Most proteins at the plasma membrane are not uniformly distributed but localize to dynamic domains of nanoscale dimensions. To investigate their functional relevance, there is a need for methods that enable comprehensive analysis of the compositions and spatial organizations of membrane protein nanodomains in cell populations. Here we describe the development of a non-microscopy-based method for ensemble analysis of membrane protein nanodomains. The method, termed nanoscale deciphering of membrane protein nanodomains (NanoDeep), is based on the use of DNA nanoassemblies to translate membrane protein organization information into a DNA sequencing readout. Using NanoDeep, we characterized the nanoenvironments of Her2, a membrane receptor of critical relevance in cancer. Importantly, we were able to modulate by design the inventory of proteins analysed by NanoDeep. NanoDeep has the potential to provide new insights into the roles of the composition and spatial organization of protein nanoenvironments in the regulation of membrane protein function.
Subscribe to Journal
Get full journal access for 1 year
only $4.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Codes for UMI processing and barcode association are available online at https://github.com/Intertangler/NanoDeep.
Sengupta, P. et al. Probing protein heterogeneity in the plasma membrane using PALM and pair correlation analysis. Nat. Methods 8, 969–975 (2011).
Bethani, I., Skånland, S. S., Dikic, I. & Acker-Palmer, A. Spatial organization of transmembrane receptor signalling. EMBO J. 29, 2677–2688 (2010).
Rossier, O. et al. Integrins β1 and β3 exhibit distinct dynamic nanoscale organizations inside focal adhesions. Nat. Cell Biol. 14, 1057–1067 (2012).
Winckler, P. et al. Identification and super-resolution imaging of ligand-activated receptor dimers in live cells. Sci. Rep. 3, 2387 (2013).
Garcia-Parajo, M. F., Cambi, A., Torreno-Pina, J. A., Thompson, N. & Jacobson, K. Nanoclustering as a dominant feature of plasma membrane organization. J. Cell. Sci. 127, 4995–5005 (2014).
Sigal, Y. M., Zhou, R. & Zhuang, X. Visualizing and discovering cellular structures with super-resolution microscopy. Science 361, 880–887 (2018).
Sahl, S. J., Hell, S. W. & Jakobs, S. Fluorescence nanoscopy in cell biology. Nat. Rev. Mol. Cell Biol. 18, 685–701 (2017).
Jungmann, R. et al. Quantitative super-resolution imaging with qPAINT. Nat. Methods 13, 439–442 (2016).
Jungmann, R. et al. Multiplexed 3D cellular super-resolution imaging with DNA-PAINT and Exchange-PAINT. Nat. Methods 11, 313–318 (2014).
Klevanski, M. et al. Automated highly multiplexed super-resolution imaging of protein nano-architecture in cells and tissues. Nat. Commun. 11, 1552 (2020).
Beghin, A. et al. Localization-based super-resolution imaging meets high-content screening. Nat. Methods 14, 1184–1190 (2017).
Dirks, R. M. & Pierce, N. A. Triggered amplification by hybridization chain reaction. Proc. Natl Acad. Sci. USA 101, 15275–15278 (2004).
Söderberg, O. et al. Direct observation of individual endogenous protein complexes in situ by proximity ligation. Nat. Methods 3, 995–1000 (2006).
Fredriksson, S. et al. Protein detection using proximity-dependent DNA ligation assays. Nat. Biotechnol. 20, 473–477 (2002).
Hoffecker, I. T., Yang, Y., Bernardinelli, G., Orponen, P. & Högberg, B. A computational framework for DNA sequencing microscopy. Proc. Natl Acad. Sci. USA 116, 19282–19287 (2019).
Weinstein, J. A., Regev, A. & Zhang, F. DNA microscopy: optics-free spatio-genetic imaging by a stand-alone chemical reaction. Cell 178, 229–241.e216 (2019).
Boulgakov, A. A., Ellington, A. D. & Marcotte, E. M. Bringing microscopy-by-sequencing into view. Trends Biotechnol. 38, 154–162 (2019).
Rubin, I. & Yarden, Y. The basic biology of HER2. Ann. Oncol. 12(Suppl. 1), S3–S8 (2001).
Yarden, Y. Biology of HER2 and its importance in breast cancer. Oncology 61(Suppl. 2), 1–13 (2001).
Yarden, Y. & Sliwkowski, M. X. Untangling the ErbB signalling network. Nat. Rev. Mol. Cell Biol. 2, 127–137 (2001).
