Simulating structurally variable Nuclear Pore Complexes for Microscopy

Theiß, M.; Hériché, Jean‐Karim; Russell, Craig; Helekal, David; Soppitt, Alisdair; Ries, Jonas; Ellenberg, Jan; Brāzma, Alvis; Uhlmann, Virginie

doi:10.1101/2022.05.17.492295

Cited by 3 publications

(4 citation statements)

References 56 publications

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“…[17] Variabilities in the NUPs shape (ring-like structure, circularity, symmetry) have been discussed in the literature. [64] In our case, we attribute the main differences to a considerable variability in the fixation process. Without localization binning, a localization precision of σ = 2.6 nm/σ = 2.9 nm was reached (Figure 4B,D).…”

Section: Minflux Imagingmentioning

confidence: 59%

“…To compare whether a cyanine marker also profits from the fast localization routine, we imaged cells stained with Alexa Fluor 647-BG on NUP107-Snap cells [64] (Figure S14, Supporting Information) with both imaging sequences (Table S2, Supporting Information). Imaging with the slow standard routine results in images of good quality, with an average localization time of 76 ms (σ = 2.9 nm, emission rate = 43 kHz).…”

Section: Minflux Imagingmentioning

confidence: 99%

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Accelerated MINFLUX Nanoscopy, through Spontaneously Fast‐Blinking Fluorophores

Remmel

Scheiderer

Butkevich³

et al. 2023

Small

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The introduction of MINFLUX nanoscopy allows single molecules to be localized with one nanometer precision in as little as one millisecond. However, current applications have so far focused on increasing this precision by optimizing photon collection, rather than minimizing the localization time. Concurrently, commonly used fluorescent switches are specifically designed for stochastic methods (e.g., STORM), optimized for a high photon yield and rather long on‐times (tens of milliseconds). Here, accelerated MINFLUX nanoscopy with up to a 30‐fold gain in localization speed is presented. The improvement is attained by designing spontaneously blinking fluorescent markers with remarkably fast on‐times, down to 1–3 ms, matching the iterative localization process used in a MINFLUX microscope. This design utilizes a silicon rhodamine amide core, shifting the spirocyclization equilibrium toward an uncharged closed form at physiological conditions and imparting intact live cell permeability, modified with a fused (benzo)thiophene spirolactam fragment. The best candidate for MINFLUX microscopy (also suitable for STORM imaging) is selected through detailed characterization of the blinking behavior of single fluorophores, bound to different protein tags. Finally, optimization of the localization routines, customized to the fast blinking times, renders a significant speed improvement on a commercial MINFLUX microscope.

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Section: Minflux Imagingmentioning

confidence: 59%

Section: Minflux Imagingmentioning

confidence: 99%

Accelerated MINFLUX Nanoscopy, through Spontaneously Fast‐Blinking Fluorophores

Remmel

Scheiderer

Butkevich³

et al. 2023

Small

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“…The magnitude of such deformations can be controlled with the parameters of the simulation. With this method, the authors generated several datasets available at [27].…”

Section: Simulation Of Npc Structuresmentioning

confidence: 99%

Improving STED microscopy with SUPPOSe: enhancing resolution from a single-image

Toscani,

Lacapmesure

2024

Methods Appl. Fluoresc.

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Here we apply the gSUPPOSe algorithm on images acquired using Stimulated Emission Depletion (STED) microscopy with the aim of improving the resolution limit achieved. We processed images of the nuclear pore complex (NPC) from cell lines in which the Nup96 nucleoporin was endogenously labeled. This reference protein forms a ring whose diameter is ∽107 nm with 8 corners ∽42 nm apart from each other. The stereotypic arrangement of proteins in the NPC has been used as reference structures to characterize the performance of a variety of microscopy techniques. STED microscopy images resolve the ring arrangement but not the eightfold symmetry of the NPC. After applying the gSUPPOSe algorithm to the STED images, we were able to solve the octagonal structure of the NPC. After processing 562 single NPC, the average radius of the NPC was found to be R = 54.2 +- 2.9 nm, being consistent with the theoretical distances of this structure. To verify that the solutions obtained are compatible with a NPC-type geometry, we rotate the solutions to optimally fit an eightfold symmetric pattern and we count the number of corners that contain at least one localization. Fitting a probabilistic model to the histogram of the number of bright corners gives an effective labeling efficiency of 31%, which is in agreement with the values reported in for other cell lines and ligands used in Single Molecule Localization microscopy, showing that SUPPOSe can reliably retrieve sub-resolution, nanoscale objects from single acquisitions even in noisy conditions.

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“…To illustrate the use of similarity measures for clustering SMLM point sets, we use simulated data inspired by the nuclear pore complex. Ground truth data is produced using the method from (Theiss et al 2022) and its acquisition in a typical SMLM experiment is simulated using the SMAP software (Ries, 2020).…”

Section: Clustering Point Setsmentioning

confidence: 99%

LOMAR: LOcalization Microscopy Analysis in R

Theiß

Brāzma

Uhlmann

et al. 2022

Preprint

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In single molecule localization microscopy data (SMLM), individual instances of a macromolecular complex come in the form of point sets. Particle averaging, which combines localization data from a large number of instances, is often used to overcome experimental noise and obtain a refined view of the underlying structure. However, SMLM point sets are often heterogeneous due to biological variations in the structure they represent and must be partitioned into groups with similar structure before averaging which calls for being able to compute structurally-relevant similarity measures between sets of points. Here we introduce LOMAR (LOcalization Microscopy Analysis in R), a software package for the R programming language that enables comparison of point sets through implementation of several point sets registration methods and similarity measures derived from topological data analysis. We demonstrate use of the package on real and simulated SMLM data of nuclear pore complexes.

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Simulating structurally variable Nuclear Pore Complexes for Microscopy

Cited by 3 publications

References 56 publications

Accelerated MINFLUX Nanoscopy, through Spontaneously Fast‐Blinking Fluorophores

Accelerated MINFLUX Nanoscopy, through Spontaneously Fast‐Blinking Fluorophores

Improving STED microscopy with SUPPOSe: enhancing resolution from a single-image

LOMAR: LOcalization Microscopy Analysis in R

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