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124-Color Super-resolution Imaging by Engineering DNA-PAINT Blinking Kinetics

  • Orsolya K. Wade
    Orsolya K. Wade
    Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, Germany
    Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
  • Johannes B. Woehrstein
    Johannes B. Woehrstein
    Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, Germany
    Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
  • Philipp C. Nickels
    Philipp C. Nickels
    Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, Germany
    Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
  • Sebastian Strauss
    Sebastian Strauss
    Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, Germany
    Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
  • Florian Stehr
    Florian Stehr
    Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
  • Johannes Stein
    Johannes Stein
    Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
  • Florian Schueder
    Florian Schueder
    Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, Germany
    Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
  • Maximilian T. Strauss
    Maximilian T. Strauss
    Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, Germany
    Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
  • Mahipal Ganji
    Mahipal Ganji
    Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, Germany
    Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
  • Joerg Schnitzbauer
    Joerg Schnitzbauer
    Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, Germany
    Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
  • Heinrich Grabmayr
    Heinrich Grabmayr
    Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, Germany
    Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
  • Peng Yin
    Peng Yin
    Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts 02138, United States
    Department of Systems Biology, Harvard Medical School, Boston, Massachusetts 02115, United States
    More by Peng Yin
  • Petra Schwille
    Petra Schwille
    Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
  • , and 
  • Ralf Jungmann*
    Ralf Jungmann
    Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, Germany
    Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
    *E-mail: [email protected]. Phone: +49 89 8578 3410.
Cite this: Nano Lett. 2019, 19, 4, 2641–2646
Publication Date (Web):March 13, 2019
https://doi.org/10.1021/acs.nanolett.9b00508

Copyright © 2019 American Chemical Society. This publication is licensed under CC-BY.

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Abstract

Optical super-resolution techniques reach unprecedented spatial resolution down to a few nanometers. However, efficient multiplexing strategies for the simultaneous detection of hundreds of molecular species are still elusive. Here, we introduce an entirely new approach to multiplexed super-resolution microscopy by designing the blinking behavior of targets with engineered binding frequency and duration in DNA-PAINT. We assay this kinetic barcoding approach in silico and in vitro using DNA origami structures, show the applicability for multiplexed RNA and protein detection in cells, and finally experimentally demonstrate 124-plex super-resolution imaging within minutes.

The development of optical super-resolution techniques allows researchers to unravel molecular properties of biological systems with thus far unprecedented detail. (1−4) While recent technical advancements propel the achievable spatial resolution to the true molecular scale of only a few nanometers, (5−7) current implementations are still limited when it comes to imaging many molecular species simultaneously in single cells and beyond. This so-called multiplexing is traditionally achieved using spectrally distinct, fixed labels (e.g., dye-coupled antibodies or nucleic acid probes) on target molecules of interest such as proteins, DNA, or RNA. While spectral multiplexing approaches are relatively straightforward to implement, the amount of “plex” is inherently limited by the number of distinguishable spectral labels in the detectable emission spectrum, which is in most instances three or four. (8) However, in order to fully understand the detailed molecular workings of the complex cellular machinery, one ideally would need to be able to look at hundreds if not thousands of unique components and their molecular interplay.

Some efforts to extend spectral multiplexing capabilities include multiparameter and combinatorial detection, (9,10) multispectral acquisition, (11) and spectrally resolved detection. (12,13) While these approaches increase the number of detectable targets, they are ultimately still limited by the spectral properties of fluorescent molecules used to label target structures.

To overcome the limitation inherent in spectral separation for multiplexed detection, several approaches have recently been devised that employ sequential labeling and imaging of targets using spectrally indistinct probes (14−17) (i.e., the same dye molecule). Some of these implementations rely on simultaneous labeling of target molecules with orthogonal DNA-barcoded affinity reagents (e.g., antibodies) followed by sequential imaging using dye-labeled complementary oligos (e.g., Exchange-PAINT (14) or Universal DNA Exchange (17,18)). Others use sequential labeling, imaging, and quenching based on dye-conjugated antibodies, e.g., STORM. (15,16) While both implementations differ slightly in the combined time for labeling and imaging of each target, the overall experimental time eventually scales linearly with the number of targets to be acquired. This fact ultimately sets a practical limit to the amount of multiplexing achievable. While it might be reasonable to obtain tens of targets with sequential multiplexing, it will become prohibitively time-intensive (and eventually impossible) for hundreds or even thousands of targets. Thus, current multiplexing approaches are inherently limited in terms of the achievable coding depth, overall acquisition time, and ease-of-use.

To overcome this limitation, we here propose an entirely orthogonal approach to achieve multiplexed detection in single-molecule-based super-resolution experiments that allows hundreds or more targets to be imaged simultaneously. Instead of relying on spectral information or sequential imaging, we engineer targets to blink autonomously with precisely adjustable kinetic signatures (i.e., frequency and duration of blinks), essentially providing a distinct kinetic barcode for hundreds of unique molecular species.

In order to implement and demonstrate the concept of engineered blinking kinetics for simultaneous multiplexed super-resolution imaging, we chose DNA-PAINT (7,19) as imaging modality. In DNA-PAINT, short dye-labeled oligonucleotides bind transiently to complementary, target-bound DNA molecules, thus creating an apparent blinking at the target site, which in turn is used for stochastic super-resolution microscopy. Due to the versatile programmability of DNA probes, the binding kinetics such as blinking frequency and duration can be tuned precisely and used downstream as “barcodes” for multiplexed detection.

The concept of engineering binding kinetics with DNA-PAINT is schematically shown in Figure 1a. In order to tune the blinking frequency of targets, we label one species with a single DNA-PAINT binding site and an orthogonal species with three binding sites. Assuming a constant influx of imager strands, the blinking frequency will scale linearly with the number of binding sites (e.g., resulting in a blinking frequency of two for the single binding site and a frequency of six for three sites; see Figure 1a). Similarly, we can modulate the blinking duration for a given target molecule by adjusting the length of the docking strand (e.g., 8 nt long docking strands will result in relatively short binding events, while 10 nt long docking sites will result in longer events; see Figure 1a). As binding frequency and duration are independent of each other in DNA-PAINT, these parameters can be combined to perform combinatorial barcoding with just a single imager strand species, thus enabling simultaneous multiplexed imaging.

Figure 1

Figure 1. Simultaneous multiplexed super-resolution imaging by engineering blinking kinetics. (a) Engineering blinking kinetics in DNA-PAINT allows the creation of “barcodes” for simultaneous multiplexing, using only a single imager strand species. Frequency can be encoded by designing a certain number of binding sites per target, e.g., a single binding site, leading to a defined blinking frequency. Tripling the number of binding sites triples the blinking frequency (left to right). Similarly, binding duration can be engineered by adjusting the length of the docking strand on a specific target: an 8 nt docking sequence will lead to a “short” binding duration, while a 10 nt docking sequence will result in longer binding (bottom to top). (b) Simulations of four kinetically different structures (40 and 120 binding sites and 8 and 10 nt lengths) show four clearly distinguishable populations corresponding to the engineered frequency and duration levels (see Supplementary Figure 1 for details on cluster detection). (c) Experimental results from DNA origami structures imaged using a single imager strand species show four distinguishable populations in good agreement with in silico data from c (see Supplementary Figure 5 for details on cluster detection). (d) Exemplary overview DNA-PAINT image of the four DNA origami structures (top). Same data set, now color-coded according to identified clusters in c (bottom). (e) Exemplary intensity versus time traces from highlighted regions in d representing each of the four unique DNA origami species. (f) Engineering frequency and duration on DNA origami below the diffraction limit. Each corner of the structure is designed to exhibit a unique kinetic fingerprint. Scale bars: 1 μm (d), 500 nm (f, top), 40 nm (f, bottom). For details regarding simulation parameters and cluster identification, see Methods in Supporting Information.

