Identification of DYRK1B as a substrate of ERK1/2 and characterisation of the kinase activity of DYRK1B mutants from cancer and metabolic syndrome.

The dual-specificity tyrosine-phosphorylation-regulated kinase, DYRK1B, is expressed de novo during myogenesis, amplified or mutated in certain cancers and mutated in familial cases of metabolic syndrome. DYRK1B is activated by cis auto-phosphorylation on tyrosine-273 (Y273) within the activation loop during translation but few other DYRK1B phosphorylation sites have been characterised to date. Here, we demonstrate that DYRK1B also undergoes trans-autophosphorylation on serine-421 (S421) in vitro and in cells and that this site contributes to DYRK1B kinase activity. Whilst a DYRK1B(S421A) mutant was completely defective for p-S421 in cells, DYRK1B inhibitors caused only a partial loss of p-S421 suggesting the existence of an additional kinase that could also phosphorylate DYRK1B S421. Indeed, a catalytically inactive DYRK1B(D239A) mutant exhibited very low levels of p-S421 in cells but this was increased by KRAS(G12V). In addition, selective activation of the RAF-MEK1/2-ERK1/2 signalling pathway rapidly increased p-S421 in cells whereas activation of the stress kinases JNK or p38 could not. S421 resides within a Ser-Pro phosphoacceptor motif that is typical for ERK1/2 and recombinant ERK2 phosphorylated DYRK1B at S421 in vitro. Our results show that DYRK1B is a novel ERK2 substrate, uncovering new links between two kinases involved in cell fate decisions. Finally, we show that DYRK1B mutants that have recently been described in cancer and metabolic syndrome exhibit normal or reduced intrinsic kinase activity.

Targeted profiling of polar intracellular metabolites using ion-pair-high performance liquid chromatography and -ultra high performance liquid chromatography coupled to tandem mass spectrometry: applications to serum, urine and tissue extracts.

The effective analysis of polar ionic metabolites by LC-MS, such as those encountered in central carbon metabolism, represents a major problem for metabolic profiling that is not adequately addressed using strategies based on either reversed-phase or HILIC methods. Here we have compared analysis of central carbon metabolites on optimized methods using HILIC, porous graphitic carbon or ion pair chromatography (IPC) using tributyl ammonium as IP reagent. Of the 3 chromatographic approaches examined only IPC enabled us to obtain a robust analytical methodology. This system was used to profile more than a hundred endogenous metabolic intermediates in urine, serum and tissue samples. However, whilst we found IPC to be the best of the approaches examined considerable care was still needed to obtain robust data. Thus, in excess of 40 of representative biological samples were needed to "condition" a new analytical column and further 10 matrix injections were then required at the beginning of each analytical batch in order to obtain robust and reproducible chromatographic separations. An additional limitation that we have found was that, for a small number of phosphorylated and poly carboxylic acid metabolites, measurement was only possible if the analytes were present in relatively high concentrations. We also found that, whilst this methodology could be used for the analysis of both in vitro cell culture media, cell extracts, tissue, and biological fluids (blood, urine), for the best results columns should only be used to analyze a single matrix. However, despite the need for extensive column conditioning, and the manifold disadvantages resulting from the contamination of the separation system and mass spectrometer with the ion pair reagent, IPC-MS currently provides the best means of analyzing these polar, ionic and problematic metabolites.

AZD3514: a small molecule that modulates androgen receptor signaling and function in vitro and in vivo.

Continued androgen receptor (AR) expression and signaling is a key driver in castration-resistant prostate cancer (CRPC) after classical androgen ablation therapies have failed, and therefore remains a target for the treatment of progressive disease. Here, we describe the biological characterization of AZD3514, an orally bioavailable drug that inhibits androgen-dependent and -independent AR signaling. AZD3514 modulates AR signaling through two distinct mechanisms, an inhibition of ligand-driven nuclear translocation of AR and a downregulation of receptor levels, both of which were observed in vitro and in vivo. AZD3514 inhibited testosterone-driven seminal vesicle development in juvenile male rats and the growth of androgen-dependent Dunning R3327H prostate tumors in adult rats. Furthermore, this class of compound showed antitumor activity in the HID28 mouse model of CRPC in vivo. AZD3514 is currently in phase I clinical evaluation.

Putative glycosyltransferases and other plant Golgi apparatus proteins are revealed by LOPIT proteomics.

The Golgi apparatus is the central organelle in the secretory pathway and plays key roles in glycosylation, protein sorting, and secretion in plants. Enzymes involved in the biosynthesis of complex polysaccharides, glycoproteins, and glycolipids are located in this organelle, but the majority of them remain uncharacterized. Here, we studied the Arabidopsis (Arabidopsis thaliana) membrane proteome with a focus on the Golgi apparatus using localization of organelle proteins by isotope tagging. By applying multivariate data analysis to a combined data set of two new and two previously published localization of organelle proteins by isotope tagging experiments, we identified the subcellular localization of 1,110 proteins with high confidence. These include 197 Golgi apparatus proteins, 79 of which have not been localized previously by a high-confidence method, as well as the localization of 304 endoplasmic reticulum and 208 plasma membrane proteins. Comparison of the hydrophobic domains of the localized proteins showed that the single-span transmembrane domains have unique properties in each organelle. Many of the novel Golgi-localized proteins belong to uncharacterized protein families. Structure-based homology analysis identified 12 putative Golgi glycosyltransferase (GT) families that have no functionally characterized members and, therefore, are not yet assigned to a Carbohydrate-Active Enzymes database GT family. The substantial numbers of these putative GTs lead us to estimate that the true number of plant Golgi GTs might be one-third above those currently annotated. Other newly identified proteins are likely to be involved in the transport and interconversion of nucleotide sugar substrates as well as polysaccharide and protein modification.

