Abstract
Three-dimensional (3D) nanoscale imaging reveals the detailed morphology of subcellular structures; however, conventional single-molecule localization microscopy is constrained by limited axial resolution. Here we introduce ROSE-3D, an interferometric localization approach that enables isotropic 3D super-resolution imaging with uniform performance across the entire depth of field. Compared with conventional astigmatism-based methods, ROSE-3D improves lateral localization precision by 2–6 times and axial precision by 3.5–8 times over a depth of field of approximately 1.2 μm. Leveraging its multicolor and whole-cell imaging capabilities, ROSE-3D resolves, in situ, the nanoscale organization of nuclear lamins and the assemblies of mitochondrial fission-related protein DRP1. These results establish ROSE-3D as a powerful tool for interrogating nanoscale cellular architecture.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$32.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to the full article PDF.
USD 39.95
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
A small raw dataset of microtubules in Fig. 2c is available in Supplementary Software. Another raw dataset is available via figshare at https://doi.org/10.6084/m9.figshare.30136318 (ref. 54). Owing to the extensive size of the whole raw data (~3 TB), other data used in this study are available from the corresponding authors upon reasonable request. Source data are provided with this paper.
Code availability
The demonstration of reconstruction code, as well as the script for the Cramér–Rao lower bound calculation in MATLAB, is provided in Supplementary Software, under the MIT License. The code is available via GitHub at https://github.com/JiweiLab/ROSE-3D. The LabVIEW program for the device control and the Python program for the drift correction during imaging are available from the corresponding authors upon reasonable request.
References
Kanchanawong, P. et al. Nanoscale architecture of integrin-based cell adhesions. Nature 468, 580–584 (2010).
Mulhall, E. M. et al. Direct observation of the conformational states of PIEZO1. Nature 620, 1117–1125 (2023).
Tábara, L.-C., Segawa, M. & Prudent, J. Molecular mechanisms of mitochondrial dynamics. Nat. Rev. Mol. Cell Biol. 26, 123–146 (2025).
Betzig, E. et al. Imaging intracellular fluorescent proteins at nanometer resolution. Science 313, 1642–1645 (2006).
Hess, S. T., Girirajan, T. P. & Mason, M. D. Ultra-high resolution imaging by fluorescence photoactivation localization microscopy. Biophys. J. 91, 4258–4272 (2006).
Rust, M. J., Bates, M. & Zhuang, X. Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM). Nat. Methods 3, 793–796 (2006).
Li, Y. et al. Real-time 3D single-molecule localization using experimental point spread functions. Nat. Methods 15, 367–369 (2018).
Xu, F. et al. Three-dimensional nanoscopy of whole cells and tissues with in situ point spread function retrieval. Nat. Methods 17, 531–540 (2020).
Liu, S. et al. Universal inverse modeling of point spread functions for SMLM localization and microscope characterization. Nat. Methods 21, 1082–1093 (2024).
Bates, M. et al. Optimal precision and accuracy in 4Pi-STORM using dynamic spline PSF models. Nat. Methods 19, 603–612 (2022).
Huang, B. et al. Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy. Science 319, 810–813 (2008).
Juette, M. F. et al. Three-dimensional sub-100 nm resolution fluorescence microscopy of thick samples. Nat. Methods 5, 527–529 (2008).
Pavani, S. R. P. et al. Three-dimensional, single-molecule fluorescence imaging beyond the diffraction limit by using a double-helix point spread function. Proc. Natl Acad. Sci. USA 106, 2995–2999 (2009).
Shechtman, Y. et al. Precise three-dimensional scan-free multiple-particle tracking over large axial ranges with tetrapod point spread functions. Nano Lett. 15, 4194–4199 (2015).
Gustavsson, A.-K. et al. 3D single-molecule super-resolution microscopy with a tilted light sheet. Nat. Commun. 9, 123 (2018).
Aristov, A. et al. ZOLA-3D allows flexible 3D localization microscopy over an adjustable axial range. Nat. Commun. 9, 2409 (2018).
Fu, S. et al. Deformable mirror based optimal PSF engineering for 3D super-resolution imaging. Opt. Lett. 47, 3031–3034 (2022).
Bourg, N. et al. Direct optical nanoscopy with axially localized detection. Nat. Photonics 9, 587–593 (2015).
Szalai, A. M. et al. Three-dimensional total-internal reflection fluorescence nanoscopy with nanometric axial resolution by photometric localization of single molecules. Nat. Commun. 12, 517 (2021).
