Transcriptional regulation and combinatorial genetic

Transcriptional regulation and combinatorial genetic logic in synthetic bacterial circuits

Chapter 1: Short-overhang randomized assembly ligation

Transcriptional regulation and combinatorial genetic logic in synthetic Bacterial circuits

Thesis by Robert Sidney Cox III

In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

California Institute of Technology Pasadena, California 2008 (Defended October 12, 2007)

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Transcriptional regulation and combinatorial genetic logic in synthetic circuits

© 2008 Robert Sidney Cox III All Rights Reserved

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Acknowledgements I would like to thank the many helpful people who made this work possible. My three research mentors: Frances Arnold, Mike Surette, and Michael Elowitz provided much of the inspiration and motivation for every aspect of the work presented here. Aaron White helped immensely with the design and construction of the DNA library (Chapter 1). Mercedes Paulino helped with the layout of the entire book, and helped design every table and figure in Chapter 2. Mary Dunlop helped with the preparation of the cross correlation analysis in Chapter 3. Erik Winfree, Yohei Yokobayashi, Manish Raizada, Jared Leadbetter, Christina Smolke, Paul Sternberg, Barbara Wold, Danny Rintoul, David Womble, Stuart Kauffman, and Michael Savageau provided helpful advice and guidance in my development as a scientist. I must thank my undergraduate mentors Pat McDonald, George Ruppeiner, and Paul Scudder—who prepared me for the academic hurdles of graduate school so well that I barely noticed them. I would also like to thank C. Davidson, J. Yang, C. Vizcarra, Y. Wang, R. Georgescu, S. Thiberge, F. Balagadde, C. Collins, S. Maerkle, and C. Kooi for general technical assistance and helpful discussions. Takeshi Irie, Avigdor Eldar, Graham Anderson, Dylan Morris, Beth Orcutt, James Locke, Andrea Choe, Ryan Baugh, and Chiraj Dalal provided useful feedback on multiple versions of this document.

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Abstract We engineered several synthetic regulatory circuits to study transcriptional regulation in bacteria. We developed a new technique for DNA construction, built and characterized in vivo a library of genetic logic gates, examined the role of genetic noise transcriptional regulation using a fluorescent multi-reporter system, and characterized a synthetic circuit for the control of population density.

We used synthetic duplex DNA fragments and very short cohesive overhangs to direct ordered assemblies of diverse combinatorial libraries. Multiple DNA fragments were simultaneously ligated in a single step to produce random concatemers, without the need for amplification or product purification. We characterized the assembly process to identify optimal cohesive overhangs. We showed that the method was 97% efficient for assembling 100 base-pair concatemers from three duplex fragments.

We constructed a library of 10,000 prokaryotic promoters, containing over 1,000 unique 100 base-pair sequences. These promoters responded to up to three inputs, and contained diverse architectural arrangements of regulatory sequences. We characterized the logical input functions of 288 promoters in Escherichia coli, and analyzed the relationship between promoter function and architecture. We defined promoter function in terms of regulatory range, logic type, and input symmetry; and identified general rules for combinatorial programming of gene expression.

We built a synthetic three-color fluorescent reporter framework. This construct was non-toxic and extensible for synthetic and systems biology applications. Three spectrally distinct and genetically isolated reporter proteins allowed independent monitoring of genetic signals at the single-cell level. We showed that the simultaneous measurement of multiple genes can exploit genetic noise to sensitively detect transcriptional co-regulation.

Chapter 1: Short-overhang randomized assembly ligation

We built and characterized a ‘population control’ circuit that autonomously regulated the density of an E. coli population. Cell density was broadcasted and detected by elements from a bacterial quorum sensing system, which regulated the death rate. The stable cell density steady-state was tuned by varying the stability of the quorum signal. This synthetic circuit coupled transcriptional regulation with population-level behavior.

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Table of Contents Acknowledgements

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Abstract

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Table of Contents

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0 Introduction 0.1 Glossary 0.2 Measuring gene expression 0.3 Engineering gene expression 0.4 Logic-symmetry space 0.5 Sequence space 0.6 Chapter outline 0.7 Figure captions 0.9 References

1 3 6 10 16 28 32 34 35

1 SORSAL: Short-Overhang Randomized Self-Assembly Ligation 1.1 Introduction 1.2 Results and discussion 1.3 Methods 1.4 Tables 1.5 Figures 1.6 References

41 44 49 52 53 57

2 Programming Promoter Logic: Programming Gene Expression with Combinatorial Promoters 2.1 Introduction 59 2.2 Results 61 2.3 Discussion 70 2.4 Methods 74 2.5 Tables 80 2.6 Figures 81 2.7 Supplementary results 87 2.8 Supplementary methods 90 2.9 Supplementary figures 93 2.10 Supplementary tables 98 2.11 References 100 2.12 Supplementary references 105

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3 The Scaffold: A Synthetic Three-Color Reporter Scaffold for Monitoring Genetic Regulation and Noise 3.1 Introduction 3.2 Results and discussion 3.3 Methods 3.4 Figures 3.5 Tables 3.6 References

108 110 115 121 125 126

4 Population Control: Programmed Population Control by Cell-Cell Communication and Regulated Killing 4.0 Contribution 131 4.1 Results 132 4.2 Methods 138 4.3 Figures 142 4.4 Tables 146 4.5 References 147 Appendicies A Promoter Library Data B The Reporter Scaffold C Repressilator Experiments D Phage Circuits E A Synthetic Predator-Prey Ecosystem

150 180 185 190 196

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Introduction

e recognize life by its ability to adapt to stimulus. The critical information for each adaptive

function is stored within DNA. With the possible exception of the very simplest obligate parasites (Perez-Brocal et al. 2006), a cell must choose which genes to express at any given time. Some genes can directly interfere with each other, or create toxic compounds when co-expressed. More importantly, a cell must make efficient use of the metabolic resources needed to express its genes. When, where, and how much of each gene must take into account the cell’s internal representation of its environment—along with its prediction of how the environment will change. Every freeliving organism can adapt to countless environmental stimuli by controlling the expression of between about 1,000 (Aquifex aeolicus) and 45,000 (Populus trichocarpa) genes.

Transcription initiation is the key step for genetic regulation in prokaryotes (Browning and Busby, 2004). Every gene is a candidate for transcriptional regulation, since all are transcribed from DNA to RNA, and genes controlled at this step will only expend the cell’s metabolic resources (for transcription, translation, etc.) as they are needed. The extremely low copy number of the chromosome (~2.1 in exponentially dividing Escherichia coli) permits a very large range of transcriptional regulation (e.g., LacI, present at ~10 copies per cell, can regulate expression over 1,000-fold). This regulation takes place at the promoter region, upstream of the coding and translational sequences, where it is possible to control transcription independently of other forms of regulation.

In this thesis, I study how multiple specific transcription factors (TFs) combine to regulate prokaryotic gene expression. The approach taken is that of “synthetic biology”: using synthetically constructed combinations of genetic sequence elements to probe cellular behaviors. I present a promoter shuffling method, described below and in Chapter 1, and use it to construct a random library of genetic control elements. These simple circuits integrate responses to a handful of environmental signals (inducers) that do not interact in nature, and allow us to focus on the general rules that limit combinatorial regulation at promoters (Chapter 2). Promoters regulated

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Transcriptional regulation and combinatorial genetic logic in synthetic circuits by one or two specific TFs are used to characterize a synthetic reporter scaffold fit to study the expression of three genes simultaneously (Chapter 3). Finally, I describe a different form of combinatorial regulation—cell-cell communication—in the context of a synthetic transcriptional regulation circuit that dynamically controls cell density (Chapter 4).

Here we employ specific TFs, as opposed to the global TFs and σ factors that regulate transcription at a higher level (similar to the chromatin remodeling systems in eukaryotes). The catabolite regulation protein CRP, a ubiquitous global TF, regulates a third of the 533 genes in E. coli for which transcriptional regulation has been characterized (Salgado et al. 2006). A perturbation of CRP activity represents a major stress to the cell (Perrenoud and Sauer, 2005), and understanding its regulatory interactions would involve decomposing hundreds of interactions. Since the specific TFs are less important to the cell, we can manipulate and modify their behaviors without massively perturbing the organism. Global TFs are often exceptions to the rules that govern specific TFs, but as we shall see below, some of the general principles will still apply.

The scientific contribution of this thesis is contained almost wholly in Chapter 2, and is the focus of this introduction. Chapters 1, 3, and 4 are contributions for biological engineering. After a brief glossary of transcriptional regulation, I discuss the current state of engineering and measurement of gene expression. This highlights the need for an integrated system for measuring gene expression, which is presented in Chapter 3. Chapter 4 is an example of a synthetic regulatory circuit. I review several other examples from the synthetic biology literature, to motivate the utility of the combinatorial promoters presented in Chapter 2.

Combinatorial promoters are the focus of the last two sections of this introduction. There I give a general description of combinatorial regulation, and show how the results of Chapter 2 can be used to understand natural combinatorial promoters. The DNA construction method of Chapter 1 provides the tools to extend this analysis to other combinations of TFs, and other organisms.

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Glossary: The Building Blocks of Prokaryotic Transcriptional Regulation In this glossary, I define the principle genetic elements of prokaryotic transcriptional regulation. Examples and statistics are also given for each element, to provide context for the reader. This section can be skipped by those already familiar with prokaryotic transcription.

Promoter: Region of regulatory DNA just upstream of a gene. The promoter region is 100 bp extending from -75 to +25, including the first transcribed base (+1). Promoters contain multiple sequence features that interact with the RNA polymerase subunits and the TF regulators. There are between 3,000 and

Figure 1.

Combinatorial promoters are common in bacteria. The frequencies of com-

binatorial regulation are shown for the 554 σ70 promoters of E. coli as annotated in RegulonDB 5.0.

12,000 functional promoter sequences

Number of TFs Unregulated

in E. coli, and countless “cryptic,” or non-

Single-input

functional, ones (Huerta and Collado-

Binary

Vides, 2003). Promoters comprise about 10% of the total genome size. When a gene has no known TF regulators, or the

7%2% 31%

18%

Trinary 4-6 Escherichia coli σ70 promoters

42%

TFs are not present in the cell, it is said to be constitutive. Combinatorial promoters are regulated by two or more TFs. 220 combinatorial promoters have been annotated in E. coli (Figure 1), but there undoubtedly many more. It is common for more than one promoter to regulate the same gene, such as when two closely spaced promoters direct transcription in the same direction (a “tandem” promoter).

Terminator: Region of regulatory DNA just downstream of a gene. This variable-length region is usually less than 100 bp in length, and always contains a self-complementary hairpin region followed by an AT rich region. In very compact genomes (phages), this AT rich region may

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Transcriptional regulation and combinatorial genetic logic in synthetic circuits contain the promoter of a downstream gene. Very strongly transcribed genes, such as the rRNA genes, often contain stacks of three or more terminators to insure efficient termination. The activity of terminators is sometimes regulated by protein factors such as ρ, though this is not nearly as common as TF regulation at promoters.

Operon: Transcriptional unit containing genes, promoters, and terminators. This is usually extended to include regulatory sites which lie may lie outside of the promoter, coding, and termination regions. Multiple (tandem) promoters that transcribe the same gene(s) are considered part of the same operon, even when one promoter is located between two genes. A minimal operon contains just one promoter, gene, and terminator.

σ factor: Subunit of bacterial RNA polymerase which recognizes the promoter region. Bacteria typically contain between 3 and 30 σ factors (Rodionov, 2007). About half of all promoters are typically recognized by the “housekeeping” σ factor, called σ70 in E. coli. These promoters express the genes necessary for normal growth: polymerases, ribosomes, membrane synthesis, DNA replication and repair, respiration, amino acid metabolism, etc. Most combinatorial promoters are recognized by this σ factor. Every promoter contains a -10 box for σ binding (σ70 consensus TATAAT) and most promoters contain a second -35 box also bound by σ (σ70 consensus TTGACA). The spacing between the -10 and -35 boxes in σ70 promoters is strongly conserved at 17 ± 1 bp. The σ factor is released from the RNA polymerase complex during transcription elongation.

TF: Transcription factor. A protein that binds to DNA, usually near the promoter, to regulate the initation of transcription. While the σ’s determine which genes can be expressed, the TFs decide which genes are actually needed. TFs usually act by regulating recognition of the promoter sequence by RNA polymerase. The seven global TFs (CRP, IHF, FNR, ArcA, Fis, NarL, Lrp) regulate about half of all characterized σ70 promoters, and most combinatorial promoters. In E. coli there are about 150 specific (non-global) TFs known, and another 150 putative TFs based on

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Figure 2. Activator operators cluster upstream of -35.

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The operator location for 298 specific activator TFs. The histogram plots Specific activator TFs the number of operators centered at each location, relative to the start site of transcription (+1). 60% of −150 −100 −50 +1 +50 +100 activator operators ocOperator center location relative to transcription start (bp) cur between -30 and -75.

homology. In free-living bacteria, TFs typically comprise 5-10% of the total number of genes (Rodionov, 2007).

Operator: TF binding site. These usually occur within the promoter region. Most operators are 12-24 bp in length, so a maximum of about 6 (non-overlapping) operators can fit within the promoter region. In special cases, multiple TFs can recognize the same operator (e.g., λ cI and cro repressor (Ptashne, 2004).

Activator: TF that increases gene expression, usually by contacting and “recruiting” the RNA polymerase to the promoter. Specific activators normally bind between -35 and -75 (Figure 2), and increase the rate of promoter recognition by binding to the σ and α RNA polymerase subunits. Most activators respond positively to environmental inducers or co-factors; which modulate DNA binding, protein folding, stability, or conformation. Some activators (e.g., λ cI) act by increasing RNA polymerase isomerization and DNA melting. All seven global TFs are activators.

Repressor: TF that decreases gene expression, usually by steric occlusion, where the repressor blocks the RNA polymerase from binding to the promoter. Specific repressors normally bind between +25 and -75 (Figure 3), and decrease the rate of promoter recognition. Most repressors respond negatively to environmental inducers or co-factors, which modulate DNA binding. Some repressors act by blocking transcription elongation (i.e., “roadblock”), or by changing the conformation of the DNA. All global TFs are also repressors.


Figure 3. Repressor operators span the promoter region. The operator location for 479 specific repressor TFs. The histogram plots the number of operators centered at each location, relative to the start site of transcription (+1). 70% of repressor operators occur between +25 and -75.

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15 10

Specific repressor TFs

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−150 −100 −50 +1 +50 +100 Operator center location relative to transcription start (bp)

Measuring Gene Expression: Choice of Reporter and System In this section, I describe the measurement of gene expression and regulation. I present a summary of qualitative differences between each measurement system, and focus on how to select the appropriate tool for a given application. This section can be skipped by those familiar with genetic reporter systems.

Reporter genes To begin any discussion of how we might control gene expression, it is necessary to understand how we measure it. Unfortunately, there is no direct way to compare the diverse forms of gene expression data. As we shall see below, even ratios of expression measurements are unreliable. Still, we can obtain insight by comparing measurements within the same experimental system. The primary tool for monitoring gene expression is the genetic reporter. Three types of genetic reporters are employed in this work: the β-galactosidase enzyme from the lactose metabolism operon (LacZ), the light-producing bacterial luciferase operon from Photorhabdus luminescens, the Green Fluorescent Protein (GFP) and its relatives. Each reporter is naturally suited to different applications (Table I). Detailed descriptions of each reporter can be found in their associated reviews (Meighen, 1991; Miller, 1972; Tsien, 1998).

LacZ is the traditional reporter of gene expression taken from bacteria, and for good reason. It is an extremely stable enzyme, even when expressed in eukaryotes, and is well-characterized biochemically.

7 LacZ is extremely sensitive, and level of signal measured is linearly proportional to the amount of LacZ present. Typically, the catalytic activity of LacZ is measured in a cell culture lysate by the fluorescence of a cleaved substrate molecule. This results in signal amplification (one LacZ enzyme can catalyze many cleavage reactions), while averaging the signal across the entire cell population. The sensitivity is ultimately determined by the background fluorescence level of the measurement condition. In optimal conditions, a single LacZ molecule can be observed inside individual living cells (Cai et al. 2006). The upper end of the dynamic range is limited by the toxicity of LacZ overexpression. LacZ is a large gene (which are often toxic at high expression levels), and is slow to mature. In one comprehensive study, LacZ was unable to distinguish differing promoter response times revealed by GFP and luciferase measurements (Zaslaver et al. 2004). Commonly, quantitative measurements can be made over three to four orders of magnitude (Oehler et al. 1994). LacZ is an

Table I. Genetic reporter properties gfp Yes In vivo reporter No Requires exogenous substrate Yes Single gene (protein fusions) Fast4 Signal maturation Moderate Toxicity ~50 Max sensitivity (molecules per cell) Moderate Dynamic range 5 Yes Single-cell measurements Yes Multiple color variants Good Linearity Fluorescence Assay type 6 High Signal Stability Intrinsic Protein activity 7 Monomer Oligomerization Reporter gene family

lacZ No1 Yes Yes Slow High ~1 Moderate No No Good Fluoresence Very high Catalytic Homotetramer

luciferase Yes No2 No3 Fast Low 106 ALU) upon induction (Table 1). Within the limits of detection, the effective repression (r) tended to increase with unregulated expression level.

Strikingly, the SIG showing the strongest regulation (r = 8.9×104, Table 1, D18) had only a single TetR operator at the core region. Furthermore, a single repression site at any of the three positions was often enough to repress the promoter below the detection limit (Fig. 3). In general, multiple operators were not more effective at repression than single operators. We found 9 LacI-regulated and 6 TetR-regulated SIGs containing multiple repressor operators. Of these, only one LacI-regulated (Table 1, A38) and one TetR-regulated (Table 1, B19) promoter produced higher regulation than corresponding promoters containing a single operator. These results show that operator position is more important than operator multiplicity for achieving strong regulation with repressors.

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Dual-input logic We next considered dual-input gates as logic functions of their two input inducers. Because of the continuous nature of the output levels in each input state, Boolean logic does not accurately represent the space of possible functions. For example, in a recent study the natural lac promoter increased activity by a factor of 3.6 when induced by cAMP alone, by a factor of 7.1 when induced by IPTG alone, and by a factor of 14 when induced by both simultaneously (Setty et al. 2003). This intermediate behavior could be described as either AND-like or OR-like, depending on the activity threshold chosen.

In order to describe such “intermediate logic” phenotypes, we introduced a 3-dimensional parameterization for the space of promoter functions. In this scheme, we represented the promoter functions with three numerical parameters that quantify dynamic range, logic type, and asymmetry of inputs (Methods). As before, r is the ratio of the maximum to minimum promoter activity. The parameter l quantifies the logical behavior of the promoter: from pure OR (l = 0) to pure AND logic (l = 1). Finally, the parameter a quantifies the asymmetry of the gate with respect to its two inducers. At a = 0, the gate responds identically to either inducer, while at a = 1, the promoter responds to one input only (pure SIG). These parameters span the full range of observed phenotypes, and have intuitive interpretations. They also represent relative promoter activities, rather than absolute levels, making them less sensitive to the choice of reporter, growth media, or other experimental conditions. Therefore, they form an ideal quantitative representation for the phenotypic behavior of these promoters.

Within this logic-symmetry space, the positive monotonic response of promoters to their inputs restricts promoter logic to the triangular region shown in Figure 4. The corners of this region include three Boolean logic functions: the switch-like SIG (l = 0.5, a = 1), along with the canonical binary gates AND (l = 1, a = 0) and OR (l = 0, a = 0). The symmetric SLOPE gate (l = 0.5, a = 0) exhibits logic intermediate between AND and OR. The asymmetric asym-AND

Chapter 2: Programming Promoter Logic (l = 0.75, a = 0.50), asym-OR (l = 0.25, a = 0.50), and asym-SLOPE (l = 0.50, a = 0.50) gates describe idealized logic functions intermediate between SIG and AND, SIG and OR, and SIG and SLOPE, respectively (Fig. 4A). This representation provides qualitative categories for the different types of logic displayed by monotonic dual-input promoters.

We identified 50 dual-input gates (Methods). Each defined a point (r, a, l) in the logical phenotype space (Fig. 4B), revealing a range of functional behaviors. Asym-AND and SIG-like gates exhibited strong regulation up to r = 105. The AND and asym-SLOPE gates were regulated up to r = 104, while the SLOPE gates were regulated up to r = 103. Notably, we found no gates exhibiting strong OR or asym-OR logic functions. However, one class of dual-input promoters (discussed below) exhibited asym-SLOPE logic approaching an asym-OR response (l < 0.50). Thus we observed a wide distribution of promoter logic types.

The library contained two classes of dual-input gates. The repressor-repressor (RR)-promoters contained operators for the repressors LacI and TetR, while the activator-repressor (AR)promoters responded to the activator AraC and one of the repressors. Due to the relative scarcity of LuxR-activated promoters, we did not find LuxR regulated AR promoters in the characterized promoter set (Fig. 2A). These two classes of dual-input gates exhibited differing, but overlapping, distributions of logical phenotypes.

Comparison of AR and RR promoter phenotypes (Fig. 4B) revealed that each has a preference for different logical categories, although both produced strong asym-AND gates. The RR promoters produced the strongest symmetric (AND and SLOPE) gates, whereas the AR promoters generated the strongest asym-SLOPE gates. This shows that RR promoters produced both symmetric and asymmetric logic, while AR promoters produced only asymmetric logic.

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Mathematical model of repressor interaction To better understand the variety of symmetric and asymmetric logic observed for the RR promoter class, we employed a simple model of promoter activity in the presence of two repressors (Methods). In this model (c1, c2, ω ) represent the strength of repression at the stronger operator, the weaker operator, and the repressor-repressor interaction, respectively (Bintu et al. 2005b). When the repressors do not interact with each other, ω = 1; whereas for exclusive interactions (only one repressor can bind at a time), ω = 0. Cooperative interactions would correspond to ω > 1.

The logic parameter l was tightly coupled to the model interaction parameter ω (Methods). A plot of a and l as parameterized functions of the microscopic model parameters (Supplementary Figure S4) showed that RR promoters with ω ranging from 0 (exclusive interaction) to 1 (independent interaction) can produce any logic function in the right half (l ≥ 0.5) of the phenotype space triangle: SIG, AND, SLOPE, asym-AND, and asym-SLOPE. In particular, exclusive interaction (ω = 0) approached pure AND logic (l = 1) whereas independent interaction (ω = 1) always resulted in SLOPE-like logic (l = 0.5). Conversely, we found that an asym-OR gate would require extremely high cooperative interaction (ω = 100); while an ideal OR gate would require infinite cooperativity. Therefore, the range of logic functions displayed by the library RR promoters (Fig. 4B) fall within the spectrum of non-cooperative interactions (1 ≥ ω ≥ 0). This model demonstrates that a variety of logic functions can be achieved without explicit protein-protein cooperativity.

RR promoters Dual-repression can be either symmetric or asymmetric (Fig. 4B), with either repressor dominant (Fig. 5A). As with the SIGs, even the strongest RR promoters could be fully repressed, exhibiting effective repression up to r = 105. RR promoter logic was always AND-like or SLOPE-like (0.5 ≤ l ≤ 1.0), indicating that there were no instances of strong cooperative interaction between the repressors (ω ≤ 1). In three cases, mutation of a repressor operator resulted in almost completely asymmetric (a = 1) SIG logic (Fig. 4B, top of triangle). In other cases the repression was more

Chapter 2: Programming Promoter Logic balanced (a < 0.25), producing symmetric AND and SLOPE responses up to r = 104. Thus, RR promoters displayed a large range of dual-input regulatory logic including AND, SLOPE, asymSLOPE, and asym-AND gates.

In principle, the logic phenotype displayed by a promoter could depend on the inducer concentrations used. Therefore, we chose three RR promoters (Fig. 5A, clones A3, D8, and D9), and measured their responses to 16 combinations of inducer concentrations (Supplementary Methods). As expected, all three promoters increased their activity monotonically with increasing concentrations of each inducer. As shown in Supplementary Figure S5, inducer concentrations primarily affected r and a, while the logic parameter l was less dependent (Supplementary information). The most AND-like gate (A3) had the highest variation in logic (l = 0.46 to l = 0.86), while the most SLOPE-like (D9) exhibited the narrowest range (l = 0.48 to l = 0.53). These results imply that r and a depend strongly on input concentration; while for l, independent (SLOPE) logic is more robust than exclusive regulation (AND).

The repressor operator location trend core ≥ proximal ≥ distal explains the combinatorial promoter behaviors shown in Fig. 5A. For RR promoters, the position of the operators determined whether LacI or TetR was dominant. We found only one clear exception to this trend (Fig. 5A, clone A3), where TetR acting at proximal slightly dominates LacI acting at core. Symmetric repression occurred for several architectures, such as with a TetR at core and two LacI operators, one at distal and the other at proximal (Fig. 5A, A28). In all other asymmetric cases core dominated proximal and distal, while proximal dominated distal. RR promoter architectures with operators at proximal and distal produced the largest range of logic behaviors including AND, SLOPE, asym-AND, and asym-SLOPE. RR promoters with operators at the core and proximal positions produced only AND and asym-AND logic. Of the 7 RRpromoters exhibiting strong AND-like logic (l > 0.8), 5 had operators at core and proximal. Finally, RR promoter architectures with operators at core and distal produced the most asymmetric logic functions (e.g., Fig. 5A, B83):

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Transcriptional Regulation and Combinatorial Genetic Logic the repressor acting at core was always strongly dominant. These results show that repressor dominance in combinatorial promoters follows the trend core ≥ proximal ≥ distal, and that close operator proximity is consistent with AND-like logic.

AR promoters Among AR promoters (Fig. 5B), repression always dominated activation (0.06 ≤ a ≤ 0.99). The AR promoters were regulated by AraC, in combination with LacI or TetR, and exhibited regulation up to r = 104. In all cases the activator functioned from the distal region, while the repressor functioned at core or proximal. We found one AR promoter that approached symmetric response (r = 3272, a = 0.06, l = 0.81, Fig. 5B, D61). The three most AND-like (l > 0.8) promoters of this class had the repressor operator at the core. The most OR-like (smallest l) promoter exhibited asym-SLOPE logic (r = 9112, a = 0.65, l = 0.46, Fig 5B, A54), with the repressor operator at proximal. Therefore, we found AR promoters are well represented by asym-AND when the repressor acts as core and asym-SLOPE when the repressor acts at proximal.

The AR promoters also confirmed our previous result relating activation to intrinsic promoter activity: The higher the unregulated activity of an AR promoter (+ IPTG/aTc, -Lara), the smaller the change upon activator induction (compare the last two columns in Fig. 5B). When the unregulated activity exceeded the activation ceiling, the AR promoter did not respond to AraC induction at all, resulting in SIG-like behavior (e.g. Fig. 5B, D46). This result indicates that AR promoters will depend on both inputs only when the unregulated promoter activity is below the activation ceiling.

Chapter 2: Programming Promoter Logic

Discussion Combinatorial synthesis of synthetic promoters, as described here, permits systematic analysis of promoter architecture and rapid identification of promoters that implement specific functions. The spectrum of promoter functions observed in this library highlights several heuristic rules for promoter design: 1. Limits of regulation. Gene expression can be regulated over five orders of magnitude. Regulated promoter activity is independent of unregulated activity. As a result, effective repression tends to increase with unregulated activity, while activation tends to decrease. Activation is limited by an absolute level of expression, at around 2.5% the level of the strongest unregulated promoter activities. 2. Repressor operator location. The effectiveness of repression depends on the operator location with core ≥ proximal ≥ distal. Dual-repression may be symmetric or asymmetric, with the dominant repressor predicted by operator locations. 3. One is enough. Full repression is possible with a single operator between -60 and +20 at high repressor concentrations. Activators function only upstream of -35 (distal), and have little positive or negative effect downstream at core or proximal. 4. Repression dominates activation, producing asymmetric logic. 5. Operator proximity. Independent regulators generate SLOPE-like logic. Operator proximity increases competitive interactions, making the logic more AND-like.

For both activation and repression, the activity of the promoter in the regulated (activated/ repressed) state is not determined by the activity in the unregulated state (Rule 1). Intuitively, activation has higher r when the unregulated activity is low, and repression has higher r when the unregulated activity is high. Furthermore, as predicted by recent theoretical work (Bintu et al. 2005a); repression is able to achieve extremely high levels of regulation (r ≤ 105), while activated regulation is moderately strong (r ≤ 103). These limits apply to both SIGs (Figs. 2-3) and dual-

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Transcriptional Regulation and Combinatorial Genetic Logic input promoters (Fig. 5). AR promoters are a special case, and exhibit a trade-off: Increasing the unregulated activity increases the regulatory range (r), at the expense of greater asymmetry (a). For example, compare the first and last promoter in Fig. 5B.

Rules 2 and 3 summarize the operator position and multiplicity effects for both activators and repressors. The repression trend (Rule 2) has been previously reported for promoters regulated by LacI (Elledge and Davis, 1989; Lanzer and Bujard, 1988). The authors of the first paper proposed a mechanistic model involving two competing effects: Core and proximal sites more effectively block polymerase binding, while core and distal sites bind repressor more rapidly (are more accessible) as the polymerase initiation complex clears the -10 and -35 boxes. We confirmed the operator location trend for SIGs regulated by LacI and TetR alone, and found that this heuristic also holds for RR promoters of both repressors. Of course, differences in operator affinity, repressor concentration, and repressor structure can overcome these rules.

We compared Rules 2 and 3 with the distribution of known E. coli operators compiled from 1,102 natural promoters in the database RegulonDB (Salgado et al. 2006) (Figure 6). In agreement with analysis made on earlier versions of the database (Collado-Vides et al. 1991; Gralla et al. 1996), we found that activator operators are most common in the distal region (Fig. 6A), while repressor operators cluster around all three promoter regions (Fig. 6B). Fig. 6C shows the operator density of the 554 promoters which are recognized by the polymerase subunit σ70. The small regulatory effect observed for activator operators in the core and proximal regions (Rule 3) appears consistent with the general scarcity of natural activator sites in these regions. Similarly, the density of repressor operators found in σ70 promoters is significantly enriched for core sites over distal and proximal locations, consistent with the repressor operator location trend (Rule 2).

The sufficiency of one operator for repressing promoter activity up to five orders of magnitude (Rule 3) raises the classic question of why natural promoters are so often regulated by redundant

Chapter 2: Programming Promoter Logic operators (Collado-Vides et al. 1991). Our study used high concentrations of repressors in the range of 2-4 µM (Lutz and Bujard, 1997), paired with strong operators (Table S1). At lower repressor concentrations and operator affinities, the presence of multiple binding sites can increase the effective repression r through looping (Becker et al. 2005; Vilar and Leibler, 2003), cooperativity (Oehler et al. 1994; Ptashne, 2004; Rosenfeld et al. 2005), or even without explicit TF-TF interactions (Bintu et al. 2005a). These effects can also increase the steepness of response to repressor concentration (Ptashne, 2004), or engender exceptions to the dominance of repression (Rule 4). Finally, the presence of multiple operators might increase the mutational plasticity of promoter functions (Mayo et al. 2006).

Rule 5 provides insight for both AR and RR promoters: Operators at neighboring sites will tend to generate more AND-like logic (higher l) than non-neighboring sites (i.e. distal and proximal). In AR promoters, repression at core produces more AND-like logic than at proximal. This effect can be understood intuitively for RR promoters: If operators are closely spaced, binding of one repressor can inhibit the binding of the other. Removing one repressor has two conflicting effects: it increases expression due to its reduced occupancy, but it simultaneously decreases expression by allowing binding of the other repressor. This makes the overall logic more AND-like. In terms of the mathematical model, AND-like (l > 0.8) RR promoters correspond to strong balanced repression (c1 ≈ c2 >> 1) and exclusive interaction (ω ≈ 0).

The library described here represents a starting point for systematic investigation of the functional repertoire of prokaryotic promoters. These simple promoters cannot include all of the complex effects found in natural promoters, including those dependent on DNA bending or specific protein-protein interactions. Nevertheless, they provide a view of what is possible with the simplest genetic elements and interactions. Within this context, the heuristics described above allow the design of particular promoter functions controlled by arbitrary TF regulators. The assembly method allows for construction of any specific promoter. Other promoter architectures

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Transcriptional Regulation and Combinatorial Genetic Logic could be generated with this method to provide more diverse logic phenotypes, or to explore regulatory DNA in eukaryotic organisms (Ligr et al. 2006). For example, the lac promoter architecture, regulated by a distal activator and multiple repressor operators (including upstream sites), can exhibit phenotypes not found in our library, such as asym-OR (Mayo et al. 2006). In another case, a synthetic activator-activator (AA) promoter has been constructed which exhibits near-symmetric SLOPE logic ( Joung et al. 1994). Tandem promoters are expected to generate additive logic functions more closely representing OR logic, and in fact many natural promoters are found in tandem repeats (Collado-Vides et al. 1991). If our heuristic rules apply to natural combinatorial promoters, we may begin to elucidate complicated functions by inspection of these non-coding DNA sequences. In this regard, effective parameterizations of logic such as the one shown in Fig. 4 can provide a more intuitive understanding of the computations performed by promoters.


Materials and Methods Reagents All inducers and chemicals were purchased from Sigma. Concentrations (unless otherwise stated) were 50 µg/mL kanamycin, 100 µg/mL ampicillin, 500 µM isopropyl β-D-1-thiogalactopyranoside (IPTG), 100 ng/mL anhydrotetracycline (aTc), 0.1% L(+)-arabinose (Lara), 1µM oxo-C6homoserine lactone (VAI). LB growth media (Lennox) was used for all experiments. All ligation reactions were carried out with 1.25 units of T4 DNA ligase (Invitrogen) and 0.1 mg/mL BSA (Invitrogen) in 20µL of T4 ligase buffer (Invitrogen) at 4°C.

Randomized assembly ligation Promoters were constructed by total synthesis and ligation (Chapter 1, Methods). Each promoter was constructed from three duplex DNA fragments comprising the distal, core, and proximal regions. An overhanging phosphorylated G on the downstream 5’ end of distal is compatible with a phosphorylated overhanging C on the upstream 5’ end of core. Likewise, an overhanging phosphorylated AA on the downstream 5’ end of core is compatible with an overhanging phosphorylated TT on the 5’ upstream end of proximal. The terminal ends of the fully assembled promoters had mutually incompatible XhoI and BamHI 4bp 5’ overhangs, which remained unphosphorylated. A total of 48 duplex units (Supplementary Table S1) were annealed out of 96 PAGE-purified synthetic DNA oligonucleotides (University of Calgary DNA synthesis and sequencing center) at 1μM in T4 ligase buffer. All 48 duplex units were mixed together in equal 50nM proportions and ligated for one week, then cloned into bacterial luciferase reporter plasmid pCS26 (Bjarnason et al. 2003). We purified the plasmids using the Qiagen Plasmid Midi kit, and transformed the library into strain MGZ1X (reference MG1655 (Riley et al. 2006) containing the native ara operon, the LacI- and TetR-overexpressing Z1 cassette (Lutz et al. 1997) and the medium-copy plasmid pCD136 which constitutively expresses LuxR). We picked 10,000 clones and chose 288 randomly for sequencing (Bjarnason et al. 2003) and functional characterization.

75

76


Luminescence measurements The library was assayed in 16 inducer conditions corresponding to all saturating combinations of the four inducers: VAI, IPTG, Lara, and aTc. Cells were grown in 96-well plates to stationary phase (16-22 hours at 37°C) and inoculated into triplicate 96-well plates containing LB media, antibiotics, and each inducer combination. These were grown at 25°C for 18 hours in the dark. Luminescence measurements were obtained using a Tecan Safire plate reader (100ms integration, default settings). To determine the background, we took the median measurements of non-functioning clones in each condition. All data reported are the median of triplicate measurements.

To assess the luminescent crosstalk between neighboring wells, we inoculated a constitutively bright clone into every other row and column of a 96-well plate (24 wells total) and measured it continuously during growth over 18 hours. This data was used to compute the horizontal/vertical (j1) and diagonal (j2) neighbor crosstalk. We assumed (linear) crosstalk of the form O = AX, where O is the observed data, A the actual luminescence of each well, and X the crosstalk matrix. We computed A = OX-1 for combinations (j1, j2) and then took the total variance of all empty wells as a metric. This metric reached a minimum of 0.017% horizontal/vertical and 0.002% diagonal crosstalk. This was a very small effect compared to other sources of error (below), and only resulted in an appreciable difference for wells neighboring the very brightest clones (~106 ALU). The vector background level (~10 ALU) was subtracted from all data points. We set each datum to a minimum level of 10, corresponding to one count/100ms.

To assess the plate-to-plate variation, we calculated the standard error between triplicates and divided by the mean. We found an average replicate error of 24%. To assess day-to-day error, we measured one set of 96 clones on two consecutive days and computed standard relative errors by a linear fit of the second day’s data to the first (44%). Similarly, we computed the well-to-well error on the same plate by identifying clones with the same sequence genotype and doing a linear fit

Chapter 2: Programming Promoter Logic between them (54%). Together these data provide an upper limit of ~50% on repeatability.

Promoter function analysis To calculate the expression levels for dual-input promoters (or SIGs) we first identified the two (one) primary inducers of each promoter. We then averaged the luminescence data over the four (eight) background conditions. Standard errors were computed from these values, and the median of the triplicate measures gave the four (two) expression levels of the gate. We then computed the regulatory ratio r, defined as the maximum expression level divided by the minimum. The error in regulation (Table 1) was computed from the relative errors for each state. For SIGs with expression levels b1 (off ) and b2 (on), the error in r is:  ∆b1  2  ∆b2  2 ∆r = r   +  .  b1   b2  We identified SIGs and dual-input promoters from their sequences (Supplementary Data 1). Functional activator operators were found at distal, and functional repressor operators occurred € at all three positions. With one exception (discussed in Supplementary information), significant (2×) regulation by a TF occurred only with one or more corresponding operators in the promoter sequence. The presence of an operator did not always guarantee regulation: non-functioning SIGs lie on the diagonal lines of Figs. 2 and 3, and dual-input promoters responding to only one input occur at the apex (a ≈ 1) of the triangle in Fig. 4B.

Logic-symmetry space In addition to the regulation r, the two-input gates displayed a variety of relative expression levels. For the dual-input promoters, we defined four measured response values (b1, b2, b3, b4) such that b4 ≥ b3 ≥ b2 ≥ b1. Since repression always dominated activation, for AR promoters b2 corresponded to the activator induced state and b3 corresponded to the repressor induced state. Similarly, for RR promoters, b2 corresponded to the expression level when the weaker repressor is induced and b3 to induction of the stronger. In order to represent the range of logical functionality we defined

77

78

Transcriptional Regulation and Combinatorial Genetic Logic the three phenotypic parameters (r, a, l) in terms of these response values: r≡

log b3 − log b2 2 log b4 − log(b2b3 ) b4 ,a ≡ ,l ≡ log r 2 log r b1 .

Specifically, l quantifies the logic type ranging from a perfect AND (b3 = b2 = b1 ⇒ l = 1) to a perfect OR (b3 = b2 = b4 ⇒ l = 0). The parameter a quantifies the asymmetry with respect to the two inputs, ranging from perfectly symmetric (b2 = b3 ⇒ a = 0) to the completely asymmetric SIG (b3 = b4 and b2 = b1 ⇒ a = 1).

