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Alzate O, editor. Neuroproteomics. Boca Raton (FL): CRC Press; 2010.

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Chapter 42-D Fluorescence Difference Gel Electrophoresis (DIGE) in Neuroproteomics

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The brain is of highest interest in biomedical research and in the pharmaceutical industry due to the appearance of widespread neurological diseases such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, multiple sclerosis, and stroke. Research into protein function in the brain and its role in health and disease is advancing swiftly. In the past, research technology allowed the examination of only a few proteins at a time; however, it is rapidly becoming more common to examine simultaneously the expression of hundreds or even thousands of proteins (1). This enables a more holistic view for the comprehension of cellular processes. The importance of harnessing quantitative methodologies for the assessment of differences in protein expression is paramount. Thus, a growing body of work in neuroproteomics using two-dimensional fluorescence difference gel electrophoresis (2D-DIGE) is rapidly emerging, and a timely review of these data is warranted.

Why is it important for neuroscience research to examine thousands of proteins simultaneously? Although certain RNA molecules can act as effector molecules, proteins perform the majority of biological actions in the cell. Identifying the thousands of different proteins in a cell, the modifications to these proteins, along with their expressional level changes under different conditions, and all the protein-protein interactions is revolutionizing biology and medicine. There are many potential applications for proteomics in neuroscience (2). Comparative protein expression profiling and post-translational protein modification profiling are tasks that are best performed with DIGE.


Two-dimensional electrophoresis is one of the most commonly used techniques in proteomics. The basic principles of two-dimensional gel electrophoresis (2D-GE) remain the same since its introduction in 1975 (3,4), namely, the initial separation of proteins by isoelectric focusing (IEF, first dimension) followed by an orthogonal separation via sodium-dodecyl sulfate Polyacrylamide gel electrophoresis (SDS-PAGE) (5). It has been shown that up to 10,000 protein spots can be separated in one gel allowing high resolution proteomic analysis (6).

IEF separates proteins according to their isoelectric point (pI) (Figure 4.1). The pI of a protein is primarily a function of its amino acid sequence, although post-translational modifications can also contribute to the pI. Proteins are amphoteric molecules, capable of acting either as an acid or a base. The side chains of the amino acids in proteins have acidic or basic buffering groups that are protonated or deprotonated, depending on the pH of the solution in which the protein is present. At a particular pH, the sum of the charges of all the amino acids in a protein equals zero. IEF takes advantage of this property by placing proteins in a pH gradient and applying an electric potential. This produces an electric force by which the protein will migrate toward the anode or cathode depending on its net charge. Eventually, the protein will reach its pI and stop migrating. Initially, the preparation and use of the pH gradients needed for IEF was very difficult and inconsistent. These pH gradients were often in the form of tube gels with carrier ampholytes. The introduction of chemistries to immobilize the pH gradient into the gel matrix (7) and the construction of the gel on a solid backing (8,9) were significant steps for making IEF more widely accessible to researchers and for producing more consistent results.

FIGURE 4.1. The 2D-PAGE concept.


The 2D-PAGE concept. For the first dimension, proteins in solution are separated on an IPG strip by applying an electric field. The electric force displaces the proteins (charges) until they reach their corresponding pI. The strip is loaded onto an SDS-PAGE, (more...)

The IEF gel or strip is equilibrated in SDS and then placed on top of the SDS-PAGE gel (Figure 4.1). This equilibration step is necessary to allow the SDS molecules to associate with the proteins and produce the anionic complexes that have a net negative charge. As a result of the electric force the proteins migrate out of the IEF gel and into the SDS gel, where they separate according to their molecular weights. Although most applications use denaturing SDS-PAGE, approaches to separate proteins under non-denaturing conditions have also been developed.

