1. Kevin Correia, Goutham Vemuri, Radhakrishnan Mahadevan Pathway Tools Conference, Menlo Park, CA March 6 th, 2013 Elucidating the xylose metabolising properties of Scheffersomyces stipitis using a genome scale metabolic model

2. Overview Challenges with lignocellulose fermentation Xylose metabolism in yeast Nature’s lignocellulose metabolizer: Scheffersomyces stipitis S. stipitis genome-scale metabolic models Exploring xylitol production mechanisms Conclusions and Future Work

3. Lignocellulose fermentation Lignocellulose feedstocks offer a sustainable source of biomass for biofuels and biochemicals They contain a variety of fermentable sugars: glucose, xylose, arabinose Xylose content can range from 10-30% of the biomass in softwood, hardwood, and herbaceous agriculture residue

4. Pentose fermentation in S. cerevisiae Wild-type Saccharomyces cerevisiae cannot efficiently ferment pentose sugars: xylose and arabinose S. cerevisiae has been genetically engineered to metabolise xylose via: –Yeast oxidoreductive pathway (Scheffersomyces stipitis) –Bacterial isomerase pathway (Thermus thermophilus) Xylitol accumulates as a by-product with the yeast pathway due to a cofactor imbalance

5. Pentose fermentation in yeasts Two enzymes exists in yeast for xylose reductase: –NADPH-dependent xylose reductase (Candida utilus) –NADPH/NADH-dependent xylose reductase (Scheffersomyces stipitis, Pachysolen tannophilus) C. utilus has excessive xylitol production P. tannophilus produces 13-30% xylitol under oxygen limiting conditions This suggests other redox balancing mechanisms exist in S. stipitis

6. Scheffersomyces stipitis Found in the gut of wood digesting beetles Can ferment all major components of lignocellulos biomass: glucose, mannose, xylose, arabinose, rhamnose, cellobiose 48% ethanol yield from xylose Little to no xylitol production

7. Scheffersomyces stipitis: genome scale metabolic models iBB814: Balaji Balagurunathan et al. Reconstruction and analysis of a genome-scale metabolic model for Scheffersomyces stipitis. Microbial Cell Factories 2012, 11:27 iSS884: Caspeta et al. Genome-scale metabolic reconstructions of Pichia stipitis and Pichia pastoris and in silico evaluation of their potentials. BMC Systems Biology 2012, 6:24 iTL885: Liu et al. A constraint-based model of Scheffersomyces stipitis for improved ethanol production. Biotechnology for Biofuels 2012, 5:7

8. iBB814: Xylose reductase study

10. In silico production of xylitol Balaguruthan, Caspeta and Liu show that xylitol is not a fermentation by- product in their models, but fail to explore metabolic mechanisms Simulations in our study show that arabinitol is a byproduct during ethanol fermentation, and xylitol if FVA is used Jeppsson et al. Appl Environ Microbiol. 1995 July; 61(7): 2596–2600.

11. Study objectives Develop a comprehensive S. stipitis model by reviewing the published models and literature Run batch and chemostat experiments to fine-tune model parameters; analyse gene expression Evaluate metabolic mechanisms that lead to xylitol production Overlay chemostat and gene expression data over the metabolic model to gain insight into regulation in S. stipitis metabolism

12. Proposed mechanisms leading to reduced xylitol production 1. Xylose reductase cofactor specificity 2. Crabtree effect and robustness analysis 3. Alternative oxidase 4. Suboptimal growth

13. Xylitol yield sensitivity to aeration and XR cofactor specificity

14. Xylitol yield and the Crabtree effect Crabtree positive yeasts have high uptake rates of substrate and low uptake of oxygen Crabtree negative yeasts have lower substrate uptake rates and metabolism is sensitive to oxygen uptake

15. Redox balancing with alternative oxidase Joseph-Horne et al. Biochim Biophys Acta. 2001 Apr 2;1504(2-3):179- 95.

16. Xylitol yield sensitivity to AOX

17. Ethanol yield sensitivity to AOX

18. Xylitol yield and suboptimal growth An alternative mechanism to account for low xylitol yields in S. stipitis is suboptimal growth S. stiptis often has lower growth rate in microaerobic conditions when grown on xylose, relative to glucose

19. Succinate bypass Jeffries (2009) proposed a succinate bypass that allows S. stipitis to convert NADH to NADPH

20. NADPH production envelope Simulations show that the bypass leads to suboptimal growth compared to NADH kinase

21. Conclusions We compiled a comprehensive S. stipitis genome scale model from published and unpublished models We evaluated metabolic mechanisms leading to xylitol production –Cofactor specificity, suboptimal growth and oxygen sensitive metabolism have a greater sensitivity to xylitol yield than alternative oxidase

22. Next steps Integrate chemostat results, metabolic model, and gene expression Perform additional experiments in different conditions to explore xylitol production in S. stipitis

23. Acknowledgments Dr. Radhakrishnan Mahadeven, University of Toronto Peter Y. Li, University of Toronto Dr. Goutham Vemuri, BioAmber Xin Wen, University of Guelph Dr. Hung Lee, University of Guelph Bioconversion Network