All living cells constantly experience and respond to mechanical stresses. The molecular networks that activate in cells in response to mechanical stimuli are yet not well-understood. Our limited knowledge stems partially from the lack of available tools that are capable of exerting controlled mechanical stress to individual cells and at the same time observing their responses at subcellular to molecular resolution. Several tools such as rheology setups, micropipetes, and magnetic tweezers have been used in the past. While allowing to quantify short-time viscoelastic responses, these setups are not suitable for long-term observations of cells and most of them have low throughput. In this Perspective, we discuss lab-on-a-chip platforms that have the potential to overcome these limitations. Our focus is on devices that apply shear, compressive, tensile, and confinement derived stresses to single cells and organoid cultures. We compare different design strategies for these devices and highlight their advantages, drawbacks, and future potential. While the majority of these devices are used for fundamental research, some of them have potential applications in medical diagnostics and these applications are also discussed.

All living organisms interact with their environment. How these interactions alter the growth and the behavior of the organism is a key question in biology. Frequently, the interactions between the organism and its surrounding environment can be analyzed in terms of continuum mechanics by coarse-graining the underlying molecular interactions. However, the mechanical response of a biological system to an external force is by far more complex than the one encountered in non-living systems. Cells as continuum mechanical objects show responses to mechanical stress that are highly non-linear and history-dependent. Moreover, beyond mechanical responses cells surmount different biochemical response mechanisms, referred to as mechanotransduction, that unfold over different time scales. Understanding the latter is an area of active research in the fields of cancer biology, immunology, developmental biology, and microbiology, among others. Studies involving mechanical properties and responses of biological systems are increasingly considered a distinct branch of biology by itself, referred to as mechanobiology.1 In addition to providing a fundamental understanding of cellular behavior, the goal for many mechanobiological studies is to understand how diseases alter the mechanical properties of cells and tissues, and how an altered mechanical environment can trigger pathological processes. This Perspective discusses some of the emerging tools used in mechanobiology with a particular emphasis on new trends. Taking the broad scope of the field, we will limit our coverage to devices and techniques that are used to study individual cells and organoid cultures. The latter mimics the responses of individual organs or tissues and consists typically of only a few types of cultivated cells in much smaller numbers than present in an actual organism. Before settling on device aspects, we will first outline key concepts that have been addressed in mechanobiology research. We will then discuss the state-of-the-art tools in mechanobiology. Our main focus will be on lab-on-a-chip approaches and we will highlight the benefits and limitations of such devices. We would like to emphasize that this article is not intended to be a review but as a Perspective that represents the authors’ own experience and interpretation of a diverse and extended body of literature. As a consequence, we focus on a limited number of techniques and applications without covering all developments in the field.

In broadest terms, the cellular responses to mechanical forces can be grouped as passive or active (Fig. 1). The passive responses arise from short-time scale mechanical interactions occurring at a time scale less than about a second and are not accompanied by the expenditure of chemical or electrochemical energy in the form of ATP, GTP, or membrane potential. During these interactions, cells behave largely as a viscoelastic material. This regime is the most commonly studied in biophysics experiments.2 However, cellular level responses unfold typically on longer time scales.

FIG. 1.

Dominant cellular responses to applied step-like mechanical compression of a cell at different time scales. The associated time scales represent approximate rankings and rough order of magnitude estimates. Different responses have significant temporal overlaps.

FIG. 1.

Dominant cellular responses to applied step-like mechanical compression of a cell at different time scales. The associated time scales represent approximate rankings and rough order of magnitude estimates. Different responses have significant temporal overlaps.

Close modal

The elastic part of the viscoelastic response involves typically the cell envelope, underlying cytoskeletal network, and internal organelles. For the most part, these layered shell-like structures have small bending rigidity but high areal stretch modulus. The compressibility of the liquid interior of a cell is low and corresponds approximately to the compressibility of water. As a result, cells deform after the application of step-like compression to them with no change in their volume and small changes in their surface area at short time scales (Fig. 1). If the cell survives such deformation without rupture of its outer membrane layer(s), then the flow of water and solutes across the cell envelope becomes the dominant response. The flow lowers the stresses in the outer membrane layer(s). The flow occurs predominantly via different membrane channels. Some of these channels activate as a response to stress in the lipid bilayer membrane(s) surrounding the cells. This activation is highly non-linear. For small stresses, channels are closed but they open above the threshold via a conformational change in the channel proteins. In bacteria, these so-called mechanosensitive channels have a size cutoff but otherwise, they are not selective to types of molecules that can pass through.3 The largest mechanosensitive channels in bacteria (MscL) have pore openings of about 3 nm allowing passage of small proteins, ∼9 kDa in size.4 In cells of most known higher organisms (eukaryotes), mechanosensitive channels typically are selective for the type of ions/molecules that can pass. Commonly, these channels allow passage of specific ions such as K+, Na+, or Ca2+ and are referred to as stretch-gated ion channels or mechanosensitive ion channels.5 The opening of ion channels in response to increased tension in the membrane leads to changes in the membrane potential. A change in membrane potential expends energy accumulated by metabolic processes of the cell, which categorizes this response as an active response (Fig. 1). Stretch-activated ion channels are responsible for the initial depolarization or hyperpolarization from a mechanical stimulus and are involved in the sensing of touch and hearing. Opening of these channels as a response to a mechanical stimulus can trigger propagation of action potential in excitable cells.

Responses that occur on a time scale longer than about 1 s (rough order of magnitude estimate) are all driven by active, energy-consuming processes. The already mentioned passive processes are also present at these time scales but one can consider them to result from the active responses to initial step-like perturbation. Among the long-time active responses, two different time regimes can be furthermore distinguished (Fig. 1). On the time scale of seconds to minutes, the response is driven by protein–protein interactions. In eukaryotic cells, this leads to reorganization of the actomyosin cortex and tubulin networks via processes that consume energy in the form of ATP and GTP, respectively.6 Part of cytoskeletal re-arrangements is driven by the influx of extracellular Ca+2 via the opening of stretch-gated ion channels.7 These cytoskeletal re-arrangements lead to cell morphogenesis8 and in some cell types drive cellular motility.9 While the dynamical behavior of actin polymers and myosin motors as single entities is relatively well understood, their collective behavior in networks is much less clear. Understanding this behavior constitutes an exciting new direction in soft matter physics known as active gel studies.10 

From a minute to hour time scale, the cells respond to mechanical stimuli by re-arranging their transcriptional networks. Mechanical forces acting via transcriptional networks are thought to play a key role in the differentiation of stem cells,11,12 controlled cell death,13 and activating tumor growth,14 among others.15 Similar to eukaryotic cells, bacteria are sensing stresses in the cell envelope and they activate specific transcription factors in response to these stresses.16 In all domains of life, these system-level responses are yet poorly understood. The lack of understanding is related to the absence of suitable systems that are able to actuate these responses in a controlled manner.