SLOPE theorem: separation of variables in combinatorial gene regulation Consider a dual-input promoter regulated by two TFs: X and Y (we use x and y to represent their respective activities). If these TFs regulate the promoter independently with single-input functions s(x) and t(y), the variables of the regulation function p(x,y) separate: p(x, y) = s(x)t(y) . Suppose (without loss of generality) that regulator X is dominant. Then the four logical output states of the promoter are:

€

b1 = p(↓↓),b2 = p(↓↑),b3 = p(↑↓),b4 = p(↑↑) . The arrows signify the high ( ) and low ( ) states of the promoter with respect to each input (e.g. induced € and uninduced, respectively). The logic parameters of the promoter are then, by definition:

r≡

b4 p(↑↑) a b3 p(↑↓) l b4 = ,r ≡ = ,r ≡ = b1 p(↓↓) b2 p(↓↑) b2b3

p(↑↑) p(↓↑) p(↑↓) .

Considering the logic parameter l, the separation of variables requires that: € 1 p(↑↑) s(↑)t(↑) s(↑)t(↑) p(↑↑) 1 rl = = = = =r2 ⇒l = s(↓)t(↓) p(↓↓) 2. p(↓↑)p(↑↓) s(↓)t(↑)s(↑)t(↓) Therefore, separation of variables—regardless of the TF regulation functions—implies that the €promoter logic is always SLOPE or asym-SLOPE (or in the case that one of the regulators is nonfunctional, SIG). The converse is not generally true, but it does hold for the model of dualrepression discussed below.


Model of RR promoter logic We employed a previously defined model of RR promoter activity under dual-repression (Bintu et al. 2005b). P (R1 , R 2 ) =

A 1+ c1 R1 + c2 R 2 +ωc1 R1c2 R 2

The maximal promoter activity is A, and the normalized repressor concentrations (R1, R2) range from 0 to 1. Here€c1 and c2 represent the effectiveness of each repressor at excluding polymerase from the promoter. The term ω represents interactions between repressors: ω < 1 corresponds to competitive binding, ω = 0 represents exclusive binding, and ω > 1 represents cooperative binding. When ω = 1 the repressors are said to act independently.

We solved for the three logic-symmetry parameters (r, a, l) in terms of the three microscopic parameters (c1, c2, ω):  1+ c1  1 log((1+ c1 )(1+ c2 )) log ,l = log(r )  1+ c2  2 log(r ) By the SLOPE theorem, independent interaction (ω = 1) produces SLOPE-like logic (l = 0.5). r = 1+ c1 + c2 +ωc1c2 , a =

The converse is also true here: when l = 0.5, RR promoters (c1 ≥ c2 > 0) are regulated by the two € repressors independently (ω = 1). 1 log((1+ c1 )(1+ c2 )) = ⇒ 1+ c1 + c2 +ωc1c2 = (1+ c1 )(1+ c2 ) ⇒ ω = 1 2 2 log(1+ c1 + c2 +ωc1c2 ) For symmetric RR promoters (c = c1 = c2 ⇒ a = 0), the independently interacting RR promoter is an ideal SLOPE gate (a = 0, l = 0.5). When the interaction is symmetric but dependent (ω ≠ 1), € the logic l is described by: l=

€

log(1+ c) log(1+ 2c + c 2ω)

79

80

Transcriptional Regulation and Combinatorial Genetic Logic For exclusive interaction (ω = 0), the logic depends only on the operator strength c. As c grows large, the logic approaches pure AND (l = 1): l≈

1

1+

1 log 2 (c)

In the opposite extreme, pure OR logic (l = 0) is only approached in the limit log c ω → ∞: €

l≈

1 2 + log c (ω)

€

RegulonDB analysis

€ Following prior analysis of transcription factor binding sites (Collado-Vides et al. 1991), we examined 1,102 E. coli regulatory promoter sequences from RegulonDB 5.0 (Salgado et al. 2006). Operator binding sites for activators and repressors in each promoter were identified. The TF operators annotated as “dual” were removed from this list. For each operator, we determined the middle of the annotated binding sequence; calculated the distance to the annotated transcription start, and calculated the number of repressor and activator operators centered at each base pair in the region (~400bp total). These distributions were plotted as histograms for activators and repressors (Fig. 6 A-B). We also calculated the distribution of operators for 554 promoters recognized by σ70 (Fig. 6C). In this histogram, the relative fraction at each region was weighted by its length in bp. This weighting was necessary to observe the enrichment of repressor operator density in the core region.


81

Table 1. SIG promoters TF

Expression

Genotype1 distal

-35

core

-10

proximal

D18

con0

TTGACA

tet1

GATACT

con1

1.2 ± 0.4×104

B10

con0

TTGACA

tet1

GATACT

con3

4.7 ± 0.2×105

3.3 ± 0.7×104

B19

ara3

TTGACA

tet2

GATACT

tet1

23 ± 7

9.9 ± 0.8×104

4.4 ± 1.4×103

A9

con0

TTGACA

tet2

TAGAGT

ara2

15 ± 5

6.9 ± 1.1×104

4.7 ± 1.6×103

B22

con4

TTGACA

con4

TAGATT

tet1

12 ± 0

3.0±0.2×105

2.5±0.2×104

B4

lac1

TTGACA

lac2

GATACT

con0

18 ± 3

2.7±0.3×104

1.5±0.2×104

A81

lac2

TTGACT

con1

GATACT

lux1

86 ± 25

3.1±0.2×105

3.6±1.1×103

A38

lac1

TTGACA

con0

TATAAT

lac4

273 ± 92

7.2±0.2×104

2.6±0.9×102

A87

con0

TTGACA

ara1

GATACT

lac4

58 ± 17

3.6±0.3×104

6.2±1.9×102

A52

lac1

TTGACA

ara1

GATACT

con1

LuxR 130 ± 50

1.4±0.1×105

1.1±0.5×103

D49

lux1

TTTACT

con2

GATAAT

lux2

420 ± 310

9.7±2.3×104

230 ± 180

D80

lux3

TTTACA

lux2

TATAAT

con3

AraC 310 ± 60

7.3±0.9×104

230 ± 50

A79

ara2

TAGACA

ara1

GATACT

lux2

250 ± 30

2.8±0.6×104

110 ± 30

A1

ara2

TAGACT

con2

GATAAT

con1

TetR

LacI

Uninduced (ALU)

Induced (ALU)

26 ± 8

2.3 ± 0.2×106

8.9 ± 0.3×104

14 ± 4

1.7 ± 0.1×105

14 ± 3

Regulatory Range (r) ID

1 The genotype refers to the three units that make up each promoter and the -10 and -35 polymerase boxes. Here “con,” “tet,” “lac,” “ara,” and “lux” refer to no operator, TetR, LacI, AraC, and LuxR operators, respectively. In each case, the number refers to the operator variant. Full sequences for each unit are available in Supplementary Table S1. Functional operators are highlighted in bold.


82

Figure 1. distal

core

-35

-10

+1

proximal

gacttgtgagcgctcacaatt tataattcgtgcaatTtttaaacctgtaggatcgtacaggt g A tcgagtacaacgtcgtgttagctgccttttagcaattttatccata atcgttaaaataggtat aacactcgcgagtgttaa tggacatcctagcatgtcca ctg

catgttgcagcacaatcgacggaaa

AraC I1 operator

atattaagcacgttaAaaatt

LacI Os operator

B

D

distal

cctag

LuxR operator core

proximal AraC

LacI luxCDA luxCDABE

KAN

LuxR

SC101

C

Lara aTc - -

TetR

10 7

-

+ +

10 3 -

+

+ -

+ IPTG + VAI

(ALU)

10 5

+

+

-

10 1

Figure 1. Random assembly ligation generates a diverse promoter library. Promoters can be assembled out of modular sequence units. (A) The assembled sequence of an example promoter. The 5’ overhangs of each unit are shown in red. The RNA polymerase boxes (-10 and -35) are highlighted in yellow, and the predicted start site of transcription (+1) is capitalized. Operator colors are consistent throughout the figure. (B) Steps in promoter assembly and ligation into the luciferase reporter vector: Promoters are assembled by mixed ligations using 1- or 2-bp cohesive ends, and then ligated into a luciferase reporter plasmid. (C) Luminescence measurements in 16 inducer conditions (± each of 4 inducers, as indicated) for the promoter shown in part A. The output levels determine promoter logic. (D) The 48 unique units used in the library contain operators responsive to the four TFs (indicated by color) in the regions distal, core, and proximal (Sequences in Table S1). The promoter fragments corresponding to (A) are boxed in red.


Figure 2. A

core/proximal 6

Induced activity (ALU)

105

105

104

104

103

Activation limit AraC distal LuxR distal

102 101

B 10

6

Induced activity (ALU)

10

distal

102 104 106 Uninduced activity (ALU)

103 102 101

AraC proximal AraC core LuxR core LuxR proximal 102 104 106 Uninduced activity (ALU)

Figure 2. Activation functions at distal, and is attenuated by intrinsic promoter strength. (A) Measurements of promoters activated at distal operators. These promoters respond only to LuxR (solid triangles) or AraC (open triangles) induction. Some promoters fail to respond even though they contain a functional operator (points on the solid line). The activation ceiling (red dashed line) represents the maximal observed activation, and does not depend on the unregulated expression level. (B) Promoters containing operators at core or proximal do not respond to induction.

83

6

84


Figure 3. distal

104

LacI TetR background

102

core

104

102

102 104 106 Unrepressed activity (ALU)

core

104


102


C Repressed activity (ALU)

Repressed activity (ALU)

B


C Repressed activity (ALU)

B Repressed activity (ALU)

Repressed activity (ALU)

A


proximal

104


102


Figure 3. Repression is effective at all three positions, following the trend core

≥ proximal ≥ distal. Measurements of repressed single-input promoters. Responses are colored according to the repressor: LacI (filled) or TetR (open). Each promoter contains a single operator located at distal (A), core (B), or proximal (C) positions. Single-input activities are plotted in the induced (unregulated) versus uninduced (repressed) states. In some promoters, operators do not effectively repress the promoter (points located near solid black line). Luciferase detection limits are shown with grey dashed lines.

proxim

104


102

102 10 Unrepressed ac


85

Figure 4. Inputs

A

B

- - + + - + - +

1

Activity

0.75 asym-OR

SIG

asym-AND

0.5 asym-SLOPE 0.25 0

0

OR

SLOPE

AND

0.25

0.5 0.75 Logic (l) more OR more AND

1

asymmetry (a)

asymmetry (a)

1

AR-promoters RR-promoters

Regulation (r) 10

5

0.75

10

4

0.5

10

3 2

0.25

10

0

10 1 0

0.25

0.5 0.75 Logic (l) more OR more AND

1

Figure 4. Dual-input gates exhibit diverse functions in logic-symmetry space. Promoter response phenotypes can be represented by their asymmetry, a (y-axis), logic type, l (x-axis), and regulatory range, r. (A) Diagram showing the space of allowed logical phenotypes, with the locations of ideal logic gates indicated. The SIG gate responds completely to one inducer and not at all to the other. The SLOPE gate represents an intermediate logical function between AND and OR, while the asymmetric gates represent intermediate between SIG and the corresponding symmetric gate. Intermediate logical behavior is represented between these ideal locations. The logic-symmetry parameterization is defined in the Methods. Points outside of the dashed triangle are not accessible if promoters respond monotonically to each input. (B) The logical phenotypes of 50 dual-input promoters exhibiting strong regulation (r > 10). AR promoters are shown as purple circles, RR promoters are shown as gold disks. The diameter of each disk is proportional to the logarithm of its regulatory range, r.


86

Figure 5. A

LacI

Architecture

DISTAL

-35 TTGACA

CORE

AraC

Input/Output IPTG - + - + aTc - - + + Clone

-10 PROXIMAL TAGAGT

B83

TTGACA

TAGAGT

C61

TTGACA

GATACT

A3

TTGACA

TAGAGT

A60

TTGACA

TATAAT

D8

TTGACA

GATACT

A90

TTGACA

GATACT

A28

TTGACA

GATACT

C68

TTGACT

GATACT

D56

TTGACA

TATAAT

D9

B

Architecture AraC/TetR genotype

Input/Output Lara - + - + aTc - - + + Clone

TAGACA

TAGAGT

D46

TAGACA

TAGATT

A78

TAGACA

TATAAT

AraC/LacI genotype

D29

L-ara - + - + IPTG - - + +

TAGACT

TATAAT

A12

TAGACA

TATAAT

B31

TAGACA

TAGAAT

A54

TAGACT

TATAAT

D91

TAGACT

GATACT

D61

TAGACT

GATAAT

B81

Figure 5. Combinatorial promoter architecture reveals rules for programming gene

expression. The architecture and function of dual-input promoters. The architecture of each promoter (colored according to Fig. 1) is shown with its functional operators and -10 and -35 boxes. Promoter functions are shown as in Fig. 4A. (A) RR promoters respond to both LacI and TetR. The fourth induction column (+ IPTG, +aTc) corresponds to the unregulated state. (B) AR promoters respond to AraC and one of the two repressors, as indicated. Here, the third column (+IPTG/aTc, -Lara) corresponds to the unregulated state.

106

(Arbitrary luminescence units)

LacI/TetR genotype

TetR

105

104 103

102 101

87

Figure 6.

# of operators

-180 -160 -140 -120 -100 -80 -60 -40 -20 +1 20 40 60 80 100 120 140 160 180 200

# of operators

Repressors 40 35 30 25 20 15 10 5 0

Operator center (bp)

Activators

40 35 30 25 20 15 10 5 0

70 60 50 40 30 5’ remote 20 10 0


C

40 35 30 25 20 15 10 5 0

Activators

relative operator density (%)

# of operators

B

C relative operator density (%)

B

-180 -160 -140 -120 -100 -80 -60 -40 -20 +1 20 40 60 80 100 120 140 160 180 200

A

-180 -160 -140 -120 -100 -80 -60 -40 -20 +1 20 40 60 80 100 120 140 160 180 200

180 200


70 60

Activators Repressors

50 40 30 5’ remote 20 10 0

3’ remote

distal core proximal


Figure 6. The distribution of operator locations in natural promoters reflects functional

trends of synthetic promoters. Operator locations are as annotated in RegulonDB 5.0 (Salgado et al. 2006). Distributions of repressor (A) and activator (B) operators found in 1,102 E. coli promoters. The number of operators centered at each position relative to the start site of transcription (+1) is plotted. (C) The density of operators found in 554 σ70 promoters broken down into three promoter regions, distal, core, and proximal, as well as regions upstream (5’ remote) and downstream (3’ remote) of the promoter. The density is shown as the fraction of sites in each position weighted by the relative size (bp) of each region.

distal cor

88


Supplementary Results -10 and -35 polymerase box strength The 288 promoters exhibited five decades of variation in unregulated promoter activity (Supplementary Figure S1). These sequences contained twelve -35 boxes which differed from the consensus TTGACA at up to three positions, and six -10 boxes which differed from the consensus TATAAT at up to two positions. The distributions of unregulated promoter activity for the -35 and -10 boxes were highly variable and overlapping (Supplementary Figure S2). We found that three of the twelve -35 boxes (TTGACA, TTGACT, and TAGACA) and five of the six -10 boxes (TATAAT, TAGATT, TAGAGT, GATACT, and GATAAT) produced sets of relatively strong promoters (~90% of the distributions were higher than 103 ALU). All of the strongest promoters in the library (~106 ALU) contained two of these ‘strong boxes.’ We used the median promoter activity of the -35 and -10 box distributions to predict the unregulated promoter activity of each promoter (Supplementary Methods). The predicted promoter activities were weakly correlated (Pearson coefficient = 0.19, Kendall τ = 0.32) with the measured promoter activities, and exhibited the best agreement for the strongest promoters (Fig. S2C). Thus, strong promoters contained strong polymerase boxes; but the presence of strong polymerase boxes did not guarantee high promoter activity.

Activator operators at core and proximal We examined the effect of activator operators at core and proximal on maximum promoter activity (fully induced). Supplementary Figure S3 shows cumulative histograms of activity for four classes of promoters: no activator operator, an activator operator at proximal, an activator operator at core, and an activator operator at distal. For LuxR (Fig. S3A) the presence of an operator had no effect on median promoter activity. For AraC (Fig. S3B) we found two notable effects. First, the distribution of maximal promoter activities was higher when AraC acted at distal. This revealed that activation increased promoter activity on average, and that the maximal

Chapter 2: Programming Promoter Logic expression in the presence of the activator was uniform (near the 105 ALU activation ceiling). This narrow distribution of activated promoter levels is consistent with the LuxR distribution, though many fewer LuxR activated promoters were measured. Second, we found that promoters with an AraC operator only at proximal exhibited lower average promoter activity. Half of these promoters had a maximum activity of less than 200 ALU, and all of them exhibited activity less than 105 ALU. Conversely, the median strength of promoters without an AraC operator (or with an AraC operator at core only) was 20,000 ALU, and their maximal activity was 106 ALU. We note that the natural repressor activity of AraC is mediated by looping, not by steric exclusion (Hamilton and Lee, 1988), so this unexpected result is still consistent with previous work. From this analysis we infer that AraC can enact mild (10-100×) arabinose-independent repression at the proximal region only, and neither AraC nor LuxR can be transformed into a strong (≥10×) inducible repressor simply by moving its operator.

Spurious regulation by TetR We found 7 promoters whose activity was induced 2-3× by aTc, without the presence of an operator for TetR. Units containing a λ cI operator (Supporting Methods) have up to 10 out of 14 conserved positions of the TetR consensus operator. Every one of the 7 spurious TetR regulated promoters contained at least one such cryptic site. These results suggest that TetR may repress weakly (3×) by binding to λ cI operators.

Dual-repressor interaction in RR promoters We used the model of RR promoters (Methods) to analyze the relationship between logical phenotype and the repressor interaction parameter ω. Fixing r, we plotted lines of equal ω, varying a (Supplementary Figure S4). The logic parameter l did not depend strongly on r, though an increase in r was found to increase l at the extremes (near l~0 and l~1; e.g., compare different marker sizes in Fig. S4). We found that the logic parameter l did not depend strongly on a when a < 0.25. This means that logic and symmetry are ‘decoupled’ for near symmetric responses. As

89

90

Transcriptional Regulation and Combinatorial Genetic Logic a result, the logic parameter l depends only on ω. Asym-OR logic was possible only when r was relatively low (r ≤ 103) and ω was high (ω ≥ 100), in agreement with the analytical results (Methods). Conversely, perfect AND logic required r to be high (r ≈ 105) and ω to be low (ω ≈ 0).

Logic robustness to inducer concentrations We examined the logical phenotypes of promoters with intermediate inducer concentrations. We chose three RR promoters from Fig. 5A, and measured their response to 16 combinations of inducer concentrations (Supplementary Methods). These three promoters exhibited diverse logic: AND (clone A3), asym-AND (clone D8), and SLOPE (clone D9). We found that all three promoters increased their activity monotonically with increasing concentrations of each inducer, both singly and in combination.

For 16 different combinations of inducer inputs, we calculated the logic parameters (r, a, l) corresponding to the fully induced and 8 partially induced states (Supplementary Figure S5). As expected, the parameters r and a were highly sensitive to inducer concentrations. The range r of each promoter decreased when either of the inducer concentrations was lowered. Lowering the concentration of only one inducer significantly below its threshold predictably resulted in asymmetric behavior (a ~ 1). Conversely, lowering the concentration of a dominant inducer could make the response more symmetric (a ~ 0).

The logic parameter l was less dependent on inducer concentrations, and varied differentially for the three promoters. Partial induction reduced l for the AND and asym-AND gates. The AND gate A3, with the largest l, had the highest variation in l (l = 0.46 to l = 0.86); while the SLOPE gate D9, with the smallest l, exhibited the least variation (l = 0.48 to l = 0.50). These results show that the SLOPE gate logic parameter l is extremely robust to different input concentrations, while the AND-like gates are more sensitive.


Supplementary Methods Library fragments with λ cI operators Each unit sequence was designed either from a consensus sequence (strong) or a sequence known to be responsive to one of five transcription factors (AraC, λ cI, LacI, TetR, LuxR), with variations in consensus signal strength, transcription factor binding site strength, spacing, and orientation (Table S1). We did not assay the response to λ cI (labeled con1-con4 for each unit, Supplementary Data 1, Supplementary Table S1, and Table 1), although 68% of the sequenced promoters contained at least one λ cI operator.

Library construction and handling The crude randomized assembly ligation mix (Methods) was diluted 20× and combined with the bacterial luciferase reporter plasmid pCS26 (Bjarnason et al. 2003). This vector was cut with XhoI and BamHI, to match the 5’ terminal overhangs on the distal and proximal ends. The vector-insert mixture was again ligated for one week, and transformed by electroporation (2.48kV, 0.2cm gap, 200uF) into Electromax DH10B cells (Invitrogen). A fraction of the recovered transformation mix was plated onto selective plates, grown overnight, and counted. These colony counts provided an estimate of 22,000 independent assembly events. The remaining transformants were directly inoculated into LB containing antibiotics and grown for 8 hours at 37°C. Harvested cells were used to prepare liquid libraries of Midi prep DNA (Qiagen) which were re-transformed into E. coli K12 strain MG1655 (Blattner et al. 1997; Riley et al. 2006) containing the native ara operon, the LacI- and TetR-overexpressing Z1 cassette (Lutz and Bujard, 1997), and the medium-copy plasmid pCD136 which constitutively expresses LuxR). Approximately 10,000 transformants were plated on selective media and picked into 35 384-well plates with a colony-picking robot (Norgren Systems). Each clone of the first 384-well plate was re-streaked on selective media and inoculated from a single colony into 96-well plates. 288 clones

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Transcriptional Regulation and Combinatorial Genetic Logic were selected randomly for commercial sequencing (Laragen Inc., Los Angeles, CA), amplified with primers pZE05 (CCAGCTGGCAATTCCGA) and pZE06 (AATCATCACTTTCGGGAA) using the Accuprime PCR System (Invitrogen), and sequenced from the purified PCR products with primer pZE05. Sequence traces were analyzed by hand for quality (4Peaks by A. Griekspoor and Tom Groothuis, mekentosj.com).

Library measurements Each set of 96 clones was assayed in LB Lennox media made from a single 1200mL batch. Cells were grown in 96-well plates to saturation (16-22 hours at 37°C) and inoculated into 3 replicate plates of each of 16 inducer conditions using a steel 96-pin replicator (V & P Scientific). The library was assayed in these 16 inducer conditions corresponding to all combinations of the four inducible factors: VAI (1μM), IPTG (500μM), L(+)-arabinose (0.1%), and aTc (100ng/mL). Plates were prepared by filling 96-well plates with 150µL of media and inducers on a Genetix QFill2 plate-filler (5% precision), triple-washing the apparatus to prevent inducer-carryover. These concentrations of inducers did not significantly inhibit cell growth in the conditions used (not shown). The 48 plates were grown at 25°C without shaking for 18 hours in the dark. This growth condition minimized evaporation and sample handling time, while providing nearly uniform culture optical densities (not shown). Luciferase activity was assayed by luminescence counts using a Tecan Safire plate reader (default settings, 100ms integration time) after 30s at 30°C. Three reads of each clone were taken to assure temperature equilibration. To insure stringent control, all 16 conditions were read for one replicate before starting the next replicate.

Polymerase box strength prediction For each -10 and -35 box in the library, we calculated the distributions of unregulated promoter activity (Fig. S2AB). We took the median of each distribution to represent the -10 and -35 box ‘strength.’ For each of the 288 promoters, we calculated a predicted promoter activity as the geometric mean of its -35 and -10 box strengths and plotted each against the measured unregulated

Chapter 2: Programming Promoter Logic promoter activity (Fig. S2C). Alternative functions of the two box strengths (arithmetic mean, product, etc.) produced similar results.

Partial induction experiment We measured three RR promoters (A3, D8, and D9) in sixteen inducer conditions. Each clone was grown in selective media to saturation at 37°C, and then diluted 60,000× and inoculated into a 96-well plate. Each well contained 150µL of selective media at 100, 50, 25, or 0 ng/mL aTc and 500, 50, 5, or 0 µM IPTG. We did not explore higher inducer concentrations, to avoid growth effects. This plate was grown at 25°C for 18 hours without shaking. Luminescence was measured as described above. The minimally induced case (5 µM IPTG and 25 ng/mL aTc) often produced outlying behavior, and was discarded from the phenotype-parameter analysis.

93


Supplementary Figures Figure S1. 60 50 # of clones

94

40 30 20 10 0

100

101

102 103 Regulatory range (r)

104

105

Figure S1. The 288 characterized clones exhibit diverse regulatory ranges (r). The characterized promoters exhibited regulation up to r = 105. Approximately half of the library promoters are regulated at least 10×.

95

Figure S2.

60 50 40 30

B

60

-35 boxes

TAGACA TAGACC TAGACT TAGGCA TAGGCT TGGTCA TGGTCT TTGACA TTGACC TTGACT TTTACA TTTACT

Number of promoters

Number of promoters

70

20

101

102 103 104 105 106 Unregulated activity (ALU)

B Number of promoters

60 50 40

-10 boxes

30 20

0


106

C GATAAT GATACT TAGAGT TAGATT TATAAT TATTTT

-10 boxes

30 20 10 0

40

GATAAT GATACT TAGAGT TAGATT TATAAT TATTTT

10

10 0

50

C Predicted promoter activity (ALU)

A


106

Predicted promoter activity (ALU)

06


106

105

104

103 0 10

102

104

106

108

Unregulated activity (ALU)

Figure S2. Many factors contribute to promoter strength. (A) Histograms of unregulated promoter activity for each -35 box reveal large variations in promoter strength. Three strong -35 boxes: TAGACA, TTGACT, and TTGACA (consensus) exhibit higher activities than the other nine. (B) Histograms of unregulated promoter activity for each -10 box reveal highly variable, overlapping distributions for five -10 boxes. The sixth -10 box (TATTTT) requires an activator to achieve high expression. (C) The median strength of each -35 box and -10 box distribution is used to predict the strength of each promoter. For each promoter, the geometric mean of the -10 and -35 box strengths are plotted against the unregulated activity.

106

105

104

103 0 10

102

Unregulated


Figure S3. B

100 80 60 40 20 0

LuxR operators none distal core proximal

100 102 104 106 108 Maximum promoter activity (ALU)

Cumultalive fraction (%)

A Cumultalive fraction (%)

96

100 80 60 40 20 0

AraC operators none distal core proximal

100 102 104 106 108 Maximum promoter activity (ALU)

Figure S3. Activators have small effects at core and proximal. The cumulative histograms of maximal promoter activity for LuxR (A) and AraC (B). The maximal activity of promoters with activator operators at the distal position (where activation is effective) are shown for comparison.


Figure S4. ω

1

100

0.75 asymmetry (a)

102

10−2 0.5 10−4 0.25

0 0

10−6

0.25 0.5 0.75 ← more OR (l) more AND →

1

10−8

Figure S4. Operator interactions determine logic in RR promoters. Parametric plots of the logic parameter l as a function of the asymmetry a and repressor interaction ω. Each point is colored corresponding to ω, from ω = 100 to ω = 0, as shown on the color bar. For each value of ω, we numerically computed the logic l as a function of a for both r = 103 (smaller circles) and r = 105 (larger circles).

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98


Figure S5. A

B 1

1

0.5 0 0 C 1

0.5

D8 D9

0.5

A3

1

0 0 D 1

D8

0.5 0 0

A3

0.5

1

0.5

1

D9

0.5

0.5

1

0 0

Figure S5. RR promoters respond differentially to partial induction. For each promoter, we measured the response in 16 different inducer conditions (Supplementary Methods). The radius of the circles is proportional to the logarithm of the regulatory range r, as in Figure 4B. The minimally induced case (5 µM IPTG and 25 ng/mL aTc) often produced outlying behavior (dashed circles). (A) The logic phenotype space coordinates of 3 RR promoters with respect to fully saturated inducer conditions. (B) The AND gate A3 exhibited differential logic when the inducer concentrations were changed. (C) The asym-AND gate D8 varied in both range r asymmetry a, and to a lesser extent, the logic parameter l. (D) The SLOPE gate D9 varied only in the range r and asymmetry a, while the logic parameter remained approximately constant (l = 0.5).


99

Table S1.The 48 synthetic units used to generate the library. Proximal units Name1 5’left Duplex Sequence2 ara1 Tt cgtggtccatattgcatcagacattgtacccaac Tt cgtgcatagcatttttatccatacgttacccaac ara2 Tt cgtgcaatttttaaaattaaaggcgttacccaac con0 Tt gaatacatctggcggtgataaggcgttacccaac con1 Tt gaatacctctggcggtgataaggcgttacccaac con2 Tt cgtgcaatttttatatcaccgccaggggtacaac con3 Tt cgttatcaccgccaggggtaaggcgttacccaac con4 Tt tgtggaattgtgagcggataacaatttcacacag lac1 Tt agattcaattgtgagcggataacaatttcacaca lac2 Tt gattcaattgtgagcggataacaatttcacacag lac3 Tt cgtgcaatttaaatgtgagcgagtaacaaccaac lac4 Tt cgtgcaatttttaaacctgtaggatcgtacaggt lux1 Tt cttgcgacaaacaataggtaaggcgttacccaac lux2 Tt cctgtaggatcgtacaggtaaggcgttacccaac lux3 Tt ccacccctatcagtgatagagagcgttacccaac tet1 4 Tt aactctatcaatgaTAGAGTgtcaacaaaaaaac tet2

5’right Length Reference3 ggatc 34 * ggatc 34 * ggatc 34 (Crooks et al. 2004) ggatc 34 (Basu et al. 2004) ggatc 34 (Basu et al. 2004) ggatc 34 (Hochschild and Ptashne, 1986) ggatc 34 (Hochschild and Ptashne, 1986) ggatc 34 (Lanzer and Bujard, 1988) ggatc 34 (Lanzer and Bujard, 1988) ggatc 34 (Lutz and Bujard, 1997) ggatc 34 (Becker et al. 2005) ggatc 34 (Egland and Greenberg, 2000) ggatc 34 * ggatc 34 * ggatc 34 (Sizemore et al. 1990) ggatc 34 (Sizemore et al. 1990)

Core units Name1 5’left Duplex Sequence2 C AatcaatgTGGATTttctGATAC ara14 C AtagcggatacttcctgaTATAA ara2 C AtttatgcttccggctcgTATAA con0 C AtaaataccactggcggtGATAC con1 C TattttacctctggcggtGATAA con2 C TtttatcccttgcggtgaTATAA con3 C AtttatcccttgcggtgaTAGAT con4 C AttgtgagcggataacaaGATAC lac1 C TtgtgagcggataacaatGATAC lac2 C TtgtgagcggataacaatTATAA lac3 C TtgtgagcgctcacaattTATAA lac4 C CctgtaggatcgtacaggTATAA lux1 C AcctgtaggatcgtacaggTATAA lux25 C AtccctatcagtgatagaGATAC tet1 C AaataactctatcaatgaTAGAG tet2 tet35

C

ActctatcattgatagagtTATTT

5’right Length Aa 23 Aa 23 Aa 23 Aa 23 Aa 23 Aa 23 Aa 23 Aa 23 Aa 23 Aa 23 Aa 23 Aa 23 Aa 24 Aa 23 Aa 23 Aa

24

Reference3 (Hamilton and Lee, 1988) * (Crooks et al. 2004) (Ptashne, 2004) (Ptashne, 2004) (Michalowski et al. 2004) (Michalowski et al. 2004) (Lutz and Bujard, 1997) (Lanzer and Bujard, 1988) (Lanzer and Bujard, 1988) (Lanzer and Bujard, 1988) * (Egland and Greenberg, 2000) (Lutz and Bujard, 1997) (Sizemore et al. 1990) (Sizemore et al. 1990)

1 The labels “tet”, “lac”, “ara”, and “lux” refer to TetR, LacI, AraC, and LuxR operators, respectively. The units named con1–con4 contain λ cI operators, and the units named con0 contain the consensus sequence with no operators. 2 The -10 and -35 boxes are capitalized. Approximate binding site locations are colored (TetR: blue, LuxR: cyan, LacI: green, AraC: magenta, cI: brown). 5’ overhangs are shown for both the left and right sides of the duplex, cloning sites are highlighted in red. 3 A (*) refers to units designed for this study. 4 This unit contains an internal -10 box, capitalized. 5 This core unit has 1 bp extra space between -10 and -35 boxes.

100


Distal units Name1 5’left Duplex Sequence2 5’right Length Reference3 G ara1 tcgag aacatagcatttttatccataagattagcggatctaaccTTTA 43 (Lutz and Bujard, 1997) G 43 (Zhang et al. 1996) ara2 tcgag tacaacgtcgtgttagctgccttttagcaattttatccaTAGA 6 G 43 (Hamilton and Lee, 1988) ara3 tcgag gtaacaaaagtgtctataatcacggcagaaaagtccacaTTGA G 43 (Crooks et al. 2004) con0 tcgag tacaacgtcgtgttagctgcctttcgtcttcaataattcTTGA G 43 (Lanzer and Bujard, 1988) con1 tcgag cagataaccatctgcggtgataaattatctctggcggtgTTGA G 43 (Ptashne, 2004) con2 tcgag tatcaccgccagaggtaaaatagtcaacacgcacggtgtTAGG G 43 (Ptashne, 2004) con3 tcgag tatcaccgccagaggtaaaatagtcaacacgcacggtgtTAGA G 43 (Hochschild and Ptashne, 1986) con4 tcgag tacaacgtcgtgttagctgtatcaccgccagaggtaagaTTGA G 43 (Lutz and Bujard, 1997) lac1 tcgag tacaacgtcgtgttagctgcaattgtgagcggataacaaTTGA G 43 (Lanzer and Bujard, 1988) lac2 tcgag tacaacgtcgtgttaaattgtgagcggataacaatttagTTGA G 43 (Becker et al. 2005) lac3 tcgag tacaattgtgagcgctcacaatttcgtcttcaataattcTTGA tcgag tacaattgtttaacataagtacctgtaggatcgtacaggTTTA G 43 (Egland and Greenberg, 1999) lux1 G 43 (Shadel and Baldwin, 1992) lux2 tcgag tacaattgtttaacataagtgaatggatcattttgcaggTTTA 6 G 43 * lux3 tcgag acatagcatttttatccataacctgtaggatcgtacaggTTTA G 43 (Lutz and Bujard, 1997) tet1 tcgag tacaacgtcgtgttagctgctccctatcagtgatagagaTTGA tet27 6 7

tcgag tacaacgtCatttcacttTTCTCTatcactgatagggagTGGT

This unit contains a non-functional AraC site. This unit contains an internal -35 box, capitalized.

G

43

(Sizemore et al. 1990)


References Atkinson MR, Savageau MA, Myers JT, Ninfa AJ (2003) Development of genetic circuitry exhibiting toggle switch or oscillatory behavior in Escherichia coli. Cell 113: 597-607. Atsumi S, Little JW (2006) A synthetic phage lambda regulatory circuit. Proc Natl Acad Sci U S A 103: 19045-19050. Basu S, Gerchman Y, Collins CH, Arnold FH, Weiss R (2005) A synthetic multicellular system for programmed pattern formation. Nature 434: 1130-1134. Basu S, Mehreja R, Thiberge S, Chen MT, Weiss R (2004) Spatiotemporal control of gene expression with pulse-generating networks. Proc Natl Acad Sci U S A 101: 6355-6360. Beck CF, Mutzel R, Barbe J, Muller W (1982) A multifunctional gene (tetR) controls Tn10encoded tetracycline resistance. J Bacteriol 150: 633-642. Becker NA, Kahn JD, Maher LJ, 3rd (2005) Bacterial repression loops require enhanced DNA flexibility. Journal of molecular biology 349: 716-730. Bintu L, Buchler NE, Garcia HG, Gerland U, Hwa T, Kondev J, Kuhlman T, Phillips R (2005a) Transcriptional regulation by the numbers: applications. Curr Opin Genet Dev 15: 125-135. Bintu L, Buchler NE, Garcia HG, Gerland U, Hwa T, Kondev J, Phillips R (2005b) Transcriptional regulation by the numbers: models. Curr Opin Genet Dev 15: 116-124. Bjarnason J, Southward CM, Surette MG (2003) Genomic profiling of iron-responsive genes in Salmonella enterica serovar typhimurium by high-throughput screening of a random promoter library. J Bacteriol 185: 4973-4982. Browning DF, Busby SJ (2004) The regulation of bacterial transcription initiation. Nat Rev Microbiol 2: 57-65. Buchler N, Gerland U, Hwa T (2003) On schemes of combinatorial transcription logic. PNAS 100: 5136-5141.

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Transcriptional Regulation and Combinatorial Genetic Logic Busby S, Ebright RH (1994) Promoter structure, promoter recognition, and transcription activation in prokaryotes. Cell 79: 743-746. Chan B, Busby S (1989) Recognition of nucleotide sequences at the Escherichia coli galactose operon P1 promoter by RNA polymerase. Gene 84: 227-236. Collado-Vides J, Magasanik B, Gralla JD (1991) Control site location and transcriptional regulation in Escherichia coli. Microbiol Mol Biol Rev 55: 371-394. Egland KA, Greenberg EP (1999) Quorum sensing in Vibrio fischeri: elements of the luxl promoter. Mol Microbiol 31: 1197-1204. Elledge SJ, Davis RW (1989) Position and density effects on repression by stationary and mobile DNA-binding proteins. Genes & development 3: 185-197. Endy D (2005) Foundations for engineering biology. Nature 438: 449-453. Fuqua WC, Winans SC, Greenberg EP (1994) Quorum sensing in bacteria: the LuxR-LuxI family of cell density-responsive transcriptional regulators. J Bacteriol 176: 269-275. Gralla JD, Collado-Vides J (1996) Organization and Function of Transcription Regulatory Elements. In Escherichia coli and Salmonella : cellular and molecular biology, Neidhardt FC, Curtiss R (eds), 2nd edn, pp 2 v. (xx, 2822 p.). Washington, D.C.: ASM Press. Gross CA, Chan C, Dombroski A, Gruber T, Sharp M, Tupy J, Young B (1998) The functional and regulatory roles of sigma factors in transcription. Cold Spring Harbor symposia on quantitative biology 63: 141-155. Guido NJ, Wang X, Adalsteinsson D, McMillen D, Hasty J, Cantor CR, Elston TC, Collins JJ (2006) A bottom-up approach to gene regulation. Nature 439: 856-860. Hasty J, McMillen D, Collins JJ (2002) Engineered gene circuits. Nature 420: 224-230. Haugen SP, Berkmen MB, Ross W, Gaal T, Ward C, Gourse RL (2006) rRNA promoter regulation by nonoptimal binding of sigma region 1.2: an additional recognition element for RNA polymerase. Cell 125: 1069-1082.

