A Mechanochemical Microarray for Studying Combinatorial Effects on Embryonic Mesenchymal Cell Differ

Advances in Biomedical Engineering Research (ABER) Volume 4, 2016 doi: 10.14355/aber.2016.04.001

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A Mechanochemical Microarray for Studying Combinatorial Effects on Embryonic Mesenchymal Cell Differentiation Basma Hashmi1,2, Keekyoung Kim1,3,4, Jalil Zerdani3,5,6, Tadanori Mammoto2, Juani Feliz1, Ali Khaddemhosseini1,3,4 and Donald E. Ingber1,2,6* Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA 02115, USA

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Vascular Biology Program, Boston Children’s Hospital and Harvard Medical School, Boston, MA 02115, USA

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Biomaterials Innovation Research Center, Biomedical Engineering Division, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School Boston, MA 02115, USA 3

Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA 4

Laboratory of Stem Cell Bioengineering, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland 5

Harvard School of Engineering and Applied Sciences, Cambridge, MA 02138, USA

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Corresponding author: Wyss Institute for Biologically Inspired Engineering, CLSB, 5th Floor, 3 Blackfan Circle, Boston, MA 02115, USA *

don.ingber@wyss.harvard.edu Abstract Embryonic mesenchymal cells mediate tooth formation during development as a result of physical and chemical interactions with their extracellular matrix (ECM) microenvironment. Engineering biomaterials relevant to tooth differentiation require a screening platform that incorporates both embryologically relevant properties relating to ECM stiffness as well as chemistry.

Current ECM microarray technologies that screen for the effects of differences in substrate mechanical properties on cell differentiationare limited to ranges of high stiffness that are not relevant for the engineering of many cell types, such as stem cells and embryonic mesenchymal cell derivatives. Here, we describe the development of a novel polyacrylamide gel microarray platform and demonstrate its utility for the selection of odontogenic biomaterials. This microarray platform uses soft substrates (132, 558, and 1510 Pa) that closely mimic the embryonic microenvironment coatedwith the ECM proteins, Collagen VI and Tenascin (either alone or in combination), which have been shown to contribute to odontogenesis and permits combinatorial analysis of their effects on cell growth and differentiation. Using expression of the odontogenic transcription factor pax9 as a measure of tooth differentiation, we found that odontogenesis was the highest when mesenchymal cells isolated from embryonic mouse mandible (day 10) were cultured on 1510 Pa with Collagen VI (100 µ g/ml). This screening method is useful for selection and design of engineered materials for dental applications, as well as any challenge that involves engineering of tissues that depends on compliant ECM materials in combination with chemical cues from the microenvironment.

Keywords Extracellular Matrix; Microarray; Combinatorial Screening; Mechanics; Polyacrylamide Gel; Differentiation; Tooth Formation; Odontogenesis

Introduction Hypodontia due to early tooth loss or agenesisis a significant problem in children. Although artificial teeth are often implanted in adulates, it is difficult to obtain stable dental implants in children who experience active jaw growth (Fekonja 2005; Bolton 1958; Holm-Pedersen, Lang, and Müller 2007), and thus tooth regeneration remains a promising alternative to existing treatments. Recent work on embryonic tooth formation has shown that the prococess by which odontogenesis is controlled involves complex interplay between mechanical and chemical cues (T. Mammoto et al. 2011; Hashmi et al. 2014). In particular, mechanical compression of cells during

