Article

Topography of Cells Revealed by Variable-Angle Total Internal Reflection Fluorescence Microscopy Marcelina Cardoso Dos Santos,1 Re´gis De´turche,1 Cyrille Ve´zy,1 and Rodolphe Jaffiol1,* 1 Laboratoire de Nanotechnologie et d’Instrumentation Optique, Institut Charles Delaunay – UMR 6281 Centre National de la Recherche Scientifique, Universite´ de Technologie de Troyes, Troyes, France

ABSTRACT We propose an improved version of variable-angle total internal reflection fluorescence microscopy (vaTIRFM) adapted to modern TIRF setup. This technique involves the recording of a stack of TIRF images, by gradually increasing the incident angle of the light beam on the sample. A comprehensive theory was developed to extract the membrane/substrate separation distance from fluorescently labeled cell membranes. A straightforward image processing was then established to compute the topography of cells with a nanometric axial resolution, typically 10–20 nm. To highlight the new opportunities offered by vaTIRFM to quantify adhesion process of motile cells, adhesion of MDA-MB-231 cancer cells on glass substrate coated with fibronectin was examined.

INTRODUCTION Adhesion and migration are essential to normal and pathological cellular activities. During these processes, cells interact with each other and with their environment through a broad range of specific and nonspecific interactions. The specific cell binding is regulated by lock-and-key mechanisms, related to the presence of protein receptors (such as integrins or cadherins) at the cell surface, which can recognize specifically ligands located on other cells or in the extracellular environment (1). Cell adhesion also results from the synergy between various long- and shortrange cell-substrate nonspecific interactions, mediated, for example, by van der Waals forces, electrostatic forces, polymer steric repulsive forces, or thermal induced undulation forces (2). To add further to the complexity, all the molecules involved in cell adhesion processes can move in accordance with the fluidity of the plasma membrane, the dynamical reorganization of the cytoskeleton, and the global elasticity of the cell envelope. Such dynamic aspect of the adhesion process is crucial and remains largely unknown. Hence, cell adhesion is a highly dynamic and multiparameter phenomenon, which can be addressed in different Submitted March 7, 2016, and accepted for publication June 28, 2016. *Correspondence: [email protected] Marcelina Cardoso Dos Santos’ present address is Institut d’Electronique Fondamentale, UMR CNRS 8622, Universite´ Paris-Sud, Baˆtiment 220 rue Andre´ Ampe`re, Centre Scientifique d’Orsay, 91 405 Orsay Cedex, France. Editor: Christopher Yip. http://dx.doi.org/10.1016/j.bpj.2016.06.043 Ó 2016 Biophysical Society.

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ways; for example, by combining optical microscopy either with micropipette manipulation of cells (3), or by using fluid microjet to induce shear force on cells (4), or simply by atomic force microscopy (5). Specific adhesion can be studied with the usual fluorescence techniques, such as that of confocal fluorescence microscopy (6), or a more resolved technique, such as interferometric photoactivated localization microscopy (PALM) (7), by labeling the proteins involved in the adhesive structures, the so-called focal adhesion complexes. Standard total internal reflection fluorescence (TIRF) microscopy is also well suited to observe focal adhesion zones (8). On the other hand, nonspecific interactions can be assessed by measuring distances from the substrate to the plasma membrane, because forces that govern nonspecific adhesions are distance-dependent. As live cell adhesion remains a complex issue, nonspecific interactions have been preferentially studied on biomimetic systems such as giant unilamellar vesicles with reflection interference contrast microscopy (RICM) (9). RICM is a very interesting technique because it does not require a complex optical setup and provides distance measurements with a nanometric resolution on micrometric beads or on giant unilamellar vesicles. Unfortunately, RICM cannot be applied optimally on living cells to precisely determine membrane/substrate separation distances, mainly because RICM image processing needs a perfect knowledge of the cytoplasmic refractive index (9). At the single cell level this index is very inhomogeneous and changes drastically in time and in space, due to the presence

