- Open Access
Accelerated super-resolution imaging with FRET-PAINT
© The Author(s). 2017
- Received: 14 December 2017
- Accepted: 20 December 2017
- Published: 28 December 2017
Super-resolution fluorescence microscopy in the current form is hard to be used to image the neural connectivity of thick tissue samples due to problems such as slow imaging speed, severe photobleaching of fluorescent probes, and high background noise. Recently developed DNA-PAINT solved the photobleaching problem, but its imaging speed is extremely low. We report accelerated super-resolution fluorescence microscopy named FRET-PAINT. Compared to conventional DNA-PAINT, the imaging speed of the microscopy increases up to ~30-fold. As demonstrations, we show that 25-50 second imaging time is long enough to provide super-resolution reconstruction of microtubules and mitochondria of COS-7 cells.
- super-resolution microscopy
- single-molecule localization microscopy
- fluorescence resonance energy transfer
Imaging of neural connectivity is challenging because the subcellular structures critical for neural communication—the axon, presynaptic active zone, synaptic cleft, postsynaptic density, and gap junction—are all in tens of nanometers in scale. Serial section electron microscopy, the sole method that is currently available to image neural connectivity with high resolution, is too laborious and error-prone. It does not provide clear pictures of gap junctions, and cannot distinguish whether a chemical synapse is excitatory or inhibitory. Furthermore, it takes huge amount of time to reconstruct a three-dimensional neural connection map from two-dimensional gray-scale image stacks of electron micrographs.
Development of super-resolution fluorescence microscopy has opened a way to study neural structures without being limited by optical diffraction [1–7]. The achievement, however, was not obtained without sacrifice. Compared to conventional fluorescence microscopy, super-resolution fluorescence microscopy techniques usually suffer from aggravated photobleaching and slowed-down imaging speed. Due to these problems, super-resolution fluorescence microscopy in the current form is hard to be directly used to image thick neural tissue samples. Recently developed DNA-PAINT (Point Accumulation for Imaging in Nanoscale Topography ) technique has overcome the photobleaching problem by using transient binding of a fluorescently labeled short DNA strand (imager strand) to a docking DNA strand conjugated to target molecules [9–14]. Since photobleached probes are continuously replaced with a new one, fluorescence imaging can be performed without being limited by photobleaching. Furthermore, DNA-PAINT technique provides more photon numbers than other single-molecule localization techniques, resulting in the best localization precision reported until now [12, 14]. The imaging speed of DNA-PAINT (1-3 frames per hour), however, is extremely slow compared to those of other super-resolution fluorescence microscopy techniques . The slow imaging speed of DNA-PAINT is due to slow binding of the imager strand. Since the binding rate of the imager strand is proportional to the ‘imager’ concentration, an obvious solution to this problem is to use higher imager concentration. In current DNA-PAINT technology, however, the imager concentration cannot be increased more than a few nanomolar because background noise also proportionally increases with the imager concentration.
We here developed DNA-PAINT based on FRET (Fluorescence Resonance Energy Transfer ). In this technique that we named FRET-PAINT, the docking strand has two DNA binding sites: one for a donor strand and the other for an acceptor strand. For single-molecule localization, FRET signal of the acceptor is used. Since the acceptor is not directly excited but by FRET, 100 times higher imager (donor and acceptor) concentrations could be used. In this paper, we demonstrated ~30-fold imaging speed increase of FRET-PAINT compared to DNA-PAINT.
Characterization of FRET-PAINT
The donor strand was labeled at the 3’-end with Alexa488 (Donor_P1_Alexa488, Additional file 1) whereas the acceptor strand was labeled with Cy5 (Acceptor_P11_Cy5, Additional file 1) at the 3’-end. We immobilized the docking strand on a polymer-coated quartz surface using a streptavidin-biotin interaction and took single-molecule images of Cy5 after injecting the donor (1000 nM) and acceptor (100 nM) strands by exciting Alexa488 using a blue laser. In the scheme, we do not directly excite Cy5 (Fig. 1b), and therefore we could use such high concentrations of donor and acceptor strands without worrying about background noise. As Fig. 1c shows, we obtained clear Cy5 fluorescence intensity time traces at such high donor and acceptor concentrations.
