Mechanistic insights into GLUT1 activation andclustering revealed by super-resolution imagingQiuyan Yana,b, Yanting Lub,c, Lulu Zhoua,b, Junling Chena, Haijiao Xua, Mingjun Caia, Yan Shia, Junguang Jianga,Wenyong Xiongc,1, Jing Gaoa,1, and Hongda Wanga,d,1

aState Key Laboratory of Electroanalytical Chemistry, Research Center of Biomembranomics, Changchun Institute of Applied Chemistry, Chinese Academyof Sciences, Changchun, 130022 Jilin, P. R. China; bSchool of Chemistry and Chemical Engineering, University of Chinese Academy of Sciences, 100049Beijing, P. R. China; cState Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences,Kunming, 650201 Yunnan, P. R. China; and dLaboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science andTechnology, Aoshanwei, Jimo, Qingdao, 266237 Shandong, P. R. China

Edited by Nieng Yan, Princeton University, Princeton, NJ, and accepted by Editorial Board Member Alan R. Fersht May 24, 2018 (received for review March9, 2018)

The glucose transporter GLUT1, a plasma membrane protein thatmediates glucose homeostasis in mammalian cells, is responsiblefor constitutive uptake of glucose into many tissues and organs.Many studies have focused on its vital physiological functions andclose relationship with diseases. However, the molecular mecha-nisms of its activation and transport are not clear, and its detaileddistribution pattern on cell membranes also remains unknown. Toaddress these, we first investigated the distribution and assemblyof GLUT1 at a nanometer resolution by super-resolution imaging.On HeLa cell membranes, the transporter formed clusters with anaverage diameter of ∼250 nm, the majority of which were regu-lated by lipid rafts, as well as being restricted in size by both thecytoskeleton and glycosylation. More importantly, we found thatthe activation of GLUT1 by azide or MβCD did not increase itsmembrane expression but induced the decrease of the large clus-ters. The results suggested that sporadic distribution of GLUT1may facilitate the transport of glucose, implying a potential asso-ciation between the distribution and activation. Collectively, ourwork characterized the clustering distribution of GLUT1 and linkedits spatial structural organization to the functions, which wouldprovide insights into the activation mechanism of the transporter.

GLUT1 | direct stochastic optical reconstruction microscopy |single molecule | cluster | activation

Glucose is the primary source of energy and substrate forcells, and its transport process is important for both normal

and diseased cellular metabolisms (1, 2). Previous studies have shownthat the uptake of glucose and other carbohydrates through the cellplasma membrane is largely dependent on members of theglucose transport (GLUT) family (3). Humans have 14 suchmembers, all of which are encoded by SLC2A genes (4). Thefirst characterized glucose transporter, GLUT1, is widelyexpressed and responsible for the constant uptake of glucose (5,6). Many researchers have been attracted to focus on its vitalphysiological and pathophysiological sense (7, 8), and its over-expression has become an important hypoxic marker in malignanttumors and a prognostic indicator for tumorigenesis (7, 9).Recently, the structure and distribution pattern of GLUT1 has

also drawn wide concern. Some studies have found that it is aninward-open uniporter with a single N-glycosylation site (10, 11),and some have showed a markedly punctate staining pattern ofGLUT1 on cell membranes under deconvolution fluorescencemicroscopy (12). However, the diffraction-limited resolutionmade it very difficult to reveal the detailed structure of GLUT1.For example, issues on whether membrane GLUT1 forms clus-ters as a working unit in the same way as many other membraneproteins, such as GPI-anchored proteins, epidermal growth re-ceptors (EGFRs), and Toll-like receptors (13–15), and whichtransmutation causes an acute increase of the maximal velocity(Vmax) for glucose uptake following exposure to osmotic ormetabolic stimuli (12, 16), have not been clarified. Fortunately,

super-resolution fluorescence microscopy, which breaks the dif-fraction barrier and achieves a lateral resolution in the tens ofnanometers (17), has provided a particularly suitable tool to solvethese problems. Meanwhile, it has been proven that multiproteinassemblies are dependent on cholesterol environment, and theirseparation and anchoring are related to the actin cytoskeleton (18,19). Nonetheless, it is still unknown whether these factors havecontributions to the spatial distribution of GLUT1.Lipid rafts, also known as the detergent-resistant membranes