Chapter 2: Programming Promoter Logic Hawley DK, McClure WR (1983) Compilation and analysis of Escherichia coli promoter DNA sequences. Nucleic acids research 11: 2237-2255. Hermsen R, Tans S, Wolde PR (2006) Transcriptional Regulation by Competing Transcription Factor Modules. PLoS Comput Biol 2: e164. Jacob F, Monod J (1961) Genetic regulatory mechanisms in the synthesis of proteins. Journal of molecular biology 3: 318-356. Joung JK, Koepp DM, Hochschild A (1994) Synergistic activation of transcription by bacteriophage lambda cI protein and E. coli cAMP receptor protein. Science 265: 1863-1866. Kammerer W, Deuschle U, Gentz R, Bujard H (1986) Functional dissection of Escherichia coli promoters: information in the transcribed region is involved in late steps of the overall process. The EMBO journal 5: 2995-3000. Kauffman S (1969) Homeostasis and Differentiation in Random Genetic Control Networks. Nature 224: 177-178. Lanzer M, Bujard H (1988) Promoters largely determine the efficiency of repressor action. Proc Natl Acad Sci U S A 85: 8973-8977. Ligr M, Siddharthan R, Cross FR, Siggia ED (2006) Gene expression from random libraries of yeast promoters. Genetics 172: 2113-2122. Lutz R, Bujard H (1997) Independent and tight regulation of transcriptional units in Escherichia coli via the LacR/O, the TetR/O and AraC/I1-I2 regulatory elements. Nucleic acids research 25: 1203-1210. Mangan S, Alon U (2003) Structure and function of the feed-forward loop network motif. Proc Natl Acad Sci U S A 100: 11980-11985. Mayo AE, Setty Y, Shavit S, Zaslaver A, Alon U (2006) Plasticity of the cis-regulatory input function of a gene. PLoS Biol 4: e45. Oehler S, Amouyal M, Kolkhof P, von Wilcken-Bergmann B, Muller-Hill B (1994) Quality and

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Transcriptional Regulation and Combinatorial Genetic Logic position of the three lac operators of E. coli define efficiency of repression. The EMBO journal 13: 3348-3355. Ogden S, Haggerty D, Stoner CM, Kolodrubetz D, Schleif R (1980) The Escherichia coli L-arabinose operon: binding sites of the regulatory proteins and a mechanism of positive and negative regulation. Proc Natl Acad Sci U S A 77: 3346-3350. Ptashne M (2004) A genetic switch : phage lambda revisited, 3rd edn. Cold Spring Harbor, N.Y.: Cold Spring Harbor Laboratory Press. Ptashne M (2005) Regulation of transcription: from lambda to eukaryotes. Trends in biochemical sciences 30: 275-279. Riley M, Abe T, Arnaud MB, Berlyn MK, Blattner FR, Chaudhuri RR, Glasner JD, Horiuchi T, Keseler IM, Kosuge T, Mori H, Perna NT, Plunkett G, 3rd, Rudd KE, Serres MH, Thomas GH, Thomson NR, Wishart D, Wanner BL (2006) Escherichia coli K-12: a cooperatively developed annotation snapshot--2005. Nucleic acids research 34: 1-9. Rosenfeld N, Young JW, Alon U, Swain PS, Elowitz MB (2005) Gene regulation at the single-cell level. Science 307: 1962-1965. Ross W, Gosink KK, Salomon J, Igarashi K, Zou C, Ishihama A, Severinov K, Gourse RL (1993) A third recognition element in bacterial promoters: DNA binding by the alpha subunit of RNA polymerase. Science 262: 1407-1413. Salgado H, Gama-Castro S, Peralta-Gil M, Diaz-Peredo E, Sanchez-Solano F, Santos-Zavaleta A, Martinez-Flores I, Jimenez-Jacinto V, Bonavides-Martinez C, Segura-Salazar J, Martinez-Antonio A, Collado-Vides J (2006) RegulonDB (version 5.0): Escherichia coli K-12 transcriptional regulatory network, operon organization, and growth conditions. Nucleic Acids Res 34: D394-397. Schleif R (2003) AraC protein: a love-hate relationship. Bioessays 25: 274-282. Setty Y, Mayo AE, Surette MG, Alon U (2003) Detailed map of a cis-regulatory input function. Proc Natl Acad Sci U S A 100: 7702-7707. Skerra A (1994) Use of the tetracycline promoter for the tightly regulated production of a murine

Chapter 2: Programming Promoter Logic antibody fragment in Escherichia coli. Gene 151: 131-135. Sprinzak D, Elowitz MB (2005) Reconstruction of genetic circuits. Nature 438: 443-448. Thomas R, D’Ari R (1990) Biological feedback. Boca Raton: CRC Press. Vilar JM, Leibler S (2003) DNA looping and physical constraints on transcription regulation. Journal of molecular biology 331: 981-989. Zubay G, Schwartz D, Beckwith J (1970) Mechanism of activation of catabolite-sensitive genes: a positive control system. Proc Natl Acad Sci U S A 66: 104-110.

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Supplementary References Basu S, Mehreja R, Thiberge S, Chen MT, Weiss R (2004) Spatiotemporal control of gene expression with pulse-generating networks. Proc Natl Acad Sci U S A 101: 6355-6360. Becker NA, Kahn JD, Maher LJ, 3rd (2005) Bacterial repression loops require enhanced DNA flexibility. Journal of molecular biology 349: 716-730. Bjarnason J, Southward CM, Surette MG (2003) Genomic profiling of iron-responsive genes in Salmonella enterica serovar typhimurium by high-throughput screening of a random promoter library. J Bacteriol 185: 4973-4982. Blattner FR, Plunkett G, 3rd, Bloch CA, Perna NT, Burland V, Riley M, Collado-Vides J, Glasner JD, Rode CK, Mayhew GF, Gregor J, Davis NW, Kirkpatrick HA, Goeden MA, Rose DJ, Mau B, Shao Y (1997) The complete genome sequence of Escherichia coli K-12. Science 277: 1453-1474. Crooks GE, Hon G, Chandonia JM, Brenner SE (2004) WebLogo: a sequence logo generator. Genome research 14: 1188-1190. Egland KA, Greenberg EP (1999) Quorum sensing in Vibrio fischeri: elements of the luxl promoter. Mol Microbiol 31: 1197-1204. Egland KA, Greenberg EP (2000) Conversion of the Vibrio fischeri transcriptional activator, LuxR, to a repressor. J Bacteriol 182: 805-811. Hamilton EP, Lee N (1988) Three binding sites for AraC protein are required for autoregulation of araC in Escherichia coli. Proc Natl Acad Sci U S A 85: 1749-1753. Hochschild A, Ptashne M (1986) Cooperative binding of lambda repressors to sites separated by integral turns of the DNA helix. Cell 44: 681-687. Lanzer M, Bujard H (1988) Promoters largely determine the efficiency of repressor action. Proc Natl Acad Sci U S A 85: 8973-8977. Lutz R, Bujard H (1997) Independent and tight regulation of transcriptional units in Escherichia coli via the LacR/O, the TetR/O and AraC/I1-I2 regulatory elements. Nucleic acids research 25:

Chapter 2: Programming Promoter Logic 1203-1210. Michalowski CB, Short MD, Little JW (2004) Sequence tolerance of the phage lambda PRM promoter: implications for evolution of gene regulatory circuitry. J Bacteriol 186: 7988-7999. Ptashne M (2004) A genetic switch : phage lambda revisited, 3rd edn. Cold Spring Harbor, N.Y.: Cold Spring Harbor Laboratory Press. Riley M, Abe T, Arnaud MB, Berlyn MK, Blattner FR, Chaudhuri RR, Glasner JD, Horiuchi T, Keseler IM, Kosuge T, Mori H, Perna NT, Plunkett G, 3rd, Rudd KE, Serres MH, Thomas GH, Thomson NR, Wishart D, Wanner BL (2006) Escherichia coli K-12: a cooperatively developed annotation snapshot--2005. Nucleic acids research 34: 1-9. Shadel GS, Baldwin TO (1992) Identification of a distantly located regulatory element in the luxD gene required for negative autoregulation of the Vibrio fischeri luxR gene. The Journal of biological chemistry 267: 7690-7695. Sizemore C, Wissmann A, Gulland U, Hillen W (1990) Quantitative analysis of Tn10 Tet repressor binding to a complete set of tet operator mutants. Nucleic acids research 18: 2875-2880. Zhang X, Reeder T, Schleif R (1996) Transcription activation parameters at ara pBAD. Journal of molecular biology 258: 14-24.

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A synthetic three-color reporter scaffold for monitoring genetic regulation and 108

Transcriptional Regulation and Combinatorial noise Genetic Logic

A Synthetic Three-Color Reporter Scaffold for Monitoring Genetic Regulation and Noise

Robert Sidney Cox III, Mary J. Dunlop, and Michael B. Elowitz

Abstract Biologists require accurate, distinguishable, non-toxic reporters for multiple genes in the same organism. Despite recent improvements in fluorescent proteins, there does not exist a single vector with which one can conveniently employ multiple reporters. Therefore, we designed and built such a system using total DNA synthesis. This scaffold will be useful for analyzing natural genetic circuits—as well as assembling synthetic circuits—in many organisms. Here we characterize the scaffold in Escherichia coli. Three spectrally distinct reporters allow independent monitoring of genetic signals and analysis of genetic noise. As an application, we show that the scaffold is a sensitive detector of transcriptional co-regulation.

Chapter 3: The Reporter Scaffold

Introduction Cells contain genetic circuits, composed of interacting genes and proteins, which control cellular functions. Although these circuits are traditionally studied on average in large populations, they actually operate in individual living cells. As a result, they are subject to substantial variation, both from stochastic effects in circuit components (intrinsic noise), and from the substantial cell-cell variability that exists in all cellular components (extrinsic noise). A critical problem in understanding such circuits is determining how both types of noise, together with circuit structure, determine the dynamics of gene expression and thereby affect cellular behavior. A complementary question is what fluctuations in specific genes, and the correlations between them, might tell us about circuit connectivity.

Recently the interaction between noise and circuit structure has been approached from two new directions: First, several studies have followed the dynamics of endogenous circuit components in individual cells using one or more fluorescent reporter proteins (Elowitz and Leibler, 2000; Rosenfeld et al. 2005; Suel et al. 2006). These dynamics can be interpreted in terms of circuit structure, cell-cell variability, and noise. Second, researchers have begun constructing simple synthetic genetic circuits composed of well-characterized genes and proteins. These circuits are designed to implement particular functions, such as oscillation or memory (bistability) (Elowitz and Leibler, 2000; Gardner et al. 2000). Like their natural counterparts, these synthetic circuits— and the noise propagating through them (Pedraza and van Oudenaarden, 2005)—can be monitored at the single cell level using fluorescent reporter genes.

Synthetic biology involves the assembly of regulatory circuits from genetic components. Typically, circuit design is based on qualitative models of the individual components, because accurate quantitative descriptions of genetic components and their in vivo interactions are lacking. In many cases, the behavior of designed genetic circuits differs significantly from predictions. In order to

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Transcriptional Regulation and Combinatorial Genetic Logic construct predictable circuits, it is important to isolate gene expression: the expression of one gene should not inadvertently affect the expression of another, except in ways determined by the intended circuit diagram. Decoupling the circuit components, such as by placing them on separate plasmids, can facilitate the ‘debugging’ of synthetic circuit function. For example, to measure the gene-regulation function of a transcription factor (Rosenfeld et al. 2005), the factor was placed on a plasmid and the target promoter in the chromosome. Independent single-cell measurements of multiple reporters will give synthetic biologists a sensitive measure of circuit function.

Experiments with both natural and synthetic circuits suffer from a lack of systematic control over reporter genes. For example, synthetic circuits are often encoded on plasmids whose copy numbers vary significantly in unpredictable ways. Similarly, multiple fluorescent reporters of natural circuits have not generally been optimized for high signal and low crosstalk. Both types of experiments will benefit from a well-characterized platform for expressing reporter genes and synthetic circuit components in a reproducible, non-toxic fashion. Many technology applications, such as metabolic engineering (Farmer and Liao, 2000; Khosla and Keasling, 2003), would benefit from continuous and independent control of multiple operons with quantitative outputs. For these reasons, one would like a general chassis into which one could insert promoters from natural genes or components of synthetic circuits, with optimized fluorescent protein reporters to independently monitor the corresponding genes.

Here we describe such an integrated platform. This system exploits our knowledge of genetic regulation and is an ideal framework for both the measurement of gene expression and the construction of synthetic networks. To create the system we exploited recent developments in total DNA synthesis to design a highly optimized sequence. We show how the scaffold can be used to analyze fluctuations of a transcription factor regulating two target promoters. In this example, we find that the co-regulation of the two promoters can be inferred from the simultaneous analysis of fluctuations of three fluorescent proteins. These results show that noise is not just an unavoidable fact of life in the single cell environment, but can be exploited to infer properties of genetic elements.


Results and Discussion We designed a three-color fluorescent reporter scaffold (Fig. 1) to fulfill several criteria: (1) Biocompatability: The scaffold was genetically stable and non-toxic to cells carrying it (not shown). This was accomplished by keeping the scaffold small (4kb), using a low copy plasmid origin of replication (SC101), moderate strength ribosome binding sites (RBSs), optimizing the fluorescent proteins to remove ‘toxic’ codons, and placing them under the control of tightly regulated promoters (Lutz and Bujard, 1997). To discourage mutation, we explicitly avoided homologous or repeated sequences. (2) Distinctness: We chose fast maturing, monomeric proteins with minimally overlapping spectra to maximize linearity of response (Campbell et al. 2002; Nagai et al. 2002; Rizzo et al. 2004; Shu et al. 2006). We determined the spectral crosstalk in our microscopy set-up to be extremely low (Methods), and correctable. (3) Sensitivity and independence: We wished to detect both strong and weak genetic signals simultaneously, with the ability to watch them change over time in single living cells (Rosenfeld et al. 2005). We used multiple genetic terminator sequences (Brendel et al. 1986; Wilson and von Hippel, 1995) along with empty ‘spacer’ regions to insure that changing the expression level of one protein did not affect the level of another, except when genetically co-regulated (see below). (4) Tunability: The scaffold was designed to allow for easy tuning of reporter parameters: promoter strengths, RBSs, and degradation tags, as well as the construction of fluorescent fusions. (5) Modularity, portability, and extensibility: Restriction sites were strategically placed to allow genetic elements to be easily swapped, inserted, or deleted. The fluorescent proteins were codon-optimized for both grampositive and gram-negative bacteria. The system can be moved between different plasmids (Lutz and Bujard, 1997), chromosomes, and organisms. Additional restriction sites were included to add the option of a fourth reporter operon (Ai et al. 2007).

We characterized the scaffold in single E. coli cells using quantitative fluorescence microscopy (Fig. 2). In our strain, all three fluorescent proteins were repressed. Cells carrying the plasmid

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Transcriptional Regulation and Combinatorial Genetic Logic showed very weak (5%), but detectable, expression of the yfp and cfp genes compared to the mean cellular autofluorescence (Fig. 2A and B). We tested whether the transcriptional units in the scaffold plasmid could be induced independently, by using combinations of saturating inducer concentrations (Methods). We found the mean expression of cfp and rfp were independent, indicating that there was no significant transcriptional read-through from rfp into cfp (Fig. 2F and H). Similarly, the mean expression of cfp and yfp was independent (Fig. 2B through E). These results showed that the design of the scaffold provided sufficient genetic isolation for independent control of the three reporter genes.

Combinatorial promoters that accept multiple genetic inputs are ubiquitous in genomes and useful for creating synthetic circuits. The combinatorial LacI/AraC regulated promoter (Lutz and Bujard, 1997) controlling rfp behaved as an asym-AND (as defined in Chapter 2) gate (Fig. 2B, D, F, and H), with the repressor LacI acting as the dominant transcription factor. Expression was undetectable when induced with Lara alone (Fig. 2F). In the absence of Lara, IPTG induced expression only slightly above the autofluorescence level (Fig. 2D-E). In the presence of Lara, IPTG induced expression up to 40× the autofluorescent background level (Fig. 2H-I). These results show that the LacI/AraC promoter controls expression combinatorially, with three distinct output expression levels.

Fluctuations in plasmid copy number, overall transcriptional or translational activity, or growth rate, would be expected to enhance or reduce expression of all genes simultaneously. For each color—cfp, yfp, and rfp—the total genetic noise was affected only by the appropriate inducers (Fig. 4). Under conditions in which all fluorescent proteins were induced (Fig. 2I), we calculated correlation coefficients for each pair of fluorescent reporters (Table I). In all cases, the linear (Pearson) correlation coefficient agreed well with the rank (Spearman) correlation. We also calculated the partial correlation coefficients (Methods), which indicated the degree of extra correlation between two variables relative to the third. We found that the correlation of genetic

Chapter 3: The Reporter Scaffold noise between rfp and yfp was consistently higher than the correlation of either rfp or yfp with cfp. This increased correlation was expected, due to their co-regulation by LacI. These results show— using multiple correlation metrics—that noise in gene expression can reveal transcriptional coregulation.

We confirmed this method of detecting co-regulation with three additional experiments (Table I). First, we measured the same system in a strain background (MG1655) containing approximately 100× lower endogenous levels of the repressor LacI (~30 copies/cell as opposed to ~3,000). In this strain, induction was not necessary to observe fluorescence significantly above background (not shown). The level of correlation between rfp and yfp was larger than the previous case (ρ = 0.94), as expected, due to the increased noise in LacI concentration at low copy number. Second, we measured the correlation between yfp and rfp in a strain containing a deletion of the lac operon (∆lacI). Third, we switched the LacI/AraC controlled rfp promoter with a constitutive one containing no lac operators (∆lacO). In both of these cases, the extra correlation between yfp and rfp disappeared when the regulatory connections were broken (Table I). These results show that the increased noise correlation of yfp and rfp was due to their transcriptional co-regulation by LacI, and that this co-regulation is observable even in the absence of the corresponding inducer IPTG.

These correlation results are consistent with a model of co-regulation by the noisy (Elowitz et al. 2002; Swain et al. 2002) transcription factor LacI. Since LacI regulates yfp and rfp simultaneously, the correlation should be symmetric in time; that is, the cross-correlation function should be symmetric with its maximum near zero. To test this prediction, we analyzed the three-color fluctuations in a growing microcolony using time-lapse microscopy (Figure 3). We used the scaffold in the wild type MG1655 strain (containing no TetR, and low LacI), and grew microcolonies with arabinose as the carbon source to ensure AraC induction. When averaged over the cells present in the microcolony (Fig. 3A), the time-series revealed strong correlation

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Transcriptional Regulation and Combinatorial Genetic Logic between yfp and rfp, consistent with the measurements of Table I (Fig. 3B). The cross correlation function (Fig. 3C) between yfp and rfp showed that the peak correlation occurs near zero lag, indicating that the co-regulation is mediated instantaneously by a separate element: LacI. These results show that the cross correlation function can reveal details into transcriptional regulation, such as whether two genes interact directly or are themselves regulated by an unobserved (and possibly unknown) factor.

By varying the induction of the reporter genes, we found that correlations in fluctuation were sensitive to shared regulatory inputs, suggesting that measurements of fluctuations might provide insight into regulatory structure of natural genetic circuits. We also found that this correlation could be detected even without inducing the transcription factor LacI, when the basal expression level was high enough to observe. Because the system is present on a plasmid of ~12 copies/cell, noise in expression of reporter genes is relatively small, allowing upstream fluctuations (Pedraza and van Oudenaarden, 2005) to be inferred. In particular, fluctuations in wild type (MG1655) LacI are large enough to cause correlated variation in two different LacI-regulated promoters. The presence of the third color acts as a control to compensate for extrinsic global and plasmid level fluctuations. Time-lapse microscopy adds to this analysis the relative delays in transcriptional regulation.

Given two uncharacterized promoters, one could test for the possibility of co-regulation by comparing their mutual correlation to that of a third, constitutively regulated promoter. This method could be used to confirm regulation by a global transcription factor with many putative binding sites, such as CRP (Brown and Callan, 2004). Alternatively, a pairwise comparison of all active promoters in E. coli (Zaslaver et al. 2006) could reveal co-regulation by as-yet uncharacterized transcription factors: about 150 transcription factors—nearly half—remain to be characterized in E. coli (Riley, 1993). Fluctuations and the correlations therein could even be used to identify unknown transcription factors or, when coupled with our prior knowledge of the natural

Chapter 3: The Reporter Scaffold distributions of regulatory network motifs (Shen-Orr et al. 2002), to infer regulatory structures of unknown networks. We note that correlation in the promoter activities does not imply transcriptional co-regulation. Rather, this method could be coupled with time-lapse analysis of the correlation lags, along with traditional biochemical and genetic characterization, to quickly identify cases worthy of detailed study.

The synthetic biologist can use our system to aid in genetic circuit design and tuning. Multiple outputs monitor the state components of the system, and tell us when expression levels are not what we expect. A noise source (such as LacI) can be used as an input of a synthetic regulatory network, and the propagation of noise (Pedraza and van Oudenaarden, 2005) can be monitored to confirm the intended network structure.

It is now possible to design extremely complex genetic sequences with well-controlled behavior, by exploiting total DNA synthesis. This quantitative reporter system permits unprecedented quantitative analysis of natural and synthetic gene networks. Simultaneously, this system will test and expand our DNA sequence-level knowledge of the regulation of gene expression.

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Materials and Methods Reagents All inducers and chemicals were purchased from Sigma. Concentrations (unless otherwise stated) were 50 µg/mL kanamycin, 100 µg/mL ampicillin, 500 µM isopropyl β-D-1-thiogalactopyranoside (IPTG), 100 ng/mL anhydrotetracycline (aTc), 0.1% L(+)-arabinose (Lara), 1µM oxo-C6homoserine lactone (VAI). LB growth media (Lennox) was used for culture growth. All enzymes for plasmid construction were obtained from New England Biolabs.

Synthetic DNA design The 3,518 bp scaffold was constructed by total synthesis by DNA2.0 (Menlo Park, CA). The sequence was cloned into the plasmid vector pDrive, and confirmed by automated sequencing. The full sequence of the scaffold in plasmid pFS2-123 is supplied in the Supplementary information, with features of the scaffold described here and bp coordinates listed in brackets. Restriction sites NotI [3], BbsI [235], BglII [1006], SalI [1088], AscI [1197], XhoI [1310], BamHI [1401], BsmBI [2165], PacI [2373], BsrGI [2590], AvrII [3348], XmaI [3462], and NheI [3511] allow for insertion and swapping of genetic elements between the promoters, open reading frames (ORFs), and terminators of the construct. The three fluorescent protein ORFs were codon optimized for expression in both gram-negative E. coli and gram-positive B. subtilis. These sequences were optimized by sampling each codon independently, in proportion to the average of the codon-usage tables for these two organisms (Nakamura et al. 2000). To explicitly avoid codons known to be toxic (Zahn, 1996), we used modified versions of the referenced codonusage tables, with the rarest (less than 10% usage) codons removed. After performing the codon optimization of each ORF the restriction sites from the above list were removed, by choosing the mutation which introduced the most common codon. For the cfp sequence [260-976], we used the amino acid sequence of the Cerulean cfp variant (Rizzo et al. 2004) for this backtranslation

Chapter 3: The Reporter Scaffold and optimization. For the yfp sequence [1434-2150], we used the amino acid sequence of the Venus yfp variant (Nagai et al. 2002), and incorporated the mutations of the Citrine yfp variant (Griesbeck et al. 2001). For the rfp sequence [2584-3294], we used the amino acid sequence of the Cherry rfp variant (Shu et al. 2006). Double stop codons (TAATAA) were used at the end of all three ORFs to ensure efficient termination of translation. We used promoters PLtetO-1 [10131086] to control cfp, PLlacO-1 [1318-1397] to control yfp, and Plac/ara-1 [3353-3455] to control rfp (Lutz and Bujard, 1997). To control translation, we used the moderate strength SD8 RBSs (Ringquist et al. 1992) for cfp [977-996] and yfp [1414-1433], and the stronger RBS from gene 10 of phage T7 (Olins et al. 1988) for rfp [3296-3336]. Terminators RNAI [19-64] and TSAL [65-238] (Reynolds et al. 1992) terminated the transcriptional unit containing cfp. Terminators TR2-17 [2166-2288] (Wilson and von Hippel, 1995), TL17 [2289-2365] (Wright et al. 1992), BS7 [2378-2430] (Reynolds et al. 1992), and T7TE+ [2451-2577] (Uptain and Chamberlin, 1997) terminated the transcriptional units containing yfp and rfp.

Plasmids The initial synthetic construct was subcloned into the modular pZ* expression vector system (Lutz and Bujard, 1997) using the NotI and NheI restriction sites on each end of the scaffold construct. This plasmid system allows easy swapping of the origin of replication (SC101, ColE1, or p15A) and antibiotic resistance markers. We designated plasmids containing the scaffold as pF*, and adopted an extended version of the pZ* naming system. Data for Figs. 2-3 is from measurement of plasmid pFS2-123, containing: a kanamycin resistance marker; the SC101 origin of replication, and the promoters described above. To measure the correlation between rfp and yfp with the LacI regulation of rfp removed (Table I, ∆lacO), we placed the rfp gene under the control of the P(R) promoter from phage λ (Ptashne, 2004). This promoter sequence was synthesized and cloned in between the restriction sites XmaI and AvrII to create plasmid pFS2-12R.

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Strains We used wild-type E. coli MG1655 (Blattner et al. 1997) for the time-lapse experiment (Figure 3), and to measure the correlation between rfp and yfp from plasmid pFS2-123 in the presence of low levels of LacI (Table I, MG1655). This strain does not contain the TetR repressor, so cfp is expressed constitutively. The MG1655Z1 strain was constructed from the wild type MG1655 strain and the TetR and LacI over-expressing DH5aZ1 (Lutz and Bujard, 1997) strain by P1 general transduction (Miller, 1972). We used MG1655Z1, which over-expresses LacI from the lacIq cassette, for the characterization of the scaffold response to induction in the presence of the (Fig. 2). We also measured the correlation between rfp and yfp in strain MC4100, which does not contain the LacI gene (Table I, ∆lacI) .

Microscopy Single-cell measurements were acquired on an Olympus IX-81 inverted fluorescence microscope at 100× magnification, with a Hammamatsu Orca ER CCD camera (2x2 binning) using custom microscope acquisition software. Phase-contrast images were acquired to measure cell morphology, position, and image quality. Fluorescent exictation was performed with a Lambda LS Xenon lamp (Sutter Instruments, Inc.) with a liquid lightguide and fluoresent filter cubes (Chroma, Inc.) for Cyan/cfp (Chroma, #31044v2), Yellow/yfp (Chroma, #41028), and Crimson/rfp (Chroma, #41027). To prevent bleaching, all images were collected as ordered exposures of (rfp, yfp, cfp), with minimal light exposure. We verified the fluorescent field provided by the Lamda LS light source and liquid light guide with fluorescent slides (Spherotech, Inc.). The field was found to be extremely flat (std/mean ~ %3) when centered in all three colors.

In order to check and correct for spectral crosstalk between fluorescent proteins, we constructed plasmids each containing each individual fluorescent protein. We measured cells expressing only one of the fluorophores cfp, yfp, and rfp in all three filter cubes (Table II). Crosstalk was very small in all cases. The highest magnitude was rfp fluorescence in the Yellow/yfp channel, which amounted

Chapter 3: The Reporter Scaffold to 0.1% of the detection level in the rfp channel. The crosstalk of cfp into the Crimson/rfp cube was undetectable on our system. All reported data are corrected for this crosstalk (using the inverse matrix of Table II). Errors in crosstalk measurement could conceivably introduce false correlations into Table I. To control for this possibility, we repeated all data analysis without the crosstalk correction and found no change in any of the results of Table I. These results confirm good spectral separation.

Induction experiment MG1655Z1 cells containing the plasmid pFS2-123 were grown to saturation overnight in LB at 37°C and diluted 100× into non-fluorescent M9 minimal glycerol media containing combinations of the three inducers. Cells were grown for 3 hours at 32°C to an OD600 of ~0.2. For cells induced with aTc, an additional 50ng/mL of aTc was then added to insure complete induction. Cells were allowed to grow to a final OD600 of ~0.3, placed on ice, and measured on 1.5% low melting temperature agarose phosphate-buffered saline slabs in the microscope. For each condition, we acquired approximately 20 fields of cells. These measurements contained 500-1000 cells per condition measured.

Time-lapse experiment MG1655 cells containing the plasmid pFS2-123 were grown to saturation overnight in LB at 37°C and diluted 1000× into non-fluorescent M9 arabinose media. Cells were grown for 3 hours at 32°C, then diluted 100× and transferred to M9 arabinose media pads made with 1.5% low melting point agarose. These pads were placed inside a glass Wilco dish chamber and sealed. Time-lapse images were acquired as described below, at 10 minute intervals in a 32°C temperaturecontrolled chamber.

Image processing We used custom software and the Matlab (The Mathworks, Inc.) Image Processing Toolbox to

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Transcriptional Regulation and Combinatorial Genetic Logic segment the phase contrast images and collect corresponding pixels from each of the three fluorescent images. The program identified individual cells on phase contrast images by progressive watershed thresholds. Shapes were filtered based on morphological properties to eliminate noncell objects, clumps of cells, and misshapen cells. For each cell, a background value of the minimum pixel contained in the bounding box was recorded for each color. Collected fields of cells were examined by eye to check for errors in segmentation and acquisition. For the time-lapse experiment, we used custom software to identify cell division events, and track lineages of cells (lines of daughter and parent cells) during microcolony growth (Rosenfeld et al. 2006).

Data analysis We extracted the data from the segmentation program, subtracted background value for each cell, and normalized each color with respect to the camera’s exposure time for that image. After extracting the data structure from the segmentation, we collected the autofluorescence measurements as a daily control. The autofluorescent values were normally distributed (not shown). We then corrected for the spectral crosstalk measured above by multiplying the 3-color data from each strain by the inverse of the spectral crosstalk matrix (Table II). We also tested many corrections for sources of systematic or experimental error. Parabolic fluorescent field correction did not change the qualitative relationships or reduce variation. The overall fluorescence variation between fields of cells remained small: Each frame analyzed was within one standard deviation of the mean over all frames of the same color. Normalization to account for morphological factors such as size and shape did not qualitatively change our results or decrease the observed variation. As a final correction, we removed outlying cells and non-cell objects from the processed data that were more than three standard deviations from the median of the (typically 500-1000) cells. Previous noise measurements have used similar corrections (Elowitz et al. 2002; Pedraza and van Oudenaarden, 2005)


Correlation analysis For each processed data set, we calculated the normalized Pearson and Spearman correlation coefficient between each pair of colors (Table I). Using these three pairwise correlations, we calculated the three partial correlation coefficients: ρ xy|z =

ρ xy − ρ xz * ρ yz 1− ρ xz

2

1− ρ yz

2

To calculate the errors in correlation and partial correlation coefficients, we uniformly re-sampled 1,000 data sets (bootstrap € sampling with replacement) of the same size and recomputed the correlation coefficients for each sample. The errors reported in Table I and Fig. 2B are determined by the 90% confidence intervals of this bootstrap procedure (i.e., by taking the 100th and 900th values of the sorted list of resampled correlation coefficients).

For the time-lapse movie, we calculated the Pearson correlation coefficient for each pair of colors over the cells present in the entire microcolony at each time point (Fig. 3B). Since the number of cells increases with time, the error bars on each correlation coefficient become smaller with time. We were able to resolve the correlation coefficients after about 7 hours of growth, corresponding to ~100 cells per microcolony. Using the same movie, we calculated the cross-correlation function between each cell lineage for all three pairs of colors. The cross correlation function measures the degree of correlation between two signals, as a function of the delay between them. As such, the cross correlation function reaches a maximum at the time-delay for which the correlation in signals is highest (Fig. 3C). The details of calculating cross correlation analysis over a branching tree will be described in an upcoming publication by Mary J. Dunlop et al. The result presented here—that the cross correlations peak near zero delay—does not depend on the particular method used to calculate the cross-correlation.

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Figure 1. A T T

P1

P2

cfp

T TT

yfp

P3

rfp

P4

kan

B TetR

LacI

AraC

SC101 plasmid Escherichia coli MG1655Z1 Figure 1. The framework design. Figure 1. The framework design. (A) Terminators are hatched boxes. RBSs are purple circles. Restriction sites are blue bars. The promoters are small black arrows. Each fluorescent operon is shown as a colored block arrow, while the (kanamycin) antibiotic resistance is shown as a black block arrow. (B) The framework is measured in the low-copy plasmid in wild type E. coli strain containing the native ara operon, and a LacI and TetR over-expressing cassette. The three reporters are controlled by promoters responsive to: tetracycline/aTc (cfp), lactose/IPTG (yfp), and both lactose/IPTG and arabinose/Lara (rfp).

T


Florescence Intensity (Arbitray Units)

Figure 2. 50 40 30

A

B

C

D

E

F

G

H

I

+ -

+ + -

+

+ +

+ +

+ + +

20 10

MG1655Z1 background

Colors Induced:

aTc:

1

IPTG: Lara:

-

+ -

Figure 2. Operons provide independent control of gene expression. Figure 2. Operons provide independent control of gene expression. Fluorescence microscopy snapshots were taken of 500-1000 cells under each combination of saturating inducer concentrations. This plot shows the response of each reporter to different combinations of these three inducers (each column is one condition, the color expected is shown as a bar below). Each cell within the population is represented by three dots—one of each color—in order to show the genetic noise in each condition. Note that for the LacI/AraC regulated promoter (rfp) the expression is only slightly increased by induction of LacI only, and not at all (0%) by induction of AraC alone.

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Figure 3. A

B

C Cross correlation (R)

Correlation (R)

1.0 0.8 0.6 0.4 Ryfp,rfp) Rcfp,rfp) Rcfp,yfp)

0.2 7

8 9 time (hours)

10

0.8 0.6 0.4 0.2 0 0.2 0.4 0.6 0.8

xcorr(yfp,rfp) xcorr(yfp,cfp) xcorr(cfp,rfp) -400 -200 0 200 400 Correlation Lag (minutes)

Figure 3. The cross-corelation function reveals regulatory connections. Figure 3. The cross-corelation function reveals regulatory connections. We monitored the levels of cfp, yfp, and rfp expression from the plasmid shown in Fig. 1B during growth in a microcolony of E. coli MG1655. This strain did not contain the TetR, leaving cfp constitutively active. We grew the microcolonies on agarose pads, using arabinose as a carbon source to ensure AraC induction. (A) Time-lapse images of 3-color expression, where the pseudo-colors indicate the expression levels of cfp (blue), yfp (green), and rfp (red), respectively. Cells appearing yellow reveal the correlation between yfp and rfp due to LacI co-regulation. (B) The average correlation between yfp and rfp persists over several hours of microcolony growth. (C) The cross correlation between yfp and rfp reveals that the co-regulation by LacI has zero-lag, i.e., it is instantaneous.


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Figure S1. 4. 0.3

noise SM

0.2

0.1

A

B

C

D

E

F

G

H

I

0 Figure 4. Total genetic noise is controlled by induction. Figure 4. Total genetic noise is controlled by induction. The total genetic noise, calculated as the standard error divided by the mean, is plotted for each of the conditions in Fig. 2. Here cyan corresponds to noise in cfp, yellow to noise in yfp, and red to noise in rfp. In each case, the noise is maximal in the fully induced state. Notably, the noise of each color is only affected by the inducer(s) which control it: aTc for cfp, IPTG for yfp, and both IPTG and Lara for rfp.

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Table I. Multi-color noise correlations reveal co-regulation.

Table I. Multi-color noise correlations reveal co-regulation.

ρ(cfp,yfp) ρ(cfp,rfp) ρ(yfp,rfp) lacIq ρ(yfp,rfp) MG1655 ρ(yfp,rfp) ∆lacI ρ(yfp,rfp) ∆lacO

CORRELATION

PARTIAL CORRELATION

RANK CORRELATION

PARTIAL RANK CORRELATION

0.43 ± 0.06 0.37 ± 0.07

0.23 ± 0.10 -0.07 ± 0.11

0.40 ± 0.06 0.36 ± 0.06

0.19 ± 0.07 -0.04 ± 0.08

0.85 ± 0.02

0.83 ± 0.02

0.85 ± 0.01

0.71 ± 0.03

0.94 ± 0.01

0.93 ± 0.01

0.94 ± 0.01

0.93 ± 0.01

0.48 ± 0.13

0.02 ± 0.18

0.51 ± 0.14

0.16 ± 0.18

0.38 ± 0.12

-0.14 ± 0.09

0.19 ± 0.07

-0.14 ± 0.07

Table II. Three fluorescent reporters exhibit spectral separation1. Cube \ gene Cyan Yellow Crimson

cfp 1.0 × 100 5.0 × 10-4 0.0 × 100

yfp 1.5 × 10-4 1.0 × 100 1.3 × 10-5

rfp 1.0 × 10-4 1.1 × 10-3 1.0 × 100

1 The crosstalk is calculated as the ratio of the intensity in the given channel divided by the intensity in the primary channel (e.g the crosstalk of yfp into the Yellow cube is 1).


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Chapter 3: The Reporter Scaffold Ringquist S, Shinedling S, Barrick D, Green L, Binkley J, Stormo GD, Gold L (1992) Translation initiation in Escherichia coli: sequences within the ribosome-binding site. Molecular microbiology 6: 1219-1229. Rizzo MA, Springer GH, Granada B, Piston DW (2004) An improved cyan fluorescent protein variant useful for FRET. Nature biotechnology 22: 445-449. Rosenfeld N, Perkins TJ, Alon U, Elowitz MB, Swain PS (2006) A fluctuation method to quantify in vivo fluorescence data. Biophys J 91: 759-766. Rosenfeld N, Young JW, Alon U, Swain PS, Elowitz MB (2005) Gene regulation at the single-cell level. Science 307: 1962-1965. Shen-Orr SS, Milo R, Mangan S, Alon U (2002) Network motifs in the transcriptional regulation network of Escherichia coli. Nature genetics 31: 64-68. Shu X, Shaner NC, Yarbrough CA, Tsien RY, Remington SJ (2006) Novel chromophores and buried charges control color in mFruits. Biochemistry 45: 9639-9647. Suel GM, Garcia-Ojalvo J, Liberman LM, Elowitz MB (2006) An excitable gene regulatory circuit induces transient cellular differentiation. Nature 440: 545-550. Swain PS, Elowitz MB, Siggia ED (2002) Intrinsic and extrinsic contributions to stochasticity in gene expression. Proceedings of the National Academy of Sciences of the United States of America 99: 12795-12800. Uptain SM, Chamberlin MJ (1997) Escherichia coli RNA polymerase terminates transcription efficiently at rho-independent terminators on single-stranded DNA templates. Proceedings of the National Academy of Sciences of the United States of America 94: 13548-13553. Wilson KS, von Hippel PH (1995) Transcription termination at intrinsic terminators: the role of the RNA hairpin. Proceedings of the National Academy of Sciences of the United States of America 92: 8793-8797. Wright JJ, Kumar A, Hayward RS (1992) Hypersymmetry in a transcriptional terminator of Escherichia coli confers increased efficiency as well as bidirectionality. The EMBO journal 11: 1957-1964.

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Transcriptional Regulation and Combinatorial Genetic Logic Zahn K (1996) Overexpression of an mRNA dependent on rare codons inhibits protein synthesis and cell growth. Journal of bacteriology 178: 2926-2933. Zaslaver A, Bren A, Ronen M, Itzkovitz S, Kikoin I, Shavit S, Liebermeister W, Surette MG, Alon U (2006) A comprehensive library of fluorescent transcriptional reporters for Escherichia coli. Nature methods 3: 623-628.

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Contribution for Chapter 4 As second author of this paper1, Cox directly participated in all theoretical and experimental aspects of the project. The construction of the synthetic circuit was performed by the first author You, while Cox assisted with the initial characterization of individual circuit components: the LuxI quorumsignal synthesis gene, the stability of AHL at various pH levels and growth media, several killer gene variants, and the promoter controlling the individual quorum sensing genes. Cox and You contributed equally to the mathematical modeling, including the analytical solutions describing the damped oscillations precededing the rise to steady level cell densities at low pH. You collected most of the primary data presented in the figures, including the LacZ gene expression assays; Cox optimized the growth curve assays and measurements of cell density. Cox further characterized the circuit response to endogenous signal, measured long-term circuit function to establish reliable limits on its function, and assessed the single-cell variability of cell death.

