Visualization of the membrane surface and cytoskeleton of oligodendrocyte progenitor cell growth cones using a combination of scanning ion conductance and four times expansion microscopy
Abstract
Growth cones of oligodendrocyte progenitor cells (OPCs) are challenging to investigate with conventional light microscopy due to their small size. Especially substructures such as filopodia, lamellipodia and their underlying cytoskeleton are difficult to resolve with diffraction limited microscopy. Light microscopy techniques, which surpass the diffraction limit such as stimulated emission depletion microscopy, often require expensive setups and specially trained personnel rendering them inaccessible to smaller research groups. Lately, the invention of expansion microscopy (ExM) has enabled super-resolution imaging with any light microscope without the need for additional equipment. Apart from the necessary resolution, investigating OPC growth cones comes with another challenge: Imaging the topography of membranes, especially label- and contact-free, is only possible with very few microscopy techniques one of them being scanning ion conductance microscopy (SICM). We here present a new imaging workflow combining SICM and ExM, which enables the visualization of OPC growth cone nanostructures. We correlated SICM recordings and ExM images of OPC growth cones captured with a conventional widefield microscope. This enabled the visualization of the growth cones’ membrane topography as well as their underlying actin and tubulin cytoskeleton.
1 Introduction
Oligodendrocyte progenitor cells (OPCs) are the precursors of the nervous system’s myelinating cells. They originate from the subventricular zone of the brain, from which they migrate towards their target cells during development. However, these precursors are not only present in developing but adult brains as well (Dawson et al. 2003). They display a bipolar morphology and highly motile behaviour (Schmidt et al. 1997) in terms of cell migration but also cell process movements. While previous investigations of soma volume changes of migrating OPCs (Happel et al. 2013) support a possible connection of OPC soma movement and migration to ion fluxes, water fluxes and cellular volume regulation (Schwab et al. 2007), their process movements appear to be mainly driven by changes of the actin cytoskeleton within their growth cones (Thomason et al. 2020). Yet, much about the exact cytoskeletal mechanisms and changes of the OPC growth cone shape as well as a comprehensive understanding about the growth cone’s exact role during migration still remains to be discovered. One major challenge when investigating OPC growth cones, is their size and especially the small size of their substructures. Filopodia and lamellipodia have diameters and heights of 100–300 nm (Chhabra and Higgs 2007; Pollard and Borisy 2003). Consequentially, investigating these structures in detail with conventional diffraction-limited light microscopy is not possible. While the overall shape of OPC process tips has been observed with light microscopy in vivo (Hughes et al. 2013), the images do not have the necessary resolution to resolve nanostructures. Sub-diffraction imaging studies of these growth cones have so far been rarely conducted and have not employed super-resolution light microscopy techniques but electron microscopy (Fox et al. 2006; Rumsby et al. 2003).
Electron microscopy studies come with the advantage of not only providing ultra-structural information but also being able to image the membrane surface in nanoscopic detail. However, the required sample preparation for electron microscopy is extensive and surface heights cannot be measured directly. An alternative imaging technique able to record membrane topographies, while requiring no specific sample preparation other than the prerequisite that the sample has to be immersed in an electrolyte solution, is scanning ion conductance microscopy (SICM) (Hansma et al. 1989). SICM maps the surface of a sample by recording the ion current between a reference and a measuring electrode, which is located inside a glass capillary, as the capillary approaches the sample. This enables a 3D reconstruction of the surface without the necessity of sample labeling or direct contact between probe and sample thereby making it an ideal technique for cell surface imaging (Korchev et al. 1997). The development of the backstep scanning mode during which the capillary is retracted before moving laterally further improved this method by providing contact-free imaging of sample surfaces with large height deviations and steep negative slopes as occur in cultured single cells (Happel et al. 2003; Mann et al. 2002; Novak et al. 2009). As SICM is not a light microscopy technique, it is not diffraction-limited. Rather its resolution is limited by the opening radius of the scanning pipette (Rheinlaender and Schäffer 2015, 2009). Capillaries with openings of a few nanometers can be produced and thus SICM has already been successfully employed to image membrane structures with diameters of 14 nm in living spermatozoa (Shevchuk et al. 2006).
