Simulating structurally variable Nuclear Pore Complexes for Microscopy

Author:

Theiss MariaORCID,Hériché Jean-KarimORCID,Russell CraigORCID,Helekal DavidORCID,Soppitt Alisdair,Ries JonasORCID,Ellenberg JanORCID,Brazma AlvisORCID,Uhlmann VirginieORCID

Abstract

AbstractMotivationThe Nuclear Pore Complex (NPC) is the only passageway for macromolecules between nucleus and cytoplasm, and one of localization microscopy’s most important reference standards: it is massive and stereotypically arranged. The average architecture of NPC proteins has been resolved with pseudo-atomic precision, however observed NPC heterogeneities evidence a high degree of divergence from this average. Single Molecule Localization Microscopy (SMLM) images NPCs at protein-level resolution, whereupon image analysis software studies NPC variability. However the true picture of NPC variability is unknown. In quantitative image analysis experiments, it is thus difficult to distinguish intrinsically high SMLM noise from true variability of the underlying structure.ResultsWe introduce CIR4MICS (“ceramics”, Configurable, Irregular Rings FOR MICroscopy Simulations), a pipeline that creates artificial datasets of structurally variable synthetic NPCs based on architectural models of the true NPC. Users can select one or more N- or C-terminally tagged NPC proteins, and simulate a wide range of geometric variations. We also represent the NPC as a spring-model such that arbitrary deforming forces, of user-defined magnitudes, simulate irregularly shaped variations. We provide an open-source simulation pipeline, as well as reference datasets of simulated human NPCs. Accompanying ground truth annotations allow to test the capabilities of image analysis software and facilitate a side-by-side comparison with real data. We demonstrate this by synthetically replicating a geometric analysis of real NPC radii and reveal that a wide range of simulated variability parameters can lead to observed results. Our simulator is therefore valuable to benchmark and develop image analysis methods, as well as to inform experimentalists about the requirements of hypothesis-driven imaging studies.AvailabilityCode:https://github.com/uhlmanngroup/cir4mics. Simulated data is available at BioStudies (Accession number S-BSST1058).Contacttheiss@ebi.ac.ukSupplementary informationSupplementary data are available at

Publisher

Cold Spring Harbor Laboratory

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