THE EFFECT OF DEXAMETHASONE ON IL-33-MEDIATED MAST CELL ACTIVATION

Dexamethasone has been shown to inhibit IgE-mediated mast cell activation, and the present research investigated its role in suppressing IL-33-mediated mast cell activation. We have found that micromolar concentrations of Dexamethasone are capable of suppressing IL-33-mediated mast cell cytokine production, on several genetic backgrounds, and in not only bone marrow derived mast cells, but also peritoneal mast cells. Intracellular staining demonstrated that Dexamethasone significantly reduces expression of the IL-33 receptor, T1/ST2, in mast cells; however, the cytokine suppression is independent of T1/ST2 downregulation. At the same time, Dexamethasone pretreatment significantly reduced ERK phosphorylation, but our data suggests that inhibition occurs even prior to ERK blockade. Finally, Dexamethasone treatment in vivo reduced IL-33-mediated cytokine production and neutrophil infiltration in the murine peritoneum. Thus, Dexamethasone, a well-established therapy for inflammatory disease, can suppress IL-33-mediated mast cell activation, and may therefore be effective for treating diseases now being attributed to IL-33 effects

A Statistically Rigorous Test for the Identification of Parent−Fragment Pairs in LC-MS Datasets

Untargeted global metabolic profiling by liquid chromato-graphy−mass spectrometry generates numerous signals that are due to unknown compounds and whose identification forms an important challenge. The analysis of metabolite fragmentation patterns, following collision-induced dissociation, provides a valuable tool for identification, but can be severely impeded by close chromatographic coelution of distinct metabolites. We propose a new algorithm for identifying related parent−fragment pairs and for distinguishing these from signals due to unrelated compounds. Unlike existing methods, our approach addresses the problem by means of a hypothesis test that is based on the distribution of the recorded ion counts, and thereby provides a statistically rigorous measure of the uncertainty involved in the classification problem. Because of technological constraints, the test is of primary use at low and intermediate ion counts, above which detector saturation causes substantial bias to the recorded ion count. The validity of the test is demonstrated through its application to pairs of coeluting isotopologues and to known parent−fragment pairs, which results in test statistics consistent with the null distribution. The performance of the test is compared with a commonly used Pearson correlation approach and found to be considerably better (e.g., false positive rate of 6.25%, compared with a value of 50% for the correlation for perfectly coeluting ions). Because the algorithm may be used for the analysis of high-mass compounds in addition to metabolic data, we expect it to facilitate the analysis of fragmentation patterns for a wide range of analytical problems

Prospects for a Statistical Theory of LC/TOFMS Data

The critical importance of employing sound statistical arguments when seeking to draw inferences from inexact measurements is well-established throughout the sciences. Yet fundamental statistical methods such as hypothesis testing can currently be applied to only a small subset of the data analytical problems encountered in LC/MS experiments. The means of inference that are more generally employed are based on a variety of heuristic techniques and a largely qualitative understanding of their behavior. In this article, we attempt to move towards a more formalized approach to the analysis of LC/TOFMS data by establishing some of the core concepts required for a detailed mathematical description of the data. Using arguments that are based on the fundamental workings of the instrument, we derive and validate a probability distribution that approximates that of the empirically obtained data and on the basis of which formal statistical tests can be constructed. Unlike many existing statistical models for MS data, the one presented here aims for rigor rather than generality. Consequently, the model is closely tailored to a particular type of TOF mass spectrometer although the general approach carries over to other instrument designs. Looking ahead, we argue that further improvements in our ability to characterize the data mathematically could enable us to address a wide range of data analytical problems in a statistically rigorous manner

Structural Organization of the 19S Proteasome Lid: Insights from MS of Intact Complexes

The 26S proteasome contains a 19S regulatory particle that selects and unfolds ubiquitinated substrates for degradation in the 20S catalytic particle. To date there are no high-resolution structures of the 19S assembly, nor of the lid or base subcomplexes that constitute the 19S. Mass spectra of the intact lid complex from Saccharomyces cerevisiae show that eight of the nine subunits are present stoichiometrically and that a stable tetrameric subcomplex forms in solution. Application of tandem mass spectrometry to the intact lid complex reveals the subunit architecture, while the coupling of a cross-linking approach identifies further interaction partners. Taking together our results with previous analyses we are able to construct a comprehensive interaction map. In summary, our findings allow us to identify a scaffold for the assembly of the particle and to propose a regulatory mechanism that prevents exposure of the active site until assembly is complete. More generally, the results highlight the potential of mass spectrometry to add crucial insight into the structural organization of an endogenous, wild-type complex

LipidXplorer: A Software for Consensual Cross-Platform Lipidomics

LipidXplorer is the open source software that supports the quantitative characterization of complex lipidomes by interpreting large datasets of shotgun mass spectra. LipidXplorer processes spectra acquired on any type of tandem mass spectrometers; it identifies and quantifies molecular species of any ionizable lipid class by considering any known or assumed molecular fragmentation pathway independently of any resource of reference mass spectra. It also supports any shotgun profiling routine, from high throughput top-down screening for molecular diagnostic and biomarker discovery to the targeted absolute quantification of low abundant lipid species. Full documentation on installation and operation of LipidXplorer, including tutorial, collection of spectra interpretation scripts, FAQ and user forum are available through the wiki site at: https://wiki.mpi-cbg.de/wiki/lipidx/index.php/Main_Page

Modular Mass Spectrometric Tool for Analysis of Composition and Phosphorylation of Protein Complexes

The combination of high accuracy, sensitivity and speed of single and multiple-stage mass spectrometric analyses enables the collection of comprehensive sets of data containing detailed information about complex biological samples. To achieve these properties, we combined two high-performance matrix-assisted laser desorption ionization mass analyzers in one modular mass spectrometric tool, and applied this tool for dissecting the composition and post-translational modifications of protein complexes. As an example of this approach, we here present studies of the Saccharomyces cerevisiae anaphase-promoting complexes (APC) and elucidation of phosphorylation sites on its components. In general, the modular concept we describe could be useful for assembling mass spectrometers operating with both matrix-assisted laser desorption ionization (MALDI) and electrospray ionization (ESI) ion sources into powerful mass spectrometric tools for the comprehensive analysis of complex biological samples