1 You L, Cox RS, 3rd, Weiss R, Arnold FH (2004) Programmed population control by cell-cell communication and regulated killing. Nature 428: 868-871.

132


Programmed Population Control by Cell-Cell Communication and Regulated Killing

Lingchong You, Robert Sidney Cox III, Ron Weiss, and Frances H. Arnold

Major challenges confront the de novo engineering of gene circuits inside cells (Atkinson et al. 2003; Becskei and Serrano, 2000; Chen et al. 1993; Elowitz and Leibler, 2000; Farmer and Liao, 2000; Gardner et al. 2000; Isaacs et al. 2003; Weiss et al. 1999; Yokobayashi et al. 2002), where efforts to realize predictable and robust performance must deal with noise in gene expression and cell-to-cell variation in phenotype (Blake et al. 2003; Elowitz et al. 2002; Ozbudak et al. 2002). Here we demonstrate that coupling gene expression with cell survival and death using cell-cell communication enables us to program the dynamics of a population despite variability in the behavior of individual cells. Specifically, we have built and characterized a “population control” circuit that autonomously regulates the density of an E. coli population. The cell density is broadcasted and detected by elements from a bacterial quorum sensing system (Fuqua et al. 1994; Miller and Bassler, 2001), which in turn regulate the death rate. As predicted by a simple mathematical model, the circuit can set a stable steady state in terms of both cell density and gene expression, which is easily tunable by varying the stability of the cell-cell communication signal. Incorporating a mechanism for programmed death in response to changes in the environment, this minimal synthetic construct allows us to probe the design principles of its more complex natural counterparts.

Chapter 4: Programmed population control by cell-cell communication and regulated killing The circuit (Fig. 1A) programs a bacterial population to maintain a cell density that is lower than the limits imposed by the environment (e.g., nutrient supply). The LuxI protein of the wellcharacterized LuxI/LuxR system from the marine bacterium Vibrio fischeri (Fuqua et al. 1994; Miller and Bassler, 2001) synthesizes a small, diffusible acyl-homoserine lactone (AHL) signaling molecule. The AHL accumulates in the medium and inside the cells as the cell density increases. At sufficiently high concentrations, it binds and activates the LuxR transcriptional regulator, which in turn induces expression of a killer gene (E) under the control of a luxI promoter (pluxI) (Egland and Greenberg, 1999). Sufficiently high levels of the killer protein cause cell death. We implemented the circuit using a two-plasmid system (Fig. 1B), where pLuxRI2 expresses LuxI and LuxR upon induction by isopropyl-beta-D-thiogalactopyranoside (IPTG), and pluxCcdB3 responds to activated LuxR (at high enough cell density) and causes cell death. The lacZα-ccdB killer gene codes for a fusion protein of LacZα and CcdB. The LacZα portion of the fusion protein retains the ability to complement LacZ∆M15 in appropriate cell strains (e.g., Top10F’ cells), allowing the measurement of fusion protein levels by LacZ assay (Methods). The CcdB portion retains the toxicity of native CcdB, which kills susceptible cells by poisoning the DNA gyrase complex (Engelberg-Kulka and Glaser, 1999).

A simple mathematical model predicted that the system would reach a stable cell density for all realistic parameter values (Methods), although it might go through damped oscillations while approaching the steady state. Experiments confirmed our predictions. Fig. 2A shows the growth of Top10F’ cells containing the population control circuit at pH 7.0. As anticipated, the uninduced culture (circuit OFF) grew exponentially and reached stationary phase upon nutrient exhaustion. The induced culture (circuit ON) grew almost identically to the OFF culture until its density reached a threshold (at 7 hr). It then deviated sharply from the OFF culture and briefly went through a damped oscillation (between 7 hr and 24 hr) of at least one cycle before reaching a steady-state density ~ 10 times lower than that of the OFF culture. The measured peak density (at 10 hr) was two-fold higher than the measured floor (12.5 hr), a difference significantly greater

133

134

Transcriptional Regulation and Combinatorial Genetic Logic than measurement variations. The steady state was maintained for more than 30 hours: the variation in cell density between 28 hr and 62 hr was < 5%, which was smaller than typical measurement variations of individual data points. The transient dynamics of circuit-ON growth was captured well in simulation, where the AHL degradation rate constant (d A) was adjusted for the simulation to match the experiment in the steady-state circuit-ON cell density. Intracellular levels of LacZα-CcdB for the ON culture, measured in terms of LacZ activity, reached a steady state after an overshoot (Fig. 2B), again predicted by simulation. The basal level of LacZα-CcdB expression in the OFF culture was negligible for all time points.

The growth curves and the LacZα-CcdB time courses illustrate the tight yet dynamic coupling between population dynamics and intracellular expression of the LacZα-CcdB killer protein. A lower than steady-state level of the killer protein allows the population to grow; conversely, its excessive production decreases cell density. After some delay, the decline in cell density leads to a decrease in the AHL concentration, which in turn leads to reduced levels of the killer protein, allowing the population to recover. Continuous production and degradation (or death) of each circuit component are essential for the observed homeostasis, and they are closely coupled. Any perturbation that decouples or overrides these processes will disrupt circuit function. For example, the circuit without luxI (thus lacking a communication link) could not control growth (not shown). Also, we observed that 200 nM exogenous AHL, which was not toxic to cells without the circuit or with the circuit OFF, completely prevented growth with the circuit ON (not shown). This is expected, because a high level of AHL would activate LuxR and lead to overproduction of the killer protein. This observation also verifies that the killer protein production rate was limited by AHL synthesis in circuit-ON growth, a key assumption in our mathematical model.

Circuit function could also be delicately manipulated in a predictable fashion. Our model predicted that the steady-state cell density would increase nearly proportionally with the AHL

Chapter 4: Programmed population control by cell-cell communication and regulated killing degradation rate constant (Methods). Thus, AHL serves as an external “dial” to operate the circuit: AHL degradation affects cell-cell communication, and rapid AHL breakdown can disrupt it completely. Degradation of AHLs is facilitated by hydrolytic enzymes (Dong et al. 2001; Leadbetter and Greenberg, 2000) or by increasing the medium pH (Schaefer et al. 2000). Confirming the model prediction, a moderate increase in the medium pH (6.2 to 7.8) significantly increased (~ 4-fold) steady-state cell densities of the ON cultures, but caused only minor changes in those of the OFF cultures (Fig. 3A–E, Table 1). For each pH value, circuit-ON populations reached a steady state after 28 hours, and the variation of cell density afterwards was smaller than typical measurement variations. Similar to the pH 7.0 case, the ON cultures grew almost identically to the OFF cultures at low cell density, but deviated from the latter at high density. Again, simulations captured the experimental behavior (Fig. 3A–D), with adjustment only of the AHL degradation rate constant (Table 1).

Our model predicted that, unlike cell density, intracellular levels of the killer protein would remain roughly constant as pH varied. At steady state, Es = k/d (1-Ns/Nm) ≈ k/d, the ratio of the growth and killing rate constants (assuming that the circuit-ON cell density is far below the carrying capacity, i.e., Ns/Nm k. Thus, the second steady state is stable for all biologically feasible parameters.

The analytical solution of the non-trivial steady state for the full model (Eqs. A1-A3) can also be N md AdE k solved, in particular, N s = . This equation was used to deduce d A (Table 1). N mvAkE d + d AdE k In simulations (carried out using Dynetica (You et al. 2003)), the following parameters were kept at their base values: d=4×10-3 nM-1hr-1, kE =5 hr-1, dE = 2 hr-1, vA = 4.8×10-7 nM ml hr-1. The others (k, Nm, d A) were computed from our experimental data (Table 1).

141

142


Figure 1. A population control circuit programs population dynamics by broadcasting,

Figure 1. A

B

Cam(r) T0

AHL

plac/ara-1

pLuxRI2

ColE1 T1

R

R*

luxR

E

luxI

T0

pluxI

plux CcdB3

E p15A

lacZA-ccdB

pluxI

luxI

Kan(r)

I

luxR

T1

Figure 1. A population control circuit programs population dynamics by broadcasting, sensing, and regulating the cell density using cell-cell communication and negative feedback. (a) Schematic diagram of the circuit. E is a “killer” gene. I, R, and R* represent LuxI, LuxR, and active LuxR, respectively. Filled circles represent AHL. (b) Experimental implementation with two plasmids, pLuxRI2 and pLuxCcdB3. LuxI and LuxR are under the control of a synthetic promoter plac/ara-132, and the killer gene (lacZα-ccdB) is under the control of pluxI15. T0 and T1 are transcription terminators. See text for details.

Chapter 4: Programmed population control by cell-cell communication and regulated killing Figure 2. Experimentally measured (a) growth curves and (b) corresponding levels of

Figure 2.

CFU/ml

10

8

10

A

LacZ activity

9

7

10

5

6

10

4

10

0

B

10

20

40

hours

60

0

20

40

60

hours

Figure 2. Experimentally measured (a) growth curves and (b) corresponding levels of LacZα-CcdB of Top10F’ cells with the population control circuit OFF (filled squares) and ON (open squares), for pH 7.0. Model predictions are shown in solid (ON) and dotted (OFF) lines, except for the OFF case of LacZ activity, where the killer protein concentration is always zero in the model. The simulated LacZ activity is obtained by multiplying the simulated killer protein concentration (in nM) by a constant factor so that the experiment and simulation are at the same scale. Insets show the growth curves and the LacZ activity in linear scale for the ON case. The similar growth of two cultures at low cell density is an intrinsic feature of the circuit and is not caused by a lag in circuit activation: when the ON culture at steady state was diluted into fresh medium with and without the inducer, the resulting cultures again grew similarly at low density but deviated at high density.

143


Figure 3. 3.Effects Effectsof ofpH pHon oncircuit circuitbehavior. behavior. Figure

Figure 3. 7

10

A

5

10

LacZ activity

10

CFU/ml

pH

8

9

10

6.2

6

10

F

4

10

6.6 G

B

7.4 C

H

7.8 D 0

20

40

I

60

0

20

m s

m

0.20

LacZ/k(1 −N /N )

hours

0.15

s

N /(N k)

144

0.10

E

0.05 6.5

7.0

7.5 pH

8.0

3

40

hours

60

7

x 10

2 1 0

J 6.5

7.0

7.5

8.0

pH

Figure 3. Effects of pH on circuit behavior. (a–d) Cell growth with the circuit OFF (filled symbols) and ON (open symbols). (e) Dependence of Ns/(Nm*k) on pH. (f–i) Time courses of LacZ activity with the circuit ON. (j) Dependence of ( LacZ activity) k (1- N s / N m ) on pH. Panels (a–d) have the same scale in both x- and y- axes, as do panels (f–i). Simulated growth curves (ON=solid line, OFF=dotted line) and killer protein time courses (ON=solid line) are shown in (a–d) and (f–i). The killer protein concentration for the OFF cases is always zero in the model. Simulated LacZ activity in (f–i) is obtained by multiplying the simulated killer protein concentration by a constant factor so that the experiment and simulation are at the same scale in each panel. In (e) and (j), steady-state pH values (Table 1) are used along the x-axes. In (e), Ns is normalized with respect to Nm and k to account for minor variations in these variables (Table 1). The dependence of Ns/(Nm*k) on pH is nearly linear (R2 = 0.98).

Chapter 4: Programmed population control by cell-cell communication and regulated killing Figure 4. Living (green) and dead (red) cells regulated by the population control

Figure 4. S1. Figure

Figure 4. Living (green) and dead (red) cells regulated by the population control circuit. These DH5αZ1 cells were more susceptible to the killer gene than TOP10F’ cells, due to the absence of the F plasmid addiction system. Noise in circuit regulation produces this individual variability in cell death.

145


146

Table 1. Effects of pH on circuit parameters

Table 1. Effects of pH on circuit parameters Medium pH

Steady state culture pHa

kb (hr-1)

Nm /109 c (CFU/ml)

Ns/107 d (CFU/ml)

dA e (hr-1)

LacZ activity/107 f (fluorescence/(ml*OD600))

6.2

6.45

0.885

1.25±0.06

4.86±0.02

0.274

1.94±0.12

6.6

6.76

0.928

1.17±0.05

5.59±0.03

0.304

2.02±0.17

7.0

7.18

0.970

1.24±0.10

11.7±0.6

0.639

1.87±0.09

7.4

7.53

0.897

1.16±0.10

13.1±0.6

0.791

1.79±0.16

7.8

8.05

0.936

1.20±0.07

19.5±1.3

1.19

2.00±0.06

measured at about 50 hrs after growth initiation in ON cultures. b obtained by fitting the exponential phase of growth curves of OFF cultures. c average of the stationary phase cell density of OFF cultures between 28hr and 62 hr. d average of the circuit-ON cell density between 28hr and 62hr. e N md AdE k obtained by solving equation N s = with d A as the only unknown. a

N mvAkE d + d AdE k

f

average of LacZ activity of ON cultures between 28hr and 62hr.

Chapter 4: Programmed population control by cell-cell communication and regulated killing

References Ameisen JC (2002) On the origin, evolution, and nature of programmed cell death: a timeline of four billion years. Cell Death Differ 9: 367-393. Atkinson MR, Savageau MA, Myers JT, Ninfa AJ (2003) Development of genetic circuitry exhibiting toggle switch or oscillatory behavior in Escherichia coli. Cell 113: 597-607. Becskei A, Serrano L (2000) Engineering stability in gene networks by autoregulation. Nature 405: 590-593. Blake WJ, M KA, Cantor CR, Collins JJ (2003) Noise in eukaryotic gene expression. Nature 422: 633-637. Bulter T, Lee SG, Woirl WWC, Fung E, Connor MR, Liao JC (2004) Design of artificial cell-cell communication using gene and metabolic networks. Proc Natl Acad Sci U S A 101: 2299-2304. Chen W, Kallio PT, Bailey JE (1993) Construction and characterization of a novel cross-regulation system for regulating cloned gene expression in Escherichia coli. Gene 130: 15-22. Dong YH, Wang LH, Xu JL, Zhang HB, Zhang XF, Zhang LH (2001) Quenching quorumsensing-dependent bacterial infection by an N-acyl homoserine lactonase. Nature 411: 813-817. Egland KA, Greenberg EP (1999) Quorum sensing in Vibrio fischeri: elements of the luxl promoter. Mol Microbiol 31: 1197-1204. Egland KA, Greenberg EP (2001) Quorum sensing in Vibrio fischeri: analysis of the LuxR DNA binding region by alanine-scanning mutagenesis. J Bacteriol 183: 382-386. Elowitz MB, Leibler S (2000) A synthetic oscillatory network of transcriptional regulators. Nature 403: 335-338. Elowitz MB, Levine AJ, Siggia ED, Swain PS (2002) Stochastic gene expression in a single cell. Science 297: 1183-1186. Engelberg-Kulka H, Glaser G (1999) Addiction modules and programmed cell death and

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Transcriptional Regulation and Combinatorial Genetic Logic antideath in bacterial cultures. Annu Rev Microbiol 53: 43-70. Farmer WR, Liao JC (2000) Improving lycopene production in Escherichia coli by engineering metabolic control. Nature biotechnology 18: 533-537. Fuqua WC, Winans SC, Greenberg EP (1994) Quorum sensing in bacteria: the LuxR-LuxI family of cell density-responsive transcriptional regulators. J Bacteriol 176: 269-275. Gardner TS, Cantor CR, Collins JJ (2000) Construction of a genetic toggle switch in Escherichia coli. Nature 403: 339-342. Gerchman Y, Weiss R (2004) Teaching bacteria a new language. Proc Natl Acad Sci U S A 101: 2221-2222. Hasty J, McMillen D, Collins JJ (2002) Engineered gene circuits. Nature 420: 224-230. Isaacs FJ, Hasty J, Cantor CR, Collins JJ (2003) Prediction and measurement of an autoregulatory genetic module. Proc Natl Acad Sci U S A 100: 7714-7719. Leadbetter JR, Greenberg EP (2000) Metabolism of acyl-homoserine lactone quorum-sensing signals by Variovorax paradoxus. J Bacteriol 182: 6921-6926. Lewis K (2000) Programmed death in bacteria. Microbiol Mol Biol Rev 64: 503-514. Lutz R, Bujard H (1997) Independent and tight regulation of transcriptional units in Escherichia coli via the LacR/O, the TetR/O and AraC/I1-I2 regulatory elements. Nucleic Acids Res 25: 12031210. Miller MB, Bassler BL (2001) Quorum sensing in bacteria. Annu Rev Microbiol 55: 165-199. Ozbudak EM, Thattai M, Kurtser I, Grossman AD, van Oudenaarden A (2002) Regulation of noise in the expression of a single gene. Nat Genet 31: 69-73. Schaefer AL, Hanzelka BL, Parsek MR, Greenberg EP (2000) Detection, purification, and structural elucidation of the acylhomoserine lactone inducer of Vibrio fischeri luminescence and other related molecules. In Bioluminescence and Chemiluminescence, Pt C, Vol. 305, pp 288-301.

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Appendix A: Promoter library data This appendix contains the promoter sequences characterized in Chapters 1 and 2, the luminescence data of Chapter 2. See Chapter 2 methods for experimental protocols and Chapter 2 Table S1 for the definitions of the 48 duplex unit sequences. Appendix A1. Promoter library sequence data. clone

Promoter sequence (between cloning sites XhoI and BamHI)

distal

core

proximal

A1

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACTATTTTACCTCTGGCGGTGATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

ara2

con2

con1

A11

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACTATTTTACCTCTGGCGGTGATAATTCTTGCGACAAACAATAGGTAAGGCGTTACCCAAC

con0

con2

lux2

A12

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACTTGTGAGCGGATAACAATTATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

ara2

lac3

lux1

A2

TACAACGTCGTGTTAGCTGCTCCCTATCAGTGATAGAGATTGACATTTATCCCTTGCGGTGATAGATTTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

tet1

con4

con1

A3

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATTGTGAGCGGATAACAAGATACTTAACTCTATCAATGATAGAGTGTCAACAAAAAAAC

con0

lac1

tet2

A4

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACATAGCGGATACTTCCTGATATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

lac1

ara2

lux1

A5

TACAACGTCGTGTTAGCTCAATTGTGAGCGGATAACAATTGACTTTTATCCCTTGCGGTGATATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

lac1

con3

con1

A6

TACAACGTCATTTCACTTTTCTCTATCACTGATAGGGAGTGGTCTTTTATCCCTTCGCGGTGATATAATTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

tet2

con3

con3

A7

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACTTTTATCCCTTGCGGTGATATAATTCTTGCGACAAACAATAGGTAAGGCGTTACCCAAC

con0

con3

lux2

A8

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACTATTTTACCTCTGGCGGTGATAATTCTTGCGACAAACAATAGGTAAGGCGTTACCCAAC

ara2

con2

lux2

A9

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACAAATAACTCTATCAATGATAGAGTTCGTGCATAGCATTTTTATCCATACGTTACCCAAC

con0

tet2

ara2

A13

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGACTTGTGAGCGGATAACAATTATAATTGAATACAGCTGGCGGTGATAAGGCGTTACCCAAC

con3

lac3

con1

A23

TACAACGTCGTGTTAGTTGCCTTTCGTCTTCAATAATTCTTGACATTTATGCTTCCGGCTCGTATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

con0

con0

lux1

A14

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACAATCAATGTGGATTTTCTGATACTTCTTGCGACAAACAATAGGTAAGGCGTTACCCAAC

con4

ara1

lux2

A16

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACACTCTATCATTGATAGAGTTATTTTTCGTGGTCCATATTGCATCAGACATTGTACCCAAC

con4

tet3

ara1

A17

TACAACGTCATTTCACTTTTCTATCACTGATAGGGAGTGGTCATTTATGCTTCCGGCTCGTATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

tet2

con0

lux1

A18

TACAACGTCGTGTTAAATTGTGAGCGGATAACAATTTAGTTGACTATTTTACCTCTGGCGGTGATAATTCCACCCCTTCAGTGATAGAGAGCGTTACCCAAC

lac2

con2

tet1

A19

TACAACGTCGTGTTAAATTAGTGAGCGGATAACAATTTAGTTGACTATTTTACCTCTGGCGGTGATAATTCCACCCCTTCAGTGATAGAGAGCGTTACCCAAC

lac2

con2

tet1

A20

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACACCTGTAGGATCGTACAGGTATAATTCTTGCGACAAACAATAGGTAAGGCGTTACCCAAC

con4

lux2

lux2

A25

TATCACCGCCAGAGGTAAAATATTCAACACGCACGGTGTTAGACACTCTATCATTGATAGAGTTATTTTTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

con3

tet3

lux1

A34 A35

TATCACCGCCAGAGTAAAATAGTCAACACGCACGGTGTTAGGCAAATAACTCTATCAATGATAGAGTTAGATTCAATTAGTGAGCGGATAACAATTTCACACA

con2

tet2

lac2

TACAACGTCGTGTTAGCTGCTCCCTATAGTGATAGAGATTGACTTGTGAGCGGATAACAATTATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

tet1

lac3

con1

A26

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTCGACACTCTATCATTGATAGAGTTATTTTTGAATACCTCTGGCGGTGATAAGGCGTTACCCAAC

con4

tet3

con2

A27

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATAGCGGATACTTCCTGATATAATTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

con4

ara2

con0

A28

TACAACGTCGTGTTAAATTGTGAGCGGATAACAATTTAGTTGACATCCCTATCAGTGATAGAGATACTTTGTGGAATTGTGAGCGGATAACAATTTCACACAG

lac2

tet1

lac1

A29

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACACCTGTAGGATCGTACAGGTATAATTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

con4

lux2

con3

A30

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACAATCAATGTGGATTTTCTGATACTTTGTGGAATTGTGAGCGGATAACAATTTCACACAG

con4

ara1

lac1


distal

core

proximal

A32

TACAACGTCGTGTTAAATTGTGAGCGGATAACAATTTAGTTGACATAGCGGATACTTCCTGATATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

lac2

ara2

con1

A33

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGGCTTGTGAGCGGATAACAATTATAATTCGTGCATTTTTAAACCTGTAGGATCGTACAGGT

con2

lac3

lux1

A37

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATCCCTATCAGTGATAGAGATACTTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con4

tet1

con4

A46

TACAACGCATTTCACTTTTCTCTATCACTGATAGGGAGTGGTCTATTTTACCTCTGGCGGTGATAATTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

tet2

con2

con3

A47

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATAGCGGATACTTCCTGATATAATTGAATACCTCTGGCGGTGATAAGCGTTACCCAAC

con4

ara2

con2

A48

TACAACGTCGTGTTAAATTGTGAGCGGATAACAATTTAGTTGACATTTATGCTTCCGGCTCGTATAATTAGATTCAATTGTGAGCGGATAACAATTTCACACA

lac2

con0

lac2

A38

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACATTTATGCTTCCGGCTCGTATAATTCGTGCAATTTAAATGTGAGCGAGTAACAACCAAC

lac1

con0

lac4

A39

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATAGCGGATACTTCCTGATATAATTCGTGGTCCATATTGCATCAGACATTGTACCCAAC

con0

ara2

ara1

A40

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATTTATCCCTTGCGGTGATAGATTTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con4

con4

con4

A41

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGGCATTTATCCCTTGCGGTGATAGATTTCGTGCATAGCATTTTTATCCATACGTTACCCAAC

con2

con4

ara2

A42

TACAACGTCGTGTTAGCTGCTCCCTATCAGTGATAGAGATTGACATTTATGCTTCCGGCTCGTATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

tet1

con0

con1

A43

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACATAGCGGATACTTCCTGATATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

ara2

ara2

lux1

A44

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACTATTTTACCTCTGGCGGTGATAATTTGTGGAATTGTGAGCGGATAACAATTTCACACAG

con4

con2

lac1

A45

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACACCTGTAGGATCGTACAGGTATAATTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

lac1

lux2

con0

A49

TACAACGTCATTTCACTTTTCTCTATCACTGATAGGGAGTGGTCATTTATGCTTCCGGCTCGTATAATTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

tet2

con0

con4

A59

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACTTGTGAGCGGATAACAATGATACTTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

con0

lac2

con0

A60

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACAAATAACTCTATCAATGATAGAGTTAGATTCAATTGTGAGCGGATAACAATTTCACACA

con0

tet2

lac2

A52

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACAATCAATGTGGATTTTCTGATACTTGAATACATCTGGCGGTGAATAAGGCGTTACCCAAC

lac1

ara1

con1

A53

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACACCTGTAGGATCGTACAGGTATAATTAGATTCAATTGTGAGCGGATAACAATTTCACACA

con0

lux2

lac2

A54

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACATTTATCCCTTGCGGTGATAGATTTAGATTCAATTGTGAGCGGATAACAATTTCACACA

ara2

con4

lac2

A56

TACAACGTCATTTCACTTTTCTCTATCACTGATAGGGAGTGGTCATTTATCCCTTGCGGTGATAGATTTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

tet2

con4

con0

A57

TACAACGTCGTGTTAGCTGCTCCCTATCAGTGATAGAGATTGACATTTATGCTTCCGGCTCGTATAATTCCTGTAGGATCGTACAGGTAAGGCGTTACCCAAC

tet1

con0

lux3

A61

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACTTTTATCCCTTGCGGTGATATAATTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

con0

con3

con3

A70

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACTTTTATCCCTTGCGGTGATATAATTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

con4

con3

con3

A72

ACATAGCATTTTTATCCATAACCTGTAGGATCGTACAGGTTTACATTTATCCCTTGCGGTGATAGATTTCCTGTAGGATCGTACAGGTAAGGCGTTACCCAAC

lux3

con4

lux3

A62

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACTTTTATCCCTTGCGGTGATATAATTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con4

con3

con4

A63

TACAACGTCATTTCACTTTTCTCTATCACTGATAGGGAGTGGTCAATCAATGTGGATTTTCTGATACTTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAC

tet2

ara1

con0

A64

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACACCTGTAGGATCGTACAGGTATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

ara2

lux2

con1

A65

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATAAATACCACTGGCGGTGATACTTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

con0

con1

con3

A66

TACAACGTCGTGTTAAATTGTGAGCGGATAACAATTTAGTTGACACCTGTAGGATCGTACAGGTATAATTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

lac2

lux2

con3

A67

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATAGCGGATACTTCCTGATATAATTCGTGCATAGCATTTTTATCCATACGTTACCCAAC

con0

ara2

ara2

A68

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACATAGCGGATACTTCCTGATATAATTGAATACCTCTGGCGGTGATAAGGCGTTACCCAAC

ara2

ara2

con2

A69

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACTTTTATCCCTTGCGGTGATATAATTAGATTCAATTGTGAGCGGATAACAATTTCACACA

con0

con3

lac2

Appendix A1.

clone

151

Transcriptional regulation and combinatorial genetic logic in synthetic circuits 152

clone


distal

core

proximal

A82

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACTATTTTACCTCTGGCGGTGATAATTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

con4

con2

con0

A83

TACAACGTCGTGTTAGCTGCTCCCTATCAGTGTAGAGATTGACTATTTTACCTCTGGCGGTGATAATTCCACCCCTTCAGTGATAGAGAGCGTTACCCAAC

tet1

con2

tet1

A76

TACAACGTCATTTCACTTTTCTCTATCACTGATAGGGAGTGGTCATTTATGCTTCCGGCTCGTATAATTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

tet2

con0

con0

A77

GTAACAAAAGTGTCTATAATCACGGCAGAAAAGTCCACATTGACTTTTATCCCTTGCGGTGATATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

ara3

con3

con1

A78

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACATTTATCCCTTGCGGTGATAGATTTCCACCCCTATCAGTGATAGAGAGCGTTACCCAAC

ara2

con4

tet1

A79

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACAATCAATGTGGATTTTCTGATACTTCTTGCGACAAACAATAGGTAAGGCGTTACCCAAC

ara2

ara1

lux2

A80

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGGATCCCTATCAGTGATAGAGATACTTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

con2

tet1

con0

A81

TACAACGTCGTGTTAAATTGTGAGCGGATAACAATTTAGTTGACATAAATACCACTGGCGGTGATACTTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

lac2

con1

lux1

A85

TACAACGTCGTGTTAGCTGCTCCCTATCAGTGATAGAGATTGACTTTTATCCCTTGCGGTGATATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

tet1

con3

con1

A95

TACAACGTCGTGTTAAATTGTGAGCGGATAACAATTTAGTTGACTTTTATCCCTTGCGGTGATATAATTAGATTCAATTGTGAGCGGATAACAATTTCACACA

lac2

con3

lac2

A96

TCTCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGACACTCTATCATTCGATAGAGTTATTTTTCCACCCCTATCAGTGATAGAGAGCGTTACCCAAC

con3

tet3

tet1

A86

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATAGCGGATACTTCCTGATATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

con0

ara2

lux1

A87

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACAATCAATGTGGATTTTCTGATACTTCGTGCAATTTAAATGTGAGCGAGTAACAACCAAC

con0

ara1

lac4

A88

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACATTTATGCTTCCGGCTCGTATAATTCGTGGTCCATATTGCATCAGACATTGTACCCAAC

ara2

con0

ara1

A89

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACACCTGTAGGATCGTACAGGTATAATTAACTCTATCAATGATAGAGTGTCAACAAAAAAAC

con4

lux2

tet2

A90

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATCCCTATCAGTGATAGAGATACTTTGTGGAATTGTGAGCGGATAACATTTCACACAG

con0

tet1

lac1

B10

TATAACGTCGTATTAGCTGCCTTTCGTCTTCAATAATTCTTGACATCCCTATCAGTGATAGAGATACTTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

con0

tet1

con3

B11

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACTATTTTACCTCTGGCGGTGATAATTTGTGGAATTGTGAGCGGATAACATTCACACAG

con0

con2

lac1

B4

TACAACGTCGTGTTAGTTGCAATTGTGAGCGGATAACAATTGACTTGTGAGCGGATAACAATGATACTTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

lac1

lac2

con0

B5

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACAAATAACTCTATCAATGATAGAGTTAGATTCAATTGTGAGCGGATAACAATTTCACACA

ara2

tet2

lac2

B13

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGACTTGTGAGCGGATAACAATGATACTTCGTGCATAGCATTTTTATCCATACGTTACCCAAC

con3

lac2

ara2

B22

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATTTATCCCTTGCGGTGATAGATTTCCACCCCTATCAGTGATAGAGAGCGTTACCCAAC

con4

con4

tet1

B23

TACAACGTCGTGTTAGCTGCTCCCTATCAGTGATAGAGATTGACAATCAATGTGGATTTTCTGATACTTGATTCAATTGTGAGCGGATAACAATTTCACACAG

tet1

ara1

lac3

B14

TACAACGTCGTGTTAGCTGTATCACCAGATAACCATCTGCGGTGATAAATTATCTCTGGCGGTGTTGACTTGTGAGCGGATAACAATGATACTTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

con1

lac2

con0

B16

TACAACGTCATTTCACTTTTCTCTATCACTGATAGGGAGTGGTCATAGCGGATACTTCCTGATATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

tet2

ara2

lux1

B17

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACTTGTGAGCGCTCACAATTTATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

con4

lac4

con1

B18

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATAAATACCACTGGCGGTGATACTTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con4

con1

con4

B19

GTAACAAAAGTGTCTATAATCACGGCAGAAAAGTCCACATTGACAAATAACTCTATCAATGATAGAGTTCCACCCCTATCAGTGATAGAGAGCGTTACCCAAC

ara3

tet2

tet1

B20

TACAACGTCGTGTGAGCTGCCTTTTAGCAATTTTATCCATAGACTTTTATCCCTTGCGGTGATATAATTCCCCCCTATCAGTGATAGAGAGCGTTACCCAAC

ara2

con3

tet1

B21

TACCACGCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACACCTGTAGGATCGTACAGGTATAATTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

ara2

lux2

con3

B25

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATTTATCCCTTGCGGTGATAGATTTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con0

con4

con4

B35

TACAACGTCGTGTTAGCTGCTCCCTATCAGTGATAGAGATTGACACCTGTAGGATCGTACAGGTATAATTCGTGCATAGCATTTTTATCCATACGTTACCCAAC

tet1

lux2

ara2


distal

core

proximal

B26

TACAACGTCGTGTTAAATTGTGAGCGGATAACAATTTAGTTGACATTTATGCTTCCGGCTCGTATAATTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

lac2

con0

con3

B27

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACACCTGTAGGATCGTACAGGTATAATTCGTGGTCCATATTGCATCAGACATTGTACCCAAC

con4

lux2

ara1

B29


con4

con2

con0

B30

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACTATTTTACCTCTGGCGGTGATAATTCGTGCAATTTTTAACTGTAGGATCGTACAGGT

con4

con2

lux1

B31

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACATAGCGGATACTTCCTGATATAATTAGATTCAATTGTGAGCGGATAACAATTTCACACA

ara2

ara2

lac2

B33

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACAATCAATGTGGATTTTCTGATACTTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

ara2

ara1

con1

B37

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATAAATACCACTGGCGGTGATACTTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

con0

con1

con3

B46

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATCCCTATCAGTGATAGAGATACTTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

con4

tet1

con1

B47

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACTTGTGAGCGGATAACAATTATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

ara2

lac3

lux1

B48

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTATCCATAGACTTGTGAGCGATAACAATTATAATTTGTGGAATTGTGAGCGGATAACAATTTCACACAG

ara2

lac3

lac1

B39

TACAACGTCATTTCACTTTTCTCTATCACTGATAGGGAGTGGTCATAAATACCACTGGCGGTGATACTTAACTCTATCAATGATAGAGTGTCAACAAAAAAAC

tet2

con1

tet2

B40

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACATAGCGGATACTTCCTGATATAATTCGTTATCACCGCCAGGGGTAAGGCGTTACCAAC

lac1

ara2

con4

B42

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGGCATAGCGGATACTTCCTGATATAATTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

con2

ara2

con0

B43

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACTTTTATCCCTTGCGGTGATATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

con0

con3

con1

B45

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACACCTGTAGGATCGTACAGGTATAATTCGTGGTCCATATTGCATCAGACATTGTACCCAAC

con0

lux2

ara1

B49

TAAACGGCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACTATTTTACCTCTGGCGGTGATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

con4

con2

con1

B60

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACAATCAATGTGGATTTTCTGATACTTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

ara2

ara1

con0

B50

TACAACGTCGTGTTAGCTGCTCCCTATCAGTGATAGAGATTGACTATTTTACCTCTGGCGGTGATAATTGAATACCTCTGGCGGTGATAAGGCGTTACCCAAC

tet1

con2

con2

B51

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACTTGTGAGCGGATAACAATTATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

ara2

lac3

con1

B52

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATTTATGCTTCCGGCTCGTATAATTCGTGCAATTTAAATGTGAGCGAGTAACAACCAAC

con4

con0

lac4

B56

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACTTTTATCCCTTGCGGTGATATAATTAGATTCAATTGTGAGCGGATAACAATTTCACACA

con0

con3

lac2

B61


ara2

con2

lux2

B71

GTAACAAAAGTGTCTATAATCACGGCAGAAAAGTCCACATTGACTTGTGAGCGGATAACAATGATACTTGAATACCTCTGGCGGTGATAAGGCGTTACCCAAC

ara3

lac2

con2

B72

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACTTGTGAGCGGATAACAATTATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

con0

lac3

lux1

B62

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACTATTTTACCTCTGGCGGTGATAATTCGTGCATAGCATTTTTATCCATACGTTACCCAAC

lac1

con2

ara2

B63

TACAATTGTGAGCGCTCACAATTTCGTCTTCAATAATTCTTGACTATTTTACCTCTGGCGGTGATAATTCGTGCATAGCATTTTTATCCATACGTTACCCAAC

lac3

con2

ara2

B66

TACAACGTCGTGTTAGTGCTCCCTATCAGTGATAGAGATTGACTATTTTACCTCTGGCGGTGATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

tet1

con2

lux1

B73

TACAACGTCGTGTTAAATTGTGAGCGGATAACAATTTAGTTGACATAGCGGATACTTCCTGATATAATTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

lac2

ara2

con4

B82

TACAACGTCTGTTAGCTGCAATTGTGAGCGGATAACAATTGACAAATAACTCTATCAATGATAGAGTTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

lac1

tet2

con4

B83


lac1

tet2

con4

B77

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATCCCTATCAGTGATAGAGATACTTCGTGCATAGCATTTTTATCCATACGTTACCCAAC

con0

tet1

ara2

B78

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACTTGTGAGCGGATAACAATGATACTTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

ara2

lac2

lux1

B79

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATTTATCCCTTGCGGTGATAGATTTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

con4

con4

con1

Appendix A1.

