The protocol presented here enables automated fabrication of micropatterns that standardizes cell shape to study cytoskeletal structures within mammalian cells. This user-friendly technique can be set up with commercially available imaging systems and does not require specialized equipment inaccessible to standard cell biology laboratories.
Micropatterning is an established technique in the cell biology community used to study connections between the morphology and function of cellular compartments while circumventing complications arising from natural cell-to-cell variations. To standardize cell shape, cells are either confined in 3D molds or controlled for adhesive geometry through adhesive islands. However, traditional micropatterning techniques based on photolithography and deep UV etching heavily depend on clean rooms or specialized equipment. Here we present an infrared laser assisted micropatterning technique (microphotopatterning) modified from Doyle et al. that can be conveniently set up with commercially available imaging systems. In this protocol, we use a Nikon A1R MP+ imaging system to generate micropatterns with micron precision through an infrared (IR) laser that ablates preset regions on poly-vinyl alcohol coated coverslips. We employ a custom script to enable automated pattern fabrication with high efficiency and accuracy in systems not equipped with a hardware autofocus. We show that this IR laser assisted micropatterning (microphotopatterning) protocol results in defined patterns to which cells attach exclusively and take on the desired shape. Furthermore, data from a large number of cells can be averaged due to the standardization of cell shape. Patterns generated with this protocol, combined with high resolution imaging and quantitative analysis, can be used for relatively high throughput screens to identify molecular players mediating the link between form and function.
Cell shape is a key determinant of fundamental biological processes such as tissue morphogenesis1, cell migration2, cell proliferation3, and gene expression4. Changes in cell shape are driven by an intricate balance between dynamic rearrangements of the cytoskeleton that deforms the plasma membrane and extrinsic factors such as external forces exerted on the cell and the geometry of cell-cell and cell-matrix adhesions5. Migrating mesenchymal cells, for instance, polymerize a dense actin network at the leading edge that pushes the plasma membrane forward and creates a wide lamellipodia6, while actomyosin contractility retracts the cell's narrow trailing edge to detach the cell from its current position7,8. Disrupting signaling events that give rise to such specialized cytoskeletal structures perturbs shape and polarity and slows cell migration9. In addition, epithelial sheet bending during gastrulation requires actomyosin-based apical constriction that causes cells and their neighbors to become wedge-shaped10. Although these studies highlight the importance of cell shape, the inherent heterogeneity in cell shape has encumbered efforts to identify mechanisms that connect morphology to function.
To this end, numerous approaches to manipulate cell shape have been developed over the past three decades. These approaches achieve their goal by either constraining the cell with a three-dimensional mold or controlling cellular adhesion geometry through patterned deposition of extracellular matrix (ECM) proteins onto an antifouling surface, a technique termed micropatterning11. Here we will review a number of techniques that have gained popularity throughout the years.
Originally pioneered as an approach for microelectronic applications, soft lithography-based microcontact printing has unequivocally become a cult favorite12. A master wafer is first fabricated by selectively exposing areas of a photoresist-coated silicon substrate to photoirradiation, leaving behind a patterned surface13. An elastomer, such as PDMS, is then poured onto the master wafer to generate a soft "stamp" that transfers ECM proteins to a desired substrate11,14. Once fabricated, a master wafer can be used to cast many PDMS stamps that give rise to highly reproducible micropatterns12. However, the patterns cannot be readily adjusted due to the lengthy photolithography process. This process also requires highly specialized equipment and cleanrooms that are not typically available in Biology departments.
More recently, direct printing using deep UV has been reported to circumvent limitations posed by traditional lithography-based approaches. Deep UV light is directed through a photomask to selective areas of a glass coverslip coated with poly-L-lysine-grafted-polyethylene glycol. Chemical groups exposed to deep UV are photoconverted without the use of photosensitive linkers to enable binding of ECM proteins15. The lack of photosensitive linkers enables patterned coverslips to remain stable at room temperature for over seven months15. This method avoids the use of cleanrooms and photolithography equipment and requires less specialized training. However, the requirement for photomasks still poses a substantial hurdle for experiments that require readily available changes in patterns.
