1. UPV-UV Valencia iGEM 2006 Alfonso Jaramillo Ecole Polytechnique, Paris & InterTech (UPV)

2. Summary of work plan April: Training lectures, promotion, team building and funding. May/June: Prototype design. July/August: Parts & Devices construction & characterization. Redesign prototype. September/October: System characterization.

4. Outline Biological modules for engineering –Parts –Devices –Systems Design of parts

5. Biological modules for engineering Chassis: Bacterial strain that will receive the engineered systems. Parts: Fragment of DNA with a given functionality. Devices: Assembly of parts with a given functionality and given interface. –Specifications –I/O is given by proteins and signals Systems: Assembly of devices with a given functionality –I/O is given only by signals

6. ‘I need a few DNA binding proteins.’ ‘Here’s a set of DNA binding proteins, 1  N, that each recognize a unique cognate DNA site, choose any.’ ‘Get me this DNA.’ ‘Here’s your DNA.’ ‘Can I have three inverters?’ ‘Here’s a set of PDP inverters, 1  N, that each send and receive via a fungible signal carrier, PoPS.’ TAATACGACTCACTATAGGGAGA DNA Zif268, Paveltich & Pabo c. 1991 Parts PoPS NOT.1 PoPS Devices PoPS NOT.2 PoPS NOT.3 PoPS NOT.1 Systems

7. Decoupling –Rules insulating design process from details of fabrication –Enable parts, device, and system designers to work together –VLSI electronics, 1970s Standardization –Predictable performance –Off-the-shelf –ME, 1800s Abstraction –Insulate relevant characteristics from overwhelming detail –Simple artifacts that can be used in combination –From Physics to EE, 1800s Biological Engineering

8. Parts Promoter RBS CDS Terminator Tag Primer Operator I13453B0034I15008B0034I15009B0015 tetR R0040B0034I15010B0015 BBa_M30109 = Notice that for the MIT registry, any combination of parts (e.g. devices and systems) is a part.

11. Parts Construction Simplified cloning procedure that allows to combine plasmids using a standardized approach. The construction of devices is reduced to the combination of parts (to generate new parts, in the MIT terminology). Careful with the maximum size of plasmids

12. Parts Construction SPXE

13. Standard PCR and sequencing primers have been chosen for pSB103 to use for colony PCR for insert length selection, and for sequencing of inserts: Verication Forward: 5' TTG TCT CAT GAG CGG ATA CA 3‘ Verication Reverse: 5' ATT ACC GCC TTT GAG TGA GC 3’.

14. cut the green plasmid with EcoRI and XbaI enzymes. cut the blue plasmid with EcoRI and SpeI, A minimum number of bases (undetermined) between the EcoRI and XbaI sites and the SpeI and PstI sites may be required to allow complete cutting with both enzymes (NotI).

15. The vector and insert must not contain any other EcoRI, XbaI, SpeI, or PstI cut sites. This excludes the following hexamer sequences: EcoRI: GAATTC XbaI: TCTAGA SpeI: ACTAGT PstI: CTGCAG And octameric recognition site for NotI, GCGGCCGC.

16. Devices They should be able to always produce the same ouput from the same input. –Need of specification of transfer functions and I/O proteins/molecules. –The engineer will be able to model the devices from the specifications without needing to know the internals. Encapsulation of data. –Devices with interface with each other. Need of a standard. –In the real world the devices will interact with the chassis.

17. Devices LacI  CI inverter CI LacI

18. Devices cI-857 O Lac RBS T CI LacI CI

19. Systems Inverter.2Inverter.3Inverter.1

20. Device-Level System Diagram

21. Parts- and Device-Level System Diagram

22. DNA Layout

23. Device Interface cI-857 O Lac RBS T cI LacI cI-857 RBS T cI O PoPS in PoPS out LacI cI PoPS out PoPS in

24. cI RBS T O cI PoPS IN Polymerase Per Second = PoPS! cI RBS T O PoPS OUT

25. cI RBS T O PoPS OUT PoPS IN cI PoPS OUT PoPS IN Polymerase Per Second = PoPS! INVERTER PoPS OUT PoPS IN PoPS OUT PoPS Source (Any)

27. Towards an Ideal Chassis We would like to have a chassis that will not interfere with our devices. We need a dedicated protein production.

