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The ability to bioengineer three-dimensional (3D) tissues is a potentially powerful approach to treat diverse diseases such as cancer, loss of tissue function, or organ failure. Traditional tissue engineering methods, however, face challenges in fabricating 3D tissue constructs that resemble the native tissue microvasculature and microarchitectures. We have developed a bioprinter that can be used to print 3D patches of smooth muscle cells (5mm×5mm×81μm) encapsulated within collagen. Current inkjet printing systems suffer from loss of cell viability and clogging. To overcome these limitations, we developed a system that uses mechanical valves to print high viscosity hydrogel precursors containing cells. The bioprinting platform that we developed enables (i) printing of multilayered 3D cell-laden hydrogel structures (16.2μm thick per layer) with controlled spatial resolution (proximal axis: 18.0±7.0μm and distal axis: 0.5±4.9μm), (ii) high-throughput droplet generation (1s per layer, 160 droplets/s), (iii) cell seeding uniformity (26±2cells/mm2 at 1 million cells/mL, 122±20cells/mm2 at 5 million cells/mL, and 216±38cells/mm2 at 10 million cells/mL), and (iv) long-term viability in culture (>90%, 14 days). This platform to print 3D tissue constructs may be beneficial for regenerative medicine applications by enabling the fabrication of printed replacement tissues.
Recent breakthroughs in regenerative medicine and tissue engineering present bioengineered three-dimensional (3D) tissues as an alternative treatment for various diseases such as loss of tissue function or organ failure.1–5 Often in tissue engineering, two-dimensional (2D) or 3D scaffolds are employed to generate tissues in vitro.6,7 However, engineered tissues generated in 2D cultures do not mimic the complex microarchitecture of native tissues. Also, current 3D polymer scaffolding approaches are not suitable for fabricating complex tissue structures due to lack of spatial and temporal control during cell seeding.8–10 In the past decade, deposition of polymers/metals/cells by printing has gained momentum in electronic circuit board printing, printing of transistors, and tissue printing.11,12 Printing technology shows promise in overcoming the limitations associated with seeding cells on scaffolds. For example, bioprinting methods, such as inkjet13–15 and laser printing16–19 techniques, have been employed to control cell placement in 2D or 3D. However, some challenges still remain in existing tissue printing systems such as low cell viability, loss of cellular functionality, and clogging.20–22 Cell printing also requires extracellular matrix (ECM) to build 3D structures for long-term culture. However, the current piezo-based inkjet printing system is not easily adapted for high viscosity solutions such as collagen ECM, since it requires high impact force to generate droplets. To overcome these limitations, alginate-based cell printing23,24 and 3D fiber deposition25 approaches were used to encapsulate cells in ECM. Alginate-based cell printing is adapted to the conventional piezo-based bioprinter to prevent the rapid clogging issues by printing a low viscosity calcium chloride as crosslinking agent. However, for gelation the calcium must diffuse into alginic acid, which limits the droplet placement resolution. During the diffusion process, a change in pH also affects cell viability.23 The other approach uses the squeezing of ECM precursors from the nozzle to eliminate clogging. This approach may be limited in terms of low resolution and throughput.
An emerging approach to enhance bioprinting is to use a nozzle-free acoustic ejector, which prevents clogging during droplet generation.26–28 Another approach features a mechanical valve ejector that uses a pressure source to overcome the surface tension of high viscosity liquids.29–31 This mechanical ejector was applied for cryopreservation of cells in droplets and for cell printing. In this article, we built on the system by creating a cell-laden hydrogel droplet deposition system that can create 3D structures made of collagen, a temperature-sensitive gel. We adopted the system to evaluate a model structure using bladder smooth muscle cells (SMCs) to engineer tissues. We demonstrate that this bioprinting system can be used to (i) pattern cell-laden hydrogel droplets with microscale resolution, (ii) print hydrogel droplets containing cells in a rapid and uniform manner, and (iii) maintain long-term cell viability.
