1
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A dynamical stochastic model of yeast translation across the cell cycle. Heliyon 2023; 9:e13101. [PMID: 36793957 PMCID: PMC9922973 DOI: 10.1016/j.heliyon.2023.e13101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 01/04/2023] [Accepted: 01/16/2023] [Indexed: 01/27/2023] Open
Abstract
Translation is a central step in gene expression, however its quantitative and time-resolved regulation is poorly understood. We developed a discrete, stochastic model for protein translation in S. cerevisiae in a whole-transcriptome, single-cell context. A "base case" scenario representing an average cell highlights translation initiation rates as the main co-translational regulatory parameters. Codon usage bias emerges as a secondary regulatory mechanism through ribosome stalling. Demand for anticodons with low abundancy is shown to cause above-average ribosome dwelling times. Codon usage bias correlates strongly both with protein synthesis rates and elongation rates. Applying the model to a time-resolved transcriptome estimated by combining data from FISH and RNA-Seq experiments, it could be shown that increased total transcript abundance during the cell cycle decreases translation efficiency at single transcript level. Translation efficiency grouped by gene function shows highest values for ribosomal and glycolytic genes. Ribosomal proteins peak in S phase while glycolytic proteins rank highest in later cell cycle phases.
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2
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Kim DJ, Kim J, Lee DH, Lee J, Woo HM. DeepTESR: A Deep Learning Framework to Predict the Degree of Translational Elongation Short Ramp for Gene Expression Control. ACS Synth Biol 2022; 11:1719-1726. [PMID: 35502843 DOI: 10.1021/acssynbio.2c00202] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Controlling translational elongation is essential for efficient protein synthesis. Ribosome profiling has revealed that the speed of ribosome movement is correlated with translational efficiency in the translational elongation ramp. In this work, we present a new deep learning model, called DeepTESR, to predict the degree of translational elongation short ramp (TESR) from mRNA sequence. The proposed deep learning model exhibited superior performance in predicting the TESR scores for 226 981 TESR sequences, resulting in the mean absolute error (MAE) of 0.285 and a coefficient of determination R2 of 0.627, superior to the conventional machine learning models (e.g., MAE of 0.335 and R2 of 0.571 for LightGBM). We experimentally validated that heterologous fluorescence expression of proteins with randomly selected TESR was moderately correlated with the predictions. Furthermore, a genome-wide analysis of TESR prediction in the 4305 coding sequences of Escherichia coli showed conserved TESRs over the clusters of orthologous groups. In this sense, DeepTESR can be used to predict the degree of TESR for gene expression control and to decipher the mechanism of translational control with ribosome profiling. DeepTESR is available at https://github.com/fmblab/DeepTESR.
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3
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Carmel Ezra S, Tuller T. Modeling the effect of rRNA-mRNA interactions and mRNA folding on mRNA translation in chloroplasts. Comput Struct Biotechnol J 2022; 20:2521-2538. [PMID: 35685358 PMCID: PMC9157439 DOI: 10.1016/j.csbj.2022.05.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 05/15/2022] [Accepted: 05/15/2022] [Indexed: 11/15/2022] Open
Abstract
The process of translation initiation in prokaryotes is mediated by the hybridization of the 16S rRNA of the small ribosomal subunit with the mRNA in a short region called the ribosomal binding site. However, translation initiation in chloroplasts, which have evolved from an ancestral bacterium, is not well understood. Some studies suggest that in many cases it differs from translation initiation in bacteria and involves various novel interactions of the mRNA structures with intracellular factors; however currently, there is no generic quantitative model related to these aspects in chloroplasts. We developed a novel computational pipeline and models that can be used for understanding and modeling translation regulation in chloroplasts. We demonstrate that local folding and co-folding energy of the rRNA and the mRNA correlates with codon usage estimators of expression levels (r = -0.63) and infer predictive models that connect these energies and codon usage to protein levels (with correlation up to 0.71). In addition, we demonstrate that the ends of the transcripts in chloroplasts are populated with various structural elements that may be functional. Furthermore, we report a database of 166 novel structures in the chloroplast transcripts that are predicted to be functional. We believe that the models reported here improve existing understandings of genomic evolution and the biophysics of translation in chloroplasts; as such, they can aid gene expression engineering in chloroplasts for various biotechnological objectives.
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Affiliation(s)
- Stav Carmel Ezra
- Department of Biomedical Engineering, Tel Aviv University, Israel
| | - Tamir Tuller
- Department of Biomedical Engineering, Tel Aviv University, Israel
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4
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Neumann T, Tuller T. Modeling the ribosomal small subunit dynamic in Saccharomyces cerevisiae based on TCP-seq data. Nucleic Acids Res 2022; 50:1297-1316. [PMID: 35100399 PMCID: PMC8860609 DOI: 10.1093/nar/gkac021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 12/31/2021] [Accepted: 01/07/2022] [Indexed: 11/13/2022] Open
Abstract
Translation Complex Profile Sequencing (TCP-seq), a protocol that was developed and implemented on Saccharomyces cerevisiae, provides the footprints of the small subunit (SSU) of the ribosome (with additional factors) across the entire transcriptome of the analyzed organism. In this study, based on the TCP-seq data, we developed for the first-time a predictive model of the SSU density and analyzed the effect of transcript features on the dynamics of the SSU scan in the 5′UTR. Among others, our model is based on novel tools for detecting complex statistical relations tailored to TCP-seq. We quantitatively estimated the effect of several important features, including the context of the upstream AUG, the upstream ORF length and the mRNA folding strength. Specifically, we suggest that around 50% of the variance related to the read counts (RC) distribution near a start codon can be attributed to the AUG context score. We provide the first large scale direct quantitative evidence that shows that indeed AUG context affects the small sub-unit movement. In addition, we suggest that strong folding may cause the detachment of the SSU from the mRNA. We also identified a number of novel sequence motifs that can affect the SSU scan; some of these motifs affect transcription factors and RNA binding proteins. The results presented in this study provide a better understanding of the biophysical aspects related to the SSU scan along the 5′UTR and of translation initiation in S. cerevisiae, a fundamental step toward a comprehensive modeling of initiation.
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Affiliation(s)
- Tamar Neumann
- Department of Biomedical Engineering, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Tamir Tuller
- Department of Biomedical Engineering, Tel Aviv University, Tel Aviv 6997801, Israel
- The Sagol School of Neuroscience, Tel-Aviv University, Tel Aviv 6997801, Israel
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5
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Bhandari BK, Lim CS, Remus DM, Chen A, van Dolleweerd C, Gardner PP. Analysis of 11,430 recombinant protein production experiments reveals that protein yield is tunable by synonymous codon changes of translation initiation sites. PLoS Comput Biol 2021; 17:e1009461. [PMID: 34610008 PMCID: PMC8519471 DOI: 10.1371/journal.pcbi.1009461] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 10/15/2021] [Accepted: 09/19/2021] [Indexed: 12/16/2022] Open
Abstract
Recombinant protein production is a key process in generating proteins of interest in the pharmaceutical industry and biomedical research. However, about 50% of recombinant proteins fail to be expressed in a variety of host cells. Here we show that the accessibility of translation initiation sites modelled using the mRNA base-unpairing across the Boltzmann's ensemble significantly outperforms alternative features. This approach accurately predicts the successes or failures of expression experiments, which utilised Escherichia coli cells to express 11,430 recombinant proteins from over 189 diverse species. On this basis, we develop TIsigner that uses simulated annealing to modify up to the first nine codons of mRNAs with synonymous substitutions. We show that accessibility captures the key propensity beyond the target region (initiation sites in this case), as a modest number of synonymous changes is sufficient to tune the recombinant protein expression levels. We build a stochastic simulation model and show that higher accessibility leads to higher protein production and slower cell growth, supporting the idea of protein cost, where cell growth is constrained by protein circuits during overexpression.