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mesenchymal condensation is sufficient to induce a transcriptional program involving the expression of odontogenic transcription factor Pax9, and thereby promote tooth formation (Mina and Kollar 1987; Maas and Bei 1997; T. Mammoto et al. 2011; Hashmi et al. 2014). This is consistent with finding that mechanical interactions between cells and their ECM adhesions contribute significantly to the control of tissue and organ development in the embryo, as well as tissue regeneration during wound healing (T. Mammoto, Mammoto, and Ingber 2013). For example, synthetic ECM substrates with different mechanical properties have been shown to produce stiffnessspecific effects on cell functions (e.g., motility, growth, contractility), stem cell differentiation, and angiogenesis (Polte et al. 2004; Discher, Mooney, and Zandstra 2009; T. Mammoto, Mammoto, and Ingber 2013; Engler et al. 2006; A. Mammoto et al. 2009). In addition, two different types of ECM proteins that are present in the condensed mesenchyme at the onset of epithelial budding, Collagen VI and Tenascin, have been suggested to contribute to tooth formation as well(Horibe et al. 2004; T. Mammoto et al. 2011, 2014; Thesleff et al. 1987; Thesleff 2003). These types of mechanical and chemical cues interplay in a complex manner during development because cells sense these signals simultaneously in the living tissue microenvironment, and changes in ECM mechanics that alter cell shape and tension regulate cell fate switching by modulating sensitivity to both adhesive signals and soluble factors (Chen et al. 1997; Dike et al. 1999; Singhvi et al. 1994). Thus, the development of tooth-regenerative biomaterialswould benefit from the development of a method that permits combinatorial analysis of the contributions of ECM mechanics and chemistry on tooth differentiation lineage switching in mesenchymal cells in vitro, particularly using ranges of ECM compliance that are similar to those present in the developing embryo.

Microarray printing technologies, initially developed for genome-wide gene profiling, have been adapted previously for tissue engineering applications. By depositing multiplexed arrays of different synthetic polymers or ECM molecules, they were utilized to screen biomaterials that have enhanced abilities to promote cell differentiation or direct stem cell fates (Lutolf, Gilbert, and Blau 2009; Flaim, Chien, and Bhatia 2005; Anderson, Levenberg, and Langer 2004; Urquhart et al. 2007; Gobaa et al. 2011) . Others have utilized microarray printing to determine the mechanical properties of a large biomaterials library(Tweedie et al. 2005).

However, current printing technologies are limited in terms of their ability to print soft mechanical substrates that are relevant to tissue development (Chowdhury et al. 2010; Eroshenko et al. 2013; Jaramillo et al. 2012), and it has been difficult to vary ECM type, density and mechanics in the same microarray printed materials. For example, in studies with microspotted islands of fibronectin, the most flexible islands fabricated were in the kPa range (Gobaa et al. 2011), which is an order of magnitude greater than the stiffness of natural living tissues such as the mammary gland, brain, liver, etc (Levental, Georges, and Janmey 2007), and embryonic tissues are even more compliant (Zhou et al. 2010).

Thus, we set out to develop a microarray system with microprinted ECM islands that exhibit mechanical properties similar to those of embryonic tissues involved in tooth formation as a proof-of-principle. To our knowledge, this is the first study analyzing the combinatorial effects of ECM protein and substrate stiffness on cell density and tooth differentiation using a microarray polyacrylamide gel platform that incorporates soft substrate stiffnesses (132, 558, and 1510 Pa), which closely mimic the embryonic microenvironment, in combination with select ECM proteins conducive to odontogenesis. The information presented in this study may be useful for designing a biomaterial for odontogenesis. This novel microarray approach also may be useful for the engineering of other tissues that similarly depend on combined extracellular mechanochemical cues.

Materials and Methods ECM Microarray Preparation Standard microscope 25 x 75 mm glass slides (Thermo Fisher Scientific, Waltham, MA) that were cleaned with concentrated sodium hydroxide solution to produce a smooth, residue free glass surface were dried and coated with 3-(trimethoxysilyl) propyl methacrylate (TMSPMA) (Sigma-Aldrich, St. Louis, MO) at 80°C overnight to provide a hydrophobic methacrylate-functionalized surface. To create a thin polyacrylamide(PAA) pad (500 ¾ m), a drop (167 ul) of liquid PAA solution [40% acrylamide (BioRad, Hercules, CA), 2% bisacrylamide (BioRad, Hercules, CA) in varying ratios (A. Mammoto et al. 2009; Pelham

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and Wang 1997) along with the free radical initiators, 50 ug/ml of 10% ammonium persulfate (Sigma -Aldrich, St. Louis, MO) and 5 ug/ml TEMED (BioRad, Hercules, CA) was placed on the me thacrylated glass slide and a 18 mm by 18 mm plastic cover slip was placed on top. The ratios of 40% acrylamide/2% bisacrylamide were 1:0.1, 1:0.25, 1:1.25 for 132 Pa, 558 Pa and 1510 Pa, respectively. A single glass slide contained all 3 substrates (132 Pa, 558 Pa, 1510 Pa) in 3 different regions marked by the 18 mm by 18 mm coverslip as shown in Figure 1.

