Gustavo A.
Higuera‡
*b,
Jeanine A. A.
Hendriks‡
c,
Joost
van Dalum
a,
Ling
Wu
a,
Roka
Schotel
c,
Liliana
Moreira-Teixeira
a,
Mirella
van den Doel
c,
Jeroen C. H.
Leijten
a,
Jens
Riesle
c,
Marcel
Karperien
a,
Clemens A.
van Blitterswijk
a and
Lorenzo
Moroni
a
aDepartment of Tissue Regeneration, MIRA Institute, University of Twente, Drienerlolaan 5, Zuidhorst, 7522 NB Enschede, The Netherlands. E-mail: gustavo.higuera@screvo.net; Fax: +31 53489 2150; Tel: +31 53489 3400
bScrevo Ltd, P.O. Box 217, 7500 AE, Enschede, The Netherlands
cCellCoTec, Prof. Bronkhorstlaan 10-48, 3723MB Bilthoven, The Netherlands
First published on 17th April 2013
Animal experiments help to progress and ensure safety of an increasing number of novel therapies, drug development and chemicals. Unfortunately, these also lead to major ethical concerns, costs and limited experimental capacity. We foresee a coercion of all these issues by implantation of well systems directly into vertebrate animals. Here, we used rapid prototyping to create wells with biomaterials to create a three-dimensional (3D) well-system that can be used in vitro and in vivo. First, the well sizes and numbers were adjusted for 3D cell culture and in vitro screening of molecules. Then, the functionality of the wells was evaluated in vivo under 36 conditions for tissue regeneration involving human mesenchymal stem cells (hMSCs) and bovine primary chondrocytes (bPCs) screened in one animal. Each biocompatible well was controlled to contain μl-size volumes of tissue, which led to tissue penetration from the host and tissue formation under implanted conditions. We quantified both physically and biologically the amounts of extracellular matrix (ECM) components found in each well. Using this new concept the co-culture of hMSCs and bPCs was identified as a positive hit for cartilage tissue repair, which was a comparable result using conventional methods. The in vivo screening of candidate conditions opens an entirely new range of experimental possibilities, which significantly abates experimental animal use and increases the pace of discovery of medical treatments.
Insight, innovation, integrationWell-plates and their experimental throughput, as invented by Dr Gyula Takatsy in 1951, are indispensable tools in biological research, where biological data throughput remains solely optimised in vitro. Here, we created implantable well-plates to increase the throughput of animal experiments. By creating wells with biocompatible materials, it was possible to evaluate μl-size volumes of tissue in vitro and in vivo and to obtain quantitative correlations of multiple conditions vs. biological markers directly in animal models. This approach embodies a practical strategy to reduce the numbers of experimental animals that rely on analysing tissue biology in units (wells) that can be controlled and compared with other units of real tissue. |
Another approach to replacing animal experiments has seen the rise of promising 3D8 and micro-fabricated systems9–13 that try to mimic the cellular environment. These systems capture some of the complexity of the 3D environment; that is, the role of physics in tissue biology.14 However, most of these fall short of representing real tissue and replacing animal models. Inevitably, millions of animals are bred every year to evaluate the impact of substances and treatments on the environment and human health.
A notable example for optimizing animal experiments has been achieved in evaluating biocompatibility,15 where 8 biomaterials can be spatio-temporally assessed in one animal through fluorescence imaging. Even though the physiological consequences for implanting multiple conditions (e.g. materials, drugs or toxins) in one animal cannot be predicted, and must therefore be investigated, there is a tangible social and economic benefit of increasing the efficiency of experiments directly in animal models.
Here, we integrate methodology in rapid prototyping, 3D cell culture and ECM biology to present in vivo screening as a viable strategy for refining animal experiments. To make this possible, we made an implantable well-system that enables screening in vitro and directly in an animal model for tissue regeneration. For cell culture, human mesenchymal stem cells (hMSCs) and bovine primary chondrocytes (bPCs) were chosen as cell sources for their extensively studied therapeutic potential. We focus on screening of ECM components as markers of the tissue formation potential of 36 cell conditions in one animal.
