Glycocalyx micro- and nanodomains in cell-cell and cell-matrix interactions revealed by enhanced click chemistry

Smits, Daan; Damen, Johannes A. M.; Li, Tianfu; van Delft, Floris L.; Albada, Bauke; Friedl, Peter

doi:10.1038/s41467-026-69242-1

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Published: 12 February 2026

Glycocalyx micro- and nanodomains in cell-cell and cell-matrix interactions revealed by enhanced click chemistry

Nature Communications volume 17, Article number: 2645 (2026) Cite this article

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Abstract

The glycocalyx consists of glycoproteins, glycolipids and extracellular polysaccharides at the cell surface which mediate viscoelastic and electrostatic barrier function. In molecular interactions, the glycocalyx is thought to segregate locally to facilitate receptor-ligand binding, yet high-resolution maps of glycocalyx domains in cell-cell and cell-matrix interactions are lacking. We here apply TMTH-sulfoximine (THS)-based biorthogonal chemistry in live-cell culture and demonstrate enhanced glycocalyx detection, compared to established dibenzocyclooctyne-based labeling. Using superresolution microscopy in cancer cells, we identify micron-scale diminished glycocalyx in cell-cell contacts and depletion in protrusions at the leading and trailing edges and membrane blebs when cells invade 3D fibrillar matrix. At contacts to collagen fibrils, focal integrin clusters segregate ~350 nm outward from the glycocalyx level, forming adhesion sites of low glycocalyx content. Thus, we identify micro- and nanodomains with altered glycocalyx density using THS-based bioorthogonal labeling of live cells, implicating local glycocalyx downregulation in functional cell-cell and cell-matrix interactions.

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Introduction

The glycocalyx consists of negatively charged polysaccharides, which regulate protein distribution and function, receptor signaling and turnover, mechanosensing, as well as cell integrity and shape^1,2,3,4. In cancer cells, protein glycosylation is abnormal due to deregulation of glycosyltransferases and glycan production, resulting in glycocalyx thickening up to tens to hundreds of nanometers^5,6,7. As a consequence, the altered glycocalyx organization impacts cell adhesion, cell-cell communication, signaling, and the immune response^5,8,9 and, in aggregate, is thought to contribute to cancer progression.

The glycocalyx can be dynamically distributed on the cell surface, and glycocalyx size and charge can vary locally and globally, thereby regulating cell adhesion or repulsion as well as the distribution, accessibility, and aggregation of membrane-resident proteins^2,3,10,11. During phagocytosis of microparticles, CD45 and CD148, both large glycoproteins that extend >25 nm beyond the membrane layer, distribute out of the contact area, resulting in micron-scale segregation of the glycocalyx¹¹. Epiglycanin and sialomucin, both bulky glycoproteins that extend >450 nm beyond the membrane, redistribute out of cell-cell contacts between cancer cells and hepatocytes^12,13. Likewise, on submicron- and nano-scale, an artificially thickened bulky glycocalyx can sterically enhance local accumulation and clustering of integrin adhesion receptors towards ECM contacts^9,14. Whereas the regulation and redistribution of individual glycoproteins has been demonstrated, it remains unclear whether the glycocalyx as a whole, comprising of multiple glycoproteins, is regulated in live cells. In addition, how glycocalyx distributes in cell-matrix interactions in complex-structured 3D tissue and during physiologically relevant processes, including invasion, remains poorly defined.

Detection of glycocalyx redistribution and function in live cell systems is achieved through a range of approaches. Addition of fluorescent probes, including sugar-specific antibodies and lectins, allows to detect glycocalyx, with the potential shortcoming of uneven, heterogeneous binding resulting from epitope accessibility masking and/or perturbation of native glycocalyx distribution by glycan crosslinking^15,16. To detect dynamic glycan distribution in a non-perturbing manner, metabolic glycan labeling can be achieved using sugar analogues that carry bio-orthogonal reactive chemical groups, such as click handles, which can be detected by complementary fluorescently labeled reagents to form a covalent bond¹⁷. One of the most popular click reactions is the Strain-Promoted Azide-Alkyne Cycloaddition (SPAAC), which forms a stable triazole linkage by reaction of a metabolically introduced azide group with a highly strained cycloalkyne probe¹⁸. Currently, most SPAAC in live cells is performed using the cycloalkyne dibenzocyclooctyne (DBCO) or its derivatives^{19,20,21,22,23,24}, and is used to label amino acids and glycans^{17,25,26,27,28}. Apart from the use of click chemistry, synthetic polymers of glycocalyx component Mucin-1 can be used to modulate glycocalyx thickness and enable the study of dynamic glycocalyx distribution upon ECM contacting, but this approach only addresses Mucin-1^5,29,30, and thus might not accurately represent the dynamics of other glycoproteins and the glycocalyx in total.

Non-perturbing metabolic labeling of cells followed by DBCO-based click chemistry to visualize the glycocalyx can achieve detection of glycan-rich regions; however, regions with intermediate to low levels of glycans are difficult to visualize due to low signal-to-background levels^17,21,26,31. In order to improve labeling efficiency, we here establish metabolic cell labeling followed by click chemistry using the recently developed highly reactive cycloheptyne TMTHSI (THS)^32,33 for live-cell detection of the glycocalyx, without perturbing cell integrity.

In this work, we demonstrate strongly accelerated glycocalyx labeling with higher efficiency than DBCO-based technology, to reliably detect glycocalyx micro- and nanodomains using superresolution microscopy, using our improved synthesis procedure for THS³³. Using THS-based labeling, we map the glycocalyx in 3D ECM models and establish an inventory of adaptive gradients and domains with low glycocalyx abundance in cell protrusions, cell-cell contacts and focal adhesion contacts to the extracellular matrix. The provided insight in glycocalyx dynamics leads to a better understanding of the biology of tumor cells.

Results

Live-cell labeling of the glycocalyx using THS-based click chemistry

To establish high-efficiency glycocalyx visualization, strain-promoted azide-alkyne cycloaddition (SPAAC) using cycloalkyne THS (3,3,6,6-tetramethyl-1-thiacyclo-heptyne sulfoximide)³³ was applied in live-cell culture. Compared to the much more commonly applied DBCO (k₂ = 0.31 M^-1s^-1; log P = 3.5), THS achieves higher second-order reaction rate constants in SPAAC (k₂ = 0.8 M^-1s^-1) and improved water solubility (log P = 0.7) (Fig. 1a)^19,32,34,35. Comparison of the single-crystal X-ray structures of THS and DBCO reveals that the almost symmetrical C–C ≡ C bond angles of 150.99° and 151.37° on each side of the alkyne in THS are smaller than those in DBCO, which has asymmetrical bond angles of 154.16° and 152.26° (Fig. 1b)^33,36. It appears that the smaller bond-angles in THS³³ are a prominent cause for the higher reactivity when compared to DBCO, as was described for other strained alkynes³⁷. In addition, we envisioned that the small ring size of THS favors reactivity with substrates embedded in crowded environments (e.g., the glycocalyx, Fig. 1c) and further suppresses apolar interactions (“observer effect”) which may label unintended target molecules^32,38. The THS warhead was tethered to charged fluorophores, isomerically pure AlexaFluor-488 and SulfoCy5, using a short polyethylene glycol (PEG) linker (Fig. 1d), resulting in water-soluble probes THS-AF488 and THS-SulfoCy5 (see Supplementary Information for synthetic procedures and crystallographic details of THS and of DBCO).