The glass slides were left overnight in a controlled humidity condition and subsequently the cover slip was peeled off from the polymerized gels in distilled deionized water. The PAA gel pads were then allowed to dry at room temperature before microarray printing.

ECM proteins were printed on the top surface of the PAA gels with a 2-pin contact microarray printer (SpotBot 3 Personal Microarray, ArrayIt,CA). The ink used for printing contained either 100, 200 or 300 µ g/ml of collagen VI (Abcam), 10 µ g/ml tenascin (EMD Millipore), or a mixture of both, diluted in 0.1% bovine serum (BSA; Sigma-Aldrich) and printing buffer. BSA was included in the solution to maintain the total amount of protein constant (24 ug) in all inks at a total volume of 80 ul per ECM protein biomaterial library.

Each slide contained 90 individual spots, with 15 replicates for each of the 6 experimental conditions and 60 replicates for each condition. The printing buffer consisted of 20% glycerol (VWR), 5 mM EDTA (VWR), 100mM acetic acid (VWR), and 0.25% Triton X-100 (BioRad, Hercules, CA) at pH 5.0 to prevent protein polymerization (Flaim, Chien, and Bhatia 2005). The printing pins also were sonicated for 30 minutes in the 50% ethanol-water solution prior to printing, and the pins were washed in the 50% DMSO-water solution, rinsed in with distilled deionized water, and dried after printing each set of samples to ensure unrestricted flow.

After printing, the glass slides were incubated for 8-16 hours at 4°C, and then washed 3 times with PBS to rehydrate the PAA gel pads prior to cell seeding.

Cells were plated on the microarray ECM spots at a density of 5.5 x 10 4 cells/cm 2 in DMEM containing 2% FBS, cultured overnight, and then fixed in 4% paraformaldehyde (PFA, BioRad, Hercules, CA) in PBS at the desired time point for immunofluorescence microscopic analysis of cell morphology and differentiation.

Mechanical Characterization The stiffness (shear and storage moduli) of arylamide gel substrates fabricated with different degrees of chemical cross-linking were characterized using a 8 mm plate geometry configuration in a Rheometer (AR -G2 TA instruments, DE). The minimum oscillation normal force limit was set to 0.1 N and maximum oscillation normal force limit was 50 N; angular frequency was held constant at 6.283 rad/s and all stud ies were carried out at 25°C. Cell Culture Embryonic stage 10 murine mandibular mesenchymal (MM) cells transfected with green fluorescent protein (GFP) were used in all studies. MM cell suspensions were added to pre-warmed Dulbecco's modified Eagle's medium (DMEM, Gibco, Carlsbad, CA) supplemented with 10% fetal bovine serum (FBS, Invitrogen, Carlsbad, CA) and 1% penicillin/streptomyocin, (Gibco, Carlsbad, CA), centrifuged at 1000 rpm, resuspended in culture medium, transferred to T75 tissue culture flasks (BD Biosciences, San Jose, CA), and cultured at 37°C under 5% CO2. Cell cultures were refed with new medium every 2-3 days, and cells were passaged using 0.05% EDTA-trypsin (Invitrogen, Carlsbad, CA) when confluency was ~90%; all studies were carried out using cells prior to passage 12.

