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A quantitative view on mRNA translation: the relative role of initiation and elongation - Luca Ciandrini

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A quantitative view on mRNA translation: the relative role of initiation and elongation - Luca Ciandrini

  1. 1. A quantitative view on mRNA translation: the relative role of initiation and elongation Luca Ciandrini (luca.ciandrini@umontpellier.fr) University of Montpellier, France 13th June 2016 Quantitative Laws II, Villa del Grumello, Como
  2. 2. Translation from nucleotide sequences to functional proteins Study the ribosome traffic to quantify the protein production rate (at the level of translation) ribosomes growing polypeptide mRNA 5’ 3’
  3. 3. coding sequence ribosome START elongating protein initiation (recruitment) tRNA amino-acid elongation (usage) termination STOP initiation (recruitment) elongation (usage) termination
  4. 4. coding sequence ribosome START elongating protein initiation (recruitment) tRNA amino-acid elongation (usage) termination STOP initiation (recruitment) elongation (usage) termination How can we predict/ vary the strength of initiation? Ribosome recruitment Ribosome usage How depletion of ribosomes affects gene expression and growth rates? Codon usage and bias? Evolution? Does noise depend on codon sequences, etc etc? Can we tune and predict, just by varying the sequence, “optimal” protein production rates?P. Geulich, L. Ciandrini, R.J. Allen and M. C. Romano, Phys Rev E (2012) Shah et al, Cell (2013)
  5. 5. Flow of ribosomes ~ driven lattice gas Macdonald et al., Biopolymers (1968) Totally Asymmetric Simple Exclusion Process coding sequence ribosome START elongating protein initiation (recruitment) tRNA amino-acid elongation (usage) termination STOP initiation (recruitment) elongation (usage) termination
  6. 6. The model can predict translation efficiency depending on initiation and elongation rates ribosomal current (mRNA efficiency) initiation rate codon dependent elongation rates termination rate L. Ciandrini, I. Stansfield and M. C. Romano, PLoS Comp Bio (2013) initiation limited elongation limited
  7. 7. The model can predict ribosome density depending on initiation and elongation rates ribosomal density initiation rate codon dependent elongation rates termination rate L. Ciandrini, I. Stansfield and M. C. Romano, PLoS Comp Bio (2013) initiation limited ribosomes queueing
  8. 8. 1. How initiation affects mRNA efficiency L. Dias Fernandes, A. de Moura, L. Ciandrini, to be submitted J.C. Walter, L. Ciandrini, in preparation
  9. 9. Observation: the density of ribosomes depends on the length of the mRNA data (yeast) from MacKay et al. (2004)
  10. 10. The local concentration of ribosomes determines translation initiation ↵ = ↵o c = ↵o(c1 + cR) initiation rate overall ribosome concentration contribution due to terminating ribosomes (feedback) Initiation depends on local concentrations of ribosomes R r
  11. 11. Contribution due to terminating ribosomes depends on the end-to-end distance and the production rate ↵ = ↵o c = ↵o(c1 + cR) initiation rate R r The probability to end up in the reaction volume is ∝ r/R J current of the driven lattice gas end-to-end distance is a constant depending on r, the affinity mRNA-ribosome,…
  12. 12. The mRNA persistence length depends on the ribosomal density R ⇠ p `pL R ⇠ q `poly p L `p= persistence length `poly p = f` + (1 f)`p f = fraction of transcript occupied by ribosomes
  13. 13. The initiation rate α is therefore length-dependent (via “recycling” and finite-size effects) • Fix a tentative initiation rate • Simulate the system and extract J and R • Compute the initiation rate • Compare to the tentative one J We develop a self-consistent method to compute the initiation rate
  14. 14. initiation rate:
  15. 15. L. Dias Fernandes, A. De Moura, L. Ciandrini, to be submitted finite size + local concentration The theory is consistent with the ribosome density data initiation rate:
  16. 16. The theory is consistent with the ribosome density data finite size + local concentration initiation rate: L. Dias Fernandes, A. De Moura, L. Ciandrini, to be submitted
  17. 17. Short transcripts are less sensitive to changes in the ribosomal pool decreasing concentration of available ribosomes
  18. 18. Short transcripts are less sensitive to changes in the ribosomal pool mRNA efficiency short transcript/ mRNA efficiency long transcript
  19. 19. 2. How elongation affects mRNA efficiency AJ Kemp, R Betney, LC, ACM Schwenger, MC Romano,I Stansfield, Molecular Microbiology (2013) B Gorgoni, L. Ciandrini, M Mc Farland, M C Romano, I Stansfield, submitted Y. Meriguet, S. Guiziou, J. Bonnet, L. Ciandrini, in preparation
  20. 20. sup70-65 mutants exhibits slow translation of the cognate CAG codon AJ Kemp, R Betney, L Ciandrini, ACM Schwenger, MC Romano,I Stansfield, Molecular Microbiology (2013)
