Defining the Basis of Cyanine Phototruncation Enables a New Approach to Single-Molecule Localization Microscopy

The light-promoted conversion of extensively used cyanine dyes to blue-shifted emissive products has been observed in various contexts. However, both the underlying mechanism and the species involved in this photoconversion reaction have remained elusive. Here we report that irradiation of heptamethine cyanines provides pentamethine cyanines, which, in turn, are photoconverted to trimethine cyanines. We detail an examination of the mechanism and substrate scope of this remarkable twocarbon phototruncation reaction. Supported by computational analysis, we propose that this reaction involves a singlet oxygeninitiated multistep sequence involving a key hydroperoxycyclobutanol intermediate. Building on this mechanistic framework, we identify conditions to improve the yield of photoconversion by over an order of magnitude. We then demonstrate that cyanine phototruncation can be applied to super-resolution single-molecule localization microscopy, leading to improved spatial resolution with shorter imaging times. We anticipate these insights will help transform a common, but previously mechanistically ill-defined, chemical transformation into a valuable optical tool

Unraveling nanotopography of cell surface receptors

Cells communicate with their environment via surface receptors, but nanoscopic receptor organization with respect to complex cell surface morphology remains unclear. This is mainly due to a lack of accessible, robust and high-resolution methods. Here, we present an approach for mapping the topography of receptors at the cell surface with nanometer precision. The method involves coating glass coverslips with glycine, which preserves the fine membrane morphology while allowing immobilized cells to be positioned close to the optical surface. We developed an advanced and simplified algorithm for the analysis of single-molecule localization data acquired in a biplane detection scheme. These advancements enable direct and quantitative mapping of protein distribution on ruffled plasma membranes with near isotropic 3D nanometer resolution. As demonstrated successfully for CD4 and CD45 receptors, the described workflow is a straightforward quantitative technique to study molecules and their interactions at the complex surface nanomorphology of differentiated metazoan cells

Approach to map nanotopography of cell surface receptors

Cells communicate with their environment via surface receptors, but nanoscopic receptor organization with respect to complex cell surface morphology remains unclear. This is mainly due to a lack of accessible, robust and high-resolution methods. Here, we present an approach for mapping the topography of receptors at the cell surface with nanometer precision. The method involves coating glass coverslips with glycine, which preserves the fine membrane morphology while allowing immobilized cells to be positioned close to the optical surface. We developed an advanced and simplified algorithm for the analysis of single-molecule localization data acquired in a biplane detection scheme. These advancements enable direct and quantitative mapping of protein distribution on ruffled plasma membranes with near isotropic 3D nanometer resolution. As demonstrated successfully for CD4 and CD45 receptors, the described workflow is a straightforward quantitative technique to study molecules and their interactions at the complex surface nanomorphology of differentiated metazoan cells

Cooperation of local motions in the Hsp90 molecular chaperone ATPase mechanism

The Hsp90 chaperone is a central node of protein homeostasis activating a large number of diverse client proteins. Hsp90 functions as a molecular clamp that closes and opens in response to the binding and hydrolysis of ATP. Crystallographic studies define distinct conformational states of the mechanistic core implying structural changes that have not yet been observed in solution. Here, we engineered one-nanometer fluorescence probes based on photo-induced electron transfer into yeast Hsp90 to observe these motions. We found that the ATPase activity of the chaperone was reflected in the kinetics of specific structural rearrangements at remote positions that acted cooperatively. Nanosecond single-molecule fluorescence fluctuation analysis uncovered that critical structural elements that undergo rearrangement are mobile on a sub-millisecond time scale. We identified a two-step mechanism for lid closure over the nucleotide-binding pocket. The activating co-chaperone Aha1 mobilizes the lid of apo Hsp90, suggesting an early role in the catalytic cycle

ReCSAI: recursive compressed sensing artificial intelligence for confocal lifetime localization microscopy

Background Localization-based super-resolution microscopy resolves macromolecular structures down to a few nanometers by computationally reconstructing fluorescent emitter coordinates from diffraction-limited spots. The most commonly used algorithms are based on fitting parametric models of the point spread function (PSF) to a measured photon distribution. These algorithms make assumptions about the symmetry of the PSF and thus, do not work well with irregular, non-linear PSFs that occur for example in confocal lifetime imaging, where a laser is scanned across the sample. An alternative method for reconstructing sparse emitter sets from noisy, diffraction-limited images is compressed sensing, but due to its high computational cost it has not yet been widely adopted. Deep neural network fitters have recently emerged as a new competitive method for localization microscopy. They can learn to fit arbitrary PSFs, but require extensive simulated training data and do not generalize well. A method to efficiently fit the irregular PSFs from confocal lifetime localization microscopy combining the advantages of deep learning and compressed sensing would greatly improve the acquisition speed and throughput of this method. Results Here we introduce ReCSAI, a compressed sensing neural network to reconstruct localizations for confocal dSTORM, together with a simulation tool to generate training data. We implemented and compared different artificial network architectures, aiming to combine the advantages of compressed sensing and deep learning. We found that a U-Net with a recursive structure inspired by iterative compressed sensing showed the best results on realistic simulated datasets with noise, as well as on real experimentally measured confocal lifetime scanning data. Adding a trainable wavelet denoising layer as prior step further improved the reconstruction quality. Conclusions Our deep learning approach can reach a similar reconstruction accuracy for confocal dSTORM as frame binning with traditional fitting without requiring the acquisition of multiple frames. In addition, our work offers generic insights on the reconstruction of sparse measurements from noisy experimental data by combining compressed sensing and deep learning. We provide the trained networks, the code for network training and inference as well as the simulation tool as python code and Jupyter notebooks for easy reproducibility

Genetic Code Expansion and Click-Chemistry Labeling to Visualize GABA-A Receptors by Super-Resolution Microscopy

Fluorescence labeling of difficult to access protein sites, e.g., in confined compartments, requires small fluorescent labels that can be covalently tethered at well-defined positions with high efficiency. Here, we report site-specific labeling of the extracellular domain of γ-aminobutyric acid type A (GABA-A) receptor subunits by genetic code expansion (GCE) with unnatural amino acids (ncAA) combined with bioorthogonal click-chemistry labeling with tetrazine dyes in HEK-293-T cells and primary cultured neurons. After optimization of GABA-A receptor expression and labeling efficiency, most effective variants were selected for super-resolution microscopy and functionality testing by whole-cell patch clamp. Our results show that GCE with ncAA and bioorthogonal click labeling with small tetrazine dyes represents a versatile method for highly efficient site-specific fluorescence labeling of proteins in a crowded environment, e.g., extracellular protein domains in confined compartments such as the synaptic cleft

Targetable conformationally restricted cyanines enable photon-count-limited applications

Cyanine dyes are exceptionally useful probes for a range of fluorescence-based applications, but their photon output can be limited by trans-to-cis photoisomerization. We recently demonstrated that appending a ring system to the pentamethine cyanine ring system improves the quantum yield and extends the fluorescence lifetime. Here, we report an optimized synthesis of persulfonated variants that enable efficient labeling of nucleic acids and proteins. We demonstrate that a bifunctional sulfonated tertiary amide significantly improves the optical properties of the resulting bioconjugates. These new conformationally restricted cyanines are compared to the parent cyanine derivatives in a range of contexts. These include their use in the plasmonic hotspot of a DNA-nanoantenna, in single-molecule Förster-resonance energy transfer (FRET) applications, far-red fluorescence-lifetime imaging microscopy (FLIM), and single-molecule localization microscopy (SMLM). These efforts define contexts in which eliminating cyanine isomerization provides meaningful benefits to imaging performance