Meclizine Inhibits Mitochondrial Respiration through Direct Targeting of Cytosolic Phosphoethanolamine Metabolism

We recently identified meclizine, an over-the-counter drug, as an inhibitor of mitochondrial respiration. Curiously, meclizine blunted respiration in intact cells but not in isolated mitochondria, suggesting an unorthodox mechanism. Using a metabolic profiling approach, we now show that treatment with meclizine leads to a sharp elevation of cellular phosphoethanolamine, an intermediate in the ethanolamine branch of the Kennedy pathway of phosphatidylethanolamine biosynthesis. Metabolic labeling and in vitro enzyme assays confirmed direct inhibition of the cytosolic enzyme CTP:phosphoethanolamine cytidylyltransferase (PCYT2). Inhibition of PCYT2 by meclizine led to rapid accumulation of its substrate, phosphoethanolamine, which is itself an inhibitor of mitochondrial respiration. Our work identifies the first pharmacologic inhibitor of the Kennedy pathway, demonstrates that its biosynthetic intermediate is an endogenous inhibitor of respiration, and provides key mechanistic insights that may facilitate repurposing meclizine for disorders of energy metabolism.     

Real-Time Subject-Independent Pattern Classification of Overt and Covert Movements from fNIRS Signals

Recently, studies have reported the use of Near Infrared Spectroscopy (NIRS) for developing Brain–Computer Interface (BCI) by applying online pattern classification of brain states from subject-specific fNIRS signals. The purpose of the present study was to develop and test a real-time method for subject-specific and subject-independent classification of multi-channel fNIRS signals using support-vector machines (SVM), so as to determine its feasibility as an online neurofeedback system. Towards this goal, we used left versus right hand movement execution and movement imagery as study paradigms in a series of experiments. In the first two experiments, activations in the motor cortex during movement execution and movement imagery were used to develop subject-dependent models that obtained high classification accuracies thereby indicating the robustness of our classification method. In the third experiment, a generalized classifier-model was developed from the first two experimental data, which was then applied for subject-independent neurofeedback training. Application of this method in new participants showed mean classification accuracy of 63% for movement imagery tasks and 80% for movement execution tasks. These results, and their corresponding offline analysis reported in this study demonstrate that SVM based real-time subject-independent classification of fNIRS signals is feasible. This method has important applications in the field of hemodynamic BCIs, and neuro-rehabilitation where patients can be trained to learn spatio-temporal patterns of healthy brain activity.     

A protocol for culturing Drosophila melanogaster stage 9 egg chambers for live imaging

This protocol describes a method for the dissection of egg chambers from intact Drosophila females and culture conditions that permit live imaging of them, with a particular emphasis on stage 9. This stage of development is characterized by oocyte growth and patterning, outer follicle cell rearrangement and migration of border cells. Although in vitro culture of egg chambers of later developmental stages has long been possible, until recently stage 9 egg chambers could only be kept alive for short periods, did not develop normally, and border cell migration failed entirely. We have established culture conditions that support overall egg chamber development including border cell migration in vitro. This protocol makes possible direct observation of molecular and cellular dynamics in both wild-type and mutant egg chambers, and opens the door to testing of pharmacological inhibitors and the use of biosensors. The entire protocol takes approximately 24 h while the preparation of egg chambers for live imaging requires only 15-20 min.     

Validation-based model selection for 13C metabolic flux analysis with uncertain measurement errors

Accurate measurements of metabolic fluxes in living cells are central to metabolism research and metabolic engineering. The gold standard method is model-based metabolic flux analysis (MFA), where fluxes are estimated indirectly from mass isotopomer data with the use of a mathematical model of the metabolic network. A critical step in MFA is model selection: choosing what compartments, metabolites, and reactions to include in the metabolic network model. Model selection is often done informally during the modelling process, based on the same data that is used for model fitting (estimation data). This can lead to either overly complex models (overfitting) or too simple ones (underfitting), in both cases resulting in poor flux estimates. Here, we propose a method for model selection based on independent validation data. We demonstrate in simulation studies that this method consistently chooses the correct model in a way that is independent on errors in measurement uncertainty. This independence is beneficial, since estimating the true magnitude of these errors can be difficult. In contrast, commonly used model selection methods based on the χ²-test choose different model structures depending on the believed measurement uncertainty; this can lead to errors in flux estimates, especially when the magnitude of the error is substantially off. We present a new approach for quantification of prediction uncertainty of mass isotopomer distributions in other labelling experiments, to check for problems with too much or too little novelty in the validation data. Finally, in an isotope tracing study on human mammary epithelial cells, the validation-based model selection method identified pyruvate carboxylase as a key model component. Our results argue that validation-based model selection should be an integral part of MFA model development.     

