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      Multicolor 3D-dSTORM Reveals Native-State Ultrastructure of Polysaccharides' Network during Plant Cell Wall Assembly

      research-article
      1 , 2 , 1 , 3 ,
      iScience
      Elsevier
      Plant Biochemistry, Molecular Biology, Plant Biology

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          Summary

          The plant cell wall, a form of the extracellular matrix, is a complex and dynamic network of polymers mediating a plethora of physiological functions. How polysaccharides assemble into a coherent and heterogeneous matrix remains mostly undefined. Further progress requires improved molecular-level visualization methods that would gain a deeper understanding of the cell wall nanoarchitecture. dSTORM, a type of super-resolution microscopy, permits quantitative nanoimaging of the cell wall. However, due to the lack of single-cell model systems and the requirement of tissue-level imaging, its use in plant science is almost absent. Here we overcome these limitations; we compare two methods to achieve three-dimensional dSTORM and identify optimal photoswitching dyes for tissue-level multicolor nanoscopy. Combining dSTORM with spatial statistics, we reveal and characterize the ultrastructure of three major polysaccharides, callose, mannan, and cellulose, in the plant cell wall precursor and provide evidence for cellulose structural re-organization related to callose content.

          Graphical Abstract

          Highlights

          • Near-stoichiometric nanoimaging of cell wall polysaccharides

          • Optimized three-color 3D-dSTORM on sectioned plant tissue

          • 3D Spatial Point Pattern analysis of cell wall probes

          • Quantitative in muro nanoimaging of cellulose, mannan, and callose during cytokinesis

          Abstract

          Plant Biochemistry; Molecular Biology; Plant Biology

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          Most cited references37

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          Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy.

          Recent advances in far-field fluorescence microscopy have led to substantial improvements in image resolution, achieving a near-molecular resolution of 20 to 30 nanometers in the two lateral dimensions. Three-dimensional (3D) nanoscale-resolution imaging, however, remains a challenge. We demonstrated 3D stochastic optical reconstruction microscopy (STORM) by using optical astigmatism to determine both axial and lateral positions of individual fluorophores with nanometer accuracy. Iterative, stochastic activation of photoswitchable probes enables high-precision 3D localization of each probe, and thus the construction of a 3D image, without scanning the sample. Using this approach, we achieved an image resolution of 20 to 30 nanometers in the lateral dimensions and 50 to 60 nanometers in the axial dimension. This development allowed us to resolve the 3D morphology of nanoscopic cellular structures.
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            Direct stochastic optical reconstruction microscopy with standard fluorescent probes.

            Direct stochastic optical reconstruction microscopy (dSTORM) uses conventional fluorescent probes such as labeled antibodies or chemical tags for subdiffraction resolution fluorescence imaging with a lateral resolution of ∼20 nm. In contrast to photoactivated localization microscopy (PALM) with photoactivatable fluorescent proteins, dSTORM experiments start with bright fluorescent samples in which the fluorophores have to be transferred to a stable and reversible OFF state. The OFF state has a lifetime in the range of 100 milliseconds to several seconds after irradiation with light intensities low enough to ensure minimal photodestruction. Either spontaneously or photoinduced on irradiation with a second laser wavelength, a sparse subset of fluorophores is reactivated and their positions are precisely determined. Repetitive activation, localization and deactivation allow a temporal separation of spatially unresolved structures in a reconstructed image. Here we present a step-by-step protocol for dSTORM imaging in fixed and living cells on a wide-field fluorescence microscope, with standard fluorescent probes focusing especially on the photoinduced fine adjustment of the ratio of fluorophores residing in the ON and OFF states. Furthermore, we discuss labeling strategies, acquisition parameters, and temporal and spatial resolution. The ultimate step of data acquisition and data processing can be performed in seconds to minutes.
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              Optimized localization-analysis for single-molecule tracking and super-resolution microscopy

              We optimally localize isolated fluorescent beads and molecules imaged as diffraction-limited spots, determine the orientation of molecules, and present reliable formulae for the precisions of various localization methods. For beads, theory and experimental data both show that unweighted least-squares fitting of a Gaussian squanders one third of the available information, a popular formula for its precision exaggerates beyond Fisher's information limit, and weighted least-squares may do worse, while maximum likelihood fitting is practically optimal.
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                Author and article information

                Contributors
                Journal
                iScience
                iScience
                iScience
                Elsevier
                2589-0042
                27 November 2020
                18 December 2020
                27 November 2020
                : 23
                : 12
                : 101862
                Affiliations
                [1 ]Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, 78000, Versailles, France
                [2 ]Microscopy Core Facility, Sainsbury Laboratory, University of Cambridge, Bateman Street, Cambridge, CB2 1LR, UK
                Author notes
                []Corresponding author kalina.haas@ 123456inrae.fr
                [3]

                Lead Contact

                Article
                S2589-0042(20)31059-2 101862
                10.1016/j.isci.2020.101862
                7733027
                33336161
                cf4ec889-191c-40d3-b0a4-30e935e27cd1
                © 2020 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 29 July 2020
                : 7 October 2020
                : 20 November 2020
                Categories
                Article

                plant biochemistry,molecular biology,plant biology
                plant biochemistry, molecular biology, plant biology

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