Programming dynamic control of bacterial gene expression with the

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Programming dynamic control of bacterial gene expression with the chimeric ligand and light-based promoter system Premkumar Jayaraman, Jing Wui Yeoh, Jingyun Zhang, and Chueh Loo Poh ACS Synth. Biol., Just Accepted Manuscript • DOI: 10.1021/acssynbio.8b00280 • Publication Date (Web): 25 Oct 2018 Downloaded from http://pubs.acs.org on October 26, 2018

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ACS Synthetic Biology

Chimeric ligand and light-based promoter system 84x63mm (96 x 96 DPI)

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Programming dynamic control of bacterial gene expression with the chimeric ligand and light-based promoter system Premkumar Jayaraman1,2#, Jing Wui Yeoh1,2, Jingyun Zhang1,2 and Chueh Loo Poh1,2* 1Department

of Biomedical Engineering, Faculty of Engineering, National University of Singapore, Singapore. 2NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), Life Sciences Institute, National University of Singapore, Singapore. #Present address: Bioprocessing Technology Institute, Agency for Science, Technology and Research, Singapore. * Correspondence: [email protected]

TABLE OF CONTENTS *Refer to the separate attached file.

ABSTRACT To control cells in a dynamic manner, synthetic biologists require precise control over the threshold levels and timing of gene expression. However, in practice modulating gene expression is widely carried out using prototypical ligand-inducible promoters which have limited tunability and spatiotemporal resolution. Here, we built two dual-input hybrid promoters, each retaining the function of the ligand-inducible promoter while being enhanced with a blue light-switchable tuning knob. Using the new promoters, we show that both ligand and light inputs can be synchronously modulated to achieve desired amplitude or independently regulated to generate desired frequency at a specific amplitude. We exploit the versatile programmability and orthogonality of the two promoters to build the first reprogrammable logic gene circuit, capable of reconfiguring into OR/N-IMPLY logic on the fly in both space and time without the need to modify the circuit. Overall, we demonstrate concentration and time-based combinatorial regulation in live bacterial cells with potential applications in biotechnology and synthetic biology. KEY WORDS Optogenetics, dual-input hybrid promoter, reprogrammable logic, spatiotemporal control, dynamic gene regulation, and modelling.


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Over the past decade, synthetic biologists have developed genetic tools and circuits to control the behavior of living cells for various functions1, 2. Despite its potential, there has been little focus on developing methods for manipulating biological systems in a dynamic manner. We know from recent studies that cells coordinate their cellular activities through changes in concentration or localization of regulatory factors at different time scales, generating pulsatile dynamics3. Mimicking this nature’s ability to control the internal dynamics by varying both levels and timing could allow us to precisely tune or regulate gene expression for obtaining an optimal response3, 4. Conventionally, control of gene expression by means of ligand-inducible promoters is the broadly applied tool for perturbing protein levels2, 5. These simple ligand-responsive transcription factors in bacteria regulate cellular functions in response to environmental and metabolic signals. Thus far, there is a large repertoire of regulatory systems (e.g., AraC, RhaR, TetR, LacI, LuxR, etc.) that has been characterized to respond to their cognate effector molecules. Correspondingly, these regulatory systems have been utilized in a wide range of applications including synthetic gene circuitry development6, metabolic pathway engineering for production of recombinant proteins and value-added products in large scale7, 8, biosensor devices9, 10 and patterning of biomaterials11. Typically, ligand-based systems are largely steady-state processes and thereby it is extremely difficult to tune the output expression in a dynamic manner. For instance, once the cells are induced it is very difficult to reverse the expression and they have limited spatial resolution12. To reverse the state of expression, the system usually depends on either deprivation or decay of the ligand cues, either by wash-out13 or majorly using microfluidics14. This tedious process increases complexity and introduces significant delay in expression15 which limits their use to program temporal changes of gene regulation in cells. In addition, tuning the dynamic range of the gene expression driven by the promoter is generally achieved either by modifying the promoter regulatory sequences, varying ribosome binding site (5’-untranslated region) sequences or copy numbers of the plasmid4. These methods are time-consuming, labor-intensive and costly, requiring multiple rounds of trial-and-error optimization. In general, transcription regulation can be programmable by fine-tuning the molecular interactions through a combination of protein-DNA interactions16. To date, numerous multi-input promoter architecture have been built by incorporating two or more ligand-responsive transcription factor operator sites in a modular way for various functions17-22. In parallel, efforts to improve dynamic expression spectrum of the promoter by altering the -35 and -10 sites have led to the identification of multi-input hybrid promoters with better input and output relationships to tune the synthetic circuits23. However, methods that allow synchronous and independent control of the amplitudes, frequencies, and durations of gene expression to achieve dynamic control is currently lacking. Importantly, this would provide us the capability to incorporate pulsatile dynamics in synthetic circuits to achieve diverse functions3. To address this, we hypothesize that combining the properties of ligand and light-controllable system into a single chimeric promoter would allow us to program custom dynamic expression waveform with ligand concentration gradient for amplitude-control and light pulsing for frequency-control. In particular, light as an input is easily reversible and offers new ways to control cells precisely in both space and time12, 24. To this end, we aimed to amalgamate the effects of ligand-based induction and blue light-based repression into a single promoter. To generate the dual-input promoter architecture, we utilized a natural photosensitive DNA-binding protein (EL222) as a repressor for the hybrid promoter.



