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May 2020

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Spatiotemporal Quantification of Cytosolic pH in Arabidopsis Pollen Tubes
拟南芥花粉管胞质pH的时空定量研究   

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Abstract

Ion-specific probes and fluorescent indicators have been key in establishing the role of ion signaling, namely calcium, protons, and anions, in plant development, providing a robust approach for monitoring spatiotemporal changes in intracellular ion dynamics. The integration of protons/pH in signaling mechanisms is especially important as reports of their biological functions continue to expand; however, attaining quantitative estimates with high spatiotemporal resolution in single cells poses a major research challenge. Here, we detail the use of the genetically encoded pH-sensitive pHluorin reporter expressed in Arabidopsis thaliana pollen tubes to assess cytosolic measurements with calibration to provide actual pH values. This technique enabled us to identify critical phenotypes and establish the importance of tip-focused pH gradient for pollen tube growth, although it can be adapted to other experimental systems.

Keywords: Intracellular pH (细胞内pH值), pH dynamics (pH动态), Phenotyping (表型), pHluorin calibration (荧光校正), Ratiometric biosensor (比率生物传感器)

Background

Fluorescent indicators and biosensors have been fundamental in establishing the role of ions and other molecules in the cell physiology of diverse biological systems. The development of a wide range of biosensors for monitoring ions, molecules, and even phytohormones in plants has greatly increased over recent decades (Hilleary et al., 2018; Walia et al., 2018). In particular, the spatiotemporal coordination of ion dynamics is essential for diverse cellular processes and signaling pathways. Genetically encoded probes such as the Ca2+ sensor CaMeleon have been extensively used to understand ion dynamics (Miyawaki et al., 1997; Nagai et al., 2004; Monshausen et al., 2008), which became an accessible tool through the generation of stable transgenic lines. The popularization of such approaches has allowed intracellular detection and monitoring, improving our understanding of the extensive role of Ca2+, especially in cell signaling, regulation, and communication (Feijó and Wudick, 2018; Walia et al., 2018). The specific expression of biosensors targeted to particular compartments or organelles, together with appropriate live-imaging and genetic tools, has led to the detection and visualization of Ca2+ waves in roots (Choi et al., 2014; Evans et al., 2016), propagation of electrical signals in leaves (Nguyen et al., 2018), Ca2+-based long-distance signaling (Toyota et al., 2018) and intercellular communication (Ngo et al., 2014). Addressing such phenomena at an organismal level elucidates how these signals are propagated, also showing the physiological integration across tissues and organs.


Although less understood than that of Ca2+, the role of pH in intracellular signaling has received increased attention, especially due to the fundamental nature of protons as water constituents and its function as a second messenger, as well as the calcium-proton interplay. Such implication is particularly relevant in pollen tubes, in which the intracellular pH is tightly regulated and the spatial gradient of cytosolic protons plays a major role in apical growth (Certal et al., 2008; Michard et al., 2008; Hoffmann et al., 2020). Substantial progress in the field has been supported by new methodologies enabling live-cell imaging with proper spatiotemporal resolution and timescales, while the quantification of intracellular ion concentration has been made possible by calibrating ratiometric probes with elevated signal-to-noise ratios and a suitable dynamic range of response. Ratiometric probes rely on a single fluorescent protein that emits different wavelengths when bound or unbound to a particular molecule/ion of interest. The ratio analysis is quantitatively reliable, allowing corrections related to image acquisition artifacts and differential expression levels of the probe throughout a cellular compartment. The present protocol describes the intracellular monitoring of protons in pollen tubes of Arabidopsis thaliana and the calibration procedure of the biosensor pHluorin (Miesenbock et al., 1998) after extraction of a cryptic intron and codon usage optimization (Hoffmann et al., 2020). To address the cytosolic proton dynamics in Arabidopsis pollen tubes, a stable transgenic line expressing the pH-sensitive ratiometric pHluorin was generated in wild-type and mutant backgrounds. The mutants investigated in Hoffmann et al. (2020) were of special interest for investigating H+ dynamics since they consisted of double- or triple-knockouts of H+-ATPases that sustained most of the H+ extrusion in the shank region of the pollen tube. The development of minimally invasive protocols enabling live imaging in pollen tubes showed a consistent spatiotemporal gradient, compatible with observations in other species, allowing the identification and characterization of mutant phenotypes (Michard et al., 2008; Certal et al., 2008; Hoffmann et al., 2020). The calibration protocol described herein required quantification of the respective signal coming from both emission channels while varying the cytosolic pH by exposing the biosensor to a diversified pH environment. Principles and experimental details described in the current protocol can be used and adjusted by other researchers to improve image acquisition procedures in diverse systems and calibration of distinct biosensors.

Materials and Reagents

  1. Safe-lock tubes, 1.5 ml (Eppendorf, catalog number: 0030120086)

  2. Glass-bottom dishes (ThermoFisher Scientific, catalog number: 150680)

  3. Glass microfiber filters (Sigma-Aldrich, catalog number: WHA1820047)

  4. Potassium chloride (Sigma-Aldrich, catalog number: P9333)

  5. Magnesium sulfate (Sigma-Aldrich, catalog number: 746452)

  6. Boric acid (Sigma-Aldrich, catalog number: B6768)

  7. Calcium chloride (Sigma-Aldrich, catalog number: C1016)

  8. HEPES (Sigma-Aldrich, catalog number: H3375)

  9. Sucrose (Sigma-Aldrich, catalog number: S7903)

  10. Nigericin sodium salt (Tocris Bioscience, catalog number: 4312)

  11. Sodium phosphate dibasic (Sigma-Aldrich, catalog number: S8282)

  12. Sodium phosphate monobasic (Sigma-Aldrich, catalog number: S7907)

  13. Agarose low gelling temperature (Sigma-Aldrich, catalog number: A9045)

  14. Germination medium (see Recipe 1)

  15. Stock solutions (see Recipe 2)

  16. Sodium phosphate buffer (see Recipe 3)

  17. Calibration solution (see Recipe 4)

Equipment

  1. Hot plate

  2. pH meter

  3. Vortex

  4. Fine needle-sharp tweezers (Sigma-Aldrich, catalog number: WHA1820047)

  5. Benchtop microcentrifuge (Eppendorf, model: 5415D)

  6. DeltaVision Imaging System (Applied Precision - GE, model: Elite)

    Note: Including an inverted microscope (Olympus, model: IX71), InsightSSI fluorescence illuminator, front-illuminated sCMOS camera (2560 × 2160, pixel size 6.45 μm), and 63 × 1.2 NA water immersion objective (Olympus, model: U-Plan S-Apo).