In order to screen for the optimal conditions to design distinguishable binding kinetics in terms of frequency and duration, we first performed in silico DNA-PAINT experiments. Tuning parameters such as binding time, imager strand concentration, number of binding sites, duration of image acquisition, and others (see online methods for details), we were able to engineer four distinguishable blinking regimes (two blinking frequencies based on 40 and 120 binding sites and two blinking durations based on 400 ms and 5 s) that can now be used for combinatorial barcoding with a single imager strand species only, allowing four-target super-resolution imaging in a relatively short duration of 25 min (Figure 1b and Supplementary Figure 1).

Next, to experimentally validate the in silico results, we turned to DNA origami (20) structures to implement the engineered frequency and duration levels, as these structures are exquisitely programmable for super-resolution microscopy. (21) We designed four structures carrying 40 and 120 binding sites either with 8 or 10 nt extensions of the same sequence and imaged them simultaneously using a single imager strand species (see also Supplementary Figure 2, Supplementary Tables 2–5, and Supplementary Note 1). In the resulting raw DNA-PAINT data, we performed kinetic analysis for each structure following an initial filtering step (Supplementary Figures 3 and 4) and plotted the obtained binding time and frequency in a 2D plot in the same manner as for the in silico data. Next, we subjected the 2D data set to a clustering analysis (hdbscan; (22) for details, see Methods in the Supporting Information), which resulted in four cluster species, in good agreement with the in silico data (Figure 1c and Supplementary Figure 5). This cluster identity now allows us to transform the raw DNA-PAINT image data (Figure 1d, top) to a barcoded pseudocolor image, where each DNA origami structure is assigned to one of the four cluster species (Figure 1d, bottom and Supplementary Figure 6). Examining the intensity versus time traces of four structures that were each assigned to one of the clusters indeed shows the distinct and expected kinetic fingerprints (Figure 1e).

To demonstrate that the kinetic barcoding approach allows satisfactory super-resolution performance, we designed a DNA origami structure with four different “binding spots”, at the four corners of the structure, each with four or 12 binding sites of either 8 or 10 nt length. Again, we performed DNA-PAINT using a single imager strand species and were able to visualize all four corners of the structure, separated by 40 nm. The blinking kinetics of the binding spots were then used to assign each to its correct corner (Figure 1f), demonstrating the application of blinking kinetics for super-resolution microscopy (Supplementary Figures 7 and 8).

Next, we designed two experiments to demonstrate the general applicability of our simultaneous multiplexing approach in situ in two biologically relevant settings. First, we implemented two-color frequency barcoding for two distinct mRNA species using a combination of DNA-PAINT implemented on a Spinning Disk Confocal microscope (23) and smRNA-FISH (14,24) (Figure 2a–d). We labeled TFRC and MKI67 mRNA species using two sets of FISH probes displaying 40 and 120 binding sites, respectively (see Figure 2a for probe design and Supplementary Tables 6 and 7 for probe sequences). After image acquisition, the RNA species appear as super-resolved spots in the resulting DNA-PAINT image (Figure 2b, see Methods in the Supporting Information for acquisition details). We then performed kinetic analysis on the individual RNA molecules and obtained a distribution of two populations corresponding to two distinct blinking frequencies, as designed (Figure 2c). Similar to the in vitro case (Figure 1), we assigned a pseudocolor to each of the blinking frequencies and rerendered a barcoded data set (Figure 2d), where we are now able to clearly distinguish TFRC from MKI67 mRNA molecules.

Figure 2

Figure 2. Engineered binding kinetics allow simultaneous multiplexed super-resolution imaging of RNA and proteins in cells. (a) Scheme showing the implementation of frequency barcoding for smRNA-FISH. Two distinct RNA species (TFRC and MKI67) are labeled with FISH probes featuring 40 binding sites for DNA-PAINT or 120 binding sites, respectively. (b) Resulting DNA-PAINT data after image acquisition shows TFRC and MKI67 mRNA molecules as single spots, which are not yet distinguishable. (c) Plotting the blinking frequency for all detected single mRNA molecules shows a clearly distinguishable distribution of a low and a high frequency, corresponding to the FISH probe set for TFRC (yellow) and MKI67 (green), respectively. (d) Distinct frequencies are used to assign a pseudocolor for each RNA species. (e) Scheme showing the implementation of duration barcoding for protein detection. Two distinct protein species are labeled with DNA-conjugated antibodies featuring an 8 and 9 nt binding site for DNA-PAINT imaging. (f) Resulting DNA-PAINT data after image acquisition shows CHC and PMP70 proteins as clusters, which are not yet distinguishable. (g) Plotting the binding duration for selected protein locations shows a clearly distinguishable distribution of short and long binding species, corresponding to the two proteins. (h) Distinct durations are used to assign a pseudocolor for each protein species. Scale bars: 1 μm.

To demonstrate that binding duration can be used in a similar fashion to barcode biomolecules in cells, we next used DNA-conjugated antibodies targeting the clathrin heavy chain (CHC) and a peroxisomal membrane protein (PMP70) inside HeLa cells, where each secondary antibody species carries a DNA-PAINT binding site of different length (Figure 2e and Supplementary Table 8). Similar to the mRNA experiments, we performed image acquisition and analysis and obtained a DNA-PAINT data set (Figure 2f). This was then transformed using kinetic analysis (Figure 2g) into a pseudocolored, barcoded image, where we were able to clearly distinguish areas of CHC and PMP70 based on the blinking duration (Figure 2h).

The proof-of-concept experiments for DNA origami, RNA, and protein barcoding underline the general applicability of the kinetic barcoding concept in vitro and in situ. However, to fully demonstrate the power of kinetic barcoding, we turned our attention to the question of how much simultaneous multiplexing can be achieved within a relatively short period of time. By combining four distinguishable binding frequencies with three spectral colors, we should be able to achieve simultaneous, 124-plex super-resolution imaging within a few minutes acquisition time. To demonstrate that this is indeed feasible, we designed and constructed 124 unique DNA origami structures carrying 0, 3, 9, 22, or 44 copies of three orthogonal binding sites each, respectively (Figure 3a and Supplementary Tables 9 and 10). After folding and purification (Supplementary Figure 9), we pooled all 124 distinct DNA origami structures into a single sample and performed 3-color DNA-PAINT imaging using Atto655-, Cy3B-, or Atto488-labeled orthogonal imager strands (Supplementary Table 11). As before, we performed kinetic analysis on each of the structures and plotted the distribution of binding frequencies for each spectral color separately (Figure 3b). We were able to clearly distinguish four distinct frequency populations in each of the three spectral colors. Using these levels, we assigned a unique barcode ID to each of the origami structures in the sample based on color and frequency and were able to render a full 124 pseudocolor super-resolution data set (Figure 3c, see also Methods in the Supporting Information for identification).