The shape of most bacteria, archaea, fungi, and plant cells is determined by their cell wall. The energy-driven response to external mechanical forces also involves remodeling of the meshwork making up the cell wall in these organisms. These responses unfold on a time scale at which the cells double their mass and cell wall area. The remodeling of the cell wall appears to occur as a direct consequence of stresses in the cell wall. It has been postulated that the stress acts on enzymes that synthesize the cell wall; in particular to lytic enzymes that cut covalent bonds in this macromolecular structure before new polymer strands can be inserted.17 These decades-old predictions yet wait to be verified in experiments.

A diverse set of tools has been developed over the years to probe the mechanical properties of cells and new techniques are emerging. The main focus of this Perspective lies on actuators and sensors that can be implemented in lab-on-a-chip devices. To put these devices into Perspective, we will first discuss some of the most promising techniques to measure cellular forces and viscoelastic properties in general (Table I). We refer to these techniques as “conventional methods.” Nevertheless, it should be stated that these techniques are also state-of-an-art and several of them have emerged quite recently. Our discussion of this very broad material is inevitably brief. In-depth reviews can be found in the references added to Table I.

TABLE I.

Comparison of “conventional” methods for mechanobiology. Viscoelastic property signifies the quantity typically extracted from experiments although other rheological functions can also be calculated. Force range for all techniques except FRET probes shows the force that the probe is capable of exerting but for FRET is the measurement range. Dynamic time scale indicates the typical time scale of the relaxation process that is probed.

TechniqueMain viscoelastic propertyForce rangeDynamic time scaleLinear dimension of the probed regionMeas. through-put (cell/h)Reference
AFM Young modulus Y = E(ω → 0) 10 pN–10 μms–s 10 nm–5 μ5–10 2 and 96  
Parallel plate rheology Elastic modulus E(ω10 pN–10 μms–s Whole cell 5–10 2  
Rotating plate rheology Shear modulus G(ωLimited by the adhesive properties of cells ms–s Whole cell <106 (5–6 h needed to prepare cells) 2 and 97  
Micropipete aspiration Stretch modulus of envelope, strength of cell-to-cell and cell-to-substrate attachments 0.1 nN–1 μms–min >1 μ5–10 20  
Magnetic tweezers Shear modulus G(ω0.1–100 pN ms–min 1–10 μ1000 2, 21, 98 and 99  
Particle tracking rheology Diffusion coefficient →G(ω) N/A ms–h 0.01–1 μ10–100 2 and 22  
FRET probes Force, stress 1–100 pN ms–min 1 nm to whole cell 10–100 24  
Brillouin scattering Spatial distribution of longitudinal modulus M(x, yN/A ns >250 nm 10–100 25 and 26  
Optical stretchers Creep function J(t<100 pN ms–s Whole cell 100 2 and 27  
Laser ablation Creep function J(tN/A ms–s >250 nm 5–10 29  
TechniqueMain viscoelastic propertyForce rangeDynamic time scaleLinear dimension of the probed regionMeas. through-put (cell/h)Reference
AFM Young modulus Y = E(ω → 0) 10 pN–10 μms–s 10 nm–5 μ5–10 2 and 96  
Parallel plate rheology Elastic modulus E(ω10 pN–10 μms–s Whole cell 5–10 2  
Rotating plate rheology Shear modulus G(ωLimited by the adhesive properties of cells ms–s Whole cell <106 (5–6 h needed to prepare cells) 2 and 97  
Micropipete aspiration Stretch modulus of envelope, strength of cell-to-cell and cell-to-substrate attachments 0.1 nN–1 μms–min >1 μ5–10 20  
Magnetic tweezers Shear modulus G(ω0.1–100 pN ms–min 1–10 μ1000 2, 21, 98 and 99  
Particle tracking rheology Diffusion coefficient →G(ω) N/A ms–h 0.01–1 μ10–100 2 and 22  
FRET probes Force, stress 1–100 pN ms–min 1 nm to whole cell 10–100 24  
Brillouin scattering Spatial distribution of longitudinal modulus M(x, yN/A ns >250 nm 10–100 25 and 26  
Optical stretchers Creep function J(t<100 pN ms–s Whole cell 100 2 and 27  
Laser ablation Creep function J(tN/A ms–s >250 nm 5–10 29  

The techniques listed in Table I have been divided into three groups. The first group comprises techniques where a solid probe comes into direct contact with cells. These techniques include AFM, parallel and rotating plate rheology setups, and micropipetes. The first three techniques allow determining complex elastic moduli of cells considering them as homogenous soft material.18 However, the moduli determined by these techniques differ by several orders of magnitude even when the same cell line in almost identical culturing conditions is used.18 Part of the variation in the moduli can be explained by differences in the contact area between the cell and the probe, loading rate, and stress level although a range of other factors could also play a role. The mechanical response in the above three techniques arises from the mechanical properties of both the envelope and the internal structures of the cell. In contrast, response to micropipete aspiration arises predominantly from the viscoelastic properties of cell membranes.2,19,20 This technique can also be used to estimate the attachment strength of cells to a substrate and other cells.

The second group includes techniques that track small particles or beads either attached to the cell surface or freely diffusing in the cytosol (Table I). These techniques include magnetic tweezers2,21 and particle tracking rheology.2,22 We exclude here optical tweezers, which make use of beads attached to the cell surface, as this technique has been rarely used due to its rather limited force range and phototoxic effects. Extraction of complex moduli using magnetic tweezers and particle tracking rheology is less direct compared to the techniques in the first group in Table I. For magnetic tweezer experiments, the determination of shear moduli has relied on finite element modeling of a cell as an isotropic medium.2,23 In particle tracking rheology, the complex shear modulus is determined from the mean square displacement of particles making use of the fluctuation-dissipation theorem.18,19 As an advantage, both techniques allow more cells to be studied in parallel compared to the techniques in the first group.18 

The last group in Table I comprises techniques that use light to directly probe the mechanical properties of cells. Our list includes FRET-based force sensors, Brillouin scattering microscopy, fiber-based optical stretchers, and laser ablation. As these techniques have emerged more recently and can be used in conjunction with lab-on-a-chip platforms, we will next also discuss briefly the concepts of these techniques.