In addition to methods that manipulate cell geometry through controlled deposition of ECM proteins on a 2D surface, other seek to control cell shape by confining cells in 3D microstructures. Many studies have adapted the soft lithography-based approach described above to generate 3D, rather than 2D, PDMS chambers to investigate shape-dependent biological processes in embryos, bacteria, yeast and plants16,17,18,19. Two-photon polymerization (2PP) has also taken the lead as a microfabrication technique that can create complex 3D hydrogel scaffolds with nanometer resolution20. 2PP relies on the principles of two-photon adsorption, where two photons delivered in femtosecond pulses are absorbed simultaneously by a molecule – photoinitiator in this case – that enables local polymerization of photopolymers21. This technique has been heavily employed to print 3D scaffolds that mimic the native ECM structures of human tissue and has been shown to induce low photochemical damage to cells22.
The debut of microphotopatterning 10 years ago gave researchers the opportunity to fabricate micropatterns while avoiding inaccessible and specialized equipment. Microphotopatterning creates patterns on the micron scale by thermally removing selective regions of poly-vinyl alcohol (PVA) coated on activated glass surfaces using an infrared laser23,24. ECM proteins that attach only the underlying glass surface and not PVA then serve as biochemical cues to enable controlled spreading dynamics and cell shape. This method also offers superior flexibility since patterns can be readily changed in real time. Here, we provide a step-by-step protocol of microphotopatterning by using a commercial multi-photon imaging system. The described protocol is designed for rapid and automated fabrication of large patterns. We demonstrated that these patterns efficiently control cell shape by constraining the geometry of cell-ECM adhesions. Finally, we demonstrate that the described patterning technique modulates the organization and dynamics of the actin cytoskeleton.
1. Coverslip preprocessing
2. PVA coating
3. Configuring the Multiphoton Microscope
NOTE: The described protocol is tuned up to create cell adhesive micropatterns of desired shape and size on upright or inverted multi-photon imaging systems, especially the ones that are not equipped with a hardware autofocus. Thus, for every field of view (FOV), the patterning script ablates a small area to create a fiduciary marker on the coverslip, uses a software autofocus to focus the microscope on the coverslip surface, and ablates the desired pattern. Running this script in a loop for adjacent FOVs robustly creates a large array of micropatterns (5 x 5 mm or larger) that constrain cell shape and modulate the activity of intracellular biological processes. The described protocol was developed for Nikon A1R MP+ imaging system controlled by NIS-Elements software. If an imaging system from another vendor is used for patterning, the optical configurations and patterning script should be adjusted according to the manufacturer's instructions.
4. Generating the ROI mask and Setting up the macro
5. Generating micropatterns using photo ablation
6. Fibronectin adsorption
7. Cell attachment
NOTE: The following protocol is optimized for primary human gingival fibroblasts.
8. Data acquisition
9. Image analysis
NOTE: The following protocol allows users to obtain the average fluorescence signal of the protein of interest over a large number of cells from Z-stacks of microscope images.
The quality of the experimental data obtained through micropatterning is largely dependent on the quality of the patterns. To determine the quality of patterns generated with the method above, we first used reflectance microscopy to assess the shape and size of the photo ablated areas of the coverslip. We found that each individual pattern looked very similar to the ablation mask and displayed clear boarders and a surface that reflected light uniformly (Figure 2B). A variety of shapes and sizes can be printed depending on the desired cytoskeleton architecture, but we used the crossbow shape that best suits our purposes. Atomic force microscopy (AFM) revealed that such patterns were approximately 140 nm in height and had a smooth surface with minimal topological variation throughout (Figure 2F). Suboptimal patterning settings, such as low laser power and incorrect focal plane, resulted in incomplete removal of the PVA surface that manifests as darker, partial patterns with uneven topology (Figure 2C). Setting laser power too high resulted in PVA "bubbling" and when extreme, coverslip surface damage that is also undesirable (Figure 2D).
