, P. F. et al. A comparative proteome analysis of hippocampal tissue from schizophrenic and Alzheimer's disease individuals. Mol. Psychiatry 4, 173–178 (1999).
Edgar, P. F. et al. Comparative proteome analysis of the hippocampus implicates chromosome 6q in schizophrenia. Mol. Psychiatry 5, 85–90 (2000).
Beasley, C. L. et al. Proteomic analysis of the anterior cingulate cortex in the major psychiatric disorders: evidence for disease-associated changes. Proteomics 6, 3414–3425 (2006).
Johnston-Wilson, N. L. et al. Disease-specific alterations in frontal cortex brain proteins in schizophrenia, bipolar disorder, and major depressive disorder. The Stanley Neuropathology Consortium. Mol. Psychiatry 5, 142–149 (2000).
Prabakaran, S. et al. Mitochondrial dysfunction in schizophrenia: evidence for compromised brain metabolism and oxidative stress. Mol. Psychiatry 9, 684–697, 643 (2004).
Mu, J. et al. Neurogenesis and major depression: implications from proteomic analyses of hippocampal proteins in a rat depression model. Neurosci. Lett. 416, 252–256 (2007).
Pennington, K. et al. Prominent synaptic and metabolic abnormalities revealed by proteomic analysis of the dorsolateral prefrontal cortex in schizophrenia and bipolar disorder. Mol. Psychiatry 13, 1102–1117 (2008). Report showing how neuroproteomics can molecularly differentiate schizophrenia from bipolar disorder and identify new molecules involved in these diseases.
Clark, D., Dedova, I., Cordwell, S. & Matsumoto, I. A proteome analysis of the anterior cingulate cortex gray matter in schizophrenia. Mol. Psychiatry 11, 459–470, 423 (2006).
Pennington, K., Dicker, P., Dunn, M. J. & Cotter, D. R. Proteomic analysis reveals protein changes within layer 2 of the insular cortex in schizophrenia. Proteomics 8, 5097–5107 (2008).
Behan, A., Byrne, C., Dunn, M. J., Cagney, G. & Cotter, D. R. Proteomic analysis of membrane microdomain-associated proteins in the dorsolateral prefrontal cortex in schizophrenia and bipolar disorder reveals alterations in LAMP, STXBP1 and BASP1 protein expression. Mol. Psychiatry 14, 601–613 (2008).
Dalrymple, A. et al. Proteomic profiling of plasma in Huntington's disease reveals neuroinflammatory activation and biomarker candidates. J. Proteome Res. 6, 2833–2840 (2007).
Hye, A. et al. Proteome-based plasma biomarkers for Alzheimer's disease. Brain 129, 3042–3050 (2006).
Kumar, C. & Mann, M. Bioinformatics analysis of mass spectrometry-based proteomics data sets. FEBS Lett. 583, 1703–1712 (2009).
Huang da, W., Sherman, B. T. & Lempicki, R. A. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 37, 1–13 (2009).
Gentleman, R. C. et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 5, R80 (2004).
Pocklington, A. J., Cumiskey, M., Armstrong, J. D. & Grant, S. G. The proteomes of neurotransmitter receptor complexes form modular networks with distributed functionality underlying plasticity and behaviour. Mol. Syst. Biol. 2, 2006.0023 (2006).
Sayers, E. W. et al. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 37, D5–D15 (2009).
Croning, M. D., Marshall, M. C., McLaren, P., Armstrong, J. D. & Grant, S. G. G2Cdb: the Genes to Cognition database. Nucleic Acids Res. 37, D846–D851 (2009).
Zhang, W. et al. SynDB: a Synapse protein DataBase based on synapse ontology. Nucleic Acids Res. 35, D737–D741 (2007).
Aebersold, R. & Mann, M. Mass spectrometry-based proteomics. Nature 422, 198–207 (2003).
Siuzdak, G. The expanding role of mass spectrometry in biotechnology, 2nd Edition. (MCC Press, San Diego 2006).
Wilson, K. E. et al. Functional genomics and proteomics: application in neurosciences. J. Neurol. Neurosurg. Psychiatry 75, 529–538 (2004).
Patterson, S. D. & Aebersold, R. H. Proteomics: the first decade and beyond. Nature Genet. 33 (Suppl), 311–323 (2003).
Twyman, R. M. Principles of Proteomics. (Garland Science, Oxon, UK, 2004).
Collins, M. O. et al. Proteomic analysis of in vivo phosphorylated synaptic proteins. J. Biol. Chem. 280, 5972–5982 (2005).
Schutkowski, M., Reineke, U. & Reimer, U. Peptide arrays for kinase profiling. Chembiochem. 6, 513–521 (2005).
Giepmans, B. N., Adams, S. R., Ellisman, M. H. & Tsien, R. Y. The fluorescent toolbox for assessing protein location and function. Science 312, 217–224 (2006).
Berth, M., Moser, F. M., Kolbe, M. & Bernhardt, J. The state of the art in the analysis of two-dimensional gel electrophoresis images. Appl. Microbiol Biotechnol. 76, 1223–1243 (2007).
Karas, M. & Hillenkamp, F. Laser desorption ionization of proteins with molecular masses exceeding 10, 000 daltons. Anal. Chem. 60, 2299–2301 (1988).
