Selective inhibition of hepatic peroxisomal fatty acid beta-oxidation by enoximone.

Although beta-oxidation of fatty acids occurs in both peroxisomes and mitochondria, beta-oxidizing enzymes in these organelles have distinct differences in their specifity and sensitivity to inhibitors. In this study, the effects of the phosphodiesterase inhibitor enoximone on hepatic peroxisomal and mitochondrial beta-oxidation were investigated. In liver homogenates from control rats, cyanide-insensitive peroxisomal beta-oxidation of palmitoyl-CoA was inhibited progressively by increasing concentrations of enoximone. Similar results were obtained in liver homogenates from rats pretreated with the known peroxisomal proliferator diethylhexylphthalate. In contrast, mitochondrial beta-oxidation of palmitoyl-CoA was not inhibited by enoximone. These data show that enoximone selectively inhibits basal as well as induced peroxisomal, but not mitochondrial, beta-oxidation of the CoA thioester of long-chain fatty acids. The availability of specific inhibitors of peroxisomal beta-oxidation should prove useful in elucidating regulatory mechanisms operative in this pathway in normal as well as in proliferated peroxisomes.     

Classification of electron sub-tomograms with neural networks and its application to template-matching

Classification of electron sub-tomograms is a challenging task, due the missing-wedge and the low signal-to-noise ratio of the data. Classification algorithms tend to classify data according to their orientation to the missing-wedge, rather than to the underlying signal. Here we use a neural network approach, called the Kernel Density Estimator Self-Organizing Map (KerDenSOM3D), which we have implemented in three-dimensions (3D), also having compensated for the missing-wedge, and we comprehensively compare it to other classification methods. For this purpose, we use various simulated macromolecules, as well as tomographically reconstructed in vitro GroEL and GroEL/GroES molecules. We show that the performance of this classification method is superior to previously used algorithms. Furthermore, we show how this algorithm can be used to provide an initial cross-validation of template-matching approaches. For the example of sub-tomogram classification extracted from cellular tomograms of Mycoplasma pneumonia and Spiroplasma melliferum cells, we show the bias of template-matching, and by using differing search and classification areas, we demonstrate how the bias can be significantly reduced.     

Cytoplasmic Relaxation of Active Eph Controls Ephrin Shedding by ADAM10

Release of cell surface-bound ligands by A-Disintegrin-And-Metalloprotease (ADAM) transmembrane metalloproteases is essential for signalling by cytokine, cell adhesion, and tyrosine kinase receptors. For Eph receptor ligands, it provides the switch between cell-cell adhesion and repulsion. Ligand shedding is tightly controlled by intrinsic tyrosine kinase activity, which for Eph receptors relies on the release of an inhibitory interaction of the cytoplasmic juxtamembrane segment with the kinase domain. However, a mechanism linking kinase and sheddase activities had remained elusive. We demonstrate that it is a membrane-proximal localisation of the latent kinase domain that prevents ephrin ligand shedding in trans. Fluorescence lifetime imaging microscopy and electron tomography reveal that activation extends the Eph receptor tyrosine kinase intracellular domain away from the cell membrane into a conformation that facilitates productive association with ADAM10. Accordingly, EphA3 mutants with constitutively-released kinase domains efficiently support shedding, even when their kinase is disabled. Our data suggest that this phosphorylation-activated conformational switch of EphA3 directly controls ADAM-mediated shedding.     

Structural characterization of the NAP; the major adhesion complex of the human pathogen Mycoplasma genitalium

Mycoplasma genitalium, the causative agent of non‐gonococcal urethritis and pelvic inflammatory disease in humans, is a small eubacterium that lacks a peptidoglycan cell wall. On the surface of its plasma membrane is the major surface adhesion complex, known as NAP that is essential for adhesion and gliding motility of the organism. Here, we have performed cryo‐electron tomography of intact cells and detergent permeabilized M. genitalium cell aggregates, providing sub‐tomogram averages of free and cell‐attached NAPs respectively, revealing a tetrameric complex with two‐fold rotational (C2) symmetry. Each NAP has two pairs of globular lobes (named α and β lobes), arranged as a dimer of heterodimers with each lobe connected by a stalk to the cell membrane. The β lobes are larger than the α lobes by 20%. Classification of NAPs showed that the complex can tilt with respect to the cell membrane. A protein complex containing exclusively the proteins P140 and P110, was purified from M. genitalium and was structurally characterized by negative‐stain single particle EM reconstruction. The close structural similarity found between intact NAPs and the isolated P140/P110 complexes, shows that dimers of P140/P110 heterodimers are the only components of the extracellular region of intact NAPs in M. genitalium.     

Classification of cryo-electron sub-tomograms using constrained correlation

Cryo-electron tomography (CET) is currently the only three-dimensional imaging technique capable of visualizing macromolecules in their cellular context at close-to-native conditions with a resolution in the nanometer range. An important component for the analysis of the data is their classification, which should discriminate among various macromolecules, conformational changes and interaction partners. Missing structure factors, typically in a wedge-shaped region in Fourier space if single-axis tilting is performed, hamper classification of cryo-electron tomographic data. Here, we describe a classification method for three-dimensional (3D) sub-tomograms extracted from cryo-electron tomograms, which takes the missing wedge into account and provides reliable results. The similarity of the individually aligned sub-tomograms is scored by constrained correlation. Subsequently, they are clustered based on their pairwise correlation values. In order to demonstrate the feasibility of this approach, we apply the proposed method to simulated tomographic data of the chaperone thermosome in different conformations. By comparison of the principal components of the resulting matrix we show that the proposed metric is significantly less prone to the orientation of the missing wedge compared to the unconstrained correlation. Moreover, we apply our classification method to an experimental dataset of GroEL with and without GroES, where we achieve a distinct discrimination between the putative GroEL and GroEL/GroES complexes.     

Clustered encouragement designs with individual noncompliance: bayesian inference with randomization,and application to advance directive forms

In many studies comparing a new 'target treatment' with a control target treatment, the received treatment does not always agree with assigned treatment-that is, the compliance is imperfect. An obvious example arises when ethical or practical constraints prevent even the randomized assignment of receipt of the new target treatment but allow the randomized assignment of the encouragement to receive this treatment. In fact, many randomized experiments where compliance is not enforced by the experimenter (e.g. with non-blinded assignment) may be more accurately thought of as randomized encouragement designs. Moreover, often the assignment of encouragement is at the level of clusters (e.g. doctors) where the compliance with the assignment varies across the units (e.g. patients) within clusters. We refer to such studies as 'clustered encouragement designs' (CEDs) and they arise relatively frequently (e.g. Sommer and Zeger, 1991; McDonald et al., 1992; Dexter et al., 1998) Here, we propose Bayesian methodology for causal inference for the effect of the new target treatment versus the control target treatment in the randomized CED with all-or-none compliance at the unit level, which generalizes the approach of Hirano et al. (2000) in important and surprisingly subtle ways, to account for the clustering, which is necessary for statistical validity. We illustrate our methods using data from a recent study exploring the role of physician consulting in increasing patients' completion of Advance Directive forms.