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Quantitative Image Analysis of Membrane Microdomains Labelled by Fluorescently Tagged Proteins in Arabidopsis thaliana and Nicotiana benthamiana
定量图像分析拟南芥和本氏烟草中荧光标记蛋白质示踪的膜微区   

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Abstract

We have recently characterized co-existing membrane microdomains that are labeled by different proteins in living plant cells (Jarsch et al., 2014). For this approach we first created a digital fingerprint for each of the twenty marker proteins using quantitative image analysis. Here we recorded parameters such as domain size, density and shape based on image segmentation. We found highly reproducible patterns of any of the proteins over a large number of biological replicates. Furthermore we exclusively acquired images from lowly expressing cells and chose our imaging conditions in a way that resulted in images where no pixel was saturated.
This protocol describes in detail the methods that have been used to analyze quantitative differences in localization of members of the remorin protein family in membrane microdomains of Arabidopsis thaliana and Nicotiana benthamiana (Jarsch et al., 2014). The proteins were either individually or pairwise expressed as fluorophore fusions in the respective plant. Image acquisition was performed using standard Confocal Laser Scanning Microscopy (CLSM) and image analysis was performed using ImageJ.

[Introduction] Since confocal laser-scanning or other state-of-the-art fluorescence microscopes are nowadays often regarded as standard equipment a modern research institution should have, the amount of published cell biological data has massively increased over the last years. This certainly also correlates with the availability of an increasing number of fluorophores and corresponding expression vectors that have made it comparably easy to generate large numbers of tagged proteins. One main concern about showing microscopy images in publications is the subjectivity they have been selected with. In addition, and certainly very unfortunate in several cases, the scientific community as well as reviewers of manuscripts have requested ‘no background-high fluorescence’ images from the authors. As a consequence researchers often started selecting the images based on aesthetic aspects rather than showing the most representative ones. Furthermore the majority of images are based on strong over-expression of proteins. Therefore quantitative image analysis has become an absolute requirement in order to make robust statements on cell biological observations and the frequency with which they have been observed. However, this does not only require gaining novel skills but also high numbers of biological repetitions in a standardized way. Furthermore, it should be the ultimate goal to work under conditions where the protein of interest is expressed at native levels. While this may have to be overcome for lowly abundant proteins, researchers should nevertheless aim for similar levels and may thus accept more background noise in the images.
It should be noted that all parameters and protocol specifications provided within this protocol have been optimized for the expression we used in a current study (Jarsch et al., 2014). Most likely they have to be adapted for any analyses in different laboratories.

Keywords: Cell biology(细胞生物学), Quantitative image analysis(图像定量分析), Microdomain(微区), Arabidopsis(拟南芥)

Materials and Reagents

  1. 4-5 weeks old Nicotiana benthamiana (N. benthamiana) plants (soil grown)
  2. 4-5 weeks individually potted stable transgenic Arabidopsis thaliana (A. thaliana) lines expressing AvrPto under control of a dexamethasone (DEX)-inducible promoter as described previously (Hauck et al., 2003; Tsuda et al., 2012) (lines available upon request from the authors of the original publication) (soil grown)
  3. Agrobacterium strains
    1. GV3101 C58 mp90RK for constructs in pAM-PAT:35S and pH7YGW2
    2. Agl1 for constructs in pUbi and pGWB1-based vectors
  4. MgCl2 (Carl Roth, catalog number: 2189 )
  5. MES KOH (pH 5.6) (Carl Roth, catalog number: 4256.2 )
  6. Acetosyringone (Sigma-Aldrich, catalog number: D134406 )
  7. Dexamethasone (Sigma-Aldrich, catalog number: D4902 )
  8. EtOH
  9. Silwett L-77 (Leu+Gygax AG, catalog number: CH-SL7-033-01 )
  10. Infiltration solution for Agrobacterium tumefaciens-mediated transient transformation of N. benthamiana or A. thaliana (see Recipes)
  11. DEX-solution for pre-treatment of AvrPto-DEX inducible A. thaliana (see Recipes)

