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Accessible and cost-effective methods for patterning cell monolayers on compliant substrates

  • Molly McCord,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliations Department of Mechanical Engineering, University of Wisconsin–Madison, Madison, Wisconsin, United States of America, Biophysics Program, University of Wisconsin–Madison, Madison, Wisconsin, United States of America

  • Aimal H. Khankhel,

    Roles Methodology, Visualization, Writing – original draft

    Affiliation Interdisciplinary Program in Quantitative Biosciences, University of California Santa Barbara, Santa Barbara, California, United States of America

  • Katherine Kafkis,

    Roles Data curation, Investigation, Methodology, Validation

    Affiliations Department of Mechanical Engineering, University of Wisconsin–Madison, Madison, Wisconsin, United States of America, Department of Biomedical Engineering, University of Wisconsin–Madison, Madison, Wisconsin, United States of America

  • Griffin Radtke,

    Roles Methodology, Writing – review & editing

    Affiliation Department of Mechanical Engineering, University of Wisconsin–Madison, Madison, Wisconsin, United States of America

  • Sinan Candan,

    Roles Methodology, Writing – review & editing

    Affiliation Department of Mechanical Engineering, University of Wisconsin–Madison, Madison, Wisconsin, United States of America

  • Hareesh Ashok Kumar,

    Roles Methodology, Writing – review & editing

    Affiliations Department of Mechanical Engineering, University of Wisconsin–Madison, Madison, Wisconsin, United States of America, Biophysics Program, University of Wisconsin–Madison, Madison, Wisconsin, United States of America

  • Pieter Derksen,

    Roles Methodology

    Affiliation Department of Physics, University of California Santa Barbara, Santa Barbara, California, United States of America

  • Michelle Tam,

    Roles Methodology

    Affiliation Interdisciplinary Program in Quantitative Biosciences, University of California Santa Barbara, Santa Barbara, California, United States of America

  • Kaiyan Zhou,

    Roles Methodology

    Affiliation Department of Physics, University of California Santa Barbara, Santa Barbara, California, United States of America

  • Markus W. Merk,

    Roles Methodology

    Affiliation Interdisciplinary Program in Quantitative Biosciences, University of California Santa Barbara, Santa Barbara, California, United States of America

  • Christian Franck,

    Roles Funding acquisition, Resources, Writing – review & editing

    Affiliations Department of Mechanical Engineering, University of Wisconsin–Madison, Madison, Wisconsin, United States of America, Department of Biomedical Engineering, University of Wisconsin–Madison, Madison, Wisconsin, United States of America

  • Sebastian J. Streichan,

    Roles Funding acquisition, Writing – review & editing

    Affiliations Interdisciplinary Program in Quantitative Biosciences, University of California Santa Barbara, Santa Barbara, California, United States of America, Department of Physics, University of California Santa Barbara, Santa Barbara, California, United States of America

  • Jacob Notbohm

    Roles Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing – review & editing

    jknotbohm@wisc.edu

    Affiliations Department of Mechanical Engineering, University of Wisconsin–Madison, Madison, Wisconsin, United States of America, Biophysics Program, University of Wisconsin–Madison, Madison, Wisconsin, United States of America, Department of Biomedical Engineering, University of Wisconsin–Madison, Madison, Wisconsin, United States of America

Abstract

Micropatterning is a versatile technique for confining single cells and cell monolayers to a particular size or shape. The resulting geometrical confinement is one means of controlling migration, differentiation, and force generation. As such, micropatterning is a valuable tool for studying the principles governing collective cell behavior, tissue morphogenesis, and other questions in mechanobiology. Here, we present two detailed and accessible protocols for micropatterning cell monolayers onto compliant substrates made of a polyacrylamide hydrogel and a polydimethylsiloxane elastomer. These protocols require minimal specialized equipment, making them broadly accessible. We validate the fidelity of our protocols across a range of confinement geometries. Furthermore, we demonstrate an example application of our hydrogel protocol to traction force microscopy, which allows for investigating effects of geometric confinement on cell-generated forces. Together, these protocols provide detailed, reproducible tools to support the widespread application of micropatterning in studies of mechanobiology and collective cell dynamics.

