Cell differentiation is regulated by a host of microenvironmental factors, including both matrix composition and substrate material properties. We describe here a technique utilizing cell microarrays in conjunction with traction force microscopy to evaluate both cell differentiation and biomechanical cell–substrate interactions as a function of microenvironmental context.
Microfabricated cellular microarrays, which consist of contact-printed combinations of biomolecules on an elastic hydrogel surface, provide a tightly controlled, high-throughput engineered system for measuring the impact of arrayed biochemical signals on cell differentiation. Recent efforts using cell microarrays have demonstrated their utility for combinatorial studies in which many microenvironmental factors are presented in parallel. However, these efforts have focused primarily on investigating the effects of biochemical cues on cell responses. Here, we present a cell microarray platform with tunable material properties for evaluating both cell differentiation by immunofluorescence and biomechanical cell–substrate interactions by traction force microscopy. To do so, we have developed two different formats utilizing polyacrylamide hydrogels of varying Young's modulus fabricated on either microscope slides or glass-bottom Petri dishes. We provide best practices and troubleshooting for the fabrication of microarrays on these hydrogel substrates, the subsequent cell culture on microarrays, and the acquisition of data. This platform is well-suited for use in investigations of biological processes for which both biochemical (e.g., extracellular matrix composition) and biophysical (e.g., substrate stiffness) cues may play significant, intersecting roles.
Interactions between cells and surrounding microenvironmental factors mediate a large variety of biological processes throughout development, homeostasis, and disease pathogenesis1,2,3,4. These microenvironmental interactions include delivery of soluble factors to cells, cell–matrix binding, and cell–cell interactions via ligand–receptor binding. In addition to the above biochemical considerations, biophysical parameters, such as substrate mechanical properties (e.g., Young's modulus, porosity) and cell shape, and associated downstream mechanotransduction have increasingly gained recognition as key mediators of cell differentiation5,6,7,8,9,10. Signals resulting from these microenvironmental interactions serve as inputs to gene networks and signaling pathways. Moreover, these cell-intrinsic components also provide feedback to the microenvironment via secreted factors and matrix-degrading enzymes, completing a complex co-regulatory loop between cell-intrinsic genetic programs and cell-extrinsic microenvironmental factors5,11,12.
The use of engineered systems for the controlled presentation of microenvironmental factors has proven useful in a range of different contexts13,14,15. Microfabricated systems in particular have facilitated precise spatial patterning of proteins and cells as well as highly parallelized analysis via miniaturization13,16,17,18,19,20,21,22. Cell microarrays represent one such microfabricated system in which combinations of biomolecules are contact-printed onto an elastic polyacrylamide hydrogel substrate23,24,25. The inclusion of cell-adhesive components (namely matrix proteins) enables sustained cell adhesion and culture on microarrays, which is frequently followed by downstream analysis via immunocytochemistry and fluorescent reporters. Cell microarrays have been productively directed towards attaining an improved understanding of liver cell phenotype23,26, neural precursor differentiation27, mammary progenitor fate decisions28, embryonic stem cell maintenance/differentiation23,29,30, lung cancer metastasis31, and therapeutic response in melanoma32. We have recently demonstrated the use of cell microarrays for defining the role of extracellular matrix (ECM) protein composition in endoderm specification33, liver progenitor differentiation34,35, and lung tumor cell drug response36. In these works, we have focused on extending the combinatorial capabilities of the array platform and exploring the intersections of cell-intrinsic signaling with extracellular matrix composition and biomechanics. In addition, we have implemented biophysical readouts in this array platform to provide the ability to quantitatively characterize the role of cell contractility in differentiation processes35. To do so, we integrated traction force microscopy (TFM) with cell microarrays to enable high-throughput assessment of cell-generated traction. TFM is a widely utilized method to measure cell-generated traction forces and has provided significant insights regarding the coordination of single-cell and tissue-level function with the composition and biomechanics of the local microenvironment37,38,39,40. Thus, combining TFM with cell microarrays provides a high-throughput system for measuring key, physiologically relevant biophysical parameters.