After electrophoresis, the proteins in the gel must be detected. Traditionally, this is accomplished by the use of a visible stain. Very common visible stains include silver nitrate (10), which is highly sensitive. However, silver staining has complications with unwanted background formation, lack of quantitative parameters, lack of reproducibility, and lack of mass spectrometry compatibility. Other visible stains such as zinc imidazol (11) and Coomassie blue (12) have been developed, with the latter reaching almost universal use. Even though both are more compatible with mass spectrometry, zinc imidazol has limited quantitation abilities and Coomassie staining is much less sensitive than silver staining. Fluorescent stains have been developed that attempt to combine simplicity, sensitivity, quantitation, and mass spectrometry compatibility, such as ruthenium bathophenanthroline disulfonate (Sypro Ruby) (13) and Deep Purple (14,15).


The problems that have bedeviled the use of conventional 2D-GE for applications like protein expression profiling in neuroscience research are lack of reproducibility and quantitation. Just as much analysis was conducted on the shortfalls of 2D-GE at the turn of the century, a new incremental technology would revitalize the scientific proteomics community and revolutionize the field. Two-dimensional difference gel electrophoresis (2D-DIGE), introduced by Unlu et al. (16), addresses the problems of traditional 2D-GE in an elegant method (Figure 4.2).

FIGURE 4.2. The 2D-DIGE concept.


The 2D-DIGE concept. Proteins from different sources (such as a protein lysate from a control sample and a protein lysate from an analytical sample) are covalently labeled with two different CyDyes. Labeled protein lysates are mixed, and separated on (more...)

DIGE uses direct labeling of proteins with fluorescent dyes (known as CyDyes: Cy2, Cy3, and Cy5) prior to IEF (17–20). CyDyes are spectrally resolvable cyanine dyes carrying an N-hydroxysuccinimidyl ester reactive group that covalently binds the ɛ-amino groups of lysine residues in proteins. Dye concentrations are kept low, such that approximately one dye molecule is added per protein. The important aspect of the DIGE technology is its ability to label two or more samples with different dyes and separate them on the same gel, eliminating gel-to-gel variability. This makes spot matching and quantitation much simpler and more accurate. Cy2 is used for a normalization pool created from a mixture of all samples in the experiment. This Cy2-labeled pool is run on all gels, allowing spot matching and normalization of signals from different gels. The DIGE approach offers great promise to researchers. The dyes are comparable in sensitivity to silver staining methods, are compatible with mass spectrometry, and offer the best quantitation of any available method.

Sample multiplexing and the use of an internal standard in 2D-DIGE allows the analysis of replicate samples from multiple experimental conditions with unsurpassed statistical confidence for differential display proteomics (21). DIGE experiments can easily accommodate sufficient independent (biological) replicate samples to control for the large interpersonal variation expected from biological samples. The use of multivariate statistical analyses can then be used to assess the global variation in a complex set of independent samples, filtering out the noise from technical variation and normal biological variation, thereby focusing on the underlying differences that can describe various disease or biological states.


Once proteins have been visualized, image analysis is required (22). Image analysis can be segregated into spot detection, spot matching, and data analysis. Manually detecting the hundreds to thousands of spots on each traditional 2D-GE gel for the number of gels in an experiment would take several days with countless inconsistencies. For any experiment requiring multiple gels for many different conditions across multiple samples (biological replicates), the different gels must be matched to each other. In other words, a spot at a certain location on one gel must be matched with the same spot on all other gels. In reality, proteins do not migrate to exactly the same point on each gel (IEF or SDS-PAGE). Complex algorithms have been developed that attempt to match these spots across gels using spot pattern recognition and correcting for shifts in these patterns. The need for computer-based spot matching cannot be underestimated, as matching by hand can take days or even weeks, depending on the sample size. These matching algorithms continue to improve, but the best thing that can be done to aid in spot matching is to develop reproducible laboratory techniques. A common concern with 2-DE is that with a long experimental protocol of protein preparation, IEF, SDS-PAGE, visualization, and data analysis, small errors compound, thus inhibiting meaningful quantitation.

