1
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Irshad IU, Sharma AK. Decoding stoichiometric protein synthesis in E. coli through translation rate parameters. BIOPHYSICAL REPORTS 2023; 3:100131. [PMID: 37789867 PMCID: PMC10542608 DOI: 10.1016/j.bpr.2023.100131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 09/11/2023] [Indexed: 10/05/2023]
Abstract
E. coli is one of the most widely used organisms for understanding the principles of cellular and molecular genetics. However, we are yet to understand the origin of several experimental observations related to the regulation of gene expression in E. coli. One of the prominent examples in this context is the proportional synthesis in multiprotein complexes where all of their obligate subunits are produced in proportion to their stoichiometry. In this work, by combining the next-generation sequencing data with the stochastic simulations of protein synthesis, we explain the origin of proportional protein synthesis in multicomponent complexes. We find that the estimated initiation rates for the translation of all subunits in those complexes are proportional to their stoichiometry. This constraint on protein synthesis kinetics enforces proportional protein synthesis without requiring any feedback mechanism. We also find that the translation initiation rates in E. coli are influenced by the coding sequence length and the enrichment of A and C nucleotides near the start codon. Thus, this study rationalizes the role of conserved and nonrandom features of genes in regulating the translation kinetics and unravels a key principle of the regulation of protein synthesis.
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Affiliation(s)
| | - Ajeet K. Sharma
- Department of Physics, Indian Institute of Technology Jammu, Jammu, India
- Department of Biosciences and Bioengineering, Indian Institute of Technology Jammu, Jammu, India
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2
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Proteome allocations change linearly with the specific growth rate of Saccharomyces cerevisiae under glucose limitation. Nat Commun 2022; 13:2819. [PMID: 35595797 PMCID: PMC9122918 DOI: 10.1038/s41467-022-30513-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 04/28/2022] [Indexed: 01/21/2023] Open
Abstract
Saccharomyces cerevisiae is a widely used cell factory; therefore, it is important to understand how it organizes key functional parts when cultured under different conditions. Here, we perform a multiomics analysis of S. cerevisiae by culturing the strain with a wide range of specific growth rates using glucose as the sole limiting nutrient. Under these different conditions, we measure the absolute transcriptome, the absolute proteome, the phosphoproteome, and the metabolome. Most functional protein groups show a linear dependence on the specific growth rate. Proteins engaged in translation show a perfect linear increase with the specific growth rate, while glycolysis and chaperone proteins show a linear decrease under respiratory conditions. Glycolytic enzymes and chaperones, however, show decreased phosphorylation with increasing specific growth rates; at the same time, an overall increased flux through these pathways is observed. Further analysis show that even though mRNA levels do not correlate with protein levels for all individual genes, the transcriptome level of functional groups correlates very well with its corresponding proteome. Finally, using enzyme-constrained genome-scale modeling, we find that enzyme usage plays an important role in controlling flux in amino acid biosynthesis. Understanding how yeast organizes its functional proteome is a fundamental task in systems biology. Here, the authors conduct a multiomics analysis on yeast cells cultured with different growth rates, identifying a linear dependence of the functional proteome on the growth rate.