The cell microarray platform described here consists of four sections: fabrication of polyacrylamide substrates, fabrication of arrays, cell culture and assay readout, and analysis of data. See Figure 1 for a schematic summary of the first three experimental sections; see Figure 2 for a schematic summary of the final section with a focus on analysis of immunofluorescence data. In order to adapt the cell microarray platform to studies of biomechanical cell–substrate interactions, we used polyacrylamide substrates of tunable Young's modulus but similar porosity, per Wen et al.41. To enable TFM measurements of forces exerted by cells on their substrate, we implemented a glass-bottom Petri dish format in addition to the thick glass microscope slides frequently utilized by other groups. Thus, this cell microarray platform is capable of parallel measurements of cell differentiation via immunofluorescence on microscope slides and cell-generated forces via TFM on separate glass-bottom dishes. We have also applied several improvements to the analytical approach commonly used with cell microarrays. Specifically, instead of parametric Z-scoring of overall island intensity, we measure single-cell intensity and apply quantile normalization in order to account for non-normal distributions and more accurately describe cellular behavior. We believe these improvements provide particular utility towards investigations of biological processes in which both biochemical and biophysical cues play significant, intersecting roles. Further, our analytical improvements enable the application of cell microarrays to studies of a range of cellular functions for which single-cell and population-level behavior diverge.
1. Fabrication of Polyacrylamide Substrates
2. Fabrication of Arrays
3. Cell Culture and Assay Readout
4. Analysis of Data
Using this platform, we investigated the role of both biochemical and biophysical cues in the fate specification of liver progenitors34,35. Protein A/G-conjugated Notch ligands showed improved retention and clustering in the polyacrylamide hydrogel (Figure 3A) and were furthermore capable of driving differentiation of liver progenitors towards a bile duct cell fate (Figure 3B). Using single-cell analysis, we quantified the response to the Notch ligands for the ECM proteins collagen I, collagen III, collagen IV, fibronectin, and laminin (Figure 3C), finding that the response of liver progenitors to the ligand depends also on the ECM context. Last, we utilized shRNA knockdown to generate liver progenitors without the ligands Dll1 and Jag1. The response to the arrayed Notch ligand varied depending on the presence of either ligand, confirming that the responsiveness to the cell-extrinsic ligand is also a function of the cell-intrinsic ligand expression (Figure 3D). Further, we observed a distinct subpopulation of double-positive (ALB+/OPN+) cells in the Dll1 knockdown (Figure 3D). Together, these representative results show: (1) the combinatorial capabilities of the array format, as exemplified by the pairing of multiple arrayed ECM proteins and Notch ligands with the knockdown of individual ligands; (2) the functionality of not only arrayed ECM proteins but also arrayed cell–cell ligand via Protein A/G-mediated conjugation; and (3) the implementation of our single-cell analysis and its ability to discern unique subpopulations.
We also observed that the differentiation of liver progenitors is dependent on both the substrate stiffness and the ECM composition (Figure 4A), specifically finding that collagen IV is supportive of differentiation on both soft and stiff substrates while fibronectin only supports differentiation on stiff substrates (Figure 4B). Representative heat maps of TFM measurements suggested that sustained traction stress at low substrate stiffness on collagen IV promoted differentiation into bile duct cells (Figure 4C), a finding confirmed by average root-mean-square values (Figure 4D). Together, these representative results show: (1) the successful integration of TFM with cell microarrays on substrates with a tunable stiffness to assess both the cell phenotype and the traction stress; (2) the coordination of the liver progenitor cell fate with both the matrix composition and the substrate stiffness; and (3) the implementation of our TFM analysis and typical traction stress profiles in cell microarrays.
Figure 1: Overview Schematic Showing the First Three Experimental Sections. In Section 1, glass substrates are cleaned and silanized to facilitate the fabrication of polyacrylamide hydrogels. In Section 2, the biomolecule combinations of interest are prepared in a 384-well source microplate. A robotic arrayer is then loaded with clean pins, the source microplate, and the polyacrylamide hydrogels and initialized, fabricating arrays on the hydrogels. In Section 3, cells are seeded onto the arrayed domains and allowed to adhere, after which the culture protocol of interest is performed. At the endpoint, cells are either fixed for immunocytochemistry/immunofluorescence or analyzed using TFM. Scale bars are 75 µm. Please click here to view a larger version of this figure.
Figure 2: Processing and Analysis of Immunofluorescence Data from Arrays. (A) Tiled, composite 32-bit RGB images are first binned and then split into individual 8-bit channels. Using a combination of arrayed fluorescent markers and cell islands, three corners of the array are identified to allow for automated orientation and gridding of the arrays. (B) Single-cell data is generated for each channel of the input arrays. In order to account for experimental drift, quantile normalization is applied by biological replicate, producing a single shared distribution across all replicates. Quantile normalized data is subsequently plotted and interpreted via calculation of ensemble measurements (e.g., cells/island, mean intensity, percentage cells positive for a label) or direct analysis of single-cell distributions. Please click here to view a larger version of this figure.
