1. ECOLITASTER: Cellular Biosensor Valencia iGEM 2006

2. Outline Introduction Parts Design Systems Design Experimental work Conclusions “To have success in science, you need some luck. Without it, I would never have become interested in genetics”. J.D. Watson.

3. Introduction Objectives: Design a genetic system consisting on few genes that is able to give a graded response according to a concentration of an input. Modular project. Different devices. Use a biological mechanism to connect the membrane receptor with the genetic network, obtaining a cellular biosensor. Use new synthetic parts.

4. Project Design This project is formed by two devices: a sensor and an actuator. We use OmpR-P as input in order to assemble them. We use a vanillin receptor (design in silico) as a sensor. Our genetic circuit (actuator) is based on Weiss’ group work (Basu, Nature 2005) in order to obtain a graded response versus the concentration of a given input. Incoherent circuit. Semi-digital interpretation. RFP & GFPVanillin

5. Actuator Behavior

6. Vanillin Receptor: mechanism pdb 2DRI 271 res V P PBP GN E. coli

7. Parts Design Promoters are critical elements designing those networks. We focus our interest in binary promoters, i.e., promoters regulated by two transcription factors. Integrating two signals. Reduce the number of genes of the circuit. Small size device. Different implementations exhibiting logic behaviors, but not necessarily. Computational protein design.

8. Vanillin Receptor: DESIGNER methodology

9. Systems Design System and expected behavior. Model and simulations. Sensitivity analysis. Robustness analysis. Our biological system.

10. System and Expected Behavior

11. Model and Simulations We use an effective model, modeling only protein concentrations: We consider generic parts to make these simulations. Thus, we take common values for the parameters from the literature. However we expect a similar behavior:

12. Sensitivity Analysis The well working of the circuit depends on the promoters upstream of the two branches: pOmpR and pOmpRm.

13. Robustness Analysis We study the robustness of the gene circuit when there are oscillations in the sensing device. To perform that, we introduce a white noise in the input (OmpR-P). OmpR-P RFP GFP RFP GFP RFP GFP time

14. Our Biological System

15. Experimental Work Parts construction. Where are the parts? Repositories. E. coli genome. Built from scratch. Making our BioBricks. pAND. Vanillin receptor. Fusion protein. FACS results. Our Registry.

16. Where are the parts? (I) Repositories: pOmpR pOmpRm pLac pTetR GFP RFP TetR cI Tar-EnvZ

17. Where are the parts? (II) E. coli genome: Trg CRP

18. Where are the parts? (III) Built from scratch: pAND Vanillin PBP

19. Making our BioBricks (I) pAND: -93,5-42 XbaI [Joung, Science 1994]

20. Making our BioBricks (I) pAND: 5’ 3’ F0F32F71 R0R16R51R91 -93,5-42 XbaI [Joung, Science 1994]

21. Making our BioBricks (I) pAND: 5’ 3’5’ 3’ DNA ligase 5’ 3’ F0F32F71 R0R16R51R91 -93,5-42 XbaI [Joung, Science 1994]

22. Making our BioBricks (I) pAND: 5’ 3’5’ 3’ DNA ligase 5’ 3’ F0F32F71 R0R16R51R91 DNA polimerase & R91 + F71PCR 5’ 3’5’ 3’ 5’ 3’5’ 3’ 5’ 3’5’ 3’ -93,5-42 XbaI [Joung, Science 1994]

23. Making our BioBricks (II) Vanillin receptor: aa sequence: KDTIALVVETLNKPDNVSLKDGAQKEADKLGYNLV VLDSQNNPAKELANVQDLTVRGTKILLIVPTDSDA VGNAVKMANQANIPVITLKRQATKGEVVSHIAADN VLGGKIAGDYIAKKAGEGAKVIELQGKAGTSAARE LGEGFQQAVAAHKFNVLASQPADEDRIKGLNVMQN LLTAHPDVQAVFAQQDEMALGALRALQTAGKSDVM VVGDVGTPDGEKAVNDGKLAATIAELPDQIGAKGV ETADKVLKGEKVQAKYPVDLKLVVKQ pBSKValencia $$ or €€ Computational design: Combinatory optimization DESIGNER

24. Making our BioBricks (III) NdeI trg NdeI tarenvZ Fusion protein Trz. [Baumgartner, J. Bact. 1993]. chemoreceptor Trg: periplasmic and transmembrane domains. osmosensor EnvZ: cytoplasmic kinase/phosphatase domain.