Previously25, we demonstrated that it is possible to develop a simple, compact and rapidly reversible blue light inducible and repressible promoter system based on the EL222 protein in E. coli. EL222 is one of the smallest photoreceptors and contains a blue light-sensitive N-terminal light-oxygen-voltage (LOV) domain and a C-terminal helix-turn-helix (HTH) 4α interdomain linker Jα -helix26. In the dark, EL222 is incapable of binding DNA because the LOV domain is bound to the HTH 4α -helix, held by the Jα -helix linker. In contrast, upon blue light irradiation, conformational changes in the LOV domain disrupt the interdomain linker Jα -helix. This disruption releases the LOV-HTH contacts to homodimerize and bind to DNA. Here, we developed two dual-input hybrid promoters that can be activated either by arabinose or N-(3-oxododecanoyl)-L-homoserine lactone (AHL) but repressible upon blue light illumination. In parallel, we also developed a kinetic model that was used to identify important parameters that could improve the promoter function and we also used the model to explain the promoter activity under different ligand and light signals. We demonstrated that our hybrid promoters can be tuned dynamically by simultaneous modulation of light and ligand cues. We went on to demonstrate that our hybrid promoters with the added new functionality of blue light switch can easily oscillate the expression of proteins at varying ligand concentration. Finally, we demonstrated the first reprogrammable logic function in living cells in both space and time. For this, we functionally layered the two dual-input promoters in a single cell. This forms a two-input (ligand-based) logic gate with blue light as a switch to reconfigure the logic from OR-gate (dark) to N-IMPLY-gate (illumination). Importantly we showed that this change was reversible over time. Taken together, this work provides a simple and modular research tool with regulatory flexibility for synthetic biologists to program both concentration and time-based combinatorial regulation in a much rapid and easier manner. METHODS Strains, reagents and plasmids The strain E. coli TOP10 (F- mcrA Δ( mrr-hsdRMS-mcrBC) Φ80lacZΔM15 Δ lacX74 recA1 araD139 Δ( araleu)7697 galU galK rpsL (StrR) endA1 nupG) was used for all characterization experiments. Unless otherwise stated, overnight cultures of E. coli were grown in Luria broth (LB) media at 37°C with shaking at 225 rpm. Characterization of the ligandinducible and light-repressible promoters and subsequent application studies were carried out using LB media. When appropriate, the antibiotics kanamycin (50 μg/ml) and chloramphenicol (25 μg/ml) were added to the media. Inducers were used in the following concentrations: 0-1 M AHL and 0-13.3 mM arabinose. All chemicals and media used were purchased from SigmaAldrich (Singapore). The backbone plasmids pBbE8k (JBEI Part ID: r r JPUB_000036, colE1 ori, Kan ), and pBbA8c (JBEI Part ID: JPUB_000038, p15A ori, Cm ) were purchased from Addgene (Cambridge, Massachusetts, USA)27. The ribosome binding sites used in this study were BBa_B0034 (rbs34) or the default RBS (rbsD) from the pBb series plasmids from Addgene27. The double terminator BBa_B0015 was used to terminate gene transcription in all cases28. All plasmids were constructed using Gibson assembly29 with NEBuilder HIFI DNA assembly master mix (New England Biolabs) and sequences were verified through Axil Scientific Pte Ltd. (1st BASE, Singapore). Primers and gene fragments (gblocks) were supplied by Integrated DNA Technologies, IDT (Coralville, Iowa, USA). All plasmid design and sequencing analysis were performed using the Benchling web-based sequence designer (Benchling, San Francisco, CA,


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USA). The sequences of the all the plasmids constructed in this study, with annotations of the promoters, RBSs, genes, and terminators, are given in Supplementary Text. All protocols for transformations and PCR and DNA manipulation used in this work were provided by Sambrook or the manufacturer’s manual and were optimized as needed30. Glycerol stocks of all cultures were made by mixing 500 μl of the overnight culture with 500 μl of 100% glycerol and stored at −80°C. For consistency, the overnight cultures for each experimental run were obtained by inoculation directly from their respective glycerol stocks. Illumination setup and microplate readings The illumination setup and experimental protocol used in this study are similar to those in our previously reported work25. For all the experiments, we fixed the light intensity at 12 W/m2. Briefly, all measurements were made in 12-well transparent, flat-bottom microplates (Nunc™) with 1 ml of total volume (exponentially growing test cultures (0.5 ml) mixed with 0.5 ml of prewarmed LB medium) in each well, distributed in triplicate. The microplate was moved into a minishaker incubator (NB-205, N-BIOTEK) with illumination (12-well plate mounted on top of our custom built 3x4 LED panel) or kept in the dark (covered with a black cloth covering all the edges) at 37°C with shaking (120 rpm) between each reading. Fluorescence data (excitation/emission wavelengths for GFP: 485/528 nm and RFP: 540/600 nm respectively) and optical density (OD600) time-course measurements were collected using a Synergy™ HTX Multi-Mode Microplate Reader (BioTek). Relevant control and blank measurements were also performed for each experimental run. Dual-input promoter design and characterization The pBAD promoter (arabinose-inducible promoter) in the pBbE8K backbone was modified by replacing the core region of the pBAD promoter with the EL222 binding region by designing flanking primers (Fwd: 5’…GGTAGCCTTTAGTCCATGTACTGTTTCTCCATACCCGTTTTTTTG…3’ and Rev: 5’…CATGGACTAAAGGCTACCCGTCAGGTAGAATCCGCTAATC…3’) to produce the modified pBbE8K backbone (pE8Kmod) consisting of pBRBAD-rbsD-RFP-B0015. The modified promoter is named pBRBAD (ctgacgGGTAGCCTTTAGTCCATGtactgt). The capital letters in the promoter sequence indicate the 18 bp EL222 binding region, and the underlined sequences indicate the -35 and -10 regions. Next, we modified the AHL-inducible promoter (plasI) in the QS108 plasmid from our earlier work9. Qs108 consists of B0015-RFP-rbsD-plasI-J23108-rbs34LasR-B0015. The transcription factor LasR that binds to AHL is expressed constitutively under the BBa_J23108 promoter with BBa_B0034 rbs (rbs34). The EL222 binding region is placed after the hypersensitive area of the plasI promoter31 after the -10 region by designing flanking primers (Fwd: 5’… CATGGACTAAAGGCTACCTAGCAAATGAGATAGATTTCGGTG…3' and Rev: 5’…GGTAGCCTTTAGTCCATGTTGCATAAATTCTTCAGCTTCCTA…3’). The modified promoter is named pBRlasI (aaatctatctcatttgctagttataaaattatgaaatttgcataaattcttcaGGTAGCCTTTAGTCCATG). The bold letters in the promoter sequence indicate the 20-bp las box (LasR binding region)31. The modified QS108 plasmid (pQSmod) then reads B0015-RFP-rbsD-pBRlasI-J23108-rbs34-LasR-B0015. To characterize the steady-state profile of the pBRBAD promoter, cells co-transformed individually