Figure 3

Figure 3. Frequency-based 124-plex super-resolution imaging. (a) DNA origami structures are extended with three unique sequences (red, green, or blue) with 0, 3, 9, 22, or 44 copies, respectively. Using combinatorial labeling, this yields a total of 53 – 1 = 124 unique target structures, achieved by distinguishing five frequency levels and using three spectral colors (i.e., three imager strand species). (b) Binding frequency distribution for all 124 DNA origami structures show four clearly distinguishable frequency levels corresponding to 3, 9, 22, and 44 binding sites for each spectral color (red, green, and blue), respectively. Based on these distributions, a unique barcode ID from a pool of 124 can be assigned to each structure. (c) DNA-PAINT super-resolution image of all 124 DNA origami structures, color-coded according to the assigned binding frequency and spectral color. (d) Quantification of the 124-plex experiment shows that all 124 structures could be identified. In total, 3289 structures were quantified, from which 243 were discarded due to ambiguous frequencies (i.e., overlap of distributions in b). (e) Twenty-five out of 124 structures were imaged in one sample in order to assess identification performance. In total, 1165 structures were quantified, from which 28 were categorized as false-positives (i.e., unexpected) resulting in an accuracy of 97.6%. The ratio between lowest expected and highest unexpected is 20 to 7. Scale bar: 5 μm.

Next, we quantified all DNA origami in the data set and were able to verify that indeed all 124 unique structures could be identified (Figure 3d). Finally, in order to assay the performance in terms of false positive identification of our multiplexing approach, we performed a similar experiment as described above, but now using only a subset of 25 out of the total 124 DNA origami structures (Figure 3e). The resulting quantitative analysis yielded a remarkable accuracy of 97.6%, underlining the robustness of our multiplexing approach based on engineered binding kinetics. We note, however, that this high number of multiplexing and robustness might not be achievable in a straightforward fashion in a cellular setting, e.g., for mRNA barcoding using smRNA-FISH as shown in the examples above, due to the increased complexity in the intracellular environment and suboptimal or target-dependent labeling efficiencies.

In conclusion, we introduced an entirely new barcoding approach for multiplexed detection based on precisely engineering blinking kinetics in stochastic super-resolution microscopy: kinetic barcoding. We demonstrated the implementation using DNA-PAINT both in vitro and in situ, currently reaching 124-plex within minutes. Zooming out, we envision that kinetic barcoding could be applied to ask Systems Biology questions in single cells with super-resolution by simultaneously imaging hundreds of DNA, RNA, and protein targets reaching transcriptomics- and proteomics-style experiments with a simple localization microscopy approach: “Localizomics”. Finally, one could envision its extension to even more multiplexing by implementing readouts such as molecular brightness of imager strands, fluorescence lifetime, and more. (25)

Supporting Information

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The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.nanolett.9b00508.

  • Materials and methods alongside detailed information about the optical setups, DNA origami self-assembly, RNA-FISH probe design and antibodies, sample preparation and data processing, sequences for DNA origami folding, DNA-PAINT docking and imager sequences, and RNA-FISH probes (PDF)

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Author Information

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  • Corresponding Author
  • Authors
    • Orsolya K. Wade - Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, GermanyMax Planck Institute of Biochemistry, 82152 Martinsried, Germany
    • Johannes B. Woehrstein - Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, GermanyMax Planck Institute of Biochemistry, 82152 Martinsried, Germany
    • Philipp C. Nickels - Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, GermanyMax Planck Institute of Biochemistry, 82152 Martinsried, Germany
    • Sebastian Strauss - Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, GermanyMax Planck Institute of Biochemistry, 82152 Martinsried, Germany
    • Florian Stehr - Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
    • Johannes Stein - Max Planck Institute of Biochemistry, 82152 Martinsried, GermanyOrcidhttp://orcid.org/0000-0002-1335-1120
    • Florian Schueder - Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, GermanyMax Planck Institute of Biochemistry, 82152 Martinsried, Germany
    • Maximilian T. Strauss - Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, GermanyMax Planck Institute of Biochemistry, 82152 Martinsried, Germany
    • Mahipal Ganji - Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, GermanyMax Planck Institute of Biochemistry, 82152 Martinsried, Germany
    • Joerg Schnitzbauer - Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, GermanyMax Planck Institute of Biochemistry, 82152 Martinsried, Germany
    • Heinrich Grabmayr - Department of Physics and Center for Nanoscience, Ludwig Maximilian University, 80539 Munich, GermanyMax Planck Institute of Biochemistry, 82152 Martinsried, Germany
    • Peng Yin - Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts 02138, United StatesDepartment of Systems Biology, Harvard Medical School, Boston, Massachusetts 02115, United StatesOrcidhttp://orcid.org/0000-0002-2769-6357
    • Petra Schwille - Max Planck Institute of Biochemistry, 82152 Martinsried, GermanyOrcidhttp://orcid.org/0000-0002-6106-4847
  • Funding

    This research was funded by the German Research Foundation through the Emmy Noether Program (DFG JU 2957/1–1) and the SFB1032 (Project A11), the European Research Council through an ERC Starting Grant (MolMap, Grant agreement number 680241), the Allen Distinguished Investigator Program through the Paul G. Allen Frontiers Group, the Max Planck Society, and the Max Planck Foundation. P.Y. acknowledges support by the NSF (CCF-1317291) and the NIH (1-U01-MH106011 and R01EB018659).

  • Notes
    The authors declare the following competing financial interest(s): J.B.W, R.J., and P.Y. filed a provisional patent based on this work. R.J. and P.Y. are co-founders of Ultivue, Inc.

Acknowledgments

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We thank Martin Spitaler and the imaging facility of the MPI of Biochemistry for confocal imaging support. We thank Alexander Auer for microscopy support and help with data acquisition. We thank Julian Bauer and Patrick Schueler for experimental support. We thank Mingjie Dai for help with data processing. We thank William M. Shih for fruitful discussions. O.K.W., S.S., F.St., and J.S. acknowledge support by the QBM graduate school. M.T.S. acknowledges support by the IMPRS-LS graduate school. M.G. acknowledges funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no 796606.

References

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This article references 25 other publications.