Introduction

Micropatterning of substrates to geometrically confine single cells and cell monolayers has emerged as a powerful tool to investigate the fundamental principles governing cellular behavior and tissue morphogenesis, as well as applied processes such as control of cardiomyocyte contraction and development of cell-based soft robots [18]. By manipulating the size and shape of a cell or tissue, a range of different behaviors can be induced. Changing the area—for example, by confining a monolayer of cells to smaller or larger circle-shaped islands—can influence cell motion. Cells confined to small islands of approximately 300 μm diameter exhibit spontaneous rotational motion [9,10], and cells confined to larger islands exhibit coordinated oscillations [11,12]. It was also seen that single cells transition from growth to apoptosis with decreasing island size [1]. The shape of the confinement additionally influences cellular behavior. For example, stem cell differentiation varies based on whether single cells are confined to circular, square, or star shaped patterns [3]. Confinement to circular islands has also been used to study topological defects in cell orientation fields [13], as well as stress organization during tissue morphogenesis [14]. Additionally, confinement can influence the organization of collective cell behaviors such as wound healing; for example, when cells are confined against a barrier and allowed to migrate into lanes of varying sizes, cell monolayers in the narrowest lanes migrate the fastest [4]. Furthermore, when cells were confined to circular islands, the cells at the edges of the island had an up-regulation in genes associated with cell movement and collective cell migration compared to the cells at the islands interior [8]. Additionally, micropatterning has been integrated with traction force microscopy to allow for force measurements during cellular confinement [1517]. These studies highlight the versatility of micropatterning as a tool to manipulate and control cellular behavior as a means to gain insight into fundamental biological processes. To support broader use, there is a need for standardized and accessible protocols that clearly describe methods for geometric cell confinement.

Various techniques have been developed to geometrically confine cells through micropatterning. Two of the most commonly used approaches are microcontact printing [1,18] and stenciling [19]. Microcontact printing involves depositing extracellular matrix (ECM) protein onto an elastomeric stamp, which is then transferred onto a surface, creating regions that are adhesive or non-adhesive for cells. This method has been used to demonstrate that when confined to ring-shaped patterns, cells undergo directional migration and chiral alignment [20] and coordinated rotational motion that depends on monolayer polarity [21]. Microcontact printing has also been used to improve the mechanical function of cardiomyocytes by guiding cellular alignment [22]. While microcontact printing offers high spatial resolution, a challenge of the technique is that it involves many steps—including stamp fabrication, inking, drying, and transfer—that can introduce variability. Microcontact printing is also difficult to apply on soft substrates like polyacrylamide hydrogels, which are a commonly used substrate in mechanobiology [2325]. In contrast, stenciling, a technique with fewer steps and compatible with soft substrates, involves creating a mask to restrict ECM deposition to specific regions of a surface, enabling the formation of well-defined cell patterns. This method has been used to study a wide range of cellular behaviors, including spreading [5,26,27] and wound closure [2831]. While stenciling is versatile and a widely used technique, many existing protocols lack sufficient detail, making it difficult for researchers to apply this method to their work.

Here we present two detailed, accessible protocols for confining cell monolayers to user-defined stenciling on (1) polyacrylamide hydrogel substrates and (2) polydimethylsiloxane (PDMS) elastomer substrates. Importantly, both of the protocols presented here use widely available laboratory materials and require minimal specialized equipment, making them straightforward to implement without access to clean room facilities or expensive lithography systems. We provide quantitative validation of pattern fidelity across a range of geometries and demonstrate that these protocols enable controlled studies of geometry-dependent collective motion in epithelial cell layers. We also provide a demonstrative application that combines our method with quantification of the cell velocities and cell-substrate tractions, wherein the data show that controlling the size and shape of cell monolayers can affect the spatial distributions of both forces applied by the cells and the resulting velocity fields.

Materials and methods

The protocol for stencil-based micropatterning on hydrogels is published on protocols.io (https://dx.doi.org/10.17504/protocols.io.eq2ly4nmwlx9/v2) and is included for printing as Supporting Information File 1 with this article. The protocol for micropatterning on PDMS substrates is included as Supporting Information File 2. Complete information on reagent brands, manufacturers, and catalog numbers are listed in the full patterning protocols in Supporting Information 1 and Supporting Information 2. Below, we describe the materials and methods used to produce the sample data sets shown in the Expected Results section.

