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bioRxiv · 10.1101/2020.08.26.267732

3D Deconvolution Processing for STEM Cryo-Tomography

Waugh, B.·Wolf, S. G.·Fass, D.·Branlund, E.·Kam, T.·Sedat, J.·Elbaum, M.
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Abstract

The complex environment of biological cells and tissues has motivated development of three dimensional imaging in both light and electron microscopies. To this end, one of the primary tools in fluorescence microscopy is that of computational deconvolution. Wide-field fluorescence images are often corrupted by haze due to out-of-focus light, i.e., to cross-talk between different object planes as represented in the 3D image. Using prior understanding of the image formation mechanism, it is possible to suppress the cross-talk and reassign the unfocused light to its proper source post facto. Electron tomography based on tilted projections also exhibits a cross-talk between distant planes due to the discrete angular sampling and limited tilt range. By use of a suitably synthesized 3D point spread function, we show here that deconvolution leads to similar improvements in volume data reconstructed from cryo-scanning transmission electron tomography (CSTET), namely a dramatic in-plane noise reduction and improved representation of features in the axial dimension. Contrast enhancement is demonstrated first with colloidal gold particles, and then in representative cryo-tomograms of intact cells. Deconvolution of CSTET data collected from the periphery of an intact nucleus revealed partially condensed, extended structures in interphase chromatin. Significance statementElectron tomography is used to reveal the structure of cells in three dimensions. The combination with cryogenic fixation provides a snapshot in time of the living state. However, cryo-tomography normally requires very thin specimens due to image formation by conventional phase contrast transmission electron microscopy (TEM). The thickness constraint can be relaxed considerably by scanning TEM (STEM), yet three-dimensional (3D) reconstruction is still subject to artifacts inherent in the collection of data by tilted projections. We show here that deconvolution algorithms developed for fluorescence microscopy can suppress these artifacts, resulting in significant contrast enhancement. The method is demonstrated by cellular tomography of complex membrane structures, and by segmentation of chromatin into distinct, contiguous domains of heterochromatin and euchromatin at high and low density, respectively.

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Waugh, B., Wolf, S. G., Fass, D., Branlund, E., Kam, T., Sedat, J., Elbaum, M.. 2020-08-27. 3D Deconvolution Processing for STEM Cryo-Tomography. https://doi.org/10.1101/2020.08.26.267732

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