""""""""Changes in the RBC proteome during health and disease"""""""" Abstract: Recent studies of the red blood cell (RBC) proteome have yielded extensive lists of both membrane and soluble proteins. While these catalogs of RBC proteins are quite impressive, they contain little if any quantitative information. The analysis of differential protein expression can be crucial for the discovery and understanding of the biological underpinnings of disease, as well as for providing novel biomarkers for diagnosis or prognosis, for assessing risk profiles and outcomes, and for identifying novel targets for individualized treatment. Within the last few years there have been significant advances in mass spectrometry and software for the quantitative, comparative analysis of complex mixtures of peptides. We hypothesize that the global quantitative expression patterns of proteins in RBC will reflect differences that exist in normal live but also those that occur due to disease. Here we propose to develop a robust, label-free proteomics platform for defining differential protein expression in RBCs. We will assess the level of technical variation, as well as define variations due to inter-individual and gender differences. We will then test the platform developed and apply it to define the differences in global protein expression patterns in two classic red blood cell disorders, Paroxysmal Nocturnal Hemoglobinuria (PNH) and Diamond Blackfan Anemia (DBA). Finally, we will use the platform developed and the signature proteins that define the disease to monitor the changes that occur in the RBC proteome during disease specific treatment. Our findings are likely to provide new insights into the pathophysiology of these diseases, and might lead to the identification of novel markers, or to the discovery of new targets for the development of diagnostic tests or drugs. Furthermore, the tools we develop should prove broadly applicable to the quantitative comparison of RBC membrane proteomes of varying physiological or disease states.
We hypothesize that the global quantitative expression patterns of red cell proteins will reflect normal physiological variations, as well as variations that occur during disease. In this grant we propose to develop a robust, label-free proteomics platform for defining differential protein expression in red blood cells. We will assess the level of technical variation associated with the platform and define variations due to normal physiological differences. We will then test the developed platform by applying it to define the differences in global protein expression patterns that occur in two classic red blood cell disorders, namely Paroxysmal Nocturnal Hemoglobinuria (PNH) and Diamond Blackfan Anemia (DBA). Our investigations are likely to provide new insights into the pathophysiology of these diseases, and might lead to the identification of novel markers, or to the discovery of new targets for the development of diagnostic tests or drugs. Furthermore, the platform we develop should prove broadly applicable to the quantitative comparison of RBC proteomes of varying physiological or disease states.
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