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Affiliation(s)
- Bikash K. Bhandari
- Department of Biochemistry, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand
| | - Chun Shen Lim
- Department of Biochemistry, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand
| | - Daniela M. Remus
- Callaghan Innovation Protein Science and Engineering, University of Canterbury, Christchurch, New Zealand
| | - Augustine Chen
- Department of Biochemistry, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand
| | - Craig van Dolleweerd
- Biomolecular Interaction Center, University of Canterbury, Christchurch, New Zealand
| | - Paul P. Gardner
- Department of Biochemistry, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand
- Biomolecular Interaction Center, University of Canterbury, Christchurch, New Zealand
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6
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Xu K, Tong Y, Li Y, Tao J, Li J, Zhou J, Liu S. Rational Design of the N-Terminal Coding Sequence for Regulating Enzyme Expression in Bacillus subtilis. ACS Synth Biol 2021; 10:265-276. [PMID: 33464830 DOI: 10.1021/acssynbio.0c00309] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Synonymous mutation of the N-terminal coding sequence (NCS) has been used to regulate gene expression. We here developed a statistical model to predict the effect of the NCSs on protein expression in Bacillus subtilis WB600. First, a synonymous mutation was performed within the first 10 residues of a superfolder green fluorescent protein to generate a library of 172 NCS synonymous mutants with different expression levels. A prediction model was then developed, which adopted G/C frequency at the third position of each codon and minimum free energy of mRNA as the independent variables, using multiple regression analysis between the 11 sequence parameters of the NCS and their fluorescence intensities. By designing the NCS of the 10 signal peptides de novo according to the model, the extracellular yield of B. subtilis pullulanase fused to each signal peptide was up-regulated by up to 515% or down-regulated by at most 79%. This work provided a candidate tool for fine-tuning gene expression or enzyme production in B. subtilis.
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Affiliation(s)
- Kuidong Xu
- National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, Wuxi 214122, China
| | - Yi Tong
- National Engineering Research Center for Corn Deep Processing, Jilin COFCO Biochemical Co. Ltd., Changchun 130033, China
| | - Yi Li
- National Engineering Research Center for Corn Deep Processing, Jilin COFCO Biochemical Co. Ltd., Changchun 130033, China
| | - Jin Tao
- National Engineering Research Center for Corn Deep Processing, Jilin COFCO Biochemical Co. Ltd., Changchun 130033, China
| | - Jianghua Li
- The Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Jingwen Zhou
- National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, Wuxi 214122, China
- Jiangsu Provisional Research Center for Bioactive Product Processing Technology, Jiangnan University, Wuxi 214122, China
| | - Song Liu
- National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, Wuxi 214122, China
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7
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Computational discovery and modeling of novel gene expression rules encoded in the mRNA. Biochem Soc Trans 2020; 48:1519-1528. [PMID: 32662820 DOI: 10.1042/bst20191048] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 06/15/2020] [Accepted: 06/17/2020] [Indexed: 11/17/2022]
Abstract
The transcript is populated with numerous overlapping codes that regulate all steps of gene expression. Deciphering these codes is very challenging due to the large number of variables involved, the non-modular nature of the codes, biases and limitations in current experimental approaches, our limited knowledge in gene expression regulation across the tree of life, and other factors. In recent years, it has been shown that computational modeling and algorithms can significantly accelerate the discovery of novel gene expression codes. Here, we briefly summarize the latest developments and different approaches in the field.
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8
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Penn WD, Harrington HR, Schlebach JP, Mukhopadhyay S. Regulators of Viral Frameshifting: More Than RNA Influences Translation Events. Annu Rev Virol 2020; 7:219-238. [PMID: 32600156 DOI: 10.1146/annurev-virology-012120-101548] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Programmed ribosomal frameshifting (PRF) is a conserved translational recoding mechanism found in all branches of life and viruses. In bacteria, archaea, and eukaryotes PRF is used to downregulate protein production by inducing a premature termination of translation, which triggers messenger RNA (mRNA) decay. In viruses, PRF is used to drive the production of a new protein while downregulating the production of another protein, thus maintaining a stoichiometry optimal for productive infection. Traditionally, PRF motifs have been defined by the characteristics of two cis elements: a slippery heptanucleotide sequence followed by an RNA pseudoknot or stem-loop within the mRNA. Recently, additional cis and new trans elements have been identified that regulate PRF in both host and viral translation. These additional factors suggest PRF is an evolutionarily conserved process whose function and regulation we are just beginning to understand.
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Affiliation(s)
- Wesley D Penn
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, USA
| | - Haley R Harrington
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, USA
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9
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Diament A, Weiner I, Shahar N, Landman S, Feldman Y, Atar S, Avitan M, Schweitzer S, Yacoby I, Tuller T. ChimeraUGEM: unsupervised gene expression modeling in any given organism. Bioinformatics 2020; 35:3365-3371. [PMID: 30715207 DOI: 10.1093/bioinformatics/btz080] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Revised: 01/07/2019] [Accepted: 01/30/2019] [Indexed: 01/06/2023] Open
Abstract
MOTIVATION Regulation of the amount of protein that is synthesized from genes has proved to be a serious challenge in terms of analysis and prediction, and in terms of engineering and optimization, due to the large diversity in expression machinery across species. RESULTS To address this challenge, we developed a methodology and a software tool (ChimeraUGEM) for predicting gene expression as well as adapting the coding sequence of a target gene to any host organism. We demonstrate these methods by predicting protein levels in seven organisms, in seven human tissues, and by increasing in vivo the expression of a synthetic gene up to 26-fold in the single-cell green alga Chlamydomonas reinhardtii. The underlying model is designed to capture sequence patterns and regulatory signals with minimal prior knowledge on the host organism and can be applied to a multitude of species and applications. AVAILABILITY AND IMPLEMENTATION Source code (MATLAB, C) and binaries are freely available for download for non-commercial use at http://www.cs.tau.ac.il/~tamirtul/ChimeraUGEM/, and supported on macOS, Linux and Windows. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Alon Diament
- Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv, Israel
| | - Iddo Weiner
- Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv, Israel.,School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv, Israel
| | - Noam Shahar
- School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv, Israel
| | - Shira Landman
- School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv, Israel
| | - Yael Feldman
- School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv, Israel
| | - Shimshi Atar
- Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv, Israel
| | - Meital Avitan
- Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv, Israel.,School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv, Israel
| | - Shira Schweitzer
- School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv, Israel
| | - Iftach Yacoby
- School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv, Israel
| | - Tamir Tuller
- Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv, Israel.,The Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
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10
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Abstract
Messenger RNAs (mRNAs) consist of a coding region (open reading frame (ORF)) and two untranslated regions (UTRs), 5'UTR and 3'UTR. Ribosomes travel along the coding region, translating nucleotide triplets (called codons) to a chain of amino acids. The coding region was long believed to mainly encode the amino acid content of proteins, whereas regulatory signals reside in the UTRs and in other genomic regions. However, in recent years we have learned that the ORF is expansively populated with various regulatory signals, or codes, which are related to all gene expression steps and additional intracellular aspects. In this paper, we review the current knowledge related to overlapping codes inside the coding regions, such as the influence of synonymous codon usage on translation speed (and, in turn, the effect of translation speed on protein folding), ribosomal frameshifting, mRNA stability, methylation, splicing, transcription and more. All these codes come together and overlap in the ORF sequence, ensuring production of the right protein at the right time.
