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Synthetic Logic Circuits in Busker-Tchta Coii and Tasnsir DISSERTATION Dbmlttecl in Partial S&Ikfkction Uf Che Requirements

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Synthetic Logic Circuits in Busker-Tchta Coii and Tasnsir DISSERTATION Dbmlttecl in Partial S&Ikfkction Uf Che Requirements Synthetic Logic Circuits in Busker-tchta coii AND Tasnsir DISSERTATION dbmlttecl in partial s&ikfkction uf Che requirements for the degree of DOCTOR Of FFilLOSOPriY Tetrad Gcedtraie Program in the GRADUATE DIVISION •••> r *-*-w> I NO ERSt I \ or C Al aOHNi A. > W I R SNiTSOO Copyright 2011 by Alvin Tamsir ii Acknowledgement This dissertation contains materials previously published in: 1. Alvin Tamsir, Jeffrey J. Tabor , Christopher A. Voigt. Robust multicellular computing using genetically encoded NOR gates and chemical „wires‟. Nature 469, 212-215, (2011). 2. Howard Salis, Alvin Tamsir, Christopher A. Voigt. Engineering bacterial signals and sensors. Contrib Microbiol. 16, 194-225, (2009). iii Abstract Synthetic Logic Circuits in Escherichia coli Alvin Tamsir Computation underlies the organization of cells into higher-order structures; for example, during development or the spatial association of bacteria in a biofilm. Each cell performs a simple computational operation, but when combined with cell-cell communication, intricate patterns emerge. Here, we study this process by combining a simple genetic circuit with quorum sensing in order to produce more complex computations in space. A simple NOR gate is constructed by arranging two tandem promoters that function as inputs to drive the transcription of a repressor. The repressor inactivates a promoter that serves as the output. Individual colonies of E. coli carry the same NOR gate, but the inputs and outputs are wired to different orthogonal quorum sensing “sender” and “receiver” devices. The quorum molecules form the wires between gates. By arranging the colonies in different spatial configurations, all possible 2-input gates are produced, including the difficult XOR and EQUALS functions. The response is strong and robust, with 5- to >300-fold changes between the ON and OFF states. This work helps elucidate the design rules by which simple logic can be harnessed to produce diverse and complex calculations by rewiring communication between cells. iv Table of Contents Page 1. Introduction 1 Figure 1: The genetic NOR gate 2. Models of Input Promoters 3 Figure 2: The transfer function of the PLas promoter Table 1: Parameters for the PBAD, PTet, and PLas promoters Figure 3: The binding states of the PBAD, PTet, and PLas promoters 3. Models of Tandem Promoters 8 Figure 4: Input modularity of the gates Figure 5: Interference between tandem promoters 4. NOT Gate Model 12 Figure 6: Binding states of the PcI promoter. Figure 7: The transfer function of the PcI promoter Table 2: NOT Gate Parameters 5. Multicellular Logic Circuits 14 Figure 8: Construction of an XOR gate Figure 9: Construction of all 16 two-input Boolean logic gates Figure 10: Flow cytometry distributions Figure 11: Fold induction of the constructed logic circuits 6. Circuits Characterization 17 Figure 12: Effect of population averaging Figure 13: XOR circuit as measured in liquid culture Figure 14: Distributions of liquid and plate cultures Figure 15: Dependence of the XOR gate on the time delay 7. Sender-Receiver Modelling 19 Figure 16: Distance, time interval, and density dependence of the plate assay Table 3: Parameters for the PDE Model 8. References 31 v 1. Introduction Boolean logic gates integrate multiple digital inputs into a digital output. Electronic integrated circuits consist of many layered gates. In cells, regulatory networks encode logic operations that integrate environmental and cellular signals6-8. Synthetic genetic logic gates have been constructed, including those that perform AND, OR and NOT functions9-12, and they have been used in pharmaceutical and biotechnological applications13,14. Multiple gates can be layered to build more complex programs15-17, but it remains difficult to predict how a combination of circuits will behave based on the functions of the individuals11,18. Here, we have compartmentalized a simple logic gate into separate E. coli strains and use quorum signalling to enable communication between the strains5. Compartmentalizing the circuit produces more reliable computation by population-averaging the response. In addition, a program can be built from a smaller number of orthogonal parts (e.g., transcription factors) by re-using them in multiple cells. NOR and NAND gates are unique because they are functionally complete. That is, any computational operation can be implemented by layering either of these gates alone19. Of these, the NOR gate is the simplest to implement using existing genetic parts. A NOR gate is ON only when both inputs are OFF (Figure 1A). We designed a simple NOR gate by adding a second input promoter to a NOT gate20. Tandem promoters with the same orientation drive the expression of a transcriptional repressor (Figure 1B). Tandem promoters are common in prokaryotic genomes21. It is