  1. 1
    Hell, S. W.; Sahl, S. J.; Bates, M.; Zhuang, X. W.; Heintzmann, R.; Booth, M. J.; Bewersdorf, J.; Shtengel, G.; Hess, H.; Tinnefeld, P.; Honigmann, A.; Jakobs, S.; Testa, I.; Cognet, L.; Lounis, B.; Ewers, H.; Davis, S. J.; Eggeling, C.; Klenerman, D.; Willig, K. I.; Vicidomini, G.; Castello, M.; Diaspro, A.; Cordes, T. The 2015 super-resolution microscopy roadmap. J. Phys. D: Appl. Phys. 2015, 48 (44), 443001,  DOI: 10.1088/0022-3727/48/44/443001
  2. 2
    Kanchanawong, P.; Shtengel, G.; Pasapera, A. M.; Ramko, E. B.; Davidson, M. W.; Hess, H. F.; Waterman, C. M. Nanoscale architecture of integrin-based cell adhesions. Nature 2010, 468 (7323), 5804,  DOI: 10.1038/nature09621
  3. 3
    Xu, K.; Zhong, G.; Zhuang, X. Actin, spectrin, and associated proteins form a periodic cytoskeletal structure in axons. Science 2013, 339 (6118), 4526,  DOI: 10.1126/science.1232251
  4. 4
    Sahl, S. J.; Hell, S. W.; Jakobs, S. Fluorescence nanoscopy in cell biology. Nat. Rev. Mol. Cell Biol. 2017, 18 (11), 685701,  DOI: 10.1038/nrm.2017.71
  5. 5
    Dai, M. J.; Jungmann, R.; Yin, P. Optical imaging of individual biomolecules in densely packed clusters. Nat. Nanotechnol. 2016, 11 (9), 798807,  DOI: 10.1038/nnano.2016.95
  6. 6
    Balzarotti, F.; Eilers, Y.; Gwosch, K. C.; Gynna, A. H.; Westphal, V.; Stefani, F. D.; Elf, J.; Hell, S. W. Nanometer resolution imaging and tracking of fluorescent molecules with minimal photon fluxes. Science 2017, 355 (6325), 606612,  DOI: 10.1126/science.aak9913
  7. 7
    Schnitzbauer, J.; Strauss, M. T.; Schlichthaerle, T.; Schueder, F.; Jungmann, R. Super-resolution microscopy with DNA-PAINT. Nat. Protoc. 2017, 12, 11981228,  DOI: 10.1038/nprot.2017.024
  8. 8
    Dempsey, G. T.; Vaughan, J. C.; Chen, K. H.; Bates, M.; Zhuang, X. Evaluation of fluorophores for optimal performance in localization-based super-resolution imaging. Nat. Methods 2011, 8 (12), 102736,  DOI: 10.1038/nmeth.1768
  9. 9
    Lubeck, E.; Cai, L. Single-cell systems biology by super-resolution imaging and combinatorial labeling. Nat. Methods 2012, 9 (7), 7438,  DOI: 10.1038/nmeth.2069
  10. 10
    Bates, M.; Dempsey, G. T.; Chen, K. H.; Zhuang, X. Multicolor super-resolution fluorescence imaging via multi-parameter fluorophore detection. ChemPhysChem 2012, 13 (1), 99107,  DOI: 10.1002/cphc.201100735
  11. 11
    Valm, A. M.; Cohen, S.; Legant, W. R.; Melunis, J.; Hershberg, U.; Wait, E.; Cohen, A. R.; Davidson, M. W.; Betzig, E.; Lippincott-Schwartz, J. Applying systems-level spectral imaging and analysis to reveal the organelle interactome. Nature 2017, 546 (7656), 162167,  DOI: 10.1038/nature22369
  12. 12
    Zhang, Z.; Kenny, S. J.; Hauser, M.; Li, W.; Xu, K. Ultrahigh-throughput single-molecule spectroscopy and spectrally resolved super-resolution microscopy. Nat. Methods 2015, 12 (10), 9358,  DOI: 10.1038/nmeth.3528
  13. 13
    Bongiovanni, M. N.; Godet, J.; Horrocks, M. H.; Tosatto, L.; Carr, A. R.; Wirthensohn, D. C.; Ranasinghe, R. T.; Lee, J. E.; Ponjavic, A.; Fritz, J. V.; Dobson, C. M.; Klenerman, D.; Lee, S. F. Multi-dimensional super-resolution imaging enables surface hydrophobicity mapping. Nat. Commun. 2016, 7, 13544,  DOI: 10.1038/ncomms13544
  14. 14
    Jungmann, R.; Avendano, M. S.; Woehrstein, J. B.; Dai, M. J.; Shih, W. M.; Yin, P. Multiplexed 3D cellular super-resolution imaging with DNA-PAINT and Exchange-PAINT. Nat. Methods 2014, 11 (3), 313U292,  DOI: 10.1038/nmeth.2835
  15. 15
    Tam, J.; Cordier, G. A.; Borbely, J. S.; Sandoval Alvarez, A.; Lakadamyali, M. Cross-talk-free multi-color STORM imaging using a single fluorophore. PLoS One 2014, 9 (7), e101772  DOI: 10.1371/journal.pone.0101772
  16. 16
    Valley, C. C.; Liu, S.; Lidke, D. S.; Lidke, K. A. Sequential superresolution imaging of multiple targets using a single fluorophore. PLoS One 2015, 10 (4), e0123941  DOI: 10.1371/journal.pone.0123941
  17. 17
    Schueder, F.; Strauss, M. T.; Hoerl, D.; Schnitzbauer, J.; Schlichthaerle, T.; Strauss, S.; Yin, P.; Harz, H.; Leonhardt, H.; Jungmann, R. Universal Super-Resolution Multiplexing by DNA Exchange. Angew. Chem., Int. Ed. 2017, 56 (14), 40524055,  DOI: 10.1002/anie.201611729
  18. 18
    Wang, Y.; Woehrstein, J. B.; Donoghue, N.; Dai, M.; Avendano, M. S.; Schackmann, R. C. J.; Zoeller, J. J.; Wang, S. S. H.; Tillberg, P. W.; Park, D.; Lapan, S. W.; Boyden, E. S.; Brugge, J. S.; Kaeser, P. S.; Church, G. M.; Agasti, S. S.; Jungmann, R.; Yin, P. Rapid Sequential in Situ Multiplexing with DNA Exchange Imaging in Neuronal Cells and Tissues. Nano Lett. 2017, 17 (10), 61316139,  DOI: 10.1021/acs.nanolett.7b02716
  19. 19
    Jungmann, R.; Steinhauer, C.; Scheible, M.; Kuzyk, A.; Tinnefeld, P.; Simmel, F. C. Single-Molecule Kinetics and Super-Resolution Microscopy by Fluorescence Imaging of Transient Binding on DNA Origami. Nano Lett. 2010, 10 (11), 47564761,  DOI: 10.1021/nl103427w
  20. 20
    Rothemund, P. W. K. Folding DNA to create nanoscale shapes and patterns. Nature 2006, 440 (7082), 297302,  DOI: 10.1038/nature04586
  21. 21
    Schlichthaerle, T.; Strauss, M. T.; Schueder, F.; Woehrstein, J. B.; Jungmann, R. DNA nanotechnology and fluorescence applications. Curr. Opin. Biotechnol. 2016, 39, 4147,  DOI: 10.1016/j.copbio.2015.12.014
  22. 22
    Campello, R. J. G. B.; Moulavi, D.; Sander, J. In Density-Based Clustering Based on Hierarchical Density Estimates; Springer Berlin Heidelberg: Berlin, Heidelberg, 2013; pp 160172.
  23. 23
    Schueder, F.; Lara-Gutierrez, J.; Beliveau, B. J.; Saka, S. K.; Sasaki, H. M.; Woehrstein, J. B.; Strauss, M. T.; Grabmayr, H.; Yin, P.; Jungmann, R. Multiplexed 3D super-resolution imaging of whole cells using spinning disk confocal microscopy and DNA-PAINT. Nat. Commun. 2017, 8 (1), 2090,  DOI: 10.1038/s41467-017-02028-8
  24. 24
    Raj, A.; van den Bogaard, P.; Rifkin, S. A.; van Oudenaarden, A.; Tyagi, S. Imaging individual mRNA molecules using multiple singly labeled probes. Nat. Methods 2008, 5 (10), 877879,  DOI: 10.1038/nmeth.1253
  25. 25
    Johnson-Buck, A.; Shih, W. M. Single-Molecule Clocks Controlled by Serial Chemical Reactions. Nano Lett. 2017, 17 (12), 79407944,  DOI: 10.1021/acs.nanolett.7b04336

