Adding Biomolecular Recognition Capability to 3D Printed Objects

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Adding biomolecular recognition capability to 3D printed objects. Celine A. Mandon, Loïc Jacques Blum, and Christophe Andre Marquette Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b03426 • Publication Date (Web): 11 Oct 2016 Downloaded from http://pubs.acs.org on October 14, 2016

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Analytical Chemistry

Adding biomolecular recognition capability to 3D printed objects. Céline A. Mandon, Loïc J. Blum and Christophe A. Marquette* Univ Lyon, Université Lyon1, CNRS, INSA, CPE-Lyon, ICBMS, UMR 5246, 43, Bd du 11 novembre 1918, 69622 Villeurbanne cedex, France. ABSTRACT: 3D printing technologies will impact in a near future the biosensor community, both at the sensor prototyping level and the sensing layer organization level. The present study aimed at demonstrating the capacity of one 3D printing technique, the Digital Light Processing (DLP), to produce hydrogel sensing layers with 3D shapes unreachable using conventional molding procedures. The first model of sensing layer was composed of a sequential enzymatic reaction (glucose oxidase and peroxidase) which generated chemiluminescent signal in the presence of glucose and luminol. Highly complex objects with assembly properties (fanciful ball, puzzle pieces, 3D pixels, propellers, fluidic and multi-compartments) with mono-, di- and tri-components configurations were achieved and the activity of the entrapped enzymes demonstrated. The second model was a sandwich immunoassay protocol for the detection of Brain Natriuretic Peptide. Here, highly complex propeller shape sensing layers were produced and the recognition capability of the antibodies demonstrated. The present study open then the path to a totally new field of development of multiplex sensing layers, printed separately and assembled on demand to create complex sensing systems.

INTRODUCTION Additive manufacturing processes generate new paradigm within the biotechnology engineer’s community 1,2. Indeed, the availability of new technologies, new materials and processes 3, but more often the access to unprecedented sensing layer complex geometries, initiate profound mutation of the biosensor developers’ way of thinking. As exemplarities of these mutations, new possibilities in active biomolecule immobilization strategies, new biosensor designs 4,5, 3D complex cell culture 6 and tissue engineering were identified 7-9 . In the field of additive technologies dedicated to 3D printing, numerous techniques are available such as thermoplastic extrusion, cold extrusion (also named bioprinting), laser writing of liquid resins or powders (ceramic, plastic, metals), stereolithography of photosensitive liquid resins and inkjet printing followed by UV polymerization. Nevertheless, when it comes to the incorporation of active biomolecules in the printed material, only few of them appeared adapted. This is particularly the case for two techniques, bioprinting (cold-extrusion) and stereolithography, since they both work at room temperature and can be adapted to print aqueous solutions. These two conditions, temperature and water content, are a prerequisite for the printing of active enzymes, antibodies and all other biomolecules one may want to add to its 3D printed objects. Within these two techniques, bioprinting was already well described, for example for living cells printing 10, but also for biomolecules printing, mostly with the aim of creating biocompatible scaffolds for tissue engineering 11. Nevertheless, the resolution of such systems based on liquid or hydrogels extrusion, rarely exceed 100 µm 11,12 and are more generally between 300 and 500 µm 13. On the contrary, stereolithography techniques, and particularly Digital Light Processing (DLP) systems, have the ability to produce layers with micron-size thickness and 10th of micron-size pixels 14 15.

In the frame of the present study, this last system was selected not only for its ability to produce high resolution prints but mainly for its compatibility with hydrogel polymerization upon visible light irradiation. The 3D printing set-up and the corresponding polymerization reaction are presented in Figure 1. The selected chemistry is an acrylate photopolymerization in the presence of a UV-visible photoinitiator (Irgacure 819). This chemistry is the chemistry classically used in DLP systems dedicated to plastic printing but the use of acrylate derivated Polyethylene Glycol (PEG) easily leads to the 3D printing of hydrogels with controlled water contents (50% of water content in the current conditions, determined using dry matter measurement). The integration of biomolecules was here performed through entrapment during polymerization and the length of the PEG chain (700 Da) was optimized to produce solid hydrogels with high biomolecule loading capacity (data not show). The studies presented here are a conceptual validation of the printability of active biomolecules rather than on a concrete work focused on a particular application. Future manuscripts from our group and others will certainly came soon to implement the important studies on how the objects’ shape influence the sensing capabilities.

