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iAB-RBC-283: A proteomically derived knowledge-base of erythrocyte metabolism that can be used to simulate its physiological and patho-physiological states

机译:iAB-RBC-283:蛋白质组学的红细胞代谢知识库,可用于模拟其生理和病理生理状态

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Background The development of high-throughput technologies capable of whole cell measurements of genes, proteins, and metabolites has led to the emergence of systems biology. Integrated analysis of the resulting omic data sets has proved to be hard to achieve. Metabolic network reconstructions enable complex relationships amongst molecular components to be represented formally in a biologically relevant manner while respecting physical constraints. In silico models derived from such reconstructions can then be queried or interrogated through mathematical simulations. Proteomic profiling studies of the mature human erythrocyte have shown more proteins present related to metabolic function than previously thought; however the significance and the causal consequences of these findings have not been explored. Results Erythrocyte proteomic data was used to reconstruct the most expansive description of erythrocyte metabolism to date, following extensive manual curation, assessment of the literature, and functional testing. The reconstruction contains 281 enzymes representing functions from glycolysis to cofactor and amino acid metabolism. Such a comprehensive view of erythrocyte metabolism implicates the erythrocyte as a potential biomarker for different diseases as well as a 'cell-based' drug-screening tool. The analysis shows that 94 erythrocyte enzymes are implicated in morbid single nucleotide polymorphisms, representing 142 pathologies. In addition, over 230 FDA-approved and experimental pharmaceuticals have enzymatic targets in the erythrocyte. Conclusion The advancement of proteomic technologies and increased generation of high-throughput proteomic data have created the need for a means to analyze these data in a coherent manner. Network reconstructions provide a systematic means to integrate and analyze proteomic data in a biologically meaning manner. Analysis of the red cell proteome has revealed an unexpected level of complexity in the functional capabilities of human erythrocyte metabolism.
机译:背景技术能够通过全细胞测量基因,蛋白质和代谢产物的高通量技术的发展导致了系统生物学的出现。事实证明,很难对所得的omic数据集进行综合分析。代谢网络的重建使分子成分之间的复杂关系能够以生物学上相关的方式正式表达,同时又尊重物理限制。然后可以通过数学模拟来查询或询问从此类重构中得出的计算机模型。对成熟的人类红细胞进行的蛋白质组分析研究表明,与代谢功能相关的蛋白质比以前想象的要多。但是,尚未探讨这些发现的意义和因果关系。结果在广泛的手动管理,文献评估和功能测试之后,使用红细胞蛋白质组学数据重建了迄今为止最广泛的红细胞代谢描述。重建包含281个酶,它们代表从糖酵解到辅因子和氨基酸代谢的功能。对红细胞代谢的这种全面了解意味着,红细胞是针对不同疾病的潜在生物标记,也是“基于细胞”的药物筛选工具。分析显示94种红细胞酶与病态的单核苷酸多态性有关,代表142种病理。另外,超过230种FDA批准的和实验性药物在红细胞中具有酶促靶标。结论蛋白质组学技术的进步和高通量蛋白质组学数据的产生增加了对以一致方式分析这些数据的方法的需求。网络重建提供了一种以生物学意义整合和分析蛋白质组数据的系统方法。对红细胞蛋白质组的分析表明,人类红细胞代谢功能的复杂程度出乎意料。

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