Summary

使用Tomoauto:一个协议,用于高通量自动化低温电子断层扫描

Published: January 30, 2016
doi:

Summary

我们提出如何利用高通量低温电子断层扫描,以确定高分辨率分子机器的结构原位的协议。该协议允许大量数据要处理,避免了常见的瓶颈,并减少停机时间资源,从而允许用户集中在重要的生物的问题。

Abstract

Cryo-electron tomography (Cryo-ET) is a powerful three-dimensional (3-D) imaging technique for visualizing macromolecular complexes in their native context at a molecular level. The technique involves initially preserving the sample in its native state by rapidly freezing the specimen in vitreous ice, then collecting a series of micrographs from different angles at high magnification, and finally computationally reconstructing a 3-D density map. The frozen-hydrated specimen is extremely sensitive to the electron beam and so micrographs are collected at very low electron doses to limit the radiation damage. As a result, the raw cryo-tomogram has a very low signal to noise ratio characterized by an intrinsically noisy image. To better visualize subjects of interest, conventional imaging analysis and sub-tomogram averaging in which sub-tomograms of the subject are extracted from the initial tomogram and aligned and averaged are utilized to improve both contrast and resolution. Large datasets of tilt-series are essential to understanding and resolving the complexes at different states, conditions, or mutations as well as obtaining a large enough collection of sub-tomograms for averaging and classification. Collecting and processing this data can be a major obstacle preventing further analysis. Here we describe a high-throughput cryo-ET protocol based on a computer-controlled 300kV cryo-electron microscope, a direct detection device (DDD) camera and a highly effective, semi-automated image-processing pipeline software wrapper library tomoauto developed in-house. This protocol has been effectively utilized to visualize the intact type III secretion system (T3SS) in Shigella flexneri minicells. It can be applicable to any project suitable for cryo-ET.

Introduction

III型分泌系统(T3SS)是必不可少的毒力决定于许多革兰氏阴性病原体。的injectisome,也被称为针复杂,是所需的效应蛋白直接易位从细菌到真核宿主细胞1,2中央T3SS机。所述injectisome包括细胞外针,一个基体,和胞质复杂也是已知作为拣杂3。先前的研究已阐明了从沙门氏菌和 志贺氏菌纯化的injectisomes的3-D结构,随着主要基体蛋白4,5的原子结构。最近沙门氏菌, 志贺氏菌耶尔森氏菌 injectisomes 原位结构进行了揭示的低温的ET 6 7,然而,胞质复杂,效应子选择和针组件必需的,还没有被可视化这些结构。

低温-ET是MOSŤ合适技术其天然细胞环境原位)内成像分子机器在纳米级分辨率。尽管如此,通过Cryo-ET可达到的分辨率由样品厚度的限制。为了克服缺点,我们在毒痢疾杆菌菌株进行基因改造,以产生小细胞的冷冻ET足够薄成像完好injectisomes。冷冻的ET的另一个限制是样品诱导的电子束,它非常快速地破坏在样品中的高分辨率信息的辐射的敏感性。其结果是,非常低剂量用于个体倾斜图像,使合适的剂量可以分布在全倾斜系列。这大大降低了在最终的重建的信噪比(SNR),这使得难以区分的大量的断层图像噪声的被检体的结构特征和限制了可以由永冻达到的分辨率ET。 Conventi可用于Onal地区的图像处理,如傅立叶和现实空间滤波器以及向下采样,以增加对比度,但在过滤掉大部分的高分辨率信息的费用。近来,子断层图像平均化使得有可能大大提高了信噪比并随后在某些情况下,以亚纳米水平8,9的尾声。配合物的更详细的分析成为可能通过计算提取数千含子断层图像从原来的断层图像,然后对准并平均所述子断层图像感兴趣的区域,以确定具有较高SNR和更高分辨率的原位复杂的结构。这些方法可以用遗传学方法,以提供更大的见解大分子组装,并在天然细胞环境的动态构象进行集成。