  7. Filter sets, excitation 390/18 nm (DAPI) and 475/28 nm (FITC); emission, 435/48 nm (DAPI) and 523/36 nm (FITC)

  8. Precise motorized X,Y stage

Software

  1. ImageJ (Multiple Kymograph plugin), Fiji (https://imagej.net/Fiji/Downloads)

  2. Statistical programming language R (R Core Team, 2020 – version 4.0.4 used here), RStudio recommended (RStudio Team, 2020 – version 1.4.1103 used here) and optionally, our custom-made analysis script CHUKNORRIS (Damineli et al., 2017)

  3. Optional use of the custom R script ‘CalibrateFromKymographs.R’ supplied as Supplementary Material

Procedure

  1. Pollen collection and sample preparation

    1. Prepare fresh liquid germination medium from stock solutions and adjust the pH to 7.5 (Recipe 1).

      Note: Store the stock solutions for the pollen germination medium at -20°C and prepare fresh germination medium on the day of the experiment.

    2. Grow Arabidopsis transgenic plants, expressing the ratiometric pHluorin under the LAT52 promoter (pLat52:pHluorin) (Hoffmann et al., 2020), in growth chambers under short-day photoperiod conditions (12 h light/12 h dark cycle) at 22°C with 70% humidity and a light intensity of ~100 μmol m-2 s−s to improve pollen integrity and density.

      Note: Growing Arabidopsis plants under short-day photoperiod conditions increases pollen quality and integrity, resulting in high germination rates (> 90%). Under these conditions, healthy plants take around 60 days to begin to flower. However, flowers grown under other photoperiod conditions can also be used.

    3. Collect flowers immediately after anthesis using thin tweezers and transfer to a 1.5-ml tube (no more than 100 flowers per tube – use 20-25 flowers per 10-mm dish).

      Notes:
      i)
      Start to collect flowers from the 10th silique. The first siliques produced have reduced pollen density and the germination rate is reduced;

      ii) Collect flowers preferentially at 3-5 h of the light exposure cycle. After that, flowers start to close and pollen viability decreases;

      iii) Density is very important for Arabidopsis pollen germination. It is recommended that 20-25 flowers per 10-mm dish be collected. The parameter used here to standardize pollen density is the number of flowers; however, pollen density could vary according to growth chamber conditions. Of relevance, pollen grains should cover the glass-bottom dish, avoiding either sparse or overcrowded conditions.

    4. Add 1 ml germination liquid medium.

    5. Vortex at high speed (~2,500 rpm) for 30-40 s.

    6. Centrifuge at 1,600 × g for 3 min.

    7. Remove the flowers and supernatant.

    8. Resuspend gently the pollen precipitate in 100 μl liquid germination medium.

      Note: For pollen precipitate resuspension, cut off the first few millimeters of the 200-μl tip to enlarge the aperture and avoid pollen grain damage.

    9. Melt 0.01% low melting agarose in 1 ml germination medium in a safe-lock tube (1.5-ml) for 30 s in the microwave.

    10. Cool down the agarose enough to touch the tube with bare hands, without allowing it to jellify.

    11. Add 100 μl agarose solution to the pollen precipitate and mix gently.

    12. Add 50 μl solution (pollen grains in solution + jellified germination medium) to each glass-bottom dish (volume sufficient to prepare four experimental dishes).

    13. Place the glass-bottom dishes on a hot plate at 50°C for 1 min.

      Note: Pollen grains are sensitive to high temperatures and prolonged heat can kill them. Keep dishes under the heat for no longer than 2 min, just enough time to allow the pollen grains to sink to the glass bottom to facilitate imaging under the inverted microscope.

    14. Remove the dishes and allow the agarose solution to jellify.

      Note: The jellification of the germination medium containing pollen grains allows the pollen tubes to grow while enabling changes in the liquid solution on top. This step is fundamental for the calibration procedure.

    15. Add 100 μl liquid germination medium on top of the jellified agarose pad containing pollen grains.

    16. Incubate the dishes at 22°C, preferentially in the dark.

    17. After 2-3 h, growing pollen tubes with a length ≥ 200 μm can be assayed.

      Note: After 2-3 h of incubation, experimental dishes should be kept in an ice tray to slow pollen tube elongation from the beginning of image acquisition until the end of the procedure; otherwise, the tube will elongate continuously and after a few hours, the pollen tube length will be different from that acquired at the beginning of the procedure.


      Steps 1-17 are illustrated in Figure 1.



      Figure 1. Sample preparation procedure. Schematic illustration of the sequence steps for dish preparation and the pHluorin calibration procedure in Arabidopsis pollen tubes. The round drawing represents the 10-mm diameter well of the glass-bottom dish.


  2. Calibration procedure and image acquisition

    1. Prepare 10 mM sodium phosphate buffer with molar ratios of mono- and dibasic forms appropriate for the following pHs: 5.8, 6.2, 6.6, 7.0, 7.4, 7.8, and 8.0; with 140 mM KCl and 30 µM nigericin (calibration solution – Recipes 3, 4 and Table 1).

