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Super-resolved 3D tracking of cargo transport through nuclear pore complexes

Nature Cell Biology volume 24, pages 112–122 (2022)Cite this article

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An Author Correction to this article was published on 01 February 2022

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Abstract

Nuclear pore complexes (NPCs) embedded within the nuclear envelope mediate rapid, selective and bidirectional traffic between the cytoplasm and the nucleoplasm. Deciphering the mechanism and dynamics of this process is challenged by the need for high spatial and temporal resolution. We report here a multicolour imaging approach that enables direct three-dimensional visualization of cargo transport trajectories relative to a super-resolved octagonal double-ring structure of the NPC scaffold. The success of this approach is enabled by the high positional stability of NPCs within permeabilized cells, as verified by a combined experimental and simulation analysis. Hourglass-shaped translocation conduits for two cargo complexes representing different nuclear transport receptor pathways indicate rapid migration through the permeability barrier on or near the NPC scaffold. Binding sites for cargo complexes extend more than 100 nm from the pore openings, which is consistent with a wide distribution of the phenylalanine-glycine polypeptides that bind nuclear transport receptors.

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Fig. 1: 3D super-resolution microscope and experimental workflow.
Fig. 2: Localization of the NPC scaffold.
Fig. 3: Effect of tilt and jiggle on resolving the NPC scaffold.
Fig. 4: 3D tracking of M9-βGal cargo complexes interacting with and transiting through NPCs.
Fig. 5: 3D tracking of NLS-2×BFP cargo complexes interacting with and transiting through NPCs.
Fig. 6: Overlap of the transportin and Imp α/Imp β import pathways.

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Data availability

Raw image and movie data are available from the corresponding author upon reasonable request. Source data are provided with this paper. All other data supporting the findings of this study are available within the paper and its supplementary information files.

Code availability

The Matlab scripts used to analyse the data are summarized in Supplementary Table 1 and are available at GitHub at https://github.com/npctat2021/npc3d2021.

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Acknowledgements

We thank M. Rout, Y. M. Chook, M. S. Moore and D. Görlich for the LaG-9 anti-GFP nanobody, transportin, Imp α and Imp β expression plasmids, respectively, and J. Chao for assisting with the double-circle fit Matlab script. This research was supported by the National Institutes of Health (GM126190 to S.M.M.).

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Author notes

  1. These authors contributed equally: Rajdeep Chowdhury, Abhishek Sau.

Authors and Affiliations

  1. Department of Molecular and Cellular Medicine, Texas A&M University, College of Medicine, The Texas A&M Health Science Center, College Station, TX, USA

    Rajdeep Chowdhury, Abhishek Sau & Siegfried M. Musser

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Contributions

All authors contributed extensively to the work presented in this paper. S.M.M. conceived the approach. R.C. assembled and calibrated the AO 3D imaging system and wrote code. R.C. and A.S. installed the z-lock system, purified proteins, collected and analysed data and wrote the manuscript. S.M.M. developed the simulations, provided advice, analysed data and edited the manuscript.

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Correspondence to Siegfried M. Musser.

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Nature Cell Biology thanks Ulrich Kubitscheck, Michael Rout and the other anonymous reviewer for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Nanobody Specificity and Fluorescence Background.

a, Specificity of the LaG-9 anti-GFP nanobody. Alexa568-labeled nanobody (100 nM) was added to permeabilized cells, incubated for 3 min and washed twice with IB + PVP. Cells were imaged at the nuclear equator. The top row shows the strong mEGFP fluorescence (λex = 488 nm) obtained from the mEGFP-tagged NPCs of U-2 OS NUP96-mEGFP cells. The Alexa568 fluorescence (λex = 561 nm) from the tagged nanobody matches the mEGFP fluorescence. In the bottom row, the wild type U-2 OS cells exhibited no fluorescence in the mEGFP channel and no nanobody binding. The range of the fluorescence images in the bottom row is 10 times smaller than in the top row, emphasizing the very low signal. These data indicate the high specificity of the nanobody for the mEGFP domain. Similar results were observed for N = 20 cells over 4 independent experiments. b, Fluorescence background and photobleaching of mEGFP. For all images, permeabilized U-2 OS NUP96-mEGFP cells labeled with HMSiR-labeled nanobodies were excited with λex = 532 nm and emission was collected by a dual bandpass (545-623 nm, 656-763 nm). The mEGFP fluorescence (left) was photobleached after ~2 s of illumination, allowing diffusing M9-βGal(Atto542) cargo complexes to be readily visualized (top right). The HMSiR dye was not detectable (bottom right). Similar results were observed for N = 20 cells over 4 independent experiments.