Using the same scheme, we tried to find the optimum labeling position of FRET probes that gives maximum FRET signal for two FRET pairs: Cy3-Cy5 and Alexa488-Cy5. The general requirements for FRET pairs are large spectral overlap between donor emission and acceptor excitation for high FRET efficiency and small spectral overlap between donor emission and acceptor emission for low background noise. The Cy5 was chosen as an acceptor due to its superior photophysical properties such as high photostability and brightness. Alexa488 and Cy3 were selected as a donor because they are photostable and their fluorescence spectra do not significantly overlap with that of Cy5. We prepared donor strands labeled with either Cy3 (Donor_P1_Cy3, Additional file 1) or Alex488 (Donor_P1_Alexa488) at the 3’-end, and acceptor strands labeled with Cy5 at varying positions (Acceptor_P2_Cy5, P4_Cy5, P6_Cy5, and P11_Cy5, Additional file 1). The Cy3-Cy5 FRET pair gave the highest Cy5 signal when the gap between donor and acceptor fluorophores was 6 nt, whereas Alexa488-Cy5 FRET pair gave the highest Cy5 signal when the gap was 2 nt (Fig. 1d). We used these optimized labeling schemes for the remaining part of the paper.
In super-resolution fluorescence imaging, HILO (Highly Inclined and Laminated Optical sheet)  microscopy is conventionally used. We compared signal-to-noise ratios (SNRs) of DNA-PAINT and FRET-PAINT at varying DNA concentrations in HILO setup. Figure 1e is DNA-PAINT images of surface immobilized docking strand (Docking_P0) at varying imager strand (Acceptor_P11_Cy3, Additional file 1) concentrations. Single-molecule images started to be overwhelmed by background noise when image concentration was above 5 nM. Figure 1f is FRET-PAINT images of the docking strand at varying donor (Donor_P1_Cy3) concentrations with acceptor (Acceptor_P6_Cy5) concentration fixed at 10 nM. Figure 1g is FRET-PAINT images of the docking strand at varying acceptor (Acceptor_P6_Cy5) concentrations with donor (Donor_P1_Cy3) concentration fixed at 10 nM and. Figure 1h is FRET-PAINT images of the docking strand at varying donor (Donor_P1_Alexa488) concentrations with acceptor (Acceptor_P2_Cy5) concentration fixed at 10 nM. Figure 1i is FRET-PAINT images of the docking strand at varying acceptor (Acceptor_P2_Cy5) concentrations with donor (Donor_P1_Alexa488) concentration fixed at 10 nM. These images clearly show that similar SNR can be obtained at much higher imager concentrations in FRET-PAINT compared to DNA-PAINT. For instance, we used 5 nM imager concentration for DNA-PAINT to obtain the 3.3 SNR (Fig. 1j, k). For the same SNR, we could use 180 nM donor and 120 nM acceptor concentrations for the Cy3-Cy5 pair, and 250 nM donor and 90 nM acceptor concentrations for the Alexa488-Cy5 pair, respectively (Fig. 1j, k). Exact sample numbers for these analyses are described in the Methods section and the error bars represent standard error.
Superresolution imaging with DNA-PAINT and FRET-PAINT
Multiplexed imaging with FRET-PAINT
Despite of several merits of DNA-PAINT, the slow imaging speed of the technique has hindered widespread applications of DNA-PAINT to cellular or tissue imaging. To increase the imaging speed of DNA-PAINT, an obvious solution has been to use higher imager concentrations, but it could not be realized yet due to background noise which proportionally increases with the imager concentration. Here we demonstrated FRET-PAINT can nicely solve the problem and increases the superresolution imaging speed more than ~30-fold. It should be noticed that the advance was achieved without compromising the other advantages of DNA-PAINT: high spatial resolution, photobleaching-resistance, and imaging multiplexing capability. We expect FRET-PAINT will be a useful addition to the advancement of super-resolution fluorescence microscopy.
