Correlative Stimulated Emission Depletion and Scanning Ion

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Correlative Stimulated Emission Depletion and Scanning Ion Conductance Microscopy Philipp Hagemann, Astrid Gesper, and Patrick Happel ACS Nano, Just Accepted Manuscript • DOI: 10.1021/acsnano.8b01731 • Publication Date (Web): 23 May 2018 Downloaded from http://pubs.acs.org on May 23, 2018

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Correlative Stimulated Emission Depletion and Scanning Ion Conductance Microscopy Philipp Hagemann,†,‡ Astrid Gesper,†,‡ and Patrick Happel∗,† †Nanoscopy Group, RUBION, Ruhr-Universität Bochum, Universitätsstraße 150, D-44801, Bochum, Germany ‡Contributed equally to this work E-mail: [email protected] Abstract

Correlation microscopy combining fluorescence and scanning probe or electron microscopy is limited to fixed samples due to the sample preparation and nonphysiological imaging conditions required by most probe or electron microscopy techniques. Among the few scanning probe techniques that allow imaging of living cells under physiological conditions, Scanning Ion Conductance Microscopy (SICM) has been shown to be the technique which minimizes the impact on the investigated sample. However, combinations of SICM and fluorescence microscopy suffered from the mismatch in resolution due to the limited resolution of conventional light microscopy. In the last years, the diffraction limit of light microscopy has been circumvented by various techniques, one of which is Stimulated Emission Depletion (STED) microscopy. Here, we aimed at demonstrating the combination of STED and a SICM. We show that both methods allow to record living cellular specimen and provide a SICM and STED image of the same sample, which allowed us to correlate the 1

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membrane surface topography and the distribution of the cytoskeletal protein actin. Our proof-of-concept study exemplifies the benefit of correlating SICM with a sub-diffraction fluorescence method and might form the basis for the development of a combined instrument which would allow the simultaneous recording of subdiffraction fluorescence and topography information. Keywords: Super-Resolution Microscopy; Nanoscopy; Stimulated Emission Depletion (STED) Microscopy; Scanning Ion Conductance Microscopy (SICM); Correlative Microscopy Correlative microscopy (CM) is the – subsequent or simultaneous – imaging of the same region of a sample with two different microscopy methods. The major advantage of CM is that it provides complementary information of the sample which is not accessible by a single technique. 1,2 For example, transmission electron microscopy provides high-resolution information about the electron density of a sample, but does not allow to identify a specific protein of interest. In contrast, confocal fluorescence microscopy allows tagging and thus identifying a protein of interest, but neither provides information about its environment nor sub-diffraction resolution. The latter has been overcome by the development of superresolution fluorescence microscopy techniques, 3–5 which have been used to correlate electron microscopy and sub-diffraction fluorescence data. 6,7 However, the investigation of the relation between structure and function in a cellular sample requires the quantification of the structural changes that occur in a cell over time, which in turn requires to image living cells. This, however, cannot be achieved by electron microscopy. While the information gathered by transmission electron microscopy cannot be recorded with another technique, the information obtained by scanning electron microscopy can also be determined by other scanning probe techniques, two of which allow imaging living cells: Atomic Force Microscopy (AFM) 8 and Scanning Ion Conductance Microscopy (SICM) 9 and thus are promising candidates to be combined with super-resolution microscopy. 2


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AFM has been combined with STED microscopy 10 and has been used to manipulate single nanoparticles 11 as well as to image migrating astrocytes and to correlate the Young’s modulus of the cells with their cytoskeleton. 12 Furthermore, AFM has been combined with stochastical fluorescence super-resolution techniques. 13,14 A detailed review of the applications of correlated AFM and super-resolution fluorescence microscopy has been published recently. 15 However, AFM has been found to bias cellular samples more than SICM. 16 The nearly contact free operating principle of SICM, 9 operated in a mode where the scanning tip is advanced to the sample at every single pixel and subsequently withdrawn before lateral movement to avoid probe sample collisions 17–19 (see also Figure 1E), allowed SICM to, for example, determine the volume changes during the migration of neural cells. 20–22 Hitherto, no combined recordings of SICM and any fluorescence super-resolution technique have been reported, but direct Stochastic Optical Reconstruction Microscopy (dSTORM) has been used to quantify the number of fluorescent molecules deposited by a SICM tip onto a surface. 23 However, SICM has been combined with conventional confocal fluorescence microscopy. 24 Recently, such an instrument has been used to investigate the changes in the cell membrane structure during the endocytosis of nanoparticles, 25 supporting a previously suggested, alternative mechanism of clathrin-based endocytosis. 26 SICM is, due to the pixel-wise mapping scheme, different from most scanning probe and scanning fluorescence microscopy methods, which are mostly operated line-by-line. Since the pixel-based mapping is much slower than line-based scanning, a putative combined instrument would have to be controlled by the SICM software, which in turn excludes the use of commercial instruments. Thus, the only option to combine STED and SICM into a single instrument is to build the combined instrument from scratch, which requires detailed experience of both imaging methods. Up to now, such an instrument has not been developed. To take a first step towards correlated sub-diffraction probe and fluorescence microscopy of living cells, here we show STED and SICM recordings of the same cellular structure. 3