However, SICM only provides information about the sample surface and can’t visualize underlying structures. This obstacle can be approached by combining SICM with light microscopy. Several groups have combined SICM and widefield or confocal light microscopy for example to identify synaptic boutons in SICM-guided patch clamp recordings (Novak et al. 2013), to image primary cilia (Zhou et al. 2018), to verify volume measurements of renal tubular cells (Korchev et al. 2000), or to correlate the cytoskeleton and cellular activity of platelets (Seifert et al. 2017). Yet, these combinations suffer from a resolution mismatch as widefield and confocal light microscopy, unlike SICM, cannot resolve structures smaller than 200 nm. Combinations of SICM and super-resolution light microscopy (Happel et al. 2022) are able to resolve this discrepancy. So far, SICM recordings have been correlated with images obtained by stimulated emission depletion (STED) microscopy to compare the membrane surface and actin skeleton of HeLa cells (Hagemann et al. 2018). It has also been combined with super-resolution optical fluctuation imaging (SOFI) to gain correlated 3D and live-cell data of the membrane surface and underlying actin and tubulin cytoskeleton of COS-7 cells (Navikas et al. 2021).
A super-resolution light microscopy technique, which has so far not been used in combination with SICM, is expansion microscopy (ExM) (Chen et al. 2015). In ExM the sample is embedded into a hydrogel, which expands when immersed in water. After anchoring a labeled sample to the gel, the labels expand isotropically with the gel (Tillberg et al. 2016). This enlargement moves molecules within the sample further apart enabling the distinction of structures, which had previously been too closely positioned to be resolved with diffraction-limited microscopy. ExM has already been used to image a variety of samples with widefield and confocal microscopes (Asano et al. 2018; Chen et al. 2016; Chozinski et al. 2016; Holsapple et al. 2023; Kunz et al. 2020) but also in combination with more sophisticated imaging modalities such as STED microscopy (Gao et al. 2018), single molecule localization microscopy (SMLM) (Zwettler et al. 2020), structured illumination microscopy (SIM) (Wang et al. 2018) or light sheet microscopy (Düring et al. 2019). Another ExM modification, which combines ExM with fluorescence fluctuation analysis (Shaib et al. 2023), has recently been proposed in a pre-print promising resolutions at the 1 nm scale on conventional light microscopes.
Advances in expansion microscopy have not only been achieved by combination with other super-resolution techniques, but also by altering the hydrogel composition increasing sample expansion from 4.5× as was originally published by Asano et al. (2018) up to 10× (Damstra et al. 2022; Truckenbrodt et al. 2018). Alternatively, the expansion factor can further be increased to 20× by embedding the gel into another gel as is done in iterative expansion microscopy (Chang et al. 2017). These extensions of the original ExM protocol are able to resolve structures with sizes of 25 nm.
Both SICM and ExM are techniques able to resolve structures below the diffraction limit with similar lateral resolutions rendering a combination of these two techniques a promising method to visualize the unlabeled membrane as well as the relative position of cytoskeletal or membrane proteins. In the following, we present an imaging workflow combining these two techniques in order to obtain images indicating the relative position of actin and tubulin fibers with respect to membrane protrusions in OPC growth cones.
2 Results
2.1 Combined SICM and ExM imaging workflow
Fixed OPCs were first imaged with a brightfield microscope at low magnification to create a large overview tile scan (Figure 1A), in which the growth cones imaged by SICM could be tagged (Figure 1B). This would later on lead to easier recognition of the same growth cone in different images with varying magnifications. In the next step, the surfaces of the OPC growth cones were imaged with SICM (Figure 1C). Afterwards, the cytoskeleton was immunofluorescently labeled. The growth cone membrane was recorded via SICM before labeling as it required membrane permeabilization, which might have altered the membrane topography. Images of the immunofluorescently labeled OPCs were acquired at low magnification (Figure 1D) and compared to the brightfield overview tile scans to re-identify the same growth cones. Cells were then expanded using a 4× ExM protocol (Asano et al. 2018) and subsequently imaged again using the same objective for retrieval and determination of the expansion factor (Figure 1E). The same sample regions, pre- and post-expansion, were compared and gauged to determine expansion factors for each expanded gel. A 4× expansion protocol was chosen as it promised to result in lateral resolutions between 100 and 200 nm in combination with our widefield microscope. This would match the resolutions obtainable with the SICM as capillaries with opening radii in the range of 40–60 nm were used. Lateral SICM resolutions approximately equal 3 times the inner capillary radius (Rheinlaender and Schäffer 2009). Capillaries with radii smaller than 40 nm can be produced (Steinbock et al. 2013). However, smaller capillaries tend to clog faster and as our SICM image acquisition times ranged between 2 and 8 h depending on the step and scanning field size, smaller capillaries would not have remained unclogged throughout the entire image acquisition risking sample-probe contact. Furthermore, these lateral resolutions should be sufficient to distinguish filopodia and lamellipodia. Finally, the same expanded growth cones previously recorded via SICM were located in the expanded gels utilizing the overview scans and imaged using a 60× magnification objective (Figure 1F). Resolutions were determined by calculating the full width at half maximum (FWHM) of a Gaussian fitted line profile through a small but still distinguishable structure within the fluorescence image. To obtain overlays, ExM images were scaled in accordance to the expansion factor of the gel as well as horizontally flipped (Figure 1G). This was necessary, as SICM images were recorded on an upright setup facing the cells from above, whereas ExM images were acquired with an inverted microscope facing the cells from below. Since SICM and ExM images were acquired on different microscopes with further sample preparations in between the two acquisitions, the respective fields of view differed in terms of their acquisition angle. Thus, the images had to be slightly rotated to match one another.

