10 research outputs found

    DeepETPicker: Fast and accurate 3D particle picking for cryo-electron tomography using weakly supervised deep learning

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    Abstract To solve three-dimensional structures of biological macromolecules in situ, large numbers of particles often need to be picked from cryo-electron tomograms. However, adoption of automated particle-picking methods remains limited because of their technical limitations. To overcome the limitations, we develop DeepETPicker, a deep learning model for fast and accurate picking of particles from cryo-electron tomograms. Training of DeepETPicker requires only weak supervision with low numbers of simplified labels, reducing the burden of manual annotation. The simplified labels combined with the customized and lightweight model architecture of DeepETPicker and accelerated pooling enable substantial performance improvement. When tested on simulated and real tomograms, DeepETPicker outperforms the competing state-of-the-art methods by achieving the highest overall accuracy and speed, which translate into higher authenticity and coordinates accuracy of picked particles and higher resolutions of final reconstruction maps. DeepETPicker is provided in open source with a user-friendly interface to support cryo-electron tomography in situ

    HOPE-SIM, a cryo-structured illumination fluorescence microscopy system for accurately targeted cryo-electron tomography

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    Abstract Cryo-focused ion beam (cryo-FIB) milling technology has been developed for the fabrication of cryo-lamella of frozen native specimens for study by in situ cryo-electron tomography (cryo-ET). However, the precision of the target of interest is still one of the major bottlenecks limiting application. Here, we have developed a cryo-correlative light and electron microscopy (cryo-CLEM) system named HOPE-SIM by incorporating a 3D structured illumination fluorescence microscopy (SIM) system and an upgraded high-vacuum stage to achieve efficiently targeted cryo-FIB. With the 3D super resolution of cryo-SIM as well as our cryo-CLEM software, 3D-View, the correlation precision of targeting region of interest can reach to 110 nm enough for the subsequent cryo-lamella fabrication. We have successfully utilized the HOPE-SIM system to prepare cryo-lamellae targeting mitochondria, centrosomes of HeLa cells and herpesvirus assembly compartment of infected BHK-21 cells, which suggests the high potency of the HOPE-SIM system for future in situ cryo-ET workflows

    ACAP1 assembles into an unusual protein lattice for membrane deformation through multiple stages

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    Studies on the Bin-Amphiphysin-Rvs (BAR) domain have advanced a fundamental understanding of how proteins deform membrane. We previously showed that a BAR domain in tandem with a Pleckstrin Homology (PH domain) underlies the assembly of ACAP1 (Arfgap with Coil-coil, Ankryin repeat, and PH domain I) into an unusual lattice structure that also uncovers a new paradigm for how a BAR protein deforms membrane. Here, we initially pursued computation-based refinement of the ACAP1 lattice to identify its critical protein contacts. Simulation studies then revealed how ACAP1, which dimerizes into a symmetrical structure in solution, is recruited asymmetrically to the membrane through dynamic behavior. We also pursued electron microscopy (EM)-based structural studies, which shed further insight into the dynamic nature of the ACAP1 lattice assembly. As ACAP1 is an unconventional BAR protein, our findings broaden the understanding of the mechanistic spectrum by which proteins assemble into higher-ordered structures to achieve membrane deformation.Published versio
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