Wnt5a induces ROR1 to associate with 14-3-3ζ for enhanced chemotaxis and proliferation of chronic lymphocytic leukemia cells.

Wnt5a can activate Rho GTPases in chronic lymphocytic leukemia (CLL) cells by inducing the recruitment of ARHGEF2 to ROR1. Mass spectrometry on immune precipitates of Wnt5a-activated ROR1 identified 14-3-3ζ, which was confirmed by co-immunoprecipitation. The capacity of Wnt5a to induce ROR1 to complex with 14-3-3ζ could be blocked in CLL cells by treatment with cirmtuzumab, a humanized mAb targeting ROR1. Silencing 14-3-3ζ via small interfering RNA impaired the capacity of Wnt5a to: (1) induce recruitment of ARHGEF2 to ROR1, (2) enhance in vitro exchange activity of ARHGEF2 and (3) induce activation of RhoA and Rac1 in CLL cells. Furthermore, CRISPR/Cas9 deletion of 14-3-3ζ in ROR1-negative CLL cell-line MEC1, and in MEC1 cells transfected to express ROR1 (MEC1-ROR1), demonstrated that 14-3-3ζ was necessary for the growth/engraftment advantage of MEC1-ROR1 over MEC1 cells. We identified a binding motif (RSPS857SAS) in ROR1 for 14-3-3ζ. Site-directed mutagenesis of ROR1 demonstrated that serine-857 was required for the recruitment of 14-3-3ζ and ARHGEF2 to ROR1, and activation of RhoA and Rac1. Collectively, this study reveals that 14-3-3ζ plays a critical role in Wnt5a/ROR1 signaling, leading to enhanced CLL migration and proliferation

Essential and checkpoint functions of budding yeast ATM and ATR during meiotic prophase are facilitated by differential phosphorylation of a meiotic adaptor protein, Hop1

A hallmark of the conserved ATM/ATR signalling is its ability to mediate a wide range of functions utilizing only a limited number of adaptors and effector kinases. During meiosis, Tel1 and Mec1, the budding yeast ATM and ATR, respectively, rely on a meiotic adaptor protein Hop1, a 53BP1/Rad9 functional analog, and its associated kinase Mek1, a CHK2/Rad53-paralog, to mediate multiple functions: control of the formation and repair of programmed meiotic DNA double strand breaks, enforcement of inter-homolog bias, regulation of meiotic progression, and implementation of checkpoint responses. Here, we present evidence that the multi-functionality of the Tel1/Mec1-to-Hop1/Mek1 signalling depends on stepwise activation of Mek1 that is mediated by Tel1/Mec1 phosphorylation of two specific residues within Hop1: phosphorylation at the threonine 318 (T318) ensures the transient basal level Mek1 activation required for viable spore formation during unperturbed meiosis. Phosphorylation at the serine 298 (S298) promotes stable Hop1-Mek1 interaction on chromosomes following the initial phospho-T318 mediated Mek1 recruitment. In the absence of Dmc1, the phospho-S298 also promotes Mek1 hyper-activation necessary for implementing meiotic checkpoint arrest. Taking these observations together, we propose that the Hop1 phospho-T318 and phospho-S298 constitute key components of the Tel1/Mec1- based meiotic recombination surveillance (MRS) network and facilitate effective coupling of meiotic recombination and progression during both unperturbed and challenged meiosis

Chimeric 14-3-3 proteins for unraveling interactions with intrinsically disordered partners

In eukaryotes, several "hub" proteins integrate signals from different interacting partners that bind through intrinsically disordered regions. The 14-3-3 protein hub, which plays wide-ranging roles in cellular processes, has been linked to numerous human disorders and is a promising target for therapeutic intervention. Partner proteins usually bind via insertion of a phosphopeptide into an amphipathic groove of 14-3-3. Structural plasticity in the groove generates promiscuity allowing accommodation of hundreds of different partners. So far, accurate structural information has been derived for only a few 14-3-3 complexes with phosphopeptide-containing proteins and a variety of complexes with short synthetic peptides. To further advance structural studies, here we propose a novel approach based on fusing 14-3-3 proteins with the target partner peptide sequences. Such chimeric proteins are easy to design, express, purify and crystallize. Peptide attachment to the C terminus of 14-3-3 via an optimal linker allows its phosphorylation by protein kinase A during bacterial co-expression and subsequent binding at the amphipathic groove. Crystal structures of 14-3-3 chimeras with three different peptides provide detailed structural information on peptide-14-3-3 interactions. This simple but powerful approach, employing chimeric proteins, can reinvigorate studies of 14-3-3/phosphoprotein assemblies, including those with challenging low-affinity partners, and may facilitate the design of novel biosensors

MCAM: Multiple Clustering Analysis Methodology for Deriving Hypotheses and Insights from High-Throughput Proteomic Datasets