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Affiliation(s)
- Shaked Bergman
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
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11
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Peeri M, Tuller T. High-resolution modeling of the selection on local mRNA folding strength in coding sequences across the tree of life. Genome Biol 2020; 21:63. [PMID: 32151272 PMCID: PMC7063772 DOI: 10.1186/s13059-020-01971-y] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Accepted: 02/22/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND mRNA can form local secondary structure within the protein-coding sequence, and the strength of this structure is thought to influence gene expression regulation. Previous studies suggest that secondary structure strength may be maintained under selection, but the details of this phenomenon are not well understood. RESULTS We perform a comprehensive study of the selection on local mRNA folding strengths considering variation between species across the tree of life. We show for the first time that local folding strength selection tends to follow a conserved characteristic profile in most phyla, with selection for weak folding at the two ends of the coding region and for strong folding elsewhere in the coding sequence, with an additional peak of selection for strong folding located downstream of the start codon. The strength of this pattern varies between species and organism groups, and we highlight contradicting cases. To better understand the underlying evolutionary process, we show that selection strengths in the different regions are strongly correlated, and report four factors which have a clear predictive effect on local mRNA folding selection within the coding sequence in different species. CONCLUSIONS The correlations observed between selection for local secondary structure strength in the different regions and with the four genomic and environmental factors suggest that they are shaped by the same evolutionary process throughout the coding sequence, and might be maintained under direct selection related to optimization of gene expression and specifically translation regulation.
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Affiliation(s)
- Michael Peeri
- Department of Biomedical Engineering, Tel-Aviv University, Tel-Aviv, Israel
| | - Tamir Tuller
- Department of Biomedical Engineering, Tel-Aviv University, Tel-Aviv, Israel.
- Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel.
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12
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Erdmann-Pham DD, Dao Duc K, Song YS. The Key Parameters that Govern Translation Efficiency. Cell Syst 2020; 10:183-192.e6. [PMID: 31954660 DOI: 10.1016/j.cels.2019.12.003] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2019] [Revised: 08/29/2019] [Accepted: 12/17/2019] [Indexed: 11/16/2022]
Abstract
Translation of mRNA into protein is a fundamental yet complex biological process with multiple factors that can potentially affect its efficiency. Here, we study a stochastic model describing the traffic flow of ribosomes along the mRNA and identify the key parameters that govern the overall rate of protein synthesis, sensitivity to initiation rate changes, and efficiency of ribosome usage. By analyzing a continuum limit of the model, we obtain closed-form expressions for stationary currents and ribosomal densities, which agree well with Monte Carlo simulations. Furthermore, we completely characterize the phase transitions in the system, and by applying our theoretical results, we formulate design principles that detail how to tune the key parameters we identified to optimize translation efficiency. Using ribosome profiling data from S. cerevisiae, we show that its translation system is generally consistent with these principles. Our theoretical results have implications for evolutionary biology, as well as for synthetic biology.
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Affiliation(s)
- Dan D Erdmann-Pham
- Department of Mathematics, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Khanh Dao Duc
- Computer Science Division, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Yun S Song
- Computer Science Division, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Statistics, University of California, Berkeley, Berkeley, CA 94720, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA.
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13
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Li JJ, Chew GL, Biggin MD. Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes. Genome Biol 2019; 20:162. [PMID: 31399036 PMCID: PMC6689182 DOI: 10.1186/s13059-019-1761-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 07/11/2019] [Indexed: 12/17/2022] Open
Abstract
Background General translational cis-elements are present in the mRNAs of all genes and affect the recruitment, assembly, and progress of preinitiation complexes and the ribosome under many physiological states. These elements include mRNA folding, upstream open reading frames, specific nucleotides flanking the initiating AUG codon, protein coding sequence length, and codon usage. The quantitative contributions of these sequence features and how and why they coordinate to control translation rates are not well understood. Results Here, we show that these sequence features specify 42–81% of the variance in translation rates in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Mus musculus, and Homo sapiens. We establish that control by RNA secondary structure is chiefly mediated by highly folded 25–60 nucleotide segments within mRNA 5′ regions, that changes in tri-nucleotide frequencies between highly and poorly translated 5′ regions are correlated between all species, and that control by distinct biochemical processes is extensively correlated as is regulation by a single process acting in different parts of the same mRNA. Conclusions Our work shows that general features control a much larger fraction of the variance in translation rates than previously realized. We provide a more detailed and accurate understanding of the aspects of RNA structure that directs translation in diverse eukaryotes. In addition, we note that the strongly correlated regulation between and within cis-control features will cause more even densities of translational complexes along each mRNA and therefore more efficient use of the translation machinery by the cell. Electronic supplementary material The online version of this article (10.1186/s13059-019-1761-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jingyi Jessica Li
- Department of Statistics, Department of Biomathematics, and Department of Human Genetics, University of California, Los Angeles, CA, 90095, USA.
| | - Guo-Liang Chew
- Computational Biology Program, Public Health Sciences and Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
| | - Mark Douglas Biggin
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94708, USA.
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14
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Petersen SD, Zhang J, Lee JS, Jakociunas T, Grav LM, Kildegaard HF, Keasling JD, Jensen MK. Modular 5'-UTR hexamers for context-independent tuning of protein expression in eukaryotes. Nucleic Acids Res 2019; 46:e127. [PMID: 30124898 PMCID: PMC6265478 DOI: 10.1093/nar/gky734] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Accepted: 08/01/2018] [Indexed: 11/25/2022] Open
Abstract
Functional characterization of regulatory DNA elements in broad genetic contexts is a prerequisite for forward engineering of biological systems. Translation initiation site (TIS) sequences are attractive to use for regulating gene activity and metabolic pathway fluxes because the genetic changes are minimal. However, limited knowledge is available on tuning gene outputs by varying TISs in different genetic and environmental contexts. Here, we created TIS hexamer libraries in baker’s yeast Saccharomyces cerevisiae directly 5′ end of a reporter gene in various promoter contexts and measured gene activity distributions for each library. Next, selected TIS sequences, resulted in almost 10-fold changes in reporter outputs, were experimentally characterized in various environmental and genetic contexts in both yeast and mammalian cells. From our analyses, we observed strong linear correlations (R2 = 0.75–0.98) between all pairwise combinations of TIS order and gene activity. Finally, our analysis enabled the identification of a TIS with almost 50% stronger output than a commonly used TIS for protein expression in mammalian cells, and selected TISs were also used to tune gene activities in yeast at a metabolic branch point in order to prototype fitness and carotenoid production landscapes. Taken together, the characterized TISs support reliable context-independent forward engineering of translation initiation in eukaryotes.