There are fundamental limits to the imaging speed in single molecule localization based microscopy techniques, which is mainly determined by the switching speed of fluorescence signals. In the scheme of DNA-PAINT and FRET-PAINT, the switching speed can be controlled in principle by changing the binding and dissociation rates of the imager strand. In case of DNA-PAINT, however, the binding rate is hard to be increased more than 2 x 10-3 Hz at 2 nM in HILO microscopy due to background noise (Fig. 1, Additional file 1: Figure S1) . We showed that in FRET-PAINT, the biding rate limited by background noise can be increased up to 0.25 Hz at 200 nM imager concentration in HILO microscopy (Fig. 1, Additional file 1: Figure S1). In this paper, however, we could not utilize the full capability of FRET-PAINT for microtubule imaging because single-molecule images started to overlap at 30-nM donor strand concentration (Additional file 1: Figure S4); we used single-emitter localization scheme, and therefore the donor and acceptor strand concentrations used for the FRET-PAINT imaging was determined to avoid the spot overlap. Since the concentration limit dictated by background noise is 10 times higher (Fig. 1f-k, Additional file 1: Figures S5-S6), the imaging speed will be further increased by incorporating shorter donor strand, higher frame rate, and multi-emitter fitting algorithms in the future [21–23].
FRET-PAINT reported in this paper has removed the two main obstacles in the way of using superresolution fulorescence microscopy for three-dimensional reconstruction of thick neural tissue samples: photobleaching of fluorophores and slow imaging speed. However, it is demonstrated only at the cellular level. For FRET-PAINT to be used for neural tissue imaging, huge background noise problem needs to be solved as well. Recently, we developed a real-time confocal microscopy that may provide superresoltion fluorescence images of thick tissue samples using video-rate confocal microscopy for single-molecule imaging . We expect that FRET-PAINT combined with our real-time confocal microscopy will finally enable us to reconstruct three-dimensional structures of thick neural tissue samples with both high speed and high resolution. During the review of our paper in other journals, the exactly same approach to increase the imaging speed of DNA-PAINT was published by Jungmann’s group .
Modified DNA oligonucleotides were purchased from Integrated DNA Technologies. Alexa488 (Alexa Fluor 488 NHS Ester, catalog number: A20000) was purchased from Thermo Fisher Scientific. Cy3 (Cy3 NHS Ester, catalog number: PA13101) and Cy5 (Cy5 NHS Ester, catalog number: PA15101) were purchased from GE Healthcare Life Sciences. COS-7 cells were purchased from Korean Cell Line Bank. Anti-tubulin antibody (catalog number: ab6160) was purchased from Abcam. Anti-Tom20 antibody (sc-11415) was purchased from Santa Cruz Biotechnology, Inc. Donkey anti-rabbit IgG antibody (catalog number: 711-005-152) and donkey anti-rat IgG antibody (catalog number: 712-005-153) were purchased from Jackson ImmunoResearch Laboratories, Inc. Carboxyl latex beads (catalog number: C37281) were purchased from Thermo Fisher Scientific. The docking strands were conjugated to the secondary antibodies using Antibody-Oligonucleotide All-in-One Conjugation Kit (catalog number: A-9202-001) purchased from Solulink. Paraformaldehyde (catalog number: 1.04005.1000) was purchased from Merck. Glutaraldehyde (catalog number: G5882), Triton X-100 (catalog number: T9284), and Bovine Serum Albumin (catalog number: A4919) were purchased from Sigma-Aldrich.