28. Biological Virtual Machines Dedicated systems are a method to decouple the function of an engineered biological system from the function of its chassis. By separating the resources and machinery used to supply and power an engineered system from those of the chassis, then perturbations in the operation of one should have less effect on the other. These dedicated synthesis systems can then be used as the basis of Biological virtual machines.Biological virtual machines

29. General Translation VM Translation General Transcription I7101 I7101 I7102 I7102 VM Transcription E7104 E7104 E7103 E7103 The T7 expression system developed by Studier and coworkers is essentially orthogonal from the E. coli transcription system. T7 RNAP does not recognize E. coli promoters and E. coli RNAP does not recognize T7 promoters.Studier and coworkers

30. Design of Parts

31. Gene Design http://slam.bs.jhmi.edu/gd/

32. Zinc-finger repressor system

33. Designed linker sequence TGEKP between E3 and F4. natural linker peptides between F1 and F2 (TGQKP) and between F2 and F3 (TGEKP), Barbas PNAS 97 bind DNA containing the 18-nt site 5'- GCGTGGGCGGCGTGGGCG-3'.

34. http://www.scripps.edu/mb/barbas/zfdesign/zfdesignhome.php

35. Codon Usage: there is little tRNA made for rare codons. In E. coli these are mainly AGA and AGG (Arg codons). The genes encoding the tRNAs can be co- overexpressed. Promoters used should be very tight. Tight promoters are for example arabinose (BAD), rhamnose and lactose (provided that lacIQ is co- overexpressed). RBS (Shine-Delgarno Sequence - serves to align the ribosome on the message in the proper reading frame.) Optimal: AGG AGG, the last G should be 9 bases upstream from the A of the AUG (start of translation) Start codons on mRNA are: AUG (90%, codon for Met), GUG (9%), UUG (1%) and CUG (0.1%). Avoid secondary structure involving SD sequence and the initiator AUG. In polycistronic mRNAs, the initiation site should be close to the termination codon of the upstream gene. Regulation of translation: is sometimes (not often) affected by sequences in the coding region: +5 and +10 should be A or T RNA Stability can be increased if stem-loop structures are cloned at the 3' end of the coding region Factors that Influence Gene Expression

36. Expression Vectors Low copy number plamids are better than high copy number plasmids (copy numbers of 5-40 is recommended). Yield of protein does not linearly correlate with copy number of a gene. Regulated promoter - the optimum is one that is induced by a substrate such as IPTG that diffuses into the cell because then induction levels can be more easily manipulated. Inducers that are a substrate of one or more active transport systems cannot be controlled at all. These inducers will be accumulated to mM levels even when added in very low concentrations to the growth medium. Co-overexpression of repressors of the promoter used can provide excellent control of transcription. Co-overexpression of activators guarantees that each promoter on the plasmids is activated. Place transcription terminator at the 3' end of target gene. This avoids formation of antisense RNAs from downstream promoters operating in reverse orientation with respect to the gene that should be expressed at high levels.

37. Getting folded proteins Broken protein domains don't fold Difficult to get folded in the cytoplasm a protein containing disulfide bonds. Coexpress other members of a hetero-oligomeric complex Inclusion body formation can often be reduced by growing cells at 20 0 C (Note that 28 0 C does not work nearly as well). If this is not successful, try adding 6% ethanol to rich medium when adding inducer. EtOH induces heat shock response which overexpresses chaperones and proteases. The latter are barely active at 20 0 C.

38. E.Coli parameters: http://redpoll.pharmacy.ualberta.ca/CCDB/cgi-bin/STAT_NEW.cgi Parameters DNA and RNA molecular weights: http://www.ambion.com/techlib/append/na_mw_tables.html

39. Design of Devices Example of devices: Regulatory, input, output, sensors, signaling, metabolic, etc…

40. The biological inverter

41. Modeling a Biochemical Inverter input output repressor promoter

42. Steady-State Behavior: Transfer Functions “ideal” transfer curve:  gain (flat,steep,flat)  adequate noise margins [input] “gain” 01 [output] This curve can be achieved using proteins that cooperatively bind dna! This curve can be achieved using proteins that cooperatively bind dna! Inverter

43. Measuring a Transfer Curve Construct a circuit that allows: –Control and observation of input protein levels –Simultaneous observation of resulting output levels “drive” geneoutput gene R YFPCFP inverter Also, need to normalize CFP vs YFP

44. Flow Cytometry (FACS)

45. Drive Input Levels by Varying Inducer IPTG (uM) 0 250 1000 IPTG (or ECFP) plasmid promoter protein coding sequence IPTG YFP lacI [high] 0 (Off) P(LtetO-1) P(R)

