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Super-Resolution Imaging of Plasma Membrane Proteins with Click Chemistry

View Article: PubMed Central - PubMed

ABSTRACT

Besides its function as a passive cell wall, the plasma membrane (PM) serves as a platform for different physiological processes such as signal transduction and cell adhesion, determining the ability of cells to communicate with the exterior, and form tissues. Therefore, the spatial distribution of PM components, and the molecular mechanisms underlying it, have important implications in various biological fields including cell development, neurobiology, and immunology. The existence of confined compartments in the plasma membrane that vary on many length scales from protein multimers to micrometer-size domains with different protein and lipid composition is today beyond all questions. As much as the physiology of cells is controlled by the spatial organization of PM components, the study of distribution, size, and composition remains challenging. Visualization of the molecular distribution of PM components has been impeded mainly due to two problems: the specific labeling of lipids and proteins without perturbing their native distribution and the diffraction-limit of fluorescence microscopy restricting the resolution to about half the wavelength of light. Here, we present a bioorthogonal chemical reporter strategy based on click chemistry and metabolic labeling for efficient and specific visualization of PM proteins and glycans with organic fluorophores in combination with super-resolution fluorescence imaging by direct stochastic optical reconstruction microscopy (dSTORM) with single-molecule sensitivity.

No MeSH data available.


Effect of two-dimensional projections of membrane structures. (A)dSTORM image of PM proteins metabolically labeled with L-AHA showing overlapping membranes, vesicle-like structures, and filipodia. (B) Sliding window analysis to estimate PM content (white circle in (A): diameter = 1 μm, step = 100 nm) lead to median values of 884 localizations per μm2 within a region under the nucleus, i.e., single membrane structure blue square in (A), and 2130 localizations per μm2 within the lamellipodia, i.e., two-fold overlapping membranes orange square in (A). Box plot: red bar = median, box = 25th and 75th percentile, □ = mean. (C,D) Consecutive images with focal planes slightly shifted (0.5–1 μm) into the cytosol reveal artificial cluster structures generated due to vesicle-like structures located above the plasma membrane blue and yellow circles as well as inhomogeneities due to membrane ruffles green circle; adapted from Burgert et al. (2015).
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Figure 3: Effect of two-dimensional projections of membrane structures. (A)dSTORM image of PM proteins metabolically labeled with L-AHA showing overlapping membranes, vesicle-like structures, and filipodia. (B) Sliding window analysis to estimate PM content (white circle in (A): diameter = 1 μm, step = 100 nm) lead to median values of 884 localizations per μm2 within a region under the nucleus, i.e., single membrane structure blue square in (A), and 2130 localizations per μm2 within the lamellipodia, i.e., two-fold overlapping membranes orange square in (A). Box plot: red bar = median, box = 25th and 75th percentile, □ = mean. (C,D) Consecutive images with focal planes slightly shifted (0.5–1 μm) into the cytosol reveal artificial cluster structures generated due to vesicle-like structures located above the plasma membrane blue and yellow circles as well as inhomogeneities due to membrane ruffles green circle; adapted from Burgert et al. (2015).

Mentions: Besides the aforementioned experimental traits of dSTORM, inherent problems and limitations appear when studying membrane components with 2D localization microscopy. Without 3D information the ability to extract unbiased information about PM can be error prone. The existence of Z-projections of inherent cell membrane structures such as invaginations and vesicle-like structures, including fluorophore-filled endosomes in contact with or located near the PM, as well as overlapping membranes in the lamellipodia, might distort severely the quantitative analysis and interpretation of super-resolution images. For example, a sliding window analysis applied to dSTORM images of PM under the nucleus reveals half of the localization density compared to lamellipodia indicating a two-fold membrane structure (Figures 3A,B). Furthermore, circular clusters with apparent sizes ranging from a few tens to a few hundred nanometers can be visually identified from more homogeneous distributions, however it is difficult to discern weather they represent nanodomains enriched in membrane proteins or projections from fluorophore-filled vesicles in close proximity to the membrane. Whereas, a 3D-dSTORM measurement would reduce any information bias on PM organization due to vertical projections, instrumentation, and implementation for 3D-dSTORM is more complex and expensive compared to 2D-dSTORM, and they usually achieve a lower axial than lateral resolution (Klein et al., 2014). In contrast, consecutive imaging of the same cell with slightly shifted focal planes above the feature of interest constitutes a fast control to determine the two-dimensional projection contribution from inherent 3D structures as shown in Figures 3C,D for vesicle-like structures located right above the plasma membrane (yellow circles) or further up (blue circle), and membrane ruffles (green circle) (Burgert et al., 2015).