Improved sub-cellular resolution via simultaneous analysis of organelle proteomics data across varied experimental conditions.

Spatial organisation of proteins according to their function plays an important role in the specificity of their molecular interactions. Emerging proteomics methods seek to assign proteins to sub-cellular locations by partial separation of organelles and computational analysis of protein abundance distributions among partially separated fractions. Such methods permit simultaneous analysis of unpurified organelles and promise proteome-wide localisation in scenarios wherein perturbation may prompt dynamic re-distribution. Resolving organelles that display similar behavior during a protocol designed to provide partial enrichment represents a possible shortcoming. We employ the Localisation of Organelle Proteins by Isotope Tagging (LOPIT) organelle proteomics platform to demonstrate that combining information from distinct separations of the same material can improve organelle resolution and assignment of proteins to sub-cellular locations. Two previously published experiments, whose distinct gradients are alone unable to fully resolve six known protein-organelle groupings, are subjected to a rigorous analysis to assess protein-organelle association via a contemporary pattern recognition algorithm. Upon straightforward combination of single-gradient data, we observe significant improvement in protein-organelle association via both a non-linear support vector machine algorithm and partial least-squares discriminant analysis. The outcome yields suggestions for further improvements to present organelle proteomics platforms, and a robust analytical methodology via which to associate proteins with sub-cellular organelles.

Determination of genuine residents of plant endomembrane organelles using isotope tagging and multivariate statistics.

The knowledge of the localization of proteins to a particular subcellular structure or organelle is an important step towards assigning function to proteins predicted by genome-sequencing projects that have yet to be characterized. Moreover, the localization of novel proteins to organelles also enhances our understanding of the functions of organelles. Many organelles cannot be purified. In several cases where the degree of contamination by organelles with similar physical parameters to the organelle being studied has gone unchecked, this has lead to the mis-localization of proteins. Recently, several techniques have emerged, which depend on characterization of the distribution pattern of organelles partially separated using density centrifugation by quantitative proteomics approaches. Here, we discuss one of these approaches, the localization of organelle proteins by isotope tagging (LOPIT) where the distribution patterns of organelles are assessed by measuring the relative abundance of proteins between fractions along the length of density gradients using stable isotope-coded tags. The subcellular localizations of proteins can be determined by comparing their distributions to those of previously localized proteins by assuming that proteins that belong to the same organelle will cofractionate in density gradients. Analysis of distribution patterns can be achieved by employing multivariate statistical methods such as principal component analysis and partial least squares discriminate analysis. In this chapter, we focus on the use of the LOPIT technique in the assignment of membrane proteins to the plant Golgi apparatus and endoplasmic reticulum.

Mapping the Arabidopsis organelle proteome.

A challenging task in the study of the secretory pathway is the identification and localization of new proteins to increase our understanding of the functions of different organelles. Previous proteomic studies of the endomembrane system have been hindered by contaminating proteins, making it impossible to assign proteins to organelles. Here we have used the localization of organelle proteins by the isotope tagging technique in conjunction with isotope tags for relative and absolute quantitation and 2D liquid chromatography for the simultaneous assignment of proteins to multiple subcellular compartments. With this approach, the density gradient distributions of 689 proteins from Arabidopsis thaliana were determined, enabling confident and simultaneous localization of 527 proteins to the endoplasmic reticulum, Golgi apparatus, vacuolar membrane, plasma membrane, or mitochondria and plastids. This parallel analysis of endomembrane components has enabled protein steady-state distributions to be determined. Consequently, genuine organelle residents have been distinguished from contaminating proteins and proteins in transit through the secretory pathway.

Quantitative proteomic approach to study subcellular localization of membrane proteins.

As proteins within cells are spatially organized according to their role, knowledge about protein localization gives insight into protein function. Here, we describe the LOPIT technique (localization of organelle proteins by isotope tagging) developed for the simultaneous and confident determination of the steady-state distribution of hundreds of integral membrane proteins within organelles. The technique uses a partial membrane fractionation strategy in conjunction with quantitative proteomics. Localization of proteins is achieved by measuring their distribution pattern across the density gradient using amine-reactive isotope tagging and comparing these patterns with those of known organelle residents. LOPIT relies on the assumption that proteins belonging to the same organelle will co-fractionate. Multivariate statistical tools are then used to group proteins according to the similarities in their distributions, and hence localization without complete centrifugal separation is achieved. The protocol requires approximately 3 weeks to complete and can be applied in a high-throughput manner to material from many varied sources.

i-Tracker: for quantitative proteomics using iTRAQ.

BACKGROUND: iTRAQ technology for protein quantitation using mass spectrometry is a recent, powerful means of determining relative protein levels in up to four samples simultaneously. Although protein identification of samples generated using iTRAQ may be carried out using any current identification software, the quantitation calculations have been restricted to the ProQuant software supplied by Applied Biosciences. i-Tracker software has been developed to extract reporter ion peak ratios from non-centroided tandem MS peak lists in a format easily linked to the results of protein identification tools such as Mascot and Sequest. Such functionality is currently not provided by ProQuant, which is restricted to matching quantitative information to the peptide identifications from Applied Biosciences' Interrogator software. RESULTS: i-Tracker is shown to generate results that are consistent with those produced by ProQuant, thus validating both systems. CONCLUSION: i-Tracker allows quantitative information gained using the iTRAQ protocol to be linked with peptide identifications from popular tandem MS identification tools and hence is both a timely and useful tool for the proteomics community.