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  25. Clément Cabriel, Tual Monfort, Christian G. Specht, Ignacio Izeddin. Event-based vision sensor for fast and dense single-molecule localization microscopy. Nature Photonics 2023, 17 (12) , 1105-1113. https://doi.org/10.1038/s41566-023-01308-8
  26. Abhinav Banerjee, Micky Anand, Simanta Kalita, Mahipal Ganji. Single-molecule analysis of DNA base-stacking energetics using patterned DNA nanostructures. Nature Nanotechnology 2023, 18 (12) , 1474-1482. https://doi.org/10.1038/s41565-023-01485-1
  27. Hua Liu, Zhongju Ye, Yanan Deng, Jie Yuan, Lin Wei, Lehui Xiao. Blinking fluorescent probes for single-molecule localization-based super-resolution imaging. TrAC Trends in Analytical Chemistry 2023, 169 , 117359. https://doi.org/10.1016/j.trac.2023.117359
  28. Ruixin Li, Anirudh S. Madhvacharyula, Yancheng Du, Harshith K. Adepu, Jong Hyun Choi. Mechanics of dynamic and deformable DNA nanostructures. Chemical Science 2023, 14 (30) , 8018-8046. https://doi.org/10.1039/D3SC01793A
  29. Marrit M. E. Tholen, Roderick P. Tas, Yuyang Wang, Lorenzo Albertazzi. Beyond DNA: new probes for PAINT super-resolution microscopy. Chemical Communications 2023, 59 (54) , 8332-8342. https://doi.org/10.1039/D3CC00757J
  30. Susanne C. M. Reinhardt, Luciano A. Masullo, Isabelle Baudrexel, Philipp R. Steen, Rafal Kowalewski, Alexandra S. Eklund, Sebastian Strauss, Eduard M. Unterauer, Thomas Schlichthaerle, Maximilian T. Strauss, Christian Klein, Ralf Jungmann. Ångström-resolution fluorescence microscopy. Nature 2023, 617 (7962) , 711-716. https://doi.org/10.1038/s41586-023-05925-9
  31. Benoît Arnould, Alexandria L. Quillin, Jennifer M. Heemstra. Tracking the Message: Applying Single Molecule Localization Microscopy to Cellular RNA Imaging. ChemBioChem 2023, 24 (10) https://doi.org/10.1002/cbic.202300049
  32. Abhinav Banerjee, Micky Anand, Mahipal Ganji. Labeling approaches for DNA-PAINT super-resolution imaging. Nanoscale 2023, 15 (14) , 6563-6580. https://doi.org/10.1039/D2NR06541J
  33. Seong Ho Kim, Isaac T. S. Li. Super‐Resolution Tension PAINT Imaging with a Molecular Beacon. Angewandte Chemie 2023, 135 (7) https://doi.org/10.1002/ange.202217028
  34. Seong Ho Kim, Isaac T. S. Li. Super‐Resolution Tension PAINT Imaging with a Molecular Beacon. Angewandte Chemie International Edition 2023, 62 (7) https://doi.org/10.1002/anie.202217028
  35. Hsiao Ju Chiang, Daniel E. S. Koo, Masahiro Kitano, Sean Burkitt, Jay R. Unruh, Cristina Zavaleta, Le A. Trinh, Scott E. Fraser, Francesco Cutrale. HyU: Hybrid Unmixing for longitudinal in vivo imaging of low signal-to-noise fluorescence. Nature Methods 2023, 20 (2) , 248-258. https://doi.org/10.1038/s41592-022-01751-5
  36. Raja Chouket, Agnès Pellissier-Tanon, Aliénor Lahlou, Ruikang Zhang, Diana Kim, Marie-Aude Plamont, Mingshu Zhang, Xi Zhang, Pingyong Xu, Nicolas Desprat, Dominique Bourgeois, Agathe Espagne, Annie Lemarchand, Thomas Le Saux, Ludovic Jullien. Extra kinetic dimensions for label discrimination. Nature Communications 2022, 13 (1) https://doi.org/10.1038/s41467-022-29172-0
  37. Nazar Oleksiievets, Yelena Sargsyan, Jan Christoph Thiele, Nikolaos Mougios, Shama Sograte-Idrissi, Oleksii Nevskyi, Ingo Gregor, Felipe Opazo, Sven Thoms, Jörg Enderlein, Roman Tsukanov. Fluorescence lifetime DNA-PAINT for multiplexed super-resolution imaging of cells. Communications Biology 2022, 5 (1) https://doi.org/10.1038/s42003-021-02976-4
  38. Zengwei Chen, Gaoqiang Yin, Jinxiu Wei, Tongsheng Qi, Ziting Qian, Zhuyuan Wang, Shenfei Zong, Yiping Cui. Quantitative analysis of multiple breast cancer biomarkers using DNA-PAINT. Analytical Methods 2022, 14 (37) , 3671-3679. https://doi.org/10.1039/D2AY00670G
  39. Zheze Dai, Xiaodong Xie, Zhaoshuai Gao, Qian Li. DNA‐PAINT Super‐Resolution Imaging for Characterization of Nucleic Acid Nanostructures. ChemPlusChem 2022, 87 (8) https://doi.org/10.1002/cplu.202200127
  40. Anna-Katharina Pumm, Wouter Engelen, Enzo Kopperger, Jonas Isensee, Matthias Vogt, Viktorija Kozina, Massimo Kube, Maximilian N. Honemann, Eva Bertosin, Martin Langecker, Ramin Golestanian, Friedrich C. Simmel, Hendrik Dietz. A DNA origami rotary ratchet motor. Nature 2022, 607 (7919) , 492-498. https://doi.org/10.1038/s41586-022-04910-y
  41. Kenny K. H. Chung, Zhao Zhang, Phylicia Kidd, Yongdeng Zhang, Nathan D. Williams, Bennett Rollins, Yang Yang, Chenxiang Lin, David Baddeley, Joerg Bewersdorf. Fluorogenic DNA-PAINT for faster, low-background super-resolution imaging. Nature Methods 2022, 19 (5) , 554-559. https://doi.org/10.1038/s41592-022-01464-9
  42. Shikha Dhiman, Teodora Andrian, Beatriz Santiago Gonzalez, Marrit M. E. Tholen, Yuyang Wang, Lorenzo Albertazzi. Can super-resolution microscopy become a standard characterization technique for materials chemistry?. Chemical Science 2022, 13 (8) , 2152-2166. https://doi.org/10.1039/D1SC05506B
  43. A. Femius Koenderink, Roman Tsukanov, Jörg Enderlein, Ignacio Izeddin, Valentina Krachmalnicoff. Super-resolution imaging: when biophysics meets nanophotonics. Nanophotonics 2022, 11 (2) , 169-202. https://doi.org/10.1515/nanoph-2021-0551
  44. Charles Bond, Adriana N. Santiago-Ruiz, Qing Tang, Melike Lakadamyali. Technological advances in super-resolution microscopy to study cellular processes. Molecular Cell 2022, 82 (2) , 315-332. https://doi.org/10.1016/j.molcel.2021.12.022
  45. Teodora Andrian, Silvia Pujals, Lorenzo Albertazzi. Quantifying the effect of PEG architecture on nanoparticle ligand availability using DNA-PAINT. Nanoscale Advances 2021, 3 (24) , 6876-6881. https://doi.org/10.1039/D1NA00696G
  46. George D. Dickinson, Golam Md Mortuza, William Clay, Luca Piantanida, Christopher M. Green, Chad Watson, Eric J. Hayden, Tim Andersen, Wan Kuang, Elton Graugnard, Reza Zadegan, William L. Hughes. An alternative approach to nucleic acid memory. Nature Communications 2021, 12 (1) https://doi.org/10.1038/s41467-021-22277-y
  47. Thomas Schlichthaerle, Caroline Lindner, Ralf Jungmann. Super-resolved visualization of single DNA-based tension sensors in cell adhesion. Nature Communications 2021, 12 (1) https://doi.org/10.1038/s41467-021-22606-1
  48. Florian Stehr, Johannes Stein, Julian Bauer, Christian Niederauer, Ralf Jungmann, Kristina Ganzinger, Petra Schwille. Tracking single particles for hours via continuous DNA-mediated fluorophore exchange. Nature Communications 2021, 12 (1) https://doi.org/10.1038/s41467-021-24223-4
