Proteomics & personalized medicine Issue in Proteomics
A new issue in Proteomics was recently edited and published by René P. Zahedi et al. regarding proteomics and personalized medicine. This Focus Issuecomprises a total of eight valuable contributions from various experts in the field of proteomics research, ranging from methodical development and optimisation to applications dealing with complex samples in biomedical research. Urbani et al. report direct analytical assessment of sample quality for biomarker investigation. They pinpoint the impact of pre-analytical variables that cause major errors in clinical testing. Marko-Varga et al. describe the usage of MALDI imaging as novel tool for personalised diagnostics, as they follow drug action upon treatment of malignant melanoma. Selheim et al. established a novel super-SILAC mix for acute myeloid leukemia (AML) and demonstrate its usage as internal standard for personalized proteomics of AML patients. Jiang et al. demonstrate how SILAC can be utilized to investigate the secretome of activated hepatic stellate cells, the main fibroblast cell type in liver fibrosis. This is an important step for a better understanding of cellular mechanisms during the recovery of liver fibrosis. Borchers et al. introduce novel software for a fast analysis of large datasets derived from crosslinking experiments in order to study protein-protein interactions from large-scale experiments. Gevaert et al. present a technology that allows studying the specificity of methionine sulfoxide reductases and apply it to human samples. The oxidation of free and protein-bound methionine into methionine sulfoxide is a frequently occurring modification caused by reactive oxygen species. This modification may interfere with the identification of posttranslational modification such as protein phosphorylation as well as the peptide identification itself. Mechtler et al. push technology development forward to ultra-low flow nanoHPLC separations. This technology allows obtaining comprehensive proteomic data from less than 100 ng of protein starting material. Finally, Shen et al. demonstrate a rapid and reproducible one-dimensional fast and quantitative LC-MS/MS technology avoiding time- and sample-consuming prefractionation strategies.