Finding evolutionary relationships protein domains is mostly based on orthology and thus commonly performed on best sequence matches. Identifying these and categorizing them depends largely on multiple sequence alignments and this will in most cases give good indications for function, fold and ultimately evolution. However, this approach usually discards apparent ambiguities that arise from speciesspecific variations (e.g., due to population size, metabolism or species-specific domain duplications or losses) and may therefore introduce significant biases [114] . Biases may also derive from the method of alignment, the rate variation model used to infer the phylogeny, and the sample size used to build the alignment [39, 40, 115] . Care should therefore be taken to not regard orthology as a one-to-one relationship, but as a family of homologous relations [91] , to select for appropriate analysis methods [39, 115] and extend comparative data to protein interactions and expression profiles [91] . Indeed, as our wealth of biological information expands, our systems perspective will improve and provide us with an opportunity to reveal protein domain evolution at the level network organization and dynamics. Large-scale expression studies are beginning to show us evolutionary correlations between gene expression levels and timings [94, 106, 107, 112, 116] , while others demonstrate spatial differences between paralogs or (partial) overlap between interaction partners [117] [118] [119] [120] . Indeed, when we are able to map the spatiotemporal aspects of inter-and intra-molecular interactions we will begin to fully understand the versatile power of evolution that shaped the protein universe and life on Earth [118] .  Quantitative Phosphoproteomics of Proteasome Inhibition in Multiple Myeloma Cells BACKGROUND: The proteasome inhibitor bortezomib represents an important advance in the treatment of multiple myeloma (MM). Bortezomib inhibits the activity of the 26S proteasome and induces cell death in a variety of tumor cells; however, the mechanism of cytotoxicity is not well understood. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the differential phosphoproteome upon proteasome inhibition by using stable isotope labeling by amino acids in cell culture (SILAC) in combination with phosphoprotein enrichment and LC-MS/MS analysis. In total 233 phosphoproteins were identified and 72 phosphoproteins showed a 1.5-fold or greater change upon bortezomib treatment. The phosphoproteins with expression alterations encompass all major protein classes, including a large number of nucleic acid binding proteins. Site-specific phosphopeptide quantitation revealed that Ser38 phosphorylation on stathmin increased upon bortezomib treatment, suggesting new mechanisms associated to bortezomib-induced apoptosis in MM cells. Further studies demonstrated that stathmin phosphorylation profile was modified in response to bortezomib treatment and the regulation of stathmin by phosphorylation at specific Ser/Thr residues participated in the cellular response induced by bortezomib. CONCLUSIONS/SIGNIFICANCE: Our systematic profiling of phosphorylation changes in response to bortezomib treatment not only advanced the global mechanistic understanding of the action of bortezomib on myeloma cells but also identified previously uncharacterized signaling proteins in myeloma cells. The ubiquitin-proteasome pathway is responsible for proteolysis of eukaryotic cellular proteins related to cell cycle regulation, cell survival, and apoptosis [1] . Inhibition of proteasome activity is a novel therapeutic strategy against cancer cells. Bortezomib (formerly known as PS-341), a cell-permeable boronic acid dipeptide, is a specific inhibitor of the proteasome pathway [2] and received Food and Drug Administration (FDA) approval for the treatment of MM and mantle cell lymphoma [3] .