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Review
, 51 (44), 443001

The 2018 Correlative Microscopy Techniques Roadmap

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Review

The 2018 Correlative Microscopy Techniques Roadmap

Toshio Ando et al. J Phys D Appl Phys.

Abstract

Developments in microscopy have been instrumental to progress in the life sciences, and many new techniques have been introduced and led to new discoveries throughout the last century. A wide and diverse range of methodologies is now available, including electron microscopy, atomic force microscopy, magnetic resonance imaging, small-angle x-ray scattering and multiple super-resolution fluorescence techniques, and each of these methods provides valuable read-outs to meet the demands set by the samples under study. Yet, the investigation of cell development requires a multi-parametric approach to address both the structure and spatio-temporal organization of organelles, and also the transduction of chemical signals and forces involved in cell-cell interactions. Although the microscopy technologies for observing each of these characteristics are well developed, none of them can offer read-out of all characteristics simultaneously, which limits the information content of a measurement. For example, while electron microscopy is able to disclose the structural layout of cells and the macromolecular arrangement of proteins, it cannot directly follow dynamics in living cells. The latter can be achieved with fluorescence microscopy which, however, requires labelling and lacks spatial resolution. A remedy is to combine and correlate different readouts from the same specimen, which opens new avenues to understand structure-function relations in biomedical research. At the same time, such correlative approaches pose new challenges concerning sample preparation, instrument stability, region of interest retrieval, and data analysis. Because the field of correlative microscopy is relatively young, the capabilities of the various approaches have yet to be fully explored, and uncertainties remain when considering the best choice of strategy and workflow for the correlative experiment. With this in mind, the Journal of Physics D: Applied Physics presents a special roadmap on the correlative microscopy techniques, giving a comprehensive overview from various leading scientists in this field, via a collection of multiple short viewpoints.

Keywords: atomic force microscopy; correlative microscopy; electron microscopy; fluorescence microscopy; magnetic resonance imaging; super-resolution microscopy; x-ray microscopy.

Figures

Figure 1.
Figure 1.
Schematic indication of realizations for integrated LM inside ((a), (b)) scanning or ((c), (d)) transmission EMs. Designs can be distinguished based on whether ((a), (c)) both microscopes share the same field of view, or (b) a translation, or (d) rotation is needed, to switch from light to electron microscopy and vice versa. Electron beam is indicated in green, light beam in blue.
Figure 1.
Figure 1.
Schematic indication of realizations for integrated LM inside ((a), (b)) scanning or ((c), (d)) transmission EMs. Designs can be distinguished based on whether ((a), (c)) both microscopes share the same field of view, or (b) a translation, or (d) rotation is needed, to switch from light to electron microscopy and vice versa. Electron beam is indicated in green, light beam in blue.
Figure 1.
Figure 1.
Schematic indication of realizations for integrated LM inside ((a), (b)) scanning or ((c), (d)) transmission EMs. Designs can be distinguished based on whether ((a), (c)) both microscopes share the same field of view, or (b) a translation, or (d) rotation is needed, to switch from light to electron microscopy and vice versa. Electron beam is indicated in green, light beam in blue.
Figure 2.
Figure 2.
Examples of (a)–(c) fiducial and (d)–(f) non-fiducial based image registration in integrated microscopes. (a) FM image in TEM (implementation according to figure 1(d)) of Tokuyasu sections of HeLa cells transfected with LAMP-1-GFP. Nuclei are shown in blue (DAPI), LAMP-1-GFP in green and fiducials in red. (b) Overlay of ROI (boxed area in (a)) of fluorescence and TEM images. (c) Zoom in on LAMP-1-GFP rich area. Fiducials consist of silica particles with a 15 nm gold core and a 40 nm fluorescently labeled silica shell. Overlay accuracy is about 30 nm. (d) FM image in SEM (implementation according to figure 1(a)) of rat pancreas sections, immuno-labelled after embedding in epon to show nuclei in blue (Hoechst), guanine quadruplexes in light blue (Alexa488), and insulin in orange (Alexa594). (e) SEM image of the ROI (boxed area in (d)). (f) Overlay of fluorescence from the ROI with the SEM image. The overlay (<20 nm accuracy) is obtained via an automated registration procedure between both microscopes [10]. Scale bars are 10 µm in (a), (d), 2 µm in (b), (e) and (f), and 0.5 µm in (c).
Figure 2.
Figure 2.
Examples of (a)–(c) fiducial and (d)–(f) non-fiducial based image registration in integrated microscopes. (a) FM image in TEM (implementation according to figure 1(d)) of Tokuyasu sections of HeLa cells transfected with LAMP-1-GFP. Nuclei are shown in blue (DAPI), LAMP-1-GFP in green and fiducials in red. (b) Overlay of ROI (boxed area in (a)) of fluorescence and TEM images. (c) Zoom in on LAMP-1-GFP rich area. Fiducials consist of silica particles with a 15 nm gold core and a 40 nm fluorescently labeled silica shell. Overlay accuracy is about 30 nm. (d) FM image in SEM (implementation according to figure 1(a)) of rat pancreas sections, immuno-labelled after embedding in epon to show nuclei in blue (Hoechst), guanine quadruplexes in light blue (Alexa488), and insulin in orange (Alexa594). (e) SEM image of the ROI (boxed area in (d)). (f) Overlay of fluorescence from the ROI with the SEM image. The overlay (<20 nm accuracy) is obtained via an automated registration procedure between both microscopes [10]. Scale bars are 10 µm in (a), (d), 2 µm in (b), (e) and (f), and 0.5 µm in (c).
Figure 2.
Figure 2.