Variable-Angle TIRF Microscopy

of numerous intracellular organelles and protein assemblies such as stress fibers. Some recent publications demonstrate that specific and nonspecific forces involved in cellular adhesion appear to have a cooperative action, as regards the influence of glycocalyx on integrins. The nonspecific forces induced by the glycocalyx are mostly ensured by the presence of glycoproteins, which expose at the cell surface a wide range of long, short, and branched chains of negatively charged oligosaccharides. Paszek et al. (10) highlighted that the glycocalyx can alter the integrin-based focal adhesion plaques and promote migration of tumor cells. The expected impact of the glycocalyx on adhesion has been also emphasized on biomimetic systems, where it is supposed to exert a nonspecific steric repulsive force (11,12). As a result, we propose a real-time imaging technique to probe simultaneously the specific and the nonspecific aspects of adhesion process. This technique, called variable-angle total internal reflection fluorescence microscopy (vaTIRFM), allows us to map the membrane-substrate separation distance with a nanometric resolution at typical acquisition rate of 1 s. Compared to other techniques of imaging that also provide a nanometric axial resolution, vaTIRFM presents two main advantages: it is compatible with usual techniques of cell observation, and it does not induce photodamage to the specimen. First, cells are placed on a common glass coverslip, which can be easily coated with various proteins such as collagen or fibronectin to promote specific adhesion. This permits conventional bright-field observations with phase contrast, differential interference contrast, or interferometric techniques such as RICM; these are very useful to check the morphology and the general health of cells. This deserves to be highlighted as, among all new techniques allowing nanoscale localization along the optical axis, some of them use nontransparent or semitransparent substrates. Consequently, regular bright-field imaging techniques either cannot be used properly or cannot be used at all. This is especially the case of scanning angle interference microscopy, which uses a reflective silicon substrate (13). In the same way, some other recent techniques propose to exploit the well-established modification of the fluorescence lifetime near plasmonic substrates, such as nanostructured metallic thin films (14), or just a thin metallic film (15). Moreover, concerning the sample preparation, the coating of metallic film or nanoparticles with proteins to probe specific interactions significantly increases the level of complexity of the system. The second advantage concerned the photodamage of cells and their preparation, which is a crucial issue for any relevant investigations about adhesion. The technique proposed in this article is not based on single molecule detection. Consequently, it enables observation at a sampling rate on the order of 1 s together with a very low laser irradiance (typically ~10 W/cm2). The corresponding surface density of energy (~10 J/cm2) is significantly smaller than

the usual light dose used in common superresolution techniques, typically at least 102–103 kJ/cm2 in single-molecule localization microscopy techniques, such as interferometric PALM (7) and stochastic optical reconstruction microscopy (STORM) combined with supercritical-angle analysis (16–18), or ~104 kJ/cm2 in stimulated emission depletion microscopy (19). Surface density of energy employed in vaTIRFM is also notably smaller than the lethal dose of irradiation recently measured on living cells, typically a few hundreds of kJ/cm2 (20). It should be noted that the irradiation dose used in most of the superresolution microscopy experiments (PALM, STORM, stimulated emission depletion, etc.) is much higher than this lethal dose, which means that these techniques lead to an important photodamage of cells during the exposure time. Furthermore, to quantify the adhesion of living cells we propose to measure membrane-substrate distances. This can be achieved with a simple plasma membrane labeling using an amphiphilic dye molecule. Specific adhesion zones would be observed when the plasma membrane most closely approaches the substrate, as highlighted many times in the literature (7,13,21,22). Thus, cell preparation is less restrictive, because no particular labeling of adhesion proteins is required in our experiments. Furthermore, the cells remain alive and do not need to be fixed. So with our approach we favor real-time nondestructive observations, where cells can freely migrate above the substrate. In these conditions, it is possible to study the dynamic aspects of the adhesion process. Last but not least, the axial range of measurement with vaTIRFM is ~300–400 nm above the substrate. This point is crucial to observe nonspecific interactions that can induce forces high enough to repel the cell far from the substrate (>100 nm). It is therefore important to note that most of the fluorescence techniques previously cited have an axial working range limited to 100–150 nm. To conclude on benefits of vaTIRFM, this approach can be easily implemented on any TIRF microscope, as the experimental setup offers a fine control of the light beam incident angle. The evanescent wave created at the glass-medium interface by total internal reflection is characterized by an exponential decay of the electric field with the distance z from the interface (23). The penetration depth of the evanescent wave is typically a few hundred nanometers. Thereby, only the dye molecules close to the interface will be excited. Consequently in TIRFM, only a small thickness of the ventral part of the cell body will be illuminated, as illustrated in Fig. 1. This point is important for long time observations of motile cells, because evanescent excitation limits significantly the photodamage of all the specimen. In fact, this is one of the reasons why, nowadays, TIRFM is widely used by biologists to observe focal adhesion zones and localize those specific events in the (x,y)-plane in regards to the cell morphology (8). As we previously explained, quantitative interpretation of TIRF picture regarding the

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FIGURE 1 Schematic drawing of an adherent cell spreads on a glass substrate illuminated by evanescent waves (the incident angle q is greater than the critical angle qv). (Inset) The plasma membrane is labeled with DiO molecules. The value z0 is the distance from the substrate to the membrane. To see this figure in color, go online.