Experimental workflow. Fixed samples are first imaged as a large brightfield tile scan with a 20× objective to create an overview map (A) in which regions of interest (ROIs) containing cells with OPC morphology can be marked (B). Growth cones within these ROIs are then imaged with SICM to capture membrane topographies (C). After fluorescently labeling the cytoskeleton, micrographs are obtained with a 20× objective (D). After sample expansion, the same regions of the sample are imaged again (E). Expansion factors are determined by measuring distances in images of the same sample region acquired with the same objective before and after expansion. A 60× objective is used to capture fluorescence images of OPC growth cones (F). Finally, expansion factors are used to scale the ExM images, which are then flipped to match the SICM images. ExM and SICM images are manually correlated (G).
2.2 SICM recordings of OPC growth cones
Figure 2 shows brightfield images of the investigated cells (Figure 2a), three- (Figure 2b) and two-dimensional (Figure 2c) projections of three growth cones imaged via SICM as well as height profiles through their widest and longest parts (Figure 2d). The height profiles along the direction of growth start at values of about 1–2 µm and then gradually decrease, with the exception of some protrusions, to about 500 nm. The height profiles along the widest sides of the growth cones are generally flatter, with the exception of growth cone A, ranging mostly around 500 nm. The shape of growth cone A slightly differs from these observations as the flat lamellipodium appears at the right side instead of the very tip of the growth cone.

SICM recordings of OPC growth cones. a) Brightfield images of cells imaged via SICM. Scale bars represent 50 µm. A white square marks the scanned growth cone. 3D (b) and 2D (c) plots of the topographies as well as height profiles (d) through the length (blue) and width (yellow) of the growth cones. Ab-c) 7.00 × 7.00 µm scan of an OPC growth cone imaged with a step size of 100 nm. Bb–c) 9.50 × 9.55 µm scan of an OPC growth cone imaged with a step size of 50 nm. Cb–c) 4.23 × 5.00 µm scan of an OPC growth cone imaged with a step size of 30 nm. Width of membrane bulges (orange) and potential filopodia (green) are highlighted.
The flattest parts display heights of 200 nm, which suggest that these could be lamellipodia. Growth cones A and B exhibit what appear to be filopodia with diameters ranging between 150 and 330 nm. These exemplary growth cone recordings correspond to our current knowledge of growth cones containing a thicker microtubule-rich domain at the center, which then flattens out into an actin-rich peripheral domain (Thomason et al. 2020).
2.3 Expansion microscopy images of OPC growth cones
An exemplary fluorescence image of tubulin-labeled cells is displayed pre-expansion in Figure 3Aa and post-expansion in Figure 3Ab. Images were captured with the same optical magnification. The expansion factor of the respective expansion gel was determined to be 3.72 ± 0.02 (n = 10). Figure 3Ba shows an OPC and one of its growth cones (Figure 3Bb) from the same expanded culture at higher magnification, enabling the visualization of fibrous microtubules. A resolution of 105 nm was estimated by measuring the width of the thinnest distinguishable microtubules within this growth cone via the full width at half maximum of an intensity profile (Figure 3C).

Expansion microscopy (ExM) of oligodendrocyte precursor cell (OPC) cultures. Widefield fluorescence microscopy images of tubulin-labeled OPCs pre- (Aa) and post-expansion (Ab). The expansion factor is 3.72 ± 0.02 (n = 10). Images captured using a 20× objective. Ba) ExM image of an expanded OPC captured with a 20× objective. Bb) Left growth cone of the OPC displayed in (Ba) captured using a 60× objective. The resulting resolution was determined via the full width at half maximum (FWHM) of the Gaussian fitted intensity profile (C) of a small but distinguishable microtubule (Bb) to be approximately 105 nm. Scale bars represent 100 µm (Aa), 27 µm (Ab), 50 µm (Ba), and 10 µm (Bb).