In a FRET-based force sensor, a donor–acceptor pair of fluorescent molecules is covalently attached to the opposite ends of a force-transducer molecule, which acts as a linear or non-linear spring.24 The transducer molecule can be an unstructured peptide chain, a DNA hairpin, or a receptor–ligand pair that unbinds when the force exceeds a threshold value. In the latter two cases, the transducer acts as an ON–OFF switch that responds to a force exceeding a threshold value. Nevertheless, a continuous force response near the threshold can still be found when the signals from a larger number of molecular sensors are averaged. The drawback of FRET and its extensions is the cumbersome labeling technique. Also, one has to be careful to ascertain that labeling itself and/or the applied light intensities do not alter cellular behavior.

In Brillouin microscopy, no labeling of cells is required. In this technique, light inelastically scatters from the acoustic phonons.25,26 Frequency shifts and linewidths of Brillouin Stokes and anti-Stokes peaks are measured as a function of spatial coordinates. Based on these quantities, the real and imaginary parts of the longitudinal elastic modulus, M, can be calculated. However, this calculation requires knowledge of the local density and refractive index. Moreover, the longitudinal modulus is distinct from the elastic modulus (E). As of now, Brillouin scattering measurements allow distinguishing a denser elastic environment from a less dense viscous environment within the cell. A further drawback is that Brillouin scattering is very weak; typically only one in 1012 of incident photons scatters.25 As a result, measurements use high light intensity over long integration times causing phototoxic effects to cells.

Optical fields can also be used for the mechanical actuation of cells. A widespread technique, referred to as the optical stretcher,27,28 uses two aligned optical fibers that are separated by a small gap. Cells are trapped into this gap by scattering forces, which arise at the cell surface due to the difference in the refractive index. The same forces also stretch the cell. The setup typically measures the creep function of the cell.18 It is less cytotoxic than the conventional optical tweezer because the light is not focused and thus the power density within the cells is lower. The technique has some potential as a tool for medical diagnostics, but its throughput is small compared to microfluidic approaches as will be discussed later.

The last technique on our list is laser ablation. In this largely qualitative technique, high-energy laser pulses are used to obliterate cytoskeletal elements, intracellular junctions, and whole cells in multi-cellular cultures.29 The surroundings of the ablated structures usually undergo damped recoil. Creep function can be extracted from these measurements, but its magnitude remains unknown because the stress in the structure before and after ablation is not directly measured. Nevertheless, the viscoelastic properties of the structures can be inferred from the speed and magnitude of recoil. These inferences typically rely on the mechanical modeling of a cell or multicellular network. Its usefulness in mapping out strains in cells and cellular networks remains limited by its destructive one-time readout. After a cell or network is probed, it is questionable if it could be measured again because the extent of the damage from the laser pulse remains unknown.

While the “conventional” techniques discussed in Sec. III have made great strides in understanding cells as soft matter systems, they are not well applicable to address questions on how cells and tissues respond to mechanical stimuli on longer, biologically relevant time scales for most active responses (cf. Fig. 1). For such studies, measurement setups are needed where actuation can be applied over hours to days and cellular responses can be observed in real-time. For meaningful interpretation of such cellular responses, cells need to be in a well-designed microenvironment during the experiment, which closely mimics their native environment. Otherwise, the cellular response to a foreign microenvironment rather than to an intended controlled mechanical perturbation is studied. A critical requirement for the reproducibility of such studies is also that the number of cells or organoid cultures is sufficiently large. It is well known that the physical properties of individual cells have large variations within the cell population.30 Probing small numbers of them can lead to misinterpretation of results.

Lab-on-a-chip-based devices offer possibilities to overcome the above limitations. First and foremost, lab-on-a-chip approaches allow the growth of cells in a steady and well-defined environment during the measurement. The techniques based on particle tracking and optical readout (groups 2 and 3 in Table I, respectively) can be carried out on lab-on-a-chip platforms to provide a cellular environment that better resembles the native one. Such transfer is not easily applicable to AFM/cantilevers and parallel plate rheology setups but devices with similar functionalities can be constructed on the lab-on-a-chip platform as will be discussed later. Integrating “conventional” techniques with lab-on-a-chip platforms thus enables mechanical stimulation and monitoring of cells over much longer periods.

Possibilities of lab-on-a-chip platforms for mechanobiology go beyond mere cell culture improvement. Frequently, lab-on-a-chip platforms enable the expansion of the measurement throughput from single cells to hundreds and thousands of cells in parallel. Lab-on-a-chip platforms also enable monitoring chemical and electrical cues using on-chip sensor arrays.31–33 It is feasible to combine mechanical and (electro)chemical sensing on the same platform in the future.

In the following, we discuss the advantages and disadvantages of different device concepts that have been used to mechanically stimulate and probe cells. We do not dwell on different fabrication aspects of these devices but point the reader to excellent discussions on the topic.34,35

Cell growth, shape, division, and differentiation are all expected to be affected by mechanical forces. In particular, embryonic, stem, and primary tumor cells are imposed to confinement and mechanical stress. Many pathogens penetrate host tissue by processes where a mechanical pushing force is important.36 The growth of single-celled organisms in the interior of colonies also requires overcoming mechanical stresses. It has been suggested that mechanical confinement can be the main growth-limiting factor for E. coli colonies on agar plates instead of nutrient availability.30 In all these cases, the force is internally generated by the cells. Forces arise as the cell pushes against surrounding cells and the extracellular environment that opposes its growth. The mechanical work performed by cells in such situations is frequently coupled to enzymatic activities that can remodel the extracellular environment. However, most microfluidic devices, especially those which are based on inorganic materials, are sufficiently inert so that the latter type of remodeling activity has a negligible effect.