(DRMs), are membrane domains containing high levels of cho-lesterol, sphingolipids, and specific proteins, which play a sig-nificant role in cell signaling and protein assembling (20, 21).Abundant evidence has proved that spatial recruitment andclustering of proteins and lipids into lipid rafts is a remarkablefeature in a variety of signaling and transferring processes (22,23), for instance insulin receptors, integrin, and T cell antigenreceptors (22, 24). Even the members of GLUT family (GLUT4and GLUT1) have been found to associate with DRMs (4, 25).However, due to the use of detergents for extracting lipid raftsin these experiments that broke the natural condition of cellmembranes, the validity and accuracy of the colocalization between

Significance

Many membrane proteins are functioning in aggregations andassociating with microdomains, which range from nanometersto micrometers in size. Therefore, it is indispensable to directlyanalyze these proteins and microdomains in native cell mem-branes at a single-molecule level. GLUT1 is a ubiquitouslyexpressed protein, contributing to basal and growth factor-stimulated glucose uptake in many tissues. It is overexpressedin almost all tumors. Herein, by direct stochastic optical re-construction microscopy, we previously mapped GLUT1 onnative cell membranes and highlighted key contributions ofthe lipid raft, cytoskeleton, and glycosylation to the formationof clusters. Moreover, we elucidated that the clustered distri-bution of the transporter was associated with its activation,which is crucial to advance our understanding of the trans-porter’s spatial organization and activation mechanism.

Author contributions: J.G. and H.W. designed research; Q.Y., Y.L., and W.X. performedresearch; H.X., M.C., Y.S., and J.J. contributed new reagents/analytic tools; Q.Y., L.Z., andJ.C. analyzed data; and Q.Y., W.X., J.G. and H.W. wrote the paper.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission. N.Y. is a guest editor invited by theEditorial Board.

Published under the PNAS license.1To whom correspondence may be addressed. Email: xiong.wenyong@mail.kib.ac.cn,gaojing@ciac.ac.cn, or hdwang@ciac.ac.cn.

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1803859115/-/DCSupplemental.

Published online June 18, 2018.

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GLUT1 and lipid rafts is still debatable. Besides, actin as a majorcytoskeleton protein is also found to be involved in almost allbiological events, contributing to the mechanical properties andshapes of cells (26). Some ion channel proteins on cell mem-branes have been identified binding to actin directly or indirectlythrough the actin binding proteins (27). Nevertheless, whetheractin filaments have an effect on the distribution of energychannel protein, GLUT1, remains unknown.As an important glucose transporter, the activation and the

transport of GLUT1 has been explored as well. Several studieshave suggested that the activation of the transporter by meta-bolic stresses is mediated by translocating of GLUT betweenintracellular storage pools and the cell surface or involves acti-vation (“unmasking”) of individual transporters preexisting inthe plasma membranes (28, 29). Little is known about whetherthe activation changes the distribution pattern of GLUT1 andhow the transporters assemble and organize with or withoutactivation. The current uncertainty on these topics calls for newmethods capable of directly monitoring the size and stability ofGLUT1 clusters.Herein, we applied direct stochastic optical reconstruction

microscopy (dSTORM) (30, 31), one of the super-resolutionimaging techniques, to observe the spatial distribution of GLUT1on HeLa cell membranes, which are found to overexpress GLUT1(SI Appendix, Fig. S1), then quantitatively analyze the distributioncharacteristics of GLUT1 clusters. By dual-color dSTORM im-aging and inhibitor treatment, we elucidated the critical roles oflipid rafts, actin cytoskeleton, and glycosylation in cluster forma-tion and stability. Moreover, combining dSTORM data with bio-chemistry results, we depicted the detailed changes of GLUT1clustering and distribution under activation by different stimuli,which revealed a probable relationship between the activation andspatial distribution.