The Cy2-labeled pool used in 2D-DIGE is useful because it provides a consistent spot map on all gels in an experiment, facilitating spot matching. With DIGE the number of gels that need to be matched is reduced and sister images from the same gel will have identical spot patterns. With spots matched and with signal intensities known, comparisons can be made to determine changes in protein expression levels. The DIGE method uses the protein pool to normalize the signal abundances among gels, correcting for any differences in overall signal intensity. This provides a consistent expression measurement across gels.

It is important to keep in mind that while a comprehensive cataloging of protein species within a system could be conclusive, it is also the beginning of much further protein profiling and data analysis. Given the complexity of the neuronal proteome, it is essential to study alterations in protein expression and post-translational modifications within specific brain regions, within specific types of neurons, and within sub-cellular compartments. Awareness of the high level of biological diversity to be expected among both the control and experimental samples and the need for rigorous statistical analysis are important elements to the analysis of protein profiling data.


Compared with traditional 2D-GE, 2D-DIGE offers major advantages for studying protein expression changes in biological samples (23):


DIGE facilitates the co-separation of two proteomes to be compared, thereby diminishing the number of gels to be processed, evaluated, and interpreted by a factor of two. This saves critical resources like time and manpower. A major advantage of this technique is a significant reduction in inter-gel variability, facilitating spot identification and matching, thus increasing the number of analyzable spots.


The pooling of both samples prior to separation diminishes the false quantification of irreproducible losses (e.g., sample entry in the first-dimension gel, transfer from the first-dimension to the second-dimension gel) during the analysis. Any imprecision of the method affects similar proteins in a similar way, compensating methodological errors. Therefore, the reliability of experimental data is significantly increased.


The internal pooled standard (17) facilitates the normalization of each spot among all gels, a feature especially useful in a comprehensive study. The internal pooled standard allows the comparison of more than two proteomes without the need to perform pair-wise analysis of all possible combinations of data points.


DIGE provides the ability to detect many protein post-translational modifications, such as phosphorylation, ubiquitination, palmitoylation, etc. which often play a key role in modulating protein function and which cannot generally be detected by other protein profiling technologies.

Overall, the major advantages of DIGE are the high sensitivity and linearity of the dyes utilized, its straightforward protocol, as well as its significant reduction of inter-gel variability, which increases the possibility to unambiguously identify biological variability and reduces bias from experimental variation. Moreover, the use of a pooled internal standard, loaded together with the control and experimental samples, increases quantification accuracy and statistical confidence (17).


Neuroscientists wishing to implement neuroproteomic approaches for their research will have to surmount difficulties particular to their systems, being the most critical limited sample amounts, heterogeneous cellular compositions in samples, and the fact that many proteins of interest are rare, hydrophobic proteins. There are a number of approaches to reduce the complexity of a protein sample for analysis. Depending on the rationale for a study, analyzing the entire contents of cellular proteins in one experimental run may cause a loss of sensitivity and result in interpretational difficulties. In such cases, it is recommended that the proteome be pre-fractionated in order to remove contaminating material from the sample and to enrich the proteins of interest for further analysis (see Chapter 3 for a complete review of pre-fractionation techniques). The starting material can be fractionated using a variety of approaches including centrifugation (e.g., soluble/insoluble, membrane/cytosolic/nuclear), salt precipitation, liquid chromatographic separation (e.g., ion exchange, affinity, gel filtration), and velocity or equilibrium sedimentation.