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3
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Joiret M, Kerff F, Rapino F, Close P, Geris L. Ribosome exit tunnel electrostatics. Phys Rev E 2022; 105:014409. [PMID: 35193250 DOI: 10.1103/physreve.105.014409] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 12/08/2021] [Indexed: 06/14/2023]
Abstract
The impact of ribosome exit tunnel electrostatics on the protein elongation rate or on forces acting upon the nascent polypeptide chain are currently not fully elucidated. In the past, researchers have measured the electrostatic potential inside the ribosome polypeptide exit tunnel at a limited number of spatial points, at least in rabbit reticulocytes. Here we present a basic electrostatic model of the exit tunnel of the ribosome, providing a quantitative physical description of the tunnel interaction with the nascent proteins at all centro-axial points inside the tunnel. We show that a strong electrostatic screening is due to water molecules (not mobile ions) attracted to the ribosomal nucleic acid phosphate moieties buried in the immediate vicinity of the tunnel wall. We also show how the tunnel wall components and local ribosomal protein protrusions impact on the electrostatic potential profile and impede charged amino acid residues from progressing through the tunnel, affecting the elongation rate in a range of -40% to +85% when compared to the average elongation rate. The time spent by the ribosome to decode the genetic encrypted message is constrained accordingly. We quantitatively derive, at single-residue resolution, the axial forces acting on the nascent peptide from its particular sequence embedded in the tunnel. The model sheds light on how the experimental data point measurements of the potential are linked to the local structural chemistry of the inner wall, shape, and size of the tunnel. The model consistently connects experimental observations coming from different fields in molecular biology, x-ray crystallography, physical chemistry, biomechanics, and synthetic and multiomics biology. Our model should be a valuable tool to gain insight into protein synthesis dynamics, translational control, and the role of the ribosome's mechanochemistry in the cotranslational protein folding.
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Affiliation(s)
- Marc Joiret
- Biomechanics Research Unit, GIGA In Silico Medicine, Liège University, CHU-B34(+5) 1 Avenue de l'Hôpital, 4000 Liège, Belgium
| | - Frederic Kerff
- UR InBios, Centre d'Ingénierie des Protéines, Bât B6a, Allée du 6 Août, 19, B-4000 Liège, Belgium
| | - Francesca Rapino
- Cancer Signaling, GIGA Stem Cells, CHU-B34(+2) 1 Avenue de l'Hôpital, B-4000 Liège, Belgium
| | - Pierre Close
- Cancer Signaling, GIGA Stem Cells, CHU-B34(+2) 1 Avenue de l'Hôpital, B-4000 Liège, Belgium
| | - Liesbet Geris
- Biomechanics Research Unit, GIGA In Silico Medicine, Liège University, CHU-B34(+5) 1 Avenue de l'Hôpital, 4000 Liège, Belgium
- Skeletal Biology & Engineering Research Center, KU Leuven, ON I Herestraat 49 - box 813, 3000 Leuven, Belgium
- Biomechanics Section, KU Leuven, Celestijnenlaan 300C box 2419, B-3001 Heverlee, Belgium
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4
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Combinations of slow-translating codon clusters can increase mRNA half-life in Saccharomyces cerevisiae. Proc Natl Acad Sci U S A 2021; 118:2026362118. [PMID: 34911752 DOI: 10.1073/pnas.2026362118] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/18/2021] [Indexed: 11/18/2022] Open
Abstract
The presence of a single cluster of nonoptimal codons was found to decrease a transcript's half-life through the interaction of the ribosome-associated quality control machinery with stalled ribosomes in Saccharomyces cerevisiae The impact of multiple nonoptimal codon clusters on a transcript's half-life, however, is unknown. Using a kinetic model, we predict that inserting a second nonoptimal cluster near the 5' end can lead to synergistic effects that increase a messenger RNA's (mRNA's) half-life in S. cerevisiae Specifically, the 5' end cluster suppresses the formation of ribosome queues, reducing the interaction of ribosome-associated quality control factors with stalled ribosomes. We experimentally validate this prediction by introducing two nonoptimal clusters into three different genes and find that their mRNA half-life increases up to fourfold. The model also predicts that in the presence of two clusters, the cluster closest to the 5' end is the primary determinant of mRNA half-life. These results suggest the "translational ramp," in which nonoptimal codons are located near the start codon and increase translational efficiency, may have the additional biological benefit of allowing downstream slow-codon clusters to be present without decreasing mRNA half-life. These results indicate that codon usage bias plays a more nuanced role in controlling cellular protein levels than previously thought.