DNA labeling with fluorophores
Amine-modified DNA oligonucleotides were labeled with fluorophores which have NHS ester chemical group. 5 ul of 1 mM DNA was mixed with 25 ul of 100 mM sodium tetraborate buffer (pH 8.5). And then 5ul of 20 mM fluorophore in DMSO was added. After thorough mixing, the mixture was incubated at 4°C overnight while protected from light. 265 ul of distilled water, 900 ul of ethanol, and 30 ul of 3 M sodium acetate (pH 5.2) were added and mixed thoroughly. The mixture was incubated at -20°C for an hour and then centrifuged for a couple of hours until the DNA pellet is clearly visible. Supernatant was discarded and the pellet was washed with cold ethanol. After ethanol was evaporated completely, the pellet was resuspended in 50 ul of distilled water and the labeling efficiency was measured. If the labeling efficiency is low, the whole labeling process was repeated.
Cell culture, fixation, and immunostaining
For drift correction of DNA-PAINT imaging, #1.5 glass coverslips were sparsely coated with carboxyl latex beads. The coverslip was coated with bead solution 1:10 diluted in distilled water, heated for 10 minutes on a 100°C hot plate, washed thoroughly with distilled water, and dried with N2 gas. COS-7 cells were grown on bead-coated coverslips for a few days and then fixed for 10 minutes. 2% glutaraldehyde in cytoskeleton buffer was used for microtubule imaging (Fig. 2) and 3% paraformaldehyde and 0.1% glutaraldehyde mixture in PBS buffer was used for microtubule and mitochondria imaging (Fig. 3) [26, 27]. Fixed samples were stored at 4°C in PBS buffer until needed. A flow channel was made by assembling the cell-covered coverslip and a glass slide using double-sided tape and epoxy. In the glass slide, two holes were pre-made for convenient buffer exchange.
Microtubules were immunostained by injecting 1:100 diluted anti-tubulin antibody in blocking solution (5% Bovine Serum Albumin and 0.25% Triton X-100 in PBS buffer) into the channel and incubating at 4°C overnight. After thorough wash-out of free anti-tubulins with PBS buffer, cells were incubated with 100 nM secondary antibody conjugated with docking strand (Docking_P1, Additional file 1) for 1 hour. Mitochondria were immunostained by injecting 1:100 diluted anti-Tom20 antibody in blocking solution into the channel and incubating at 4°C overnight. After thorough wash-out of free anti-Tom20 antibody with PBS buffer, cells were incubated with 100 nM secondary antibody conjugated with docking strand (Docking_P2) for 1 hour.
For single-molecule imaging, a prism-type total internal reflection fluorescence (TIRF) microscopy and highly inclined and laminated optical sheet (HILO) microscopy were used. The microscope was built by modifying a commercial inverted microscope (IX71, Olympus), and equipped with a 100X 1.4 NA oil-immersion objective lens (UPlanSApo, Olympus). To obtain data in Fig. 1, docking strands were immobilized on the polymer-coated quartz slide surface by using streptavidin-biotin interaction, and donor and acceptor strands were added into the imaging channel. Alexa488, Cy3, and Cy5 were excited by a blue laser (473 nm, 100 mW, MBL-III-473-100mW, CNI), a green laser (532 nm, 50 mW, Compass 215M-50, Coherent), and a red laser (642 nm, 60 mW, Excelsior-642-60, Spectra-Physics), respectively. Cy3 signal was filtered using a dichroic mirror (640dcxr, Chroma), and Cy5 signal was filtered using a dichroic mirror (740dcxr, Chroma). Single-molecule images were recorded at a frame rate of 10 Hz with electron multiplying charge coupled device (EMCCD) camera (iXon Ultra DU-897U-CS0-#BV, Andor).
FRET pair characterization
To characterize detected photons per frame in Fig. 1d, 13997 (8096), 11021 (5100), 11208 (3451), and 17051 (3980) single-molecule spots were collected for 2 nt, 4 nt, 6 nt, and 11 nt Cy3-Cy5 (Alexa488-Cy5) FRET pairs, respectively. To characterize SNR in Fig. 1j-k, 795, 2322, and 742 single-molecule spots were collected for Cy3, Cy3-Cy5 pair, and Alexa488-Cy5 pair, respectively.