Neuroscientists face complications specific to brain and neural tissues. When planning proteomic research, careful attention must be paid to the sample amount available relative to the sample needs of techniques being used. The temptation to use large amounts of brain tissue must be weighed against the need for regional and cellular specificity. All current methods in proteomics, including 2D-GE and DIGE, tend to identify preferentially the most abundant proteins. For neuroscientists, this represents a challenge because many proteins of interest in the brain are expressed at relatively low levels and are hydrophobic proteins. Pre-fractionation is important for extending the dynamic range of the analysis, whether it is enrichment of sub-cellular fractions or enrichment of classes of proteins (e.g., DNA binding proteins or phosphorylated proteins). Because of the deleterious effects that accompany protein overloading of samples, less abundant (and often, more important regulatory) proteins can only be detected with pre-fractionation and/or depletion of highly abundant proteins (see Chapter 3). It is important that any pre-fractionation method be standardized to avoid introduction of potential artifacts and technical variability. Another important sample preparation consideration is that without careful dissection of the tissue being analyzed, significant changes in one cell type or cell population within a given tissue may be diluted by homogenization and mixing with other neighboring unaffected cell types and subsequently disappear beneath the threshold of significance (24). With respect to sample preparation and origin, of notable concern also is postmortem brain tissue (particularly human; see Chapter 2 for a discussion of brain tissue banking and storage), of which little is known about quantitative postmortem changes in the brain protein profile (25). For studies on human brain proteomes it is important to standardize the protocols used for preparation of protein extracts.

Bernocco et al. (26) refined a detergent-based fractionation method which reduces complexity of the protein extracts. The sequential use of detergent-containing buffers on neurons in culture plates yields four extracts enriched in cytosolic, membrane-bound or enclosed, nuclear, and cytoskeletal proteins. Comparison of extracts by DIGE showed a clear difference in protein composition. An extraction efficiency of 85% was calculated for cytosolic proteins in extract 1, 90% for membrane-bound and membrane-enclosed proteins in extract 2, 82% for nuclear proteins in extract 3, and 38% for cytoskeletal and RAFT proteins in extract 4.

One of the distinct advantages of proteomic analysis, not attainable with RNA expression data, is the ability to fractionate the cell’s proteins into various subpopulations. Purification of protein from other cellular substances is also necessary. Lipids are particularly abundant in the brain, and along with nucleic acids must be eliminated from the protein sample for good-quality results. The most common methods of protein purification rely on selective precipitation. Acetone, trichloroacetic acid (TCA), and other precipitation methods can be performed, and a number of commercially available kits make this a routine procedure (27,28). In some instances proteins such as IgGs or albumin constitute the vast majority of a protein sample. Selective elimination of these proteins improves detection of less highly expressed proteins (see Chapter 3).

Protein stability and purity are of critical importance to proteomic studies; therefore, it is important to prevent protein degradation and modification(s) during sample preparation. Rapid removal of brain tissue, dissection, and freezing are obvious imperatives for the maintenance of the proteome as close as possible as it was in the animal. Human postmortem studies pose unique challenges, but these can be addressed by careful documentation of postmortem interval, brain pH, and agonal state (29) (and see Chapter 2). Specific proteins have been shown to degrade in a time-dependent manner, highlighting the need for careful selection of controls in human brain postmortem studies (30). Protease and phosphatase inhibitors are commonly used to help prevent degradation and dephosphorylation of proteins during protein preparation (31).

The number of proteomics studies concerning human brain samples has increased in recent years, in particular in the discovery of biomarkers for neurological diseases. The human brain samples are obtained from brain banks, which are interested in providing high quality human nervous tissue. In order to provide brain banks as well as scientists working in the proteomics field with measures for tissue quality, the critical factors after death, the effect of postmortem interval (PMI), and storage temperature on the human brain proteome were investigated (32). This study was focused on the gray matter of the frontal cortex. The PMI was artificially prolonged from the time of autopsy (two hours after death) by storing samples at 47°C or room temperature over 18, 24, and 48 hours. The DIGE experiment revealed the degradation of three proteins: peroxiredoxin-1, stathmin, and glial fibrillary acidic protein. These were further confirmed by Western blot analysis. In the second part of the study, prefrontal cortex samples were compared among three individual donors. 2D-DIGE was selected as the quantitative proteomics technique of choice because delayed PMI was expected to also affect post-translational modifications of proteins, which would be very difficult to monitor by any other method.


