Translation termination factor aRF1 from the archaeon Methanococcus jannaschii is active with eukaryotic ribosomes

A bacterioferritin was recently isolated from the anaerobic sulphate-reducing bacterium Desulfovibrio desulfuricans ATCC 27774 [Romão et al. (2000) Biochemistry 39, 6841–6849]. Although its properties are in general similar to those of the other bacterioferritins, it contains a haem quite distinct from the haem B, found in bacterioferritins from aerobic organisms. Using visible and NMR spectroscopies, as well as mass spectrometry analysis, the haem is now unambiguously identified as iron-coproporphyrin III, the first example of such a prosthetic group in a biological system. This unexpected finding is discussed in the framework of haem biosynthetic pathways in anaerobes and particularly in sulphate-reducing bacteria.     

LPS-Induced Formation of Immunoproteasomes: TNF-α and Nitric Oxide Production are Regulated by Altered Composition of Proteasome-Active Sites

Stimulation of mouse macrophages with LPS leads to tumor necrosis factor (TNF-α) secretion and nitric oxide (NO) release at different times through independent signaling pathways. While the precise regulatory mechanisms responsible for these distinct phenotypic responses have not been fully delineated, results of our recent studies strongly implicate the cellular cytoplasmic ubiquitin-proteasome pathway as a key regulator of LPS-induced macrophage inflammatory responses. Our objective in this study was to define the relative contribution of specific proteasomal active-sites in induction of TNF-α and NO after LPS treatment of RAW 264.7 macrophages using selective inhibitors of these active sites. Our data provide evidence that LPS stimulation of mouse macrophages triggers a selective increase in the levels of gene and protein expression of the immunoproteasomes, resulting in a modulation of specific functional activities of the proteasome and a corresponding increase in NO production as compared to untreated controls. These findings suggest the LPS-dependent induction of immunoproteasome. In contrast, we also demonstrate that TNF-α expression is primarily dependent on both the chymotrypsin- and the trypsin-like activities of X, Y, Z subunits of the proteasome. Proteasome-associated post-acidic activity alone also contributes to LPS-induced expression of TNF-α. Taken together; our results indicate that LPS-induced TNF-α in macrophages is differentially regulated by each of the three proteasome activities. Since addition of proteasome inhibitors to mouse macrophages profoundly affects the degradation of proteins involved in signal transduction, we conclude that proteasome-specific degradation of several signaling proteins is likely involved in differential regulation of LPS-dependent secretion of proinflammatory mediators.     

<Emphasis Type="Italic">Scoredist</Emphasis>: A simple and robust protein sequence distance estimator

Background  

Distance-based methods are popular for reconstructing evolutionary trees thanks to their speed and generality. A number of methods exist for estimating distances from sequence alignments, which often involves some sort of correction for multiple substitutions. The problem is to accurately estimate the number of true substitutions given an observed alignment. So far, the most accurate protein distance estimators have looked for the optimal matrix in a series of transition probability matrices, e.g. the Dayhoff series. The evolutionary distance between two aligned sequences is here estimated as the evolutionary distance of the optimal matrix. The optimal matrix can be found either by an iterative search for the Maximum Likelihood matrix, or by integration to find the Expected Distance. As a consequence, these methods are more complex to implement and computationally heavier than correction-based methods. Another problem is that the result may vary substantially depending on the evolutionary model used for the matrices. An ideal distance estimator should produce consistent and accurate distances independent of the evolutionary model used.     

Improved profile HMM performance by assessment of critical algorithmic features in SAM and HMMER

Background  

Profile hidden Markov model (HMM) techniques are among the most powerful methods for protein homology detection. Yet, the critical features for successful modelling are not fully known. In the present work we approached this by using two of the most popular HMM packages: SAM and HMMER. The programs' abilities to build models and score sequences were compared on a SCOP/Pfam based test set. The comparison was done separately for local and global HMM scoring.     

Human CYP1A1 variants lead to differential eicosapentaenoic acid metabolite patterns