with pE8Kmod and pEL222 were transferred into 12-well plates and induced with arabinose concentrations of 0 mM, 0.00133 mM, 0.0133 mM, 0.133 mM, 1.33 mM and 13.3 mM under varying pulse illumination (0%, 8.333%, 25%, 50%, 75% and 100%). Similarly, the transfer function of the pBRlasI promoter was obtained by growing the cells carrying pQSmod and pEL222 induced with varying AHL concentrations (0 µM, 0.0001 µM, 0.001 µM, 0.01 µM, 0.1 µM and 1 µM) under varying pulse illumination. The plates were moved into the mini-shaker incubator, and the microplate readings were recorded every 1 h for a total period of 6 h. For characterization of the dynamic profiles of the two promoters, co-transformed cells were transferred into 12-well plates with arabinose (0.133 mM, 1.33 mM and 13.3 mM) or AHL (0.001 µM, 0.01 µM, 0.1 µM) for 8 h total in a 2 h-OFF‒ON‒OFF‒ON cycle. Microplate readings were recorded every 30 min. Reprogrammable logic circuit design and characterization We constructed two different plasmids to characterize the reprogrammable logic circuit in E. coli. The plasmid backbone pBbA8C containing the pBAD promoter was used to drive the EL222 gene, resulting in the pBAD-rbs34-EL222-B0015 (pAEL222) plasmid. Next, the plasmid backbone pBbE8K was used to construct the pRPLC plasmid with both the pBRBAD and pBRlasI promoters driving RFP expression individually, placed in parallel to each other. That is, pRPLC now reads as pBRBAD-rbsD-RFP-B0015-B0015-LasR-rbs34-J23108-pBRlasI-rbsD-RFP-B0015. Cells cotransformed with pRPLC and pAEL222 plasmids and grown to the exponential growth phase were transferred into 2 x 12-well plates. Each column had its own input conditions loaded in triplicate, i.e., column 1: no inducers, column 2: arabinose (13.3 mM), column 3: AHL (0.01 µM), and column 4: both arabinose (13.3 mM) and AHL (0.01 µM). Both the plates were moved into the mini-shaker incubator with one kept in the dark and the other illuminated for the total experimental period of 6 h. Subsequently, the plates were moved to the microplate reader, and readings were taken every 1 h. For measuring the reprogrammable logic change over time, we performed the same experiment as mentioned above with 1 x 12-well plate in 2 h-OFF‒ON‒OFF‒ON cycle. Microplate readings were recorded every 30 min for the total period of 8 h. Spatial pattern formation The illumination device and the agar plate preparation used in this study are similar to our previous work25. For this study, we modified the pRPLC plasmid by replacing the RFP under pBRlasI with GFP. The modified pRPLC_mod reads pBRBAD-rbsD-RFP-B0015-B0015-LasR-rbs34-J23108pBRlasI-rbsD-GFP-B0015. Briefly, overnight cultures co-transformed with pAEL222 and pRPLC_mod plasmids were mixed homogenously with the soft agar solution. The plate was left to dry for 5 min and sterile forceps was used to place an empty disc on the center of the dried soft agar. Test conditions: (a) No inducers: Plate contained only soft agar solution with cells and empty disc. (b) Plate contained only soft agar solution with cells and disc loaded with 40 µl of 133 mM arabinose. (c) Plate contained soft agar solution with cells and 0.01 µM AHL mixed and poured with disc loaded with 40 µl of DI water. (d) Plate contained soft agar solution with cells and 0.01 µM AHL mixed and poured with disc loaded with 40 µl of 133 mM arabinose. The test conditions plates were prepared in duplicates and one was kept in dark covered with black cloth and the other was exposed to blue light. The whole setup was kept inside the incubator at 37°C and photographs