Examples of (a)–(c) fiducial and (d)–(f) non-fiducial based image registration in integrated microscopes. (a) FM image in TEM (implementation according to figure 1(d)) of Tokuyasu sections of HeLa cells transfected with LAMP-1-GFP. Nuclei are shown in blue (DAPI), LAMP-1-GFP in green and fiducials in red. (b) Overlay of ROI (boxed area in (a)) of fluorescence and TEM images. (c) Zoom in on LAMP-1-GFP rich area. Fiducials consist of silica particles with a 15 nm gold core and a 40 nm fluorescently labeled silica shell. Overlay accuracy is about 30 nm. (d) FM image in SEM (implementation according to figure 1(a)) of rat pancreas sections, immuno-labelled after embedding in epon to show nuclei in blue (Hoechst), guanine quadruplexes in light blue (Alexa488), and insulin in orange (Alexa594). (e) SEM image of the ROI (boxed area in (d)). (f) Overlay of fluorescence from the ROI with the SEM image. The overlay (<20 nm accuracy) is obtained via an automated registration procedure between both microscopes [10]. Scale bars are 10 µm in (a), (d), 2 µm in (b), (e) and (f), and 0.5 µm in (c).
Figure 3.
Figure 3.
‘ColorEM’ using elemental analysis by energy dispersive x-ray imaging. ColorEM: label-free (P), paint (Os) and labeling DNA (Au) and peptides (Cd) is compatible. (a) Part of an islet of Langerhans immuno-labeled for structures in DNA (10 nm gold) and insulin (QD). (b) Overlay image of Au (red), Cd (green), Os (yellow) and P (blue) allows identification of G4 structures (gold labels) and insulin (Cd). Note the localization of Au to heterochromatin enriched in P, whereas the Cd signal is enclosed within a combination of Os rings and P that likely identifies phospholipid membranes of the vesicles. Large scale data and full resolution data is available via www.nanotomy.org; Reproduced from [22]. CC BY 4.0.
Figure 3.
Figure 3.
‘ColorEM’ using elemental analysis by energy dispersive x-ray imaging. ColorEM: label-free (P), paint (Os) and labeling DNA (Au) and peptides (Cd) is compatible. (a) Part of an islet of Langerhans immuno-labeled for structures in DNA (10 nm gold) and insulin (QD). (b) Overlay image of Au (red), Cd (green), Os (yellow) and P (blue) allows identification of G4 structures (gold labels) and insulin (Cd). Note the localization of Au to heterochromatin enriched in P, whereas the Cd signal is enclosed within a combination of Os rings and P that likely identifies phospholipid membranes of the vesicles. Large scale data and full resolution data is available via www.nanotomy.org; Reproduced from [22]. CC BY 4.0.
Figure 3.
Figure 3.
‘ColorEM’ using elemental analysis by energy dispersive x-ray imaging. ColorEM: label-free (P), paint (Os) and labeling DNA (Au) and peptides (Cd) is compatible. (a) Part of an islet of Langerhans immuno-labeled for structures in DNA (10 nm gold) and insulin (QD). (b) Overlay image of Au (red), Cd (green), Os (yellow) and P (blue) allows identification of G4 structures (gold labels) and insulin (Cd). Note the localization of Au to heterochromatin enriched in P, whereas the Cd signal is enclosed within a combination of Os rings and P that likely identifies phospholipid membranes of the vesicles. Large scale data and full resolution data is available via www.nanotomy.org; Reproduced from [22]. CC BY 4.0.
Figure 4.
Figure 4.
Overlay of fluorescence signal of mVenus-labelled EphA2 protein imaged by conventional FM (top) and super-resolution single molecule localization microscopy (SMLM) (bottom) with a TEM image in a freeze substituted and resin embedded HEK293T cell using a dedicated super-resolution CLEM protocol [34]. The structural resolution of in-resin SMLM was approx. 50 nm with an average single molecule localization accuracy of 17 nm. Reproduced from [29]. CC BY 4.0.
Figure 4.
Figure 4.
Overlay of fluorescence signal of mVenus-labelled EphA2 protein imaged by conventional FM (top) and super-resolution single molecule localization microscopy (SMLM) (bottom) with a TEM image in a freeze substituted and resin embedded HEK293T cell using a dedicated super-resolution CLEM protocol [34]. The structural resolution of in-resin SMLM was approx. 50 nm with an average single molecule localization accuracy of 17 nm. Reproduced from [29]. CC BY 4.0.
Figure 4.
Figure 4.
Overlay of fluorescence signal of mVenus-labelled EphA2 protein imaged by conventional FM (top) and super-resolution single molecule localization microscopy (SMLM) (bottom) with a TEM image in a freeze substituted and resin embedded HEK293T cell using a dedicated super-resolution CLEM protocol [34]. The structural resolution of in-resin SMLM was approx. 50 nm with an average single molecule localization accuracy of 17 nm. Reproduced from [29]. CC BY 4.0.
Figure 5.
Figure 5.
Top: cryo-SMLM of a mitochondrial protein labelled with clover in a whole vitrified COS7 cell before thinning by focused ion beam milling (for method see [12]). For cryo-SMLM a laser intensity of approx. 1.6 kW cm−2 was used. Bottom: cryo-EM images after thinning of the areas (blue rectangles) indicated in the cryo-SMLM image. Segregation artefacts and Bragg reflections indicate devitrification (ice crystal formation) caused by cryo-SMLM imaging.
Figure 5.
Figure 5.
Top: cryo-SMLM of a mitochondrial protein labelled with clover in a whole vitrified COS7 cell before thinning by focused ion beam milling (for method see [12]). For cryo-SMLM a laser intensity of approx. 1.6 kW cm−2 was used. Bottom: cryo-EM images after thinning of the areas (blue rectangles) indicated in the cryo-SMLM image. Segregation artefacts and Bragg reflections indicate devitrification (ice crystal formation) caused by cryo-SMLM imaging.
Figure 5.
Figure 5.
Top: cryo-SMLM of a mitochondrial protein labelled with clover in a whole vitrified COS7 cell before thinning by focused ion beam milling (for method see [12]). For cryo-SMLM a laser intensity of approx. 1.6 kW cm−2 was used. Bottom: cryo-EM images after thinning of the areas (blue rectangles) indicated in the cryo-SMLM image. Segregation artefacts and Bragg reflections indicate devitrification (ice crystal formation) caused by cryo-SMLM imaging.
Figure 6.
Figure 6.