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Fig. 1 Screening systems can be made of different sizes, materials and architectures. We were able to manufacture: 1024 wells in a 32 × 32 matrix made of PEOT–PBT of 300/55/45 composition (A); 100 wells in a 10 × 10 matrix made of PEOT–PBT of 1000/70/30 composition (B); 100 wells in a 10 × 10 matrix made of poly lactic acid (C); 100 wells in a 10 × 10 matrix made of alginate (in PBS) (D). The architecture of well systems could also be modified to create: a double matrix (top and bottom of a system) with a polymer layer in between (E); wells with a porous layer of material in the middle for potential co-culture studies (F). White arrow points to the pipette tip size that fits into a well. Scale bar: 1 mm. |
We then tested the robustness of wells by dispensing specimens that could be manually seeded and that were compatible with standard laboratory equipment (Fig. S2, ESI†) such as an automatic confocal microscope (Fig. S2B, ESI†). In these in vitro experiments, the wells were randomly seeded with dyes of different colors (Fig. S2A–E, ESI†) to confirm that there was no cross-contamination between different wells and unbiased readouts. We first used microspheres and fluorescent markers (Fig. S2F, ESI†) to evaluate if compounds with different sizes and fluorescent properties could be quantified in the wells. The intensity of light emitted from poly lactic acid wells containing microspheres revealed that the mean fluorescent intensity (n = 3) significantly decreased with increasing dilution factors (Fig. S2B, ESI†). When the fluorescent markers rhodamine and fluorescein isothiocyanate (FITC) were seeded at different dilutions in photo-sensible resin-made wells (Fig. S2F, ESI†), these also displayed a significant correlation between the dilution factor and mean light intensity (Fig. S2G, ESI†). Overall, these results demonstrated that wells could be implemented in vitro for the screening and quantification of molecules. In practice, these results showed that up to 9 wells per screening device could be consistently dispensed manually, and that the sensitivity of results was not compromised by the materials or the designs.
As a popular tissue regeneration cell source, hMSCs were selected for testing the cell culture compatibility of wells (Fig. 2) made of PEOT–PBT, a biocompatible copolymer already used in skin and musculoskeletal regenerative medicine applications.8 The material was selected for its slow in vivo degradation,17 low water uptake (∼5%) and high tensile strength (up to 23 MPa).18 In addition, attachment, proliferation and differentiation of chondrocytes16 and hMSCs19 can be tuned by varying the PEOT/PBT ratio of the copolymer chains. A 2D film of the material itself showed that when hMSCs were cultured on 300PEOT55PBT45 discs, cells organized in colony forming units (CFU's) (Fig. 2A), which resembled their known monolayer behavior on tissue culture plastic. In contrast, hMSCs cultured on rectangular wells formed 3D aggregates conditioned by the number of cells seeded (Fig. 2B). Remarkably, wells with the highest number of hMSCs contained 3D aggregates of random shapes whereas dilutions of hMSCs yielded wells with monolayer-type cultures. We determined that 3D aggregates augmented in size in a time-dependent manner due to the non-monolayer aggregation of hMSCs. To examine the effect of well-volume on hMSCs, the well size was varied in width and length and 1.2 × 104 hMSCs were seeded in three different types of wells (Fig. 2C–E), which effectively increases the cell concentration by decreasing the well volume instead of increasing the cell numbers. By adjusting the well size, an inverse correlation between hMSCs organization and well size was derived: hMSCs form 3D aggregates in the 0.45 μl well (Fig. 2C), while in the 1.8 and 4 μl wells (Fig. 2D and E) they organized into CFU's, leading to the conclusion that above 5 × 104 cells per μl of well hMSCs readily assemble in 3D aggregates. When low numbers of hMSCs are deposited in the well, these proliferate, increasing the cell concentration in time (Fig. 2F). From these data, we discovered that the 3D organization of hMSCs in the wells could be controlled through the well volume, cell number and culture time.
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Fig. 2 Cell culture in the PEOT–PBT wells. 300![]() ![]() ![]() |
Based on molecular and cell culture results, we chose to fabricate PEOT–PBT screening systems with 9 wells and volumes of 1.8 μl per well. This meant that thirty six conditions could be housed in four subcutaneous sites in every immune-deficient mouse (Fig. S3, ESI†). The thirty six implanted conditions consisted of numbers of hMSCs, numbers of bovine primary chondrocytes (bPCs) and coculture ratios of hMSCs:
bPCs that were screened for tissue regeneration markers (Table 1).