Primary bladder SMCs from Sprague Dawley rat were harvested according to a previously established protocol.32 SMC culture medium was prepared by mixing 445mL Dulbecco's modified Eagle's medium (Gibco, Carlsbad, CA, 11965-092), 50mL fetal bovine serum (Gibco, 10439-024), and 5mL Pen/Strep (Sigma, St. Louis, MO, P4333) through a sterile filter (500mL, Express Plus 0.22μm membrane, SCGPU05RE). SMCs were cultured under standard conditions (37°C, 5% CO2) in a humidified incubator (Forma Scientific, Waltham, MA, CO2 water jacketed incubator). After the culture reached 80% confluency, cells were trypsinized (10×, 0.5 trypsin–EDTA; Gibco, 15400), washed, and resuspended in SMC medium to be mixed with collagen. Collagen solution was prepared by mixing 250μL type I bovine collagen (MP Biomedicals, Solon, OH) with 50μL sterile H2O, 50μL 10× phosphate-buffered saline (PBS) (DPBS, Carlsbad, CA, 14190), 50μL fetal bovine serum, 50μL SMC medium, and 50μL NaOH (0.1M, Sigma, 55881) and kept at 4°C before being mixed with SMCs (1:1 ratio).
The droplet generation process was adjusted by controlling nitrogen gas pressure, valve opening duration, and cell concentration (Fig. 1). To fabricate a collagen-coated substrate, agarose (10% v/v mixture with distilled water and agarose powder; Fisher, Pittsburgh, PA, BP1360-100) was poured on the bare Petri dish (Falcon, Pittsburgh, PA, 35-3002) to enhance adhesion between the Petri dish and collagen. Collagen solution was then manually spread on the agarose surface and gelled. The cell-laden collagen droplets were printed onto the collagen-coated substrate. To maintain the droplet size, we kept the valve opening duration at 60μs and nitrogen gas pressure at 34.4kPa. To control the cell density in droplets, we used three different cell concentrations, 1×106, 5×106, and 10×106 cells/mL. The cell viability before and after printing was evaluated using a Live/Dead kit (Invitrogen, Carlsbad, CA, L3224). The staining solution was prepared with 0.5μL of (1mg/mL) calcein AM and 2μL of (1mg/mL) ethidium homodimer solution in 1mL of PBS for 1min. The staining solution was poured onto printed structures and incubated for 10min at 37°C. The stained cells in the patch were manually counted under a florescent microscope (Eclipse Ti-s; Nikon, Melville, NY).
Using the valve-based droplet ejector setup that was previously described,29,30 cells were ejected on the prepared substrate. Using 1×106, 5×106, or 10×106 cells/mL, the 10mL syringe attached to the ejector was filled with the desired cell/collagen suspension. The ejector and collagen were kept cool with liquid nitrogen (LN2, ~5°C in gas phase) vapor to minimize viscosity changes of collagen that can solidify at room temperature. Each printed layer was gelled by incubation at 37°C for 5min. Subsequently, another layer of collagen was printed onto the first layer. This process of layering was repeated to create 3D tissue structures.
Printed SMC patches were gelled at 37°C for 5min before SMC medium was added and incubated overnight. After 24h, medium was aspirated off, and printed patches were washed three times with PBS at room temperature and fixed in 2mL of 4% paraformaldehyde (Sigma). These patches were then rinsed with PBS three times and permeabilized with 1mL of detergent solution (mixture of 4% bovine serum albumin and 0.1% TritonX-100 in PBS solution; Sigma). The specimens were incubated with primary antibody (actin, connexin-43, and mouse monoclonal immunoglobulin G [IgG], 1:50 dilution in PBS; Santa Cruz Biotechnology, Santa Cruz, CA) and 5μg/mL nuclear stain 4′,6-diamidino-2-phenylindole (Invitrogen) at 37°C for 40min. Secondary antibodies (goat anti-mouse IgG fluorescein isothiocyanate and IgG R, 1:50 dilution in PBS; Santa Cruz Biotechnology) were also incubated at 25°C for 40min. After each incubation process, excess antibody was washed off, and stained SMC patches were imaged under the florescent microscope (Eclipse Ti-s; Nikon). The number of cells per square millimeter was plotted using SigmaPlot® that depicted cell distribution as a contour plot of an entire patch.