在一般情况下,几十甚至几十万子断层需要,以确定高被平均-分辨率结构原位 。采集的倾斜系列足够数量需要产生这种大数目的子断层图像很快成为一个瓶颈。所得倾斜系列往往受光束诱发移位,阶段齿隙,以及倍率,旋转和歪斜缺陷,这必须得到解决,以使倾斜系列对准前重建。倾斜系列典型地通过跟踪金基准标记,这是传统选过倾斜系列的检查手动,引起另一个瓶颈对齐。许多软件包已通过计算机控制的电子显微镜10,11,12,倾斜系列对准和重建13,14和子断层图像平均15-18开发用于自动倾斜系列采集。由于这些产品的处理在低温的ET的工作流分立操作,就变成希望建立一个更高的抽象水平进入过程的Systema角度讲简化整个计划到一个单一的管道。因此,我们开发了软件包装库“tomoauto”旨在组织一些这些包成一个单一的半自动化单元,允许简单的用户操作,同时保持以集中的方式各成分的完整配置。该库是开源的,有据可查的,不断发展和可以自由使用,定制开发或进一步集成通过网上远程源代码库(http://github.com/DustinMorado/tomoauto)的手段。

这种高通量冷冻ET管道已被用来可视化完好injectisomes S的微细胞。使用该方法生成总共1917断层图像,揭示一个高分辨率在完整的机器的原位结构,包括由子断层图像 19确定的细胞质分拣平台。连同野生型和米的分子模拟utant机,我们的高通量管道提供了一种新的途径,以了解在天然细胞环境的完整injectisome的结构和功能。

Protocol

1.小细准备为了使S.菌微细胞,变换1微升质粒pBS58,其组成型表达的大肠杆菌细胞分裂的基因ftsQ,ftsA,和ftsZ超从低拷贝壮观霉素抗性质粒入5微升电感受链霉素抗性5a血清型(M90T钐)细胞通过电穿孔的在2.5千伏为5毫秒,以1毫米试管。 商店微细胞的样品在-80℃下在15%甘油在1.5ml微管中的低温。当准备使用时,刮大约5微升用枪头从unthawed微管细胞和悬浮细?…

Representative Results

小细胞S.样品菌 ,收集并处理的结果显示在原理图1采用tomoauto在图2中详述的管道下面。 使用SerialEM 10,其允许高通量倾斜系列采集在上低倍率蒙太奇地图由用户指定的点( 图3)倾斜系列收集。使用剂量分馏模式直接检测器件照相机上,以减少束诱发运动22(图4),收集显微镜?…

Discussion

此处所描述的高通量方法,使我们能够处理1917低温倾斜系列和产生超过4500分断层图像的完好S的菌 injectisome 19。所收集的数据导致原位 injectisome的详细的表征,包括胞质排序复杂。该方法也被用来可视化几个突变的细胞与特异性缺失推定的蛋白质组分,这有助于阐明injectisome的排序平台的组成。我们的方法提供了新的途径,调查injectisome的结构与功能的关系。其结果是?…

Divulgazioni

The authors have nothing to disclose.

Acknowledgements

我们感谢威廉·马戈林医生征求意见。我们感谢来自博士的SerialEM的支持。大卫Mastronarde和陈旭。 DM,BH和JL被授予R01AI087946从国家过敏和传染病研究所,资助R01GM110243和R01GM107629从普通医学科学研究所(NIGMS)和格兰特AU-1714从韦尔奇基金会的支持。直接电子探测器是由美国卫生奖S10OD016279国家机构。