Cell culture

Madin-Darby Canine Kidney (MDCK) type II cells (purchased from Millipore Sigma) were maintained in low-glucose Dulbecco’s modified Eagle’s Medium (DMEM, 10–014, Corning) supplemented with 10 fetal bovine serum (FBS, Corning) and 1% Penicillin-Streptomycin (Corning). Human keratinocytes (HaCaTs, provided by Professor Kristyn Masters’ Lab) were maintained in high-glucose Dulbecco’s modified Eagle’s Medium (DMEM, 10–013, Corning) supplemented with 10 fetal bovine serum (FBS, Corning) and 1% Penicillin-Streptomycin (Corning). Cells were maintained at 37°C and 5% CO2. Experiments involving human induced pluripotent (hiPS) stem cells reported in this paper were approved by the Human Stem Cell Research Oversight Committee (hSCRO) at the University of California Irvine, study no. 2018–1072. We used early passages (50) of hiPS cell line CTR217 (which were a gift from Kenneth Kosik’s lab and first used for this study on 04/15/2025). The cell line was previously karyotyped as normal. The hiPS cells were cultured with mTESR+ medium (Stemcell Technologies 100–0276) on Matrigel (Corning 354277)-coated 6-well plates. Cell culture medium was exchanged daily, and cells were maintained at 37°C and 5% CO2.

Method 1 Sample Preparation and optical microscopy

Polyacrylamide (PA) gels of 6 kPa Young’s modulus were prepared using previously described methods [12,28,32]. To begin, the surface of a glass bottom dish with a 1.5 cover glass was covered with a solution containing 0.2 (v/v) acetic acid and 0.3 (v/v) 3-(Trimethoxysilyl)propyl methacrylate 98 in ultrapure water and allowed to sit for 30 min. The dishes were then washed in ultrapure water and dried. A solution of polyacrylamide and bisacrylamide (Bio-Rad) (see [33] or similar literature for recipes with different Young’s modulus) containing fluorescent particles (Life Technologies) was prepared. Once the ammonium persulfate is added, it is important to work quickly, and polymerization times might need to be adjusted depending on the user. This can be done by changing concentrations of N,N,N´,N´-tetramethylethylenediamine (TEMED, Bio-Rad) and ammonium persulfate (Bio-Rad). 20 μL of the polyacrylamide solution was pipetted onto the center of the dish, and a 18 mm coverslip was gently placed over the top of the gel solution. It is important that the coverslip be in the middle of the dish and not touching the plastic on the sides to minimize leakage. Next, the dishes were covered with a lid, stacked, taped together, and placed upside down in a centrifuge. It is important to prevent any rattling of the dishes as it can contribute to leakage. To this end, dishes were stacked and wrapped with paper towels before placing them into the centrifuge buckets. Dishes were centrifuged upside down for 14 min at 60–80 relative centrifugal force. The gel typically polymerized in about 5–7 min, and the longer centrifugation time was used as a precaution. Ultrapure water was added to each dish to cover the gels, and the gels were allowed to swell overnight. Next, we followed our stencil-based micropatterning protocol to micropattern 0.1 mg/mL type I rat tail collagen (BD Biosciences) and seed the cells. Samples were then imaged using an Eclipse Ti-E microscope (Nikon) running on Elements AR software with a 10 × numerical aperture 0.5 objective (Nikon) and an Orca Flash 4.0 digital camera (Hamamatsu).

Some experiments imaged only the collagen I bound to the substrate. For these experiments, samples were prepared according to the protocol, but no cells were seeded on the surface. Collagen I was fluorescently labeled using a polyclonal collagen I antibody 1:300 (ThermoFisher, cat. PA 1–36145), and dishes were incubated overnight at 4°C in the antibody solution. A secondary antibody, Alexa Fluor 488 goat anti-rabbit antibody (Invitrogen, cat. R37116), was added according to manufacturer instructions, and incubated at 4°C for 4 hr. Samples were imaged on a Nikon A1R confocal microscope with a numerical aperture 0.13 objective (Nikon) using NIS-Elements Ar software (Nikon) and an Orca Flash 4.0 digital camera (Hamamatsu).

Traction force microscopy and monolayer stress microscopy

Cell velocities were computed using Fast Iterative Digital Image Correlation (FIDIC) [34] on successive phase-contrast images of the cell monolayers using 64 × 64 pixel subsets with spacing of 16 pixels and dividing by the time between images (10 or 15 min).