Dilution factor | hMSCs [cell #] | bPCs [cell #] | Co-culture ratios | hMSCs![]() ![]() |
---|---|---|---|---|
1× | 25![]() |
25![]() |
80![]() ![]() |
20![]() ![]() ![]() |
2× | 12![]() |
12![]() |
50![]() ![]() |
12![]() ![]() ![]() ![]() |
4× | 6000 | 6000 | 20![]() ![]() |
5000![]() ![]() ![]() |
First, the systemic effect on the host tissue under the different conditions confined in the screening device was assessed in all twenty mice with markers for the cell nuclei, the cytoplasm of cells, keratin and collagen (Fig. 3). Interestingly, hair growth (Fig. 3A) was stimulated on the skin of nude mice in wells containing hMSCs, indicating a systemic response to trophic factors.20 Upon histopathological examination of tissue morphology in slides from all mice, there was no indication of cross-contamination of conditions or inflammatory responses (Fig. 3A). Instead, the first evident effect was the penetration/formation of tissue in the wells (Fig. 3B).
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Fig. 3 In vivo screening is performed on histological sections showing three wells of a well system with the subcutaneous host tissue located above the wells. The representative staining of 80 screening devices is shown in this cross section of a 9-well device in 3 rows × 3 columns configuration. The red arrow points to hair growth on the skin of nude mice in wells containing hMSCs. The black arrow points to the area of the screening device stained with India ink to pinpoint the location of conditions (rows and columns) after histological processing. Sections of screening devices were stained with haematoxylin and counterstained with eosin showing the cytoplasm (red) and nuclei (dark blue), where the well is delineated with black lines and the material of the screening device appears to be white and enveloped by the host tissue (A). The dotted oval in (A) displays the area of interest for screening purposes, where implanted conditions interact with the host tissue. (B) The three wells are shown after Masson's tri-chrome staining: keratin (red), collagen (blue) and nuclei (dark brown) to evaluate the extracellular matrix in the wells. Notably, potential differences in the tissue penetration/formation per well were observed in each well. Scale bar: 1 mm. |
To evaluate the presence of tissue in the wells, we quantified the physical accumulation (tissue area/total well area) of tissue in each well for all mice (Fig. 4). Since the objective was to compare tissue penetration in all wells vs. the total well area, the analysed tissue area included implanted cells, host tissue and new ECM. Then we proceeded to identify patterns in time according to each condition. For example, the percent area of tissue in a well increased gradually with increasing numbers of hMSCs (Fig. 4A). Also bovine PCs exhibited an increase in tissue percent areas with increasing cell numbers on week 4 (Fig. 4B), but not on week 2. Despite seeding a maximum of 25000 cells in all wells, co-cultures revealed growing tissue percent areas for wells containing increasing numbers of hMSCs (Fig. 4C). We analyzed the means of the percent area of tissue to determine whether there were significant differences between conditions. These led to variability of results between members of the same species when comparing all mice with each other. In wells with hMSCs, half of the mice displayed a significantly higher percent area of tissue between 6000 cells vs. control (no seeded cells, week 2), and 25
000, 12
000 cells vs. control (week 4) (Table S1, ESI†). Similarly, in wells with bPCs, half of the mice presented a significantly higher percent area of tissue between 25
000 cells vs. 12
000 cells (weeks 2 and 4), 12
000 cells vs. control (week 2) (Table S2, ESI†). Finally, in wells with co-cultures, 56% of the mice revealed significantly higher percent areas of tissue in the 20
000 hMSCs to 5000 bPCs (80
:
20) ratio vs. control (week 4) (Table S3, ESI†). Notably, there was no indication that the implantation site influenced the correlation between cell numbers and tissue percent areas according to the random distribution of conditions (Fig. S2, ESI†).