In preliminary experiments we attempted to increase the patterning area by abating multiple FOVs on a single coverslip. We found that this approach, although works in principle, is unreliable and tedious due to Z-drift of the microscope stand and slight tilt of the coverslip. To achieve high-quality patterns over a large number of FOVs in an automated fashion, we implemented a customized macro that improved the precision of microscope focusing during the patterning process. The multiphoton microscope employs a pulse laser that efficiently degrades PVA with high power in a narrow focal plane, making the patterning process sensitive to any unevenness or tilt in the sample. As a result, it is important to identify the precise focal plane in each FOV. This is even more problematic for systems lacking a perfect focus module, as deviations as little as one to two microns can render the patterning process fruitless. To address this problem, the customized macro script first patterns a small square in the center of each new FOV that need only be roughly in focus by scanning through a relatively thick Z-stack (≈20 μm). The microscope then quickly scans through the stack of images and uses NIS Elements autofocus function to identify the optimal focal plane. The pattern mask is then loaded and set as stimulation ROI for IR stimulation to occur. The stage subsequently moves to the next FOV and repeats this process. In addition, the square-wave shaped path of the microscope stage movement ensured minimal error accumulation between sequential FOVs. By using this protocol, we routinely fabricate patterns composed of 49 microscope FOVs covering 3.5 x 3.5 mm area of the coverslip in less than 3 h.
To test if patterned areas, not unperturbed PVA, could adsorb ECM proteins, we coated patterned coverslips with 10 μg/mL FN and stained them with anti-FN antibody. Using wide field fluorescent microscopy, we found that FN uniformly adsorbed to the patterned areas where PVA had been removed by laser ablation (Figure 2E).
To determine if cytoskeleton architecture and tension distribution could be modified as expected on the patterns, we seeded cells on patterned coverslips and visualized the distribution of myosin light chain, a marker of contractility, through fluorescence microscopy. After initial seeding, cells gradually gravitated towards the coverslip. Those that landed on patterned areas attached and spread into the shape of the pattern over time. Those that landed on PVA only loosely attached and were removed after several washes and media changes. We found that cells spread on patterns displayed phenotypical fibroblast structures including an actin-dense rim of lamellipodia, thick ventral stress fibers along the two sides, and dorsal stress fibers emanating from the lamellipodia connected by transverse arcs (Figure 3A). Myosin light chain (MLC) sat behind the dense lamellipodia rim and displayed a striated pattern along actin bundles. As indicated by averaged images of many cells, this phenotype was consistent across a large number of patterns (Figure 3B).
Figure 1. Schematic of IR laser assisted micropatterning (microphotopatterning). (A) Glass coverslips are chemically conjugated with APTMS, GA and PVA, in the respective order. The PVA surface is non-adhesive to cells and proteins. (B) PVA is removed in preset patterns by an IR laser. (C) Patterned coverslips are coated with an ECM protein that will only adsorb to patterned areas. (D) Cells are plated on coverslips, fixed, and immunostained for proteins of interest. Cells that land on patterned islands spread into the shape of the pattern that gives rise to characteristic cytoskeletal structures, while those that land on PVA remain spherical. Please click here to view a larger version of this figure.
Figure 2. Micropattern validation and characterization. (A) IR laser assisted micropatterning (microphotopatterning) setup on a microscope stage. The IR laser thermally ablates PVA in multiple FOVs. (B) A reflectance microscopy image of micropatterns that have clear boarders and are identical to the ROI masks. (C) A reflectance microscopy image of incomplete removal of PVA resulting from suboptimal laser power. (D) A reflectance microscopy image of PVA bubbling resulting from excess laser power. (E) Immunofluorescence images of FN coated patterned coverslips stained with anti-FN primary antibodies and fluorophore-conjugated secondary antibodies. (F) An AFM topology scan line and a representative AFM image of a crossbow pattern. To measure the topology of the micropattern, contact mode imaging was performed using a Bruker AFM probe (MLCT-B) mounted on a NanoWizard 4 atomic force microscope. Please click here to view a larger version of this figure.