Figure 3: Notch Ligand Presentation Mediates Liver Progenitor Differentiation. (A) Fc-recombinant Notch ligands Jagged-1 (JAG1) and Delta-like 1 (DLL1) exhibited improved retention and clustering when arrayed with Protein A/G. Scale bar is 50 µm. (B) Liver progenitors differentiated into bile duct cells upon presentation with Notch ligand. 4',6-Diamidino-2-phenylindole (DAPI) is a nuclear label, albumin (ALB) is a hepatic cell marker, and osteopontin (OPN) is a bile duct cell marker. Scale bar is 150 µm. (C) Quantification of percentage of cells positive for OPN for the Notch ligands JAG1, DLL1, and Delta-like 4 (DLL4) on the ECM proteins collagen I, collagen III, collagen IV, fibronectin, and laminin. Student's t-tests were performed against control IgG for each arrayed Notch ligand within each ECM protein with P-values indicated for P<0.05 (*). (D) Imaging cytometry of ALB and OPN for cells on collagen III presented with the Notch ligands JAG1, DLL1, and DLL4. Liver progenitors without the Notch ligands Dll1 and Jag1 (i.e., shDll1 and shJag1) were generated using shRNA knockdown. Data in (C) presented as mean ± s.e.m. This figure has been modified from Kaylan et al.34. Please click here to view a larger version of this figure.
Figure 4: Matrix Composition and Substrate Stiffness Coordinate Liver Progenitor Differentiation. (A) Liver progenitor differentiation to bile duct cells is dependent on both ECM composition and substrate stiffness. DAPI is a nuclear label, ALB is a hepatic cell marker, and OPN is a bile duct cell marker. (B) Quantification of percentage of cells positive for OPN on substrates of Young's modulus 30 kPa, 13 kPa, and 4 kPa for collagen I (C1), collagen IV (C4), fibronectin (FN), and all two-way combinations of those ECM proteins. (C) Cell traction stress is dependent on both substrate stiffness and ECM composition. (D) Quantification of root-mean-square values of traction stress on substrates of Young's modulus 30 kPa and 4 kPa for collagen I (C1), collagen IV (C4), fibronectin (FN), and all two-way combinations of those ECM proteins. In (B) and (D), data were presented as mean ± s.e.m and Student's t-tests were performed against 30 kPa for each ECM combination with P-values indicated for P< 0.05 (*), P< 0.01 (**), and P< 0.001 (***). Scale bars are 50 µm. This figure has been modified from Kourouklis et al.35. Please click here to view a larger version of this figure.
Section | Problem | Potential Causes | Solution |
1. Fabrication of Polyacrylamide Substrate. | Coverglass cannot be removed from hydrogel. | Overpolymerization. | Reduce polymerization time to <10 minutes (4 W/m2). Check that UV crosslinker output is within expected range. |
Poor polyacrylamide hydrogel polymerization. | Underpolymerization. | Increase polymerization time to >10 minutes (4 W/m2). Check that UV crosslinker output is within expected range. | |
Polyacrylamide hydrogels are damaged after removal of coverglass. | Soft polyacrylamide hydrogels are easy to damage. | We observe decreasing hydrogel fabrication yield (~50%) for the softest (i.e., 4 kPa) hydrogels in particular. Handle hydrogels gently and increase starting numbers to attain desired yield. | |
2. Fabrication of Arrays. | Poor or inconsistent spot morphology. | Inconsistent humidifier function. | Check that humidifier and rheometer a functional throughout each print run and maintain 65% RH. |
Pins stuck in printhead or clogged. | Clean the printhead to allow for free pin movement. Clean pins thoroughly before or after each print run to remove aggregates from pin channels. | ||
3. Cell Culture and Assay Execution. | Cell detachment or death on arrays after initial attachment. | Overseeding and excessive proliferation. | Reduce initial seeding density and time. Use "maintenance" or "differentiation" media during array culture to reduce cell proliferation. |
Release of toxic acrylamide monomer from hydrogel. | Soak hydrogels in dH2O for at least 3 d to allow for diffusion/release of acrylamide monomer and reduce cell toxicity. | ||
Cells don't attach to arrays. | Underseeding. | Increase initial seeding density and time. Use a more strongly adherent cell type. | |
Poor deposition of matrix or biomolecule condition. | Clean pins of particles and aggregates, confirm printing parameters, and evaluate spotting of fluorescent markers, e.g., rhodamine-conjugated dextran. | ||
Specificity of cell–matrix interactions. | Different cell types adhere specifically to some but not other ECM proteins. Test multiple different ECM proteins with your cells. | ||
Suboptimal array storage after fabrication. | We recommend storing fabricated arrays overnight at 65% RH and room temperature, in part to avoid phase changes during freezing. Cell adhesion is sensitive to both humidity, temperature, and storage time; make sure these parameters are consistent/optimized for your experiments. | ||
Detachment of hydrogel from glass substrate during cell culture. | Poor slide cleaning and silanization. | Replace working solutions for slide cleaning and silanization. | |
Overdehydrated hydrogel. | Don't leave hydrogels dehydrating on a hot plate for longer than 15–30 min. | ||
4. Analysis of Data. | High variability between replicate spots and slides. | Variability in array fabrication. | Check that pins and printhead are clean. Confirm humidifier function. Visualize and quantify spot and array quality using fluorescent markers. Store arrays as recommended above. |
Table 1: Troubleshooting.
