Programming Surface Chemistry with Engineered Cells - ACS

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Programming Surface Chemistry with Engineered Cells Ruihua Zhang, Keith Cameron Heyde, Felicia Yi Xia Scott, Sung-Ho Paek, and Warren Christopher Ruder ACS Synth. Biol., Just Accepted Manuscript • DOI: 10.1021/acssynbio.6b00037 • Publication Date (Web): 20 May 2016 Downloaded from http://pubs.acs.org on May 27, 2016

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ACS Synthetic Biology

Programming Surface Chemistry with Engineered Cells Ruihua Zhang‡,†, Keith C. Heyde‡,§, Felicia Y. Scott†, Sung-Ho Paek†, Warren C. Ruder*,† † Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, United States § Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, United States

Supporting Information Placeholder

ABSTRACT: We have developed synthetic gene networks that enable engineered cells to selectively program surface chemistry. E. coli were engineered to upregulate biotin synthase, and therefore biotin synthesis, upon biochemical induction. Additionally, two different functionalized surfaces were developed that utilized binding between biotin and streptavidin to regulate enzyme assembly on programmable surfaces. When combined, the interactions between engineered cells and surfaces demonstrated that synthetic biology can be used to engineer cells that selectively control and modify molecular assembly by exploiting surface chemistry. Our system is highly modular and has the potential to influence fields ranging from tissue engineering to drug development and delivery.

Here, we report the development of a system that uses synthetic biology to engineer cells that program surface chemistry. Programmable surfaces have been designed with capabilities that include processes such as selfhealing1, self-cleaning2, and tissue-templating3. These programmable surfaces use targeted molecular assembly, and have impacted fields ranging from drug delivery4 to space exploration5. Although these materials can regulate complex chemical reactions6-8, they lack the ability to adapt and evolve to changing environmental conditions with the robustness of living organisms. As a result, linking programmable surfaces to chemical inputs from engineered living organisms has the synergistic potential to expand their utility. Fortunately, the ability to engineer living organisms to perform useful tasks has been a hallmark of synthetic biology. Over the past fifteen years, the field has advanced beyond the development of simple information processing networks9, 10 and now includes a toolset enabling scientists to design and engineer a range of behaviors in living cells. Fundamentally, synthetic biology is a

tool to reprogram the molecular outputs of an organic living system. For example, researchers have modified living systems to create value-added products such as narcotics11, to manipulate chemical information flow12, and to guide amyloid material assembly13. These abilities enable synthetic biologists to target specific molecular assembly pathways and control information exchange between different organism strains14, species, and even kingdoms15. Here, we describe a system that uses synthetic biology to control extracellular molecular assembly. We do this by exploiting the biotin-streptavidin binding event, a ubiquitous and well-characterized tool for pairing molecules16-18. The binding between biotin-streptavidin is one of the strongest non-covalent attractions found in nature19, and both biotin and streptavidin can be easily conjugated to other molecules20. By exploiting the versatility of this binding system, we can create both direct (Figure 1a) and indirect (Figure 1b) schemes for modularly manipulating extracellular chemistry. The first component in this system is an Escherichia coli (E. coli) strain that can produce elevated levels of biotin under inducible control. To engineer this strain, we transformed wild-type K-12 E. coli MG1655 with a plasmid, pKE1-lacI-bioB (Figure S1), encoding a synthetic gene network (Figure 1c). This network contained the gene for biotin synthase (bioB)21, repressed by the LacI transcription factor22. This repression is compromised by the addition of LacI’s natural inducer, lactose, or by Isopropyl β-D-1-thiogalactopyranoside (IPTG). When de-repressed, the network produces elevated levels of biotin synthase, an enzyme that is normally tightly repressed by biotin in vivo. In wild-type E. coli, biotin synthase catalyzes the formation of biotin from desthiobiotin (DTB)23 in the final step of the biotin production metabolic pathway24 (Figure S2). The complete plasmid causes cells to produce elevated levels of extracellular biotin when induced with IPTG (Figure 2a).

