Tamir Tuller

Translation efficiency is determined by both codon bias and folding energy

Synonymous mutations do not alter the protein produced yet can have a significant effect on protein levels. The mechanisms by which this effect is achieved are controversial; although some previous studies have suggested that codon bias is the most important determinant of translation efficiency, a recent study suggested that mRNA folding at the beginning of genes is the dominant factor via its effect on translation initiation. Using the Escherichia coli and Saccharomyces cerevisiae transcriptomes, we conducted a genome-scale study aiming at dissecting the determinants of translation efficiency. There is a significant association between codon bias and translation efficiency across all endogenous genes in E. coli and S. cerevisiae but no association between folding energy and translation efficiency, demonstrating the role of codon bias as an important determinant of translation efficiency. However, folding energy does modulate the strength of association between codon bias and translation efficiency, which is maximized at very weak mRNA folding (i.e., high folding energy) levels. We find a strong correlation between the genomic profiles of ribosomal density and genomic profiles of folding energy across mRNA, suggesting that lower folding energies slow down the ribosomes and decrease translation efficiency. Accordingly, we find that selection forces act near uniformly to decrease the folding energy at the beginning of genes. In summary, these findings testify that in endogenous genes, folding energy affects translation efficiency in a global manner that is not related to the expression levels of individual genes, and thus cannot be detected by correlation with their expression levels.

Composite effects of gene determinants on the translation speed and density of ribosomes

BackgroundTranslation is a central process of life, and its regulation is crucial for cell growth. In this article, focusing on two model organisms, Escherichia coli and Saccharomyces cerevisiae, we study how three major local features of a genes coding sequence (its adaptation to the tRNA pool, its amino acid charge, and its mRNA folding energy) affect its translation elongation.ResultsWe find that each of these three different features has a non-negligible distinct correlation with the speed of translation elongation. In addition, each of these features might contribute independently to slowing down ribosomal speed at the beginning of genes, which was suggested in previous studies to improve ribosomal allocation and the cost of translation, and to decrease ribosomal jamming. Remarkably, a model of ribosomal translation based on these three basic features highly correlated with the genomic profile of ribosomal density. The robustness to transcription errors in terms of the values of these features is higher at the beginnings of genes, suggesting that this region is important for translation.ConclusionsThe reported results support the conjecture that translation elongation speed is affected by the three coding sequence determinants mentioned above, and not only by adaptation to the tRNA pool; thus, evolution shapes all these determinants along the coding sequences and across genes to improve the organisms translation efficiency.

Maximum likelihood of phylogenetic networks

MOTIVATION Horizontal gene transfer (HGT) is believed to be ubiquitous among bacteria, and plays a major role in their genome diversification as well as their ability to develop resistance to antibiotics. In light of its evolutionary significance and implications for human health, developing accurate and efficient methods for detecting and reconstructing HGT is imperative. RESULTS In this article we provide a new HGT-oriented likelihood framework for many problems that involve phylogeny-based HGT detection and reconstruction. Beside the formulation of various likelihood criteria, we show that most of these problems are NP-hard, and offer heuristics for efficient and accurate reconstruction of HGT under these criteria. We implemented our heuristics and used them to analyze biological as well as synthetic data. In both cases, our criteria and heuristics exhibited very good performance with respect to identifying the correct number of HGT events as well as inferring their correct location on the species tree. AVAILABILITY Implementation of the criteria as well as heuristics and hardness proofs are available from the authors upon request. Hardness proofs can also be downloaded at http://www.cs.tau.ac.il/~tamirtul/MLNET/Supp-ML.pdf

Determinants of Protein Abundance and Translation Efficiency in S. cerevisiae

The translation efficiency of most Saccharomyces cerevisiae genes remains fairly constant across poor and rich growth media. This observation has led us to revisit the available data and to examine the potential utility of a protein abundance predictor in reinterpreting existing mRNA expression data. Our predictor is based on large-scale data of mRNA levels, the tRNA adaptation index, and the evolutionary rate. It attains a correlation of 0.76 with experimentally determined protein abundance levels on unseen data and successfully cross-predicts protein abundance levels in another yeast species (Schizosaccharomyces pombe). The predicted abundance levels of proteins in known S. cerevisiae complexes, and of interacting proteins, are significantly more coherent than their corresponding mRNA expression levels. Analysis of gene expression measurement experiments using the predicted protein abundance levels yields new insights that are not readily discernable when clustering the corresponding mRNA expression levels. Comparing protein abundance levels across poor and rich media, we find a general trend for homeostatic regulation where transcription and translation change in a reciprocal manner. This phenomenon is more prominent near origins of replications. Our analysis shows that in parallel to the adaptation occurring at the tRNA level via the codon bias, proteins do undergo a complementary adaptation at the amino acid level to further increase their abundance.