Chizhik, A. I. et al. Metal-induced energy transfer for live cell nanoscopy. Nat. Photonics 8, 124–127 (2014).
Kamińska, I. et al. Graphene energy transfer for single-molecule biophysics, biosensing, and super-resolution microscopy. Adv. Mater. 33, 2101099 (2021).
Fan, D. et al. Three-dimensional localization microscopy with increased axial precision through TIRF angle modulation. Opt. Commun. 542, 129548 (2023).
Gu, L. et al. Molecular-scale axial localization by repetitive optical selective exposure. Nat. Methods 18, 369–373 (2021).
Aquino, D. et al. Two-color nanoscopy of three-dimensional volumes by 4Pi detection of stochastically switched fluorophores. Nat. Methods 8, 353–359 (2011).
Huang, F. et al. Ultra-high resolution 3D imaging of whole cells. Cell 166, 1028–1040 (2016).
Zhang, Y. et al. Nanoscale subcellular architecture revealed by multicolor three-dimensional salvaged fluorescence imaging. Nat. Methods 17, 225–231 (2020).
Gu, L. et al. Molecular resolution imaging by repetitive optical selective exposure. Nat. Methods 16, 1114–1118 (2019).
Reymond, L. et al. SIMPLE: structured illumination based point localization estimator with enhanced precision. Opt. Express 27, 24578–24590 (2019).
Cnossen, J. et al. Localization microscopy at doubled precision with patterned illumination. Nat. Methods 17, 59–63 (2020).
Jouchet, P. et al. Nanometric axial localization of single fluorescent molecules with modulated excitation. Nat. Photonics 15, 297–304 (2021).
Thompson, R. E., Larson, D. R. & Webb, W. W. Precise nanometer localization analysis for individual fluorescent probes. Biophys. J. 82, 2775–2783 (2002).
Ober, R. J., Ram, S. & Ward, E. S. Localization accuracy in single-molecule microscopy. Biophys. J. 86, 1185–1200 (2004).
Wu, W. et al. Tetra-color superresolution microscopy based on excitation spectral demixing. Light. Sci. Appl. 12, 9 (2023).
Steen, P. R. et al. The DNA-PAINT palette: a comprehensive performance analysis of fluorescent dyes. Nat. Methods 21, 1755–1762 (2024).
Lampe, A. et al. Multi-colour direct STORM with red emitting carbocyanines. Biol. Cell 104, 229–237 (2012).
Lampe, A., Tadeus, G. & Schmoranzer, J. Spectral demixing avoids registration errors and reduces noise in multicolor localization-based super-resolution microscopy. Methods Appl. Fluoresc. 3, 034006 (2015).
Goldberg, M. W. et al. Filaments made from A- and B-type lamins differ in structure and organization. J. Cell Sci. 121, 215–225 (2008).
Pujadas Liwag, E. M. et al. Depletion of lamins B1 and B2 promotes chromatin mobility and induces differential gene expression by a mesoscale-motion-dependent mechanism. Genome Biol. 25, 77 (2024).
Nmezi, B. et al. Concentric organization of A- and B-type lamins predicts their distinct roles in the spatial organization and stability of the nuclear lamina. Proc. Natl Acad. Sci. USA 116, 4307–4315 (2019).
Chang, L. et al. Nuclear peripheral chromatin–lamin B1 interaction is required for global integrity of chromatin architecture and dynamics in human cells. Protein Cell 13, 258–280 (2022).
Tilokani, L. et al. Mitochondrial dynamics: overview of molecular mechanisms. Essays Biochem. 62, 341–360 (2018).
Giacomello, M. et al. The cell biology of mitochondrial membrane dynamics. Nat. Rev. Mol. Cell Biol. 21, 204–224 (2020).
Smirnova, E. et al. Dynamin-related protein Drp1 is required for mitochondrial division in mammalian cells. Mol. Biol. Cell 12, 2245–2256 (2001).
Mears, J. A. et al. Conformational changes in Dnm1 support a contractile mechanism for mitochondrial fission. Nat. Struct. Mol. Biol. 18, 20–26 (2011).
Kalia, R. et al. Structural basis of mitochondrial receptor binding and constriction by DRP1. Nature 558, 401–405 (2018).
Losón, O. C. et al. Fis1, Mff, MiD49, and MiD51 mediate Drp1 recruitment in mitochondrial fission. Mol. Biol. Cell 24, 659–667 (2013).