Nutrient-responsive O-GlcNAcylation dynamically modulates the secretion of glycan-binding protein galectin 3

Endomembrane glycosylation and cytoplasmic O-GlcNAcylation each play essential roles in nutrient sensing, and characteristic changes in glycan patterns have been described in disease states such as diabetes and cancer. These changes in glycosylation have important functional roles and can drive disease progression. However, little is known about the molecular mechanisms underlying how these signals are integrated and transduced into biological effects. Galectins are proteins that bind glycans and that are secreted by a poorly characterized nonclassical secretory mechanism. Once outside the cell, galectins bind to the terminal galactose residues of cell surface glycans and modulate numerous extracellular functions, such as clathrin-independent endocytosis (CIE). Originating in the cytoplasm, galectins are predicted substrates for O-GlcNAc addition and removal; and as we have shown, galectin 3 is a substrate for O-GlcNAc transferase. In this study, we also show that galectin 3 secretion is sensitive to changes in O-GlcNAc levels. We determined using immunoprecipitation and Western blotting that there is a significant difference in O-GlcNAcylation status between cytoplasmic and secreted galectin 3. We observed dramatic alterations in galectin 3 secretion in response to nutrient conditions, which were dependent on dynamic O-GlcNAcylation. Importantly, we showed that these O-GlcNAc-driven alterations in galectin 3 secretion also facilitated changes in CIE. These results indicate that dynamic O-GlcNAcylation of galectin 3 plays a role in modulating its secretion and can tune its function in transducing nutrient-sensing information coded in cell surface glycosylation into biological effects.     

Monoclonal antibodies as therapeutics in oncology

The specificity of antibodies has been harnessed to target cancer cells and the first therapeutic antibodies for use in oncology are now finding application in the clinic. Studies are currently under way to develop new and improved antibodies. Recent developments have been made in the identification of novel targets, including the use of genomic and proteomic technologies. Several methods are also being developed to enhance antibody efficacy.     

Increased Protease-Activated Receptor-2 (PAR-2) Expression on CD14++CD16+ Peripheral Blood Monocytes of Patients with Severe Asthma

Background

Protease-Activated Receptor-2 (PAR-2), a G protein coupled receptor activated by serine proteases, is widely expressed in humans and is involved in inflammation. PAR-2 activation in the airways plays an important role in the development of allergic airway inflammation. PAR-2 expression is known to be upregulated in the epithelium of asthmatic subjects, but its expression on immune and inflammatory cells in patients with asthma has not been studied.

Methods

We recruited 12 severe and 24 mild/moderate asthmatics from the University of Alberta Hospital Asthma Clinics and collected baseline demographic information, medication use and parameters of asthma severity. PAR-2 expression on blood inflammatory cells was analyzed by flow cytometry.

Results

Subjects with severe asthma had higher PAR-2 expression on CD14⁺⁺CD16⁺ monocytes (intermediate monocytes) and also higher percentage of CD14⁺⁺CD16⁺PAR-2⁺ monocytes (intermediate monocytes expressing PAR-2) in blood compared to subjects with mild/moderate asthma. Receiver operating characteristics (ROC) curve analysis showed that the percent of CD14⁺⁺CD16⁺PAR-2⁺ in peripheral blood was able to discriminate between patients with severe and those with mild/moderate asthma with high sensitivity and specificity. In addition, among the whole populations, subjects with a history of asthma exacerbations over the last year had higher percent of CD14⁺⁺CD16⁺ PAR-2⁺ cells in peripheral blood compared to subjects without exacerbations.

Conclusions

PAR-2 expression is increased on CD14⁺⁺CD16⁺ monocytes in the peripheral blood of subjects with severe asthma and may be a biomarker of asthma severity. Our data suggest that PAR-2 -mediated activation of CD14⁺⁺CD16⁺ monocytes may play a role in the pathogenesis of severe asthma.