EXPERIMENTAL SECTION Materials Brain natriuretic peptide (BNP), CDP-Star® chemiluminescent substrate, cresol red, glucose oxidase from Aspergillus Niger (GOx type X-S), horseradish peroxidase-labeled streptavidin, Irgacure 819, luminol (3-aminophthalhydrazide), poly(ethylene glycol) diacrylate with mean molecular weight of 700 Da (PEG700-DA) were purchased from Sigma (Lyon, France). Potassium chloride, Veronal (diethylmalonylurea sodium) and sodium phosphate were obtained from Prolabo (Fontenay Sous Bois, France). Anti-BNP monoclonal antibodies (clone 50B7) and biotinylated anti-BNP monoclonal antibodies (clone 24C5) were supplied by HyTest (Turku, Finland). Phosphate Buffer

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Saline (PBS) tablets were purchased from Applichem GmbH (Darmstadt, Germany). All solution were prepared using milliQ water. Transparent plastic photoresin for DLP printing was purchase from SPOT-A Materials (Barcelona, Spain). Luminol stock solution was prepared as 0.1 M solution in DMSO. 3D printing procedure Plain printing ink was prepared by mixing 2.5 mL of aqueous solution of cresol red at a concentration of 250 µg/mL with 1.5 mL of PEG-700-DA and 150 µL of Irgacure 819 at a concentration of 10 mg/mL in ethanol. Once this solution prepared, the different biomolecules were added: 2.5 µg/mL of peroxidase; 2.5 µg/mL of glucose oxidase; 2.5 µg/mL of peroxidase and glucose oxidase; 50 µg/mL of anti-BNP monoclonal antibodies (clone 50B7). The printing procedure was performed using a B9Creator open source system (B9Creation, Rapid City, USA) with a slicing thickness of 101 µm and a pixel size of 50 µm. The hardware parameters adapted to the present ink formulation were: attach two first layers exposure time 30 seconds, initial image exposure time 12 seconds and perimeter exposure time 3 seconds. All 3D CAD files were generated using SkechUp 8 (Trimble Navigation Limited, Sunnyvale, USA). For multicomponents printing, different troughs of resin were successively used with rinsing of the object between each trough using PBS buffer. For acrylate plastic plus hydrogel printing, acrylate platforms were printed using Spot-HT (Spot-A materials, Barcelona, Spain) in a first trough, the printed plastic objects were then washed with ethanol, air dried while still on the building platform and then introduced in a new trough filled with hydrogel ink. For assembled objects (puzzle pieces and cube/ring pieces), the pieces were printed separately and assembled before use, just like classical puzzle pieces.

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The antibody modified propellers were mounted on a 1 mm diameter plastic axis and connected to an IKA mechanical stirring apparatus rotating at 150 rpm. The propellers were first dipped in a saturation solution composed of LowCross buffer (Candor Bioscience, Germany) for 15 minutes. Then, a concentration of 0.5 µg/mL of BNP was introduce in the saturation solution together with 1.8 µg/mL of biotinylated anti-BNP and 2 µg/mL of alkaline phosphatase labelled streptavidine. The propellers were left to react for 30 minutes and washed twice in PBS for 15 minutes before being transferred to the charged coupled device (CCD) cooled camera light measurement system (Las1000 Plus, Intelligent Dark Box II, FUJIFILM). Integration times were, unless described differently, of 30 seconds. 1.

2.

+ Enzymes

Antibody Example of antibody entrapment in PEG hydrogel

Enzyme assays Concerning the sequential activity of the two enzymes, glucose oxidase and horseradish peroxidase, glucose was used as substrate for the glucose oxidase, generating hydrogen peroxide which was subsequently used as substrate by the peroxidase to produce chemiluminescence in the presence of luminol. All enzyme assays were performed, unless described differently, at room temperature in the presence of 500 µL of of luminol 220 µM and glucose 100 mM in a pH 8.5 buffered solution composed of Veronal at a concentration of 30 mM and KCl at a concentration of 30 mM (VBS). In the case of the two honeycomb compartments measurements, one compartment was filled with glucose at a concentration of 100 mM in a pH 6.5 buffered solution composed of phosphate sodium 0.1 M and the second compartment filled with luminol 200 µm in VBS. All chemiluminescent assays were imaged using a charged coupled device (CCD) cooled camera light measurement system (Las-1000 Plus, Intelligent Dark Box II, FUJIFILM). The numeric micrographs obtained were quantified with a FUJIFILM image analysis program (Image Gauge 3.122). Integration times were, unless described differently, of 3 minutes. Sandwich assay