Two-dimensional electrophoresis is also limited in its ability to detect very basic proteins (pI > 10) (33). This assumption has been challenged by a recent study (34). In this instance, 2D-GE was found to be better for small-molecular-weight, hydrophobic, and cysteine-lacking proteins, whereas isotope coded affinity tag (ICAT) was found to be superior in examining high-molecular-weight proteins. Immunoblotting/ Western blotting, enzyme-linked immunoabsorbent assay (ELISA) and immunocytochemistry are all well established methods commonly used in molecular biology laboratories. These methods serve as excellent tools for validation of candidate proteins and further experimentation on targets found by DIGE in combination with mass spectrometry. At the moment, unfortunately, although this validation step should be regarded as an absolute prerequisite, antibodies are not available for every protein and high-throughput confirmation of expression changes from a DIGE experiment is practically and economically not feasible.

There are a wide variety of applications for proteomic technology in neuroscience (2). These applications range from defining the proteome of a particular cell type, identifying changes in brain protein expression under different experimental or disease conditions, profiling protein modifications (e.g., phosphorylation) and mapping protein-protein interactions. With the incredible cellular heterogeneity of the brain, there are a number of defined cell types awaiting proteomic characterization. The possibility of an international collaborative effort, along the lines of the human genome project, to catalog the brain proteome is being discussed to take on this herculean task (35).

Perhaps the proteomic application of greatest interest to neuroscience is protein expression profiling. The number of such studies is still small but growing rapidly. An advantage of profiling by proteomic methods such as DIGE is that it offers an open and unbiased screen. Protein microarrays are closed screens, on the other hand, limited to examining those genes that are deposited on the chip used in the experiment. Techniques like 2D-GE or 2D-DIGE and MS/MS can, theoretically, detect any protein in an unbiased fashion.


Since its inception in 1997, DIGE has been widely adopted in most areas of biology and medicine. DIGE has become an important tool among proteomics technologies for studying the mechanisms of disease, pinpointing new therapeutic targets or finding potential biomarkers (36). Among many other applications, DIGE has been applied to cancer research (37–41), renal physiology (42), plant biology (43–45), and the elucidation of signal transduction pathways (46), just to name a few. In neurology and neuroscience, many applications have been entertained in neurotoxi-cology and neurometabolism, and used in the determination of specific proteomic aspects of individual brain areas and body fluids in neurodegeneration to identify biomarkers. The concomitant detection of several hundred proteins on a gel provides comprehensive data to elucidate a physiological protein network and its peripheral representatives.

4.8.1. Synaptic Physiology and Structure

The auditory forebrain area in songbirds called the caudomedial nidopallium (NCM) plays a key role in auditory learning and song discrimination. The expression of few transcription factors is increased in NCM in response to the neural processes associated with auditory processing of sounds (47). DIGE-based proteomics was used to investigate the NCM of adult songbirds hearing novel songs (47). After one and three hours of stimulation of freely behaving birds with conspecific songs, a significant number of proteins were consistently regulated in NCM. These proteins included metabolic enzymes, cytoskeletal molecules, and proteins involved in neurotransmitter secretion and calcium binding (47) (see Chapter 14 for a detailed discussion of neuroproteomics studies of auditory processing of vocal communications in songbirds).

Neuroproteomics techniques including 2D-DIGE, mass spectrometry, and subcellular fractionation have been used to elucidate the protein constituents of the synapse. The proteomic characterization of the synapses will contribute in the understanding of their essential role in neurotransmission and plasticity. A map of the synapse proteome is emerging, including the proteomes of structures such as pre- and post-synaptic densities.

