Neuroproteomics approaches to decipher neuronal regeneration and degeneration

Abstract

Given the complexity of brain and nerve tissues, systematic approaches are essential to understand normal physiological conditions and functional alterations in neurological diseases. Mass spectrometry-based proteomics is increasingly used in neurosciences to determine both basic and clinical differential protein expression, protein-protein interactions, and post-translational modifications. Proteomics approaches are especially useful to understand the mechanisms of nerve regeneration and degeneration because changes in axons following injury or in disease states often occur without the contribution of transcriptional events in the cell body. Indeed, the current understanding of axonal function in health and disease emphasizes the role of proteolysis, local axonal protein synthesis, and a broad range of post-translational modifications. Deciphering how axons regenerate and degenerate has thus become a postgenomics problem, which depends in part on proteomics approaches. This review focuses on recent proteomics approaches designed to uncover the mechanisms and molecules involved in neuronal regeneration and degeneration. It emerges that the principal degenerative mechanisms converge to oxidative stress, dysfunctions of axonal transport, mitochondria, chaperones, and the ubiquitin-proteasome systems. The mechanisms regulating nerve regeneration also impinge on axonal transport, cytoskeleton, and chaperones in addition to changes in signaling pathways. We also discuss the major challenges to proteomics work in the nervous system given the complex organization of the brain and nerve tissue at the anatomical, cellular, and subcellular levels.

Fig. 1.

Schematic of molecular events involved in neuronal regeneration and degeneration as revealed by proteomics studies. A correlation emerges between axonal regeneration and degeneration: most proteins mediating regeneration are found to be either modified (and thus possibly malfunctioning) or reduced in degeneration. A, multiple molecular events contribute to the regeneration scenario. Elevation in protein levels of growth cone-enriched proteins such as stathmin, GAP-43, and CRMP-2 enhances axonal outgrowth. The retrograde transport of several positive axonal injury signaling complexes plays a role in initiating the regeneration response. Chaperones (crystallin and HSP27) and antioxidant proteins (Prdx2) also contribute to axonal regeneration and collateral sprouting. B, proteins involved in promoting regeneration appear to be modified by oxidation, indicative of their possible malfunction during degeneration. Retrograde transport of a specific death signal and mitochondrial dysfunction also contribute to degeneration. P-, phospho-; GDNF, glial cell-derived neurotrophic factor; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; Prdx, peroxiredoxin; Trax, translin-associated factor X.

Fig. 2.

Flowchart outlining overall strategies for neuroproteomics studies. Black arrows, tissue or cells are first fractionated to enrich for organelle, protein complex, or structure of interest. The protein mixture is then digested by a protease, typically trypsin, to produce peptides. The resulting peptides are then separated by LC and analyzed by a first mass spectrometer (MS), which determines the mass of a given peptide. Peptides are further analyzed by fragmentation in a second mass spectrometer, which determines the peptide sequence and thus the protein identity by simultaneously searching against a protein database. Characterization of complex protein mixtures using LC/MS/MS is also called shotgun proteomics (see Ref. for more details on mass-spectrometry based proteomics). Gray arrows, two-dimensional (2D) PAGE offers another approach to protein identification. The protein mixture is first analyzed by 2D-PAGE, and then protein spots of interest are excised, digested, and analyzed by MS/MS. Orange arrows, metabolic and chemical labeling or fluorescence labeling are commonly used for quantification of proteins by mass spectrometry (quantitative proteomics). In the metabolic and chemical labeling, different isotopes are incorporated into each sample to be compared. Pairs of peptides with different isotope composition are identified, and their peak intensities provide a quantitative measurement of their relative abundance. Metabolic labeling with SILAC allows mixing samples early in the analysis process, decreasing variation due to the numerous steps in sample preparation. Chemical labeling strategies of protein mixture such as ICAT and iTRAQ offer the ability to perform quantitative proteomics on samples prepared from different tissue sources and control for some possible errors due to sample preparation. “Semiquantitative” mass spectrometry can be performed without sample labeling: the peak intensity (or area) or the peptide counts are correlated with the amount of protein in the sample. However, because samples are never mixed, errors due to sample preparation can be relatively high. When using fluorescence labeling (two-dimensional DIGE), the “spot maps” generated from the two different dyes discern the pattern of the two samples being compared. Although two-dimensional DIGE is a sensitive technique, it is limited by the two-dimensional gel electrophoresis step, which limits the type and amount of proteins being studied. Blue arrows, in addition to protein identification and quantification, mass spectrometry allows determination of post-translational modifications. For example, single phosphorylation of a peptide results in a known mass gain that allows searching for peptides with such a mass shift. However, the stoichiometry of modified versus unmodified protein species can be low, and enrichment strategies can be used before MS/MS analysis. Current strategies used to enrich for phosphoproteins include affinity purification using IMAC or titanium dioxide chromatography. Other post-translational modifications such as ubiquitination can be identified and/or quantified using affinity chromatography (AC) prior to mass spectrometry. Protein oxidation can also be studied using derivatization of oxidized proteins followed by immunodetection on two-dimensional PAGE (oxyblot). Biological networks can also be identified when proteomics approaches are combined with powerful statistical and cluster analysis.