For traction experiments, the particles in the substrate were imaged via fluorescence and the cells were imaged via phase contrast every 10 or 15 min. Then the cells were removed from the substrate with trypsin, allowing the substrate to recover to an undeformed reference state, and a reference image of the fluorescent particles was collected. Cell-induced substrate displacements were computed by correlating the cell-deformed image of fluorescent particles to the reference one with FIDIC [34] using the same subset size and spacing as described above. Cell-substrate tractions were computed via unconstrained Fourier Transform Traction Cytometry [35] with a correction for finite substrate thickness [36,37]. The in-plane components of the stress tensor were computed using Monolayer Stress Microscopy [32,38,39]. The maximal and minimal eigenvalues of the stress tensor are the first and second principal stresses, and , respectively. The maximal shear stress was computed by taking half the difference in principal stresses ().

Method 2 sample preparation and optical microscopy

Soft elastomeric silicone substrates were prepared using established protocols. In brief, a silicone elastomer was synthesized by mixing a 6:5 weight ratio of CY52-276A and CY52-276B polydimethylsiloxane (Dow Corning Toray). After degassing for 5 min, the elastomer solution was spin-coated onto a 22 mm round coverslip (10200−036, VWR) for 60 s at 500 rpm followed by a spin-off step of 1000 rpm for 3 s. A 35 mm plastic bottomed petri-dish (Corning 351008) with a custom pre-drilled 20 mm hole was then placed onto the PDMS coated coverslip to create a sealed PDMS-coated glass-bottomed dish. These dishes were then cured at 65°C overnight. The substrates were kept in a clean dust-free and dry environment and always used within 4 weeks of fabrication.

After curing, the soft PDMS substrates were treated with (3-aminopropyl)triethoxysilane (APTES, Sigma-Aldrich, cat. no. A3648) diluted at 10 in absolute ethanol (Sigma, 459844) for 4.5 min, rinsed 3 times with ethanol, followed by a rinse with deionized water and carefully aspirated without touching the substrate surfaces until thoroughly dry. To attach fluorescent beads as fiducial markers, PDMS substrates were incubated for 17 hr with a solution containing 400-nm-diameter sky-blue fluorescent carboxylate-modified beads (1:50 v/v dilution, Spherotech, CFP-0570–2), MES buffer (0.5M pH 5.0, ThermoFisher J62081.AE), and 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC, 0.4 mg/ml, Sigma-Aldrich). Next, substrates were rinsed 3 times with deionized water and immediately used in photopatterning steps.

Images were recorded on a Leica SP8 confocal microscope with a 633 nm laser at 0.75 laser power utilizing a HyD detector with a 643–743 nm bandpass detector window. Images were recorded with 20 × magnification using a resolution of 2048 × 2048 pixels at 8-bit depth.

Results

Method 1

Both complete protocols can be found in Supporting Information Files 1 and 2. In Method 1, a photomask with the desired geometries is designed and printed. Then, SU-8 is heated, and a ∼400 μm thick layer is spread onto a silicon wafer with a razor blade. This 400 μm thickness is larger than the thickness commonly used for many microfluidics assays, and it is chosen to facilitate handling of the PDMS masks in later steps. The wafer undergoes a soft bake. Once the wafer has returned to room temperature, the photomask is secured over the wafer, and the wafer is exposed to UV light, which crosslinks the exposed SU-8. The SU-8 that went unexposed is developed away, leaving the desired features behind. The wafer is then silanized to prevent PDMS from sticking to the surface. A mask is created by spin coating a thin layer of PDMS onto the chip and curing overnight in the oven. The mask is then removed, with the result being a pliable PDMS sheet with through-holes in the shape of the features. Next, the masks were treated with oxygen plasma and attached to the surface of a polyacrylamide hydrogel. Sulfo-SANPAH is added over the mask, and exposed to UV light. Collagen I is then added and allowed to covalently bind to the substrate overnight. At this point, the mask is removed and the gel is treated with bovine serum albumin to prevent non-specific adhesion. Finally, cells are seeded onto the gel, and are confined to the desired geometries. A schematic of this procedure is illustrated in Fig 1.