Figure 1 Principles: 1. The DLP printing set-up and concept. Images of each layer are projected in a liquid resin trough to generate polymerization. 2. Poly(ethylene glycol) diacrylate polymerization reaction.

RESULTS The first study presented here intends to demonstrate the capacity of DLP to print 3D objects composed of hydrogels entrapping enzymes. The rational was here to open new avenues for the biosensors community in term of sensing layer architecture and organization. The first example of 3D printed enzyme is depicted in Figure 2 where 1.5 mm thick and 5.5 mm wide puzzle pieces were printed separately, containing each either horseradish peroxidase or glucose oxidase. These enzymes were chosen since they are well known to be able to work sequentially16 in chemiluminescent glucose biosensors. The puzzle shape was chosen as an example of a simple structure which can lead, when print with accuracy, to the achievement of complex sensing layers composed of different puzzle pieces assembled together, leading for example to multiplex biosensing layer.


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A first row of experiments was conduct with two puzzle pieces (Figure 2-A) which were locked together after printing and extensive washing of the excess enzyme content. The two pieces were assembled and perfectly fitted one in the other as can be seen on the Figure 2-A-2 micrograph. Then, in order to observe the sequential activity of the two enzymes, glucose was used as substrate for the glucose oxidase, generating hydrogen peroxide which was subsequently used as substrate by the peroxidase to produce chemiluminescence in the presence of luminol. Figure 2-A-3 presents the chemiluminescent image of the puzzle assembly dipped in a buffered solution containing glucose and luminol. As a matter of fact, both enzymes were active since no chemiluminescent signal could have been generated if one of them was inactivated by the 3D printing process. Moreover and interestingly, the generated chemiluminescent signal was localized at the contact points between the two objects (see Figure 2-A-3 light intensity profile obtained from the dash line), demonstrating the overconcentration of the hydrogen peroxide in the microcompartment (not characterized yet) created between the two puzzle pieces 17-19. It is also worth to note that no signal was observed when the objects were not assembled or at least distant of more than 3 mm (data not show).

Figure 2 A and B: Puzzle shaped 3D printed hydrogels entrapping horseradish peroxidase or glucose oxidase. A: two puzzle pieces are assembled. B: four puzzle pieces are assembled. C and D: Block and fit shaped 3D printed hydrogels entrapping horseradish peroxidase or glucose oxidase. C: two fit shape pieces are assembled. D: three fit shape pieces are assembled. 1. CAD designs of the 3D printed objects, 2. Micrographs of the printed objects, 3. Chemiluminescent images (3 minutes integration) and light intensity profile obtained from the dash line in the presence of glucose 100 mM, luminol 220 µM, Veronal buffer 30 mM, KCl 30 mM, pH 8.5.