**Fig. 1: Improved glycocalyx detection after THS-based live-cell labeling.**

Using these probes, SPAAC was performed in live-cell culture to link the fluorophore via a triazole to the azide-functionalized glycocalyx. For this, B16F10 melanoma cells were cultured in the presence of the azidosugar tetra-acetylated N-azidoacetyl-D-mannosamine (Ac₄ManNAz) for five days. High lipophilicity due to peracetylation of Ac₄ManNAz allows passive diffusion across the cell membrane into the cell, where it is deacetylated and metabolized to azide-carrying sialic acid, and subsequently incorporated into glycoproteins, including the cell surface glycocalyx^39,40. To limit membrane turnover and internalization during SPAAC labeling, azido sugar-labeled cells were incubated with THS- or DBCO-conjugated fluorophore at 4 °C. Whole-cell fluorescence increased with prolonged SPAAC incubation in a linear fashion with increasing signal-to-background ratio over 60 min of incubation (Supplementary Fig. 1a). Cell viability remained unaffected (> 98.5% live cells) directly after 60-min THS/ DBCO labeling and after 24 h (Supplementary Fig. 1b, c). Nonetheless, due to the extreme reactivity of the head group, the SPAAC reaction at 4 °C may cause collateral damage to functionally relevant biomolecules. To address whether THS labeling introduced more subtle, sublethal cell stress that can potentially impact cell function, live-cell reporters for reversible nuclear and/or oxidative stress-related damage were used⁴¹. Neither the DNA damage response as detected by 53BP1trunc-mApple (Supplementary Fig. 1d) nor calcium elevation associated with endoplasmic reticulum stress, mitochondrial stress, and oxidative stress as detected by GCamP6s^42,43,44,45 were induced by SPAAC-labeling (Supplementary Fig. 1e). Finally, to exclude that metabolic labeling causes subtle cell perturbation and cell stress, we assessed transcriptional changes. The transcriptome of Ac₄ManNAz-treated cells indicated4 differentially expressed of identified 20501 genes, without differential clustering between samples and/or detectable regulated pathways compared to untreated cells (Supplementary Fig. 1f, g). These changes are within the expected range of statistical error due to random variations. Thus, metabolic uptake and THS labeling did not cause detectable cell stress, transcriptional changes, or cell death.

To verify that THS-based metabolic labeling represents the glycocalyx broadly, rather than selective glycan subspecies and/or subdomains, colocalization analysis with Concanavalin A (Con A) and hyaluronic acid (HA) binding protein (HABP) was performed (Supplementary Fig. 2a). Con A binds α-glucopyranose and α-mannopyranose residues and is an acknowledged broad-band glycocalyx probe for fixed samples^46,47, while HA is a secreted bulky polysaccharide that binds to the cell surface⁴. Moreover, we compared Ac₄ManNAz with alternative metabolic labels, including Ac₄GalNAz and Ac₄GlcNAz. Ac₄GalNAz is metabolized into N-acetylgalactosamine, which is the core residue of mucin-type O-linked glycans and is present in glycolipids, chondroitin sulfate proteoglycans and as a terminal residue of rare N-linked glycans²². Ac₄GlcNAz selectively labels glycoproteins that carry β-O-N-acetylglucosamine residues, though often at low efficiency^22,24. At single pixel resolution, the Ac₄ManNAz and Ac₄GalNAz labels conjugated with DBCO or THS strongly colocalized with Con A (colocalization coefficient >0.90), and Ac₄GlcNAz colocalized with ConA with lower efficacy (coefficient ~0.83) (Fig. 1e, Supplementary Fig. 2b). Likewise, all tested labels strongly overlapped with HABP (colocalization ~0.85) (Supplementary Fig. 2c). Whereas Con A binding positionally overlapped with all metabolic glycan labels, HABP localized beyond the glycan label, forming an HA-rich outer rim in the submicron range (Supplementary Fig. 2c, inset, arrowheads). Notably, no further subregions of exclusive distribution of either signal was detected (Supplementary Figs. 2b, c, insets). Further, colocalization scaled with high azido-sugar label intensity (Supplementary Fig. 2d), indicating that the metabolic label effectively detects the glycocalyx non-selectively, except the very outer HA-rich domain. When directly compared, using the same secondary label, Ac₄ManNAz achieved ~2.4-fold and ~17-fold higher fluorescence intensity than Ac₄GalNAz and Ac₄GlcNAz, respectively (Supplementary Figs. 3a, b). We validated the broad detection range of Ac₄ManNAz in B16F10 cells, resulting in comparably high colocalization with Con A (Fig. 1e). Thus, Ac₄ManNAz labeling broadly represents the glycocalyx. Due to its superior labeling efficacy compared to the other tested azidosugars, we performed all subsequent experiments using Ac₄ManNAz.

To determine whether THS indeed resulted in increased conjugation efficiency compared to DBCO, cellular and subcellular fluorescence was detected. Compared to DBCO, THS labeling increased the average whole-cell fluorescence by 1.7-fold as detected using flow cytometry (Fig. 1f; Supplementary Fig. 3c) and 1.5-fold as detected using fluorescence microscopy (Fig. 1g, left, Supplementary Fig. 3a, b). Treatment of cells with DBCO or THS without prior metabolic labeling with an azidosugar did not cause fluorescence above background levels (Fig. 1g, right), indicating that non-specific interactions with the membrane are below detectable levels for both probes. The Ac₄ManNAz labeling resulted in a >5-fold increased fraction of cells with high glycocalyx using the THS reaction (based on the 95^th percentile of DBCO as a reference) for different detection methods, including flow cytometry (Fig. 1f, right panel), low-resolution microscopy (Fig. 1g, middle panel), and high-resolution microscopy (Fig. 1h, Supplementary Fig. 3d). This included a significantly improved signal-to-background ratio (Fig. 1h, Supplementary Fig. 3e–g).

To substantiate the combined benefits of increased frequency of cells with high glycocalyx label and increased signal-to-noise ratio for detecting domains of differential glycocalyx density, we examined the glycocalyx in small membrane blebs on the cell surface⁴⁸ in 3D collagen matrix culture. Membrane blebs are micrometer-sized protrusions that, besides preceding apoptosis⁴⁸, are formed by cells migrating to contact the ECM^49,50. THS labeling resulted in a 6-fold enriched and ~40% brighter glycocalyx^high cell subset compared to DBCO (Fig. 1i). Robust glycocalyx detection on blebs was obtained in the glycocalyx^high but not in the glycocalyx^median subset, based on the deviance (goodness-of-fit) and signal-to-noise ratio of the signal at the membrane vs. cytoplasm (Fig. 1j, k). Moreover, within glycocalyx^high cells, the glycocalyx detection using THS was improved 1.34-fold (deviance) and 1.26-fold (signal-to-background) over DBCO-labeled cells (Fig. 1j, k, Supplementary Fig. 3h). In aggregate, THS-based labeling outperforms DBCO-based click chemistry by shifting the spectrum of intensities and increasing the frequency of glycocalyx^high subsets, which jointly results in ~5-fold improved sampling efficiency in whole cells and, particularly, subcellular structures.