Equipment

  1. Table-top centrifuge for 2 ml tubes (Eppendorf, model: 5424 )
  2. Spectrometer (Pharmacia Biotech (now: GE Healthcare, Ultrospec 3000 pro)
  3. 1 ml syringes (Braun catalog number: 9161406V )
  4. 2 ml reaction tubes for centrifugation (SARSTEDT AG, catalog number: 72.695.500 )
  5. 50 ml spray flask (Carl Roth, Karlsruhe, catalog number: EP66 )
  6. 4 mm biopsy punch or similar tool (cork borer) to excise leaf discs (recommended: Produkte für Medizintechnik (pfm), 4 mm, catalog number: 49401 )
  7. Microscope cover glasses (Carl Roth, 24 x 60 mm, #1,5 (170 micron), catalog number: H878 )
  8. Microscope slides (Langenbrick, 76 x 26 x 1 mm, catalog number: 03-0010/90 )
  9. Confocal microscope (Leica Microsystems, model: SP5 )
  10. Leica DFC350FX digital camera
  11. Objectives used for this experiment: HC PL APO 20x/0.70 ImmCorr CS and HCX PL APO 63x/1.20 W CORR CS)
  12. Excitation using an argon laser (100 mW, Lasos LGK 7872 ML05 SP5) [for YFP: 514 nm (excitation), 525-600 nm (emission); for CFP: 456 nm (excitation); 475-620 nm (emission)]

Software

  1. ImageJ (Plug-in supplemented version: Fiji)
  2. Intensity Correlation Analysis Bundle from the Wright Cell Imaging Facility (WCIF Image) (Li et al., 2004)

Procedure

A. tumefaciens-mediated transient transformation of N. benthamiana

  1. Culture bacterial strains carrying the constructs of choice in 5 ml liquid LB under appropriate antibiotic selection overnight (ON) at 28 °C.
  2. Harvest bacteria by centrifugation in 2 ml reaction tubes at 6,500 x g and resuspend in infiltration solution. For pUbi-YFP constructs use a final OD600 of 0.01 and for pAM-PAT-35S-CFP/YFP constructs use a final OD600 of 0.2-0.4.
  3. To improve expression, add an A. tumefaciens Agl1 strain containing a construct mediating expression of the viral silencing inhibitor P19 (Voinnet et al., 2003) to each sample at a final OD600 of 0.1. Excess presence of the same type of RNA may cause RNA degradation by the plant as part of the immune response to a putative viral infection. P19 helps to reduce such RNA degradation.
  4. Incubate the solution for 2 h in the dark at room temperature (RT).
  5. Subsequently syringe-infiltrate the youngest fully expanded leaves with the individual samples using a 1 ml syringe (as demonstrated in Video 1). The infiltrated area will be clearly visible. Use sufficient infiltration solution to cover sufficient leave area for later imaging (usually 100-300 µl).

    Video 1. Infiltration of Agrobacterium tumefaciens into Nicotiana benthamiana leaves

  6. Continue plant growth for 2 days prior to imaging. Water plants moderately. The time between infiltration and imaging strongly depends on the type of protein (e.g. solubility of transmembrane), the used promoters and the growth conditions of the N. benthamiana plants.

A. tumefaciens-mediated transient transformation of A. thaliana

  1. 24 h prior to infiltration, spray five to six weeks old plants grown under short-day conditions with the 2 μM DEX solution containing 0.04% Silwett-77. Spray under fume hood to prevent inhalation of Silwet-77. Turn plants multiple times and ensure leaves are completely covered by a thin film of liquid until drip-of. In case of drops forming on the leave surface with the liquid not spreading to make a film, slightly increase the Silwett-77 concentration.
  2. Prepare the infiltration solution containing A. tumefaciens strains of your choice as described for transformation of N. benthamiana above.
  3. Subsequently syringe-infiltrate the youngest fully expanded leaves with the individual samples using a 1 ml syringe (see Video 1 for the corresponding infiltration procedure in N. benthamiana). The infiltrated area will be clearly visible. Use sufficient infiltration solution to cover sufficient leave area for later imaging (usually 100-300 µl).
  4. Grow plants for 2 days for imaging, water moderately.