A second row of experiments was performed using a third puzzle piece composition (negative control: plain hydrogel) without enzyme entrapment (Figure 2-B). In this case, four pieces were assembled, two negative controls, one peroxidase and one glucose oxidase. One more time, the chemiluminescent signal of the assembly in the presence of glucose and luminol was localized between the two enzyme puzzle parts and interestingly, no signal was observed, in contact between negative control and either peroxidase or glucose oxidase, demonstrating the specificity of the observed signal. These kind of assemblies open the path to the achievement of complex enzymatic sequences or sensing layers in which different oxidases pieces shall be assembled together with peroxidase pieces in an ordered way to produce multiparameter biosensors. In the next experiments, 3D printing of enzyme was pushed a step forward with the production of objects with mixed composition, both plain hydrogel and enzyme loaded hydrogel, but still with assembly capability. Figure 2-C and 2-D depicted the first set-up composed of a 3D printed flat layer (2 mm thick, 17 mm wide) of plain hydrogel on top of which peroxidase cubes (2.5 mm wide) were printed. Two or three ring shape objects (5 mm wide) composed of glucose oxidase were then placed around peroxidase cubes to generate localized chemiluminescent glucose sensing layers. One more time, this particular structure was chosen as for its capacity to generate multiplex biosensing systems in which different ring shape objects can be assembled in one complex sensing layer. The objects assemble together easily (Figure 2-C-2 and 2-D2) thanks to the high resolution of the DLP printing process which generate precise size and shape of the enzyme hydrogels. Then once again, in the presence of glucose and luminol, glucose oxidase/peroxidase assembled objects were able to locally generate chemiluminescent signals (see Figure 2-C-3 light intensity profile obtained from the dash line). In this particular configuration, since the distances between the glucose oxidase object and the next peroxidase object were less than 1 mm, the presence of hydrogen peroxide produced by the glucose oxidase ring generated parasite signals, observed on peroxidase cubes without glucose oxidase rings assembled. Nevertheless, these experiments enabled us to demonstrate the possibility of printing increasingly complex objects with entrapped active enzymes which open the path to a totally new field of development of multiplex sensing layers, printed separately and assembled on demand to create complex sensing systems. Then, since the 3D printing of enzymes loaded hydrogels was demonstrated, a new level of complexity was seek with the printing of complex objects encapsulating two enzymes in two parts of one single object. This set-up was chosen for its capacity to permit the concomitant use of two enzymes in two different conditions, useful for sequential enzymatic reaction for example. The model chosen here is still the peroxidase/glucose oxidase one but this time with an object composed of two honeycomb compartments with one common 900 µm thick wall (Figure 3). This two compartments, encapsulating each enzyme, gave then the possibility to work with two different buffer compositions at the same time in one single object (Figure 3-2). For example here, in the case of the peroxidase/glucose oxidase system, since each enzyme have different optimal pH (6.5 and 8.5 for glucose oxidase and peroxidase, respectively), the two compartments design enabled the use of each enzyme in its best condition.



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Figures 3-3, 3-4 and 3-5 depict the chemiluminescent signals obtained when the peroxidase compartment was filled with pH 8.5 buffered luminol solution and the glucose oxidase compartment was filled with pH 6.5 buffered glucose solution. As expected, chemiluminescent signal was observed only from the wall separating the two compartments (Figure 3-3 and light intensity profile obtained from the dash line), demonstrating the ability of the two successively printed enzymes to work properly in sequence with an efficient transfer of the hydrogen peroxide produced between the two enzymes. Then, as the reaction time increased (up to 90 minutes, Figure 3-5) and the hydrogen peroxide accumulates and diffuses through the separating membrane, the chemiluminescent signal burst into the peroxidase compartment. The kinetic of the chemiluminescent signal appearance can be follow through the integration of the separating membrane emitted light and could also be used as an analytical signal for glucose detection or enzyme activity study. Here for example, obvious behavior of a diffusion driven catalysis is observed with a sigmoid shape kinetic curve 20.

Figure 3 1. The two-compartments objects with one peroxidase hydrogel and one glucose oxidase hydrogel 2. Micrograph of the printed objects. 3-5. Chemiluminescent images (3 minutes integration) in the presence of glucose 100 mM pH 6.5 in the right compartment and luminol 220 µM pH 8.5 in the left compartment, after 3. 30 minutes and light intensity profile obtained from the dash line 4. 60 minutes and 5. 90 minutes. 6. Quantification of the light intensity emitted by the separating membrane.

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Finally, in order to fully evaluate the potentiality of the 3D printing of enzyme loaded hydrogels for biosensing, highly complex sensing layers were produced, encapsulating both peroxidase and glucose oxidase. Here, large surface to volume ratio were targeted in order to generate to largest chemiluminescent signal from the smallest printed objects. These hydrogels were printed with shapes at the limit of the DLP possible capacities (not in size but in shape complexity). To do so, three challenging designs were selected. The first one, named fanciful ball (Figure 4-1), is a 1 cm diameter ball composed of 1 mm diameter crossing structures. The second one, named 3D pixel (Figure 4-2), is a structure composed of 200 cubes of 1 mm3 stack of top of each other with only 200 µm of overlapping. The third, named propeller (Figure 4-3), was shaped as a four blades propeller of 1 cm diameter with a hollowed axis. Each design have its own challenge: the fanciful ball is a very airy structure with thin edifices but still a large size of the complete object; the 3D pixel is a dense object with only 800 µm space between the different blocks and the propeller is a large structure with 800 µm thin blades of 0.5 cm² surface. All three objects were printed with entrapped peroxidase and glucose oxidase in the same hydrogel, producing a chemiluminescent glucose sensing layer when immersed in a pH 8.5 buffered solution containing glucose and luminol. As can be seen in Figure 4, the three objects were successfully printed and exhibit strong chemiluminescent signal. Moreover, the details of the objects, particularly the fanciful ball and the 3D pixel, appeared clearly in the obtained chemiluminescent images and the ability of the propeller to freely rotate in a flow was also demonstrated and will be used in forthcoming experiments to induce solution mixing.