Extended Data Fig. 2 Workflow for NPC Cluster Selection.

a, Initial image obtained from ThunderSTORM. b, Image after photon filtering (≥ 3000 photons) and z filtering (0 ± 300 nm) (corresponds to Fig. 2e). c, Clusters remaining after applying a rough diameter threshold (59-153 nm) and with ≥ 10 localizations/cluster. d, Clusters remaining after the double-circle fit and subsequent curating (fit diameter = 80-135 nm; distance between the rings = 40-65 nm; z-centroid = 0 ± 200 nm). These remaining clusters are considered well-localized NPCs (image corresponds to Fig. 2h), and were used to construct the composite images in Fig. 2i–l. Dye localizations in a-d are color-coded based on z-height. e, Distribution of the number of localizations per cluster for the experiment in Fig. 2. The number of localizations per cluster followed an approximately exponential distribution (decay constant = 2.9) with an average of 13.2 following the filtering described in (a-c) and with a z-centroid = 0 ± 200 nm (N = 2362 total localizations obtained from 142 clusters from 10 nuclei; each nucleus was an independent biological replicate). f, Photon frequency histograms. The HMSiR-labeled nanobody was bound to NPCs (Fig. 2) and the Atto542-labeled M9-βGal and Imp α were undergoing transport (Figs. 4 and 5). The log-normal fit parameters were used for the simulations in Supplementary Data 1 (software file 1) and Supplementary Data 2 (software file 2). Source numerical data are provided in source data.

Source data

Extended Data Fig. 3 Rotation of Individual NPC Clusters.

a, Estimating the rotational phase angle (φ). The angles of individual localizations relative to the double-circle centroid of well-localized NPC clusters (Extended Data Fig. 2d) were estimated and binned (5° bins, θ = 0-45°). Four examples are shown here for a range of localizations/cluster (the number of localizations/cluster, n, is given in each figure panel). Distributions were fit to y = 1/9 + (1/20.6)*cos[8(θ-φ)]. The 1/9 term reflects the 9 bins, and the cosine scaling factor is a reasonable average based on simulations. This amplitude scaling factor is insensitive to the goodness-of-fit due to orthogonality – the phase angle shifts the curve laterally, and identical phase angles are obtained by the fitting routine regardless of the scaling factor. The fixed scaling factor enables rapid convergence of the fit. The phase angles from these fits were used to rotate pore clusters before aligning them based on their centroids. b, Angular distribution of localizations in the initially aligned pore clusters (Fig. 2i). Inset: Fig. 2i, bar: 50 nm. c, Angular distribution of rotationally-corrected localizations (Fig. 2k). Inset: Fig. 2k, bar: 50 nm. Pore clusters were rotated based on the phase angle as determined in (a) before aligning. The distribution was fit to y = y0 + c1*sin(8(x-ϕ)), where y0, c1 and ϕ are fit parameters. The minima define the angles of the dashed spokes in Fig. 2m. Source numerical data are provided in source data.

Source data

Extended Data Fig. 4 Nuclear Accumulation of M9-βGal and Imp α in Permeabilized U-2 OS NUP96-mEGFP Cells.

a, Nuclear import of M9-βGal(Atto542). The M9-βGal cargo is an ~500 kDa tetramer with four M9 nuclear localization sequences (NLSs) that are recognized by the transportin NTR. Transport reactions were monitored using wide-field fluorescence (λex = 532 nm) in the presence or absence of transportin or RanGTP (RanGDP + GTP) as indicated. The ‘transport mix’ was flowed in at t = 0.5 min. Representative images from four time points are shown (N = 20 cells from 4 independent experiments). [M9-βGal] = 0.25 µM, [transportin] = 0.25 or 1.0 µM, [RanGDP] = 0.5 µM, [NTF2] = 1 µM, [GTP] = 1 mM. b, Kinetics of nuclear import of M9-βGal. Average nuclear fluorescence (±s.d.) was quantified over time for N = 15 (-transportin), 17 (-RanGTP), or 20 (high and low transportin) cells from 4 independent experiments). Background refers to an area far from the cells. c, Cargo-dependent nuclear uptake of Imp α. Robust accumulation of Imp α(Atto542) into the nucleus (λex = 532 nm) occurs in the presence of the NLS-2xBFP cargo (top row) but not in its absence (bottom row). The range of the fluorescence images in the bottom row is 5 times smaller than in the top row, emphasizing the very low nuclear accumulation (N = 18 cells over 4 independent experiments). [Imp α(Atto542)] = 0.5 µM, [Imp β] = 0.5 µM, [NLS-2xBFP] = 0.5 µM, [RanGDP] = 1.5 µM, [NTF2] = 1 µM and [GTP] = 1 mM. Source numerical data are provided in source data.

