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Biology

Real-Time Detection of Reactive Oxygen Species Production in Immune Response in Rice with a Chemiluminescence Assay

Published: November 25, 2022 doi: 10.3791/64776

Summary

Here, we describe a method for the real-time detection of apoplastic reactive oxygen species (ROS) production in rice tissues in pathogen-associated molecular pattern-triggered immune response. This method is simple, standardized, and generates highly reproducible results under controlled conditions.

Abstract

Reactive oxygen species (ROS) play vital roles in a variety of biological processes, including the sensing of abiotic and biotic stresses. Upon pathogen infection or challenge with pathogen-associated chemicals (pathogen-associated molecular patterns [PAMPs]), an array of immune responses, including a ROS burst, are quickly induced in plants, which is called PAMP-triggered immunity (PTI). A ROS burst is a hallmark PTI response, which is catalyzed by a group of plasma membrane-localized NADPH oxidases-the RBOH family proteins. The vast majority of ROS comprise hydrogen peroxide (H2O2), which can be easily and steadily detected by a luminol-based chemiluminescence method. Chemiluminescence is a photon-producing reaction in which luminol, or its derivative (such as L-012), undergoes a redox reaction with ROS under the action of a catalyst. This paper describes an optimized L-012-based chemiluminescence method to detect apoplast ROS production in real-time upon PAMP elicitation in rice tissues. The method is easy, steady, standardized, and highly reproducible under firmly controlled conditions.

Introduction

Reactive oxygen species (ROS) comprise a series of chemically active oxygen derivatives, including superoxide anion radicals (O2-) and its derivatives, hydroxyl radicals (OH-), hydrogen peroxide, and products of singlet oxygen or oxidation-reduction reactions, which are constantly produced in plastids and chloroplasts, mitochondria, peroxisomes, and other subcellular locations1. ROS play important roles in many biological processes and are essential for all plants2,3,4. The broad spectrum of ROS functions varies from the regulation of growth and development to the perception of abiotic and biotic stresses5,6,7,8.

In the plant immune system, plant cell plasma membrane-localized receptors-so-called pattern recognition receptors (PRRs)-perceive pathogen-derived chemicals-pathogen-associated molecular patterns (PAMPs). This recognition triggers a series of fast immune responses, including calcium influx, ROS burst, and MAPK cascade; thus, this layer of immunity is named PAMP-triggered immunity (PTI). ROS burst is a hallmark PTI response, the determination of which is widely applied to PTI-related studies9,10. ROS production triggered by PAMPs is attributed to plasma membrane-resident NADPH oxidase, or respiratory burst oxidase homolog (RBOH) family proteins, which transfer electrons from cytosolic NADPH or NADH to extracellular oxygen to produce superoxide (O2-) which is spontaneously converted to hydrogen peroxide (H2O2) by superoxide dismutase8. PAMP-triggered ROS burst is quite rapid, appearing only a few minutes after PAMP treatment and peaking at ~10-12 min. The vast majority of the ROS molecules comprise hydrogen peroxide (H2O2), which can be easily and steadily detected with a chemiluminescence assay.

In chemiluminescence, the chemiluminescence reagent reacts with active oxygen, under the action of a catalyst, to produce the excited state intermediates. Then, the electrons in the product return to the ground state through non-radiative transition and emit photons. Common chemiluminescence reagents include luminol and L-012, with luminol dominating the application11,12,13. However, more researchers are choosing L-012 to detect ROS production, since L-012 has a much higher light emission efficiency under neutral or near neutral pH conditions compared to luminol.

This paper describes an optimized chemiluminescence method, based on L-012, for the real-time detection of ROS production after the elicitation of PAMPs in rice (Oryza sativa) tissues-leaf discs and sheath. The method provided here is simple, stable, and standardized, and is highly adaptable to meet different experimental needs. The data obtained with this method are highly reproducible under firmly controlled conditions.

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Protocol

NOTE: The protocol is applicable to different plant tissues. Rice sheath and leaf discs were used in this protocol for ROS detection upon PAMP elicitation. As differences mainly arise due to the method of sampling, only the common procedures are described below, with specific steps being mentioned wherever necessary.

1. Plant culture

  1. Sterilize the dehusked rice seeds with 70% ethanol for 1 min, then with 40% sodium hypochlorite (NaClO) for 1 h. Then, rinse the seeds 5x with sterile water to remove residual chlorine.
  2. Plate the seeds aseptically on 1/2 MS medium (2.37 g/L Murashige and Skoog (MS) medium, 30 g/L sucrose, 2.1 g/L phytagel, pH 5.7, autoclaved).
    1. In the rice sheath method, directly plate the seeds in the sterile glass vessel with MS medium.
    2. In the leaf disc method, plate the seeds on MS plates for 5-7 days and transplant them to growth matrix or soil (Figure 1A).
  3. Grow the seedlings in a growth room with a 12 h light/12 h dark photoperiod.