Burre et al. (48) induced massive exocytosis and analyzed the protein contents of the synaptic vesicle compartment using DIGE-based proteomics, to identify proteins that undergo modifications as a result of synaptic activation. They identified eight proteins that revealed significant changes in abundance following nerve terminal depolarization. Based on these results it was proposed that depolarization of the presynaptic compartment induces changes in the abundance of synaptic vesicle proteins and post-translational protein modification.

Synaptic dysfunction is an early event in Alzheimer’s disease. In a study by Gillardon et al. (49) synaptosomal fractions from Tg2576 mice over-expressing mutant human APP and from wild-type littermates were analyzed for proteomic changes. Crude synaptosomal fractions from cortical and hippocampal micro-dissected tissue were prepared by differential centrifugation and the proteins were separated by DIGE. Significant alterations were detected in the mitochondrial heat shock protein 70, which is associated with mitochondrial stress response. In addition, numerous changes in the protein subunit composition of the respiratory chain complexes I and III were identified. It is suggested that “early impairment of axonal transport may lead to aberrant axonal amyloid-beta generation and intraneuronal oligomer formation.” It is then suggested that amyloid-beta oligomers may then cause mitochondrial dysfunction and synaptic impairment leading to cognitive decline before amyloid plaque deposition (49).

4.8.2. Alzheimer’s Disease

The amyloid precursor protein (APP) plays a central role in Alzheimer’s disease pathology. Hartl et al. (50) analyzed the APP-transgenic mouse model APP23 using DIGE. Cortex and hippocampus of transgenic and wild-type mice at 1, 2, 7, and 15 months of age and cortices of 16-days-old embryos were investigated. A large number of proteins were found to be altered in wild-type mice, which were largely absent in hippocampus of APP23. From these results it was proposed that the absence of developmental proteome alterations along with the down-regulation of proteins related to plasticity suggests the disruption of a normally occurring peak of hip-pocampal plasticity during adolescence in APP23 mice (50).

In another study, it was found that mortalin (the mitochondrial Hsp70 chaperone) is differentially regulated in the brains of apoE-e4 targeted replacement (TR) mice, compared with apoE-e3 TR mice used as controls (51). Similar analysis indicated that this protein is also differentially regulated in Alzheimer’s disease patients, and that this protein regulation depends on the APOE genotype and the disease state (51).

4.8.3. Phosphorylation Trends

Profiling of protein modifications is as important as determining the proteins present in a cell and their relative expression levels. Many important cellular processes in the nervous system rely on protein modifications as a mechanism to regulate protein function. The most studied protein modifications are phosphorylation cascades in signal transduction. Using DIGE-based proteomics and lambda-phosphatase treatment, a map of phosphorylated proteins in rat cortical neurons was created (52). Losing of a phosphate group makes the pI of a protein more basic by altering its net charge; therefore, the protein migrates to a different position in a 2D-GE map compared to the phosphorylated protein. Because DIGE allows separation of phosphorylated and dephosphorylated protein samples in the same gel, changes in protein patterns after phosphatase treatment are easily detectable. Small differences in migration and small shifts toward more basic pHs are easier to detect with DIGE than with any other technique (52).

4.8.4. Brain Regions

Jacobs et al. used DIGE to screen for region-specific protein markers (53). By comparing proteome maps of the primary visual and somatosensory areas in mouse brain, they found 22 protein spots with different expression levels in one of the two primary sensory areas. Specific brain-region protein characterization is a promising method for the understanding of cortical networks and their physiological interactions.

4.8.5. Brain Regions and Development

Van den Bergh et al. (54) used DIGE to help elucidate protein expression differences in cat and kitten striate visual cortex, identifying 12 proteins that are differentially expressed. Again using DIGE, the group compared P10-P30 and P30-adult brain protein samples (55). Thirty-four proteins in cat primary visual area-17, whose expression levels from the time of eye opening toward adulthood change with age, were identified. These changes in protein expression levels could be correlated to age-dependent postnatal brain development. Western blot was used to validate some of these results in cat visual cortex (see Chapter 11 for a detailed discussion of neuroproteomics studies on the cat visual cortex). Jin et al. (56) used DIGE to study differential protein expression in immature and mature neurons in culture.

