1. Tricks and improvements in Structural Genomics Chantal Abergel Structural and Genomic Information Laboratory UMR 2589-CNRS, IBSM, 31 chemin J. Aiguier, 13009 Marseille, FRANCE http://www.igs.cnrs-mrs.fr

2. Microbial Genomics Bioinformatics Structural Genomics Mimivirus - T. whipplei - M. timonensis - A. baumannii Functional Genomics Experiments R. felis - R. africae - R. belli - R. massiliae, R. conorii - Exploration of microbial genomes Fundamental: surprises Directed: biomedical

3. Structural genomics projects: TargetDB Escherichia coli Orfan genes Conserved genes of unknown function search for new antibiotic targets PROFUN : search for new antifungal targets Saccharomyces cerevisiae: Essential genes conserved in fungi absent in vertebrate genomes Candida albicans: Conserved in fungal pathogens absent in vertebrate genomes

4. MasterDB

5. ~ 300 Targets

6. Incomplete Factorial Design: Experimental matrix (SAmBa) Automated protocol, 12 conditions (out of 96 possible) 4 strains 3 temperatures 3 growth media

7. Dot Blot for recombinant protein detection  Total extracts and soluble extracts (supernatant after centrifugation) deposited on nitrocellulose membranes  Use of anti (his) 5 antibody coupled HRP (Qiagen)  ECL detection Dot blot statistical analysis Soluble expression condition Up to 12 proteins tested a day 90% Rosetta 17°C 2YT

8. Microdialysis Affinity purification Scale up (1L culture) pI Non ionic ionic pH Overnight dialysis OD total OD soluble

9. Desalting Concentration Best buffer: OD total /OD soluble ~1 λ nm Absorbance

10. Electrophoresis (native, IEF, SDS) N-terminal Sequencing /Mass Spectrometry Circular Dichroïsm Dynamic light scattering Stability over time Biochemical & Biophysical Characterization Purification optimization Crystallization Stability of produced proteins ? Folding ? Protein solution monodispersity

11. Combinatorial approach Functional & Structural predictions Functional & Structural predictions Bioinformatics Bioinformatics sequence homologies (BMCD) binding motif, hypothetical ligand, co-factors… Electrophoresis (native, IEF…) Electrophoresis (native, IEF…) Set of variables to be tested

12. SAmBA: For crystallization prospection www.igs.cnrs.fr/samba

13. Tecan diluting distributing robot 8 needles Greiner crystallization plates 5x96 wells

14. Promising crystals...

15. In house testing...

16. Poor diffraction

17. Soaking/desiccation

18. YbgL Step 1

19. Step 2 YbgL

20. Final YbgL

21. YggV Step 1

22. Final YggV

23. CA0996 Step 1

24. Final CA0996

25. What do they have in common ? (1) Mol. weight (kDa) Oligomerization Space group Cell dimension (Å) Molecule per AU YbgL26monomerC2C2 a = 70.3 b = 36.7 c = 79.7 β = 3.5 1 YggV21monomerP4 3 2 1 2 a = 78 c = 7.9 1 CA099616dodecamerP222 a = 93 b = 304.5 c = 155.5 24

26. What do they have in common ? (2) Crystallization conditions CryoprotectantSoaking time Dataset Resolution ESRF YbgL Sodium citrate pH 9.15 Ethylene glycol 10% 2h FIP :2.29 Å R merge : 5.8% (28.7) YggV (NH 4 ) 2 SO 4 pH 9 glycerol 10%30 mins ID14: 2.0 Å R merge : 6.4 % (29.3) CA0996 PEG8000 LiSO 4 pH 7 glycerol 10 %15 minsFIP: 3.0

27. Experimental Team Sabine Chenivesse Sophie Cozzani Céline Deregnaucourt Sandra Jeudy Marjorie Varagnol Bioinformatics Team Hiroyuki Ogata Stéphane Audic Olivier Poirot Pr. Jean-Michel Claverie