Super-resolution microscopy: a brief history and new avenues

Abstract

Super-resolution microscopy (SRM) is a fast-developing field that encompasses fluorescence imaging techniques with the capability to resolve objects below the classical diffraction limit of optical resolution. Acknowledged with the Nobel prize in 2014, numerous SRM methods have meanwhile evolved and are being widely applied in biomedical research, all with specific strengths and shortcomings. While some techniques are capable of nanometre-scale molecular resolution, others are geared towards volumetric three-dimensional multi-colour or fast live-cell imaging. In this editorial review, we pick on the latest trends in the field. We start with a brief historical overview of both conceptual and commercial developments. Next, we highlight important parameters for imaging successfully with a particular super-resolution modality. Finally, we discuss the importance of reproducibility and quality control and the significance of open-source tools in microscopy. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 2)'.

Small training dataset convolutional neural networks for application-specific super-resolution microscopy

“…In this case, the ML model works as an inverse problem to detect the upsampled/up-scaled (HR) image from the down-sampled/down-scaled (LR) images. In contrast, in the case of optical microscopy, the low-resolution images are captured using an instrument that cannot separate close-by cells/samples 76 . Typically, this instrument is low in cost with limited resolution.…”

Structural Investigation of Therapeutic Antibodies Using Hydroxyl Radical Protein Footprinting Methods

“…In parallel, high-resolution structural biology characterization methods continue to improve, with recent significant advances in cryoEM structural resolution [ 9 ] and continual advances in X-ray and electron diffraction methods [ 10 ], as well as nuclear magnetic resonance (NMR) methods [ 11 ], and thousands of structures of antibodies or antibody fragments are currently available in Protein Data Bank [ 12 ]. Other imaging methods, such as fluorescence microscopy, have continued to make improvements in achievable resolution [ 13 ], while computational tools are also widely used in antibody development to predict protein interfaces and assess biophysical characteristics such as immunogenicity or solubility. Protein modeling recently made a significant leap in successful structure prediction with AlphaFold [ 14 ] as well as RoseTTAFold [ 15 ].…”

Super resolution live imaging: The key for unveiling the true dynamics of membrane traffic around the Golgi apparatus in plant cells

“…As Ernst Abbe and Lord Rayleigh formulated in the 19 th century, the resolution of microscopy is limited to approximately half of the wavelength of the light, meaning that objects closer than about 200 nm cannot be resolved even with perfect lenses as long as we use the visible light. In this respect, the light microscopy is far less advantageous than the electron microscopy, which uses electrons with a 10 5 times smaller wavelength (Schermelleh et al, 2010;Prakash et al, 2022).…”

“…Among them, the most famous are the Nobel prize-winning methods called stimulated emission depletion (STED), structured illumination microscopy (SIM), and photoactivated localization microscopy or stochastic optical reconstruction microscopy (PALM/STORM). Each of them realizes the super-resolution less than 100 nm in XY plane by unique techniques taking advantage of the physical nature of the light or fluorescent proteins (Prakash et al, 2022). In addition, microscopy companies have developed easy-to-use "soft superresolution" methods that can be added to conventional confocal systems, such as ZEISS Airyscan with the resolution 1.7 times better than the diffraction limit (Huff, 2015).…”

“…The low acquisition rate is also a bottleneck for 3D observation, while the organelles and carriers move around in 3D. Some of the systems have also a limitation in the multicolor acquisition with more than two colors, which means that for example there is a high hurdle for the observation of a cargo transported between two different organelles (Colin et al, 2021;Prakash et al, 2022).…”