Figure 3. Representative images of cells plated on micropatterns. (A) Representative images of a primary human gingival fibroblast plated on crossbow patterns immunostained for actin and MLC. Images were acquired with a confocal microscope equipped with a 100x objective. (B) Averaged immunofluorescence images of actin and MLC in cells plated on crossbow patterns generated by a custom Python script. Please click here to view a larger version of this figure.
The results above demonstrate that the described IR laser assisted micropatterning (microphotopatterning) protocol provides reproducible adherent patterns of various shapes that enables the manipulation of cell shape and cytoskeletal architecture. Although numerous micropatterning methods have been developed both prior to and after the debut of microphotopatterning, this method possesses several advantages. First, it does not require specialized equipment and cleanrooms that are usually only found within Engineering departments. In fact, as multiphoton microscopes are becoming a more common sight in Biology departments, microphotopatterning expands the applications of the multiphoton microscope and adds to the potential pool of users. Patterns can also be changed on demand and printed immediately, instead of having to fabricate a new master wafer that entails a lengthy lithography process.
Compared to the pre-existing microphotopatterning protocol, one improvement in our protocol is the elimination of several time-consuming curing steps during coverslip preparation. We show that the quality of PVA-coverslip attachment remains unperturbed as the patterns were still intact and could bind cells even two weeks after fabrication. More importantly, we improved automation of the patterning process by eliminating the need to preset the position of each FOV24. Instead, we implement an understandable macro that allows patterning of a large area while precisely identifying the optimal focal plane of each FOV.
Although the macros in the protocol enable automation of patterning on our system, we understand that every commercial laser scanning microscope comes with their own proprietary software that is rarely compatible with others, making it difficult to implement our exact protocol on other systems. However, the overall workflow can be well adapted to other commercial systems to facilitate automated micropatterning, namely the process of focusing on each individual FOV, loading the mask, ablating PVA, and moving the microscope stage to a new FOV.
Several steps in the patterning protocol should be undertaken with great care to ensure efficient patterning. The most critical step is to optimize stimulation conditions before generating patterns. In multi-photon microscopy, two or more photons must arrive almost simultaneously at a fluorescent molecule and combine their energy to excite fluorescence. This low probability event creates an extremely thin optical section that increases signal-to-noise ratio28. Although beneficial for imaging, this feature makes the removal of the thin PVA coating extremely sensitive to the sample's Z-position. Several measures can be implemented to counter this. First, laser power should be fine-tuned to ensure thorough removal of PVA without "boiling" the polymer or damaging the glass coverslip. If PVA removal is consistently incomplete, we recommend checking laser alignment as this usually increases laser power. Second, the microscope stage should be leveled to avoid sample tilt, which could result in incomplete patterns. IR stimulations in multiple Z-positions should also be set up to ensure that the PVA layer is targeted. Alternatively, if the microscope is equipped with a perfect focus module, preliminary tests can be conducted to determine the optimal offset in Z-position for PVA targeting. Another critical step is to set up a microscope macro that allows pattern stimulation in an automated fashion. The macro should find the focal plane of each new FOV to avoid complications from sample tilt or surface unevenness. It should also allow the stage to move in an S-shape from row to row, analogous to the path taken in bi-directional scanning, to minimize deviations in Z between consecutive FOVs.