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Affiliation(s)
- Søren D Petersen
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
| | - Jie Zhang
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
| | - Jae S Lee
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
| | - Tadas Jakociunas
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
| | - Lise M Grav
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
| | - Helene F Kildegaard
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
| | - Jay D Keasling
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.,Joint BioEnergy Institute, Emeryville, CA 94608, USA.,Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.,Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA 94720, USA.,Department of Bioengineering, University of California, Berkeley, CA 94720, USA.,Center for Synthetic Biochemistry, Institute for Synthetic Biology, Shenzhen Institutes of Advanced Technologies, Shenzhen 518055, China
| | - Michael K Jensen
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
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15
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Sabi R, Tuller T. Novel insights into gene expression regulation during meiosis revealed by translation elongation dynamics. NPJ Syst Biol Appl 2019; 5:12. [PMID: 30962948 PMCID: PMC6449359 DOI: 10.1038/s41540-019-0089-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Accepted: 03/20/2019] [Indexed: 01/14/2023] Open
Abstract
The ability to dynamically control mRNA translation has a great impact on many intracellular processes. Whereas it is believed that translational control in eukaryotes occurs mainly at initiation, the condition-specific changes at the elongation level and their potential regulatory role remain unclear. Using computational approaches applied to ribosome profiling data, we show that elongation rate is dynamic and can change considerably during the yeast meiosis to facilitate the selective translation of stage-specific transcripts. We observed unique elongation changes during meiosis II, including a global inhibition of translation elongation at the onset of anaphase II accompanied by a sharp shift toward increased elongation for genes required at this meiotic stage. We also show that ribosomal proteins counteract the global decreased elongation by maintaining high initiation rates. Our findings provide new insights into gene expression regulation during meiosis and demonstrate that codon usage evolved, among others, to optimize timely translation.
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Affiliation(s)
- Renana Sabi
- Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel
| | - Tamir Tuller
- Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel
- The Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel
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16
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Ding W, Cheng J, Guo D, Mao L, Li J, Lu L, Zhang Y, Yang J, Jiang H. Engineering the 5' UTR-Mediated Regulation of Protein Abundance in Yeast Using Nucleotide Sequence Activity Relationships. ACS Synth Biol 2018; 7:2709-2714. [PMID: 30525473 DOI: 10.1021/acssynbio.8b00127] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The 5' untranslated region (5'UTR) plays a key role in post-transcriptional regulation, but interaction between nucleotides and directed evolution of 5'UTRs as synthetic regulatory elements remain unclear. By constructing a library of synthesized random 5'UTRs of 24 nucleotides in Saccharomyces cerevisiae, we observed strong epistatic interactions among bases from different positions in the 5'UTR. Taking into account these base interactions, we constructed a mathematical model to predict protein abundance with a precision of R2 = 0.60. On the basis of this model, we developed an approach to engineer 5'UTRs according to nucleotide sequence activity relationships (NuSAR), in which 5'UTRs were engineered stepwise through repeated cycles of backbone design, directed screening, and model reconstruction. After three rounds of NuSAR, the predictive accuracy of our model was improved to R2 = 0.71, and a strong 5'UTR was obtained with 5-fold higher protein abundance than the starting 5'UTR. Our findings provide new insights into the mechanism of 5'UTR regulation and contribute to a new translational elements engineering approach in synthetic biology.
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Affiliation(s)
- Wentao Ding
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
- Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Jian Cheng
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
| | - Dan Guo
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
| | - Ling Mao
- College of Biology and Pharmaceutical Engineering, Wuhan Polytechnic University, Wuhan 430023, China
| | - Jingwei Li
- Laboratory of Mathematics for Nonlinear Science, Shanghai Key Laboratory for Contemporary Applied Mathematics, Centre for Computational Systems Biology, School of Mathematical Sciences, Fudan University, Shanghai 200433, China
| | - Lina Lu
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
| | - Yunxin Zhang
- Laboratory of Mathematics for Nonlinear Science, Shanghai Key Laboratory for Contemporary Applied Mathematics, Centre for Computational Systems Biology, School of Mathematical Sciences, Fudan University, Shanghai 200433, China
| | - Jiangke Yang
- College of Biology and Pharmaceutical Engineering, Wuhan Polytechnic University, Wuhan 430023, China
| | - Huifeng Jiang
- Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
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17
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Zheng B, Ma X, Wang N, Ding T, Guo L, Zhang X, Yang Y, Li C, Huo YX. Utilization of rare codon-rich markers for screening amino acid overproducers. Nat Commun 2018; 9:3616. [PMID: 30190534 PMCID: PMC6127279 DOI: 10.1038/s41467-018-05830-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2017] [Accepted: 07/27/2018] [Indexed: 11/24/2022] Open
Abstract
The translation of rare codons relies on their corresponding rare tRNAs, which could not be fully charged under amino acid starvation. Theoretically, disrupted or retarded translation caused by the lack of charged rare tRNAs can be partially restored by feeding or intracellular synthesis of the corresponding amino acids. Inspired by this assumption, we develop a screening or selection system for obtaining overproducers of a target amino acid by replacing its common codons with the corresponding synonymous rare alternative in the coding sequence of selected reporter proteins or antibiotic-resistant markers. Results show that integration of rare codons can inhibit gene translations in a frequency-dependent manner. As a proof-of-concept, Escherichia coli strains overproducing L-leucine, L-arginine or L-serine are successfully selected from random mutation libraries. The system is also applied to Corynebacterium glutamicum to screen out L-arginine overproducers. This strategy sheds new light on obtaining and understanding amino acid overproduction strains.
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Affiliation(s)
- Bo Zheng
- School of Life Science, Beijing Institute of Technology, No. 5 South Zhongguancun Street, 100081, Beijing, China
| | - Xiaoyan Ma
- School of Life Science, Beijing Institute of Technology, No. 5 South Zhongguancun Street, 100081, Beijing, China
| | - Ning Wang
- School of Life Science, Beijing Institute of Technology, No. 5 South Zhongguancun Street, 100081, Beijing, China
| | - Tingting Ding
- School of Life Science, Beijing Institute of Technology, No. 5 South Zhongguancun Street, 100081, Beijing, China
| | - Liwei Guo
- School of Life Science, Beijing Institute of Technology, No. 5 South Zhongguancun Street, 100081, Beijing, China
- UCLA Institute of Advancement (Suzhou), 10 Yueliangwan Road, Suzhou Industrial Park, 215123, Suzhou, China
| | - Xiaorong Zhang
- Institute of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Chaoyang District, 100101, Beijing, China
| | - Yu Yang
- School of Life Science, Beijing Institute of Technology, No. 5 South Zhongguancun Street, 100081, Beijing, China
| | - Chun Li
- School of Chemistry and Chemical Engineering, Beijing Institute of Technology, No. 5 South Zhongguancun Street, 100081, Beijing, China
| | - Yi-Xin Huo
- School of Life Science, Beijing Institute of Technology, No. 5 South Zhongguancun Street, 100081, Beijing, China.
