Saccharomyces cerevisiae
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PROVIDER: PRJNA305643 | ENA |
REPOSITORIES: ENA
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Project description:Ribosome-footprint profiling provides genome-wide snapshots of translation, but technical challenges can confound its analysis. Here, we use improved methods to obtain ribosome-footprint profiles and mRNA abundances that more faithfully reflect gene expression in Saccharomyces cerevisiae. Our results support proposals that both the beginning of coding regions and codons matching rare tRNAs are more slowly translated. They also indicate that emergent polypeptides with as few as three basic residues within a 10-residue window tend to slow translation. With the improved mRNA measurements, the variation attributable to translational control in exponentially growing yeast was less than previously reported, and most of this variation could be predicted with a simple model that considered mRNA abundance, upstream open reading frames, cap-proximal structure and nucleotide composition, and lengths of the coding and 5'-untranslated regions. Collectively, our results provide a framework for executing and interpreting ribosome-profiling studies and reveal key features of translational control in yeast. Ribosome-footprint profiling and RNA-seq (total RNA, poly(A) selected, RiboMinus treated, or Ribo-Zero treated) from log-phase S. cerevisiae. The study includes a reanalysis of the two Samples from GSE53313. The reanalyzed data is linked to the Series record.
2016-02-10 | E-GEOD-75897 | biostudies-arrayexpress
Project description:Ribosome-footprint profiling provides genome-wide snapshots of translation, but technical challenges can confound its analysis. Here, we use improved methods to obtain ribosome-footprint profiles and mRNA abundances that more faithfully reflect gene expression in Saccharomyces cerevisiae. Our results support proposals that both the beginning of coding regions and codons matching rare tRNAs are more slowly translated. They also indicate that emergent polypeptides with as few as three basic residues within a 10-residue window tend to slow translation. With the improved mRNA measurements, the variation attributable to translational control in exponentially growing yeast was less than previously reported, and most of this variation could be predicted with a simple model that considered mRNA abundance, upstream open reading frames, cap-proximal structure and nucleotide composition, and lengths of the coding and 5'-untranslated regions. Collectively, our results provide a framework for executing and interpreting ribosome-profiling studies and reveal key features of translational control in yeast.
2016-02-10 | GSE75897 | GEO
Project description:During translation elongation, the ribosome ratchets along its mRNA template, incorporating each new amino acid and translocating from one codon to the next. The elongation cycle requires dramatic structural rearrangements of the ribosome. We show here that deep sequencing of ribosome-protected mRNA fragments reveals not only the position of each ribosome but also, unexpectedly, its particular stage of the elongation cycle. Sequencing reveals two distinct populations of ribosome footprints, 28-30 nucleotides and 20-22 nucleotides long, representing translating ribosomes in distinct states, differentially stabilized by specific elongation inhibitors. We find that the balance of small and large footprints varies by codon and is correlated with translation speed. The ability to visualize conformational changes in the ribosome during elongation, at single-codon resolution, provides a new way to study the detailed kinetics of translation and a new probe with which to identify the factors that affect each step in the elongation cycle. Ribosome profiling, or sequencing of ribosome-protected mRNA fragments, in yeast. We assay ribosome footprint sizes and positions in three conditions: untreated yeast (3 replicates) and yeast treated with translation inhibitors cycloheximide (2 replicates) and anisomycin (2 biological replicates, one technical replicate). We also treat yeast with 3-aminotriazole to measure the effect of limited histidine tRNAs on ribosome footprint size and distribution (two treatment durations).
2014-06-10 | E-GEOD-58321 | biostudies-arrayexpress
Project description:Ribosome profiling measures genome-wide translation dynamics at sub-codon resolution. Cycloheximide (CHX), a widely used translation inhibitor to arrest ribosomes in these experiments, has been shown to induce biases in yeast, questioning its use. However, whether such biases are present in datasets of other organisms including humans is unknown. Here we compare different CHX-treatment conditions in human cells and yeast in parallel experiments using an optimized protocol. We find that human ribosomes are not susceptible to conformational restrictions by CHX, nor does it distort gene-level measurements of ribosome occupancy, measured decoding speed or the translational ramp. Furthermore, CHX-induced codon-specific biases on ribosome occupancy are not detectable in human cells or other model organisms. This shows that reported biases of CHX are species-specific and that CHX does not affect the outcome of ribosome profiling experiments in most settings. Our findings provide a solid framework to conduct and analyze ribosome profiling experiments.