In our experiments, we have found that the most common failures are related to the quality of fabricated arrays and poorly characterized response in the biological system of interest. We refer the reader to Table 1 for common failure modes in cell microarray experiments and associated troubleshooting steps. Regarding quality of arrays in particular, we recommend the following. Confirm the technical quality and robustness of arraying programs, parameters, and buffers using fluorescently labeled molecules such as rhodamine-conjugated dextran. Thoroughly clean pins either before or after arraying per the manufacturer's instructions and further visually check that the pin channels are clear of debris using a light microscope. Confirm arrayed biomolecule retention using general protein stains or immunolabeling. Note that biomolecules with a molecular weight below 70 kDa are frequently not retained in the hydrogel23,31. Validate arrayed biomolecule cell-functionality using multiple cell types. Note that only adherent cells are compatible with arrays; additionally, adhesion to arrays is dependent on both cell-specific properties (e.g., integrin expression profile) and the selected ECM proteins.
Due to limited space, we have not provided an extensive treatment of array design, layout, and fabrication here and refer the reader to previous works23,25. We generally use 100 spot subarrays (150 µm spot diameter, 450 µm center-to-center distance) composed of 10–20 unique biomolecule conditions (i.e., 5–10 spots/condition). The number of subarrays in one array varies depending on the number of biomolecule conditions of interest, which can be comfortably scaled up to 1,280 on one 25 × 75 mm microscope slide (~ 6,400 spots in 64 subarrays)25,31. The parameters above will further vary depending on the pattern size of interest; pins capable of generating patterns from 75 – 450 µm are readily available.
Array experiments are best complemented by validation of high-scoring arrayed conditions of interest using other culture formats, assay readouts, and biological model systems. Specifically, we recommend further validating effects of select arrayed conditions using bulk cultures in conjunction with standard molecular biology techniques (e.g., qRT-PCR, immunoblotting) or standard TFM. Genetic manipulation (e.g., knockdown or overexpression) of the factor of interest in an appropriate biological model system can also serve to confirm effects observed in arrays. In vivo animal models represent another means of validation and were recently used, for example, to confirm the central role of galectin-3 and galectin-8 in the lung cancer metastatic niche, as initially identified via cell microarray31,49.
A number of other methods have been used to probe microenvironmental regulation of cellular functions, including a variety of two-dimensional microfabricated systems18,50,51,52,53,54,55 and three-dimensional engineered biomaterial systems56,57,58,59,60,61. In comparison with other methods, the particular advantages of the cell microarray platform described here consist of: (1) throughput up to hundreds or thousands of different combinations of factors, enabling analysis of interaction effects; (2) accessible, automated imaging and analysis; (3) integration of both biochemical and biophysical readouts with controlled presentation of arrayed factors; (4) ability to vary substrate material properties; and (5) high-content single-cell analysis of cell fate and function.
In summary, the combination of cell microarrays with TFM on substrates of tunable substrate stiffness enables thorough characterization of both biochemical and biophysical cues. As presented here, this platform is generalizable and can be readily applied to a variety of adherent cell types and tissue contexts towards an improved understanding of combinatorial microenvironmental regulation of cell differentiation and mechanotransduction.
The authors have nothing to disclose.
We acknowledge Austin Cyphersmith and Mayandi Sivaguru (Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana–Champaign) for assistance with microscopy and for generously accommodating screen and video capture at the microscopy core.