A fundamental question related to cell physiology is how much force a cell can generate by its growth before stalling. The question about stall force has been extensively studied in individual motor proteins in vitro conditions using optical and magnetic tweezers. However, the “conventional” tools are not suitable to answer this question in cells because of the much higher forces involved. Using microfluidics, the stall force can be readily measured using simple circular-shaped microfluidic chambers made of soft polydimethylsiloxane (PDMS), which is deformable by individual cells [Fig. 2(a)]. It has been found that the fission yeast (and some other fungal) cells are capable of exerting up to about 10 μN forces to their surrounding environment.37,36 So far, it is not clear how these findings translate to the other types of cells. It can be expected that the above approach will be more extensively used to map out growth-generated forces in different single-celled organisms. Making use of the same setup and fluorescent reporters, one will also be able to better understand how forces affect biochemical pathways involved in cell growth.

FIG. 2.

Confinement induced forces in microchannels and chambers. (a) Time-lapse images of growing fission yeast cell in a circular-shaped microchamber for 3 h. The deformable chamber is fabricated using soft PDMS with Young's modulus of 0.16 MPa. Scale bar, 10 μm. [Reproduced with permission from Minc et al., Curr. Biol. 19, 1096–1101 (2009). Copyright 2009 Elsevier Ltd.] (b) Time-lapse images of an MDA-MB-231 breast cancer cell during migration through a microfluidic constriction. The bright region corresponds to the cell nucleus. Scale bar, 5 μm. [Reproduced with permission from Denais et al., Science 352, 353–358 (2016). Copyright 2016 AAAS.] (c) Left: E. coli growing in slit-like channels with widths about half the size of the typical diameter of the cells (0.8 μm). Confined cells transform into large irregular shapes. Right: regular unconfined E. coli cell for comparison. [Reproduced from Männik et al., Proc. Natl. Acad. Sci. U.S.A. 106, 14861–14866 (2009). Copyright 2009 National Academy of Sciences.] (d) Schematics of fabrication of self-foldable microtubes. By removing the sacrificial layer, a strained bilayer is released and bent, resulting in a microtubular structure. (e) Encapsulation and arrangement of yeast cells in a self-foldable microtube. [Reproduced with permission from Mei et al., Adv. Mater. 20, 4085–4090 (2008). Copyright 2008 John Wiley and Sons, Ltd.]

FIG. 2.

Confinement induced forces in microchannels and chambers. (a) Time-lapse images of growing fission yeast cell in a circular-shaped microchamber for 3 h. The deformable chamber is fabricated using soft PDMS with Young's modulus of 0.16 MPa. Scale bar, 10 μm. [Reproduced with permission from Minc et al., Curr. Biol. 19, 1096–1101 (2009). Copyright 2009 Elsevier Ltd.] (b) Time-lapse images of an MDA-MB-231 breast cancer cell during migration through a microfluidic constriction. The bright region corresponds to the cell nucleus. Scale bar, 5 μm. [Reproduced with permission from Denais et al., Science 352, 353–358 (2016). Copyright 2016 AAAS.] (c) Left: E. coli growing in slit-like channels with widths about half the size of the typical diameter of the cells (0.8 μm). Confined cells transform into large irregular shapes. Right: regular unconfined E. coli cell for comparison. [Reproduced from Männik et al., Proc. Natl. Acad. Sci. U.S.A. 106, 14861–14866 (2009). Copyright 2009 National Academy of Sciences.] (d) Schematics of fabrication of self-foldable microtubes. By removing the sacrificial layer, a strained bilayer is released and bent, resulting in a microtubular structure. (e) Encapsulation and arrangement of yeast cells in a self-foldable microtube. [Reproduced with permission from Mei et al., Adv. Mater. 20, 4085–4090 (2008). Copyright 2008 John Wiley and Sons, Ltd.]

Close modal

Microfluidic channels can also be used to study how cells respond to mechanical deformations that squeeze them in the direction perpendicular to their main symmetry axes, which frequently determines their direction of movement. The migration of squeezed cells is relevant for metastatic cancer cells and immune cells. Many of these studies have made use of slit-like channels and pores. It has been found that the dimension of the nucleus significantly limits the migration of cancer cells. However, the cell can squeeze through pores smaller than the linear dimension of the nucleus in its relaxed state [Fig. 2(b)]. In doing so, cell's nuclear envelope can rupture, which could result in genomic instability.38 The latter refers to the fragmentation of DNA and its subsequent partial degradation. Interestingly, the cells are usually able to repair the damage to the nuclear envelope while the damage to the DNA can be irreversible. The stiffness of the nuclear envelope has shown to be also a limiting factor for the migration of other cell types through confined spaces.39,40 The next anticipated frontier for these studies would be to combine cell migration studies with single-cell sequencing to quantitatively assess the damage to the genome. Furthermore, these studies can be combined with single-cell proteomic analysis to understand how mechanical stress stimulates the excretion of enzymes and small molecules that are capable of remodeling extracellular matrix and cell-to-cell junctions.

The migration of bacteria in narrow slit-like channels has also revealed unexpected behavior. It was found that E. coli in slit-like channels with widths about half their unperturbed diameter transformed to very wide and irregularly shaped cells41,42 [Fig. 2(c)]. Interestingly, most cellular processes including DNA replication and mass growth only showed a minor perturbance in response to the change in cell shape and size.42 On the other hand, the widening of bacteria under uniaxial stress indicates that the synthesis of the E. coli cell wall is strongly influenced by the stresses in it. Similar conclusions were also drawn from different types of experiments in microfluidics chips.43,44 In the latter, E. coli cells grew out of short side channels into the main channel. A fluid flow in the main channel exerted stress effectively bending the cells in the flow direction. Both types of measurements indicate that regions of the cell wall, which are exposed to tensile stresses and strains, favor the addition of new cell wall material. While these experiments established the phenomenological relationship between cell wall growth and mechanical stress, the underlying molecular mechanisms remain to be understood. For that end, one could tag enzymes involved in the cell wall synthesis with fluorescent fusions and/or use recently developed fluorescent precursors for cell wall45 in imaging of cells that grow in microfluidic channels.

In the above studies, cells have been strongly confined by one spatial direction. Studies are mostly making use of uniaxial instead of biaxial confinement because of the difficulty in fabricating a range of channels of different heights on a single device using conventional soft lithography methods. Some workarounds for this limitation have been demonstrated recently but these are applicable for large channels.46 Promising alternative to conventional methods is to use self-foldable tubes.47–49 Their circular geometry mimics better in vivo constraints than the rectangular geometry of conventional microchannels.