clone

153


clone


distal

core

proximal

B80

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACTATTTTACCTCTGGCGGTGATAATTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

lac1

con2

con3

B81

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACTATTTTACCTCTGGCGGTGATAATTGATTCAATTGTGAGCGGATAACAATTTCACACAG

ara2

con2

lac3

B85

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACTATTTTACCTCTGGCGGTGAGAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

lac1

con2

con1

B95

TACAATTGTGAGCGCTCACAATTTCGTCTTCAATAATTCTTGACATTGTGAGCGGATAACAAGATACTTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

lac3

lac1

con1

B96


lac1

tet2

con4

B86

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACTTGTGAGCGGATAACAATTATAATTCGTGCAATTTTTAAACCTGTAGGATGTACAGGT

ara2

lac3

lux1

B91

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACACCTGTAGGATCGTACAGGTATAATTAACTCTATCAATGATAGAGTGTCAACAAAAAAAC

con0

lux2

tet2

B92

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATTGTGAGCGGATAACAAGATACTTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con4

lac1

con4

B93

TACAACGACATGGTAGCTGCAATTGTGAGCGGATAACAATTGACATAGCGGATACTTCCTGATATAATTGAATACCTCTGGCGGTGATAAGGCGTTACCCAAC

lac1

ara2

con2

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACAAATAACTCTATCAATGATAGAGTTCCACCCCTATCAGTGATAGAGAGCGTTACCCAAC

ara2

tet2

tet1

C11

C1

TACAACGTCGTGTTAGCTGCCTTTGTCTTCAATAATTCTTGACAATCAATGTGGATTTTCTGATACTTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

con0

ara1

lux1

C12


con0

ara1

lux1

C3


ara2

tet2

tet1

C4

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATCCCTATCAGTGATAGAGATACTTAGATTCAATTGTGAGCGGATAACAATTTCACACA

con0

tet1

lac2

C5

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACAAATAACTCTATCAATGATAGAGTTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

lac1

tet2

con4

C6

TACAATTAGTTTAACATAAGTACCTAGTAGGATCGTACAGGTTTACTATTTTACCTCTGGCGGTGATAATTCTTAGCAACAAACAATAGGTAAGGCGTTACCCAAC

lux1

con2

lux2

C9

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATTTATCCCTTGCGGTGATAGATTTTGTGGAATTGTGAGCGGATAACAATTTCACACAG

con4

con4

lac1

C13


con4

con2

con0

C22

TACAACGTCATTTCACTTTTCTCTATCACTGATAGGGAGTGGTCATAGCGGATACTTCCTGATATAATTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

tet2

ara2

con4

C23


con0

ara1

lux1

C24

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACACCTGTAGGATCGTACAGGTATAATTAGATTCAATTAGTGAGCGGATAACAATTTCACACA

con0

lux2

lac2

C14


ara2

tet2

tet1

C15

TACAACGTCGTGTTAGCTGCTCCCTATCAGTGATAGAGATTGACTATTTTACCTCTGGCGGTGATAATTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

tet1

con2

con0

C16

TACAACGTCGTGTTAGCTGCTCCCTATCAGTGATAGAGATTGACTATTTTACCTCTGGCGGTGATAATTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

tet1

con2

con0

C18

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATAGCGGATACTTCCTGATATAATTCGTGGTCCATATTGCATCAGACATTGTACCCAAC

con0

ara2

ara1

C19

TACAACGTCGTGTTAAATTGTGAGCGGATAACAATTTAGTTGACAAATAACTCTATCAATGATAGAGTTTGTGGAATTTGAGCGGATAACAATTTCACACAG

lac2

tet2

lac1

C20

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGGCTTTTATCCCTTGCGGTGATATAATTAGATTCAATTGTGAGCGGATAACAATTTCACACA

con2

con3

lac2

C21

TACAACGTCGTGTTAGCTGCTCCCTATCAGTGATAGAGATTGACATTTATCCCTTGCGGTGATAGATTTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

tet1

con4

lux1

C34


con0

tet1

ara2

C35


ara2

tet2

tet1

C26

TACAACGTCGTGTTAAATTGTGAGCGGATAACAATTTAGTTGACATTTATGCTTCCGGCTCGTATAATTCCACCCCTATCAGTGATAGAGAGCGTTACCCAAC

lac2

con0

tet1

C27

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACACCTGTAGGATCGTACAGGTATAATTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con4

lux2

con4

C29

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATAGCGGATACTTCCTGATATAATTCTTGCGACAAACAATAGGTAAGGCGTTACCCAAC

con0

ara2

lux2

clone


distal

core

proximal

C31

TACAACGTCATTTCTTCTCTATCACTGATAGGGAGTGGTCTTGTGAGCGGATAACAATTATAATTCGTGCATAGCATTTTTATCCATACGTTACCCAAC

tet2

lac3

ara2

C32

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATAGCGGATACTTCCTGATATAATTCCTGTAGGATCGTACAGGTAAGGCGTTACCCAAC

con0

ara2

lux3

C33

TACAACGTCGTGTTAGCTGCCTATCAGTGATAGAGATTGACATTTATGCTTCCGGCTCGTATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

tet1

con0

con1

C37

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACACCTGTAGGATCGTACAGGTATAATTCCTGTAGGATCGTACAGGTAAGGCGTTACCCAAC

ara2

lux2

lux3

C46

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATTTATCCCTTGCGGTGATAGATTTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

con0

con4

con1

C47

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACACCTGTAGGATCGTACAGGTATAATTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

lac1

lux2

con0

C48


ara2

tet2

tet1

C38

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGACCCTGTAGGATCGTACAGGTATAATTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

con3

lux1

con0

C39

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACTTGTGAGCGGATAACAATGATACTTTGTGGAATTGTGAGCGGATAACAATTCACACAG

con0

lac2

lac1

C40


con0

tet1

ara2

C41


ara2

con2

lux2

C42

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATTGTGAGCGGATAACAAGATACTTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

con4

lac1

lux1

C44

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGGCACCTGTAGGATCGTACAGGTATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

con2

lux2

lux1

C45

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACATTTATGCTTCCGGCTCGTATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

ara2

con0

lux1

C49

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGACATAGCGGATACTTCCTGATATAATTCGTGCAATTTTAAACCTGTAGGATCGTACAGGT

con3

ara2

lux1

C59

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATAGCGGATACTTCCTGATATAATTCCTGTAGGATCGTACAGGTAAGGCGTTACCCAAC

con4

ara2

lux3

C51

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATTTATCCCTTGCGGTGATAGATTTCGTGCATAGCATTTTTATCCATACGTTACCCAAC

con0

con4

ara2

C52

TACAACGTCGTGTTAGCTGCTCCCTATCAGTGATAGAGATTGACATAGCGGATACTTCCTGATATAATTGAATACCTCTGGCGGTGATAAGGCGTTACCCAAC

tet1

ara2

con2

C53

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGGCTATTTTACCTCTGGCGGTGATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

con2

con2

lux1

C54

TACAATTGTTTAACATAAGTGAATGGATCATTTTGCAGGTTTACACCTGTAGGATCGACAGGTATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

lux2

lux2

lux1

C55

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACCCTGTAGGATCGTACAGGTATAATTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con4

lux1

con4

Appendix A1. 155


clone

distal

core

proximal

C56

TACAACGTCGTGTTAGCTAGCCTTTCGTCTTCAATAATTCTTAGACTTGTGAGCGGATAACAATTATAATTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

con0

lac3

con3

C61

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACAAATAACTCTATCAATGATAGAGTTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

lac1

tet2

con3

C70


con0

tet1

ara2

C71

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACATAGCGGATACTTCCTGATATAATTCGTGCAATTTTTAAACCTGTGGATCGTACAGGT

ara2

ara2

lux1

C63

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGGCAAATAACTCTATCAATGATAGAGTTCTTGCGACAAACAATAGGTAAGGCGTTACCCAAC

con2

tet2

lux2

C64


tet1

ara2

con2

C65

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGACATTTATGCTTCCGGCTCGTATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

con3

con0

lux1

C66

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACACCTGTAGGATCGTACAGGTATAATTCGTGGTCCATATTGCATCAGACATTGTACCCAAC

con0

lux2

ara1

C67

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATAGCGGATACTTCCTGATATAATTCGTGCATAGCATTTTTATCCATACGTTACCCAAC

con4

ara2

ara2

C68

TACAACGTCGTGTTAGCTGCTCCCTATCAGTGATAGAGATTGACATTGTGAGCGGATAACAAGATACTTTGTGGAATTTGAGCGGATAACAATTTCACACAG

tet1

lac1

lac1

C69

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACTTTTATCCCTTGCGGTGATATAATTCGTGCATAGCATTTTTATCCATACGTTACCCAAC

ara2

con3

ara2

C82


con0

tet1

ara2

C83

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATTTATGCTTCCGGCTCGTATAATTCGTGCAATTTTTATATTACCGCCAGGGGTACAAC

con4

con0

con3

C84

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATTTATGCTTCCGGCTCGTATAATTCGTGCAATTTTTATATTACCGCCAGGGGTACAAC

con4

con0

con3

C75


con0

con0

lux1

C76

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACATTTATGCTTCCGGCTCGTATAATTAGATTCAATTGTGAGCGGATAACAATTTCACACA

lac1

con0

lac2

C77

TACAACGTCATTTCACTTTTCTCTATCACTGATAGGGAGTGGTCATTTATGCTTCCGGCTCGTATAATTGAATACATCTGGCGTGATAAGGCGTTACCCAAC

tet2

con0

con1

C78

TACAACGTCATTTCACTTTTCTCTATCACTGATAGGGAGTGGTCATAGCGGATACTTCCTGATATAATTGAATACCTCTGGCGGTGATAAGGCGTTACCCAAC

tet2

ara2

con2

C79

TACAACGTCGTGTTAGCTGCCTTTCGTTTTCAATAATTCTTGACTTGTGAGCGGATAACAATTATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

con0

lac3

con1

C80

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGATAAGATTGACTTTTATCCCTTGCGGTGATATAATTTGTGGAATTGTGAGCGGATAACAATTTCACACAG

con4

con3

lac1

C81

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATCCCTATCAGTGATAGAGATACTTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con0

tet1

con4

C85

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACAATCAATGTGGATTTTCTGATACTTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con0

ara1

con4

C94


con0

tet1

ara2

C96

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATAGCGGATACTTCCTGATATAATTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

con4

ara2

con3

C86

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACATAGCGGATACTTCCTGATATAATTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

lac1

ara2

con4

C87

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGATTAGACTTTTATCCCTTGCGGTGATATAATTCGTGCAATTTAAATAGTGAGCGAGTAACAACCAAC

con3

con3

lac4

C90


con4

ara2

con3

C91

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACCCTGTAGGATCGTACAGGTATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

con4

lux1

lux1

C92

TACAACGTCGTATTAGCTGCCTTTCGTCTTCAATAATTCTTGACATCCCTATCAGTGATAGAGATACTTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

con0

tet1

con3

C93

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACTTTTATCCCTTGCGGTGATATAATTCGTGCAATTTTTAAACCTTAGGATCGTACAGGT

con4

con3

lux1

D52

TACAACGCCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACTTTTATCCCTTGCGGTGATATAATTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con0

con3

con4

D10

TACAACGTCGTGTTAAATTGTGAGCGGATAACAATTTAGTTGACTATTTTACCTCTGGCGGTGATAATTCCACCCCTATCAGTGATAGAGAGCGTTACCCAAC

lac2

con2

tet1

D11

TACAACGTCGTGTTAGCTGCTCCTATCAGTGATAGAGATTGACAAATAACTCTATCAATGATAGAGTTCTTGCGACAAACAATAGGTAAGGCGTTACCCAAC

tet1

tet2

lux2

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATAAATACCACTGGCGGTGATACTTCGTGGTTCATATTGCATCAGACATTGTACCCAAC

con4

con1

ara1

D3

156



distal

core

proximal

D4

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACATTTATCCCTTGCGGTGATAGATTTAGATTCAATTGTGAGCGGATAACAATTTCACACA

ara2

con4

lac2

D5

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACTTGTGAGCGGATAACAATTATAATTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con4

lac3

con4

D7

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATTGTGAGCGGATAACAAGATACTTAACTCTATCAATGATAGAGTGTCAACAAAAAAAC

con0

lac1

tet2

D8

TACAACGTCGTGTTAAATTGTGAGCGGATAACAATTTAGTTGACATTTATGCTTCCGGCTCGTATAATTCCACCCCTATCAGTGATAGAGAGCGTTACCCAAC

lac2

con0

tet1

D9

TACAACGTCGTGTTAGCTGCTCCCTATCAGTGATAGAGATTGACACCTGTAGGATCGTACAGGTATAATTCGTGCAATTTAAATGTGAGCGAGTAACAACCAAC

tet1

lux2

lac4

D13

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATTTATGCTTCCGGCTCGTATAATTGATTCAATTGTGAGCGGATAACAATTTCACACAG

con0

con0

lac3

D24


con0

ara2

lux3

D14

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACACCTGTAGGATCGTACAGGTATAATTCCTGTAGGATCGTACAGGTAAGGCGTTACCCAAC

ara2

lux2

lux3

D16

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGGCATCCCTATCAGTGATAGAGATACTTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

con2

tet1

con1

D17

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTCGACATAGCGGATACTTCCTGATATAATTCCTGTAGNATCGTACAGGTAAGGCGTTACCCAAC

con0

ara2

lux3

D18

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATCCCTATCAGTGATAGAGATACTTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

con0

tet1

con1

D19

TACAACGTCGTGTTAACTGTATCACCGCCAGAGGTAAGATTGACATTTATGCTTCCGGCTCGTATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

con4

con0

con1

D20

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGACTTGTGAGCGGATAACAATAATACTTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

con3

lac2

lux1

D25

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATTGTGAGCGGATAACAAGATACTTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

con4

lac1

con1

D34


con4

ara2

con3

D35

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATTTATCCCTTGCGGTGATAGATTTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con4

con4

con4

D36

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATTTATCCCTTGCGGTGATAGATTTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

con0

con4

lux1

D27


tet1

ara2

con2

D28

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACTTTTATCCCTTGCGGTGATATAATTAGATTCAATTATGAGCGGATAACAATTTCACACA

con0

con3

lac2

D29

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACACCTGTAGGATCGTACAGGTATAATTAACTCTATCAATGATAGAGTGTCAACAAAAAAAC

ara2

lux2

tet2

D31

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGGCTTGTGAGCGGATAACAATTATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

con2

lac3

con1

D32

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACAATCAATGTGGATTTTCTGATACTTGAATACATCTGGCGGTGATAAGGCATTACCCAAC

con4

ara1

con1

D37

TACAACGTCATTTCACTTTTCTCTATCACTGATAGGGATGGTCATAGCGGATACTTCCTGATATAATTCGTGGTCCATATTGCATCAGACATTGTACCCAAC

tet2

ara2

ara1

D46


ara2

tet2

tet1

D38

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTTAGACATTTATCCCTTGCGGTGATAGATTTCTTGCGACAAACAATAGGTAAGGCGTTACCCAAC

con2

con4

lux2

D40

TACAACGTCGTGTTAAATTGGAGCGGATAACAATTTAGTTGACACCTGTAGGATCGTACAGGTATAATTGAATACCTCTGGCGGTGATAAGGCGTTACCCAAC

lac2

lux2

con2

D41

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATAGCGGATACTTCCTGATATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

con0

ara2

con1

D42


con0

ara2

lux3

D43

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATTTATGCTTCCGGCTCGTATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

con4

con0

lux1

D44


con4

con2

con0

D45

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACAAATAACTCTATCAATGATAGAGTTGAATACCTCTGGCGGTGATAAGGCGTTACCCAAC

con4

tet2

con2

D49

TACAATTGTTTAACATAAGTACCTGTAGGATCGTACAGGTTTACTATTTTACCTCTGGCGGTGATAATTCTTGCAACAAACAATAGGTAAGGCGTTACCCAAC

lux1

con2

lux2

D60

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATTTATGCTTCCGGCTCGTATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

con4

con0

lux1

D50

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATCCCTATCAGTGATAGAGATACTTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

con0

tet1

con3

Appendix A1.

clone

157


clone


distal

core

proximal

D51

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATNGACTATTTTACCTCTGGCGGTGATAATTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

con4

con2

con0

D53

GTAACAAAAGTGTCTATAATCACGGCAGAAAAGTCCACATTGACATTGTGAGCGGATAACAAGATACTTGAATACCTCTGGCGGTGATAAGGCGTTACCCAAC

ara3

lac1

con2

D54

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGACTTTTATCCCTTGCGGTGATATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

con3

con3

lux1

D56

TACAACGTCGTGTTAGCTGCTCCCTATCAGTGATAGAGATTGACTTGTGAGCGGATAACAATGATACTTCGTGCAATTTTTAAAATTAAAGGCGTTACCCAAC

tet1

lac2

con0

D57

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACATAGCGGATACTTCCTGATATAATTCGTGGTCCATATTGCATCAGACATTGTACCCAAC

lac1

ara2

ara1

D61

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACTTGTGAGCGGATAACAATGATACTTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

ara2

lac2

con1

D70

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGACTATTTTACTTCTGGCGGTGATAATTCTTGCGACAAACAATAGGTAAGGCGTTACCCAAC

con3

con2

lux2

D71

TATCACCGCCAGAGGTAAAATAGTCAACACGCACGGTGTTAGACATAGCGGATACTTCCTGATATAATTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con3

ara2

con4

D72

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACTATTTTACCTCTGGCGGTGATAATTCGTGCAATTTTTAAACCTGAGGATCGTACAGGT

con0

con2

lux1

D62

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACTATTTTACCTCTGGCGGTGATAATTCCACCCCTATCAGTGATAGAGAGCGTTACCCAAC

con0

con2

tet1

D64


con0

con0

lux1

D65

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACTATTTTACCTCTGGCGGTGATAATTCGTGCATAGCATTTTTATCCATACGTTACCCAAC

lac1

con2

ara2

D66

TACAACGTCGTGTTAGCTGTATCACCGCAGAGGTAAGATTGACTTTTATCCCTTGCGGTGATATAATTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con4

con3

con4

D68

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATAAATACCACTGGCGGTGATACTTTTGGAATTGTGAGCGGATAACAATTTCACACAG

con0

con1

lac1

D69

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATTTATGCTTCCGGCTCGTATAATTGAATACCTCTGGCGGTGATAAGGCTTACCCAAC

con4

con0

con2

D73

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACACCTGTAGGATCGTACAGGTATAATTCCTGTAGGATCGTACAGGTAAGGCGTTACCCAAC

con4

lux2

lux3

D83


con4

con2

con0

D77

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATAGCGGATACTTCCTGATATAATTCCACCCCTATCAGTGATAGAGAGCGTTACCCAAC

con4

ara2

tet1

D78

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATAGCGGATACTTCCTGATATAATTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con0

ara2

con4

D79

TACAACGTCGTGTTAGCTAGCCTTTCGTCTTCAATAATTCTTAGACATCCCTATCAGTGATAGAGATACTTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

con0

tet1

con1

D80

ACATAGCATTTTTATCCATAACCTGTAGGATCGTACAGGTTTACACCTGTAGGATCGTACAGGTATAATTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

lux3

lux2

con3

D81

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACAATCAATGTGGATTTTCTGATACTTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con4

ara1

con4

D85

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACTTGTGAGCGCTACAATTTATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

con0

lac4

lux1

D94

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACATAGCGGATACTTCCTGATATAATTCGTGCAATTTTTATATCACCGCCGGGGGTACAAC

lac1

ara2

con3

D95

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACACCTGTAGGATCGTACAGGTATAATTCGTGCAATTTTTATATCACCGCCAGGGGTACAAC

ara2

lux2

con3

D96

TACAACGTCGTGTTAGCTGTATCACCGCCAGAGGTAAGATTGACATTTATGCTTCCGGCTCGTATAATTGAATACATCTGGCGGTGATAAGGCGTTACCCAAC

con4

con0

con1

D86

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACATAGCGGATACTTCCTGATATAATTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

lac1

ara2

con4

D87

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACACCTGTAGGATCGTACAGGTATAATTCCTGTAGGATCGTACAGGTAAGGCGTTACCCAAC

lac1

lux2

lux3

D89

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACCCTGTAGGATCGTACAGGTATAATTCGTGGTCCATATTGCATCAGACATTGTACCCAAC

con0

lux1

ara1

D90

TACAACGTCGTGTTAGCTGCAATTGTGAGCGGATAACAATTGACTTGTGAGCGGATAACAATTATAATTTGTGGAATTGTGAGCGGATAACAATTTCACACAG

lac1

lac3

lac1

D91

TACAACGTCGTGTTAGCTGCCTTTTAGCAATTTTATCCATAGACTTGTGAGCGCTCACAATTTATAATTCGTGCAATTTTTAAACCTGTAGGATCGTACAGGT

ara2

lac4

lux1

D92

TACAACGTCGTGTTAGCTGTATCACCGCAGAGGTAAGATTGACTATTTTACCTCTGGCGGTGATAATTCCTGTAGGATCGTACAGGTAAGGCGTTACCCAAC

con4

con2

lux3

D93

TACAACGTCGTGTTAGCTGCCTTTCGTCTTCAATAATTCTTGACATAGCGGATACTTCCTGATATAATTCGTTATCACCGCCAGGGGTAAGGCGTTACCCAAC

con0

ara2

con4

A55

GTACCCGGGAATTCGATC

Appendix A2. Promoter library luminescence data. Clone inducers

None

Lara

VAI

Lara VAI

IPTG

Lara VAI Lara VAI VAI aTc Lara(ALU) aTc VAI aTc Lara Promoter IPTG ITPG activity ITPG in triplicate aTc

IPTG aTc

Lara IPTG aTc

VAI ITPG aTc

Lara VAI ITPG aTc

inducers

None

Lara

VAI

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

aTc

Lara IPTG aTc

VAI ITPG aTc

Lara VAI ITPG aTc

413 193 262 32334 31449 36931 10 24 10 13340 16025 18270 20066 22635 32286 20260 20844 40163 174178 155808 145397 1186 1082 621 15 10 10 856490 793790 803309 10 10 10 10 27 47 4215 3566 4164

16797 24260 29883 25931 42534 62174 10 10 10 13178 20488 28066 20278 27675 44318 15521 23224 56264 141523 204755 191217 99560 119910 73998 10 12 10 913426 1042590 1044418 10 10 10 25 10 10 2864 5181 7238

15755 24020 29793 19858 38296 53762 10 10 10 9522 19896 27544 17419 26058 41328 16958 23837 51511 126497 197808 192405 69746 125297 82381 10 10 10 891068 1027894 968853 10 10 10 10 10 21 2756 4912 7468

254 322 202 25602 36921 37645 10 10 10 142645 170909 175447 67067 108636 118836 12907 28601 39696 132513 150201 130545 886 796 705 10 27 10 787058 781287 732263 65825 65412 60912 128 227 237 2724 3904 3986

17158 27965 31682 23962 48126 58477 10 10 10 157541 232688 242808 84940 127996 144809 15748 28454 49535 140630 211466 215449 72955 112669 100395 34 25 15 931087 1029048 1064891 318294 357101 363274 195 302 281 2693 6439 7767

244 242 342 24507 35452 35794 16 10 10 131719 170105 175488 62035 115574 118101 13511 37461 41928 117117 146439 144942 1033 912 919 91 49 19 777213 773809 767107 60198 63330 62655 118 187 237 2513 4105 4384

19225 24610 31009 27115 47188 56780 10 10 29 162512 223051 240569 87293 123706 144266 16428 34003 53681 155084 208878 206250 85100 102591 103547 54 38 35 977956 1015158 1067431 333497 363325 350298 184 252 351 3533 6559 7546

186 133 116 251230 325226 309501 2364 843 1055 11505 15352 16575 19744 28818 32198 25809 332836 379339 129295 132063 122352 784 582 533 10 89556 84625 785126 725168 728163 10 10 10 43 21 10 2732 3415 3757

A01

A02

A03

A04

A05

A06

A07

A08

A09

A11

A13

A14

Lara VAI aTc

IPTG aTc

21475 30845 33337 370381 488022 498499 714 270 307 14301 26490 29301 21383 38276 46964 239170 415964 496739 161759 219729 204106 105081 110123 98947 95526 110141 107109 1081384 1106510 1117810 10 10 10 10 10 32 3810 6980 7459

19403 30346 32052 334570 469562 484921 320 253 319 12627 27845 27653 19514 41429 48579 263965 462618 547255 165980 197688 185859 108250 126579 75731 73135 99547 96322 960771 985246 1070664 10 10 10 58 63 10 3265 6965 8513

226 192 364 367697 329401 317529 925578

325 253 282 312459 328203 329149 1142542 986154

25406 31084 33950 391528 442638 560239

163884 177115 171984 99711 115127 117571 217349 374699 403526 162203 135565 131234 949 753 652 116067 96270 96066 882714 729445 762613 70117 61094 61958 191 201 211 3575 3541 3804

222660 249644 285707 110233 151564 150989 289484 459080 487548 198147 206460 232548 139434 71727 114680 108999 111565 119130 1136974 1030242 1193776 403309 364851 409043 175 402 530 4494 6954 8849

206192 235387 287866 110842 151256 150587 316371 479585 499714 202883 208115 246356 123446 69855 122769 94946 101561 112788 1093945 958702 1165630 370120 334937 385033 246 373 490 4671 7242 9065

276 191 216 305869 336910 309869 2075 989 675 12405 16906 16956 23113 30768 33017 225740 389701 409941 157007 158354 128883 1068 1210 714 92400 95131 87628 813492 867995 733053 10 10 10 42 10 10 2982 4239 4138

23793 32725 34214 428286 493064 540940

1144582 1031996 1325067 1054722 1342502 1047987 1431281 1079441 1381706

170146 183892 180289 98870 117193 122033 254611 392918 431613 174830 142296 137641 825 969 953 108385 91445 92957 891982 756230 786771 73870 62010 63984 222 241 231 3092 4581 4870

Appendix A2.

A12

274 163 303 26104 32485 34718 10 14 10 12898 15513 17738 21772 27033 36519 17015 25170 46436 142525 156262 153353 1115 938 833 10 10 10 778014 823192 762804 10 10 10 10 10 10 3554 3855 4475

Lara aTc VAI aTc

159

inducers

160


A16

A17

A18

A19

A20

A23

A25

A26

A27

A28

A29

A30

A32

A33

None

Lara

10 10 10 10 49 23 10 10 10 10 10 10 485447 472871 484700 169664 128213 133781 10 28 10 10 10 10 754790 636520 643717 10 60 20 38189 31270 49422 10 28 10 2912 2305 2612 10 13

10 10 10 20 10 10 10 39 10 10 10 10 479832 662302 688766 169658 169358 140821 10 48 10 10 10 10 734849 740892 758269 30 40 40 25441 43193 67538 10 10 10 2026 2976 4529 10 10

VAI 14 10 10 10 10 10 10 10 10 10 10 10 347310 375231 407995 139782 127219 123849 28 10 10 10 10 10 808537 649363 639816 40 30 10 31429 31370 48313 10 10 10 2754 2373 2565 15 10

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

aTc

10 12 10 10 10 10 12 10 10 10 10 10 342270 507835 603070 155617 182324 141581 10 10 18 10 10 10 698948 737286 824885 10 20 40 17532 34407 66476 10 10 41 1682 3122 4634 10 11

42 10 10 10 10 25 58585 60115 59234 81366 84083 84600 345252 444093 408216 126466 131063 128742 43 10 14 10 36 10 691434 643223 560218 20 20 40 26414 39023 50418 48 47 84 11514 12522 12037 10 10

10 10 10 26 10 10 61258 77326 93925 92805 105805 125800 487702 591223 682608 169102 167857 164120 32 101 32 58 10 10 752994 803923 844486 10 20 50 25631 53556 73941 89 111 140 12038 17596 19704 10 10

10 10 10 41 10 24 62100 56821 66803 79214 84668 84440 258766 353749 370152 118475 127069 130962 33 14 54 39 10 10 781969 592424 651860 10 10 10 21223 37342 50257 59 118 123 11441 12287 13205 10 10

10 23 27 66 60 10 58016 80080 95540 87835 111315 127923 383165 524503 639854 171037 169310 159394 73 22 62 10 10 10 713887 798193 861148 20 20 10 22217 50166 67050 101 241 132 12109 17948 20947 10 10

10 10 10 50 20 10 20 10 10 10 10 10 426615 464044 413260 127602 113013 118060 10 38 28 55 11 10 718878 567756 598942 30 10 30 26162 41439 49511 27 18 10 1850 1955 2603 10 10

VAI Lara aTc VAI aTc Lara aTc 10 10 10 15 52 47 10 10 10 10 10 10 621629 837049 812274 192869 161802 152756 18 10 48 46 57 24 828669 874886 836110 50 30 30 29627 63248 75034 45 20 16 2428 4042 4795 28 10

10 10 15 10 18 26 10 10 10 10 10 10 399312 442868 400682 130786 135940 114857 98 28 18 35 51 23 717956 682742 555015 10 10 30 20861 42224 48633 36 36 10 1504 2208 2375 26 10

10 10 10 26 22 47 10 10 10 10 10 10 440978 668409 708062 178696 149815 149711 28 38 58 10 56 86 812627 763516 823896 10 10 10 21222 58046 72148 29 43 66 2130 4011 4101 62 48

IPTG aTc 10 10 10 66 47 115 73995 73260 79696 108154 102645 108353 527378 433057 444732 133202 127393 125548 33 103 10 35 10 10 738368 670128 598252 1770 220 3110 29134 47230 52372 31 113 89 12862 11439 12348 10 10

Lara IPTG aTc 45 17 10 10 10 71 89143 107327 128377 130279 146302 178774 634274 744803 840322 203168 146681 174337 30 51 69 82 167 120 923517 842747

VAI ITPG aTc

53 10 69 115 26 42 75761 80376 88005 102986 109580 117521 430199 399763 438072 138293 127082 141750 43 53 73 10 10 99 700314 649822 1051614 713376 2110 1770 1940 2490 3521 420 39029 29728 64277 45204 82954 53038 154 82 109 131 160 116 17520 13351 16064 12847 21763 13118 10 10 10 10

Lara VAI ITPG aTc 118 29 10 37 50 111 91321 106549 137424 128692 150319 177491 525737 626876 775970 178497 136015 201322 161 81 49 72 88 167 894022 807700 1119185

2100 1370 420 36765 61286 76629 256 140 216 16549 16204 24459 10 10

inducers

A34

A35

A37

A38

A39

A40

A41

A42

A43

A44

A45

A47

A48

Lara

13 10 16 10 10 10 10 19 19 10 143 66 66 12 10 13 48832 33861 33127 10 10 22 14548 13193 13565 456504 459220 454034 10 10 10 21110 19035 17489 10 10 10 30032 19891 20070 10 10

10 10 60 10 10 12 10 10 49 29 134 74 73 26 10 11 45143 37561 51020 10 20 54 14442 17179 19344 778409 724214 900964 10 10 10 23200 25106 23499 10 10 10 25562 27590 27912 10 10

VAI 15 10 10 10 10 10 10 19 29 29 192 106 136 33 10 10 49709 33288 35400 42 10 10 14852 12333 13677 488162 387787 442190 10 10 10 21341 17570 16727 10 10 10 31319 20944 21034 10 10

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

aTc

39 10 10 10 10 10 10 19 10 59 125 10 102 13 10 41 41780 35519 43711 14 10 46 12395 15437 19382 681785 707697 861396 10 10 10 19326 24514 23137 10 10 10 22500 29218 29942 10 10

10 10 42 10 14779 16382 16554 21 27 50 278806 243061 223735 54 22 10 50363 33758 35560 10 37 10 13333 11931 11875 398500 339475 371601 1448 1789 2794 646408 578979 522669 10 10 10 22770 21542 21433 8469 10156

10 10 59 31 16375 23900 27073 10 70 52 303405 343476 334929 10 10 20 43264 41781 44641 10 10 14 13259 18147 19364 813143 718025 875867 1100 2057 2957 809931 796746 752528 10 10 10 24486 29223 32743 8063 13353

10 45 10 10 13989 16564 18197 13 80 40 269249 229239 226017 10 82 13 47882 36123 36010 10 10 20 13406 12261 12917 374866 338353 368762 1306 2039 2346 563263 522483 511062 10 10 10 20688 20602 22293 7810 9950

10 72 40 23 18149 24531 26943 59 24 122 292563 319696 331673 10 11 27 44495 41108 45085 10 15 28 14431 17983 19670 760736 737730 859277 1249 2207 2983 748879 775483 676824 10 10 10 25833 32686 34243 10536 15678

10 10 10 10 10 10 10 49 79 19 74 37 27 17 10 10 113384 96543 100081 10 10 10 72200 55196 50180 489181 447929 455762 10 10 10 19308 15158 13213 10 10 10 19489 16681 18766 35 10

VAI Lara aTc VAI aTc Lara aTc 16 10 10 10 10 10 10 49 189 139 102 91 132 27 10 10 123490 138678 149710 57 10 10 79380 74963 71164 911236 907460 984670 10 10 10 25038 22576 17149 10 16 10 24960 29027 29962 10 10

10 10 10 10 10 10 10 59 109 89 84 85 67 10 36 10 112507 95108 103773 10 10 10 73329 59064 53892 520431 440029 455082 10 10 10 14574 15206 13433 10 10 10 21085 21546 19198 10 10

49 10 41 25 10 10 10 49 159 78 102 73 162 62 16 10 110509 131223 144873 21 10 58 77412 70911 73115 806504 869454 997468 10 10 10 22931 20089 16949 19 10 10 26285 30002 29429 10 10

IPTG aTc 10 20 43 10 18478 19001 19663 132 106 104 275413 252511 263525 10 10 10 102260 95805 109092 37 53 10 68720 55614 57616 503113 394978 428673 1883 2387 3183 625305 531058 518761 10 10 10 20501 20099 21139 8541 9822

Lara IPTG aTc

VAI ITPG aTc

Lara VAI ITPG aTc

10 19 19 55 27920 23763 33453 121 273 202 398232 387467 450786 12 46 10 122733 131080 165081 32 10 10 86902 70467 96726 866083 906539

12 10 10 29 19440 20386 23313 113 75 112 268581 257269 272922 10 18 81 94728 94129 109761 10 10 10 66829 58649 63734 446201 408207 446180 2096 2855 3366 602017 531058 547981 10 10 10 22461 21047 23923 10242 10111

10 86 39 10 27804 25111 36746 106 178 110 366988 353890 460726 15 28 10 109968 129907 168934 12 10 21 82368 73730 113756 806224 884031

1115063

1864 3524 3734 952141 565941 819686 10 10 10 31810 26373 36181 13933 13270

1129179

1869 3553 3598 808882 598077 1013806

10 10 10 31182 29659 41229 13186 14359

Appendix A2.

A46

None

161

162


inducers

A49

A52

A53

A54

A56

A57

A59

A60

A61

A62

A63

A64

A65

A66

None

Lara

15 30 10 17 10 50 60 5243 2364 3150 10 10 10 10 10 10 24318 15261 16995 1224 10 42 40 20 30 167203 134766 125158 6603 2485 2587 10 28 10 5353 2774 3321 155595 81476 100157 4332

14 10 10 10 27 90 107 12363 9798 6939 66 67 13 10 10 10 15860 19900 24243 101 10 15 10 20 10 131340 142288 150639 3557 3605 3714 18 39 10 55752 50575 56452 88798 95897 123406 1551

VAI 10 10 34 14 86 70 49 3025 2482 2759 10 10 14 10 10 10 23092 15732 16873 213 10 10 40 10 10 177793 142933 142697 4930 2884 2524 10 10 38 4207 2693 2980 127940 89926 106303 1966

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

aTc

10 49 15 22 10 70 47 12053 10248 5725 69 10 24 10 10 10 14348 18484 23880 42 10 10 20 20 10 116822 136413 154342 3299 3766 4313 10 10 10 49083 53783 59784 91449 94516 133235 1001

9762 33 21 34 36845 30020 32266 333721 327386 359109 31715 23243 19634 10 29 10 14542 15954 16214

16993 43 58 85 28712 32346 36422 573768 536833 520390 82021 88040 86833 37 10 10 13290 21520 23120

11282 52 63 30 30194 29839 30024 354186 332130 354099 32235 22855 21820 10 10 17 15166 15423 16966

17134 70 56 64 28784 30275 35357 509158 483932 445815 84558 91955 85722 10 24 10 16105 21882 23836 858127 727532 615499 20 10 10 131862 154671 163554 3326 3723 3702 79 78 67 47061 54299 58253 96339 119704 140145 608570

10 38 10 28 56 99 19 3090 2430 2418 84 10 18 304 264 186 63438 52654 52017 72 10 32 240 260 340 120627 109067 118342 2828 2310 2478 10 10 10 3083 2453 2920 88216 88938 104509 2424

1045453 1283105 1010589

824804 517585 20 10 20 115313 131749 117495 2849 2496 2288 57 47 10 3319 3031 2828 90498 88932 98965 589321

764994 682799 10 10 10 116506 137814 156365 3339 3806 3453 98 10 77 52457 56732 60515 82602 110531 131098 669868

627301 596102 30 10 10 126109 124445 140813 2817 2677 2744 10 47 57 2300 2420 3217 94467 95091 111248 525651


10 35 36 36 67 29 68 2020 2508 2436 33 17 10 325 309 285 60689 62506 53267 10 10 10 540 90 270 138223 131115 131576 2585 2646 2356 10 18 10 2433 3080 2829 84331 103134 111698 1946

10 16 63 40 27 105 91 12680 4804 4360 225 145 122 333 457 444 61594 67343 73101 78 24 34 220 290 500 133303 149449 168333 3787 3564 3541 39 10 59 50908 45228 51817 96347 122289 143779 1196

IPTG aTc 10783 50 10 62 45023 36985 40772 328207 352449 386153 57536 47011 47970 324 320 343 62371 56991 59447 978044 564517 522508 34379 48738 53206 136709 114498 123321 2965 2629 2417 47 67 10 3248 2668 2703 88535 99380 115816 769602

Lara IPTG aTc

VAI ITPG aTc

Lara VAI ITPG aTc

18271 115 126 88 43242 47090 56921 587455 479485 683162 164983 131459 174634 261 275 448 73800 65660 96802

12443 48 51 98 39049 35658 41391 348218 407566 408393 57518 49218 51527 340 313 406 62829 58456 64926 958678 592498 618710 25825 52218 36733 148784 131800 148578 3153 2646 3253 67 87 87 2657 2925 3532 99345 107377 127652 689441

18666 64 73 101 36395 44151 56055 609377 454020 772494 161504 133607 197197 485 333 461 71162 66441 104464 931524 492615 939106 85459 63608 55719 158756 169382 225686 4132 3941 4932 47 10 83 58475 56112 79053 116951 132037 181937 749832

1139498

384038 737159 57536 42974 116713 148230 147747 187153 3804 3604 4787 87 48 74 61211 50412 73801 117017 121067 161679 847330

inducers

A67

A68

A69

A70

A72

A76

A77

A78

A79

A80

A82

A83

A85

Lara

2224 3081 216 60 83 303673 282570 263494 611 177 60 10 10 10 3109 1962 2455 15 10 20 53441 34012 34098 10 31 10 482 353 253 10 10 10 10 10 10 8511 5028 4557 4558 2431 3525 4030 2164 2270

1820 3396 50 116 186 377799 403516 396370 181 75 115 10 10 10 2744 3292 3753 20 41 19 41063 39542 45489 10 36 10 82996 82488 83026 10 10 10 10 10 19 6039 6109 6900 3393 3782 5193 3123 2712 3057

VAI 1773 2300 247 24 103 303073 259693 267507 422 81 109 10 10 10 16802 10169 9090 10 20 10 46367 34271 32518 10 10 10 442 333 233 17 10 10 10 10 22 6199 5488 5378 3228 2790 3504 3572 2573 2719

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

aTc

1020 2293 52 59 250 271585 334269 377766 129 77 199 10 10 17 12988 14136 11713 52 10 18 35528 38545 43120 10 10 10 58519 71843 82925 10 10 10 10 10 10 5808 6069 7901 3293 4330 5263 3034 3393 3577

617453 618526 53 65 10 261222 280971 253424 15075 17374 18381 21 10 10 3036 2579 2218 88 19 10 39934 35174 29421 30 10 46 351 401 231 49 10 10 204215 222253 227704 5963 5399 4978 2975 3034 3518 2961 2121 2100

694458 800142 99 56 173 329063 357491 381122 12713 20196 24285 98 10 15 3013 3609 4392 50 28 37 38011 41771 42400 78 89 10 49101 68722 74337 25 10 18 228804 299562 310753 5528 7317 8427 3238 4602 5404 3081 2517 3646

528991 566012 108 24 52 238101 262130 237121 16960 17879 20310 10 10 10 16138 10433 10975 39 10 49 36725 32229 32456 31 31 25 353 313 372 40 10 29 164965 225170 225107 5559 5269 5659 3365 3155 4207 2652 2693 2897

641043 727988 11 87 50 317394 349201 356758 15774 22522 24230 31 10 76 12631 13323 13747 51 48 57 38221 42022 42329 10 10 32 52248 65204 73862 10 10 24 223041 261905 300222 6150 7854 7728 4104 5572 5835 3343 3229 3677

2740 3088 81 59 71 314049 272935 259317 143 72 34 34 10 10 6596 5896 6658 249 300 210 41826 33015 30550 170950 134595 129882 323 210 211 10 10 10 10 10 10 4958 4998 4747 5284 6126 6727 6105 3513 3630

VAI Lara aTc VAI aTc Lara aTc 2384 4183 82 154 91 544066 471414 435991 94 44 61 10 27 16 8177 9939 10942 189 308 347 44167 44201 44268 419249 421167 412329 89211 89892 83919 10 10 10 27 10 10 6408 7780 7279 7225 9167 9798 7036 5638 5297

1797 2577 82 136 110 370628 291326 266765 94 77 10 10 11 10 16975 15242 14263 189 329 290 37226 36724 32157 159426 138267 128983 304 309 211 10 10 10 10 32 12 5498 5058 4537 5922 7106 7209 6665 4681 5110

2532 3476 100 86 55 402426 427476 423537 158 53 62 10 10 10 20346 14358 16675 250 380 448 42131 42758 44160 371118 373914 393732 70978 71301 74305 10 10 44 29 19 10 6538 6488 6979 7976 8476 9788 8459 5991 6098

IPTG aTc 670100 742105 62 122 84 359425 288422 265210 15436 19548 21168 10 10 10 7039 6880 7081 257 248 228 40702 34659 34209 151182 128840 135074 544 390 318 57 86 70 234457 249418 247220 5427 5204 4904 5505 6409 7410 5245 4511 3770

Lara IPTG aTc

VAI ITPG aTc

925732 615608 1066294 727997 10 121 28 54 102 31 516823 331227 425233 271546 498076 295664 18285 18330 22011 19001 28893 23496 27 10 10 10 10 10 10184 19856 9797 15774 12565 16664 255 327 297 228 289 306 50859 39717 43845 35643 58367 39267 397646 136853 369516 127634 488181 142616 76991 288 66541 282 104128 335 10 32 10 71 82 51 290243 227816 316187 237360 370082 268177 7939 6368 6733 5236 9277 6171 8926 6654 8280 8139 10869 9059 8435 6215 5597 5771 7054 4998

Lara VAI ITPG aTc 821862 1054528

181 114 190 458934 429750 501301 19365 23576 34242 61 20 10 22113 15263 21613 415 316 646 48629 46800 68292 364935 359324 519545 67849 70337 117193 24 149 10 254993 314290 356509 7044 7414 10941 9287 10353 13590 7985 7930 10288

Appendix A2.

