Traction force microscopy (TFM) is the process of approximating cellular tractions using interpolated displacement fields of fiducial markers generated by an adherent and contractile cell. Using TFM, the influence of mechanical cues in the extracellular environment on important cellular processes such as proliferation, differentiation, and migration can be investigated1,2,3,4,5,6,7,8,9,10,11,12. Unfortunately, many existing approaches can be difficult to implement or require familiarity with highly specialized analytical and computational tools making TFM difficult for inexperienced researchers to use. We describe a methodology to generate a TFM platform that eliminates some of the difficulty in analysis while also providing high-throughput data acquisition.
Of the existing TFM approaches, the most commonly used for quantifying material strain involves incorporation of small fluorescent markers (typically nano- or micrometer-sized fluorescent beads) into a deformable hydrogel, such as polyacrylamide (PAA) or poly(ethylene glycol) diacrylate (PEGDA)13,14,15. These bead-based approaches provide the ability to densely cluster fiducial markers around a cell of interest to maximize displacement sampling. Unfortunately, the distribution of the beads throughout the hydrogel cannot be directly controlled so the spatial organization is random. This random placement leads to problems such as beads which are too close to each other to accurately resolve, or so spread that patches of the substrate yield low quality data. The inability to predict where fiducial markers lie in the absence of cells also creates a constraint that, for every collected set of cell traction data, an additional reference image of the underlying markers in a relaxed state must also be captured. The reference image is required so that displacement in the stressed image can be approximated as the difference between the stressed and unstressed images. To achieve a relaxed state, the cells being measured are either chemically relaxed or completely removed. This process often prevents acquisition of further experimental measurements, inhibits long-term cell studies, and limits throughput. A reference image also requires image registration techniques to accommodate for drift which may have occurred during experimentation, often leading to cumbersome manual matching of stress state images to reference images.
Other TFM methods deemed reference-free, implement some form of control over the distribution of fiducial markers, either by high resolution lithography, microcontact printing, or micromolding16,17,18,19,20. Reference-free TFM is achieved through the assumption that the relaxed state for each fiducial marker can be predicted based on how marker positions were prescribed during the fabrication process. These methods allow for complete capture of a cell’s tension state within a single image capture in which fiducial marker displacements are measured in comparison to an implied reference than can be inferred from the fiducial marker geometry. While consistency in marker placement is typically achieved using these platforms, they generally suffer from their own shortcomings relative to the widely used bead-based approaches including: 1) decreased traction resolution; 2) decreased accuracy of out-of-plane displacements (in some cases a complete inability to measure); and 3) decreased customizability of platform substrates and materials (e.g., ligand presentation, mechanical properties).
To address these shortcomings, we designed a new reference-free TFM platform. The platform utilizes multiphoton activated chemistry to crosslink a small volume of a fluorophore into specific 3D locations within the hydrogel that serve as fiducial markers to measure material strain. In this way, we have designed a platform that operates similarly to bead-based approaches but with the significant benefit that fiducial markers are organized into gridded arrays allowing for reference-free material strain tracking. This reference-free property affords many advantages. First and foremost, it allows for non-intrusive monitoring of cellular traction states (i.e., circumvents the need to relax or remove cells to acquire reference positions of displaced fiducial markers). This was our primary goal in designing this system, as we intended to incorporate other downstream analytical methods in tandem with TFM, which can be difficult with destructive end-point TFM approaches. Second, using an implied reference based on gridded arrays allows for near-complete automation of displacement analysis. The regularity of the arrays creates a predictable workflow where the occurrence of exceptional cases (i.e., sample cell data containing unanticipated artifacts such as suboptimal marker spacing or registration mismatches) can be maintained at a minimum. Third, forgoing the need to acquire a reference image provides the freedom to monitor many cells on a single sample over extended periods of time. This contrasts with traditional bead-based approaches, where, depending on the fidelity of the microscope’s automated stage movements, errors in positioning can accumulate and increase the difficulty of properly registering reference images to cell tension images. Overall, this platform facilitates higher throughput in collecting cellular tension data.
With this protocol, we hope to familiarize the readers with the two-photon, laser scanning lithography technique that we implemented to generate this reference-free TFM platform to measure in-plane and out-of-plane traction components generated by cells seeded on the surface. Not covered in this protocol is the synthesis of some of the monomeric components. In general, these reactions include nearly identical “one-pot” synthesis reaction schemes described previously21, and alternatives to these products can also be purchased. We also aim to familiarize readers with the software-based tools we generated to promote the use of commercially-available laser-scanning microscopes as 3D printing tools and to facilitate analysis of fiducial marker displacements.