Example of a mismatch between fluorescence and gold coupling to proteins of interest. Epidermal growth factor coupled to Alexa488 and 10 nm gold particles internalised into HeLa cells shows bright fluorescence but only one gold particle at the region of interest. Transferrin coupled to Alexa488 and 5 nm gold particles, however, shows a lower fluorescence signal but numerous gold particles. Quenching of the fluorophore and coupling efficiency may play a role in this mismatch. See also [14].
Figure 6.
Figure 6.
Example of a mismatch between fluorescence and gold coupling to proteins of interest. Epidermal growth factor coupled to Alexa488 and 10 nm gold particles internalised into HeLa cells shows bright fluorescence but only one gold particle at the region of interest. Transferrin coupled to Alexa488 and 5 nm gold particles, however, shows a lower fluorescence signal but numerous gold particles. Quenching of the fluorophore and coupling efficiency may play a role in this mismatch. See also [14].
Figure 6.
Figure 6.
Example of a mismatch between fluorescence and gold coupling to proteins of interest. Epidermal growth factor coupled to Alexa488 and 10 nm gold particles internalised into HeLa cells shows bright fluorescence but only one gold particle at the region of interest. Transferrin coupled to Alexa488 and 5 nm gold particles, however, shows a lower fluorescence signal but numerous gold particles. Quenching of the fluorophore and coupling efficiency may play a role in this mismatch. See also [14].
Figure 7.
Figure 7.
(A) When studying catalyst materials, optical microscopy can be used to visualize chemical events, e.g. using fluorogenic reagents (top left). By carefully tuning reaction conditions, the locations of chemical events can even be mapped on a particle with nanometer accuracy (bottom and right left). Unfortunately, the diffraction limit allows only a very limited amount to be derived from the particle itself (right), making it hard to correlate chemical reactivity with nanoscale structural features. Reproduced from [42] with permission of The Royal Society of Chemistry. (B) The combination of SRF imaging and EM allows individual chemical events to be correlated with ultrastructure at the single particle level. Reprinted with permission from [48]. Copyright 2017 American Chemical Society.
Figure 7.
Figure 7.
(A) When studying catalyst materials, optical microscopy can be used to visualize chemical events, e.g. using fluorogenic reagents (top left). By carefully tuning reaction conditions, the locations of chemical events can even be mapped on a particle with nanometer accuracy (bottom and right left). Unfortunately, the diffraction limit allows only a very limited amount to be derived from the particle itself (right), making it hard to correlate chemical reactivity with nanoscale structural features. Reproduced from [42] with permission of The Royal Society of Chemistry. (B) The combination of SRF imaging and EM allows individual chemical events to be correlated with ultrastructure at the single particle level. Reprinted with permission from [48]. Copyright 2017 American Chemical Society.
Figure 7.
Figure 7.
(A) When studying catalyst materials, optical microscopy can be used to visualize chemical events, e.g. using fluorogenic reagents (top left). By carefully tuning reaction conditions, the locations of chemical events can even be mapped on a particle with nanometer accuracy (bottom and right left). Unfortunately, the diffraction limit allows only a very limited amount to be derived from the particle itself (right), making it hard to correlate chemical reactivity with nanoscale structural features. Reproduced from [42] with permission of The Royal Society of Chemistry. (B) The combination of SRF imaging and EM allows individual chemical events to be correlated with ultrastructure at the single particle level. Reprinted with permission from [48]. Copyright 2017 American Chemical Society.
Figure 8.
Figure 8.
(A) The principle of ET. (B) ET allows the open (green) and closed (orange) mesopore volume in a zeolite Y crystal to be quantified. Reprinted from [54], Copyright 2015, with permission from Elsevier.
Figure 8.
Figure 8.
(A) The principle of ET. (B) ET allows the open (green) and closed (orange) mesopore volume in a zeolite Y crystal to be quantified. Reprinted from [54], Copyright 2015, with permission from Elsevier.
Figure 8.
Figure 8.
(A) The principle of ET. (B) ET allows the open (green) and closed (orange) mesopore volume in a zeolite Y crystal to be quantified. Reprinted from [54], Copyright 2015, with permission from Elsevier.
Figure 9.
Figure 9.
Correlative microscopy of membrane proteins in whole cells in liquid. (A) Cells are grown on a silicon nitride (SiN) membrane, supported by a silicon chip. A microchip with quantum dot (QD) labelled and fixed cells is positioned upside down in liquid in a glass-bottom dish. Fluorescence imaging is performed with an oil immersion lens on an inverted microscope. (B) For ESEM, the same microchip is positioned upright on a cooled stage and kept in a saturated water vapour atmosphere. The cells are covered with a thin layer of water. Contrast is obtained on the QDs attached to membrane proteins using the STEM detector. From [61]. Reprinted with permission from AAAS.
Figure 9.
Figure 9.
Correlative microscopy of membrane proteins in whole cells in liquid. (A) Cells are grown on a silicon nitride (SiN) membrane, supported by a silicon chip. A microchip with quantum dot (QD) labelled and fixed cells is positioned upside down in liquid in a glass-bottom dish. Fluorescence imaging is performed with an oil immersion lens on an inverted microscope. (B) For ESEM, the same microchip is positioned upright on a cooled stage and kept in a saturated water vapour atmosphere. The cells are covered with a thin layer of water. Contrast is obtained on the QDs attached to membrane proteins using the STEM detector. From [61]. Reprinted with permission from AAAS.
Figure 9.
Figure 9.
Correlative microscopy of membrane proteins in whole cells in liquid. (A) Cells are grown on a silicon nitride (SiN) membrane, supported by a silicon chip. A microchip with quantum dot (QD) labelled and fixed cells is positioned upside down in liquid in a glass-bottom dish. Fluorescence imaging is performed with an oil immersion lens on an inverted microscope. (B) For ESEM, the same microchip is positioned upright on a cooled stage and kept in a saturated water vapour atmosphere. The cells are covered with a thin layer of water. Contrast is obtained on the QDs attached to membrane proteins using the STEM detector. From [61]. Reprinted with permission from AAAS.
Figure 10.
Figure 10.