  1. Sample preparation for image acquisition
    1. For microscopic analysis, cut leaf discs from infiltrated areas using biopsy punches or cork borers.
    2. Prepare cover glasses with drops of water.
    3. Mount lower side of the leaf on cover slips on top of water drops, make sure there is no air between leaf tissue and glass.
    4. Add microscope slides and image directly.

  2. Image acquisition
    1. In transiently expressing systems, choose lowly expressing cells. To be able to differentiate between autofluorescence and real fluorophore signal, choose a non-infiltrated cell area and adjust imaging settings in order to eliminate background. Use these setting to search for cells displaying non-saturating intensities. In an 8-bit greyscale image these values should ideally not exceed 100 (out of 255 possible grey levels).
    2. For stably expressing system, use lines, if possible, expressing your protein of interest under control of its native promoter (ideally in a mutant background). Select lines where expression of the transgene is similar to levels of the endogenous transcript (e.g. by quantitative Real Time PCR) or compare protein levels if an antibody against the endogenous protein is available.
    3. For single pictures of PM surfaces, use 2 line averages per frame.
    4. For co-localization experiments (especially when using fluorophores with partially overlapping excitation/emission spectra), use the microscope in the sequential scanning mode to avoid ‘bleed-through’ between the channels.
    5. Export images as .tif files for further processing or use original microscope files if readable by the processing software.
    6. To be able to compare images, make sure settings are identical between different takes (e.g. laser intensity, gain, offset, scan speed, etc.…)

  3. Image processing
    Quantitative analysis of subcellular single protein localization: The analysis includes the creation of a mask, which will be overlaid with the original image for measurements.
    1. Open individual pictures of single infiltrations in Fiji.
    2. If necessary, change properties according to your image setting (adjust pixel and voxel size).
    3. Change Image → Type to 8-bit.
    4. Image → Duplicate image and continue working on the duplicated image.
    5. Run Process → Filters → Mean filter of 2 pixels.
    6. Subject to Process → Subtract background choosing a rolling ball radius of 20 pixels (be aware that background subtraction is critical and should be carefully evaluated prior to application. E. g. measure the size of the objects you are interested in and make sure the radius you chose is significantly bigger than your biggest object!).
    7. Image → Adjust → Threshold to segment the image in foreground and background, try this for a number of different images and then decide on a default setting to process all images you want to compare.
    8. Process → Binary → Convert to mask.
    9. Process → Binary → Create a binary image.
    10. In case of overlapping regions of interest, apply Plugins → Watershed.
    11. Choose Analyze → Set measurements and define which parameters you would like to analyze, tick “add to Roi manager”.
    12. Analyze particles (the output will be a table including all parameters previously defined in the “Set measurements” menu).
    13. Select the original image, click “Show all” and “Measure” in the ROI manager.
    14. The original image will show all regions selected by the mask for measurements, the table will now include a second set of measurements for the original image.
    15. To perform statistical analysis on the results we recommend R using ANOVA and Tukey’s honestly significant difference.

Representative data



Figure 1. Creation of a binary image to segment the picture. The mask B is used as an overlay onto the original image A to carry out the desired analysis on a non-processed picture.


Figure 2. Intensity correlation analysis and simulation of a random distribution. Two fusion proteins A, B were expressed to assess intensity correlation. The merged imaged C should be used to confirm that the ROI was chosen appropriately, including intensities in both channels and excluding regions of the image without signal or containing out-of-focus intensities. To simulate a random distribution of the two proteins D-F one of the two images is flipped either horizontally or vertically E and again the intensity correlation analysis is carried out using a ROI chosen to exclude parts of the picture which are not suitable.