expected that this would produce an OR function; however, interference between the promoters can occur. The repressor turns off a downstream promoter, which serves as the output of the gate. Both 1 the inputs and the output of this gate are promoters; thus, multiple gates could be layered in order to produce more complex operations. Each logic gate is encoded in separate strains of E. coli. Acetyl homoserine lactone (AHL) cell-cell communication devices (quorum sensing devices) are used as signal carrying “wires” to connect the logic gates encoded in different strains4,5,22. A quorum sensor is a sensor system that detects and responds to a diffusible molecule that is produced by a population of organisms, frequently from multiple species. The concentration of the diffusible molecule – often called an autoinducer – dynamically changes according to multiple factors, including the production rate of the autoinducer, the number of organisms producing the autoinducer, and the volume of the enclosed space. As the number of autoinducer-producing organisms increases, the concomitant increase in autoinducer concentration can activate or repress gene expression. Many physiological behaviors, such as virulence and biofilm formation, only become effective at high or low population densities and are regulated accordingly by quorum-sensing systems. While there is no single architecture for a quorum-sensing system, there are conserved families of sensor systems that detect quorum signals. In Gram-negative bacteria, there is a prototypical architecture that consists of an autoinducer synthetase that produces a diffusible, membrane-permeable homoserine lactone (HSL) and an allosteric transcription factor that binds to it. This architecture is named the LuxIR type after the first such quorum sensor system discovered in the marine bacterium Vibrio fischeri. Gates are connected in series where the output of the first gate is the expression of the AHL synthetase (LasI or RhlI). AHL diffuses through the cell membrane and binds to 2 its cognate transcription factor (LasR or RhlR). The promoter that is turned on by the transcription factor is used as the input to the next logic gate. These systems have been used previously to program cell-cell communication and have been shown to exhibit little crosstalk4. Analogous to a series of electrical gates arrayed on a circuit board, compartmentalization of genetic gates in individual cells allows them to be added, removed or replaced by simply changing the spatial arrangement of the E. coli strains. The step-wise construction of a NOR gate with PBAD and PTet as the input promoters and yellow fluorescent protein (YFP) as the output gene is shown in Figure 1C. PBAD and PTet are activated in the presence of arabinose (Ara) and anhydrotetracycline (aTc), respectively. The individual transfer functions of PBAD and PTet are measured using flow cytometry (Figure 1C). An OR gate is constructed by placing the PBAD and PTet promoter in tandem. PBAD-PTet demonstrates OR logic with 7000-fold induction between the OFF state (-Ara, -aTc) and the ON state (+Ara, +aTc). Finally, to convert the OR gate into a NOR gate, the cI repressor gene is placed under the control of PBAD-PTet and YFP is expressed from a second plasmid under the control of the cI-repressible PR promoter. While the OR gates have some characteristics of fuzzy logic, the NOR gates are nearly digital (Figure 1C). 3 Figure 1: The genetic NOR gate. The symbol, truth table (A) and genetic diagram (B) of the NOR gate are shown. (C) The transfer function is defined as the output as a function of input at steady-state. The transfer functions of PBAD and PTet (top), the PBAD-PTet tandem promoter (middle), and NOR gate (bottom) are shown. The inducer concentrations for the tandem promoter and NOR gate characterizations are [0, 0.0005, 0.005, 0.05, 0.5, 5] mM Ara and [0, 0.025, 0.25, 2.5, 25, 250] ng/mL aTc. Fluorescence values and their error bars are calculated as averages and one standard deviation from three experiments. 4 2. Models of Input Promoters The binding of ligands to transcription factors and transcription factors to DNA is modelled for three inducible promoters (Ara-inducible PBAD, aTc-inducible PTet, and 3OC12-HSL inducible PLas). The binding of a ligand to its transcription factor at equilibrium is Ln C C0 n n Kd L , (1) where C is the concentration of bound transcription factor, C0 is the total concentration, Kd is the dissociation constant, and n is the cooperativity. By mass conservation, the concentration of free transcription factor CF is CCC F0 . (2) The binding of transcription factors to their promoters are modelled according to the Shea-Ackers formulism. The binding states for each promoter are shown in Figure 3. The probability for each promoter being in open complex P is described by the following equations: KKC P 12 BAD 1KKCKC 1 2 3 F , (3) K P 1 Tet 12KKCKC 22 1 2FF 2 and (4) KKC P 12 Las 1KKC 12 . (5) 5 To parameterize Equations 3-5, the transfer functions of each promoter are determined by varying the concentration of inducer and measuring the expression of YFP.
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