To assess the fidelity of Method 1, we compared the intended geometries with both the deposited extracellular matrix and the resulting confined cell monolayers. For this, we designed three patterns, a circle, a square, and a five-pointed star, all having widths of approximately 1 mm (Fig 2 a,b,c). The three patterns are useful for testing, as they provide a range of complexity, with the circle being the simplest and the star being the most complex. We began by patterning the polyacrylamide substrate with collagen I and labeling it fluorescently to visualize how well the deposited collagen matched the initial design. Across all geometries, the collagen deposition generally matched the design (Fig 2 d,e,f). The collagen transfer was not as strong at sharp corners, as seen in the corners of the square and the tips of the star (Fig 2 e,f). On separate micropatterned substrates, we seeded MDCK cells on the patterns, as described in the protocol. The resulting monolayers adhered well to the patterned regions (Fig 2 g,h,i). Cell confinement was robust in all cases, although some bridging was observed in regions of acute angles in the star pattern (Fig 2i). It is important to note that the passivation of non-patterned regions with bovine serum albumin (BSA) prevents nonspecific cell adhesion and limits spreading outside the collagen-treated areas. To ensure this method is compatible with other cell types, we confined human keratinocytes to 1 mm circular islands (S3 Fig S1 in S3 File).

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Fig 2. Pattern fidelity of Method 1.

(a) Schematic of the 1 mm circular pattern. (d) Patterned collagen I. (g) Epithelial cells confined by the pattern. (j) Binarized cell island. Panels (b,e,h,k) and (c,f,i,l) repeat the patterning for square and star geometries, respectively. (m) Dice coefficient for circle, square, and star geometry. (n) Area difference between initial design and confined cell monolayers for square, star, and circle geometry. Gray dots represent individual cell monolayers, and black bars indicate means. At least 7 monolayers were used per shape.

https://doi.org/10.1371/journal.pone.0344657.g002

To quantify pattern fidelity, we calculated the Dice coefficient between the designed patterns and the confined cell monolayer. The Dice coefficient was calculated according to , where A is the designed confinement mask (Fig 2 a,b,c), B is the binarized mask of the confined cell monolayers (Fig 2 j,k,l), and is the intersection of A and B. Each point in A and B is a pixel, and each pixel has a width of 0.65 μm. The Dice coefficient ranges from 0 to 1, with 1 indicating perfect overlap between A and B, and 0 indicating no overlap. The mean Dice coefficient was greater than 0.9 for both the circle and square patterns, indicating high pattern fidelity (Fig 2m). For the star pattern, the mean Dice coefficient was ≈ 0.8, due to reduced fidelity in sharp and narrow regions. All patterns had Dice coefficients above 0.8, demonstrating that the confined cell monolayer matched the designed confinement well. We next quantified the area difference between the designed pattern and the confined cell monolayer. The area difference is calculated as , where C is the area of the designed confinement mask in pixels, and D is the area of the binarized mask of the cell monolayer. The circular pattern showed the smallest difference in area of ∼5 (Fig 2n). The square and star pattern had larger area differences of ∼10 and ∼30 , respectively. As expected, increasing pattern complexity led to decreased pattern fidelity, as more intricate designs were more susceptible to incomplete pattern transfer or cell bridging. However, the Dice coefficient and area difference metrics show that our protocol achieves high pattern fidelity, particularly for geometries with smooth, continuous boundaries.

Method 2

Method 2 (Supporting Information File 2), which is used to pattern PDMS substrates, has been previously established in similar systems [4044]. Briefly, a PDMS substrate is fabricated on a glass sheet. A photopatterning solution composed of PLL-PEG is placed between the substrate and a photomask. Next, the sample is exposed to UV, which degrades the PEG in the illuminated regions, allowing for protein conjugation. Finally, the sample is washed and an ECM is added, which binds to the UV-exposed areas, as illustrated in Fig 3. Cells are then seeded onto the substrate and allowed to adhere. A description of the method, and a custom UV setup is described in the Supporting Information.

We also quantified the pattern fidelity for Method 2. Fluorescently labeled bovine serum albumin (BSA) of protein deposition and confined monolayers showed strong alignment with the designed pattern (Fig 4a-c). The Dice coefficient was calculated as described above, and was greater than 0.9, indicating high pattern fidelity (Fig 4e). Area difference was quantified as described above, and was less than 5, demonstrating that the confined cell monolayer matched the designed confinement well (Fig 4f). Together, these results show that both Method 1 and Method 2 achieve high pattern fidelity.