Materials

Glycerol Sigma-Aldrich G9012
Tyrptic Soy Broth Sigma-Aldrich 22092
Spectinomycin Sigma-Aldrich S0692
Electroporation Apparatus Bio-rad 165-2100
1 mm Cuvette BTX 45-0124
1.5 mL Cryogenic Tube Thermoscientific 5000-1020
1.5 mL Microcentrifuge Tube Sigma-Aldrich Z336769
Holey Carbon Grids Quantifoil
(Electron Microscopy Sciences)
Q2100CR2 R2/2 200 Cu
Glow Discharge Device In-House Commercial Alternative Available
Vacuum Desiccator Sigma-Aldrich Z119016  Used in In-House Glow Discharge Device
High-Frequency Generator Electro-Technic Products BD-10A Used in In-House Glow Discharge Device.  CAUTION: This device generates high voltages.
Centrifuge
Forceps Dumont
(Electron Microscopy Sciences)
72705-D Style 5 Anti-magnetic
Colliodal Gold Aurion BSA 10nm
Filter Paper Whatman #2
Ethane  Matheson Tri-Gas UN1035
Nitrogen Matheson Tri-Gas UN1977
Plunger Device In-House Commercial Alternative Available
Cryogenic Grid Storage Box Electron Microscopy Sciences 71166-30
Transmission Electron Microscope FEI Tecnai Polara F30
(300 KeV)
Direct Detection Device Camera Gatan K2 Summit
Tomogram Acquisiton Software SerialEM http://bio3d.colorado.eud/SerialEM Alternatives: UCSF Tomography, Leginon, FEI Batch Tomography
Beam-induced Motion Correction Software MOTIONCORR http://cryoem.ucsf.edu/software/driftcorr.html Requires >2GB Nvidia GPU
Tilt-Series Alignment Software IMOD http://bio3d.colorado.edu/IMOD Alternatives: XMIPP, Protomo
Automatic Fiducial Marker Modelling Software IMOD Alternatives: RAPTOR (Included in IMOD0
(Usable in tomoauto)
CTF Determination Software IMOD Alternatives: CTFFIND http://grigoriefflab.janelia.org/ctf
(Usable in tomoauto)
Tilt-Series Reconstruction Software tomo3d https://sites.google.com/site/3demimageprocessing/tomo3d Alternatives: IMOD, XMIPP http://xmipp.cnb.csic.es , Protomo
Tilt-Series Automated Processing Software tomoauto https://github.com/DustinMorado/tomoauto
Particle Picking Software i3 http://www.electrontomography.org Alternatives: IMOD
Subvolume Averaging Software i3 Alternatives: PEET http://bio3d.colorado.edu/PEET, Dynamo https://dynamo.bioz.unibas.ch , PyTom http://pytom.org