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We obtained the data by first recording the STED image and subsequently recording a SICM image of the same region of the sample. The imaging conditions were the same for both recordings, although we used two different instruments. Thus, we hypothesize that a combined STED/SICM could be developed which would provide the advantages of both methods. In particular—as we also exemplify here—both methods allow recording living cellular samples, hence a combined instrument would not only allow to correlate topographic features and protein distribution with a resolution not limited by diffraction, but additionally correlate changes in the cell topography with changes in the protein distribution at diffraction-unlimited resolution.

Results and discussion STED and SICM allow imaging at sub-diffraction resolution STED exploits the physico-chemical properties of the fluorescent dye to enable imaging beyond the diffraction limit of light. 3 As an example, Figure 1Aa shows confocal (top) and STED (bottom) recordings of fluorescent nanoparticles, clearly demonstrating the effect of the improved resolution. We analyzed the profile of the fluorescence intensity of a single nanoparticle (indicated by the white triangles). The corresponding data is shown as dots in Figure 1Ab (confocal: gray, STED: blue). The solid traces indicate fits of a Gaussian (confocal, gray) and Lorentzian (STED, blue) distribution to the data. The corresponding FWHMs were 250 nm ± 24 nm (confocal) and 75 nm ± 30 nm (STED). Figure 1B shows an exemplary confocal (left) and STED (right) recording of tubulin in a fixed Vero cell. The enhanced resolution of the STED recording allows to distinguish single tubulin fibers even at locations where they form crowded networks. In contrast to STED, SICM is a scanning probe technique and thus its resolution is not limited by the diffraction of light. It uses the distance-dependence of the current i through the opening of a nanometer-sized glass pipette to register the sample surface. The current is 4


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Figure 1: Imaging at sub-diffraction resolution by STED and SICM. Aa: Confocal (top) and STED (bottom) recording of the same region of a sample of fluorescent nanoparticles. Scale bar (bottom) applies to both images. Ab: Normalized fluorescence intensity (Fn ) profiles of the single nanoparticle between the white triangles in Aa. Gray dots indicate confocal data, blue dots STED data. The gray line represents a fit of a Gaussian distribution to the confocal data, yielding a FWHM of 250 nm ± 24 nm. The blue line represents a fit of a Lorentzian distribution to the STED data, yielding a FWHM of 75 nm ± 30 nm (errors indicate 95 % confidence interval of the fits.) B: Confocal (left) and STED (right) recording of tubulin in a Vero cell, showing that due to the enhanced resolution of STED, more details can be recognized in the STED recording. Scale bar applies to both images. Blue areas indicate areas brighter than the look-up table applied here. C: Sketch of a SICM setup. D: Current-distance relation utilized by SICM, the dotted line indicates a typical set-point of 1 %. Insets illustrate the corresponding tip-sample distances. E: Scanning mode applied to avoid lateral tip-sample collisions. The pipette is withdrawn after the detection of one pixel, moved laterally and then advanced towards the sample. F: SICM image of the leading tip of a process from an oligodendrocyte progenitor cell from rat brain. Black arrow points to a lamellipodium-like structure at the end of the tip, white arrows point to filopodia.

