Dissecting eukaryotic translation and its control by ribosome density mapping

Basic anatomy and tumor biology of the RPS6KA6 gene that encodes the p90 ribosomal S6 kinase-4

The RPS6KA6 gene encodes the p90 ribosomal S6 kinase-4 (RSK4) that is still largely uncharacterized. In this study we identified a new RSK4 transcription initiation site and several alternative splice sites with a 5’RACE approach. The resulting mRNA variants encompass four possible first start codons. The first 15 nucleotides (nt) of exon 22 in mouse and the penultimate exon in both human (exon 21) and mouse (exon 24) RSK4 underwent alternative splicing, although the penultimate exon deleted variant appeared mainly in cell clines, but not in most normal tissues. Demethylation agent 5-azacytidine inhibited the deletion of the penultimate exon whereas two indolocarbazole-derived inhibitors of cyclin dependent kinase 4 or 6 induced deletion of the first 39 nt from exon 21 of human RSK4. In all human cancer cell lines studied, the 90-kD wild type RSK4 was sparse but, surprisingly, several isoforms at or smaller than 72-kD were expressed as detected by seven different antibodies. On immunoblots, each of these smaller isoforms often appeared as a duplet or triplet and the levels of these isoforms varied greatly among different cell lines and culture conditions. Cyclin D1 inhibited RSK4 expression and serum starvation enhanced the inhibition, whereas c-Myc and RSK4 inhibited cyclin D1. The effects of RSK4 on cell growth, cell death and chemoresponse depended on the mRNA variant or the protein isoform expressed, on the specificity of the cell lines, as well as on the anchorage-dependent or -independent growth conditions and the in vivo situation. Moreover, we also observed that even a given cDNA might be expressed to multiple proteins; therefore, when using a cDNA, one needs to exclude this possibility before attribution of the biological results from the cDNA to the anticipated protein. Collectively, our results suggest that whether RSK4 is oncogenic or tumor suppressive depends on many factors.

Mechanisms underlying the protein-kinase mediated regulation of the HERG potassium channel synthesis

The HERG (human ether-a-go-go related gene) potassium channel aids in the repolarization of the cardiomyocyte membrane at the end of each action potential. We have previously shown that sustained protein kinase A or C (PKA and PKC) activity specifically enhances channel synthesis over the course of hours to days in heterologous expression and cardiac myocytes. The kinase-mediated augmentation of the channel is post-transcriptional and occurs near or at the endoplasmic reticulum. Here we report our further investigations into the mechanisms of kinase-mediated augmentation of HERG channel protein. We show that HERG channel phosphorylation alone is not sufficient for the PKA-dependent increase to occur. In vitro translation studies indicate that an additional factor is required for the process. Pharmacologic inhibitors suggest that the channel augmentation is not due to kinase-mediated alteration in proteasome or lysosome activity. PKA activation had no effect on stability of HERG mRNA and polyribosomal profiling showed that kinase activity did not elevate translation from low to high rates. Transcriptional inhibition results suggest that the additional cellular factor is a PKA-regulated protein. Together, these findings suggest that PKA-mediated augmentation of HERG abundance is more complex than previously appreciated involving enhancement of already active translation rates, phosphorylation of the channel protein and at least one other cyclic-AMP/PKA-responsive protein. Further exploration of molecular components of this regulatory pathway will be necessary to determine exact mechanism and the biomedical impact of this process in vivo.

Sequestration of highly expressed mRNAs in cytoplasmic granules, P-bodies, and stress granules enhances cell viability

Transcriptome analyses indicate that a core 10%–15% of the yeast genome is modulated by a variety of different stresses. However, not all the induced genes undergo translation, and null mutants of many induced genes do not show elevated sensitivity to the particular stress. Elucidation of the RNA lifecycle reveals accumulation of non-translating mRNAs in cytoplasmic granules, P-bodies, and stress granules for future regulation. P-bodies contain enzymes for mRNA degradation; under stress conditions mRNAs may be transferred to stress granules for storage and return to translation. Protein degradation by the ubiquitin-proteasome system is elevated by stress; and here we analyzed the steady state levels, decay, and subcellular localization of the mRNA of the gene encoding the F-box protein, UFO1, that is induced by stress. Using the MS2L mRNA reporter system UFO1 mRNA was observed in granules that colocalized with P-bodies and stress granules. These P-bodies stored diverse mRNAs. Granules of two mRNAs transported prior to translation, ASH1-MS2L and OXA1-MS2L, docked with P-bodies. HSP12 mRNA that gave rise to highly elevated protein levels was not observed in granules under these stress conditions. ecd3, pat1 double mutants that are defective in P-body formation were sensitive to mRNAs expressed ectopically from strong promoters. These highly expressed mRNAs showed elevated translation compared with wild-type cells, and the viability of the mutants was strongly reduced. ecd3, pat1 mutants also exhibited increased sensitivity to different stresses. Our interpretation is that sequestration of highly expressed mRNAs in P-bodies is essential for viability. Storage of mRNAs for future regulation may contribute to the discrepancy between the steady state levels of many stress-induced mRNAs and their proteins. Sorting of mRNAs for future translation or decay by individual cells could generate potentially different phenotypes in a genetically identical population and enhance its ability to withstand stress.

10%–15% of the yeast genome is modulated by stress; however, there is a discrepancy between the genes that are upregulated and the sensitivity of the null mutants of those genes to the stress. The question is: what happens to these highly expressed mRNAs? mRNAs have a complex lifecycle and non-translating mRNAs can be stored in cytoplasmic granules, processing P-bodies, and stress granules for decay or future translation, respectively. UFO1 encodes a component of the regulated protein degradation system, and its transcription is elevated by stress; however, the deletion mutants do not show enhanced sensitivity. UFO1 mRNA is stored in P-bodies and stress granules. Storage of mRNAs may contribute to the discrepancy between the steady state levels of stress-induced mRNAs and their proteins. To test this hypothesis, we expressed high levels of mRNA in cells unable to form P-bodies. We found that translation of these mRNAs was 3–8 fold higher than in wild-type cells. Furthermore high level expression of mRNA affected the viability of the mutants. The ability to store mRNAs for future translation or decay would generate different phenotypes in a genetically identical population and enhance its ability to withstand stress.

Mathematical and Computational Modelling of Ribosomal Movement and Protein Synthesis: an overview

Translation or protein synthesis consists of a complex system of chemical reactions, which ultimately result in decoding of the mRNA and the production of a protein. The complexity of this reaction system makes it difficult to quantitatively connect its input parameters (such as translation factor or ribosome concentrations, codon composition of the mRNA, or energy availability) to output parameters (such as protein synthesis rates or ribosome densities on mRNAs). Mathematical and computational models of translation have now been used for nearly five decades to investigate translation, and to shed light on the relationship between the different reactions in the system. This review gives an overview over the principal approaches used in the modelling efforts, and summarises some of the major findings that were made.

Disrupted post-transcriptional regulation of the cystic fibrosis transmembrane conductance regulator (CFTR) by a 5'UTR mutation is associated with a CFTR-related disease

Cystic fibrosis (CF) is characterized as a single-gene disorder with a simple, autosomal recessive mode of inheritance. However, translation of cystic fibrosis transmembrane conductance regulator (CFTR) genotype into CF phenotype is influenced by nucleotide sequence variations at multiple genetic loci, and individuals heterozygous for CFTR mutations are predisposed to a range of CFTR-related conditions, such as disseminated bronchiectasis. CF disease severity and CFTR-related conditions are more akin to complex, multifactorial traits, which are increasingly being associated with mutations that perturb gene expression. We have identified a patient with disseminated bronchiectasis, who is heterozygous for a single-nucleotide substitution in the CFTR 5' untranslated region (UTR) (c.-34C>T). The c.-34C>T mutation creates an upstream AUG codon and upstream open reading frame that overlaps, and is out of frame with, the CFTR protein coding sequence. Using luciferase reporter constructs, we have shown that the c.-34C>T mutation decreases gene expression by 85-99%, by reducing translation efficiency and mRNA stability. This is the first CFTR regulatory mutation shown to act at a posttranscriptional level that reduces the synthesis of normal CFTR (Class V), and reaffirms the importance of regulatory mutations as a genetic basis of multifactorial phenotypes.