46. Also use for yfp/cfp calibration Controlling Input Levels

47. Measuring a Transfer Curve for lacI/p(lac) aTc “drive” output aTc YFP lacI CFP tetR [high] 0 (Off) P(LtetO-1) P(R) P(lac) measure TC

48. Transfer Curve Data Points 01011010 1 ng/ml aTc undefined 10 ng/ml aTc100 ng/ml aTc

49. lacI/p(lac) Transfer Curve aTc YFP lacI CFP tetR [high] 0 (Off) P(LtetO-1) P(R) P(lac) gain = 4.72

50. Evaluating the Transfer Curve Noise margins:Gain / Signal restoration (95%): high gain * note: graphing vs. aTc (i.e. transfer curve of 2 gates) FACS cell population data

51. Logic Circuits based on Inverters Proteins are the wires/signals Promoter + decay implement the gates NAND gate is a universal logic element: –any (finite) digital circuit can be built! X Y R1R1 Z R1R1 R1R1 X Y Z = gene NANDNOT

52. The IMPLIES Gate Inducers that inactivate repressors: –IPTG (Isopropylthio-ß-galactoside)  Lac repressor –aTc (Anhydrotetracycline)  Tet repressor Use as a logical Implies gate: (NOT R) OR I operatorpromoter gene RNA P active repressor operator promoter gene RNA P inactive repressor inducer no transcription transcription Repressor Inducer Output

53. Transfer Curve of Implies YFP lacI aTc IPTG tetR [high]

54. Device Optimization

55. Measure cI/ P(R) Inverter OR1OR1OR2OR2 structural gene P(R-O12) cI is a highly efficient repressor cooperative binding IPTG YFP cI CFP lacI [high] 0 (Off) P(R) P(lac) Use lacI/p(lac) as driver high gain cI bound to DNA lacI CI+CFP YFP IPTG

56. Initial Transfer Curve for cI/ P(R) Completely flat –Reducing IPTG  no additional fluorescence Hard to debug! Process engineering:  Is there a mismatch between inverters based on lacI/p(lac) and cI/ P(R) ?

57. Inverters Rely on Transcription & Translation mRNA ribosome promoter mRNA ribosome operator translation transcription RNAp

58. Process Engineering I: Different Ribosome Binding Sites BioSpice Simulations RBS translation start Orig: ATTAAAGAGGAGAAATTAAGCATG strong RBS-1: TCACACAGGAAACCGGTTCGATG RBS-2: TCACACAGGAAAGGCCTCGATG RBS-3: TCACACAGGACGGCCGGATG weak

59. Experimental Results for Modified Inverter Strong Weak

60. Process Engineering II: Mutating the P(R) orig: TACCTCTGGCGGTGATA mut4: TACATCTGGCGGTGATA mut5: TACATATGGCGGTGATA mut6 TACAGATGGCGGTGATA OR1OR1

61. Experimental Results for Mutating P(R) Strong Weak

62. Lessons for BioCircuit Design Naive coupling of gates not likely to work Need to understand “device physics” –enables construction of complex circuits Use process engineering –modify gate characteristics RBS RBS+O1

64. (a)Reducing the repressor/operator binding affinity (b)Reducing the strength of the promoter (c)Reducing the strength of the RBS (d)Increasing the cistron count (e)Adding autorepression

65. Other Gates

68. The Toggle Switch [Gardner & Collins, 2000] pIKE = lac/tet pTAK = lac/cIts

69. Actual Behavior of Toggle Switch [Gardner & Collins, 2000] promoter protein coding sequence

70. Example of Devices

71. Input Membrane proteins (including ion channels) Sensors (some of them membrane prots)

72. Sensors Using inducible promoters –IPTG, tetracycline, etc... –Temperature (sigma32) Using RNA Design custom sensors –Light detector (using phytochrome)

73. Genetic light switch Phytochrome suffers a (reversible) conformational change upon red light induction. Tested in Yeast, but it can be implanted in any organism able to synthesize the chromophore and assemble it. Shimizu-Sato et al. Nat. Biotech. 2002

74. Chromophore Biosynthesis Gambetta et al. PNAS 2001

75. Output Reporters –GFP, RFP, YFP –LacZ

76. GFP Highly resistant to temperature, pH, chemical denaturants, and proteases Intrinsic and independent fluorescence allows in vivo monitoring Easily measured by UV light, fluorescence microscopy, or FACS GFP fusion proteins retain biological activity (N and C-terminal) Applicable to many systems (E. coli, Drosophila, mammalian) BBa_E0040

