Activity-based E3 ligase profiling uncovers an E3 ligase with esterification activity

Ubiquitination is initiated by transfer of ubiquitin (Ub) from a ubiquitin-activating enzyme (E1) to a ubiquitin-conjugating enzyme (E2), producing a covalently linked intermediate (E2-Ub)(1). Ubiquitin ligases (E3s) of the 'really interesting new gene' (RING) class recruit E2-Ub via their RING domain and then mediate direct transfer of ubiquitin to substrates(2). By contrast, 'homologous to E6-AP carboxy terminus' (HECT) E3 ligases undergo a catalytic cysteine-dependent transthiolation reaction with E2-Ub, forming a covalent E3-Ub intermediate(3,4). Additionally, RING-between-RING (RBR) E3 ligases have a canonical RING domain that is linked to an ancillary domain. This ancillary domain contains a catalytic cysteine that enables a hybrid RING-HECT mechanism(5). Ubiquitination is typically considered a post-translational modification of lysine residues, as there are no known human E3 ligases with non-lysine activity. Here we perform activity-based protein profiling of HECT or RBR-like E3 ligases and identify the neuron-associated E3 ligase MYCBP2 (also known as PHR1) as the apparent single member of a class of RING-linked E3 ligase with esterification activity and intrinsic selectivity for threonine over serine. MYCBP2 contains two essential catalytic cysteine residues that relay ubiquitin to its substrate via thioester intermediates. Crystallographic characterization of this class of E3 ligase, which we designate RING-Cys-relay (RCR), provides insights into its mechanism and threonine selectivity. These findings implicate non-lysine ubiquitination in cellular regulation of higher eukaryotes and suggest that E3 enzymes have an unappreciated mechanistic diversity

Machine learning on normalized protein sequences

<p>Abstract</p> <p>Background</p> <p>Machine learning techniques have been widely applied to biological sequences, e.g. to predict drug resistance in HIV-1 from sequences of drug target proteins and protein functional classes. As deletions and insertions are frequent in biological sequences, a major limitation of current methods is the inability to handle varying sequence lengths.</p> <p>Findings</p> <p>We propose to normalize sequences to uniform length. To this end, we tested one linear and four different non-linear interpolation methods for the normalization of sequence lengths of 19 classification datasets. Classification tasks included prediction of HIV-1 drug resistance from drug target sequences and sequence-based prediction of protein function. We applied random forests to the classification of sequences into "positive" and "negative" samples. Statistical tests showed that the linear interpolation outperforms the non-linear interpolation methods in most of the analyzed datasets, while in a few cases non-linear methods had a small but significant advantage. Compared to other published methods, our prediction scheme leads to an improvement in prediction accuracy by up to 14%.</p> <p>Conclusions</p> <p>We found that machine learning on sequences normalized by simple linear interpolation gave better or at least competitive results compared to state-of-the-art procedures, and thus, is a promising alternative to existing methods, especially for protein sequences of variable length.</p

Chemical Modification of Graphene Oxide by Nitrogenation: An X-ray Absorption and EmissionSpectroscopy Study

Nitrogen-doped graphene oxides (GO:Nx) were synthesized by a partial reduction of graphene oxide (GO) using urea [CO(NH2)2]. Their electronic/bonding structures were investigated using X-ray absorption near-edge structure (XANES), valence-band photoemission spectroscopy (VB-PES), X-ray emission spectroscopy (XES) and resonant inelastic X-ray scattering (RIXS). During GO:Nx synthesis, different nitrogen-bonding species, such as pyrrolic/graphitic-nitrogen, were formed by replacing of oxygen-containing functional groups. At lower N-content (2.7 at%), pyrrolic-N, owing to surface and subsurface diffusion of C, N and NH is deduced from various X-ray spectroscopies. In contrast, at higher N-content (5.0 at%) graphitic nitrogen was formed in which each N-atom trigonally bonds to three distinct sp2-hybridized carbons with substitution of the N-atoms for C atoms in the graphite layer. Upon nitrogen substitution, the total density of state close to Fermi level is increased to raise the valence-band maximum, as revealed by VB-PES spectra, indicating an electron donation from nitrogen, molecular bonding C/N/O coordination or/and lattice structure reorganization in GO:Nx. The well-ordered chemical environments induced by nitrogen dopant are revealed by XANES and RIXS measurements

B cell depletion in autoimmune diabetes:insights from murine models

INTRODUCTION: The incidence of type 1 diabetes (T1D) is rising for reasons that largely elude us. New strategies aimed at halting the disease process are needed. One type of immune cell thought to contribute to T1D is the B lymphocyte. The first Phase II trial of B cell depletion in new onset T1D patients indicated that this slowed the destruction of insulin-producing pancreatic beta cells. The mechanistic basis of the beneficial effects remains unclear. AREAS COVERED: Studies of B cell depletion and deficiency in animal models of T1D. How B cells can influence T cell-dependent autoimmune diabetes in animal models. The heterogeneity of B cell populations and current evidence for the potential contribution of specific B cell subsets to diabetes, with emphasis on marginal zone B cells and B1 B cells. EXPERT OPINION: B cells can influence the T cell response to islet antigens and B cell depletion or genetic deficiency is associated with decreased insulitis in animal models. New evidence suggests that B1 cells may contribute to diabetes pathogenesis. A better understanding of the roles of individual B cell subsets in disease will permit fine-tuning of therapeutic strategies to modify these populations

Green Tea Is Neuroprotective in Diabetic Retinopathy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)PURPOSE. Green tea (GT), widely studied for its beneficial properties in protecting against brain ischemia, is a rich source of polyphenols, particularly (-)-epigallocatechin gallate (EGCG). The results presented here demonstrate the beneficial effects of GT in diabetic retinas and in retinal cells under diabetic conditions. METHODS. Diabetes was induced in spontaneously hypertensive rats (SHR) and Wistar-Kyoto rats. Treatment animals received GT orally for 12 weeks. A vehicle was administered orally to the control animals. The protective effects of GT were also evaluated in Muller and in ARPE-19 cells. RESULTS. In diabetic rats, there was an increase in the expression of glial fibrillary acidic protein (GFAP), oxidative retinal markers, and glutamine synthetase levels. In addition, there was a decrease in occludin and glutamate transporter and receptor. Diabetic SHR also demonstrated blood-retinal barrier breakdown and impaired electroretinography results. Muller cells exposed to high-glucose medium produced higher levels of reactive oxygen species (ROS) and glutamine synthetase but reduced levels of glutathione, glutamate transporter, and glutamate receptor. Similarly, ARPE-19 cells exhibited increased ROS production accompanied by decreased expression of claudin-1 and glutamate transporter. Treatment with GT fully restored all the above-mentioned alterations in diabetic animals as well as in retinal cells. CONCLUSIONS. GT protected the retina against glutamate toxicity via an antioxidant mechanism. These findings reveal a novel mechanism by which GT protects the retina against neurodegeneration in disorders such as diabetic retinopathy. (Invest Ophthalmol Vis Sci. 2013;54:1325-1336) DOI:10.1167/iovs.12-10647O TEXTO COMPLETO DESTE ARTIGO, ESTARÁ DISPONÍVEL À PARTIR DE FEVEREIRO DE 2015.54213251336Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)FAPESP [2008/57560-0, 2010/11514-7