Balzarotti, F. et al. Nanometer resolution imaging and tracking of fluorescent molecules with minimal photon fluxes. Science 355, 606–612 (2017).
Reinhardt, S. C. et al. Ångström-resolution fluorescence microscopy. Nature 617, 711–716 (2023).
Ning, K. et al. Deep self-learning enables fast, high-fidelity isotropic resolution restoration for volumetric fluorescence microscopy. Light Sci. Appl. 12, 204 (2023).
Przybylski, A. et al. Gpufit: an open-source toolkit for GPU-accelerated curve fitting. Sci. Rep. 7, 15722 (2017).
Wang, Y. et al. Localization events-based sample drift correction for localization microscopy with redundant cross-correlation algorithm. Opt. Express 22, 15982–15991 (2014).
Dai, M., Jungmann, R. & Yin, P. Optical imaging of individual biomolecules in densely packed clusters. Nat. Nanotechnol. 11, 798–807 (2016).
Ma, H. et al. Toward drift-free high-throughput nanoscopy through adaptive intersection maximization. Sci. Adv. 10, eadm7765 (2024).
Luo, S. et al. Example dataset for ‘molecular-scale isotropic 3D super-resolution microscopy via interference localization’. figshare https://doi.org/10.6084/m9.figshare.30136318 (2025).
Acknowledgements
This work was supported by the National Natural Science Foundation of China (grant nos. 32027901 to T.X.; T2225020 and 92254306 to W.J.; 32322050 and 32170704 to L.G.; and 32370745 to W.L.), the National Key Research and Development Program of China (grant nos. 2022YFC3400600 and 2021YFA1301500 to W.J. and 2024YFA1307403 to W.L.), the Beijing Natural Science Foundation (grant no. Z240009 to W.J.), the National Science and Technology Innovation 2030 Major Program (grant no. 2022ZD0211900 to L.G.), the Chinese Academy of Sciences Project for Young Scientists in Basic Research (grant no. YSBR-104 to W.J.) and the Postdoctoral Fellowship Program of CPSF (grant no. GZC20241859 to S.L.). We also thank Y. Feng from the Center for Biological Imaging, Institute of Biophysics, Chinese Academy of Sciences, for 3D image analysis.
Author information
Authors and Affiliations
Contributions
W.J., T.X. and L.G. designed the experiments. S.L. and L.G. developed the ROSE-3D system. S.L. performed the data acquisition and analysis. X.Z., Y.L. and C.F. conducted sample preparation. R.L., R.G. and N.M. helped in the sample preparation. L.G., S.L., W.L. and Z.Y. interpreted the results. L.G. and S.L. wrote the paper, which was modified by all other authors.
Corresponding authors
Ethics declarations
Competing interests
A CN patent (ZL 201910393370.9) has been issued describing the ROSE detection system used in this work; L.G., W.J. and T.X. are the co-inventors. The other authors declare no competing interests.
Peer review
Peer review information
Nature Methods thanks Alan Szalai and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. Primary Handling Editors: Rita Strack and Nina Vogt, in collaboration with the Nature Methods team.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Detailed optical design of ROSE-3D.
Detailed information of the components used in the optical setup is provided in Supplementary Table 1.
Extended Data Fig. 2 Flowchart of the image reconstruction pipeline.
Raw images are first segmented and registered to generate aligned subimage stacks. Single molecules are then identified within these subimages, followed by Gaussian fitting to estimate their rough 3D positions, phases, and photon numbers. The three phases are subsequently aligned with corresponding rough positions to refine the localization. The pipeline further includes drift correction and additional single-molecule identification steps. Finally, the refined localizations and identification results are integrated to reconstruct the final super-resolution image.
Extended Data Fig. 3 Comparison of single-molecule localization precision at different depths.
Comparison between ROSE-3D and conventional method, using 3D scatter plots and histograms of the repeated single-molecule localizations from Fig. 1e, with defocus values of -400 nm (a), 0 nm (b) and +400 nm (c), respectively. The molecules which were present for more than 5 consecutive frames with photon number larger than 1000 were selected and aligned for the 3D scatter plot and histogram.
Extended Data Fig. 4 Resolution comparison of ROSE-3D and ROSE-Z.
a, Color-coded image showing the region selected for comparison. b-d, Zoomed-in images of the regions indicated in a, with ROSE-3D and ROSE-Z, respectively. The ROSE-Z data were simulated by combining the axial interferometric data and lateral centroid fitting data of ROSE-3D. e-h, Sections of the microtubule filaments indicated in b-d. Scale bars: 2 μm in a, 1 μm in b, and 100 nm in e. Three experiments were repeated independently with similar results.