Advances in proteomic technologies continue to substantially accelerate capability for generating experimental data on protein levels, states, and activities in biological samples. For example, studies on receptor tyrosine kinase signaling networks can now capture the phosphorylation state of hundreds to thousands of proteins across multiple conditions. However, little is known about the function of many of these protein modifications, or the enzymes responsible for modifying them. To address this challenge, we have developed an approach that enhances the power of clustering techniques to infer functional and regulatory meaning of protein states in cell signaling networks. We have created a new computational framework for applying clustering to biological data in order to overcome the typical dependence on specific a priori assumptions and expert knowledge concerning the technical aspects of clustering. Multiple clustering analysis methodology (‘MCAM’) employs an array of diverse data transformations, distance metrics, set sizes, and clustering algorithms, in a combinatorial fashion, to create a suite of clustering sets. These sets are then evaluated based on their ability to produce biological insights through statistical enrichment of metadata relating to knowledge concerning protein functions, kinase substrates, and sequence motifs. We applied MCAM to a set of dynamic phosphorylation measurements of the ERRB network to explore the relationships between algorithmic parameters and the biological meaning that could be inferred and report on interesting biological predictions. Further, we applied MCAM to multiple phosphoproteomic datasets for the ERBB network, which allowed us to compare independent and incomplete overlapping measurements of phosphorylation sites in the network. We report specific and global differences of the ERBB network stimulated with different ligands and with changes in HER2 expression. Overall, we offer MCAM as a broadly-applicable approach for analysis of proteomic data which may help increase the current understanding of molecular networks in a variety of biological problems.National Institutes of Health (U.S.) (NIH-U54-CA112967 )National Institutes of Health (U.S.) (NIH-R01-CA096504

Partitioning of Minimotifs Based on Function with Improved Prediction Accuracy

Background: Minimotifs are short contiguous peptide sequences in proteins that are known to have a function in at least one other protein. One of the principal limitations in minimotif prediction is that false positives limit the usefulness of this approach. As a step toward resolving this problem we have built, implemented, and tested a new data-driven algorithm that reduces false-positive predictions. Methodology/Principal Findings: Certain domains and minimotifs are known to be strongly associated with a known cellular process or molecular function. Therefore, we hypothesized that by restricting minimotif predictions to those where the minimotif containing protein and target protein have a related cellular or molecular function, the prediction is more likely to be accurate. This filter was implemented in Minimotif Miner using function annotations from the Gene Ontology. We have also combined two filters that are based on entirely different principles and this combined filter has a better predictability than the individual components. Conclusions/Significance: Testing these functional filters on known and random minimotifs has revealed that they are capable of separating true motifs from false positives. In particular, for the cellular function filter, the percentage of known minimotifs that are not removed by the filter is,4.6 times that of random minimotifs. For the molecular function filter this ratio is,2.9. These results, together with the comparison with the published frequency score filter, strongly suggest tha

Mouse Sphingosine Kinase 1a Is Negatively Regulated through Conventional PKC-Dependent Phosphorylation at S373 Residue

Sphingosine kinase is a lipid kinase that converts sphingosine into sphingosine-1-phosphate, an important signaling molecule with intracellular and extracellular functions. Although diverse extracellular stimuli influence cellular sphingosine kinase activity, the molecular mechanisms underlying its regulation remain to be clarified. In this study, we investigated the phosphorylation-dependent regulation of mouse sphingosine kinase (mSK) isoforms 1 and 2. mSK1a was robustly phosphorylated in response to extracellular stimuli such as phorbol ester, whereas mSK2 exhibited a high basal level of phosphorylation in quiescent cells regardless of agonist stimulation. Interestingly, phorbol ester-induced phosphorylation of mSK1a correlated with suppression of its activity. Chemical inhibition of conventional PKCs (cPKCs) abolished mSK1a phosphorylation, while overexpression of PKC alpha, a cPKC isoform, potentiated the phosphorylation, in response to phorbol ester. Furthermore, an in vitro kinase assay showed that PKC alpha directly phosphorylated mSK1a. In addition, phosphopeptide mapping analysis determined that the S373 residue of mSK1a was the only site phosphorylated by cPKC. Interestingly, alanine substitution of S373 made mSK1a refractory to the inhibitory effect of phorbol esters, whereas glutamate substitution of the same residue resulted in a significant reduction in mSK1a activity, suggesting the significant role of this phosphorylation event. Taken together, we propose that mSK1a is negatively regulated through cPKC-dependent phosphorylation at S373 residueopen

Systematic review of methods used in meta-analyses where a primary outcome is an adverse or unintended event

addresses: Peninsula College of Medicine and Dentistry, St Luke's Campus, University of Exeter, Exeter, UK. [email protected]: PMCID: PMC3528446types: Journal Article; Research Support, Non-U.S. Gov't© 2012 Warren et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Adverse consequences of medical interventions are a source of concern, but clinical trials may lack power to detect elevated rates of such events, while observational studies have inherent limitations. Meta-analysis allows the combination of individual studies, which can increase power and provide stronger evidence relating to adverse events. However, meta-analysis of adverse events has associated methodological challenges. The aim of this study was to systematically identify and review the methodology used in meta-analyses where a primary outcome is an adverse or unintended event, following a therapeutic intervention

Single-cell analysis tools for drug discovery and development

The genetic, functional or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development. Such heterogeneity hinders the design of accurate disease models and can confound the interpretation of biomarker levels and of patient responses to specific therapies. The complex nature of virtually all tissues has motivated the development of tools for single-cell genomic, transcriptomic and multiplex proteomic analyses. Here, we review these tools and assess their advantages and limitations. Emerging applications of single cell analysis tools in drug discovery and development, particularly in the field of oncology, are discussed

Ovarian cancer molecular pathology.

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