      Note: Nigericin, a potassium ionophore that disrupts the membrane potential and intracellular H+ and K+ concentrations, is used to promote equilibrium between the pH in the cytosol and in the external solution.

    2. Remove the germination liquid medium from the dish with a pipette, retaining the agarose pad containing the growing pollen tubes.

    3. Add 100 μl of a given pH calibration solution.

    4. Wait 5 min for stabilization.

    5. Acquire time-lapse images of both channels (DAPI and FITC) every 4 s for 2 min for each growing pollen tube sampled at a given pH (Recipe 5).

      Notes:
      i)
      Apply the same acquisition protocol and microscope parameters to both experimental and calibration samples.

      ii) The Deltavision system was used to develop this protocol; however, the minimum imaging setup requirement to carry out the protocol would be any system capable of performing live-cell imaging with appropriate spatiotemporal resolution and timescales. Such a system should include an inverted microscope with a fluorescence source, a camera, and the appropriate emission/excitation filter set.

    6. Repeat steps 2-6 for all given pHs and replicates.

      Note: Acquire images of multiple tubes (10-20 replicates in individual tubes) at all pHs from at least two different dishes, but ideally three or more to avoid potential block effects.


      Table 1. Sodium phosphate buffer preparation from pH 5.8 to 8.0

      pH Volume (ml) of 1 M Na2HPO4 Volume (ml) of 1 M NaH2PO4
      5.8 0.79 9.21
      6.2 1.78 8.22
      6.6 3.52 6.48
      7.0 5.77 4.23
      7.4 7.74 2.26
      7.8 8.96 1.04
      8.0 9.32 0.68


  3. Kymograph extraction

    1. Generate kymographs from time-lapses.

      Watch a tutorial in Video 1.


      Video 1. Screen capture of the kymograph extraction procedure performed in ImageJ


    2. Open each file in ImageJ (Fiji recommended), splitting both DAPI and FITC channels.

    3. Trace a line along the midline of the pollen tube on the strongest channel using the 'segmented line' tool, starting from the shank and going to the tip. Make sure to extend the trace well beyond the pollen tube tip in order to sample enough background. It may be useful to start the trace at the last frame, for reference, and adjust the trace to make sure that it is roughly in the midline in every frame. Moreover, avoid the border of the shank with the observation window (Figure 2).



      Figure 2. Tracing for kymograph generation. Illustrative representation of the manual trace through the pollen tube midline drawn to generate the kymograph, using the Multiple kymograph plugin (ImageJ), averaging over a 7-pixel neighborhood along the trace for both pHluorin channels. Extending the trace out of the fluorescent image is fundamental to estimating the pixel intensity for background subtraction.


    4. Extract a kymograph along the midline, choosing a 7-pixel neighborhood using the 'Multiple Kymograph' plugin available under the Menu 'Analyze' in Fiji.

    5. Copy the line from one channel to the other using Command + Shift + E (on a Mac, replace ‘command’ with ‘control’ on Windows) and extract a kymograph as described in the previous step.

    6. Save each kymograph as text under 'File,' 'Save as,' 'Text Image.' To facilitate analysis, it is advisable to adopt a file-naming system; here, we recommend starting with the channel name and specifying the external pH and replicate number. Thus, each file acquired with the microscope will yield two kymographs named “FITC_5.8_1.txt” and “DAPI_ 5.8_1.txt,” in the case of the first replicate at pH 5.8. This file must have time as rows and space as columns, with the signal from the pollen tube on the left-hand side and the background on the right-hand side.


  4. Data analysis

    1. Perform a linear regression of the ratio values as a function of external pH.
      Option 1: R script provided here that requires essentially no programming experience.

      Note: We exemplify the data analysis workflow using both data from Hoffmann et al. (2020) and surrogate data generated with the script “GenerateSurrogateData.R” provided as Supplementary Material. The surrogate data were generated to mimic kymographs used in the pH calibration, employing an asymptotic curve to represent the tip signal with added noise and actual pH values.


      Watch a tutorial in Video 2.

      Video 2. Screen capture of the calibration script performed in RStudio

      The supplementary R script “CalibrateFromKymographs.R” implements all the steps required to generate the calibration curve from the kymographs obtained at different external pHs, provided the file-naming system specified in Section C.6. is followed strictly. Any naming discrepancies will produce errors.

      1. Open RStudio and open the file ‘CalibrateFromKymographs.R’ through the menu “File” and “Open File…” The required parameters will be specified in the “User defined section” of the script.

      2. Specify where your files are located (‘fl.dir’) and where you want the output to be saved (‘out.dir’). Make sure the directory slash is in the correct orientation for your operating system: ‘/’ for MacOs and ‘\’ for Windows.

      3. Specify the name of the channel that is the denominator in calculating the ratio (‘top.ch’); here, it is ‘DAPI’ since we aim to calculate DAPI/FITC. This name must be exactly as in the prefix used to name the kymograph files, as explained in Section C.6. Any inconsistency will lead to errors.

      4. Choose the number of pixels to be used as a margin to calculate the background of each channel (‘mar’), counting from the tip location toward the right side of the matrix (see Figure 3A as a reference). This number cannot be larger than the distance from the furthest tip location to the end of the matrix; otherwise, it will cause an error.

      5. Choose the number of pixels to be used as a margin to define your region of interest behind the tip location and calculate the ratio signal (‘roi.mar’) counting from the tip location toward the left side of the matrix (see Figure 3A as a reference). This number cannot be larger than the shortest tip location plus the width defined in the next step.

      6. Define the width of your region of interest (‘roi.wdth’) in number of pixels, which will be placed behind the tip location estimate toward the left side of the matrix (see Figure 3A as a reference). This number cannot be larger than the shortest tip location plus the margin defined in the previous step.