Results and DiscussionMapping GLUT1 on Cell Membranes Using STORM. Considering thefluidity of the cell membrane, we used fixed HeLa cells to ob-serve the distribution of GLUT1. When the fixation was notadequate, proteins on cell membranes would not be completelyimmobilized, causing the redistribution of proteins (32, 33). So,we first optimized the fixation time and found that the mor-phology of GLUT1 has no significant difference on cell mem-branes with different fixation time (SI Appendix, Fig. S2). Thus,20 min for fixation was used in all subsequent experiments.

Cultured HeLa cells present adherent growth and their adherentside and medium exposed side face different environments,which we think may influence the distribution of GLUT1. To testthis idea, we used dSTORM to investigate the spatial distribu-tion of GLUT1 on both the medium exposed side and adherentside (see Experimental Section and SI Appendix, Fig. S3 for de-tail). The reconstructed dSTORM images and the correspondingmagnified pictures showed that GLUT1 tended to form ellipticand dense clusters on the medium exposed side (Fig. 1 A and B)but sparse clusters with irregular shapes on the adherent side(Fig. 1 C and D). The same phenomenon was also observed onOS-RC-2 cell (human renal carcinoma cell) membranes (SIAppendix, Fig. S4).To quantify the features of the clusters, we used Ripley’s K

function (13) to analyze the spatial clustering in nanoscale do-mains (see SI Appendix, Fig. S5 for detail). The maxima of theL(r)-r (medium exposed side: 180 ± 20, adherent side: 101 ± 4)in Fig. 1E indicated that the degree of clustering on the mediumexposed side was higher than that on the adherent side. The rmaxvalue corresponding to the maximum of L(r)-r was defined as theaverage size of the analyzed clusters in the region of 2 × 2 μm2,which showed that GLUT1 formed clusters with an average di-ameter of 250 ± 20 nm on the medium exposed side and 137 ±16 nm on the adherent side. We also extracted the informationof the amount (Fig. 1F) and size (Fig. 1G) of the GLUT1 clusterson the medium exposed side and adherent side of HeLa cells.The results showed that the transporter formed much more andlarger clusters on the medium exposed side than on the adherentside. To further clarify the sporadic GLUT1 and the molecularorganization in clusters, we applied semiquantitative analysis(Experimental Section) to calculate the amount of distribution ofsporadic GLUT1 (one molecule) and clustered GLUT1 containingmore than two molecules (Fig. 1H). The statistical result showedthat GLUT1 formed clusters with different numbers of molecules,ranging from 2 to more than 10, but a few were more than 25.Small clusters containing two to four molecules were in the ma-jority. Moreover, more large clusters that consisted of more thanfour molecules were found to generate on the medium exposedside, while sporadic GLUT1 were more on the adherent side.By comparison, we found that GLUT1 formed clusters with

different numbers and sizes on HeLa medium exposed side andadherent side. High-density and large-diameter clusters wereseen on the medium exposed side, while sparse and small clusterswere observed on the adherent side. These discrepancies may be

Fig. 1. GLUT1 proteins form clusters of different sizes and amounts on HeLa medium exposed side and adherent side. (A–D) Reconstructed dSTORM imagesof GLUT1 on medium exposed side (A) and adherent side (C), and the corresponding magnified images (B and D). (Scale bars: A and C, 5 μm; B and D, 2 μm.) (E)Representative Ripley’s K function plots of GLUT1 on different membranes. Data are from 30 stochastically selected regions of 2 × 2 μm2 in 10 cells of threeindependent experiments. (F) The average number of GLUT1 clusters per μm2. (G) The average cluster area. (H) The number of sporadic GLUT1 and clusterscontaining different amounts of molecules per μm2. Data in F–H are obtained from 10 cells of three independent experiments (mean ± SD). **P < 0.01 (two-tailed unpaired t test).

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caused by the varying external environments experienced bydifferent surfaces. The medium exposed side are entirely ex-posed to the external environment and are able to contact withmore external factors, such as hormones and extracellular growthfactors. As previous studies reported that growth factors like IGFand SCF can increase glucose metabolism (34), it is thus possiblethat the changes of glucose levels induced by extracellular factorscould result in the difference of GLUT1 distribution on themedium exposed side and adherent side.

