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Jahr, W.

Publications and source records attributed to Jahr, W..

3 recordsLinked to original sources

Image-based 3D active sample stabilization on the nanometer scale for optical microscopy

Super-resolution microscopy often entails long acquisition times of minutes to hours. Since drifts during the acquisition adversely affect data quality, active sample stabilization is commonly used for some of these techniques to reach their full potential. While drifts in the lateral plane can often be corrected after acquisition, this is not always possible or may come with drawbacks. Therefore, it is appealing to stabilize sample position in three dimensions during acquisition. Various schemes for active sample stabilization have been demonstrated previously, with some reaching sub-nm stability in three dimensions. However, these high-performance implementations significantly added to the complexity of the hardware and/or sample preparation. Here, we present a scheme for active drift correction that delivers the nm-scale 3D stability demanded by state-of-the-art super-resolution techniques and is straightforward to implement. Using a refined algorithm that does not depend on sparse peaks typically provided by fiducial markers added to the sample, we stabilized our sample position to [~]1 nm in 3D using objective lenses both with high and low numerical aperture. Our implementation requires only the addition of a standard widefield imaging path and we provide an open-source control software with graphical user interface to facilitate easy adoption of the module. Finally, we demonstrate how this has the potential to enhance data collection for diffraction-limited and super-resolution imaging techniques using single-molecule localization microscopy and cryo-confocal imaging as showcases. Why it mattersSuper-resolution light microscopy has enabled the visualization of biological structures down to the nm-scale. However, uncorrected drifts during often extended acquisition times may adversely affect data quality. Active drift correction in three dimensions has achieved sub-nm stabilization, but state-of-the-art techniques come with considerable overhead on sample preparation and/or hardware. Here, we demonstrate an image-based stabilization scheme which allows for flexibility regarding structures used for stabilization and is straightforward to adopt. Using a maximally simple implementation, we stabilized the position of our sample to around 1 nm over extended acquisition times and demonstrated usefulness in two example imaging settings where sample drifts are critical, super-resolution single-molecule localization microscopy and confocal imaging at cryogenic temperatures.

biophysics↗

Super-resolution expansion microscopy in plant roots

Super-resolution methods enable spatial resolution far better than the optical diffraction limit of about half the wavelength of light ([~]200-300 nm) but have yet to attain widespread use in plants, owing in large part to plants challenging optical properties. Expansion microscopy improves effective resolution by isotropically increasing physical distances between sample structures while preserving relative spatial arrangements, and clears the sample. However, its application to plants has been hindered by the rigid, mechanically cohesive structure of plant tissues. Here, we report on whole-mount expansion microscopy of Arabidopsis thaliana root tissues (PlantEx), achieving 4-fold resolution increase over conventional microscopy, highlighting microtubule cytoskeleton organization and interaction between molecularly defined cellular constituents. By combining PlantEx with STED microscopy, we increase nanoscale resolution further and visualize the complex organization of subcellular organelles from intact tissues by example of the densely packed COPI-coated vesicles associated with the Golgi apparatus and put these into cellular structural context.

plant biology↗

Saturated reconstruction of living brain tissue

Complex wiring between neurons underlies the information-processing network enabling all brain functions, including cognition and memory. For understanding how the network is structured, processes information, and changes over time, comprehensive visualization of the architecture of living brain tissue with its cellular and molecular components would open up major opportunities. However, electron microscopy (EM) provides nanometre-scale resolution required for full in-silico reconstruction1-5, yet is limited to fixed specimens and static representations. Light microscopy allows live observation, with super-resolution approaches6-12 facilitating nanoscale visualization, but comprehensive 3D-reconstruction of living brain tissue has been hindered by tissue photo-burden, photobleaching, insufficient 3D-resolution, and inadequate signal-to-noise ratio (SNR). Here we demonstrate saturated reconstruction of living brain tissue. We developed an integrated imaging and analysis technology, adapting stimulated emission depletion (STED) microscopy6,13 in extracellularly labelled tissue14 for high SNR and near-isotropic resolution. Centrally, a two-stage deep-learning approach leveraged previously obtained information on sample structure to drastically reduce photo-burden and enable automated volumetric reconstruction down to single synapse level. Live reconstruction provides unbiased analysis of tissue architecture across time in relation to functional activity and targeted activation, and contextual understanding of molecular labelling. This adoptable technology will facilitate novel insights into the dynamic functional architecture of living brain tissue.

neuroscience↗