2021-07-28 | GSE136940 | GEO
Project description:Ribosome profiling is a widespread tool for studying translational dynamics in human cells. Its central assumption is that ribosome footprint density on a transcript quantitatively reflects protein synthesis. Here, we test this assumption using pulsed-SILAC (pSILAC) high-accuracy targeted proteomics. We focus on multiple myeloma cells exposed to bortezomib, a first-line chemotherapy and proteasome inhibitor. In the absence of drug effects, we found that direct measurement of protein synthesis by pSILAC correlated well with indirect measurement of synthesis from ribosome footprint density. This correlation, however, broke down under bortezomib-induced stress. By developing a statistical model integrating longitudinal proteomic and mRNA-seq measurements, we found that proteomics could directly detect global alterations in translational rate caused by bortezomib; these changes are not detectable by ribosomal profiling alone. Further, by incorporating pSILAC data into a gene expression model, we predict cell-stress specific proteome remodeling events. These results demonstrate that pSILAC provides an important complement to ribosome profiling in measuring proteome dynamics. Timecourse experiment with six points over 48hr after bortezomib exposure in MM.1S myeloma cells. mRNA-seq and ribosome profiling data at each time point.
2017-05-18 | E-GEOD-69047 | biostudies-arrayexpress
Project description:Work summary: Full-transcriptome methods have brought versatile power to protein biosynthesis research, but remain difficult to apply for the quantification of absolute protein synthesis rates. Here we propose and, using modified translation complex profiling, confirm co-localisation of ribosomes on messenger(m)RNA resulting from the ribosomal diffusional dynamics. We demonstrate that the stochastically co-localised ribosomes are linked with the translation initiation rate and provide a robust variable to model and quantify specific absolute protein output from mRNA. The new type of signal originating from the stochastic co-localisation of ribosomes on mRNA is evidenced by long disome-derived (potentially but rarely, multisome-derived) footprints outside the regions of non-random elongation stalls. Using the stochastic co-localisation component of the translation complex profiling data, we propose a new approach to assess absolute translation rates across mRNA, based on the calculation of Stochastic Translation Efficiency (STE) measure. STE employs a machine learning model trained with multiple TCP-seq-sourced variables. The variables, among others, include stochastic disome signal derived from the total disome footprint data and normalised to the ribosome (RS) footprint abundance across the respective open reading frames (ORFs). The variables also include SSU footprint occurrences over the respective start codons normalised to the RS signal averaged and normalised by the ORF length, to better distinguish between the cases of actively initiated or densely populated but slowly initiated mRNAs. Importantly, STE does not employ any variables resulting from normalisation of the signals of different nature, such as any normalisation of the footprint data by relative RNA abundance measured by RNA-seq. We propose STE as a more robust, sometimes more convenient, alternative to the classical TE (translation efficiency). The main distinguishing features of the STE are the inherent single-molecule-event nature of the main measure component (the long stochastic disome footprint signal), similar type of data used for the numerator(s) and denominator(s) of the calculated variables, resistance to the abundance changes and variations in the differential localisation of RNA and insensitivity to the library preparation techniques. We further hypothesise that similar high-throughput data-derived measures based on parameters dependent on random individual molecular co-incidences can be utilised to provide robust assessment of many molecular processes in dynamic biological systems. Methods summary: Wild-type (WT) yeast cell line BY4741 (MATa his3Δ1 leu2Δ0 met15Δ0 ura3Δ0; Dharmacon) (Non Starved, NS) was used for the glucose starvation (10 minutes; Starved, S10) studies. 2-3 replicates were used for each type of footprinting library and the NS and S10 biological points. The cells were subjected to snap-chilling followed by rapid formaldehyde fixation. The fixed material was separated into the ribosome-associated and non-associated fractions using ultracentrifugation. The ribosome-associated fraction was RNase-digested and separated into small ribosomal subunit (SSU), monosomal (ribosomes, RS), and disomal (disomes, DS) fractions of complexes using ultracentrifugation. The resultant translational complexes were de-crosslinked, and their RNA isolated to construct TCP-seq libraries, which were deep sequenced. Results summary: Preliminary theoretical investigations revealed monotonous dependence of the stochastic DS frequency on translation initiation rate in a broad range of initiation and elongation rates and variances, well-covering all biologically meaningful combination of parameters. Biomimetic in silico modelling utilising elongation and initiation rate distributions extrapolated from in vivo single-molecule measurements available in the published data confirmed the