Subdiffraction Imaging of Cleared and Expanded Large-Scale Tissues

Abstract

The quest for high spatial resolution in molecular identification is critical across various domains, including physiology, pathology, and pharmaceutical research. Super-resolution microscopy has made strides by surpassing the Abbe diffraction limit, but it relies on sophisticated equipment and is limited by the sample size to handle. Expansion microscopy, an emerging technique, has broadened the scope of subdiffraction imaging. It chemically preserves tissues at a large scale and physically enlarges them 4−20 times linearly, enabling superresolution observation. This review begins by exploring the foundational concepts of tissue clearing and the latest methodologies in the field. It then delves into the core tenets of expansion microscopy, covering a range of protocols. The review spotlights advancements in enhancing resolution, improving labeling efficiency, and ensuring isotropic tissue expansion. Finally, the review offers insights into the prospective evolution of expansion microscopy. It emphasizes the potential role of machine learning in refining image quality and in the autonomous extraction of data, which could revolutionize the way we visualize and understand biological tissues.