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Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
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Managing the Introduction of Super-Resolution Microscopy into a Core Facility
Jeffrey A Kamykowski1, Brian Storrie2
1Digital Microscopy Laboratory, Department of Physiology and Biophysics, Slot 505, University of Arkansas for Medical Sciences, 4301 West Markham St, Little Rock, AR, 72202, USA.
Methods in Molecular Biology (Clifton, N.J.)
|September 20, 2017
Summary
Super resolution microscopy enhances fluorescence imaging, with structured illumination offering accessible 100 nm resolution using existing dyes. Other methods like PALM/STORM and STED require new dyes and more training.
Area of Science:
- Microscopy and imaging technologies
- Cell biology and molecular imaging
Background:
- Super resolution microscopy techniques aim to improve the resolution of fluorescence microscopy.
- Current methods approach the scale of cellular structures and molecular machinery.
Purpose of the Study:
- To compare different super resolution microscopy techniques.
- To highlight the trade-offs between resolution, ease of use, and required resources.
Main Methods:
- Structured illumination microscopy (SIM) offers near-field resolution with existing dyes.
- Stochastic optical reconstruction microscopy (STORM) and photoactivated localization microscopy (PALM) require new dyes and have a steeper learning curve.
- Stimulated emission depletion (STED) microscopy also necessitates new dyes.
Main Results:
- Structured illumination microscopy achieves resolutions approaching 100 nm in the XY plane.
- Stochastic methods offer potential for fivefold higher resolution but demand significant user expertise.
- Stimulated depletion techniques provide another route to enhanced resolution.
Conclusions:
- Each super resolution technique presents distinct advantages and challenges.
- Structured illumination is more accessible for users familiar with conventional microscopy.
- Significant investment in equipment and training is common across advanced super resolution methods.
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