ImmunohistoChemistry ECM microarrays with adherent cells were fixed, rinsed with PBS, permeabilized with 0.1% TritonX -100 (BioRad, Hercules, CA, USA) in PBS, and then incubated in 0.1% TritonX-100 containing 10% FBS in PBS for 1 hour prior to carrying out immunostaining using an antibody directed against rat Pax 9 (1:100 dilution; Abcam, Cambridge, MA, USA) followed by incubation with an Alexa Fluor 594 conjugated secondary antibody (1:200; Abcam, Cambridge, MA, USA) at room temperature. Upon completion, slides were dip coated with immunofluorescence mounting medium containing DAPI to visualize nuclei prior to placing the coverslip. Microarray spots and adherent cells were imaged using an inverted laser scanning confocal microscope (Leica SP5XMP, Buffalo Grove, IL, USA) with acquisition of multiple z-stack sections as well as an inverted fluorescent microscope (Zeiss Axio Observer Z12, USA).

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Morphometric Analysis A customized pipeline in Cell Profiler r10997 (Broad Institute, MIT) was written to calculate the Pax 9 intensity of each cell and to count the number of DAPI-stained nuclei in each microarray spot. Cells were identified as primary objects based on their stained nuclei and cell bodies (labelled with GFP) were defined as the secondary objects; thresholds were defined for both to respectively separate nuclei and labelled cell bodies from the background using the Otsu Adaptive algorithm. The range of diameters of nuclei was measured using ImageJ (NIH, Bethesda, Maryland); threshold bounds were set between 0.1 and 1.0 to rule out detection of background signals. The Laplacian of Gaussian method was found to give the best result when coupled with the Intensity module as a parameter to distinguish between clumped objects. From these identified objects, the total number of cells per spot and the average intensity of the Pax9 signal was measured and normalized against the varying level of cell adherence per condition. Cell densities were determined based on the total number of nuclei measured per spot, and the area of each spot (in um2), which was quantified using ImageJ. The accuracy of the automated analysis was confirmed by manually measuring similar properties of cells adherent to microarray spots and quantifying using Image J software (NIH, Bethesda, Maryland).

Quantitative PCR Quantititave PCR was performed on cells cultured on PAA gels of stiffness of 1510 Pa coated with Collagen VI at a concentration of 100 µ g/mland 558 Pa coated with Collagen VI at 300 µ g/ml. Changes in expression levels of Pax9 were analyzed as described previously(T. Mammoto et al. 2011; Hashmi et al. 2014).

Statistical Analysis Statistical analyses were conducted using one-way ANOVA for mechanical characterization tests and twoway ANOVA with replication to compare the effects of ECM protein and substrate stiffness on cell adhesion and odontogenic differentiation. These were followed by tukey-post hoc tests. Results are presented as mean +/- standard error of the mean (SEM) unless otherwise stated.

Results and Discussion Fabrication of ECM Microarrays We fabricated a mechanochemical microarray system using PAA gels (Fig. 1A). We microspottedand polymerized PAA gel pads (18 X 18 mm) with three different ratios (1:0.1,1:0.25 and 1:1.25) of 40% acrylamide to 2% bisacrylamide to alter cross-linking densities and thereby create three different stiffnesses on a single microscope glass slide (Fig. 1B). We then microprinted collagen VI (100, 200 or 300 µ g/ml), tenascin (10 µ g/ml) or a mixture of both ECM proteins on top of each pad to create microarrays containing circular ECM islands (425m diameter) in a square array (spot-to-spot pitch of 900m) with defined mechanical and chemical properties (Fig. 1A,B).

FIG. 1 (A) SCHEMATIC OF PRINTING PROTOCOL OF STIFFNESS DEPENDENT SUBSTRATE. (B) MACRO IMAGE OF PR INTED SPOTS ON A STANDARD 25 MM X 75 MM GLASS SLIDE WITH ACRYLAMIDE GEL PAD SUBSTRATE AT 1510, 558, AND 132 PA. FIFTEEN REPLICATE SPOTS/SLIDE FOR EACH CONDITION WERE PRINTED AND 4 MICROARRAY DATA SETS ANALYZED.