Liquid-phase ESEM-STEM image of a membrane region of a breast cancer cell showing the locations of HER2 receptors labelled with QDs. The overlay shows molecular models of the HER receptor with label consisting of an Affibody molecule (blue) coupled to a streptavidin-coated QD. The labels are attached to a monomer (left) or a homodimer (right). From [61]. Reprinted with permission from AAAS.
Figure 10.
Figure 10.
Liquid-phase ESEM-STEM image of a membrane region of a breast cancer cell showing the locations of HER2 receptors labelled with QDs. The overlay shows molecular models of the HER receptor with label consisting of an Affibody molecule (blue) coupled to a streptavidin-coated QD. The labels are attached to a monomer (left) or a homodimer (right). From [61]. Reprinted with permission from AAAS.
Figure 10.
Figure 10.
Liquid-phase ESEM-STEM image of a membrane region of a breast cancer cell showing the locations of HER2 receptors labelled with QDs. The overlay shows molecular models of the HER receptor with label consisting of an Affibody molecule (blue) coupled to a streptavidin-coated QD. The labels are attached to a monomer (left) or a homodimer (right). From [61]. Reprinted with permission from AAAS.
Figure 11.
Figure 11.
Volume-CLEM providing a direct link between live cell dynamics and 3D ultrastructure on the single organelle level [82]. (A) Schematic representation of the complete live-cell fluorescence to volume-EM workflow. (B) As an example, a fluorescence image of a LAMP-1-GFP transfected cell, incubated with Dextran-Alexa568 as an endocytic marker. (C) The cell was imaged live for several minutes, followed by in situ fixation. Stills show the LAMP-1-GFP spots (spot 1, 2) during 142 s of imaging. After fixation the cell is stained, embedded in resin, and imaged in FIB-SEM. (D) Shows the slices on all three viewing axes (XZ/XY/YZ) of the reconstructed FIB-SEM dataset containing the live-cell ROI ((B), (C) red square). Both spots 1 and 2 are classified as late endosomes based on their high number of intraluminal vesicles. (E) FIB-SEM segmentation and 3D reconstructions of spots 1 and 2; the organelles imaged in live-cell fluorescence microscopy (1,2) were segmented and correlated with reference LM data.
Figure 11.
Figure 11.
Volume-CLEM providing a direct link between live cell dynamics and 3D ultrastructure on the single organelle level [82]. (A) Schematic representation of the complete live-cell fluorescence to volume-EM workflow. (B) As an example, a fluorescence image of a LAMP-1-GFP transfected cell, incubated with Dextran-Alexa568 as an endocytic marker. (C) The cell was imaged live for several minutes, followed by in situ fixation. Stills show the LAMP-1-GFP spots (spot 1, 2) during 142 s of imaging. After fixation the cell is stained, embedded in resin, and imaged in FIB-SEM. (D) Shows the slices on all three viewing axes (XZ/XY/YZ) of the reconstructed FIB-SEM dataset containing the live-cell ROI ((B), (C) red square). Both spots 1 and 2 are classified as late endosomes based on their high number of intraluminal vesicles. (E) FIB-SEM segmentation and 3D reconstructions of spots 1 and 2; the organelles imaged in live-cell fluorescence microscopy (1,2) were segmented and correlated with reference LM data.
Figure 11.
Figure 11.
Volume-CLEM providing a direct link between live cell dynamics and 3D ultrastructure on the single organelle level [82]. (A) Schematic representation of the complete live-cell fluorescence to volume-EM workflow. (B) As an example, a fluorescence image of a LAMP-1-GFP transfected cell, incubated with Dextran-Alexa568 as an endocytic marker. (C) The cell was imaged live for several minutes, followed by in situ fixation. Stills show the LAMP-1-GFP spots (spot 1, 2) during 142 s of imaging. After fixation the cell is stained, embedded in resin, and imaged in FIB-SEM. (D) Shows the slices on all three viewing axes (XZ/XY/YZ) of the reconstructed FIB-SEM dataset containing the live-cell ROI ((B), (C) red square). Both spots 1 and 2 are classified as late endosomes based on their high number of intraluminal vesicles. (E) FIB-SEM segmentation and 3D reconstructions of spots 1 and 2; the organelles imaged in live-cell fluorescence microscopy (1,2) were segmented and correlated with reference LM data.
Figure 12.
Figure 12.
(A) A schematic of a simultaneous force spectroscopy and single molecule fluorescence experiment on a virus. An AFM tip is used for both imaging and manipulation purposes at the nanoscale. The molecular response is simultaneously tracked by imaging fluorescent markers (green) that are excited by an evanescent wave (blue). The microscope objective is shown in grey. (B) An example from a virus before and after mechanical manipulation. Top row: AFM scans (200  ×  200 nm), showing the disassembly of a virus capsid. Bottom row: fluorescence images (4  ×  4 µm) showing the release of YOYO-1 labelled DNA. The DNA remains invisible in the AFM scans because it is not immobilized to the surface.
Figure 12.
Figure 12.
(A) A schematic of a simultaneous force spectroscopy and single molecule fluorescence experiment on a virus. An AFM tip is used for both imaging and manipulation purposes at the nanoscale. The molecular response is simultaneously tracked by imaging fluorescent markers (green) that are excited by an evanescent wave (blue). The microscope objective is shown in grey. (B) An example from a virus before and after mechanical manipulation. Top row: AFM scans (200  ×  200 nm), showing the disassembly of a virus capsid. Bottom row: fluorescence images (4  ×  4 µm) showing the release of YOYO-1 labelled DNA. The DNA remains invisible in the AFM scans because it is not immobilized to the surface.
Figure 12.
Figure 12.
(A) A schematic of a simultaneous force spectroscopy and single molecule fluorescence experiment on a virus. An AFM tip is used for both imaging and manipulation purposes at the nanoscale. The molecular response is simultaneously tracked by imaging fluorescent markers (green) that are excited by an evanescent wave (blue). The microscope objective is shown in grey. (B) An example from a virus before and after mechanical manipulation. Top row: AFM scans (200  ×  200 nm), showing the disassembly of a virus capsid. Bottom row: fluorescence images (4  ×  4 µm) showing the release of YOYO-1 labelled DNA. The DNA remains invisible in the AFM scans because it is not immobilized to the surface.
