Phosphoproteomics toolbox: computational biology, protein chemistry and mass spectrometry.

Protein phosphorylation is important for regulation of most biological functions and up to 50% of all proteins are thought to be modified by protein kinases. Increased knowledge about potential phosphorylation of a protein may increase our understanding of the molecular processes in which it takes part. Despite the importance of protein phosphorylation, identification of phosphoproteins and localization of phosphorylation sites is still a major challenge in proteomics. However, high-throughput methods for identification of phosphoproteins are being developed, in particular within the fields of bioinformatics and mass spectrometry. In this review, we present a toolbox of current technology applied in phosphoproteomics including computational prediction, chemical approaches and mass spectrometry-based analysis, and propose an integrated strategy for experimental phosphoproteomics.

Protein kinase A phosphorylates serine 267 in the homeodomain of engrailed-2 leading to decreased DNA binding.

Engrailed-2 (En-2) belongs to an evolutionarily conserved family of DNA binding homeodomain-containing proteins that are expressed in mammalian brain during development. Here, we demonstrate that serine 267 in the homeodomain of En-2 is phosphorylated by protein kinase A (PKA) in forskolin-treated COS-7 cells. Furthermore, we analyze the physiological function of En-2 phosphorylation by PKA. The nuclear localization of En-2 is not influenced by the phosphorylation of serine 267. However, substitution of serine 267 with alanine resulted in increased binding of En-2 to DNA, while replacing serine 267 with glutamic acid resulted in decreased En-2 DNA binding. These results suggest that the transcriptional activity of En-2 is regulated by PKA.

Proteomic screen defines the Polo-box domain interactome and identifies Rock2 as a Plk1 substrate.

Polo-like kinase-1 (Plk1) phosphorylates a number of mitotic substrates, but the diversity of Plk1-dependent processes suggests the existence of additional targets. Plk1 contains a specialized phosphoserine-threonine binding domain, the Polo-box domain (PBD), postulated to target the kinase to its substrates. Using the specialized PBD of Plk1 as an affinity capture agent, we performed a screen to define the mitotic Plk1-PBD interactome by mass spectrometry. We identified 622 proteins that showed phosphorylation-dependent mitosis-specific interactions, including proteins involved in well-established Plk1-regulated processes, and in processes not previously linked to Plk1 such as translational control, RNA processing, and vesicle transport. Many proteins identified in our screen play important roles in cytokinesis, where, in mammalian cells, the detailed mechanistic role of Plk1 remains poorly defined. We go on to characterize the mitosis-specific interaction of the Plk1-PBD with the cytokinesis effector kinase Rho-associated coiled-coil domain-containing protein kinase 2 (Rock2), demonstrate that Rock2 is a Plk1 substrate, and show that Rock2 colocalizes with Plk1 during cytokinesis. Finally, we show that Plk1 and RhoA function together to maximally enhance Rock2 kinase activity in vitro and within cells, and implicate Plk1 as a central regulator of multiple pathways that synergistically converge to regulate actomyosin ring contraction during cleavage furrow ingression.

Identification of phosphorylation sites in protein kinase A substrates using artificial neural networks and mass spectrometry.

Protein phosphorylation plays a key role in cell regulation and identification of phosphorylation sites is important for understanding their functional significance. Here, we present an artificial neural network algorithm: NetPhosK (http://www.cbs.dtu.dk/services/NetPhosK/) that predicts protein kinase A (PKA) phosphorylation sites. The neural network was trained with a positive set of 258 experimentally verified PKA phosphorylation sites. The predictions by NetPhosK were validated using four novel PKA substrates: Necdin, RFX5, En-2, and Wee 1. The four proteins were phosphorylated by PKA in vitro and 13 PKA phosphorylation sites were identified by mass spectrometry. NetPhosK was 100% sensitive and 41% specific in predicting PKA sites in the four proteins. These results demonstrate the potential of using integrated computational and experimental methods for detailed investigations of the phosphoproteome.

Integrated analysis of protein composition, tissue diversity, and gene regulation in mouse mitochondria.

Mitochondria are tailored to meet the metabolic and signaling needs of each cell. To explore its molecular composition, we performed a proteomic survey of mitochondria from mouse brain, heart, kidney, and liver and combined the results with existing gene annotations to produce a list of 591 mitochondrial proteins, including 163 proteins not previously associated with this organelle. The protein expression data were largely concordant with large-scale surveys of RNA abundance and both measures indicate tissue-specific differences in organelle composition. RNA expression profiles across tissues revealed networks of mitochondrial genes that share functional and regulatory mechanisms. We also determined a larger "neighborhood" of genes whose expression is closely correlated to the mitochondrial genes. The combined analysis identifies specific genes of biological interest, such as candidates for mtDNA repair enzymes, offers new insights into the biogenesis and ancestry of mammalian mitochondria, and provides a framework for understanding the organelle's contribution to human disease.

Identification of a gene causing human cytochrome c oxidase deficiency by integrative genomics.

Identifying the genes responsible for human diseases requires combining information about gene position with clues about biological function. The recent availability of whole-genome data sets of RNA and protein expression provides powerful new sources of functional insight. Here we illustrate how such data sets can expedite disease-gene discovery, by using them to identify the gene causing Leigh syndrome, French-Canadian type (LSFC, Online Mendelian Inheritance in Man no. 220111), a human cytochrome c oxidase deficiency that maps to chromosome 2p16-21. Using four public RNA expression data sets, we assigned to all human genes a "score" reflecting their similarity in RNA-expression profiles to known mitochondrial genes. Using a large survey of organellar proteomics, we similarly classified human genes according to the likelihood of their protein product being associated with the mitochondrion. By intersecting this information with the relevant genomic region, we identified a single clear candidate gene, LRPPRC. Resequencing identified two mutations on two independent haplotypes, providing definitive genetic proof that LRPPRC indeed causes LSFC. LRPPRC encodes an mRNA-binding protein likely involved with mtDNA transcript processing, suggesting an additional mechanism of mitochondrial pathophysiology. Similar strategies to integrate diverse genomic information can be applied likewise to other disease pathways and will become increasingly powerful with the growing wealth of diverse, functional genomics data.