Summary

单分子跟踪显微镜 - 确定细胞分子扩散状态的工具

Published: September 05, 2019
doi:

Summary

3D 单分子定位显微镜用于探测活细菌细胞中荧光标记蛋白质的空间位置和运动轨迹。本文描述的实验和数据分析方案根据集合的单分子轨迹确定细胞蛋白的普遍扩散行为。

Abstract

单分子定位显微镜可探测活细胞中单个分子的位置和运动,具有几十纳米空间和毫秒的时间分辨率。这些功能使单分子定位显微镜非常适合研究生理相关环境中的分子级生物功能。在这里,我们演示了单分子跟踪数据的采集和处理/分析的集成协议,以提取感兴趣的蛋白质可能表现出的不同扩散状态。这些信息可用于量化活细胞中的分子复合形成。我们详细介绍了基于摄像头的 3D 单分子定位实验,以及随后产生单个分子轨迹的数据处理步骤。然后,使用数值分析框架对这些轨迹进行分析,以提取荧光标记分子的普遍扩散状态和这些状态的相对丰度。分析框架基于细胞内布朗扩散轨迹的随机模拟,这些轨迹在空间上被任意细胞几何体所限制。基于模拟轨迹,以与实验图像相同的方式生成和分析原始单分子图像。通过这种方式,实验精度和精度限制被明确纳入分析工作流中,这些限制很难进行实验校准。使用模拟分布的线性组合拟合实验值的分布,确定普遍扩散状态的扩散系数和相对总体分数。通过解决在细菌病原体的细胞溶质中形成同质和异寡体复合物时表现出不同扩散状态的蛋白质,我们证明了我们的协议效用。

Introduction

研究生物分子的扩散行为可以深入了解其生物功能。基于荧光显微镜的技术已成为观察其原生细胞环境中的生物分子的宝贵工具。光漂白 (FRAP) 和荧光相关光谱 (FCS)1之后的荧光恢复提供整体平均扩散行为。相反,单分子定位显微镜能够观察具有高空间和时间分辨率2、3、4的单个荧光标记分子。观察单个分子是有利的,因为感兴趣的蛋白质可能存在于不同的扩散状态。例如,当转录调节器(如大肠杆菌中的 CueR)在细胞醇中自由扩散或与DNA序列结合,并在测量时间尺度上固定时,会出现两种易于区分的扩散状态。.单分子跟踪为直接观察这些不同状态提供了工具,并且不需要复杂的分析来解析它们。然而,在扩散率更相似的情况下,解决多种扩散状态及其人口分数就变得更加困难。例如,由于扩散系数的大小依赖性,蛋白质的不同寡聚状态表现为不同的扩散状态6、7、8、9,10.这类案件需要在数据采集、处理和分析方面采取综合办法。

影响细胞分子扩散率的一个关键因素是细胞边界约束的影响。细菌细胞边界对分子运动的限制导致细胞分子的测量扩散速率看起来比在未封闭空间中发生相同运动时要慢。对于非常缓慢的扩散分子,由于没有与边界碰撞,细胞禁闭的影响可以忽略不计。在这种情况下,可以使用基于布朗运动方程的分析模型,通过拟合分子位移、r或表观扩散系数D+的分布,可以准确求解扩散状态(随机扩散)11,12,13。然而,对于快速扩散的细胞分子,由于扩散分子与细胞边界的碰撞,实验分布不再类似于未限制的布朗运动。必须考虑约束效应,以准确确定荧光标记分子的未封闭扩散系数。最近已经开发出几种方法,通过蒙特卡罗模拟,从分析上解释5、14、15、16或数字的禁闭效果。布朗扩散6,10,16,17,18,19。

在这里,我们提供一个集成协议,用于收集和分析单分子定位显微镜数据,特别注重单分子跟踪。该协议的最终目标是解决荧光标记的细胞蛋白内部(本例中为棒状细菌细胞)的扩散状态。我们的工作建立在以前的单分子跟踪协议之上,其中DNA聚合酶PolI通过扩散分析20证明存在于DNA结合和未结合状态。在这里,我们将单分子跟踪分析扩展到 3D 测量,并执行更逼真的计算模拟,以解决和量化同时存在于细胞中的多种扩散状态。这些数据是使用自制3D超分辨率荧光显微镜获取的,该显微镜能够通过双螺旋点扩散功能(DHPSF)21、22的成像来确定荧光发射器的3D位置。使用定制软件处理原始单分子图像,提取 3D 单分子定位,然后组合成单分子轨迹。数千个轨迹被汇集在一起,以产生表观扩散系数的分布。在最后一步中,实验分布与通过蒙特卡洛模拟布朗运动在密闭体积中获得的数值生成的分布相得一拟。我们应用这个协议来解决3型分泌系统蛋白YscQ在活叶尔西尼亚肠胆病中扩散状态。由于其模块化性质,我们的协议通常适用于任意细胞几何结构中的任何类型的单分子或单粒子跟踪实验。