  49. Martin L. Tomov, Alison O’Neil, Hamdah S. Abbasi, Beth A. Cimini, Anne E. Carpenter, Lee L. Rubin, Mark Bathe. Resolving cell state in iPSC-derived human neural samples with multiplexed fluorescence imaging. Communications Biology 2021, 4 (1) https://doi.org/10.1038/s42003-021-02276-x
  50. Mickaël Lelek, Melina T. Gyparaki, Gerti Beliu, Florian Schueder, Juliette Griffié, Suliana Manley, Ralf Jungmann, Markus Sauer, Melike Lakadamyali, Christophe Zimmer. Single-molecule localization microscopy. Nature Reviews Methods Primers 2021, 1 (1) https://doi.org/10.1038/s43586-021-00038-x
  51. Roger Rubio-Sánchez, Giacomo Fabrini, Pietro Cicuta, Lorenzo Di Michele. Amphiphilic DNA nanostructures for bottom-up synthetic biology. Chemical Communications 2021, 57 (95) , 12725-12740. https://doi.org/10.1039/D1CC04311K
  52. Raman van Wee, Mike Filius, Chirlmin Joo. Completing the canvas: advances and challenges for DNA-PAINT super-resolution imaging. Trends in Biochemical Sciences 2021, 46 (11) , 918-930. https://doi.org/10.1016/j.tibs.2021.05.010
  53. Yuang Chen, Fei Wang, Jiandong Feng, Chunhai Fan. Empowering single-molecule analysis with self-assembled DNA nanostructures. Matter 2021, 4 (10) , 3121-3145. https://doi.org/10.1016/j.matt.2021.08.003
  54. Somanna Kollimada, Fabrice Senger, Timothée Vignaud, Manuel Théry, Laurent Blanchoin, Laëtitia Kurzawa, . The biochemical composition of the actomyosin network sets the magnitude of cellular traction forces. Molecular Biology of the Cell 2021, 32 (18) , 1737-1748. https://doi.org/10.1091/mbc.E21-03-0109
  55. Colin S. Swenson, Hershel H. Lackey, Eric J. Reece, Joel M. Harris, Jennifer M. Heemstra, Eric M. Peterson. Evaluating the effect of ionic strength on PNA:DNA duplex formation kinetics. RSC Chemical Biology 2021, 2 (4) , 1249-1256. https://doi.org/10.1039/D1CB00025J
  56. Shengnan Fu, Tengfang Zhang, Huanling Jiang, Yan Xu, Jing Chen, Linghao Zhang, Xin Su. DNA nanotechnology enhanced single-molecule biosensing and imaging. TrAC Trends in Analytical Chemistry 2021, 140 , 116267. https://doi.org/10.1016/j.trac.2021.116267
  57. Fan Li, Jiang Li, Baijun Dong, Fei Wang, Chunhai Fan, Xiaolei Zuo. DNA nanotechnology-empowered nanoscopic imaging of biomolecules. Chemical Society Reviews 2021, 50 (9) , 5650-5667. https://doi.org/10.1039/D0CS01281E
  58. S. Hugelier, R. Van den Eynde, W. Vandenberg, P. Dedecker. Fluorophore unmixing based on bleaching and recovery kinetics using MCR-ALS. Talanta 2021, 226 , 122117. https://doi.org/10.1016/j.talanta.2021.122117
  59. , Rebecca Andrews. DNA hybridisation kinetics using single-molecule fluorescence imaging. Essays in Biochemistry 2021, 65 (1) , 27-36. https://doi.org/10.1042/EBC20200040
  60. Yuyoung Joo, David R. Benavides. Local Protein Translation and RNA Processing of Synaptic Proteins in Autism Spectrum Disorder. International Journal of Molecular Sciences 2021, 22 (6) , 2811. https://doi.org/10.3390/ijms22062811
  61. Teodora Andrian, Roger Riera, Silvia Pujals, Lorenzo Albertazzi. Nanoscopy for endosomal escape quantification. Nanoscale Advances 2021, 3 (1) , 10-23. https://doi.org/10.1039/D0NA00454E
  62. Francisco J. Barrantes. Fluorescence sensors for imaging membrane lipid domains and cholesterol. 2021, 257-314. https://doi.org/10.1016/bs.ctm.2021.09.004
  63. Tingting Zhai, Qian Li, Jianlei Shen, Jiang Li, Chunhai Fan. DNA nanostructure‐encoded fluorescent barcodes. Aggregate 2020, 1 (1) , 107-116. https://doi.org/10.1002/agt2.8
  64. Florian Schueder, Eduard M. Unterauer, Mahipal Ganji, Ralf Jungmann. DNA‐Barcoded Fluorescence Microscopy for Spatial Omics. PROTEOMICS 2020, 20 (23) https://doi.org/10.1002/pmic.201900368
  65. Curran Oi, Simon G. J. Mochrie, Mathew H. Horrocks, Lynne Regan. PAINT using proteins: A new brush for super‐resolution artists. Protein Science 2020, 29 (11) , 2142-2149. https://doi.org/10.1002/pro.3953
  66. Michael Scheckenbach, Julian Bauer, Jonas Zähringer, Florian Selbach, Philip Tinnefeld. DNA origami nanorulers and emerging reference structures. APL Materials 2020, 8 (11) https://doi.org/10.1063/5.0022885
  67. Jie Wang, Zicheng Wang, Yangyue Xu, Xuefei Wang, Zhiyong Yang, Hongda Wang, Zhiyuan Tian. Correlative dual-alternating-color photoswitching fluorescence imaging and AFM enable ultrastructural analyses of complex structures with nanoscale resolution. Nanoscale 2020, 12 (33) , 17203-17212. https://doi.org/10.1039/D0NR04584E
  68. Sebastian Strauss, Ralf Jungmann. Up to 100-fold speed-up and multiplexing in optimized DNA-PAINT. Nature Methods 2020, 17 (8) , 789-791. https://doi.org/10.1038/s41592-020-0869-x
  69. Zhishuang Xue, Xiaofang Liu, Hui Huang, Gen Zhang. Image Super-Resolution via Residual Blocks and Non-Negative Matrix Decomposition. Journal of Physics: Conference Series 2020, 1617 (1) , 012060. https://doi.org/10.1088/1742-6596/1617/1/012060
  70. Casey M. Platnich, Felix J. Rizzuto, Gonzalo Cosa, Hanadi F. Sleiman. Single-molecule methods in structural DNA nanotechnology. Chemical Society Reviews 2020, 49 (13) , 4220-4233. https://doi.org/10.1039/C9CS00776H
  71. Shama Sograte-Idrissi, Thomas Schlichthaerle, Carlos J. Duque-Afonso, Mihai Alevra, Sebastian Strauss, Tobias Moser, Ralf Jungmann, Silvio O. Rizzoli, Felipe Opazo. Circumvention of common labelling artefacts using secondary nanobodies. Nanoscale 2020, 12 (18) , 10226-10239. https://doi.org/10.1039/D0NR00227E
  72. Vesal Yaghoobi, Sandra Martinez-Morilla, Yuting Liu, Lori Charette, David L. Rimm, Malini Harigopal. Advances in quantitative immunohistochemistry and their contribution to breast cancer. Expert Review of Molecular Diagnostics 2020, 20 (5) , 509-522. https://doi.org/10.1080/14737159.2020.1743178
  73. Melike Lakadamyali, Maria Pia Cosma. Visualizing the genome in high resolution challenges our textbook understanding. Nature Methods 2020, 17 (4) , 371-379. https://doi.org/10.1038/s41592-020-0758-3
  74. Leonhard Möckl, Anish R. Roy, Petar N. Petrov, W. E. Moerner. Accurate and rapid background estimation in single-molecule localization microscopy using the deep neural network BGnet. Proceedings of the National Academy of Sciences 2020, 117 (1) , 60-67. https://doi.org/10.1073/pnas.1916219117
  75. Chen Chen, Shenfei Zong, Yun Liu, Zhuyuan Wang, Yizhi Zhang, Baoan Chen, Yiping Cui. Profiling of Exosomal Biomarkers for Accurate Cancer Identification: Combining DNA‐PAINT with Machine‐ Learning‐Based Classification. Small 2019, 15 (43) https://doi.org/10.1002/smll.201901014
  • Abstract

