In Histochemistry and cell biology
Expensive and time-consuming approaches of immunoelectron microscopy of biopsy tissues continues to serve as the gold-standard for diagnostic pathology. The recent development of the new approach of expansion microscopy (ExM) capable of fourfold lateral expansion of biological specimens for their morphological examination at approximately 70 nm lateral resolution using ordinary diffraction limited optical microscopy, is a major advancement in cellular imaging. Here we report (1) an optimized fixation protocol for retention of cellular morphology while obtaining optimal expansion, (2) an ExM procedure for up to eightfold lateral and over 500-fold volumetric expansion, (3) demonstrate that ExM is anisotropic or differential between tissues, cellular organelles and domains within organelles themselves, and (4) apply image analysis and machine learning (ML) approaches to precisely assess differentially expanded cellular structures. We refer to this enhanced ExM approach combined with ML as differential expansion microscopy (DiExM), applicable to profiling biological specimens at the nanometer scale. DiExM holds great promise for the precise, rapid and inexpensive diagnosis of disease from pathological specimen slides.
Pernal Sebastian P, Liyanaarachchi Asiri, Gatti Domenico L, Formosa Brent, Pulvender Rishika, Kuhn Eric R, Ramos Rafael, Naik Akshata R, George Kathleen, Arslanturk Suzan, Taatjes Douglas J, Jena Bhanu P
Differential expansion, Machine learning, Nanoscale imaging, Optical microscopy