Evolution in vitro Theorie und Praxis der Herstellung maßgeschneiderter Moleküle Peter Schuster Institut für Theoretische Chemie und Molekulare Strukturbiologie der Universität Wien Vortragsreihe zum Jahr der Chemie TU Ilmenau, 22.11.2003
Web-Page for further information: http://www.tbi.univie.ac.at/~pks
10 6 generations 10 7 generations Generation time 10 000 generations RNA molecules 10 sec 27.8 h = 1.16 d 115.7 d 3.17 a 1 min 6.94 d 1.90 a 19.01 a Bacteria 20 min 138.9 d 38.03 a 380 a 10 h 11.40 a 1 140 a 11 408 a Higher multicelluar 10 d 274 a 27 380 a 273 800 a 2 × 10 7 a 2 × 10 8 a organisms 20 a 20 000 a Time scales of evolutionary change
1. Controlled evolution experiments with bacteria and RNA 2. Optimization in the RNA model 3. Sequence-structure maps, neutral networks, and intersections 4. Selection experiments and design of RNA molecules
1. Controlled evolution experiments with bacteria and RNA 2. Optimization in the RNA model 3. Sequence-structure maps, neutral networks, and intersections 4. Selection experiments and design of RNA molecules
Bacterial Evolution S. F. Elena, V. S. Cooper, R. E. Lenski. Punctuated evolution caused by selection of rare beneficial mutants . Science 272 (1996), 1802-1804 D. Papadopoulos, D. Schneider, J. Meier-Eiss, W. Arber, R. E. Lenski, M. Blot. Genomic evolution during a 10,000-generation experiment with bacteria . Proc.Natl.Acad.Sci.USA 96 (1999), 3807-3812
lawn of E.coli 24 h 24 h nutrient agar Serial transfer of Escherichia coli cultures in Petri dishes � 1 day 6.67 generations � 1 month 200 generations � 1 year 2400 generations
1 year Epochal evolution of bacteria in serial transfer experiments under constant conditions S. F. Elena, V. S. Cooper, R. E. Lenski. Punctuated evolution caused by selection of rare beneficial mutants . Science 272 (1996), 1802-1804
Hamming distance to ancestor 25 20 15 10 5 2000 4000 6000 8000 Generations Time Variation of genotypes in a bacterial serial transfer experiment D. Papadopoulos, D. Schneider, J. Meier-Eiss, W. Arber, R. E. Lenski, M. Blot. Genomic evolution during a 10,000-generation experiment with bacteria . Proc.Natl.Acad.Sci.USA 96 (1999), 3807-3812
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.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
RNA sample Time 0 1 2 3 4 5 6 69 70 � Stock solution: Q RNA-replicase, ATP, CTP, GTP and UTP, buffer The serial transfer technique applied to RNA evolution in vitro
Reproduction of the original figure of the β serial transfer experiment with Q RNA 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
Decrease in mean fitness due to quasispecies formation The increase in RNA production rate during a serial transfer experiment
1. Controlled evolution experiments with bacteria and RNA 2. Optimization in the RNA model 3. Sequence-structure maps, neutral networks, and intersections 4. Selection experiments and design of RNA molecules
RNA as adapter molecule RNA is the catalytic subunit in RNA as scaffold for supramolecular RNA as transmitter of genetic information supramolecular complexes complexes DNA transcription ... CUG ... leu ...AGAGCGCCAGACUGAAGAUCUGGAGGUCCUGUGUUC... GAC messenger- RNA genetic code translation protein ribosome RNA as working copy of genetic information ? ? ? ? ? RNA as catalyst RNA RNA is modified by epigenetic control RNA editing Alternative splicing of messenger RNA ribozyme RNA as regulator of gene expression RNA as carrier of genetic information The RNA world as a precursor of RNA viruses and retroviruses the current DNA + protein biology RNA as information carrier in evolution in vitro and evolutionary biotechnology Functions of RNA molecules gene silencing by small interfering RNAs
5' - end N 1 O CH 2 O 5'-e nd GCGGAU UUA GCUC AGUUGGGA GAGC CCAGA G CUGAAGA UCUGG AGGUC CUGUG UUCGAUC CACAG A AUUCGC ACCA 3’-end N A U G C k = , , , OH O N 2 O P O CH 2 O Na � O O OH N 3 O P O CH 2 O Na � 3'-end O O OH Definition of RNA structure 5’-end N 4 O O CH 2 P O Na � 70 O O OH 60 3' - end O P O 10 Na � O 50 20 30 40