4.8.6. Schizophrenia

Comparing human prefrontal cortex from control and schizophrenic individuals using DIGE, 55 proteins with significant differences in expression in white versus grey matter were identified (57). These proteins are known to be associated with metabolism, axonal growth, protein turnover and trafficking, cell signaling, and cytoskeleton structure. In a systematic extension to this study, results were compared with mRNA microarray analysis and measurement of metabolites (58). Many of these proteins were associated with mitochondrial function or with oxidative stress responses, with the changes in protein expression correlating with changes in mRNA expression. Later, the same group used DIGE to analyze liver and red blood cells, providing further evidence for oxidative stress in schizophrenia (59).

4.8.7. Parkinson’s Disease

The protein contents of the striatum of 6 control and 21 MPTP-treated monkeys used as animal models of Parkinson’s disease were studied in a DIGE experiment, with or without de novo or long-term L-DOPA administration (60). Several sets of proteins associated with the priming effects of L-DOPA in the striatum in Parkinsonian animals were identified, including proteins involved in energy metabolism and the microtubule cytoskeleton.

4.8.8. Drug Addiction

A study was carried out aimed at understanding the effects of epidemic cocaine use entangled with HIV-1 infection, and the enhancement of HIV-1 replication in normal human astrocytes (61). Twenty-two proteins were identified in normal human astrocytes that were differentially regulated by cocaine, which directly or indirectly play a supportive role in the neuropathogenesis of HIV-1 infection.

The nucleus accumbens has been associated with the reinforcing effects and long-term consequences of cocaine self-administration. To improve the knowledge about cocaine-induced biochemical adaptations in rodent models, DIGE was used to compare changes in cytosolic protein abundance in the nucleus accumbens of rhesus monkeys self-administering cocaine and controls (62). Several protein spots were found to be differentially abundant, of which 18 proteins were identified by mass spectrometry.

In another study, Reynolds et al. (63) used DIGE to analyze the effects of meth-amphetamine (METH) on HIV-1 infectivity. It was found that METH modulates the expression of several proteins including CXCR3, protein disulfide isomerase, procathepsin B, peroxiredoxin, and galectin-1. This study suggests a mechanism for METH on HIV-1 infectivity.

4.8.9. West Nile Virus

Dhingra et al. (64) applied DIGE to study the mechanisms of neurodegeneration associated with West Nile virus infections. DIGE was used to characterize protein expression in primary rat neurons and to examine the proteomic profiling to understand the pathogenesis of meningoencephalitis associated with the disease.

4.8.10. Other Applications

There are many other examples of research projects in which DIGE-based proteomics has been used to identify molecular bases of neurological processes. These examples include protein composition in cerebrospinal fluid of traumatic brain injury patients (65); molecular mechanisms of sleep deprivation and aging (66), Western Pacific amyotrophic lateral sclerosis-Parkinsonism-dementia complex (ALS/PDC) (67); the effects of chronic ethanol treatment on the brain proteome in the long-fin striped strain of zebra fish (68); hypoxia-related protein regulation in medaka fish brain tissue (69); identification of potential biomarkers of developmental neurotoxicity of organohalogen compounds (70); phosphorylation/dephosphorylation cycles (71,72); stress response (51,73); and prion diseases (74).


There are situations where the available sample is limited, e.g., samples from clinical studies employing cerebrospinal fluid and small but functionally important regions of brain such as pituitary, especially from small animals such as rats, post- and presynaptic density preparations, and nerve fibers. In most cases, brain tissue complexity represents a major challenge. In such situations it is common to use laser microdissection (LMD) for obtaining samples suitable for proteomic studies (75). Experimental situations involving such limited amounts of protein may be addressed using other types of fluorescent dyes.

