Super-resolution microscopy

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Introduction to Super Resolution Microscopy

The diffraction limit defined by Abbe (1873) corresponds to the radius of the spot where the light is diffracted. The Abbe diffraction limit depends on the light wavelength (λ), the refractive index of the medium (n) and the half-angle of the converging spot (ϴ). One limiting parameter is the numerical aperture (NA) and nowadays best optics reach about 1.4 NA leading to an Abbe limit of λ/2NA i.e. 0.25µm (for green light at 500nm) (200nm laterally/ 500nm axially). This is much higher than the resolution needed to observe and discriminate between different single molecules or compounds inside a cell. Super-resolution microscopy (SRM)  allows scientists to pass the diffraction limit of light, giving them the chance to observe cellular structures at the nanometer scale [1], from entire organelles to individual proteins.

The super resolution microscopy techniques can be mainly classified into two groups that differ in lateral/axial resolution and in their inherent maximal temporal resolution. First are the patterned light illumination techniques such as Stimulated Emission Depletion (STED) and Structured Illumination Microscopy (SIM). Second are localization-based techniques which include Stochastic Optical Reconstruction Microscopy (STORM) and Photo-activation Localization Microscopy (PALM).

Super-resolution microscopy Comparation techniques
Figure 1: Scheme of spatial Resolution of biological Imaging Techniques [2]
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Super resolution: Stimulated Emission Depletion (STED) microscopy

The Stimulated Emission Depletion (STED) microscopy technique’s principle is to generate super resolution microscopy images by selectively deactivating fluorophores which minimizes the area of illumination and enhances the obtainable resolution.

Figure 2: Scheme showing the STED principle [3]

Super resolution: Stochastic Optical Reconstruction Microscopy (STORM)

The Stochastic Optical Reconstruction microscopy or STORM is a super resolution microscopy technique that uses sequential activation and time resolved location of fluorophores that are photo-switchable to obtain images with higher resolution.

Figure 4: Scheme of the principle behind the STORM, the location-based super-resolution microscopy technique [4,5].

Super-resolution: Photoactivated localization microscopy (PALM)

Even if the PALM and STORM techniques are very similar, the PALM one uses fluorescent proteins that are optically highlighted to stochastically switch on a sub-population of molecules to obtain a sequential single-molecule readout [6,7].

Figure 5: Scheme of the PALM technique [8].
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[1] Sydor AM, Czymmek KJ, Puchner EM, Mennella V. Super-Resolution Microscopy: From Single Molecules to Supramolecular Assemblies. Trends Cell Biol [Internet]. 2015 [cited 2017 Jun 15];25:730–48.

[2] ZEISS Microscopy Online Campus | Introduction to Superresolution Microscopy [Internet]. [cited 2017 Jun 22].

[3] S. J, A. J. Advanced Optical Imaging of Endocytosis. In: Molecular Regulation of Endocytosis [Internet]. InTech; 2012 [cited 2017 Jun 21].

[4] Kamiyama D, Huang B. Development in the STORM. Dev Cell [Internet]. 2012 Dec [cited 2017 Jun 21];23(6):1103–10.

[5] Huang B, Babcock H, Zhuang X. Breaking the Diffraction Barrier: Super-Resolution Imaging of Cells. Cell [Internet]. 2010 Dec [cited 2017 Jun 21];143(7):1047–58.

[6] Hess ST, Girirajan TPK, Mason MD. Ultra-High Resolution Imaging by Fluorescence Photoactivation Localization Microscopy. Biophys J [Internet]. 2006 Dec [cited 2017 Jun 21];91(11):4258–72.

[7] Henriques R, Mhlanga MM. PALM and STORM: What hides beyond the Rayleigh limit? Biotechnol J [Internet]. 2009 Jun [cited 2017 Jun 21];4(6):846–57.

[8] Habuchi S. Super-Resolution Molecular and Functional Imaging of Nanoscale Architectures in Life and Materials Science. Front Bioeng Biotechnol [Internet]. 2014 Jun 12 [cited 2017 Jun 21];2:20.[/vc_column_text][/vc_column][vc_column width=”1/3″][vc_team title=”Written by Pablo Salaverria” subtitle=”PHD STUDENT | INNOVATION UNIT | H2020-MSCA-ITN-DIVIDE” image=”7073″]

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