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induced by a voltage applied between two Ag/AgCl wires, one located in the glass pipette and one in the bulk electrolyte solution that contains the sample (Figure 1C). To allow scanning the sample, the pipette can be moved in all three dimensions with respect to the sample. The current through the pipette depends on the geometry of the pipette and the electrical properties of the electrolyte solution. 27 The most important parameter for the resolution of SICM is the inner opening radius ri of the scanning pipette, since the resolution limit of a SICM has been found to be approximately 3ri . 28,29 If one summarizes the geometry of the pipette into a single parameter C and neglects surface charge and differences in sample conductance, the current-distance relation that underlies SICM imaging can be approximated 30 as −1 C . i(d) = i0 1 + d

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Here, d is the distance between pipette tip and sample surface and i0 is the current that flows if the tip is far away from the sample. As shown in Figure 1D, eq. (1) describes a curve that approaches i0 for d C and 0 for d < C. For imaging, the pipette is advanced towards the sample until the drop in current reaches a selected set-point, which is commonly in the range of 1 %. As indicated in the gray insets in Figure 1D, this corresponds to a tip-sample distance of approximately 2ri for typical scanning pipettes. SICM has been shown to be able to provide a resolution at the level of single proteins. 31 To avoid lateral probe-sample-collisions at steep sides as they occur in samples of cultured cells, SICM is commonly operated in a point-mapping manner: Instead of scanning the pipette over the sample, the pipette is retracted after a single pixel has been detected, then moved laterally and advanced again (Figure 1E). 17–19 Figure 1F shows an exemplary recording of the leading tip of a process of a fixed oligodendrocyte progenitor cell which featured a lamellipodium-like structure (black arrow) with several filopodia (white arrows) at its very end. However, the simplified approximation of the current-distance relation in SICM as given 6


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in eq. (1) is only valid under certain conditions commonly used for SICM imaging. The interaction between the ionic current through the SICM pipette and the surface is more complex 27,32 and depends on the electro-chemical properties of the surface, i.e., its charge and conductance and the bias voltage applied between the two Ag/AgCl electrodes. This dependence allows to use SICM not only for imaging, but to determine the surface charge of the scanned object 33,34 and to investigate nanometer-sized pores in the scanned surface. 35,36 Furthermore, SICM does allow to map reaction fluxes at the surface of the specimen at subdiffraction resolution. 37 For a more detailed review of the use of SICM as a multi-functional electro-chemical tool, we refer the reader to the literature. 38 If pressure is applied to the scanning pipette, the scanned sample is indented during the approach of the scanning pipette, which also results in a different current-distance relation. This can be used to determine the stiffness of the scanned object. 39

Live cell imaging with STED and SICM Since both SICM and STED recordings can be obtained under physiologic conditions, both methods are able to record living cells. We recorded five consecutive STED images of the tubulin network of a living astrocyte from rat brain (Figure 2A). The tubulin network was highly dynamic at the rims of the cell, suggesting that the cell explored its environment or grew in size to attach more stiffly to the substrate. However, the recording lacks detailed information about the cell’s shape and its topography since the cell membrane could not be traced simultaneously. Thus, it is not possible to link changes in the tubulin network to changes in the cell shape and cell topography and thus to conclude the role of tubulin during cell growth or cellular exploration of the environment. Figure 2B and C show the dynamics of the cell membrane of the tip of a living HeLa cell imaged by SICM. The cell membrane topography underwent large changes during the recording of approximately two hours, from a smooth structure with only a few extending processes (yellow arrows in Figure 2C at 0 min) to a very convoluted structure exhibiting 7


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Figure 2: Dynamics of living cells imaged by STED and SICM. A: Tubulin dynamics in a living astrocyte from rat brain imaged by STED microscopy. Arrows point at regions that underwent strong changes between two consecutive scans. Confocal counterparts of the images at 0 min and 20 min are shown in Figure S2. B, C: Changes in topography of the tip of a living HeLa cell imaged by SICM. Images in B indicate the height of each pixel according to the color scale bar, images in C indicate the height difference between two adjacent pixels in the fast scanning direction according to the gray scale bar. Scale bar in B applies to the images in C, too.

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multiple tiny processes in the second scan (28 min). During the next four scans, it returned to the smooth structure, with most of the processes disappearing. This recording, however, does not provide any information about the underlying changes in the cytoskeleton. Thus, a correlated recording of topography and fluorescence data is required.

