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A DNA-nanoassembly-based approach to map membrane protein nanoenvironments

Abstract

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.

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Fig. 1: Schematic of the NanoDeep method.
Fig. 2: NanoComb characterization.
Fig. 3: Toehold exchange reversibly blocked the hybridization of affibody–oligonucleotide conjugates to the NanoCombs.
Fig. 4: DNA polymerase and nuclease reactions generated barcoded dsDNA sequences.
Fig. 5: NanoDeep on model SPR surfaces.
Fig. 6: NanoDeep on cells.
Fig. 7: NanoDeep with expanded library.

Data availability

All data supporting the results of this study are available from the Swedish National Data Service (https://snd.gu/se/en). Source data are provided with this paper.

Code availability

Codes for UMI processing and barcode association are available online at https://github.com/Intertangler/NanoDeep.

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Acknowledgements

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.).

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Contributions

E.A. designed the study and performed the experiments; G.B. designed the affibody plasmids; G.B. and B.H. provided key insights for the design of experiments; I.H. developed NGS data analysis; L.H. and R.S. contributed to performance and interpretation of the NGS experiments; G.K. and A.d.M. contributed to development of the expanded library. A.I.T. conceived and supervised the study; E.A. and A.I.T. wrote the manuscript, with input from all authors; all authors contributed to the manuscript revision and gave approval to the final version.

Corresponding author

Correspondence to Ana I. Teixeira.

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Extended data

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.

Extended Data Fig. 2 Characterization of affibody-oligo conjugates.

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.

Extended Data Fig. 5 Assessment of the specificity of the binding of NanoCombs to cells.

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

Extended Data Fig. 6 Characterization of Her3-NanoCombs and performance in NanoDeep.

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

Extended Data Fig. 7 NanoDeep on SH-SY5Y cells.

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

Extended Data Fig. 8 Anti-integrin α5β1 binder-oligo conjugate production and characterization.

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.

Extended Data Fig. 9 Anti-CD63 binder-oligo conjugate production and characterization.

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.

Extended Data Fig. 10 Anti-CD71 binder-oligo conjugate modification and characterization.

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.

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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

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