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Dive into the research topics where Shawn Q. Zheng is active.

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Featured researches published by Shawn Q. Zheng.


Nature Methods | 2013

Electron counting and beam-induced motion correction enable near-atomic-resolution single-particle cryo-EM

Xueming Li; Paul Mooney; Shawn Q. Zheng; Christopher R Booth; Michael B. Braunfeld; Sander Gubbens; David A. Agard; Yifan Cheng

In recent work with large high-symmetry viruses, single-particle electron cryomicroscopy (cryo-EM) has achieved the determination of near-atomic-resolution structures by allowing direct fitting of atomic models into experimental density maps. However, achieving this goal with smaller particles of lower symmetry remains challenging. Using a newly developed single electron–counting detector, we confirmed that electron beam–induced motion substantially degrades resolution, and we showed that the combination of rapid readout and nearly noiseless electron counting allow image blurring to be corrected to subpixel accuracy, restoring intrinsic image information to high resolution (Thon rings visible to ∼3 Å). Using this approach, we determined a 3.3-Å-resolution structure of an ∼700-kDa protein with D7 symmetry, the Thermoplasma acidophilum 20S proteasome, showing clear side-chain density. Our method greatly enhances image quality and data acquisition efficiency—key bottlenecks in applying near-atomic-resolution cryo-EM to a broad range of protein samples.


Nature Methods | 2017

MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy

Shawn Q. Zheng; Eugene Palovcak; Jean-Paul Armache; Kliment A. Verba; Yifan Cheng; David A. Agard

MotionCor2 software corrects for beam-induced sample motion, improving the resolution of cryo-EM reconstructions.


Journal of Structural Biology | 2009

Fully automated, sequential tilt-series acquisition with Leginon

Christian Suloway; Jian Shi; Anchi Cheng; James Pulokas; Bridget Carragher; Clinton S. Potter; Shawn Q. Zheng; David A. Agard; Grant J. Jensen

Electron tomography has become a uniquely powerful tool for investigating the structures of individual cells, viruses, and macromolecules. Data collection is, however, time consuming and requires expensive instruments. To optimize productivity, we have incorporated one of the existing tilt-series acquisition programs, UCSF Tomo, into the well-developed automatic electron microscopy data collection package Leginon to enable fully automatic, sequential tilt-series acquisition. Here we describe how UCSF Tomo was integrated into Leginon, what users must do to set up a data collection session, how the automatic collection proceeds, how archived data about the process can be accessed and used, and how the software has been tested.


Journal of Structural Biology | 2015

Asynchronous data acquisition and on-the-fly analysis of dose fractionated cryoEM images by UCSFImage.

Xueming Li; Shawn Q. Zheng; David A. Agard; Yifan Cheng

Newly developed direct electron detection cameras have a high image output frame rate that enables recording dose fractionated image stacks of frozen hydrated biological samples by electron cryomicroscopy (cryoEM). Such novel image acquisition schemes provide opportunities to analyze cryoEM data in ways that were previously impossible. The file size of a dose fractionated image stack is 20-60 times larger than that of a single image. Thus, efficient data acquisition and on-the-fly analysis of a large number of dose-fractionated image stacks become a serious challenge to any cryoEM data acquisition system. We have developed a computer-assisted system, named UCSFImage4, for semi-automated cryo-EM image acquisition that implements an asynchronous data acquisition scheme. This facilitates efficient acquisition, on-the-fly motion correction, and CTF analysis of dose fractionated image stacks with a total time of ∼60s/exposure. Here we report the technical details and configuration of this system.