distance z0 between a stained membrane and the substrate (Fig. 1) is not trivial (24). Indeed, the contrast of TIRF images depends on several parameters more or less well known, such as the local concentration of dyes, their orientation, and consequences on their absorption cross section and angular emission pattern (25). The strategy to get around this problem is to exploit a series of TIRF pictures recorded at different incident angles in evanescent regime, as proposed in vaTIRFM. This technique was introduced for the first time by Lanni et al. (21) and Gingell et al. (26) in 1985. In the middle of the 1990s, two noteworthy studies proposed, for the first time a quantification of the membrane/substrate distance on focal adhesion zones (22), and a map of these distances providing the topography of cells above a substrate (27). More recently, vaTIRFM was used to measure the axial motion of secretory-granule in the ventral side of living cells (28) and to reveal the influence of 5-aminolevulinic acid on the adhesion of tumor cells (29). The shared characteristic of all these vaTIRFM experiments, which also constitutes their major drawback, is that a prism is employed to produce the evanescent wave. The microscope objective is then automatically mounted at the opposite side of the sample to collect the signal, and the fluorescence image of the ventral membrane is obtained through the cell body. By this method, however, the image quality is not good enough to observe the plasma membrane in detail. To address this issue, a prismless approach in TIRFM has been proposed (30). Indeed, a prismless setup based on an inverted microscope equipped with a high numerical aperture (NA) objective (NA > 1.4), gives pictures with the full resolution defined by the

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NA. In this configuration, the objective was used to create the evanescent excitation and to collect the signal. With the prismless setup, it is also much easier to install and develop optical systems to tune the light beam incident angle. Boulanger et al. (31) demonstrates the great capability provided by a prismless setup employed in vaTIRFM to image, with a high resolution, the cortical actin network. We propose in this article an updated version of vaTIRFM, including a convenient prismless setup and an improvement of data processing of TIRF images. Our custom microscope only uses a rotatable mirror to precisely and quickly adjust the focused laser beam on the back focal plane (BFP) of the objective. No azimuthal scanning of the laser beam in the BFP (as it is performed in Boulanger et al. (31)) is needed with our setup, which is a great advantage regarding data acquisition. Moreover, we have developed a complete theory based on the scalar treatment of incoherent image formation, to take into account the parameters that influence the contrast of TIRF images. Furthermore, an original data processing is proposed to eliminate all the unknown parameters previously mentioned, thus allowing us to extract easily the membrane/substrate separation distance z0 from fluorescently labeled cell membranes. As a result, a series of TIRF images recorded at different incident angles enables us to calculate z0 over the entire ventral part of the cell, thus allowing us to reconstruct the cell topography with a nanometric accuracy. Finally, we will highlight the benefits of vaTIRFM to investigate cellular adhesion in the case of MDA-MB-231 motile cells, in adhesion on glass substrate coated with a thin layer of fibronectin, a well-known protein that gives rise to specific adhesion.

MATERIALS AND METHODS Microscope To accurately control the incident angle of the laser beam, we developed our own setup (see Fig. 2; a more detailed optical setup is given in Fig. S1 in the Supporting Material). The most significant part of the setup is a mirror (M, Fig. 2) mounted onto a motorized rotation stage outside the microscope. It allows us to adjust the incident angle q at the glass-water interface by tilting the mirror by an angle a. The working range is from 0 (epi-illumination mode) to the maximum angle q z 72 given by the numerical aperture of the objective (PlanApoN 60, NA ¼ 1.45; Olympus, Melville, NY). The calibration procedure required to establish the magnification relationship between a and q is detailed in a previous publication (32). The angle a can be continuously tuned with an accuracy of 51  104 degrees (PRS-110; PI Micos, Eschbach, Germany). In epi-fluorescence, the laser beam at 488 nm (Sapphire 488– 200 mW; Coherent, Santa Clara, CA) is redirected onto the sample with a dichroic mirror (DM) and focused with an appropriate lens (L1) on the center of the BFP of the objective. The illumination area of the sample is very large, allowing us to simultaneously observe several cells. The lateral waist of the excitation profile uL is ~120 mm (see Fig. S2 for more details). To avoid a maximum of aberrations, the rotatable