Self-foldable tubes form when a thin film with the tube material is released from a sacrificial layer by etching [Fig. 2(d)]. The radius of the self-foldable tube is controlled by the lattice mismatch elastic properties of two layers that form the wall of the tube. A wide range of tube materials can be used including inorganic materials, cell-friendly polymers,47 or graphene.50 Typically, the self-foldable tubes are not part of a fluidic circuitry, as usually encountered in lab-on-a-chip devices. Nevertheless, different tubes can be arranged into a network using micropipetes.47 The cells can enter these channels on their own without any external force applied49 [Fig. 2(e)] or encapsulated during the folding process.47 As for 2D cases, the propagation of cells in the channels depends sensitively on the channel diameter. Below a certain diameter, which for HeLa cells is about 8 μm, disruptions to cell divisions and genome instability occur.51,52 The advantage of self-foldable tubes over conventional microfabricated channels is the flexibility to use a range of different materials as the channel walls. This will enable future systematic studies on how cells respond to tight contact with different surface materials. Moreover, electrical,50 magnetic,53 or optical sensing54 capabilities in microchannels of self-foldable tubes have been demonstrated recently. These sensing modalities can be used for real-time measurements of encapsulated cells.55 A potential advantage of self-foldable tubes over conventional microfabricated channels is also a simpler determination of forces exerted by the cells on the channel walls. Thanks to the simple geometry of the tube, the average stress acting on the cells can be analytically calculated from the deformation of the tube.48,49 For conventional microfluidic channels, such calculations are much more complicated and prone to uncertainties.

Cells in blood vessels, such as red and white blood cells and endothelial cells, experience shear flows and stresses.56 Deformability of these cells is important for their proper function.57 The deformation of the cells in shear flow can help to distinguish diseased cells from normal cells in medical diagnostics. This so-called mechanical phenotyping can be also used for other cell types, in particular, for the detection of metastatic cancer cells.58,59 The underlying group of techniques has been referred to as deformability cytometry.60 Note that the term deformability has a rather loose definition in the biomedical field and is mostly used as a relative measure when comparing one cell type to another. In some measurements, it may refer to the change in the aspect ratio of cells while in others, deformability is characterized by the time of how fast a cell can pass a constriction.

Several microfluidic approaches for implementing deformability cytometry have emerged. In one class of devices, the cells are pushed through a constricting channel where one of the lateral dimensions is smaller than the relevant dimension of the cell.61 This setup is similar to the one discussed in Sec. IV A but with the difference that the driving force to push cells through the constriction is created by advection and not by the cells themselves.

In other types of devices, cells are not in contact with channel walls and shear arises solely from the flow profile [Figs. 3(a) and 3(b)]. Here, two approaches have been used more broadly. In the first approach, referred to as a shear flow deformability cytometry, the fluid with the cell suspension passes from wider to a narrower channel [Fig. 3(a)].62 Shear stress and pressure in the channel deform from a spherical cell into a bullet-like shape. This deformation is imaged by a high frame-rate camera and deformability is calculated based on a segmented image of the cell in real time [Fig. 3(a), bottom]. In the second approach, cells are trapped and stretched by an extensional flow that forms in a four-way junction of fluidic channels [Fig. 3(b)].63,64 To achieve stretching, high Reynolds number (Re>50) flows are required. In this approach too, cell deformation is determined from images acquired by a high-speed camera. The method has shown very promising results allowing to screen cancer cells at rates of 2000 cells/s and to distinguish normal and malignant leukocytes with about 90% accuracy.63 At the same time, it appears to be less sensitive in detecting perturbations of cell stiffness compared to shear flow deformability cytometry.60 Whether any of the above-mentioned approaches will be able to compete in their reliability with the existing detection methods for cancer markers in body fluids remains to be seen. Their current use in cell cytometry applications is also hindered by the need for expensive high-resolution microscopes and high-speed cameras.

FIG. 3.

Fluidic and contact shear forces in microchannels. (a) Top: schematics for shear flow deformability cytometry where cells are flown from wider channels to narrower ones. Bottom: in narrower channels, cells deform from spherical (not shown) to bullet-like shapes. [Reproduced with permission from Mietke et al., Biophys. J. 109, 2023–2036 (2015) Copyright 2017 Author(s), licensed under a Creative Commons Attribution (CC BY-NC-ND) license.] (b) Top: schematics for extensional flow deformability cytometry. Bottom: the extensional flow stretches the cell to prolate spheroid shape. [Reproduced from Gossett et al., Proc. Natl. Acad. Sci. U.S.A. 109, 7630–7635 (2012). Copyright 2012 National Academy of Sciences.] (c) Schematics of a constricting channel fabricated within a silicon cantilever. The presence of the cell is detected by the change of resonance frequency of the cantilever. [Reproduced from Byun et al., Proc. Natl. Acad. Sci. U.S.A. 110, 7580–7585 (2013) Copyright 2013 National Academy of Sciences.]

FIG. 3.

Fluidic and contact shear forces in microchannels. (a) Top: schematics for shear flow deformability cytometry where cells are flown from wider channels to narrower ones. Bottom: in narrower channels, cells deform from spherical (not shown) to bullet-like shapes. [Reproduced with permission from Mietke et al., Biophys. J. 109, 2023–2036 (2015) Copyright 2017 Author(s), licensed under a Creative Commons Attribution (CC BY-NC-ND) license.] (b) Top: schematics for extensional flow deformability cytometry. Bottom: the extensional flow stretches the cell to prolate spheroid shape. [Reproduced from Gossett et al., Proc. Natl. Acad. Sci. U.S.A. 109, 7630–7635 (2012). Copyright 2012 National Academy of Sciences.] (c) Schematics of a constricting channel fabricated within a silicon cantilever. The presence of the cell is detected by the change of resonance frequency of the cantilever. [Reproduced from Byun et al., Proc. Natl. Acad. Sci. U.S.A. 110, 7580–7585 (2013) Copyright 2013 National Academy of Sciences.]