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Figure 1. Engineered Cells Control a Functionalized Surface. (a) A scheme for indirect cellular control of a functionalized surface relying upon the competition between surface-immobilized biotin (i.e., surface-adsorbed biotin-BSA conjugates), as well as cell-produced biotin, for streptavidin binding sites. (b) A scheme for direct cellular control of a functionalized surface; by binding streptavidin directly to the polystyrene surface, cell-produced biotin is in competition with biotinylated horseradish peroxidase (i.e., biotin-HRP) for the binding sites of immobilized streptavidin. (c) A synthetic gene circuit was constructed in E. coli MG1655 enabling the cells to produce elevated levels of biotin synthase when induced with IPTG. Biotin synthase (bioB) then converted DTB into biotin. (d) Experimental data and model-fit (R2=0.958) for the indirect control scheme.

In order to assemble this plasmid, we first performed whole-cell PCR on wild-type K-12 E. coli MG1655 to extract the bioB gene. Additionally, the LacI-repressible Ptrc-2 promoter and the synthetic lacI cassettes were extracted from the pKDL071 plasmid25. One at a time, the gene sequences were inserted into pKE1-MCS25 to create the construct reported here, pKE1-lacI-bioB, using molecular cloning approaches from a recently reported system for fast DNA assembly25. All sub-clones were performed in competent NEB Turbo E. coli and grown on agar plates containing Luria-Bertani (LB) media supplemented with 1.5% carbenicillin. The completed plasmid (Figure S1) was transformed into an E. coli MG1655 strain. Concomitantly, the gene circuit topology was tested and verified by using mCherry25 (a red fluorescent protein) as a proxy biomarker (Figure S3) and monitoring red fluorescence. Primers for all of the molecular cloning processes are shown in Supporting Table 1.

The next step was to engineer a programmable surface that could use biotin as an input to regulate molecular assembly. The initial system was based upon an indirect control method and utilized biotin-streptavidin binding. Specifically, we established a competitive binding scheme in which free biotin, produced by the cells, would compete with surface-immobilized biotin for environmentally available streptavidin binding sites. Biotin was surface-immobilized by conjugating it to bovine serum albumin (BSA) and adsorbing the conjugate to a polystyrene surface. Furthermore, streptavidin was conjugated to a catalytically active enzyme and introduced to this biotin-rich environment. Specifically, we used streptavidin-conjugated horseradish peroxidase (HRP) capable of modifying 3, 3', 5, 5'-tetramethylbenzidine (TMB) to produce an optical signal26 that could be measured by monitoring OD450. In principle, the HRP could be substituted for any enzyme or molecule that can be conjugated to streptavidin. Protocols for the


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preparation of these conjugates are found in the supporting information.

The indirect control scheme showed (Figure 1d) a dynamic response within the range of expected E. coli biotin production27. Furthermore, we were able to demonstrate a significant difference between this surface’s response to biotin and the surface’s response to DTB (Figure S4), a necessity to allow the engineered E. coli to control the functionalized surface. Additionally, experimental data from the indirect control scheme fit well (R2=0.958) with a modified four-parameter logistic fit for the kinetics of competitive binding surfaces28, providing us with a predictive system. With the engineered cell line and functionalized surface constructed, we tested whether the engineered cells could be induced by IPTG to produce biotin (Figure 2a) and thereby affect a chemical change to the functionalized surface. E. coli wild-type cells containing the pKE1-lacI-bioB were induced with IPTG. The resulting extracellular biotin concentration limited the binding of streptavidinHRP molecules to the functionalized surface. As a result, when TMB was next added to the surface, the resulting OD450 signal was attenuated. Complete results were gathered from IPTG-induced E. coli cultured in the presence and absence of supplemental DTB, as well as from uninduced E. coli. These findings (Figure 2a) showed a statistical significance between all of these conditions with the key comparison between induced and uninduced cells having a p-value below 0.05. Furthermore, native E. coli production of biotin is very low (~1 ng/mL)29, and this level is sufficient to cause repression of the biotin operon (including bioB) by birA30. While birA is essential31, to further explore the