This is within the range of what we expected to be resolved laterally and roughly matches the sizes of structures resolved in the SICM recordings (Figure 2b). The smallest structure, which was measured within the SICM images, was a membrane protrusion with a width of 130 nm (Figure 2Cb).
2.4 Correlation of SICM and ExM images of OPC growth cones
In order to find out, whether prominent structures of the cytosceleton can be matched to defined irregularities of the growth cone surfaces as visualized by SICM recordings, overlays from successive SICM and ExM images were assembled. Figure 4A shows an SICM scan from a growth cone displaying several peripheral membrane protrusions emerging from a higher central tube-like structure at the right side of the image. The ExM image shows a bundle of microtubules entering the growth cone from the right. The superimposed SICM and ExM images shown in Figure 4C confirm that in fact microtubules are mainly located at the higher central domain whereas the flatter peripheral regions, most likely lamellipodia and filopodia, are void of labeled microtubules.

Correlation of membrane topography and tubulin labeling of an OPC growth cone. (A) Growth cone membrane surface imaged with a SICM step size of 50 nm. (B) Expansion microscopical image of the tubulin cytoskeleton. The image was horizontally flipped to match the SICM image as SICM images show the growth cone from above while the ExM images show the growth cone from below. (C) Overlay of SICM and ExM images of the same growth cone. Grey dotted squares indicate the rotation angle of the SICM image. Colored triangles indicate identical positions. Scale bars correspond to 9.5 µm.
To determine, whether the flatter filopodia- and lamellipodia-like regions of the growth cones contain actin, double stainings were performed (Figure 5). Both growth cones show a dense staining for actin in the peripheral membrane regions, whereas tubulin is concentrated in the elevated central regions. While an approximate match between prominent structures in the SICM and ExM images is clearly possible, the superimposed images shown in Figure 5C and F do not perfectly align. This can be explained by the inherent differences of 2- and 3-dimensional data sets. Fluorescence signals from higher or lower planes than the focal plane are lost as background fluorescence. Furthermore, during the sample preparation processes necessary for ExM loosely attached filopodia or lamellipodia might have shifted slightly.

Correlated SICM and ExM images of OPC growth cones. (A, D) SICM images of the growth cone membranes. SICM step sizes: 100 nm (A) and 30 nm (D). (B, E) Expansion microscopical images of the actin (magenta) and tubulin (green) cytoskeletons. Images horizontally flipped to match the SICM images as SICM images show the growth cone from above while the ExM images show the growth cone from below. (C, F) Overlays of SICM and ExM images of the same growth cones. Grey dotted squares indicate the rotation of the SICM with respect to the ExM images. Colored triangles point to identical positions. Scale bars represent 7 µm (B, C) or 5 µm (E, F).
3 Discussion
Our results demonstrate that the position of proteins with respect to cell membrane topography can be analyzed with a lateral resolution of less than 200 nm using successive imaging with a home-build scanning ion conductance microscope and 4× expansion microscopy visualized with a widefield fluorescence microscope. Our observations in terms of lamellipodia and filopodia sizes as well as actin and tubulin localization in oligodendrocyte progenitor cells are in accordance with observations of these structures investigated via electronmicroscopy (Rumsby et al. 2003) or in other cell types such as neurons (Mattila and Lappalainen 2008; Okabe and Hirokawa 1991; Schaefer et al. 2002).
Although our results show, that the combination of SICM and ExM can yield valuable information about the relative position of identified proteins with respect to the membrane surfaces, several problems are evident, which need to be solved in the future. The first problem concerns the manual rotation of the SICM images to match the acquisition angle of the ExM images, which is not well defined. While Figure 5C and F demonstrate a satisfactory match of ExM and SICM images, the correlation process would have benefited from size-defined landmarks such as fluorescent beads, which could be used to automate the superimposition of the data sets. However, when trying to include fluorescent beads in our experiments, they did not anchor to the gel and therefore could not be visualized via ExM. DNA origami nanorulers could potentially be utilized as landmarks to improve the overlay process. They have been successfully used as reference structures in super-resolution fluorescence microscopy (Scheckenbach et al. 2020), but it remains to be tested, whether such nanorulers are visualizable via SICM without clogging the pipette or moving during ExM sample preparation. If they fulfill all these requirements, they should enable automated data set correlation rendering the image acquisition protocol more reliable and reproducible.
