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The Eli and Edythe L. Broad Institute

Lessons learned from the Genome -scale metabolic reconstruction and curation of Neurospora crassa. Jeremy Zucker Jonathan Dreyfuss Heather Hood James Galagan. The Eli and Edythe L. Broad Institute

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The Eli and Edythe L. Broad Institute

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  1. Lessons learned from the Genome-scale metabolic reconstruction and curation of Neurosporacrassa Jeremy Zucker Jonathan Dreyfuss Heather Hood James Galagan The Eli and Edythe L. Broad Institute A Collaboration of Massachusetts Institute of Technology, Harvard University and affiliated Hospitals, and Whitehead Institute for Biomedical Research

  2. Capture Metabolic Knowledge Pathway-tools/BioCyc KEGG • Reactions • Interactions • Literature

  3. Visualizing ‘omics Data Provide a visually intuitive, metabolic framework for interpreting large ‘omics datasets

  4. in silico Predictions AlgorithmicallyInterpret Expression Data in a Metabolic Context?

  5. Example: Plasmodium Eflux* • Validation • KO Phenotype Predictions – 90% Accuracy • External Metabolite Changes – 70% Accuracy • New Predictions • 40 Enzymatic drug targets • Experimental validation of novel target *Colijn, C., A. Brandes, J. Zucker, et al. (2009). PLoSComputBiol

  6. Modeling in the Neurospora PO1 Clock Profiling Visualization and Analysis RNA-Seq ChIP-Seq Interpretation of Expression Profiling and Regulatory Network Data in a Metabolic Context – Inform Experiments

  7. Building The MODEL

  8. Manual reconstruction protocol Nature Protocols, Vol. 5, No. 1. (07 January 2010), pp. 93-121.

  9. Automated Model SEED reconstruction pipeline Nature biotechnology, Vol. 28, No. 9. (29 September 2010), pp. 977-982

  10. Genome sequence to metabolic model Elements Pathways Literature Metadata Nutrient media (Vogels) Complexes Reactions NeurosporaCyc Biomass composition Transporters

  11. EFICAz2 predicts enzymes Databases 1993 enzymes 1770 reactions 9934 protein sequences HMMs FDR … Decision tree SVM BMC Bioinformatics 2009, 10:107

  12. Protein Complex editor 31 complexes experimentally validated through literature search 182 reactions with isozymes or complexes Identify multiple genes of reaction Present all possible combinations of complexes 2-oxoisovalerate complex • 2-oxoisovalerate alpha subunit • 2-oxoisovalerate beta subunit • … • fatty acid synthase beta • subunit dehydratase • fatty acid synthase alpha • subunit reductase … Allow curator to validate potential complexes Fatty acid synthase complex

  13. Transport inference parser (TIP) 176 transporters assigned to 97 transport reactions Filter proteins for transporters 9934 free-text Protein annotations Infer multimeric complex • MFS glucose transporter • ATP synthase • … • sucrose transporter Infer substrate … Infer energy-coupling mechanism Bioinformatics (2008) 24 (13): i259-i267.

  14. Pathologic predicts pathways 1770 enzyme- catalyzed reactions 265 Pathways X = #rxns in metacycpwy … Y = #rxns with enzyme evidence … Z = #unique rxns in pwy P(X|Y|Z) = prob of pwy in Neurospora Science 293:2040-4, 2001.

  15. Literature curation validates predictions 1212 citations associated with 307 pathways 31 complexes 168 genes … …

  16. Neurospora Cellular overview

  17. neurosporaCYC

  18. New feature on Broad website

  19. NeurosporaCyc Cellular overview

  20. NeurosporaCyc cellular overview

  21. Googlemaps-like zoomable interface

  22. Highlight genes on overview

  23. Highlight genes on overview

  24. Highlight genes on overview

  25. NeurosporaCycOmics Viewer

  26. Omics data mapped onto metabolism

  27. Omics data mapped onto metabolism

  28. Omics data mapped onto metabolism

  29. Omics data mapped onto Genome

  30. Omics data mapped onto Genome

  31. Omics data mapped onto Genome

  32. Debugging the Bug

  33. The problem with EC numbers

  34. Generic Reactions

  35. 3.6.1.42 instance of 3.6.1.6?

  36. Protein Modification reactions

  37. Reactions with instanceless classes

  38. Solution: Instantiate classes

  39. Generic Redox reactions

  40. Polymeric reactions

  41. Polymerization Pathway reactions

  42. Solution: Instantiate polymerization steps • POLYMER-INST-Fatty-Acids-C16 + coenzyme A + ATP -> POLYMER-INST-Saturated-Fatty-Acyl-CoA-C16 + diphosphate + AMP + H+ • POLYMER-INST-Fatty-Acids-C14 + coenzyme A + ATP -> POLYMER-INST-Saturated-Fatty-Acyl-CoA-C14 + diphosphate + AMP + H+ • … • POLYMER-INST-Fatty-Acids-C0 + coenzyme A + ATP -> POLYMER-INST-Saturated-Fatty-Acyl-CoA-C0 + diphosphate + AMP + H+

  43. What happens when the metabolic network is infeasible? • Add a “reaction” with the smallest number of reactants and products that results in a feasible model minimize card(r) subject to Sv + r = 0 l ≤ v ≤ u

  44. Fast Automated Reconstruction of Metabolism • Input: • EFICAz probabilities for each reaction • Biomass components • Experimental growth / no growth phenotypes in different nutrient conditions • Gene essentiality • Manual curation of pathways • Output: • Metabolic network of MetaCyc reactions maximally consistent with input

  45. Validating the model with in silico knockout predictions

  46. Neurospora phenotypes for validation Neurosporae-Compendium 29 Mutants essential on minimal media Non-essential on supplemental media PO1 Phenotype Collection 79 non-essential KOs under minimal media Additional phenotypes are observed. Used FBA with Neurospora model to simulate gene knockouts in minimal medium

  47. Neurospora phenotype prediction results

  48. Comparison of model organisms under minimal media [1] Genome Res. 2004. 14: 1298-1309 [2] Molecular Systems Biology 2007 3:121

  49. Modeling the effect of oxygen limitation on xylose fermentation

  50. Biofuels from Neurospora? • Growing interest for obtaining biofuels from fungi • Neurosporacrassahas more cellulytic enzymes than Trichodermareesei • N. crassacan degrade cellulose and hemicellulose to ethanol [Rao83] • Simultaneous saccharification and fermentation means that N. crassais a possible candidate for consolidated bioprocessing Xylose Ethanol

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