- UCLA Institute of Advancement (Suzhou), 10 Yueliangwan Road, Suzhou Industrial Park, 215123, Suzhou, China.
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18
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Torrent M, Chalancon G, de Groot NS, Wuster A, Madan Babu M. Cells alter their tRNA abundance to selectively regulate protein synthesis during stress conditions. Sci Signal 2018; 11:11/546/eaat6409. [PMID: 30181241 PMCID: PMC6130803 DOI: 10.1126/scisignal.aat6409] [Citation(s) in RCA: 147] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Decoding the information in mRNA during protein synthesis relies on tRNA adaptors, the abundance of which can affect the decoding rate and translation efficiency. To determine whether cells alter tRNA abundance to selectively regulate protein expression, we quantified changes in the abundance of individual tRNAs at different time points in response to diverse stress conditions in Saccharomyces cerevisiae. We found that the tRNA pool was dynamic and rearranged in a manner that facilitated selective translation of stress-related transcripts. Through genomic analysis of multiple data sets, stochastic simulations, and experiments with designed sequences of proteins with identical amino acids but altered codon usage, we showed that changes in tRNA abundance affected protein expression independently of factors such as mRNA abundance. We suggest that cells alter their tRNA abundance to selectively affect the translation rates of specific transcripts to increase the amounts of required proteins under diverse stress conditions.
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Affiliation(s)
- Marc Torrent
- Laboratory of Molecular Biology, Medical Research Council, Francis Crick Avenue, Cambridge CB2 0QH, UK. .,Systems Biology of Infection Lab, Department of Biochemistry and Molecular Biology, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
| | - Guilhem Chalancon
- Laboratory of Molecular Biology, Medical Research Council, Francis Crick Avenue, Cambridge CB2 0QH, UK
| | - Natalia S de Groot
- Laboratory of Molecular Biology, Medical Research Council, Francis Crick Avenue, Cambridge CB2 0QH, UK
| | - Arthur Wuster
- Laboratory of Molecular Biology, Medical Research Council, Francis Crick Avenue, Cambridge CB2 0QH, UK
| | - M Madan Babu
- Laboratory of Molecular Biology, Medical Research Council, Francis Crick Avenue, Cambridge CB2 0QH, UK.
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19
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Mignon C, Mariano N, Stadthagen G, Lugari A, Lagoutte P, Donnat S, Chenavas S, Perot C, Sodoyer R, Werle B. Codon harmonization - going beyond the speed limit for protein expression. FEBS Lett 2018; 592:1554-1564. [PMID: 29624661 DOI: 10.1002/1873-3468.13046] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2017] [Revised: 02/26/2018] [Accepted: 03/09/2018] [Indexed: 12/14/2022]
Abstract
Codon usage distribution has been soundly used by nature to fine tune protein biogenesis. Alteration of the mRNA structure or sequential scheduling of codons can profoundly affect translation, thus altering protein yield, functionality, solubility, and proper folding. Building on these observations, here, we present an evaluation of different recently designed algorithms of sequence adaptation based on Codon Adaptation Index (CAI) profiling. The first algorithm globally harmonizes synonymous codons in the original sequence in full respect to the heterologous expression host codon usage. The second recodes the sequence in accordance with the native sequence CAI profile. Our data, generated on three model proteins, highlights the importance to consider gene recoding as a parameter itself for recombinant protein expression improvement.
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Affiliation(s)
- Charlotte Mignon
- Protein and Expression System Engineering Unit, BIOASTER, Lyon, France
| | - Natacha Mariano
- Protein and Expression System Engineering Unit, BIOASTER, Lyon, France
| | | | - Adrien Lugari
- Protein and Expression System Engineering Unit, BIOASTER, Lyon, France
| | | | - Stéphanie Donnat
- Protein and Expression System Engineering Unit, BIOASTER, Lyon, France
| | | | | | | | - Bettina Werle
- Protein and Expression System Engineering Unit, BIOASTER, Lyon, France
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20
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Weiner I, Atar S, Schweitzer S, Eilenberg H, Feldman Y, Avitan M, Blau M, Danon A, Tuller T, Yacoby I. Enhancing heterologous expression in Chlamydomonas reinhardtii by transcript sequence optimization. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2018; 94:22-31. [PMID: 29383789 DOI: 10.1111/tpj.13836] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Revised: 12/22/2017] [Accepted: 01/04/2018] [Indexed: 05/11/2023]
Abstract
Various species of microalgae have recently emerged as promising host-organisms for use in biotechnology industries due to their unique properties. These include efficient conversion of sunlight into organic compounds, the ability to grow in extreme conditions and the occurrence of numerous post-translational modification pathways. However, the inability to obtain high levels of nuclear heterologous gene expression in microalgae hinders the development of the entire field. To overcome this limitation, we analyzed different sequence optimization algorithms while studying the effect of transcript sequence features on heterologous expression in the model microalga Chlamydomonas reinhardtii, whose genome consists of rare features such as a high GC content. Based on the analysis of genomic data, we created eight unique sequences coding for a synthetic ferredoxin-hydrogenase enzyme, used here as a reporter gene. Following in silico design, these synthetic genes were transformed into the C. reinhardtii nucleus, after which gene expression levels were measured. The empirical data, measured in vivo show a discrepancy of up to 65-fold between the different constructs. In this work we demonstrate how the combination of computational methods and our empirical results enable us to learn about the way gene expression is encoded in the C. reinhardtii transcripts. We describe the deleterious effect on overall expression of codons encoding for splicing signals. Subsequently, our analysis shows that utilization of a frequent subset of preferred codons results in elevated transcript levels, and that mRNA folding energy in the vicinity of translation initiation significantly affects gene expression.
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Affiliation(s)
- Iddo Weiner
- The George S. Wise Faculty of Life Sciences, School of Plant Sciences and Food Security, Tel Aviv University, Ramat Aviv, Tel Aviv, 69978, Israel
- Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv University, Tel Aviv, 6997801, Israel
| | - Shimshi Atar
- Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv University, Tel Aviv, 6997801, Israel
| | - Shira Schweitzer
- The George S. Wise Faculty of Life Sciences, School of Plant Sciences and Food Security, Tel Aviv University, Ramat Aviv, Tel Aviv, 69978, Israel
| | - Haviva Eilenberg
- The George S. Wise Faculty of Life Sciences, School of Plant Sciences and Food Security, Tel Aviv University, Ramat Aviv, Tel Aviv, 69978, Israel
| | - Yael Feldman
- The George S. Wise Faculty of Life Sciences, School of Plant Sciences and Food Security, Tel Aviv University, Ramat Aviv, Tel Aviv, 69978, Israel
| | - Meital Avitan
- The George S. Wise Faculty of Life Sciences, School of Plant Sciences and Food Security, Tel Aviv University, Ramat Aviv, Tel Aviv, 69978, Israel
- Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv University, Tel Aviv, 6997801, Israel
| | - Mor Blau
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Avihai Danon
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel
| | - Tamir Tuller
- Department of Biomedical Engineering, The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv University, Tel Aviv, 6997801, Israel
- The Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, 6997801, Israel
| | - Iftach Yacoby
- The George S. Wise Faculty of Life Sciences, School of Plant Sciences and Food Security, Tel Aviv University, Ramat Aviv, Tel Aviv, 69978, Israel
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21
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Churkin A, Retwitzer MD, Reinharz V, Ponty Y, Waldispühl J, Barash D. Design of RNAs: comparing programs for inverse RNA folding. Brief Bioinform 2018; 19:350-358. [PMID: 28049135 PMCID: PMC6018860 DOI: 10.1093/bib/bbw120] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Computational programs for predicting RNA sequences with desired folding properties have been extensively developed and expanded in the past several years. Given a secondary structure, these programs aim to predict sequences that fold into a target minimum free energy secondary structure, while considering various constraints. This procedure is called inverse RNA folding. Inverse RNA folding has been traditionally used to design optimized RNAs with favorable properties, an application that is expected to grow considerably in the future in light of advances in the expanding new fields of synthetic biology and RNA nanostructures. Moreover, it was recently demonstrated that inverse RNA folding can successfully be used as a valuable preprocessing step in computational detection of novel noncoding RNAs. This review describes the most popular freeware programs that have been developed for such purposes, starting from RNAinverse that was devised when formulating the inverse RNA folding problem. The most recently published ones that consider RNA secondary structure as input are antaRNA, RNAiFold and incaRNAfbinv, each having different features that could be beneficial to specific biological problems in practice. The various programs also use distinct approaches, ranging from ant colony optimization to constraint programming, in addition to adaptive walk, simulated annealing and Boltzmann sampling. This review compares between the various programs and provides a simple description of the various possibilities that would benefit practitioners in selecting the most suitable program. It is geared for specific tasks requiring RNA design based on input secondary structure, with an outlook toward the future of RNA design programs.