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were taken under UV illumination after 18–20 h of incubation. Post-processing of the images by adjusting both brightness and contrast was performed using GIMP 2.10.2 image editor tool. Mathematical modelling to understand dual-input promoter dynamics To gain quantitative insights into the dynamics of the dual-input, ligand-inducible and blue lightrepressible promoter system, we built kinetic models accounting for key reactions involved in the functioning system and described their kinetics in terms of ordinary differential equations (ODEs) after applying the law of mass action kinetics (Supplementary Table 1-4). First, an empirical phenomenological formalism was used to reproduce the sigmoidal growth pattern of the experimental cell density profile, and the inducer concentration-dependent behaviors were well represented by Hill equations. Thereafter, the gene expression dynamics of the pBRBAD and pBRlasI inducible promoters were modelled by a separate system of two non-linear ODEs to elaborate the transcription and translation activities. Next, a combined equation was used to represent the intricate underlying blue light-inducible EL222 activation kinetics upon triggering by different illumination pulses, followed by the incorporation of the blue light-mediated repression into the transcription processes. Ultimately, the same framework was extended to describe the temporal control of expression dynamics regulated by the dual-input promoter system. All simulations were performed in Matlab R2016b (Mathworks, MA). The system of ODEs was numerically integrated using a variable-step continuous solver. The model parameters were then estimated using an unconstrained and a boundary constrained optimization algorithm based on a Nelder-Mead simplex search method, which is accessible in the Matlab Optimization toolbox (Supplementary Table 5 and 6). The optimization tool was implemented to facilitate the fitting of the model to multiple experimental data simultaneously by minimizing the weighted sum squared residuals for each individual data set. A comprehensive description of the model is detailed in the Supplementary Text. Data analysis The fluorescence/OD600 (Fluo/OD600) of a sample culture at a specific time was determined after subtracting from each of the technical triplicate readings of the negative (fluorescence-free) control cultures at the same time. The fluorescence synthesis rate (Fluo.OD600−1/min) of any sample at time ‘t’ was calculated by taking the difference between Fluo/OD600 values at two time points and dividing the result by the time interval δt. The Fluo/OD600 values were normalized into a new arbitrary range (min = 0) to (max = 1) using the observed min and max values from the original dataset. Statistical significance was determined by performing a one-way ANOVA test using Prism 7.0a (GraphPad Software, Inc., CA, USA). A p-value 2-fold) in the presence of blue light compared to the dark state (Fig. 1b and 1d). This feature is important for studies that require tight regulation of gene expression. The ability to tune the response curve based on certain input conditions is important to achieve the desired output function4. The steady-state response profiles of the dual-input promoters were characterized by titration with varying ligand concentrations and blue light illumination pulses, as shown in Fig. 2a and 2b; Supplementary Figs. 2 and 3. For each curve, the ligand concentrations were fixed at certain levels, while varying the blue light illumination pulse ON-OFF cycle. Strikingly, we were able to achieve a wide range of steady-state response curves which is difficult


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to achieve just by varying ligand concentrations. The model-predicted dose-response for both promoter systems are in good agreement with the experimental results. Based on the model, it was observed that the blue light repression affinity on both pBRBAD and pBRlasI promoter systems were not constant but concentration-dependent (Supplementary Text). At high inducer concentrations, our model revealed a reduction in the blue light repression affinity on the transcription initiation or elongation processes. This behavior might occur because, at maximum induction, most of the promoters would be bound to RNA polymerase (RNAP), hindering the ability of EL222 to reach and bind to DNA and thereby reducing the repression level. This insight from the model suggests that at any level of inducer concentrations, the magnitude of blue light illumination pulses should be properly manipulated in order to achieve an effective repression capability. To tune the profile of the output response curve of a promoter, one of the conventional methods is to modify RBSs to alter the efficiency of translation initiation, which requires the design and development of many different constructs based on the established libraries10, 37, 38. Fig. 2c and 2d demonstrate the corresponding model predicted pBRBAD and pBRlasI promoter systems expression profile driven by different RBSs in the absence of blue light illumination. The relative strength of the RBSs were derived from a recent study by Wang et al. with the same backbone plasmid39. Interestingly, incorporating the light-controllable feature to the ligand-inducible system enables one to assess the wide dynamic range of expression window (similar to that obtained by varying the RBSs as predicted from our model) to fine tune the system of interest to the desired absolute expression level, by simply manipulating the illumination pulse tuning knob and the inducer concentration. This eliminates the need to construct combinatorial variants using library of RBS sequences/promoters during the fine-tuning stage10, 38. Overall, these results demonstrate the ability to dynamically tune the dual-input promoter’s output response over a wide range when exposed to varying dosages of inducers (for activation) and blue light illumination pulses (for repression). Temporal control dynamics of dual-input promoter system Understanding the promoter’s temporal dynamics both from experiments and mathematical modelling is crucial to determine how light pulsing should be generated and controlled. In line with this, we tested the temporal control of expression over 8 h duration in a 2 hOFF‒ON‒OFF‒ON cycle using three different inducer concentrations to generate high-, mediumand low-level expression amplitudes (Fig. 3). The model simulations correlate well with the experimental data, recapitulating the system behavior closely (Fig. 3 and Supplementary Fig. 4). As shown in Fig. 3a and 3c, during the first 2 h illuminated ‘OFF’ cycle there was a significant initial delay in the pBRBAD-activation curve for all three arabinose concentrations tested. Further, the modelling results of the pBRBAD system show that the delay in mRNA abundance during the first 2 h-OFF cycle is higher at lower arabinose concentrations (Fig. 3e). Presumably, this delay could be because the active transport system for arabinose uptake is slower than the fast diffusion mechanism for AHL. Interestingly, the delay in expression decreased with increasing arabinose concentrations. It has been shown that the expression of the arabinose transport protein AraE is controlled by arabinose (autocatalytic positive feedback loop)40. Thus, at low arabinose