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Figure 3: Simulated diffraction limited and sub-diffraction recordings of a hypothetical protein involved in protrusion formation. A: Zoom into a section of the topography of a tip of a HeLa cell as indicated by the white arrow in Figure 2B (28 min). Black traces indicate a putative location of a hypothetical filamentous protein involved in the formation of the membrane protrusions. B: Simulated diffraction-limited recording of the hypothetical protein with a resolution of 250 nm as experimentally obtained in Figure 1A. C: Simulated sub-diffraction with a resolution of 75 nm as experimentally obtained in Figure 1A. Scale bar in A applies to all images. If one assumes that a filamentous cytoskeletal protein is present in the tiny protrusion visible in Figure 2B and C, a correlated fluorescence and topography microscope would show a co-localization of the hypothetical protein and the protrusions. Figure 3A shows a section of the second topography recording in Figure 2B (indicated by the white arrow in the corresponding image at 28 min). We manually added one conceivable distribution of the hypothetical cytoskeletal protein (black traces in Figure 3A) and computed the images that would be formed if this protein would be recorded by diffraction limited confocal microscopy with a resolution of 250 nm (Figure 3B, the resolution corresponds to the experimental confocal resolution obtained in Figure 1A) or with a sub-diffraction resolution of 75 nm (Figure 3C, resolution corresponds to the experimental resolution of the STED image in Figure 1A). Clearly, the analysis of the putative protein would benefit from the improved resolution. While in the calculated diffraction limited recording (Figure 3B), the protein distribution appears as a single, blurred spot, the single filaments can be easily resolved in the computed sub-diffraction recording (Figure 3C).

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Figure 4: Correlative STED and SICM recording. A: SICM recording of fixed HeLa cells. Aa depicts the color coded height, Ab the gray coded height difference of adjacent pixels. Scale bar in Aa applies to the image in Ab, too. B shows a cropped and rotated confocal (Ba) and STED (Bb) recording of fluorescently labeled actin in the same region of the sample. Scale bar in Ba is the same as in A and applies to Bb as well. C indicates the relative positions of the SICM (yellow rectangle) and confocal/STED (gray rectangle) relative to each other. D: Magnification of the STED (Da), confocal (Db) recording and the color coded height (Dd) and gray coded height difference (De) representations of SICM recording of the region indicated by the white arrowhead in Aa. Df, Dg: Overlays of the STED recording with the two representations of the SICM recording, with black pixels made transparent in the fluorescence recordings. Dc: Height profile of the protrusion along the dotted line in Dd. Scale bar in Dd applies to all images in this panel. We then recorded a SICM (Figure 4A), a confocal and a STED (Figure 4B) image of the same region of a sample of fixed HeLa cells with fluorescently labeled actin. The recordings were performed on different instruments, the corresponding images are shifted and rotated with respect to each other as indicated in Figure 4C. The yellow frame represents the SICM image, the gray frame the confocal/STED image. We observed very different cell topographies in the SICM recording. In the upper right part of the image (magenta arrows in Figure 4A and B) a roundish, high (approx. 16.4 µm) 10


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cell was located. Except for some faint, dot-like structures (magenta arrowheads in Figure 4B), no actin signal was detected in the inner part of this cell. In contrast, numerous hair-like protrusions with an approximate length of 2 µm extended from the cell’s border. These structures were less pronounced in the topography recording, but, as clearly visible in the height difference representation of the SICM data (Figure 4Ab), the cell surface featured numerous tiny, hair-like protrusions. The corresponding roughness of the cell surface was 122 nm ± 50 nm (n = 12377 pixels, mean ± standard deviation, Figure 5, cell “a”). C 0.05 a d c b

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Figure 5: Roughness analysis of the surfaces of the HeLa cells shown in Figure 4. A: Roughness map of the cell surfaces. n.c.: not considered. B: Labeling (a–d) of the cells for panels C and D. C: Histograms of the cell surface roughness. Bin width: 7.1 nm. Lowercase letters indicate the cell as shown in B. D: Box plots of the cell surface roughness. Note that due to the large amounts of pixel contributing to the statistics (n = 12377; 38883; 5909; 13187, respectively) all means are significantly different from each other with p-values below 10−9 (Anova followed by Tukey-Kramer post-hoc test). The white arrow points to a section of the sample where the hair-like protrusions of the roundish cell (magenta arrows in Figure 4A and B) seem to touch the elongated, neighbouring cell (marked by the yellow arrows in Figure 4A and B) in the fluorescence recordings. This was not observed in the corresponding section of the SICM recording. Most likely, in this area, the roundish cell had a overhanging membrane and the elongated cell is located underneath the roundish one. The height difference, however, was not large enough to be filtered by the confocal pinhole, thus both structures appear in the fluorescence recordings. The scanning pipette of SICM here, most likely, slightly pushed the overhanging membrane structure to the side before the current drop reached the threshold. Thus, the pipette 11