Reduced glycocalyx density at cell-cell-contacts

To address whether the glycocalyx is generally uniformly distributed at the cell surface and only redistributes when cells interact with their environment, Airyscan microscopy with ~160 nm lateral and ~370 nm axial resolution (Supplementary Fig. 4a) was used to quantify the THS-signal in contact-free membrane segments and cell-cell contacts, and the interconnecting zone between both zones (Fig. 2a, Supplementary Fig. 4b, c for image analysis). After Ac₄ManNAz-metabolic labeling, glycocalyx labeling was uniform in contact-free membranes, and non-clustered with random local variation by ~20% (Fig. 2b). Likewise, glycocalyx distribution remained diffuse and non-clustered along cell-cell interactions with median ~1.58-fold (fixed) and ~1.39-fold increased fluorescence intensity compared to contact-free single membrane zones (Fig. 2b, c, Supplementary Fig. 4d). Additionally, the analysis was performed after Ac₄GalNAz-metabolic labeling followed by THS-SPAAC or HABP staining. With a uniform labeling and a median fluorescent intensity of ~1.65-fold the single-membrane intensity in the cell-cell contact (Supplementary Fig. 5a), Ac₄GalNAz labeling was very similar to Ac₄ManNAz. HABP displayed a clustered pattern at the membrane, and a median ~0.38-fold the intensity of the single membrane zones at cell-cell contacts, which indicates HA exclusion from the cell-cell contact (Supplementary Fig. 5b). Without glycocalyx redistribution, the fluorescence in cell-cell contacts was expected two-fold of the contributing single membranes, thus the detected glycocalyx enrichment was subadditive. We ruled out effects by potentially confounding technical parameters that could account for subadditive signal in cell-cell-contacts, including fluorophore bleaching, saturation and quenching (Supplementary Fig. 6a, b). We further excluded the possibility of label mobility out of the cell-cell contact after fixation, using fluorescence recovery after photobleaching (Supplementary Fig. 6c). Thus, cell-cell contacts were relatively depleted of glycocalyx, compared to contact-free membrane.

**Fig. 2: Reduced glycocalyx density in cell-cell contacts.**

We hypothesized that glycocalyx depletion in cell-cell contacts requires glycoprotein flux away from the cell-cell contact and tested whether a gradient-like density change was present in the transition zone. Therefore, we calculated the steepness of the glycocalyx gradient between contact-free and interacting membrane. The transition zone contained a shallow negative intensity gradient away from the cell-cell contact with variable length between individual contacts, ranging from below 1 µm to >4 µm (Fig. 2e; average 1.7 ± 0.48 µm). The transition zone length positively correlated with the amplitude of the intensity difference (Fig. 2e), suggesting previously unappreciated gradient-driven glycocalyx redistribution out of the cell-cell contact.

To monitor whether differential glycocalyx-flux accounted for glycocalyx redistribution out of cell-cell contacts, we monitored fluorescence recovery after photobleaching (FRAP) in the transition zone between single membranes and cell-cell contacts in live cell (Supplementary Fig. 7a, b). To account for potential gradient-driven mobility, we subdivided transition zones in single membrane and cell-cell contact subsegments to spatially resolve monitored fluorescence recovery and calculated the time required for half-maximum fluorescence recovery (Supplementary Fig. 7c). Across the transition zone and without apparent spatial gradient, the glycocalyx half-maximum recovery time was ~40% reduced, i.e. the recovery speed increased, compared to glycocalyx in contact-free membrane and equal to the dynamics in cell-cell contacts (Fig. 2f, g). These data suggest increased glycan mobility may account for the subadditive glycocalyx density in cell-cell-contacts.

Submicron-scale redistribution of glycocalyx in focal ECM contacts

To assess whether the glycocalyx becomes excluded from cell-ECM contacts, as predicted using 2D adhesion and glycocalyx probing using artificial glycomimetic polymers⁵, we labeled the glycocalyx on live MV3 melanoma cells migrating in fibrillar collagen, fixed the samples and co-registered glycocalyx and β1 integrin adhesion receptors. MV3 melanoma cells develop mesenchymal migration, which depends on integrin engagement and clustering at contacts to ECM, while integrins remain non-clustered in membrane regions lacking contact to ECM^51,52. Upon initiating migration, MV3 cells developed leading edge protrusions (Fig. 3a, inset 1; for analysis pipeline, Supplementary Fig. 8a), lateral blebs (Fig. 3a, inset 2), as well as retraction fibers that remain tethered to the collagen network from the cell rear (Fig. 3a, inset 3; Supplementary Fig. 8a). Cell regions without contact to collagen contained evenly distributed β1 integrin (Fig. 3a, inset 4; Supplementary Fig. 8b), whereas cell regions contacting individual collagen fibrils, including leading pseudopods and retraction fibers, contained β1 integrin clusters of varying size with diameters ranging from 0.3 to 2.9 µm (Fig. 3b, white arrowheads, Fig. 3c).

**Fig. 3: Submicron glycocalyx segregation in cell-matrix adhesions.**

On the submicron scale, we noticed an outward phase-shift of the β1 integrin cluster relative to the more inward glycocalyx layer (Fig. 3b, white arrowheads) and, hence, analyzed potential molecular segregation. In membrane segments containing non-focal β1 integrin, β1 integrin and glycocalyx both displayed even, non-focal distribution in membrane-parallel orientation (Supplementary Fig. 8b), and also were highly colocalized when the membrane was cross-sectioned (Supplementary Fig. 8c). In contacts to collagen with β1 integrin clustered, a biphasic distribution relative to the glycocalyx position with an outer major β1 integrin peak and an inner zone with lower β1 integrin levels was detected (Fig. 3d, e, blue arrowhead/box), while the glycocalyx signal was inversely distributed with diminished intensity in the outward β1 integrin-dense cluster (Fig. 3d, e, white arrowhead, Supplementary Fig. 8d). To test relative abundance in inner compared to outer subregions of the integrin cluster, we calculated β1 integrin and glycocalyx enrichment using their respective intensity directly adjacent to the inner zone as a reference (Supplementary Fig. 8e). Across multiple clusters, the inner nanodomain was neither significantly enriched nor depleted in β1 integrin, while the outer domain was enriched by ~1.7-fold (Fig. 3f). Notably, the inner zone lacked any change of glycocalyx distribution, while the outer cluster contained 2-fold reduced glycocalyx levels (Fig. 3g). The spatial distance between inner and outer integrin and glycocalyx nanodomains ranged from 160 nm or below (i.e., the lateral resolution of the microscope) up to ~1.7 µm (median ~350 nm) (Fig. 3h). To test whether the local abundance of glycocalyx was associated with stronger integrin clustering, we cross-correlated integrin enrichment in the outer ECM contact with its locally adjacent glycocalyx level. In the outer domain, β1 integrin and glycocalyx density were uncorrelated (Fig. 3i). Likewise, no association of outer β1 integrin cluster and matched glycocalyx intensity was detected in the inner zone (Supplementary Fig. 8f). Since both β1 integrin and glycocalyx are membrane-bound, we examined whether the segregation domain corresponds to locally confined membrane protrusions, which contain filamentous actin⁵³. Indeed, outward β1 integrin clusters segregated from glycocalyx in association with protrusive filamentous actin (Supplementary Fig. 8g, arrowheads). These data indicate that focal contacts to collagen fibrils consist of two nanodomains associated with submicron-scale protrusions containing an outer domain with high β1 integrin and low glycocalyx content and an inner domain lacking integrin and glycocalyx segregation.