Variable-Angle TIRF Microscopy 10 mg/mL (phosphate buffer solution at pH ¼ 7.2) during 1 h. Fibronectin proteins are physisorbed as a result of electrostatic interactions between silanol and their amine groups. Finally, to remove the nonabsorbed fibronectin on SiOH surfaces, coverslips were rinsed with ultra-pure water and dried with argon gas. The fibronectin-coated coverslips were then characterized with contact angle measurement to ensure the homogeneity of the layer. Water contact angles were measured under ambient atmosphere at room temperature by using the sessile drop method and an image analysis of the drop profile (OCA15EC system; Data Physics, San Jose, CA). As expected, SiOH surfaces are hydrophilic, with a contact angle qs (see Fig. S5 for more details). After measurements on numerous MDA-MB-231 cells in adhesion on fibronectin, we have chosen qs ¼ 63.6 as the lowest value of the incident angle suitable for collecting TIRF images. So, for qRqs, only the fluorescence signal emitted from the ventral side of the cell membrane is collected. Consequently, the fluorescence signal recorded at the pixel ðxd ; yd Þ of the camera is given by Eq. 6. Furthermore, even if the theoretical maximum angle achievable with our oil objective is z72 , significant defects were observed on TIRF pictures obtained for q > 68 . This is the main reason why we have decided to stop the vaTIRF measurements at qz 67.5 . In Eq. 9, the fluorescence signal fd ðxd ; yd ; qi ; z0 Þ is normalized by the irradiance correction factor ðgðqi Þ=gðq1 ÞÞ. This factor takes into account the variation of the laser intensity at the glass/medium interface according to the incidence angle. As previously explained for s-polarized light, this correction factor is equal to ðcos2 ðqi Þ=cos2 ðq1 ÞÞ. Thus, it does not depend on any refractive indices. In other words, ðgðqi Þ=gðq1 ÞÞ factors can be obtained experimentally on a simple interface, which separates two homogeneous media such as glass/water interface. This requires us to observe the signal emitted by a monolayer of randomly oriented fluorescent species fixed on the

Z Z I0 dxs dys cðxd ; yd ; z0 Þ ¼ hd ðz0 Þsabs ðz0 Þff ðz0 Þ c0 hnL 2ðxs2 þy2s Þ  u2L e PSFdet ðxd  xs ; yd  ys ; 0Þ:

(7) VaTIRFM takes advantage of dependence of the attenuation length k on the incident angle q (Eq. 3). By gradually increasing the incident angle, a series of TIRF images (for example, 10 images) for different attenuation lengths is recorded. As we will demonstrate, these stacks of images are then used to calculate the separating distance z0 between the fluorescent plane and the interface. The fluorescence signals recorded at the pixel ðxd ; yd Þ of the camera, for different incident angle qi > qc (qc the critical angle), with sinqc ¼ neff =ng and q1 < q2 < q3 . < q10 , are:

fd ðxd ; yd ; q1 ; z0 Þzcðxd ; yd ; z0 Þ gðq1 Þ e fd ðxd ; yd ; q2 ; z0 Þzcðxd ; yd ; z0 Þ gðq2 Þ e





z0 kðq1 Þ ;

z0 kðq2 Þ ;

fd ðxd ; yd ; q10 ; z0 Þzcðxd ; yd ; z0 Þ gðq10 Þ e



etc:

(8)

z0 kðq10 Þ :

Taking the natural logarithm of the expressions in Eq. 8 after easy rearrangement yields the following new expressions:

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interface, as previously proposed in the literature (24,32). This kind of sample can be obtained by spincoating on the glass coverslip a thin PMMA film doped with quantum dots (QDs). The value gðqi Þ was obtained just by measuring the photoluminescence of the QD layer, because the QDs were excited with a very low laser power (far from any saturation process). After 10 repeated measurements at different incident angles, we calculated the mean values of ðgðqi Þ=gðq1 ÞÞ with the error Dðgðqi Þ=gðq1 ÞÞ, provided by the standard deviation. As expected, the mean experimental values of the irradiance correction factors are similar to the theoretical ones (see Fig. S6). All the results presented in this section were obtained for an s-polarized incident light beam. The (x,y)-profile of the laser illumination was large enough to fill the CMOS detector used in our experiment (Fig. S2). The waist uL of this Gaussian (x,y)-profile was measured to be ~120 mm (Eq. 4). The laser irradiance in epi-fluorescence, i.e., for q ¼ 0, was fixed to 5 W/cm2. Hence the light irradiation

in TIRFM was typically 10–20 W/cm2, because g is typically comprised between 2.2 and 3.6 in our experiment. To limit cell exposure, and so the photodamage of the specimen, each TIRF image was typically recorded in 25 or 100 ms. With such laser irradiance and at this acquisition rate, dye photobleaching does not affect the data analysis, as this process only becomes visible after a few seconds of continuous excitation (see Fig. S7). vaTIRFM is based on the recording of a series of several TIRF images on the same area of the sample, by gradually increasing the incident angle q. As we will demonstrate in this section, only 10 different TIRF images are needed. The incident angle q was then incremented by 0.4 , starting from 63.6 to 67.2 . Using this method, the total acquisition time for one vaTIRF run is typically in the range of ~250 ms to ~1 s (the rotational speed of the mirror is very fast, only a few milliseconds for each step of 0.4 ). Fig. 4 A shows a typical vaTIRF acquisition obtained for a MDA-MB-231 cell in adhesion on a coverslip coated with a

