1. Pathogenomics: Focusing studies of bacterial pathogenicity through evolutionary analysis of genomes

2. Pathogenomics Goal: Identify previously unrecognized mechanisms of microbial pathogenicity using a unique combination of informatics, evolutionary biology, microbiology and genetics.

3. Explosion of data 23 of the 37 publicly available microbial genome sequences are for bacterial pathogens Approximately 21,000 pathogen genes with no known function! >95 bacterial pathogen genome projects in progress …

4. The need for new tools Prioritize new genes for further laboratory study Capitalize on the existing genomic data

5. Bacterial Pathogenicity Processes of microbial pathogenicity at the molecular level are still minimally understood Pathogen proteins identified that manipulate host cells by interacting with, or mimicking, host proteins

6. Approach Idea: Could we identify novel virulence factors by identifying pathogen genes more similar to host genes than you would expect based on phylogeny?

7. Prioritize for biological study. - Previously studied in the laboratory? - Can UBC microbiologists study it? - C. elegans homolog? Search pathogen genes against databases. Identify those with eukaryotic similarity. Evolutionary significance. - Horizontal transfer? Similar by chance? Modify screening method /algorithm Approach

8. Pathogens Chlamydophila psittaci Respiratory disease, primarily in birds Mycoplasma mycoides Contagious bovine pleuropneumonia Mycoplasma hyopneumoniae Pneumonia in pigs Pasteurella haemolytica Cattle shipping fever Pasteurella multicoda Cattle septicemia, pig rhinitis Ralstonia solanacearum Plant bacterial wilt Xanthomonas citri Citrus canker Xylella fastidiosa Pierce’s Disease - grapevines Bacterial wilt

9. World Research Community Approach Prioritized candidates Study function of homolog in model host (C. elegans) Study function of gene in bacterium. Infection of mutant in model host C. elegans DATABASE Collaborations with others

10. Fundamental research Interdisciplinary Major potential impact Lack of fit with alternative funding sources Peter Wall Major Thematic Grant

11. Database front end

12. Haemophilus influenzae Rd-KW20 proteins most strongly matching eukaryotic proteins

13. PhyloBLAST – a tool for analysis Brinkman et al. Bioinformatics. Accepted

15. Eukaryote Bacteria Horizontal Transfer? 0.1 Rat Human Escherichia coli Caenorhabditis elegans Pig roundworm Methanococcus jannaschii Methanobacterium thermoautotrophicum Bacillus subtilis Streptococcus pyogenes Aquifex aeolicus Acinetobacter calcoaceticus Haemophilus influenzae Chlorobium vibrioforme E. coli Guanosine monophosphate reductase 81% similar to corresponding enzyme in humans and rats Role in virulence not yet investigated.

16. Variance of the Mean %G+C for all Genes in a Genome: Correlation with bacteria’s clonal nature nonclonal clonal

17. Variance of the Mean %G+C for all Genes in a Genome Is this a measure of clonality of a bacterium? Are intracellular bacteria more clonal because they are ecologically isolated from other bacteria?

18. Pathogenomics Project: Future Developments Identify eukaryotic motifs and domains in pathogen genes Identify further motifs associated with Pathogenicity islands Virulence determinants Functional tests for new predicted virulence factors

19. Peter Wall Institute for Advanced Studies Pathogenomics group Ann M. Rose, Yossef Av-Gay, David L. Baillie, Fiona S. L. Brinkman, Robert Brunham, Stefanie Butland, Rachel C. Fernandez, B. Brett Finlay, Hans Greberg, Robert E.W. Hancock, Steven J. Jones, Patrick Keeling, Audrey de Koning, Don G. Moerman, Sarah P. Otto, B. Francis Ouellette, Ivan Wan. www.pathogenomics.bc.ca