Due to the high lysine content of most proteins, labeling to saturation with the N-hydroxysuccinimide (NHS)-reactive CyDyes described so far in this chapter would require excessive amounts of reagents, and due to the hydrophobic nature of the dyes, it is likely to cause protein precipitation. Cysteine residues are typically less abundant than lysine in mammalian proteins and are therefore more amenable to total labeling. CyDye dyes containing a maleimide group (Cy-maleimides, or Cy-M) that reacts with the thiol groups of cysteine residues are available. These labels do not alter the pI of a labeled protein because they do not have a net charge (19). Each Cy-M dye adds a mass of approximately 680 Da to the protein, but all available cysteine groups are modified. This approach is commonly known as “saturation labeling.” Saturation labeling DIGE is more sensitive than traditional stains such as Coomassie, silver, or Sypro Ruby, and as little as 0.1 ng albumin has been detected with Cy5-M dye compared to 1 ng with the Cy5 minimal dye. Saturation labeling also has a greater dynamic range, around 103–104, which is an order of magnitude greater than for Sypro Ruby and for minimal labeling (76).

Wilson et al. (77) combined LMD with saturation labeling DIGE to identify protein changes in the isolated CA1 pyramidal neuron layer of a transgenic rat carrying a human amyloid precursor protein transgene. Saturation dye labeling proved to be extremely sensitive with a spot map of over 5000 proteins readily produced from 5 μg total protein, with over 100 proteins significantly altered, although identification of those proteins by mass spectrometry represented yet another substantial challenge. Saturation labeling DIGE is useful for applications in which there is limited sample.


The Human Proteome Organization Brain Proteome Project (HUPO-BPP; http:// aims at coordinating neuroproteomics efforts with respect to analysis of development, aging, and evolution in humans and mice and at analyzing normal aging processes as well as neurodegenerative diseases. A major goal of the HUPO-BPP pilot study is the evaluation of different proteomics technologies (78). Frohlich et al. (79) contributed a pilot study with a DIGE analysis of standardized mouse brain samples, consisting of whole brains from mice of three different developmental stages. Five brains per stage were differentially analyzed by DIGE using overlapping pH gradients (pH 4–7 and 6–9). In total, 214 protein spots showing stage-dependent intensity alterations were detected, 56 of which were identified. In another study Focking et al. found 206 protein spots that were differentially expressed among the different stages: 122 spots were highest in intensity in embryonic stage, 26 highest in the juvenile group, and 58 spots highest in the adult stage (80).


One of the most fundamental approaches to understanding protein function is to correlate expression level changes as a function of growth conditions, cell cycle stage, disease state, external stimuli, level of expression of other proteins, and other possible variables involving protein regulation and potential protein modifications. Along with the interrogation of DNA microarrays for their ability to indicate relative levels of mRNA expression, protein expression levels, their post-translational modifications, and their interactions should also be interrogated.

Proteomic studies complemented by genomics and more traditional molecular biology techniques are contributing significantly to build complete proteome maps of cells and organelles, under both normal and altered conditions. The valuable information provided in qualitative and quantitative proteome maps will enable further identification of mechanisms of diseases, as well as those underlying drug actions, and may contribute to the development of more effective drug treatments. Understanding the complex changes taking place in biological systems or disease at the molecular level will lead to a better understanding of the underlying mechanisms. DIGE-based proteomics is well suited to describe the molecular anatomy of a system and its changes in levels of protein and their expression pattern, including post-translational modifications.

The studies mentioned in this chapter all indicate that 2D-DIGE-based proteomics provides an alternative approach to explore and understand the molecular basis of complex mechanisms associated with neurodegenerative diseases and neurobiology. They illustrate the potential of DIGE for neuroproteomics to profile differences in the distribution and regulation of thousands of proteins at a time, to study the function of disease markers, and to identify molecular pathways that could lead to novel therapeutic targets.


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