Interactions Between GLUT1 and Lipid Rafts. Many studies havebeen reported that GLUT1 is partly localized to DRM domainsand that the transporter activity is sensitive to the phospholipid

and cholesterol environment (12, 34). Besides, several studieshave depicted that lipid rafts exist as nanodomains or micro-domains on the cell membrane (14, 35), and our previous studiesalso observed lipid rafts with the size ranging from 10 to 200 nm(14, 36, 37), which was consistent with the average diameter ofGLUT1 (∼200 nm). Accordingly, we hypothesized that GLUT1clustering might be associated with lipid rafts. To verify this as-sumption, dual-color dSTORM imaging was performed to locatethe lipid rafts and GLUT1 on the medium exposed side ofHeLa cells (Fig. 2). The merged image of lipid rafts and GLUT1(Fig. 2C) showed a degree of colocalization between the two.Mander’s coefficients (38), M1 and M2, were used to analyzesaid colocalization. These coefficients represented the amountof colocalized pixels relative to the total covered by each com-ponent. Based on their values, we sorted the positional rela-tionships into four types: overlap (M1/M2 > 0.66, Fig. 2D),partial overlap (0.33 < M1/M2 <0.66, Fig. 2E), edge connection(0 < M1 and M2 < 0.33, Fig. 2F), and isolation (M1/M2 = 0, Fig.2G), then we determined the percentage of the four localizationstates (Fig. 2H). Overlap and partial overlap were collectivelyreferred to as colocalization. The data showed that 35% (over-lap: 11%, partial overlap: 24%) of total GLUT1 was associatedwith lipid rafts, whereas the remaining might be localized inother lipid compositions of rafts or nonlipid rafts domains. Thishinted us that the clusters’ formation was not only affected bylipid rafts and there might be other factors that contributed tothe aggregation of GLUT1.

Lipid Rafts Disruption Weakens GLUT1 Clustering. The reasons whyGLUT1 clusters did not totally colocalize with GM1-enrichedlipid rafts (CT-B labeled) may be two: (i) other compositions ofrafts may colocalize with GLUT1 clusters; and (ii) other factorsmay participate in regulating clustering. Hence, we decided tofurther confirm the role of lipid rafts at first. We treated HeLacells with 10 mM methyl-β-cyclodextrin (MβCD) for 20–30 min,which can remove the cholesterol from the lipid rafts (39), toinvestigate whether the alteration of the cholesterol environmentcould influence GLUT1 distribution. We found that a lot ofGLUT1 clusters became smaller or even disappeared afteradding MβCD (Fig. 3). The Ripley’s K-function plots indicatedthat the degree of clustering decreased dramatically and that theaverage diameter of the clusters dropped from ∼250 nm to∼140 nm (Fig. 3E). Moreover, the number of clusters per unitarea reduced from ∼2.3 ± 0.3 to ∼1.2 ± 0.3 (Fig. 3F), andclusters consisting of more than two molecules declined sharply

Fig. 2. Dual-color dSTORM images revealing the relative spatial distributionof GLUT1 and lipid rafts on the HeLa membrane. (A and B) ReconstructeddSTORM images of lipid rafts with Alexa647-conjugated CT-B (A) and GLUT1labeled with Alexa532-conjugated antibody (B) on the same cell membrane.(C) The merged image of A and B, showing significant colocalization of thetwo. (D–G) Enlarged dual-color dSTORM images of white Inset squares in C,displaying four types of location relationship: overlap (D), partial overlap (E),edge connection (F), and isolation (G). (H) The percentage of the four typesof location states. Data are from 10 cells in three independent experiments.(Scale bars: A–C, 5 μm; D–G, 200 nm.)

Fig. 3. The changes of GLUT1 clusters after lipid rafts disruption. (A–D) Reconstructed dSTORM images of GLUT1 on control (A) and MβCD-treated (C) HeLa cellmembranes and the corresponding magnified images with clusters circled in white (B and D). (Scale bars: A and C, 5 μm; B and D, 2 μm.) (E) Ripley’s K functionplots of GLUT1 on control and MβCD-treated HeLa membranes. (F) The number of clusters per μm2. (G) The number of sporadic GLUT1 and clusters containing adifferent amount of molecules per μm2. Data are obtained from 10 cells of three independent experiments (mean ± SD). **P < 0.01 (two-tailed unpaired t test).