Peckys, D. B., Korf, U. & de Jonge, N. Local variations of HER2 dimerization in breast cancer cells discovered by correlative fluorescence and liquid electron microscopy. Sci. Adv. 1, e1500165 (2015).
Stove, C. & Bracke, M. Roles for neuregulins in human cancer. Clin. Exp. Metastasis 21, 665–684 (2004).
Ho-Pun-Cheung, A. et al. Quantification of HER expression and dimerization in patients’ tumor samples using time-resolved Förster resonance energy transfer. PLoS ONE 7, e37065 (2012).
Weitsman, G. et al. HER2–HER3 dimer quantification by FLIM-FRET predicts breast cancer metastatic relapse independently of HER2 IHC status. Oncotarget 7, 51012–51026 (2016).
Claus, J. et al. Inhibitor-induced HER2–HER3 heterodimerisation promotes proliferation through a novel dimer interface. eLife 7, e32271 (2018).
Jeon, M. et al. Dimerization of EGFR and HER2 induces breast cancer cell motility through STAT1-dependent ACTA2 induction. Oncotarget 8, 50570–50581 (2017).
Kaufmann, R., Müller, P., Hildenbrand, G., Hausmann, M. & Cremer, C. Analysis of Her2/neu membrane protein clusters in different types of breast cancer cells using localization microscopy. J. Microsc. 242, 46–54 (2011).
Iqbal, N. Human epidermal growth factor receptor 2 (HER2) in cancers: overexpression and therapeutic implications. Mol. Biol. Int. 2014, 852748 (2014).
Needham, S. R. et al. EGFR oligomerization organizes kinase-active dimers into competent signalling platforms. Nat. Commun. 7, 13307 (2016).
Hiroshima, M. et al. Transient acceleration of epidermal growth factor receptor dynamics produces higher-order signaling clusters. J. Mol. Biol. 430, 1386–1401 (2018).
Liang, S. I. et al. Phosphorylated EGFR dimers are not sufficient to activate Ras. Cell. Rep. 22, 2593–2600 (2018).
van Lengerich, B., Agnew, C., Puchner, E. M., Huang, B. & Jura, N. EGF and NRG induce phosphorylation of HER3/ERBB3 by EGFR using distinct oligomeric mechanisms. Proc. Natl Acad. Sci. USA 114, E2836–E2845 (2017).
Baumann, C. G., Smith, S. B., Bloomfield, V. A. & Bustamante, C. Ionic effects on the elasticity of single DNA molecules. Proc. Natl Acad. Sci. USA 94, 6185–6190 (1997).
Bernardinelli, G. & Högberg, B. Entirely enzymatic nanofabrication of DNA–protein conjugates. Nucleic Acids Res. 45, e160 (2017).
Yurke, B., Turberfield, A. J., Mills, A. P., Simmel, F. C. & Neumann, J. L. A DNA-fuelled molecular machine made of DNA. Nature 406, 605–608 (2000).
Xu, H. et al. Enhanced DNA toehold exchange reaction on a chip surface to discriminate single-base changes. Chem. Commun. 50, 14171–14174 (2014).
Tan, M., Grijalva, R. & Yu, D. Heregulin beta1-activated phosphatidylinositol 3-kinase enhances aggregation of MCF-7 breast cancer cells independent of extracellular signal-regulated kinase. Cancer Res. 59, 1620–1625 (1999).
Breuleux, M. Role of heregulin in human cancer. Cell Mol. Life Sci. 64, 2358–2377 (2007).
Yang, C., Klein, E. A., Assoian, R. K. & Kazanietz, M. G. Heregulin beta1 promotes breast cancer cell proliferation through Rac/ERK-dependent induction of cyclin D1 and p21Cip1. Biochem. J. 410, 167–175 (2008).
Atlas, E. et al. Heregulin is sufficient for the promotion of tumorigenicity and metastasis of breast cancer cells in vivo. Mol. Cancer Res. 1, 165–175 (2003).
Huang, Y. et al. Molecular basis for multimerization in the activation of the epidermal growth factor receptor. eLife 5, e14107 (2016).
Desgrosellier, J. S. & Cheresh, D. A. Integrins in cancer: biological implications and therapeutic opportunities. Nat. Rev. Cancer 10, 9–22 (2010).
Stoeltzing, O. et al. Inhibition of integrin α5β1 function with a small peptide (ATN-161) plus continuous 5-FU infusion reduces colorectal liver metastases and improves survival in mice. Int. J. Cancer 104, 496–503 (2003).