Micron-scale redistribution of the glycocalyx in cell protrusions

Besides nanoscale glycocalyx depletion in focal contacts, micron-scale reduction of glycocalyx was detected in cell protrusions, independent of β1 integrin clustering. Membrane regions free of collagen contact as well as membrane zones at the rear of leading edge protrusions containing β1 integrin clusters containeded uniform glycocalyx distribution at baseline levels, however the intensity of the glycocalyx at β1 integrin clusters located at the shaft and the front of the leading pseudopod was decreased by 2- and 4-fold, respectively (Fig. 4a–c). The length of these glycocalyx-depleted zones reached up to several microns, with a gradual transition zone between glycocalyx^low to the glycocalyx^high compartments spanning, typically, several µm and several β1 integrin clusters (Fig. 4d).

**Fig. 4: Micron-scale glycocalyx segregation from the outer poles of leading-edge protrusions, blebs and retraction fibers.**

We next tested whether regions of high glycocalyx abundance are associated with stronger integrin clustering, as predicted by studies that investigated glycocalyx displacement upon cellular interaction with planar ECM^5,6. While the level of β1 integrin within β1 integrin clusters was indifferent along the length of leading edge protrusions (Supplementary Fig. 9a), β1 integrin clusters in glycocalyx^low pseudopodal protrusions (Fig. 4e, red zone) were locally enriched, by 3.2-fold, while in glycocalyx^high domains, local integrin enrichment in clusters reached only 1.9-fold enrichment (Fig. 4e, f, blue zone/label). Conversely, no local change of glycocalyx density was detected in integrin clusters along these pseudopods regardless of locally adjacent glycocalyx abundance (Supplementary Fig. 9b, c). Thus, even though β1 integrin clustering was favored in glycocalyx^low regions, no lateral segregation of glycocalyx from β1 integrin clusters was detected.

In membrane blebs, β1 integrins were non-clustered, with levels reduced in the apex and gradual increase towards the neck and bleb-adjacent zone (Fig. 4g, h; Supplementary Fig. 9d) Likewise, the glycocalyx was non-clustered in blebs, but the intensity was reduced by 2-fold using the bleb-adjacent cell body as a reference (Fig. 4h, i, Supplementary Fig. 9e). When cross-correlated pairwise, for each bleb, glycocalyx and integrin gradients from bleb neck to apex were concordant in steepness, and co-depleted towards the bleb apex in the majority ( ~ 69%) of blebs (Fig. 4j). These data suggest that glycocalyx and integrins co-migrate from the bleb neck towards the bleb apex.

Retraction fibers are membrane extensions from the rear of the forward-moving cell that remain attached to the solid substrate⁵⁴. Similarly to leading edge protrusions, glycocalyx was lowest at the outer end of retraction fibers (4-fold decreased), with an extended gradual transition zone over tens of µm towards the cell body (Fig. 4k, n). As in leading protrusions, no association of glycocalyx intensity with the position and intensity of β1 integrin clusters along the same retraction fiber was detected (Supplementary Fig. 9f). Thus, retraction fibers contain long-range glycocalyx gradients near β1 integrin clusters, with equal levels of β1 integrin.

In summary, in protrusive pseudopods, blebs, and retraction fibers, irrespective of cell-matrix interactions, the glycocalyx undergoes a redistribution towards low abundance and, thereby, may create microdomains that favor integrin availability for interacting with ECM.

Discussion

In combination with 3D Airyscan microscopy, THS-based fast SPAAC click chemistry revealed previously unappreciated nanoscale and micron-scale phase separation of the glycocalyx from cell-cell and cell-matrix interactions. We identified five types of glycocalyx segregation with distinct scale, localization and, likely, function: (i) nanoscale glycocalyx depletion from actin-rich nanoprotrusions containing integrin clusters in contact with ECM; micron-scale depletion in cell protrusions including (ii) leading pseudopods, (iii) blebs, and (iv) retraction fibers; as well as (v) moderately reduced abundance in cell-cell contacts (Fig. 5). These results establish THS as a standard for copper-free click chemistry for sensitive non-perturbing glycocalyx detection in live-cell biology to probe its role in complex cell functions in 2D and 3D environments.

**Fig. 5: Spatially and functionally distinct domains of glycocalyx segregation.**

THS-based bio-orthogonal chemistry, which enables increased reactivity and reduced hydrophobicity over contemporary probes³², was previously used for conjugation of non-living matter, including proteins⁵⁵, nanoparticles^56,57, and antibodies⁵⁸. We here showcase that the significantly improved reaction kinetics of THS-based click chemistry are also suitable for live-cell labeling and enable enhanced intensity and a higher signal-to-background ratio of glycocalyx labeling compared to contemporary (i.e., DBCO-based) labeling. Non-specific effects, particularly against thiols, are known to occur for both peracetylated sugars and strained alkynes^59,60,61. This alkyne of THS is even more strained than in DBCO, based on the bond angle in the crystal structures (Fig. 1a, b), yet non-specific labeling at the membrane or toxicity-inducing off-target towards cell structures was not detected. This low off-target reactivity towards cellular structures may be explained by the slow reaction rate of such competitive reactions compared to SPAAC in physiological conditions⁵⁹. Using sensitive damage sensors, including Ca²⁺ transients, which report even sublethal, reversible phototoxicity^41,45, we ruled out even subtle cell stress by THS, which was comparable to DBCO labeling. The increased labeling efficacy of THS enables particularly quick live-cell labeling. This minimizes glycan internalization and turnover during the labeling period and enables precise detection of glycocalyx micro- and nanodomains at the cell surface.

Using THS labeling, we uncover previously unappreciated 3D nanodomains that segregate the glycocalyx from cell-matrix adhesions. Our data support the concept of nanotopographic segregation of integrin clusters from the glycocalyx layer when engaging with a natural fibrillar ligand (Fig. 5a). Since integrins are ~5-10 nm in size^62,63 and surrounded and exceeded in size by glycocalyx, glycocalyx thickening has previously been shown to impact integrin-based adhesion or clustering on rigid glass substrates^5,6,14. Our data using non-perturbing glycan labeling indicate that integrin-rich nanodomains segregate from the glycocalyx domain, independent of the glycocalyx content immediately adjacent to integrin clusters. The finding that integrin-rich adhesions can segregate into a two-domain contact to collagen fibrils, with an outward integrin cluster surrounded by low glycocalyx abundance, implicates a topography-based segregation mechanism. We here detected endogenous glycocalyx in cells migrating in a 3D fibrillar matrix, which represents physiological, soft-tissue rigidity⁶⁴. The fibrillar environment enables actin-rich protrusive 3D nanodomains with integrin-glycocalyx segregation. The setpoints, topology and extent of integrin-glycocalyx segregation in 3D nanodomains may differ from adhesive interactions with 2D planer stiff substrate which precludes integrin and glycocalyx segregation within protrusive domains^5,6.