      7. Watch the ‘KymoTimePoint’ plots (Figure 3A) in the output folder to see whether the tip location estimates seem adequate, that is, approximately locate the transition from signal to background. If not, one option is to set the fraction of the signal range used to automatically detect the tip (‘frac’) at a smaller value, if the location estimates are too far into the background region, or at a larger value, if the locations are found too far into the signal region.

      8. Make sure there is no significant trend in the median ratio signal over time (Figure 3B), which may suggest that the intracellular and extracellular concentrations did not equilibrate. See the ‘RatioInROI” plots in the output folder. If there is a consistent change over time, either discard the time points in the original file or discard the replicate.

      9. Click on “Source” on the top icons of the script and watch for errors, warnings, and messages on the ‘R Console.’

      10. Obtain the calibration curve in the output directory, which contains the estimated parameters, P-value, and R2 in the legend (Figure 3C).



      Figure 3. Calibration of surrogate data mimicking pHluorin in Arabidopsis pollen tubes. A. Single timepoint where the tip location was estimated. B. Median ratio signal over time and overall distribution to verify whether there is a trend, plotted for each file in the output. C. Final calibration with coefficients and significance of the linear model.


    2. Linear regression Option 2: Custom R script that requires experience with programming. These are the steps implemented in Option 1 using the supplied script ‘CalibrateFromKymographs.R,’ but explained individually, allowing for greater flexibility in usage.

      1. Open the kymograph file in R (or Rstudio) using the function 'read.table.' This process will be described for a single file but can be easily automated.

      2. Estimate the boundary between the pollen tube tip and the background on the strongest channel either by using CHUKNORRIS (Damineli et al., 2017), the web app (https://feijolab.shinyapps.io/CHUK/), or simply with a threshold. The threshold value can be estimated visually by looking at which fluorescence value clearly separates signal from noise. Alternatively, one can attempt to automatically estimate the threshold, for example, as a fraction of the median signal range. To obtain the position (column) in the matrix 'm' at each time (row) where the pollen tube ends – for an arbitrary fluorescence threshold 'thrsh' – use 'apply(m, 1, function(v) max(which(v > thrsh))).'

      3. Estimate the median background value by subsetting the matrix 'm' after the position where the pollen tube ends on each row. This can be carried out in one command, for example, with 'median(unlist(lapply(pos, function(p) m[, (p+mar):dim(m)[2]]))),' where 'pos' is the vector of pollen tube tip positions obtained in the previous step, and 'mar' is an integer specifying the number of pixels to use as a margin (e.g., 5-25, depending on the number of pixels remaining to the right of each position).

      4. Estimate the signal value for that channel by averaging a region of a few pixels behind the pollen tube tip and subtracting the background.

      5. Open the file for the other channel and use the pollen tube tip position to estimate background (as in Section D.2.iii) and fluorescence signal (Section D.2.iv).

      6. Finally, calculate the ratio between the background-subtracted signal of each channel: pHluorin ratio = [(DAPI-DAPIBackground)/(FITC-FITCBackground)].

      7. Repeat D.2.i. - D.2.vi. for all other replicates and perform a linear model using 'lm,' where 'y' is the ratio values and 'x' is the extracellular pH (Figure 3C). Extract the coefficients for the slope and intercept and convert all ratio data into pH, provided that a satisfactory R2 and p-value are attained. Typically, one expects a p-value well below 10-2 and an R2 above 0.5; although, one must check whether a linear fit looks like an appropriate description of the data. Alternatively, a sigmoidal fit may be more adequate, but that is outside the scope of this protocol.

    3. Use the linear model to estimate the real pH or concentration values.

      1. Now that a linear model has been fitted to the calibration data, one can estimate real values for the cytosolic concentration using an adapted equation for the line y=slope*x+intercept to yield pH:



      2. Substitute the ratio values obtained from the desired experimental results in the equation above. If you extracted kymographs as in Section C.1. or as defined in Damineli et al. (2017) for your measurements of interest, this procedure allows a quantitative spatiotemporal estimate of pH (Figure 4) or other cytosolic concentrations.

      3. The intracellular gradient can be separately estimated as defined in Damineli et al. (2020).



      Figure 4. Spatiotemporal quantification of cytosolic pH. A. Kymograph generated from ratiometric pHluorin calibration. B. Time series data from the aha6 aha8 mutant Arabidopsis pollen tubes presented in Hoffmann et al. (2020).

Recipes

  1. Germination medium

    500 μM potassium chloride (KCl)

    500 μM calcium chloride (CaCl2)

    125 μM magnesium sulfate (MgSO4)

    0.005% (w/v) boric acid (H3BO3)

    125 μM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES)

    16% (w/v) sucrose

    Adjust pH to 7.5 with sodium hydroxide (NaOH)

  2. Stock solutions

    Potassium chloride (KCl) 100 mM

    Calcium chloride (CaCl2) 100 mM

    Magnesium sulphate (MgSO4) 100 mM

    Boric acid (H3BO3) 1%

    4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) 100 mM

  3. Sodium phosphate buffer

    Prepare 1 M sodium phosphate dibasic (Na2HPO4)

    Prepare 1 M sodium phosphate monobasic (NaH2PO4)

  4. Calibration solution

    10 mM sodium phosphate at the following pHs: 5.8, 6.2, 6.6, 7.0, 7.4, 7.8, 8.0

    140 mM KCl

    30 µM nigericin

  5. Image acquisition protocol used in the Deltavision System

    Intensity: 10%

    Exposure time: 250 ms (for both channels)

    Channel 1: DAPI, FITC

    Channel 2: FITC, FITC

    Interval: 4 s

    Time-lapse: 16 points (64 s)

Acknowledgments

The J.F. lab was supported by National Science Foundation grants (MCB 1616437/2016 and 1930165/2019) and the University of Maryland. M.T.P. was funded by the grants 2019/26129-6 and 2021/05363-0 from the São Paulo Research Foundation (FAPESP). D.S.C.D. was funded by grants 19/23343-7 and 15/22308-2 from the São Paulo Research Foundation (FAPESP). We also acknowledge Majon et al. (2011) from where the protocol was adapted.