concentrations, there would not be enough AraE expressed to import arabinose into the cell, which might contribute to the delay. In the second OFF-ON cycle, there was a rapid increase in mRNA abundance once the blue light was switched ‘OFF’ with minimal delay (Fig. 3e), probably due to the increased in the internal concentration of arabinose that has accumulated over time. In the case of the pBRlasI promoter, the model reveals no delay in the first OFF‒ON cycle, but there is a critical delay period of 90 mins, irrespective of the AHL concentrations, in the subsequent OFF‒ON cycle (Figs. 3b and 3d). This behavior might be due to the delayed activation in the second ‘OFF’ phase in combination with subsequently delayed repression at the transcription elongation phase in the second ‘ON’ phase. Our model reveals that there was a slow increase in mRNA abundance for the pBRlasI promoter during the second OFF‒ON cycle (Fig. 3f). It has been shown that the activation of these quorum-controlled promoters is quite complex, and a number of factors such as LasR-AHL complex stability, the recruiting of RNA polymerase due to the LasR-AHL complex binding to the las box, and the interaction of the LasR-AHL complex with RNA polymerase could contribute significantly to the promoter strength and the timing of induction36. This suggests that the LasR-AHL complex concentration could be saturated during the first OFF‒ON cycle, and the delay in activation during the second 2 h-OFF phase might be due to the combined effect of LasR-AHL complex instability and the delay in transcription initiation caused by the RNA polymerase recruiting mechanism. Unlike the pBRlasI promoter, the model shows that the pBRBAD promoter exhibits a delay in blue light repression and that the delay behaves in an inducer concentration-dependent manner, meaning that there is an increase in time delay for blue light repression with decreasing arabinose concentrations (Figs. 3g and 3h). We next analysed the model to provide useful quantitative information that could potentially facilitate future experimental designs. To achieve higher blue light-mediated repression capability, proper control of the temporal duration of ligand induction and the presence of blue light illumination could be a crucial factor. We thus proceeded to examine the effect of a range of different ‘OFF’ and ‘ON’ duration combinations on the level of repression efficiency. The repression efficiency was computed based on the simulated peak and final mRNA expression level at the end of the first OFF‒ON cycle. Contour representations illustrating the different ‘OFF’ and ‘ON’ duration combinations for both pBRBAD and pBRlasI promoter systems (1.33 mM arabinose; 0.1 µM AHL) are shown in Supplementary Figs. 5 and 6. This information could serve as a reference for tuning the durations of induction and repression to achieve the desired repression capability in future temporal control studies. The figures show that the repression capabilities increase with increased ‘ON’ time, which represents the duration under ligand induction. This suggests that the longer the induction duration, the higher the expression level and thus more promoter binding sites are available for EL222 binding to sterically hinder RNAP or mRNA elongation. Further, it would be of interest to examine how the repression capability of our promoter system could be improved. The results from the model simulations suggest that an increase in the parameter controlling the rate of blue light repression kinetics could greatly enhance the repression efficiency for both promoter systems, as shown in Supplementary Fig. 5c and 5d. The effect appeared to be more profound in the pBRBAD promoter system, as can be observed from the


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markedly increased repression efficiency values represented by the color bar after a 4-fold increase in the blue light activation parameter. The model was also used to study the temporal behavior of the promoters over a prolonged period of 24 h using the same blue light activation and deactivation cycle period (Supplementary Figs. 7 and 8). Interestingly, the model predicts synchronous oscillatory behavior with the progressive delay over the period. Taken together, the dual-input promoters offer different temporal dynamics profiles based on the difference in the inducer’s activation kinetics, which is interconnected with the blue light repression kinetics, and vice versa. Reprogrammable logic gene circuit based on layered dual-mode promoters One recent functionality in the field of electronics that is gaining momentum is the ability to reconfigure the hardware on the run for superior functionality41. These devices are programmed to perform different logic functions by simply tuning the input conditions. This ability is important because these devices impart multiple logic functions by dynamically switching among logics without having to change the circuit, which also minimizes the need to wire multiple components to perform complex logic calculations. Based on this interesting approach, we built a reprogrammable logic gene circuit for living bacteria cells by layering the two dual-input promoters in a manner that we would achieve two different logics when blue light is turned ‘ON’ or ‘OFF’. In this gene circuit, the expression of the EL222 protein is driven by the pBAD promoter. This circuit has two data inputs (i.e., arabinose and AHL) and two selection inputs (blue light ‘OFF’ or ‘ON’). Based on either selection input, the logic function will be varied (Fig. 4a). For instance, the cells will perform an OR gate function when the selection input blue light is ‘OFF’ (Fig. 4b), resulting in strong RFP expression upon induction with arabinose (35-fold), AHL (58fold) or both arabinose and AHL (46-fold) respectively. When the selection input is ‘ON’, the cells instead perform N-IMPLY logic (Fig. 4c), resulting in 38-fold expression when treated with AHL only. Simultaneous induction with both arabinose and AHL (6.3-fold) or induction with arabinose (3.4-fold) results in modest activation. In parallel, we investigated whether our reprogrammable logic function can be demonstrated spatially (Fig. 5). To achieve this, we first replaced the RFP gene encoded under pBRlasI promoter with GFP in pRPLC plasmid into pRPLC_mod (see Methods) to differentiate between the two inputs. For all the input conditions, we prepared two sets of plates and each of the plate was placed in dark and blue light conditions accordingly. Cells co-transformed with pRPLC_mod and pAEL222 was poured as lawn culture in a soft agar solution with or without AHL. A disk loaded with either DI water or arabinose was placed on the middle of the plate. As seen in Fig. 5, cells exposed to arabinose and kept in dark formed a RFP ring corresponding to the ligand diffusion area. Also, cells mixed with AHL expressed GFP lawn irrespective of being kept in dark or illumination conditions. Similarly, in the dark when the cells were exposed to both arabinose and AHL both the RFP ring and the outer green fluorescent ring were observed, creating a bull’s eye pattern (OR-logic). Conversely, when exposed to blue light, the expression at the region exposed to arabinose was repressed and the RFP ring was not present. While the region out of arabinose diffusion and when AHL was present, GFP was expressed (N-IMPLY logic). Next, we sought to demonstrate dynamic temporal change in logic with one-cycle (3 h-OFF‒ON) and two-cycle (2 h-OFF‒ON‒OFF‒ON) illumination pattern (Supplementary Fig. 9 and Fig. 6).