link of stochastic DS signal with the initiation frequency. The in silico-modelled stochastic DS frequency has shown resistance to local alterations of the elongation rate over ORFs and monotonous dependence on the initiation rate, even in the extreme cases of elongation rate discontinuity. DS footprint fractions derived from the TCP-seq material prominently demonstrated the presence of longer footprints, and revealed a complex pattern of footprint lengths. The TCP-seq DS footprint pattern allowed us to propose a generalised case of ribosomal co-localisation, whereby DS can form as a result of non-random co-localisations of serially occurring ribosomes, as well as co-localisations resulting from the spatial proximity and the geometry and spatial arrangement of the respective source poly(ribo)somes. Bioinformatically segregating all of the DS signal into its stochastic and non-random components, and combining the derived components with the other TCP-seq-sourced variables and known ORF lengths, we further implemented a machine learning approach that results in Stochastic Translation Efficiency (STE) measure with high correlation (Pearson’s r ~0.7 for train and ~0.6 for test data, respectively) to the absolute protein synthesis rates as directly measured in the published data using metabolic labelling and mass spectrometry. Applying STE to the NS and S10 cell stress scenarios, we identified mRNAs from 5,238 genes with distinct translational behaviour. Multiple classes of mRNAs demonstrated acute (~50) and moderate (~50) translational up-regulation in the starved cells, while others were moderately (~300) and severely (~280) down-regulated. We dissected TCP-seq variable contribution strength into the STE, revealing strong input and role of the scanning process and stochastic co-localisation of ribosomes in the definition of translation rate. We found that the stressed cells retained high median elongation rate capacity, while losing their ability to translate proteins with the maximum rate, thus highlighting that the safety translation shutdown is permissive of translation and is largely aimed at capping the highest-producing mRNAs. Using STE, we demonstrated that translational control in rapid stress response is vastly differential, with mRNAs showing highly specific magnitude and direction of the response. Conclusions: The stochastic disome signal, together with the other measurements sourced from TCP-seq and calculated as Stochastic Translation Efficiency (STE) measure, provide a link to the absolute translation initiation and protein biosynthesis rates. Using STE, it is possible to rank mRNAs by the absolute protein output and thus, characterise the ‘power’ of translation control elements across transcripts in a single setting or between different conditions. STE does not use bias-inducing normalisation to the RNA abundance or signals of different types and relies on self-normalised signal pairs. STE thus evades imprecisions arising from the different accessibility across mRNAs to translation machinery (such as in nucleus, phase-separated foci or condensates, etc.) and coincidental transcription- and stability-driven mRNA abundance alterations, and provides a robust measure suitable for investigating protein biosynthesis during rapidly changing transcriptome background, as occurs in cell stress response and reprogramming. With STE, we demonstrate that the prototypical example of translational control during yeast response to glucose starvation is more complex than previously thought and includes translational acceleration as well as re-adjustment of the RNA metabolism to suit new translational demands. More details can be uncovered in the future, as STE application is permissive to finer dynamics dissection and elucidation of very rapid cell responses at the level of RNA translation.
2024-03-31 | GSE200091 | GEO
Project description:A fundamental goal of genomics is to identify the complete set of expressed proteins. Automated annotation strategies rely on assumptions about protein-coding sequences (CDSs), e.g., they are conserved, do not overlap, and exceed a minimum length. However, an increasing number of newly discovered proteins violate these rules. Here we present an experimental and analytical framework, based on ribosome profiling and linear regression, for systematic identification and quantification of translation. Application of this approach to lipopolysaccharide-stimulated mouse dendritic cells and HCMV-infected human fibroblasts identifies thousands of novel CDSs, including micropeptides and variants of known proteins, that bear the hallmarks of canonical translation and exhibit comparable translation levels and dynamics to annotated CDSs. Remarkably, many translation events are identified in both mouse and human cells even when the peptide sequence is not conserved. Our work thus reveals an unexpected complexity to mammalian translation suited to provide both conserved regulatory or protein-based functions. 37 ribosome footprint samples from mouse BMDCs across a time course of LPS stimulation and in the presence or absence of translation inhibitors cycloheximide, harringtonine, or lactimidomycin. A mock (non-LPS stimulated) time course is also included, collected in the presence of cycloheximide. Two replicates are available for the LPS timecourse under CHX treatment.
