Nanoscale pattern extraction from relative positions of sparse 3D localisations

Abstract

We present a method for extracting high-resolution ordered features from localisation microscopy data by analysis of relative molecular positions in 2D or 3D. This approach allows pattern recognition at sub-1% protein detection efficiencies, in large and heterogeneous samples, and in 2D and 3D datasets. We used this method to infer ultrastructure of the nuclear pore, the cardiomyocyte Z-disk, DNA origami structures and the centriole. of Biomedical Imaging and Bioengineering, US National Institutes of Health. The dSTORM system was funded by alumnus M. Beverley, in support of the University of Leeds 'making a world of difference' campaign. R.J. acknowledges support by the DFG through the Emmy Noether Program (DFG JU 2957/1-1), the ERC through an ERC Starting Grant (MolMap, Grant agreement number 680241), the Max Planck Society, the Max Planck Foundation and the Center for Nanoscience (CeNS). T.S. acknowledges support from the DFG through the Graduate School of Quantitative Biosciences Munich (QBM). Isolated cardiomyocytes were a kind gift from the Steele Group, University of Leeds. We thank Ulf Matti and Philipp Hoess for sample preparation and imaging of the Nup107 cells, and Niccolò Banterle for the centriole sample preparation. We would also like to acknowledge Michael W. Davidson for his contributions to the development of the mEos3.2 constructs. Author contributionsA.Curd conceived and implemented the analysis approach, and developed software. J.L. developed software. R.H. and A.Cleasby imaged Z-disk proteins in 3D PALM. B.R. imaged ACTN2 Affimer in 3D dSTORM. C.H and B.R. crystallised the Affimer-CH domain construct and solved its structure. M.B. and M.P. developed fluorescent protein constructs. H.T., H.S. and M.P. developed 3D PALM labelling and imaging techniques. C.S and S.M. provided the Cep152 localisation data and conceived the particle quality assessment concept. J.R. provided the 3D Nup107 localisation data. M.P. conceived the Z-disk protein experiment and acquired confocal data on Z-disk protein labelling. A.Curd and M.P. wrote the manuscript with input from all other authors.

Simulating structurally variable Nuclear Pore Complexes for Microscopy

“…Geometric variability can be set as a fixed parameter or randomised Geometric variability of the NPC is commonly observed in imaging data [9], [11]- [20]. We simulate differences in radius, ring distance and twist angle between CR and NR, rotational symmetry, and elongations (See Figure 4A for an overview, excluding ring distance, and Table 3).…”

“…Here, we introduce a toolbox that simulates irregularly shaped NPCs as well as a wide range of geometric NPC variability reported in literature and anecdotally. This geometric variability encompasses elongated NPCs [14]- [16], varying radii [9], [13], [18], [19] and rotational symmetry [11]- [13], ring distance [17], [18], [20] and twist angle [17]. Finally, we used our software to generate a reference dataset that includes deformed ground truth NPCs, annotated features, as well as corresponding simulated imaging data using the SMLM simulation engine of SMAP [39].…”

“…Examples of this NPC variability are deviations from the 8-fold rotational symmetry [11]- [13], elliptical deformations [14]- [16], varying twist angle between CR and NR [17], and varying pore diameters [9], [13], [18], [19]. Furthermore, distance between CR and NR is inconsistently reported [17], [18], [20].…”

A correlative super-resolution protocol to visualise structural underpinnings of fast second-messenger signalling in primary cell types

“…However, for many groups studying the biophysics of proteins or cellular structures which are critical for normal cell function, these animal models are beyond their technical, collaborative and/or financial means. In vitro gene transfection of primary cells with FP-fusion protein constructs are an alternative (25,26); however marker sparsity, depending on transfection efficiency and native protein turnover rates, are a major drawback. Cell types such as muscle also undergo severe maladaptive remodelling ex vivo (27) which limits the utility of gene transfection as a route of delivering the protein markers for super-resolution imaging.…”