(direct) stochastic optical reconstruction microscopy ((d)STORM)
[2, 3], photoactivated localization microscopy (PALM) [4], and
point accumulation for imaging in nanoscale topography (PAINT)
[5], has proven to produce the highest resolution even using basic
optical setups and common sample preparation protocols. SMLM
relies on stochastic switching of fluorophores between a fluorescently active “on” and a fluorescently inactive “dark” state that can
be controlled by the intensity of the excitation light and composition of the sample mounting medium. Using appropriate buffer
and imaging conditions, many different fluorophores can be made
suitable for SMLM, including organic fluorophores [6] and fluorescent proteins [7]. SMLM not only provides super-resolution
images but also gives access to properties of individual molecules,
allowing cluster analysis [8], segmentation [9], colocalization estimation [10], molecular counting [11], and probing of stoichiometry of macromolecular complexes [12].
In this chapter, we describe how to perform a typical dSTORM
experiment from sample preparation to image acquisition and data
processing, which includes event list generation, image reconstruction and post-processing of SMLM data that can eventually be
analyzed and segmented by 2D and 3D clustering methods.
2 Materials
2.1 Cell Culture
and Immunolabeling
In addition to your favorite adherent cell line, you need:
1. Glass-bottom petri dishes with a diameter of 35 mm for cell
culture (CELLView, Greiner Bio-One).
2. Phosphate-buffered saline (PBS), 1 and 10 times concentrated
(PBS 1Â and 10Â).
3. Paraformaldehyde (PFA) 4% solution in PBS.
4. 0.1% Triton X-100 in PBS (PBS/Tx).
5. Primary antibody.
6. Secondary antibody coupled to compatible fluorophores
(if primary antibody was not directly labeled).
7. Bovine serum albumin (BSA).
8. Normal goat serum (NGS).
9. Fetal bovine serum (FBS).
Compatible fluorophores:
Alexa Fluor family (Thermo Fisher Scientific): Alexa
647 (the most commonly used fluorophore for SMLM),
Alexa 555, Alexa 532, Alexa 488; Atto 488 (ATTO-TEC
GmbH); Cy3B [13] and others [6].
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Leonid Andronov et al.
[2, 3], photoactivated localization microscopy (PALM) [4], and
point accumulation for imaging in nanoscale topography (PAINT)
[5], has proven to produce the highest resolution even using basic
optical setups and common sample preparation protocols. SMLM
relies on stochastic switching of fluorophores between a fluorescently active “on” and a fluorescently inactive “dark” state that can
be controlled by the intensity of the excitation light and composition of the sample mounting medium. Using appropriate buffer
and imaging conditions, many different fluorophores can be made
suitable for SMLM, including organic fluorophores [6] and fluorescent proteins [7]. SMLM not only provides super-resolution
images but also gives access to properties of individual molecules,
allowing cluster analysis [8], segmentation [9], colocalization estimation [10], molecular counting [11], and probing of stoichiometry of macromolecular complexes [12].
In this chapter, we describe how to perform a typical dSTORM
experiment from sample preparation to image acquisition and data
processing, which includes event list generation, image reconstruction and post-processing of SMLM data that can eventually be
analyzed and segmented by 2D and 3D clustering methods.
2 Materials
2.1 Cell Culture
and Immunolabeling
In addition to your favorite adherent cell line, you need:
1. Glass-bottom petri dishes with a diameter of 35 mm for cell
culture (CELLView, Greiner Bio-One).
2. Phosphate-buffered saline (PBS), 1 and 10 times concentrated
(PBS 1Â and 10Â).
3. Paraformaldehyde (PFA) 4% solution in PBS.
4. 0.1% Triton X-100 in PBS (PBS/Tx).
5. Primary antibody.
6. Secondary antibody coupled to compatible fluorophores
(if primary antibody was not directly labeled).
7. Bovine serum albumin (BSA).
8. Normal goat serum (NGS).
9. Fetal bovine serum (FBS).
Compatible fluorophores:
Alexa Fluor family (Thermo Fisher Scientific): Alexa
647 (the most commonly used fluorophore for SMLM),
Alexa 555, Alexa 532, Alexa 488; Atto 488 (ATTO-TEC
GmbH); Cy3B [13] and others [6].
272
Leonid Andronov et al.