Figure 13.
Figure 13.
(a) HS-AFM images of α3β3 subcomplex of F1-ATPase undergoing conformational changes in the presence of adenosine triphosphate (ATP). The height of a nucleotide-free β subunit is larger than those containing ATP or adenosine diphosphate. The highest pixel positions marked with red dots shift counterclockwise. At 1.44 s, the α subunit adjacent to the nucleotide-free β subunit appears higher than the β subunit. Imaging rate, 12.5 fps. (b) HS-AFM images showing spiral filament formation by polymerization of the ESCRT-III protein Snf7 on a supported lipid membrane. Imaging rate, 3 fps. (c), (d) Simultaneously captured HS-AFM (c) and total internal reflection fluorescence microscopy (d) images of Cy3-labeled chitinase A (arrows) moving unidirectionally on a chitin microfibril. Imaging rate, 3 fps.
Figure 13.
Figure 13.
(a) HS-AFM images of α3β3 subcomplex of F1-ATPase undergoing conformational changes in the presence of adenosine triphosphate (ATP). The height of a nucleotide-free β subunit is larger than those containing ATP or adenosine diphosphate. The highest pixel positions marked with red dots shift counterclockwise. At 1.44 s, the α subunit adjacent to the nucleotide-free β subunit appears higher than the β subunit. Imaging rate, 12.5 fps. (b) HS-AFM images showing spiral filament formation by polymerization of the ESCRT-III protein Snf7 on a supported lipid membrane. Imaging rate, 3 fps. (c), (d) Simultaneously captured HS-AFM (c) and total internal reflection fluorescence microscopy (d) images of Cy3-labeled chitinase A (arrows) moving unidirectionally on a chitin microfibril. Imaging rate, 3 fps.
Figure 13.
Figure 13.
(a) HS-AFM images of α3β3 subcomplex of F1-ATPase undergoing conformational changes in the presence of adenosine triphosphate (ATP). The height of a nucleotide-free β subunit is larger than those containing ATP or adenosine diphosphate. The highest pixel positions marked with red dots shift counterclockwise. At 1.44 s, the α subunit adjacent to the nucleotide-free β subunit appears higher than the β subunit. Imaging rate, 12.5 fps. (b) HS-AFM images showing spiral filament formation by polymerization of the ESCRT-III protein Snf7 on a supported lipid membrane. Imaging rate, 3 fps. (c), (d) Simultaneously captured HS-AFM (c) and total internal reflection fluorescence microscopy (d) images of Cy3-labeled chitinase A (arrows) moving unidirectionally on a chitin microfibril. Imaging rate, 3 fps.
Figure 14.
Figure 14.
Various configurations of cantilever-based NSOM. (a) Aperture NSOM relying on a specially designed cantilever chip. The tip has a small optical opening at the apex, where a localized evanescent light is produced. (b) Aperture-less NSOM based on a metal-coated cantilever tip that acts as a local electromagnetic antenna (plasmon resonator). (c) NSOM combining a small aperture with an electromagnetic nano-antenna. The nano-antenna is a metal particle with the shape of a bow-tie, rod, sphere or dumb-bell.
Figure 14.
Figure 14.
Various configurations of cantilever-based NSOM. (a) Aperture NSOM relying on a specially designed cantilever chip. The tip has a small optical opening at the apex, where a localized evanescent light is produced. (b) Aperture-less NSOM based on a metal-coated cantilever tip that acts as a local electromagnetic antenna (plasmon resonator). (c) NSOM combining a small aperture with an electromagnetic nano-antenna. The nano-antenna is a metal particle with the shape of a bow-tie, rod, sphere or dumb-bell.
Figure 14.
Figure 14.
Various configurations of cantilever-based NSOM. (a) Aperture NSOM relying on a specially designed cantilever chip. The tip has a small optical opening at the apex, where a localized evanescent light is produced. (b) Aperture-less NSOM based on a metal-coated cantilever tip that acts as a local electromagnetic antenna (plasmon resonator). (c) NSOM combining a small aperture with an electromagnetic nano-antenna. The nano-antenna is a metal particle with the shape of a bow-tie, rod, sphere or dumb-bell.
Figure 15.
Figure 15.
2D TFM. (A) Movement of marker beads in the flat elastic substrate are converted into an estimate of the cellular forces at adhesion sites. (B) An adherent U2OS-cell has many adhesion sites (marked by paxillin) and actin-based stress fibers. (C) Image processing is used to track substrate displacement. (D) Elasticity theory is used to calculate the traction stresses. (E) The image data can be used with a mechanical model for the cell to estimate forces in individual stress fibers. Reproduced from [121]. CC BY 4.0.
Figure 15.
Figure 15.
2D TFM. (A) Movement of marker beads in the flat elastic substrate are converted into an estimate of the cellular forces at adhesion sites. (B) An adherent U2OS-cell has many adhesion sites (marked by paxillin) and actin-based stress fibers. (C) Image processing is used to track substrate displacement. (D) Elasticity theory is used to calculate the traction stresses. (E) The image data can be used with a mechanical model for the cell to estimate forces in individual stress fibers. Reproduced from [121]. CC BY 4.0.
Figure 15.
Figure 15.
2D TFM. (A) Movement of marker beads in the flat elastic substrate are converted into an estimate of the cellular forces at adhesion sites. (B) An adherent U2OS-cell has many adhesion sites (marked by paxillin) and actin-based stress fibers. (C) Image processing is used to track substrate displacement. (D) Elasticity theory is used to calculate the traction stresses. (E) The image data can be used with a mechanical model for the cell to estimate forces in individual stress fibers. Reproduced from [121]. CC BY 4.0.
Figure 16.
Figure 16.