One limitation to the protocol described is the time required to produce a large number of patterned coverslips, an unparalleled advantage offered by lithography-based microcontact printing29,30. As a result, this protocol is best suited for experiments in which a limited number of conditions are required, or those that require readily available adjustments in pattern shape and size. Furthermore, for systems lacking a hardware autofocus module, we integrate a series of stimulation events in different Z-planes to ensure automated and effective PVA removal. Since IR stimulation is the most time-consuming step, the addition of each stimulation event (~30 sec) significantly lengthens the patterning process. If time is of concern, we suggest fine tuning autofocus by decreasing step size. This facilitates the identification of the best focal plane which will decrease the number of IR stimulation events required. In our experiments, decreasing the number of stimulation events from five to two reduces the time by half (1.5 h).
In conclusion, the IR laser assisted micropatterning (microphotopatterning) protocol we describe can be used in any lab that has access to an IR laser-equipped microscope. In addition to studying cytoskeletal architecture and signaling pathways that connect form to function, this technique can also be applied to drug screening and other applications that are sensitive to cell-to-cell variability.
The authors have nothing to disclose.
This work was supported by Connaught Fund New Investigator Award to S.P., Canada Foundation for Innovation, NSERC Discovery Grant Program (grants RGPIN-2015-05114 and RGPIN-2020-05881), University of Manchester and University of Toronto Joint Research Fund, and University of Toronto XSeed Program. C.T. was supported by NSERC USRA fellowship.
(3-Aminopropyl)trimethoxysilane | Aldrich | 281778 | |
10 cm Cell Culture Dish | VWR | 10062-880 | Polysterene, TC treated, vented |
25X Apo LWD Water Dipping Objective | Nikon | MRD77225 | |
3.5 cm Cell Culture Dish | VWR | 10861-586 | Polysterene, TC treated, vented |
4',6-Diamidino-2-Phenylindole (DAPI) | Thermo | 62248 | 1mg/mL dihydrochloride solution |
Bovine Serine Albumin | BioShop | ALB005 | |
Dulbecco's Phosphate-Buffered Saline | Wisent | 311-425-CL | |
Ethanolamine | Sigma-Aldrich | E9508 | |
Fibronectin | Sigma-Aldrich | FC010 | 1mg/mL in pH 7.5 buffer |
Fibronectin Antibody | BD | 610077 | Mouse |
Fiji | ImageJ | Version 1.53c | |
Fluorescent Phalloidin | Invitrogen | A12380 | 568nm |
Glass Coverslip | VWR | 16004-302 | 22 × 22 mm |
Glutaraldehyde | Electron Microscopy Sciences | 16220 | 25% aqueous solution |
Hydrochloric Acid | Caledon | 6025-1-29 | 37% aqueous solution |
IR Laser | Coherent | Chameleon Vision | |
Minimal Essential Medium α | Gibco | 12561-056 | |
Mounting Medium | Sigma | F4680 | |
Mouse Secondary Antibody | Cell Signaling Technology | 4408S | Goat, 488nm |
Multi-Photon Microscope | Nikon | A1R MP+ | |
Myosin Light Chain Antibody | Cell Signaling Technology | 3672S | Rabbit |
NIS Elements | Nikon | Version 5.21.03 | |
Nitric Acid | Caledon | 7525-1-29 | 70% aqueous solution |
Photoshop | Adobe | Version 21.2.1 | |
Pluronic F-127 | Sigma | P2443 | Powder |
Poly(vinyl alchohol) | Aldrich | 341584 | MW 89000-98000, 98% hydrolyzed |
Rabbit Secondary Antibody | Cell Signaling Technology | 4412S | Goat, 488nm |
Shaker | VWR | 10127-876 | Alsoknown as analog rocker |
Sodium Borohydride | Aldrich | 452882 | Powder |
Sodium Hydroxide | Sigma-Aldrich | S8045 | |
Sodium Phosphate Dibasic | Sigma | S5136 | Powder |
Sodium Phosphate Monobasic | Sigma | S5011 | Powder |
Spyder | Anaconda | 4.1.4 | |
Trypsin | Wisent | 325-042-CL | 0.05% aqueous solution with 0.53mM EDTA |