2′-deoxy-ADPR activates human TRPM2 faster than ADPR and thereby induces higher currents at physiological Ca2+ concentrations

TRPM2 is a Ca2+ permeable, non-selective cation channel in the plasma membrane that is involved in the innate immune response regulating, for example, chemotaxis in neutrophils and cytokine secretion in monocytes and macrophages. The intracellular adenine nucleotides ADP-ribose (ADPR) and 2′-deoxy-ADPR (2dADPR) activate the channel, in combination with their co-agonist Ca2+. Interestingly, activation of human TRPM2 (hsTRPM2) by 2dADPR is much more effective than activation by ADPR. However, the underlying mechanism of the nucleotides’ differential effect on the channel is not yet fully understood. In this study, we performed whole-cell patch clamp experiments with HEK293 cells heterologously expressing hsTRPM2. We show that 2dADPR has an approx. 4-fold higher Ca2+ sensitivity than ADPR (EC50 = 190 and 690 nM). This allows 2dADPR to activate the channel at lower and thus physiological intracellular Ca2+ concentrations. Kinetic analysis of our data reveals that activation by 2dADPR is faster than activation by ADPR. Mutation in a calmodulin binding N-terminal IQ-like motif in hsTRPM2 completely abrogated channel activation by both agonists. However, mutation of a single amino acid residue (W1355A) in the C-terminus of hsTRPM2, at a site of extensive inter-domain interaction, resulted in slower activation by 2dADPR and neutralized the difference in rate of activation between the two agonists. Taken together, we propose a mechanism by which 2dADPR induces higher hsTRPM2 currents than ADPR by means of faster channel activation. The finding that 2dADPR has a higher Ca2+ sensitivity than ADPR may indicate that 2dADPR rather than ADPR activates hsTRPM2 in physiological contexts such as the innate immune response

MC EMiNEM Maps the Interaction Landscape of the Mediator

The Mediator is a highly conserved, large multiprotein complex that is involved essentially in the regulation of eukaryotic mRNA transcription. It acts as a general transcription factor by integrating regulatory signals from gene-specific activators or repressors to the RNA Polymerase II. The internal network of interactions between Mediator subunits that conveys these signals is largely unknown. Here, we introduce MC EMiNEM, a novel method for the retrieval of functional dependencies between proteins that have pleiotropic effects on mRNA transcription. MC EMiNEM is based on Nested Effects Models (NEMs), a class of probabilistic graphical models that extends the idea of hierarchical clustering. It combines mode-hopping Monte Carlo (MC) sampling with an Expectation-Maximization (EM) algorithm for NEMs to increase sensitivity compared to existing methods. A meta-analysis of four Mediator perturbation studies in Saccharomyces cerevisiae, three of which are unpublished, provides new insight into the Mediator signaling network. In addition to the known modular organization of the Mediator subunits, MC EMiNEM reveals a hierarchical ordering of its internal information flow, which is putatively transmitted through structural changes within the complex. We identify the N-terminus of Med7 as a peripheral entity, entailing only local structural changes upon perturbation, while the C-terminus of Med7 and Med19 appear to play a central role. MC EMiNEM associates Mediator subunits to most directly affected genes, which, in conjunction with gene set enrichment analysis, allows us to construct an interaction map of Mediator subunits and transcription factors

Combining autoclave and LCWM reactor studies to shed light on the kinetics of glucose oxidation catalyzed by doped molybdenum-based heteropoly acids

In this work we combined kinetic studies for aqueous-phase glucose oxidation in a high-pressure autoclave setup with catalyst reoxidation studies in a liquid-core waveguide membrane reactor. Hereby, we investigated the influence of Nb- and Ta-doping on Mo-based Keggin-polyoxometalates for both reaction steps independently. Most importantly, we could demonstrate a significant increase of glucose oxidation kinetics by Ta- and especially Nb-doping by factors of 1.1 and 1.5 compared to the classical HPA-Mo. Moreover, activation energies for the substrate oxidation step could be significantly reduced from around 80 kJ mol(−1) for the classical HPA-Mo to 61 kJ mol(−1) for the Ta- and 55 kJ mol(−1) for the Nb-doped species, respectively. Regarding catalyst reoxidation kinetics, the doping did not show significant differences between the different catalysts

One Hand Clapping: detection of condition-specific transcription factor interactions from genome-wide gene activity data

We present One Hand Clapping (OHC), a method for the detection of condition-specific interactions between transcription factors (TFs) from genome-wide gene activity measurements. OHC is based on a mapping between transcription factors and their target genes. Given a single case-control experiment, it uses a linear regression model to assess whether the common targets of two arbitrary TFs behave differently than expected from the genes targeted by only one of the TFs. When applied to osmotic stress data in S. cerevisiae, OHC produces consistent results across three types of expression measurements: gene expression microarray data, RNA Polymerase II ChIP-chip binding data and messenger RNA synthesis rates. Among the eight novel, condition-specific TF pairs, we validate the interaction between Gcn4p and Arr1p experimentally. We apply OHC to a large gene activity dataset in S. cerevisiae and provide a compendium of condition-specific TF interactions

Gene set enrichment analysis.