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imaged the elongated cell and the cell culture dish underneath the overhanging structure. This phenomenon has been described and explained earlier 30,40,41 and is a well-known inaccuracy of SICM. In contrast to the roundish cell, the elongated cell exhibited several long stress fibres spanning from the highest region (maximum height 6.49 µm) of the cell, putatively the position of the nucleus, to the cell’s tips (yellow arrowheads in Figure 4B). In addition, the cell surface was much smoother than the surface of the roundish cell (average roughness 77 nm ± 50 nm, n = 38883 pixels, Figure 5, cell “b”). The third cell visible in the recordings (labeled by orange arrows in Figure 4A and by cyan arrows in Figure 4B) again had a more roundish shape. However, in contrast to the roundish cell described previously, this cell was located between three rather elongated cells, as can be seen in the SICM recordings (Figure 4A). This cell showed two interesting properties: First, it was the cell with the highest average cell surface roughness (110 nm ± 63 nm, n = 13187 pixels Figure 5, cell “c”) in the scan. Note that the high membrane roughness was predominantly located at the borders of the cell, while the central, highest section only had a small roughness (Figure 5A). Second, it showed two very different actin structures: The first ones were fan-shaped structures with various protrusions as known from lamellipodia and filopodia (white and cyan arrows with dotted end in Figure 4B). We could only find a few, smaller topographic features that correspond to fan-like structures in the actin recordings (black arrowheads in Figure 4A). We thus conclude that these structures were located beneath the neighbouring cells and thus were invisible to the SICM. The second actin structure were agglomerations of actin (cyan arrow in Figure 4A) that appeared as dots in the confocal recording. Interestingly, the dot-like agglomerations turned out to consist of ring-like structures in the STED recording, which in some cases featured a central dot (cyan circle in Figure 4B). Note that, apart from one exception, we could not correlate these actin structures to topographical features. However, Figure 4Da shows a magnification of the STED recording 12


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of the section of the sample labeled by the white arrowheads in Figure 4A and B. STED revealed that the agglomerations of actin, which appeared dot-like in the confocal recording (Figure 4Db), consist of ring-like structures with, in this case, two central dots (black arrowheads in Figure 4Da). Figure 4Dd and De show the corresponding height and height difference representations of the SICM data, and Df and De show overlays of the STED and the SICM data. The actin structure is located in a thicker (approximately 2.75 µm) section of a protrusion with a total length of approximately 4 µm. This section of the protrusion was approximately 5 µm high (Figure 4Dc). The protrusion then declined to a height of approximately 2.5 µm at its end. Interestingly, we did not observe any actin signal at the lower part of the protrusion. However, a single actin filament next to the ring-like structure (labeled by the white arrowhead in Figure 4Da) pointed towards the end of the protrusion. It remains unclear if that part of the protrusion was located outside the confocal plane or if there was no actin located in that part of the protrusion. Because we measured the STED and the SICM recordings consecutively on two different instruments, we had to fix the sample to avoid changes of the cells in the sample between the two measurements. Thus, we could not investigate whether the observed cell was attaching to or detaching from the culture dish. In turn, we can only speculate on the role of the ring-like actin structures, which, to our knowledge, have not been described before. While ring-like actin structures are well known and play a role in wound closing, cell division and cell-cell-contact stability, 42 these actin rings are much larger than the actin structures we observed here. Furthermore, actin has been found to transiently assemble in the outer mitochondrial membrane in mitochondrial fission. 43 Various interpretations are conceivable, ranging from digesting processes in apoptosis to a structure that its required to form the fan-like structures described above. However, this question can be only addressed by a combined instrument that allows to record several frames of STED and SICM data simultaneously. 13


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Conclusion and outlook We presented the correlative recording of topographical and sub-diffraction fluorescence data by SICM and STED. Our measurements allowed us to link cell membrane roughness, cell shape and height to the structure of cellular actin. We found ring-shaped actin structures that, to our knowledge, have not been described before. In some cases, these structures showed one or two central actin spots. Furthermore, in one case a ring-shaped structure was located in a cellular protrusion, although it remains unclear whether this protrusion was attaching or detaching and whether the ring-like actin structure play a role in this process. Since we recorded our data on two different instruments, we were limited to recording snapshots of the cells. This not only limits our method to fixed cells, but also restricts its usage to imaging two different z-sections of the sample. SICM images the sample surface, while STED images a confocal plane through the sample. Thus, topographical and fluorescence information of the same section is only available at locations where the sample surface crosses the plane imaged by STED, as for example in the section shown in Figure 4D. Nonetheless, we have shown in Figure 2 that both techniques allow live cell imaging under physiological conditions, but recording the dynamics of actin and the membrane simultaneously demands an instrument which combines STED and SICM recording. In principle, such an instrument could re-use the implementation of a combined SICM/confocal microscope, which would also allow surface scanning, i.e., recording STED data from the same spot in x, y and z as SICM. 24 A combined instrument would solve some obstacles that we had to hurdle here. First, it is time consuming to find the same section in a sample in two different instruments, which is why we recorded relatively large areas here. This, in turn, leads to long recording times for SICM, since one has to chose a retraction distance that allows to hurdle large height differences. We have recorded the SICM image shown in Figure 4 with an average acquisition time of approximately 5 s/µm2 . However, more flat samples allow to record SICM images with an average acquisition time of 0.125 s/µm2 with sub-diffraction resolution, 44 which 14