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(Fig. 3G). To rule out the destructive possibility of MβCD onmembrane structure or other membrane constituents, we per-formed the experiment of cholesterol repletion (MβCD satu-rated with cholesterol at a MβCD:cholesterol molar ratio of 8:1).As shown in SI Appendix, Fig. S6A, lipid rafts returned to theclustered structure after repletion of cholesterol. The localiza-tions and size of lipid rafts decreased sharply with MβCDtreatment, while these values increased to the level of controlcells after cholesterol repletion (SI Appendix, Fig. S6 B and C).Thus, these results indicated that MβCD had no effect on otherconstitutes except lipid rafts. In addition, we also validated thatGLUT1 clusters formed again and the average cluster size re-covered to that on control cell membranes (∼0.12 μm2) (SI Ap-pendix, Fig. S6 D–F).Dual-color imaging, together with the disruption and repletion of

lipid rafts, demonstrated that the stable existence of most GLUT1clusters is dependent on the integrality of lipid rafts. The destruc-tion of lipid rafts may induce to partial or complete fragmentationof larger GLUT1 clusters. Of note, although the number of largeclusters reduced after MβCD treatment, there were a portion ofGLUT1 that still formed clusters. This finding was consistent withthat only 35% of GLUT1 colocalized with lipid rafts, suggestingother mechanisms in regulation of its distribution.

The Limitation of the Actin Cytoskeleton in GLUT1 Clustering. Asabove mentioned, there are other factors participating in GLUT1clustering, and previous studies have reported that various mem-brane channel proteins directly interact with actin (27). Thus, toclarify whether the actin cytoskeleton plays a role in controllingthe distribution and clustering of GLUT1, we first imaged GLUT1on HeLa membranes treated by 20 μg/mL cytochalasin B (CB) for

30 min, which can depolymerize actin cytoskeleton. The averagecluster area (Fig. 4) and the molecules within clusters (SI Appendix,Fig. S7A) decreased significantly compared with that on controlcell membranes. However, CB not only inhibits actin filamentsfrom generating networks, but also weakens glucose transport byinteracting with the substrate efflux site (40). Our results alsoshowed that CB-treated cells consumed less glucose than control(see Fig. 7). To exclude the effect of glucose transport on GLUT1distribution, we used another inhibitor cytochalasin D (CD).Likewise, it inhibits actin polymerization but hardly affects thecellular permeability to sugars (41), which was supported by ourdata of glucose consumption as well (see Fig. 7). After CD treat-ment, the total localizations of GLUT1 did not change, whereasclusters became scattered and small (Fig. 4 and SI Appendix, Fig.S7B). These findings demonstrated that the disruption of actinfilaments limited the ability of GLUT1 to form clusters, but did notchange its total level, therefore verifying the role of actin cyto-skeleton in transporter clustering.

The Impairment of N-Glycosylation Disruption in GLUT1 Clustering.Glycosylation is a prevalent protein modification with a pro-found effect on protein stability, folding, and a multitude of bi-ological processes (42). Since GLUT1 owns an N-glycosylationsite, we presupposed that GLUT1 clustering would be related toglycosylation. To prove this, HeLa cells were pretreated with50 μg/mL N-acetyl-β-D-gulcosaminides (NAG) for 30 min, whichhas an effective transglycosylation of N-acetyl-β-D-gulcosaminides,a common motif of N-linked sugar chains in proteins (36); thenthe nanoscale organizations of GLUT1 on cell membranes wereinvestigated. The deglycosylation made GLUT1 clusters disperse,and almost all of the large clusters disappeared (Fig. 5 A–D).

Fig. 4. Comparative analysis of the morphologies ofGLUT1 after the disruption of actin cytoskeleton. (A–F) Reconstructed dSTORM images of GLUT1 on con-trol (A), CB-treated (C) and CD-treated (E) cellmembranes, and the corresponding magnified im-ages (B, D, and F). (Scale bars: A, C, and E, 5 μm; B, D,and F, 2 μm.) (G) The number of localizations per μm2

on these three kinds of membranes. (H) The averagecluster area. Data are obtained from 10 cells of threeindependent experiments (mean ± SD). *P < 0.5,**P < 0.01 (two-tailed unpaired t test).