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Yadav V, Ullah Irshad I, Kumar H, Sharma AK. Quantitative Modeling of Protein Synthesis Using Ribosome Profiling Data. Front Mol Biosci 2021; 8:688700. [PMID: 34262940 PMCID: PMC8274658 DOI: 10.3389/fmolb.2021.688700] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 05/25/2021] [Indexed: 12/12/2022] Open
Abstract
Quantitative prediction on protein synthesis requires accurate translation initiation and codon translation rates. Ribosome profiling data, which provide steady-state distribution of relative ribosome occupancies along a transcript, can be used to extract these rate parameters. Various methods have been developed in the past few years to measure translation-initiation and codon translation rates from ribosome profiling data. In the review, we provide a detailed analysis of the key methods employed to extract the translation rate parameters from ribosome profiling data. We further discuss how these approaches were used to decipher the role of various structural and sequence-based features of mRNA molecules in the regulation of gene expression. The utilization of these accurate rate parameters in computational modeling of protein synthesis may provide new insights into the kinetic control of the process of gene expression.
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Affiliation(s)
- Vandana Yadav
- Department of Physics, Indian Institute of Technology Madras, Chennai, India
| | | | - Hemant Kumar
- School of Basic Sciences, Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
| | - Ajeet K Sharma
- Department of Physics, Indian Institute of Technology Jammu, Jammu, India
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6
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Sharma AK. Translational autoregulation of RF2 protein in E. coli through programmed frameshifting. Phys Rev E 2021; 103:062412. [PMID: 34271674 DOI: 10.1103/physreve.103.062412] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 06/04/2021] [Indexed: 11/07/2022]
Abstract
Various feedback mechanisms regulate the expression of different genes to ensure the required protein levels inside a cell. In this paper, we develop a kinetic model for one such mechanism that autoregulates RF2 protein synthesis in E. coli through programmed frameshifting. The model finds that the programmed frameshifting autoregulates RF2 protein synthesis by two independent mechanisms. First, it increases the rate of RF2 synthesis from each mRNA transcript at low RF2 concentration. Second, programmed frameshifting can dramatically increase the lifetime of RF2 transcripts when RF2 protein levels are lower than a threshold. This sharp increase in mRNA lifetime is caused by a first-order phase transition from a low to a high ribosome density on an RF2 transcript. The high ribosome density prevents the transcript's degradation by shielding it from nucleases, which increases its average lifetime and hence RF2 protein levels. Our study identifies this quality control mechanism that regulates the cellular protein levels by breaking the hierarchy of processes involved in gene expression.
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Affiliation(s)
- Ajeet K Sharma
- Department of Physics, Indian Institute of Technology, Jammu 181221, India
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7
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Rapino F, Zhou Z, Roncero Sanchez AM, Joiret M, Seca C, El Hachem N, Valenti G, Latini S, Shostak K, Geris L, Li P, Huang G, Mazzucchelli G, Baiwir D, Desmet CJ, Chariot A, Georges M, Close P. Wobble tRNA modification and hydrophilic amino acid patterns dictate protein fate. Nat Commun 2021; 12:2170. [PMID: 33859181 PMCID: PMC8050329 DOI: 10.1038/s41467-021-22254-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 03/05/2021] [Indexed: 02/07/2023] Open
Abstract
Regulation of mRNA translation elongation impacts nascent protein synthesis and integrity and plays a critical role in disease establishment. Here, we investigate features linking regulation of codon-dependent translation elongation to protein expression and homeostasis. Using knockdown models of enzymes that catalyze the mcm5s2 wobble uridine tRNA modification (U34-enzymes), we show that gene codon content is necessary but not sufficient to predict protein fate. While translation defects upon perturbation of U34-enzymes are strictly dependent on codon content, the consequences on protein output are determined by other features. Specific hydrophilic motifs cause protein aggregation and degradation upon codon-dependent translation elongation defects. Accordingly, the combination of codon content and the presence of hydrophilic motifs define the proteome whose maintenance relies on U34-tRNA modification. Together, these results uncover the mechanism linking wobble tRNA modification to mRNA translation and aggregation to maintain proteome homeostasis.
