Integrative in silico reconstruction of Fe-S biogenesis pathway in yeast.

1. Integrative in silico reconstruction of Fe-S biogenesis pathway in yeast. RuiAlves CienciesMèdiquesBàsiques Universitat de Lleida ralves@cmb.udl.es http://web.udl.es/usuaris/pg193845/Courses/Other%20Seminars/

2. Index of talk Network Reconstruction for Novel Pathways Integrative in silicoreconstruction of Fe-S biogenesis pathway in yeast. Summary & Perspectives

3. Introduction • Understanding pathway assembly and function is fundamental to the understanding of how a cell works. • In annotated genomes, network of cellular pathways is “known”. • Mapping orthologues onto known maps (KEGG, BIOCYC, etc.). • However, regulatory topology is organism specific. • Nevertheless, reconstructing the topology of new pathways can not be done by mapping. • No maps available. • How to reconstruct?

4. Oriented reconstruction • Traditionally, identification & reconstruction of a pathway/circuit would entail painstaking, mostly blind, experimental work. • Currently, availability of “omics” data provides information to facilitate this task. • Computational Biology and Bioinformatics. • Integrate information, predict systemic behavior and rank hypothesis for experimental testing • Facilitates a better understanding of how cellular systems work.

5. Objective of the research line • Develop and apply coherent yet flexible framework where different computational methods and data sets are integrated to predict the connectivity of biological pathways & circuits. • Today: focus on the biology and the reconstruction of FeS cluster biogenesis in yeast S. cerevisiae.

6. Index of talk Network Reconstruction for Novel Pathways Integrative in silicoreconstruction of Fe-S biogenesis pathway in yeast. Summary & Perspectives

7. S Protein Cysteine Protein Cysteine Fe Fe S Fe-S clusters • Iron-Sulfur Clusters are coordinated ions that participate in electron transfer. e- e-

8. What is known about FeSC biogenesis • About 15 different mitochondrial proteins are known to be involved in yeast. • The assembly process is ill-understood. • It is unclear how most of the proteins assemble as a pathway and how the activity of this pathway is regulated. • All 15 proteins have one thing in common.

9. Phenotype of FeSC machinery deletion mutants FeSC Dependent Protein Activity Fe Level WT D WT D FeSC dependent protein activity is impaired Fe Accumulates

10. Scaffold Scaffold Scaffold Scaffold Fe S FeSC FeSC Holo-P Apo-P Damaged FeSC Holo-P FeSC biogenesis in a nutshell Grx5 Isa1 Isa2 Isu1 Isu2 Nfu1 Atm1 Nfs1 Arh1 Yah1 Yfh1 Isd11 Ssq1 Jac1 Mge1 Synthesis (S) Transfer (T) Repair (R)

11. The reconstruction method Getproteinstructures (PDB, models) Identifyadditional Genes involved in process Identify Genes involved in process 2. Phylogeneticanalysis 1. Bibliometricanalysis 2. Interrogate 2H databases 3. In silicoproteindocking Process of interest Genes with similar co-evolutionprofiles List of reportedTwo-hybridinteractions List of predictedinteractions Humancuration ExpertKnowledge New Simulationexperiments Validatedmodels Createmathematicalmodelsforeachalternativenetwork Derive alternativenetworkstructures No ValidModel 4. Simulation and comparisonto experimental results Falsifiedmodels

12. 1. Literature-basednetworkreconstruction • Literature co-occurence of genes can be taken as a signal that they are functionaly related and maybe interact physically. • iHOP performes this type of analysis automatically.

13. Weuse a textminerthatanalyzes full text of documentsliveoverthe web

14. Database of proteins in fullysequencedgenomes Database of profilesforeachprotein in eachorganism 2. Usingphylogeneticprofilestopredictproteininteractions Proteinsthat are present and absent in thesame set of genomes are likelytobeinvolved in thesameprocess and thereforeinteract. Sequence (Grx5) Protein id Grx5 Calculatecoincidenceindex.

15. 3. Low level study of docking interactions in silico Sequence with known structure. …SSQIE… …SSQEE… Homologue sequence for structure prediction. THREAD DOCK OPTIMIZE Differential scores for docking to different targets.