Close modal

The need for a high-speed camera and a microscope is circumvented in an approach where a microfluidic channel with a constriction is fabricated within a cantilever.60,65 In this measurement scheme, the readout is obtained from the resonant frequency shift of the cantilever. Deformability is characterized by the time the cells spend in the constricting region where it is in contact with channel walls [Fig. 3(c)]. The technique also allows the readout of the cell's buoyant mass. This precision measurement adds a high-quality feature, which in addition to deformability helps in distinguishing diseased cells from normal ones. Adding further modalities to this setup would be potentially useful. For example, one could perform impedance spectroscopy in this setup. The potential for higher-dimensional datasets and at the same time simpler readout may give the cantilever-based setup an advantage in medical diagnostics compared to the purely fluidic based deformability measurements.

Many types of animal cells, including myocytes, lung, and epithelial cells, experience tensile mechanical forces in their native environment. Studying these cells in a static environment is not guaranteed to represent their native responses to different stimuli/insults such as drugs and pathogens. These recognitions have led to the development of tools where cells are stretched via a flexible substrate to which these cells are attached.66,67 Many macro-scale systems exist that implement this concept; some of them being commercially available. These systems differ primarily by the actuation mechanism, which includes for example stepper motors, as well as electromagnetic and piezoelectric actuators.66,67 Different approaches allow different strain rates and magnitudes to be applied. Here, we focus on a pneumatic actuation mechanism that is compatible with the lab-on-a-chip platform. In our opinion, it has the highest potential to yield transformative biological insights and to develop a broadly applicable screening platform for biomedical research. One of the pioneering works in this direction was by Huh et al.68 who developed a so-called lung-on-a-chip device that allowed periodic stretching of lung cells. Further work in this field has produced a heart-on-a-chip,69 gut-on-a-chip,70 and kidney-on-a-chip platforms.71 The common design element for all these platforms is a stretchable microporous substrate made of PDMS, which is cyclically stretched by applying vacuum to the side channels [Fig. 4(a)]. The stretchable porous substrate separates two parallel channels where different fluids or gases can be present. The substrate can also be stretched by fabricating a pressure channel underneath it and applying overpressure to this channel so that the substrate bulges [Fig. 4(b)]. The first of the two designs is more difficult to fabricate but allows the flowing of different liquids/gases on either side of the membrane. Also, different cell types can be grown on the two sides of the membrane. For example, in a lung-on-a-chip platform, lung epithelial cells have been cultivated on one side of the membrane and endothelial cells on the other side. Epithelial cells are exposed to airflow in the top channel while endothelial cells are exposed to the flow of cell culture medium in the bottom channel as depicted in Fig. 4(a). In some measurements, neutrophils (type of white blood cell) were also present in the bottom channel. It was found that mechanical stimulation increased recruitment of neutrophils to the epithelium via the endothelial layer upon exposure of the former to silica nanoparticles or to E. coli bacteria.

FIG. 4.

Designs of pneumatic cell stretchers integrated into lab-on-a-chip platforms. (a) Schematics for a lung-on-a-chip. Lung epithelial and endothelial cells are cultivated on different sides of a stretchable membrane. Vacuum suction is applied to side chambers to stretch the membrane. [Reproduced with permission from Huh et al., Science 328, 1662–1668 (2010). Copyright 2010 AAAS.] (b) Schematics of a cell stretching device in which overpressure is applied to a pneumatic channel underneath the cells. [Reproduced with permission from Kamble et al., Lab Chip 16, 3193–3203 (2016). Copyright 2016 the Royal Society of Chemistry.]

FIG. 4.

Designs of pneumatic cell stretchers integrated into lab-on-a-chip platforms. (a) Schematics for a lung-on-a-chip. Lung epithelial and endothelial cells are cultivated on different sides of a stretchable membrane. Vacuum suction is applied to side chambers to stretch the membrane. [Reproduced with permission from Huh et al., Science 328, 1662–1668 (2010). Copyright 2010 AAAS.] (b) Schematics of a cell stretching device in which overpressure is applied to a pneumatic channel underneath the cells. [Reproduced with permission from Kamble et al., Lab Chip 16, 3193–3203 (2016). Copyright 2016 the Royal Society of Chemistry.]

Close modal

In current studies, organ-on-a-chip devices have been used to study drug efficacies, toxicity, and interactions of tissue with pathogens.52 Organ-on-a-chip devices hold great promise in reducing the number of in vivo studies with animal models. Using cultivated human cells, which closely mimic cells in a tissue, could provide a more representative model than a living animal for certain research questions and be ethically less problematic. Such a platform would also allow a more detailed observation of individual cells as many organ-on-a-chip platforms are compatible with high-resolution optical imaging. Finally, these platforms facilitate the integration of on-chip electrical sensors that can detect metabolites and signaling molecules from cells in real time72 although this integration is yet in the early stages of development. A challenge for many organ-on-a-chip platforms is the difficulty to stably preserve cell cultures over one month.52 The latter is still a relatively short time in terms of (human) development. The factors that affect the viability of cells in lab-on-chip devices are not completely understood. They involve degradation of adhesive layers (typically fibronectin or collagen) and absorption of small hydrophobic molecules from culture medium into PDMS,73 which has been the dominant material for stretchable lab-on-a-chip devices. It has also been argued that PDMS has some cytotoxic effects.74 The toxicity has been assigned to PDMS oligomers that are not cross-linked and can diffuse out from the PDMS matrix. Finding easily processable biocompatible alternatives to PDMS, such as stretchable hydrogels,75 is therefore desirable. Despite these shortcomings, we expect that in coming years organ-on-a-chip platforms will find more and more adoption by pharmacological companies and that this adoption will help to speed up the lengthy and costly drug-screening process. The platforms will also allow relevant in basic research and help to elucidate how individual cells in a tissue respond to mechanical forces.

Lab-on-a-chip devices allow the application of compressive stresses to groups or individual cells, as well as sub-cellular regions. A promising approach of applying compressive stresses to cells makes use of PDMS-based pneumatic microvalves. These devices were originally designed to turn on and off flow in microfluidic channels.76 The microvalve consists of two perpendicular fluidic lines separated by a thin (tens of micrometers) elastomer membrane [Figs. 5(a) and 5(b)]. The application of hydrostatic pressure to one of the fluidic channels (control line) leads to the expansion of this channel and deflection of the membrane between the fluidic lines. If a cell is placed underneath the valve, a compressive force is applied to the cell [Fig. 5(c)]. Stresses of several hundreds of kPa can be applied to cells this way.