FIGURE 4 (A) vaTIRFM images of the same cell (scale bar ¼ 20 mm.). The incident angles are indicated on the images and the acquisition rate of each TIRF image was 100 ms. (B and C) Data processing on the pixel (xd ¼ 267, yd ¼ 171) of the vaTIRFM images presented in (A). These data were fitted according to Eq. 10 for plot (B) and Eq. 11 for plot (C). After the fitting procedure, we obtained neff ¼ 1:37050:002 and z0 ¼ ð80516Þ nm from data plotted in (B), and z0 ¼ ð80510Þ nm from data plotted in (C).

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Variable-Angle TIRF Microscopy

thin layer of fibronectin. Increasing the incident angle q has a major effect on the TIRF images. The fluorescence signal in each pixel diminishes together with the laser irradiance gðqÞ on the glass/medium interface, as predicted by Eq. 6, demonstrating the relevance of the normalization procedure according to the irradiance correction factor ðgðqi Þ=gðq1 ÞÞ. Before data processing, the background signal has to be subtracted to the raw data. Therefore, mean background images were obtained for the same laser power and the same incident angles after taking the cells out of the field of view. The first source of the background signal is the dark noise of the CMOS camera, which is ~100 counts per pixel, whatever the acquisition time. Next, an additional nonconstant background will appear for acquisition time higher than a few milliseconds. This second one is related to the Raman scattering of water and glass substrate, and more significantly, to the autofluorescence of FBS. This second source of background depends on the laser (x,y)-profile and q, and it is typically comprised between 50 and 120 counts per pixel for an acquisition time of 100 ms. On the contrary, the fluorescence signal recorded in TIRF on living cells is significantly more important, typically a few thousand counts per pixel (of course this value may change from one cell to another). Although the signal/noise is quite good in our experiment, background subtraction is crucial in data processing. Assuming that the detected fluorescence signal is related to DiO molecules located in the ventral part of the cell membrane, as illustrated in Fig. 1, the membrane/substrate distance z0 can be calculated as theoretically proposed. Image processing and analysis routines were developed with IGOR Pro (WaveMetrics, Lake Oswego, OR). First, the background is subtracted on all vaTIRFM images. Next, z0 is determined pixel by pixel, according to a dual signal thresholding defined on the first image of the series (i.e., for q ¼ q1 ). The first threshold corresponds to fd ðxd ; yd ; q1 Þ > fdmin , allowing us thereafter to evaluate z0 only on the contact region of cell, because it is not relevant to calculate z0 outside the cell. The second threshold permits us to remove the few bright spots appearing on vaTIRFM images, such as those that arise in the center of the cell in Fig. 4 A, which may produce some artifacts. It corresponds to fd ðxd ; yd ; q1 Þ < fdmax . Even though our cell labeling method is optimal, it is quite normal to observe bright spots related to a probable local bending of the membrane appearing during endocytosis or a membrane budding during exocytosis process, or just dye aggregation. Hence, when fdmin < fd ðxd ; yd ; q1 Þ < fdmax , lnðfd ðxd ; yd ; qi ; z0 Þ=ðgðqi Þ=gðq1 ÞÞÞ is firstly plotted with respect to sinðqi Þ (Fig. 4 B). According to the theory proposed in the previous section, these data were then fitted with the following function: fd ðxd ; yd ; qi ; z0 Þ 4p qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ¼ U  z0 ln n2g sin2 ðqi Þ  n2eff ; (10) gðqi Þ=gðq1 Þ lL

where U ¼ ln½cðxd ; yd ; z0 Þgðq1 Þ. Thus one can extract the values of z0 and neff in each pixel of the image, as in the example shown in Fig. 4 B. Nevertheless, as this fitting procedure includes three free-parameters (U, z0 , and neff ), it is not possible to determine all these parameters with a high accuracy. Investigations on many different cells have revealed that the distance z0 cannot be assessed with a good precision, whereas the accuracy of neff is excellent. So, to improve the precision on z0 , denoted Dz0 , we have implemented a second fitting procedure by fixing neff to its value just obtained. Therefore the second fitting function will be: ln

fd ðxd ; yd ; qi ; z0 Þ z0 ¼ U : gðqi Þ=gðq1 Þ kðqi Þ

(11)