Protocol

1. 双螺旋点扩散功能校准 注:本部分和以下各节中描述的图像是使用定制内向荧光显微镜获取的,如Rocha等人23所述。相同的程序适用于不同的显微镜实现设计单分子定位和跟踪显微镜2,3,4。本文中描述的所有图像采集和数据处理软件均可用(https://github.com/GahlmannLab2014/Single-Molecule-Tracking…

Representative Results

在此描述的实验条件下(20,000 帧,轨迹长度最小为 4 个定位),并根据荧光标记融合蛋白的表达水平,大约 200-3,000 个定位,产生 10-150每个细胞可以生成轨迹 (图 2a, b)。大量的轨迹是产生表观扩散系数的采样分布所必需的。这里收集的FOV大小为+55 x 55 μm,每个实验收集10个FOV。因此,要获得每个实验的 >5,000 个轨迹,每个 FOV 应?…

Discussion

成功应用所提出的协议的一个关键因素是确保单分子信号彼此很好地分离(即,它们需要在空间和时间上稀疏(补充Mov.1)。如果同时细胞中有多个荧光分子,则定位可能错误地分配给另一个分子的轨迹。这称为链接问题30。可以选择蛋白质表达水平和激发激光强度等实验条件,以避免连接问题。然而,应注意获得野生型蛋白质表达水平,以确保有代表性的结果。在?…

Declarações

The authors have nothing to disclose.

Acknowledgements

我们感谢阿列西亚·阿希莫维奇和丁燕对手稿的批判性阅读。我们感谢弗吉尼亚大学高级研究计算服务小组的高级职员科学家Ed Hall帮助建立这项工作中使用的优化例程。这项工作的资金由弗吉尼亚大学提供。

Materials

2,6-diaminopimelic acid Chem Impex International 5411 Necessary for growth of Y. enterocolitica cells used.
4f lenses Thorlabs AC508-080-A f = 80mm, 2"
514 nm laser Coherent Genesis MX514 MTM Use for fluorescence excitation
agarose Inivtrogen 16520100 Used to make gel pads to mount liquid bacterial sample on microscope.
ammonium chloride Sigma Aldrich A9434 M2G ingredient.
bandpass filter Chroma ET510/bp Excitation pathway.
Brain Heart Infusion Sigma Aldrich 53286 Growth media for Y. enterocolitica.
calcium chloride Sigma Aldrich 223506 M2G ingredient.
camera Imaging Source DMK 23UP031 Camera for phase contrast imaging.
dielectric phase mask Double Helix, LLC N/A Produces DHPSF signal.
disodium phosphate Sigma Aldrich 795410 M2G ingredient.
ethylenediaminetetraacetic acid Fisher Scientific S311-100 Chelates Ca2+. Induces secretion in the T3SS.
flip mirror Newport 8892-K Allows for switching between fluorescence and phase contrast pathways.
fluospheres Invitrogen F8792 Fluorescent beads. 540/560 exication and emission wavelengths. 40 nm diameter.
glass cover slip VWR 16004-302 #1.5, 22mmx22mm
glucose Chem Impex International 811 M2G ingredient.
immersion oil Olympus Z-81025 Placed on objective lens.
iron(II) sulfate Sigma Aldrich F0518 M2G ingredient.
long pass filter Semrock LP02-514RU-25 Emission pathway.
magnesium sulfate Fisher Scientific S25414A M2G ingredient.
microscope platform Mad City Labs custom Platform for inverted microscope.
nalidixic acid Sigma Aldrich N4382 Y. enterocolitica cells used are resistant to nalidixic acid.
objective lens Olympus 1-U2B991 60X, 1.4 NA
Ozone cleaner Novascan PSD-UV4 Used to eliminate background fluorescence on glass cover slips.
potassium phosphate Sigma Aldrich 795488 M2G ingredient.
Red LED Thorlabs M625L3 Illuminates sample for phase contrast imaging. 625nm.
sCMOS camera Hamamatsu ORCA-Flash 4.0 V2 Camera for fluorescence imaging.
short pass filter Chroma ET700SP-2P8 Emission pathway.
Tube lens Thorlabs AC508-180-A f=180 mm, 2"
Yersinia enterocolitica dHOPEMTasd N/A N/A Strain AD4442, eYFP-YscQ
zero-order quarter-wave plate Thorlabs WPQ05M-514 Excitation pathway.