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Fig. 4 Histological sections (>300 slides) contained tissue penetration/formation in wells which was evaluated through the percent area of tissue, defined as tissue area/well area × 100%. The means (n = 3 slides of a well) of the percent tissue area for each condition are graphically shown for two representative mice; one from week 2 and one from week 4. The percent tissue area increased as the number of cells in a well increased as depicted for hMSCs dilutions and control (empty well system) (A); bPCs dilutions and control (B). With a total of 25![]() |
While in vivo cell proliferation was not investigated directly, the statistics (Tables S1 and S2, ESI†) did not support a significant correlation between increasing cell numbers and increasing percent areas of tissue (Fig. 4A and B). Since not higher than 50% of mice displayed a higher percent area of tissue under most conditions, it was concluded that increasing cell numbers were not sufficient to significantly increase the percent area of tissue in a well. Other effects such as the reverse trends in percent area of tissue for chondrocytes (week 2, Fig. 4B) were not significant. The most significant effect (in 56% of the mice) detected by quantifying the amount of tissue in a well was found for co-cultures, suggesting that co-cultures have the potential to induce higher percent areas of tissue when compared to the readings on empty wells (control), through ECM formation rather than cell numbers. Thus, it was concluded that the main contributor to the percent area of tissue in a well is the well itself probably due to tissue bulging21 or penetration, which occurs spontaneously when host tissue is in contact with the well. In order of importance, tissue penetration was followed by tissue formation as the factor that increases the amount of tissue in a well as observed in 56% of the mice in wells with cocultures of four hMSCs to one bPC (80:
20).
Since hMSCs:
bPCs cocultures have a known22,23 cartilage regeneration potential, slides under all conditions were stained for proteoglycans (Fig. 5). It was found that when compared to other conditions (Fig. 5B–D), the co-culture containing the highest amount of hMSCs (80
:
20) was more strongly stained for proteoglycans (Fig. 5E). Upon histological grading24 (Fig. 5F) of the quality of neo-cartilage, it was confirmed that all hMSCs
:
bPCs combinations produced a cartilage matrix. The 80
:
20 co-culture was the most promising condition tested in this screening showing in vivo cartilage regeneration as shown by the significantly higher cartilage (Bern) score on week 4.
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Fig. 5 Proteoglycan production was screened as a marker for cartilage formation. Glycosaminoglycans (GAG) (blue) and cytoplasm (red) seen in three wells of a screening device (A, scale bar: 1 mm). A representative slide of the control and three conditions expressing GAG are displayed: empty wells (B); 25![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
To evaluate the results obtained for co-culture ratios using a conventional method (Fig. S4, ESI†), conditions were seeded in porous 3D scaffolds16 and implanted subcutaneously in nude mice. These data also showed that proteoglycans increased in PEOT–PBT scaffolds containing cocultures with higher quantities of hMSCs (Fig. S4A, ESI†). The amount of GAG/DNA did not show a significant difference between groups (Fig. S4B, ESI†). However, the efficiency of proteoglycans production augmented with increasing ratios of hMSCs (Fig. S4B, ESI†). Sulphated-proteoglycans, collagen types I, II and IX confirmed that hyaline (healthy) cartilage-like tissue was more abundant in scaffolds with 80% and 90% hMSCs (Fig. S4C, ESI†).
Increasing the number of conditions that could be screened simultaneously in one animal improves the efficiency and speed at which therapies and treatments can be identified and translated into clinical practice. In fact, evaluating the same 36 in vivo conditions using conventional methods would have required 9 times the number of mice (Table 2).
Species | Experimental conditions | # Animals with conventional methods (n = 10 animals) | 3D HTS well matrix | Size [mm] | Conditions per 3D HTS | Wells per animal | # Animals with 3D HTS | Animals saved |
---|---|---|---|---|---|---|---|---|
Mouse | 36 | 90 | 3 × 3 | 4.2 | 9 | 36 | 10 | 80 |
Rats | 576 | 1440 | 12 × 12 | 16.8 | 144 | 576 | 10 | 1430 |
Rabbits | 1600 | 4000 | 20 × 20 | 28 | 400 | 1600 | 10 | 3990 |
Goats | 4096 | 10![]() |
32 × 32 | 44.8 | 1024 | 4096 | 10 | 10![]() |
Cross talk between wells and their physiological effect is condition-dependent. While wells in vitro can be independent of each other by adjusting the well volumes and the relative humidity, wells in vivo can interact with each other through soluble factors. The degree of interaction between wells will be dependent on molecule diffusion dynamics and time. In this study, ECM markers at 2 and 4 weeks did not indicate any cross talk between wells. However, this will be relative to the marker of interest. Even though cell therapy in conventional scaffold systems (50 mm3) occurs in volumes over 25 times larger than well volumes (1.8 mm3), both systems are consistent with the regions, where ECM production occurs, which is in the pores in scaffolds or inside the wells. This indicates that by reducing the volume of interest in the animal with wells, the extent of desired and undesired effects such as cross contamination is identifiable and controllable. As shown here, control can be achieved through randomization of implanted conditions, which ensures the discrimination of relevant biological responses, such as ECM production from irrelevant effects – for the purpose of this study – such as host tissue penetration in the wells.