As a morphologically distinct process, we observed large-range micron-scale glycocalyx depletion towards the apical pole of leading pseudopods, which coincides with stronger integrin clustering at cell-ECM contacts in this domain (Fig. 5b, I). Here, depletion of glycocalyx might form a zone of high integrin sensitivity, where steric integrin-glycocalyx competition is reduced, thus resulting in high-efficiency integrin clustering, facilitated ECM binding and force generation in a region of high actin flow (Fig. 5b, II)¹⁴.

Protrusion shape can be regulated by high-density glycoproteins due to their high intermolecular steric and electrostatic repulsion^2,65. However, integrin-rich nanoprotrusions contacting collagen contained filamentous actin, suggesting that actin protrusiveness rather than intrinsic electrostatic properties of the glycocalyx regulates protrusion shape and size when connecting to the ECM^66,67. Internal pressure perpendicular to the membrane exerted by the actin bundle can cause glycocalyx translocation towards non-compressed regions, as shown by mathematical modeling⁶⁸. Thus, cytoskeletal-induced outward pressure rather than glycocalyx-intrinsic properties may explain glycocalyx depletion in collagen-engaged integrin clusters located on nanoprotrusions.

In emerging protrusions at the cell tip, the membrane is dynamically pushed by polymerizing actin filaments^69,70,71. As a consequence, membrane flow may outperform the movement of glycoproteins⁷². Consistently, bulky glycoproteins preferentially do not localize to the leading edge in migrating cells^73,74. Similarly, membrane blebs displayed a micron-scale glycocalyx gradient (Fig. 5c), potentially caused by their fast emergence and membrane flow. Blebs protrude within (milli)seconds, are driven by internal hydrostatic pressure, and are halted by F-actin assembly at the bleb cortex^75,76. Bleb formation can occur with a speed of 2.5 µm/s⁴⁹, resulting in transient detachment from the underlying cortical actin network⁴⁹. Though diffusing membrane proteins move faster than cytoskeleton-anchored proteins⁷⁶, blebs protrude even faster than the lateral mobility of lipids in the membrane of 1-2 µm/s^70,77. Thus, based on the delayed mobility of glycoprotein movement compared to the rapidly extending membrane, protrusive tips at the leading edge and membrane blebs may contain reduced glycocalyx content compared to non-protrusive compartments.

Lastly, glycocalyx density was underrepresented in cell-cell contacts, which represented a compartment of accelerated glycocalyx mobility and gradient-like redistribution towards the single-membrane zone (Fig. 5e). Redistribution from cell-cell contacts is reminiscent of kinetic glycocalyx mobility and segregation, which predicts that in zones of tight membrane apposition between T cells and antigen-presenting cells, large glycoproteins are sterically excluded to facilitate T cell receptor engagement MHC¹⁰.

In aggregate, our data indicate distinct scales and mechanisms of dynamic redistribution of the glycocalyx out of cell-matrix and cell-cell contacts. The here identified spatial/ segregation mechanisms of glycocalyx, including outward positioning of integrin clusters in protrusive nano- and microdomains, support the concept of topographic heterogeneity of glycocalyx organization and threshold regulation of receptor-ligand interactions.

Methods

For synthesis of THS, molecular and analytical details, and fluorophore conjugation, see Supplementary Methods, Supplementary Figs. S10–S17, Supplementary Tables 1–8 and Supplementary References.

Cells and cell culture

Mouse B16F10 cells (RRID:CVCL_0159) that express the ovalbumin-derived CTL epitope SIINFEKL (B16F10-OVA, used in previous studies^41,78; further referred to as B16F10) were generated by electroporation after obtaining as B16F10 from ATCC (CRL-6475). MV3 cells (RRID:CVCL_W280) were provided by G. van Muijen, Dept. of Pathology, RadboudUMC, Nijmegen, the Netherlands. The identity of B16F10 and MV3 cells was verified by short tandem repeat DNA profiling (IDEXX BioResearch). No respective mammalian or mouse interspecies contamination was detected. Lack of contamination with mycoplasma was routinely verified using the MycoAlert Mycoplasma Detection Kit (Lonza, LT07-318).

Cells were cultured in RPMI 1640 medium (GIBCO, 21875-034) supplemented with 10% FCS (SIGMA, F7524), 1% sodium pyruvate (GIBCO, 13360-039), and 1% penicillin and streptomycin (PAA, P11-010).

Metabolic labeling and SPAAC

For metabolic labeling, 50 µM 1,3,4,6-tetra-O-acetyl-N-azidoacetylmannosamine (Ac₄ManNAz; Carbosynth, MA46004) was added to the culture medium for 5 days (refreshed every 3 days). To assess glycocalyx labeling intensity for method optimization and at cell-cell contacts in 2D culture, cells were seeded in 8- or 18-well microscopy plates prior to fixation (Ibidi, Cat# 80826 and Cat# 81816, respectively). To determine glycocalyx at cell-matrix interactions during MV3 cell migration initiation, MV3 cells were embedded in 3 mg/mL rat-tail collagen (Corning® GmbH HQ, Cat# 354249, LOT# 9280010, stock 9.33 mg/mL). Collagen fibrils were visualized using Alexa Fluor 568-conjugated rat-tail collagen during polymerization. To generate fluorescent collagen, gels (3.4 mg/mL, pH 7-7.4), were prepared by mixing rat-tail collagen (Corning® GmbH HQ, Cat# 354249, LOT# 9280010, stock 9.59 mg/mL), MEM (10X concentrated, Sigma-Aldrich, Cat# M0275), NaOH (Merck KGaA, Cat# 106462), and Milli Q. 100 µL droplets were pipetted and polymerized (37 °C, 30 min, washed 2x, PBS and 1x, 0.2 M bicarbonate buffer (0.2 M NaHCO₃ with Na₂CO₃ to end pH of 8.3), RT, 10 min). 5 gels were combined and mixed with 800 µL 1 mM Alexa Fluor 568 carboxyl acid-succinimidyl ester (Invitrogen, Cat# A-20003, Lot# 953612, in 0.2 M bicarbonate buffer) and incubated (overnight, 4 °C, washed 3x, 1 minute, 6×30 min, PBS), dissolved (400 µL 20 mM HCl, 48 h), mixed on ice and incubated for another 24 h (overnight, 4 °C). Subsequently, cells were added a mixture of rat-tail collagen with a labeled: unlabeled ratio of 1:30 and MEM, and neutralized (pH 7-7.4) using NaOH and diluted to 3 mg/mL using 10X PBS and Milli Q. The cell-collagen suspension was pre-polymerized (5 min, 20 °C) and 25 µL droplets were pipetted in an 48-well plate and polymerized (37 °C, 20 min, plate turned each minute), followed by addition of medium. After 5 days of metabolic labeling, cells were allowed to initiate invasion in 3D collagen for 6-24 h. To detect sialic acid-containing surface glycans, a strain-promoted-azide-alkyne cycloaddition (SPAAC) reaction was performed in live cell culture in 2D or 3D collagen-based culture. B16F10-OVA or MV3 cells were washed (3x, PBS, 10 min), incubated with DBCO-Alexa Fluor 488 (Jena Bioscience, Cat# CLK-1278-AZ-1), DBCO-sulfo-Cy5 (Lumiprobe, Cat# 133F0), THS-Alexa Fluor 488 or THS-sulfo-Cy5 (all 50 µM, 60 min, 4 °C), washed 3x (PBS, 10 min) and subjected to flow cytometry or live microscopy. Alternatively, samples were fixed after the SPAAC reaction (2% PBS-buffered PFA, 30 min, 20 °C), washed 3x (PBS, 10 min). Fixed cells were stored in 0.05% NaN₃ in PBS at 4 °C.