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Affiliation(s)
- Francesca Rapino
- Laboratory of Cancer Signaling, University of Liège, Liège, Belgium.
- GIGA-Institute, University of Liège, Liège, Belgium.
- University of Liège, Liège, Belgium.
- Department of Radiation Oncology (Maastro), GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre+, Maastricht, The Netherlands.
| | - Zhaoli Zhou
- Laboratory of Cancer Signaling, University of Liège, Liège, Belgium
- GIGA-Institute, University of Liège, Liège, Belgium
- University of Liège, Liège, Belgium
- Shanghai Key Laboratory of Molecular Imaging, Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Ana Maria Roncero Sanchez
- Laboratory of Cancer Signaling, University of Liège, Liège, Belgium
- GIGA-Institute, University of Liège, Liège, Belgium
- University of Liège, Liège, Belgium
| | - Marc Joiret
- Laboratory of Cancer Signaling, University of Liège, Liège, Belgium
- GIGA-Institute, University of Liège, Liège, Belgium
- University of Liège, Liège, Belgium
- Biomechanics Research Unit, University of Liège, Liège, Belgium
| | - Christian Seca
- Laboratory of Cancer Signaling, University of Liège, Liège, Belgium
- GIGA-Institute, University of Liège, Liège, Belgium
- University of Liège, Liège, Belgium
| | - Najla El Hachem
- Laboratory of Cancer Signaling, University of Liège, Liège, Belgium
- GIGA-Institute, University of Liège, Liège, Belgium
- University of Liège, Liège, Belgium
| | - Gianluca Valenti
- University of Liège, Liège, Belgium
- Unité de Recherche Transitions, University of Liège, Liège, Belgium
| | - Sara Latini
- Laboratory of Cancer Signaling, University of Liège, Liège, Belgium
- GIGA-Institute, University of Liège, Liège, Belgium
- University of Liège, Liège, Belgium
| | - Kateryna Shostak
- GIGA-Institute, University of Liège, Liège, Belgium
- University of Liège, Liège, Belgium
- Laboratory of Medical Chemistry, University of Liège, Liège, Belgium
| | - Liesbet Geris
- GIGA-Institute, University of Liège, Liège, Belgium
- University of Liège, Liège, Belgium
- Biomechanics Research Unit, University of Liège, Liège, Belgium
| | - Ping Li
- Shanghai Key Laboratory of Molecular Imaging, Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Gang Huang
- Shanghai Key Laboratory of Molecular Imaging, Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Gabriel Mazzucchelli
- GIGA-Institute, University of Liège, Liège, Belgium
- University of Liège, Liège, Belgium
- Mass Spectrometry Laboratory, System Biology and Chemical Biology, University of Liège, Liège, Belgium
| | - Dominique Baiwir
- GIGA-Institute, University of Liège, Liège, Belgium
- University of Liège, Liège, Belgium
- Mass Spectrometry Laboratory, System Biology and Chemical Biology, University of Liège, Liège, Belgium
| | - Christophe J Desmet
- GIGA-Institute, University of Liège, Liège, Belgium
- University of Liège, Liège, Belgium
- Laboratory of Cellular and Molecular Immunology, University of Liège, Liège, Belgium
- Faculty of Veterinary Medicine, University of Liege, Liege, Belgium
| | - Alain Chariot
- GIGA-Institute, University of Liège, Liège, Belgium
- University of Liège, Liège, Belgium
- Laboratory of Medical Chemistry, University of Liège, Liège, Belgium
- WELBIO, University of Liege, Liege, Belgium
| | - Michel Georges
- GIGA-Institute, University of Liège, Liège, Belgium
- University of Liège, Liège, Belgium
- Faculty of Veterinary Medicine, University of Liege, Liege, Belgium
- Unit of Animal Genomics, University of Liège, Liège, Belgium
| | - Pierre Close
- Laboratory of Cancer Signaling, University of Liège, Liège, Belgium.
- GIGA-Institute, University of Liège, Liège, Belgium.
- University of Liège, Liège, Belgium.