Another challenge in correlating these images arose due to the fact that SICM records 3D surface data, while ExM images yield 2D data from only one focal plane. Thus, a satisfactory correlation of fluorescence and topographical data can only be achieved at positions where the ExM focal plane is traversed by the membrane. From the present data, it is therefore difficult to judge, if some of the membrane protrusions seen in Figures 3, 4, and 5 are induced by actin fiber formation or underlying mitochondria or fluid-filled cavities.
This challenge was also reported by Hagemann et al. (2018) in their publication on correlated SICM and STED microscopy. A possible solution to this problem would be the acquisition of ExM images as z-stacks yielding 3D reconstructions of the intracellular proteins. In case of 3D ExM data, the axial resolution would have to be increased to better match the axial SICM resolution. This could be achieved by using a 10× ExM protocol (Damstra et al. 2022; Truckenbrodt et al. 2018) instead of the 4× protocol applied here. If the scanning field or scanning times of the SICM are further reduced, smaller capillaries could be used, which would then match the lateral resolution of the 10× expansion protocols. Further improvements could also be made by acquiring the ExM images not via widefield but confocal or super-resolution light microscopy. Despite these draw backs, our present imaging protocol can be applied to routinely obtain information about the localization of antibody accessible intracellular proteins with respect to the outer membrane in many cell types in culture at resolutions below 200 nm. This should prove especially useful to laboratories in which only basic fluorescence microscopy is available.
The lack of dynamic information is an obvious disadvantage of correlated SICM and ExM, which other correlated SICM techniques such as correlated SICM and SOFI (Navikas et al. 2021) do not suffer from. Yet, in case of very fast occurring processes such as synaptic vesicle release, it could be an advantage to not have to worry about temporal resolution but rather investigate samples which have been frozen in time due to the fixation.
An extension of the present imaging workflow, which might partially compensate for the lack of dynamic information, could be the inclusion of time-lapse live cell imaging either via light microscopy or SICM or both before sample fixation. In case of the visualized growth cones, it would have yielded information on whether the imaged growth cones were part of a retracting or proceeding process. If for example the growth cone presented in Figure 5A–C would have been observed live previous to fixation and would have been observed to be part of the retracting process, it would explain why this growth cone has small lamellipodia-like structures only at the side instead of at the process tip.
In its present form, the presented method can be employed to obtain information about the relative position of proteins with respect to membranes in fixed cells. After slight improvements concerning alignment and 3D reconstruction of the fluorescence signals, it will be possible to study the relative positions of proteins with respect to the plasma membrane topography of cultured cells at resolutions below 200 nm. In the case of OPC growth cones the analysis of a large series of such pictures could be the first step in understanding membrane rearrangements with respect to identified cytoskeletal proteins during growth cone protrusion and retraction. Since the precise mechanisms leading to target finding, directed cell migration, axon myelination and growth arrest remain to be fully understood, the insights obtained by such studies may help to develop strategies to alleviate demyelinating diseases such as periventricular leucomalacia or multiple sclerosis. To obtain information about membrane dynamics with respect to cytoskeletal proteins, however, the development of a combined instrument, which allows for SICM image acquisition simultaneous to super-resolution fluorescence imaging at defined nanoscopic structures, will be required as a further step.