Imaging protein synthesis in cells and tissues with an alkyne analog of puromycin

Synthesis of many proteins is tightly controlled at the level of translation, and plays an essential role in fundamental processes such as cell growth and proliferation, signaling, differentiation, or death. Methods that allow imaging and identification of nascent proteins are critical for dissecting regulation of translation, both spatially and temporally, particularly in whole organisms. We introduce a simple and robust chemical method to image and affinity-purify nascent proteins in cells and in animals, based on an alkyne analog of puromycin, O-propargyl-puromycin (OP-puro). OP-puro forms covalent conjugates with nascent polypeptide chains, which are rapidly turned over by the proteasome and can be visualized or captured by copper(I)-catalyzed azide-alkyne cycloaddition. Unlike methionine analogs, OP-puro does not require methionine-free conditions and, uniquely, can be used to label and assay nascent proteins in whole organisms. This strategy should have broad applicability for imaging protein synthesis and for identifying proteins synthesized under various physiological and pathological conditions in vivo.

Protein expression regulation under oxidative stress

Oxidative stress is known to affect both translation and protein turnover, but very few large scale studies describe protein expression under stress. We measure protein concentrations in Saccharomyces cerevisiae over the course of 2 h in response to a mild oxidative stress induced by diamide, providing detailed time-resolved information for 815 proteins, with additional data for another ~1,100 proteins. For the majority of proteins, we discover major differences between the global transcript and protein response. Although mRNA levels often return to baseline 1 h after treatment, protein concentrations continue to change. Integrating our data with features of translation and protein degradation, we are able to predict expression patterns for 41% of the proteins in the core data set. Predictive features include, among others, targeting by RNA-binding proteins (Lhp1 and Khd1), RNA secondary structures, RNA half-life, and translation efficiency under unperturbed conditions and in response to oxidative reagents, but not chaperone binding. We are able to both describe general dynamics of protein concentration changes and suggest possible regulatory mechanisms for individual proteins.

Polyamine sensing by nascent ornithine decarboxylase antizyme stimulates decoding of its mRNA

Polyamines are essential organic polycations with multiple cellular functions relevant for cell division, cancer and ageing. Regulation of polyamine synthesis is mainly achieved by controlling the activity of ornithine decarboxylase (ODC) through an unusual mechanism involving ODC antizyme, the binding of which disrupts homodimeric ODC and targets it for ubiquitin-independent degradation by the 26S proteasome. Whereas mammals express several antizyme genes, we have identified a single orthologue, termed OAZ1, in Saccharomyces cerevisiae. Similar to its mammalian counterparts, OAZ1 synthesis is induced with rising intracellular polyamine concentrations, which also inhibit ubiquitin-dependent degradation of the OAZ1 protein. Together, these mechanisms contribute to a homeostatic feedback regulation of polyamines. Antizyme synthesis involves a conserved +1 ribosomal frameshifting (RFS) event at an internal STOP codon during decoding of its messenger RNA. Here we used S. cerevisiae OAZ1 to dissect the enigmatic mechanism underlying polyamine regulation of RFS. In contrast with previous assumptions, we report here that the nascent antizyme polypeptide is the relevant polyamine sensor that operates in cis to negatively regulate upstream RFS on the polysomes, where its own mRNA is being translated. At low polyamine levels, the emerging antizyme polypeptide inhibits completion of its synthesis causing a ribosome pile-up on antizyme mRNA, whereas polyamine binding to nascent antizyme promotes completion of its synthesis. Thus, our study reveals a novel autoregulatory mechanism, in which binding of a small metabolite to a nascent sensor protein stimulates the latter's synthesis co-translationally.

Analysing GCN4 translational control in yeast by stochastic chemical kinetics modelling and simulation

Background

The yeast Saccharomyces cerevisiae responds to amino acid starvation by inducing the transcription factor Gcn4. This is mainly mediated via a translational control mechanism dependent upon the translation initiation eIF2·GTP·Met-tRNA_i^Met ternary complex, and the four short upstream open reading frames (uORFs) in its 5' mRNA leader. These uORFs act to attenuate GCN4 mRNA translation under normal conditions. During amino acid starvation, levels of ternary complex are reduced. This overcomes the GCN4 translation attenuation effect via a scanning/reinitiation control mechanism dependent upon uORF spacing.

Results

Using published experimental data, we have developed and validated a probabilistic formulation of GCN4 translation using the Chemical Master Equation (Model 1). Model 1 explains GCN4 translation's nonlinear dependency upon uORF placements, and predicts that an as yet unidentified factor, which was proposed to regulate GCN4 translation under some conditions, only has pronounced effects upon GCN4 translation when intercistronic distances are unnaturally short. A simpler Model 2 that does not include this unidentified factor could well represent the regulation of a natural GCN4 mRNA. Using parameter values optimised for this algebraic Model 2, we performed stochastic simulations by Gillespie algorithm to investigate the distribution of ribosomes in different sections of GCN4 mRNA under distinct conditions. Our simulations demonstrated that ribosomal loading in the 5'-untranslated region is mainly determined by the ratio between the rates of 5'-initiation and ribosome scanning, but was not significantly affected by rate of ternary complex binding. Importantly, the translation rate for codons starved of cognate tRNAs is predicted to be the most significant contributor to the changes in ribosomal loading in the coding region under repressing and derepressing conditions.

Conclusions

Our integrated probabilistic Models 1 and 2 explained GCN4 translation and helped to elucidate the role of a yet unidentified factor. The ensuing stochastic simulations evaluated different factors that may impact on the translation of GCN4 mRNA, and integrated translation status with ribosomal density.

Explaining complex codon usage patterns with selection for translational efficiency, mutation bias, and genetic drift

The genetic code is redundant with most amino acids using multiple codons. In many organisms, codon usage is biased toward particular codons. Understanding the adaptive and nonadaptive forces driving the evolution of codon usage bias (CUB) has been an area of intense focus and debate in the fields of molecular and evolutionary biology. However, their relative importance in shaping genomic patterns of CUB remains unsolved. Using a nested model of protein translation and population genetics, we show that observed gene level variation of CUB in Saccharomyces cerevisiae can be explained almost entirely by selection for efficient ribosomal usage, genetic drift, and biased mutation. The correlation between observed codon counts within individual genes and our model predictions is 0.96. Although a variety of factors shape patterns of CUB at the level of individual sites within genes, our results suggest that selection for efficient ribosome usage is a central force in shaping codon usage at the genomic scale. In addition, our model allows direct estimation of codon-specific mutation rates and elongation times and can be readily applied to any organism with high-throughput expression datasets. More generally, we have developed a natural framework for integrating models of molecular processes to population genetics models to quantitatively estimate parameters underlying fundamental biological processes, such a protein translation.

Global quantification of mammalian gene expression control

Gene expression is a multistep process that involves the transcription, translation and turnover of messenger RNAs and proteins. Although it is one of the most fundamental processes of life, the entire cascade has never been quantified on a genome-wide scale. Here we simultaneously measured absolute mRNA and protein abundance and turnover by parallel metabolic pulse labelling for more than 5,000 genes in mammalian cells. Whereas mRNA and protein levels correlated better than previously thought, corresponding half-lives showed no correlation. Using a quantitative model we have obtained the first genome-scale prediction of synthesis rates of mRNAs and proteins. We find that the cellular abundance of proteins is predominantly controlled at the level of translation. Genes with similar combinations of mRNA and protein stability shared functional properties, indicating that half-lives evolved under energetic and dynamic constraints. Quantitative information about all stages of gene expression provides a rich resource and helps to provide a greater understanding of the underlying design principles.

Selective constraints in yeast genes with differential expressivity: codon pair usage and mRNA stability perspectives

Protein translation has been elucidated to be dictated by evolutionary constraints, namely, variations in tRNA availabilities and/or variations in codon-anticodon binding that is manifested in biased codon usage. Taking advantage of publicly available mRNA expression and protein abundance data for Saccharomyces cerevisiae, we have performed a comprehensive analysis of the diverse factors guiding translation leading to desired protein levels irrespective of the corresponding high or low mRNA levels. It has been elucidated in this study that different combinations of most abundant/non abundant tRNA isoacceptors are selected for in S. cerevisiae that helps in achieving the optimum speed and accuracy in the protein translation process. This is also accompanied by the strategic location of codon pairs in coherence to mRNA secondary structure folding stability for the above mentioned combinations of tRNA isoacceptors. We thus find that codon pair contextual effects; in addition to tRNA abundance and mRNA folding stability during translation elongation process play plausible roles in maintaining translation accuracy and speed that can achieve desired protein levels.

