Recent advances in neuroproteomics and potential application to studies of drug addiction
Introduction
Recent advances in technology, instrumentation, molecular biology, and bioinformatics have made it possible to begin to analyze entire units of cellular components such as the genome, transcriptome and more recently, the proteome. Although the human genome is estimated to encode for >30 000 proteins, only a fraction of these proteins are expressed in any given cell type. Different proteins vary widely in their level of expression, with some being present in only a few copies while others (e.g., those found in muscles) may be present in millions of copies/cell. Identifying specific cellular proteomes provides opportunities for understanding the physiology of different types of cells and tissues, and as a consequence, how alterations in protein expression are responsible for specific cellular phenotypes. Moreover, identification of cellular proteomes should provide critical information about specific diseases, disease susceptibility and the effects of therapeutic intervention.
The goal of proteomic research is to comprehensively identify all proteins, their associated biological activities, and protein–protein interactions occurring in a given cell. There often is not a direct relationship between the in vivo concentration of an mRNA and its encoded protein (Gygi et al., 1999a, Greenbaum et al., 2003). Differential rates of translation of mRNAs into protein, compartmentalized protein synthesis, and differential rates of protein degradation are factors that confound the extrapolation of mRNA to protein expression profiles. It is estimated that there is an ~100-fold increase in the level of complexity of the proteome compared to the genome that results from differential splicing, protein processing, and post-translational modifications. There is also a huge range in the levels of expression of proteins in different proteomes that limits the ability to analyze all proteins in any given sample. For example, in the serum/plasma proteome there is a 1010 range in plasma protein concentrations (i.e., from 0 to 5 pg/ml for interleukin 6 to 35–50 mg/ml for albumin (Anderson and Anderson, 2002). Unlike mRNA microarray analysis there is no method available to amplify the levels of proteins. Thus, the field of proteomics faces a number of significant technical challenges.
The central nervous system (CNS) poses particular challenges to studying protein function. There is a huge level of cellular heterogeneity, with complex neuronal morphologies and the existence of unique sub-cellular compartments, such as neuronal dendrites, post-synaptic dendritic spines, axons, and pre-synaptic terminals. Alternative splicing is a common feature in the nervous system, and examples include proteins such as neurexin and cadherin, where there is the possibility to generate many thousands of different closely related splice forms from a single gene (Missler and Sudhof, 1998, Wu and Maniatis, 1999). Other examples of alternatively spliced proteins that are particularly important in the CNS include the isoforms of many different neurotransmitter receptors, ion channels, and proteins and enzymes involved in signal transduction. Splicing in neurons may therefore rival the immune system and contribute to the complexity of inter-neuronal communication found in the CNS.
There are many billions of neurons in the CNS, each neuron elaborating often many thousands of synaptic contacts. Thus, intercellular and intracellular signal transduction is a centerpiece of CNS function. It has been estimated that ~20% of human genes are involved in signal transduction (Blume-Jensen and Hunter, 2001). It is not surprising then that many of the close to 600 protein kinases and several 100s of protein phosphatases in the mammalian genome are likely to be expressed in the CNS. As a result, an added complexity of any understanding of neuronal function will require identification of the complex neuronal phosphoproteome.
In this article we briefly review recent advances in proteomic methods and their application to studies of the nervous system. To date, virtually no proteomic approaches have been used in drug addiction research. We therefore briefly discuss several potential applications of neuroproteomic techniques that we believe will be important in future studies of the actions of drugs of abuse.
Section snippets
MS-based protein identification
A common feature of protein profiling methods is their dependence upon proteolytic digestion and analysis by mass spectrometry (MS) for protein identification (Fig. 1). Peptide mass database searching compares experimentally determined peptide masses to theoretical peptide masses calculated from an in silico protein database resulting in a ranked listing of potential proteins in the sample. This approach requires that the masses of a reasonable fraction (e.g., >25%) of the candidate database
Recent studies of neuroproteomics
Analysis of the literature indicates that state-of-the-art proteomic methods have begun in the last 3 years to make some impact in neuroscience (Table 2A–D). The application of these novel techniques will be expected to provide a detailed understanding of biological pathways relevant to the nervous system. Moreover, these studies should accelerate the development of specific diagnostic and prognostic markers of diseases of the nervous system, as well as help in the development of therapeutic
Application of proteomic methods to studies of the actions of drugs of abuse
Gene microarray studies have begun to be used to elucidate some of the transcriptional changes that occur in various animal models of drug abuse (McClung and Nestler, 2003, Sokolov et al., 2003, Yuperov et al., 2003; Yao et al., 2004). However, little is known about the effects of drugs of abuse on the neuronal proteome. Changes in the levels of expression of some “likely suspects” including neurotransmitter receptors, and proteins involved in signal transduction and gene expression, are
Conclusions and future directions
In summary, it is clear from this brief survey that neuroproteomic protein profiling is currently advancing in stride with the emerging, available technologies—with DIGE and ICAT-based protein profiling representing two very attractive and perhaps complementary approaches. In all cases, sample origin and preparation are key concerns for the validity of comparative proteomic analysis. In general, it appears that in terms of sample preparation the more, the better! Prefractionation is key to
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