Riferimenti

  1. Cornelis, G. R. The type III secretion injectisome. Nat. Rev. Microbiol. 4 (11), 811-825 (2006).
  2. Galan, J. E., Wolf-Watz, H. Protein delivery into eukaryotic cells by type III secretion machines. Nature. 444 (7119), 567-573 (2006).
  3. Kubori, T., et al. Supramolecular structure of the Salmonella typhimurium type III protein secretion system. Science. 280 (5363), 602-605 (1998).
  4. Schraidt, O., Marlovits, T. C. Three-dimensional model of Salmonella’s needle complex at subnanometer resolution. Science. 331 (6021), 1192-1195 (2011).
  5. Hodgkinson, J. L., et al. Three-dimensional reconstruction of the Shigella T3SS transmembrane regions reveals 12-fold symmetry and novel features throughout. Nat. Struct. Mol. Biol. 16 (5), 477-485 (2009).
  6. Kudryashev, M., et al. In situ structural analysis of the Yersinia enterocolitica injectisome. eLife. 2, e00792 (2013).
  7. Kawamoto, A., et al. Common and distinct structural features of Salmonella injectisome and flagellar basal body. Scientific Reports. 3, 3369-3369 (2013).
  8. Briggs, J. A. Structural biology in situ-the potential of subtomogram averaging. Curr. Opin. Struct. Biol. 23 (2), 261-267 (2013).
  9. Schur, F. K., Hagen, W. J., de Marco, A., Briggs, J. A. Determination of protein structure at 8.5Å resolution using cryo-electron tomography and sub-tomogram averaging. J. Struct. Biol. 184 (3), 394-400 (2013).
  10. Mastronarde, D. N. Automated electron microscope tomography using robust prediction of specimen movements. J. Struct. Biol. 152 (1), 36-51 (2005).
  11. Zheng, S. Q., et al. UCSF tomography: an integrated software suite for real-time electron microscopic tomographic data collection, alignment and reconstruction. J. Struct. Biol. 157 (1), 138-147 (2007).
  12. Suloway, C., et al. Fully automated, sequential tilt-series acquisition with Leginon. J. Struct. Biol. 167 (1), 11-18 (2009).
  13. Kremer, J. R., Mastronarde, D. N., McIntosh, J. R. Computer visualization of three-dimensional image data using IMOD. J. Struct. Biol. 116 (1), 71-76 (1996).
  14. Winkler, H., Taylor, K. A. Accurate marker-free alignment with simultaneous geometry determination and reconstruction of tilt-series in electron tomography. Ultramicroscopy. 106 (3), 240-254 (2006).
  15. Winkler, H., Zhu, P., Liu, J., Ye, F., Roux, K. H., Taylor, K. A. Tomographic subvolume alignment and classification applied to myosin V and SIV envelope spikes. J. Struct. Biol. 165 (2), 64-77 (2009).
  16. Nicastro, D., Schwartz, C. L., Pierson, J., Gaudette, R., Porter, M. E., McIntosh, J. R. The Molecular Architecture of Axonemes Revealed by Cryoelectron Tomography. Science. 313 (5789), 944-948 (2006).
  17. Castaño-Díez, D., Kudryashev, M., Arheit, M., Stahlberg, H. Dynamo: a flexible, user-friendly development tool for subtomogram averaging of cryo-EM data in high-performance computing environments. J. Struct. Biol. 178 (2), 139-151 (2012).
  18. Hrabe, T., Chen, Y., Pfeffer, S., Cuellar, L. K., Mangold, A. V., Förster, F. PyTom: a python-based toolbox for localization of macromolecules in cryo-electron tomograms and subtomogram analysis. J. Struct. Biol. 178 (2), 177-188 (2012).
  19. Hu, B., et al. Visualization of the type III secretion sorting platform of Shigella flexneri. Proc. Natl. Acad. Sci. 112 (4), 1047-1052 (2015).
  20. Iancu, C. V., et al. Electron cryotomography sample preparation using the Vitrobot. Nat. Protoc. 1 (6), 2813-2819 (2007).
  21. Chen, S., et al. Electron Cryoelectrontomography of Bacterial Cells. J. Vis. Exp. (39), e1943 (2010).
  22. Li, X., et al. Electron counting and beam-induced motion correction enable near-atomic-resolution single-particle cryo-EM. Nat. Methods. 10 (6), 584-590 (2013).
  23. Xiong, Q., Morphew, M. K., Schwartz, C. L., Hoenger, A. H., Mastronarde, D. M. CTF determination and correction for low dose tomographic tilt series. J. Struct. Biol. 168 (3), 378-387 (2009).
  24. Amat, F., Moussavi, F., Comolli, L. R., Elidan, G., Downing, K. H., Horowitz, M. Markov random field based automatic image alignment for electron tomography. J. Struct. Biol. 161 (3), 260-275 (2008).
  25. Rouhou, A., Grigorieff, N. CTFFIND4: Fast and accurate defocus estimation from electron micrographs. bioRxiv. , (2015).
  26. Agulleiro, J. I., Fernandez, J. J. Tomo3D 2.0 – Exploitation of Advanced Vector eXtensions (AVX) for 3D reconstruction. J. Struct. Biol. 189 (2), 147-152 (2015).
  27. Zhao, X., Zhang, K., Boquoi, T., Hu, B., Motaleb, M. A., Miller, K., James, M., Charon, N. W., Manon, M. D., Norris, S. J., Li, C., Liu, J. Cryo-Electron Tomography Reveals the Sequential Assembly of Bacterial Flagella in Borrelia burgdorferi. Proc Natl Acad Sci U S A. 110 (35), 14390-14395 (2013).
  28. Hu, B., Margolin, W., Molineux, I. J., Liu, J. The Bacteriophage T7 Virion Undergoes Extensive Structural Remodeling during infection. Science. 339 (6119), 576-579 (2013).
  29. Liu, J., Hu, B., Morado, D. R., Jani, S., Manson, M. D., Margolin, W. W: Molecular architecture of chemoreceptor arrays revealed by cryoelectron tomography of Escherichia coli minicells. Proc Natl Acad Sci USA. 109 (23), e1481-e1488 (2012).
  30. Russo, C. J., Passmore, L. A. Electron microscopy: Ultrastable gold substrates for electron cryomicroscopy. Science. 346 (6215), 1377-1380 (2014).

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Citazione di questo articolo
Morado, D. R., Hu, B., Liu, J. Using Tomoauto: A Protocol for High-throughput Automated Cryo-electron Tomography. J. Vis. Exp. (107), e53608, doi:10.3791/53608 (2016).

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