1. http://creativecommons.org/licens es/by-sa/2.0/

2. Design Principles in Systems Molecular Biology Prof:Rui Alves ralves@cmb.udl.es 973702406 Dept Ciencies Mediques Basiques, 1st Floor, Room 1.08 Website of the Course:http://web.udl.es/usuaris/pg193845/Courses/Bioinformatics_2007/ Course: http://10.100.14.36/Student_Server/

3. Outline What are design principles  How to study design principles Examples

4. What are design principles? Recurrent qualitative or quantitative rules that are observed in similar types of systems as a solution to a given functional problem Exist at different levels Nuclear Targeting Sequences Operon Gene 1 Gene 2Gene 3

5. Outline Design Principles in Network Topology  Overall Feedback  Signal Transduction  Gene Circuits

6. Regulation by overall feedback X0X0 X1X1 _ + X2X2 X3X3 X4X4 X0X0 X1X1 + X2X2 X3X3 X4X4 ___ Overall feedback Cascade feedback

7. Why overall feedback Why is overall feedback so prevalent?  Hypothesis:  Random thing  Alternative hypothesis:  There are functional advantages to this type of overall feedback that led to its selection and account for its maintenance

8. How to test the alternative hypothesis? 1 – Identify functional criteria that have physiological relevance X0X0 X1X1 _ X2X2 X3X3 + X4X4 Appropriate Flux Flux Responsive to Demand Low concentrations Low gains with respect to supply Low sensitivities to parameter fluctuations

9. How to test the alternative hypothesis? 1 – Identify functional criteria that have physiological relevance X0X0 X1X1 _ X2X2 X3X3 + X4X4 Time [X 3 ] Change in X 4 Fast transient response Stable steady state Fluctuation in X 3

10. Functionality criteria for effectiveness Low concentrations Appropriate fluxes Sharp flux regulation by demand Low log gains to supply Low sensitivities to parameter changes Fast transient responses Large margins of stability

11. How to test the alternative hypothesis? 1 – Identify functional criteria that have physiological relevance 2 – Create Mathematical models for the alternatives S-system has analytical steady state solution Analytical solutions → General features of the model that are independent of parameter values

12. A model with overall feedback X0X0 X1X1 _ + X2X2 X3X3 X4X4 Constant Protein using X 3

13. A model without overall feedback X0X0 X1X1 + X2X2 X3X3 X4X4

14. How to test the alternative hypothesis? 1 – Identify functional criteria that have physiological relevance 2 – Create Mathematical models for the alternatives S-system has analytical steady state solution Analytical solutions → General features of the model that are independent of parameter values 3 – Compare the behavior of the two models with respect to the functional criteria determined in 1 Comparison must be made appropriately

15. Mathematicaly Controlled Comparison Internal Constraints: All processes that are equal must have the same parameter values External Constraints: Parameters that are different are degrees of freedom that the system can use to squeeze out differences (e.g. mutation in catalytic power)

16. Implementing external constraints External Constraint 1: Both systems can achieve the same steady state concentrations AND fluxes Fixes  10 ’ Both systems can achieve the same Log gains to substrate Fixes g 10 ’

17. How to test the alternative hypothesis? 1 – Identify functional criteria that have physiological relevance 2 – Create Mathematical models for the alternatives S-system has analytical steady state solution Analytical solutions → General features of the model that are independent of parameter values 3 – Compare the behavior of the two models with respect to the functional criteria determined in 1 Use a Mathematically controlled comparison

18. Functionality criteria for effectiveness Low Concentrations → Both Systems = Appropriate Fluxes → Both Systems = Sharp flux regulation by demand → Overall Better Low log gains to supply → Both Systems = Low sensitivities to parameter changes → Overall Better Fast transient responses → Overall Better Large margins of stability → Overall worst

19. Complications to the comparisons More complicated models  Results may depend on parameter values Smaller models  How much better or worst?

20. A solution to both problems Use Statistical mathematically controlled comparisons  Sample parameters exhaustively and use statistical methods to analyze the results

21. Functionality criteria for effectiveness Sharp flux regulation by demand → Overall Better ~5-10% Low sensitivities to parameter changes → Overall ~5-10% Better Fast transient responses → Overall Better ~5-10% Large margins of stability → Overall worst =<1% Alves & Savageau 2000,a,b; 2001 Bioinformatics; 2000, 2001 Biophysical Journal

22. Outline Design Principles in Network Topology  Overall Feedback  Signal Transduction  Gene Circuits

23. Alternative sensor design in Two Component Systems S S* R* R Q1 Q2 Monofunctional Sensor Bifunctional Sensor S S* R* R Q1 Q2

24. Studying physiological differences of alternative designs A Q A Q A Q A Q

25. Physiological Predictions Bifunctional design lowers Q2 signal amplification  prefered when cross-talk is undesirable Monofunctional design elevates Q2 signal amplification  prefered when cross-talk is desirable.

26. Predicting Monofunctionality from structure Alves & Savageau 2003 Mol. Microbiol. ~1000 sequences from genomic data of dozens of bacteria Bifunctional Sensor Monofunctional Sensor Differences in ATP lid 100s predicted structures by modeling 25 monofunctional sensors

27. A new design principle 10/19/201527 Existence of a dead end complex and of a flux channel for the dephosphorylation of the RR that is independent of the sensor allow for TCS that have bistable responses.

28. A new design principle 10/19/201528

29. Outline Design Principles in Network Topology  Overall Feedback  Signal Transduction  Gene Circuits

30. Dual Modes of gene control

31. Demand theory of gene control Wall et al, 2004, Nature Genetics Reviews High demand for gene expression→ Positive Regulation Low demand for gene expression → Negative mode of regulation

32. Acknowledgments Mike Savageau Albert Sorribas Armindo Salvador PGDBM JNICT FCT Spanish Government Portuguese Government NIH (Mike Savageau) DOD (ONR) (Mike Savageau)