25. Making our BioBricks (III) BioBrick PCR Genomic PCR NdeI trg NdeI tarenvZ Fusion protein Trz. [Baumgartner, J. Bact. 1993]. chemoreceptor Trg: periplasmic and transmembrane domains. osmosensor EnvZ: cytoplasmic kinase/phosphatase domain.

26. Making our BioBricks (III) NdeI digestion NdeI digestion & dephosphorilation BioBrick PCR Genomic PCR NdeI trg NdeI tarenvZ Fusion protein Trz. [Baumgartner, J. Bact. 1993]. chemoreceptor Trg: periplasmic and transmembrane domains. osmosensor EnvZ: cytoplasmic kinase/phosphatase domain.

27. Making our BioBricks (III) NdeI digestion NdeI digestion & dephosphorilation mix + ligate BioBrick PCR Genomic PCR NdeItrgenvZ NdeI trg NdeI tarenvZ Fusion protein Trz. [Baumgartner, J. Bact. 1993]. chemoreceptor Trg: periplasmic and transmembrane domains. osmosensor EnvZ: cytoplasmic kinase/phosphatase domain.

28. Making our BioBricks (III) NdeI digestion NdeI digestion & dephosphorilation mix + ligate BioBrick PCR Genomic PCR NdeItrgenvZ NdeI trg NdeI tarenvZ Fusion protein Trz. [Baumgartner, J. Bact. 1993]. chemoreceptor Trg: periplasmic and transmembrane domains. osmosensor EnvZ: cytoplasmic kinase/phosphatase domain.

29. Making our BioBricks (IV) From wild type to BioBrick, a powerful screening method: S P pTetR-RFP E X Trg-envZ S P E X

30. Making our BioBricks (IV) From wild type to BioBrick, a powerful screening method: S P pTetR-RFP E X Trg-envZ S P E X EcoRI + PstI digestion & dephosphorilation EcoRI + PstI digestion

31. Making our BioBricks (IV) From wild type to BioBrick, a powerful screening method: S P pTetR-RFP E X Trg-envZ S P E X EcoRI + PstI digestion & dephosphorilation EcoRI + PstI digestion mix & ligate & transformation

32. Making our BioBricks (IV) From wild type to BioBrick, a powerful screening method: S P pTetR-RFP E X Trg-envZ S P E X EcoRI + PstI digestion & dephosphorilation EcoRI + PstI digestion mix & ligate & transformation pTetR-RFP trg-envZ

33. FACS results (I) Promoter pOmpR with GFP as reporter: Negative control: XL1-Blue Positive control: Green fluorophore Set: pOmpR-RBS-GFP-T

34. FACS results (II) Characterization of pOmpR and pOmpRm. Negative control: XL1-Blue Positive control: Green fluorophore Set: pOmpR-RBS-GFP-T Set: pOmpR-RBS-GFP-T

35. Our Registry Parts submited by Valencia:

36. Conclusions We have designed a genetic system consisting on 7 genes, expected to give a graded response according to vanillin concentration. We use the phosphorilation mechanism to connect the membrane receptor with the genetic network, obtaining a cellular biosensor. Our use of a two-regulator promoter allows to integrate signals and reduce the number of genes required for a device. Computational design of a PBP-vanillin receptor.

37. Acknowledgements EU FP6 NEST SYNBIOCOMM project (financial support). Escuela Técnica Superior de Ingenieros Industriales (Universidad Politécnica de Valencia). Instituto de Ciencia Molecular (Universitat de València). E. O’Connor (FACS services). A. Moya and A. Latorre (Cavanilles).

38. UPV-UV Valencia iGEM 2006

39. Our team