The dynamic state of protein turnover: It's about time

The continual destruction and renewal of proteins that maintain cellular homeostasis has been rigorously studied since the late 1930s. Experimental techniques for measuring protein turnover have evolved to measure the dynamic regulation of key proteins and now, entire proteomes. In the past decade, the proteomics field has aimed to discover how cells adjust their proteomes to execute numerous regulatory programs in response to specific cellular and environmental cues. By combining classical biochemical techniques with modern, high-throughput technologies, researchers have begun to reveal the synthesis and degradation mechanisms that shape protein turnover on a global scale. This review examines several recent developments in protein turnover research, emphasizing the combination of metabolic labeling and mass spectrometry.

Sequence signatures and mRNA concentration can explain two-thirds of protein abundance variation in a human cell line

We provide a large-scale dataset on absolute protein and matching mRNA concentrations from the human medulloblastoma cell line Daoy. The correlation between mRNA and protein concentrations is significant and positive (R_s=0.46, R²=0.29, P-value<2e16), although non-linear.

Out of ∼200 tested sequence features, sequence length, frequency and properties of amino acids, as well as translation initiation-related features are the strongest individual correlates of protein abundance when accounting for variation in mRNA concentration.

When integrating mRNA expression data and all sequence features into a non-parametric regression model (Multivariate Adaptive Regression Splines), we were able to explain up to 67% of the variation in protein concentrations. Half of the contributions were attributed to mRNA concentrations, the other half to sequence features relating to regulation of translation and protein degradation. The sequence features are primarily linked to the coding and 3′ untranslated region. To our knowledge, this is the most comprehensive predictive model of human protein concentrations achieved so far.

mRNA decay, translation regulation and protein degradation are essential parts of eukaryotic gene expression regulation (Hieronymus and Silver, 2004; Mata et al, 2005), which enable the dynamics of cellular systems and their responses to external and internal stimuli without having to rely exclusively on transcription regulation. The importance of these processes is emphasized by the generally low correlation between mRNA and protein concentrations. For many prokaryotic and eukaryotic organisms, <50% of variation in protein abundance variation is explained by variation in mRNA concentrations (de Sousa Abreu et al, 2009).

Given the plethora of regulatory mechanisms involved, most studies have focused so far on individual regulators and specific targets. Particularly in human, we currently lack system-wide, quantitative analyses that evaluate the relative contribution of regulatory elements encoded in the mRNA and protein sequence. Existing studies have been carried out only in bacteria and yeast (Nie et al, 2006; Brockmann et al, 2007; Tuller et al, 2007; Wu et al, 2008). Here, we present the first comprehensive analysis on the impact of translation and protein degradation on protein abundance variation in a human cell line. For this purpose, we experimentally measured absolute protein and mRNA concentrations in the Daoy medulloblastoma cell line, using shotgun proteomics and microarrays, respectively (Figure 1). These data comprise one of the largest such sets available today for human. We focused on sequence features that likely impact protein translation and protein degradation, including length, nucleotide composition, structure of the untranslated regions (UTRs), coding sequence, composition of the translation initiation site, presence of upstream open reading frames putative target sites of miRNAs, codon usage, amino-acid composition and protein degradation signals.

Three types of tests have been conducted: (a) we examined partial Spearman's rank correlation of numerical features (e.g. length) with protein concentration, accounting for variation in mRNA concentrations; (b) for numerical and categorical features (e.g. function), we compared two extreme populations with Welch's t-test and (c) using a Multivariate Adaptive Regression Splines model, we analyzed the combined contributions of mRNA expression and sequence features to protein abundance variation (Figure 1). To account for the non-linearity of many relationships, we use non-parametric approaches throughout the analysis.

We observed a significant positive correlation between mRNA and protein concentrations, larger than many previous measurements (de Sousa Abreu et al, 2009). We also show that the contribution of translation and protein degradation is at least as important as the contribution of mRNA transcription and stability to the abundance variation of the final protein products. Although variation in mRNA expression explains ∼25–30% of the variation in protein abundance, another 30–40% can be accounted for by characteristics of the sequences, which we identified in a comparative assessment of global correlates. Among these characteristics, sequence length, amino-acid frequencies and also nucleotide frequencies in the coding region are of strong influence (Figure 3A). Characteristics of the 3′UTR and of the 5′UTR, that is length, nucleotide composition and secondary structures, describe another part of the variation, leaving 33% expression variation unexplained. The unexplained fraction may be accounted for by mechanisms not considered in this analysis (e.g. regulation by RNA-binding proteins or gene-specific structural motifs), as well as expression and measurement noise.

Our combined model including mRNA concentration and sequence features can explain 67% of the variation of protein abundance in this system—and thus has the highest predictive power for human protein abundance achieved so far (Figure 3B).

Transcription, mRNA decay, translation and protein degradation are essential processes during eukaryotic gene expression, but their relative global contributions to steady-state protein concentrations in multi-cellular eukaryotes are largely unknown. Using measurements of absolute protein and mRNA abundances in cellular lysate from the human Daoy medulloblastoma cell line, we quantitatively evaluate the impact of mRNA concentration and sequence features implicated in translation and protein degradation on protein expression. Sequence features related to translation and protein degradation have an impact similar to that of mRNA abundance, and their combined contribution explains two-thirds of protein abundance variation. mRNA sequence lengths, amino-acid properties, upstream open reading frames and secondary structures in the 5′ untranslated region (UTR) were the strongest individual correlates of protein concentrations. In a combined model, characteristics of the coding region and the 3′UTR explained a larger proportion of protein abundance variation than characteristics of the 5′UTR. The absolute protein and mRNA concentration measurements for >1000 human genes described here represent one of the largest datasets currently available, and reveal both general trends and specific examples of post-transcriptional regulation.

Method to isolate polyribosomal mRNA from scarce samples such as mammalian oocytes and early embryos

Background

Although the transcriptome of minute quantities of cells can be profiled using nucleic acid amplification techniques, it remains difficult to distinguish between active and stored messenger RNA. Transcript storage occurs at specific stages of gametogenesis and is particularly important in oogenesis as stored maternal mRNA is used to sustain de novo protein synthesis during the early developmental stages until the embryonic genome gets activated. In many cases, stored mRNA can be several times more abundant than mRNA ready for translation. In order to identify active mRNA in bovine oocytes, we sought to develop a method of isolating very small amounts of polyribosome mRNA.

Results

The proposed method is based on mixing the extracted oocyte cytoplasm with a preparation of polyribosomes obtained from a non-homologous source (Drosophila) and using sucrose density gradient ultracentrifugation to separate the polyribosomes. It involves cross-linking the non-homologous polyribosomes and neutralizing the cross-linking agent. Using this method, we show that certain stages of oocyte maturation coincide with changes in the abundance of polyribosomal mRNA but not total RNA or poly(A). We also show that the abundance of selected sequences matched changes in the corresponding protein levels.

Conclusions

We report here the successful use of a method to profile mRNA present in the polyribosomal fraction obtained from as little as 75 mammalian oocytes. Polyribosomal mRNA fractionation thus provides a new tool for studying gametogenesis and early development with better representation of the underlying physiological status.

A quantitative model for mRNA translation in Saccharomyces cerevisiae

Messenger RNA (mRNA) translation is an essential step in eukaryotic gene expression that contributes to the regulation of this process. We describe a deterministic model based on ordinary differential equations that describe mRNA translation in Saccharomyces cerevisiae. This model, which was parameterized using published data, was developed to examine the kinetic behaviour of translation initiation factors in response to amino acid availability. The model predicts that the abundance of the eIF1-eIF3-eIF5 complex increases under amino acid starvation conditions, suggesting a possible auxiliary role for these factors in modulating translation initiation in addition to the known mechanisms involving eIF2. Our analyses of the robustness of the mRNA translation model suggest that individual cells within a randomly generated population are sensitive to external perturbations (such as changes in amino acid availability) through Gcn2 signalling. However, the model predicts that individual cells exhibit robustness against internal perturbations (such as changes in the abundance of translation initiation factors and kinetic parameters). Gcn2 appears to enhance this robustness within the system. These findings suggest a trade-off between the robustness and performance of this biological network. The model also predicts that individual cells exhibit considerable heterogeneity with respect to their absolute translation rates, due to random internal perturbations. Therefore, averaging the kinetic behaviour of cell populations probably obscures the dynamic robustness of individual cells. This highlights the importance of single-cell measurements for evaluating network properties.