77. LacZ By addition of S-gal (3,4- cyclohexenoesculetin-D-galactopyranoside), LacZ catalyses the formation of a stable, insoluble,black precipitate from S-gal. BBa_E0033

78. Signaling Devices

79. Signaling Senders Receivers Transmitters Amplifiers

80. Intercellular Communications Certain inducers useful for communications: 1.A cell produces inducer 2.Inducer diffuses outside the cell 3.Inducer enters another cell 4.Inducer interacts with repressor/activator  change signal (1)(2)(3)(4) main metabolism

81. Quorum Sensing Cell density dependent gene expression Example: Vibrio fischeri [density dependent bioluminscence] The lux OperonLuxI metabolism  autoinducer (VAI) luxRluxIluxCluxDluxAluxBluxEluxG LuxR LuxI (Light) hv (Light) hv Luciferase P P Regulatory Genes Structural Genes

82. Light organ Eupryma scolopes

83. Density Dependent Bioluminescence free living, 10 cells/liter <0.8 photons/second/cell symbiotic, 10 10 cells/liter 800 photons/second/cell  A positive feedback circuit luxRluxIluxCluxDluxAluxBluxEluxG LuxR LuxI P P Low Cell Density luxRluxIluxCluxDluxAluxBluxEluxG LuxR LuxI (Light) hv (Light) hv Luciferase P P High Cell Density LuxR OO O O NHNH OO O O NHNH OO O O NHNH OO O O NHNH (+) OO O O NHNH OO O O NHNH OO O O NHNH OO O O NHNH OO O O NHNH OO O O NHNH OO O O NHNH OO O O NHNH OO O O NHNH OO O O NHNH OO O O NHNH OO O O NHNH

84. (a)LuxI/R quorum sensing. (b)Peptide-mediated quorum sensing in development of competence. (c)Quorum sensing in V. harveyi. Quorum Sensing Systems ComD: histidine kinase the periplasmic LuxP protein that is involved in recogni-tion of AI-2 is not shown for simplicity.

85. Similar Signalling Systems N-acyl-L-Homoserine Lactone Autoinducers in Bacteria SpeciesRelation to HostRegulate Production ofI GeneR Gene Vibrio fischerimarine symbiontBioluminescenceluxIluxR Vibrio harveyimarine symbiontBioluminescenceluxL,MluxN,P,Q Pseudomonas aeruginosaHuman pathogenVirulence factorslasIlasR RhamnolipidsrhlIrhlR Yersinia enterocoliticaHuman pathogen?yenIyenR Chromobacterium violaceumHuman pathogen Violaceum production Hemolysin Exoprotease cviIcviR Enterobacter agglomeransHuman pathogen?eagI? Agrobacterium tumefaciensPlant pathogenTi plasmid conjugationtraItraR Erwinia caratovoraPlant pathogen Virulence factors Carbapenem production expIexpR Erwinia stewartiiPlant pathogenExtracellular CapsuleesaIesaR Rhizobium leguminosarumPlant symbiontRhizome interactionsrhiIrhiR Pseudomonas aureofaciensPlant beneficialPhenazine productionphzIphzR

86. Circuits for Controlled Sender & Receiver pLuxI-Tet-8pRCV-3 Genetic networks: Logic circuits: VAI aTc luxI  VAI * E. coli strain expresses TetR (not shown) * VAI LuxR GFP tetR aTc 0 0

87. receiverssenders overlay

88. receiverssenders overlay

89. Remarks About Control Theory

91. Becskei & Serrano, Nature 2000

93. Model of tryptophan biosynthesis

94. 05101520 0.8 0.85 0.9 0.95 1 1.05 Time (minutes) [P] h = 3 h = 0 0246810 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 Frequency Log(Sn/S0) h = 3 h = 0 Spectrum Time response Robust Yet fragile

95. 0246810 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 Frequency Log(Sn/S0) h = 3 h = 2 h = 1 h = 0 Tighter steady-state regulation Transients, Oscillations Theorem

96. log|S |  Tighter regulation Transients, Oscillations Biological complexity is dominated by the evolution of mechanisms to more finely tune this robustness/fragility tradeoff. This tradeoff is a law.

97. log|S |  Conservation of “fragility”

98. Bacterial chemotaxis Yi et al. PNAS 2000 Integral control Integral Control