Competing interests

There are no conflicts of interest or competing interests.

References

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简介

[摘要]离子特异性探针和荧光指标已在建立离子信令,即钙,质子的作用键,和阴离子,在植物发育中,提供用于监测时空变化的可靠的方法在细胞内离子动力学。随着有关其生物学功能的报道不断扩大,质子/pH 在信号机制中的整合尤为重要。^ h H但是,实现定量估计与单细胞的高时空分辨率构成了重大的研究挑战。在这里,我们详细介绍了利用基因编码的pH -敏感素-pHlurin 记者在表达拟南芥花粉管,以评估细胞内测量与calibrat离子,以提供实际的pH值。这项技术使我们能够识别关键表型并确定以尖端为重点的 pH 梯度对花粉管生长的重要性,尽管它可以适用于其他实验系统。


[背景]荧光指示剂和生物传感器在确定离子和其他分子在不同生物系统的细胞生理学中的作用方面发挥了重要作用。用于监测离子,分子大范围的生物传感器的发展,甚至植物激素植物中大大增加了在最近数十年(Hilleary等人,2018;瓦利亚等人,2018)。特别是,离子动力学的时空协调对于不同的细胞过程和信号通路至关重要。遗传编码的探针,例如钙2+传感器CAMELEON已经被广泛地用于理解离子动力学(宫胁等人。,1997;永井等人,2004; Monshausen 。等人,2008),这成为通过生成可访问的工具稳定的转基因品系。这样的方法的普及已经允许细胞内检测和监测,提高我们的理解的Ca的广泛作用2+ ,特别是在细胞信号传导,调节,和交流(费若和Wudick ,2018;瓦利亚等人,2018)。针对特定隔室或细胞器的生物传感器的特异性表达,以及适当的实时成像和遗传工具,已导致根中 Ca 2+波的检测和可视化(Choi等人,2014 年;Evans等人,2016 年) )、叶中电信号的传播(Nguyen等人,2018 年)、基于Ca 2+的长距离信号(Toyota等人,2018 年)和细胞间通讯(Ngo等人,2014 年)。解决这些现象在一个有机体水平阐发š如何这些信号被传播,也示出了生理整合跨组织和器官。

尽管不太理解比其的钙2+ ,pH值的作用在细胞内信号传导已经受到越来越多的关注,特别是由于质子作为水成分及其基本性质功能作为一个第二信使,以及钙-质子相互作用。这种含义在花粉管中尤其相关,其中细胞内 pH 值受到严格调节,并且细胞质质子的空间梯度在顶端生长中起主要作用(Certal等,2008;Michard等,2008;Hoffmann等) . , 2020)。实质性的领域的进展ħ作为被支持通过新的方法使得能够与适当的时空分辨率和时间刻度的活细胞成像小号,而细胞内的离子浓度的定量ħ如已取得由可能校准比率与升高的信噪比探针小号以及合适的动态响应范围。比率探针依赖于单个荧光蛋白,当与特定的目标分子/离子结合或未结合时,该蛋白会发出不同的波长。比率分析在定量上是可靠的,允许与整个细胞隔室中的探针的图像采集伪影和差异表达水平相关的校正。本协议描述了拟南芥花粉管中质子的细胞内监测和生物传感器pHluorin的校准程序(Miesenbock等人,1998 年),在提取隐含的内含子和密码子使用优化(Hoffmann等人,2020 年)后。为了解决在胞质质子动力学拟南芥花粉管,表达pH敏感稳定的转基因品系比例素-pHlurin在野生型和突变体背景生成小号。Hoffmann等人研究的突变体。(2020年)是特殊利益的对investigat荷兰国际集团^ h +动态,因为它们是由双-或三- H的击倒+ -ATP酶是最持久的H +挤压在花粉管的柄部区域。在花粉管中进行实时成像的微创方案的发展显示出一致的时空梯度,与其他物种的观察结果相容,从而可以识别和表征突变表型(Michard等人,2008 年;Certal等人,2008 年;Hoffmann等人) al. , 2020)。此处描述的校准协议需要量化来自两个发射通道的相应信号,同时通过将生物传感器暴露于多样化的 pH 环境来改变细胞质的 pH。当前协议中描述的原理和实验细节可以被其他研究人员使用和调整,以改进不同系统中的图像采集程序和不同生物传感器的校准。

关键字:细胞内pH值, pH动态, 表型, 荧光校正, 比率生物传感器


材料和试剂

Safe-升玉珠吨ubes,1.5毫升(的Eppendorf,目录号:0030120086)
玻璃-底菜ES (赛默飞世科学,目录号:150680)
玻璃微纤维过滤器(Sigma-Aldrich,目录号:WHA1820047)
氯化钾(Sigma-Aldrich,目录号:P9333)
硫酸镁(Sigma-Aldrich,目录号:746452)
硼酸(Sigma-Aldrich,目录号:B6768)
氯化钙(Sigma-Aldrich,目录号:C1016)
HEPES(Sigma-Aldrich,目录号:H3375)
蔗糖(Sigma-Aldrich,目录号:S7903)
尼日利亚菌素钠盐(Tocris Bioscience,目录号:4312)
磷酸氢二钠(Sigma-Aldrich,目录号:S8282)
磷酸二氢钠(Sigma-Aldrich,目录号:S7907)
琼脂糖低胶凝温度(Sigma-Aldrich,目录号:A9045)
萌发培养基(小号EE配方1)
储备溶液(š EE配方2 )
磷酸钠缓冲液(小号EE配方3 )
校准溶液(š EE配方4 )