3D TFM. (A) Movement of marker beads in a 3D soft matrix are converted into an estimate of the 3D cellular displacements forces at adhesion sites. (B) A fully embedded human neutrophil (red) inside a collagen-I matrix (blue). (C) Image processing is used to track 3D matrix displacements. (D) 3D surface projections onto the cell surface for deduction of matrix displacements and strains. Cellular surface tractions can be deduced from (D) if matrix properties are known. Reproduced with permission from [120].
Figure 16.
Figure 16.
3D TFM. (A) Movement of marker beads in a 3D soft matrix are converted into an estimate of the 3D cellular displacements forces at adhesion sites. (B) A fully embedded human neutrophil (red) inside a collagen-I matrix (blue). (C) Image processing is used to track 3D matrix displacements. (D) 3D surface projections onto the cell surface for deduction of matrix displacements and strains. Cellular surface tractions can be deduced from (D) if matrix properties are known. Reproduced with permission from [120].
Figure 16.
Figure 16.
3D TFM. (A) Movement of marker beads in a 3D soft matrix are converted into an estimate of the 3D cellular displacements forces at adhesion sites. (B) A fully embedded human neutrophil (red) inside a collagen-I matrix (blue). (C) Image processing is used to track 3D matrix displacements. (D) 3D surface projections onto the cell surface for deduction of matrix displacements and strains. Cellular surface tractions can be deduced from (D) if matrix properties are known. Reproduced with permission from [120].
Figure 17.
Figure 17.
STFM applied to HeLa cell focal adhesions. (a), (b) Traction magnitude calculated from the measured confocal (a) and STED (b) recordings of the bead displacements. Scale bars, 2 µm.
Figure 17.
Figure 17.
STFM applied to HeLa cell focal adhesions. (a), (b) Traction magnitude calculated from the measured confocal (a) and STED (b) recordings of the bead displacements. Scale bars, 2 µm.
Figure 17.
Figure 17.
STFM applied to HeLa cell focal adhesions. (a), (b) Traction magnitude calculated from the measured confocal (a) and STED (b) recordings of the bead displacements. Scale bars, 2 µm.
Figure 18.
Figure 18.
Principal setup of a horizontal lipid bilayer (HLB) combined with a confocal scanning spectrometer allowing high resolution fluorescence imaging and spectroscopy [–134].
Figure 18.
Figure 18.
Principal setup of a horizontal lipid bilayer (HLB) combined with a confocal scanning spectrometer allowing high resolution fluorescence imaging and spectroscopy [–134].
Figure 18.
Figure 18.
Principal setup of a horizontal lipid bilayer (HLB) combined with a confocal scanning spectrometer allowing high resolution fluorescence imaging and spectroscopy [–134].
Figure 19.
Figure 19.
(A) shows a stack of confocal x-z scans through a LamB containing bilayer (POPC/POPE/POPS 8:1:1) after addition of 60 nM MDP-1 (cis side, buffer symmetrical (cis/trans) 1 M KCl 10 mM HEPES pH 7.2) at t  =  0 recorded with time intervals of Δt  =  2 min for each following x-z scan (total distance per scan 100 µm). (B) Recorded fluorescence intensity along the HLB z-coordinate. (B) Corresponding molecular brightness along the z-direction. (C)–(E) FCS measurements along the HLB z-coordinate. (F) Electrical single channel recording from a bilayer revealing that MDP-1 induces channel blocking only from the cis site. As shown by sequential confocal z-scans of the HLB MDP-1 when added to the cis HLB-compartment binds in a time dependent course to the bilayer (A) and (B) and remained stably bound to the membrane after repeated careful perfusion of the cis compartment (not shown). Intensity profile along the z-direction of the HLB (D) indicates that MDP-1 is stable bound to LamB in the bilayer which was confirmed by competition with non-labelled MDP which released the bound MDP-1 from the membrane (not shown).
Figure 19.
Figure 19.
(A) shows a stack of confocal x-z scans through a LamB containing bilayer (POPC/POPE/POPS 8:1:1) after addition of 60 nM MDP-1 (cis side, buffer symmetrical (cis/trans) 1 M KCl 10 mM HEPES pH 7.2) at t  =  0 recorded with time intervals of Δt  =  2 min for each following x-z scan (total distance per scan 100 µm). (B) Recorded fluorescence intensity along the HLB z-coordinate. (B) Corresponding molecular brightness along the z-direction. (C)–(E) FCS measurements along the HLB z-coordinate. (F) Electrical single channel recording from a bilayer revealing that MDP-1 induces channel blocking only from the cis site. As shown by sequential confocal z-scans of the HLB MDP-1 when added to the cis HLB-compartment binds in a time dependent course to the bilayer (A) and (B) and remained stably bound to the membrane after repeated careful perfusion of the cis compartment (not shown). Intensity profile along the z-direction of the HLB (D) indicates that MDP-1 is stable bound to LamB in the bilayer which was confirmed by competition with non-labelled MDP which released the bound MDP-1 from the membrane (not shown).
Figure 19.
Figure 19.
(A) shows a stack of confocal x-z scans through a LamB containing bilayer (POPC/POPE/POPS 8:1:1) after addition of 60 nM MDP-1 (cis side, buffer symmetrical (cis/trans) 1 M KCl 10 mM HEPES pH 7.2) at t  =  0 recorded with time intervals of Δt  =  2 min for each following x-z scan (total distance per scan 100 µm). (B) Recorded fluorescence intensity along the HLB z-coordinate. (B) Corresponding molecular brightness along the z-direction. (C)–(E) FCS measurements along the HLB z-coordinate. (F) Electrical single channel recording from a bilayer revealing that MDP-1 induces channel blocking only from the cis site. As shown by sequential confocal z-scans of the HLB MDP-1 when added to the cis HLB-compartment binds in a time dependent course to the bilayer (A) and (B) and remained stably bound to the membrane after repeated careful perfusion of the cis compartment (not shown). Intensity profile along the z-direction of the HLB (D) indicates that MDP-1 is stable bound to LamB in the bilayer which was confirmed by competition with non-labelled MDP which released the bound MDP-1 from the membrane (not shown).
Figure 20.
Figure 20.
