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Super-resolution molecular and functional imaging of nanoscale architectures in life and materials science.

Habuchi S - Front Bioeng Biotechnol (2014)

Bottom Line: Super-resolution (SR) fluorescence microscopy has been revolutionizing the way in which we investigate the structures, dynamics, and functions of a wide range of nanoscale systems.I discuss the applications of SR microscopy in the fields of life science and materials science with a special emphasis on quantitative molecular imaging and nanoscale functional imaging.These studies open new opportunities for unraveling the physical, chemical, and optical properties of a wide range of nanoscale architectures together with their nanostructures and will enable the development of new (bio-)nanotechnology.

View Article: PubMed Central - PubMed

Affiliation: Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology , Jeddah , Saudi Arabia.

ABSTRACT
Super-resolution (SR) fluorescence microscopy has been revolutionizing the way in which we investigate the structures, dynamics, and functions of a wide range of nanoscale systems. In this review, I describe the current state of various SR fluorescence microscopy techniques along with the latest developments of fluorophores and labeling for the SR microscopy. I discuss the applications of SR microscopy in the fields of life science and materials science with a special emphasis on quantitative molecular imaging and nanoscale functional imaging. These studies open new opportunities for unraveling the physical, chemical, and optical properties of a wide range of nanoscale architectures together with their nanostructures and will enable the development of new (bio-)nanotechnology.

No MeSH data available.


Related in: MedlinePlus

Quantitative super-resolution fluorescence imaging. (A) (Top left) PALM image of transferrin receptor (TfR) across the plasma membrane of COS7 cells. A photoactivatable fluorescent protein PAGFP is fused to TfR; (top right) plot of calculated autocorrelation function [g(r)peaks] of PAGFP molecules in the PALM image. g(r)stoch and g(r)protein are the correlation owing to multiple appearances of a single protein and the protein correlation. The cluster size and average numbers of the molecule in clusters are estimated by a fitting of the autocorrelation plot with an exponential decaying function; (bottom) size and number of molecules in clusters of a transmembrane protein, Lat (Sengupta et al., 2011). (B) (Top) bright-field microscopy, wide-field fluorescence microscopy, and PALM images of a flagellar motor protein, FliM, in bacterial cells. A photoconvertable fluorescent protein Dendra2 is fused to FliM; (bottom) frequency histogram of number of FliM molecules in each cluster determined using the Fermi activation with optimal tolerance time (blue bars). The red bars show the histogram without optimizing the tolerance time (Lee et al., 2012). Reproduced with permission from Sengupta et al. (2011), copyright 2011, Nature Publishing Group (A), and Lee et al. (2012), copyright 2012, National Academy of Science, USA (B).
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Figure 3: Quantitative super-resolution fluorescence imaging. (A) (Top left) PALM image of transferrin receptor (TfR) across the plasma membrane of COS7 cells. A photoactivatable fluorescent protein PAGFP is fused to TfR; (top right) plot of calculated autocorrelation function [g(r)peaks] of PAGFP molecules in the PALM image. g(r)stoch and g(r)protein are the correlation owing to multiple appearances of a single protein and the protein correlation. The cluster size and average numbers of the molecule in clusters are estimated by a fitting of the autocorrelation plot with an exponential decaying function; (bottom) size and number of molecules in clusters of a transmembrane protein, Lat (Sengupta et al., 2011). (B) (Top) bright-field microscopy, wide-field fluorescence microscopy, and PALM images of a flagellar motor protein, FliM, in bacterial cells. A photoconvertable fluorescent protein Dendra2 is fused to FliM; (bottom) frequency histogram of number of FliM molecules in each cluster determined using the Fermi activation with optimal tolerance time (blue bars). The red bars show the histogram without optimizing the tolerance time (Lee et al., 2012). Reproduced with permission from Sengupta et al. (2011), copyright 2011, Nature Publishing Group (A), and Lee et al. (2012), copyright 2012, National Academy of Science, USA (B).

Mentions: The spatial distribution of membrane proteins is believed to play an important role in many ligand–receptor binding systems, such as cell adhesion. Since the spatial locations of individual molecules can be determined with a precision of approximately 10 nm in SR localization microscopy, the spatial distribution of individual molecules [e.g., transferrin receptor (TfR) across the plasma membrane, see Figure 3A (Sengupta et al., 2011)] can be characterized quantitatively using statistical analysis (Owen et al., 2010; Scarselli et al., 2012; Veatch et al., 2012; Malkusch et al., 2013). The size of the TfR cluster in the membrane (~150 nm in radius) is estimated roughly from the autocorrelation function [g(r)protein] obtained by pair correlation analysis of the spatial distribution of the individual molecules. This analysis allows a quantitative estimation of the size of molecular clusters together with the average number of molecules in a cluster (Sengupta et al., 2011). Although in principle the quantitative determination of the number of molecules in a cluster is possible, in practice this is not straightforward due to the blinking behavior of most of the fluorophores. To achieve such quantitative determination, a single-molecule counting method has been developed, which enables determination of the number of the molecules within diffraction-limited space with high accuracy (Lee et al., 2012). In this method, the counting error is minimized by temporally modulating the intensity of the activation laser (i.e., Fermi activation), which maximally separates the activation of the different molecules together with optimizing the tolerance time τc which is the characteristic time of the blinking. Using this approach, the number of photoconvertable proteins, which are fused to a flagellar motor protein, FliM, has been determined accurately along with obtaining an SR image of FliM in the cells (Figure 3B) (Lee et al., 2012). The development of less blinking fluorophores will further improve the accuracy of counting the number of the molecules.