The slope of lnðfd ðxd ; yd ; qi ; z0 Þ=ðgðqi Þ=gðq1 ÞÞÞ with respect to ð1=kðqi ÞÞ yields the membrane/substrate separation distance z0 with an optimal accuracy Dz0 (Fig. 4 C). After this second fit, the z0 values are slightly modified; only the accuracy Dz0 is improved, as highlighted in Fig. S8. Finally, by this way, i.e., two successive fits in each pixel where fdmin < fd ðxd ; yd ; q1 Þ < fdmax , one can obtain the distance z0 from the interface to the membrane over the whole contact area, as represented in Fig. 5 A. This reconstructed image represents the cell surface topography above the glass coverslip coated with fibronectin. As given in Fig. 4, B and C, a weighted fit of the data was performed according to the least-squares method. The absolute error of lnðfd ðxd ; yd ; qi ; z0 Þ=ðgðqi Þ=gðq1 ÞÞÞ is simply the sum of the relative error of the irradiance correction factor ðDðgðqi Þ=gðq1 ÞÞ=ðgðqi Þ=gðq1 ÞÞÞ and the relative error of the fluorescence signal ðDfd ðxd ; yd ; qi ; z0 Þ=fd ðxd ; yd ; qi ; z0 ÞÞ. Instead of a repetitive measurement at the same incident angle, we propose an alternative way to evaluate Dfd ðxd ; yd ; qi ; z0 Þ. In fact, a diffraction-limited spot is typically included in at least a (33) pixels square (the actual size of one pixel is ~0.11 mm). This implies that the fluorescence signal between two adjacent pixels must be relatively close due to the diffraction. Hence Dfd ðxd ; yd ; qi ; z0 Þ can be roughly obtained by calculating the mean absolute difference value between the fluorescence signal in pixel ðxd ; yd Þ and its eight nearest neighbors ðxd þ 1; yd Þ, ðxd þ 1; yd þ 1Þ, ðxd ; yd þ 1Þ, ðxd  1; yd þ 1Þ, etc. Fig. 5 shows maps of z0 -distances and neff , which correspond to the vaTIRFM measurements presented in Fig. 4. A map of the error Dz0 is also plotted, as well as the histograms of the z0 and Dz0 values. To present a different case of cell adhesion, an additional example of vaTIRFM investigation recorded on another cell is presented in Fig. 6. One can recognize in Figs. 5 and 6 the typical morphology of motile cells, characterized by a teardrop shape and a large membrane protrusion (called the lamellipodium) appearing at the cell front. Such morphology is usually observed on surfaces coated with extracellular matrix proteins, such as collagen or fibronectin, or other substrates that promote

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FIGURE 5 Data processing of the vaTIRFM images presented in Fig. 4: z0 image (A) and the corresponding distance histogram (B), Dz0 image (C), and the error histogram (D), neff image (E). From image (A), one can calculate the mean membrane/substrate distance hz0 i ¼ 143 nm and the standard deviation sz0 ¼ 35 nm. From image (C), one can also calculate the mean z0 error hDz0 i ¼ 13 nm and the standard deviation sDz0 ¼ 8 nm. Scale bar ¼ 20 mm. (A) The red arrow indicates the direction of migration. To see this figure in color, go online.

cell migration (1,6). The direction of migration, as well as the front and the rear of the cell, are indicated in Figs. 5 A and 6 B. Cell surface topography appears on Figs. 5 A and 6 B. As expected, cells do not make a flat contact on a glass substrate coated with fibronectin, but display numerous discrete close contacts that appear primarily at the front and the rear of the cells (see the dark blue regions that correspond to z0 < 50 nm). Moreover, the histograms of z0 distances (Figs. 5 B and 6 C), clearly reveal that most of the cell membrane is located between 100 and 200 nm, as previously reported in Lassalle et al. (29). Many different types of information can be extracted from z0 images. The first interesting parameter is the mean distance that separates the cell membrane from the substrate, denoted hz0 i. We studied 10 different MDA-MB-231 cells on fibronectin, and we obtained an averaged mean value hz0 i ¼ 137 nm, according to a standard deviation between each cell shz0 i ¼ 13 nm, which means that membrane/substrate distances will not change drastically between cells. More interestingly, one can also proceed to local measurements on the tight adhesion zones, such as those numbered in Figs. 5 A and 6 B. The characteristics of these close contacts are given in Table 1. We measured a mean membrane/substrate distance comprised between 30 and 45 nm in these regions. It should be noted that the effective refractive index neff is also the highest on these tight adhesion areas (typically ~1.37) (Figs. 5 E and 6 D). This implies that the local cytoplasmic refractive index ncyto in these regions is slightly higher than 1.37, as indicated by Fig. 3 C. As a result, these close adhesion zones