Referências

  1. Kapanidis, A. N., Uphoff, S., Stracy, M. Understanding Protein Mobility in Bacteria by Tracking Single Molecules. Journal of Molecular Biology. , (2018).
  2. Betzig, E., et al. Imaging intracellular fluorescent proteins at nanometer resolution. Science. 313 (5793), 1642-1645 (2006).
  3. Hess, S. T., Girirajan, T. P. K., Mason, M. D. Ultra-high resolution imaging by fluorescence photoactivation localization microscopy. Biophysical Journal. 91 (11), 4258-4272 (2006).
  4. Rust, M. J., Bates, M., Zhuang, X. W. Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM). Nature Methods. 3 (10), 793-795 (2006).
  5. Chen, T. Y., et al. Quantifying Multistate Cytoplasmic Molecular Diffusion in Bacterial Cells via Inverse Transform of Confined Displacement Distribution. Journal of Physical Chemistry B. 119 (45), 14451-14459 (2015).
  6. Mohapatra, S., Choi, H., Ge, X., Sanyal, S., Weisshaar, J. C. Spatial Distribution and Ribosome-Binding Dynamics of EF-P in Live Escherichia coli. mBio. 8 (3), (2017).
  7. Stracy, M., et al. Single-molecule imaging of UvrA and UvrB recruitment to DNA lesions in living Escherichia coli. Nature Communications. 7, 12568 (2016).
  8. Persson, F., Lindén, M., Unoson, C., Elf, J. Extracting intracellular diffusive states and transition rates from single-molecule tracking data. Nature Methods. 10 (3), 265-269 (2013).
  9. Bakshi, S., Choi, H., Weisshaar, J. C. The spatial biology of transcription and translation in rapidly growing Escherichia coli. Frontiers in Microbiology. 6, 636 (2015).
  10. Mustafi, M., Weisshaar, J. C. Simultaneous Binding of Multiple EF-Tu Copies to Translating Ribosomes in Live Escherichia coli. mBio. 9 (1), (2018).
  11. Michalet, X., Berglund, A. J. Optimal diffusion coefficient estimation in single-particle tracking. Physical Review E. 85 (6), (2012).
  12. Michalet, X. Mean square displacement analysis of single-particle trajectories with localization error: Brownian motion in an isotropic medium. Physical Review E Statistical, Nonlinear, and Soft Matter Physics. 82 (4 Pt 1), 041914 (2010).
  13. Backlund, M. P., Joyner, R., Moerner, W. E. Chromosomal locus tracking with proper accounting of static and dynamic errors. Physical Review E Statistical, Nonlinear, and Soft Matter Physics. 91 (6), 062716 (2015).
  14. Stracy, M., et al. Live-cell superresolution microscopy reveals the organization of RNA polymerase in the bacterial nucleoid. Proceedings of the National Academy of Sciences of the United States of America. 112 (32), E4390-E4399 (2015).
  15. Plochowietz, A., Farrell, I., Smilansky, Z., Cooperman, B. S., Kapanidis, A. N. In vivo single-RNA tracking shows that most tRNA diffuses freely in live bacteria. Nucleic Acids Research. 45 (2), 926-937 (2017).
  16. Koo, P. K., Mochrie, S. G. Systems-level approach to uncovering diffusive states and their transitions from single-particle trajectories. Physical Review E. 94 (5-1), 052412 (2016).
  17. Uphoff, S., Reyes-Lamothe, R., Garza de Leon, F., Sherratt, D. J., Kapanidis, A. N. Single-molecule DNA repair in live bacteria. Proceedings of the National Academy of Sciences of the United States of America. 110 (20), 8063-8068 (2013).
  18. Bakshi, S., Bratton, B. P., Weisshaar, J. C. Subdiffraction-Limit Study of Kaede Diffusion and Spatial Distribution in Live Escherichia coli. Biophysical Journal. 101 (10), 2535-2544 (2011).
  19. Bakshi, S., Siryaporn, A., Goulian, M., Weisshaar, J. C. Superresolution imaging of ribosomes and RNA polymerase in live Escherichia coli cells. Molecular Microbiology. 85 (1), 21-38 (2012).
  20. Uphoff, S., Sherratt, D. J., Kapanidis, A. N. Visualizing Protein-DNA Interactions in Live Bacterial Cells Using Photoactivated Single-molecule Tracking. JoVE. (85), e51177 (2014).
  21. Pavani, S. R. P., Piestun, R. Three dimensional tracking of fluorescent microparticles using a photon-limited double-helix response system. Optics Express. 16 (26), 22048-22057 (2008).
  22. Pavani, S. R. P., et al. Three-dimensional, single-molecule fluorescence imaging beyond the diffraction limit by using a double-helix point spread function. Proceedings of the National Academy of Sciences of the United States of America. 106 (9), 2995-2999 (2009).
  23. Rocha, J. M., et al. Single-molecule tracking in live Yersinia enterocolitica reveals distinct cytosolic complexes of injectisome subunits. Integrative Biology. 10 (9), 502-515 (2018).