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When we quantified the mechanical properties of the PAA pads prior to ECM printing using rheometry, we found that gels created with the low(1:0.1), middle(1:0.25) and high (1:1.25) ratios of acrylamide to bisacrylamideexhibited elastic moduli of 132, 558 and 1510 Pa, respectively (Fig. 2A). The storage modulus (G’) of each of the PAA gel pads also remained stable when the level of oscillatory stress was increased from 1 to 10 Pa (Fig. 2B), which is critical to ensure the stability of the soft gels under printing conditions. To analyze the efficiency of ECM deposition on the PAA gel pads with different stiffnesses, we printed spots of rhodamine-labeled fibronectin. This confirmed our ability to spot ECM protein consistently at defined concentrations on the PAA pads and that the ECM proteins remained limited to precisely defined circular islands of approximately the same diameter that we printed (424 51.8 µ m) (Fig. 2C). Importantly, fluorescence microscopic analysis of these printed substrates confirmed that the fluorescent intensity increased in direct proportion to the concentration of fibronectin protein deposited on the PAA pad, regardless of its stiffness (Fig. 2C,D).

FIG. 2 (A) SHEAR MODULUS OF THE THREE DIFFERENT POLYACRYLAMIDE (PAA) GEL PADS (* **P<0.0001, MEAN ± S.E.M.). (B) STORAGE MODULUS AS A FUNCTION OF OSCILLATORY STRESS OF THE THREE POLYACRYLAMIDE GEL PADS. (C) MICROARRAY IMAGES OF RHODAMINE-LABELED FIBRONECTIN ON 132 PA PAA. (D) FLUORESCENT INTENSITY (ARBITRARY UNITS) MEASUREMENTS AS A FUNCTION OF FIBRONECTIN CONCENTRATION.

Effects of ECM Mechanics on Cell Size and Density To analyze the effects of these various combinations of ECM type and mechanics on cell form and function, we plated mouse embryonic mesenchymal cells isolated from E10 tooth germ on the slides, cultured them overnight in serum-containing medium, and fixed 24 hours later. Analysis of these substrates using fluorescence microscopy combined with computerized image analysis revealed that the cells exclusively attached to individual ECM protein spotsregardless of the stiffness of the PAA pad, and not to the intervening control regions printed with the non-adhesive protein, BSA (Fig. 3). Moreover, nearly identical adhesion responses were obtained in control studies in which cells were plated on ECM islands spotted on standard glass slides without any PAA pads (Supp. Fig.1).

To be able to quantify cell adhesion and shape on the microprinted ECM substrates, we developed a cell morphometric approach that automatically outlines nuclei and cell outlines using CellProfiler software (Supp.

Fig. 2). This automated method enabled us to measure the numbers of adherent cells as well as their mean projected cell areas. These studies revealed that increasing the collagen VI concentration from 100 to 300 µ g/ml resulted in a corresponding rise in the density of cells adherent to each ECM island, however, the degree of this response varied depending on the stiffness of the underlying PAA pad (Figs. 3&4A). In particular, at 558 Pa and 1510 Pa, there was a significant increase in the cell density on collagen VI when its concentration was raised from 200 to 300 µ g/ml, whereas there was a minimal difference in cell adhesion between these ECM coating densities on the more flexible (132 Pa) PAA pad (Fig. 4A). Interestingly, tenascin

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and the highest collagen VI density (300 µ g/ml) supported similar levels of cell adhesion on all stiffnesses, whereas printing them in combination on the same spot resulted in a lower level of cell attachment similar to those produced by 100 µ g/ml collagen VI alone. This is consistent with past work showing that tenascin can inhibit integrin-dependent cell adhesion on substrates coated with other types of ECM molecules (Rüegg, Chiquet-Ehrismann, and Alkan 1989; Chiquet-Ehrismann et al. 1988; Probstmeier and Pesheva 1999).

FIG. 3 IMMUNOFLUORESCENT STAINING OF MICROARRAY SPOTS. PRINTING OF BOVINE ALBUMIN SERUM, COLLAGEN VI AT 100, 200, 300 µ g/ml, TENASCIN 10 µ g/ml, AND COLLAGEN VI WITH TENASCIN (MIX) ON 132, 558, 1510 PA SUBSTRATES. (SCALE BAR = 200 µ m)

FIG. 4 COMBINATORIAL EFFECTS OF (B) CELL DENSITY AND (C) CELL SIZE AS A FUNCTION OF VARYING POLYACRYLAMIDE GEL PAD SUBSTRATES AND ECM PROTEINS. (***p<0.0001, **p<0.001, *p<0.01, MEAN ± S.E.M.)