A81

None

163

164


inducers A86

A87

A88

A89

A90

A95

A96

B04

B05

B10

B11

B13

B14

B16

None

Lara

110158 80194 101140 830 685 511 27 38 10 10 13 13 10 18 10 10 10 10 10 10 10 10 10 10 20 30 10 28 48 69 162 79 138 39 10 38 5665 7261 7512 77 57

85386 92765 113867 154 183 119 10 38 10 12 32 41 10 10 26 10 10 10 10 10 10 10 14 13 10 10 10 18 10 10 30 40 19 33 10 10 3115 2866 2314 27 47

VAI 99482 85112 109343 982 364 290 27 18 10 10 10 13 10 10 38 10 10 18 58 10 10 10 10 10 20 70 10 10 18 10 89 91 79 10 10 16 7746 6540 7270 57 10

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

84686 90877 126600 174 103 147 18 10 38 12 10 51 27 10 10 10 10 10 10 10 10 10 10 14 10 20 30 10 17 18 40 69 59 10 10 10 2114 1954 2013 27 27

96432 93730 100051 65349 61438 62266 67 10 10 52 23 10 18 10 10 3048 2478 1568 10 10 10 368497 351587 306198 10 10 20 10 10 20 9677 8063 9523 10 10 10

96361 118678 130448 66127 69906 86034 67 66 33 22 11 71 37 36 16 2508 2958 3177 10 10 10 243538 225836 236113 10 10 10 10 10 10 10487 9515 6250 10 10 10

89962 85396 120116 65188 61268 70625 57 47 46 12 13 13 28 28 18 3038 2438 2158 10 10 10 315461 297852 309276 10 10 20 29 10 50 9397 9286 9995 10 10 10

86573 109921 127965 59944 74524 81035 48 35 44 52 61 61 47 56 10 3579 2827 2267 10 10 10 243720 247981 217828 10 10 20 10 10 10 12381 11970 14221 10 10 34

aTc

90662 87862 103775 503 414 351 14 11 11 23092 39913 41032 15 48 10 28 10 10 10 10 10 10 10 27 10 10 10 152166 158167 170239 69 66 115 24 10 10 2422970 2471654 2451402 2509650 11536 1781722 2691458 2584312 2814416 9331 2198997 3023759 1614853 2754390 12758 34 74 42 83 2846 67 27 26 42 4028


90124 100621 111604 353 261 260 31 11 51 38543 38806 41504 44 68 10 10 10 10 10 10 10 15 21 10 10 10 20 139109 179522 198897 33 104 141 14 30 10 9041 7646 7425 3236 4327

88195 108558 128182 164 100 147 52 39 57 35258 49872 59428 57 34 39 10 10 10 10 10 10 36 10 32 60 40 110 181334 145668 173582 96 41 37 50 25 36 2851 2594 2795 2536 3375

IPTG aTc

Lara IPTG aTc

VAI ITPG aTc

Lara VAI ITPG aTc

85952 101555 107020 68809 66925 71375 59 50 68 44005 38356 45122 91894 99997 104716 2347 1587 1407 18 10 10 339622 341269 329911 196212 71922 191378 109491 185039 188245 7995 11040 12534 10 10 10

107893 126606 153987 78737 85334 99863 156 34 89 49377 54512 68427 108679 112951 137229 3528 1677 2457 10 10 10 406690 320570 273955 250294 161502 384085 201558 152408 183266 11890 7420 7147 10 10 10

90490 104333 121063 61701 68321 80458 80 10 56 41375 39301 46722 99742 103517 116631 2867 2147 2227 10 10 10 310647 325836 340246 96323 153237 151709 191355 195835 209025 13505 12192 11058 10 10 30

102326 127657 155595 79113 85953 112322 96 84 85 44883 51284 74070 104115 115889 142043 3538 2167 2966 10 10 10 310628 283128 226322 162405 186105 22883 195105 172578 181691 11342 8861 8540 10 10 10

2863449 3211668 3481556 2938677 2992939 3430892 3213402 3338558 3456947 3939473 3107916 3421408

3786 4436

3082 2776

4170 5229

3049 3733

inducers

B17

B18

B19

B20

B21

B22

B23

B25

B26

B27

B29

B31

B33

Lara

57 38 18 10 1062 764 883 25 12 10 5542 80 70 104822 89760 67802 10 10 28 10 10 10 37149 35623 41943 9067 8977 10629 10 10 18 5971 6923 7954 5740 2988 2127 308 389 359 242

27 48 28 28 868 1258 898 10 10 10 220 150 130 599651 638020 588067 10 10 10 10 10 10 35681 27381 34155 12565 11304 11454 10 18 10 5421 4740 5291 6841 5950 5100 658 588 579 25492

VAI

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

aTc

27 10 10 38 882 754 854 10 10 10 330 190 130 91830 82749 72446 24 16 10 10 10 10 48400 39898 53752 10388 11171 14235 18 10 10 7053 6402 8965 4468 3418 2497 648 458 409 214

57 10 10 38 1068 1028 1210 10 10 10 60 160 130 642216 627760 590710 10 10 10 10 10 10 35219 35109 37574 12364 9309 11553 10 28 18 5561 5101 5982 6691 6651 4859 518 438 439 23748

34 7243 5860 8913 920 775 954 43 44 10 60 180 230 106791 94913 69536 10 35 83 10 10 10 46190 42971 43680 416024 384408 547701 62 10 23 8454 6191 7382 3136 3129 2449 64141 52710 46338 123

45 9964 9591 9731 777 907 798 10 10 10 90 290 330 606844 658690 619195 10 10 10 10 10 10 33443 32343 28861 595522 658449 694813 21 17 14 5869 5789 5990 6253 6413 4421 48555 49008 44071 16171

34 8494 7786 6485 1185 1213 854 10 10 10 40 90 80 89987 86194 77121 16 17 10 10 10 10 42395 49036 55155 502673 545849 316645 10 10 10 8093 8403 7993 2827 3367 3147 61908 60918 57120 177

87 10757 11998 10794 1013 1029 1328 10 10 10 190 120 170 683246 683122 626551 10 10 10 10 10 10 38019 38878 45827 603417 540409 679906 31 10 31 6901 7410 8252 6870 7992 7120 58403 58361 64161 18947

2866 37 27 37 1051 1053 879 476286 412135 483187 8085 9297 12743 97267 95781 79985 79282 88764 55888 10 10 10 51163 87457 55893 14355 15501 18646 27 37 26 8995 10428 7683 2888 3419 2378 640 597 363 124


2835 27 47 57 1348 1281 1260 378925 419074 532220 11641 10168 29673 97003 85751 65847 96222 79290 57209 10 10 10 57489 80334 56479 12921 17488 21065 47 37 46 9386 9897 9095 3109 3999 2506 631 504 193 209

2945 67 17 57 1336 1610 1661 420400 453303 450014 10098 18819 10379 705767 620804 615686 80855 61769 60441 10 10 10 44672 56125 52786 14527 18175 17093 17 67 10 7623 8645 8705 6162 5450 5630 607 558 465 33624

IPTG aTc

Lara IPTG aTc

VAI ITPG aTc

Lara VAI ITPG aTc

4657 10070 11969 12579 1216 1083 1434 498989 555260 570709 23476 19421 29854 111044 92461 98827 95786 69357 83657 2917 1491 1905 60935 80884 63245 696428 695500 861907 10 71 10 10816 11578 12510 3944 3485 3804 75549 64834 68086 178

3505 12860 12753 13202 1092 902 2068 510272 405659 468687 21840 19562 49414 757933 643670 742617 79458 54995 74006 2335 1683 1971 48018 59086 57864 630619 700892 949452 10 73 27 7550 7832 9994 5939 4431 5897 61734 55628 70623 22225

4345 12036 13041 12830 1601 1502 1547 589383 560535 542705 13294 24761 16031 100037 79839 84576 113267 79188 75701 3171 1646 2151 54727 78031 66211 841298 753252 751564 68 56 10 10726 11808 12409 3493 3865 3463 72205 61305 73426 162

3963 11805 12364 13759 1252 1178 1431 472911 467901 481706 16121 28608 31322 738342 608707 731238 78582 63904 76791 2678 1846 2800 53480 64718 68370 710182 772604 866668 43 112 10 8982 9012 11066 6508 6040 7287 71157 64106 79628 23707

Appendix A2.

B30

None

165

166


inducers

B35

B37

B39

B40

B42

B43

B45

B46

B47

B48

B49

B50

B51

None

Lara

VAI

125 78 112 130 89 81993 63703 70598 39 19 10 2108 1048 1479 3589 5351 5241 7333 4290 4170 40 10 20 10 19 29 36 10 24 10 10 10 925 949 1348 868 1178 1268 14 10 25

19745 16051 151 192 60 73170 53484 56410 29 10 19 1729 1399 1709 4639 3769 4060 4850 3640 2699 10 27 17 39 49 10 66 35 58 10 31 35 1173 733 1050 1025 836 1056 127 67 97

136 138 79 121 100 83178 77342 96923 49 10 19 1388 1369 1489 5340 4980 6412 6953 5291 3349 10 20 10 19 10 19 10 10 15 29 10 10 845 926 1103 1158 1108 1697 24 16 10

Lara VAI 18612 14888 142 130 110 77100 73869 70730 10 10 19 1449 1459 1559 4069 4029 3890 4220 3840 2979 10 10 17 19 39 10 48 28 48 10 10 10 817 1041 1080 956 866 1116 37 57 87

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

aTc

76 154 180 180 90 66680 86725 77021 10 79 16 4648 4438 5590 6360 5249 5770 6710 6032 3601 38 18 10 10 20 32 10894 11145 13035 147 127 157 949 1097 1186 1119 1347 1527 15064 20541 26573

14898 10859 175 106 132 70327 72380 73082 10 10 10 5801 5250 5379 4078 4348 4519 4611 4630 3581 65 55 10 34 36 22 98799 88450 63415 44 228 135 952 780 1198 897 966 1288 60131 63607 70250

78 151 131 100 119 90317 85331 98717 57 55 18 5798 5981 5386 6110 5499 6170 6640 5739 5880 10 28 28 10 30 61 12217 10092 11874 126 167 117 1368 1138 1376 1277 1166 1334 23813 26014 19897

17552 15836 205 145 104 82191 85333 69314 109 37 52 5807 7832 7679 6039 5288 7030 6620 6401 6209 54 45 45 34 24 37 107622 101078 76363 285 248 187 974 1050 1361 1039 1146 1454 71706 68287 88012

141 72 6859 5766 5477 78626 106161 84454 18 10 18 1778 2208 2069 5420 6571 5511 5158 5637 3216 67 17 27 87 56 46 13 10 10 10 10 66 826 1450 1214 61585 65141 66719 25 64 34


171 152 5189 4826 4067 86552 123278 80184 58 37 10 2178 2408 1969 6051 7332 6872 7179 6458 4447 46 46 57 107 106 55 23 17 29 16 36 25 1004 1546 1233 67458 76242 77195 44 42 81

25988 27460 6181 2527 3017 73421 85000 81949 58 48 28 2359 2099 2149 5750 5750 6581 5707 4687 4947 40 42 32 154 85 84 62 73 62 11 66 10 1199 1078 1132 62654 71562 69113 96 174 145

IPTG aTc 204 272 6070 5854 6737 80489 90056 86278 70 15 97 7018 8418 8768 7741 7742 8833 8235 4944 6504 43 84 74 175 45 65 14205 18667 20157 114 282 231 1316 1390 1420 73457 79661 83905 29191 32693 35296

Lara IPTG aTc 15572 24441 5417 3935 5294 86155 59179 86364 38 38 49 6469 7089 8227 5179 5599 6839 5065 3656 5643 69 92 79 95 75 70 116979 73076 90830 199 247 209 903 1655 1581 60709 65399 67812 71815 93157 106928

VAI ITPG aTc

Lara VAI ITPG aTc

146 276 9828 5426 4966 81178 92711 97721 28 97 35 7467 8147 9218 8482 7792 8391 8005 6206 6974 93 84 44 103 115 85 23253 19906 19473 241 181 251 1083 1947 1418 85426 91138 85017 31469 36150 36816

18149 26044 4648 3053 3270 83484 95423 99882 43 74 10 7457 8038 9687 7110 6200 8451 7084 5485 8353 69 81 108 116 153 58 118685 84465 104971 122 173 150 1148 1200 1792 65597 69361 76808 89897 101754 112417

inducers B52

B56

B60

B61

B62

B63

B66

B71

B72

B73

B77

B79

B80

11800 8124 7834 1880 2000 1490 5048 2995 1094 2800 1090 1510 76 17 47 20102 17203 17243 19 29 19 32 10 10 499 249 219 410 300 370 10 20 40 13 10 10 38695 38856 25745 82 92

Lara 5361 4300 3950 1070 780 760 333492 280938 202623 140632 107125 119834 34 10 18 12953 11450 10908 49 29 10 33 10 32 122 71 85 306 202 300 10 30 30 14 25 25 34871 30538 29653 42 23

VAI

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

aTc

11460 6722 6432 2370 2010 1740 3696 2766 1635 2260 1270 2030 26 10 10 19149 15298 18196 19 10 19 10 10 10 459 239 239 510 270 470 10 10 10 10 10 14 36984 44526 34992 122 32

3299 3490 3279 830 770 610 238029 262539 216945 113298 97319 106748 10 81 10 11690 11029 10748 19 19 19 10 10 24 69 35 102 411 373 412 30 20 30 10 14 15 39510 32568 31442 62 23

71260 71461 64541 56143 47327 69483 6241 3968 1709 1950 1820 1470 165 106 185 22768 19988 25970 19 29 39 10853 9052 4660 102644 106582 129195 659 659 729 10 29 29 145 67 160 47221 41942 28042 22671 22270

59574 62675 65009 65710 69452 64002 223161 211744 136559 105099 120732 127000 168 45 134 14826 16299 15606 37 36 86 17094 15632 11721 149103 161647 123482 1021 918 807 47 46 36 14835 19428 18287 39826 38426 32532 14730 14701

76036 67515 89198 57244 58304 51542 6270 4267 2225 1490 1460 2340 155 136 146 22456 20168 18332 39 29 29 9421 8615 6856 109332 109271 107764 619 629 749 10 10 10 57 95 78 40895 45063 38147 24058 32064

77031 69793 75833 79122 74250 82943 210843 199866 113437 93671 110455 112635 110 127 76 15867 16749 18371 17 27 57 18281 16311 14434 160249 143891 134131 943 760 1250 47 36 36 15146 14845 15316 39575 39796 37551 16815 17016

8334 8905 7063 2510 2480 1910 3526 2151 1636 1139 2728 1748 26 35 25 20633 20292 22329 908 958 788 10 10 21 386 266 345 340 400 450 20239 21133 21054 46 10 77 101932 95853 78926 37 69


7964 9034 5931 2350 2290 2250 3725 2047 1270 1508 2188 1688 65 33 42 19881 20392 25562 1387 1057 968 24 10 10 286 206 175 370 420 450 21063 22538 23955 19 10 10 113294 102990 83950 56 69

4800 4280 4620 1090 1190 1310 316942 114639 205681 107673 146642 132281 19 70 83 13723 14706 15267 1138 968 1028 17 18 10 31 156 70 322 545 367 13431 11677 13001 20 23 42 110387 89843 98426 56 52

IPTG aTc

Lara IPTG aTc

VAI ITPG aTc

Lara VAI ITPG aTc

91593 94120 99546 60950 91183 109223 7486 2044 2444 2308 2738 2828 192 370 319 25003 30427 32306 1537 987 1577 11985 6530 6762 101887 148982 177755 629 679 729 23942 29431 32878 96 214 205 148784 95769 116870 24537 17604

74904 78719 91283 78322 70940 87650 268506 145927 173275 128071 144706 173510 204 179 283 16557 17968 20653 974 1074 1073 20596 12112 12553 204848 140217 166331 987 1094 1149 13410 10646 14179 19278 20791 26574 124024 92255 123011 16833 16675

93124 98031 102944 81291 101731 116254 5823 2167 2293 1628 2318 2708 150 258 280 29221 29009 28085 1387 1207 1177 13079 8022 6170 167638 161820 168564 609 829 949 27095 28346 30626 151 143 160 121164 102013 104830 28941 21666

87704 86849 104538 92940 86818 103756 254887 164287 280327 111757 133508 162722 85 160 173 18941 18868 21144 1144 1125 1253 21007 15276 16303 158406 136367 133492 1040 886 1361 13581 11610 16085 17813 15161 22850 120810 99027 130097 19323 16875

Appendix A2.

B78

None

167

168


inducers

B81

B82

B83

B85

B86

B91

B92

B93

B95

B96

C01

C03

C04

C05

None

Lara

VAI

55 18 10 20 25 37 42 17 10 18 10 10 20 10 60 10 1223 1023 766 10 11 51 55729 48900 47307 210 160 100 60 10 10 40 130 10 65 36 34 140 200 160 101

34 10 41 10 35 24 10 14 10 26 10 50 30 30 30 40 1494 1185 1215 10 35 10 92645 80510 63122 50 70 50 30 10 10 40 60 90 95 76 26 240 100 110 131

33 46 11 10 12 10 40 10 10 10 20 10 20 10 40 20 1204 822 744 10 10 31 61678 41393 47851 190 160 90 30 10 10 30 60 130 106 26 76 240 220 210 826

Lara VAI 33 10 10 10 10 10 24 14 10 10 40 10 10 10 10 10 1153 984 1015 10 10 10 84373 80287 71405 40 40 90 10 10 30 100 31 100 66 46 76 260 210 130 727

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

15832 243 220 141 10 43 33 21 21 30 1819 1779 1669 7353 6342 4830 1504 1206 1150 10 10 10 178806 196635 200242 72083 73501 86037 10 37 25 60 30 90 116 46 56 80 190 200 231

11607 20020 19885 16517 10 88 11 31 82 16 3124 2934 3014 33321 33783 32948 1297 1336 1168 41 16 18 380672 350882 289563 101040 95540 90482 13 14 25 60 130 110 66 56 76 200 180 210 131

19049 367 235 237 12 10 41 12 10 10 1569 1939 1739 5962 6252 5961 1516 1335 1117 39 27 79 154150 215978 216455 69270 69240 82000 10 10 86 40 80 50 76 26 56 320 260 320 780

20557 21521 23243 29310 37 51 48 40 10 32 3044 3384 3164 35895 34527 35654 1467 1386 1317 28 23 22 400042 369362 309497 98193 103929 100318 13 22 33 140 90 170 56 96 66 310 310 340 729

aTc

VAI Lara aTc VAI aTc Lara aTc

54 24 13 44 14086 14088 15133 14311 15886 12999 40 40 40 70 20 40 710238 648332 542969 10 10 10 59596 70535 66054 226 156 86 8946 7254 6573 392773 419649 463745 974720

114 10 22 24 16852 14736 15937 17549 15423 14863 30 40 50 40 10 50 659576 598927 506603 10 34 10 64012 72509 65943 185 146 76 9407 7404 6733 472410 436675 475738 972251

48 12 67 87 17840 16228 13308 18799 17125 17566 30 30 20 60 120 50 741043 621928 639468 10 10 10 107929 84647 88391 85 86 66 10369 6483 6763 334953 354708 376691 788248 1021409 894320 1101966 882765 1821 1810 2285 2025 2049 1983 26094 22288

90 102 58 57 18069 13960 13849 20163 16784 16072 40 30 40 50 20 60 677057 576389 582843 55 27 10 104916 80125 85956 64 46 56 10108 6553 7614 350106 349722 353566 831049 1070064 877472 1035690 915434 2123 2076 2117 2234 2093 1967 30478 24306

IPTG aTc

Lara IPTG aTc

VAI ITPG aTc

19915 329 244 429 120374 151450 156088 122375 136534 172879 2179 2289 2589 6251 5421 5621 685982 527443 592413 10 10 45 195672 265666 285754 73570 126994 127465 52768 65171 77638 393336 361572 434317 946944 954432 991001 23066 22460 21159 169753

21149 27735 21263 26843 231782 151602 194917 240070 166995 204294 3824 4105 4454 37686 34527 41773 802074 619753 738689 10 29 34 411392 300176 373333 136364 112195 102370 88891 65446 82365 369388 371431 341640 864680 913014 951096 13621 14341 12429 175342

23783 591 384 323 174008 147931 150325 169020 147748 164764 2609 2179 2849 5520 6021 6501 696730 515162 523765 73 42 10 240134 262834 261111 95881 120203 130318 74250 64221 73860 391452 425192 422569 872338 889117

Lara VAI ITPG aTc

19683 25106 22015 26845 214533 144269 187064 224566 156456 204147 3465 3455 4243 33431 35433 47789 734656 599440 765685 10 10 11 408419 303919 369601 129917 104856 122394 84631 62758 82249 346090 394314 281764 811638 918281 1003269 951354 19928 14367 21260 14495 26410 12764 171807 168558

inducers

C06

C09

C11

C12

C13

C14

C15

C16

C18

C19

C21

C22

Lara

171 111 171 241 241 1337 1408 2396 693302 721211 789651 720065 754726 877937 9551 8345 9442 186 157 86 8094 9466 8565 7590 9154 8962 147 105 122 171 321 91 147 118 256 7844 7303 7674 4880 4951 5598

151 131 251 301 131 1767 1577 1507 630551 624628 661947 686573 683093 759955 8712 7794 8201 197 187 127 7364 7755 7274 7821 7580 7742 166 60 140 221 171 141 257 126 86 5821 5631 6152 4795 5001 5099

VAI 721 761 149191 121321 121545 1637 1488 1368 651194 614291 704477 645911 689158 880845 9301 8362 8677 156 196 136 9237 9937 9087 8120 9725 8932 104 201 161 719 632 461 147 148 167 6692 6293 7203 4857 4592 5954

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

aTc

692 803 142901 113957 108710 1477 1127 1347 552732 573249 603931 624969 619927 679319 6749 6272 7339 177 88 227 7434 7945 7234 7620 7911 8071 125 133 201 571 593 833 136 166 116 5201 5081 4851 4917 4540 4967

141 251 191 201 431 29510 29018 28464 637635 714039 729464 655207 841702 879736 9674 10024 11675 227 196 306 6904 8985 7745 7281 8813 7731 124 73 183 271 241 251 1317 1277 1107 7231 7081 7281 4576 5562 5212

171 261 281 211 271 31691 33721 32675 591905 618778 667639 658772 650016 749973 8539 7672 9651 377 207 276 7504 7845 7044 8131 8031 7881 79 149 118 301 351 381 1935 1815 1745 6429 6599 7240 4918 5053 5124

701 773 124649 116844 110107 29370 27722 29611 601858 609017 647666 617084 702175 794973 8751 7347 10421 207 267 306 7955 7944 8496 7712 8983 8612 201 176 202 742 563 773 1107 1207 1127 6560 6841 7280 5020 4882 5288

638 808 131602 134375 137309 31701 29198 33128 561011 560293 594784 600992 616187 705440 6922 6869 8358 247 227 206 7064 8205 8356 7861 8181 8851 205 105 170 808 899 868 1855 1635 2185 5920 5648 6239 4318 4854 5140

29218 26827 717 816 667 22338 23391 24554 711617 761459 789063 732130 795730 946731 13853 14989 16817 377550 436359 425493 210069 252069 216162 203198 243491 204034 202 211 192 531 521 381 154 153 202 79794 92638 89887 9125 10321 9444


32502 28895 150303 133897 127879 22246 21654 24343 652787 729671 711012 747813 858444 818592 13246 13237 14368 433864 448194 415802 248651 255692 211068 247096 251858 207386 187 213 181 1067 938 1100 134 153 262 88790 98727 87827 9941 10789 9650

22729 22862 119388 115880 109144 21896 23882 23582 557976 578904 625691 617296 627489 658500 9906 10290 11151 361996 340668 330689 258784 259067 227476 253726 254007 218161 227 324 198 901 911 832 103 142 103 67332 65360 66492 7140 7896 7539

IPTG aTc

Lara IPTG aTc

VAI ITPG aTc

Lara VAI ITPG aTc

173714 157195 1120 1200 1153 96512 101178 107964 700890 829732 781629 776655 903344 887332 15929 15844 17455 412410 394921 404329 230441 224343 195397 212836 221089 185840 243 262 301 27171 28899 26508 4231 3519 3427 78672 90710 83437 10121 11291 10806

176969 154333 1450 1189 1104 127640 131917 136734 614331 688393 604324 689444 689589 658754 13495 14764 14400 350716 359626 311896 246710 250898 211268 246237 239885 212054 256 354 244 19088 20664 17505 4129 4805 5004 89958 90739 88871 7954 9056 7885

168301 161742 143391 132822 126997 97975 97650 107862 642673 694405 670184 657445 826660 835167 13587 14303 15778 396467 426423 369357 210166 213857 185927 203026 201359 185716 345 172 315 28716 26629 27914 3709 3479 3557 74712 77710 77448 9425 10116 8822

193592 147627 129099 138585 113482 107847 112978 116836 546463 580303 474240 587919 665547 515268 11522 12735 10157 334984 348117 242261 234216 263244 187742 225417 251268 189405 193 252 383 18796 19699 15470 4433 4291 4293 77840 92132 81621 7812 8258 7619

Appendix A2.

C20

None

169

170


inducers C23

C24

C26

C27

C29

C31

C32

C33

C34

C35

C37

C38

C39

C40

None

Lara

691907 678043 690198 5877 5971 6747 423 267 349 4782 3270 3080 209818 153087 181819 290 131 121 5197 3971 4411 5985 5855 5705 190 177 290 1057 1016 1283 4630 3796 4491 302 136 264 50 30 20 574 446

612104 632466 637953 5747 5734 6119 327 372 379 2480 2130 1990 211259 191137 173373 231 151 221 2977 2529 3269 9515 7864 8654 235 250 216 1521 1153 1104 27113 22908 25777 360 303 381 10 10 10 816 747

VAI 594535 623601 671223 5375 6224 7241 407 303 363 3270 2169 2560 242964 145899 183634 450 291 411 4618 4161 4081 5135 4505 5245 172 252 340 1094 1022 1004 3389 2011 2776 322 324 343 40 50 10 664 456

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

548969 585406 601005 4929 4893 5259 257 491 360 2060 1400 1610 226268 195837 213831 291 231 411 2799 2749 2939 7474 6743 6933 166 266 225 978 948 1060 15681 14993 18217 283 284 292 50 30 20 878 739

592680 729438 667952 35832 42227 43238 451 673 441 3303 3094 3444 166315 152307 179232 291 449 550 4239 4159 4419 6277 5236 5486 293 270 382 1152 1044 884 3883 3893 5401 328 419 457 2930 10128 6693 589 650

592935 620763 668169 29446 31120 33206 391 532 421 2702 2252 2902 193759 194875 209676 520 470 509 3858 3688 4068 8002 8002 8412 229 223 225 1050 1179 940 29632 27042 30636 501 523 671 2140 17505 3751 930 1080

581688 625283 588134 36192 41172 45453 442 472 649 2832 2722 2562 162111 157644 173660 390 389 490 3769 4099 4359 5166 4475 5356 225 217 232 1024 784 745 2191 2248 3418 337 536 566 450 12473 9747 788 568

534753 563528 583479 31527 31188 38551 608 360 479 2172 1893 2482 200550 207999 218454 571 760 700 3868 3908 4218 7542 7042 7932 149 193 284 1087 1212 1265 15553 17897 21455 575 565 553 12463 3741 4882 920 861

aTc

VAI Lara aTc VAI aTc Lara aTc

676154 799585 718677 7189 7264 7794 22389 21075 23042 5754 5595 5582 172163 169517 194257 310 550 580 4534 4885 5225 32938 31779 33478 170121 167149 181646

627537 758528 640195 6554 7871 7049 21917 22171 21486 4926 5244 4602 187464 161293 202184 510 580 580 6005 5456 5076 36826 28450 30253 160226 173442 166854

641037 658896 666752 5943 5536 6113 18859 20171 19491 4567 4504 4730 215150 213169 227329 651 431 430 3411 3732 3901 47478 45977 46913 132270 137531 137401 1103994 858360 1084387 880962 1105619 903631 4041 23648 5180 26982 6009 28716 843 860 982 750 1021 1009 20 30 10 50 50 10 41649 19966 43240 20247

580477 609853 589811 5527 4970 5387 18798 18140 18467 3625 3625 3682 218086 221466 228339 590 460 540 3563 3553 3693 36957 37138 38738 125204 126132 125720 1047307 879005 1025243 867436 1049696 885367 2598 17136 2934 19493 3346 20675 902 812 882 712 953 871 20 10 10 20 10 10 42424 17823 40430 18173

IPTG aTc 730241 771020 702428 49293 55123 56361 179518 176262 182403 6155 6505 5870 168273 176033 204875 941 1060 1021 5212 6093 5552 35270 33930 34515 175695 156640 170429

Lara IPTG aTc

614837 664931 622172 36247 39175 38214 225669 238954 233998 5198 5407 5126 234292 228160 245344 1105 944 805 5259 5269 5019 49369 49832 54474 130265 133889 140747 1034645 912711 923040 912265 956416 1003197 5538 28713 5556 35064 6867 35419 1396 1468 1494 1505 1583 1636 4491 8325 3420 9337 3270 13104 42456 21061 43321 20619

VAI ITPG aTc

Lara VAI ITPG aTc

600488 657376 614868 43190 51870 48791 171985 164290 168453 4617 5036 4691 174386 194764 230560 1092 1162 1133 5203 5323 5854 30727 29913 29260 161551 154409 160238 932317 879575 976917 3177 4014 3885 1277 1286 1265 2530 11010 3020 37080 37563

533855 607350 520173 33694 37440 32707 206791 203742 213581 4601 4464 3992 234295 239006 250911 1056 1005 957 4430 4660 4350 43970 40917 44777 115431 121326 121866 842940 884368 981484 18848 24550 23122 1382 1507 1141 2890 8696 10869 19618 18223

inducers

C41

C42

C44

C45

C46

C47

C48

C49

C51

C52

C53

C55

C56

455 1885 1335 1470 325 357 276 25730 1287 1316 28077 22254 23401 88261 99975 89541 22722 24792 23920 62 91 131 24414 25653 26908 7527 6480 6598 14377 11922 11681 216 187 267 9578 7325 7125 2808 2169 2579 1136

Lara 797 53495 48001 51393 327 368 388 7676 932 922 55498 50202 53320 108151 108589 102126 23292 25893 22531 78 258 157 28632 26243 27949 4096 3508 3556 13554 10459 11831 468 400 399 7204 5862 5742 2339 2110 2310 548

VAI

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

aTc

575 2040 1306 1620 235 297 276 19157 917 977 25505 19596 21995 98704 98552 97769 21969 25425 25615 121 110 110 26655 25150 29631 6827 4917 5557 13084 11240 12302 317 178 277 8306 6444 7075 2038 1749 2169 1167

839 38507 37798 39234 629 470 329 2473 923 1033 46785 43127 47238 107013 109131 108580 20925 21277 21526 60 148 149 26534 25139 28071 2666 2767 3166 10369 9507 10409 362 392 342 6063 4651 5442 1920 1470 2070 330

919 1602 1405 1780 1747 1795 1575 2032 1478 1341 19994 19193 20096 92303 89313 86945 382646 412487 370196 897 1242 1027 22770 24729 25029 6592 6613 7173 11209 11119 11530 457 337 387 6963 7143 7093 2624 2820 2863 87121

949 45129 44121 48220 1568 1288 1636 1454 1594 1482 58321 57048 62755 107318 114604 112176 541243 472317 476696 1326 1897 1654 29173 27426 30238 4769 4259 4487 13063 13213 13794 530 580 839 7512 6982 7843 3364 3253 3261 91240

738 1503 1544 1681 1306 1416 1586 1691 1389 1459 18219 18831 19815 94500 91326 89301 372725 397027 361780 1073 1227 1287 23132 24959 24316 5740 5819 6631 11400 11570 11820 248 328 418 6482 6352 6082 2333 2341 2392 91699

970 39720 37815 41931 920 1259 1549 1827 1395 1575 51984 52939 55401 106638 123453 124440 423181 455831 463055 1537 1920 1955 25630 26745 30381 3928 3460 4178 12772 12422 13133 621 691 660 7553 6181 7352 2804 2843 2933 90123

43280 1784 1935 2040 586 626 565 1816 1715 1205 23491 25146 25749 167169 184518 180664 26507 32007 29930 196468 235609 216834 26605 31619 31045 13487 13196 14097 20577 21350 22052 635 634 724 7736 8946 9157 2719 2828 3248 1130


41275 1822 1916 2179 586 516 636 1665 1365 1476 27270 27301 24635 213762 216406 179304 30746 34763 28768 184156 216526 217873 28825 32605 28876 13055 10050 12465 23358 22696 22504 644 664 755 7916 8667 7636 2308 2488 2339 1570

18243 45414 46119 47166 628 608 648 1682 1191 1151 48997 51215 51720 170186 172603 164530 25124 25172 23309 172519 214523 187665 28272 28704 28171 5846 6068 6697 17592 18164 19066 629 579 788 5742 5372 5852 2079 2189 2059 600

IPTG aTc

Lara IPTG aTc

VAI ITPG aTc

Lara VAI ITPG aTc

43562 2195 2633 2718 2142 2090 2241 2064 2118 2009 25692 27631 27513 186215 182320 169577 479704 516771 492828 203077 261426 258662 27557 29031 28227 14011 15473 17669 24391 24771 24219 634 814 953 8894 8374 9786 3207 3583 3893 100810

19233 55374 59869 62230 2003 1982 1992 2297 1895 2167 66109 70601 67324 181039 176456 166432 538580 525758 475020 205861 205977 215452 31102 31562 28254 8519 10371 9930 26021 26734 26181 925 1014 964 8973 8953 8593 4409 4488 3919 105110

38397 2305 2391 2215 1783 2022 1993 2405 2254 2265 21708 23787 23135 181484 177680 168676 422978 440818 421442 214400 257717 246366 24666 26753 26149 11696 13309 13558 22103 23127 23889 575 904 774 7033 7383 8425 2818 2997 2848 104413

16819 45874 47134 49511 1626 1626 1716 2192 2151 1932 57402 59260 58456 172854 182946 160072 469518 499536 435148 190538 201600 220990 27870 31244 26592 6648 7227 8421 22477 22809 23632 828 987 837 7292 7713 7302 3121 3631 3261 96761

Appendix A2.

