Details

Autor(en) / Beteiligte

• Chen, Jie
• Liu, Wenjuan
• Xu, Zhaochao

Titel

Comparison and progress review of various super-resolution fluorescence imaging techniques

Ist Teil von

• Sepu, 2021-10, Vol.39 (10), p.1055

Ort / Verlag

China

Erscheinungsjahr

2021

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• "Seeing is believing" is the central philosophy of life science research, which runs through the continuous understanding of individual molecules, molecular complexes, molecular dynamic behavior, and the entire molecular network. Living and dynamic molecules are functional in nature; therefore, fluorescence microscopy has emerged as an irreplaceable tool in life science research. However, when fluorescence imaging is performed at the molecular level, some artificial signals may lead to erroneous experimental results. This obstacle is due to the limitation of the optical diffraction limit, and the fluorescence microscope cannot distinguish the target in the diffraction-limited space. Super-resolution fluorescence imaging technology breaks through the diffraction limit, allows visualization of biomolecules at the nanometer scale to the single-molecule level, and allows us to study the structure and dynamic processes of living cells with unprecedented spatial and temporal resolution. It has become a powerful tool for life science research and is gradually being applied to material science, catalytic reaction processes, and photolithography as well. The principle of super-resolution imaging technologies is different; therefore, it has different technical performances, thus limiting their specific technical characteristics and application scope. Current mainstream super-resolution imaging technologies can be classified into three types: structured illumination microscopy (SIM), stimulated emission depletion (STED), and single-molecule localization microscopy (SMLM). These microscopes use different complex technologies, but the strategy is the same and simple, i.e. two adjacent luminous points in a diffraction-limited space can be spatially resolved by time resolution. SIM has been used for three-dimensional real-time imaging in multicellular organisms; however, compared with other technologies, its lower horizontal and vertical resolutions need to be further optimized. STED is limited by its small imaging field of view and high photobleaching; however, the best time resolution can be considered at a high spatial resolution, and it has been proven that three-color STED imaging can be performed. In SMLM super-resolution imaging, the time resolution is affected by the time required to locate all fluorophores, which is closely related to the switching and luminescence properties of the fluorophore. With the improvement in horizontal and vertical resolution of imaging, the image acquisition speed, photobleaching characteristics, and the possibility of multi-color and dynamic imaging have increasingly become the key determinants of super-resolution fluorescence imaging. Thus far, the main use of super-resolution imaging technology has been focused on biological applications for studying structural changes less than 200 nm in dimension. In addition to the combination of structural and morphological characterization with biomolecular detection and identification, super-resolution imaging technology is rapidly expanding into the fields of interaction mapping, multi-target detection, and real-time imaging. In the latter applications, super-resolution imaging technology is particularly advantageous because of more flexible sample staining, higher labeling efficiency, faster and simpler readings, and gentler sample preparation procedures. In this article, we compare the principles of these three technologies and introduce their application progress in biology. We expect the results described herein will help researchers clarify the technical advantages and applicable application directions of different super-resolution imaging technologies, thus facilitating researchers in making reasonable choices in future research.