evolution ohne zellul re strukturen szenen aus einer rna
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Evolution ohne zellulre Strukturen Szenen aus einer RNA-Welt Peter - PowerPoint PPT Presentation

Evolution ohne zellulre Strukturen Szenen aus einer RNA-Welt Peter Schuster Institut fr Theoretische Chemie, Universitt Wien, sterreich und The Santa Fe Institute, Santa Fe, New Mexico, USA Seminar: Evolution Im Mittelpukt der


  1. Evolution ohne zelluläre Strukturen Szenen aus einer RNA-Welt Peter Schuster Institut für Theoretische Chemie, Universität Wien, Österreich und The Santa Fe Institute, Santa Fe, New Mexico, USA Seminar: Evolution – Im Mittelpukt der Mensch Martin Luther UniversitätHalle (Saale), 10.05.2010

  2. Web-Page for further information: http://www.tbi.univie.ac.at/~pks

  3. RNA as scaffold for supramolecular complexes RNA as catalyst Ribozyme ribosome ? ? ? ? ? RNA The world as a precursor of DNA protein the current + biology RNA as carrier of genetic information RNA viruses and retroviruses RNA evolution in vitro RNA – The magic molecule

  4. The thiamine-pyrophosphate riboswitch S. Thore, M. Leibundgut, N. Ban. Science 312 :1208-1211, 2006.

  5. M. Mandal, B. Boese, J.E. Barrick, W.C. Winkler, R.R, Breaker. Cell 113:577-586 (2003)

  6. ENCODE stands for ENC yclopedia O f D NA E lements. ENCODE Project Consortium. Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature 447 :799-816, 2007

  7. 1. RNA-Replication in vitro und in vivo 2. Evolution von RNA-Molekülen 3. RNA-Sequenzen and -strukturen 4. Evolutionäre Optimierung von RNA-Strukturen

  8. 1. RNA-Replication in vitro und in vivo 2. Evolution von RNA-Molekülen 3. RNA-Sequenzen and -strukturen 4. Evolutionäre Optimierung von RNA-Strukturen

  9. Evolution of RNA molecules based on Q β phage D.R.Mills, R.L.Peterson, S.Spiegelman, An extracellular Darwinian experiment with a self-duplicating nucleic acid molecule . Proc.Natl.Acad.Sci.USA 58 (1967), 217-224 S.Spiegelman, An approach to the experimental analysis of precellular evolution . Quart.Rev.Biophys. 4 (1971), 213-253 C. Weissmann, The making of a phage . FEBS Letters 40 (1974), S10-S18 C.K.Biebricher, Darwinian selection of self-replicating RNA molecules . Evolutionary Biology 16 (1983), 1-52 G.Bauer, H.Otten, J.S.McCaskill, Travelling waves of in vitro evolving RNA. Proc.Natl.Acad.Sci.USA 86 (1989), 7937-7941 C.K.Biebricher, W.C.Gardiner, Molecular evolution of RNA in vitro . Biophysical Chemistry 66 (1997), 179-192 G.Strunk, T.Ederhof, Machines for automated evolution experiments in vitro based on the serial transfer concept . Biophysical Chemistry 66 (1997), 193-202 F.Öhlenschlager, M.Eigen, 30 years later – A new approach to Sol Spiegelman‘s and Leslie Orgel‘s in vitro evolutionary studies . Orig.Life Evol.Biosph. 27 (1997), 437-457

  10. RNA sample Time 0 1 2 3 4 5 6 69 70 � Stock solution: Q RNA-replicase, ATP, CTP, GTP and UTP, buffer Application of serial transfer to RNA evolution in vitro

  11. Decrease in mean fitness due to quasispecies formation The increase in RNA production rate during a serial transfer experiment

  12. A collection of reviews on evolution in vitro and in silico

  13. Stock solution : activated monomers, ATP, CTP, GTP, UTP (TTP); a replicase, an enzyme that performs complemantary replication; buffer solution The flowreactor is a device for studies of evolution in vitro and in silico .

  14. James D. Watson, 1928-, and Francis H.C. Crick, 1916-2004 Nobel prize 1962 1953 – 2003 fifty years double helix The three-dimensional structure of a short double helical stack of B-DNA

  15. Complementary replication is the simplest copying mechanism of RNA. Complementarity is determined by Watson-Crick base pairs: G � C and A = U

  16. dx dx = = 1 f x 2 f x and 2 2 1 1 dt dt = ξ = ξ ζ = ξ + ξ η = ξ − ξ = x f x f f f f , , , , 1 2 1 2 1 2 1 2 1 2 1 2 − η = η ft t e ( ) ( 0 ) ζ = ζ ft t e ( ) ( 0 ) Complementary replication as the simplest molecular mechanism of reproduction

  17. RNA replication by Q � -replicase C. Weissmann, The making of a phage . FEBS Letters 40 (1974), S10-S18

  18. Christof K. Biebricher 1941-2009 metastable stable C.K. Biebricher, R. Luce. 1992. In vitro recombination and terminal recombination of RNA by Q � replicase. The EMBO Journal 11:5129-5135.