  24. Lew, M. D., von Diezmann, A. R. S., Moerner, W. E. Easy-DHPSF open-source software for three-dimensional localization of single molecules with precision beyond the optical diffraction limit. Protocol Exchange. , (2013).
  25. Biteen, J. S., et al. Super-resolution imaging in live Caulobacter crescentus cells using photoswitchable EYFP. Nature Methods. 5 (11), 947-949 (2008).
  26. Huang, F., et al. Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms. Nature Methods. 10 (7), 653-658 (2013).
  27. Hoogendoorn, E., et al. The fidelity of stochastic single-molecule super-resolution reconstructions critically depends upon robust background estimation. Scientific Reports. 4, 3854 (2014).
  28. Paintdakhi, A., et al. Oufti: An integrated software package for high-accuracy, high-throughput quantitative microscopy analysis. Molecular microbiology. 99 (4), 767-777 (2016).
  29. Rocha, J. M., Corbitt, J., Yan, T., Richardson, C., Gahlmann, A. Resolving Cytosolic Diffusive States in Bacteria by Single-Molecule Tracking. bioRxiv. , 483321 (2018).
  30. Lee, A., Tsekouras, K., Calderon, C., Bustamante, C., Presse, S. Unraveling the Thousand Word Picture: An Introduction to Super-Resolution Data Analysis. Chemical Reviews. 117 (11), 7276-7330 (2017).
  31. Los, G. V., et al. HaloTag: A Novel Protein Labeling Technology for Cell Imaging and Protein Analysis. ACS Chemical Biology. , (2008).
  32. Gautier, A., et al. An Engineered Protein Tag for Multiprotein Labeling in Living Cells. Chemistry & Biology. 15 (2), 128-136 (2008).
  33. Bisson-Filho, A. W., et al. Treadmilling by FtsZ filaments drives peptidoglycan synthesis and bacterial cell division. Science. 355 (6326), 739-743 (2017).
  34. Douglass, K. M., Sieben, C., Archetti, A., Lambert, A., Manley, S. Super-resolution imaging of multiple cells by optimised flat-field epi-illumination. Nature Photonics. 10 (11), 705-708 (2016).
  35. Zhao, Z., Xin, B., Li, L., Huang, Z. L. High-power homogeneous illumination for super-resolution localization microscopy with large field-of-view. Optics Express. 25 (12), 13382-13395 (2017).
  36. Yan, T., Richardson, C. J., Zhang, M., Gahlmann, A. Computational Correction of Spatially-Variant Optical Aberrations in 3D Single Molecule Localization Microscopy. bioRxiv. , 504712 (2018).
  37. Gahlmann, A., Moerner, W. E. Exploring bacterial cell biology with single-molecule tracking and super-resolution imaging. Nature Reviews Microbiology. 12 (1), 9-22 (2014).
  38. Liu, Z., Lavis, L. D., Betzig, E. Imaging live-cell dynamics and structure at the single-molecule level. Mol Cell. 58 (4), 644-659 (2015).
  39. Berglund, A. J. Statistics of camera-based single-particle tracking. Physical Review E. 82 (1), 011917 (2010).
  40. Parry, B. R., et al. The bacterial cytoplasm has glass-like properties and is fluidized by metabolic activity. Cell. 156 (1-2), 183-194 (2014).
  41. English, B. P., et al. Single-molecule investigations of the stringent response machinery in living bacterial cells. Proceedings of the National Academy of Sciences of the United States of America. 108 (31), E365-E373 (2011).
  42. Niu, L. L., Yu, J. Investigating intracellular dynamics of FtsZ cytoskeleton with photoactivation single-molecule tracking. Biophysical Journal. 95 (4), 2009-2016 (2008).
  43. Coquel, A. S., et al. Localization of protein aggregation in Escherichia coli is governed by diffusion and nucleoid macromolecular crowding effect. PLoS Computational Biology. 9 (4), e1003038 (2013).
  44. Nenninger, A., Mastroianni, G., Mullineaux, C. W. Size Dependence of Protein Diffusion in the Cytoplasm of Escherichia coli. Journal of Bacteriology. 192 (18), 4535-4540 (2010).
  45. Dix, J. A., Verkman, A. S. Crowding effects on diffusion in solutions and cells. Annual Review of Biophysics. 37, 247-263 (2008).
  46. Elliott, L. C., Barhoum, M., Harris, J. M., Bohn, P. W. Trajectory analysis of single molecules exhibiting non-brownian motion. Physical Chemistry Chemical Physics. 13 (10), 4326-4334 (2011).

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Rocha, J. M., Gahlmann, A. Single-Molecule Tracking Microscopy – A Tool for Determining the Diffusive States of Cytosolic Molecules. J. Vis. Exp. (151), e59387, doi:10.3791/59387 (2019).

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