A quantitative comparison of cell-type-specific microarray gene expression profiling methods in the mouse brain

Expression profiling of restricted neural populations using microarrays can facilitate neuronal classification and provide insight into the molecular bases of cellular phenotypes. Due to the formidable heterogeneity of intermixed cell types that make up the brain, isolating cell types prior to microarray processing poses steep technical challenges that have been met in various ways. These methodological differences have the potential to distort cell-type-specific gene expression profiles insofar as they may insufficiently filter out contaminating mRNAs or induce aberrant cellular responses not normally present in vivo. Thus we have compared the repeatability, susceptibility to contamination from off-target cell-types, and evidence for stress-responsive gene expression of five different purification methods - Laser Capture Microdissection (LCM), Translating Ribosome Affinity Purification (TRAP), Immunopanning (PAN), Fluorescence Activated Cell Sorting (FACS), and manual sorting of fluorescently labeled cells (Manual). We found that all methods obtained comparably high levels of repeatability, however, data from LCM and TRAP showed significantly higher levels of contamination than the other methods. While PAN samples showed higher activation of apoptosis-related, stress-related and immediate early genes, samples from FACS and Manual studies, which also require dissociated cells, did not. Given that TRAP targets actively translated mRNAs, whereas other methods target all transcribed mRNAs, observed differences may also reflect translational regulation.

An upstream ORF with non-AUG start codon is translated in vivo but dispensable for translational control of GCN4 mRNA

Genome-wide analysis of ribosome locations in mRNAs of Saccharomyces cerevisiae has revealed the translation of upstream open reading frames that initiate with near-cognate start codons in many transcripts. Two such non-translation initiation codon (AUG)-initiated upstream open reading frames (uORFs) (nAuORFs 1 and 2) occur in GCN4 mRNA upstream of the four AUG-initiated uORFs (uORFs 1–4) that regulate GCN4 translation. We verified that nAuORF2 is translated in vivo by demonstrating β-galactosidase production from lacZ coding sequences fused to nAuORF2, in a manner abolished by replacing its non-AUG initiation codon (AUA) start codon with the non-cognate triplet AAA, whereas translation of nAuORF1 was not detected. Importantly, replacing the near-cognate start codons of both nAuORFs with non-cognate triplets had little or no effect on the repression of GCN4 translation in non-starved cells, nor on its derepression in response to histidine limitation, nutritional shift-down or treatment with rapamycin, hydrogen peroxide or methyl methanesulfonate. Additionally, we found no evidence that initiation from the AUA codon of nAuORF2 is substantially elevated, or dependent on Gcn2, the sole eIF2α kinase of yeast, in histidine-deprived cells. Thus, although nAuORF2 is translated in vivo, it appears that this event is not stimulated by eIF2α phosphorylation nor significantly influences GCN4 translational induction under various starvation or stress conditions.

Synonymous but not the same: the causes and consequences of codon bias

Despite their name, synonymous mutations have significant consequences for cellular processes in all taxa. As a result, an understanding of codon bias is central to fields as diverse as molecular evolution and biotechnology. Although recent advances in sequencing and synthetic biology have helped to resolve longstanding questions about codon bias, they have also uncovered striking patterns that suggest new hypotheses about protein synthesis. Ongoing work to quantify the dynamics of initiation and elongation is as important for understanding natural synonymous variation as it is for designing transgenes in applied contexts.

Quantitative analysis of mRNA translation in mammalian spermatogenic cells with sucrose and Nycodenz gradients

BACKGROUND

Developmental and global regulation of mRNA translation plays a major role in regulating gene expression in mammalian spermatogenic cells. Sucrose gradients are widely used to analyze mRNA translation. Unfortunately, the information from sucrose gradient experiments is often compromised by the absence of quantification and absorbance tracings, and confusion about the basic properties of sucrose gradients.

METHODS

The Additional Materials contain detailed protocols for the preparation and analysis of sucrose and Nycodenz gradients, obtaining absorbance tracings of sucrose gradients, aligning tracings and fractions, and extraction of equal proportions of RNA from all fractions.

RESULTS

The techniques described here have produced consistent measurements despite changes in personnel and minor variations in RNA extraction, gradient analysis, and mRNA quantification, and describes for the first time potential problems in using gradients to analyze mRNA translation in purified spermatogenic cells.

CONCLUSIONS

Accurate quantification of the proportion of polysomal mRNA is useful in comparing translational activity at different developmental stages, different mRNAs, different techniques and different laboratories. The techniques described here are sufficiently accurate to elucidate the contributions of multiple regulatory elements of variable strength in regulating translation of the sperm mitochondria associated cysteine-rich protein (Smcp) mRNA in transgenic mice.

Identification of differential translation in genome wide studies

Regulation of gene expression through translational control is a fundamental mechanism implicated in many biological processes ranging from memory formation to innate immunity and whose dysregulation contributes to human diseases. Genome wide analyses of translational control strive to identify differential translation independent of cytosolic mRNA levels. For this reason, most studies measure genes' translation levels as log ratios (translation levels divided by corresponding cytosolic mRNA levels obtained in parallel). Counterintuitively, arising from a mathematical necessity, these log ratios tend to be highly correlated with the cytosolic mRNA levels. Accordingly, they do not effectively correct for cytosolic mRNA level and generate substantial numbers of biological false positives and false negatives. We show that analysis of partial variance, which produces estimates of translational activity that are independent of cytosolic mRNA levels, is a superior alternative. When combined with a variance shrinkage method for estimating error variance, analysis of partial variance has the additional benefit of having greater statistical power and identifying fewer genes as translationally regulated resulting merely from unrealistically low variance estimates rather than from large changes in translational activity. In contrast to log ratios, this formal analytical approach estimates translation effects in a statistically rigorous manner, eliminates the need for inefficient and error-prone heuristics, and produces results that agree with biological function. The method is applicable to datasets obtained from both the commonly used polysome microarray method and the sequencing-based ribosome profiling method.

Missense suppressor mutations in 16S rRNA reveal the importance of helices h8 and h14 in aminoacyl-tRNA selection

The molecular basis of the induced-fit mechanism that determines the fidelity of protein synthesis remains unclear. Here, we isolated mutations in 16S rRNA that increase the rate of miscoding and stop codon read-through. Many of the mutations clustered along interfaces between the 30S shoulder domain and other parts of the ribosome, strongly implicating shoulder movement in the induced-fit mechanism of decoding. The largest subset of mutations mapped to helices h8 and h14. These helices interact with each other and with the 50S subunit to form bridge B8. Previous cryo-EM studies revealed a contact between h14 and the switch 1 motif of EF-Tu, raising the possibility that h14 plays a direct role in GTPase activation. To investigate this possibility, we constructed both deletions and insertions in h14. While ribosomes harboring a 2-base-pair (bp) insertion in h14 were completely inactive in vivo, those containing a 2-bp deletion retained activity but were error prone. In vitro, the truncation of h14 accelerated GTP hydrolysis for EF-Tu bearing near-cognate aminoacyl-tRNA, an effect that can largely account for the observed miscoding in vivo. These data show that h14 does not help activate EF-Tu but instead negatively controls GTP hydrolysis by the factor. We propose that bridge B8 normally acts to counter inward rotation of the shoulder domain; hence, mutations in h8 and h14 that compromise this bridge decrease the stringency of aminoacyl-tRNA selection.