- WELBIO, University of Liege, Liege, Belgium.
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8
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Variability in mRNA translation: a random matrix theory approach. Sci Rep 2021; 11:5300. [PMID: 33674667 PMCID: PMC7970873 DOI: 10.1038/s41598-021-84738-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 02/19/2021] [Indexed: 01/31/2023] Open
Abstract
The rate of mRNA translation depends on the initiation, elongation, and termination rates of ribosomes along the mRNA. These rates depend on many "local" factors like the abundance of free ribosomes and tRNA molecules in the vicinity of the mRNA molecule. All these factors are stochastic and their experimental measurements are also noisy. An important question is how protein production in the cell is affected by this considerable variability. We develop a new theoretical framework for addressing this question by modeling the rates as identically and independently distributed random variables and using tools from random matrix theory to analyze the steady-state production rate. The analysis reveals a principle of universality: the average protein production rate depends only on the of the set of possible values that the random variable may attain. This explains how total protein production can be stabilized despite the overwhelming stochasticticity underlying cellular processes.
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9
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Neelagandan N, Lamberti I, Carvalho HJF, Gobet C, Naef F. What determines eukaryotic translation elongation: recent molecular and quantitative analyses of protein synthesis. Open Biol 2020; 10:200292. [PMID: 33292102 PMCID: PMC7776565 DOI: 10.1098/rsob.200292] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 11/10/2020] [Indexed: 12/14/2022] Open
Abstract
Protein synthesis from mRNA is an energy-intensive and tightly controlled cellular process. Translation elongation is a well-coordinated, multifactorial step in translation that undergoes dynamic regulation owing to cellular state and environmental determinants. Recent studies involving genome-wide approaches have uncovered some crucial aspects of translation elongation including the mRNA itself and the nascent polypeptide chain. Additionally, these studies have fuelled quantitative and mathematical modelling of translation elongation. In this review, we provide a comprehensive overview of the key determinants of translation elongation. We discuss consequences of ribosome stalling or collision, and how the cells regulate translation in case of such events. Next, we review theoretical approaches and widely used mathematical models that have become an essential ingredient to interpret complex molecular datasets and study translation dynamics quantitatively. Finally, we review recent advances in live-cell reporter and related analysis techniques, to monitor the translation dynamics of single cells and single-mRNA molecules in real time.
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Affiliation(s)
| | | | | | | | - Felix Naef
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland
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10
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Szavits-Nossan J, Ciandrini L. Inferring efficiency of translation initiation and elongation from ribosome profiling. Nucleic Acids Res 2020; 48:9478-9490. [PMID: 32821926 PMCID: PMC7515720 DOI: 10.1093/nar/gkaa678] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2020] [Revised: 07/29/2020] [Accepted: 08/15/2020] [Indexed: 01/13/2023] Open
Abstract
One of the main goals of ribosome profiling is to quantify the rate of protein synthesis at the level of translation. Here, we develop a method for inferring translation elongation kinetics from ribosome profiling data using recent advances in mathematical modelling of mRNA translation. Our method distinguishes between the elongation rate intrinsic to the ribosome’s stepping cycle and the actual elongation rate that takes into account ribosome interference. This distinction allows us to quantify the extent of ribosomal collisions along the transcript and identify individual codons where ribosomal collisions are likely. When examining ribosome profiling in yeast, we observe that translation initiation and elongation are close to their optima and traffic is minimized at the beginning of the transcript to favour ribosome recruitment. However, we find many individual sites of congestion along the mRNAs where the probability of ribosome interference can reach \documentclass[12pt]{minimal}
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}{}$50\%$\end{document}. Our work provides new measures of translation initiation and elongation efficiencies, emphasizing the importance of rating these two stages of translation separately.