  19. Kinetics of RNA replication C.K. Biebricher, M. Eigen, W.C. Gardiner, Jr. Biochemistry 22 :2544-2559, 1983

  20. J. Demez. European and mediterranean plant protection organization archive. France R.W. Hammond, R.A. Owens. Molecular Plant Pathology Laboratory, US Department of Agriculture Plant damage by viroids

  21. Nucleotide sequence and secondary structure of the potato spindle tuber viroid RNA H.J.Gross, H. Domdey, C. Lossow, P Jank, M. Raba, H. Alberty, and H.L. Sänger. Nature 273 :203-208 (1978)

  22. Vienna RNA Package 1.8.2 Biochemically supported structure Nucleotide sequence and secondary structure of the potato spindle tuber viroid RNA H.J.Gross, H. Domdey, C. Lossow, P Jank, M. Raba, H. Alberty, and H.L. Sänger. Nature 273 :203-208 (1978)

  23. 1. RNA-Replication in vitro und in vivo 2. Evolution von RNA-Molekülen 3. RNA-Sequenzen and -strukturen 4. Evolutionäre Optimierung von RNA-Strukturen

  24. 1971 1977 1988 Chemical kinetics of molecular evolution

  25. Replication and mutation are parallel chemical reactions.

  26. x d = ∑ = − = j n Q f x x Φ j n ; 1 , 2 , K , i 1 ji i i j dt Manfred Eigen 1927 - Mutation and (correct) replication as parallel chemical reactions M. Eigen. 1971. Naturwissenschaften 58:465, M. Eigen & P. Schuster.1977. Naturwissenschaften 64:541, 65:7 und 65:341

  27. Quasispecies Driving virus populations through threshold The error threshold in replication

  28. Chain length and error threshold ⋅ σ = − ⋅ σ ≥ ⇒ ⋅ − ≥ − σ n Q p n p ( 1 ) 1 ln ( 1 ) ln σ ln ≈ p n constant : K max p σ ln ≈ n p K constant : max n = − n Q p ( 1 ) replicatio n accuracy K p error rate K n chain length K f = m σ superiorit y of master sequence K ∑ ≠ f j j m

  29. Molecular evolution of viruses

  30. linear and multiplicative hyperbolic Smooth fitness landscapes

  31. The linear fitness landscape shows no error threshold

  32. Error threshold on the hyperbolic landscape

  33. single peak landscape step linear landscape Rugged fitness landscapes

  34. Error threshold on the single peak landscape

  35. Error threshold on the step linear landscape

  36. The error threshold can be separated into three phenomena: 1. Decrease in the concentration of the master sequence to very small values. 2. Sharp change in the stationary concentration of the quasispecies distribuiton. 3. Transition to the uniform distribution at small mutation rates. All three phenomena coincide for the quasispecies on the single peak fitness lanscape.

  37. The error threshold can be separated into three phenomena: 1. Decrease in the concentration of the master sequence to very small values. 2. Sharp change in the stationary concentration of the quasispecies distribuiton. 3. Transition to the uniform distribution at small mutation rates. All three phenomena coincide for the quasispecies on the single peak fitness lanscape.

  38. Fitness landscapes showing error thresholds

  39. Error threshold: Individual sequences n = 10, � = 2 and d = 0, 1.0, 1.85

  40. � 0 , � 0 � largest eigenvalue and eigenvector diagonalization of matrix W „ complicated but not complex “ � W = G F mutation matrix fitness landscape „ complex “ ( complex ) sequence structure � „ complex “ mutation selection Complexity in molecular evolution

  41. 1. RNA-Replication in vitro und in vivo 2. Evolution von RNA-Molekülen 3. RNA-Sequenzen and -strukturen 4. Evolutionäre Optimierung von RNA-Strukturen

  42. The notion of RNA (secondary) structure 1. Minimum free energy structure 2. Many sequences one structure 3. Suboptimal structures 4. Kinetic structures

  43. The notion of RNA (secondary) structure 1. Minimum free energy structure 2. Many sequences one structure 3. Suboptimal structures 4. Kinetic structures

  44. Extension of the notion of structure

  45. N = 4 n N S < 3 n Criterion: Minimum free energy (mfe) Rules: _ ( _ ) _ � { AU , CG , GC , GU , UA , UG } A symbolic notation of RNA secondary structure that is equivalent to the conventional graphs

  46. The notion of RNA (secondary) structure 1. Minimum free energy structure 2. Many sequences one structure 3. Suboptimal structures 4. Kinetic structures

  47. The inverse folding algorithm searches for sequences that form a given RNA secondary structure under the minimum free energy criterion.

  48. I I I I I I Space of genotypes: = { , , , , ... , } ; Hamming metric 1 2 3 4 N S S S S S S Space of phenotypes: = { , , , , ... , } ; metric (not required) 1 2 3 4 M �� N M � ( ) = I S j k U � � -1 � � G k = S I S ( ) | ( ) = I k j j k � A mapping and its inversion

  49. many genotypes � one phenotype

  50. RNA 9 :1456-1463, 2003 Evidence for neutral networks and shape space covering

  51. Evidence for neutral networks and intersection of apatamer functions

  52. An example of ‘artificial selection’ with RNA molecules or ‘breeding’ of biomolecules

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