2. Tissue preparation and pretreatment

  1. Rice sheath
    1. Cut the sheath from 10-day-old rice seedlings into 3 mm segments with a sharp razor blade or surgical blade for pretreatment 1 day before the ROS assay (Figure 1B).
    2. Place five sheath segments in an individual well of a 96-well microtiter plate containing 100 µL of ddH2O for 10-12 h, in the dark at 25 °C, which allows wound injury-related ion leakage and defense responses to abate (Figure 2).
      NOTE: Taking care to keep the cuts vertical to ensure a consistent cutting surface area exposed to the elicitation solution is an important step to obtain highly reproducible results. Move the segments gently. Do not make extra cuts or wounds on the segments, which could be a source of data variation. As a principle, each test must contain at least five replicates since the variation of the ROS value is large. The more replicates set, the more reliable the data are.
  2. Leaf disc
    1. Cut the leaf discs (4 mm in diameter) from 4-6-week-old rice plants using a biopsy punch with a plunger. Always cut leaf discs from the middle third of the second leaf (numbered from the top) of the main tiller to reduce data variation (Figure 1C).
    2. Place one leaf disc in an individual well of a 96-well microtiter plate containing 100 µL of ddH2O for 10-12 h for pretreatment, which allows wounding-related responses to abate as these could interfere with the induction of ROS by PAMPs (Figure 2).
      NOTE: Operate the leaf discs gently. Do not make extra cuts or wounds on the discs in the experiment, which could result in data variation. The induction of ROS mostly occurs from the cells of the cut edge, since the surfaces of rice tissues (leaves or sheaths), are covered with hydrophobic layers. Only the cells of the cut edges are in contact with the elicitation solution (refer to the discussion section).
    3. Keep all the leaf disks floating, with the abaxial surface facing up, in the wells of a microtiter plate for water pretreatment to avoid leaf side-associated variation.

Figure 1
Figure 1: The growth condition and stages of rice seedlings for sheath sampling and parts of the rice sheath and rice leaves used in the assay. (A) Rice seedlings grown on 1/2 MS medium under sterile conditions for 10 days can be sampled for ROS assay. Sterilized rice seeds were cultured on 1/2 MS medium and grown in a 12 h light/12 h dark photoperiod in clear glass vial, 8.5 cm in diameter and 15 cm in height. (B) Schematic diagram of the sampling parts of leaf sheaths. Leaf sheaths were cut from 10-day-old rice seedlings. The positions of leaf sheaths were above the roots and below the first leaf. (C) Schematic diagram of the sampling position of leaf discs. The leaf discs can be cut from the middle third of the second leaf (count from the top) of the main tiller of healthy rice plants at any growth stage. Abbreviations: ROS = reactive oxygen species; MS = Murashige and Skoog. Please click here to view a larger version of this figure.

Figure 2
Figure 2: Schematic diagram of the plate setup for measuring ROS production with different lines of Oryza sativa. Pretreatment and test of rice tissues using a 96-well plate. Line 1, Line 2, and Line 3 (up to eight lines on one plate) can be any material of interest, different cultivars, mutants, or transgenic lines. The tissues were stimulated with elicitation solutions with PAMP (PAMP, white) or without PAMP (ddH2O, gray) to measure ROS response. It should be noted that the more the samples to be tested, the longer the time interval between readings. Abbreviations: ROS = reactive oxygen species; PAMP = pathogen-associated molecular pattern; ddH2O = double-distilled water. Please click here to view a larger version of this figure.

3. Preparing the elicitation solution

  1. Dissolve L-012 powder into 20 mM (6.23 mg/mL) aqueous solution with ddH2O to make the stock solution. Then, dilute the stock solution with 50 mM Tris HCl buffer (pH 7.5) to make the working solution at the final concentration of 500 µM L-012. Keep the stock solution frozen and dilute to the working solution before use.
  2. Prepare the elicitation solution containing PAMP, L-012, and horseradish peroxidase (HRP; 10 mg/mL in ddH2O). For a 10 mL elicitation solution, mix 9.4 mL of 50 mM Tris HCl (pH 7.5) solution, 400 µL of the L-012 solution, 100 µL of HRP, and 100 µL of flg22 (PAMP; 10 mM in ddH2O). For the negative control, add 100 µL of ddH2O instead of PAMP.
    NOTE: Keep the prepared elicitation solutions at room temperature to avoid cold stress to rice tissues. Other PAMPs can also be used for treatment as required, such as chitin (20 ng/mL in final concentration). Since L-012 is light-sensitive, cover all the tubes containing L-012 solution with aluminum foil.