Journal of Structural Biology | 2013

Influence of electron dose rate on electron counting images recorded with the K2 camera

Xueming Li; Shawn Q. Zheng; Kiyoshi Egami; David A. Agard; Yifan Cheng

A recent technological breakthrough in electron cryomicroscopy (cryoEM) is the development of direct electron detection cameras for data acquisition. By bypassing the traditional phosphor scintillator and fiber optic coupling, these cameras have greatly enhanced sensitivity and detective quantum efficiency (DQE). Of the three currently available commercial cameras, the Gatan K2 Summit was designed specifically for counting individual electron events. Counting further enhances the DQE, allows for practical doubling of detector resolution and eliminates noise arising from the variable deposition of energy by each primary electron. While counting has many advantages, undercounting of electrons happens when more than one electron strikes the same area of the detector within the analog readout period (coincidence loss), which influences image quality. In this work, we characterized the K2 Summit in electron counting mode, and studied the relationship of dose rate and coincidence loss and its influence on the quality of counted images. We found that coincidence loss reduces low frequency amplitudes but has no significant influence on the signal-to-noise ratio of the recorded image. It also has little influence on high frequency signals. Images of frozen hydrated archaeal 20S proteasome (~700 kDa, D7 symmetry) recorded at the optimal dose rate retained both high-resolution signal and low-resolution contrast and enabled calculating a 3.6 Å three-dimensional reconstruction from only 10,000 particles.


bioRxiv | 2016

Anisotropic Correction of Beam-induced Motion for Improved Single-particle Electron Cryo-microscopy

Shawn Q. Zheng; Eugene Palovcak; Jean-Paul Armache; Yifan Cheng; David A. Agard

Correction of electron beam-induced sample motion is one of the major factors contributing to the recent resolution breakthroughs in cryo-electron microscopy. Improving the accuracy and efficiency of motion correction can lead to further resolution improvement. Based on observations that the electron beam induces doming of the thin vitreous ice layer, we developed an algorithm to correct anisotropic image motion at the single pixel level across the whole frame, suitable for both single particle and tomographic images. Iterative, patch-based motion detection is combined with spatial and temporal constraints and dose weighting. The multi-GPU accelerated program, MotionCor2, is sufficiently fast to keep up with automated data collection. The result is an exceptionally robust strategy that can work on a wide range of data sets, including those very close to focus or with very short integration times, obviating the need for particle polishing. Application significantly improves Thon ring quality and 3D reconstruction resolution.


Methods in Enzymology | 2010

Automated data collection for electron microscopic tomography.

Shawn Q. Zheng; John W. Sedat; David A. Agard

A fundamental challenge in electron microscopic tomography (EMT) has been to develop automated data collection strategies that are both efficient and robust. UCSF Tomography was developed to provide an inclusive solution from target finding, sequential EMT data collection, to real-time reconstruction for both single and dual axes. The predictive data collection method that is the cornerstone of UCSF Tomography assumes that the sample follows a simple geometric rotation. As a result, the image movement in the x, y, and z directions due to stage tilt can be dynamically predicted with the required accuracy (15nm in x-y position and 100nm in focus) rather than being measured with additional images. Lacking immediate feedback during cryo-EMT data collection can offset the efficiency and robustness reaped from the predictive data collection and this motivated the development of an integrated real-time reconstruction scheme. Moderate resolution reconstructions were achieved by performing weighted back-projection on a small cluster in parallel with the data collection. To facilitate dual-axis EMT data collection, a hierarchical scheme for target finding and relocation after specimen rotation was developed and integrated with the predictive data collection and real-time reconstruction, allowing full automation from target finding to data collection and to reconstruction of 3D volumes with little user intervention. For nonprofit use the software can be freely downloaded from http://www.msg.ucsf.edu/tomography.


Ultramicroscopy | 2011

A distributed multi-GPU system for high speed electron microscopic tomographic reconstruction.

Shawn Q. Zheng; Eric Branlund; Bettina Kesthelyi; Michael B. Braunfeld; Yifan Cheng; John W. Sedat; David A. Agard

