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Multi-modal on-chip nanoscopy and quantitative phase image reveals the morphology of liver sinusoidal enodthelial cells

Visualization of three-dimensional morphological changes in the subcellular structures of a biological specimen is one of the greatest challenges in life science. Despite conspicuous refinements in optical nanoscopy, determination of quantitative changes in subcellular structure, i.e., size and thickness, remains elusive. We present an integrated chip-based optical nanoscopy set-up that provides a lateral optical resolution of 61 nm combined with a highly sensitive quantitative phase microscopy (QPM) system with a spatial phase sensitivity of $\pm$20 mrad. We use the system to obtain the 3D morphology of liver sinusoidal endothelial cells (LSECs) combined with super-resolved spatial information. LSECs have a unique morphology with nanopores that are present in the plasma membrane, called fenestration. The fenestrations are grouped in clusters called sieve plates, which are around 100 nm thick. Thus, imaging and quantification of fenestration and sieve plate thickness requires resolution and sensitivity of sub-100 nm along both lateral and axial directions. In the chip-based nanoscope, the optical waveguides are used both for hosting and illuminating the sample. A strong evanescent field is generated on top of the waveguide surface for single molecule fluorescence excitation. The fluorescence signal is captured by an upright microscope, which is converted into a Linnik-type interferometer to sequentially acquire both super-resolved images and quantitative phase information of the sample. The multi-modal microscope provided an estimate of the fenestration diameter of 124$\pm$41 nm and revealed the average estimated thickness of the sieve plates in the range of 91.2$\pm$43.5 nm for two different cells. The combination of these techniques offers visualization of both the lateral size (using nanoscopy) and the thickness map of sieve plates, i.e. discrete clusters fenestrations in QPM mode.

preprint2020arXivOpen access
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