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Affiliation(s)
- Juraj Szavits-Nossan
- SUPA, School of Physics and Astronomy, University of Edinburgh, Peter Guthrie Tait Road, Edinburgh EH9 3FD, UK
| | - Luca Ciandrini
- Centre de Biologie Structurale (CBS), CNRS, INSERM, Univ Montpellier, Montpellier 34090, France
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11
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Szavits-Nossan J, Evans MR. Dynamics of ribosomes in mRNA translation under steady- and nonsteady-state conditions. Phys Rev E 2020; 101:062404. [PMID: 32688522 DOI: 10.1103/physreve.101.062404] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 05/20/2020] [Indexed: 11/07/2022]
Abstract
Recent advances in DNA sequencing and fluorescence imaging have made it possible to monitor the dynamics of ribosomes actively engaged in messenger RNA (mRNA) translation. Here, we model these experiments within the inhomogeneous totally asymmetric simple exclusion process (TASEP) using realistic kinetic parameters. In particular, we present analytic expressions to describe the following three cases: (a) translation of a newly transcribed mRNA, (b) translation in the steady state and, specifically, the dynamics of individual (tagged) ribosomes, and (c) runoff translation after inhibition of translation initiation. In cases (b) and (c) we develop an effective medium approximation to describe many-ribosome dynamics in terms of a single tagged ribosome in an effective medium. The predictions are in good agreement with stochastic simulations.
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Affiliation(s)
- Juraj Szavits-Nossan
- SUPA, School of Physics and Astronomy, University of Edinburgh, Peter Guthrie Tait Road, Edinburgh EH9 3FD, United Kingdom
| | - Martin R Evans
- SUPA, School of Physics and Astronomy, University of Edinburgh, Peter Guthrie Tait Road, Edinburgh EH9 3FD, United Kingdom
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12
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T Magalhães B, Lourenço A, Azevedo NF. Computational resources and strategies to assess single-molecule dynamics of the translation process in S. cerevisiae. Brief Bioinform 2019; 22:219-231. [PMID: 31879749 DOI: 10.1093/bib/bbz149] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Revised: 10/16/2019] [Accepted: 10/30/2019] [Indexed: 11/13/2022] Open
Abstract
This work provides a systematic and comprehensive overview of available resources for the molecular-scale modelling of the translation process through agent-based modelling. The case study is the translation in Saccharomyces cerevisiae, one of the most studied yeasts. The data curation workflow encompassed structural information about the yeast (i.e. the simulation environment), and the proteins, ribonucleic acids and other types of molecules involved in the process (i.e. the agents). Moreover, it covers the main process events, such as diffusion (i.e. motion of molecules in the environment) and collision efficiency (i.e. interaction between molecules). Data previously determined by wet-lab techniques were preferred, resorting to computational predictions/extrapolations only when strictly necessary. The computational modelling of the translation processes is of added industrial interest, since it may bring forward knowledge on how to control such phenomena and enhance the production of proteins of interest in a faster and more efficient manner.
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Affiliation(s)
| | - Anália Lourenço
- Department of Computer Science, University of Vigo, Spain, Centre of Biological Engineering, University of Minho, Portugal
| | - Nuno F Azevedo
- Department of Chemical Engineering, Faculty of Engineering of the University of Porto, Portugal
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13
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Mishra B, Chowdhury D. Biologically motivated three-species exclusion model: Effects of leaky scanning and overlapping genes on initiation of protein synthesis. Phys Rev E 2019; 100:022106. [PMID: 31574638 DOI: 10.1103/physreve.100.022106] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Indexed: 11/07/2022]
Abstract
The totally asymmetric simple exclusion process was originally introduced as a model for the trafficlike collective movement of ribosomes on a messenger RNA (mRNA) that serves as the track for the motorlike forward stepping of individual ribosomes. In each step, a ribosome elongates a protein by a single unit using the track also as a template for protein synthesis. But, prefabricated functionally competent ribosomes are not available to begin synthesis of protein; a subunit directionally scans the mRNA in search of the predesignated site where it is supposed to bind with the other subunit and begin the synthesis of the corresponding protein. However, because of "leaky" scanning, a fraction of the scanning subunits miss the target site and continue their search beyond the first target. Sometimes such scanners successfully identify the site that marks the site for initiation of the synthesis of a different protein. In this paper, we develop an exclusion model with three interconvertible species of hard rods to capture some of the key features of these biological phenomena and study the effects of the interference of the flow of the different species of rods on the same lattice. More specifically, we identify the mean time for the initiation of protein synthesis as appropriate mean first-passage time that we calculate analytically using the formalism of backward master equations. Despite the approximations made, our analytical predictions are in reasonably good agreement with the numerical data that we obtain by performing Monte Carlo simulations.
