Translation efficiency in humans: tissue specificity,global optimization and differences between developmental stages

Various studies in unicellular and multicellular organisms have shown that codon bias plays a significant role in translation efficiency (TE) by co-adaptation to the tRNA pool. Yet, in humans and other mammals the role of codon bias is still an open question, with contradictory results from different studies. Here we address this question, performing a large-scale tissue-specific analysis of TE in humans, using the tRNA Adaptation Index (tAI) as a direct measure for TE. We find tAI to significantly correlate with expression levels both in tissue-specific and in global expression measures, testifying to the TE of human tissues. Interestingly, we find significantly higher correlations in adult tissues as opposed to fetal tissues, suggesting that the tRNA pool is more adjusted to the adult period. Optimization based analysis suggests that the tRNA pool—codon bias co-adaptation is globally (and not tissue-specific) driven. Additionally, we find that tAI correlates with several measures related to the protein functionally importance, including gene essentiality. Using inferred tissue-specific tRNA pools lead to similar results and shows that tissue-specific genes are more adapted to their tRNA pool than other genes and that related sets of functional gene groups are translated efficiently in each tissue. Similar results are obtained for other mammals. Taken together, these results demonstrate the role of codon bias in TE in humans, and pave the way for future studies of tissue-specific TE in multicellular organisms.     

Network-Free Inference of Knockout Effects in Yeast

Perturbation experiments, in which a certain gene is knocked out and the expression levels of other genes are observed, constitute a fundamental step in uncovering the intricate wiring diagrams in the living cell and elucidating the causal roles of genes in signaling and regulation. Here we present a novel framework for analyzing large cohorts of gene knockout experiments and their genome-wide effects on expression levels. We devise clustering-like algorithms that identify groups of genes that behave similarly with respect to the knockout data, and utilize them to predict knockout effects and to annotate physical interactions between proteins as inhibiting or activating. Differing from previous approaches, our prediction approach does not depend on physical network information; the latter is used only for the annotation task. Consequently, it is both more efficient and of wider applicability than previous methods. We evaluate our approach using a large scale collection of gene knockout experiments in yeast, comparing it to the state-of-the-art SPINE algorithm. In cross validation tests, our algorithm exhibits superior prediction accuracy, while at the same time increasing the coverage by over 25-fold. Significant coverage gains are obtained also in the annotation of the physical network.     

Energy-linked nicotinamide-nucleotide transhydrogenase. Characterization of reconstituted ATP-driven transhydrogenase from beef heart mitochondria

The interaction between pure transhydrogenase and ATPase (Complex V) from beef heart mitochondria was investigated with transhydrogenase-ATPase vesicles in which the two proteins were co-reconstituted by dialysis or dilution procedures. In addition to phosphatidylcholine and phosphatidylethanolamine, reconstitution required phosphatidylserine and lysophosphatidylcholine. Transhydrogenase-ATPase vesicles catalyzed a 20-30-fold stimulation of the reduction of NADP+ or thio-NADP+ by NADH and a 70-fold shift of the apparent equilibrium expressed as the nicotinamide nucleotide ratio [NADPH][NAD+]/[NADP+][NADH]. In both of these respects, the transhydrogenase-ATPase vesicles were severalfold more efficient than beef heart submitochondrial particles. By measuring the ATP-driven transhydrogenase and the oligomycin-sensitive ATPase activities simultaneously and under the same conditions at low ATP concentrations, i.e. below 15 microM, the ATP-driven transhydrogenase/oligomycin-sensitive ATPase activity ratio was found to be about 3. This value is consistent with the stoichiometries of three protons translocated per ATP hydrolyzed and one proton translocated per NADPH formed and with a mechanism where the two enzymes interact through a delocalized proton-motive force.     

The protein substrate binding site of the ubiquitin-protein ligase system

In order to gain insight into the mechanisms that determine the selectivity of the ubiquitin proteolytic pathway, the protein substrate binding site of the ubiquitin-protein ligase system was identified and examined. Previous studies had shown that the ligase system consists of three components: a ubiquitin-activating enzyme (E1), ubiquitin-carrier protein (E2), and a third enzyme, E3, the mode of action of which has not been defined. E3 from rabbit reticulocytes was further purified by a combination of affinity chromatography, hydrophobic chromatography, and gel filtration procedures. A 180-kDa protein was identified as the subunit of E3. Two independent methods indicate that E3 has the protein binding site of the ubiquitin ligase system. These are the chemical cross-linking of 125I-labeled proteins to the E3 subunit and the functional conversion of enzyme-bound labeled proteins to ubiquitin conjugates in pulse-chase experiments. The trapping of E3-bound protein for labeled product formation was allowed by the slow dissociation of E3 X protein complex. The specificity of binding of different proteins to E3, examined by both methods, showed a direct correlation with their susceptibility to degradation by the ubiquitin system. Proteins with free alpha-NH2 groups, which are good substrates, bind better to E3 than corresponding proteins with blocked NH2 termini, which are not substrates. Oxidation of methionine residues to sulfoxide derivatives greatly increases the susceptibility of some proteins to ligation with ubiquitin, with a corresponding increase in their binding to E3. However, a protein derivative which was subjected to both amino group modification and oxidation binds strongly to the enzyme, even though it cannot be ligated to ubiquitin. It thus seems that the substrate binding site of E3 participates in determining the specificity of proteins that enter the ubiquitin pathway of protein degradation.     