Fig. 5. The glycosylation regulates the GLUT1 clus-tering on HeLa cell membranes. (A–D) ReconstructeddSTORM images of GLUT1 on control (A) and NAG-treated (C) cell membranes, and the correspondingmagnified images (B and D). (Scale bars: A and C,5 μm; B and D, 2 μm.) (E) Ripley’s K function analysisof GLUT1 under the two conditions. (F) The averagenumber of localizations per μm2. (G) The averagenumber of GLUT1 clusters per μm2. Data are obtainedfrom 10 cells of three independent experiments(mean ± SD). *P < 0.05 (two-tailed unpaired t test).

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From the Ripley’s K function analysis (Fig. 5E), we found thatthe degree of clustering and the diameter of GLUT1 clusters felldown significantly (from ∼250 nm to ∼130 nm). Further statis-tical data indicated that there was a distinguishable decline inboth the number of localizations (Fig. 5F) and clusters (Fig. 5G).Moreover, sporadic molecules and clusters containing two mol-ecules increased, whereas other large clusters with more thantwo molecules fell down (SI Appendix, Fig. S7C). The reasons forthe decrease of cluster size and number might be two: One is thatdeglycosylation directly inhibits the formation of clusters, and theother is that the lower level of total GLUT1 could not generatelarger and more clusters as it could on control cell membranes.However, we could not determine which one or both were theright reasons. Even so, the results clearly supported the hypothesisthat glycosylation was an indispensable element in maintaining ofthe distribution and clustering of GLUT1 on cell membranes.

The Effect of GLUT1 Activation on Its Clustering. Exposure to os-motic or metabolic stimuli like MβCD or azide can increase themaximal transfer rate of GLUT1 (12, 34), we wondered whatchanges would be brought to GLUT1’s membrane distribution byactivating. So, we first performed glucose uptake assay to confirmthe activation of sodium azide and MβCD on GLUT1. As shownin Fig. 7, the glucose consumption increased, and the cell viabilitydid not change after treatment with azide or MβCD, validatingthat these two reagents can effectively activate glucose transporter.Then we used 5 mM sodium azide to stimulate the adherentHeLa cells for 30 min before staining. From the reconstructeddSTORM images, most of the molecules on treated membranesseemed to form clusters in the same way as those on controlmembranes (Fig. 6 A and B). Further Ripley’s K function anal-ysis and statistical results showed some differences in the size,number, and molecular organization of GLUT1 clusters. The total

localizations of GLUT1 remained stable (Fig. 6D), and even thecluster number reduced slightly on azide-treated cell membranes(Fig. 6E). However, the degree of clustering and diameter ofclusters reduced, which was only ∼170 ± 25 nm (Fig. 6C).Moreover, the number of monomer GLUT1 increased followingactivation, and small clusters with less than five molecules went upsignificantly (Fig. 6F). These results indicated that the activationof GLUT1 might change the molecular organization of clustersand inhibit the formation of large clusters on cell membranes.At this time, we focused on the results of MβCD treatment

again. The cluster number decreased (Fig. 3F) and only mono-mer GLUT1 increased, but small clusters with less than fourmolecules were not as many as those on control cells (Fig. 3G).The results indicated that the inhibition of MβCD on GLUT1clustering was stronger than that of sodium azide. It is easy tounderstand. MβCD has two functions, i.e., disrupting lipid raftsand activating glucose transporter, both of which can weaken theclustering. Additionally, we also tested the influence of CB, CD,and NAG treatment on the activity of glucose transport (Fig. 7).Only CB reduced the glucose uptake compared with controlgroups. CB has two antagonistic effects on clustering. One isinhibiting actin polymerization that could limit the aggregation ofGLUT1, the opposite one is inhibiting GLUT1 activity that mayinduce the formation of clusters. Therefore, the changes of clus-tering features after adding CB were not as obvious as those withCD treatment (Fig. 4), because CD only affects the actin cyto-skeleton. For NAG groups, we thought the glucose consumptionwould decrease due to the disruption of N-glycosylation, while itdid not change as we expected. This might be because there isanother family of glucose transporters, sodium-linked glucosetransporters (SGLTs) (43), which are not affected by the degly-cosylation of NAG. Together, the detailed molecular mechanismfor the clustering of GLUT1 and glucose uptake is complex; even