设备

热板
pH计
涡流
细针尖镊子(Sigma-Aldrich,目录号:WHA1820047)
台式微量离心机(Eppendorf,型号:5415D)
DeltaVision成像系统(Applied Precision - GE,型号:Elite)
注意:包括一个我nverted显微镜(Olympus,型号:IX71),InsightSSI荧光照明器,前照SCMOS相机(2560×2160,像素尺寸6.45 微米),和6 3 × 1.2 NA水浸物镜(奥林巴斯,型号:U -计划S-Apo)。
滤光片组,激发 390/18 nm (DAPI) 和 475/28 nm (FITC);发射,435/48 nm (DAPI) 和 523/36 nm (FITC)
精密电动 X、Y 载物台

软件

ImageJ(多个 Kymograph 插件),斐济(https://imagej.net/Fiji/Downloads)
统计编程语言 R(R 核心团队,2020 –此处使用 4.0.4 版),推荐使用RStudio(RStudio 团队,2020 –此处使用 1.4.1103 版)以及我们定制的分析脚本 CHUKNORRIS(Damineli等人,2017 年)
可选使用作为补充材料提供的自定义 R 脚本“ CalibrateFromKymographs.R ”

程序

花粉收集和样品制备
从原液中制备新鲜的液体发芽培养基,并将pH 值调整为 7.5(配方 1)。
注意:将花粉发芽培养基的库存溶液储存在-20 °C,并在实验当天准备新鲜的发芽培养基。
生长拟南芥转基因植物,在LAT52 启动子(pLat52:pHluorin)下表达比率pHluorin (Hoffmann等人,2020 年),在 22 ° 的短日光周期条件(12 小时光照/12 小时黑暗周期)下的生长室中C 具有 70% 的湿度和~100 μmol m -2 s -s的光强度,以提高花粉完整性和密度。
注:生长在短日照条件,光照增加拟南芥植物小号花粉质量和完整性,导致高发芽率(> 90%)。在这些条件下,健康的植物大约需要 60 天才能开始开花。然而,也可以使用在其他光周期条件下生长的花。
收集开花的花使用薄镊子后立即小号和转移到1.5 - ml管(每管不超过100鲜花-使用每10月20日至25日的花-毫米皿)。
注意小号:
i )开始从第 10个长角果中收集鲜花。初生长角果花粉密度降低,发芽率降低;
ii)优先在光照周期的 3-5 小时采花。一个是压脚提升,鲜花开始关闭和花粉活力降低;
iii)密度对于拟南芥花粉的萌发非常重要。据建议的是每10月20日至25日的花-毫米培养皿中收集。这里用来标准化花粉密度的参数是花的数量;然而,花粉密度可能因生长室条件而异。的相关性,花粉粒应覆盖玻璃-底皿中,避免了任一稀疏或拥挤的情况。
添加 1 ml 发芽液体培养基。
高速涡旋 (~2,500 rpm) 30-40 秒。
以 1 , 600 × g离心3 分钟。
删除了鲜花和上清液。
轻轻重悬花粉沉淀 100 μ l液体发芽培养基。
注意:对于花粉沉淀再悬浮,切断所述第一几200的毫米- μ升尖端扩大孔径和避免花粉粒损坏。
将 0.01% 低熔点琼脂糖在安全锁管 (1.5 - ml)中的 1 ml 萌发培养基中融化30 秒,在微波炉中。
冷静下来琼脂糖足以用裸手接触的管小号,而不允许它jellify。
添加100 μ升琼脂糖溶液到花粉沉淀物,并轻轻混匀。
添加50 μ升溶液(在溶液+胶凝萌发培养基花粉粒)到各玻璃底培养皿(体积足以制备4个的实验品)。
放置玻璃底培养皿ö Ñ的热板上在50℃下1分钟。
注意:花粉粒对高温很敏感,长时间加热会杀死它们。保持菜肴的热量下不长于2分钟,刚好足够的时间,以允许花粉粒至下沉到玻璃底部,以促进成像下倒置显微镜。
取出菜肴和允许琼脂糖溶液到jellify。
注意:萌发培养基的凝胶化含有花粉粒允许š花粉管生长,同时使变化š在顶部液体溶液。此步骤是校准程序的基础。
添加100 μ升的胶凝琼脂糖垫的顶部液体萌发培养基含有花粉粒。
在 22°C 下孵育培养皿,最好在黑暗中孵育。
2-3 小时后,可以检测长度≥ 200 μ m 的花粉管。
注意:孵育2 -3小时后,实验菜肴应保存在冰盘中,以减缓从图像采集开始到程序结束的花粉管伸长;Ó therwise,管将连续细长的,并且后一几小时,花粉管长度将是不同的从第在在过程开始时取得的。

步骤1 - 17如图 1 所示。


图 1. 样品制备程序。序列的示意图用于菜制备和步骤的素-pHlurin在校准过程拟南芥花粉管。圆形图表示10 -玻璃毫米直径以及-底部培养皿。

校准程序和图像采集
制备10mM磷酸钠缓冲液中的单-和二元形式的摩尔比适合在以下pH值小号:5.8,6.2,6.6,7.0,7.4,7.8,以及8.0; 用140毫氯化钾和30μM的尼日利亚菌素(校准溶液-配方小号3,图4和表1)。
注:尼日利亚菌素,钾离子载体破坏š的膜电位和细胞内ħ +和K +浓度小号,被用来促进pH值在胞质溶胶之间和在外部溶液平衡。
用移液管从培养皿中取出萌发液体培养基,保留含有生长花粉管的琼脂糖垫。
加入100 μ升的给定的pH校正液。
等待 5 分钟稳定。
对于在给定 pH 值下采样的每个生长花粉管,每 4 秒获取两个通道(DAPI 和 FITC)的延时图像,持续 2 分钟(配方 5)。
注意小号:
我)应用相同的采集协议和显微镜参数到两个实验和校准样品。
ii) Deltavision系统用于开发此协议;然而,执行该协议的最低成像设置要求是任何能够以适当的时空分辨率和时间尺度进行活细胞成像的系统。这样一个系统应包括与流感倒置显微镜orescence源,一个照相机,和相应的发射/激发滤波器集合。
重复步骤2-6,˚F或全部给出的pH小号和重复。
注意:多个管的获取图像(10-20次重复在单独的管)在所有pH值小号从至少两个不同的菜肴,但理想3或更多以避免潜在的块效应。

