When engineering mechanical cues to study cell mechanotransduction, it is important to take into account how the cells sense the mechanical properties. Material mechanical properties ought to be measured at timescales and frequencies relevant to the properties sensed by adhering cells (Cameron et al., 2014; Charrier et al., 2018). When cells interact with a substrate, they can apply forces parallel and perpendicular to the surface (Janmey et al., 2020). This implies that the method used for assessing cellular forces may affect the results in mechanotransduction studies. One more factor to consider is the depth into a material that cells can sense the mechanical properties. Modeling, and studies on thin gels, suggest that cells sense mechanical properties in the range of their radius (Sen et al., 2009; Buxboim et al., 2010; He et al., 2014). The range within which cells can sense mechanical properties may be material-dependent though, and it has been shown that strain stiffening fibrous networks enable long-range force sensing of up to hundreds of microns (Leiphart et al., 2019). It is therefore relevant to consider the sensing depth of surface and bulk mechanical characterization techniques, respectively. How cells sense their environment is also cell-type dependent and, while many excellent model studies have been performed in 2D, cell sensing is likely to be different in three-dimensional (3D) culture environments (Doyle and Yamada, 2016).

Many model substrates have been adopted to study cellular mechanotransduction. In 1980, silicone rubber was first used as a deformable elastic substrate for cell culture, which revealed that cells constantly exert forces on substrates (Harris et al., 1980). Building on this work, gels gained interest as model substrates due to their tunable viscoelastic properties and close resemblance, mechanically, to the extracellular matrix (ECM) (Tibbitt and Anseth, 2009; Chaudhuri, 2017). However, thin films and liquids have also been used as substrates (Yang et al., 2014; Kong et al., 2018). To precisely determine the mechanical cues that substrates display to cells is crucial for biological studies. It is also important to assess the changes in the mechanical properties of cells in response to various biophysical and biochemical cues. Therefore, this review describes and contrasts the most commonly used techniques to determine the mechanical properties of materials and cells (Figure 1 and Table 1).

The mechanical properties of substrates such as gels used in mechanotransduction studies are usually characterized globally by rheology, tensile, and compression testing.

Shear rheology can be used to monitor the gelation process, or to measure the elastic and viscous properties of gels (denoted by storage and loss modulus) by applying small amplitude oscillatory shear forces (Zuidema et al., 2014). Time-dependent aspects of viscoelasticity are quantified by relaxation time and relaxation modulus (Fitzgerald et al., 2015; Chaudhuri et al., 2016). Strain stiffening materials are characterized by monitoring the elastic modulus as a function of increasing stress. It is important to note the significance of the geometries used for probing the sample. For instance, a recent study showed that a crosshatched geometry revealed the strain stiffening property of agarose, while a parallel plate geometry obscured it due to the wall slippage effect (Bertula et al., 2019). The main limitation of rheology to characterize gels is that the spatial variation in moduli arising from sample heterogeneities cannot be probed.

Compression and tensile testing are also techniques commonly used to probe the global mechanical properties, especially for biomaterials (Xiao et al., 2013; Vedadghavami et al., 2017). The elastic, or Young’s modulus, of the sample is generally obtained from the slope of the stress-strain curve, but the viscoelastic properties can also be accessed through this kind of characterization (Mirahmadi et al., 2013; Bosnjak et al., 2020). Variations in the testing protocols can, however, influence the results (Patel et al., 2019) and difficulties can also arise in tensile testing from the breakage or slipping of the sample at the clamps (Oyen, 2014).

Several of the aforementioned mechanical parameters can be probed using different techniques, and it is important to understand how the parameters are measured. For example, tensile testing measures the elastic properties (Young’s modulus) by applying tensile forces, while in rheology shear forces are applied (storage modulus).

The local mechanical properties are relevant for measuring what properties cells sense at the surface of a material. The resolution of the techniques described below enable the mechanical properties of cells to be probed in real time due to their specificity and sensitivity.

Recent research has propagated the development of modern characterization techniques, all with unique advantages and limitations. Some of the most promising emerging techniques for mechanical characterization are summarized in this section.

Brillouin microscopy was originally demonstrated on cells over a decade ago (Scarcelli and Yun, 2008) and has since garnered attention within the biological and medical research fields for its novel approach to non-destructive viscoelastic measurements of biological samples. The method involves interacting the intrinsic acoustic waves of a material with probe laser pulses and interpreting how the light is scattered – which is heavily linked to the material’s viscoelastic properties (Gusev and Ruello, 2018). Recent works have demonstrated a submicrometric spatial resolution (Caponi et al., 2020). Brillouin microscopy is also largely non-destructive while still possessing resolution capabilities for cellular characterization (μm scale) (Prevedel et al., 2019). Since its pioneering application in 2005 (Koski and Yarger, 2005), Brillouin microscopy has been utilized in tissue-level sensing (Mathieu et al., 2011; Margueritat et al., 2019) and subcellular-level characterization (Steelman et al., 2015; Bevilacqua et al., 2019). However, interpretation of results requires specific knowledge of the refractive index and material density (Prevedel et al., 2019) which is difficult to experimentally attain (Liu et al., 2016), and the weakness of the measured signal causes extended scanning and data acquisition times (Ballmann et al., 2019). Scrutinous evaluation of Brillouin output is also required, especially in biological matter, due to the spatiotemporal inhomogeneity causing differences in the material’s intrinsic acoustic wave behavior (Wu et al., 2018; Ballmann et al., 2019).