Flow cytometry

For whole-cell surface detection of glycans, cells were detached (2 mM EDTA, 20 min), washed (3x, PBS, 4 °C), resuspended in medium, and stained with SytoxBlue viability dye (2.5 µM; ThermoFisher Scientific, S11348) directly prior to flow cytometry (BD MACSQuant). For fluorescence detection, cells were gated on intact morphology using FlowJo software (V10.4), based on FSC-SSC gating and lack of Sytox Blue staining using the V450 detector (Supplementary Fig. 1b).

Live-cell microscopy and fluorescence recovery after photobleaching

To determine whether metabolic glycan labeling and SPAAC reaction introduced cell stress by sublethal damage, DNA damage, and cytoplasmic calcium transients were co-registered in live B16F10-OVA cells expressing 53BP1-mApple (DNA damage sensor) and GCaMP6s (calcium sensor) by widefield microscopy (Zeiss Axio Observer live imager; 20x/1.2 NA air objective).

To record relative intensity of glycocalyx in cell-cell contacts compared to single membrane regions in live cells and for fluorescence recovery after photobleaching (FRAP) analysis, perpendicularly-oriented membrane regions containing either interconnected membrane regions with single membrane, transition zone and cell-cell contact or granules (as control) were selected in B16F10 cells after metabolic labeling and THS-AF488-based SPAAC and imaged using a confocal microscope (Zeiss LSM880, 63x/1.4NA objective, 1.0 A.U; voxel size 0.083×0.083×1.0 µm). Fluorescence was measured for 10 frames (0.92 ± 0.17 sec/frame), and for FRAP analysis, fluorophores were subsequently bleached with 100% laser power of the Argon laser (488 nm; 20 iterations), after which fluorescence was monitored in the bleached and surrounding regions for 70 frames. For FRAP analysis, line ROIs were subdivided into subregions (0.336 µm), which were normalized to the minimum and maximum to generate FRAP curves (Supplementary Fig. 7a–c) and considered bleached when bleaching was higher than 40% and lower than 80%.

Fluorescence labeling and microscopy of fixed samples

To quantify lateral and axial resolution, 100 nm beads (Tetra Speck™, Thermo Fisher Scientific, Cat# T7284) were embedded in 1% agar in MilliQ. For Concanavalin A (Con A)- THS/DBCO and HA-binding protein (HABP)-THS/DBCO colocalization analysis, cells were washed 3x (PBS, 10 min, 20 °C) and stained using Concanavalin A-AlexaFluor647 conjugate (50 µg/mL, Invitrogen, Cat# C21421; 30 min, 4 °C) or biotinylated HABP (5 µg/mL, Sigma-Aldrich, Cat# 385911; overnight, 4 °C) together with DAPI (1 µg/mL, Sigma-Aldrich, Cat# D9542). HABP was detected after washing 3x (PBS, 10 min, 20 °C) followed by incubation with Streptavadin-AlexaFluor647 (using 10 µg/mL, Invitrogen™, Cat# S21374; overnight, 4 °C). For β1 integrin staining, collagen-embedded cells were incubated in blocking buffer (1 % bovine serum albumin, Sigma-Aldrich, Cat# A9647; 10 % normal goat serum, Thermo Fisher Scientific, Cat# 10000 C; PBS, 1 h, 20 °C), incubated with a mixture of two mouse anti-human β1 integrin antibodies (clone K20, Novus Biochemicals, NBP2-52708; clone 4B4LDC9LDH8, Beckman Coulter, 6603113; both 10 ug/mL in 50 µl, blocking buffer, 24 h, 4 °C, mild agitation), washed 3 times (blocking buffer, 15 min, 4 °C) and incubated with secondary antibody mouse IgG (H + L) highly cross-adsorbed AlexaFluor647 (2 µg/ml in 50 µl, Thermo Fisher Scientific, Cat# A21236, 24 h, 4 °C), 1 µg/mL DAPI (Merck, Cat# D9542), and when non-fluorescent collagen was used, with 2U/ml Phalloidin-Alexa Fluor 568 (Thermo Fisher Scientific, Cat# A12380) (washed again 3x, PBS, 15 min, 4 °C).

Unless stated otherwise, fixed imaging was performed using a Zeiss LSM880, Airyscan mode, Plan-Apochromat 63x/1.4NA oil objective, voxel size 0.042×0.042×0.17 µm. Airyscan imaging is a type of pinhole-plane image-detection approach based on an area detector subdivided in 32 elements functioning as small pinholes, allowing for ~1.7-fold the resolution of traditional diffraction-limited confocal microscopy after linear deconvolution⁷⁹. For Con A-THS/DBCO colocalization analysis, high-resolution imaging of cell-cell and cell-matrix contacts was obtained using confocal structured illumination microscopy. For pixel-based large-field analysis, cells were imaged in Airyscan mode (Plan-Apochromat 20x/0.8 NA objective, 8-bit, voxel size, 0.21 × 0.21 × 1.5 µm). For comparative whole-cell glycocalyx detection using THS or DBCO labeling, cells were additionally stained using DAPI (1 µg/mL; 30 min, 20 °C, washed 3x in PBS), and scanned at low-resolution (Plan-Apochromat 10x air objective, 0.45 NA, 1.0 A.U, 8-bit, voxel size 1.38 × 1.38 × 2.54 µm).

To control for potential fluorophore bleaching during 3D microscopy, single slices were continuously scanned with a 200 ms interval using 0.5%, 1%, 3% and 10% laser power. To study intensity saturation and exclude potential fluorophore quenching in dependence of high labeling density and laser intensity, identical regions were sequentially exposed with 0.13%, 0.25%, 0.5% and 1% laser power. To examine post-fixation preservation of lateral glycocalyx mobility, regions of interest (ROIs) were bleached (90% laser power) or left unbleached and fluorescent recovery was monitored over 20 min (5 frames/minute) using low (0.02%) laser power (Apochromat 20x objective, 0.7 NA, 1.6 A.U, voxel size 0.073×0.073×1 µm).