Super-resolution molecular and functional imaging of nanoscale architectures in life and materials science.

Habuchi S - Front Bioeng Biotechnol (2014)

Quantitative super-resolution fluorescence imaging. (A) (Top left) PALM image of transferrin receptor (TfR) across the plasma membrane of COS7 cells. A photoactivatable fluorescent protein PAGFP is fused to TfR; (top right) plot of calculated autocorrelation function [g(r)peaks] of PAGFP molecules in the PALM image. g(r)stoch and g(r)protein are the correlation owing to multiple appearances of a single protein and the protein correlation. The cluster size and average numbers of the molecule in clusters are estimated by a fitting of the autocorrelation plot with an exponential decaying function; (bottom) size and number of molecules in clusters of a transmembrane protein, Lat (Sengupta et al., 2011). (B) (Top) bright-field microscopy, wide-field fluorescence microscopy, and PALM images of a flagellar motor protein, FliM, in bacterial cells. A photoconvertable fluorescent protein Dendra2 is fused to FliM; (bottom) frequency histogram of number of FliM molecules in each cluster determined using the Fermi activation with optimal tolerance time (blue bars). The red bars show the histogram without optimizing the tolerance time (Lee et al., 2012). Reproduced with permission from Sengupta et al. (2011), copyright 2011, Nature Publishing Group (A), and Lee et al. (2012), copyright 2012, National Academy of Science, USA (B).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4126472&req=5

Figure 3: Quantitative super-resolution fluorescence imaging. (A) (Top left) PALM image of transferrin receptor (TfR) across the plasma membrane of COS7 cells. A photoactivatable fluorescent protein PAGFP is fused to TfR; (top right) plot of calculated autocorrelation function [g(r)peaks] of PAGFP molecules in the PALM image. g(r)stoch and g(r)protein are the correlation owing to multiple appearances of a single protein and the protein correlation. The cluster size and average numbers of the molecule in clusters are estimated by a fitting of the autocorrelation plot with an exponential decaying function; (bottom) size and number of molecules in clusters of a transmembrane protein, Lat (Sengupta et al., 2011). (B) (Top) bright-field microscopy, wide-field fluorescence microscopy, and PALM images of a flagellar motor protein, FliM, in bacterial cells. A photoconvertable fluorescent protein Dendra2 is fused to FliM; (bottom) frequency histogram of number of FliM molecules in each cluster determined using the Fermi activation with optimal tolerance time (blue bars). The red bars show the histogram without optimizing the tolerance time (Lee et al., 2012). Reproduced with permission from Sengupta et al. (2011), copyright 2011, Nature Publishing Group (A), and Lee et al. (2012), copyright 2012, National Academy of Science, USA (B).
Mentions: The spatial distribution of membrane proteins is believed to play an important role in many ligand–receptor binding systems, such as cell adhesion. Since the spatial locations of individual molecules can be determined with a precision of approximately 10 nm in SR localization microscopy, the spatial distribution of individual molecules [e.g., transferrin receptor (TfR) across the plasma membrane, see Figure 3A (Sengupta et al., 2011)] can be characterized quantitatively using statistical analysis (Owen et al., 2010; Scarselli et al., 2012; Veatch et al., 2012; Malkusch et al., 2013). The size of the TfR cluster in the membrane (~150 nm in radius) is estimated roughly from the autocorrelation function [g(r)protein] obtained by pair correlation analysis of the spatial distribution of the individual molecules. This analysis allows a quantitative estimation of the size of molecular clusters together with the average number of molecules in a cluster (Sengupta et al., 2011). Although in principle the quantitative determination of the number of molecules in a cluster is possible, in practice this is not straightforward due to the blinking behavior of most of the fluorophores. To achieve such quantitative determination, a single-molecule counting method has been developed, which enables determination of the number of the molecules within diffraction-limited space with high accuracy (Lee et al., 2012). In this method, the counting error is minimized by temporally modulating the intensity of the activation laser (i.e., Fermi activation), which maximally separates the activation of the different molecules together with optimizing the tolerance time τc which is the characteristic time of the blinking. Using this approach, the number of photoconvertable proteins, which are fused to a flagellar motor protein, FliM, has been determined accurately along with obtaining an SR image of FliM in the cells (Figure 3B) (Lee et al., 2012). The development of less blinking fluorophores will further improve the accuracy of counting the number of the molecules.

Bottom Line: Super-resolution (SR) fluorescence microscopy has been revolutionizing the way in which we investigate the structures, dynamics, and functions of a wide range of nanoscale systems.I discuss the applications of SR microscopy in the fields of life science and materials science with a special emphasis on quantitative molecular imaging and nanoscale functional imaging.These studies open new opportunities for unraveling the physical, chemical, and optical properties of a wide range of nanoscale architectures together with their nanostructures and will enable the development of new (bio-)nanotechnology.

View Article: PubMed Central - PubMed

Affiliation: Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology , Jeddah , Saudi Arabia.

ABSTRACT
Super-resolution (SR) fluorescence microscopy has been revolutionizing the way in which we investigate the structures, dynamics, and functions of a wide range of nanoscale systems. In this review, I describe the current state of various SR fluorescence microscopy techniques along with the latest developments of fluorophores and labeling for the SR microscopy. I discuss the applications of SR microscopy in the fields of life science and materials science with a special emphasis on quantitative molecular imaging and nanoscale functional imaging. These studies open new opportunities for unraveling the physical, chemical, and optical properties of a wide range of nanoscale architectures together with their nanostructures and will enable the development of new (bio-)nanotechnology.

No MeSH data available.


Related in: MedlinePlus