Extended Data Fig. 5 Imaging and morphological analysis of the DRP1 complexes.
a, Two-color image of DRP1 and TOM-20 in COS-7 cells. b, Zoomed-in view of the dashed box indicated in a. c-d, Cross-sections indicated in b, showing the DRP1 complexes with large radii (c) and small radii (d). e, 3D view of one DRP1 complex at the fission site indicated in b. f, Intensity profiles indicated in c, showing that DRP1 is located 10-20 nm outside the outer membrane of the mitochondria. g, Volume rendering of four typical shapes of DRP1 complexes. In total, n = 75 DRP1 complexes were analyzed and classified into four categories: helix type, segmented torus type, torus type and arc type. h, Morphological illustration of the corresponding DRP1 complexes in g and their geometry measurement results. Scale bars: 5 μm in a, 1 μm in b, 100 nm in c. Three experiments were repeated independently with similar results.
Extended Data Fig. 6 Performance of ROSE-3D with high photon budget.
a, ROSE-3D imaging of DNA origami of 20 nm and 10 nm 3×4 grids structures, the mean photon budget was 23287. b, Zoomed in of structures indicated in a. c-e, Intensity profiles and multiple Gaussian fitting results of the DNA origami structures indicated in b, respectively. The numbers on each peak indicate the standard deviation of the peak. f-h, Analysis of the 3D localization precision at different Z positions. DNA-PAINT imaging was performed and repeated localization analysis was used to evaluate the 3D localization precision. Molecules which were present for more than 8 consecutive frames and photon budget larger than 20000 were used for analysis. Scale bars: 100 nm in a, 20 nm in b. Three experiments were repeated independently with similar results.
Extended Data Fig. 7 Phase drift measurement of ROSE-3D.
a-c, Interference patterns of a thin layer of fluorescent dye were recorded continuously for over one hour at a frame rate of 20 Hz to measure phase drift for X direction. The phase was determined by calculating the argument of the principal frequency component of the Fast Fourier Transform (FFT) result. The raw phase drift (blue) and smoothed phase data (red) vs time was shown (a), with the smoothed data calculated by averaging of 100 frames. The phase fluctuation calculated by subtracting smoothed phase from raw phase (b). The phase fluctuation was converted into distance based on 260 nm fringe width. The fluctuation histogram showed a std of 0.007 rad, corresponding to 0.28 nm (c). d-f, Phase drift measurement for Y direction. g-i, Phase drift measurement for Z direction. Three experiments were repeated independently with similar results.
Supplementary information
Supplementary Information
Supplementary Figs. 1–10, Tables 1 and 2 and Note 1.
Supplementary Software 1
Demonstration code of ROSE-3D. This supplementary software package includes demonstration and reconstruction code for ROSE-3D, along with the corresponding image dataset. Additionally, it contains a script for calculating the Cramér–Rao lower bound.
Supplementary Video 1
Video rendering of the data shown in Fig. 5e. Image of Drp1 complexes in a COS-7 cell. Representative 28/32 images of one experiment are shown.
Supplementary Video 2
Video rendering of the data shown in Fig. 5f–h. Image of one Drp1 helical structure details.
Supplementary Video 1
Video rendering of the data shown in Fig. 5e. Image of Drp1 complexes in a COS-7 cell. Representative images of one experiment are shown.
Supplementary Video 2
Video rendering of the data shown in Fig. 5f–h. Image of one Drp1 helical structure details.
Source data
Source Data Fig. 1
The localization precision data of ROSE-3D and the conventional method.
Source Data Fig. 2
The profile data of Fig. 2g,h.
Source Data Fig. 3
The profile data of Fig. 3d–f.
Source Data Fig. 4
The profile data of Fig. 4c–f, as well as the data to build the histogram in Fig. 4g,h.
Source Data Fig. 5
The profile data of Fig. 5d.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Luo, S., Zhao, X., Li, Y. et al. Molecular-scale isotropic 3D super-resolution microscopy via interference localization. Nat Methods 23, 183–192 (2026). https://doi.org/10.1038/s41592-025-02911-z
Received:
Accepted:
Published:
Version of record:
Issue date:
DOI: https://doi.org/10.1038/s41592-025-02911-z