Source data

Extended Data Fig. 5 Localizations of M9-βGal and NLS-2xBFP Complexes.

a,b, Brief M9-βGal complex appearances. Shown are the localizations from Fig. 4a that remained visible for one (a) or two (b) 3 ms frames. The N values are the number of localizations from 142 NPCs from 10 nuclei; each nucleus was an independent biological replicate. c,d, Brief NLS-2xBFP complex appearances. Shown are the localizations from the experiment in Fig. 5 that remained visible for one (c) or two (d) 2 ms frames. The N values are the number of localizations from 115 NPCs from 10 nuclei; each nucleus was an independent biological replicate. Localizations shown in (a-d) appear randomly distributed, consistent with particles that are largely diffusing and not interacting with the NPC. e, Simulated distribution of particles penetrating a barrier. In this simulation [Supplementary Data 2 (software file 2)], particles appeared randomly within two compartments separated by a 50 nm thick barrier with a 100 nm diameter pore. This distribution models the M9-βGal complex localizations in Fig. 4a. The localizations appearing within the barrier result from the precision error, indicating that the localizations observed within the NE region in Fig. 4a are likely a consequence of localization error. f,g, Localizations along the transport axis. Distribution of z values for M9-βGal complexes (f; from Fig. 4e,f) and NLS-2xBFP complexes (g; from Fig. 5e,f) undergoing import or abortive import. Distributions are fit to a double Gaussian function yielding mean values (±s.d.) of −100 ± 48 nm and 68 ± 56 nm for M9-βGal complexes, and −104 ± 82 nm and 122 ± 47 nm for NLS-2xBFP complexes. Source numerical data are provided in source data.

Source data

Extended Data Fig. 6 Cargo Complex Diffusion Constants.

a, 3D step-size histogram for M9-βGal complexes. Step sizes of M9-βGal complexes were calculated from consecutive localizations in the trajectories of Fig. 4c (N = 824 total jump distances from 10 nuclei; each nucleus was an independent biological replicate). Data were fit using Eq. 4, yielding three distinct diffusion constants of 0.2 (18%), 0.8 (50%) and 2.6 (32%) µm2/s, or a weighted average diffusion constant of 1.3 µm2/s. b, 3D step-size histogram for NLS-2xBFP complexes. Step sizes of NLS-2xBFP complexes were calculated from consecutive localizations in the trajectories of Fig. 5c (N = 660 total jump distances from 10 nuclei; each nucleus was an independent biological replicate). Fitting the histogram yielded two distinct diffusion constants of 0.6 (25%) and 2.7 (75%) µm2/s, or a weighted average diffusion constant of 2.2 µm2/s. Due to the highly confined, irrregular volume sampled by the cargo complexes, these average diffusion constant estimates are considered both approximate and an underestimate. For comparison, the diffusion constant of the M9-βGal and NLS-2xBFP cargo complexes in aqueous buffer are approximated as ~34 and 55 µm2/s, respectively, using the Stokes-Einstein equation and a protein density of ~1.35 g/cm3 (ref. 83). Source numerical data are provided in source data.

Source data

Supplementary information

Reporting Summary

Supplementary Video 1

Blinking of the HMSiR dye on nanobody-decorated NPCs. The LaG-9 anti-GFP nanobody labelled with HMSiR was added to permeabilized U-2 OS-CRISPR-NUP96-mEGFP cells, incubated for 3 min and then washed twice. Cells were imaged (50 ms frame–1) at the nuclear equator using excitation at 488 nm (mEGFP fluorescence, green) and 647 nm (HMSiR fluorescence, red). The blinking of HMSiR molecules was observed mostly along the NE. Pixel size, 118 nm.

