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Nanoscale Spatiotemporal Diffusion Modes Measured by Simultaneous Confocal and Stimulated Emission Depletion Nanoscopy Imaging
The diffusion dynamics in the cellular plasma membrane provide crucial insights into molecular interactions, organization, and bioactivity. Beam-scanning fluorescence correlation spectroscopy combined with super-resolution stimulated emission depletion nanoscopy (scanning STED–FCS) measures such dynamics with high spatial and temporal resolution. It reveals nanoscale diffusion characteristics by measuring the molecular diffusion in conventional confocal mode and super-resolved STED mode sequentially for each pixel along the scanned line. However, to directly link the spatial and the temporal information, a method that simultaneously measures the diffusion in confocal and STED modes is needed. Here, to overcome this problem, we establish an advanced STED–FCS measurement method, line interleaved excitation scanning STED–FCS (LIESS–FCS), that discloses the molecular diffusion modes at different spatial positions with a single measurement. It relies on fast beam-scanning along a line with alternating laser illumination that yields, for each pixel, the apparent diffusion coefficients for two different observation spot sizes (conventional confocal and super-resolved STED). We demonstrate the potential of the LIESS–FCS approach with simulations and experiments on lipid diffusion in model and live cell plasma membranes. We also apply LIESS–FCS to investigate the spatiotemporal organization of glycosylphosphatidylinositol-anchored proteins in the plasma membrane of live cells, which, interestingly, show multiple diffusion modes at different spatial positions.
Object detection networks and augmented reality for cellular detection in fluorescence microscopy
Object detection networks are high-performance algorithms famously applied to the task of identifying and localizing objects in photography images. We demonstrate their application for the classification and localization of cells in fluorescence microscopy by benchmarking four leading object detection algorithms across multiple challenging 2D microscopy datasets. Furthermore we develop and demonstrate an algorithm that can localize and image cells in 3D, in close to real time, at the microscope using widely available and inexpensive hardware. Furthermore, we exploit the fast processing of these networks and develop a simple and effective augmented reality (AR) system for fluorescence microscopy systems using a display screen and back-projection onto the eyepiece. We show that it is possible to achieve very high classification accuracy using datasets with as few as 26 images present. Using our approach, it is possible for relatively nonskilled users to automate detection of cell classes with a variety of appearances and enable new avenues for automation of fluorescence microscopy acquisition pipelines. © 2020 Waithe et al.
Statistical Analysis of Scanning Fluorescence Correlation Spectroscopy Data Differentiates Free from Hindered Diffusion
Cells rely on versatile diffusion dynamics in their plasma membrane. Quantification of this often heterogeneous diffusion is essential to the understanding of cell regulation and function. Yet such measurements remain a major challenge in cell biology, usually due to low sampling throughput, a necessity for dedicated equipment, sophisticated fluorescent label strategies, and limited sensitivity. Here, we introduce a robust, broadly applicable statistical analysis pipeline for large scanning fluorescence correlation spectroscopy data sets, which uncovers the nanoscale heterogeneity of the plasma membrane in living cells by differentiating free from hindered diffusion modes of fluorescent lipid and protein analogues.
Molecular recognition of the native HIV-1 MPER revealed by STED microscopy of single virions
Antibodies against the Membrane-Proximal External Region (MPER) of the Env gp41 subunit neutralize HIV-1 with exceptional breadth and potency. Due to the lack of knowledge on the MPER native structure and accessibility, different and exclusive models have been proposed for the molecular mechanism of MPER recognition by broadly neutralizing antibodies. Here, accessibility of antibodies to the native Env MPER on single virions has been addressed through STED microscopy. STED imaging of fluorescently labeled Fabs reveals a common pattern of native Env recognition for HIV-1 antibodies targeting MPER or the surface subunit gp120. In the case of anti-MPER antibodies, the process evolves with extra contribution of interactions with the viral lipid membrane to binding specificity. Our data provide biophysical insights into the recognition of the potent and broadly neutralizing MPER epitope on HIV virions, and as such is of importance for the design of therapeutic interventions.
Lipid Composition but Not Curvature Is the Determinant Factor for the Low Molecular Mobility Observed on the Membrane of Virus-Like Vesicles
Human Immunodeficiency Virus type-1 (HIV-1) acquires its lipid membrane from the plasma membrane of the infected cell from which it buds out. Previous studies have shown that the HIV-1 envelope is an environment of very low mobility, with the diffusion of incorporated proteins two orders of magnitude slower than in the plasma membrane. One of the reasons for this difference is thought to be the HIV-1 membrane composition that is characterised by a high degree of rigidity and lipid packing, which has, until now, been difficult to assess experimentally. To further refine the model of the molecular mobility on the HIV-1 surface, we herein investigated the relative importance of membrane composition and curvature in simplified model membrane systems, large unilamellar vesicles (LUVs) of different lipid compositions and sizes (0.1–1 µm), using super-resolution stimulated emission depletion (STED) microscopy-based fluorescence correlation spectroscopy (STED-FCS). Establishing an approach that is also applicable to measurements of molecule dynamics in virus-sized particles, we found, at least for the 0.1–1 µm sized vesicles, that the lipid composition and thus membrane rigidity, but not the curvature, play an important role in the decreased molecular mobility on the vesicles’ surface. This observation suggests that the composition of the envelope rather than the particle geometry contributes to the previously described low mobility of proteins on the HIV-1 surface. Our vesicle-based study thus provides further insight into the dynamic properties of the surface of individual HIV-1 particles, as well as paves the methodological way towards better characterisation of the properties and function of viral lipid envelopes in general.