James D. Watson, 1928- , and Francis Crick, 1916- , Nobel Prize 1962 1953 – 2003 fifty years double helix The three-dimensional structure of a short double helical stack of B-DNA
5' 3' Plus Strand G C C C G Synthesis 5' 3' Plus Strand G C C C G C G 3' Synthesis 5' 3' Plus Strand G C C C G Minus Strand C G G G C 5' 3' Complex Dissociation Complementary replication as the 3' 5' simplest copying mechanism of RNA Plus Strand C C C G G Complementarity is determined by Watson-Crick base pairs: + 5' 3' G � C and A = U Minus Strand G C G G C
5’-end 3’-end A C C U G C U A A U U G C G G C A U A A A C C U A U G G C C A G G U U U G G G A C C A U G A G RNAStudio.lnk G G C GGCGCGCCCGGCGCC U G GUAUCGAAAUACGUAGCGUAUGGGGAUGCUGGACGGUCCCAUCGGUACUCCA UGGUUACGCGUUGGGGUAACGAAGAUUCCGAGAGGAGUUUAGUGACUAGAGG Folding of RNA sequences into secondary structures of minimal free energy, � G 0 300
Replication rate constant: f k = � / [ � + � d S (k) ] � (k) = d H (S k ,S � d S ) f 6 f 7 f 5 f 0 f � f 4 f 3 f 1 f 2 Evaluation of RNA secondary structures yields replication rate constants
Stock Solution Reaction Mixture Replication rate constant: f k = � / [ � + � d S (k) ] � (k) = d H (S k ,S � d S ) Selection constraint: # RNA molecules is controlled by the flow ≈ ± N ( t ) N N The flowreactor as a device for studies of evolution in vitro and in silico
Master sequence Mutant cloud “Off-the-cloud” Concentration mutations Sequence e c a p s The molecular quasispecies in sequence space
Genotype-Phenotype Mapping Evaluation of the = � S { ( ) I { S { Phenotype I { ƒ f = ( S ) { { f { Q { f 1 j f 1 Mutation I 1 f n+1 f 2 I 1 I n+1 I 2 f n f 2 I n I 2 f 3 I 3 Q Q I 3 f 3 I 4 I { f 4 f { I 5 I 4 I 5 f 4 f 5 f 5 Evolutionary dynamics including molecular phenotypes
50 S d � - 0 5 40 e r u t c u r Evolutionary trajectory t s 30 l a i t i n i m o r f 20 e c n a t s i d e g 10 a r e v A 0 0 250 500 750 1000 1250 Time (arbitrary units) In silico optimization in the flow reactor: Trajectory ( biologists‘ view )
50 S d � 40 t e g r a t o t e 30 c n a t s i d e r u 20 t c u r t s e g a r 10 e v A Evolutionary trajectory 0 0 250 500 750 1000 1250 Time (arbitrary units) In silico optimization in the flow reactor: Trajectory ( physicists‘ view )
AUGC GC Movies of optimization trajectories over the AUGC and the GC alphabet
0.2 0.15 y c n e 0.1 u q e r F 0.05 0 0 1000 2000 3000 4000 5000 Runtime of trajectories Statistics of the lengths of trajectories from initial structure to target ( AUGC -sequences)
Average structure distance to target dS 36 � Relay steps Number of relay step 10 38 40 42 44 Evolutionary trajectory 0 1250 Time 44 Endconformation of optimization
Average structure distance to target dS 36 � Relay steps Number of relay step 10 38 40 42 44 Evolutionary trajectory 0 1250 Time 43 44 Reconstruction of the last step 43 � 44
Average structure distance to target dS 36 � Relay steps Number of relay step 10 38 40 42 44 Evolutionary trajectory 0 1250 Time 42 43 44 Reconstruction of last-but-one step 42 � 43 ( � 44)
Average structure distance to target dS 36 � Relay steps Number of relay step 10 38 40 42 44 Evolutionary trajectory 0 1250 Time 41 42 43 44 Reconstruction of step 41 � 42 ( � 43 � 44)
Average structure distance to target dS 36 � Relay steps Number of relay step 10 38 40 42 44 Evolutionary trajectory 0 1250 Time 40 41 42 43 44 Reconstruction of step 40 � 41 ( � 42 � 43 � 44)
Average structure distance to target dS 36 � Relay steps Number of relay step 10 38 40 42 44 Evolutionary trajectory 0 1250 Time Evolutionary process 39 40 41 42 43 44 Reconstruction Reconstruction of the relay series
Transition inducing point mutations Neutral point mutations Change in RNA sequences during the final five relay steps 39 � 44
Recommend
More recommend