Microfluidic devices constitute an efficient and relatively high-throughput method to characterize the mechanical properties of cells. For instance, micropipette aspiration on microfluidic chips using giant vesicles as cell models have been developed to access cell membrane mechanics (Elias et al., 2020). Other techniques use flow field analysis to study the deformations applied by fluids to cells to deduce their viscoelastic properties (Guillou et al., 2016). The influence of fluid flows on cells has also been combined with computational models to determine the elastic modulus of cells (Song et al., 2012) and such flows have also been demonstrated to impact cell behavior and maturation (Song et al., 2013; Shemesh et al., 2015).

Optical tweezers (OTs) is a single-molecule technique initially designed in 1986 (Ashkin et al., 1986). OTs involve the precise manipulation of beads (0.1–100 pN) with molecules tethered to them by trapping them with strongly focused light. In the context of mechanobiology, OTs have been used to assess ligand-receptor bond properties using ligand-functionalized trapped particles (Jiang et al., 2003), to explore forces on the structures at the surface of the cell involved in mechanotransduction (Choquet et al., 1997), to assess forces on structures within the cell (Welte et al., 1998), and to investigate the mechanical properties of the cell (Tan et al., 2012). OTs are, however, accompanied by drawbacks such as photo-entrapment of impurity particles, local heating and photodamage (Peterman et al., 2003). Some of these challenges are solved by magnetic tweezers (MTs). This single-molecule technique is relevant for biological applications such as single-molecule force measurements and cellular micromanipulation (Basoli et al., 2018). It operates by utilizing superparamagnetic beads (0.1–100 μm) as a force transducer for a tethered single large molecule by applying a magnetic field (Xin et al., 2017). Advantages of MT include its cost-effectiveness and ease of implementation, superior to other single-molecule techniques (Kemmerich et al., 2016). Furthermore, MTs can generate forces inside closed opaque bodies, such as living cells, which is not the case with other non-invasive methods (Timonen and Grzybowski, 2017). MTs have been used extensively to generate tension on cell adhesion molecules, and then observing the cellular response to reveal mechanotransduction pathways(Guilluy et al., 2014; Marjoram et al., 2016). The main challenge in MT development has been their subpar resolution that is limited by relying on camera-based measurements of magnetic beads (De Vlaminck and Dekker, 2012). However, high spatiotemporal resolution magnetic tweezers (Å scale) are being implemented with help from more sophisticated cameras and computer hardware (Huhle et al., 2015; Ostrofet et al., 2020). There are also difficulties working with particles susceptible to magnetic fields. Furthermore, the requirement that bulky magnets must be situated close to the sample complicates the combination of MTs with other applications (Sarkar and Rybenkov, 2016).

Concerning substrates, a relatively new and inexpensive technique to probe local mechanical properties is cavitation rheology (Zimberlin et al., 2007). Cavitation rheology quantifies the elastic properties by growing a bubble in a gel or fluid and monitoring the pressure dynamics (Hashemnejad and Kundu, 2017). The resolution of cavitation rheology can go as low as 1 μm and requires only small sample volumes (Barney et al., 2020). One drawback of this method is that it is destructive to the sample. Questions also remain around relating gel fracture to cavitation and the influence of local network structures on cavitation bubble growth (Barney et al., 2020).

One of the fundamental challenging aspects of characterizing substrates is the relevance of a particular technique in capturing the properties of substrates experienced by the cell. Each technique probes the mechanical properties in a different way, and it is necessary to compare the parameters obtained using different techniques. Rheology or compression tests, for instance, can provide the elastic and loss modulus of a material, but only as a mean value for the whole material, whereas probe-based techniques such as AFM assess the local mechanical properties at the microscopic scale, which can differ from the macroscopic one. A recent study showed that the bulk elastic modulus obtained for stiffer gels using rheology and AFM correlate well but showed marked differences for softer gels (Megone et al., 2018). There has also been a recent trend in using simple and inexpensive techniques for probing mechanical properties. For instance, using fluorescent bead density as a readout for stiffness gradients in gels instead of using expensive techniques like AFM (Barber-Pérez et al., 2020). Recent technology also allows assessment of mechanical properties of materials with extremely precise force (resolution down to 10 nN claimed by the manufacturer) through micro-scale compression testing, particularly for soft biomaterials (Kerscher et al., 2017).

Emerging techniques are now focusing on probing these properties even more precisely and in-depth. Cell-substrate interactions are also highly relevant to assess mechanotransduction and techniques such as traction force microscopy and magnetic tweezers can be applied to survey such interactions. Forces in the order of pico-Newtons, applied by integrins on ligands, have also been assessed by DNA mechanotechnology (Brockman et al., 2018; Glazier et al., 2019; Ma et al., 2019). However, significant challenges regarding the integrity of the DNA probes in cell culture conditions and the type of receptor-ligand interactions that can be probed remain (Ma and Salaita, 2019; Yasunaga et al., 2019).

Many of the existing tools for measuring the mechanical properties of cells are limited in terms of throughput. To mitigate this issue, high throughput based methods have been explored to separate large populations of cells based on mechanical properties using microfluidics and shear stress (Otto et al., 2015). A combination of smart design of microfluidic geometries and powerful computational approaches such as microparticle image velocimetry and machine learning promise to further progress the field of mechanobiology (Song et al., 2010; Guillou et al., 2016).

The influence of substrate mechanical properties on processes such as nascent protein deposition has been explored in recent studies by using metabolic labeling techniques (Loebel et al., 2019, 2020). It would be interesting to combine such labeling with 3D traction force microscopy in order to directly visualize the effects of cell traction forces on nascent protein deposition.

Going forward, standard mechanical characterization techniques combined with newer, more accurate and more local assessments of the mechanical properties, will enable the development of more complex engineered matrices. Such materials with spatiotemporally-controlled mechanical properties will further the understanding of how cells interact with their environment in vitro, and indirectly in vivo. This is important to fully use the potential of stem cells in tissue engineering and stem cell therapy.

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.