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Fig 4. Pattern fidelity of Method 2.

(a) Schematic of the 300 μm circular pattern. (b) Patterned BSA-488. (c) Epithelial cells confined by the pattern. (d) Binarized cell island. (e) Dice coefficient for circle geometry. (f) Area difference between initial design and confined cell monolayers for the circle geometry. Gray dots represent individual cell monolayers, and black bars indicate means. Results are from 6 cell monolayers.

https://doi.org/10.1371/journal.pone.0344657.g004

To illustrate how this protocol can be used to study tissue mechanics and collective cell behavior, we applied Method 1 to confine MDCK monolayers to circular islands of three different diameters, 300 μm, 400 μm, and 1 mm (Fig 5a-c), and imaged over several hours. The 300 μm and 400 μm islands were generated using lithography-based micropatterning, while the 1 mm island was created using a biopsy punch, which is a convenient alternative for producing patterns with features mm. Both approaches are detailed in Method 1 (Supporting Information File 1). For each island size, cells filled the island. Occasionally, some cells appeared outside of the micropatterned area. These cells had rounded morphology, suggesting that they were not well adhered. This system allows for controlled study of how the size of an epithelial monolayer influences the magnitude and spatial organization of cellular velocity. For each cell island, we quantified the cell velocity using digital image correlation. The resulting heat maps of velocity magnitude overlaid with velocity vectors are shown in Fig 5d-f. Smaller cell islands exhibited smoother and more coherent patterns of motion compared to the 1 mm island, which had visible vortices in the velocity field. Consistent with prior observations [9,10] the 300 μm island showed rotational motion about the center of the island (Fig 5d). Interestingly, the average velocity magnitude in the 300 μm and 400 μm island was approximately half that of the 1 mm islands, suggesting that the confinement caused by the smaller island size reduced the average cellular motion. Additionally, further analysis can be done to quantify the motion of the cell islands. For example, the distribution of velocity magnitude and direction can be seen in Fig 5g,h. These methods have been previously used to quantitatively characterize cell motion and its relationship to force generation in epithelial monolayers, including analyses of stress-strain rate relationships and stress-cell shape relationships [4547]. Together, these results demonstrate that our protocol enables controlled investigation of confinement size-dependent collective motion in epithelial monolayers.

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Fig 5. Representative experiment showing effects of island size on cell velocity.

(a-c) Phase contrast image of 300 μm, 400 μm, and 1 mm diameter cell islands. (d-f) Heat map of velocity magnitude overlaid with arrows indicating velocity direction and magnitude for 300 μm, 400 μm, and 1 mm cell islands. (g) Histogram of the velocity magnitude over 1 cell island over 15 hr. (h) Histogram of the direction of velocity over one cell island over 15 hr.

https://doi.org/10.1371/journal.pone.0344657.g005

To demonstrate that this protocol can be used in conjunction with traction force microscopy, we measured forces exerted by cell monolayers prepared using Method 1. First, we patterned a 1 mm diameter circular island (Fig 6a) and quantified the traction magnitude over space (Fig 6b). Tractions were spatially heterogeneous, consistent with previously reported patterns of force generation in epithelial monolayers [37,47,48]. Also consistent with prior observations [5,12,32,37,49], tractions applied by cells to the substrate pointed radially inward at the edge of the island, indicating that epithelial cells have a tendency to pull themselves toward free space (Fig 6c). We also used monolayer stress microscopy to compute the in-plane components of the stress tensor. Here, we plot the maximum shear stress by where and are the first and second principal stresses, respectively. Similar to traction magnitude, the maximum shear stress was spatially heterogeneous (Fig 6d) [45]. We next applied the same approach to an elongated cell island, illustrating how this protocol can be used to examine force generation in more complex geometries (Fig 6e). The traction magnitude was heterogeneous in space. Because circular symmetry does not apply to the elongated island, we decomposed the tractions into components parallel and perpendicular to the long axis of the island to assess whether traction organization was aligned with geometric confinement. Similar to the circular pattern, cells at the edges of the elongated islands pulled inward on the substrate, meaning they pulled themselves towards the free space (Fig 6g). Finally, we computed the maximum shear stress of the elongated island, which was visually smoother over space than that of the circular island (Fig 6h). Additionally, these methods have been used previously to relate cell motion, force generation, and alignment in epithelial monolayers [45,47,50] These data demonstrate use of our protocol for experiments measuring cell-substrate tractions and monolayer stresses and suggest that cellular confinement geometry can influence the spatial organization of force production and transmission in epithelial monolayers.

