Information and Information Processing in Biological Systems Peter - PowerPoint PPT Presentation

Information and Information Processing in Biological Systems Peter Schuster, Eörs Szathmáry, and Avshalom Elitzur Institut für Theoretische Chemie, Universität Wien, Austria, Collegium Budapest – Institute for Advanced Study , Ungarn, and Bar-Ilan University, Israel Europäisches Forum Alpbach Alpbach, 18.– 25.08.2005

Web-Pages for further information: http://www.tbi.univie.ac.at/~pks http://www.colbud.hu/fellows/szathmary.shtml http://faculty.biu.ac.il/~elitzua/

Evolution Experiments in the Laboratory Peter Schuster, Institut für Theoretische Chemie, Universität Wien

Selection and Genetic drift in Genetic drift in Generation time adaptation small populations large populations 10 6 generations 10 7 generations 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 Multicelluar organisms 10 d 274 a 27 380 a 273 800 a 2 × 10 7 a 2 × 10 8 a 20 a 20 000 a Time scales of evolutionary change

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

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

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

Evolutionary design of RNA molecules D.B.Bartel, J.W.Szostak, In vitro selection of RNA molecules that bind specific ligands . Nature 346 (1990), 818-822 C.Tuerk, L.Gold, SELEX - Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase . Science 249 (1990), 505-510 D.P.Bartel, J.W.Szostak, Isolation of new ribozymes from a large pool of random sequences . Science 261 (1993), 1411-1418 R.D.Jenison, S.C.Gill, A.Pardi, B.Poliski, High-resolution molecular discrimination by RNA . Science 263 (1994), 1425-1429 Y. Wang, R.R.Rando, Specific binding of aminoglycoside antibiotics to RNA . Chemistry & Biology 2 (1995), 281-290 Jiang, A. K. Suri, R. Fiala, D. J. Patel, Saccharide-RNA recognition in an aminoglycoside antibiotic-RNA aptamer complex . Chemistry & Biology 4 (1997), 35-50

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

The SELEX technique for the evolutionary preparation of aptamers

additional methyl group Dissociation constants and specificity of theophylline, caffeine, and related derivatives of uric acid for binding to a discriminating aptamer TCT8-4

Secondary structures of aptamers binding theophyllin, caffeine, and related compounds

Schematic drawing of the aptamer binding site for the theophylline molecule

Aptamer binding to aminoglycosid antibiotics: Structure of ligands Y. Wang, R.R.Rando, Specific binding of aminoglycoside antibiotics to RNA . Chemistry & Biology 2 (1995), 281-290

tobramycin G C A C G A U U U A C U A C A C U C G U C -3’ 5’- G G G G G C U U G C A C G A 5’- G G G U A RNA aptamer G C C G U 3’- C C A G U C A U C Formation of secondary structure of the tobramycin binding RNA aptamer with K D = 9 nM L. Jiang, A. K. Suri, R. Fiala, D. J. Patel, Saccharide-RNA recognition in an aminoglycoside antibiotic- RNA aptamer complex. Chemistry & Biology 4 :35-50 (1997)

The three-dimensional structure of the tobramycin aptamer complex L. Jiang, A. K. Suri, R. Fiala, D. J. Patel, Chemistry & Biology 4 :35-50 (1997)

No new principle will declare itself from below a heap of facts. Sir Peter Medawar, 1985

RNA as transmitter of genetic information RNA as adapter molecule RNA is the catalytic subunit in RNA as scaffold for supramolecular supramolecular complexes complexes DNA RNA as catalyst transcription ...AGAGCGCCAGACUGAAGAUCUGGAGGUCCUGUGUUC... messenger- RNA . . . C translation G A leu U G C protein genetic code . . . RNA as working copy of genetic information Ribozyme ribosome ? ? ? ? ? RNA is modified by epigenetic control RNA The RNA world as a precursor of RNA editing the current DNA + protein biology Alternative splicing of messenger RNA RNA as regulator of gene expression Allosteric control of transcribed RNA RNA as carrier of genetic information RNA viruses and retroviruses RNA evolution in vitro Evolutionary biotechnology RNA aptamers, artificial ribozymes, allosteric ribozymes Riboswitches controlling Gene silencing by transcription and translation small interfering RNAs Functions of RNA molecules through metabolites

5' - end N 1 O CH 2 O GCGGAU UUA GCUC AGUUGGGA GAGC CCAGA G CUGAAGA UCUGG AGGUC CUGUG UUCGAUC CACAG A AUUCGC ACCA 5'-end 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 � O Definition of RNA structure O OH N 4 O P O CH 2 O Na � O O OH 3' - end O P O Na � O

Examples of ‘natural selection’ with RNA molecules

Genotype = Genome Mutation GGCUAUCGUACGUUUACCCAAAAAGUCUACGUUGGACCCAGGCAUUGGAC.......G Fitness in reproduction: Unfolding of the genotype: Number of genotypes in RNA structure formation the next generation Phenotype Selection Evolution of phenotypes

Genotype = Genome Mutation GGCTATCGTACGTTTACCCAAAAAGTCTACGTTGGACCCAGGCATTGGAC.......G Fitness in reproduction: Unfolding of the genotype: Number of genotypes in Development the next generation Phenotype Selection Evolution of phenotypes

Genotype = Genome Mutation GGCTATCGTACGTTTACCCAAAAAGTCTACGTTGGACCCAGGCATTGGAC.......G Fitness in reproduction: Unfolding of the genotype: Number of genotypes in Development the next generation Phenotype Selection Evolution of phenotypes

Reaction Mixture Stock Solution Replication rate constant: f k = � / [ � + � d S (k) ] � d S (k) = d H (S k ,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

Replication rate constant: f k = � / [ � + � d S (k) ] � d S (k) = d H (S k ,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

Randomly chosen Phenylalanyl-tRNA as initial structure target structure

Formation of a quasispecies in sequence space

Migration of a quasispecies through sequence space

Genotype-Phenotype Mapping Evaluation of the = � ( ) S { I { Phenotype S { I { ƒ f = ( S ) { { f { Q { f 1 j Mutation f 1 I 1 f 2 f n+1 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 { I 4 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 )

Number of relay step 36 38 40 42 44 44 Time Evolutionary trajectory 1250 Relay steps 0 10 Average structure distance to target dS � Endconformation of optimization

Number of relay step 36 38 40 42 44 44 Time Evolutionary trajectory 1250 43 Relay steps 0 10 Average structure distance to target dS � Reconstruction of the last step 43 � 44

Average structure distance to target dS 36 � Relay steps Number of relay step 38 10 40 42 44 Evolutionary trajectory 0 1250 Time 42 43 44 Reconstruction of last-but-one step 42 � 43 ( � 44)

Number of relay step 36 38 40 42 44 44 Time Evolutionary trajectory 1250 43 Relay steps 0 10 42 Average structure distance to target dS � Reconstruction of step 41 � 42 ( � 43 � 44) 41

Average structure distance to target dS 36 � Relay steps Number of relay step 38 10 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 38 10 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