Optimal firing in sparsely-connected low-activity attractor networks

We examine the performance of Hebbian-like attractor neural networks, recalling stored memory patterns from their distorted versions. Searching for an activation (firing-rate) function that maximizes the performance in sparsely connected low-activity networks, we show that the optimal activation function is a threshold-sigmoid of the neuron's input field. This function is shown to be in close correspondence with the dependence of the firing rate of cortical neurons on their integrated input current, as described by neurophysiological recordings and conduction-based models. It also accounts for the decreasing-density shape of firing rates that has been reported in the literature. Received:9 December 1994 / Accepted in revised form: 9 January 1996     

Hypothetical Outcome Plots Outperform Error Bars and Violin Plots for Inferences about Reliability of Variable Ordering

Many visual depictions of probability distributions, such as error bars, are difficult for users to accurately interpret. We present and study an alternative representation, Hypothetical Outcome Plots (HOPs), that animates a finite set of individual draws. In contrast to the statistical background required to interpret many static representations of distributions, HOPs require relatively little background knowledge to interpret. Instead, HOPs enables viewers to infer properties of the distribution using mental processes like counting and integration. We conducted an experiment comparing HOPs to error bars and violin plots. With HOPs, people made much more accurate judgments about plots of two and three quantities. Accuracy was similar with all three representations for most questions about distributions of a single quantity.     

Cole Disease Results from Mutations in ENPP1

The coexistence of abnormal keratinization and aberrant pigmentation in a number of cornification disorders has long suggested a mechanistic link between these two processes. Here, we deciphered the genetic basis of Cole disease, a rare autosomal-dominant genodermatosis featuring punctate keratoderma, patchy hypopigmentation, and uncommonly, cutaneous calcifications. Using a combination of exome and direct sequencing, we showed complete cosegregation of the disease phenotype with three heterozygous ENPP1 mutations in three unrelated families. All mutations were found to affect cysteine residues in the somatomedin-B-like 2 (SMB2) domain in the encoded protein, which has been implicated in insulin signaling. ENPP1 encodes ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1), which is responsible for the generation of inorganic pyrophosphate, a natural inhibitor of mineralization. Previously, biallelic mutations in ENPP1 were shown to underlie a number of recessive conditions characterized by ectopic calcification, thus providing evidence of profound phenotypic heterogeneity in ENPP1-associated genetic diseases.     

Evolutionary conservation and over-representation of functionally enriched network patterns in the yeast regulatory network

Background  

Localized network patterns are assumed to represent an optimal design principle in different biological networks. A widely used method for identifying functional components in biological networks is looking for network motifs – over-represented network patterns. A number of recent studies have undermined the claim that these over-represented patterns are indicative of optimal design principles and question whether localized network patterns are indeed of functional significance. This paper examines the functional significance of regulatory network patterns via their biological annotation and evolutionary conservation.     

Functional representation of enzymes by specific peptides

Predicting the function of a protein from its sequence is a long-standing goal of bioinformatic research. While sequence similarity is the most popular tool used for this purpose, sequence motifs may also subserve this goal. Here we develop a motif-based method consisting of applying an unsupervised motif extraction algorithm (MEX) to all enzyme sequences, and filtering the results by the four-level classification hierarchy of the Enzyme Commission (EC). The resulting motifs serve as specific peptides (SPs), appearing on single branches of the EC. In contrast to previous motif-based methods, the new method does not require any preprocessing by multiple sequence alignment, nor does it rely on over-representation of motifs within EC branches. The SPs obtained comprise on average 8.4 +/- 4.5 amino acids, and specify the functions of 93% of all enzymes, which is much higher than the coverage of 63% provided by ProSite motifs. The SP classification thus compares favorably with previous function annotation methods and successfully demonstrates an added value in extreme cases where sequence similarity fails. Interestingly, SPs cover most of the annotated active and binding site amino acids, and occur in active-site neighboring 3-D pockets in a highly statistically significant manner. The latter are assumed to have strong biological relevance to the activity of the enzyme. Further filtering of SPs by biological functional annotations results in reduced small subsets of SPs that possess very large enzyme coverage. Overall, SPs both form a very useful tool for enzyme functional classification and bear responsibility for the catalytic biological function carried out by enzymes.     

SKP2 is required for ubiquitin-mediated degradation of the CDK inhibitor p27

Degradation of the mammalian cyclin-dependent kinase (CDK) inhibitor p27 is required for the cellular transition from quiescence to the proliferative state. The ubiquitination and subsequent degradation of p27 depend on its phosphorylation by cyclin-CDK complexes. However, the ubiquitin-protein ligase necessary for p27 ubiquitination has not been identified. Here we show that the F-box protein SKP2 specifically recognizes p27 in a phosphorylation-dependent manner that is characteristic of an F-box-protein-substrate interaction. Furthermore, both in vivo and in vitro, SKP2 is a rate-limiting component of the machinery that ubiquitinates and degrades phosphorylated p27. Thus, p27 degradation is subject to dual control by the accumulation of both SKP2 and cyclins following mitogenic stimulation.