Uniform cell seeding density is critical for tissue engineering, since it controls the average cell-to-cell distances that influence cell-to-cell communication. The overall morphological characteristics of a tissue construct depend on this uniformity. To achieve 3D tissue structures with spatial control of cell seeding, we characterized (i) the number of cells per droplet as a function of cell loading concentration, (ii) droplet printing precision, (iii) overlapping cell-laden collagen droplets to fabricate seamless line structures, and (iv) number of cells per unit area in a printed patch.
The mechanical valve was attached to a micrometer precision xyz stage that enabled 3D spatial motion. The movement of the stage was synchronized with droplet generation signal resulting in 3D patterning capability. The platform spatially and temporally controlled the droplet placement (Fig. 1). First, we evaluated the position and density of cells in the biomaterial by printing cell-laden droplets in multiple layers. The cell-laden collagen droplets landed onto a Petri dish surface that was coated with collagen gel (Fig. 2a). This controlled placement allowed the system to deposit a cell-laden hydrogel droplet epitaxially in 2D and 3D using droplets with 650±18μm spread diameter on the surface. Uniform cell seeding was investigated by characterizing where droplets land onto a surface during droplet generation and xyz stage movement along a temporal line (distal axis, Fig. 2a). The landing locations and placement variation (δx and δy) of droplets determine the overlap between droplets when patterning lines and patches in 3D. The droplet ejection directionality was the major determinant of this variation. The system achieves 0.5±4.9 and 18.0±7.0μm variation in the x (distal) and y (proximal) directions, respectively. These variations were negligible compared to the 650±18μm spread droplet diameter. To create layered structures using an intermediate collagen layer was printed between the first layer of droplets and second layer of droplets (Fig. 2b). The adjacent droplets gel together and form a single seamless layer. Further, a secondary droplet array was printed on top of the gelled layers to pattern droplets in a 3D microarchitecture (Fig. 2c). The cell-laden collagen droplet in the first layer was printed at a lower cell concentration on the substrate than the collagen droplet printed in the secondary layer to depict a layered structure.
Second, we characterized the number of cells per droplet at three cell loading densities and the cell viability of the printing platform (Fig. 2d). It showed 6±1cells per droplet at 1×106cells/mL, 29±5cells per droplet at 5×106cells/mL, and 54±8cells per droplet at 10×106cells/mL. The number of cells per droplet was repeatable over ejected droplets at various cell loading concentrations. Further, the number of cells per droplet increased with increasing cell loading density in the ejector reservoir. The number of cells that can be packed in a single droplet does not increase linearly with the loading density. Consequently, it is harder to pack more cells into a fixed droplet volume. To better understand cell seeding density, the mean and standard deviation for number of cells per droplet were investigated. Smaller standard deviation can be translated into a more uniform seeding density as cells are patterned to create 3D constructs. The platform also printed cells with high viability 94.8±0.8% compared to the culture flask viability. The viability was calculated by the ratio of pre-ejection cell viability (96.1±1.9%) and post-ejection cell viability (91.1±2.3%) by counting 250 printed cells (Fig. 2d). The results showed that system precision, printing cell viability, and cells per droplet uniformity sufficed to establish controlled cell seeding density with high cell viability.
The third step was to print overlapping collagen droplets to pattern cell-laden collagen lines as we build a 3D structure. An illustration describing placement of droplets in a printed line pattern is shown by overhanging printed cell-line bridges in separate layers (Fig. 3a). The overlap between the adjacent droplets was maintained at 50% by the temporally controlled ejection. To test the system operation, two collagen lines were printed side by side in a single layer (Fig. 3b), and multiple lines were printed within separate layers of a 3D structure in a crossover pattern (Fig. 3c). These cell-laden collagen lines were placed on top of each other in the z direction by printing a cell-less collagen layer within between two layers. The magnified images of the cross-pattern bridges of printed cell lines are shown in Figures 3d and e.