C54

None

171

172


inducers

C59

C61

C63

C64

C65

C66

C67

C68

C69

C70

C71

C75

C76

None

Lara

1000 760 94805 76050 75989 317 177 146 563 429 250 345 306 246 5133 5003 4773 307 258 168 7675 6204 6284 30 10 90 100 140 149 837 640 580 65190 52674 52520 153363 121611 115267 425 341 222

460 540 94636 84577 90047 266 187 206 417 359 368 356 286 216 3171 3632 3432 298 198 198 5693 4923 5363 10 50 20 110 140 70 1052 1033 752 98030 94151 94169 133371 125257 128158 469 350 480

VAI 840 910 86928 73043 80591 246 137 186 405 437 366 295 236 296 4172 4032 4342 258 298 168 6404 5763 6714 10 30 10 120 180 120 780 671 611 52186 44216 43649 141883 134934 139252 557 338 407

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

aTc

330 420 84954 75357 85492 237 147 216 420 301 321 237 287 267 2751 2711 2541 189 239 299 5013 4362 4662 20 30 10 140 90 80 985 895 864 83787 79663 83218 119725 115890 113667 291 312 342

99198 90186 67174 63610 67611 257 227 237 409 438 359 322 382 342 4761 4091 5072 396 366 456 6419 6970 6069 180 350 670 276 197 157 800 950 870 49044 53141 51392 118255 125031 116999 22402 23636 22994

90975 96552 98470 102771 113035 346 266 336 653 365 604 471 511 380 3641 3761 3551 456 436 436 6586 7327 7226 290 770 630 195 215 185 1520 1418 1387 106098 116835 116526 151516 141892 148030 26684 29399 29548

101100 101446 70019 63250 71347 187 327 237 598 537 398 412 342 302 3891 4071 3881 477 367 447 6300 6440 5980 110 320 390 156 187 196 791 1041 910 45476 47583 46864 122632 129372 120999 25805 24408 26629

90083 93840 90922 104018 128313 287 366 336 358 467 486 491 361 470 3200 3140 3441 527 447 466 6548 6839 6847 510 360 420 167 207 277 1062 1180 1468 96221 101243 110521 126113 131355 137429 28387 29551 31459

1410 1320 74322 83906 77086 3466 3284 4315 834 600 622 424 633 523 4742 5092 5332 427 527 597 7184 7244 7695 20 10 10 150 111 230 58160 61815 58481 59940 62787 63728 143459 166107 152696 497 523 645


1240 1390 90198 98957 81242 4146 3535 4006 901 1010 867 633 663 624 5142 4681 4061 437 647 418 7765 8015 6643 30 10 10 142 321 132 69438 61747 59684 64503 55868 59674 160055 165954 124796 604 463 510

760 740 83589 87647 89809 2505 2255 3085 597 728 698 495 465 505 2811 2901 2941 359 359 358 5353 5433 5733 10 10 10 242 181 142 25441 25743 26565 97641 98890 103791 131939 128873 125032 579 399 380

IPTG aTc

Lara IPTG aTc

VAI ITPG aTc

Lara VAI ITPG aTc

123839 125177 81375 87089 85024 79250 89006 91686 909 1201 899 898 878 638 5022 5522 5622 825 735 934 8756 8854 9573 29593 22080 47962 267 307 196 66331 66593 65005 72043 71109 73630 163423 152590 164061 29013 27849 26792

111057 107941 108982 115057 115296 63613 73769 75288 789 889 980 767 677 828 4211 3971 3761 865 885 845 8644 8602 8404 45332 33061 73217 308 317 335 27903 29792 33818 136786 142280 169189 171289 170755 165654 30790 31605 28731

106457 106764 80131 82286 77859 68629 83964 80365 872 834 814 799 669 649 4341 5092 4211 696 606 686 7186 7936 8186 26890 43538 23737 259 299 157 56746 60613 59571 59343 64191 72699 150099 137193 136171 29658 27650 25180

97331 98704 103654 108341 98812 54504 62542 61401 905 873 765 569 789 649 3461 3401 3060 676 836 566 7125 7374 7434 30467 44052 830 193 293 249 25507 26853 27209 117470 118908 150019 138420 150592 134821 31429 29658 27038

inducers C77

C78

C79

C80

C81

C82

C83

C84

C85

C86

C87

C91

C92

188 218 118 3924 3483 3546 1067 907 1067 4149 4199 4289 10 20 50 927 581 589 60182 38832 52453 64672 40172 56008 26750 26218 25404 31941 24433 36198 7278 7413 7214 107219 109989 92100 883 872 565 914 856

Lara 189 229 139 3519 3560 3750 538 488 598 1958 1979 1729 30 10 30 660 542 650 36551 33151 43799 32195 32408 40151 20284 19321 17646 22736 21319 22453 3579 3219 3699 75670 72622 69920 748 529 719 668 692

VAI 228 198 238 4183 3455 3501 927 757 727 4069 4040 4090 20 20 30 649 522 540 46373 36660 45781 49248 38402 47847 27654 24751 26720 30148 27015 27195 6469 6710 7711 113086 102090 125645 662 404 560 655 560

Lara VAI 189 269 149 3088 2879 2889 358 289 309 1219 1359 1359 10 20 20 511 462 630 37127 35287 40578 35595 33172 39771 20666 18599 17987 21200 22303 24151 2510 2801 2781 79672 74272 72420 458 449 339 631 514

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

aTc

441 570 480 4007 4001 4052 62901 63164 65116 106392 101751 98029 60 20 40 830 661 670 39321 35849 43570 44715 37827 43816 27512 27332 28928 39495 42687 40644 33009 35503 34196 84675 116069 107642 1024 1049 1270 1170 1029

399 389 629 4273 4604 4533 79630 78739 84019 106765 103967 108353 10 40 20 930 849 1028 29778 37720 39198 31311 36367 38127 22873 20885 22140 49381 47891 49422 38195 37542 36384 90681 83831 86580 1290 1202 1200 1367 1227

390 480 550 3396 3493 3683 54932 54781 58051 112382 105040 106392 20 10 10 751 671 739 39805 38747 46854 40897 42106 51134 26608 25674 32296 42941 43555 44118 32204 35492 31591 95020 117119 109740 854 1070 1011 1142 1331

499 488 388 3706 3895 4471 67663 68502 76647 103216 111820 133764 10 10 20 819 820 979 38306 36585 39582 39176 35523 35872 19772 22140 21687 46755 46845 46252 35966 37937 41136 81460 89189 105716 1064 1052 1328 1270 1248

428 457 437 4263 4438 4223 1747 1844 1687 5523 6438 6301 5232 4451 6713 69566 71650 75801 41503 40487 45832 49775 40836 49236 28035 28818 29663 27020 29601 30204 8951 8577 7979 111038 140306 108766 3098 3849 3307 434279 527570


407 587 537 4802 4807 4190 1557 1365 1477 6650 6334 6027 5122 4952 15169 75281 67269 67813 42739 34431 52429 50459 37162 52968 28647 28335 29411 29513 31009 31623 8658 9058 7382 122479 151989 129229 2603 3202 2738 395062 492835

339 469 449 3538 3388 3196 760 881 851 2227 1997 1889 6003 7935 13956 26983 27926 26880 37159 42010 47489 37003 40042 43806 19661 21056 20223 26187 27391 24861 2958 2828 2879 85744 83604 88515 2567 2507 2449 351583 355240

IPTG aTc

Lara IPTG aTc

VAI ITPG aTc

Lara VAI ITPG aTc

788 788 858 5169 4615 5262 80344 87089 98627 126977 124741 122250 5692 5112 23395 77703 77885 82323 36766 40379 43489 39286 42647 45113 30103 30776 32888 47500 46259 48031 42814 39875 38988 117137 125709 138172 4762 4151 4368 503112 488638

717 588 749 4750 4909 4109 93367 100684 92831 115781 117940 104364 7554 9016 38927 31924 32224 30158 39349 45420 56843 37874 47150 52268 22489 24578 21656 58568 55792 62455 43175 39742 39471 95860 95301 97975 3633 3349 3394 381494 398702

618 628 610 4420 4155 3940 69076 72638 74603 121677 121248 121490 8035 7895 13976 65124 65608 66405 43575 50931 57519 46415 53220 58721 29389 31772 26857 48901 47974 49998 39624 42647 34958 118740 142502 111990 3630 3537 3748 458876 452256

738 688 620 3852 3790 3821 78618 84234 86883 113650 114615 108182 11340 9147 25092 28074 27934 25953 47784 46302 56364 45316 47079 47865 21014 24457 21286 53304 52940 56239 41851 41990 36286 94906 100517 94530 3372 3118 2894 342754 354781

Appendix A2.

C90

None

173

174


inducers

C93

C94

C96

D03

D04

D05

D07

D08

D09

D10

D11

D13

D14

D16

None

Lara

708 159687 145858 130907 543 406 368 47256 38981 40056 20 10 30 10 20 30 20 20 20 10 20 20 10 10 10 1070 970 150 10 10 20 30 10 40 2710 3791 600 43065 36028 38292 20

581 136889 111650 117787 447 302 330 30634 25359 34444 10 40 20 40 20 30 10 10 60 20 10 20 20 10 10 480 320 180 10 20 30 10 10 10 460 310 230 388168 357249 232306 30

VAI 589 151271 121102 128209 345 360 469 44145 36858 49003 30 20 10 40 10 40 10 10 40 30 10 50 10 20 10 640 740 190 20 10 50 40 10 60 2590 4541 380 38161 32739 32297 40

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

aTc

543 117909 102538 110285 431 353 472 26263 23742 31236 20 30 60 30 40 40 10 20 30 20 10 10 70 40 30 340 300 190 30 80 50 10 40 60 510 270 160 408748 358097 207608 50

1232 129515 139436 125622 655 603 626 36804 38888 44214 20 40 10 18478 15500 13876 8876 10359 1920 10 20 30 200 150 160 8866 10088 3170 10 10 50 20 70 20 141205 135402 95926 31553 38192 42319 10

1336 147661 146943 150059 601 691 690 30218 35707 39451 40 20 20 58465 55901 42974 5342 8556 2360 30 60 20 90 30 110 6083 8065 3140 30 20 20 30 50 20 115439 128941 105262 415257 401040 262075 50

1130 115256 127758 129463 637 605 515 34701 37297 39700 30 10 30 21458 19090 14327 11441 11771 2380 10 10 20 240 210 140 8656 11691 3110 30 40 10 10 10 40 133644 149935 93712 29171 32166 34892 40

1443 129688 134944 141062 674 643 892 30980 35677 45050 10 30 20 56113 47932 41625 6964 9026 2420 40 20 30 80 60 120 6073 8115 4061 40 50 10 50 60 30 120017 121079 102159 385299 413800 237901 50

451652 142783 160604 148415 37734 40076 38074 38979 44278 53189 80 10 60 30 40 60 90 30 40 210 90 60 760 430 430 8626 3741 1580 50 60 50 212403 204617 189964 3370 580 790 44284 60889 50846 70


419428 152895 163476 142089 42211 43097 39062 45375 50801 46905 60 50 30 70 50 30 70 70 60 160 100 70 850 500 430 8435 1910 1680 40 70 110 243063 191110 158759 3180 340 390 41906 43579 42591 80

338240 120364 122037 124898 18133 19938 20139 29397 31055 34583 70 40 40 190 40 80 110 40 30 80 50 90 1000 520 520 2680 1560 1660 80 50 60 251722 185279 180536 470 220 290 383434 248323 249282 100

IPTG aTc

Lara IPTG aTc

VAI ITPG aTc

Lara VAI ITPG aTc

479389 164355 158357 168522 44713 42034 47563 44808 49383 59405 50 60 30 42924 31312 31010 5062 2230 2500 105598 72215 90076 238483 230363 237131 117671 61586 64275 30377 22361 27131 265888 180155 208281 179815 98294 125305 58576 56315 55426 60

374973 172568 155464 162151 22062 20951 27808 42712 41644 49654 60 40 70 112167 70039 79852 6233 2330 3340 133491 79193 84364 204764 265983 254998 98031 73936 78747 45594 25775 29462 339400 226177 244803 174275 121303 145323 447204 290689 341378 40

414138 151682 156762 131988 42491 41956 40158 48647 50239 47032 40 60 70 40769 29372 31070 8095 3440 3110 108520 87325 87549 219784 229033 217772 134646 61910 64437 29201 27252 26428 260456 208985 205756 189850 110353 129207 42682 43478 46581 50

321498 149800 153081 144116 19758 19687 18185 34769 42429 32537 70 90 60 96892 66661 73409 7885 2070 4021 122946 74726 83795 168255 230508 198795 98498 69989 74918 36219 23596 27101 309987 169828 207246 159570 112971 137100 385310 245521 320744 100

inducers

D17

D18

D19

D20

D24

D25

D27

D28

D29

D31

D34

D35

Lara

10 50 55214 43629 49182 40 10 70 62092 20515 4511 40 20 10 5332 7124 1810 10 40 40 37447 36551 55911 97797 94484 121507 10 40 30 20 20 30 370 280 80 197059 164800 303904 50594 45110 66206

40 40 69797 67915 43357 10 10 40 53398 11982 3991 40 10 70 6643 5362 2080 10 30 20 61829 56567 48033 91447 91031 88097 10 10 30 30 10 50 370 270 60 331576 338637 240273 50765 52783 60960

VAI 10 60 48043 44596 51713 10 10 20 42994 28236 4371 40 30 30 4882 7644 1870 40 10 50 39450 42360 57859 94768 117814 117763 30 30 10 40 10 10 260 470 140 157650 201514 323445 51441 45483 68097

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

30 10 46319 56244 39561 20 10 40 24550 9798 3561 20 30 30 7704 5632 2150 40 80 30 57607 60758 51612 88848 96729 94534 10 20 20 10 30 60 430 310 90 323688 362225 274747 50735 46027 59071

10 10 38947 57445 52561 40 40 20 28457 16061 4321 20 20 20 4801 6703 1620 780 360 240 29724 40275 56143 116723 120783 162077 20 40 10 40 30 70 280 180 80 141973 172545 267122 41866 46964 63658

40 30 96313 54669 49000 40 30 40 18528 23064 5442 10 80 30 6443 8756 2510 470 720 330 73582 51330 57738 166692 148694 149586 20 60 10 30 30 20 400 270 110 400068 258671 289629 54609 36109 61061

10 10 50059 54094 53105 10 20 20 27704 12513 3290 20 20 40 5892 7254 1840 780 580 310 41101 42098 62061 156449 120293 170898 10 40 10 10 10 30 570 280 150 217451 204607 316834 41856 45896 63972

40 40 71092 61940 51441 40 20 30 21579 26227 3661 30 80 30 7084 8726 2560 480 890 300 69776 56759 60031 164779 171680 157517 40 10 20 40 70 40 360 310 70 392518 327603 336278 48395 30136 57092

aTc 100 90 59465 60344 52450

VAI Lara aTc VAI aTc Lara aTc 70 100 45966 49131 48567

60 60 53337 60586 54922

110 110 47528 47236 47801

IPTG aTc

Lara IPTG aTc

VAI ITPG aTc

60 70 46642 66499 62304

40 80 83086 57658 74959

100 170 47841 64740 58142

Lara VAI ITPG aTc 140 110 51774 51360 66034

1986291 1915247 2209744 2399427 1917144 1773607 1872940 1912606 2052013 2376710 2325011 2477130 2375257 2442023 2271526 2468000 2319984 2372351 2317496 2522016 2315013 2459564 2256303 2343586

26267 5662 4251 70 50 70 7104 2790 1930 90 50 100 80865 91619 88716 113216 147823 143755 6173 6373 5382 70 80 80 430 150 230 226125 328438 329695 91995 105903 117468

27724 4021 4932 20 70 60 7074 2390 2480 60 70 60 79193 75323 78818 95266 109823 107960 8245 9958 24912 70 110 100 390 200 180 318046 303747 285936 95784 128532 120283

16944 4231 4031 120 40 60 7875 2520 1990 50 50 70 72964 94778 90624 121089 145917 142270 5892 4511 13896 100 50 130 400 180 230 245458 353166 365285 96343 100552 109864

33212 4331 4041 40 40 60 6613 2600 2970 100 90 80 77237 80034 81737 102983 109304 112676 10349 8486 10649 190 80 140 370 110 210 348099 315242 305051 88848 117182 112126

14637 3430 5472 80 30 120 5952 1900 3140 600 190 300 74483 88482 89112 161542 200821 190882 9327 3100 15831 100 130 100 230 220 200 236049 362937 307713 110088 113084 105781

13655 4311 6383 100 60 50 7014 2810 3861 750 260 320 106322 91264 96862 171167 177395 183001 17947 19010 98366 50 110 80 440 190 180 396556 348132 379580 96598 128155 122243

10909 4311 4922 110 80 90 5742 2270 2920 630 370 380 82021 98701 85936 162673 200873 197348 9056 11481 10669 110 80 170 300 180 240 252202 337250 286367 97166 110964 93214

14607 2940 6323 40 140 70 7715 2510 3631 850 340 380 92696 89619 94971 155710 178795 171094 13214 25022 840 90 110 110 400 180 250 314789 338837 365072 76630 112859 102922

Appendix A2.

D32

None

175

inducers

176


D36

D37

D38

D40

D41

D42

D43

D44

D45

D46

D49

D50

D51

D52

None

Lara

57819 51158 25363 60 20 20 28668 19170 30286 144738 104550 224121 33111 11430 2620 6813 6493 4771 81402 59162 85317 9016 7885 2730 40 30 30 40 60 30 190 120 70 50 60 30 40487 32508 20916 330 160

48053 40225 29985 20 10 10 44697 46601 28638 189252 205870 201990 10008 7985 3420 8486 6463 3651 129984 119140 82497 8446 6353 2410 10 10 10 60 10 50 80 70 30 50 60 30 39369 31362 21960 230 170

VAI 53035 58718 24078 40 20 40 26910 24440 28940 130045 133633 219939 18207 20364 3000 6493 8626 5112 58182 70110 91914 7164 9036 2300 30 20 20 80 20 40 147382 131026 135259 50 60 50 35304 35928 20133 230 320

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

aTc

52419 43276 30809 40 30 40 36219 39752 27784 154550 184918 189086 11901 8075 3300 7004 6613 3481 112666 115632 81859 7905 6003 2520 50 10 40 20 80 50 132835 114123 130402 120 80 80 35062 30970 22151 210 130

53287 51673 27804 20 10 20 26750 33413 29643 136292 161255 287342 19030 12823 2930 6233 6163 4872 50251 59758 89721 9217 10539 2490 60 70 20 40 70 40 280 130 40 50 30 30 37377 32407 21779 260 160

55477 62708 33825 70 50 30 53106 38574 36028 319702 222097 278842 10599 14768 4441 8626 7274 4791 127695 99352 93844 9267 10098 3030 30 50 30 80 60 40 130 130 90 100 100 40 39651 41675 25554 250 290

65973 60768 27131 50 10 50 28879 33735 29040 183104 173060 275533 29884 13294 2710 8405 5832 4952 65832 62607 92655 12733 10559 2360 40 30 10 40 50 110 173904 158256 137899 120 40 60 40134 34348 19822 420 110

56093 67166 35666 60 70 50 44495 32639 30668 295507 234614 295403 11681 19040 4191 7995 7704 4071 122477 111779 89477 8696 10248 2850 30 80 30 80 90 60 150109 119426 149237 90 50 90 38403 40396 22251 290 310

105008 43810 37980 60 90 60 46742 58294 49273 158276 262514 231517 16743 3871 2740 8165 6493 4751 77622 123835 106820 10228 4251 2590 137909 63628 49656 415556 608589 475915 190 150 70 155987 164451 148582 42632 32759 25514 280 140


90350 43397 37799 60 80 80 43528 53307 48305 158964 237496 240211 20896 3641 3170 8145 5682 4942 81899 119110 108754 10609 2930 2430 143550 59496 49363 447297 580425 490999 145814 145558 146285 157814 174810 158040 38252 29000 23978 360 130

86696 48809 52147 80 110 160 69321 50916 52914 156192 214631 209565 16512 4771 4841 7244 4411 4211 118069 96963 99077 9006 3571 3360 302969 74402 69685 380068 402097 391654 100196 146060 135402 180536 148940 144390 36411 27563 25846 370 150

IPTG aTc

Lara IPTG aTc

VAI ITPG aTc

Lara VAI ITPG aTc

81179 37910 50523 100 80 70 62031 54659 52944 272487 345483 321578 7334 3410 4511 6703 5412 6173 87721 104753 120334 6994 2890 4071 108031 50130 64467 573376 516039 577301 220 140 110 204482 163351 175314 34268 26197 26097 190 130

78656 51683 67632 80 100 90 100929 68461 77359 312611 333499 365201 11210 4611 7925 7855 5722 6203 128299 113288 120498 9507 3831 5332 225234 82335 101345 472058 463004 472845 270 180 150 221777 166168 179486 47408 28096 35093 260 110

86220 42309 52510 80 70 130 61829 53216 51713 255603 327741 313041 8235 3721 5402 7334 5862 6403 91934 114704 116254 9026 3631 4211 137408 66974 68087 521910 590572 581205 235883 166074 159981 212206 177219 188302 40114 24711 26920 230 170

81342 47408 64052 120 160 140 79933 58405 69098 240190 319785 325228 15901 3771 8786 7084 4641 5182 108846 101782 116600 8976 3390 5322 251681 68603 106616 357439 420410 448428 178260 164954 163844 202342 158974 186981 42138 25544 35254 260 210

inducers

D53

D54

D56

D57

D60

D61

D62

D64

D65

D66

D68

D70

D71

Lara

70 60 100 50 20555 18338 29734 10 10 10 60 40 40 252108 268952 338117 30 50 40 60 30 50 133459 95235 29914 30 30 20 4922 4141 1090 100 140 60 91853 74888 131506 30 10 30 22462

100 90 90 30 36179 34459 24480 10 20 20 50 20 40 501102 445706 372342 120 50 130 30 60 70 89457 70889 41665 40 30 40 3831 3020 1570 10 10 40 143632 152673 139976 40 40 50 29884

VAI 130 60 60 80 18930 21227 28488 40 10 40 50 50 70 292273 250451 365104 10 30 10 70 20 70 116254 102322 31221 70 40 20 3891 5542 1340 50 110 50 63264 75222 143663 30 10 60 19782

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

aTc

90 50 20 40 31814 31261 23014 40 20 30 100 50 30 458784 444854 359211 120 110 60 60 80 50 90309 69857 39440 80 30 20 4431 3350 1450 70 40 20 138594 152642 140437 60 90 50 26719

90 32830 39410 75404 15339 19040 28508 2330 3010 4561 510 480 180 224817 250273 356941 200 160 220 80 70 70 130219 102047 31804 1620 1340 870 5062 4091 1310 183928 212962 123273 60132 73146 138677 40 70 20 16643

180 152612 79396 147567 36853 26157 27573 4992 3491 4241 800 640 190 506469 432341 412451 73491 105425 92097 110 80 80 95530 101203 53196 1170 1330 370 4081 4721 1440 240586 226696 141471 166887 121313 149760 30 80 30 29312

120 43448 42179 77967 18889 19481 28689 2930 3100 4751 590 570 220 271787 266558 354141 60 180 190 60 20 60 132703 100338 31191 2300 1300 680 6813 3801 1340 209824 211430 111678 75931 73774 138155 60 10 70 19261

140 140529 89995 157876 34670 28437 24098 4751 3501 4531 660 880 270 497528 425117 410140 87275 72934 61748 70 70 40 92289 115662 44193 1230 1670 400 5232 5732 1480 223540 236850 123324 158471 121252 150201 10 40 80 30990

160 180 140 60 25946 38353 33021 90 110 140 70 50 120 294961 505740 409038 30 10 40 119313 74635 57809 108591 42813 32478 70 60 80 4351 2040 1290 140 70 70 98996 162632 150058 40 40 60 24460


130 160 100 50 25926 34882 33172 120 70 60 60 50 40 328374 485538 418299 10 30 30 141194 64396 64406 130147 35173 35264 70 100 80 5572 1980 1540 130 110 150 94748 162868 152119 60 40 80 24249

170 80 90 100 30276 28538 27905 60 80 70 140 70 80 445532 421449 434757 40 70 60 124365 70353 73227 103593 51915 50382 110 60 50 5182 2100 1980 60 100 90 113929 162600 149996 110 80 60 23275

IPTG aTc

Lara IPTG aTc

VAI ITPG aTc

Lara VAI ITPG aTc

280 56385 92482 86524 29713 37135 35777 144461 222170 223208 580 350 310 430472 405400 463975 160 70 130 125734 63800 72205 77217 34399 44848 1550 1170 1140 3721 1690 1960 274957 158153 159827 166373 146490 160546 70 20 30 33483

220 146194 179507 194012 37739 34157 38665 205105 259799 235925 840 310 350 540552 486166 557393 102210 99769 120089 143551 81230 103665 105741 54902 78413 1150 390 570 4821 1850 2460 271401 182980 209566 166744 172370 161985 50 50 50 34308

170 63224 92614 86767 27141 34992 34781 147936 232233 218736 660 400 270 357026 454482 462334 100 240 150 133316 67288 77926 75131 38071 47549 1630 1050 1150 3891 1990 1840 287132 167000 163207 130249 172349 159036 50 90 70 29422

310 112625 168285 177291 29030 29171 31613 158266 232555 224079 820 350 380 483024 434274 525920 70110 92706 106382 148684 73663 104295 108612 45886 79760 1290 460 540 4511 1910 2920 245219 157321 189953 140140 160844 162374 80 90 100 30749

Appendix A2.

D69

None

177

178


inducers

D72

D73

D77

D78

D79

D80

D81

D83

D85

D86

D87

D89

D90

None

Lara

18930 16232 232629 258034 147966 23636 21127 5672 570 520 110 2060 1560 300 20 10 10 710 420 90 160 90 50 14186 13525 6473 123089 95479 94727 22803 18759 15289 1210 910 230 60 30 30 40 30 10

24550 15620 326422 226593 185764 31583 16462 7975 80 140 90 2570 970 230 40 10 10 990 350 40 140 180 60 13846 11070 7564 97065 73592 75050 22964 14387 10218 1110 330 140 100 70 10 10 10 10

VAI 19301 16563 245927 230748 140939 18879 17004 4391 480 630 110 2000 2730 290 40 20 10 97075 71223 50261 130 180 70 14658 13966 6803 96414 91802 76944 21498 17886 19150 810 1230 180 70 20 30 40 20 20

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

24801 15299 290426 252849 176560 29925 12402 5382 140 210 140 2110 760 270 50 30 30 77632 46027 41544 210 130 80 12402 10459 6964 93285 74695 75850 25384 16613 11370 790 360 150 100 60 40 30 30 20

16181 16492 219898 251899 141297 29714 16883 7044 1160 440 140 3230 1480 240 20 30 10 920 420 170 250 100 60 13184 14447 6493 127940 100572 109355 28709 28960 22843 36773 27141 20826 110 70 30 87863 60516 43025

24108 16111 339568 323372 187342 21007 31855 10128 180 200 150 1480 1780 340 30 60 20 940 990 140 180 200 40 16813 15740 7795 104560 94768 99586 29543 30317 15810 26448 25785 16161 100 100 30 78220 74017 57163

19090 15841 252265 330255 132283 24159 14026 5462 1440 350 60 4091 1760 270 70 10 10 88422 96191 49444 370 80 70 16823 16974 5942 126817 99596 98376 28809 28920 25795 38152 28357 18679 100 70 40 95520 67875 45442

23988 18478 337673 305198 183000 18729 30256 6223 180 140 100 1990 2410 360 30 30 20 72245 65771 47095 260 240 90 16643 14768 7694 102484 87691 98966 35455 35052 18047 26960 28498 17054 70 140 60 87833 91122 61981

aTc 22843 17505 267906 197761 151729 19231 9147 6894 132263 59435 43669 2310 680 490

VAI Lara aTc VAI aTc Lara aTc 20565 18709 335792 222191 221900 33282 9317 11962 142311 66519 70130 2380 530 650

20615 17355 332335 182000 150468 18538 5352 5832 143785 46410 48285 2630 630 500

19602 18639 268115 211036 221423 31493 6403 6483 145886 63961 62223 2710 780 570

IPTG aTc

Lara IPTG aTc

VAI ITPG aTc

Lara VAI ITPG aTc

18819 21679 330349 159262 187734 16462 7634 8916 101314 50301 60536 1520 440 810

21127 21107 335794 220106 262724 27111 11861 15229 136825 69948 95581 1610 480 890

20675 20083 338657 175840 186692 15901 6273 8115 119579 52752 63173 1230 740 730

19471 20746 304462 210124 272916 26217 6343 10759 145630 62526 98650 1820 830 1020

1849937 1658333 2057674 1889256 2077786 1751911 2093520 1737058 2117706 2178466 2211959 2243646 1923685 2217220 2054456 2120724 1828671 2233413 1984362 2267458 2161418 2596919 2374815 2685795

870 400 200 150 60 60 15279 9076 7865 151739 114959 113033 20756 18057 16563 760 370 300 160 120 80 150 110 80

1080 370 410 100 60 70 16161 9317 9127 90868 101355 92960 21067 11110 10869 940 200 270 190 110 170 70 110 140

116539 52298 48456 190 90 90 16863 9257 7034 103949 86169 96089 20164 20485 18779 900 210 390 270 140 120 150 100 90

51542 53650 46752 230 110 90 14257 8225 8926 77248 90076 87031 22793 12322 11661 980 220 220 180 130 80 150 100 160

750 260 410 120 100 60 17445 7014 8736 137264 115244 139096 30879 25655 25645 30196 17224 26036 160 130 160 78706 40517 57658

880 350 400 140 140 60 15580 9868 11080 140469 128206 119967 29804 18217 17275 28719 18769 21910 150 90 140 81859 63082 75060

96994 66115 62809 180 120 80 17204 9417 8556 124263 109467 122732 32508 26247 28789 30427 19822 26026 110 110 150 75951 51431 61041

69260 51693 64032 210 190 140 14748 8496 10960 131783 116539 99616 30397 18639 18107 28719 17565 17736 160 110 170 91376 61778 75698

inducers D91

D92

D93

D94

D95

D96

None 40 10 50 1870 1310 380 1410 1130 630 12954 12132 6673 28136 24389 14497 37407 35928 15480

Lara 20 10 20 2460 740 340 2020 1010 300 18879 11982 6563 311030 200181 125060 30568 18147 13896

VAI

Lara VAI

IPTG

Lara IPTG

VAI ITPG

Lara VAI ITPG

30 10 20 1640 2080 420 1660 1500 630 16422 15770 6924 27644 28528 13385 33664 41474 17595

20 30 10 2310 860 670 2010 1160 290 20404 12583 9387 369609 204979 140836 34751 22371 15871

930 1230 710 2300 1300 490 1690 970 480 125785 88797 62435 23165 19090 12693 39903 29724 18308

41886 38262 21569 1440 1420 500 1680 1500 420 159540 140857 78717 282771 287174 140365 32166 29804 15069

880 1220 730 2440 1170 430 2200 1210 600 149545 102485 68239 28277 20836 13515 44908 35676 17555

40376 37517 23024 1610 1580 660 1880 2190 370 142730 146859 86169 326442 333044 156326 40537 35928 19221

aTc 430 390 520 2110 610 520 2200 730 620 19030 6113 6213 32920 17666 16482 57284 21067 15981

VAI Lara aTc VAI aTc Lara aTc 470 490 480 1860 540 610 2240 430 420 18749 6813 8235 373481 180588 173306 39832 15480 18167

590 470 430 2090 530 510 1970 680 670 20033 7815 7715 35716 15309 16583 49817 18488 18930

510 500 500 1850 620 650 2520 390 380 24982 8946 10799 389883 189592 183443 45331 17736 19511

IPTG aTc

Lara IPTG aTc

VAI ITPG aTc

Lara VAI ITPG aTc

1680 1280 1350 930 350 650 790 610 590 124641 45856 81169 18869 14447 14186 30578 10288 25564

39973 24801 27935 1290 640 800 1420 350 480 128687 74250 107125 248428 187683 204070 27312 17375 21990

1620 1100 1440 1220 660 740 1010 660 680 131047 78200 94849 17746 13525 14818 32277 19592 25153

38876 23476 22763 1160 670 960 1440 440 530 141205 93549 119181 250263 178136 181443 27965 20174 19120

Appendix A2. 179

180


Appendix B: The Reporter Scaffold This appendix contains the complete sequence of the 3-color reporter plasmid pFS2-123 described in Chapter 3. Here the beginning of the scaffold is numbered as the first base pair, corresponding to the description of the genetic features in the Chapter 3 Methods and Materials. A map of the plasmid shows the layout of the relevant genetic features. The replacement promoter sequence used to remove LacI repression of yfp is shown separately.

pFS2-123 6806 bp cerulean CFP RNAI TSAL2

SC101 Origin

P(TET) P(LAC)

venus YFP TR2-17 TL17 BS7 T7TE+

T1

Kan resistance cherry RFP P(LAC/ARA)

Map of scaffold sequence

cccgggcatacgttaaatctatcaccgcaagggataaatatctaacaccgtgcgtgTTGACTattttacctctggcggtGATAATggttgcatgcctagg XmaI site -35 box -10 box AvrII site ~~~~~~ ~~~~~~ ~~~~~~ ~~~~~~

Lambda P(R) promoter inserted between XmaI and AvrII in plasmid pFS2-12R Lamba P(R) promoter inserted between XmaI and AvrII sitessites in plasmid pFS2-12R

Appendix B.

RNAI ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ NotI ~~~~~~~~ 1 GCGGCCGCAA AAGGAAAAGA TCCGGCAAAC AAACCACCGT TGGTAGCGGT GGTTTTTTTG TTTGGATCGA CAATCTTCGT AAGCGTCATC AATAAGCGTA ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ TSAL2 101 AAAAAACCGG GCAATGCCCG GTTTTTTAAT GAGAAATTTT ACCTGTCGTA GCCGCCACCA TCCGGCAAAG AAGCATACAA GGCTTTTGGC TTATAGCTAC ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ TSAL2 BbsI ~~~~~~ 201 GTAGCGCATT GCGTCGCAGC ACAATCCCGG CACCGATCAA GTCTTCGCGA TGATTATTAT TATTTATACA GCTCATCCAT GCCATGCGTG ATGCCAGCAG ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ TSAL2 cerulean CFP 301 CCGTTACAAA TTCCAGCAGC ACCATGTGAT CGCGCTTCTC ATTAGGATCT TTGCTCAGCT TAGATTGAGT GCTCAGATAG TGATTGTCCG GCAGCAGAAC ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ cerulean CFP 401 AGGACCGTCG CCAATCGGGG TATTTTGTTG ATAATGGTCA GCCAGTTGCA CAGAGCCGTC CTCGATATTA TGGCGAATTT TAAAATGCGC CTTAATACCA ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ cerulean CFP 501 TTCTTTTGTT TATCGGCGGT GATATACACA TTATCGCTAA TCGCATTATA TTCCAGTTTA TGGCCCAGGA TATTACCATC TTCCTTAAAA TCGATGCCCT ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ cerulean CFP 601 TCAGCTCAAT ACGATTCACC AGAGTGTCGC CTTCAAACTT CACCTCTGCG CGAGTCTTGT AATTACCATC ATCTTTAAAG AAAATGGTGC GCTCCTGAAC ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ cerulean CFP 701 GTAACCCTCT GGCATGGCGC TCTTAAAAAA ATCGTGCTGC TTCATGTGGT CTGGATAGCG AGCGAAGCAT TGAACACCCC AGGTCAGGGT GGTAACCAGG ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ cerulean CFP 801 GTAGGCCAAG GCACCGGCAG CTTACCCGTC GTACAAATGA ACTTCAGGGT CAGCTTACCG TAGGTTGCGT CGCCTTCACC CTCGCCGCTA ACGCTGAACT ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ cerulean CFP 901 TATGACCGTT GACATCACCG TCCAGTTCGA CCAGGATAGG AACCACACCA GTAAACAGCT CCTCGCCCTT GCTCATTTTT TTTTCCTCCT TATTTTCTCC ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ cerulean CFP ~~~~~~~~~~~~~~~~~~ UTR ~~~~~~~~~~~~~~~~~~ SD8 SalI ~~~~~~~ 1001 AGGAAGATCT TCGGTCAGTG CGTCCTGCTG ATGTGCTCAG TATCTCTATC ACTGATAGGG ATGTCAATCT CTATCACTGA TAGGGAGTCG ACAAAAATAA ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~ ~~~~~~~ UTR -10 -35 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ P(TET) ~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~ tetO2 tetO2 AscI ~~~~~~ 1101 TGAGAATCAA TAGAACTTCC GAGAAGTTCA GCCGCTAATA ATCGCCCTGC TCCATTGTGC GCCGCAATAA AAGTACCGGC ATTACGGGTG CATTGGCGCG AscI ~~ 1201 CCAAATGCGG CCATCTGTGG GCAACCTGTG CGGTAAGACC CAAACTTAGT GTAATAGGTA TCCTATGATT ATTTTTTCAT TTGATGCCAA AAAGACAATG P(LAC) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -35 -10 ~~~~~~ ~~~~~~~ XhoI BamHI ~~~~~~~ ~ 1301 AACCCCCGCT CGAGCGGTCG AGAATTGTGA GCGGATAACA ATTGACATTG TGAGCGGATA ACAAGATACT GAGCACATCA GCAGGACGCA CTGACCGCGG SD8 ~~~~~~~~~~~~~~~~~~~~~~ venus YFP ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ BamHI ~~~~~ 1401 GATCCCGGTG CAGAAAATAA GGAGGAAAAA AAAATGAGCA AAGGTGAAGA ACTGTTCACC GGCGTTGTGC CAATTCTGGT TGAGCTGGAT GGTGACGTGA venus YFP ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 1501 ATGGCCACAA ATTTTCCGTG TCTGGTGAAG GCGAGGGTGA TGCTACTTAT GGCAAACTGA CTCTGAAACT GATCTGTACC ACCGGCAAAC TGCCTGTTCC venus YFP ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The pFS2-123 Sequence

181

182


1601 GTGGCCAACT CTGGTCACTA CTCTGGGTTA CGGCCTGATG TGTTTTGCGC GTTACCCGGA TCACATGAAA CAGCATGACT TCTTCAAATC TGCCATGCCG venus YFP ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 1701 GAAGGCTATG TCCAAGAACG TACGATCTTT TTCAAGGACG ACGGCAACTA TAAAACCCGT GCCGAAGTTA AATTCGAGGG TGACACCCTG GTTAACCGCA venus YFP ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 1801 TCGAACTGAA AGGCATTGAC TTCAAAGAGG ACGGCAACAT TCTGGGTCAC AAGCTGGAAT ACAACTACAA CTCCCACAAC GTTTACATTA CTGCTGACAA venus YFP ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 1901 GCAGAAAAAC GGCATCAAAG CAAACTTCAA GATCCGTCAC AACATTGAAG ATGGTGGCGT ACAGCTGGCA GATCACTACC AGCAGAACAC TCCAATCGGT venus YFP ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2001 GATGGCCCAG TACTGCTGCC AGATAACCAT TACCTGTCCT ACCAGAGCAA ACTGTCTAAA GACCCGAACG AAAAACGTGA CCACATGGTA CTGCTGGAAT venus YFP TR2-17 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ BsmBI ~~~~~~~ 2101 TTGTTACCGC GGCAGGCATT ACCCACGGTA TGGACGAACT GTATAAATAA TGCAGGTCGT CTCGGATCGA GAAGGACACG GTTAATACTA GGCCTGCTGG TL17 ~~~~~~~~~~~~~ TR2-17 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2201 CTGGTAATCG CCAGCAGGCC TTTTTATTTG GGGGAGAGGG AAGTCATGAA AAAACTAACC TTTGAAATTC GATCTCCACC ACATCAGCTC TGAAGCAACG TL17 BS7 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~ PacI ~~~~~~~~~ 2301 TAAAAAAACC CGCCCCGGCG GGTTTTTTTA TACCCGTAGT ATCCCCACTT ATCTACAATA GCTGTCCTTA ATTAAGGTTG AATAAATAAA AACAGCCGTT BS7 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2401 GCCAGAAAGA GGCACGGCTG TTTTTATTTT CTAGTGAGAC CGGGAGCAGT TAAACGCAGA AAGGCCCACC CGAAGGTGAG CCAGTGTGAC TCTAGTAGAG ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ UTR ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ T7TE+ BsrGI ~~~~~~~ 2501 AGCGTTCACC GACAAACAAC AGATAAAACG AAAGGCCCAG TCTTTCGACT GAGCCTTTCG TTTTATTTGA TGCCTGGTTA TTATTATTTG TACAGCTCAT ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~ T7TE+ cherry RFP ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ UTR 2601 CCATGCCACC GGTAGAATGA CGACCCTCCG CGCGCTCATA TTGCTCTACG ATCGTATAAT CTTCATTATG AGAGGTGATG TCCAGTTTAA TATTCACATT ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ cherry RFP 2701 GTACGCGCCA GGCAGCTGCA CAGGTTTCTT GGCTTTGTAC GTGGTTTTCA CTTCAGCGTC ATAATGGCCG CCATCTTTCA GTTTCAGGCG CTGTTTAATT ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ cherry RFP 2801 TCGCCTTTCA GCGCACCATC TTCCGGATAC ATGCGTTCGC TAGACGCCTC CCAACCCATC GTCTTTTTCT GCATCACCGG GCCATCAGAT GGAAAATTAG ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ cherry RFP 2901 TACCACGCAG TTTAACTTTA TAGATGAACT CGCCATCCTG CAGGGAGGAG TCCTGAGTGA CGGTCACGAC ACCACCATCT TCAAAATTCA TTACGCGTTC ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ cherry RFP 3001 CCACTTGAAA CCTTCCGGAA AAGACAGCTT CAGATAGTCC GGGATATCCG CTGGGTGTTT AACATACGCT TTAGAACCGT ACATAAATTG CGGGCTCAGG ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ cherry RFP 3101 ATGTCCCACG CAAAAGGCAG CGGGCCGCCT TTAGTCACTT TCAGTTTGGC GGTCTGGGTG CCTTCATACG GACGGCCCTC GCCTTCGCCT TCGATCTCGA ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ cherry RFP 3201 ACTCGTGACC GTTAACAGAA CCCTCCATGT GAACTTTGAA GCGCATGAAC TCTTTAATGA TAGCCATGTT ATCCTCCTCG CCCTTGGAAA CCATGGCAGG ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ cherry RFP t7g10 AvrII ~~~~~~~ 3301 TGCTCCTTCT TAAAGTTAAA CAAAATTATT TCTAGATTTT CTCAAGCCTA GGTCTGTGTG AAATTGTTAT CCGCTCACAA TTGAATCTAT CATAATTGTG ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~ t7g10 lacO1 -10 ~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SD P(LAC/ARA) XmaI ~~~~~~ 3401 AGCGCTCACA ATTGTAAAGG TTAGATCCGC TAATCTTATG GATAAAAATG CTATGTTCCC CCCGGGGGGA TATCAACAGG AGTCCAAGCG ACCGGTGGTT ~~~~~~ ~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~


Appendix B.