Overview of the main electrophysiological and spectroscopic tools combined in PCF. The high variability of PCF, given by the number of possible combinations of electrophysiological and spectroscopic tools, makes it a potent approach for studying ion channels, thus overcoming the limitations of the individual techniques. Reprinted from [143], Copyright 2014, with permission from Elsevier.
Figure 20.
Figure 20.
Overview of the main electrophysiological and spectroscopic tools combined in PCF. The high variability of PCF, given by the number of possible combinations of electrophysiological and spectroscopic tools, makes it a potent approach for studying ion channels, thus overcoming the limitations of the individual techniques. Reprinted from [143], Copyright 2014, with permission from Elsevier.
Figure 20.
Figure 20.
Overview of the main electrophysiological and spectroscopic tools combined in PCF. The high variability of PCF, given by the number of possible combinations of electrophysiological and spectroscopic tools, makes it a potent approach for studying ion channels, thus overcoming the limitations of the individual techniques. Reprinted from [143], Copyright 2014, with permission from Elsevier.
Figure 21.
Figure 21.
Three examples illustrating the wide variety of combining electrophysiological and spectroscopic approaches. (A) VCF with Xenopus laevis oocytes expressing voltage-dependent potassium channels (KV1.2/2.1 chimera). Fluorescence signals arising from the incorporated unnatural amino acid Anap (red traces) and gating currents (black traces) were recorded in response to depolarizing voltage jumps. Reproduced with permission from [145]. (B) PCF combining single-particle tracking and whole-cell patch clamp. Neurons expressing P2X2FLAG–YFP receptors were labeled with QDs and imaged over time with epifluorescence optics (black trajectories). At the same time, whole-cell voltage-clamp electrophysiology (green trace) was used to measure transmembrane currents before, during and after ATP applications. Reproduced with permission from [146]. (C) PCF combining confocal laser scanning microscopy and inside-out patch-clamp configuration. Patches were excised from Xenopus laevis oocytes expressing mHCN2 channels. Fluorescently labeled cAMP (fcAMP) was applied to study ligand binding (green trace) and channel activation (black trace) in response to an activating hyperpolarizing voltage jump (black triangle). Reprinted from [147], Copyright 2010, with permission from Elsevier.
Figure 21.
Figure 21.
Three examples illustrating the wide variety of combining electrophysiological and spectroscopic approaches. (A) VCF with Xenopus laevis oocytes expressing voltage-dependent potassium channels (KV1.2/2.1 chimera). Fluorescence signals arising from the incorporated unnatural amino acid Anap (red traces) and gating currents (black traces) were recorded in response to depolarizing voltage jumps. Reproduced with permission from [145]. (B) PCF combining single-particle tracking and whole-cell patch clamp. Neurons expressing P2X2FLAG–YFP receptors were labeled with QDs and imaged over time with epifluorescence optics (black trajectories). At the same time, whole-cell voltage-clamp electrophysiology (green trace) was used to measure transmembrane currents before, during and after ATP applications. Reproduced with permission from [146]. (C) PCF combining confocal laser scanning microscopy and inside-out patch-clamp configuration. Patches were excised from Xenopus laevis oocytes expressing mHCN2 channels. Fluorescently labeled cAMP (fcAMP) was applied to study ligand binding (green trace) and channel activation (black trace) in response to an activating hyperpolarizing voltage jump (black triangle). Reprinted from [147], Copyright 2010, with permission from Elsevier.
Figure 21.
Figure 21.
Three examples illustrating the wide variety of combining electrophysiological and spectroscopic approaches. (A) VCF with Xenopus laevis oocytes expressing voltage-dependent potassium channels (KV1.2/2.1 chimera). Fluorescence signals arising from the incorporated unnatural amino acid Anap (red traces) and gating currents (black traces) were recorded in response to depolarizing voltage jumps. Reproduced with permission from [145]. (B) PCF combining single-particle tracking and whole-cell patch clamp. Neurons expressing P2X2FLAG–YFP receptors were labeled with QDs and imaged over time with epifluorescence optics (black trajectories). At the same time, whole-cell voltage-clamp electrophysiology (green trace) was used to measure transmembrane currents before, during and after ATP applications. Reproduced with permission from [146]. (C) PCF combining confocal laser scanning microscopy and inside-out patch-clamp configuration. Patches were excised from Xenopus laevis oocytes expressing mHCN2 channels. Fluorescently labeled cAMP (fcAMP) was applied to study ligand binding (green trace) and channel activation (black trace) in response to an activating hyperpolarizing voltage jump (black triangle). Reprinted from [147], Copyright 2010, with permission from Elsevier.
Figure 22.
Figure 22.
A platform for simultaneous in vitro fMRI and FI. (a) This system is based on an open MRI at 0.32 T (bottom table), a brain slice chamber with constant nutrient flow (middle) and a camera (top) for detection of fluorescence. (b) Two surface coils placed below and over the slices, (c) microscope image of the brain slice, (d) simulated excitation profile of the coils. [155] John Wiley & Sons. Copyright © 2015 John Wiley & Sons, Ltd.
Figure 22.
Figure 22.
A platform for simultaneous in vitro fMRI and FI. (a) This system is based on an open MRI at 0.32 T (bottom table), a brain slice chamber with constant nutrient flow (middle) and a camera (top) for detection of fluorescence. (b) Two surface coils placed below and over the slices, (c) microscope image of the brain slice, (d) simulated excitation profile of the coils. [155] John Wiley & Sons. Copyright © 2015 John Wiley & Sons, Ltd.
Figure 22.
Figure 22.
A platform for simultaneous in vitro fMRI and FI. (a) This system is based on an open MRI at 0.32 T (bottom table), a brain slice chamber with constant nutrient flow (middle) and a camera (top) for detection of fluorescence. (b) Two surface coils placed below and over the slices, (c) microscope image of the brain slice, (d) simulated excitation profile of the coils. [155] John Wiley & Sons. Copyright © 2015 John Wiley & Sons, Ltd.
Figure 23.
Figure 23.