2015-12-03 | E-GEOD-74139 | biostudies-arrayexpress
Project description:DEAD-box RNA helicases eIF4A and Ded1 are believed to promote translation initiation by resolving mRNA secondary structures that impede ribosome attachment at the mRNA 5’ end or subsequent scanning of the 5’UTR, but whether they perform distinct functions or act redundantly in vivo is poorly understood. We compared the effects of mutations in Ded1 or eIF4A on global translational efficiencies (TEs) in yeast by ribosome footprint profiling. Despite similar reductions in bulk translation, inactivation of a cold-sensitive Ded1 mutant substantially reduced the TEs of >600 mRNAs, whereas inactivation of a temperature-sensitive eIF4A mutant yielded <40 similarly impaired mRNAs. The broader requirement for Ded1 did not reflect more pervasive secondary structures at low temperature, as inactivation of temperature-sensitive and cold-sensitive ded1 mutants gave highly correlated results. Interestingly, Ded1-dependent mRNAs exhibit greater than average 5’UTR length and propensity for secondary structure, implicating Ded1 in scanning though structured 5' UTRs. Reporter assays confirmed that cap- distal stem-loop insertions increase dependence on Ded1 but not eIF4A for efficient translation. While only a small fraction of mRNAs is strongly dependent on eIF4A, this dependence is significantly correlated with requirements for Ded1 and 5’UTR features characteristic of Ded1- dependent mRNAs. Our findings suggest that Ded1 is critically required to promote scanning through secondary structures within 5’UTRs; and while eIF4A cooperates with Ded1 in this function, it also promotes a step of initiation common to virtually all yeast mRNAs. We compared the effects of mutations in Ded1 or eIF4A on global translational efficiencies (TEs) in yeast by ribosome footprint profiling.The study includes 32 samples, comprised of 16 mRNA-Seq samples and 16 ribosome footprint profiling samples, derived from biological replicates of 3 mutant strains, ded1-cs, ded1-ts and tif1-ts, and the corresponding wild-type strains. The tif1-ts mutant and its wild-type counterpart were analyzed at 30°C and 37°C.
2015-03-02 | E-GEOD-66411 | biostudies-arrayexpress
Project description:Ribosome profiling is a widespread tool for studying translational dynamics in human cells. Its central assumption is that ribosome footprint density on a transcript quantitatively reflects protein synthesis. Here, we test this assumption using pulsed-SILAC (pSILAC) high-accuracy targeted proteomics. We focus on multiple myeloma cells exposed to bortezomib, a first-line chemotherapy and proteasome inhibitor. In the absence of drug effects, we found that direct measurement of protein synthesis by pSILAC correlated well with indirect measurement of synthesis from ribosome footprint density. This correlation, however, broke down under bortezomib-induced stress. By developing a statistical model integrating longitudinal proteomic and mRNA-seq measurements, we found that proteomics could directly detect global alterations in translational rate caused by bortezomib; these changes are not detectable by ribosomal profiling alone. Further, by incorporating pSILAC data into a gene expression model, we predict cell-stress specific proteome remodeling events. These results demonstrate that pSILAC provides an important complement to ribosome profiling in measuring proteome dynamics.
2017-05-18 | GSE69047 | GEO
Project description:Heritable differences in gene expression between individuals are an important source of phenotypic variation. The question of how closely the effects of genetic variation on protein levels mirror those on mRNA levels remains open. Here, we addressed this question by using ribosomal footprinting to examine how genetic differences between two strains of the yeast S. cerevisiae affect translation. Strain differences in translation were observed for hundreds of genes, more than half as many as showed genetic differences in mRNA levels. Similarly, allele specific measurements in the diploid hybrid between the two strains found roughly half as many cis-acting effects on translation as were observed for mRNA levels. In both the parents and the hybrid, strong effects on translation were rare, such that the direction of an mRNA difference was typically reflected in a concordant footprint difference. The relative importance of cis and trans acting variation on footprint levels was similar to that for mRNA levels. Across all expressed genes, there was a tendency for translation to more often reinforce than buffer mRNA differences, resulting in footprint differences with greater magnitudes than the mRNA differences. Finally, we catalogued instances of premature translation termination in the two yeast strains. Overall, genetic variation clearly influences translation, but primarily does so by subtly modulating differences in mRNA levels. Translation does not appear to create strong discrepancies between genetic influences on mRNA and protein levels. Ribsosomal footprinting and RNASeq in the two yeast strains BY and RM as well as their diploid hybrid. We generated one library each for the BY and RM parents, and two libraries (biological replicates) for the hybrid data.
2014-03-31 | E-GEOD-55400 | biostudies-arrayexpress