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Affiliation(s)
- Alexander Churkin
- Shamoon College of Engineering and Physics Department at Ben-Gurion University, Beer-Sheva, Israel
| | | | - Vladimir Reinharz
- Department of Computer Science, Ben-Gurion University, Beer-Sheva, Israel
- School of Computer Science, McGill University, Montréal QC, Canada
| | - Yann Ponty
- Laboratoire d’informatique, École Polytechnique, Palaiseau, France
| | | | - Danny Barash
- Department of Computer Science, Ben-Gurion University, Beer-Sheva, Israel
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22
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Diament A, Feldman A, Schochet E, Kupiec M, Arava Y, Tuller T. The extent of ribosome queuing in budding yeast. PLoS Comput Biol 2018; 14:e1005951. [PMID: 29377894 PMCID: PMC5805374 DOI: 10.1371/journal.pcbi.1005951] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2017] [Revised: 02/08/2018] [Accepted: 01/05/2018] [Indexed: 11/18/2022] Open
Abstract
Ribosome queuing is a fundamental phenomenon suggested to be related to topics such as genome evolution, synthetic biology, gene expression regulation, intracellular biophysics, and more. However, this phenomenon hasn't been quantified yet at a genomic level. Nevertheless, methodologies for studying translation (e.g. ribosome footprints) are usually calibrated to capture only single ribosome protected footprints (mRPFs) and thus limited in their ability to detect ribosome queuing. On the other hand, most of the models in the field assume and analyze a certain level of queuing. Here we present an experimental-computational approach for studying ribosome queuing based on sequencing of RNA footprints extracted from pairs of ribosomes (dRPFs) using a modified ribosome profiling protocol. We combine our approach with traditional ribosome profiling to generate a detailed profile of ribosome traffic. The data are analyzed using computational models of translation dynamics. The approach was implemented on the Saccharomyces cerevisiae transcriptome. Our data shows that ribosome queuing is more frequent than previously thought: the measured ratio of ribosomes within dRPFs to mRPFs is 0.2–0.35, suggesting that at least one to five translating ribosomes is in a traffic jam; these queued ribosomes cannot be captured by traditional methods. We found that specific regions are enriched with queued ribosomes, such as the 5’-end of ORFs, and regions upstream to mRPF peaks, among others. While queuing is related to higher density of ribosomes on the transcript (characteristic of highly translated genes), we report cases where traffic jams are relatively more severe in lowly expressed genes and possibly even selected for. In addition, our analysis demonstrates that higher adaptation of the coding region to the intracellular tRNA levels is associated with lower queuing levels. Our analysis also suggests that the Saccharomyces cerevisiae transcriptome undergoes selection for eliminating traffic jams. Thus, our proposed approach is an essential tool for high resolution analysis of ribosome traffic during mRNA translation and understanding its evolution. During translation, multiple ribosomes may translate the same mRNA. The density of ribosomal traffic across the transcript poses several open questions, such as how often a ribosome’s path is blocked by a second ribosome, do queues of multiple ribosomes typically form on mRNAs and what is their effect on the overall translation rate of an mRNA. However, this phenomenon hasn't been quantified yet at a genomic level. Nevertheless, methodologies for monitoring translation are limited in their ability to detect ribosome queuing. On the other hand, most of the models in the field assume and analyze a certain level of queuing. Here we present an experimental-computational approach for studying ribosome queuing based on sequencing of RNA footprints extracted from pairs of adjacent translating ribosomes, and a computational model of translation dynamics. Our data shows that ribosome queuing in Saccharomyces cerevisiae is more frequent than previously thought, suggesting that at least one to five translating ribosomes is in a traffic jam; these queued ribosomes cannot be captured by traditional methods. Our analysis also suggests that the S. cerevisiae transcriptome undergoes selection for eliminating traffic jams, while specific regions and genes may possibly be under selection for increased queuing.
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Affiliation(s)
- Alon Diament
- Biomedical Engineering Dept., Tel Aviv University, Tel Aviv, Israel
| | - Anna Feldman
- Biomedical Engineering Dept., Tel Aviv University, Tel Aviv, Israel
| | - Elisheva Schochet
- The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
| | - Martin Kupiec
- Dept. of Molecular Microbiology and Biotechnology, Tel Aviv University, Tel Aviv, Israel
| | - Yoav Arava
- Biology Dept., Technion-Israel Institute of Technology, Haifa, Israel
| | - Tamir Tuller
- Biomedical Engineering Dept., Tel Aviv University, Tel Aviv, Israel
- The Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- * E-mail:
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23
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Abstract
The two major steps of gene expression are transcription and translation. While hundreds of studies regarding the effect of sequence features on the translation elongation process have been published, very few connect sequence features to the transcription elongation rate. We suggest, for the first time, that short transcript sub-sequences have a typical effect on RNA polymerase (RNAP) speed: we show that nucleotide 5-mers tend to have typical RNAP speed (or transcription rate), which is consistent along different parts of genes and among different groups of genes with high correlation. We also demonstrate that relative RNAP speed correlates with mRNA levels of endogenous and heterologous genes. Furthermore, we show that the estimated transcription and translation elongation rates correlate in endogenous genes. Finally, we demonstrate that our results are consistent for different high resolution experimental measurements of RNAP densities. These results suggest for the first time that transcription elongation is partly encoded in the transcript, affected by the codon-usage, and optimized by evolution with a significant effect on gene expression and organismal fitness.