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pointed out in Figs. 5 A and 6 B are probably specific adhesion zones, namely old and nascent focal adhesion zones mediated by integrins. The first reason that might validate this claim is the close proximity of the cell membrane above the substrate. Indeed, previous experimental studies have revealed that the typical membrane/substrate distance on focal adhesion regions is typically 25–50 nm (7,22). The second reason is that MDA-MB-231 cells exhibit receptors (av b1 and a5 b1 integrins) that specifically recognize fibronectin (40–42). Thereby, focal adhesion at the rear and at the front of MDA-MB-231 cells should be expected on fibronectin. Furthermore, the functional unit of focal contacts includes a lot of intracellular proteins (FAK, vinculin, talin, actin, etc.) (1,7). This gives rise to a significant increase of the local ncyto , as measured in Bereiter-Hahn et al. (37). Next, the presence of extracellular components such as glycocalyx on adhesion plaques will also influence the effective refractive index. Thus, neff needs to be higher on focal adhesion zones. In other words, focal adhesion regions should appear where the plasma membrane closely approaches the substrate (i.e., z0 ( 50 nm) and the effective refractive index is high (i.e., neff T 1.37). This approach to localize focal adhesion regions by taking into account the cell/substrate distance and the cytoplasmic refractive index, is not new in the literature. In fact, this is the basis of interference reflection microscopy and RICM images analysis to recognize cell/substrate attachments (37,43). However, it should be interesting to identify integrin-based focal contacts on Figs. 5 and 6, to confirm the role of integrin av b1 . This requires us to implement a second source of light on our setup

Variable-Angle TIRF Microscopy

FIGURE 6 (A) TIRFM image for q1 ¼ 63.6 (acquisition rate ¼ 100 ms). (B–F) Data processing of the vaTIRFM images: z0 image (B) and the corresponding distance histogram (C), neff image (D), Dz0 image (E), and the corresponding histogram (F). From image (B), the mean membrane/substrate distance is hz0 i ¼ 120 nm and the standard deviation is sz0 ¼ 42 nm. From image (E), the mean z0 error is hDz0 i ¼ 13 nm and the standard deviation is sDz0 ¼ 5 nm. Scale bar ¼ 20 mm. (B) The red arrow indicates the direction of migration. To see this figure in color, go online.

to selectively excite another fluorescent molecule linked specifically to integrins. Such types of investigations are behind the scope of this article, which is rather devoted to show the feasibility and the reliability of our technique. Regarding the error Dz0 (see Figs. 5, C and D, and 6, E and F), the error distribution is very narrow and Dz0 is typically comprised between 5 and 20 nm, with a mean value hDz0 i z 15 nm. To confirm that the axial precision of our technique is typically 10–20 nm, vaTIRFM was used on two different control samples. One easy way to characterize the axial resolution of any imaging technique is to study its response to a uniform thin planar object. For this purpose, we simply used a monolayer of QDs fixed at a glass/water interface. This sample was also applied to calibrate the incident angle (32) and to determine the illumination (x,y)-pro-

file (Figs. S2 and S4). This QD monolayer (which is precisely located at the interface, i.e., z0 ¼ 0) was detected at hz0 i ¼ 2 nm, with a standard deviation sz0 ¼ 15 nm. As a result, the axial instrumental response of vaTIRFM was typically ~15 nm. We have also examined the height profile of a lipid membrane around adhesion patches appearing when biotinylated vesicles encounter a streptavidin-coated substrate. In this case, adhesion process is related to the specific binding between biotin proteins present on the lipid membrane and streptavidin fixed on the coverslip, as illustrated in Fig. S9. More details about vesicle and surface preparation were given in a previous publication (44). As previously depicted, the specific recognition between biotin and streptavidin will give rise to adhesion patches that clearly appear on vaTIRFM image in Fig. S9 (44). The axial

Biophysical Journal 111, 1316–1327, September 20, 2016 1325

Cardoso Dos Santos et al. TABLE 1 Membrane/Substrate Distance Evaluation on Some Close Contacts Region

hz0 i (nm)

sz0 (nm)