Notes

  1. To optimize the segregation process, alter the rolling ball radius for the background subtraction or the threshold settings. In case of salt and pepper noise, addition of “Erode” and “Dilate” steps on the binary image might be necessary.
    The steps for the creation of the mask can be automatized using a Macro (see example).
    Example Macro:
    run("Mean...", "radius=2");
    run("Subtract Background...", "rolling=20");
    setAutoThreshold("Default");
    //run("Threshold...");
    setThreshold(0, 22);
    setOption("BlackBackground", false);
    run("Convert to Mask");
    run("Make Binary");
    run("Erode");
    run("Erode");
    run("Dilate");
    run("Dilate");
    run("Watershed");
    run("Save");
    run("Close");
  2. Intensity correlation analysis to assess of pairwise expressed proteins in a quantitative manner
    1. Open single images in ImageJ.
    2. Subject to Process → Filters → Mean Blur Filter of 2 pixels.
    3. Apply Process → Subtract background with a rolling ball radius of 20 pixels.
    4. Draw a region of interest around the area containing the intensities you are interested in, if necessary (exclude regions without signal, auto-fluorescence of out-of focus fluorescence).
    5. Open the Intensity correlation Plugin from WCIF ImageJ (link for download: http://www.uhnresearch.ca/facilities/wcif/fdownload.html).
    6. Choose “use ROI” if applicable.
    7. Tick options you are interested in, run.
    8. The Pearson correlation coefficient (Rr) (Manders et al., 1992) and the Manders overlap coefficient (R2) (Manders et al., 1993) as well as pixel ratios (Ch1: Ch2), Mander’s Colocalization coefficients for channel 1 (M1) and channel 2 (M2), the number of pixel pairs that have a positive PDM value (N+ve), the number of pixels pairs in the images that where at least one of the pixel pairs is above zero (Ntotal) and the Intensity Correlation Quotient (ICQ) will be displayed in a separate window showing a table that can be saved as a excel file.
    9. To define significantly positive or negative covariance of intensities, a simulated random distribution should be addressed by flipping or rotating one of the images. The results of at least 10 repetitions can be statistically analyzed using standard student TTest.

Recipes

  1. Infiltration solution for A. tumefaciens mediated transient transformation of N. benthamiana or A. thaliana
    10 mM MgCl2
    10 mM MES KOH (pH 5.6)
    150 μM acetosyringone
    Agrobacteria in appropriate OD
  2. DEX-solution for pre-treatment of AvrPto-DEX inducible A. thaliana
    2 μM dexamethasone
    1% EtOH
    0.04% Silwett L-77

Acknowledgments

This work was kindly supported by the Sonderforschungsbereich SFB924 funded by the Deutsche Forschungsgemeinschaft (DFG). The original work was published in Jarsch et al. (2014).

References

  1. Hauck, P., Thilmony, R. and He, S. Y. (2003). A Pseudomonas syringae type III effector suppresses cell wall-based extracellular defense in susceptible Arabidopsis plants. Proc Natl Acad Sci U S A 100(14): 8577-8582.
  2. Jarsch, I. K., Konrad, S. S., Stratil, T. F., Urbanus, S. L., Szymanski, W., Braun, P., Braun, K. H. and Ott, T. (2014). Plasma membranes are subcompartmentalized into a plethora of coexisting and diverse microdomains in Arabidopsis and Nicotiana benthamiana. Plant Cell 26(4): 1698-1711.
  3. Li, Q., Lau, A., Morris, T. J., Guo, L., Fordyce, C. B. and Stanley, E. F. (2004). A syntaxin 1, Galpha(o), and N-type calcium channel complex at a presynaptic nerve terminal: analysis by quantitative immunocolocalization. J Neurosci 24(16): 4070-4081.
  4. Manders, E. M., Verbeek, F. J., and Aten, J. A. (1993). Measurement of co-localization of objects in dual-colour confocal images. J Microscopy 169: 375-382.
  5. Manders, E. M., Stap, J., Brakenhoff, G. J., van Driel, R. and Aten, J. A. (1992). Dynamics of three-dimensional replication patterns during the S-phase, analysed by double labelling of DNA and confocal microscopy. J Cell Sci 103 (Pt 3): 857-862.
  6. Tsuda, K., Qi, Y., Nguyen le, V., Bethke, G., Tsuda, Y., Glazebrook, J. and Katagiri, F. (2012). An efficient Agrobacterium-mediated transient transformation of Arabidopsis. Plant J 69(4): 713-719.
  7. Voinnet, O., Rivas, S., Mestre, P. and Baulcombe, D. (2003). An enhanced transient expression system in plants based on suppression of gene silencing by the p19 protein of tomato bushy stunt virus. Plant J 33(5): 949-956.

