Abstract
Expansion microscopy (ExM) involves the use of hydration-competent polymers to physically expand biological specimens approximately 4-fold linear increase to achieve 70 nanometer resolution using an ordinary diffraction limited optical microscope. Optimal conditions however for antigen retention during the expansion process and the relative expansion between organelles within cells has remained unclear. It is reported that different tissues expand to different extents, suggesting that although isotropic expansion is believed to occur, different subcellular compartments with different composition would undergo anisotropic or differential expansion (DiEx). Consequently, there would be distortion of the native shape and size of subcellular compartments upon expansion, parameters which are critical in assessing cellular states in health and disease. Here we report optimal fixation and expansion conditions that retain structural integrity of cells while exhibiting up to 8-fold linear and therefore 512-fold volumetric expansion. Anisotropic expansion is observed not just between tissues, but between different subcellular compartments and even within subcellular compartments themselves. Combining image analysis and machine learning, we provide an approach for the rapid and precise measurement of cellular and subcellular structures in expanded tissue. Using both manual and computation assessment of morphometric parameters, we demonstrate expansion to be anisotropic and therefore refer to this this method as differential expansion microscopy (DiExM).