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Affiliation(s)
- Bhavya Mishra
- Department of Physics, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh 208016, India
| | - Debashish Chowdhury
- Department of Physics, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh 208016, India
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14
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Abstract
Heterologously expressed genes require adaptation to the host organism to ensure adequate levels of protein synthesis, which is typically approached by replacing codons by the target organism’s preferred codons. In view of frequently encountered suboptimal outcomes we introduce the codon-specific elongation model (COSEM) as an alternative concept. COSEM simulates ribosome dynamics during mRNA translation and informs about protein synthesis rates per mRNA in an organism- and context-dependent way. Protein synthesis rates from COSEM are integrated with further relevant covariates such as translation accuracy into a protein expression score that we use for codon optimization. The scoring algorithm further enables fine-tuning of protein expression including deoptimization and is implemented in the software OCTOPOS. The protein expression score produces competitive predictions on proteomic data from prokaryotic, eukaryotic, and human expression systems. In addition, we optimized and tested heterologous expression of manA and ova genes in Salmonella enterica serovar Typhimurium. Superiority over standard methodology was demonstrated by a threefold increase in protein yield compared to wildtype and commercially optimized sequences.
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15
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Sharma AK, Sormanni P, Ahmed N, Ciryam P, Friedrich UA, Kramer G, O’Brien EP. A chemical kinetic basis for measuring translation initiation and elongation rates from ribosome profiling data. PLoS Comput Biol 2019; 15:e1007070. [PMID: 31120880 PMCID: PMC6559674 DOI: 10.1371/journal.pcbi.1007070] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Revised: 06/11/2019] [Accepted: 05/06/2019] [Indexed: 01/23/2023] Open
Abstract
Analysis methods based on simulations and optimization have been previously developed to estimate relative translation rates from next-generation sequencing data. Translation involves molecules and chemical reactions, hence bioinformatics methods consistent with the laws of chemistry and physics are more likely to produce accurate results. Here, we derive simple equations based on chemical kinetic principles to measure the translation-initiation rate, transcriptome-wide elongation rate, and individual codon translation rates from ribosome profiling experiments. Our methods reproduce the known rates from ribosome profiles generated from detailed simulations of translation. By applying our methods to data from S. cerevisiae and mouse embryonic stem cells, we find that the extracted rates reproduce expected correlations with various molecular properties, and we also find that mouse embryonic stem cells have a global translation speed of 5.2 AA/s, in agreement with previous reports that used other approaches. Our analysis further reveals that a codon can exhibit up to 26-fold variability in its translation rate depending upon its context within a transcript. This broad distribution means that the average translation rate of a codon is not representative of the rate at which most instances of that codon are translated, and it suggests that translational regulation might be used by cells to a greater degree than previously thought.
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Affiliation(s)
- Ajeet K. Sharma
- Department of Chemistry, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Pietro Sormanni
- Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
| | - Nabeel Ahmed
- Bioinformatics and Genomics Graduate Program, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Prajwal Ciryam
- Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
| | - Ulrike A. Friedrich
- Center for Molecular Biology of the Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Günter Kramer
- Center for Molecular Biology of the Heidelberg University (ZMBH), DKFZ-ZMBH Alliance, Heidelberg, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Edward P. O’Brien
- Department of Chemistry, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Bioinformatics and Genomics Graduate Program, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Institute for CyberScience, Pennsylvania State University, University Park, Pennsylvania, United States of America
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