4 Materials and methods
4.1 Cell culture
Cortices from 0- to 2-day-old Wistar-Hannover rats were dissected and collected in 10 mL tubes filled with ice cold Minimum Essential Medium (MEM; Gibco™, Thermo Fisher Scientific, 11095080) supplemented with 10 μg/mL desoxyribonuclease I (Sigma-Aldrich, Merck, DN25), 2.5 mg/mL trypsin (Sigma-Aldrich, Merck, T4549), 25 U/mL penicillin and 25 μg/mL streptomycin (1 % P/S; Sigma-Aldrich, Merck, P0781). Dissected cortices were incubated at 37 °C for 5 min on a thermal shaker (ThermoMixer, Eppendorf) at 1000 rpm. The enzymatic digestion was stopped by addition of 10 % (v/v) heat inactivated fetal calf serum (FCS; Gibco™, Thermo Fisher Scientific, 10270106). To complete tissue dissociation, the resulting tissue suspension was gently triturated 10 times with a 1000 µL pipette. Afterwards, the suspension was left undisturbed for 5 min to let any left-over tissue debris settle at the bottom of the reaction tube. The supernatant was aspirated and centrifuged for 10 min at 180 g and 20 °C. In the following, the pellet was resuspended in Dulbecco’s Modified Eagle Medium (DMEM)/Ham’s F12 nutrient mixture (F12) (Gibco™, Thermo Fisher Scientific, 31330095) containing 10 % (v/v) FCS, 1 % P/S, and 1 mM sodium pyruvate (Gibco™, Thermo Fisher Scientific, 11360070). The resuspended pellet was then seeded into T75 flasks (Sarsted, 83.3911), which had been coated with a 5 μg/mL poly-d-lysine (Sigma-Aldrich, Merck, P6407) solution, and incubated at 37 °C and 5 % CO2 in a humidified atmosphere (Heraeus, B5060 incubator). One T75 flask eventually contained cells from two cortices. The flask medium was exchanged for fresh medium 3 h after seeding and afterwards every 2 days.
After 7–10 days, flasks were shaken at 37 °C and 180 rpm (Kühner, ES-W) to separate different cell types in accordance to their adherence to the flask bottom. After 3 h of shaking, the flask medium, which mostly contained microglia, was discarded and replaced with fresh medium. After another 18 h of shaking, the medium was removed again. Fresh medium (DMEM/F12, 1 % P/S, 10 % FCS) was added to the flasks before they were put back into the incubator. Cells could be harvested again after another 7–10 days up to two more times.
The removed flask medium was centrifuged at 180 g for 5 min to obtain the desired OPCs. The centrifuged pellet was resuspended in DMEM/F12, which was supplemented with a customized version of B27 supplement (Lesslich et al. 2022) as well as 10 ng/mL platelet-derived growth factor (PDGF; HumanKine, Proteintech, HZ-1215) and 10 ng/mL fibroblast growth factor 2 (FGF-2; HumanKine, Proteintech, HZ-1285). Cells were seeded in glass bottom dishes (ibidi, 81218-200) aiming for a density of 30,000 cells/cm2. To enable better cell adhesion, dishes had been pre-coated with a 5 μg/mL poly-d-lysine solution. The dish medium (DMEM/F12, customized B27, 10 ng/mL PDGF, 10 ng/mL FGF-2) was replaced with fresh medium 3 h after seeding and following every 24 h. Dishes with OPCs were maintained at 37 °C and 5 % CO2 in a humidified incubator. This procedure provided a higher OPC yield than the previous protocol used in our laboratory (Feldhaus et al. 2004).
4.2 Sample preparation
3–6 days after seeding, OPCs were fixed with a mixture of 4 % (w/v) formaldehyde (Roth, 0335.3) and 1 % glutaraldehyde (Fluka™, 49629) in phosphate buffered saline (PBS; Gibco™, Thermo Fisher Scientific, 14190144). In the following, samples were washed twice with PBS and incubated for 5 min at room temperature (RT) with a quenching solution containing 100 mM glycine (Fischer Chemical™, Fischer Scientific, 10070150) and 10 mM ethanolamine (Merck Chemicals, 8008491000) to reduce the autofluorescence caused by the aldehyde fixatives. Afterwards, samples were washed again twice with PBS. A paint marker was used to draw a cross from the outside of the dish onto the glass bottom. This marking aided with orientation and made it easier to locate the same cell and growth cone at different microscope setups.
After acquiring brightfield tile scans of the samples, all cells were identified as OPCs, which displayed a circular soma and had exactly two processes with process tips further than 15 µm apart from each other. These cells had previously been identified as OPCs in similar cultures (Feldhaus et al. 2004) using anti-A2B5 immunostaining and were clearly morphologically distinguishable from the contaminating GFAP-positive astrocytes and the multipolar or amoeboid microglia. The identified OPCs were then imaged via SICM, and afterwards fluorescently labeled: For membrane permeabilization and unspecific binding site blocking, samples were incubated twice for 5 min at RT with PBS additionally containing 0.1 % (v/v) Triton X-100 (Boehringer, 759704) and 3 % (v/v) FCS. They were washed twice with PBS afterwards. Then, the cells were incubated for 1 h at 37 °C with a primary antibody solution containing mouse anti-β-tubulin (Proteintech, 66240-1-Ig) and rabbit anti-β-actin (Proteintech, 20536-1-AP) antibodies each diluted 1:1000 in PBS. In the following, samples were washed again twice with PBS before being incubated at 37 °C in the dark with a PBS-based secondary antibody solution containing AlexaFluor488 goat anti-mouse IgG (Invitrogen, A11001) and AlexaFluor594 goat anti-rabbit IgG (Invitrogen, A11012) antibodies at a dilution of 1:250. After 4 h, 10 μg/mL Hoechst33258 dye (Sigma-Aldrich, B2883) were added to the samples to label the cell nuclei. Cells incubated for another 20 min before the samples were washed again twice with PBS.