16. 4.Studying the effect of a protein: The modeling Grx5,… Nfs1-SSG Nfs1 • Use approximate formalism: • Power Law Formalism • No need for detailed mechanism. • Semi quantitative estimation of many parameter values. g<0 inhibits flux. g=0 no influence on flux. g>0 activates flux.

17. Studying the effect of a protein: the modelling • Create models for alternative networks. • Normalize equations and scan parameters to see what happens when a gene is deleted from the model. • Compare simulations with known systemic behavior to validate or invalidate alternatives.

18. Grx5 is involved in FeSC biogenesis in S. cerevisiae • Glutaredoxin: • Mediatesglutathionylationstate of Cysresidues. • Maymediateprotein-proteindisulfide bridge reduction (Belli et al. 2002, Tamarit et al. 2003, JBC). • FeSCcoordinate (mostly) withCysresidues. • Is Grx5 regulation of Cysreductionstate in anyspecificprotein(s) involved in FeSCbiogenesissufficientforphenotype?

19. Possible partners of Grx5 in FeSC biogenesis Bibliography Docking Phylogeny+ Docking Scaffolds Isu1 Isa1 Isa2 Nfs1 Grx5

20. 1 1 0.5 0.1 0.1 WT D Model reproduces effect of gene deletion on protein activity if Grx5 recovers Nfs1 activity FeSC Dependent Protein Activity 10000s of simulations 0.5 Recovering Nfs1 and Scaffold Not recovering Nfs1 and Scaffold Belli et al. 2002 MBC 13:1109

21. Model reproduces effect of gene deletion on protein activity if Grx5 recovers Nfs1 activity Fe Levels 10000s of simulations 1 1 WT D Not recovering Nfs1and Scaffold Recovering Nfs1 and Scaffold Belli et al. 2002 MBC 13:1109

22. No Predictions: Possible Modes of action for Grx5 Grx5 modulates Nfs1 and Scaffold activity/Interactions. Reproducing experimental phenotype? 6 9 Yes 3 Nfs1-Scaffold

23. Grx5 Scaffold Positive Control Negative Controls Grx5 interacts with scaffold in two-hybrid assay

24. The proteins and their function Alves & Sorribas 2007 BMC Systems Biology 1:10 Alves et. al. 2004 Proteins 56:354 Alves et. al. 2004 Proteins 57:481 Vilella et. al. 2004 Comp. Func. Genomics 5:328

25. Index of talk Network Reconstruction for Novel Pathways Integrative in silicoreconstruction of Fe-S biogenesis pathway in yeast. Summary & Perspectives

26. Metabolic Reconstruction: FeSC biogenesisThe view from here • Create a FLEXIBLE tool for other researchers. • Automation of text search 75% done; Phylogenetic profiling 75% done, Protein interactions 75% done, Automation of structural modeling & docking 0%. • Data sets very noise, human curation required & very important in the forseeable future.

27. The reconstruction method Getproteinstructures (PDB, models) Identifyadditional Genes involved in process Identify Genes involved in process 2. Phylogeneticanalysis 1. Bibliometricanalysis 2. Interrogate 2H databases 3. In silicoproteindocking Process of interest Add Genomics, Proteomics, Metabolomics, Fluxomics Genes with similar co-evolutionprofiles List of reportedTwo-hybridinteractions List of predictedinteractions Humancuration ExpertKnowledge New Simulationexperiments Validatedmodels Createmathematicalmodelsforeachalternativenetwork Derive alternativenetworkstructures No ValidModel Simulation and comparisonto experimental results Falsifiedmodels

28. Application to other systems • Fe-S Human, chimp, coli, subtilis, xanthus, albicans. • Fe-S biogenesis pathways shows variations in the different organisms we are analyzing (coli, human, chimp, xanthus, subtilis). Design principles? • Signal transduction reconstruction in xanthus.

29. Acknowledgments EnricHerrero FelipVillela Albert Sorribas Ester Vilaprinyo Armindo Salvador FCT (PORTUGAL) MCyT(SPAIN)