Advances in proteomics analytical techniques

Proteins are fundamental components of cells which mediate many essential biological processes. Proteomics is a rapidly growing field for the study of proteome, the protein complement expressed by the genome of an organism or cell type. The large-scale analysis of proteins leads to a more comprehensive view of molecular and cellular pathways that improves the overall understanding of the complex processes supporting the living systems. The analysis of proteome is significantly challenging due to high dynamic range and difficulties in assessment of low abundance proteins and the absence of efficient purification and identification techniques. A variety of methods have been utilized for protein studies including gel-based techniques, protein microarrays, mass spectrometry-based approaches such as MALDI and SELDI, high and ultra-performance liquid chromatography and fourier transform ion cyclotron resonance mass spectrometry. NMR spectroscopy and X-Ray crystallography methods are also used for structural study of proteins. This review aims to give a brief overview of some of the above techniques and their most recent advances. We also introduce Proteominer, a recent protein enrichment technology for the exploration of the entire proteome content

Pathway and network analysis in primary open angle glaucoma

Glaucoma, a group of multifactor ocular diseases, is the second leading cause of blindness worldwide. Primary open angle [POA] is the most common type of glaucoma, characterized by progressive optic nerve degeneration. Numerous genes and proteins have been revealed to be associated with POAG, but the pathologic mechanisms of the disease are still poorly understood. Proteomics, the collective study of proteins in an organism at a given condition, has extensively been used for the high-throughput identification of proteins related to POAG. A significant obstacle in proteomics studies is the data variability which makes it hard to interpret the results. Pathway analysis and network topological information can help address the challenge and provide a greater appreciation of the disease mechanism and progression. The purpose of this paper is to determine POAG biological and network information to further understand the mechanisms associated with POAG. PANTHER classification system was used, including classification with gene ontology, protein class and pathway. 474 gene/protein IDs were extracted from previous proteomic studies. Among pathways found by PANTHER classification, apoptosis signaling pathway was the most significant pathway [with the p-value of 5.54E-12]. Other PANTHER categories results demonstrated that developmental processes, receptor binding, extracellular region and extracellular matrix proteins were the most significant biological process, molecular function, cellular component and protein class respectively. Pathway analysis aids to find probable mechanisms involved in POAG. A network analysis on proteins was also performed using STRING database and cytoscape software. From network analysis, candidate biomarkers for the disease were introduced