FIG. 5.

Pneumatic microvalves for cell squeezing experiments. (a) A basic design of the valve. Pneumatic valve forms at the region where flow and control lines overlap. (b) A photograph of a finished microfluidic chip showing the flow (blue) and the control (red) lines. (c) If a cell is placed in the valving region and external pressure is applied to the control line, then the cell will be squeezed. (d) Calculated profiles for the ceilings of the flow lines at pressures of 0, 2, and 4 bars in the control line. Due to a convex shape, the ceiling of a half-closed valve exerts a lateral force (blue arrows) that tends to displace cells from the center of the channel. [Reproduced with permission from Yang et al., J. Vac. Sci. Technol., B 33, 06F202 (2015). Copyright 2015 AIP Publishing LLC.]

FIG. 5.

Pneumatic microvalves for cell squeezing experiments. (a) A basic design of the valve. Pneumatic valve forms at the region where flow and control lines overlap. (b) A photograph of a finished microfluidic chip showing the flow (blue) and the control (red) lines. (c) If a cell is placed in the valving region and external pressure is applied to the control line, then the cell will be squeezed. (d) Calculated profiles for the ceilings of the flow lines at pressures of 0, 2, and 4 bars in the control line. Due to a convex shape, the ceiling of a half-closed valve exerts a lateral force (blue arrows) that tends to displace cells from the center of the channel. [Reproduced with permission from Yang et al., J. Vac. Sci. Technol., B 33, 06F202 (2015). Copyright 2015 AIP Publishing LLC.]

Close modal

Early attempts to use this approach employed valves where the fluid line had either a concave (semi-circular) or rectangular cross section. A wide fluidic line (100–200 μm) with a concave cross section can be fully closed by the pressure in the control line. In principle, such valves can be used to study very large cells, such as neurons. However, this approach is not practical for smaller cells, including bacteria, because the possible range of uniaxial stress that can be applied is very limited. For higher applied stresses, the elastomer ceiling curves effectively embedding the cells.77 Consequently, the cells are cut off from the media supply and become dehydrated as water and possibly some small molecules are pressed out.78 Both are highly undesired outcomes for most studies, although there are also useful applications.78 The embedding of cells can be avoided in valves where the flow line has a rectangular cross section. However, this induces in addition to the compressive force also a lateral force that pushes cells away from the center of the valve [Fig. 5(d)].79 To overcome this shortcoming, a different design of the valve has emerged, featuring a protrusion in the ceiling of the flow line at the center of the valve [Figs. 6(a) and 6(b)].80–83 This design, referred to as the microanvil, has been used to study both eukaryotic and prokaryotic cells. By growing axons across the microvalve area, it was found that at loads higher than about 95 kPa, axons were instantaneously transected.80 However, nearly half of these axons were able to regrow within about a 10 h period in the absence of exogenous stimulating factors [Fig. 6(c)]. A similar approach was also used to study damage to vascular tissue.83 The approach holds much promise to better understand how different tissues respond to mechanical trauma at the single-cell level. It will also help to elucidate the molecular pathways involved in the immediate response and repair pathways.

FIG. 6.

Microanvil valve actuators. (a) A conceptual design of the microanvil. A protrusion (anvil) is fabricated in the ceiling of the valve that contacts the cell and compresses it. (b) A phase-contrast image of the microanvil and trapped E. coli cell. The scale bar is 2 μm. [Panels (a) and (b) are reproduced with permission from Yang et al., Mol. Microbiol. 113, 1022–1037 (2020). Copyright 2020 John Wiley and Sons, Ltd.) (c) Transection of the axon by a microanvil. 0 min: an axon (green) before transection, 20 min: the same axon right after transection. The later images show the regrowth of this axon. [Reproduced with permission from Hosmane et al., Lab Chip 11, 3888–3895 (2011). Copyright 2011 the Royal Society of Chemistry.] (d) Fluorescence images of E. coli cells under rapid compression (left) and release (right) of the microvalve. Fluorescence originates from the HupA-mCherry label that stains bacterial DNA (the nucleoids). (e) Fluorescence intensity from the center of the same cell as a function of time. Panels (d) and (e) are authors’ unpublished results.

FIG. 6.

Microanvil valve actuators. (a) A conceptual design of the microanvil. A protrusion (anvil) is fabricated in the ceiling of the valve that contacts the cell and compresses it. (b) A phase-contrast image of the microanvil and trapped E. coli cell. The scale bar is 2 μm. [Panels (a) and (b) are reproduced with permission from Yang et al., Mol. Microbiol. 113, 1022–1037 (2020). Copyright 2020 John Wiley and Sons, Ltd.) (c) Transection of the axon by a microanvil. 0 min: an axon (green) before transection, 20 min: the same axon right after transection. The later images show the regrowth of this axon. [Reproduced with permission from Hosmane et al., Lab Chip 11, 3888–3895 (2011). Copyright 2011 the Royal Society of Chemistry.] (d) Fluorescence images of E. coli cells under rapid compression (left) and release (right) of the microvalve. Fluorescence originates from the HupA-mCherry label that stains bacterial DNA (the nucleoids). (e) Fluorescence intensity from the center of the same cell as a function of time. Panels (d) and (e) are authors’ unpublished results.

Close modal

To study bacterial cells, the dimensions of the valve were scaled down about 20 times reaching lateral dimensions of about 4 × 8 μm2 and a height of about 1 μm [Fig. 6(b)]. Using this device, filamentous E. coli with a length of about 8–10 μm have been studied. Among other findings, the measurements have given new insights into how fast cytosolic water and small molecules can leave E. coli cells. The initial slow speed measurements showed loss of about 30% of the cytosolic volume upon compression in the 1-min range.81 A more recent high-speed measurement revealed that the outflow of water occurs in a mere 50 ms [Figs. 6(d) and 6(e)]. Interestingly, the outflow of water was reversible and also the influx occurred on a fast time scale (≈100 ms) [Fig. 6(e)]. The rapid outflow of water can be explained by the opening of mechanosensitive channels when there is a sudden increase in cytosolic pressure and cell membrane tension but these channels should be closed during the restoration of cell volume when there is no overpressure. It remains to be determined what mechanism allows cells to refill their volume rapidly. In future work, the dimensions of the valve should be scaled down to accommodate regularly sized E. coli and other bacterial cells. Also, deformation of the anvil portion could be used to determine the actual stress applied to the cells.