Figure 2. Synthetically Engineered E. coli with Inducible Production of Biotin. (a) Engineered cells were exposed to varying concentrations of a biotin precursor, DTB, and a synthetic network inducer, IPTG. Extracellular biotin concentrations were measured using the indirect detection scheme. Supplemental DTB concentrations were varied to characterize the system. Statistically significant variations were detected between the IPTG-induced and uninduced engineered cells (pvalues: ** = 2.6 × 10-3, && = 1.34 × 10-2, ## = 2.5 × 103 , and ββ = 4.9 × 10-2), as well as induced and uninduced wildtype E. coli (p-values: * = 2.8 × 10-3, & = 9.2 × 10-3, # = 2.0 × 10-3, and β = 7.3 × 10-4) cell lines. (§) Figure 3. Direct Control of Cell-Programmed Surface the units for the vertical axis are ng/mL per OD600. (b) Chemistry. By binding streptavidin directly to the polystyComputational simulations of a kinetic model of the rene surface, engineered cells can directly control surface indirect control scheme reveal that changing the relachemistry. Additionally, this direct control scheme can tive concentration of the competitive biotin species easily be modified by varying the concentration of the shifts the scheme’s dynamic detection range. Here, competitive biotin-HRP, thus shifting the dynamic detecincreases in order of magnitude of the simulated comtion range. Experimental results from the direct control petitive biotin are: red= 100, green= 101, black= 102, scheme closely fit our predicted model (R2=0.986). yellow= 103). ACS Paragon Plus Environment


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interplay between our engineered construct and the native pathways, we examined the growth characteristics of wild-type, ∆lacI, ∆bioB, and ∆lacI∆bioB MG1655 cells in the presence and absence of the construct and inducers (Figures S5 and S6). Ultimately, we found that wild-type cells had the most favorable growth characteristics for our system when harboring the construct. Our results led us to examine how we could optimize the response and versatility of the cell-surface system. For example, modeling and computational simulations showed that having an ability to change the concentration of competing chemical species would enable a shift of the system’s dynamic range (Figure 2b). However, the indirect control scheme does not allow us to easily modify the concentrations of the competing species in the binding scheme, as the biotinylated conjugate is immobilized to the surface. In order to overcome this challenge, we developed a scheme for direct cellular control of surface chemistry (Figure 3). Similar to the indirect method, this scheme exploited a competitive binding scheme between biotin species for streptavidin binding sites. However, the direct control scheme utilized competition between free biotin and a biotinylated conjugate. Specifically, the use of surface-immobilized streptavidin allowed us to establish competition between cell-produced free biotin and biotin that had been conjugated to HRP. Preparation of the direct control scheme is described in the supporting information. The direct control scheme (Figure 3) was capable of responding to a distinctly different dynamic range of biotin production in comparison to the indirect scheme.

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Furthermore, a predictive model for this scheme fit the data well (R2=0.986), and showed that the scheme’s dynamic range could be altered by modifying the initial concentration of biotinylated conjugate in the solution. We thus created a biotin-surface interaction that can be tuned to respond to a range of biotin concentrations produced by engineered cells. Our results reveal two robust new approaches for utilizing synthetic biology to control extracellular molecular structures. By exploiting biotin-streptavidin competitive binding interactions, we have created schemes for cell-surface interactions that allow synthetically engineered E. coli to send chemical signals that cause extracellular molecular manipulation. Effectively, we have created cell-surface systems that allow synthetically engineered cells to behave as programmers of extracellular surface chemistry. By fitting well-established models32 to our experimental findings, we were able to formulate response profiles for both our engineered cell line (Figure 4a) and the functionalized surface (Figure 4b). These models can be concatenated to form a cell-surface response profile (Figure 4c) allowing us to predict how induced cells will affect extracellular molecular assembly. The linked model provides us with a predictive tool for understanding how synthetically engineered features such as ribosome binding site may be used in conjunction with a tunable programmable interface to modulate surface chemistry. Our system has a variety of potential applications. By expanding our system beyond the surfaces of laboratory polystyrene vessels, and deploying these reaction