4.3 Widefield microscopy
Before samples were imaged at the SICM, images were captured in brightfield mode at an Olympus IX83 P2ZF microscope with IX3 LED illumination and a 20× objective (air, NA 0.45, WD 7200 µm, LUCPlanFLN, Olympus). Using the Olympus cellSens Dimension software (version 3.2, build 23706) a large tile scan of the whole sample was captured. This overview was then used to locate single cells and growth cones and to help identify the same cells again later on.
After SICM images had been captured and samples were fluorescently labeled, more overview tile scans and images were captured to later on enable expansion factor determination and easier identification of the same growth cones previously recorded with the SICM. These images were captured with the same Olympus IX83 microscope using the 20× objective, 385 nm excitation light and 442 nm emission light for the Hoechst33258 labeled nuclei, 465 nm excitation light and 519 nm emission light for the AlexaFluor488 labeled beta-tubulin, and 559 nm excitation light and 575 nm emission light for the AlexaFluor594 labeled beta-actin.
4.4 Scanning ion conductance microscopy
SICM imaging was conducted with an in-house built setup (Gesper et al. 2017). Nano-capillaries (access resistances: 50–100 MΩ; estimated opening radii: 40–60 nm) were pulled from borosilicate glass (World Precision Instruments) with a P2000 laser puller (Sutter Instrument). A Python 2.7 software written by Dr. Patrick Happel recorded the data and controlled the instrument. We used approach velocities in the range of 25–100 nm/ms and retraction distances of 5–10 μm to ensure contact-free scanning of the growth cones. Pixel sizes ranged from 30 to 100 nm. We used thresholds of 0.5–2 %, bias voltages of 150–300 mV and filtered the current with a low-pass filter of 0.3, 0.7, or 1 kHz. A 150 mM NaCl solution was used as electrode and bath solution. A chlorinated silver wire served as an Ag|AgCl measuring electrode and a chlorinated silver pellet was used as an Ag|AgCl counter electrode. Cells were imaged using backstep mode scanning (Happel and Dietzel 2009) to enable contact-free scanning.
4.5 Expansion microscopy
After imaging the fluorescently labeled cells with the same Olympus IX83 P2ZF microscope, the coverslip glass bottoms of the Petri dishes containing the OPCs were separated from the rest of the dishes by gently pushing them downwards with forceps. The cells were then treated according to the four times protein retention expansion microscopy (proExM) protocol published by Asano et al. (2018). This protocol has been demonstrated to yield expansion with nanoscale isotropy (Chen et al. 2015). As soon as the samples had been expanded, they were placed into single specimen plates with a No. 1.5 glass coverslip bottom and a viewing area of 96 mm × 67 mm (Mattek, P384G-1.5-10872-C) to accommodate the expanded gels. They were imaged with the same Olympus IX83 P2ZF microscope with increased exposure times due to the decreased fluorescence intensity caused by the expansion (Wassie et al. 2019). Using the identical 20× objective enabled expansion factor determination by comparison with the images of the unexpanded samples. Finally, the samples were imaged with a 60× water immersion objective (NA 1.20, WD 280 µm, UPlanSApo, Olympus) to further increase the resolution.
4.6 Data processing and analysis
Raw data used to generate the displayed figures was made available in an open access data repository (doi: 10.5281/zenodo.7931003).
SICM images were cropped to the region of interest and filtered using a median filter with a width of 2 or 3 pixels. Furthermore, the lowest z value of the data set was subtracted from all z values to set the origin of the z axis to zero. All SICM data processing and analysis was conducted with a self-developed software written in Python 3.10 (pySICM Analysis, version 0.1.1, doi: 10.5281/zenodo.7930581).
Light microscopy images were processed and analyzed using FIJI/ImageJ 1.53t (Schindelin et al. 2012). Any quantitative measurements such as expansion factor or resolution determinations were conducted on unprocessed raw data. Images displayed within this manuscript have been contrast adjusted for better visualization. Also, images shown in Figures 3, 4, and 5 have been post processed with FIJI’s ‘Subtract Background…’ function (radius: 100 px).