  21. 21. How do we affect translation if we insert CAA and CAG repeats at the 5’end? 1.0 1.2 on B A luc luc luc luc 5 x CAA 10 x CAA 5 x CAG 10 x CAG *** *** ****** 0.0 0.00 0.02 0.04 0.06 0.08 0.10 Fold luciferaseexpressionrate D E
  22. 22. 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG0.0 0.2 0.4 0.6 0.8 1.0 1.2 SUP70 wild-type multicopy tRNACUG sup70-65 Fold-changein luciferaseexpression B C luc luc luc luc 5 x CAA 10 x CAA 5 x CAG 10 x CAG *** *** ****** *** *** ****** pSUP70 (CEN) pSUP70-[2µ] psup70-65 (CEN) 0.0 0.5 1.0 1.5 2.0 6 9 12 15 0.00 0.02 0.04 0.06 0.08 Fold concentration of tRNACUG Gln relative to wild type luciferaseexpressi 0 2 4 6 8 10 0.020 0.040 0.060 0.080 Number of CAG codons in tandem repea Luciferaseexpressionrate F E 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 0.0 0.2 0.4 0.6 0.8 1.0 1.2 SUP70 wild-type multicopy tRNACUG sup70-65 Fold-changein luciferaseexpression B C luc luc luc luc 5 x CAA 10 x CAA 5 x CAG 10 x CAG *** *** ****** *** *** ****** pSUP70 (CEN) pSUP70-[2µ] psup70-65 (CEN) 0.0 0.5 1.0 1.5 2.0 6 9 12 15 0.00 0.02 0.04 0.06 0.08 Fold concentration of tRNACUG Gln relative to wild type luciferaseexpressio 0 2 4 6 8 10 0.020 0.040 0.060 0.080 Number of CAG codons in tandem repeats Luciferaseexpressionrate F E 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 0.0 SUP70 wild-type multicopy tRNACUG sup70-65 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Modelprediction:fold-changein luciferaseexpression C *** *** ****** pSUP70 (CEN) pSUP70-[2µ] psup70-65 (CEN) pSUP70 (CEN) pSUP70-[2µ] psup70-65 (CEN) 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 0.0 SUP70 wild-type multicopy tRNACUG sup70-65 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Modelprediction:fold-changein luciferaseexpression C *** *** ****** pSUP70 (CEN) pSUP70-[2µ] psup70-65 (CEN) pSUP70 (CEN) pSUP70-[2µ] psup70-65 (CEN) 0.0 0.0 0.1 0.1 ribosomaldensity 0.0 Lu Fmodelexperiments sup70-65 mutants exhibits slow translation of the cognate CAG codon
  23. 23. The method: we simulated the translation in WT and sup70-65 mutant to perform an in silico genetic screen sensitive genesinsensitive genes
  24. 24. The predicted targets of tRNAGln CUG regulation are confirmed by experiments 54% relative to WT control 103% relative to WT control predicted to be sensitive predicted to be insensitive
  25. 25. We used constitutively active mutants of the Gcn2 protein kinase to decrease the initiation Gcn2 reduces (globally) the translation initiation rate via the phosphorylation of the essential translation initiation factor eIF2-α We tested our hypothesis on a gene (FAR7) Also, we observed a significant (almost 2-fold) shift in the population away from chains and towards single cells initiation rate mutant/WT translationrate model
  26. 26. Conclusions • Initiation might be the origin of the ribosome density/ mRNA length dependence • Elongation can be used to regulate gene expression through the tuning of single-codon elongation rates • Both initiation and elongation can be limiting steps of translation
  27. 27. Further perspectives • How to independently study and modulate initiation and elongation? …undergoing experiments…
  28. 28. Acknowledgements Thank you Ian Stansfield Barbara Gorgoni IMS, University of Aberdeen Jean-Charles Walter L2C, University of Montpellier soutien UM Défi InPhyNiTi (Interfaces physiques Numérique et Théorique) Sarah Guiziou Jerome Bonnet CBS, University of Montpellier Yoann Meriguet DIMNP, University of Montpellier Lucas Dias Fernandes Alessandro de Moura Maria C Romano ICSMB, University of Aberdeen
  29. 29. The relative positioning of codons (elongation) affects translational efficiency Shuffling synonymous codons does not affect the final product (aa-sequence) and keeps the same codon usage (codon used in a sequence). original synonymous
  30. 30. The relative positioning of codons (elongation) affects translational efficiency
  31. 31. The relative positioning of codons (elongation) affects translational efficiency
  32. 32. We are going to design sequences with high, medium and small translation efficiencies and test them
  33. 33. The limited amount of resources constrains translation efficiency* *Translation efficiency = overall rate of translation per mRNA Scott et al., Science 2010 There is evidence that the amount of ribosomes restrains translation efficiency (see works by Scott, Klumpp, Hwa; Shah et al. from Plotkin-Kudla groups). Competition for translational resources affects translation
  34. 34. The limited amount of resources constrains translation efficiency* *Translation efficiency = overall rate of translation per mRNA Scott et al., Science 2010 There is evidence that the amount of ribosomes restrains translation efficiency (see works by Scott, Klumpp, Hwa; Shah et al. from Plotkin-Kudla groups). Competition for translational resources affects translation Can competition for resources be exploited to regulate gene expression?