Interestingly, cell spreading (projected cell area) was much less dependent on the ECM protein than on the physical properties of the gel, with average cell areas increasing progressively as the stiffness of the substrate was raised (Fig. 4B). This is consistent with previous reports which have shown that cell spreading increases as ECM substrate stiffness is raised (Polte et al., 2004; Yeung et al. 2005; Engler et al. 2006; Discher, Janmey, and Wang 2005). In addition, cell extension was found to increase as the coating density of collagen VI was increased on rigid glass slides, as previously demonstrated with various other ECM proteins (Ingber and Folkman 1989; Mooney et al. 1992). While a similar increase in spreading was observed when the coating concentrations of collagen VI were increased from 100 to 200 ug/ml on the moderate stiffness substrate, this was less evident on the stiffest substrate and it was completely lost on the most flexible PAA pad (Fig. 4B).

Interestingly, while the spots containing a mixture of collagen VI and tenascin were less effective at supporting cell adhesion than tenascin alone (Fig. 4A), the cells that adhered to these spots spread to similar degrees, although again spreading increased in directproportion to the stiffness of the substrate (Fig. 4B). In summary, this combinatorial microprinting method allowed us to establish a quantitative framework for how cell numbers and morphology of adherent embryonic mesenchymal cells are influenced by substrate stiffness and ECM compositionin vitro.

ECM-specific Effects on Tooth Differentiation To determine whether this mechanochemical ECM microarray platform can be used to identify unique biomaterial properties that induce tissue-specific tooth differentiation, we measured expression of the odontogenic transcription factor, Pax9, within embryonic mandibular mesenchymal cells. These studies

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revealed that, in general, cells exhibited the lowest levels of Pax9 fluorescent intensity on the intermediate stiffness (558 Pa) PAA pads regardless of the type or density of ECM coating, and the highest levels on the stiffest (1510 Pa) PAA gel pads and rigid control glass substrates (Fig. 5) when expression levels were normalized based on equivalent numbers of adherent cells. When we analyzed effects of varying ECM type, there was no detectable difference on Pax9 expression on the most flexible or intermediate (558 Pa) stiffness PAA pads. However, cells on the stiffest (1510 Pa)gel coated with the lowest collagen VI density (100 ug/ml) exhibited significantly (p < 0.05) higher levels of Pax9 expression than cells on higher coating densities. This raises the intriguing possibility that the particular in vitro mechanochemical features of this ECM spot more closely mimic the inductive tissue microenvironment that promotes tooth differentiation invivo. Interestingly, tenascin had little effect on mandibular mesenchymal cell differentiation on any of the flexible substrates, whereas it was a potent inducer on a highly rigid glass substrate (Fig. 5).

FIG. 5 QUANTIFICATION OF PAX 9 FLUORESCENT INTENSITY IN ARBITRARY UNITS. (***p<0.0001, **p<0.001, *p<0.01, MEAN ± S.E.M.)

In a recent study, it was found that the porosity of PAA gels, which is inversely proportional to its stiffness, influences collagen anchoring density that can alter stem cell fate; specifically, lower collagen anchoring densitieson softer gels were responsible for inducing increased differentiation (Trappmann et al. 2012). This may explain, in part, why the stiffest PAA pad (1510 Pa) induced higher Pax9 intensity when coated withthe lowest collagen VI concentration (100 ug/ml). However, cell shape also has been shown to play a central role in control of cell fate switching, with cell spreading inhibiting expression of tissue-specific differentiation (Singhvi et al., 1994; Chen et al., 1997; Polte et al., 2004). Thus, cell geometry may play a greater role in inducing odontogenesis in cells adherent to very soft gels (~100 Pa), whereas protein coating densities have greater influence in cells anchored to stiffer gels.