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allows to investigate fast physiologic processes. The technique that will limit the temporal resolution in a combined instrument will be SICM, at least if surface scanning is targeted since it would not allow for fast, resonant beam scanning, but the STED information would be recorded pixel by pixel after the surface has been detected by SICM. However, STED illumination schemes that reduce photo-bleaching such as RESCUE 45 or DyMIN 46 would still be possible, which is promising for live cell recordings. Furthermore, the manual alignment of the two recordings is prone to errors, while a combined instrument would intrinsically image the same section of the sample. However, for surface scanning, it should be noted that any lateral offset in the STED and SICM scans can impede meaningful correlated imaging. While in the subsequent usage of two instruments, an offset can be corrected, the fluorescent information that corresponds to a topographical structure is not recorded in surface scanning mode if a too large offset is present. Thus, a combined instrument will have to be aligned with a precision below the lateral resolution of the two methods. While it will be technically challenging, in our opinion, this would be the major advantage of the instrument. It would, for example, allow to investigate the distribution of any fluorescently labeled species on the cell membrane, ranging from fluorescently tagged nanoparticles to membrane proteins, at sub-diffraction resolution and allow to link this to topographic features of the cell membrane and its dynamics. Hitherto, studies on nanoparticlecell membrane-interaction and protein distribution and cell membrane topography have only been performed with diffraction limited techniques. 25,47–49 However, applying a fast beam scanning STED using an objective positioning system to change the z-position of the STED recording might allow to record a SICM image of the topography and simultaneously a STED z-stack of a structure, if the structure is not too large, such as for example the OPC tip shown in Figure 1F. Furthermore, SICM is not only a tool for topographic imaging. The use of SICM to 15


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map the surface charge, to determine the conductivity through tight junctions, or to map the cellular stiffness have all been shown on living cells, 39,50–52 the latter even in time-lapse imaging. 39,53 Since none of these techniques requires modification of the optical part of a SICM, it is conceivable to combine them with STED imaging, too, which would in turn allow to correlate surface charge, sample conductance or sample stiffness with topography and fluorescence data, all with a resolution beyond the diffraction limit.

Methods STED microscope setup The STED recordings have been performed on a setup similar to one published previously, 54 based on a 20 MHz supercontinuum laser with fixed output wavelengths for two depletion beams (ALP-710-745-SC, Fianium, Southampton, UK). A sketch of the STED setup is provided in Figure S3. For the recordings from cells shown in this study, we used the 745 nm line for depletion and selected 647 nm ± 5 nm for the excitation beam via a bandpass filter (Z647/10, Semrock, USA) after splitting the beam into its horizontally and vertically polarized components by a polarizing beam splitter (PTW 1.25, B. Halle Nachfl., Berlin Germany). For the recording of fluorescent nanoparticles, we used the 710 nm laser line for depletion and selected 572 nm ± 7.5 nm for excitation via a bandpass filter (572/15 BrightLine HC, Semrock, USA). Both depletion beams and both excitation beams were coupled into polarizations maintaining fibres to clean the beams and allow for the adjustment of the beam path lengths. After leaving the fibres, the beams were widened to approximately 1 cm and the depletion beams were send through a vortex phase plate (VPP-1a, RPC Photonics, Rochester, NY, USA) which imprinted a helical phase shift from 0 to 2π onto the beams’ wavefronts. The depletion and excitation beams were combined by a dichroic mirror (zt647 rdc, Chroma, USA) and subsequently send onto the mirrors of a Yanus beam scanner (Till Photonics, Gräfelfing, Germany), which was in turn coupled into the beam path 16