Full resolution electron microscopic tomographic (EMT) reconstruction of large-scale tilt series requires significant computing power. The desire to perform multiple cycles of iterative reconstruction and realignment dramatically increases the pressing need to improve reconstruction performance. This has motivated us to develop a distributed multi-GPU (graphics processing unit) system to provide the required computing power for rapid constrained, iterative reconstructions of very large three-dimensional (3D) volumes. The participating GPUs reconstruct segments of the volume in parallel, and subsequently, the segments are assembled to form the complete 3D volume. Owing to its power and versatility, the CUDA (NVIDIA, USA) platform was selected for GPU implementation of the EMT reconstruction. For a system containing 10 GPUs provided by 5 GTX295 cards, 10 cycles of SIRT reconstruction for a tomogram of 4096(2) × 512 voxels from an input tilt series containing 122 projection images of 4096(2) pixels (single precision float) takes a total of 1845 s of which 1032 s are for computation with the remainder being the system overhead. The same system takes only 39 s total to reconstruct 1024(2) × 256 voxels from 122 1024(2) pixel projections. While the system overhead is non-trivial, performance analysis indicates that adding extra GPUs to the system would lead to steadily enhanced overall performance. Therefore, this system can be easily expanded to generate superior computing power for very large tomographic reconstructions and especially to empower iterative cycles of reconstruction and realignment.


Journal of Structural Biology | 2009

Dual-axis target mapping and automated sequential acquisition of dual-axis EM tomographic data.

Shawn Q. Zheng; Atsushi Matsuda; Michael B. Braunfeld; John W. Sedat; David A. Agard

Dual-axis electron microscopic tomography minimizes the missing wedge-induced resolution loss by taking two complementary tilt data sets of the same target along two orthogonal axes. The potential of this powerful approach has been hampered by the practical challenges inherent in finding the original targets that are dramatically displaced due to non-eucentric specimen rotation. Not only is the manual search for the original targets time consuming and tedious but the added dose during manual searching is uncontrollable. We have developed a hierarchical alignment scheme that allows tomographic data to be collected from an arbitrary number of target sites in one grid orientation and then to find and collect orthogonal data sets with little or no user intervention. Inspired by the successful multi-scale mapping in Leginon, our alignment is performed in three levels to gradually pinpoint the original targets. At the lowest level the grid lattice is used to determine the rotation angle and translational shift resulting from specimen rotation via auto- and cross-correlative analysis of a pair of atlas maps constructed before and after specimen rotation. The target locations are further refined at the next level using a pair of smaller atlas maps. The final refinement of target positions is done by aligning the target contained image tiles. Given the batch processing nature of this hierarchical alignment, multiple targets are initially selected in a group and then sequentially acquired. Upon completion of the data collection on all the targets along the first axis and after specimen rotation, the hierarchical alignment is performed to relocate the original targets. The data collection is then resumed on these targets for the second axis. Therefore, only one specimen rotation is needed for collecting multiple dual-axis tomographic data sets. The experiment of acquiring 20S Proteasomes dual-axis tomographic data sets in vitreous ice at 86,000x CCD magnification on our FEI Tecnai Polara TF30 electron microscope has suggested that the developed scheme is very robust. The extra doses for finding and centering the original targets are almost negligible. This scheme has been integrated into UCSF Tomography software suite that can be downloaded at www.msg.ucsf.edu/tomography free for academic use.


Journal of Structural Biology | 2018

A simple and robust procedure for preparing graphene-oxide cryo-EM grids

Eugene Palovcak; Feng Wang; Shawn Q. Zheng; Zanlin Yu; Sam Li; Miguel Betegon; David Bulkley; David A. Agard; Yifan Cheng

Graphene oxide (GO) sheets have been used successfully as a supporting substrate film in several recent cryogenic electron-microscopy (cryo-EM) studies of challenging biological macromolecules. However, difficulties in preparing GO-covered holey carbon EM grids have limited their widespread use. Here, we report a simple and robust method for covering holey carbon EM grids with GO sheets and demonstrate that these grids can be used for high-resolution single particle cryo-EM. GO substrates adhere macromolecules, allowing cryo-EM grid preparation with lower specimen concentrations and provide partial protection from the air-water interface. Additionally, the signal of the GO lattice beneath the frozen-hydrated specimen can be discerned in many motion-corrected micrographs, providing a high-resolution fiducial for evaluating beam-induced motion correction.

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David A. Agard

University of California

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Yifan Cheng

University of California

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John W. Sedat

University of California

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Xueming Li

University of California

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David Bulkley

University of California

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Eric Branlund

University of California

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Feng Wang

University of California

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