表 1. pH 5.8 至 8.0 的磷酸钠缓冲液制备
酸碱度
1 M Na 2 HPO 4 的体积 ( ml )
1 M NaH 2 PO 4 的体积 ( ml )
5.8
0.79
9.21
6.2
1.78
8.22
6.6
3.52
6.48
7.0
5.77
4.23
7.4
7.74
2.26
7.8
8.96
1.04
8.0
9.32
0.68

Kymograph 提取
从延时生成 kymographs。
观看视频 1 中的教程。


视频 1. 在 ImageJ 中执行的 kymograph 提取程序的屏幕截图

在 ImageJ(推荐斐济)中打开每个文件,拆分 DAPI 和 FITC 通道。
使用“分段线”工具沿着最强通道上的花粉管中线追踪一条线,从柄开始到尖端。确保将迹线延伸到花粉管尖端之外,以便对足够的背景进行采样。这可能是有用的启动跟踪在最后一帧,以供参考,并调整跟踪,以确保这大致是在中线的每一帧。此外,避免与所述柄部的边界观察窗(图URE 2)。
图 2. kymograph 生成的跟踪。使用多 kymograph 插件 (ImageJ) 通过绘制花粉管中线生成 kymograph 的手动轨迹的说明性表示,沿两个pHluorin通道的轨迹对 7 像素邻域进行平均。延伸的迹线出来的荧光图像的是estimat基本荷兰国际集团为背景的像素强度减法。

沿中线提取 kymograph ,使用斐济“分析”菜单下的“多个 Kymograph”插件选择一个 7 像素的邻域。
行从一个信道复制到其他使用Command + Shift键+ E(上一个Mac上,代替“与Windows“控制”命令”)和提取kymograp为h描述在前面的步骤。
保存每个kymograph如本文“文件的文本,”'另存为,“文本图像。“牛逼Ø便于分析,最好是采用文件-命名系统; 在这里,我们建议从通道名称开始并指定外部 pH 值和重复次数。因此,取得的各文件与显微镜将产生两个kymographs名d “FITC_5.8_1.txt”和“DAPI_ 5.8_1.txt ,”在第一复制的情况下,在pH值5.8。该文件必须有时间为行和空间列,从左边的花粉管的信号-手侧和右侧的背景-右手边。

数据分析
执行作为外部pH值函数的比率值的线性回归。
选项 1:此处提供的 R 脚本基本上不需要编程经验。
注意:我们使用Hoffmann 等人的数据举例说明了数据分析工作流程。(2020)和替代数据与脚本“而生成GenerateSurrogateData.R作为提供”小号upplementary中号aterial。替代数据瓦特ERE产生在pH校正使用模拟kymographs,采用渐近曲线来表示具有噪声添加和实际的pH值的前端信号。

观看视频 2 中的教程。


视频 2. 在 RStudio 中执行的校准脚本的屏幕截图

该补充ř脚本“ CalibrateFromKymographs.R ”工具所需的所有步骤,以生成从所获得的kymographs校准曲线在不同的外部pH值,所提供的文件-部分C指定的命名系统6 。被严格遵守。任何命名差异都会产生错误。
打开 RStudio 并通过菜单“文件”和“打开文件...”打开文件 ' CalibrateFromKymographs.R ' 所需的参数将在脚本的“用户定义部分”中指定。
指定您的文件位于(“ fl.dir ‘)以及要输出被保存(’ out.dir ”)。确保目录斜杠的方向适合您的操作系统:“/”适用于MacO ,“\”适用于 Windows。
指定作为计算比率的分母的通道名称 ('top.ch') ; 在这里,它是“DAPI”,因为我们的目标是计算e DAPI/FITC。该名称必须是完全按照使用前缀来南é的kymograph文件,如第C.解释6 。任何不一致都会导致错误。
选择要使用的像素的数量作为一个余量,以计算每个信道的背景(“擦伤”),从朝向所述矩阵的右侧的端部位置的计数(参见图URE 3A作为一个参考)。这个数字不能大于从最远尖端位置到矩阵末端的距离;否则,会导致错误。
选择要使用的像素的数量作为一个余量来定义的前端位置后面关心区域,并计算比率信号(“ roi.mar ”)朝向矩阵的左侧的端部位置的计数(参见图URE 3A作为一个参考)。此数字不能大于最短尖端位置加上下一步中定义的宽度。
定义感兴趣的(“区域的宽度roi.wdth以像素为单位的数”) ,其将被放置后面的尖端位置估计朝向矩阵的左侧(参照图URE 3A作为一个参考)。此数字不能大于最短尖端位置加上上一步中定义的边距。
观看“ KymoTimePoint ”图(图URE在输出文件夹3A),以查看是否尖端位置估计似乎足够,即,大约从定位信号与背景的过渡。如果不是这样,一个选项是设定用来自动检测尖端(“压裂”)的信号范围的分数在一个较小的值,如果该位置估计太远的背景区域,或在一个较大的值,如果发现位置离信号区域太远。
确保有中位数比信号中没有显著趋势随着时间的推移(图3B),这可能表明,在细胞内外的浓度没有达到平衡。查看输出文件夹中的“ RatioInROI ”图。如果随着时间的推移有一致的变化,要么放弃原始文件中的时间点,要么放弃复制。
点击“源”的脚本顶部的图标,并注意错误,警告,并在“R控制台消息。'
获得在输出目录的校准曲线,它包含所估计的参数,P -值,和R 2在图例中(图3C)。
图3.替代数据模拟的校准素-pHlurin在拟南芥花粉管。A.单一时间点,其中的尖端位置估计。B.中号随时间和总体分布edian比率信号,以验证是否有一种趋势,用于绘制在输出每个文件。C. 使用线性模型的系数和显着性进行最终校准。