For super-resolution imaging with DNA-PAINT, we used a home-made auto-focusing and drift correction system based on image correlation method. Before filming, one in-focus bright field image and two out-of-focus images were taken. These three reference images were used to keep track of x, y, and z axes drift . The drift in z-direction was corrected in real time using a piezo stage (PZ-2000, Applied Scientific Instrumentation) whereas the drift in x-y plane was corrected during image analysis.
Availability of data and material
The datasets generated and analysed during the current study are available from the corresponding author on reasonable request.
This work was supported by a Creative Research Initiative grant (Physical Genetics Laboratory, 2009-0081562) to S.H.
JL conceived the main idea and designed experiments. JL and SP, performed experiments and analyzed data. WK contributed to the optimization of the microscope. All authors contributed to writing of the paper. SH supervised the research. All authors read and approved the final manuscript.
Ethics approval and consent to participate
Consent for publication
The authors declare that they have no competing interests
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Hell SW, Wichmann J. Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy. J. Opt. Lett. 1994;19:780–2.View ArticleGoogle Scholar
- Hell SW, Kroug M. Ground-state-depletion fluorscence microscopy: A concept for breaking the diffraction resolution limit. Appl. Phys. B. 1995;60:495–7.View ArticleGoogle Scholar
- Gustafsson MGL. Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy. J. Microsc. 2000;198:82–7.View ArticlePubMedGoogle Scholar
- Gustafsson MGL. Nonlinear structured-illumination microscopy: Wide-field fluorescence imaging with theoretically unlimited resolution. Proc. Natl. Acad. Sci. USA. 2005;102:13081–6.View ArticlePubMedPubMed CentralGoogle Scholar
- Betzig E, Patterson GH, Sougrat R, Lindwasser OW, Olenych S, Bonifacino JS, Davidson MW, Lippincott-Schwartz J, Hess HF. Imaging Intracellular Fluorescent Proteins at Nanometer Resolution. Science. 2006;313:1642–5.View ArticlePubMedGoogle Scholar
- Hess ST, Girirajan TPK, Mason MD. Ultra-High Resolution Imaging by Fluorescence Photoactivation Localization Microscopy. Biophys. J. 2006;91:4258–72.View ArticlePubMedPubMed CentralGoogle Scholar
- Rust MJ, Bates M, Zhuang X. Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM). Nat. Methods. 2006;3:793–6.View ArticlePubMedPubMed CentralGoogle Scholar
- Sharonov A, Hochstrasser RM. Wide-field subdiffraction imaging by accumulated binding of diffusing probes. Proc. Natl. Acad. Sci. USA. 2006;103:18911–6.View ArticlePubMedPubMed CentralGoogle Scholar
- Jungmann R, Steinhauer C, Scheible M, Kuzyk A, Tinnefeld P, Simmel FC. Single-Molecule Kinetics and Super-Resolution Microscopy by Fluorescence Imaging of Transient Binding on DNA Origami. Nano Lett. 2010;10:4756–61.View ArticlePubMedGoogle Scholar
- Jungmann R, Avendano MS, Woehrstein JB, Dai M, Shih WM, Yin P. Multiplexed 3D cellular super-resolution imaging with DNA-PAINT and Exchange-PAINT. Nat. Methods. 2014;11:313–8.View ArticlePubMedPubMed CentralGoogle Scholar