From both the experiments, the cells exhibited OR-logic (based on synthesis rate) in the first ‘OFF’ period as the output was high when either one or both ligand inputs were present. In the subsequent ‘ON’ period, cells rapidly switched from OR-logic to N-IMPLY logic function where the gene expression occurred only when AHL was present and arabinose was absent (Supplementary Fig. 9 and Fig. 6). In the case of the two-cycle study, the following 2 h-OFF period cells reverted back to OR-logic and re-illumination of light in the final 2 h-ON period, the N-IMPLY logic function was restored back again (Fig. 6). More importantly, we observed smooth ON-OFF curve without any delay in repression (Fig. 6a and Supplementary Fig. 9a). This is in line with our model’s prediction that by increasing the EL222 concentration which in this case is under pBAD promoter with maximal induction (Supplementary Fig. 5 and 6), could greatly enhance the repression efficiency for both promoter systems. Overall, this circuit can regulate the same cells to perform either OR/N-IMPLY logic spatiotemporally by switching the blue light selection signal. DISCUSSION and Gradual Control of Microbial Gene Expression To date, ligand and light-controllable systems which have evolved from disparate pathways have been characterized independently in prokaryotes. In this study, we built two novel dual-input hybrid promoters controllable by both ligand and light by integrating the blue light switch into the existing ligand-inducible promoter system (Fig. 1). The resulting chimeric architecture allows gene expression to be tuned dynamically to achieve desired amplitude by simultaneously varying both the inducer concentrations and the illumination pulse dosages in conjunction (Fig. 2). This feature allows the creation of a wider range of different expression levels, which extends the static transfer functions achieved by varying only the inducer concentrations or illumination pulse independently. Ideally, the blue light switch can serve as a genetic rheostat in vertically scaling the response curves without the need to physically modify the RBS strength or through copy number optimization. This ability should prove useful for rapid prototyping of synthetic gene networks and applications that face difficulty in finding the optimum expression level to control the timing of delivery and dosage of therapeutics in a dynamic manner10, 42, 43. In addition, with the hybrid promoter we can now fix a certain inducer concentration to achieve desired amplitude and independently modulate the blue light illumination cycle to create oscillation at a particular frequency (Fig. 3). This useful property can enable dynamic control of gene expression (e.g., shutting down or resuming) at varying levels at defined time points using blue light as a tuning knob. In fact, from previous studies we know that periodic pulsing of enzyme expression has been shown to increase yields44, 45. In addition, it is now possible to create patterns with inducer gradient as demonstrated previously46 coupled with light irradiation which could restrict regions of induction to derive complex spatial resolutions as shown in Supplementary Fig. 10. Potentially, cells with our hybrid promoters can be grown in the presence of chemical and light for studies that require tight regulation and spatiotemporal organization such as patterning of materials11. Recently, in silico-based feedback control has been applied for real-time control of gene expression47-50. Typically, based on the difference between the observed and target expression levels, a computer algorithm automatically maintains the desired output condition by tuning the input signal. Successful application of such external feedback control would require fast, precise


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and reversible means to regulate the gene expression in real-time. Nonetheless, programming accurate expression level remains currently limited. We anticipate that our dual-input promoters with the combined ligand and light mediated co-regulation with two orthogonal control parameters which can be adjusted synchronously and independently would be more optimal for accurate realtime programming in a number of applications, including metabolic engineering51, debugging of complex genetic circuits47 or characterization of host effects such as burden52. Due to its simplicity, it is also possible to layer these promoters to create a distinct reprogrammable logic function using blue light as a switch (Figs. 4-6). This circuit is unique in its behavior because a single cell can be reprogrammed to toggle the logic function spatiotemporally between an OR gate (blue light 'OFF’) and an N-IMPLY gate (blue light ‘ON’) without the need to reconfigure the circuit architecture. Importantly, this can be done on the fly with simple switching of light and in a reversible manner. Perhaps, this transcriptional reprogramming circuit or these hybrid promoters can be used to study phenotypic switching53, 54 to better understand developmental processes and to model biological pattern formation for applications such as biomaterial fabrication, tissue engineering, and regenerative medicine55. Using in silico hypothesis testing, our model has enhanced our understanding on the potential mechanisms underlie the system and unraveled some unintuitive system’s behaviors. For instance, the model uncovers the non-linear relation between illumination pulses and inducer concentrations. Further, we also reveal the concentration-dependent initial delay in pBRBAD activation and the blue light repression which could be due to its autocatalytic mechanism. On top of that, our model analysis has identified the key parameter for boosting the system performance with improved repression efficiency. Nevertheless, it could still be challenging to precisely predict and control the expression level in real time using a predetermined set of parameters from our existing system, due to the potential multifactorial variations. Incorporating parameter uncertainties into model predictions as deployed in the system by Olson EJ et al. could be useful for better model predictions24. To better capture system dynamics, the maturation time of the fluorescent protein which may cause significant delay is an important consideration, particularly for predictive real-time monitoring and control system. In our existing system, the reporter red fluorescent protein mRFP1 used was determined to exhibit a fast maturation rate (half time to maximum fluorescence) of approximately 22 min60. A good agreement was observed between our current model and experiments and has advanced our understanding of the new system. However, it is important to note that the maturation rate of the reporter should be considered for programming precise and accurate tailor-made gene expression feedback control system, as demonstrated in a previous study24. Overall, our approach is distinct from prior studies in mammalian cells that did not explore temporal control of dynamics produced by the interplay of both ligand and light systems. For instance, Chen et al. engineered a set of chimeric promoters that simultaneously responded to tetracycline and blue light for spatial control of toxin gene expression for gene therapy56. Liu et al. built a synthetic circuit that can respond simultaneously to multiple light and ligand outputs57. Finally, our approach can be easily adapted to other commonly used ligand-inducible promoters with only minor refactoring and could be applied in prokaryotic hosts other than E. coli. Additionally, more in-depth mechanistic understanding on the interplay between ligand and light-



