Systems biology and biotechnology

1. Systems biology and biotechnology Ž. Kurtanjek, H. Žilić, A. Jurinjak Tušek University of Zagreb, Faculty of Food Technology and Biotechnology Zagreb, Croatia

2. Content 1) From mathematical models in biology to BST biological systems theory 2) Data driven systems theory: high-throughput “omic” systems and internet based global cooperative project 3) Basic mathematical systemic views and genome based biotechnology 4) Emerging biotechnology innovations on interface of systems and synthetic biology 5) Our case studies: E. coli PTS regulation, synergy analysis in the glycogenoloysis flux S. cerevisiae ergosterol and sphingolipids pathways 6) Conclusions

3. What is systems biology and what it promises? Systems biology presumes that we can understand a living cell on a molecular level as a goal oriented system (a cybernetic view) and represent this knowledge as a “life in silico” or as a computer program. From industrial view point, systems biology has led to the new paradigm of “genome based biotechnology”. • It promises: • Improvements of existing technologies by process parameter optimization • Better microbial strain selection • New industrially important products • Tailoring of cell metabolism by genetic engineering • Invention of new “synthetic life and molecules” for industrial purpose Are the promises realistic??? Richard Feynman, ‘‘What I cannot create, I do not understand.’’

4. Change of paradigm ofclassical biotechnology (strain selelectio, substrate optimization, reaqctor intensificatio, process control) to genome based biotechnology (exploit and engineer at genome molecular leve)l Motivation: to exploit full knowledge at cellular level for new industrial process (pharmaceuticals, energy, food, ..) The change of the required paradigm could be given by systemsbiology. Systemsbiology recognizes that only very rarely a given biological functionstrictly depends upon on a single gene product, but rather it is generated by the dynamic interaction of hundreds or thousands of gene products.

5. Systems biology is considered as “top down “ approach. Genetic engineering (recombinant DNA technology) and synthetic biology is seen as a “bottom up” approach. A new biotechnology emerges from the intersections of the both approaches. New biotechnology will emerge not as products of interpolation of isolated gene, but it is generated on a system level as an emergent property by their interactions structured in a network, controlled by small molecule signaling networks. The expectation are very high and uncertain and require collective effort of global scientific community. On academic level systems biology require “open source” approach with massive Internet data basis of bioinformatics from biological “high throughput” studies and highly sophisticated mathematical algorithms (soft tools).

6. BST white biotechnology promises or reality ? Cell factory for advanced biofuell production (beyond ethanol) Yeast Saccharomyces cerevisiae is already the most intensively researched and applied microbial cell factory. Its robustness under process conditions, genetic accessibility and a strong fundamental knowledge base in physiology and systems biology contribute makes it a ‘general purpose’ metabolic engineering platform. The ‘holy grail’ of current yeast bioethanol research is to efficiently express all enzymes (systemic interaction) required for: ► effective feedstock hydrolysis (decisive cost factor), ► reduction of gycerol production ► cell robustness ► interaction of yeast cells with solid substrates ►·······

7. Systemic concept of cell factory platforms for production of advanced biofuells (high energy content, lower emissions, lower hydroscopic, better gasoline miscibility): ►butanols (Du Pont S.cerevisae higher yield than E. coli), ►sesquiterpenes (jet fuel, diesel), ►fatty acid derived biofuels. Jens Nielsen, Christer Larsson, Antonius van Maris and Jack Pronk, Current Opinion in Biotechnology 2013, 24:1–7

8. BST systemic tools: • Major BST toolboxes: • software (data bases and mathematical algortihms) • optimization box • control box

10. COPASI is a simulator for biochemical networks. It is a joint project by the Mendes group (VBI and University of Manchester) and the Kummer group (University of Heidelberg and EML Research)

11. BST systemic tools: Optimization box ►Constrained multidimensional Paretto optimization of integration of thermodynamic information in genome-scale metabolic network models. ►Network topological analysis ►Linear algebra analysis os stoichiometric matrix solution space

12. Tool box for metabolic network control Fluxcontrol coefficients Concentration control coefficients Elasticities are defined by:

13. Probabilistic metabolic network model

14. Metabolic network of E. coli central metabolism Ana Tusek, Christian Lorenz Müller,  Jochen Supper, Andreas Zell, Želimir Kurtanjek, and Ivo F. Sbalzarini: "A Systems Biology Markup Language Model of a T-Cell Receptor Activated Signal Transduction Network", Proceedings of 29-thITI2007 D. Degenring, C. Fromel, G. Dikata, R. Takors., Journal of Process Control, 14 (2004) 729-745

15. A. Tušek, Ž. Kurtanjek, “Model and global sensitivity analysis of E. coli central metabolism”, Proceedings MATHMOD 09 Vienna Ž. Kurtanjek, „Probabilistic Metabolic control Analysis“, Systems Biology of Microorganisms, 22-24, March, 2010, Paris, France

16. A. Tušek, Ž. Kurtanjek, “Model and global sensitivity analysis of E. coli central metabolism”, Proceedings MATHMOD 09 Vienna Ž. Kurtanjek, „Probabilistic Metabolic control Analysis“, Systems Biology of Microorganisms, 22-24, March, 2010, Paris, France

17. Gly Pi G1P G6P PCr Cr F6P ATP ATP ADP ADP FBP DHAP ATP ADP GAP NAD+Pi NADH 1,3 BPG AMP ADP P3G ADP Pi P2G AMP PEP ATP ADP PYR NADH NAD LAC JLAC The relative measures, here termed as synergism Syn of the input interactions, are evaluated by ratio of the variances Ž. KURTANJEK: Synergism in Biochemical Networks, Food Technol. Biotechnol. 48 (3) (2010)

18. Ergosterol pathway

19. Alvarez-Vasquez, F., Riezman, H., Hannun, Y.A., Voit, E.O. (2011) Mathematical Modeling and Validation of the Ergosterol Pathway in Saccharomyces cerevisiae. PloS ONE. 6, 1-17. Cell Designer model; Hrvoje Žilić, “MATHEMATICAL PARAMETER ANALYSISOF ERGOSTEROL BIOSYNTHESIS PATHWAY, Masters diploma, University of Zagreb, PBF, Zagreb, 2013

20. Hrvoje Žilić, “MATHEMATICAL PARAMETER ANALYSISOF ERGOSTEROL BIOSYNTHESIS PATHWAY, Masters diploma, University of Zagreb, PBF, Zagreb, 2013 Heat map of flux sensitivities for ergosterol synthesis

21. Hrvoje Žilić, “MATHEMATICAL PARAMETER ANALYSISOF ERGOSTEROL BIOSYNTHESIS PATHWAY, Masters diploma, University of Zagreb, PBF, Zagreb, 2013 Heat map of flux sensitivities for sphingolipid synthesis

22. Conclusions BST is integrative science between molecular biology, mathematics, informatics, (bio)chemistry, physics(“window of opportunity for Croatian academic institutions”) BST expected results are presently “over optimistic” but are becoming realistic Large industrial companies are highly investing in BST for new biotechnology Richard Feynman, ‘‘WhatI cannot create (life), I do not understand.’’ Nature knows how to do it ! Presently humans can do it only in parts, but “future” is possible!