RNA isolation and bulk RNA sequencing

RNA was isolated according to the manufacturer's instructions of the Aurum™ Total RNA Mini Kit (Bio-Rad, Cat# 7326820). RNA concentration was measured using a Nanodrop™ 2000 spectrophotometer (Thermo Scientific™). Total RNA was used for RNA sample preparation and library construction using RNA Library Prep Kit for Illumina with rRNA removed. Standard RNA sequencing was performed by Novogene GmbH (Munich, Germany) on the Illumina NovoSeq X Plus platform based on the required library concentration with the PE150 strategy. Quality control was performed using Fastp⁸⁰ (v0.23.1). Clean reads were then aligned to the reference genome using Hisat2⁸¹. Stringtie⁸² (v1.3.3) was used to assemble and quantify transcripts based on mapping results, with library-specific parameters enhancing accuracy. Transcripts from concatenated samples were merged and compared against known databases using Gffcompare (v0.10.6) to filter known transcripts and predict coding potential. Finally, transcript expression levels were quantified using fragments per kilobase of transcripts per million mapped reads (FPKM).

Differential gene expression analysis was conducted using edgeR⁸³ to identify significant expression differences. Analysis involved standardizing raw read counts to correct for sequencing depth, calculating p-values using a statistical model, and applying multiple hypothesis testing to obtain FDR values. Differential gene expression data were analyzed in R (v4.3.2). Principal Component Analysis (PCA) was performed using the prcomp function on scaled expression data.

Gene set enrichment analysis (GSEA) was performed to identify enriched biological pathways and functional categories in the differentially expressed gene (DEG) dataset. ENSEMBL gene IDs from the DEG dataset were mapped to ENTREZ IDs using the org. Mm.eg.db annotation package. Only genes with valid ENTREZ IDs were included, and they were ranked by log2 fold change, with higher values indicating upregulation and lower values indicating downregulation. GSEA was conducted using the clusterProfiler (v4.0)^84,85, ReactomePA (v1.36)⁸⁶, and DOSE (v3.18)⁸⁷ R packages. Functional enrichment analyses were performed for KEGG pathways using gseKEGG functions, respectively. The Benjamini-Hochberg (BH) method was applied to adjust p-values for multiple testing. Parameters for all GSEA analyses included a minimum gene set size of 10, a maximum gene set size of 500, and 1000 permutations.

Image analysis and quantification

Airyscan images were processed using standard Airyscan Processing parameters in Zen Black Software (Zeiss). Image analysis was performed using Fiji/ImageJ (Version 1.54 f). Statistical analysis and data visualization were obtained using RStudio (Version 2023.06.1+524, R version 4.3.2 using the plot package ggplot v3.5.1 or ggord v1.1.8) or GraphPad Prism (Version 10.1.0). Basic image processing consisted of background subtraction using manually selected background ROIs and signal subtraction. For multi-slice images, maximum projections of acquired z-stacks were generated. To quantify lateral and axial resolution, line ROIs with 1 pixel thickness (0.042 µm) were drawn in xy and xz direction across the middle of multiple beads, and the Full Width at Half Maximum (FWHM) values were determined by calculating the pixel offset between the maximum and half-maximum intensity, based on the smoothened average of multiple quantifications. To quantify DNA damage foci, nuclei were segmented based on the nuclear background signal of 53BP1-mApple using gaussian blur (3 pixels) and Triangle auto threshold. Nuclei were separated using watershed, and foci/nucleus counted using the find maxima plugin (prominence of 25). GCaMP6s in the cytoplasm was obtained as mean fluorescence of a 5-pixel band generated around the segmented nucleus. For colocalization analysis of THS and DBCO with Con A or HA-binding protein at the membrane, individual cells were segmented and pixels directed intracellularly from the cell membrane were manually removed to exclude signal not associated with the cell surface (e.g., endocytic vesicles) (Supplementary Fig. 2a). Pearson’s colocalization coefficient was obtained by correlating single-pixel signals of the green (THS/DBCO) with red channel (Con A/ HA binding protein) (BIOP JaCoP plugin⁸⁸) without thresholding and with mean background signals of the relevant channels of untreated condition as thresholds. In case of channel misalignment, drift correction was performed (bUnwarpJ plugin⁸⁹). The tM1 (fraction Con A/HABP overlapping glycocalyx) and tM2 (glycocalyx overlapping Con A /HABP – reverse channel order of tM1) coefficients after thresholding (thresholded Manders M1/M2 coefficients⁹⁰) were calculated at the membrane using formula (1).

$${tM}1=\frac{\sum ({I}_{{ch}1}\cap {I}_{{ch}2})}{\sum {I}_{{ch}2}}*100$$

(1)

Whole-cell fluorescence intensity was measured in segments detected using the cytoplasmic segmentation pretrained model cyto2_cp3 (restore type: denoise_cyto3) or cyto4 using the Cellpose algorithm⁹¹ in Python language (v. 3.12.4) via the Anaconda platform. To measure glycocalyx signal vs. background ratio in high-resolution imaging, single slices with perpendicularly-oriented membrane sections were selected, and 1-pixel line ROIs perpendicular to the membrane and intracellular ROIs were drawn. Cross-sectional high-resolution signal-to-noise was quantified according to Supplementary Fig. 3d. To ensure measurement of glycocalyx signal of the entire membrane, the mean signal was measured of the region flanking 1.68 µm at both sides relative to the point of highest intensity. For low-resolution imaging, the slice with the highest fluorescence intensity was selected per cell and segmented. The intracellular signal was the segmented area shrunk by 3 pixels, and the extracellular signal was the 3-pixel area surrounding the intracellular region. Signal vs. background was subsequently calculated using formula (2). Adjusted coefficient of determination (R²) was derived by comparing fitting line of formula y~log(x) with the residuals.

$${Signal}\,{vs}.{background}=\frac{{mean}\left({Membrane}\right)}{{mean}\left({Background}\right)}$$

(2)

For analysis of glycocalyx at cell-cell-contacts, images of interest with vertically oriented glycocalyx were analyzed in substacks of 3 adjacent slices for fixed-sample imaging, using the mean fluorescence of 9 subsequent non-bleached frames for live imaging, or per individual frame for FRAP analysis. Here, the central slice was defined as the slice with the narrowest full width at half-maximum intensity of the cross-sectional fluorescence profile. Using the segmented line tool, lines were drawn over the membrane (line widths ranging between 1–50 pixels for fixed and 1-10 pixels for live imaging, as annotated in each dataset), followed by detection of the fluorescence intensity profile. A matching background signal was obtained from the extracellular glycocalyx-free regions of each image and used for background correction. Using the Airyscan mode for fixed samples, the mean fluorescence of 5 adjacent pixels were used, resulting in ~210 nm bins. Non-Airyscan mode was used for FRAP imaging, followed by binning of 3 adjacent pixels ( ~ 255 nm in length). The membrane convergence point, cell-cell-contact free membrane region, transition zone, and cell-cell contact are defined in Supplementary Fig. 4b. The transition zone length was defined by formula (3).

$${L}_{{transition}\,{per}\,{cell}}=|\left(X\left[{{MFI}}_{{singlecell}}\right]-X\left[{{MFI}}_{{cellcontact}}\right]\right)|*{pixel}\,{size}$$

(3)

In (3), $X$ represents pixel number along the profile. When multiple transition zones were identified using this formula, the transition zone with the largest delta in fluorescence was considered, and adjacent regions before and after the transition zone were redefined single-membrane segments and cell-cell contacts, respectively (detailed by Supplementary Fig. 4b). For FRAP analysis, each bin along the axis of the line profile was considered bleached when the mean fluorescence of the first 2 frames ranged at least 3 standard deviations below the mean fluorescence of the 9 frames before bleaching. Maximum diffusion speed for each subsegments was obtained by 1) normalizing for minimum and maximum fluorescence, 2) generating time vs. normalized fluorescence plots, 3) fitting exponential curves in these plots, to 4) determine the maximal recovery yf of the exponential fit and 5) the half-maximum recovery (y ½ max) and the time to reach y ½ max (t ½ max).