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of an iMic epifluorescence microscope (Till Photonics, Gräfelfing, Germany). The iMic was equipped with a 60× oil objective with NA = 1.49 (APON 60XOTIRF, Olympus Lifesciences, Hamburg, Germany) and a scanning stage with motorized lateral and piezo-driven vertical positioning for coarse and fine positioning, respectively (PZ 2300, ASI, Eugene, USA). Fluorescence was separated from the excitation and depletion beam by a custom-designed dichroic mirror (zt570/650/710-755, Chroma, Bellows Falls, USA). The fluorescence of different dyes was then separated by a dichroic beam splitter (zt647 rdc, Chroma, USA), and each beam of fluorescence was focused onto a pinhole of 75 µm diameter (corresponding to approximately 1 AU) and collected by an avalanche photo diode (SPCM AQRH-14-TR, Excelitas Technologies, Waltham, USA). The corresponding signals were digitized using a DAQ board (NI-6259-PCI, National Instruments, Munich, Germany), which also controlled the Yanus beam scanner and the vertical axis of the scanning stage. To control the instrument, the software Imspector (Abberior Instruments, Göttingen, Germany) was used.

SICM setup The setup used for SICM imaging was the same one as introduced previously. 55 In brief, the scanning pipette was mounted into the optical axis of an inverted light microscope (Telaval, Carl-Zeiss, Jena, Germany) on a three-way piezo system (Nanocube, PI-611.3, Physik Instrumente, Karlsruhe, Germany) which was additionally equipped with a stiff, short-range shear-force actor (PI-111.05, PI Ceramics, Germany) for fast retraction of the pipette. For coarse positioning of the sample, a three-way piezo stage with manual micrometer screws was used (NanoMax 311D/M, Thorlabs, Munich, Germany). The current through the pipette opening was recoded using a patch-clamp amplifier (ELC-03X npi electronic, Tamm, Germany) and digitized using a data acquisition board (NI-6259-PCI, National Instruments, Munich, Germany), which also controlled the position of the scanning pipette. We used an in-house software written in Python 2.7 to record the data and control the instrument. 17


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SICM pipettes and imaging settings We used pipettes drawn from borosilicate glass (World precision instruments, Florida, USA) with a P2000 laser puller (Sutter Instrument, Novato, California, USA) with an access resistance in the range of 50 MOhm (Figures 1 and 2) and 110 MOhm (Figure 4). We have previously described the geometry of the pipettes pulled under these conditions with this instrument, 55 thus we estimate the opening radius ri of the pipettes to be in the range of 50 nm (for the 50 MOhm pipettes) and 25 nm (for the 110 MOhm pipette). We used approach velocities in the range of 50 nm/ms–100 nm/ms and retraction distances of 10 µm – 15 µm to safely scan the cells. This led to an approximate imaging time of 15 min to 20 min for the images shown in Figure 1 (pixel size was 100 nm, scan size was 10 µm × 10 µm) and Figure 2 (pixel size was 125 nm, scan size was 10 µm × 10 µm) and of more than eight hours for the recording shown in Figure 4 (pixel size was 167 nm, scan size was 80 µm × 67 µm). We used thresholds of 0.5 % for live-cell and 1 % for fixed cell imaging and a bias voltage of +300 mV. The current was filtered using a low-pass filter of 1.3 kHz, or 2 kHz or 3 kHz.

Data processing and analysis SICM data SICM data shown was filtered by a median filter with a width of 2 or 3 pixels and corrected for tilt by an in-house correction algorithm that fits a straight line to a selectable percentile of the data in the line and subsequently subtracts the line from the data. In all cases, we used the lowest 25 % percentile here for fitting. The SICM recording in Figure 1 was interpolated by cubic splines.

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STED data The recordings of the fluorescent nanoparticle are raw data smoothed with ImageJ’s smooth command, the recording of tubulin in a Vero cell (Figure 2F) is raw data. All other STED recordings are deconvolved by the Richardson-Lucy algorithm as implemented in Imspector. The FHWM for the deconvolution PSF was determined by fitting a Lorentzian distribution to the intensity profile of the thinnest structure that clearly exceeded the background in the image (as exemplified in Figure 1Ab). Simulation of fluorescence microscopy recordings The manually drawn structure in Figure 3A was convoluted with a Gaussian distribution with a full width at half maximum of the respective resolution. Alignment of STED and SICM data STED and SICM images were aligned manually with the help of a home-written alignment tool implemented in Matlab (R2017a, Mathworks, USA). First the images were scaled to match. Next, the images were shifted and rotated with respect to each other to find the best optical match. No stretching or shearing was used. Roughness analysis Roughness was computed by dividing the SICM scan into sections of 11 px×11 px with an offset of one Pixel between the section. Then, a two-dimensional polynomial of fifth degree was fitted to the data and subsequently subtracted. The roughness was then determined as the root of the mean squared error of the data points. For the analysis of the average roughness, we only used roughness values up to 250 nm. Higher roughness values occurred at abrupt transition from the cell culture dish to the cell surface (that is, at the of rims of the cell), where a polynomial of fifth degree is not sufficient to remove the underlying shape. Note that this threshold resulted in two spots in the center of the cell labeled “b” in 19


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Figure 5 that were excluded. We neglected these spots due to the very clear difference in the corresponding roughness data histograms (Figure 5C).