Supplementary Video 2

360° rotation of the NPC scaffold. 3D representation of the NPC scaffold from Fig. 2k,l showing the eightfold rotational symmetry for each of the two rings, constructed using the 3D Viewer plugin in Fiji80. The image of the NPC is tilted for visualization purposes. The difference in the rotation angles between successive frames is 2°.

Supplementary Video 3

Nuclear import of M9-βGal(Atto542). The M9-βGal(Atto542) cargo (red) was tracked in 3D as in Fig. 4 (3 ms frame–1, λex = 532 nm) with an astigmatic PSF. For reference, this video was overlaid onto a 2D AO-corrected wide-field image of the NE showing the location of NPCs tagged with NUP96-mEGFP as in Fig. 2d (λex = 488 nm). This raw image data illustrates the spot shape of the cargo fluorescence changing from elongated in y, to symmetric, to elongated in x as the particle migrates from negative topositive z. Pixel size, 118 nm.

Supplementary Video 4

3D super-resolved nuclear export of M9-βGal(Atto542). The position of a NPC scaffold was determined as in Fig. 2f,g from HMSiR localizations. An M9-βGal(Atto542) cargo undergoing nuclear export (approach of Fig. 4) was determined via successive localizations. On the left, the x and y coordinates are reflected by the two spatial dimensions, and the colour indicates the position along the z coordinate (transport axis). Inset: z colour scale. On the right, the same trajectory is presented in the x-z plane, the NPC is identified in red, and the cargo is in green. The abscissa is the x axis in both cases. Spot widths correspond to the average localization precision based on photon counts. Pixel size, 2.95 nm.

Supplementary Video 5

3D Super-resolved nuclear import of an NLS-2×BFP/Imp α(Atto542)/Imp β complex. The position of a NPC scaffold was determined as in Fig. 2f,g from HMSiR localizations. A NLS-2×BFP cargo complex undergoing nuclear import (approach of Fig. 5) was determined via successive localizations. On the left, the x and y coordinates are reflected by the two spatial dimensions, and the colour indicates the position along the z coordinate (transport axis). Inset: z colour scale. On the right, the same trajectory is presented in the x-z plane, the NPC is identified in red, and the cargo is in green. The abscissa is the x axis in both cases. Spot widths correspond to the average localization precision based on photon counts. Pixel size, 2.95 nm.

Supplementary Video 6

3D super-resolved nuclear abortive import of an NLS-2×BFP/Imp α(Atto542)/Imp β complex. The position of a NPC scaffold was determined as in Fig. 2f,g from HMSiR localizations. A NLS-2×BFP cargo complex undergoing abortive import (approach of Fig. 5) was determined via successive localizations. On the left, the x and y coordinates are reflected by the two spatial dimensions, and the colour indicates the position along the z coordinate (transport axis). Inset: z colour scale. On the right, the same trajectory is presented in the x-z plane, the NPC is identified in red, and the cargo is in green. The abscissa is the x axis in both cases. Spot widths correspond to the average localization precision based on photon counts. Pixel size, 2.95 nm.

Supplementary Data 1 (software file 1)

This Excel file was used to model the random appearance in 3D of fluorescent spots from labelled NUP96 molecules based on coordinates from the electron microscopy density map of the human NPC. The ‘final coordinates’ (output) will automatically recalculate after any of the input parameters are changed. Additional outputs are the average single-particle precision values, which are estimated over input z and photon ranges (the photon range is determined by the minimum photons and the log-normal distribution used). See Methods and the file itself for additional details.

Supplementary Data 2 (software file 2)

This Excel file was used to model the random appearance of fluorescence spots appearing in the cytoplasmic and nucleoplasmic compartments and within the NPC central pore (Extended Data Fig. 5e). See Methods and the file itself for additional details.

Supplementary Table 1

List of Matlab scripts used for data analyses. All scripts are available at GitHub at https://github.com/npctat2021/npc3d2021.

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Chowdhury, R., Sau, A. & Musser, S.M. Super-resolved 3D tracking of cargo transport through nuclear pore complexes. Nat Cell Biol 24, 112–122 (2022). https://doi.org/10.1038/s41556-021-00815-6

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