0.2 µm syringe filter | Pall Corporation | 4433 | Match with appropriately-sized Luer lock plastic syringes. |
100× penicillin–streptomycin solution | Fisher Scientific | SV30010 | |
22×60 mm coverglasses | Electron Microscope Sciences | 63765 | |
3-(trimethoxysilyl)propyl methacrylate (3-TPM) | Sigma-Aldrich | 440159 | Store under inert gas per manufacturer's instructions. Exposure of 3-TPM to air could compromise silanization of glass substrates. CAUTION: 3-TPM is a combustible liquid. Keep away from heat, sparks, open flames, and hot surfaces and use only in a chemical fume hood. |
3-[(3-Cholamidopropyl)dimethylammonio]-1-propanesulfonate hydrate (CHAPS) | Sigma-Aldrich | C3023 | |
35 mm glass-bottom Petri dishes | Cell E&G | GBD00002-200 | 13 mm well consisting of #1.5 coverglass. Enables TFM and live-cell imaging. |
384-well polypropylene V-bottom microplate, non-sterile | USA Scientific | 1823-8400 | |
6-well polystyrene microplates | Fisher Scientific | 08-772-1B | 35 mm glass-bottom Petri dishes fit into wells of microplate, easying array fabrication. |
Acetone | Sigma-Aldrich | 179973 | |
Acrylamide | Sigma-Aldrich | A3553 | CAUTION: Exposure to acrylamide can result in acute toxicity and irritation. Wear protective gloves, clothing, and eye protection. |
Collagen I, rat tail | EMD Millipore | 08-115MI | |
Collagen III, human | EMD Millipore | CC054 | |
Collagen IV, human | EMD Millipore | CC076 | |
Crosslinker, 365 nm | UVP | CL-1000 | |
Dextran, rhodamine B-conjugated, 70 kDa | ThermoFisher Scientific | D1841 | Used as a marker for array location. |
Dimethyl sulfoxide | Fisher Scientific | BP231 | |
Dulbecco's phosphate-buffered saline (PBS) | Fisher Scientific (HyClone) | SH3001302 | |
Ethyl alcohol | Decon Labs | 2701 | |
Ethylenediaminetetraacetic acid (EDTA) | Sigma-Aldrich | ED | |
Fc-recombinant DLL1, mouse | R&D Systems | 5026-DL-050 | |
Fc-recombinant DLL4, mouse | AdipoGen | AG-40A-0145-C050 | |
Fc-recombinant JAG1, rat | R&D Systems | 599-JG-100 | |
Fibronectin, human | Sigma-Aldrich | F2006 | |
Fluorescent microscope, inverted | Zeiss | Axiovert 200M | Ensure microscope is equipped with a robotic stage for both automated fluorescent imaging and TFM. Environmental control (i.e., 37 °C and 5% CO2) is highly advisable for TFM. |
Fluoromount G with DAPI | SouthernBiotech | 0100-20 | |
Glacial acetic acid | Sigma-Aldrich | 695092 | CAUTION: Acetic acid is flammable and corrosive. Wear protective gloves, clothing, and eye protection. |
Glycerol | Sigma-Aldrich | M6145 | |
Irgacure 2959 | BASF Corporation | 55047962 | |
Laminin, mouse | EMD Millipore | CC095 | |
Methanol | Sigma-Aldrich | 179957 | |
Microarray scanner | GenePix | 4000B | Fluorophores must be Cy3- or Cy5-compatible. |
Microarrayer | Digilab | OmniGrid Micro | Other microarrayerse of similar or greater capability can readily be substituted. |
Microscope slides, 25×75 mm | Sigma-Aldrich | CLS294775X25 | ~0.9–1.1 mm thickness. |
N,N′-Methylenebisacrylamide (bisacrylamide) | Sigma-Aldrich | M7279 | CAUTION: Exposure to acrylamide can result in acute toxicity and irritation. Wear protective gloves, clothing, and eye protection. |
Paraformaldehyde (PFA), 16% v/v | Electron Microscope Sciences | RT15710 | Prepare PFA fresh (do not store) for optimal fixation. CAUTION: Exposure to PFA can result in acute toxicity and can also irritate or corrode skin on contact. Wear protective gloves, clothing, and eye protection and use only in a chemical fume hood. |
Protein A/G, recombinant | ThermoFisher Scientific | 21186 | |
Pyrex drying tray, 2000 ml | Fisher Scientific | 15-242B | |
Rectangular 4-chambered culture dish | Fisher Scientific (Nunc) | 12-565-495 | For cell culture on arrayed microscope slides. |
Sodium acetate | Sigma-Aldrich | S2889 | |
Sodium hydroxide | Sigma-Aldrich | 415413 | CAUTION: NaOH is highly caustic and can cause severe skin burns and eye damage. Wear protective gloves, clothing, and eye protection. |
Stealth pin for arraying | ArrayIt | SMP3 | Clean pins after each array run using the instructions of the manufacturer. Produces 150 micron domains; purchase other pin sizes (75–450 microns) as suited to your particular application. |
Triton X-100 | Sigma-Aldrich | X100 |