Sample preparation Fluorescent nanoparticles Poly-D-Lysine coated cover slips were incubated for 45 min with a 1 : 105 dilution of FluoSpheres ((580/605), diameter 0.04 µm, Thermo Fisher Scientific, Waltham, USA). After washing with water, the sample was mounted on a slide with 30 % Mowiol (Kuraray, Chiyoda, Japan). Tubulin staining in living astrocytes Astrocytes from rat brain (2 × 104 per well) were cultured on cover slips in a 24-well-plate in high glucose Dulbecco’s Modified Eagle Medium (DMEM, D6546, Sigma-Aldrich, Missouri, USA) supplemented with 1 % L-glutamine, 1 % penicillin/streptomycin and 10 % fetal calf serum. After one day in culture, the cells were stained with 8 µM SiR-Tubulin (Spirochrome, Cytoskeleton Kit SC006, Stein am Rhein, Switzerland), a membrane-permeable dye for live-cell staining of tubulin 56 and treated with 40 µM Verapamil (Sigma-Aldrich, Missouri, USA), solved in d6-DMSO (Carl Roth, Karlsruhe, Germany). After one hour of incubation (37℃ and 5 % CO2 ), the cover slip was mounted with a droplet of staining medium onto a microscope Sslide. Actin staining of fixed HeLa cells HeLa cells (105 per dish) were cultured in a 3.5 cm glass bottom dish (Ibidi, Martinsried, Germany) in high glucose DMEM (D6546, Sigma-Aldrich, Missouri, USA) supplemented with 1 % L-glutamine, 1 % penicillin/streptomycin and 10 % fetal calf serum. After one day in culture, the cells were rinsed with phosphate buffered saline, fixed with 4 % paraformaldehyde for 15 min and subsequently washed with phosphate buffered saline. The cells were then 20


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stained for one hour with 8 µM SiR-Actin 56 (Spirochrome, Cytoskeleton Kit SC006, Stein am Rhein, Switzerland). For the SICM measurement, the medium was exchanged to 150 mM sodium chloride. Living HeLa cells HeLa cells (105 per dish) were cultured in a 3.5 cm plastic cell culture dish in high glucose DMEM (D6546, Sigma-Aldrich, Missouri, USA) supplemented with 1 % L-glutamine, 1 % penicillin/streptomycin and 10 % fetal calf serum. For SICM measurements, the medium was exchanged to Leibovitz Medium (L-15, L5520, Sigma-Aldrich, Missouri, USA). Vero cells The Vero cell shown in Figure 1 was from a commercial test sample with tubulin stained with Star Red (Abberior, Göttingen, Germany).

Competing interests The authors declare that they have no competing interests.

Author’s contributions PhH recorded the STED data, AG recorded the SICM data. PhH and PaH build the STED microscope, PaH designed the study, wrote the initial version of the manuscript and build the SICM. PhH and AG prepared the samples. All authors analyzed the data, revised the initial manuscript and approved the final manuscript.

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Acknowledgement AG and PaH acknowledge funding from the Volkswagen Foundation (grant 88 390). The authors thank Steffen Murke for recording the tip of the oligodendrocyte progenitor cell (Figure 1F) during his Bachelor thesis. The components of the STED microscope were funded by the Deutsche Forschungsgemeinschaft (INST 213/819-1 FUGG), we performed some initial test experiments regarding live-cell recording with SiR-dyes on an instrument also funded by the Deutsche Forschungsgemeinschaft (INST 213/886-1 FUGG). We thank Wolfgang Schuhmann, Thomas Günther-Pomorski and Irmgard D. Dietzel-Meyer for sharing their equipment and the entire RUBION team for their support.

Supporting Information Available Supporting information describing the operating principle of STED microscopy, the confocal counterparts of the STED recordings shown in Figure 2 and a sketch of the STED setup accompanies this article. This material is available free of charge via the Internet at http://pubs.acs.org

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Graphical TOC Entry STED

SICM

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Correlative Stimulated Emission Depletion and Scanning Ion

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