System Validation We next set out to validate the robustness of our microarray results by using qPCR to analyze Pax9 expression levels in cells on 1510 Pa padscoated with collagen VI at 100 ug/ml and 558 Pa gels coated with collagen VI at 300 ug/ml, which are the combinations that yielded the highest and lowest Pax9 intensities in our ECM microarray cultures, respectively. PCR analysis again revealed that Pax9 mRNA levels were higher in cells seeded on 1510 Pa gels coated with Collagen VI (100 ug/ml) compared to the 558 Pa-Collagen VI (300 ug/ml) combination (Fig. 6). Thus, these results independently confirmed the findings we obtained by analyzing Pax9 protein levels using fluorescence microscopy (Fig.5), thus validating our ECM microarray results.

FIG. 6 QUANTIFICATION OF MRNA EXPRESSION LEVELS OF PAX9 OF CELLS SEEDED ON 1510 PA WITH COL VI AT EITHER 100 µ g/ml OR 300 µ g/ml AND CELLS SEEDED ON 558 PA WITH COL VI AT EITHER 100 µ g/ml OR 300 µ g/ml. (*p<0.01, MEAN ± S.E.M.)

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Conclusions The methodology we developed here provides a unique and customized array that permits combinatorial analysis of the effects of various combinations of ECM types and mechanics on tooth differention in embryonic mesenchymal cells. While the biomaterial library analyzedhere was small compared to past high throughput screening technologies, our findings clearly demonstrate the concept and ease of developing a customized combinatorial microarray for determining the inductive capacity of very specific concentrations and combinations of ECM proteins on substrates with a range of mechanical properties that are relevant for analysis of embryological processes that are highly relevant for developmental biology as well as regenerative medicine. The results we generated using tooth differentiation as a model system also might be useful for the design of dental biomaterials that induce tooth formation in the future. In addition, this microarray system may be easily tuned to study combinatorial effects of mechanics and chemistry of other cell types of interest. Hence, it may be applied for a variety of tissue engineering studies that need to investigate the effects of mechanochemical microenvironmental cues on cell and tissue development in vitro. Finally, while we carried out our studies in 2D, there is currently a shift towards 3D printing technologies that can more closely recapitulate cell behaviour and interactions (Kolesky et al. 2014; Dolatshahi-Pirouz et al. 2014). Thus, it would be useful to extend this work to microarrays consisting of 3D gels of varying mechanical stiffness and coated with a greater range of ECM protein combinations in the future.

ACKNOWLEDGMENT

This work was conducted with support by grants from the NIH Common Fund (RL1DE019023 to D.E.I.) and the Wyss Institute for Biologically Inspired Engineering at Harvard University. We would like to thank A. Mammoto for providing helpful feedback on quantative PCR experiments.

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Supplementary Figures

FIG. S1IMMUNOFLUORESCENT STAINING OF GLASS SURFACE TREATED WITH COLLAGEN VI 100, 200, AND 300μg/ml, TENASCIN 10 μg/ml, ANDTENASCIN-COLLAGEN VI MIXTURE. (SCALE BAR = 200 µ m)

FIG. S2SAMPLE IMAGE OF CELLPROFILER ANALYSIS. (A) INPUT DAPI STAINED NUCLEI IMAGE. (B) OUTPUT IMAGE PROCESSED

BY CELLPROFILER IDENTIFYING CELL NUCLEI (WHITE). (C) SAMPLE MICROARRAY SPOT WITH DAPI STAINED NUCLEI AND GFP LABELED CELL BODY. (D) OUTPUT IMAGE PROCESSED BY CELLPROFILER DISTINGUISHING CELL BODY (RED) FROM CELL NUCLEI (WHITE). (SCALE BAR = 200 µ m).

FIG. S3PAX 9 FLUORESCENT INTENSITY IN ARBITRARY UNITS CORRELATING WITH (A) CELL DENSITY AND (B) CELL SIZE. (MEAN ± S.E.M.)

11