1. Functional and Evolutionary Attributes through Analysis of Metabolism Sophia Tsoka European Bioinformatics Institute Cambridge UK

2. Outline Metabolic reconstruction in a variety of species Analysis of sequence to function in metabolism Evolution of metabolic enzymes and pathways Gene fusion analysis in enzymatic sets

3. Enzyme Dataset Characterisation –Experimental information for the entire known metabolic complement of E. coli –Representation of metabolic pathways includes reactions compounds stoichiometry isozymes … etc –Powerful query capabilities using lisp, java

4. Metabolic Reconstruction - 1 Tsoka, Simon, Ouzounis, Archaea, 1(4), 223, 2004 For genome characterisation Methanococcus jannaschii 40% of genome archaeal-specific 1792 proteins 130 pathways (22 complete) 297 reactions identified 609 reaction frames 461 enzymatic reaction frames 510 compound framesc

5. Metabolic Reconstruction - 2 For drug target discovery Plasmodium falciparum 5366 proteins 122 pathways 697 reactions 861 enzymatic reaction 525 compounds 216 chokepoint reactions as drug targets Yeh, Hanekamp, Tsoka, Karp, Altman, Genome Research, 14, 917, 2004

6. Molecular and Functional Diversity of Metabolic Pathways  Associate enzyme sequence and function for E. coli small-molecule metabolism set –Sequence: enzyme families –Function: reaction types and pathways  How many enzyme families changed in function?  How easily is each new function invented?  Provide insight to: –function prediction based on sequence homology –evolution of biochemical pathways Tsoka & Ouzounis, Genome Research, 11, 1503-1510, 2001

7. E. coli enzyme dataset  548 enzymes –208 monomers –348 complexes –132 pathways Taxonomic groups  non-redundant set of all known protein sequences SwissProt+TrEMBL Archaea - (21K) Bacteria - (139K) Eukarya –Protista(17K) –Fungi(24K) –ViridiPlantae(72K) –Metazoa(187K) Viruses - (122K) Evolution of Metabolic Networks Peregrin-Alvarez, Tsoka, Ouzounis, Genome Research, 13, 422-427, 2003

8. How Conserved is Small-Molecule Metabolism across Taxonomic Groups? Are ‘Other’ Proteins More/Less Conserved than Metabolic Enzymes? Bacterial enzymes are less-species specific … … and more phylogenetically diverse, compared to control samples

9. Sequence-based prediction of protein interactions phylogenetic profiles (Pellegrini et al. PNAS, 96, 4286, 1999) gene order – (Dandekar et al. Trends Bioch. Sci. 324, 1998) gene clusters –(Overbeek et al. PNAS, 96, 2896, 1999) gene fusion – (Enright et al. Nature, 402, 86, 1999, Marcotte et al. Science, 285, 751, 1999) Computational Prediction of Protein Interactions A Gene Fusion Event Is Fusion Frequency in E. coli Enzymes Higher than in Other Classes of Proteins? Tsoka & Ouzounis, Nature Genetics, 26, 141-142, 2000

10. Conclusions Analysis of sequence to function in metabolic networks Evolution of metabolic enzymes and pathways Genome constraints as a means to detect protein interactions Analysis of entire genomes has the potential to discover the organisational principles of cells and the mechanisms of their evolution

11. Acknowledgements  Medical Research Council  Computational Genomics Group, EBI Christos Ouzounis Jose Manuel Peregrin-Alvarez Leon Goldovsky  Russ Altman and Iwei Yeh  Peter Karp.. and his group