Khalili, P. et al. A non-RGD-based integrin binding peptide (ATN-161) blocks breast cancer growth and metastasis in vivo. Mol. Cancer Ther. 5, 2271–2280 (2006).
Kuwada, S. K., Kuang, J. & Li, X. Integrin α5/β1 expression mediates HER-2 down-regulation in colon cancer cells. J. Biol. Chem. 280, 19027–19035 (2005).
Wang, S. E. et al. Transforming growth factor β induces clustering of HER2 and integrins by activating Src-focal adhesion kinase and receptor association to the cytoskeleton. Cancer Res. 69, 475–482 (2009).
Pols, M. S. & Klumperman, J. Trafficking and function of the tetraspanin CD63. Exp. Cell. Res. 315, 1584–1592 (2009).
Khushman, M. et al. Exosomal markers (CD63 and CD9) expression and their prognostic significance using immunohistochemistry in patients with pancreatic ductal adenocarcinoma. J. Gastrointest. Oncol. 10, 695–702 (2019).
Ng, Y. H. et al. Endometrial exosomes/microvesicles in the uterine microenvironment: a new paradigm for embryo–endometrial cross talk at implantation. PLoS ONE 8, e58502 (2013).
de Goeij, B. E. et al. Efficient payload delivery by a bispecific antibody–drug conjugate targeting HER2 and CD63. Mol. Cancer Ther. 15, 2688–2697 (2016).
Livant, D. L. et al. Anti-invasive, antitumorigenic, and antimetastatic activities of the PHSCN sequence in prostate carcinoma. Cancer Res. 60, 309–320 (2000).
Maier, K. E. et al. A new transferrin receptor aptamer inhibits new world hemorrhagic fever mammarenavirus entry. Mol. Ther. Nucleic Acids 5, e321 (2016).
Porciani, D. et al. Modular cell-internalizing aptamer nanostructure enables targeted delivery of large functional RNAs in cancer cell lines. Nat. Commun. 9, 2283 (2018).
Orlova, A. et al. Tumor imaging using a picomolar affinity HER2 binding affibody molecule. Cancer Res. 66, 4339–4348 (2006).
Malm, M. et al. Inhibiting HER3-mediated tumor cell growth with affibody molecules engineered to low picomolar affinity by position-directed error-prone PCR-like diversification. PLoS ONE 8, e62791 (2013).
Andersson, K. G. et al. Feasibility of imaging of epidermal growth factor receptor expression with ZEGFR:2377 affibody molecule labeled with 99mTc using a peptide-based cysteine-containing chelator. Int. J. Oncol. 49, 2285–2293 (2016).
Popovic, M., Mazzega, E., Toffoletto, B. & de Marco, A. Isolation of anti-extra-cellular vesicle single-domain antibodies by direct panning on vesicle-enriched fractions. Microb. Cell Fact. 17, 6 (2018).
Oloketuyi, S. et al. Electrochemical immunosensor functionalized with nanobodies for the detection of the toxic microalgae Alexandrium minutum using glassy carbon electrode modified with gold nanoparticles. Biosens. Bioelectron. 154, 112052 (2020).
Reddington, S. C. & Howarth, M. Secrets of a covalent interaction for biomaterials and biotechnology: SpyTag and SpyCatcher. Curr. Opin. Chem. Biol. 29, 94–99 (2015).
Keeble, A. H. et al. Evolving accelerated amidation by SpyTag/SpyCatcher to analyze membrane dynamics. Angew. Chem. Int. Ed. Engl. 56, 16521–16525 (2017).
Li, L., Fierer, J. O., Rapoport, T. A. & Howarth, M. Structural analysis and optimization of the covalent association between SpyCatcher and a peptide tag. J. Mol. Biol. 426, 309–317 (2014).
Zakeri, B. et al. Peptide tag forming a rapid covalent bond to a protein, through engineering a bacterial adhesin. Proc. Natl Acad. Sci. USA 109, E690–E697 (2012).
Hatlem, D., Trunk, T., Linke, D. & Leo, J. C. Catching a SPY: using the SpyCatcher–SpyTag and related systems for labeling and localizing bacterial proteins. Int. J. Mol. Sci. 20, 2129 (2019).
We acknowledge B. Reinius for helpful discussions and S. Dal Zilio for the development and fabrication of micropatterned surfaces, performed at the Facility of Nano Fabrication FNF-IOM, CNR, Trieste. A.I.T. acknowledges support from the European Research Council under the European Union’s Seventh Framework Programme (ERC, grant no. 617711), the Swedish Research Council (grant no. 2015-03520) and the Knut and Alice Wallenberg Foundation (grant no. KAW 2017.0114, A.I.T. and B.H.).