Figure 4. Response Profiles for Engineered Cells and Programmable Surface Chemistry (a) A kinetics-based model for inducible cellular biotin synthesis was developed and fit with experimental data. Using this model, a biotin synthesis response profile was developed by simulating IPTG and DTB inputs over a two-dimensional, discrete input grid. (b) A small-ligand model for surface chemistry interactions was adapted and fit to experimental data for the direct-control scheme presented in Figure 3. An OD450 response profile, indicative of the concentration of immobilized biotin-HRP, was developed by simulating the model over a discrete, two-dimensional input grid. The diagonal yellow line through the response profile indicates the input regions corresponding to the surface’s dynamic range. (c) By setting the biotinylated HRP concentration to a constant (106 pg/mL), a response profile was developed that showed surface response as a function of [IPTG] and [DTB].


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schemes with functionalized microparticles, synthetically engineered cells could potentially transmit chemical information across spatial distances by microparticle transport. The mobilized microparticle surfaces could be used as a building block for complex systems of spatially segregated chemical reactions, controlled and modified by synthetically engineered cells. Our system enables engineered cells to control and manipulate the chemistry of a programmable surface with many possible applications. For example, by enhancing the engineered cell’s surface chemistry capabilities with synthetic circuits that leverage the cell’s native capacity to respond to mechanical cues33 and chemical inducers,34, these we can envision a system where engineered cells could both sense spatiotemporal surface cues and modify surface chemistry and material assembly to produce biological nanomaterials35. This ability would allow cells to “read” instructions written into the chemistry and physics of a material. These instructions would then activate cells, causing them to respond by modifying the material surface chemistry using our engineered biotin-streptavidin system. Our direct and indirect schemes give us two approaches for allowing synthetically engineered cells to control extracellular chemistry. We expect these systems will have implications in fields ranging from biochemistry to bioengineering and molecular medicine. Methods Indirect Control Scheme Surface Preparation. Biotin was conjugated to BSA via an Nhydroxysuccinimide ester (NHS) reaction described previously36. Streptavidin was conjugated to HRP using thiol-based and maleimide-based crosslinkers described previously37. In order to surface-immobilize the conjugate, biotin-BSA was diluted in PBS and 100 µL of the dissolved solution (0.03 µg/mL) was added to polystyrene wells. The wells were then covered with a plastic film and incubated for 1 h at 37 °C. Next, the wells were washed three times with 200 µL of 0.1% Tween 80 in PBS. After this immobilization process, the wells were blocked with 200 µL of 0.5% casein in PBS at 37 °C for 1 h to reduce non-specific binding. After blocking, 20 µL of biotin samples and 80 µL of streptavidin-HRP conjugate (0.2 µg /mL) were added to the wells and incubated at 37 °C for 1 h. To start the chromogenic reaction, 50 mM sodium acetate, 1 % TMB and 3% H2O2 were mixed at a 1000:10:1 ratio, and 200 µL of this solution was added immediately to each well. The reaction was allowed to proceed for 15 min at room temperature in the absence of ambient light. Next, 50 µL of 2 M H2SO4 was added to each well to stop the reaction, and absorbance was measured at 450 nm (OD450). Direct Control Scheme Surface Preparation. Biotin was conjugated to HRP via an N-hydroxysuccinimide

ester (NHS) reaction described previously37. Streptavidin was directly adsorbed to polystyrene well surfaces. In order to surface-immobilize streptavidin, it was diluted in PBS and 100 µL of the dissolved solution (0.17 µg/mL) was added to polystyrene wells. The wells were then covered with a plastic film and incubated for 1 h at 37 °C. Next, the wells were then washed three times with 200 µL of 0.1% Tween 80 in PBS. After this immobilization process, the wells were blocked with 200 µL of 0.5% casein in PBS at 37 °C for 1 h to reduce non-specific binding. After blocking, 20 µL of biotin samples and 80 µL of biotin-HRP conjugate (0.2 µg/mL) were added to the wells and incubated at 37 °C for 1 h. To start the chromogenic reaction, 50 mM sodium acetate, 1 % TMB and 3% H2O2 were mixed at a 1000:10:1 ratio, and 200 µL of this solution was added immediately to each well. The reaction was allowed to proceed for 15 min at room temperature in the absence of ambient light. Next, 50 µL of 2 M H2SO4 was added to each well to stop the reaction, and absorbance was measured at 450 nm (OD450).

