ABSTRACT
BACKGROUND: In proteomics studies, liquid chromatography tandem mass spectrometry data (LC-MS/MS) is quantified by spectral counts or by some measure of ion abundance. Downstream comparative analysis of protein content (e.g. Venn diagrams and network analysis) typically does not include this quantitative data and critical information is often lost. To avoid loss of spectral count data in comparative proteomic analyses, it is critical to implement a tool that can rapidly retrieve this information. RESULTS: We developed ProSave, a free and user-friendly Java-based program that retrieves spectral count data from a curated list of proteins in a large proteomics dataset. ProSave allows for the management of LC-MS/MS datasets and rapidly retrieves spectral count information for a desired list of proteins. CONCLUSIONS: ProSave is open source and freely available at https://github.com/MahajanLab/ProSave. The user manual, implementation notes, and description of methodology and examples are available on the site.
ABSTRACT
Proteomic analysis is an attractive and powerful tool for characterizing the molecular profiles of diseased tissues, such as the vitreous. The complexity of data available for analysis ranges from single (e.g., enzyme-linked immunosorbent assay [ELISA]) to thousands (e.g., mass spectrometry) of proteins, and unlike genomic analysis, which is limited to denoting risk, proteomic methods take snapshots of a diseased vitreous to evaluate ongoing molecular processes in real time. The proteome of diseased ocular tissues was recently characterized, uncovering numerous biomarkers for vitreoretinal diseases and identifying protein targets for approved drugs, allowing for drug repositioning. These biomarkers merit more attention regarding their therapeutic potential and prospective validation, as well as their value as reproducible, sensitive, and specific diagnostic markers. TRANSLATIONAL RELEVANCE: Personalized proteomics offers many advantages over alternative precision-health platforms for the diagnosis and treatment of vitreoretinal diseases, including identification of molecular constituents in the diseased tissue that can be targeted by available drugs.
ABSTRACT
Differences in regional protein expression within the human retina may explain molecular predisposition of specific regions to ophthalmic diseases like age-related macular degeneration, cystoid macular edema, retinitis pigmentosa, and diabetic retinopathy. To quantify protein levels in the human retina and identify patterns of differentially-expressed proteins, we collected foveomacular, juxta-macular, and peripheral retina punch biopsies from healthy donor eyes and analyzed protein content by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Protein expression was analyzed with 1-way ANOVA, gene ontology, pathway representation, and network analysis. We identified a mean of 1,974 proteins in the foveomacular retina, 1,999 in the juxta-macular retina, and 1,779 in the peripheral retina. Six hundred ninety-seven differentially-expressed proteins included those unique to and abundant in each anatomic region. Proteins with higher expression in each region include: heat-shock protein 90-alpha (HSP90AA1), and pyruvate kinase (PKM) in the foveomacular retina; vimentin (VIM) and fructose-bisphosphate aldolase C (ALDOC); and guanine nucleotide-binding protein subunit beta-1 (GNB1) and guanine nucleotide-binding protein subunit alpha-1 (GNAT1) in the peripheral retina. Pathway analysis identified downstream mediators of the integrin signaling pathway to be highly represented in the foveomacular region (P = 6.48 e-06). Metabolic pathways were differentially expressed among all retinal regions. Gene ontology analysis showed that proteins related to antioxidant activity were higher in the juxta-macular and the peripheral retina, but present in lower amounts in the foveomacular retina. Our proteomic analysis suggests that certain retinal regions are susceptible to different forms of metabolic and oxidative stress. The findings give mechanistic insight into retina function, reveal important molecular processes, and prioritize new pathways for therapeutic targeting.
