1. A design for cellular evolutionary computation by using bacteria 2004.07.22

2. Introduction Molecular Evolution –Various nucleotide sequences generation Single-base substitution in the polynucleotides Crossover method –DNA shuffling, Block shuffling –Evaluation and Selection Cellular Evolution –Vast array of genes –Complex interaction and networking –Optimization of gene expression

3. Design of Cellular Evolutionary Computation

4. Coding Male and female plasmids –An array of genes –Equivalent and interchangeable except for the region of antibiotic resistance gene (Tc R, Cm R ) –All plasmids have same set of genes and only promoter regions are variable

5. Crossover Step1 –Plasmid  E. coli –Culture under both antibiotic substances –One point crossover between circular plasmids  double length fusion plasmid –Extraction Step2 –Plasmid  E. coli –Incubation under both antibiotic substances –Crossover between homologous sequences fusion plasmid  single size plasmid –Extraction Step3 –Delete residual fusion plasmids Split  EcoRV, EcoRI digestion Combine after deactivation of enzymes

6. Selection and Restore Selection –Plasmid  Cell –Dispersion to the LB agarose plate and incubation –Colony selection by selection criteria Restore –To avoid early convergence, the selected plasmids are combined to a plasmid library at the final step of each generation

7. Preliminary Experiment

10. Discussion Why two-phase crossover –Minimize the loss of population variety Two-point crossover occurs with low frequency. After phase 1  double size fusion plasmid by one- point crossover Double size fusion plasmids are allowed to grow at first to maintain the diversification of the population. They are deleted after generation of single size plasmids. Population size –About 10 Because of picking up colony by hand.