- Iinuma R, Ke Y, Jungmann R, Schlichthaerle T, Woehrstein JB, Yin P. Polyhedra Self-Assembled from DNA Tripods and Characterized with 3D DNA-PAINT. Science. 2014;344:65–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Raab M, Schmied JJ, Jusuk I, Forthmann C, Tinnefeld P. Fluorescence Microscopy with 6 nm Resolution on DNA Origami. ChemPhysChem. 2014;15:2431–5.View ArticlePubMedGoogle Scholar
- Jungmann R, Avendano MS, Dai M, Woehrstein JB, Agasti SS, Feiger Z, Rodal A, Yin P. Quantitative Super-Resolution Imaging with qPAINT using Transient Binding Analysis. Nat. Methods. 2016;13:439–42.View ArticlePubMedPubMed CentralGoogle Scholar
- Dai M, Jungmann R, Yin P. Optical visualisation of individual biomolecules in densely packed clusters. Nat. Nanotechnol. 2016;11:798–807.View ArticlePubMedPubMed CentralGoogle Scholar
- Nienhaus K, Nienhaus GU. Where Do We Stand with Super-Resolution Optical Microscopy? J. Mol. Biol. 2016;428:308–22.View ArticlePubMedGoogle Scholar
- Roy R, Hohng S, Ha T. A practical guide to single-molecule FRET. Nat. Methods. 2008;5:507–16.View ArticlePubMedPubMed CentralGoogle Scholar
- Tokunaga M, Imamoto N, Sakata-Sogawa K. Highly inclined thin illumination enables clear single-molecule imaging in cells. Nat. Methods. 2008;5:159–61.View ArticlePubMedGoogle Scholar
- Jones SA, Shim SH, He J, Zhuang X. Fast, three-dimensional super-resolution imaging of live cells. Nat. Methods. 2011;8:499–508.View ArticlePubMedPubMed CentralGoogle Scholar
- Shroff H, Galbraith CG, Galbraith JA, Betzig E. Live-cell photoactivated localization microscopy of nanoscale adhesion dynamics. Nat. Methods. 2008;5:417–23.View ArticlePubMedPubMed CentralGoogle Scholar
- Cisse I, Kim H, Ha T. A rule of seven in Watson-Crick base-pairing of mismatched sequences. Nat. Struct. Mol. Biol. 2012;19:623–7.View ArticlePubMedPubMed CentralGoogle Scholar
- Holden SJ, Uphoff S, Kapanidis AN. DAOSTORM: an algorithm for high- density super-resolution microscopy. Nat. Methods. 2011;8:279–80.View ArticlePubMedGoogle Scholar
- Huang F, Schwartz SL, Byars JM, Lidke KA. Simultaneous multiple-emitter fitting for single molecule super-resolution imaging. Biomed. Opt. Express. 2011;2:1377–93.View ArticlePubMedPubMed CentralGoogle Scholar
- Babcock H, Sigal YM, Zhuang X. A high-density 3D localization algorithm for stochastic optical reconstruction microscopy. Opt. Nanoscopy. 2012;1:6.View ArticleGoogle Scholar
- Lee J, Miyanaga Y, Ueda M, Hohng S. Video-rate confocal microscopy for single-molecule imaging in live cells and superresolution fluorescence imaging. Biophys J. 2012;103:1691–7.View ArticlePubMedPubMed CentralGoogle Scholar
- Auer A, Strauss MT, Schlichthaerle T, Jungmann R. Fast, Background-Free DNA-PAINT Imaging Using FRET-Based Probes. Nano Lett. 2017;17:6428–34.View ArticlePubMedGoogle Scholar
- Xu K, Babcock HP, Zhuang X. Dual-objective STORM reveals three-dimensional filament organization in the actin cytoskeleton. Nat. Methods. 2012;9:185–8.View ArticlePubMedPubMed CentralGoogle Scholar
- Whelan DR, Bell TDM. Image artifacts in Single Molecule Localization Microscopy: why optimization of sample preparation protocols matters. Sci. Rep. 2015;5:7924.View ArticlePubMedPubMed CentralGoogle Scholar
- Huang B, Wang WQ, Bates M, Zhuang X. Three-Dimensional Super-Resolution Imaging by Stochastic Optical Reconstruction Microscopy. Science. 2008;319:810–3.View ArticlePubMedPubMed CentralGoogle Scholar