Effect of correlated tRNA abundances on translation errors and evolution of codon usage bias

Despite the fact that tRNA abundances are thought to play a major role in determining translation error rates, their distribution across the genetic code and the resulting implications have received little attention. In general, studies of codon usage bias (CUB) assume that codons with higher tRNA abundance have lower missense error rates. Using a model of protein translation based on tRNA competition and intra-ribosomal kinetics, we show that this assumption can be violated when tRNA abundances are positively correlated across the genetic code. Examining the distribution of tRNA abundances across 73 bacterial genomes from 20 different genera, we find a consistent positive correlation between tRNA abundances across the genetic code. This work challenges one of the fundamental assumptions made in over 30 years of research on CUB that codons with higher tRNA abundances have lower missense error rates and that missense errors are the primary selective force responsible for CUB.

Codon usage bias (CUB) is a ubiquitous and important phenomenon. CUB is thought to be driven primarily due to selection against missense errors. For over 30 years, the standard model of translation errors has implicitly assumed that the relationship between translation errors and tRNA abundances are inversely related. This is based on an implicit and unstated assumption that the distribution of tRNA abundances across the genetic code are uncorrelated. Examining these abundance distributions across 73 bacterial genomes from 20 different genera, we find a consistent positive correlation between tRNA abundances across the genetic code. We further show that codons with higher tRNA abundances are not always “optimal” with respect to reducing the missense error rate and hence cannot explain the observed patterns of CUB.

A comprehensive, quantitative, and genome-wide model of translation

Translation is still poorly characterised at the level of individual proteins and its role in regulation of gene expression has been constantly underestimated. To better understand the process of protein synthesis we developed a comprehensive and quantitative model of translation, characterising protein synthesis separately for individual genes. The main advantage of the model is that basing it on only a few datasets and general assumptions allows the calculation of many important translational parameters, which are extremely difficult to measure experimentally. In the model, each gene is attributed with a set of translational parameters, namely the absolute number of transcripts, ribosome density, mean codon translation time, total transcript translation time, total time required for translation initiation and elongation, translation initiation rate, mean mRNA lifetime, and absolute number of proteins produced by gene transcripts. Most parameters were calculated based on only one experimental dataset of genome-wide ribosome profiling. The model was implemented in Saccharomyces cerevisiae, and its results were compared with available data, yielding reasonably good correlations. The calculated coefficients were used to perform a global analysis of translation in yeast, revealing some interesting aspects of the process. We have shown that two commonly used measures of translation efficiency – ribosome density and number of protein molecules produced – are affected by two distinct factors. High values of both measures are caused, i.a., by very short times of translation initiation, however, the origins of initiation time reduction are completely different in both cases. The model is universal and can be applied to any organism, if the necessary input data are available. The model allows us to better integrate transcriptomic and proteomic data. A few other possibilities of the model utilisation are discussed concerning the example of the yeast system.

Translation is the production of proteins by decoding mRNA produced in transcription, and is a part of the overall process of gene expression. Although the general theoretical background of translation is known, the process is still poorly characterised at the level of individual proteins. In particular, the quantitative parameters of translation, such as time required to complete it or the number of protein molecules produced from a transcript during its lifetime, are extremely difficult to measure experimentally. To overcome this problem, we developed a computational model that, on the basis of only few datasets and general assumptions, measures quantitatively the translational activity at the level of individual genes. We discussed it concerning the example of the yeast system; however, it can be applied to any organism of known genome. We used the obtained results to study the general characteristics of the yeast translational system, revealing the diversity of strategies of gene expression regulation. We exemplified and discussed other possible ways of model utilisation, as it may help in examining protein-protein interactions, metabolic pathways, gene annotation, ribosome queueing, protein folding, and translation initiation. It also may be crucial for better integration of cell-wide, high-throughput experiments.

Time-dependent increase in ribosome processivity

We created a novel tripartite reporter RNA to separately and simultaneously examine ribosome translation rates at the 5′- and 3′-ends of a large open reading frame (ORF) in vitro in HeLa cell lysates. The construct contained Renilla luciferase (RLuc), β-galactosidase and firefly luciferase (FLuc) ORFs linked in frame and separated by a viral peptide sequence that causes cotranslational scission of emerging peptide chains. The length of the ORF contributed to low ribosome processivity, a low number of initiating ribosomes completing translation of the entire ORF. We observed a time-dependent increase in FLuc production rate that was dependent on a poly(A) tail and poly(A)-binding protein, but was independent of eIF4F function. Stimulation of FLuc production occurred earlier on shorter RNA templates. Cleavage of eIF4G at times after ribosome loading on templates occurred did not cause immediate cessation of 5′-RLuc translation; rather, a delay was observed that shortened when shorter templates were translated. Electron microscopic analysis of polysome structures in translation lysates revealed a time-dependent increase in ribosome packing and contact that correlated with increased processivity on the FLuc ORF. The results suggest that ORF transit combined with PABP function contribute to interactions between ribosomes that increase or sustain processivity on long ORFs.

Estrogen coordinates translation and transcription, revealing a role for NRSF in human breast cancer cells

Posttranscriptional regulation may enhance or inhibit estrogen transcriptional control to promote proliferation of breast cancer cells. To understand how transcriptome and translational responses coordinate to drive proliferation, we determined estrogen's global and specific effects on translation regulation by comparing the genome-wide profiles of total mRNA, polysome-associated mRNA, and monosome-associated mRNAs in MCF-7 cells after stimulation by 1 h of 10 nm 17beta-estradiol (E2). We observe three significant, novel findings. 1) E2 regulates several transcripts and pathways at the translation level. 2) We find that polysome analysis has higher sensitivity than total RNA in detecting E2-regulated transcripts as exemplified by observing stronger E2-induced enrichment of E2 expression signatures in polysomes more than in total RNA. This increased sensitivity allowed the identification of the repression of neural restrictive silencing factor targets in polysome-associated RNA but not total RNA. NRSF activity was required for E2 stimulation of the cell cycle. 3) We observe that the initial translation state is already high for E2 up-regulated transcripts before E2 treatment and vice versa for E2 down-regulated transcripts. This suggests that the translation state anticipates potential E2-induced transcriptome levels. Together, these data suggest that E2 stimulates breast cancer cells by regulating translation using multiple mechanisms. In sum, we show that polysome profiling of E2 regulation of breast cancer cells provides novel insights into hormone action and can identify novel factors critical for breast cancer cell growth.

The origins of time-delay in template biopolymerization processes

Time-delays are common in many physical and biological systems and they give rise to complex dynamic phenomena. The elementary processes involved in template biopolymerization, such as mRNA and protein synthesis, introduce significant time delays. However, there is not currently a systematic mapping between the individual mechanistic parameters and the time delays in these networks. We present here the development of mathematical, time-delay models for protein translation, based on PDE models, which in turn are derived through systematic approximations of first-principles mechanistic models. Theoretical analysis suggests that the key features that determine the time-delays and the agreement between the time-delay and the mechanistic models are ribosome density and distribution, i.e., the number of ribosomes on the mRNA chain relative to their maximum and their distribution along the mRNA chain. Based on analytical considerations and on computational studies, we show that the steady-state and dynamic responses of the time-delay models are in excellent agreement with the detailed mechanistic models, under physiological conditions that correspond to uniform ribosome distribution and for ribosome density up to 70%. The methodology presented here can be used for the development of reduced time-delay models of mRNA synthesis and large genetic networks. The good agreement between the time-delay and the mechanistic models will allow us to use the reduced model and advanced computational methods from nonlinear dynamics in order to perform studies that are not practical using the large-scale mechanistic models.

Functional overlap between eIF4G isoforms in Saccharomyces cerevisiae

Initiation factor eIF4G is a key regulator of eukaryotic protein synthesis, recognizing proteins bound at both ends of an mRNA to help recruit messages to the small (40S) ribosomal subunit. Notably, the genomes of a wide variety of eukaryotes encode multiple distinct variants of eIF4G. We found that deletion of eIF4G1, but not eIF4G2, impairs growth and global translation initiation rates in budding yeast under standard laboratory conditions. Not all mRNAs are equally sensitive to loss of eIF4G1; genes that encode messages with longer poly(A) tails are preferentially affected. However, eIF4G1-deletion strains contain significantly lower levels of total eIF4G, relative to eIF4G2-delete or wild type strains. Homogenic strains, which encode two copies of either eIF4G1 or eIF4G2 under native promoter control, express a single isoform at levels similar to the total amount of eIF4G in a wild type cell and have a similar capacity to support normal translation initiation rates. Polysome microarray analysis of these strains and the wild type parent showed that translationally active mRNAs are similar. These results suggest that total eIF4G levels, but not isoform-specific functions, determine mRNA-specific translational efficiency.