As mentioned earlier (cf. Table I), experiments with magnetic tweezers are typically carried out at low sample numbers. An implementation of electromagnetic actuator techniques within a lab-on-a-chip device promises to open up the possibility for automation and high-throughput experiments.84 Prominent methods to apply on-chip tweezers rely on magnetophoretic and dielectrophoretic particle actuation.85,86 While the required magnetic fields to generate magnetophoresis are conventionally produced using external coils, the suitable structures can also be directly incorporated into the chip design, e.g., making use of a crossbar layout.87 Driving specific loop-like current patterns through the crossbar array allows generating magnetic fields at specific locations of the chip in a time-dependent manner. The generated fields apply a force on an induced (or a permanent) dipole and can be used to actuate multiple particles in different locations of the chip surface (Fig. 7). Since most biological cells show only negligible response to moderate magnetic fields themselves, magnetic tags need to be attached to them.88,89 While the generation of chip-based magnetophoretic forces is intrinsically limited to 2D using the crossbar architecture, it is possible to additionally generate dielectrophoretic forces with the same chip design. To this end, the DC sequences for the generation of the magnetic field are overlaid with an AC sequence, generating an inhomogeneous electrical field. This approach allows a precise actuation in three dimensions using a single chip without any moving parts or external components [Fig. 7(d)].90 Yet, care has to be taken to avoid the generation of excessive temperatures at the chip surface caused by resistive heating from the applied currents. Such temperature changes might interfere with the response of cells to mechanical stimuli. Future applications of on-chip electromagnetic tweezers for high-throughput mechanobiological cell experiments will thus critically depend on advanced chip designs, which allow the application of significant forces and minimize heat dissipation. This could enable the precise and localized generation of tensile and compressive forces to adherent cell networks in a parallel configuration using arrays of individually trapped and actuated particles.

FIG. 7.

On-chip electromagnetic tweezers implemented by a crossbar array architecture. (a) Concept of attractive magnetic and repulsive dielectrophoretic forces that can be generated simultaneously by driving DC and AC currents, respectively, through the crossbar array. (b) Microscopic image of a single magnetic particle captured at the center of a crossbar array. (c) and (d) Defined application of forces resulting in 3D actuation of a particle along defined trajectories above the chip surface (c: microscopic top view at the levitation plane overlaid with the particle trajectory and d: 3D plot of the particle trajectory. The corresponding time is indicated by the color code). Scale bars in (b) and (c) are 15μm. [Reproduced with permission from Rinklin et al., Lab Chip 16, 4749–4758 (2016). Copyright 2016 the Royal Society of Chemistry.]

FIG. 7.

On-chip electromagnetic tweezers implemented by a crossbar array architecture. (a) Concept of attractive magnetic and repulsive dielectrophoretic forces that can be generated simultaneously by driving DC and AC currents, respectively, through the crossbar array. (b) Microscopic image of a single magnetic particle captured at the center of a crossbar array. (c) and (d) Defined application of forces resulting in 3D actuation of a particle along defined trajectories above the chip surface (c: microscopic top view at the levitation plane overlaid with the particle trajectory and d: 3D plot of the particle trajectory. The corresponding time is indicated by the color code). Scale bars in (b) and (c) are 15μm. [Reproduced with permission from Rinklin et al., Lab Chip 16, 4749–4758 (2016). Copyright 2016 the Royal Society of Chemistry.]

Close modal

Cells actively respond to mechanical cues in their environment. Understanding these responses at the molecular and cellular level is currently limited because of a lack of available tools to stimulate individual cells and cell networks in a controlled manner. Lab-on-a-chip platforms provide unique capabilities to study responses in conditions that closely match the cellular environment over extended periods. Parallelization that is inherent to microfabrication technology enables to drastically increase the measurement throughput. Despite these promises, many challenges remain that limit the use of such devices. An important issue is the complexity of fabrication and device handling. Devices that allow the application of forces to individual cells in a controlled manner typically require multilayer processes and the capability to align different layers together. This is usually done manually and as such the process is time-consuming and prone to a high failure rate. Multi-layered devices can also be fabricated using 3D printing.34 Although more reliable, 3D printing is also a serial process and as of now, its resolution is not sufficient to fabricate devices for smaller cell types such as bacteria. Material compatibility issues with long-term cell cultures remain also a concern. Making further use of hydrogels and biopolymers instead of traditional PDMS could alleviate these issues. Recently, intensive efforts have been directed at 3D printing of diverse materials for the fabrications of microfluidic devices,91–95 which could potentially be used in studies related to mechanotransduction. Further improvement is also needed in determining the exact force and stress magnitudes that microfluidic actuators apply to cells. As of now, most in situ force-sensing in lab-on-a-chip devices relies on rather complicated mechanical or fluid dynamic simulations. Furthermore, in many measurements force and stress magnitudes are not known and the device is just used to stimulate the cells. Miniaturized pressure and force sensors that are integrated into microfluidic circuits could significantly improve the accuracy of the force readout. Different fluorescent probes represent a promising approach in this direction as most lab-on-a-chip devices are used in conjunction with fluorescent microscopy setups. The development of new integrated sensor arrays could also facilitate adding electrical and electrochemical detectors to the microfluidic chips that are capable of monitoring signaling molecules, cell metabolites, and secreted enzymes in a cell culture medium. These chemical signals form an integral part of cellular response to a mechanical stimulus. Finally, to investigate organoids, the lab-on-a-chip platform needs to extend from mostly 2D cell cultures to more realistic 3D systems. Including blood vessels within these cultures would be highly desired. Indeed, engineering cells so that they partly fabricate the microfluidic device on their own is a logical next step in the development of lab-on-a-chip platforms.

The authors thank Jaana Männik for useful discussions. A part of this research was conducted at the Center for Nanophase Materials Sciences, which is sponsored at Oak Ridge National Laboratory by the Scientific User Facilities Division, Office of Basic Energy Sciences, U.S. Department of Energy. This work has been supported by the US-Israel BSF Research Grant (No. 2017004) (J.M.), and the National Institutes of Health Award (No. R01GM127413) (J.M.).

The data that support the findings of this study are available within the article.

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