ExM images of the same growth cones but illuminated with different wavelengths to excite fluorophores either labeling tubulin or actin were manually corrected for gel drift, cropped and merged in FIJI.
Expansion factors were determined by measuring the distances between or lengths of the same sample structures e.g. cell processes in pre- and post-expansion images of the same sample region captured with the 20× objective. Per expanded sample 10 distances were measured pre- and post-expansion. Post-expansion distances were divided by pre-expansion distances, the mean and standard error were calculated and the mean value regarded as the expansion factor.
Resolutions were determined by plotting the gray scale values along a line through a small but distinguishable structure within the image. Plotted values were then fitted with a Gaussian fit and the full width at half maximum (FWHM) was determined as the resolution.
SICM and ExM images were aligned manually by first cropping, scaling and flipping the ExM images to match the SICM recording. SICM and ExM images were then rotated with respect to each other. Images were not sheared or stretched.
Funding source: Deutsche Forschungsgemeinschaft
Award Identifier / Grant number: 411517989
Award Identifier / Grant number: INST 213/985-1 FUGG
Acknowledgments
We thank Stephanie Koll for assistance in the laboratory as well as Roger Genschur, Timo Wegener and Martin Korbel for their technical support. We also thank Max Halupczok for testing some of the ExM-related handling procedures. Furthermore, we thank the entire RUBION team, especially Arnd Apool and Sumit Chakraborty, as well as the Department of Biochemistry II of the Ruhr-Universität Bochum, especially Thomas Günther-Pomorski, for their continued support. We dedicate this publication to Patrick Happel, who inspired us shortly before his death to tackle this project.
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Research ethics: The sacrificed animals were bred and cared for in the Faculty of Medicine’s animal facility at the Ruhr-Universität Bochum. All procedures were strictly in accordance with the German Animal Welfare Act (deutsches Tierschutzgesetz).
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Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission. The authors contributed as follows: Annika Haak: Conceptualization, Data curation, Formal analysis, Investigation, Project administration, Visualization, Writing – original draft, Writing – review & editing; Heiko M. Lesslich: Software Development, Visualization, Writing – review & editing; Irmgard D. Dietzel: Visualization, Writing – review & editing.
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Competing interests: The authors state no conflict of interest.
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Research funding: The presented research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) ‒ project number: 411517989. Furthermore, an equipment grant from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) is gratefully acknowledged (INST 213/985-1 FUGG) for the used Olympus IX83 P2ZF microscope.
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Data availability: All raw and processed data can be found in an open access repository (doi: 10.5281/zenodo.7931003). In addition, the raw data can also be obtained on request from the corresponding author.
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© 2023 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Highlight: Horizons in Neuroscience - Organoids, Optogenetics and Remote Control
- Highlight: Horizons in Neuroscience – Organoids, Optogenetics and Remote Control
- Towards correlative archaeology of the human mind
- The promise of genetic screens in human in vitro brain models
- Schwann cells in neuromuscular in vitro models
- Visualization of the membrane surface and cytoskeleton of oligodendrocyte progenitor cell growth cones using a combination of scanning ion conductance and four times expansion microscopy
- Optogenetics 2.0: challenges and solutions towards a quantitative probing of neural circuits
- Illuminating the brain-genetically encoded single wavelength fluorescent biosensors to unravel neurotransmitter dynamics
- Microtubules as a signal hub for axon growth in response to mechanical force
- The good or the bad: an overview of autoantibodies in traumatic spinal cord injury
Articles in the same Issue
- Frontmatter
- Highlight: Horizons in Neuroscience - Organoids, Optogenetics and Remote Control
- Highlight: Horizons in Neuroscience – Organoids, Optogenetics and Remote Control
- Towards correlative archaeology of the human mind
- The promise of genetic screens in human in vitro brain models
- Schwann cells in neuromuscular in vitro models
- Visualization of the membrane surface and cytoskeleton of oligodendrocyte progenitor cell growth cones using a combination of scanning ion conductance and four times expansion microscopy
- Optogenetics 2.0: challenges and solutions towards a quantitative probing of neural circuits
- Illuminating the brain-genetically encoded single wavelength fluorescent biosensors to unravel neurotransmitter dynamics
- Microtubules as a signal hub for axon growth in response to mechanical force
- The good or the bad: an overview of autoantibodies in traumatic spinal cord injury