Fenn, J. B., Mann, M., Meng, C. K., Wong, S. F. & Whitehouse, C. M. Electrospray ionization for mass spectrometry of large biomolecules. Science 246, 64–71 (1989).
Walsh, M. J. & Kuruc, N. The postsynaptic density: constituent and associated proteins characterized by electrophoresis, immunoblotting, and peptide sequencing. J. Neurochem. 59, 667–678 (1992).
Cottrell, J. S. Protein identification by peptide mass fingerprinting. Pept. Res. 7, 115–124 (1994).
Miller, D. L. et al. Peptide compositions of the cerebrovascular and senile plaque core amyloid deposits of Alzheimer's disease. Arch. Biochem. Biophys. 301, 41–52 (1993).
Appella, E., Padlan, E. A. & Hunt, D. F. Analysis of the structure of naturally processed peptides bound by class I and class II major histocompatibility complex molecules. Exs 73, 105–119 (1995).
Gygi, S. P. et al. Quantitative analysis of complex protein mixtures using isotope-coded affinity tags. Nature Biotechnol. 17, 994–999 (1999).
MacBeath, G. & Schreiber, S. L. Printing proteins as microarrays for high-throughput function determination. Science 289, 1760–1763 (2000).
Aksenov, M. Y., Aksenova, M. V., Butterfield, D. A., Geddes, J. W. & Markesbery, W. R. Protein oxidation in the brain in Alzheimer's disease. Neuroscience 103, 373–383 (2001).
Krapfenbauer, K., Berger, M., Lubec, G. & Fountoulakis, M. Changes in the brain protein levels following administration of kainic acid. Electrophoresis 22, 2086–2091 (2001).
Gavin, A. C. et al. Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature 415, 141–147 (2002).
Ficarro, S. B. et al. Phosphoproteome analysis by mass spectrometry and its application to Saccharomyces cerevisiae. Nature Biotechnol. 20, 301–305 (2002).
Hiratsuka, M. et al. Proteomics-based identification of differentially expressed genes in human gliomas: down-regulation of SIRT2 gene. Biochem. Biophys. Res. Commun. 309, 558–566 (2003).
Sugiyama, Y., Kawabata, I., Sobue, K. & Okabe, S. Determination of absolute protein numbers in single synapses by a GFP-based calibration technique. Nature Methods 2, 677–684 (2005). Absolute quantification method determines the number of PSD95 molecules in a synapse to be around 300.
Acknowledgements
A.B. acknowledges J.A. Vizcaino and L.N. van de Lagemaat for discussions; EMBO and the European Commission for funding. S.G.N.G. is supported by the Wellcome Trust Genes to Cognition Programme, European Union and the Medical Research Council.
Author information
Authors and Affiliations
Corresponding author
Supplementary information
Supplementary information S1 (table)
Biomarkers for neurological and psychiatric diseases found by proteomics in human cerebrospinal fluid. (PDF 281 kb)
Supplementary information S2 (table)
Examples of databases used in bioinformatic analyses of neuroproteomics data. (PDF 241 kb)
Related links
Glossary
- Two-dimensional electrophoresis
-
(2DE). An electrophoresis method that separates complex protein mixtures first by charge and then by molecular weight in a two-dimensional gel.
- 2DE map
-
A reference map of the spot location in a 2DE (two-dimensional electrophoresis) gel for a certain biological sample; spots in the same location in different 2DE gels correspond to the same protein.
- Liquid chromatography-tandem mass spectrometry
-
(LC-MS/MS). A gel-free technology that combines one or more chromatographic steps with two rounds of mass spectrometry to identify, with high confidence, proteins within a complex mixture.
- Synaptosomes
-
Isolated synapses from neurons, which are obtained through a fractionation procedure of a brain homogenate, in which the synapses are sheared from their dendrites and axons and enriched into a subcellular fraction.
- Yeast two hybrid
-
(Y2H). An approach to study protein-protein interactions by expressing hybrid 'bait' and 'prey' proteins fused with subunits of yeast transcription factors; if bait and prey interact the transcription factors will trigger the expression of a reporter gene.
- Redox proteomics
-
A set of proteomic methodologies focused on identifying protein post-translational modifications caused by oxidative stress.
Rights and permissions
About this article
Cite this article
Bayés, A., Grant, S. Neuroproteomics: understanding the molecular organization and complexity of the brain. Nat Rev Neurosci 10, 635–646 (2009). https://doi.org/10.1038/nrn2701
Issue Date:
DOI: https://doi.org/10.1038/nrn2701
This article is cited by
-
Protein signature of human skin fibroblasts allows the study of the molecular etiology of rare neurological diseases
Orphanet Journal of Rare Diseases (2021)
-
Proteomic insights into synaptic signaling in the brain: the past, present and future
Molecular Brain (2021)
-
Proteomic analysis of human frontal and temporal cortex using iTRAQ-based 2D LC-MS/MS
Chinese Neurosurgical Journal (2021)
-
Nanostructural Diversity of Synapses in the Mammalian Spinal Cord
Scientific Reports (2020)
-
Setting the stage for a role of the postsynaptic proteome in inherited neurometabolic disorders
Journal of Inherited Metabolic Disease (2018)