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.
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.
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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.
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)
- 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.
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.
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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
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