简介

我们最近描述了在活植物细胞中由不同蛋白质标记的共存膜微结构域(Jarsch等人,2014)。对于这种方法,我们首先使用定量图像分析为二十个标记蛋白质中的每一个创建数字指纹。这里我们基于图像分割记录诸如域大小,密度和形状的参数。我们发现任何蛋白质的高度可重复的模式在大量的生物复制。此外,我们专门从低表达细胞中获取图像,并选择我们的成像条件以产生没有像素饱和的图像。
该方案详细描述了用于分析成员的定位差异的方法的拟南芥(Arabidopsis thaliana)和本塞姆氏烟草(Nicotiana benthamiana)的膜微结构域中的remorin蛋白家族(Jarsch等人,2014)。蛋白质单独地或成对地表达为相应植物中的荧光团融合体。使用标准共焦激光扫描显微镜(CLSM)进行图像采集,并使用ImageJ进行图像分析。

[简介] 由于共聚焦激光扫描或其他状态现代荧光显微镜如今经常被认为是现代研究机构应该具有的标准设备,已公布的细胞生物学数据的数量在过去几年中大量增加。这当然也与增加数量的荧光团和相应的表达载体的可用性相关,所述荧光团和相应的表达载体使得其可以相当容易地产生大量的标记蛋白。关于在出版物中显示显微镜图像的一个主要关心是它们被选择的主观性。此外,当然在一些情况下非常不幸,科学界以及手稿审稿人都要求作者没有背景高荧光的图像。因此,研究人员经常开始基于美学方面选择图像,而不是显示最具代表性的图像。此外,大多数图像基于蛋白质的强过表达。因此,定量图像分析已成为绝对要求,以便对细胞生物学观察和观察它们的频率做出鲁棒的声明。然而,这不仅需要获得新的技能,而且需要以标准化的方式进行大量的生物重复。此外,它应该是在感兴趣的蛋白质以天然水平表达的条件下工作的最终目标。虽然对于低丰度蛋白质可能需要克服这一点,但是研究人员应当针对相似的水平,并且因此可以在图像中接受更多的背景噪声。
应当注意,本协议中提供的所有参数和协议规范针对我们在当前研究中使用的表达进行优化(Jarsch等人,2014)。很可能,他们必须适应不同实验室的任何分析。

关键字:细胞生物学, 图像定量分析, 微区, 拟南芥

材料和试剂

  1. 4-5周龄的本氏烟草(本生烟草)植物(土壤生长)
  2. (DEX)诱导型启动子控制下表达AvrPto的4-5周单独盆栽的稳定转基因拟南芥(拟南芥)品系(Hauck >,2003; Tsuda等人,2012)(根据原始出版物的作者的请求可获得的行)(土壤生长)
  3. 土壤杆菌菌株
    1. 用于pAM-PAT:35S和pH7YGW2中构建体的GV3101 C58mp90RK
    2. Agl1用于基于pUbi和pGWB1的载体中的构建体
  4. MgCl 2(Carl Roth,目录号:2189)
  5. MES KOH(pH 5.6)(Carl Roth,目录号:4256.2)
  6. Acetosyringone(Sigma-Aldrich,目录号:D134406)
  7. 地塞米松(Sigma-Aldrich,目录号:D4902)
  8. EtOH
  9. Silwett L-77(Leu + Gygax AG,目录号:CH-SL7-033-01)
  10. 用于根癌土壤杆菌介导的瞬时转化的渗透溶液。 本bentiana 或 A。 thaliana (请参阅食谱)
  11. DEX溶液用于预处理AvrPto-DEX诱导型A。 thaliana (请参阅食谱)

