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. 2021 Jan;16(1):532-560.
doi: 10.1038/s41596-020-00440-x. Epub 2020 Dec 14.

High-speed super-resolution imaging of rotationally symmetric structures using SPEED microscopy and 2D-to-3D transformation

Yichen Li #  1 , Mark Tingey #  1 , Andrew Ruba  2 , Weidong Yang  3
Affiliations

High-speed super-resolution imaging of rotationally symmetric structures using SPEED microscopy and 2D-to-3D transformation

Yichen Li et al. Nat Protoc. 2021 Jan.

Abstract

Various super-resolution imaging techniques have been developed to break the diffraction-limited resolution of light microscopy. However, it still remains challenging to obtain three-dimensional (3D) super-resolution information of structures and dynamic processes in live cells at high speed. We recently developed high-speed single-point edge-excitation sub-diffraction (SPEED) microscopy and its two-dimensional (2D)-to-3D transformation algorithm to provide an effective approach to achieving 3D sub-diffraction-limit information in subcellular structures and organelles that have rotational symmetry. In contrast to most other 3D super-resolution microscopy or 3D particle-tracking microscopy approaches, SPEED microscopy does not depend on complex optical components and can be implemented onto a standard inverted epifluorescence microscope. SPEED microscopy is specifically designed to obtain 2D spatial locations of individual immobile or moving fluorescent molecules inside sub-micrometer biological channels or cavities at high spatiotemporal resolution. After data collection, post-localization 2D-to-3D transformation is applied to obtain 3D super-resolution structural and dynamic information. The complete protocol, including cell culture and sample preparation (6-7 d), SPEED imaging (4-5 h), data analysis and validation through simulation (5-13 h), takes ~9 d to complete.

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Conflict of interest statement

Competing interests

The authors declare no competing interests.