To answer the question whether the most common allelic variants of human CYP1A1, namely CYP1A1.1 (wild type), CYP1A1.2 (Ile462Val), and CYP1A1.4 (Thr461Asn), differ in their catalytic activity towards eicosapentaenoic acid (EPA), in vitro enzymatic assays were performed in reconstituted CYP1A1 systems. All CYP1A1 variants catalyzed EPA epoxygenation and hydroxylation to 17(R),18(S)-epoxyeicosatetraenoic acid (17(R),18(S)-EETeTr) and 19-OH-EPA, yet with varying catalytic efficiency and distinct regiospecificity. CYP1A1.1 and CYP1A1.4 formed 17(R),18(S)-EETeTr as main product (K(m)=53 and 50 microM; V(max)=0.60 and 0.50 pmol/min/pmol; V(max)/K(m)=0.11 and 0.10 microM(-1)min(-1), respectively), followed by 19-OH-EPA (K(m)=76 and 93 microM; V(max)=0.37 and 0.37 pmol/min/pmol; V(max)/K(m)=0.005 and 0.004 microM(-1)min(-1), respectively). The variant CYP1A1.2 produced almost equal amounts of both metabolites, but its catalytic efficiency for hydroxylation was five times higher (K(m)=66 microM; V(max)=1.7 pmol/min/pmol; V(max)/K(m)=0.026 microM(-1)min(-1)) and that for epoxygenation was twice higher (K(m)=66 microM; V(max)=1.5 pmol/min/pmol; V(max)/K(m)=0.023 microM(-1)min(-1)) than those of the wild-type enzyme. Thus, the Ile462Val polymorphism in human CYP1A1 affects EPA metabolism and may contribute to interindividual variance in the local production of physiologically active fatty acid metabolites in the cardiovascular system and other extrahepatic tissues, where CYP1A1 is expressed or induced by polycyclic aromatic hydrocarbons and other xenobiotics.     

The arrestin-bound conformation and dynamics of the phosphorylated carboxy-terminal region of rhodopsin

Visual arrestin binds to the phosphorylated carboxy-terminal region of rhodopsin to block interactions with transducin and terminate signaling in the rod photoreceptor cells. A synthetic seven-phospho-peptide from the C-terminal region of rhodopsin, Rh(330-348), has been shown to bind arrestin and mimic inhibition of signal transduction. In this study, we examine conformational changes in this synthetic peptide upon binding to arrestin by high-resolution proton nuclear magnetic resonance (NMR). We show that the peptide is completely disordered in solution, but becomes structured upon binding to arrestin. A control, unphosphorylated peptide that fails to bind to arrestin remains highly disordered. Specific NMR distance constraints are used to model the arrestin-bound conformation. The models suggest that the phosphorylated carboxy-terminal region of rhodopsin, Rh(330-348), undergoes significant conformational changes and becomes structured upon binding to arrestin.     

Termination of translation in eukaryotes is mediated by the quaternary eRF1*eRF3*GTP*Mg2+ complex. The biological roles of eRF3 and prokaryotic RF3 are profoundly distinct

GTP hydrolysis catalyzed in the ribosome by a complex of two polypeptide release factors, eRF1 and eRF3, is required for fast and efficient termination of translation in eukaryotes. Here, isothermal titration calorimetry is used for the quantitative thermodynamic characterization of eRF3 interactions with guanine nucleotides, eRF1 and Mg²⁺. We show that (i) eRF3 binds GDP (K_d = 1.9 μM) and this interaction depends only minimally on the Mg²⁺ concentration; (ii) GTP binds to eRF3 (K_d = 0.5 μM) only in the presence of eRF1 and this interaction depends on the Mg²⁺ concentration; (iii) GTP displaces GDP from the eRF1•eRF3•GDP complex, and vice versa; (iv) eRF3 in the GDP-bound form improves its ability to bind eRF1; (v) the eRF1•eRF3 complex binds GDP as efficiently as free eRF3; (vi) the eRF1•eRF3 complex is efficiently formed in the absence of GDP/GTP but requires the presence of the C-terminus of eRF1 for complex formation. Our results show that eRF1 mediates GDP/GTP displacement on eRF3. We suggest that after formation of eRF1•eRF3•GTP•Mg²⁺, this quaternary complex binds to the ribosomal pretermination complex containing P-site-bound peptidyl-tRNA and the A-site-bound stop codon. The guanine nucleotide binding properties of eRF3 and of the eRF3•eRF1 complex profoundly differ from those of prokaryotic RF3.     

Interface of the interaction of the middle domain of human translation termination factor eRF1 with eukaryotic ribosomes

Translation termination in eukaryotes is governed by the interaction of two, class 1 and class 2, polypeptide chain release factors with the ribosome. The middle (M) domain of the class 1 factor eRF1 contains the strictly conserved GGQ motif and is involved in hydrolysis of the peptidyl-tRNA ester bond in the peptidyl transferase center of the large ribosome subunit. Heteronuclear NMR spectroscopy was used to map the interaction interface of the M domain of human eRF1 with eukaryotic ribosomes. The protein was found to specifically interact with the 60S subunit, since no interaction was detected with the 40S subunit. The amino acid residues forming the interface mostly belong to long helix α1 of the M domain. Some residues adjacent to α1 and belonging to strand β5 and short helices α2 and α3 are also involved in the protein-ribosome contact. The functionally inactive G183A mutant interacted with the ribosome far more weakly as compared with the wild-type eRF1. The interaction interfaces of the two proteins were nonidentical. It was concluded that long helix α1 is functionally important and that the conformational flexibility of the GGQ loop is essential for the tight protein-ribosome contact.