1 2 3 1 2 3

35 33 40 33 37 43

8 9 8 11 9 10

Fig. 5 A

Fig. 6 B

Regions 1, 2, and 3 are shown in Figs. 5 A and 6 B. The value hz0 i is the mean membrane/substrate distance observed in each region. The value sz0 corresponds to the fluctuation of the axial position of the membrane in the same region.

profile plotted in Fig. S9 reveals the contour of the lipid membrane around a small adhesion patch. The height between the free membrane and the one linked to the substrate was ~25 nm, which gives experimental evidence that the axial resolution of vaTIRFM is at least 25 nm. This is quite similar to the axial resolution achieved with other superresolution techniques, such as interferometric PALM (7), supercritical-angle STORM (16), or metal-induced energy transfer microscopy (15). As previously explained, z0 cannot be estimated properly on the edge of the cell, because the membrane is curved and we excite simultaneously the dorsal and ventral sides of the cell. As a result, the error Dz0 is maximum along the contour of the cell and on filopodia (see Figs. 5 C and 6 E). CONCLUSIONS We propose in this article a new strategy, to our knowledge, to manage variable-angle TIRF microscopy, to explore quantitatively the adhesion of living cells. By observing only the cell membrane in contact with the substrate, we have demonstrated that a series of 10 TIRF images recorded for different incident angles is useful to reconstruct the topography of motile cells with a nanometric axial resolution. The extreme axial resolution achievable with our nondestructive method, 10–20 nm, is remarkable and well adapted to quantify precisely cell adhesion processes. Compared to previous approaches, we proposed several new, to our knowledge, strategies that yield an easier-touse vaTIRFM. First, we introduced a new straightforward prismless setup that offers a fine control of the incident angle, with no distortion of the illumination. Moreover, we developed a complete theory that proposes new, to our knowledge, data processing to restore the cell topography. We have notably shown that it does not require a perfect knowledge of the refractive indices of all the layers that compose a cell in adhesion. Only an effective index is required. The value neff was also precisely determined, as well as the membrane/substrate distance. Furthermore, we have shown that it is not necessary to know accurately some parameters that affect the TIRF signal, such as the absorption cross section, the detection efficiency, and the

1326 Biophysical Journal 111, 1316–1327, September 20, 2016

quantum yield, commonly related to the dye orientation and its distance from the substrate. By monitoring the distance z0 from the substrate to the cell membrane together with the effective refractive index neff , it appeared possible to localize the focal adhesion zones without any specific labeling of proteins involved in the focal adhesion units. Moreover, the long axial working range of vaTIRFM (300–400 nm) is well suited to probe nonspecific interactions—for example, steric repulsion induced by a membrane component such as the glycocalyx. More interestingly, vaTIRFM enables us to follow the dynamic of adhesion during the displacement of the cell above the substrate (see Movie S1 in the Supporting Material). One can observe, in this movie, the singular localization of close contacts in time, especially when the rear of the cell is retracted. The distance distribution is also clearly affected during the cell motion. This movie highlights the real opportunities offered by vaTIRFM to examine cell-substrate interactions, for example to follow attachment/detachment kinetics on various functionalized substrates. After a relevant improvement of the theoretical description, vaTIRFM can be also extended to observe other biological structures such as the actin cortex. SUPPORTING MATERIAL Nine figures and one movie are available at http://www.biophysj.org/ biophysj/supplemental/S0006-3495(16)30613-0.

AUTHOR CONTRIBUTIONS M.C.D.S. designed the TIRF setup and performed vaTIRF measurements on MDA-MB-231 cells; R.J. designed the TIRF setup, supervised the experiments, developed the vaTIRFM theory and the data processing, and wrote the article; C.V. developed the data processing routine on IGOR Pro software and co-supervised the experiments; and R.D. developed the vaTIRF acquisition software that controlled the rotation stage and the camera.

ACKNOWLEDGMENTS The authors thank Hamid Morjani for providing MDA-MB-231 cells, Martin Oheim for fruitful discussions, and Christophe Couteau for his careful reading of this article. This work was supported by the Conseil Re´gional Champagne-Ardenne, the Fonds Europe´en de De´veloppement Re´gional: CELLnanoFLUO project, and the Ligue Contre le Cancer (Comite´ de l’Aube).

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Topography of Cells Revealed by Variable-Angle Total Internal Reflection Fluorescence Microscopy.

We propose an improved version of variable-angle total internal reflection fluorescence microscopy (vaTIRFM) adapted to modern TIRF setup. This techni...
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