Search bioRxivSearch

Biology subjects

Arslanturk, S.

Publications and source records attributed to Arslanturk, S..

2 recordsLinked to original sources

Deep Learning Strategies for Differential Expansion Microscopy

Differential expansion microscopy (DiExM) achieves greater than 500-fold volumetric expansion of biological specimens without loss of cellular antigens. The anisotropic character of this expansion, which affects tissues, cells, organelles and even sub-organelle features, requires the application of novel machine learning approaches to extract accurate and meaningful morphological and biochemical information from DiExM images. Here we describe current strategies to achieve this goal.

cell biology

Differential expansion microscopy

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. 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 name this method differential expansion microscopy (DiExM).

cell biology