inducible regulatory elements could be achieved in future work through thermodynamics-based protein-DNA binding models and experimental technologies58, 59. In conclusion, we present hybrid promoters which enables the dynamic regulation of gene expression with the combination of ligand and light inputs. We have demonstrated rapid and reversible control of ligand-inducible promoters by adding a blue light tuning knob, complementing these frequently used traditional systems. We anticipate that these tools with the versatile programmability will have broader applications in synthetic biology as a standard genetic perturbation method. AUTHOR CONTRIBUTIONS P.J. and C.L.P. conceived the project. P.J. designed and performed the experiments and analysed the data. J.W.Y. constructed the kinetic model and analysed the data. J.Z carried out spatial and temporal control of reprogrammable logic circuit characterization experiments. P.J and J.W.Y. wrote the manuscript with inputs from C.L.P. All authors commented and approved the manuscript. ACKNOWLEDGEMENTS This work was supported by an NUS Startup Grant and MOE AcRF Tier 1. SUPPORTING INFORMATION Detailed model development, analysis and predictions, additional figures, including plasmid sequences and tables with model equations and parameters,

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31. Rampioni, G.; Bertani, I.; Zennaro, E.; Polticelli, F.; Venturi, V.; Leoni, L., The Quorum-Sensing Negative Regulator RsaL of Pseudomonas aeruginosa Binds to the lasI Promoter. J. Bacteriol. 2006, 188 (2), 815-819. 32. Song, J.; Ryu, H.; Chung, M.; Kim, Y.; Blum, Y.; Lee, S. S.; Pertz, O.; Jeon, N. L., Microfluidic platform for single cell analysis under dynamic spatial and temporal stimulation. Biosens. Bioelectron. 2018, 104, 58-64. 33. Piehler, A.; Ghorashian, N.; Zhang, C.; Tay, S., Universal signal generator for dynamic cell stimulation. Lab Chip 2017, 17 (13), 2218-2224. 34. Schleif, R., AraC protein, regulation of the l-arabinose operon in Escherichia coli, and the light switch mechanism of AraC action. FEMS Microbiol. Rev. 2010, 34 (5), 779-796. 35. Soma, Y.; Hanai, T., Self-induced metabolic state switching by a tunable cell density sensor for microbial isopropanol production. Metab. Eng. 2015, 30, 7-15. 36. Schuster, M.; Urbanowski, M. L.; Greenberg, E. P., Promoter specificity in Pseudomonas aeruginosa quorum sensing revealed by DNA binding of purified LasR. Proc. Natl. Acad. Sci. U. S. A. 2004, 101 (45), 15833-15839. 37. Wang, B.; Kitney, R. I.; Joly, N.; Buck, M., Engineering modular and orthogonal genetic logic gates for robust digital-like synthetic biology. Nat. Commun. 2011, 2, 508. 38. Wong, A.; Wang, H.; Poh, C. L.; Kitney, R. I., Layering genetic circuits to build a single cell, bacterial half adder. BMC Biol. 2015, 13 (1), 40. 39. Wang, H.; Ling, M. H. T.; Chua, T. K.; Poh, C. L. Two cellular resource-based models linking growth and parts characteristics aids the study and optimisation of synthetic gene circuits Eng. Biol. 2017, 1(1), 30-39. 40. Siegele, D. A.; Hu, J. C., Gene expression from plasmids containing the araBAD promoter at subsaturating inducer concentrations represents mixed populations. Proc. Natl. Acad. Sci. U. S. A. 1997, 94 (15), 8168-8172. 41. Hafiz, M. A. A.; Kosuru, L.; Younis, M. I., Microelectromechanical reprogrammable logic device. Nat. Commun. 2016, 7, 11137. 42. Jayaraman, P.; Holowko, M. B.; Yeoh, J. W.; Lim, S.; Poh, C. L., Repurposing a Two-Component System-Based Biosensor for the Killing of Vibrio cholerae. ACS Synth. Biol. 2017, 6 (7), 1403-1415. 43. Ruder, W. C.; Lu, T.; Collins, J. J., Synthetic Biology Moving into the Clinic. Science 2011, 333 (6047), 1248-1252. 44. Zhao, E. M.; Zhang, Y.; Mehl, J.; Park, H.; Lalwani, M. A.; Toettcher, J. E.; Avalos, J. L., Optogenetic regulation of engineered cellular metabolism for microbial chemical production. Nature 2018, 555, 683. 45. Sowa, S. W.; Baldea, M.; Contreras, L. M., Optimizing Metabolite Production Using Periodic Oscillations. PLOS Comput. Biol. 2014, 10 (6), e1003658. 46. Basu, S.; Gerchman, Y.; Collins, C. H.; Arnold, F. H.; Weiss, R., A synthetic multicellular system for programmed pattern formation. Nature 2005, 434, 1130. 47. Lugagne, J.-B.; Sosa Carrillo, S.; Kirch, M.; Köhler, A.; Batt, G.; Hersen, P., Balancing a genetic toggle switch by real-time feedback control and periodic forcing. Nat. Commun. 2017, 8 (1), 1671. 48. Menolascina, F.; Fiore, G.; Orabona, E.; De Stefano, L.; Ferry, M.; Hasty, J.; di Bernardo, M.; di Bernardo, D., In-Vivo Real-Time Control of Protein Expression from Endogenous and Synthetic Gene Networks. PLOS Comput. Biol. 2014, 10 (5), e1003625. 49. Milias-Argeitis, A.; Rullan, M.; Aoki, S. K.; Buchmann, P.; Khammash, M., Automated optogenetic feedback control for precise and robust regulation of gene expression and cell growth. Nat. Commun. 2016, 7, 12546. 50. Uhlendorf, J.; Miermont, A.; Delaveau, T.; Charvin, G.; Fages, F.; Bottani, S.; Batt, G.; Hersen, P., Long-term model predictive control of gene expression at the population and single-cell levels. Proc. Natl. Acad. Sci. U. S. A. 2012, 109 (35), 14271.