Figures

Fig. 1 |
Fig. 1 |. A schematic of excitation optical paths for both vertical and inclined illumination.
a, Schematic of the microscope setup for both the inclined and the vertical illumination in SPEED microscopy. A 488-nm (blue) and a 568-nm (green) laser are directed into the objective in vertical illumination or offset so that the lasers pass through the focal plane at an angle of θ3. The inset depicts a diagram of the edge excitation optics. The refractive angle (θi) at the interface of two different mediums with different refractive indexes (ni). The θ3 depends on the focal length of the objective (a), the refractive indexes of the different mediums in the optical path and the distance (d) between the center and edge excitation beams. The relationship between θ3 and d follows the equation: d=a*tan[sin−1(ncellnoilsinθ3)], where a = 300 μm, ncell = 1.33 and noil = 1.516. For example, to obtain θ3 = 45°, d needs to be 237 μm. b, An illustration of a molecule traveling in three dimensions as it passes through an NPC. A 2D projection of the same pathway is depicted in the lower panel. c, An illustration of the effect of the optical chopper on laser intensity. The chopper is calibrated to be open for 1/10 of frames captured.
Fig. 2 |
Fig. 2 |. 3D information derived from 2D single-molecule data using a 2D-to-3D transformation.
a, Simulated single-molecule data in the x, y and z dimensions in a rotationally symmetric cylinder with a radius of 25 nm. Below the cylinder is the 2D projection onto the x,y plane. A projection of an axial slice is shown in the R,θ dimensions. b, Single-molecule data from the y,z plane are projected onto an area matrix. A histogram is generated from the y,z plane with a bin size of 10 nm. c, The projection of single-molecule data onto the x,y plane as well as a histogram of the x,y plane with a 10-nm bin value. d, A representative radial density map of the 2D projections with a corresponding histogram with a 10-nm bin size. The equation for 2D-to-3D transformation is also shown here. Given the high number of randomly distributed molecules in the rotationally symmetric cylinder, the spatial density of locations (ρi) in each sub-region (s(i,j)) between two neighboring rings will be rotationally symmetrical and uniform. These locations can be further projected into one dimension along the y dimension. The locations along the y dimension can be clustered in a histogram with j columns. The total number of locations in each column (A(i,j)) is equal to 2*∑i=jnρi*s(i,j).
Fig. 3 |
Fig. 3 |. Representative data from SPEED microscopy experiments.
a,b, 2D single-molecular movies tracking molecules of interest around an NPC. A series of 2D locations of mRNA-mCherry (red spots) were captured by SPEED microscopy as they transported through the NPC (green spot). Numbers denote time in milliseconds. The scale bar represents 1 μm. a and b are representative of successful nuclear transport and abortive nuclear transport, respectively. The fluorescent spots of single mRNA and NPC in a series of images were fitted via a 2D Gaussian function, yielding the 2D spatial trajectory of mRNA (c,d). A 2D spatial trajectory of mRNA (black circle) transporting through the NPC (red circle) (c,d). c and d show representative trajectories for successful nuclear transport and abortive nuclear transport of mRNA, respectively. e, Superimposed single-molecule trajectories of successful mRNA export events. The central region of the NPC (221220 to 20 nm) is highlighted in yellow. C, cytoplasm; N, nucleoplasm. f, Superimposed single-molecule trajectories of abortive mRNA export events. The central region of the NPC (−20 to 20 nm) is highlighted in yellow. C, cytoplasm; N, nucleoplasm. g, Histogram depicting the export time distribution of successful mRNA export events. This histogram was fit with a mono-exponential decay function (red line), yielding the indicated median export time. Error bars represent SEM; n = 256 events. h, Histogram depicting the export time distribution of abortive messenger ribonucleoprotein (mRNP) export events. Error bars indicate SEM; n = 431 events. i, Representative mean-squared displacement versus time plots for two cytoplasmic (Cyto) and two nuclear (Nuc) mRNAs. The plots show cytoplasmic mRNA undergoing Brownian diffusion (open square, D = 0.108 μm2/s) and biased diffusion (filled square, D = 0.103 μm2/s), as well as nuclear mRNA that diffuse in a corralled fashion (filled circle, D = 0.025 μm2/s) or remain more or less stationary (open circle, D = 0.00043 μm2/s). j, Distribution of cytoplasmic (Cyto) and nuclear (Nuc) mRNP diffusion coefficients in HeLa cells. Diffusion coefficients were calculated from the mean squared displacement versus time plots of individual particles that were visible for at least nine consecutive frames. Cytoplasmic mRNPs distributed predominantly into two Gaussian distributions with average diffusion coefficients of ~0.49 μm2/s and ~0.05 μm2/s for the major (81%) and minor (19%) population, respectively. Distribution of nuclear mRNP diffusion coefficients was best fit with two Gaussian populations with average diffusion coefficients of 0.067 μm2/s (47%) and 0.009 μm2/s (53%), respectively. k, Experimentally determined 2D spatial locations of mRNPs in the NPC. A schematic of the NPC (light blue) is superimposed, and the central region of the NPC (−20 to 20 nm) is highlighted in yellow. C, cytoplasmic side of the NPC; N, nucleoplasmic side of the NPC. l, 3D spatial density map of mRNPs (red; deeper shade indicates higher density), generated using a 2D-to-3D transformation algorithm, is shown in both an axial and radial view superimposed on the NPC architecture (gray). Five regions with distinct spatial location distributions for mRNPs are marked with relative distances (in nm) from the centroid of the NPC. C, cytoplasmic side of the NPC; N, nucleoplasmic side of the NPC. Data were originally published in ref. .
Fig. 4 |
Fig. 4 |. Representatives of 3D probability density maps in three rotationally symmetric systems.
a–c, Schematic of the NPC, primary cilium and the GNC tube. d–i, 2D spatial location distribution of Alexa Fluor (small molecule), importin-β1 (nuclear transport receptor), NET59 (nuclear membrane protein) and yNup116 (FG-Nups) around NPCs. h, 2D spatial location distribution of IFT20 in primary cilia. i, 2D spatial location distribution of Alexa Fluor in a GNC tube. j–l, The 3D probability density maps for the nuclear transport route of Alexa Fluor, importin-β1 and NET59. The transport route of Alexa Fluor represents the passive diffusion pattern in NPC, whereas the transport route of importin-β1 represents the facilitated diffusion pattern in NPC. The 3D density map of NET59 represents the nuclear transport route of nuclear membrane protein. The scale bar represents 50 nm. m, The 3D probability density maps of yNup116 in NPC. This depicts the configuration of the NPC’s selectivity barrier formed by FG-Nups. The scale bar represents 50 nm. n, The 3D probability density maps for the transport route of IFT20 in primary cilia. This depicts the IFT pathway in primary cilia. The scale bar represents 100 nm. o, The 3D probability density maps for the transport route of Alexa Fluor in GNC tubes. Depicted here is a random diffusion pattern within GNC tubes. The scale bar represents 50 nm. N, nucleoplasm; C, cytoplasm. Data in a, b and c were originally published in refs. ,. Data in d, e, j, k and m were originally published in ref. . Data in f and l were originally published in ref. . Data in g were originally published in ref. . Data in h, i, n, and o were originally published in ref. .
Fig. 5 |
Fig. 5 |. Schematic workflow for SPEED microscopy.
The schematic shows the five major experimental stages, including specific steps and customizations for different experiments.
Fig. 6 |
Fig. 6 |. Optical paths in the SPEED microscope and other microscopes.
a, Schematic representation of different optical paths in different microscopes. Epi, epifluorescence microscopy. b, An example showing the different number of NPCs on the NE that could be excited by the distinct illumination patterns of these microscopes. c, A vertical illumination volume of SPEED microscopy is used to image a primary cilium. d, SPEED microscopy is used to image a GNC with the vertical illumination pattern.
Fig. 7 |
Fig. 7 |. Validation of the reproducibility of SPEED microscopy and its 2D-to-3D histogram.
a, Table showing the effect of poor single-molecule localization precision and a low numbers of single-molecule localizations. b, Flowchart outlining the simulation process for determining the reproducibility rate. c, Graphical user interface for the reproducibility rate simulation. Results are displayed in the message section after the simulation has been run.
Fig. 8 |
Fig. 8 |. A schematic showing data normalization and 2D-to-3D transformation.
a, Density distribution histograms of the radial dimension within different axial regions. b, Discrete axial region density distribution histograms of the radial dimension normalized to the maximum value density observed within the axial dimension. c, Concentric circles are populated with the probability density distributions to form a radial view of probability density maps. d, Exemplars of preliminary probability density maps. e, Application of a Gaussian blur finalizes the probability density maps of axial regions. f, A section of the composite 3D probability density map. An animation of the composite probability density map is available in the Supplementary Materials.
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