Liquid–liquid phase separation (LLPS) is an emerging phenomenon involved in various biological processes. The formation of phase-separated condensates is crucial for many intrinsically disordered proteins to fulfill their biological functions. Using the recombinant protein to reconstitute the formation of condensates in vitro has become the standard method to investigate the behavior and function of LLPS. Meanwhile, there is an urgent need to characterize the LLPS in living cells. Importantly, condensates formed through LLPS at physical relevant concentrations are often smaller than the optical diffraction limit, which makes precise characterization and quantification inaccurate due to the scatter of light. The booming development of super-resolution optical microscopy enables the visualization of multiple obscured subcellular components and processes, which is also suitable for the LLPS research. In this protocol, we provide step-by-step instructions to help users take advantage of super-resolution imaging to depict the morphology and quantify the molecule number of endogenous condensates in living cells using RNA Pol II as an example. This streamlined workflow offers exceptional robustness, sensitivity, and precision, which could be easily implemented in any laboratory with an inverted total internal reflection microscope. We expect that super-resolution microscopy will contribute to the investigation of both large and tiny condensates under physiological and pathological conditions and lead our understanding of the mechanism of LLPS to a higher and deeper layer.

When imaging the nucleus structure of a cell, the out-of-focus fluorescence acts as background and hinders the detection of weak signals. Light-sheet fluorescence microscopy (LSFM) is a wide-field imaging approach which has the best of both background removal and imaging speed. However, the commonly adopted orthogonal excitation/detection scheme is hard to be applied to single-cell imaging due to steric hindrance. For LSFMs capable of high spatiotemporal single-cell imaging, the complex instrument design and operation largely limit their throughput of data collection. Here, we propose an approach for high-throughput background-free fluorescence imaging of single cells facilitated by the Immersion Tilted Light Sheet Microscopy (ImTLSM). ImTLSM is based on a light-sheet projected off the optical axis of a water immersion objective. With the illumination objective and the detection objective placed opposingly, ImTLSM can rapidly patrol and optically section multiple individual cells while maintaining single-molecule detection sensitivity and resolution. Further, the simplicity and robustness of ImTLSM in operation and maintenance enables high-throughput image collection to establish background removal datasets for deep learning. Using a deep learning model to train the mapping from epi-illumination images to ImTLSM illumination images, namely PN-ImTLSM, we demonstrated cross-modality fluorescence imaging, transforming the epi-illumination image to approach the background removal performance obtained with ImTLSM. We demonstrated that PN-ImTLSM can be generalized to large-field homogeneous illumination imaging, thereby further improving the imaging throughput. In addition, compared to commonly used background removal methods, PN-ImTLSM showed much better performance for areas where the background intensity changes sharply in space, facilitating high-density single-molecule localization microscopy. In summary, PN-ImTLSM paves the way for background-free fluorescence imaging on ordinary inverted microscopes.