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FIGURES



Figure 1. Design and characterization of ligand-inducible and blue light-repressible hybrid promoters. (a) Schematic of pBRBAD promoter characteristics. In the presence of arabinose and kept in dark, conformational change in the AraC binding allows transcription and expression of RFP reporter. However, in the presence of both arabinose and blue light, EL222 sterically blocks transcription initiation and represses RFP expression. (b) Logic output and response function measurement of the pBRBAD promoter. The arabinose concentration used was 13.3 mM. (c) Schematic of pBRlasI promoter characteristics. In the presence of AHL and kept in dark, LasRAHL complex binds to the pBRlasI promoter and enables transcription initiation and the expression of RFP reporter. In contrast, in the presence of both AHL and blue light, EL222 blocks the transcriptional apparatus elongation, thereby represses RFP expression. (d) Logic output and response function measurement of the pBRlasI promoter (Bottom). The AHL concentration used was 1 µM. The statistical significance of ****P < 0.0001 was calculated based on one-way ANOVA. All data are represented as mean ± s.d (n = 3).


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Figure 2. Dose-response curves of ligand-inducible and blue light-repressible hybrid promoters. Transfer functions of (a) pBRBAD and (b) pBRlasI promoters induced with varying ligand concentrations and blue light illumination pulse. The illumination pulse (%):0% (OFF), 8.33% (5 s ON; 55 s OFF), 25% (15 s ON; 45 s OFF), 50% (30 s ON; 30 s OFF), 75% (45 s ON; 15 s OFF) and 100% (ON). Model predicted pBRBAD (c) and pBRlasI (d) promoter systems expression levels driven by different ribosome binding sites (RBS) in the absence of blue light illuminations. The relative strengths of RBSs used as follows: rbsD = 1, rbs35 = 0.4560, rbs64 = 0.3273, rbs30 = 0.3226, rbs34 = 0.2679 and rbs32 = 0.0498. All data points were normalized to the highest value obtained and represented as mean ± s.d (n = 3). Solid lines represent model simulations.




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Figure 3. Characterization of dual-input hybrid promoters temporal dynamics. Response curves of pBRBAD (a, c) and pBRlasI (b, d) promoters based on three different ligand concentrations and blue light illumination OFF‒ON‒OFF‒ON cycle for every 2 h over a period of 8 h. All data points are represented as mean ± s.d (n = 3). The solid lines represent the model predicted temporal behavior. Model predicted (e) and (f) mRNA abundance (M) and (g) and (h) underlying blue light illumination pulse kinetics (%) for the two dual-input hybrid promoter systems. Grey areas refer to the ‘OFF’ state in the absence of light, and blue areas refer to the ‘ON’ state in the presence of blue light.



Figure 4. Reprogrammable logic circuit. (a) Genetic circuit diagram (left) illustrating the reprogrammable logic by combinatorial assembly of dual-input promoters in parallel (right). Blue light is used as a logic selection bioswitch to reprogram the biological logic behavior in a single cell. (b, c) Measured outputs of the circuit following the truth table as indicated. The circuit functions as an ‘OR’ logic gate when the cells are kept in the dark (left) and can switch to NIMPLY logic upon blue light illumination (right) under the same ligand input conditions without the need to change the circuit backbone. The statistical significance of ****P < 0.0001 was


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calculated based on one-way ANOVA. All data were normalized to the highest value obtained and are represented as mean ± s.d (n = 3).



Figure 5. Spatial control of reprogrammable logic circuit. (a) Modified pRPLC plasmid circuit. For this, we replaced the RFP gene downstream of the pBRlasI promoter with GFP in pRPLC plasmid (see Methods). (b) Plates were either kept in dark (top row) or exposed to blue light (bottom row) respectively. Panel 1: Empty disc loaded with DI water. Panel 2: Disc was loaded only with arabinose. In the dark, cells exposed to diffused arabinose formed the RFP ring and when exposed to light the expression was repressed. Panel 3: Disc loaded with DI water and AHL was added to the soft agar. Both in dark and light, cells expressed GFP homogenously. Panel 4: Disc loaded with arabinose and AHL was added to the soft agar. In the dark, cells formed bull’s eye


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pattern accordingly. When exposed to light, only the region exposed to arabinose gets repressed. All the images were taken under UV illumination after 18-20 h of incubation period.




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Figure 6. Temporal control of reprogrammable logic circuit. (a) Top panel shows the selection signal corresponding to blue light switch OFF/ON time period (2hOFF-ON-OFF-ON). Bottom panels represent the temporal change in logic over time based on the two ligand input signals. Red lines indicate the normalized RFP/OD600 values, while the black line correspond to synthesis rate calculated every 1 h. (b) The bar graph details the dynamic change in logic function based on the measured synthesis rates under all input combinations. All data are represented as mean ± s.d (n = 3).


Programming dynamic control of bacterial gene expression with the

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