<p>A) Expression changes of the target genes of SKO1 across all experiments. Experiments correspond to rows; the respective Mediator subunit perturbations are indicated by the colored boxes to the left of the heat map (coloring is in accordance with the Mediator module structure in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002568#pcbi-1002568-g003" target="_blank">Fig. 3</a>). Target genes correspond to columns. If a target gene is attached to a Mediator subunit in the MC EMiNEM effects graph, this is indicated by a colored box on top of the respective column, using the same color code as for the experiments. Expression changes relative to wild type are color coded by the panel on the right. In the gene set enrichment analysis, SKO1 target genes were found enriched for upregulated genes attached to the Med10Med21 node in the MC EMiNEM effects graph. These genes lie to the left of the bold vertical line in the heat map. Briefly, our Mediator NEM model predicts that they should also change their expression in the Med19 and Med7C perturbations, which lie above the bold horizontal line. Ideally, the expression changes in the upper left corner defined by the two bold lines should be strong and consistent, while those in the remaining part should be weaker and less consistent. B) Same plot as A), for the target genes of SWI5. Since SWI5 targets are enriched for downregulated genes attached to Med7N, and Med7N is downstream of all other nodes in the signals graph, we expect consistent expression changes of the Med7N attached genes across all perturbations.</p

Prediction quality and influence of the Empirical Bayes procedure.

<p>(A) Prediction quality. Comparison of the sensitivity of MC EMiNEM and four alternative methods for four different noise levels (top) and four different signals graph sizes (bottom). The sensitivity is depicted on the y-axis, each frame corresponds to one parameter setting. Top: For a signals graph of 11 nodes, noisy data was generated such that for an optimal test with a type-I error (-level) of 5%, a type II error (-level) of , and would be achieved, respectively. Bottom: For a noise level corresponding to an error level of (, ), signals graph sizes of are investigated. We expect our application to range within the four central scenarios. The comparisons of sensitivities is a fair comparison of the prediction qualities since the specificities for all methods and parameter settings are located (see also Fig. S3.7 in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002568#pcbi.1002568.s004" target="_blank">Text S1</a>). (B) Influence of the Empirical Bayes procedure. Here, for the standard setting and (, ). The x-axis shows the calculated marginal posterior values centered at (indicated by the dashed vertical line), on the y-axis the frequency is displayed. In the table, the percentages of signals graphs scoring higher than are provided, as well as the -distances (relative to the maximum).</p

Mediator network inferred by MC EMiNEM, with associated transcription factors (the basic Mediator cartoon was modified from [63]).

<p>The numbers of the Mediator subunits correspond to the unified Mediator nomenclature <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002568#pcbi.1002568-Bourbon2" target="_blank">[64]</a> and subunits that are part of this study are enlarged and have saturated colors. The two subunits Med10 and Med21 were merged as explained in the main text. The N-terminus and the C-terminus of Med7, which are represented by two individual perturbations in this study, are shown separately. Physically, they are connected by a flexible linker <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002568#pcbi.1002568-Koschubs2" target="_blank">[8]</a>. The arrows between the Mediator subunits show the signals graph of our MC EMiNEM analysis, arrow colors correspond to the module they originate from. The TFs surrounding the Mediator are the outcome of a gene set enrichment analysis of the MC EMiNEM effects graph. TFs are grouped into gray areas which link them to the Mediator subunit for whose target genes they are enriched. For each TF, minus resp. plus signs indicate whether their targets are down- resp. upregulated upon perturbation of the corresponding Mediator subunit. The results of the gene set enrichment analysis were compared to known interactions between TFs and Mediator subunits in BioGRID <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002568#pcbi.1002568-Stark1" target="_blank">[60]</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002568#pcbi.1002568-Stark2" target="_blank">[65]</a>). Red: the interaction with the corresponding Mediator subunit is known; orange: an interaction with a Mediator subunit in the same module is known; dark yellow: confirmed interaction with the Mediator; white: no known interaction.</p

Effects graph inferred from the Mediator data.

<p>Shown are the log-odds ratios which serve as MC EMiNEM's input. Genes that are likely to change in a given condition are depicted in red,and they are blue otherwise. Color saturation indicates the absolute value of the log-odds ratio (cf. Fig. S4.3 in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002568#pcbi.1002568.s004" target="_blank">Text S1</a>). Rows correspond to Mediator perturbation experiments, columns correspond to genes, sorted according to their attachment to Mediator subunits. Mediator subunits are colored as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002568#pcbi-1002568-g003" target="_blank">Fig. 3</a> and <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002568#pcbi-1002568-g005" target="_blank">Fig. 5</a>.</p

Example NEM.

<p>, . Shaded matrix fields correspond to an expression change of effect gene upon perturbation of signal , white fields indicate no change in expression. The edges and cause an effect in genes directly attached to signal and respectively, when is perturbed.</p

Characterization of the honeybee venom proteins C1q-like protein and PVF1 and their allergenic potential

Honeybee (Apis mellifera) venom (HBV) represents an ideal model to study the role of particular venom components in allergic reactions in sensitized individuals as well as in the eusociality of Hymenoptera species. The aim of this study was to further characterize the HBV components C1q-like protein (C1q) and PDGF/VEGF-like factor 1 (PVF1). C1q and PVF1 were produced as recombinant proteins in insect cells. Their allergenic properties were examined by determining the level of specific IgE antibodies in the sera of HBV-allergic patients (n = 26) as well as by their capacity to activate patients' basophils (n = 11). Moreover, the transcript heterogeneity of PVF1 was analyzed. It could be demonstrated that at least three PVF1 variants are present in the venom gland, which all result from alternative splicing of one transcript. Additionally, recombinant C1q and PVF1 from Spodoptera frugiperda insect cells exhibited specific IgE reactivity with approximately 38.5% of sera of HBV-allergic patients. Interestingly, both proteins were unable to activate basophils of the patients, questioning their role in the context of clinically relevant sensitization. Recombinant C1q and PVF1 can build the basis for a deeper understanding of the molecular mechanisms of Hymenoptera venoms. Moreover, the conflicting results between IgE sensitization and lack of basophil activation, might in the future contribute to the identification of factors that determine the allergenic potential of proteins