Transcriptome and proteome exploration to model translation efficiency and protein stability in Lactococcus lactis

This genome-scale study analysed the various parameters influencing protein levels in cells. To achieve this goal, the model bacterium Lactococcus lactis was grown at steady state in continuous cultures at different growth rates, and proteomic and transcriptomic data were thoroughly compared. Ratios of mRNA to protein were highly variable among proteins but also, for a given gene, between the different growth conditions. The modeling of cellular processes combined with a data fitting modeling approach allowed both translation efficiencies and degradation rates to be estimated for each protein in each growth condition. Estimated translational efficiencies and degradation rates strongly differed between proteins and were tested for their biological significance through statistical correlations with relevant parameters such as codon or amino acid bias. These efficiencies and degradation rates were not constant in all growth conditions and were inversely proportional to the growth rate, indicating a more efficient translation at low growth rate but an antagonistic higher rate of protein degradation. Estimated protein median half-lives ranged from 23 to 224 min, underlying the importance of protein degradation notably at low growth rates. The regulation of intracellular protein level was analysed through regulatory coefficient calculations, revealing a complex control depending on protein and growth conditions. The modeling approach enabled translational efficiencies and protein degradation rates to be estimated, two biological parameters extremely difficult to determine experimentally and generally lacking in bacteria. This method is generic and can now be extended to other environments and/or other micro-organisms.

This work is in the field of systems biology. Via an in-depth comparison of proteomic and transcriptomic data in various culture conditions, our objective was to better understand the regulation of protein levels. We have demonstrated that bacteria exert a tight control on intracellular protein levels, through a multi-level regulation involving translation but also dilution due to growth and protein degradation. We have estimated translational efficiencies and protein degradation rates by modeling. These two biological parameters are extremely difficult to measure experimentally and have not been previously determined in bacteria. We have found that they are growth rate dependent, indicating a fine control of translation and degradation processes. We have worked with the small genome bacterium Lactococcus lactis on a limited number of mRNA-protein couples but keeping in mind that this approach could be extended to other micro-organisms and biological phenomena. We have exhibited that mathematical modeling associated to experimental steady-states cultures is a powerful tool to understand microbial physiology.

Measuring and detecting molecular adaptation in codon usage against nonsense errors during protein translation

Codon usage bias (CUB) has been documented across a wide range of taxa and is the subject of numerous studies. While most explanations of CUB invoke some type of natural selection, most measures of CUB adaptation are heuristically defined. In contrast, we present a novel and mechanistic method for defining and contextualizing CUB adaptation to reduce the cost of nonsense errors during protein translation. Using a model of protein translation, we develop a general approach for measuring the protein production cost in the face of nonsense errors of a given allele as well as the mean and variance of these costs across its coding synonyms. We then use these results to define the nonsense error adaptation index (NAI) of the allele or a contiguous subset thereof. Conceptually, the NAI value of an allele is a relative measure of its elevation on a specific and well-defined adaptive landscape. To illustrate its utility, we calculate NAI values for the entire coding sequence and across a set of nonoverlapping windows for each gene in the Saccharomyces cerevisiae S288c genome. Our results provide clear evidence of adaptation to reduce the cost of nonsense errors and increasing adaptation with codon position and expression. The magnitude and nature of this adaptation are also largely consistent with simulation results in which nonsense errors are the only selective force driving CUB evolution. Because NAI is derived from mechanistic models, it is both easier to interpret and more amenable to future refinement than other commonly used measures of codon bias. Further, our approach can also be used as a starting point for developing other mechanistically derived measures of adaptation such as for translational accuracy.

Concordant regulation of translation and mRNA abundance for hundreds of targets of a human microRNA

A specific microRNA reduces the synthesis of hundreds of proteins via concordant effects on the abundance and translation of the mRNAs that encode them.

MicroRNAs (miRNAs) regulate gene expression posttranscriptionally by interfering with a target mRNA's translation, stability, or both. We sought to dissect the respective contributions of translational inhibition and mRNA decay to microRNA regulation. We identified direct targets of a specific miRNA, miR-124, by virtue of their association with Argonaute proteins, core components of miRNA effector complexes, in response to miR-124 transfection in human tissue culture cells. In parallel, we assessed mRNA levels and obtained translation profiles using a novel global approach to analyze polysomes separated on sucrose gradients. Analysis of translation profiles for ∼8,000 genes in these proliferative human cells revealed that basic features of translation are similar to those previously observed in rapidly growing Saccharomyces cerevisiae. For ∼600 mRNAs specifically recruited to Argonaute proteins by miR-124, we found reductions in both the mRNA abundance and inferred translation rate spanning a large dynamic range. The changes in mRNA levels of these miR-124 targets were larger than the changes in translation, with average decreases of 35% and 12%, respectively. Further, there was no identifiable subgroup of mRNA targets for which the translational response was dominant. Both ribosome occupancy (the fraction of a given gene's transcripts associated with ribosomes) and ribosome density (the average number of ribosomes bound per unit length of coding sequence) were selectively reduced for hundreds of miR-124 targets by the presence of miR-124. Changes in protein abundance inferred from the observed changes in mRNA abundance and translation profiles closely matched changes directly determined by Western analysis for 11 of 12 proteins, suggesting that our assays captured most of miR-124–mediated regulation. These results suggest that miRNAs inhibit translation initiation or stimulate ribosome drop-off preferentially near the start site and are not consistent with inhibition of polypeptide elongation, or nascent polypeptide degradation contributing significantly to miRNA-mediated regulation in proliferating HEK293T cells. The observation of concordant changes in mRNA abundance and translational rate for hundreds of miR-124 targets is consistent with a functional link between these two regulatory outcomes of miRNA targeting, and the well-documented interrelationship between translation and mRNA decay.

The human genome contains directions to regulate the timing and magnitude of expression of its thousands of genes. MicroRNAs are important regulatory RNAs that tune the expression levels of tens to hundreds of specific genes by pairing to complimentary stretches in the messenger RNAs from these genes, thereby reducing their stability and their translation into protein. Although the importance of microRNAs is appreciated, little is known about the relative contributions of degradation or repression of translation of the cognate mRNAs to the overall effects on protein synthesis, or the links between these two regulatory mechanisms. We devised a simple, economical method to systematically measure mRNA translation profiles, then applied this method, in combination with gene expression analysis, to measure the effects of the human microRNA miR-124 on the abundance and apparent translation rate of its mRNA targets. We found that for the ∼600 mRNA targets of miR-124 that were identified by their association with microRNA effector complexes, around three quarters of the reduction in estimated protein synthesis was explained by changes in mRNA abundance. Although the apparent changes in translation efficiencies of the targeted mRNAs were smaller in magnitude, they were highly correlated with changes in the abundance of those RNAs, suggesting a functional link between microRNA-mediated repression of translation and mRNA decay.

Evolutionary roles of upstream open reading frames in mediating gene regulation in fungi

Upstream open reading frames (uORFs) are frequently present in the 5'-leader regions of fungal mRNAs. They can affect translation by controlling the ability of ribosomes that scan from the mRNA 5' end to reach the downstream genic reading frame. The translation of uORFs can also affect mRNA stability. For several genes, including Saccharomyces cerevisiae GCN4, S. cerevisiae CPA1, and Neurospora crassa arg-2, regulation by uORFs controls expression in response to specific physiological signals. The roles of many uORFs that are identified by genome-level approaches, as have been initiated for Saccharomyces, Aspergillus, and Cryptococcus species, remain to be determined. Some uORFs may have regulatory roles, while others may exist to insulate the genic reading frame from the negative impacts of upstream translation start sites in the mRNA 5' leader.

The evolutionary consequences of erroneous protein synthesis

Errors in protein synthesis disrupt cellular fitness, cause disease phenotypes and shape gene and genome evolution. Experimental and theoretical results on this topic have accumulated rapidly in disparate fields, such as neurobiology, protein biosynthesis and degradation and molecular evolution, but with limited communication among disciplines. Here, we review studies of error frequencies, the cellular and organismal consequences of errors and the attendant long-range evolutionary responses to errors. We emphasize major areas in which little is known, such as the failure rates of protein folding, in addition to areas in which technological innovations may enable imminent gains, such as the elucidation of translational missense error frequencies. Evolutionary responses to errors fall into two broad categories: adaptations that minimize errors and their attendant costs and adaptations that exploit errors for the organism's benefit.