A proof-of-concept ex vivo platform for TPM and MRI at 16.4 T. The laser scanning module (upper left corner) was located outside the 16.4 T magnet room and the excitation laser beam was guided into the in-MRI imaging module (centre image) using fibreoptics. Simultaneous view of whole mouse brain using TPM (top right corner) and MRI (bottom right corner). Reproduced from [157] CC BY 4.0.
Figure 23.
Figure 23.
A proof-of-concept ex vivo platform for TPM and MRI at 16.4 T. The laser scanning module (upper left corner) was located outside the 16.4 T magnet room and the excitation laser beam was guided into the in-MRI imaging module (centre image) using fibreoptics. Simultaneous view of whole mouse brain using TPM (top right corner) and MRI (bottom right corner). Reproduced from [157] CC BY 4.0.
Figure 23.
Figure 23.
A proof-of-concept ex vivo platform for TPM and MRI at 16.4 T. The laser scanning module (upper left corner) was located outside the 16.4 T magnet room and the excitation laser beam was guided into the in-MRI imaging module (centre image) using fibreoptics. Simultaneous view of whole mouse brain using TPM (top right corner) and MRI (bottom right corner). Reproduced from [157] CC BY 4.0.
Figure 24.
Figure 24.
Scanning x-ray microscopy using a micro- or nano-focused beam. (a) Fluorescence microscopy shows the actin fiber distribution that is pixelwise analysed in (b). (c) Composite image of the scan area including the two rescaled eigenvectors (gray and black) from PCA. (d) Total SAXS signal provides an x-ray darkfield map and (e) anisotropy from PCA for each pixel. (f) Radial intensity profiles can be fitted to get more information in terms of form and structure factors. Reproduced from [163]. © 2017 IOP Publishing Ltd and Deutsche Physikalische Gesellschaft. CC BY 3.0.
Figure 24.
Figure 24.
Scanning x-ray microscopy using a micro- or nano-focused beam. (a) Fluorescence microscopy shows the actin fiber distribution that is pixelwise analysed in (b). (c) Composite image of the scan area including the two rescaled eigenvectors (gray and black) from PCA. (d) Total SAXS signal provides an x-ray darkfield map and (e) anisotropy from PCA for each pixel. (f) Radial intensity profiles can be fitted to get more information in terms of form and structure factors. Reproduced from [163]. © 2017 IOP Publishing Ltd and Deutsche Physikalische Gesellschaft. CC BY 3.0.
Figure 24.
Figure 24.
Scanning x-ray microscopy using a micro- or nano-focused beam. (a) Fluorescence microscopy shows the actin fiber distribution that is pixelwise analysed in (b). (c) Composite image of the scan area including the two rescaled eigenvectors (gray and black) from PCA. (d) Total SAXS signal provides an x-ray darkfield map and (e) anisotropy from PCA for each pixel. (f) Radial intensity profiles can be fitted to get more information in terms of form and structure factors. Reproduced from [163]. © 2017 IOP Publishing Ltd and Deutsche Physikalische Gesellschaft. CC BY 3.0.
Figure 25.
Figure 25.
Correlating fluorescence and x-ray scattering anisotropy. (a) Most significant filaments determined by the filament sensor from a fluorescence micrograph of neonatal rat cardiac tissue. (b) PCA-results of a nano-diffraction scan showing the order parameter Ωpa (grey scale) and filament orientation θpa. (c) Histogram of the angular deviation between both methods revealing excellent correlation. Reproduced from [163]. © 2017 IOP Publishing Ltd and Deutsche Physikalische Gesellschaft. CC BY 3.0.
Figure 25.
Figure 25.
Correlating fluorescence and x-ray scattering anisotropy. (a) Most significant filaments determined by the filament sensor from a fluorescence micrograph of neonatal rat cardiac tissue. (b) PCA-results of a nano-diffraction scan showing the order parameter Ωpa (grey scale) and filament orientation θpa. (c) Histogram of the angular deviation between both methods revealing excellent correlation. Reproduced from [163]. © 2017 IOP Publishing Ltd and Deutsche Physikalische Gesellschaft. CC BY 3.0.
Figure 25.
Figure 25.
Correlating fluorescence and x-ray scattering anisotropy. (a) Most significant filaments determined by the filament sensor from a fluorescence micrograph of neonatal rat cardiac tissue. (b) PCA-results of a nano-diffraction scan showing the order parameter Ωpa (grey scale) and filament orientation θpa. (c) Histogram of the angular deviation between both methods revealing excellent correlation. Reproduced from [163]. © 2017 IOP Publishing Ltd and Deutsche Physikalische Gesellschaft. CC BY 3.0.

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References

    1. de Boer P, Hoogenboom J P, Giepmans B N G. Correlated light and electron microscopy: ultrastructure lights up! Nat. Methods. 2015;12:503–13. doi: 10.1038/nmeth.3400. - DOI - PubMed
    1. Timmermans F J, Otto C. Review of integrated light and electron microscopy. Rev. Sci. Instrum. 2015;86:011501 doi: 10.1063/1.4905434. - DOI - PubMed
    1. Agronskaia A V, Valentijn J A, van Driel L F, Schneijdenberg C T W M, Humbel B M, van Bergen en Henegouwen P M P, Verkleij A J, Koster A J, Gerritsen H C. Integrated fluorescence and transmission electron microscopy. J. Struct. Biol. 2008;164:183–9. doi: 10.1016/j.jsb.2008.07.003. - DOI - PubMed
    1. Karreman M A, Agronskaia A V, van Donselaar E G, Vocking K, Fereidouni F, Humbel B M, Verrips C T, Verkleij A J, Gerritsen H C. Optimizing immuno-labeling for correlative fluorescence and electron microscopy on a single specimen. J. Struct. Biol. 2012;180:382–6. doi: 10.1016/j.jsb.2012.09.002. - DOI - PubMed
    1. Kukulski W, Schorb M, Welsch S, Picco A, Kaksonen M, Briggs J A G. Correlated fluorescence and 3D electron microscopy with high sensitivity and spatial precision. J. Cell Biol. 2011;192:111–9. doi: 10.1083/jcb.201009037. - DOI - PMC - PubMed

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