Super-Resolution Imaging of Plasma Membrane Proteins with Click Chemistry
Effect of two-dimensional projections of membrane structures. (A)dSTORM image of PM proteins metabolically labeled with L-AHA showing overlapping membranes, vesicle-like structures, and filipodia. (B) Sliding window analysis to estimate PM content (white circle in (A): diameter = 1 μm, step = 100 nm) lead to median values of 884 localizations per μm2 within a region under the nucleus, i.e., single membrane structure blue square in (A), and 2130 localizations per μm2 within the lamellipodia, i.e., two-fold overlapping membranes orange square in (A). Box plot: red bar = median, box = 25th and 75th percentile, □ = mean. (C,D) Consecutive images with focal planes slightly shifted (0.5–1 μm) into the cytosol reveal artificial cluster structures generated due to vesicle-like structures located above the plasma membrane blue and yellow circles as well as inhomogeneities due to membrane ruffles green circle; adapted from Burgert et al. (2015).
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Figure 3: Effect of two-dimensional projections of membrane structures. (A)dSTORM image of PM proteins metabolically labeled with L-AHA showing overlapping membranes, vesicle-like structures, and filipodia. (B) Sliding window analysis to estimate PM content (white circle in (A): diameter = 1 μm, step = 100 nm) lead to median values of 884 localizations per μm2 within a region under the nucleus, i.e., single membrane structure blue square in (A), and 2130 localizations per μm2 within the lamellipodia, i.e., two-fold overlapping membranes orange square in (A). Box plot: red bar = median, box = 25th and 75th percentile, □ = mean. (C,D) Consecutive images with focal planes slightly shifted (0.5–1 μm) into the cytosol reveal artificial cluster structures generated due to vesicle-like structures located above the plasma membrane blue and yellow circles as well as inhomogeneities due to membrane ruffles green circle; adapted from Burgert et al. (2015).
Mentions: Besides the aforementioned experimental traits of dSTORM, inherent problems and limitations appear when studying membrane components with 2D localization microscopy. Without 3D information the ability to extract unbiased information about PM can be error prone. The existence of Z-projections of inherent cell membrane structures such as invaginations and vesicle-like structures, including fluorophore-filled endosomes in contact with or located near the PM, as well as overlapping membranes in the lamellipodia, might distort severely the quantitative analysis and interpretation of super-resolution images. For example, a sliding window analysis applied to dSTORM images of PM under the nucleus reveals half of the localization density compared to lamellipodia indicating a two-fold membrane structure (Figures 3A,B). Furthermore, circular clusters with apparent sizes ranging from a few tens to a few hundred nanometers can be visually identified from more homogeneous distributions, however it is difficult to discern weather they represent nanodomains enriched in membrane proteins or projections from fluorophore-filled vesicles in close proximity to the membrane. Whereas, a 3D-dSTORM measurement would reduce any information bias on PM organization due to vertical projections, instrumentation, and implementation for 3D-dSTORM is more complex and expensive compared to 2D-dSTORM, and they usually achieve a lower axial than lateral resolution (Klein et al., 2014). In contrast, consecutive imaging of the same cell with slightly shifted focal planes above the feature of interest constitutes a fast control to determine the two-dimensional projection contribution from inherent 3D structures as shown in Figures 3C,D for vesicle-like structures located right above the plasma membrane (yellow circles) or further up (blue circle), and membrane ruffles (green circle) (Burgert et al., 2015).

View Article: PubMed Central - PubMed

ABSTRACT

Besides its function as a passive cell wall, the plasma membrane (PM) serves as a platform for different physiological processes such as signal transduction and cell adhesion, determining the ability of cells to communicate with the exterior, and form tissues. Therefore, the spatial distribution of PM components, and the molecular mechanisms underlying it, have important implications in various biological fields including cell development, neurobiology, and immunology. The existence of confined compartments in the plasma membrane that vary on many length scales from protein multimers to micrometer-size domains with different protein and lipid composition is today beyond all questions. As much as the physiology of cells is controlled by the spatial organization of PM components, the study of distribution, size, and composition remains challenging. Visualization of the molecular distribution of PM components has been impeded mainly due to two problems: the specific labeling of lipids and proteins without perturbing their native distribution and the diffraction-limit of fluorescence microscopy restricting the resolution to about half the wavelength of light. Here, we present a bioorthogonal chemical reporter strategy based on click chemistry and metabolic labeling for efficient and specific visualization of PM proteins and glycans with organic fluorophores in combination with super-resolution fluorescence imaging by direct stochastic optical reconstruction microscopy (dSTORM) with single-molecule sensitivity.

No MeSH data available.