-35 ara2 ara1 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ P(LAC/ARA) NheI ~~~~~~~ 3501 GCATGTCTAG CTAGCTAGAA CAGGACTAGC TAATGGTTTC TTAGACGTCG GAATTGCCAG CTGGGGCGCC CTCTGGTAAG GTTGGGAAGC CCTGCAAAGT Kan resistance ~~~~~~~~~~~~~~~~ 3601 AAACTGGATG GCTTTCTTGC CGCCAAGGAT CTGATGGCGC AGGGGATCAA GATCTGATCA AGAGACAGGA TGAGGATCGT TTCGCATGAT TGAACAAGAT Kan resistance ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 3701 GGATTGCACG CAGGTTCTCC GGCCGCTTGG GTGGAGAGGC TATTCGGCTA TGACTGGGCA CAACAGACAA TCGGCTGCTC TGATGCCGCC GTGTTCCGGC Kan resistance ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 3801 TGTCAGCGCA GGGGCGCCCG GTTCTTTTTG TCAAGACCGA CCTGTCCGGT GCCCTGAATG AACTGCAGGA CGAGGCAGCG CGGCTATCGT GGCTGGCCAC Kan resistance ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 3901 GACGGGCGTT CCTTGCGCAG CTGTGCTCGA CGTTGTCACT GAAGCGGGAA GGGACTGGCT GCTATTGGGC GAAGTGCCGG GGCAGGATCT CCTGTCATCT Kan resistance ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 4001 CACCTTGCTC CTGCCGAGAA AGTATCCATC ATGGCTGATG CAATGCGGCG GCTGCATACG CTTGATCCGG CTACCTGCCC ATTCGACCAC CAAGCGAAAC Kan resistance ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 4101 ATCGCATCGA GCGAGCACGT ACTCGGATGG AAGCCGGTCT TGTCGATCAG GATGATCTGG ACGAAGAGCA TCAGGGGCTC GCGCCAGCCG AACTGTTCGC Kan resistance ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 4201 CAGGCTCAAG GCGCGCATGC CCGACGGCGA GGATCTCGTC GTGACCCATG GCGATGCCTG CTTGCCGAAT ATCATGGTGG AAAATGGCCG CTTTTCTGGA Kan resistance ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 4301 TTCATCGACT GTGGCCGGCT GGGTGTGGCG GACCGCTATC AGGACATAGC GTTGGCTACC CGTGATATTG CTGAAGAGCT TGGCGGCGAA TGGGCTGACC Kan resistance ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 4401 GCTTCCTCGT GCTTTACGGT ATCGCCGCTC CCGATTCGCA GCGCATCGCC TTCTATCGCC TTCTTGACGA GTTCTTCTGA GCGGGACTCT GGGGTTCGAG 4501 AGCTCGCTTG GACTCCTGTT GATAGATCCA GTAATGACCT CAGAACTCCA TCTGGATTTG TTCAGAACGC TCGGTTGCCG CCGGGCGTTT TTTATTGGTG ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ T1 4601 AGAATCCAAG CACTAGGGAC AGTAAGACGG GTAAGCCTGT TGATGATACC GCTGCCTTAC TGGGTGCATT AGCCAGTCTG AATGACCTGT CACGGGATAA ~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ T1 SC101 Origin 4701 TCCGAAGTGG TCAGACTGGA AAATCAGAGG GCAGGAACTG CTGAACAGCA AAAAGTCAGA TAGCACCACA TAGCAGACCC GCCATAAAAC GCCCTGAGAA ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 4801 GCCCGTGACG GGCTTTTCTT GTATTATGGG TAGTTTCCTT GCATGAATCC ATAAAAGGCG CCTGTAGTGC CATTTACCCC CATTCACTGC CAGAGCCGTG ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 4901 AGCGCAGCGA ACTGAATGTC ACGAAAAAGA CAGCGACTCA GGTGCCTGAT GGTCGGAGAC AAAAGGAATA TTCAGCGATT TGCCCGAGCT TGCGAGGGTG ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 5001 CTACTTAAGC CTTTAGGGTT TTAAGGTCTG TTTTGTAGAG GAGCAAACAG CGTTTGCGAC ATCCTTTTGT AATACTGCGG AACTGACTAA AGTAGTGAGT ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 5101 TATACACAGG GCTGGGATCT ATTCTTTTTA TCTTTTTTTA TTCTTTCTTT ATTCTATAAA TTATAACCAC TTGAATATAA ACAAAAAAAA CACACAAAGG ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 5201 TCTAGCGGAA TTTACAGAGG GTCTAGCAGA ATTTACAAGT TTTCCAGCAA AGGTCTAGCA GAATTTACAG ATACCCACAA CTCAAAGGAA AAGGACTAGT ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 5301 AATTATCATT GACTAGCCCA TCTCAATTGG TATAGTGATT AAAATCACCT AGACCAATTG AGATGTATGT CTGAATTAGT TGTTTTCAAA GCAAATGAAC ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 5401 TAGCGATTAG TCGCTATGAC TTAACGGAGC ATGAAACCAA GCTAATTTTA TGCTGTGTGG CACTACTCAA CCCCACGATT GAAAACCCTA CAAGGAAAGA ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 5501 ACGGACGGTA TCGTTCACTT ATAACCAATA CGCTCAGATG ATGAACATCA GTAGGGAAAA TGCTTATGGT GTATTAGCTA AAGCAACCAG AGAGCTGATG ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 5601 ACGAGAACTG TGGAAATCAG GAATCCTTTG GTTAAAGGCT TTGAGATTTT CCAGTGGACA AACTATGCCA AGTTCTCAAG CGAAAAATTA GAATTAGTTT ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 5701 TTAGTGAAGA GATATTGCCT TATCTTTTCC AGTTAAAAAA ATTCATAAAA TATAATCTGG AACATGTTAA GTCTTTTGAA AACAAATACT CTATGAGGAT ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 5801 TTATGAGTGG TTATTAAAAG AACTAACACA AAAGAAAACT CACAAGGCAA ATATAGAGAT TAGCCTTGAT GAATTTAAGT TCATGTTAAT GCTTGAAAAT ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin


183

184


5901 AACTACCATG AGTTTAAAAG GCTTAACCAA TGGGTTTTGA AACCAATAAG TAAAGATTTA AACACTTACA GCAATATGAA ATTGGTGGTT GATAAGCGAG ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 6001 GCCGCCCGAC TGATACGTTG ATTTTCCAAG TTGAACTAGA TAGACAAATG GATCTCGTAA CCGAACTTGA GAACAACCAG ATAAAAATGA ATGGTGACAA ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 6101 AATACCAACA ACCATTACAT CAGATTCCTA CCTACGTAAC GGACTAAGAA AAACACTACA CGATGCTTTA ACTGCAAAAA TTCAGCTCAC CAGTTTTGAG ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 6201 GCAAAATTTT TGAGTGACAT GCAAAGTAAG CATGATCTCA ATGGTTCGTT CTCATGGCTC ACGCAAAAAC AACGAACCAC ACTAGAGAAC ATACTGGCTA ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 6301 AATACGGAAG GATCTGAGGT TCTTATGGCT CTTGTATCTA TCAGTGAAGC ATCAAGACTA ACAAACAAAA GTAGAACAAC TGTTCACCGT TAGATATCAA ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 6401 AGGGAAAACT GTCCATATGC ACAGATGAAA ACGGTGTAAA AAAGATAGAT ACATCAGAGC TTTTACGAGT TTTTGGTGCA TTTAAAGCTG TTCACCATGA ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 6501 ACAGATCGAC AATGTAACAG ATGAACAGCA TGTAACACCT AATAGAACAG GTGAAACCAG TAAAACAAAG CAACTAGAAC ATGAAATTGA ACACCTGAGA ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 6601 CAACTTGTTA CAGCTCAACA GTCACACATA GACAGCCTGA AACAGGCGAT GCTGCTTATC GAATCAAAGC TGCCGACAAC ACGGGAGCCA GTGACGCCTC ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 6701 CCGTGGGGAA AAAATCATGG CAATTCTGGA AGAAATAGCG CTTTCAGCCG GCAAACCTGA AGCCGGATCT GCGATTCTGA TAACAAACTA GCAACACCAG ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SC101 Origin 6801 AACAGC ~~~~~~ ......


Appendix C.

Appendix C: Repressilator Experiments This appendix describes two simple experiments with the repressilator, an oscillatory network composed of three repressor TFs: LacI represses TetR represses λ cI represses LacI. In the original experiment (Elowitz and Leibler, 2000), TetR also repressed the expression of GFP, where GFP was tagged with a moderate ssrA degradation signal (ASV, the repressors were tagged with a stronger signal LVA). The behavior of the ‘classic’ repressilator is noisy and unsynchronized: genetically identical daughter cells from the same parent rapidly become uncorrelated. The first experiment below describes a somewhat more appealing “christmas tree” version of the repressilator circuit. The second experiment confirms some underlying assumptions of the original design.

Making the repressilator “blink” One small mystery of the repressilator circuit was that the magnitude of the fluorescent GFP signal increased over time. This must be due to a changing environment: in the experimental protocol, the cells are first grown in liquid media before they are sandwiched between a slab of (the same) media with 1.5% low melting-point agarose and a coverslip, sealed, and grown within a temperature controlled chamber at 32°C. Since the cell culture is very dilute, some difference between the liquid- and solid-phase environments creates a steady increase in the average cellular fluorescence during microcolony growth. The resulting oscillations look more like the waves of an incoming tide than the steady pulse of a sine wave.

To make the oscillations more regular, I simply strengthened the GFP degradation tag. For this I used a different reporter plasmid pZE12-cfplva containing: the same origin of replication (ColE1), an ampicillin resistance marker (instead of kanamycin), a LacI controlled promoter (instead of a TetR controlled one) (Lutz and Bujard, 1997), CFP instead of GFP, and a strong ssrA degradation tag (LVA) instead of a moderate one (ASV). I used CFP for this experiment because it is very photostable—I didn’t want to accidentally bleach the reporter to get the desired result.

185

186


t = 1 hours

t=2 hours

t=3 hours The switch to the LacI regulated promoter was motivated by

t = 3.5 hours

our observation that has higher maximal activity than the TetR repressed one—in order to compensate for the reduced signal of

the destabilized CFP. To accommodate this new reporter plasmid, I swapped the antibiotic resistance marker in the original repressilator (ampicillin) for a spectinomycin resistance gene. Except for the antibiotics, the repressilator experiment was repeated as described (Elowitz and Leibler, 2000). With the new reporter plasmid, the oscillations become more pulse-like. Some daughter cells appeared to completely repress CFP expression, even after several hours of growth (~50 min

Appendix C.

/ division). These cells appeared to be “stuck” in a non-fluorescent state. No cells were found to persist in a fluorescent state for more than 2-3 cell cycles. This experiment revealed that sister cells carrying the repressilator can exhibit different oscillation periods, and that the noisy phenotype is exacerbated by asymmetry in the circuit components.

Three color oscillations The repressilator is a remarkably robust circuit. It is also genetically stable: after multiple generations, almost every cell containing the repressilator plasmids will oscillate when grown in a microcolony. The above experiments make use of promoter fusions controlling GFP variants to observe the repressor oscillations. Ideally, one would like to construct a repressilator circuit in which each repressor is tagged (protein fusion) with a different, distinguishable fluorescent protein. With only one fluorescent protein, we must infer that the reporter oscillations are representative of the underlying circuit behavior. With this simple three-repressor circuit, there are very few ways in which oscillations could be generated—we assume that LacI represses TetR, TetR represses cI, and cI represses LacI.

To verify this assumption, I constructed a repressilator containing three (stable) reporter genes with three promoter fusions. The reporter plasmid, pFE2-12R, is a variant of one of the constructs characterized in Chapter 3 (it only differs in the origin of replication, in this case it is ColE1). To avoid saturation of protein expression (Introduction, Figure 4), no degradation tags were used on the reporters. Here, TetR represses the cfp gene, LacI represses the yfp gene, and cI represses the rfp gene. To represent these colors, I use blue (cfp), green (yfp), and red (rfp).

The period of the repressilator is about 2 cell cycles, so it is possible to observe oscillations with these stable reporters: after a promoter is shut off, its reporter concentration will dilute to about a fourth of its maximal value before production starts anew. If we begin with a cell where cI concentration is high and LacI concentration is low, yfp will be high and rfp will be low (and the cell is green). In this state the TetR concentration will increase, so both cfp and cI will be on the decline.

187

188


As the cI concentration drops, rfp and LacI production will increase until the cell becomes red. This increase in LacI results in a decrease in TetR (along with yfp). When TetR has diluted sufficiently, the cell becomes blue.

The repressilator with reporter plasmid pFE2-12R reveals this directionality. Frame numbers correspond

to

ten-

minute increments; the movie shows microcolony growth from 120 to 510 minutes. Inspection the time-lapse images confirms this trend: green → red → blue → green. A repressilator with the inverse “wiring diagram” (LacI → c I → Te t R → L a c I ) would oscillate in the opposite direction: green → blue → red → green.

Appendix C.

References Elowitz MB, Leibler S (2000) A synthetic oscillatory network of transcriptional regulators. Nature 403: 335-338.

Lutz R, Bujard H (1997) Independent and tight regulation of transcriptional units in Escherichia coli via the LacR/O, the TetR/O and AraC/I1-I2 regulatory elements. Nucleic Acids Res 25: 1203-1210.

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Appendix D: Phage Circuits In this appendix, I discuss several regulatory circuits I designed and built from the “lambdoid phage” repressors. I initially examined four of these repressors: cI from λ, cI from 434, c2 from Salmonella phage P22, and the HK022 repressor protein. I used the sequences for the repressors and promoters available in the Biobricks parts registry (parts.mit.edu). The HK022 repressor has been reported to have an extremely high cooperativity, but its target promoters are extremely weak compared to the other three phages—I was not able to detect unregulated promoter activity with rfp. The remaining three phage promoters showed very strong activity: 434 was the strongest, followed by P22 and λ. I was able to control the expression of target promoters with the p22 and λ repressor genes—unfortunately, the 434 repressor did not effectively repress its target.

Noise distributions of lambdoid promoters Studies of stochastic noise in gene expression (Cai et al, 2006; Elowitz et al, 2002) have revealed transcription to be a bursty process. Transcripts are created in bursts, which occur during a transient active state of the promoter. Each transcriptional burst produces multiple mRNAs, and each mRNA can then produce several proteins. For an unregulated promoter, bursty behavior can be characterized with two noise parameters: the burst frequency a and the burst size b. These parameters describe a gamma distribution, a general stochastic form derived from the chemical master equation (Friedman et al, 2006). When the variance of autofluorescence is significant, the distributions are no longer gamma. For this reason, rfp is the optimal reporter for measuring burst parameters, since autofluorescence is barely detectable in the Crimson channel (Chapter 3). Experimentally, when a strong unregulated promoter drives the expression of a stable reporter protein such as RFP, these two parameters represent the number of transcriptional bursts per cell cycle (a) and the amount of fluorescence (in arbitrary units) generated by each burst (b). The burst size could be further calibrated in terms of proteins per cell (Rosenfeld et al, 2006)—here we use arbitrary units simply to compare the different promoters.

Appendix D.

Measurements of ~500 cells for

Cumulative Fraction

1

each of these three promoters

0.8

revealed a very good fit to a gamma

0.6

distribution. Interestingly, the burst

0.4

size b increased with promoter P22 434 L

0.2

0 0 100 200 300 400 500 Single-Cell P(R) promoter strength (AU)

strength while the burst frequency a remained roughly constant at about 40 bursts per cell cycle. Since the mRNA transcripts from all three

promoters are identical, this difference corresponds simply to the number of transcripts generated per burst. Biochemical studies have shown that strong promoters are rate-limited at the late stages of transcription initiation (Kammerer et al, 1986). We do not know why transcripts are produced in bursts, though these results indicate a functional link between the late stages of transcription and the number of transcripts produced during a burst. Promoter λ P(R) P22 P(R) 434 P(R)

Reporter rfp rfp rfp

Relative strength1 1.7 2.4 3.3

Burst size b 3.5-4.1 6.0-6.9 7.3-9.3

Burst frequency a 38-45 33-38 35-44

Noise inference of cooperativity We next asked whether genetic noise could be exploited to infer properties of gene regulation. A critical characteristic of any gene regulation system is the sharpness, or cooperativity, of the regulation. Circuit behaviors such as oscillation or bistability are sensitive to this property, which is frequently parameterized by an approximate Hill coefficient. It was recently shown that it is possible to make in vivo measurement of effective cooperativity using time-lapse movies (Rosenfeld et al, 2006). In that work, the repressor level was varied by dilution during growth. Here, we asked whether cooperativity 1

Median fluorescence relative to the Plac/ara1 promoter under the fully inducing conditions, measured in Chapter 3.

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could be inferred instantaneously, by using natural fluctuations to vary a transcription factor level, and observing correlations between its concentration and that of its target protein.

We built two variants of a synthetic repressor cascade. The first, on plasmid pFS1-1/2cI*/R, expressed a destabilized form of the λ cI repressor gene as an operon fusion with yfp. The cI-repressed promoter P(R) controls rfp. The second variant, pFS1-1/2cI*/R2, contained the same cascade circuit with the affinity-lowering OR2* point mutation in the P(R) promoter (Ptashne, 2005). Wild type (MG1655) cells containing each circuit were grown and measured in minimal media. Here, the “leaky” expression of cI* (i.e., without IPTG induction) was sufficient to partially repress rfp.

Figure 2. A repressor cascade (pFS1-1/2cI*/R). A noisy TF (green) regulates the epxression of an operon containing an unstable repressor (blue) and an operon fusion reporter (yellow). This repressor is actively degraded by the cell, and represses the expression of a second reporter gene (magenta). A third reporter (cyan) monitors the extrinsic noise in the circuit.

There was a distinct anti-correlation between the repressor operon (yfp) and its target genes (rfp). This indicated that the level of cI* expression was close to the threshold level required to repress the target promoters. The Hill equation captures this threshold response: P ( x) =

α xη 1+ η κ

Appendix D.

When the repressor concentration (x) is near the threshold level (κ) the output level is most sensitive to input fluctuations. Several factors contribute to output level fluctuations. Intrinsic (uncorrelated) noise contributes a purely stochastic component to the output level. Extrinsic noise between cells results in a positive correlation between the input and output levels. The intrinsic component of noise in the cI* 120

as is the extrinsic component of cI* noise.

100

Both of these contributions result in anticorrelation between the input and output. The ideal measurement system would have large intrinsic noise in cI*, and zero noise

Promoter Activity (RFP/CFP)

level is propagated through the cascade,

P(R2)

80 60 40 20 0

P(R)

(both intrinsic and extrinsic) for the other contributions. Since the MG1655 strain

102 103 Repressor Activity (YFP/CFP)

104

does not contain the TetR repressor, the cfp level reflects the extrinsic noise contribution. To account for extrinsic fluctuations, we normalized both the input (yfp) and output (rfp) levels by the constitutive (cfp) level. This correction mitigates the extrinsic noise contributions to cI* and the output, respectively. A plot of input versus output shows that the cell populations sample a large range of the promoter response functions.

We used these input-output distributions to fit the Hill function model. In each case, we measured the maximal promoter strength (α, arbitrary units) by deleting the cI* repressor gene from the circuit. We then fit the promoter threshold (κ, arbitrary units) and cooperativity (η¸dimensionless) to the distributions by a simple non-linear fitting algorithm (Matlab function nlinfit). We used a bootstrap (with replacement) sampling procedure to determine 95% confidence intervals for each parameter. The change in the cooperativity of the OR2* mutation is detectable, and goes from about 2.4 to about 1.7. These values agree with previous in vivo measurements of the stable cI repressor (Rosenfeld et al, 2006).

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Promoter Strength (α) λR 36.5-42.2 λ R2 78.1-86.9

Threshold (κ) 350-408 502-588

Cooperativity (η) 2.05-2.88 1.59-1.91

This experiment shows two important results. First, we can exploit genetic noise to infer quantitative parameters of a genetic circuit. In this case, we were able to determine the cooperativity parameter for two different promoters. Though we did not measure the circuit threshold and promoter strength directly, we were able to obtain consistent relative values by comparison of the two circuits. This shows that the (LVA) degradation tag on the cI repressor does not significantly change the response parameters: the effect of protein degradation is merely to lower the concentration (activity) of the repressor. Importantly, this result could not be determined with a repressor dilution method (Rosenfeld et al, 2006) which relies on the systematic lowering of repressor concentration during cell growth. The second result is that we were able to measure a promoter response function instantaneously, without any external circuit perturbation. Since the cI* activity was poised near its threshold, we did not need to induce any aspect of the circuit to infer its behavior. Since the experiment was instantaneous (i.e., snapshots), this method could be extended to flow cytometry measurements. The advantage here is throughput: it is conceivable to measure every single-input promoter response function in an organism such as E. coli with this method. All that is needed is to identify the TF and promoter of interest, use a noise source (such as LacI) to control the TF expression level, and tune the system so that the TF activity fluctuates about its threshold value (κ). Coupling this analysis with the rules for combinatorial promoter function (Chapter 2), we can hope to build a quantitative model of promoter function that takes into account regulation by multiple—noisy—interacting inputs.

Appendix D.

References Cai L, Friedman N, Xie XS (2006) Stochastic protein expression in individual cells at the single molecule level. Nature 440: 358-362. Elowitz MB, Leibler S (2000) A synthetic oscillatory network of transcriptional regulators. Nature 403: 335-338. Elowitz MB, Levine AJ, Siggia ED, Swain PS (2002) Stochastic gene expression in a single cell. Science 297: 1183-1186. Friedman N, Cai L, Xie XS (2006) Linking stochastic dynamics to population distribution: an analytical framework of gene expression. Phys Rev Lett 97: 168302. Kammerer W, Deuschle U, Gentz R, Bujard H (1986) Functional dissection of Escherichia coli promoters: information in the transcribed region is involved in late steps of the overall process. The EMBO journal 5: 2995-3000. Ptashne M (2005) Regulation of transcription: from lambda to eukaryotes. Trends in biochemical sciences 30: 275-279. Rosenfeld N, Perkins TJ, Alon U, Elowitz MB, Swain PS (2006) A fluctuation method to quantify in vivo fluorescence data. Biophys J 91: 759-766.

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Appendix E: A Synthetic Escherichia coli Predator-Prey Ecosystem

Lingchong You, Robert Sidney Cox III, and Frances H. Arnold

Abstract We describe synthetic ecosystems of interacting E. coli populations that communicate and influence each other’s behavior via de novo engineered genetic regulatory circuits. To establish cell-cell communication, we exploit components from “quorum sensing” systems that bacteria use to sense population density and coordinate behavior for diverse physiological functions. Mimicking mechanisms of programmed cell death, we use bacteriophage lysis genes to regulate population densities by controlling rates of cell death. Here we describe an ecosystem consisting of two types of cells that mutually regulate their gene expression and therefore survival; it resembles wellstudied predator-prey systems in terms of basic logic and dynamics. Numerical analysis shows that the circuit generates stable oscillations in population densities and intracellular gene expression for a wide range of biologically feasible parameter values. In addition, the analysis highlights the key design features required to achieve the target circuit function in an experimental system. Systems such as this, which couple genetic regulation and cell-cell communication, will allow us to explore the dynamics of interacting populations in a well-defined experimental framework.

Appendix E.

Introduction We wish to construct interacting Escherichia coli populations—in essence, synthetic ecosystems— using genetic regulatory networks and intercellular communications systems to control and coordinate the behavior. One goal is to explore how single-celled bacteria can be programmed to exhibit complex behaviors, reminiscent of multicellular organisms. A second goal is to build simple, artificial ecosystems, where we can observe how well-controlled exchanges of information, in the form of signaling compounds that regulate gene expression, manifest themselves in the dynamics of interacting populations. Here we describe a simple circuit design based on naturallyoccuring intercellular communications and genetic regulatory components that can convert E. coli into two populations whose dynamics mimic a predator-prey system.

We use the components of “quorum-sensing” systems to establish intercellular communication and coordinate behavior across a bacterial population. Many bacteria can sense their population density and coordinate a response via a small-molecule signal, called an autoinducer, that is produced intracellularly and can diffuse across the cell membrane into the medium(1, 2). The extracellular and, because they are coupled by diffusion, the intracellular concentrations of the signal reflect the density of the cells that are producing it. As the cell density increases, so does the total concentration of the autoinducer. When the intracellular concentration reaches a sufficient level, the autoinducer activates a cognate transcriptional regulator which further stimulates the production of autoinducer. This positive feedback results in a bistability: after a certain cell density all cells in the population express the autoinducer maximally. Other genes are also expressed in the same operon, including diverse physiological functions such as bioluminescence, pathogenicity, and biofilm formation. The use of quorum sensing in engineering applications has been demonstrated experimentally in recent work (3,20).

To construct populations that can interact in a programmable fashion, we want to connect

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198


intracellular communication to cell growth and survival. Here we chose to mimic mechanisms of programmed cell death (4–6) and use bacteriophage lysis genes to control death rates. The lysis genes encode proteins that effect cell death and/or cell wall disruption at the late stage of infection by lytic bacterial viruses (7). Previous studies have demonstrated that rates of cell death can be regulated by expressing lysis genes with inducible promoters (8–10). Here, we use lysis genes and quorum sensing components to engineer a feedback circuit in which two populations of cells communicate to control the death rate of the other.

Many different circuits, programming different fundamental ecological interactions, can be built from these basic components. Here, we present a prototype ecosystem consisting of two E. coli populations that mutually regulate their gene expression and survival in a manner similar to the classic relationship of predator and prey. Based on results from mathematical modeling and numerical analysis, we point out potential experimental strategies that will facilitate the desired system function.

Circuit Design The two E. coli population types, detailed in Figure 1, communicate and control each other’s population density by producing small-molecule signals (acyl-homoserine lactones, or AHLs) that can freely diffuse across cell membranes into the medium (11) and regulate gene expression. The dynamics are similar to a predator-prey system: without the ‘prey’, the ‘predator’ population decays at a high rate due to expression of a lysis gene it carries. As the prey grows, it produces an AHL that diffuses through the medium into the predator, where it rescues the predator by inhibiting lysis gene expression. The predator produces a second AHL that diffuses into the prey and initiates synthesis of the lysis gene, effecting “predation”. This circuit differs from a canonical predator-prey system in that, instead of acting as a food source, the prey provides an ‘antidote’. It satisfies the broader definition of predation for a two-species ecosystem, where one species suffers from the growth of the second and the second benefits from the growth of the first (12).

Appendix E.

We employ ordinary differential equations (ODEs) to model the major kinetic events during the functioning of this circuit, including cell growth and death, production, diffusion, and degradation of AHLs, production and degradation of transcriptional regulators, activation of the transcriptional regulators by AHLs, and regulation of lysis protein expression by activated transcriptional regulators. The resulting model contains 20 coupled ODEs and 40 kinetic parameters, many of which are as yet poorly characterized. Because the objective of this model is to capture overall dynamics of the underlying system, we followed conventional model reduction techniques to simplify it (13). Model reduction can also highlight parameters that have similar effects on system dynamics, which is useful for guiding experiments when “fine-tuning” system dynamics. By assuming that 1) concentrations of all interacting species other than the lysis proteins and the cells are at a quasisteady state, 2) cell densities (in volume fraction) are much smaller than unity, and 3) diffusion of AHLs is much faster than their degradation, we reduce the model to four differential equations: dc1 = c1 ( cmax1 − c1 ) / cmax1 − e1c1 dτ

1a

dc2 = μ c2 ( cmax 2 − c2 ) / cmax 2 − e2c2 dτ

1b

de1 κE1 = − δ E 1e1 dτ 1 + α1c2 β

1c

de2 κ E 2α 2c1β = − δ E 2e2 dτ 1 + α 2c1β

1d

All state variables and parameters in these equations are scaled with respect to the predator growth rate and written in a dimensionless form. Briefly, τ denotes time; c1 and c2 are the volume fraction of the predator and the prey, respectively; ei (i = 1 for predator or 2 for prey) lumps effects of the concentration and lethality of the lysis protein in the corresponding cell. We assume that cell growth follows logistic kinetics with a carrying capacity of cmaxi. We further assume that regulation by AHLs (via binding to transcriptional regulators) follows Hill kinetics, with a cooperativity of

β. The parameter μ represents the growth rate constant of the prey; κEi and δEi are the full synthesis

199

200


rate (uninhibited for the predator or fully induced for the prey) and the degradation rate constants of the corresponding lysis proteins; αi lumps effects of production, diffusion, and degradation of the corresponding AHL with the sensitivity of its target regulatory protein to AHL concentration.

Results and Discussion In addition to its resemblance to a predator-prey system in overall population dynamics, the system also demonstrates rich temporal patterns in intracellular gene expression. For example, a typical set of simulation results demonstrates stable oscillations in the cell densities and the concentrations of lysis proteins (Figure 2). Further analysis shows that the qualitative behavior of the system depends on parameters that directly affect accumulation of lysis proteins in either cell type, in particular, κE1, κE2, δE1, and δE2. Because δEi and κEi have opposite effects on the system dynamics, we focus our discussion on κEi. As shown in Figure 3a, the system has a stable steady state when κE1 is small. As κE1 increases, the steady state becomes unstable by passing a Hopf bifurcation point(14); it becomes stable again upon passing another Hopf bifurcation point. Between these two points the system generates stable oscillations, with amplitude that first increases and then decreases with increasing κE1. The system does not oscillate when κE1 is too κE1 small or too large. The system will fail to oscillate if = κ E 1 < δ E 1 ; under these 1 + α1c2 β c =0 2 conditions the predator will survive even without prey. Likewise, oscillation will fail when κE1 1 + α 1c m ax 2 β

> δ E 1 ; here, the predator will die even if the prey is in abundance. These inequalities

highlight how the system dynamics depends on the model parameters.

The system will also fail to oscillate if κE2 is small, due to insufficient regulation by the predator on the prey (Figure 3b). Unlike the case of κE1, however, the system continues to oscillate for large κE2 (Figure 3b). In this case, the maximum death rate of the prey is high. However, as the prey density drops to a low level, the predator density will eventually decrease because it needs the AHL from

Appendix E.

the prey to repress its lysis gene. As predator density drops, expression of the lysis gene in the prey will slow down, and the prey will resume growth. Mathematically, for any finite value of κE2, the κ E 2α 2c1β effective production rate of the lysis protein in the prey (represented by the term ) will 1 + α 2c1β approach zero with decreasing predator density, permitting the prey to recover.

The other parameters are less critical. For example, our results show that cooperativity in AHL action is unimportant: the system can oscillate for all β values equal to or greater than 1, which encompasses essentially all biologically feasible regimes. In addition, when the other parameters are held constant at their base-case values, either α1 or α2 can be changed over orders of magnitude with only minor effects on the qualitative behavior of the circuit (not shown). However, these variations can result in significant changes in the oscillatory region defined by κE1 and κE2, particularly in the case of α1. In general, the oscillatory region is larger for larger α1, because the κE1 κE1) for the lysis protein synthesis rate in the predator will be 1 + α1cmax 2 β broader. Interestingly, the same changes in α2 have no significant effect on the oscillatory region

regulatory range (

(not shown). These changes will have very minor effect on the regulatory range of the lysis protein κ αc β in the prey ( E 2 2 max1β ), whose upper limit is essentially constant (≈ κE2) when α2 > 100. 1 + α 2cmax1 These numerical results provide detailed guidance for experimental implementation. In particular, they highlight the importance of controlling the expression, lethality, and stability of the lysis proteins. This should be feasible, considering that a wide spectrum of phage λ holin gene mutants of varying lethality have been characterized(10, 15). In addition, production of the lysis proteins can be controlled by manipulating the strength of the corresponding promoters and ribosome binding sites. Our results indicate that oscillation is more likely when the accumulation rate and signaling sensitivity of AHL1 are large. This can be engineered by using strong promoters and ribosome binding sites for luxI, along with high copy number plasmids (if necessary). These design features should also reduce interference from intracellular noise. Our laboratory has demonstrated

201

202


that the function of a genetic circuit can be optimized by directed evolution (16), a well-established technology for improving protein functions in vitro and in vivo (17–19). In particular, directed evolution was used to achieve proper matching of the different components in the circuit, and allowed rapid optimization of a nonfunctional initial design. We anticipate that a similar strategy of mutagenesis and screening will facilitate tuning of kinetic parameters to achieve oscillatory behavior and will allow us to efficiently explore circuit function in different regions of the parameter space. Finally, we note that the idea of building synthetic ecosystems that incorporate population sensing and regulation goes well beyond the particular implementation described here. Addiction modules(6) that bacteria use to program death can be used in place of a lysis gene to regulate population density; the “killing” circuitry can also be reversed—to create a mutualistic relationship—by regulating a complementing gene to allow growth of an auxotroph.

Recent studies have demonstrated the feasibility of constructing xenobiotic input-output modules(20) and autonomous circuits that lead to stable(21), bi-stable(22), or oscillatory(23) gene expression. Yet these studies also indicate several engineering hurdles that may interfere with circuit function: noise in intracellular processes (24, 25), cell-to-cell variation across a population(23), and uncontrolled cell growth. These hurdles are likely to be overcome by the circuit design strategy described here. In particular, synchronization of intra-cellular behavior across a population, achieved by inter-cellular communication (26, 27), may render the circuit more resistant to noise in individual cells. And, by imposing limits on population densities, regulated cell death will allow a substantially wider time window for experimentation and characterization than offered by cell populations without density control.

In addition to addressing particular engineering challenges in genetic circuit design, these synthetic ecosystems will serve as well-defined systems for exploring evolutionary and ecological questions regarding, for example, the generation and maintenance of biodiversity (28-30) and the role of programmed cell death in bacteria (5). In these systems, there is a clear and explicit mapping

Appendix E.

between the genetic construct and population dynamics. This mapping illuminates one of the central questions in ecology(31): how interactions at the molecular level are manifested in the temporal patterns of population dynamics. Although the current circuit demonstrates predation, the basic design strategy can be applied in a straightforward manner to program other ecological interactions, including mutualism (or symbiosis), competition, commensalism and amensalism(12). For instance, mutualism can be established when two types of cells produce AHLs that repress cell death in each other. Similarly, cells can be programmed to synthesize AHLs that mutually activate cell death, thereby creating competing populations.

The essentially unlimited

configurations that are possible with these basic elements will allow us to study the interplay between environment, gene regulation and population dynamics. With the addition of control over population mixing or segregation, it will be possible to program bacterial populations to mimic development and differentiation in multicellular organisms.

Computational Methods The design and numerical analysis were carried out using modeling software Dynetica (32) (also see http://www.its.caltech.edu/~you). Stability and bifurcation analysis were carried out using XPP version 5.53 (http://www.math.pitt.edu/~bard/xpp/xpp.html) implementing a subset of a bifurcation analysis software AUTO.

Acknowledgments We thank Cynthia Collins, Jared Leadbetter, Lianhong Sun, Yohei Yokobayashi, Ron Weiss, and Erik Winfree for discussions and comments. This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Award No. N66001-02-1-8929. Disclaimer: Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the DARPA.

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Figure 1. A synthetic predator-prey ecosystem. We use two orthogonal quorum sensing modules to effect two-way communications between cell populations: the LuxI/LuxR system from the marine luminous bacterium Vibrio fischeri (33) and the RhlI/RhlR system from bacterium Pseudomonas aeruginosa(34). A lysis gene, such as the phage λ holin gene(35) or phage φX174 E gene(36), is used to regulate cell death. The gene is ON in the predator but OFF in the prey in the absence of regulation. The LuxI gene in rhlI

predator

AHL2

lactone (AHL1), which diffuses across the cell

E

RhlI

the prey leads to the synthesis of an acyl-homoserine

membrane into the medium and then into the AHL1

predator, where it binds and activates LuxR. Active LuxR represses transcription of the lysis gene (E1)

AHL2

AHL1 LuxI

E

luxI

prey

carried by the predator by binding to an engineered promoter containing a binding site for LuxR(37). The predator produces another AHL (AHL2) that diffuses into the prey, where it activates RhlR. Active RhlR activates transcription of the lysis gene

(E2) by binding to its native promoter. AHL turnover, necessary for the proper functioning of the circuit, can be modulated by varying the medium pH(38) or with enzymes (acylase or lactonase) that can degrade AHL(39, 40). The outer boxes represent cells; solid arrows represent activation or production; dotted arrows denote diffusion; bars represent inhibition or degradation. The cognate receptors (LuxR and RhlR) for the AHLs are expressed constitutively and are omitted from the figure for clarity.

Appendix E.

densities and lysis protein concentrations (E1 and E2 correspond to the predator and the

predator

0.05 0.04 0.03 0.02 0.01 0

Cell density

Figure 2. Simulated time courses of cell

prey, respectively) for the base parameter Concentration (nM)

0

setting: μ = 1; cmax1= cmax2 = 0.05; κE1 = κE2 = 2;

α1 = α2 = 500; δE1 = δE2 =1; β = 1.2. See Supplementary !"#$%&'*information for sources and justification of parameter values.

50

prey

100

150

E1

1000

205

E2

800 600 400 200 0 0

50

100

150

Time (hour)

Figure 3. Dependence of the steady-state prey density and/or its oscillation amplitudes on

(a)

-3 x 10

Prey density

$%&'*

+

0.05

4

High value of stable oscillation

2

0.04 0

0.8

1

1.2

1.4

0.03 Stable steady state

Unstable steady state

0.02 0.01

Prey density

0.05

2

4 N E1

6

8

10

250 , steady state that may be stable (thick - solid non-trivial

High value of stable oscillation

0.05

0

0.8

1

1.2

1.4

Stable steady state


Prey density

2

lines) or unstable (thin dotted lines), depending on

0.03

parameter

0.02

Stable values. Oscillations steady state

0.01

NE2

6

(thick dotted lines) 4 2

steady state

corresponding to the small box at the left corner, shows 0 10

0

2

4

6

0 0

8

5

in detail the first Hopf NE2 bifurcation with increasing κE1.

4 N E1

6

8

10

0.03

0 0

-

250

500

750

8

NE2

Stable steady state

2

4

N E2

6 4


0.01

Low value of stable oscillation

2

10

,

0.04

0.02

750

8

0.04

-3 x 10 4

500

result when theUnstable steady state is unstable. Inset in (a),

Low value of stable oscillation

0 0

κE1 and (b) κE2. The system will always have a

2

6

8

0 0

5

10

NE1

15

10

NE1

206


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The rest of the text is Written by Robert Sidney Cox III, Designed by Mercedes Paulino from February to December, 2007 A.D. God bless this work and all knowledge and applications derived henceforth. May the knowledge only be used with wisdom, prudence, benevolence and patience by all generations to come. In other words, don’t use this to screw things up because you are a scientist and think you’re more smarter than the rest of the monkeys. No matter how much more clever and patient you may think you are, you’re still a monkey.