Proteomic approaches and identification of novel therapeutic targets for alcoholism

Abstract

Recent studies have shown that gene regulation is far more complex than previously believed and does not completely explain changes at the protein level. Therefore, the direct study of the proteome, considerably different in both complexity and dynamicity to the genome/transcriptome, has provided unique insights to an increasing number of researchers. During the past decade, extraordinary advances in proteomic techniques have changed the way we can analyze the composition, regulation, and function of protein complexes and pathways underlying altered neurobiological conditions. When combined with complementary approaches, these advances provide the contextual information for decoding large data sets into meaningful biologically adaptive processes. Neuroproteomics offers potential breakthroughs in the field of alcohol research by leading to a deeper understanding of how alcohol globally affects protein structure, function, interactions, and networks. The wealth of information gained from these advances can help pinpoint relevant biomarkers for early diagnosis and improved prognosis of alcoholism and identify future pharmacological targets for the treatment of this addiction.

Figure 1

Neurobiological effects of alcohol suggested by proteomic studies. To elucidate the complex effects of excessive alcohol consumption on neurons, regulated proteins reported by proteomic studies were analyzed with Ingenuity Pathway Analysis (IPA). Alcohol modulates multiple pathways, affects several biological processes, and likely activates the molecular machinery responsible for preserving cellular homeostasis. Related direct or indirect mechanisms can in turn alter several signaling pathways (including those involved in receptor-mediated neurotransmission), disturb energy metabolism, produce oxidative stress, perturb vesicular trafficking, affect cell fate, and ultimately induce permanent plastic neuronal modifications responsible for addictive behavior. White boxes describe major biological processes; blue boxes indicate enriched Ingenuity molecular and cellular functions; purple boxes display enriched ingenuity canonical pathways resulting from core analysis of 54 proteins differentially expressed in at least three independent alcohol-related proteomic studies; yellow boxes show the pathways resulting from a similar analysis involving 460 proteins collectively reported by 22 proteomic studies. Significantly enriched pathways are defined as the ones with P<0.05 and a false discovery ratio (FDR) <0.05. The P-value is calculated by Fisher's exact test right-tailed. The FDR is calculated by the method of Benjamini and Hochberg (1995).

Figure 2

Protein interaction network involving alcohol-sensitive proteins described by proteomic studies. The figure offers an example of how PPI data from different sources could be integrated with protein expression profiles by weaving molecular interaction networks. These networks provide an easy visualization (by zooming in/out, rotating, using layouts to group nodes, etc) on how sets of candidate proteins are interconnected. Plus, precise analysis of interconnectedness can be calculated, which is particularly useful in the case of large networks. The most connected node is polyubiquitin-C (UBC), a protein involved in ubiquitination pathways. As in case of other bioinformatics tools, data obtained should be verified with additional experiments and researchers should carefully filter out interactions that have not been validated, to avoid possible overinterpretation of related biological meaning. In this case, Ingenuity Pathway Analysis (IPA) functional analysis and previous literature confirm the perturbation of protein ubiquitination pathways in alcoholism. The network was generated as follows. Interacting partners from proteins listed in Table 1 were obtained from STRING 9.05 database (http://string-db.org, settings: homo sapiens, highest confidence 0.900, and no more than 50 interactors). Data were imported in Cytoscape 2.8.3 and a network was generated using the plugin NetworkAnalyzer 2.7. Purple circles indicate the original proteins identified by at least four proteomic studies, and node degree is mapped to node size. DE, number of directed edges; NC, neighborhood connectivity.