Finally, native tissue comprises multiple cell layers. To mimic such tissue architecture, the bioprinting system employs a 3D printing capability using an epitaxial method (layer by layer) (Fig. 4a). To print smooth muscle tissue constructs, cell-laden collagen droplets were patterned on top of earlier printed layers. The challenge of 3D patterning was overcome by first gelling the initial printed layer and then depositing additional cell-laden hydrogel droplets on top of the previously printed layer like in layer-by-layer epitaxy. First, a bottom cell-less collagen layer was placed in agarose. Then, on top of this layer a cell-laden collagen layer was printed. This process was repeated creating five cell-less and two cell-laden collagen layers (81μm thick). To observe the multiple layers, a motorized system was created that steps the microscope focus (Fig. 5). Images were taken at each focus point with 16.2μm steps (Fig. 4b–e). The printed 3D multilayer SMC-laden collagen construct was stained with 4′,6-diamidino-2-phenylindole. Focal images show printed layers with stained cells and without cells. The cell-laden layers (Fig. 4c, e) show stained circular cellular nuclei, whereas the cell-less collagen layers only show background due to staining of the gel (Fig. 4b, d). The described epitaxial method was used to observe cell seeding densities within a single printed layer at three different cell densities, 1×106, 5×106, and 10×106cells/mL (Fig. 4f). As shown, the cell seeding density of the printed patches was uniform right after printing: 216±38cells/mm2 at 10×106cells/mL, 122±20cells/mm2 at 5×106cells/mL, and 26±2cells/mm2 at 1×106cells/mL.
The patches were imaged after printing, and the number of cells was averaged per square millimeter in each image for an entire patch area of 25mm2. We validated the distribution, uniformity, and variation of cell seeding density by the printing method. The topographic color coding of the top view of these patches reveals the cell distribution over 1–7 days for 5×106cells/mL cell printing concentration (Fig. 6a–d). The color coding indicates the cell concentration in that area (see the legend). The increased cell seeding density correlates with the increased number of cells per droplet (Fig. 7a). This characterization is crucial, since it builds the logical tie between a cell-laden hydrogel droplet and a printed 3D tissue construct. However, the proliferation rate is not linear as a function of cell density and culture time. The rates show a sigmoid tendency as a function of culture duration, which indicates that initial high proliferation rates decrease as the number of cells per unit area increases. The inflection time, tinflection, of the sigmoid regression curves were 2.6 days for 5×106cells/mL and 3.2 days 10×106cells/mL. In case of 26±1.7cells/mm2 initial cell loading density, the proliferation rate of cells showed an exponential increment. The exponent and the sigmoid regression functions feature unknown factor, b, which is related to cell proliferation, 0.2 for 1×106cells/mL, 1.3 for 5×106cells/mL, and 1.7 for 10×106cells/mL. The number of cells per droplet and the precise positioning of these droplets in a 3D architecture determine the cell seeding density of the patch before the long-term culture. Such high-throughput capability and cell seeding control to create 3D tissue constructs allow potentially rapid characterization and optimization of tissues. Printing a 5×5mm patch takes 10s with 160Hz ejection frequency. The total time becomes 10min including the gelation time to build a secondary layer. This processing time indicates the high-throughput aspect of the system compared to the conventional scaffold methods that take 1–2h to build a single patch. Cells are also observed to adhere and spread within the printed cell-laden collagen layer (Fig. 7b–e). In long-term culture, cells were observed to be viable as demonstrated by histological stains. During days 4 and 7, the printed cells expressed actin after the printing and culturing steps (Fig. 7b, c). Patches on the 14th day of culture expressed connexin-43 (Fig. 7d, e). This marks a positive turning point for the printed patches and indicates future possibilities for tissue engineering by this 3D bioprinting platform technology. This technology employed for tissue engineering and regenerative medicine could create avenues for functional tissues and could create a clinical impact by enhancing the quality of life for patients.
Briefly, we presented a 3D cell patterning platform that allows efficient cell–matrix deposition with microscale spatial resolution and uniform initial cell seeding density, while maintaining cell viability over long-term culture. This high-throughput system to print tissue constructs from microdroplets has the potential to enable future therapies by providing (i) uniform cell seeding, (ii) 3D cell patterning layer by layer, and (iii) viability over long-term culture.
We would like to thank The Randolph Hearst Foundation and the department of Medicine, Brigham and Women's Hospital for the Young Investigators in Medicine Award. Y.S., F.X., and U.D. were also partially supported by R21 (EB007707). This work was performed at the BAMM Labs at the HST-Brigham and Women's Hospital Center for Bioengineering, Harvard Medical School.
No competing financial interests exist.