Figure 4 CAD design of four complex 3D hydrogel objects entrapping both horseradish peroxidase and glucose oxidase: 1. Fanciful ball, 2. 3D pixel, 3. Propeller and 4. Fluidic multicomponent object. Chemiluminescent images (3 minutes integration) were obtained in the presence of glucose 100 mM, luminol 220 mM, Veronal buffer 30 mM, KCl 30 mM, pH 8.5. One more object was produced, integrating both enzymes in the same sensing layer but this time in a mixed object composed of enzyme hydrogel, plain hydrogel and plastic acrylate, all three


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printed sequentially using the DLP technique. The CAD design depicted in Figure 4-4 presents the features of the object which is composed of a fluidic-to-real-world interface in plastic acrylate on top of which a 1.5 mm diameter tubing composed of both plain hydrogel and enzyme hydrogel was printed. A micrograph of the printed systems is shown in the insert of the chemiluminescent image in Figure 4-4. Then, flowing buffered solution containing glucose and luminol through the hydrogel tubing led to the emission of strong chemiluminescent signal from the peroxidase/glucose oxidase hydrogel tube part, demonstrating i) the ability of the technique to produce fluidic parts with active enzyme and ii) the possibility to produce objects with mixed formulations (hydrogel and plastic).

maybe even through covalent binding, during the radical polymerization process.

DISCUSSION In the field of biosensing, antibodies are the most used non-catalytic recognition elements, particularly because of their ease of production toward almost any molecular and supramolecular targets. Nevertheless, their successful use in biosensing is often related to i) the remaining activity of the immobilized antibody and ii) the accessibility of the target (epitope) to the recognition moiety (paratope). It was then worth to demonstrate, in the present framework, the capacity of the 3D printing technique to generate objects with recognition ability based on entrapped antibodies. The immunoassay model chosen here is a sandwich assay for the detection of the Brain Natriuretic Peptide (BNP) in which monoclonal antibodies are used 21. This assay is a good model since the target is a challenging one for sandwich detection with its 3.5 kDa molecular weight. The object shape chosen for this study was the propeller already used in the previous enzymatic demonstration (Figure 5-1). This choice was driven by the ability of the propeller to rotate freely around its axis and then generate stirring of the assay solution, increasing then the interaction between the assay components. As a demonstration of this stirring effect, the impact of the rotation rate on the chemiluminescent signal obtained following the detection of 0.5 µg/mL of BNP is depicted in Figure 5-2 where increasing the propeller rotation rate from 0 to 150 rpm induces a 5-time enhancement of the analytical signal. The micrograph in Figure 5-3, 4 depicted two propellers, one composed of plain hydrogel and one encapsulating anti-BNP monoclonal antibodies, assembled together around a plastic axis. The propellers were subjected to a standard sandwich assay (contact with the target protein together with biotinylated anti-BNP antibody and alkaline phosphatase labelled streptavidin followed by extensive washing) and then immersed in a solution containing CDP-Star® chemiluminescent substrates. The different steps were performed at once, under stirring through rotation of the two propellers. As can be seen in Figure 5-3, an intense specific signal was obtained all over the antibody modified propeller while a background level signal was obtained from the negative control propeller (see Figure 6-3 light intensity profile obtained from the dash line). It was then demonstrated here that i) monoclonal antibodies could be entrapped in a 3D object produced by DLP and retain their binding capacity and ii) that the hydrogel used for DLP printing was easily passivated to avoid non-specific binding. It is also worth to mention that in the present assay format, large biomolecules (antibody, alkaline phosphatase labelled streptavidin) shall diffuse through the hydrogel to reach the target bound to the encapsulate antibodies. This point suggests that the entrapped antibodies might interact strongly with the photopolymerized matrix,

Figure 5 1. CAD design of the two propellers system: one composed of plain hydrogel, the second one encapsulating anti-BNP antibodies. 2. Impact of the propeller rotation rate on the chemiluminescent signal obtained in the presence of BNP 0.5 µg/mL. 3. Micrograph of the two propellers on their rotating axis. 4. Chemiluminescent image (30 seconds integration) obtained after sandwich assay and light intensity profile obtained from the dash line.