Global signatures of protein and mRNA expression levels

Cellular states are determined by differential expression of the cell's proteins. The relationship between protein and mRNA expression levels informs about the combined outcomes of translation and protein degradation which are, in addition to transcription and mRNA stability, essential contributors to gene expression regulation. This review summarizes the state of knowledge about large-scale measurements of absolute protein and mRNA expression levels, and the degree of correlation between the two parameters. We summarize the information that can be derived from comparison of protein and mRNA expression levels and discuss how corresponding sequence characteristics suggest modes of regulation.

Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling

Techniques for systematically monitoring protein translation have lagged far behind methods for measuring messenger RNA (mRNA) levels. Here, we present a ribosome-profiling strategy that is based on the deep sequencing of ribosome-protected mRNA fragments and enables genome-wide investigation of translation with subcodon resolution. We used this technique to monitor translation in budding yeast under both rich and starvation conditions. These studies defined the protein sequences being translated and found extensive translational control in both determining absolute protein abundance and responding to environmental stress. We also observed distinct phases during translation that involve a large decrease in ribosome density going from early to late peptide elongation as well as widespread regulated initiation at non-adenine-uracil-guanine (AUG) codons. Ribosome profiling is readily adaptable to other organisms, making high-precision investigation of protein translation experimentally accessible.

Upstream sequence elements direct post-transcriptional regulation of gene expression under stress conditions in yeast

BACKGROUND

The control of gene expression in eukaryotic cells occurs both transcriptionally and post-transcriptionally. Although many genes are now known to be regulated at the translational level, in general, the mechanisms are poorly understood. We have previously presented polysomal gradient and array-based evidence that translational control is widespread in a significant number of genes when yeast cells are exposed to a range of stresses. Here we have re-examined these gene sets, considering the role of UTR sequences in the translational responses of these genes using recent large-scale datasets which define 5' and 3' transcriptional ends for many yeast genes. In particular, we highlight the potential role of 5' UTRs and upstream open reading frames (uORFs).

RESULTS

We show a highly significant enrichment in specific GO functional classes for genes that are translationally up- and down-regulated under given stresses (e.g. carbohydrate metabolism is up-regulated under amino acid starvation). Cross-referencing these data with the stress response data we show that translationally upregulated genes have longer 5' UTRs, consistent with their role in translational regulation. In the first genome-wide study of uORFs in a set of mapped 5' UTRs, we show that uORFs are rare, being statistically under-represented in UTR sequences. However, they have distinct compositional biases consistent with their putative role in translational control and are more common in genes which are apparently translationally up-regulated.

CONCLUSION

These results demonstrate a central regulatory role for UTR sequences, and 5' UTRs in particular, highlighting the significant role of uORFs in post-transcriptional control in yeast. Yeast uORFs are more highly conserved than has been suggested, lending further weight to their significance as functional elements involved in gene regulation. It also suggests a more complex and novel mechanism of control, whereby uORFs permit genes to escape from a more general attenuation of translation under conditions of stress. However, since uORFs are relatively rare (only ~13% of yeast genes have them) there remain many unanswered questions as to how UTR elements can direct translational control of many hundreds of genes under stress.

A quantitative estimation of the global translational activity in logarithmically growing yeast cells

Background

Translation of messenger mRNAs makes significant contributions to the control of gene expression in all eukaryotes. Because translational control often involves fractional changes in translational activity, good quantitative descriptions of translational activity will be required to achieve a comprehensive understanding of this aspect of biology. Data on translational activity are difficult to generate experimentally under physiological conditions, however, translational activity as a parameter is in principle accessible through published genome-wide datasets.

Results

An examination of the accuracy of genome-wide expression datasets generated for Saccharomyces cerevisiae shows that the available datasets suffer from large random errors within studies as well as systematic shifts in reported values between studies, which make predictions of translational activity at the level of individual genes relatively inaccurate. In contrast, predictions of cell-wide translational activity are possible from such datasets with higher accuracy, and current datasets predict a production rate of about 13,000 proteins per haploid cell per second under fast growth conditions. This prediction is shown to be consistent with independently derived kinetic information on nucleotide exchange reactions that occur during translation, and on the ribosomal content of yeast cells.

Conclusion

This study highlights some of the limitations in published genome-wide expression datasets, but also demonstrates a novel use for such datasets in examining global properties of cells. The global translational activity of yeast cells predicted in this study is a useful benchmark against which biochemical data on individual translation factor activities can be interpreted.

Site-specific release of nascent chains from ribosomes at a sense codon

"2A" oligopeptides are autonomous elements containing a D(V/I)EXNPGP motif at the C terminus. Protein synthesis from an open reading frame containing an internal 2A coding sequence yields two separate polypeptides, corresponding to sequences up to and including 2A and those downstream. We show that the 2A reaction occurs in the ribosomal peptidyltransferase center. Ribosomes pause at the end of the 2A coding sequence, over the glycine and proline codons, and the nascent chain up to and including this glycine is released. Translation-terminating release factors eRF1 and eRF3 play key roles in the reaction. On the depletion of eRF1, a greater proportion of ribosomes extend through the 2A coding sequence, yielding the full-length protein. In contrast, impaired eRF3 GTPase activity leads to many ribosomes failing to translate beyond 2A. Further, high-level expression of a 2A peptide-containing protein inhibits the growth of cells compromised for release factor activity and leads to errors in stop codon recognition. We propose that the nascent 2A peptide interacts with ribosomes to drive a highly unusual and specific "termination" reaction, despite the presence of a proline codon in the A site. After this, the majority of ribosomes continue translation, generating the separate downstream product.

The 3'-UTR mediates the cellular localization of an mRNA encoding a short plasma membrane protein

Cotranslational synthesis of proteins into the endoplasmic reticulum is preceded by targeting of the translating mRNA once a signal peptide emerges from the ribosome exit tunnel. Many mRNAs, however, are unlikely to be targeted by this process because they encode proteins that do not contain a signal peptide or because they are too short to be recognized by the signal recognition particle. Herein we tested the possible involvement of the 3'-UTR in the localization of an mRNA that encodes a very short Saccharomyces cerevisiae protein (Pmp1). We found by ribosome density mapping, sedimentation analysis, differential centrifugation, and fluorescent in situ hybridization that the 3'-UTR is essential for the association of the transcript with membrane compartments. Fusion of the 3'-UTR to heterologous open reading frames conferred on them a sedimentation and cellular localization pattern resembling that of PMP1. Mutation analysis revealed that a repeating UG-rich sequence within the 3'-UTR is important for membrane association. Taken together, our results reveal an essential role for elements within the 3'-UTR in the localization of an mRNA that is likely to be ignored by the standard signal-dependant mechanism.

A ribosomal density-mapping procedure to explore ribosome positions along translating mRNAs

The number and distribution of ribosomes on a transcript provide useful information in ascertaining the efficiency of translation. Herein we describe a direct method to determine the association of ribosomes with specific regions of an mRNA. The method, termed Ribosome Density Mapping (RDM), includes cleavage of ribosomes-associated mRNAs with RNase H and complementary oligodeoxynucleotide followed by separation of the cleavage products on a sucrose gradient. The gradient is then fractionated and the sedimentation position of each mRNA fragment is determined by northern analysis. Although developed for yeast mRNAs, RDM is likely to be applicable to various other systems.

Genome-wide analysis of growth phase-dependent translational and transcriptional regulation in halophilic archaea

BACKGROUND

Differential expression of genes can be regulated on many different levels. Most global studies of gene regulation concentrate on transcript level regulation, and very few global analyses of differential translational efficiencies exist. The studies have revealed that in Saccharomyces cerevisiae, Arabidopsis thaliana, and human cell lines translational regulation plays a significant role. Additional species have not been investigated yet. Particularly, until now no global study of translational control with any prokaryotic species was available.