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Affiliation(s)
- Eyal Cohen
- a Balavatnick School of Computer Science , Tel Aviv University , Tel Aviv , Israel
| | - Zohar Zafrir
- b Department of Biomedical Engineering , Tel Aviv University , Tel Aviv , Israel
| | - Tamir Tuller
- b Department of Biomedical Engineering , Tel Aviv University , Tel Aviv , Israel.,c Sagol School of Neuroscience , Tel Aviv University , Tel Aviv , Israel
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24
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Generation of an arginine-tRNA-adapted Saccharomyces cerevisiae strain for effective heterologous protein expression. Curr Genet 2017; 64:589-598. [PMID: 29098364 DOI: 10.1007/s00294-017-0774-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Revised: 09/30/2017] [Accepted: 10/27/2017] [Indexed: 10/18/2022]
Abstract
The tRNA population reflects the codon bias of the organism and affects the translation of heterologous target mRNA molecules. In this study, Saccharomyces cerevisiae strains with modified levels of rare tRNA were engineered, that allowed efficient generation of recombinant proteins with unfavorable codon usage. We established a novel synthetic tRNA expression cassette and verified functional nonsense suppressor tRNAGlnSCUA generation in a stop codon read-through assay with a modified β-galactosidase reporter gene. Correlation between altered tRNA and protein level was shown by survival of copper sensitive S. cerevisiae cells in the presence of copper ions by an increased transcription of tRNAArgCCG molecules, recognizing rare codons in a modified CUP1 gene. Genome integration of tRNA expression cassette led to the generation of arginine-tRNA-adapted S. cerevisiae strains, which showed elevated tRNA levels (tRNAArgCCG, tRNAArgGCG and tRNAArgUCG) pairing to rare codons. The modified strain MNY3 revealed a considerably improved monitoring of protein-protein interaction from Aspergillus fumigatus bait and prey sequences in yeast two-hybrid experiments. In future, this principle to overcome limited recombinant protein expression by tRNA adaption of expression strains instead of codon adaption might provide new designer yeast cells for an efficient protein production and for improved genome-wide protein-protein interaction analyses.
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25
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Zarai Y, Margaliot M, Tuller T. Optimal Down Regulation of mRNA Translation. Sci Rep 2017; 7:41243. [PMID: 28120903 PMCID: PMC5264618 DOI: 10.1038/srep41243] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2016] [Accepted: 12/19/2016] [Indexed: 01/02/2023] Open
Abstract
Down regulation of mRNA translation is an important problem in various bio-medical domains ranging from developing effective medicines for tumors and for viral diseases to developing attenuated virus strains that can be used for vaccination. Here, we study the problem of down regulation of mRNA translation using a mathematical model called the ribosome flow model (RFM). In the RFM, the mRNA molecule is modeled as a chain of n sites. The flow of ribosomes between consecutive sites is regulated by n + 1 transition rates. Given a set of feasible transition rates, that models the outcome of all possible mutations, we consider the problem of maximally down regulating protein production by altering the rates within this set of feasible rates. Under certain conditions on the feasible set, we show that an optimal solution can be determined efficiently. We also rigorously analyze two special cases of the down regulation optimization problem. Our results suggest that one must focus on the position along the mRNA molecule where the transition rate has the strongest effect on the protein production rate. However, this rate is not necessarily the slowest transition rate along the mRNA molecule. We discuss some of the biological implications of these results.
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Affiliation(s)
- Yoram Zarai
- School of Electrical Engineering, Tel-Aviv University, Tel-Aviv 69978, Israel
| | - Michael Margaliot
- School of Electrical Engineering, Tel-Aviv University, Tel-Aviv 69978, Israel.,Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv 69978, Israel
| | - Tamir Tuller
- Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv 69978, Israel.,Dept. of Biomedical Engineering, Tel-Aviv University, Tel-Aviv 69978, Israel
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26
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Ribosome profiling-guided depletion of an mRNA increases cell growth rate and protein secretion. Sci Rep 2017; 7:40388. [PMID: 28091612 PMCID: PMC5238448 DOI: 10.1038/srep40388] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2016] [Accepted: 12/05/2016] [Indexed: 12/22/2022] Open
Abstract
Recombinant protein production coopts the host cell machinery to provide high protein yields of industrial enzymes or biotherapeutics. However, since protein translation is energetically expensive and tightly controlled, it is unclear if highly expressed recombinant genes are translated as efficiently as host genes. Furthermore, it is unclear how the high expression impacts global translation. Here, we present the first genome-wide view of protein translation in an IgG-producing CHO cell line, measured with ribosome profiling. Through this we found that our recombinant mRNAs were translated as efficiently as the host cell transcriptome, and sequestered up to 15% of the total ribosome occupancy. During cell culture, changes in recombinant mRNA translation were consistent with changes in transcription, demonstrating that transcript levels influence specific productivity. Using this information, we identified the unnecessary resistance marker NeoR to be a highly transcribed and translated gene. Through siRNA knock-down of NeoR, we improved the production- and growth capacity of the host cell. Thus, ribosomal profiling provides valuable insights into translation in CHO cells and can guide efforts to enhance protein production.
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27
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Raveh A, Margaliot M, Sontag ED, Tuller T. A model for competition for ribosomes in the cell. J R Soc Interface 2016; 13:rsif.2015.1062. [PMID: 26962028 DOI: 10.1098/rsif.2015.1062] [Citation(s) in RCA: 79] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
A single mammalian cell includes an order of 10(4)-10(5) mRNA molecules and as many as 10(5)-10(6) ribosomes. Large-scale simultaneous mRNA translation induces correlations between the mRNA molecules, as they all compete for the finite pool of available ribosomes. This has important implications for the cell's functioning and evolution. Developing a better understanding of the intricate correlations between these simultaneous processes, rather than focusing on the translation of a single isolated transcript, should help in gaining a better understanding of mRNA translation regulation and the way elongation rates affect organismal fitness. A model of simultaneous translation is specifically important when dealing with highly expressed genes, as these consume more resources. In addition, such a model can lead to more accurate predictions that are needed in the interconnection of translational modules in synthetic biology. We develop and analyse a general dynamical model for large-scale simultaneous mRNA translation and competition for ribosomes. This is based on combining several ribosome flow models (RFMs) interconnected via a pool of free ribosomes. We use this model to explore the interactions between the various mRNA molecules and ribosomes at steady state. We show that the compound system always converges to a steady state and that it always entrains or phase locks to periodically time-varying transition rates in any of the mRNA molecules. We then study the effect of changing the transition rates in one mRNA molecule on the steady-state translation rates of the other mRNAs that results from the competition for ribosomes. We show that increasing any of the codon translation rates in a specific mRNA molecule yields a local effect, an increase in the translation rate of this mRNA, and also a global effect, the translation rates in the other mRNA molecules all increase or all decrease. These results suggest that the effect of codon decoding rates of endogenous and heterologous mRNAs on protein production is more complicated than previously thought. In addition, we show that increasing the length of an mRNA molecule decreases the production rate of all the mRNAs.