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Fig 6. Representative experiment showing effect of island shape on force production and transmission within the cell monolayer.

(a) Phase contrast image of 1 mm cell island. (b) Heat map of traction magnitude. (c) Heat map of the radial component of traction applied by the cells to the substrate, with outward being positive. (d) Heat map of maximum shear stress. (e) Phase contrast image of an elongated cell island. (f) Heat map of traction magnitude. (g) Heat map of traction components parallel and perpendicular to the long axis of the elongated island. Arrows indicate direction of positive traction. (h) Heat map of maximum shear stress.

https://doi.org/10.1371/journal.pone.0344657.g006

Discussion and conclusion

This work demonstrates two reliable and accessible protocols for confining cell monolayers to user-defined geometries using stenciling. We show that a range of patterns can be fabricated and that cell monolayers remain confined to these regions. This level of geometric control of cell monolayers provides a framework for studying how spatial constraints influence collective cell behavior. Quantitative analysis showed high fidelity between the designed patterns and the resulting confined cell monolayers. Values of the Dice coefficient were greater than 0.9 for circular patterns in both methods as well as square patterns using Method 1. The Dice coefficient was greater than ∼0.8 for all geometries, indicating strong agreement between the designed geometry and the confined monolayers across both Methods. These patterns were stable over time, with confined monolayers maintaining their geometry throughout the duration of the experiments (S2, S3 Fig).

Some bridging of cells beyond the confined region was observed at sharp corners, particularly in the star pattern. This behavior is a characteristic of epithelial tissues, which tend to extend beyond imposed boundaries [31,5153]. Additionally, images of collagen deposition revealed that small features, such as sharp corners, exhibited reduced collagen deposition. This tradeoff should be considered when designing experiments that rely on highly intricate confinement shapes. For smaller or sharper features, microcontact printing may be a better suited technique. Due to the lack of clean room and UV source limitations, the spatial resolution for both techniques is ∼ 300 μm, making it insufficient for single cell patterning. If spatial resolution below 300 μm is desired, microcontact printing is likely to be a more suitable approach. In Method 1, the patterning is compatible with a range of polyacrylamide stiffness. We have used the method on substrates having Young’s modulus ranging from 2 to 18 kPa (S3 Fig in S3 File). We note that we expect the method to work with even stiffer substrates though on very soft substrates (< 2 kPa), ECM transfer can become incomplete.

In practice, these protocols perform well overall, and perform best for smooth, continuous geometries. A key feature of this approach is its adaptability. These protocols are compatible with a range of cell types and substrates, and can be implemented without specialized microfabrication equipment or clean room facility access, making them broadly accessible. Moreover, the ability to impose user-defined 2D geometries creates an opportunity to systematically test the effects of confinement on processes such as cell alignment, topological defect formation, and jamming transitions. Notably, as both of these methods utilize compliant substrates, the patterned monolayers are fully compatible with traction force microscopy. This allows for direct quantification of the cell force production within the defined geometries, providing a controlled platform to investigate how geometry regulates force generation.

In summary, these protocols provide a versatile platform for spatially confining cell monolayers on both hydrogels and PDMS substrates. Method 1’s tunability and compatibility with force production measurements makes it a valuable approach for studying the physical and biological principles underlying multicellular organization and mechanics. These protocols are also highly accessible, as they rely on widely available equipment rather than specialized microfabrication tools. The combination of accessibility and compatibility with force measurements makes these protocols well suited for studying collective cell behavior.

Supporting information

S1 File. Step-by-step procedure for Method 1.

This method is for micropatterning on polyacrylamide substrates.

https://doi.org/10.1371/journal.pone.0344657.s001

(PDF)

S2 File. Step-by-step procedure for Method 2.

This method is for micropatterning on PDMS substrates.

https://doi.org/10.1371/journal.pone.0344657.s002

(PDF)

S3 File. Supplemental Figures.

Supplemental figures referenced in the text.

https://doi.org/10.1371/journal.pone.0344657.s003

(PDF)

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