RESULTS

A global analysis of translational control was performed with two haloarchaeal model species, Halobacterium salinarum and Haloferax volcanii. To identify differentially regulated genes, exponentially growing and stationary phase cells were compared. More than 20% of H. salinarum transcripts are translated with non-average efficiencies. By far the largest group is comprised of genes that are translated with above-average efficiency specifically in exponential phase, including genes for many ribosomal proteins, RNA polymerase subunits, enzymes, and chemotaxis proteins. Translation of 1% of all genes is specifically repressed in either of the two growth phases. For comparison, DNA microarrays were also used to identify differential transcriptional regulation in H. salinarum, and 17% of all genes were found to have non-average transcript levels in exponential versus stationary phase. In H. volcanii, 12% of all genes are translated with non-average efficiencies. The overlap with H. salinarum is negligible. In contrast to H. salinarum, 4.6% of genes have non-average translational efficiency in both growth phases, and thus they might be regulated by other stimuli than growth phase.

CONCLUSION

For the first time in any prokaryotic species it was shown that a significant fraction of genes is under differential translational control. Groups of genes with different regulatory patterns were discovered. However, neither the fractions nor the identity of regulated genes are conserved between H. salinarum and H. volcanii, indicating that prokaryotes as well as eukaryotes use differential translational control for the regulation of gene expression, but that the identity of regulated genes is not conserved. For 70 H. salinarum genes potentiation of regulation was observed, but for the majority of regulated genes either transcriptional or translational regulation is employed.

Genome-wide polysomal analysis of a yeast strain with mutated ribosomal protein S9

Background

The yeast ribosomal protein S9 (S9) is located at the entrance tunnel of the mRNA into the ribosome. It is known to play a role in accurate decoding and its bacterial homolog (S4) has recently been shown to be involved in opening RNA duplexes. Here we examined the effects of changing the C terminus of S9, which is rich in acidic amino acids and extends out of the ribosome surface.

Results

We performed a genome-wide analysis to reveal effects at the transcription and translation levels of all yeast genes. While negligible relative changes were observed in steady-state mRNA levels, a significant number of mRNAs appeared to have altered ribosomal density. Notably, 40% of the genes having reliable signals changed their ribosomal association by more than one ribosome. Yet, no general correlations with physical or functional features of the mRNA were observed. Ribosome Density Mapping (RDM) along four of the mRNAs with increased association revealed an increase in ribosomal density towards the end of the coding region for at least two of them. Read-through analysis did not reveal any increase in read-through of a premature stop codon by the mutant strain.

Conclusion

The ribosomal protein rpS9 appears to be involved in the translation of many mRNAs, since altering its C terminus led to a significant change in ribosomal association of many mRNAs. We did not find strong correlations between these changes and several physical features of the mRNA, yet future studies with advanced tools may allow such correlations to be determined. Importantly, our results indicate an accumulation of ribosomes towards the end of the coding regions of some mRNAs. This suggests an involvement of S9 in ribosomal dissociation during translation termination.

Ribosomal slowdown mediates translational arrest during cellular division

Global mRNA translation is transiently inhibited during cellular division. We demonstrate that mitotic cells contain heavy polysomes, but these are significantly less translationally active than polysomes in cycling cells. Several observations indicate that mitotic translational attenuation occurs during the elongation stage: (i) in cycling nonsynchronized cultures, only mitotic cells fail to assemble stress granules when treated with agents that inhibit translational initiation; (ii) mitotic cells contain fewer free 80S complexes, which are less sensitive to high salt disassembly; (iii) mitotic polysomes are more resistant to enforced disassembly using puromycin; and (iv) ribosome transit time increases during mitosis. Elongation slowdown guarantees that polysomes are retained even if initiation is inhibited at the same time. Stalling translating ribosomes during mitosis may protect mRNAs and allow rapid resumption of translation immediately upon entry into the G(1) phase.

A network of multiple regulatory layers shapes gene expression in fission yeast

Gene expression is controlled at multiple layers, and cells may integrate different regulatory steps for coherent production of proper protein levels. We applied various microarray-based approaches to determine key gene-expression intermediates in exponentially growing fission yeast, providing genome-wide data for translational profiles, mRNA steady-state levels, polyadenylation profiles, start-codon sequence context, mRNA half-lives, and RNA polymerase II occupancy. We uncovered widespread and unexpected relationships between distinct aspects of gene expression. Translation and polyadenylation are aligned on a global scale with both the lengths and levels of mRNAs: efficiently translated mRNAs have longer poly(A) tails and are shorter, more stable, and more efficiently transcribed on average. Transcription and translation may be independently but congruently optimized to streamline protein production. These rich data sets, all acquired under a standardized condition, reveal a substantial coordination between regulatory layers and provide a basis for a systems-level understanding of multilayered gene-expression programs.

Growth control of the eukaryote cell: a systems biology study in yeast

BACKGROUND

Cell growth underlies many key cellular and developmental processes, yet a limited number of studies have been carried out on cell-growth regulation. Comprehensive studies at the transcriptional, proteomic and metabolic levels under defined controlled conditions are currently lacking.

RESULTS

Metabolic control analysis is being exploited in a systems biology study of the eukaryotic cell. Using chemostat culture, we have measured the impact of changes in flux (growth rate) on the transcriptome, proteome, endometabolome and exometabolome of the yeast Saccharomyces cerevisiae. Each functional genomic level shows clear growth-rate-associated trends and discriminates between carbon-sufficient and carbon-limited conditions. Genes consistently and significantly upregulated with increasing growth rate are frequently essential and encode evolutionarily conserved proteins of known function that participate in many protein-protein interactions. In contrast, more unknown, and fewer essential, genes are downregulated with increasing growth rate; their protein products rarely interact with one another. A large proportion of yeast genes under positive growth-rate control share orthologs with other eukaryotes, including humans. Significantly, transcription of genes encoding components of the TOR complex (a major controller of eukaryotic cell growth) is not subject to growth-rate regulation. Moreover, integrative studies reveal the extent and importance of post-transcriptional control, patterns of control of metabolic fluxes at the level of enzyme synthesis, and the relevance of specific enzymatic reactions in the control of metabolic fluxes during cell growth.

CONCLUSION

This work constitutes a first comprehensive systems biology study on growth-rate control in the eukaryotic cell. The results have direct implications for advanced studies on cell growth, in vivo regulation of metabolic fluxes for comprehensive metabolic engineering, and for the design of genome-scale systems biology models of the eukaryotic cell.

Global analyses of mRNA translational control during early Drosophila embryogenesis

BACKGROUND

In many animals, the first few hours of life proceed with little or no transcription, and developmental regulation at these early stages is dependent on maternal cytoplasm rather than the zygotic nucleus. Translational control is critical for early Drosophila embryogenesis and is exerted mainly at the gene level. To understand post-transcriptional regulation during Drosophila early embryonic development, we used sucrose polysomal gradient analyses and GeneChip analysis to illustrate the translation profile of individual mRNAs.

RESULTS

We determined ribosomal density and ribosomal occupancy of over 10,000 transcripts during the first ten hours after egg laying.

CONCLUSION

We report the extent and general nature of gene regulation at the translational level during early Drosophila embryogenesis on a genome-wide basis. The diversity of the translation profiles indicates multiple mechanisms modulating transcript-specific translation. Cluster analyses suggest that the genes involved in some biological processes are co-regulated at the translational level at certain developmental stages.

Polyamine sensing during antizyme mRNA programmed frameshifting

A key regulator of cellular polyamine levels from yeasts to mammals is the protein antizyme. The antizyme gene consists of two overlapping reading frames with ORF2 in the +1 frame relative to ORF1. A programmed +1 ribosomal frameshift occurs at the last codon of ORF1 and results in the production of full-length antizyme protein. The efficiency of frameshifting is proportional to the concentration of polyamines, thus creating an autoregulatory circuit for controlling polyamine levels. The mRNA recoding signals for frameshifting include an element 5' and a pseudoknot 3' of the shift site. The present work illustrates that the ORF1 stop codon and the 5' element are critical for polyamine sensing, whereas the 3' pseudoknot acts to stimulate frameshifting in a polyamine independent manner. We also demonstrate that polyamines are required to stimulate stop codon readthrough at the MuLV redefinition site required for normal expression of the GagPol precursor protein.