线性回归选项 2:需要编程经验的自定义 R 脚本。这些是步骤小号实现我N选项1使用提供的脚本“ CalibrateFromK ymographs.R ,”但单独说明,允许在使用更大的灵活性。
使用函数“ read.table ”在 R(或Rstudio )中打开 kymograph 文件。' 此过程将针对单个文件进行描述,但可以轻松实现自动化。
或者通过使用CHUKNORRIS估计花粉管尖端和上最强信道的背景之间的边界(Damineli等人,2017),所述网络应用程序(https://feijolab.shinyapps.io/CHUK/),简单地用一个或临界点。可以通过观察哪个荧光值清楚地将信号与噪声分开来直观地估计阈值。或者,可以尝试自动估计阈值,例如,作为中值信号范围的一部分。要在花粉管结束的每个时间(行)获取矩阵 'm' 中的位置(列) - 对于任意荧光阈值 ' thrsh ' -使用 'apply(m, 1, function(v) max(which(which( v > thrsh ))) 。'
通过在每行花粉管结束的位置之后对矩阵“m”进行子集化来估计中值背景值。这可以进行在一个命令,例如,'(中位数与不公开(lapply (POS ,函数(P)M [,(P +擦伤):昏暗(M)[2]]))) ,'其中' POS'是在先前步骤中获得的花粉管尖端的位置的矢量,和‘擦伤’是整数,指定像素使用的数量为一个余量(例如,5-25,取决于剩余向右的像素数每个位置)。
通过平均花粉管尖端后面几个像素的区域并减去背景来估计该通道的信号值。
打开用于其他信道的文件,并使用花粉管尖端位置来估计背景(如在第D.2.iii )和荧光信号(第d 。2 .IV)。
最后,计算每个通道的背景-减去信号之间的比率:pHluorin比率 = [(DAPI-DAPI背景)/(FITC- FITC背景)]。
重复d 。2次。我。- d 。2个.vi的。对于所有其他重复并使用“lm ”执行线性模型,其中“y”是比率值,“x”是细胞外 pH(图3C )。提取的系数的斜率和截距,并转换在所有比率数据到pH值,提供的是一个令人满意的[R 2和p值被达到。一般地,一个期望的p值远低于10 -2和一个- [R 2在0.5以上; 虽然,必须检查是否线性拟合看起来像一个适当的描述O ˚F的数据。或者,sigmoidal 拟合可能更合适,但这超出了本协议的范围。
使用线性模型来估计的实际pH值或浓度值。
现在,一个线性模型已被装配到校准数据,可以估算实数值为所述使用胞质浓度的适于方程为线以获得pH: 


用上面的等式替换从所需的实验结果中获得的比率值。如果您像第 C 节那样提取了 kymographs。1 。或如Damineli等人所定义。(2017)对于您感兴趣的测量,此过程允许对 pH 值(图4)或其他细胞溶质浓度s进行定量时空估计。
可以按照Damineli等人的定义分别估计细胞内梯度。(2020)。
图 4. 细胞质pH 值的时空量化。A. 由比率pHluorin校准生成的 Kymograph 。B. Ť IME系列d从ATA的aha6 aha8突变拟南芥在霍夫曼呈现花粉管等。(2020)。

食谱

发芽培养基
500  μM p otassium Ç hloride(氯化钾)
500  μM Ç alcium酰氯(氯化钙2 )
125  μM米agnesium硫酸(硫酸镁4 )
0.005% (w/v) b硼酸 (H 3 BO 3 )
125  μM 4-(2-羟乙基)-1-哌嗪乙磺酸 ( HEPES)
16%(W / V)小号ucrose
甲djust pH至7.5与小号裂果ħ ydroxide(氢氧化钠)
库存解决方案
钾Ç hloride(氯化钾)100毫
氯化钙 (CaCl 2 ) 100 mM
硫酸镁 (MgSO 4 ) 100 mM
硼酸 (H 3 BO 3 ) 1%
4-(2-羟乙基)-1-哌嗪乙磺酸(HEPES) 100 mM
磷酸钠缓冲液
制备1M的小号裂果磷酸氢二(娜2 HPO 4 )
制备1M的小号裂果磷酸二氢(的NaH 2 PO 4 )
校准溶液
10mM磷酸钠在以下pH值小号:5.8,6.2,6.6,7.0,7.4,7.8,8.0
140毫米氯化钾
30 µM 尼日利亚菌素
Deltavision系统中使用的图像采集协议
强度:10%
曝光时间:250 ms (两个通道)
渠道一:DAPI、FITC
通道 2:FITC、FITC
间隔:4秒
时间-推移:16点(64个S)

致谢

该JF实验室是由美国国家科学基金会资助(MCB2016分之1616437和二千零十九分之一百九十三万零一百六十五)和马里兰大学的支持。MTP是由基金资助小号2019 / 26129-6和2021 / 05363-0从圣保罗研究基金会(FAPESP)。DSCD由津贴资助小号19 / 23343-7,然后从圣保罗研究基金会15 / 22308-2(FAPESP)。我们也承认Majon等人。(2011)从那里改编了协议。

利益争夺

有没有利益或竞争利益冲突小号。


参考

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引用:Portes, M. T., Damineli, D. S. and Feijó, J. A. (2021). Spatiotemporal Quantification of Cytosolic pH in Arabidopsis Pollen Tubes. Bio-protocol 11(14): e4084. DOI: 10.21769/BioProtoc.4084.
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