    Figure 1

    Figure 1. Simultaneous multiplexed super-resolution imaging by engineering blinking kinetics. (a) Engineering blinking kinetics in DNA-PAINT allows the creation of “barcodes” for simultaneous multiplexing, using only a single imager strand species. Frequency can be encoded by designing a certain number of binding sites per target, e.g., a single binding site, leading to a defined blinking frequency. Tripling the number of binding sites triples the blinking frequency (left to right). Similarly, binding duration can be engineered by adjusting the length of the docking strand on a specific target: an 8 nt docking sequence will lead to a “short” binding duration, while a 10 nt docking sequence will result in longer binding (bottom to top). (b) Simulations of four kinetically different structures (40 and 120 binding sites and 8 and 10 nt lengths) show four clearly distinguishable populations corresponding to the engineered frequency and duration levels (see Supplementary Figure 1 for details on cluster detection). (c) Experimental results from DNA origami structures imaged using a single imager strand species show four distinguishable populations in good agreement with in silico data from c (see Supplementary Figure 5 for details on cluster detection). (d) Exemplary overview DNA-PAINT image of the four DNA origami structures (top). Same data set, now color-coded according to identified clusters in c (bottom). (e) Exemplary intensity versus time traces from highlighted regions in d representing each of the four unique DNA origami species. (f) Engineering frequency and duration on DNA origami below the diffraction limit. Each corner of the structure is designed to exhibit a unique kinetic fingerprint. Scale bars: 1 μm (d), 500 nm (f, top), 40 nm (f, bottom). For details regarding simulation parameters and cluster identification, see Methods in Supporting Information.

    Figure 2

    Figure 2. Engineered binding kinetics allow simultaneous multiplexed super-resolution imaging of RNA and proteins in cells. (a) Scheme showing the implementation of frequency barcoding for smRNA-FISH. Two distinct RNA species (TFRC and MKI67) are labeled with FISH probes featuring 40 binding sites for DNA-PAINT or 120 binding sites, respectively. (b) Resulting DNA-PAINT data after image acquisition shows TFRC and MKI67 mRNA molecules as single spots, which are not yet distinguishable. (c) Plotting the blinking frequency for all detected single mRNA molecules shows a clearly distinguishable distribution of a low and a high frequency, corresponding to the FISH probe set for TFRC (yellow) and MKI67 (green), respectively. (d) Distinct frequencies are used to assign a pseudocolor for each RNA species. (e) Scheme showing the implementation of duration barcoding for protein detection. Two distinct protein species are labeled with DNA-conjugated antibodies featuring an 8 and 9 nt binding site for DNA-PAINT imaging. (f) Resulting DNA-PAINT data after image acquisition shows CHC and PMP70 proteins as clusters, which are not yet distinguishable. (g) Plotting the binding duration for selected protein locations shows a clearly distinguishable distribution of short and long binding species, corresponding to the two proteins. (h) Distinct durations are used to assign a pseudocolor for each protein species. Scale bars: 1 μm.

    Figure 3

    Figure 3. Frequency-based 124-plex super-resolution imaging. (a) DNA origami structures are extended with three unique sequences (red, green, or blue) with 0, 3, 9, 22, or 44 copies, respectively. Using combinatorial labeling, this yields a total of 53 – 1 = 124 unique target structures, achieved by distinguishing five frequency levels and using three spectral colors (i.e., three imager strand species). (b) Binding frequency distribution for all 124 DNA origami structures show four clearly distinguishable frequency levels corresponding to 3, 9, 22, and 44 binding sites for each spectral color (red, green, and blue), respectively. Based on these distributions, a unique barcode ID from a pool of 124 can be assigned to each structure. (c) DNA-PAINT super-resolution image of all 124 DNA origami structures, color-coded according to the assigned binding frequency and spectral color. (d) Quantification of the 124-plex experiment shows that all 124 structures could be identified. In total, 3289 structures were quantified, from which 243 were discarded due to ambiguous frequencies (i.e., overlap of distributions in b). (e) Twenty-five out of 124 structures were imaged in one sample in order to assess identification performance. In total, 1165 structures were quantified, from which 28 were categorized as false-positives (i.e., unexpected) resulting in an accuracy of 97.6%. The ratio between lowest expected and highest unexpected is 20 to 7. Scale bar: 5 μm.

  • References

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    Jump To

    This article references 25 other publications.