Induced Biotin Production. The construction of the plasmid containing bioB gene was discussed previously in this study. The pKE1-lacI-bioB plasmid was transformed into E. coli MG1655 to enable biotin synthesis from its precursor, DTB. To induce biotin synthesis, the engineered strain was first grown overnight in LB media at 37 ºC and 400 RPM. Next, the culture was inoculated at 1% into biotin-free minimal M9 media. This media consisted of M9 salts (SigmaAldrich ® Product No. M9956 ) supplemented with 2 mM magnesium sulfate, 0.1 mM calcium chloride, 0.4% glucose and 0.02% biotin-free casamino acids (BD DifcoTM). DTB was supplemented at 30 - 200 ng/ml. Next, 0.5 mM IPTG was added to induce biotin synthesis. After 24 h of growth at 37 ºC and 400 RPM, cell cultures were and centrifuged and the biotin-enriched supernatant was collected. The biotin concentration was then detected using the indirect control scheme. Modeling and Simulation. The induction profile for K-12 E. coli MG1655 with a plasmid, pKE1-lacI-bioB was modeled using Michaelis-Menten formalism38, 39. This modeling approach allowed us to build up a set of ordinary differential equations from a set of chemical master equations The biotin-streptavidin competitive binding scheme was modeled with a small-ligand model approach. A full derivation of the modeling motivation is presented in the supporting information. All simulations were coded in Python and numerically integrated using LSODE40 in the FORTRAN library.

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Supporting Information. Supporting figures, experimental protocol, and modeling details and motivation. The Supporting Information is available free of charge on the ACS Publications Website at DOI: AUTHOR INFORMATION Corresponding Author

[email protected] Author Contributions

‡These authors contributed equally. Notes

The authors declare no competing financial interests.

ACKNOWLEDGMENT The authors thank James J. Collins for kindly sharing the pKDL071 plasmid. The authors also thank M.J.K. Rice for editing suggestions. The authors gratefully acknowledge support from award FA9550-13-1-0108 from the Air Force Office of Scientific Research of the USA and from the Institute for Critical Technology and Applied Science at Virginia Polytechnic Institute and State University. REFERENCES [1] Ying, H., Zhang, Y., and Cheng, J. (2014) Dynamic urea bond for the design of reversible and selfhealing polymers, Nat Commun 5. [2] Min, W.-L., Jiang, B., and Jiang, P. (2008) Bioinspired Self-Cleaning Antireflection Coatings, Advanced Materials 20, 3914-3918. [3] Ansari, A., Lee-Montiel, F. T., Amos, J. R., and Imoukhuede, P. I. (2015) Secondary anchor targeted cell release, Biotechnology and Bioengineering 112, 2214-2227. [4] Mura, S., Nicolas, J., and Couvreur, P. (2013) Stimuliresponsive nanocarriers for drug delivery, Nat Mater 12, 991-1003. [5] Nathal, M., and Stefko, G. (2012) Smart Materials and Active Structures, Journal of Aerospace Engineering 26, 491-499. [6] Liu, J., Xie, C., Dai, X., Jin, L., Zhou, W., and Lieber, C. M. (2013) Multifunctional three-dimensional macroporous nanoelectronic networks for smart materials, Proceedings of the National Academy of Sciences 110, 6694-6699. [7] Cobo, I., Li, M., Sumerlin, B. S., and Perrier, S. (2015) Smart hybrid materials by conjugation of responsive polymers to biomacromolecules, Nat Mater 14, 143-159. [8] Ruder, W. C., Hsu, C.-P. D., Edelman, B. D., Schwartz, R., and LeDuc, P. R. (2012) Biological colloid engineering: Self-assembly of dipolar ferromagnetic chains in a functionalized biogenic ferrofluid, Applied Physics Letters 101, 063701.

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