In multichannel stacks, axial chromatic aberration in the far-red channel (~170 nm) was corrected by shifting the far-red channel 1 slice down relative to the other slices. For analysis of MV3 cells migrating through collagen, single cells were selected to allow imaging of the entire focal volume of each cell without contacting other cells. For analysis of glycocalyx distribution across multiple blebs, three-pixel line ROIs (132 nm) were drawn perpendicularly across each bleb, and a generalized additive model (GAM) was used to generate a smoothened average fit across all blebs, which outputs the deviance parameter that is a goodness-of-fit measure, where all datapoints are compared with a saturated (perfect) model (saturated model would show deviance = 1). To analyze the differential distribution of glycocalyx and β1 integrin in cell protrusions at cell-matrix interactions with collagen fibrils diagonally positioned in the z-plane, the shifting focal plane in z-direction was defined by adjacent rectangular ROIs as 20-pixel (0.86 µm) rectangles. To account for lossless detection of focal interactions, the in-focus slice within each ROI (defined by the slice with the highest glycocalyx signal-to-background ratio) was obtained as a 3-slice maximum projection of the central slice spanning 510 nm. To determine fluorescence intensity gradients in protrusions, the line ROIs along the membrane, including leading edge protrusions, blebs, and retraction fibers, were subclassified into distal and proximal subregions. To determine spatial segregation of integrin and glycocalyx of collagen-free membrane regions and cell-collagen contacts, cross-sectional intensity profiles were obtained from perpendicular line ROIs drawn from the center of the integrin cluster to the center of membrane segments without collagen contact (Supplementary Fig. 8c) or with contact to collagen fibrils (Supplementary Fig. 8d). To analyze glycocalyx and β1 integrin enrichment within individual in perpendicularly-oriented clusters, the maximal β1 integrin signal of the cluster was divided by average signal of the inner membrane zone edges (defined in Supplementary Fig. 8d). In laterally-oriented clusters, enrichment was determined according to Supplementary Fig. 8e. To compare intensity gradients along the membrane in protrusions, the signal in protrusion subregions was normalized against the lateral, contact-free protrusion region.

Data presentation

Unless stated otherwise, violin plots were scaled to maximum width per group, and boxplots present medians as lines, 1^st-3^rd quartiles as box limits. Superviolin plots indicate intraexperimental distribution with color shade, dots present median per experiment, and line displays median ± 95% confidence interval. Boxplots present the median as the box middle, 1st-3rd quantiles as the box outlines, and quantiles ± 1.5x interquantile range by whiskers. Statistical differences are indicated by: *, p < 0,05; **, p < 0,01; ***, p < 0,001; or, where relevant, the statistical indifference is indicated by n.s. XRD structures for THS and DBCO in Fig. 1b were generated via Olex2 (v. 1.5)⁹². Figures were organized, edited and formatted using Adobe Illustrator (v. 28.5).

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

Unless stated otherwise, all data and raw data supporting the results of this study can be found in the article, supplementary files, and source data files. The RNA sequencing raw data is provided in the Gene Expression Omnibus (GEO) database (accession number: GSE287160). The X-ray crystallographic coordinates for structures reported in this study have been deposited at the Cambridge Crystallographic Data Centre (CCDC), under deposition numbers 2249007 (for THS) and 2378938 (for DBCO). These data can be obtained free of charge from The Cambridge Crystallographic Data Centre [www.ccdc.cam.ac.uk/data_request/cif]. The dataset of fixed cell-cell interactions is available via Figshare: [https://figshare.com/s/4ee3347a5f19357de049]. The used code for microscopic analysis and statistics can be retrieved via GitHub [https://github.com/daansmits2/Glycocalyx-THS-paper-code]. The chemical synthesis protocol and validation data are available in the Supplementary Information. Other raw microscopy and flow cytometry data files are not provided due to size restrictions and the complex data structure, and will be made available upon request from the corresponding author (peter.friedl@radboudumc.nl). Additional, large-scale data, such as raw micrographs from 3D imaging stacks and large source data underlying line graphs (typically consisting of ~2.000-10.000 rows), can be obtained from the authors upon request. Source data are provided with this paper.

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Acknowledgements

We gratefully acknowledge Esther Wagena for expert support with cell culture, Koen van den Dries for helpful discussions, and Gert-Jan Bakker for assistance with microscopy analysis for rebuttal experiments. This work was supported by the Institute of Chemical Immunology (project number ICI00027), funded by NWO (024.002.009) to P.F. and F.L.v.D., and the European Research Council (ERC-AdG-2021-101054921), NWO (R0006694, OCENW.GROOT.2019.022), and NIH U54 CA261694-01 to P.F.

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These authors contributed equally: Daan Smits, Johannes A. M. Damen.

Authors and Affiliations

Department of Medical BioSciences, Radboud Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, the Netherlands
Daan Smits, Tianfu Li & Peter Friedl
Laboratory of Organic Chemistry, Wageningen University & Research, Wageningen, the Netherlands
Johannes A. M. Damen, Floris L. van Delft & Bauke Albada

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Daan Smits
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Johannes A. M. Damen
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Tianfu Li
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Floris L. van Delft
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Bauke Albada
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Peter Friedl
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Contributions

P.F. and F.L.v.D. conceived the project; all authors were involved in refining its shape. J.A.M.D. performed the chemical experiments, syntheses, fluorophore conjugations, and quality control. D.S. performed the cell-related experiments and analyses, and wrote the code for large-scale data analysis. T.L. analyzed the Bulk RNA sequencing data. D.S., J.A.M.D., and P.F. wrote the paper, and together with B.A. and F.L.v.D., revised the manuscript.

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Correspondence to Peter Friedl.

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Smits, D., Damen, J.A.M., Li, T. et al. Glycocalyx micro- and nanodomains in cell-cell and cell-matrix interactions revealed by enhanced click chemistry. Nat Commun 17, 2645 (2026). https://doi.org/10.1038/s41467-026-69242-1

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Received: 26 February 2025
Accepted: 26 January 2026
Published: 12 February 2026
Version of record: 20 March 2026
DOI: https://doi.org/10.1038/s41467-026-69242-1