  35. 35. Conclusions • Finite-size effects are relevant in translation • The three-dimensional conformation of the polysome might enhance initiation (ribosome “recycling”) • The selfish mRNA: is recycling a way to build up a personal pool of ribosomes?
  36. 36. 2. Use strep-tag at the 5‘end to detect the queue 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG0.0 0.2 0.4 0.6 0.8 1.0 1.2 SUP70 wild-type multicopy tRNACUG sup70-65 Fold-changein luciferaseexpression B C luc luc luc luc 5 x CAA 10 x CAA 5 x CAG 10 x CAG *** *** ****** *** *** ****** pSUP70 (CEN) pSUP70-[2µ] psup70-65 (CEN) 0.0 0.5 1.0 1.5 2.0 6 9 12 15 0.00 0.02 0.04 0.06 0.08 Fold concentration of tRNACUG Gln relative to wild type luciferaseexpressi 0 2 4 6 8 10 0.020 0.040 0.060 0.080 Number of CAG codons in tandem repea Luciferaseexpressionrate F E 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 0.0 0.2 0.4 0.6 0.8 1.0 1.2 SUP70 wild-type multicopy tRNACUG sup70-65 Fold-changein luciferaseexpression B C luc luc luc luc 5 x CAA 10 x CAA 5 x CAG 10 x CAG *** *** ****** *** *** ****** pSUP70 (CEN) pSUP70-[2µ] psup70-65 (CEN) 0.0 0.5 1.0 1.5 2.0 6 9 12 15 0.00 0.02 0.04 0.06 0.08 Fold concentration of tRNACUG Gln relative to wild type luciferaseexpressio 0 2 4 6 8 10 0.020 0.040 0.060 0.080 Number of CAG codons in tandem repeats Luciferaseexpressionrate F E 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 0.0 SUP70 wild-type multicopy tRNACUG sup70-65 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Modelprediction:fold-changein luciferaseexpression C *** *** ****** pSUP70 (CEN) pSUP70-[2µ] psup70-65 (CEN) pSUP70 (CEN) pSUP70-[2µ] psup70-65 (CEN) 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 0.0 SUP70 wild-type multicopy tRNACUG sup70-65 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 5 x C AA 10 x C AA 5 x C AG 10 x C AG 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Modelprediction:fold-changein luciferaseexpression C *** *** ****** pSUP70 (CEN) pSUP70-[2µ] psup70-65 (CEN) pSUP70 (CEN) pSUP70-[2µ] psup70-65 (CEN) 0.0 0.0 0.1 0.1 ribosomaldensity 0.0 Lu F A.J. Kemp, R. Betney, L. Ciandrini, A.C.M. Schwenger, M.C. Romano, I. Stansfield, Molecular Microbiology (2013) Good agreement with theory
  37. 37. 2. Use strep-tag at the 5‘end to detect the queue CAG causes ribosomes queue upstream the 1 1 y G sup70-65 G 5 x C AA 10 x C AA 5 x C AG 10 x C AG *** *** 2µ] psup70-65 (CEN) 2µ] psup70-65 10 20 30 40 50 0.00 0.05 0.10 0.15 codon number ribosomaldensity F CAG repeats CAA repeats
  38. 38. mRNA-dependent estimates of the initiation rates density from experiments initiation rates Integration between model and experimental data = = 1 site = 1 codon mRNA 1D-lattice ribosome particle initiation elongation termination α β γ γ
  39. 39. mRNA-dependent estimates of the initiation rates Important to discern the interplay between initiation and elongation Gene Ontology: (i) regulatory proteins (ii) cytoplasmic translation (iii) constituents of ribosomes (iv) respiratory chains - unannotated L. Ciandrini, I. Stansfield and M. C. Romano, PLoS Comp Bio
  40. 40. : mRNA-dependent estimates of the initiation rates Protein production rates L. Ciandrini, I. Stansfield and M. C. Romano, PLoS Comp Bio (2013)

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