Albeit 36 wells were investigated in nude mice as a proof of principle, the screening device has the potential to become a high throughput screening (HTS)25,26 system where hundreds of wells can be contained in one animal with one well (1.8 μl) for every 1.4 mm of an implantation site. Depending on the size of the animal, these platforms can be tailored to fit the required dimensions of an implantation site, which defines the number of conditions that can be implanted (Movie S1, ESI†). Thus, the larger the animal, the higher the number of conditions that can be investigated simultaneously. However, the seeding of macroscopic and large numbers (>100) of wells requires special equipment to control the microenvironment while dispensing conditions in all wells with reproducibility. Using the well system, the number of lives required to perform experiments in vertebrate animals is inversely proportional to the size of the animal (Table 2), extending the possibility to assess multiple in vivo conditions. As shown here, standard histological methods offer an extensive wealth of data, yet methods that avoid histological processing15,27,28 would be convenient to further optimize animal experiments, automatize the quantification and imaging, and improve the sensitivity and throughput of in vivo screening.
The efficiency of the developed animal-implantable well system not only lies in optimizing animal experiments, but also in bridging both in vitro and in vivo milieus. For example, the well system could be adapted to monitor biomechanics29 and to elucidate gene regulatory networks30,31 in live tissues. Multiple compounds such as nanoparticles, drugs or chemicals could be covalently or non-covalently attached to wells to increase the throughput of toxicity assessments and thereby drastically dwindle the use of vertebrate animal lives and costs in pharmaceutical, toxicological, chemical, and disease screening, while allowing for the first time to execute such screening in true three-dimensional tissues.
Different architecture designs were fabricated to maximize the number of wells and to create co-culture systems as shown in Fig. 1E and F. For the design in Fig. 1E, first and second layer strand distances were maintained as shown in Table S1 (ESI†) and a strand distance (0.5 mm) in the middle of the well height (at 2 mm) was introduced. The design in Fig. 1F did not have a closed first layer where a constant strand distance (Table S1, ESI†) was maintained until deposition of a closed layer in the middle of the well height (at 2 mm). Subsequently, layer deposition with a constant strand distance was resumed.
Four 3 × 3 well systems containing 36 conditions were subcutaneously implanted per mouse in the posterior-lateral side of the back and sutured. The 36 conditions implanted were triplicates of: three dilutions of hMSCs (25000; 12
000; and 6000 cells); three dilutions of bPCs (25
000; 12
000; and 6000 cells); three hMSCs
:
bPCs ratios (0.8
:
0.2, 0.5
:
0.5, and 0.2
:
0.8) and empty wells with no cells. Conditions were randomized by dispensing them in different wells of screening devices and implanting devices in different pockets from one mouse to another (Fig. S3A, ESI†). After 2 weeks (n = 10) and 4 weeks (n = 10) mice were euthanized via CO2 asphyxiation and screening systems were excised and processed for analysis.
In vivo screening of conditions was organized in replicates with a multi-dimensional sample number, which was defined by N = 10 animals and n = 3 replicates per well for each condition in each animal. So that n = 3 replicates per condition per mouse and the total sample number per condition is N × n = 30.
The mean (n′ = 3 histological slides) of the percent area of tissue was analyzed for each screening device in each statistically independent mouse (n = 3 wells per condition in each animal) with one-way Anova followed by Tukey's honestly significant difference criterion where statistical significance was set at p < 0.05. So that for each mouse, there were n′ × n = 9 images of the same condition available for analysis.
Since Bern score data are non-parametric, it was not normally distributed data. To account for that, Bern scores of differences of means (N = 10 mice) for glycosaminoglycans in the well system were analyzed with Kruskal–Wallis with Bonferroni post hoc correction. Three independent observers assessed the Bern scores for each slide, where inter-observer reproducibility was evaluated with the hypothesis of a combined effect on Bern scores by both mean observers' score for a slide and a mean score for a condition causing a statistical significant difference set at p < 0.05.
Footnotes |
† Electronic supplementary information (ESI) available. See DOI: 10.1039/c3ib40023a |
‡ Both authors contributed equally. |
This journal is © The Royal Society of Chemistry 2013 |