CONCLUSIONS DLP 3D printing process has been demonstrated to be compatible with the production of biosensing components, both for enzyme and antibody based assays. The freedom to operate in term of shape complexity and multiple component capacity of the technique open the path to a complete new field of investigation for the biosensor community. Of course, numerous complementary studies will be required to fully understand the impact of the technique, first on the performances of 3D printed biosensors and then on the development of new biosensing concepts, but it is already clear that biosensors and biochips with complex architecture will in a near future benefit of the tech-



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nique, with impact not only in immunosensors or enzyme biosensors, but also in cell-on-chip, organ-on-chip and of course tissue engineering.

AUTHOR INFORMATION Corresponding Author * E-mail: [email protected]; Fax: +334 72 44 79 70; Tel: +334 72 43 13 69

Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

ACKNOWLEDGMENT This project has received funding from the European Union Horizon 2020 research and innovation program under grant agreement No 634137.

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(7) Pati, F.; Gantelius, J.; Svahn, H. A. Angewandte Chemie International Edition 2016, 55, 4650-4665. (8) Ho, C. M. B.; Ng, S. H.; Li, K. H. H.; Yoon, Y.-J. Lab Chip 2015, 15, 3627-3637. (9) Hribar, K. C.; Soman, P.; Warner, J.; Chung, P.; Chen, S. Lab Chip 2014, 14, 268-275. (10) Kang, H. W.; Lee, S. J.; Ko, I. K.; Kengla, C.; Yoo, J. J.; Atala, A. Nat Biotechnol 2016, 34, 312-319. (11) Kolesky, D. B.; Truby, R. L.; Gladman, A. S.; Busbee, T. A.; Homan, K. A.; Lewis, J. A. Adv Mater 2014, 26, 3124-3130. (12) Miller, J. S.; Stevens, K. R.; Yang, M. T.; Baker, B. M.; Nguyen, D. H. T.; Cohen, D. M.; Toro, E.; Chen, A. A.; Galie, P. A.; Yu, X.; Chaturvedi, R.; Bhatia, S. N.; Chen, C. S. Nat Mater 2012, 11, 768-774. (13) Mandrycky, C.; Wang, Z.; Kim, K.; Kim, D. H. Biotechnol Adv 2015. (14) Jacobsen, A.; Jorgensen, T.; Tafjord, O.; Kirkhorn, E. Proc Spie 2015, 9376. (15) Dean, D.; Jonathan, W.; Siblani, A.; Wang, M. O.; Kim, K.; Mikos, A. G.; Fisher, J. P. Virtual and physical prototyping 2012, 7, 13-24. (16) Marquette, C. A.; Blum, L. J. Biosens Bioelectron 2006, 21, 1424-1433 (17) Berger, A.; Blum, L. J. Enzyme Microb Technol 1994, 16, 979984. (18) Michel, P. E.; Gautier, S. M.; Blum, L. J. Anal Lett 1996, 29, 1139-1155. (19) Bosch, M. E.; Sánchez, A. J. R.; Rojas, F. S.; Ojeda, C. B. Sensors (Basel, Switzerland) 2007, 7, 797-859. (20) Illanes, A.; Fernández-Lafuente, R.; Guisán, J. M.; Wilson, L. In Enzyme Biocatalysis: Principles and Applications, Illanes, A., Ed.; Springer Netherlands: Dordrecht, 2008, pp 155-203. (21) Marquette, C. A.; Bouteille, F.; Corgier, B. P.; Degiuli, A.; Blum, L. J. Anal Bioanal Chem 2009, 393, 1191-1198.


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Adding Biomolecular Recognition Capability to 3D Printed Objects

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