设备

  1. 用于2ml管(Eppendorf,型号:5424)的台式离心机
  2. 光谱仪(Pharmacia Biotech(现在:GE Healthcare,Ultrospec 3000pro))
  3. 1ml注射器(Braun目录号:9161406V)
  4. 2ml用于离心的反应管(SARSTEDT AG,目录号:72.695.500)
  5. (Carl Roth,Karlsruhe,目录号:EP66)
  6. 4 mm活检穿孔器或类似工具(软木钻孔器)切除叶盘(推荐:4 mm,目录号:49401的ProduktefürMedizintechnik(pfm))
  7. 显微镜盖玻片(Carl Roth,24×60mm,#1,5(170微米),目录号:H878)
  8. 显微镜载玻片(Langenbrick,76×26×1mm,目录号:03-0010/90)
  9. 共焦显微镜(Leica Microsystems,型号:SP5)
  10. Leica DFC350FX数码相机
  11. 本实验使用的目标:HC PL APO 20x/0.70 ImmCorr CS和HCX PL APO 63x/1.20 W CORR CS)
  12. 使用氩激光器(100mW,Lasos LGK 7872ML05SP5)[对于YFP:514nm(激发),525-600nm(发射)]进行激发; 对于CFP:456nm(激发); 475-620nm(发射)]

软件

  1. ImageJ(插件补充版本:Fiji)
  2. 来自Wright细胞成像设备的强度相关分析束(WCIF图像)(Li等人,2004)

程序

A。 tumefaciens - 介导的瞬时转化。 本bent

  1. 携带选择的构建体在5ml中的培养菌株 液体LB在适当的抗生素选择下在28℃过夜(ON) ℃。
  2. 通过在2ml反应管中离心收获细菌 6,500×g 并重悬于浸润溶液中。 对于pUbi-YFP 构建体使用0.01的最终OD <600>和对于pAM-PAT-35S-CFP/YFP 构建体使用0.2-0.4的最终OD <600>。
  3. 为了改善表达, 添加 A。 tumefaciens Agl1菌株 病毒沉默抑制剂P19的表达(Voinnet等,2003) 以最终OD 600为0.1的每个样品。 过多存在相同类型   的RNA可引起植物作为免疫的一部分的RNA降解 对假定的病毒感染的反应。 P19有助于减少这种RNA 退化
  4. 在室温(RT)下在黑暗中孵育溶液2小时
  5. 随后注射器渗入最年轻的完全扩张的叶 与单个样品使用1ml注射器(如 视频1)。 渗透区域将清晰可见。 使用充分 浸润溶液以覆盖足够的离开面积用于以后成像 (通常为100-300μl)
    视频1. 根癌土壤杆菌渗入本塞姆氏烟草叶
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  6. 在成像前继续植物生长2天。 水生植物 适度地。 渗透和成像之间的时间强烈依赖 对于蛋白质的类型(例如跨膜的溶解度),使用的 启动子和本氏烟草植物的生长条件。

A。 tumefaciens - 介导的瞬态转换 A。 thaliana

  1. 在浸润前24小时,喷雾生长5至6周龄的植物 在短日条件下用2μMDEX溶液含有0.04% Silwett-77。 在通风橱下喷洒,以防止吸入Silwet-77。 多次转动植物,确保叶子被完全覆盖   液体薄膜直到滴液。 在液滴形成的情况下 离开表面,液体不扩散,形成薄膜 增加Silwett-77浓度
  2. 准备渗透 溶液。 tumefaciens 菌株 用于N的变换。 本bent。
  3. 后来 注射器浸润最年轻的完全扩张的叶子 单个样品使用1ml注射器(见视频1的 相应的渗透程序。 本bent)。 渗透   区域将清晰可见。 使用足够的浸润溶液 覆盖足够的离开区域用于以后成像(通常为100-300μl)
  4. 生长植物2天成像,适度水。


  1. 图像采集的样品准备
    1. 对于显微镜分析,使用活检穿孔器或软木钻孔器从浸润区域切割叶盘
    2. 用水滴准备护目镜。
    3. 将叶片的下侧安装在水滴顶部的盖玻片上,确保叶片组织和玻璃之间没有空气。
    4. 直接添加显微镜幻灯片和图像。