Fig. 6. NaN3 activation of GLUT1 changed themolecular organization of it clusters. (A and B)Reconstructed dSTORM images of GLUT1 on control(A) and NaN3-treated (B) cell membranes. (Scalebars: 5 μm.) (C) Ripley’s K function analysis of GLUT1under the two conditions. (D) The average numberof localizations per μm2. (E) The average number ofGLUT1 clusters per μm2. (F) The number of sporadicGLUT1 and clusters containing different amount ofmolecules per μm2. Data are obtained from 10 cellsin three independent experiments (mean ± SD). ns,no significance (two-tailed unpaired t test).

Fig. 7. Glucose uptake assay with different treat-ments. (A) Normalized cell viability under the dif-ferent conditions. (B) The glucose consumption ofevery group, which was normalized by living cellnumbers. (C) The glucose consumption relative tocontrol. Data are from three independent experi-ments (mean ± SD). *P < 0.05; **P < 0.01; ns, nosignificance (two-tailed unpaired t test).

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so, our findings revealed a potential relationship between GLUT1clustering and activation and suggested that small clusters may bemore beneficial to glucose transport.

ConclusionsIn summary, by the combination of dSTORM imaging andproposed single molecule analysis methods, we observed thatmost of GLUT1 was aggregated in clusters on the HeLa mem-brane and found a precise spatial association between GLUT1and lipid rafts, which resolved the debate surrounding on thelocalization of the transporter in membrane domains. Regardingthe organizational mechanism of GLUT1 clusters, our studyrevealed that not only the lipid rafts’ environment can stabilizetheir existence, but also the actin cytoskeleton and N-glycosylationplay important roles in the clusters’ formation. Furthermore, un-der the activation by MβCD and sodium azide, we found thatmany transporters were prone to distribute sporadically or formsmall clusters, which might facilitate glucose uptake. The ability todirectly visualize the transporter’s distribution at a nanometricresolution provided crucial information of clustering features,clarified many regulatory factors, and captured a probable re-lationship between GLUT1 distribution and activation. Withfurther studies such as mutation and simultaneously observationof multiple glucose transporters, these initial observations mayform a significant step forward in our understanding of the mo-lecular mechanism of GLUT clustering and glucose uptake.

Experimental SectionCell Culture. Cells were cultured in Dulbecco’s modified Eagle medium(DMEM; HyClone) supplemented with 10% FBS (Gibco) and antibiotics andmaintained in a humidified environment with 5% CO2 at 37 °C. Before theimaging experiment, HeLa cells were divided into a dish where a cleancoverslip was placed and cultured at least 24 h.

Glucose Uptake Analysis. The glucose consumption of HeLa cells with differenttreatment was measured as described in SI Appendix, SI Materials andMethods.

Preparation of dSTORM Samples. Cells were fixed, blocked, and labeled withantibodies and sealed on microscopes as described in SI Appendix, SI Ma-terials and Methods.

Superresolution Imaging. The raw data were captured by our home-builtdSTORM and analyzed by Quickpalm as described in SI Appendix, SI Mate-rials and Methods.

Data Analysis. The spatial distribution of molecules was analyzed by Ripley’s Kfunction and the molecular organization of clusters was estimated bysemiquantitative analysis method as described in SI Appendix, SI Materialsand Methods.

ACKNOWLEDGMENTS. This work was financially supported by National KeyR&D Program of China Grant 2017YFA0505300 (to H.W.), National NatureScience Foundation of China Grants 21727816, 21525314, 21721003 (toH.W.), 21703231 (to J.G.), 21503213 (to M.C.), and 31330082 (to J.J.), andYunnan Provincial Science and Technology Department of China Grants2017FA044 and 2013HA023 (to W.X.).

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