The effect of tRNA levels on decoding times of mRNA codons

The possible effect of transfer ribonucleic acid (tRNA) concentrations on codons decoding time is a fundamental biomedical research question; however, due to a large number of variables affecting this process and the non-direct relation between them, a conclusive answer to this question has eluded so far researchers in the field. In this study, we perform a novel analysis of the ribosome profiling data of four organisms which enables ranking the decoding times of different codons while filtering translational phenomena such as experimental biases, extreme ribosomal pauses and ribosome traffic jams. Based on this filtering, we show for the first time that there is a significant correlation between tRNA concentrations and the codons estimated decoding time both in prokaryotes and in eukaryotes in natural conditions (−0.38 to −0.66, all P values <0.006); in addition, we show that when considering tRNA concentrations, codons decoding times are not correlated with aminoacyl-tRNA levels. The reported results support the conjecture that translation efficiency is directly influenced by the tRNA levels in the cell. Thus, they should help to understand the evolution of synonymous aspects of coding sequences via the adaptation of their codons to the tRNA pool.

Determinants of Translation Elongation Speed and Ribosomal Profiling Biases in Mouse Embryonic Stem Cells

Ribosomal profiling is a promising approach with increasing popularity for studying translation. This approach enables monitoring the ribosomal density along genes at a resolution of single nucleotides. In this study, we focused on ribosomal density profiles of mouse embryonic stem cells. Our analysis suggests, for the first time, that even in mammals such as M. musculus the elongation speed is significantly and directly affected by determinants of the coding sequence such as: 1) the adaptation of codons to the tRNA pool; 2) the local mRNA folding of the coding sequence; 3) the local charge of amino acids encoded in the codon sequence. In addition, our analyses suggest that in general, the translation velocity of ribosomes is slower at the beginning of the coding sequence and tends to increase downstream. Finally, a comparison of these data to the expected biophysical behavior of translation suggests that it suffers from some unknown biases. Specifically, the ribosomal flux measured on the experimental data increases along the coding sequence; however, according to any biophysical model of ribosomal movement lacking internal initiation sites, the flux is expected to remain constant or decrease. Thus, developing experimental and/or statistical methods for understanding, detecting and dealing with such biases is of high importance.

Multiple roles of the coding sequence 5′ end in gene expression regulation

The codon composition of the coding sequences (ORF) 5′ end first few dozen codons is known to be distinct to that of the rest of the ORF. Various explanations for the unusual codon distribution in this region have been proposed in recent years, and include, among others, novel regulatory mechanisms of translation initiation and elongation. However, due to the fact that many overlapping regulatory signals are suggested to be associated with this relatively short region, its research is challenging. Here, we review the currently known signals that appear in this region, the theories related to the way they regulate translation and affect the organismal fitness, and the debates they provoke.

Strong association between mRNA folding strength and protein abundance in S. cerevisiae

One of the open questions in regulatory genomics is how the efficiency of gene translation is encoded in the coding sequence. Here we analyse recently generated measurements of folding energy in Saccharomyces cerevisiae, showing that genes with high protein abundance tend to have strong mRNA folding (mF; R=0.68). mF strength also strongly correlates with ribosomal density and mRNA levels, suggesting that this relation at least partially pertains to the efficiency of translation elongation, presumably by preventing aggregation of mRNA molecules.

Maximum likelihood of evolutionary trees: hardness and approximation

MOTIVATION Maximum likelihood (ML) is an increasingly popular optimality criterion for selecting evolutionary trees. Yet the computational complexity of ML was open for over 20 years, and only recently resolved by the authors for the Jukes-Cantor model of substitution and its generalizations. It was proved that reconstructing the ML tree is computationally intractable (NP-hard). In this work we explore three directions, which extend that result. RESULTS (1) We show that ML under the assumption of molecular clock is still computationally intractable (NP-hard). (2) We show that not only is it computationally intractable to find the exact ML tree, even approximating the logarithm of the ML for any multiplicative factor smaller than 1.00175 is computationally intractable. (3) We develop an algorithm for approximating log-likelihood under the condition that the input sequences are sparse. It employs any approximation algorithm for parsimony, and asymptotically achieves the same approximation ratio. We note that ML reconstruction for sparse inputs is still hard under this condition, and furthermore many real datasets satisfy it.

Laquinimod suppress antigen presentation in relapsing-remitting multiple sclerosis: in-vitro high-throughput gene expression study.

Laquinimod (LAQ) is a new immunomodulatory drug shown to be effective in the treatment of relapsing-remitting multiple sclerosis (RRMS); however, its molecular target pathways are not well recognized. In this study we characterized in-vitro the molecular effects of LAQ in peripheral blood mononuclear cells (PBMC) of healthy subjects and RRMS patients by gene expression microarrays. We demonstrated that LAQ induced suppression of genes related to antigen presentation and corresponding inflammatory pathways. These findings were demonstrated mainly via the NFkB pathway. Analysis of PBMC subpopulations identified activation of Th2 response in CD14+ and CD4+ cells and suppression of proliferation in CD8+ cells.