  2. 图像采集
    1. 在瞬时表达系统中,选择低表达细胞。 成为 能够区分自体荧光和真实荧光团 信号,选择未浸润的细胞区域并调整成像设置 以消除背景。 使用这些设置搜索单元格 显示非饱和强度。 在8位灰度图像中   值应理想地不超过100(在255个可能的灰度级中)。
    2. 对于稳定表达系统,使用线,如果可能, 在其天然启动子的控制下表达目的蛋白质   (理想地在突变背景中)。 选择行的表达式 转基因的水平类似于内源转录物的水平(例如) 定量实时PCR)或比较抗体的蛋白质水平 针对内源性蛋白质。
    3. 对于PM表面的单张照片,请使用每帧2行平均值
    4. 用于共定位实验(特别是当使用荧光团时) 与部分重叠的激发/发射光谱),使用 显微镜在顺序扫描模式下避免"渗透" 通道之间。
    5. 将图像导出为.tif文件以供进一步处理,或者如果处理软件可读,则使用原始显微镜文件
    6. 要能够比较图像,请确保设置相同 (例如激光强度,增益,偏移,扫描速度,等)

  3. 图像处理
    亚细胞单蛋白定位的定量分析:分析包括创建一个掩模,它将覆盖原始图像进行测量。
    1. 在斐济打开单个渗透的单个图片。
    2. 如果需要,根据图像设置更改属性(调整像素和体素大小)。
    3. 更改图像→键入到8位。
    4. 图像→复制图像并继续处理复制的图像。
    5. 运行过程→过滤器→2个像素的平均过滤器
    6. 根据过程→减去背景选择滚动球 半径为20像素(注意背景减除是至关重要的 并应在使用前仔细评估。 E. 测量 您感兴趣的对象的大小,并确保半径 你选择的是比你最大的对象大得多!)。
    7. 图像→调整→阈值以分割前景图像和 背景,尝试这个为一些不同的图像,然后决定   用于处理要比较的所有图像的默认设置
    8. 过程→二进制→转换为屏蔽。
    9. 过程→二进制→创建二进制图像。
    10. 如果感兴趣的区域重叠,请应用插件→流域。
    11. 选择分析→设置测量并定义要分析的参数,勾选"添加到Roi管理器"
    12. 分析粒子(输出将是包括先前在"设置测量"菜单中定义的所有参数的表格)。
    13. 选择原始图像,在ROI管理器中单击"全部显示"和"测量"
    14. 原始图像将显示由遮罩选择的所有区域 测量,该表现在将包括第二组测量 为原始图像。
    15. 为了对结果进行统计分析,我们推荐R使用ANOVA和Tukey的诚实显着性差异。

代表数据



图1.创建二进制图像以分割图片。掩码B用作原始图像A上的叠加层,以对未处理的图片执行所需的分析。


图2.强度相关分析和随机分布的模拟。表达两种融合蛋白A,B以评估强度相关性。合并的成像C应该用于确认ROI被适当地选择,包括在两个通道中的强度,并且排除没有信号或包含离焦强度的图像的区域。为了模拟两个蛋白质D-F的随机分布,两个图像之一被水平或垂直E翻转,并且使用选择的ROI来进行强度相关分析,以排除不适合的图片部分。