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Affiliation(s)
- Alon Raveh
- School of Electrical Engineering, Tel-Aviv University, Tel-Aviv 69978, Israel
| | - Michael Margaliot
- School of Electrical Engineering and the Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv 69978, Israel
| | - Eduardo D Sontag
- Department of Mathematics and the Center for Quantitative Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Tamir Tuller
- Department of Biomedical Engineering and the Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv 69978, Israel
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28
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Zur H, Tuller T. Predictive biophysical modeling and understanding of the dynamics of mRNA translation and its evolution. Nucleic Acids Res 2016; 44:9031-9049. [PMID: 27591251 PMCID: PMC5100582 DOI: 10.1093/nar/gkw764] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2016] [Accepted: 08/19/2016] [Indexed: 12/12/2022] Open
Abstract
mRNA translation is the fundamental process of decoding the information encoded in mRNA molecules by the ribosome for the synthesis of proteins. The centrality of this process in various biomedical disciplines such as cell biology, evolution and biotechnology, encouraged the development of dozens of mathematical and computational models of translation in recent years. These models aimed at capturing various biophysical aspects of the process. The objective of this review is to survey these models, focusing on those based and/or validated on real large-scale genomic data. We consider aspects such as the complexity of the models, the biophysical aspects they regard and the predictions they may provide. Furthermore, we survey the central systems biology discoveries reported on their basis. This review demonstrates the fundamental advantages of employing computational biophysical translation models in general, and discusses the relative advantages of the different approaches and the challenges in the field.
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Affiliation(s)
- Hadas Zur
- Department of Biomedical Engineering, the Engineering Faculty, Tel Aviv University, Tel-Aviv 69978, Israel
| | - Tamir Tuller
- Department of Biomedical Engineering, the Engineering Faculty, Tel Aviv University, Tel-Aviv 69978, Israel
- The Sagol School of Neuroscience, Tel Aviv University, Tel-Aviv 69978, Israel
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Zafrir Z, Zur H, Tuller T. Selection for reduced translation costs at the intronic 5' end in fungi. DNA Res 2016; 23:377-94. [PMID: 27260512 PMCID: PMC4991832 DOI: 10.1093/dnares/dsw019] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Accepted: 04/26/2016] [Indexed: 12/12/2022] Open
Abstract
It is generally believed that introns are not translated; therefore, the potential intronic features that may be related to the translation step (occurring after splicing) have yet to be thoroughly studied. Here, focusing on four fungi, we performed for the first time a comprehensive study aimed at characterizing how translation efficiency is encoded in introns and affects their evolution. By analysing their intronome we provide evidence of selection for STOP codons close to the intronic 5′ end, and show that the beginning of introns are selected for significantly high translation, presumably to reduce translation and metabolic costs in cases of non-spliced introns. Ribosomal profiling data analysis in Saccharomyces cerevisiae supports the conjecture that in this organism intron retention frequently occurs, introns are partially translated, and their translation efficiency affects organismal fitness. We show that the reported results are more significant in highly translated and highly spliced genes, but are not associated only with genes with a specific function. We also discuss the potential relation of the reported signals to efficient nonsense-mediated decay due to splicing errors. These new discoveries are supported by population-genetics considerations. In addition, they are contributory steps towards a broader understanding of intron evolution and the effect of silent mutations on gene expression and organismal fitness.
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Affiliation(s)
- Zohar Zafrir
- Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel
| | - Hadas Zur
- Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel
| | - Tamir Tuller
- Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel The Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 69978, Israel
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Diament A, Tuller T. Estimation of ribosome profiling performance and reproducibility at various levels of resolution. Biol Direct 2016; 11:24. [PMID: 27160013 PMCID: PMC4862193 DOI: 10.1186/s13062-016-0127-4] [Citation(s) in RCA: 62] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2016] [Accepted: 04/29/2016] [Indexed: 01/23/2023] Open
Abstract
BACKGROUND Ribosome profiling (or Ribo-seq) is currently the most popular methodology for studying translation; it has been employed in recent years to decipher various fundamental gene expression regulation aspects. The main promise of the approach is its ability to detect ribosome densities over an entire transcriptome in high resolution of single codons. Indeed, dozens of ribo-seq studies have included results related to local ribosome densities in different parts of the transcript; nevertheless, the performance of Ribo-seq has yet to be quantitatively evaluated and reported in a large-scale multi-organismal and multi-protocol study of currently available datasets. RESULTS Here we provide the first objective evaluation of Ribo-seq at the resolution of a single nucleotide(s) using clear, interpretable measures, based on the analysis of 15 experiments, 6 organisms, and a total of 612, 961 transcripts. Our major conclusion is that the ability to infer signals of ribosomal densities at nucleotide scale is considerably lower than previously thought, as signals at this level are not reproduced well in experimental replicates. In addition, we provide various quantitative measures that connect the expected error rate with Ribo-seq analysis resolution. CONCLUSIONS The analysis of Ribo-seq data at the resolution of codons and nucleotides provides a challenging task, calls for task-specific statistical methods and further protocol improvements. We believe that our results are important for every researcher studying translation and specifically for researchers analyzing data generated by the Ribo-seq approach. REVIEWERS This article was reviewed by Dmitrij Frishman, Eugene Koonin and Frank Eisenhaber.
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Affiliation(s)
- Alon Diament
- Biomedical Engineering Department, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Tamir Tuller
- Biomedical Engineering Department, Tel Aviv University, Tel Aviv-Yafo, Israel. .,The Sagol School of Neuroscience, Tel Aviv University, Tel Aviv-Yafo, Israel.
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Fernandes A, Vinga S. Improving Protein Expression Prediction Using Extra Features and Ensemble Averaging. PLoS One 2016; 11:e0150369. [PMID: 26934190 PMCID: PMC4775025 DOI: 10.1371/journal.pone.0150369] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Accepted: 02/12/2016] [Indexed: 11/25/2022] Open
Abstract
The article focus is the improvement of machine learning models capable of predicting protein expression levels based on their codon encoding. Support vector regression (SVR) and partial least squares (PLS) were used to create the models. SVR yields predictions that surpass those of PLS. It is shown that it is possible to improve the models predictive ability by using two more input features, codon identification number and codon count, besides the already used codon bias and minimum free energy. In addition, applying ensemble averaging to the SVR or PLS models also improves the results even further. The present work motivates the test of different ensembles and features with the aim of improving the prediction models whose correlation coefficients are still far from perfect. These results are relevant for the optimization of codon usage and enhancement of protein expression levels in synthetic biology problems.
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Affiliation(s)
- Armando Fernandes
- IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal
- * E-mail:
| | - Susana Vinga
- IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal
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Abstract
Using the dynamic mean-field approximation of the totally asymmetric simple exclusion process (TASEP), we investigate the effect of small changes in the initiation, elongation, and termination rates along the mRNA strand on the steady-state protein translation rate. We show that the sensitivity of mRNA translation is equal to the sensitivity of the maximal eigenvalue of a symmetric, nonnegative, tridiagonal, and irreducible matrix. This leads to new analytical results as well as efficient numerical schemes that are applicable for large-scale models. Our results show that in the usual endogenous case, when initiation is more rate-limiting than elongation, the sensitivity of the translation rate to small mutations rapidly increases towards the 5′ end of the ORF. When the initiation rate is high, as may be the case for highly expressed and/or heterologous optimized genes, the maximal sensitivity is with respect to the elongation rates at the middle of the mRNA strand. We also show that the maximal possible effect of a small increase/decrease in any of the rates along the mRNA is an increase/decrease of the same magnitude in the translation rate. These results are in agreement with previous molecular evolutionary and synthetic biology experimental studies.
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