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended Data Fig. 1 Binding affinity and target selectivity characterization of VirD2-affibody fusion proteins.
a, SPR binding analysis of VirD2-affibody fusion proteins targeting Her2, Her3 and EGFR performed at concentrations ranging between 0.33 nM and 5 nM, to cover the kinetic spectrum. Fitting was performed using a 1:1 kinetic model to determine the dissociation constant, KD, association (kon) and dissociation (koff) rate constants. Recorded sensorgrams are shown in black, while fitting curves are in red. b, Selective binding of VirD2-affibody fusion proteins to their specific targets was verified by recoding the binding sensorgrams of VirD2-affibodies to the ECDs of Her2, Her3 and EGFR immobilized on three different flow cells.
a, Equivalent amounts of anti-Her2-, anti-Her3- or anti-EGFR-VirD2-affibody fusion proteins were incubated with increasing concentrations of their corresponding oligos for 2 h at 37 °C. Native PAGE (10%) was used to detect DNA by staining with SybrGold. The same gel was stained with Coomassie Blue to visualize proteins, thereby revealing the formation of DNA–protein conjugates. b, SPR real-time kinetic analysis of VirD2-affibodies (light color) and the respective VirD2-affibody-oligo conjugates (dark color) on sensor surfaces functionalized with their respective target proteins. The dissociation rate constants (koff) reported for each sensorgram were determined by fitting with 1:1 kinetic model.
Extended Data Fig. 3 Toehold exchange reversibly blocked the hybridization of oligos to the NanoCombs.
Biotinylated versions of the oligos used to produce the affibody-oligo conjugates were immobilized onto streptavidin sensor surfaces. a, Hybridization with the blocking strand caused an increase in the SPR signal, which was followed by a decrease in the signal when the invading strand was injected. The resulting unblocked oligos were capable of hybridizing to the NanoCombs. b, Without the strand invasion step, the blocked oligos were not able to bind to the NanoCombs (negative control). c, In the positive control there were no blocking/unblocking steps and the NanoComb hybridized to the anchored oligos.
Extended Data Fig. 4 Binding sensorgrams of library binders on SPR surfaces presenting different compositions of EGFR family receptors.
We created SPR surfaces presenting different combinations of the ECD-Her2, -Her3 and -EGFR, covalently attached to three different flow cells of the same sensor chip. Then we performed NanoDeep using Her2-NanoCombs and binder libraries consisting of anti-Her2, -Her3 and -EGFR conjugates. Sensorgrams display the binding of each of the library binders to anchored proteins. The binding of each of the affibody-oligo conjugates is specific to the targets present on the surface.
a, NanoDeep was performed on SKBR3 cells, using Her2-NanoCombs or NanoCombs that were not functionalized with anti-Her2 affibody-oligo conjugate on the reference prong, as a negative control. Reference and detection sequences, amplified by PCR and visualized on native PAGE (13%), were recovered only in presence of Her2-NanoComb (1) and not on the negative control (2), showing that NanoCombs bound to the cells through a specific interaction between the binder and the reference protein and not through a non-specific DNA interaction with the cell surface. b, NanoDeep was performed on SKBR3 cells, testing different conditions in parallel on four different cell plates with equal number of cells. Plate 1 was incubated with Her2-Nanocombs and then with binder library; Plate 2 was treated with NanoCombs that were not functionalized with anti-Her2 affibody-oligo conjugate on the reference prong and then with the binder library; Plate 3 was treated only with NanoCombs that were not functionalized with anti-Her2 affibody-oligo conjugate on the reference prong and Plate 4 was treated only with the binder library. After performing NanoDeep, reference and detection sequences were amplified by PCR and stained in solution to quantify the amount of DNA recovered. Optical Density (OD) measurements for each condition are plotted in the histogram; error bars represent SD. Source data