笔记

  1. 为了优化分离过程,改变滚动球半径用于背景扣除或阈值设置。 在盐和胡椒噪声的情况下,可能需要在二进制图像上添加"Erode"和"Dilate"步骤。
    创建掩码的步骤可以使用宏自动化(参见示例)。
    示例宏:
    run("Mean ...","radius = 2");
    run("Subtract Background ...","rolling = 20");
    setAutoThreshold("Default");
    //run("Threshold ...");
    setThreshold(0,22);
    setOption("BlackBackground",false);
    运行("转换为掩码");
    运行("Make Binary");
    运行("Erode");
    运行("Erode");
    run("Dilate");
    run("Dilate");
    run("Watershed");
    运行("保存");
    运行("关闭");
  2. 强度相关分析以定量方式评估成对表达的蛋白质
    1. 在ImageJ中打开单个图像。
    2. 按照过程→过滤器→平均模糊过滤器,2像素。
    3. 应用过程→用20像素的滚球半径减去背景
    4. 在包含强度的区域周围绘制感兴趣区域   你有兴趣,如果有必要(排除没有信号的地区, 离焦荧光的自发荧光)。
    5. 打开 强度相关从WCIF ImageJ插件(链接下载: http://www.uhnresearch.ca/facilities/wcif/fdownload.html)。
    6. 如果适用,请选择"使用投资回报率"
    7. 勾选您感兴趣的选项,运行。
    8. Pearson相关系数(Rr)(Manders等人,1992)和 Manders重叠系数(R2)(Manders等人,1993)以及 像素比(Ch1:Ch2),Mander的Colocalization系数 通道1(M1)和通道2(M2),具有a的像素对的数量   正PDM值(N + ve),图像中的像素对的数量 其中像素对中的至少一个高于零(Ntotal)和 强度相关项(ICQ)将单独显示   窗口,显示可以另存为excel文件的表格
    9. 至 定义显着的正或负的强度协方差,a 模拟随机分布应通过翻转或 旋转图像之一。 至少10次重复的结果可以 使用标准学生TTest进行统计分析。

食谱

  1. 用于A的渗透溶液。 tumefaciens 介导的 N的瞬时转化。 本bentiana 或 A。 thaliana
    10mM MgCl 2/
    10mM MES KOH(pH 5.6)
    150μM乙酰丁香酮 土壤杆菌在适当的OD
  2. DEX溶液用于预处理AvrPto-DEX诱导型A。 thaliana
    2μM地塞米松
    1%EtOH
    0.04%Silwett L-77

致谢

这项工作得到了德意志交易所(DFG)资助的Sonderforschungsbereich SFB924的支持。 原创作品发表在Jarsch (2014)。

参考文献

  1. Hauck,P.,Thilmony,R.and He,S.Y。(2003)。 A pseudo emonas syringae type III effector suppresses cell wall-based extracellular defence in易感的拟南芥植物。 Proc Natl Acad Sci USA 100(14):8577-8582。
  2. Jarsch,I.K.,Konrad,S.S.,Stratil,T.F.,Urbanus,S.L.,Szymanski,W.,Braun,P.,Braun,K.H.and Ott,T。(2014)。 等离子膜在拟南芥中亚区域化为多个共存且多样的微结构域, 26(4):1698-1711。
  3. Li,Q.,Lau,A.,Morris,T.J.,Guo,L.,Fordyce,C.B。和Stanley,E.F。(2004)。 突触前神经末梢的syntaxin 1,Galpha(o)和N型钙通道复合物:assay by quantitative immunocolocalization。 J Neurosci 24(16):4070-4081。
  4. Manders,E.M.,Verbeek,F.J。,和Aten,J.A。(1993)。 测量双色共焦图像中物体的共定位。 J Microscopy 169:375-382。
  5. Manders,E.M.,Stap,J.,Brakenhoff,G.J.,van Driel,R。和Aten,J.A。(1992)。 S期三维复制模式的动力学,通过双重标记DNA和共聚焦 显微镜。细胞科学 103(Pt 3):857-862。
  6. Tsuda,K.,Qi,Y.,Nguyen le,V.,Bethke,G.,Tsuda,Y.,Glazebrook,J.and Katagiri,F。(2012)。 有效的土壤杆菌 - 介导的拟南芥的瞬时转化 69(4):713-719。
  7. Voinnet,O.,Rivas,S.,Mestre,P。和Baulcombe,D。(2003)。 基于通过番茄丛生特技的p19蛋白对基因沉默的抑制而在植物中增强的瞬时表达系统 病毒。植物J 33(5):949-956。
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Copyright: © 2015 The Authors; exclusive licensee Bio-protocol LLC.
引用:Jarsch, I. K. and Ott, T. (2015). Quantitative Image Analysis of Membrane Microdomains Labelled by Fluorescently Tagged Proteins in Arabidopsis thaliana and Nicotiana benthamiana. Bio-protocol 5(11): e1497. DOI: 10.21769/BioProtoc.1497.
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