    1. 1
      Hell, S. W.; Sahl, S. J.; Bates, M.; Zhuang, X. W.; Heintzmann, R.; Booth, M. J.; Bewersdorf, J.; Shtengel, G.; Hess, H.; Tinnefeld, P.; Honigmann, A.; Jakobs, S.; Testa, I.; Cognet, L.; Lounis, B.; Ewers, H.; Davis, S. J.; Eggeling, C.; Klenerman, D.; Willig, K. I.; Vicidomini, G.; Castello, M.; Diaspro, A.; Cordes, T. The 2015 super-resolution microscopy roadmap. J. Phys. D: Appl. Phys. 2015, 48 (44), 443001,  DOI: 10.1088/0022-3727/48/44/443001
    2. 2
      Kanchanawong, P.; Shtengel, G.; Pasapera, A. M.; Ramko, E. B.; Davidson, M. W.; Hess, H. F.; Waterman, C. M. Nanoscale architecture of integrin-based cell adhesions. Nature 2010, 468 (7323), 5804,  DOI: 10.1038/nature09621
    3. 3
      Xu, K.; Zhong, G.; Zhuang, X. Actin, spectrin, and associated proteins form a periodic cytoskeletal structure in axons. Science 2013, 339 (6118), 4526,  DOI: 10.1126/science.1232251
    4. 4
      Sahl, S. J.; Hell, S. W.; Jakobs, S. Fluorescence nanoscopy in cell biology. Nat. Rev. Mol. Cell Biol. 2017, 18 (11), 685701,  DOI: 10.1038/nrm.2017.71
    5. 5
      Dai, M. J.; Jungmann, R.; Yin, P. Optical imaging of individual biomolecules in densely packed clusters. Nat. Nanotechnol. 2016, 11 (9), 798807,  DOI: 10.1038/nnano.2016.95
    6. 6
      Balzarotti, F.; Eilers, Y.; Gwosch, K. C.; Gynna, A. H.; Westphal, V.; Stefani, F. D.; Elf, J.; Hell, S. W. Nanometer resolution imaging and tracking of fluorescent molecules with minimal photon fluxes. Science 2017, 355 (6325), 606612,  DOI: 10.1126/science.aak9913
    7. 7
      Schnitzbauer, J.; Strauss, M. T.; Schlichthaerle, T.; Schueder, F.; Jungmann, R. Super-resolution microscopy with DNA-PAINT. Nat. Protoc. 2017, 12, 11981228,  DOI: 10.1038/nprot.2017.024
    8. 8
      Dempsey, G. T.; Vaughan, J. C.; Chen, K. H.; Bates, M.; Zhuang, X. Evaluation of fluorophores for optimal performance in localization-based super-resolution imaging. Nat. Methods 2011, 8 (12), 102736,  DOI: 10.1038/nmeth.1768
    9. 9
      Lubeck, E.; Cai, L. Single-cell systems biology by super-resolution imaging and combinatorial labeling. Nat. Methods 2012, 9 (7), 7438,  DOI: 10.1038/nmeth.2069
    10. 10
      Bates, M.; Dempsey, G. T.; Chen, K. H.; Zhuang, X. Multicolor super-resolution fluorescence imaging via multi-parameter fluorophore detection. ChemPhysChem 2012, 13 (1), 99107,  DOI: 10.1002/cphc.201100735
    11. 11
      Valm, A. M.; Cohen, S.; Legant, W. R.; Melunis, J.; Hershberg, U.; Wait, E.; Cohen, A. R.; Davidson, M. W.; Betzig, E.; Lippincott-Schwartz, J. Applying systems-level spectral imaging and analysis to reveal the organelle interactome. Nature 2017, 546 (7656), 162167,  DOI: 10.1038/nature22369
    12. 12
      Zhang, Z.; Kenny, S. J.; Hauser, M.; Li, W.; Xu, K. Ultrahigh-throughput single-molecule spectroscopy and spectrally resolved super-resolution microscopy. Nat. Methods 2015, 12 (10), 9358,  DOI: 10.1038/nmeth.3528
    13. 13
      Bongiovanni, M. N.; Godet, J.; Horrocks, M. H.; Tosatto, L.; Carr, A. R.; Wirthensohn, D. C.; Ranasinghe, R. T.; Lee, J. E.; Ponjavic, A.; Fritz, J. V.; Dobson, C. M.; Klenerman, D.; Lee, S. F. Multi-dimensional super-resolution imaging enables surface hydrophobicity mapping. Nat. Commun. 2016, 7, 13544,  DOI: 10.1038/ncomms13544
    14. 14
      Jungmann, R.; Avendano, M. S.; Woehrstein, J. B.; Dai, M. J.; Shih, W. M.; Yin, P. Multiplexed 3D cellular super-resolution imaging with DNA-PAINT and Exchange-PAINT. Nat. Methods 2014, 11 (3), 313U292,  DOI: 10.1038/nmeth.2835
    15. 15
      Tam, J.; Cordier, G. A.; Borbely, J. S.; Sandoval Alvarez, A.; Lakadamyali, M. Cross-talk-free multi-color STORM imaging using a single fluorophore. PLoS One 2014, 9 (7), e101772  DOI: 10.1371/journal.pone.0101772
    16. 16
      Valley, C. C.; Liu, S.; Lidke, D. S.; Lidke, K. A. Sequential superresolution imaging of multiple targets using a single fluorophore. PLoS One 2015, 10 (4), e0123941  DOI: 10.1371/journal.pone.0123941
    17. 17
      Schueder, F.; Strauss, M. T.; Hoerl, D.; Schnitzbauer, J.; Schlichthaerle, T.; Strauss, S.; Yin, P.; Harz, H.; Leonhardt, H.; Jungmann, R. Universal Super-Resolution Multiplexing by DNA Exchange. Angew. Chem., Int. Ed. 2017, 56 (14), 40524055,  DOI: 10.1002/anie.201611729
    18. 18
      Wang, Y.; Woehrstein, J. B.; Donoghue, N.; Dai, M.; Avendano, M. S.; Schackmann, R. C. J.; Zoeller, J. J.; Wang, S. S. H.; Tillberg, P. W.; Park, D.; Lapan, S. W.; Boyden, E. S.; Brugge, J. S.; Kaeser, P. S.; Church, G. M.; Agasti, S. S.; Jungmann, R.; Yin, P. Rapid Sequential in Situ Multiplexing with DNA Exchange Imaging in Neuronal Cells and Tissues. Nano Lett. 2017, 17 (10), 61316139,  DOI: 10.1021/acs.nanolett.7b02716
    19. 19
      Jungmann, R.; Steinhauer, C.; Scheible, M.; Kuzyk, A.; Tinnefeld, P.; Simmel, F. C. Single-Molecule Kinetics and Super-Resolution Microscopy by Fluorescence Imaging of Transient Binding on DNA Origami. Nano Lett. 2010, 10 (11), 47564761,  DOI: 10.1021/nl103427w
    20. 20
      Rothemund, P. W. K. Folding DNA to create nanoscale shapes and patterns. Nature 2006, 440 (7082), 297302,  DOI: 10.1038/nature04586
    21. 21
      Schlichthaerle, T.; Strauss, M. T.; Schueder, F.; Woehrstein, J. B.; Jungmann, R. DNA nanotechnology and fluorescence applications. Curr. Opin. Biotechnol. 2016, 39, 4147,  DOI: 10.1016/j.copbio.2015.12.014
    22. 22
      Campello, R. J. G. B.; Moulavi, D.; Sander, J. In Density-Based Clustering Based on Hierarchical Density Estimates; Springer Berlin Heidelberg: Berlin, Heidelberg, 2013; pp 160172.
    23. 23
      Schueder, F.; Lara-Gutierrez, J.; Beliveau, B. J.; Saka, S. K.; Sasaki, H. M.; Woehrstein, J. B.; Strauss, M. T.; Grabmayr, H.; Yin, P.; Jungmann, R. Multiplexed 3D super-resolution imaging of whole cells using spinning disk confocal microscopy and DNA-PAINT. Nat. Commun. 2017, 8 (1), 2090,  DOI: 10.1038/s41467-017-02028-8
    24. 24
      Raj, A.; van den Bogaard, P.; Rifkin, S. A.; van Oudenaarden, A.; Tyagi, S. Imaging individual mRNA molecules using multiple singly labeled probes. Nat. Methods 2008, 5 (10), 877879,  DOI: 10.1038/nmeth.1253
    25. 25
      Johnson-Buck, A.; Shih, W. M. Single-Molecule Clocks Controlled by Serial Chemical Reactions. Nano Lett. 2017, 17 (12), 79407944,  DOI: 10.1021/acs.nanolett.7b04336
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    • Materials and methods alongside detailed information about the optical setups, DNA origami self-assembly, RNA-FISH probe design and antibodies, sample preparation and data processing, sequences for DNA origami folding, DNA-PAINT docking and imager sequences, and RNA-FISH probes (PDF)


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