a, 1:1 mixtures of ECD-Her2 and ECD-Her3 were covalently attached to the SPR surfaces of two sensor chips. Her2- and Her3-NanoCombs were injected and binding to the anchored target proteins was detected by single cycle kinetic mode. Fitting was performed using a 1:1 kinetic model to determine the dissociation constant, KD, association (kon) and dissociation (koff) rate constants. b, Micropatterned surfaces were used to verify the specificity of binding of Her2- and Her3-Nanocombs to the immobilized proteins. ECD-Her2, ECD-Her3 were anchored to different surfaces exploiting chemical amine coupling. Surfaces without immobilized protein were used as a negative control. We treated the ECD-Her2, ECD-Her3 and control surfaces with Her2- or Her3-Nanocombs modified with desthiobiotin at the 3’ end of the backbone. Peroxidase conjugated to streptavidin could bind to the desthiobiotin and catalysed a substrate conversion to obtain a luminescence signal proportional to the amount of NanoCombs. Luminescence values are presented in the histogram. c, SKBR3 cells were analysed by NanoDeep using Her3-NanoCombs and anti-Her2, -Her3 and -EGFR binder libraries. Measurements were performed in duplicate and presented as mean values in two types of heatmaps, showing the reads from the reference sequences (top) and detection sequences (bottom). d, SKBR3 cells were treated with Her2- and Her3-Nanocombs and binding was measured by the chemiluminescence assay; error bars represent SD. Source data
a, Her2 RNA expression levels reported in “The Human Protein Atlas” (www.proteinatlas.org). We used a chemiluminescence assay to detect Her2-NanoCombs bound to SH-SY5Y cells, which show minimal levels of expression of Her2, SKBR3 cells (Her2 overexpression) and MCF7 cells (basal levels of Her2). Luminescence signals are presented in the histogram on the right; error bars represent SD. b, NanoDeep was performed on SH-SY5Y cells and SKBR3 cells, as positive control. Measurements were performed in duplicate and presented as mean values in two types of heatmaps, showing the reads from the reference sequences (top) and detection sequences (bottom). Source data
a, Schematic representation of conjugation of anti-integrin α5β1 peptide and oligo sequence; click chemistry amine coupling reaction was used in order to covalently attach DNA oligo to the peptide, exploiting amine groups present on both molecules. This bioconjugation is a three step procedure in which both peptide and DNA oligo are first modified with specific chemical groups, then the two modified biomolecules react, resulting in the formation of a stable peptide-oligo bond. The total degree of peptide-oligo conjugation was visualised by UV spectrophotometry, since the bis-arylhydrazone group formed in the peptide-oligo anchoring points adsorbs at a specific wavelength (354 nm). b, The formation of the conjugate was assessed by loading DNA oligo and the peptide-oligo conjugate on native PAGE (16%). Staining with SybrGold revealed a slight band shift corresponding to the conjugate with respect to unmodified DNA oligo.
a, Schematic representation of conjugation of anti-CD63 nanobody (VHH) and oligo sequence; SpyCatcher protein with N-terminal cysteine was first conjugated to a maleimide-oligo sequence. Then SpyCatcher–oligo complex was bound to SpyTag–nanobody specific for CD63. b, Two steps-based conjugation was visualised by Electrophoretic Mobility Shift assay (EMSA). Protein staining of PA gel shows the delayed migration of SpyCatcher after the conjugation with oligo sequence and a further band shift was observed due to the binding with SpyTag–nanobody. c, SPR real-time kinetic analysis of SpyTag-VHH (top) and the respective VHH-oligo conjugates (bottom) on sensor surfaces functionalized with CD63 proteins. Fitting was performed using a 1:1 kinetic model to the single cycle kinetic analysis to determine the dissociation constant, KD, association (kon) and dissociation (koff) rate constants.
a, Schematic representation of anti-CD71 aptamer modified with oligo sequence; b, The binding of the modified anti-CD71 aptamer to its target CD71 was verified by SPR real-time kinetic analysis. After immobilizing a biotinylated oligo that is complementary to the RNA sequence used to modify the aptamer on a streptavidin SPR surface, DNA–RNA hybridization was exploited to anchor the aptamer–oligo conjugate. Binding of CD71 to the immobilized aptamer was verified by single cycle kinetic mode measurement. Fitting was performed using a two-state reaction kinetic model to the single cycle kinetic analysis to determine the dissociation constant, KD, association (kon) and dissociation (koff) rate constants.
Heatmap numerical data.
Heatmap numerical data.
Heatmap numerical data.
Histogram numerical data.
Histogram and heatmap numerical data.
Histogram and heatmap numerical data.
About this article
Cite this article
Ambrosetti, E., Bernardinelli, G., Hoffecker, I. et al. A DNA-nanoassembly-based approach to map membrane protein nanoenvironments. Nat. Nanotechnol. 16, 85–95 (2021). https://doi.org/10.1038/s41565-020-00785-0
Cellular macromolecules-tethered DNA walking indexing to explore nanoenvironments of chromatin modifications
Nature Communications (2021)
Applied Sciences (2021)
Trends in Biotechnology (2021)
Physica A: Statistical Mechanics and its Applications (2021)