4. Starting the software and setting up the protocol with the referenced microplate reader (see Table of Materials)

NOTE: It takes some time to set up the parameters of the microplate reader software. It is recommended to get the machine and protocol ready (one click to proceed) before adding the elicitation solution.

  1. Start the software. Click the Experiments button to create a new protocol or use an existing protocol.
  2. Click Procedure in the pop-up to set up the plate. Select the wells from the plate to be monitored.
  3. Click Start Kinetic to set up the total run time and reading interval. Set the Run time to 35 min or longer, depending on the experimental requirements. To obtain readings as frequently as possible, select Minimum Interval. For integration time, choose 1 s or longer, depending on the signal intensity.
    NOTE: The reading interval depends on the number of samples and signal integration duration.
  4. Click Validate | OK to confirm the settings.
  5. Click on Detect the new plate in the pop-up and wait for the software to prompt the load plate dialog box. Place the plate to be tested on the carrier.
  6. Stop here to wait for the elicitation system to be established (in the next section). As soon as the elicitation system is ready, click on Run to start the reading.

5. Establishing the elicitation system and measuring real-time ROS production

  1. Carefully remove the ddH2O from the wells containing the pretreated tissues, avoiding any tissue damage or desiccation.
  2. Use a multichannel pipette to add 200 µL of the elicitation solution to the wells containing the tissues.
  3. Gently shake to mix. Click Run to begin detection.
    NOTE: With PAMP treatment, plant tissues respond and produce ROS very quickly. Therefore, it is suggested that the negative control without PAMP be treated first to reduce the operation time, when there are multiple treatments. Operate as quickly as possible to reduce the elicitation delay between treatments. The shorter the time between the addition of the elicitation solution and the start of detection, the better the capture of important experimental data will be.

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Representative Results

Here, we take rice material as an example to determine the ROS produced with flg22 treatment. The generation of ROS after elicitation is transient. In rice, the increase in ROS production was first detected in 1-2 min, peaked at 10-12 min, and returned to the baseline in ~30-35 min (Figure 3). Compared to the control test, in which PAMP was absent in the elicitation solution resulting in no obvious ROS induction, a specific ROS burst was induced only when the elicitation solution containing flg22, or other PAMP, such as chitin. Meanwhile, the total amount of ROS can be calculated from the curve (Figure 4).

Figure 3
Figure 3: ROS induction in rice tissues. (A) Leaf discs (4 mm in diameter) and (B) 3 mm long sheaths were used to induce ROS by flg22. ROS generation is monitored for 35 min. Bars indicate the means of SD calculated from five technical repeats. The reading data were imported into a spreadsheet. Apply the formulas "AVERAGE" and "STDEV. P" to the dataset to calculate the average value and standard error, respectively, from the replicates for each data point. Then, the curves were generated from the ROS values (average value and standard error). Abbreviations: ROS = reactive oxygen species; flg22 = 22-amino acid flagellin peptide; ddH2O = double-distilled water; RLU = relative luminescence units. Please click here to view a larger version of this figure.

Figure 4
Figure 4: The total amount of ROS generated with the sheath. The total amount of ROS is usually calculated from the curve obtained from the test. The total ROS amounts shown here were calculated from the curve corresponding to Figure 3A. To obtain the total amount of ROS values, apply the formula "= (y̅ n+ Equation 1n + 1) × time interval/2" to the corresponding datasets to calculate the ROS generated at each time interval, which can be combined by applying the formula "SUM" to calculate the total amount generated. Abbreviations: ROS = reactive oxygen species; flg22 = 22-amino acid flagellin peptide; ddH2O = double-distilled water. Please click here to view a larger version of this figure.

Figure 5
Figure 5: ROS production in the exposed cells of the cut edge. A single whole or two halves of a leaf disc were placed into the wells of a 96-well microtiter plate, pretreated with 100 µL of ddH2O for 10-12 h, and then treated with flg22 for ROS induction. The reading values from the two half-disc samples are much higher than that from the whole leaf disc (A). On average, the total values from the two half-disc samples are ~1.6 times that from the whole leaf disc (B), which is proportional to the edge length, not to the area, of the samples. This result supports that ROS are mainly generated in cells at the wound site. Abbreviations: ROS = reactive oxygen species; flg22 = 22-amino acid flagellin peptide; ddH2O = double-distilled water. Please click here to view a larger version of this figure.

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Discussion

The purpose of this study was to establish a highly efficient method to quantify early ROS production in response to PAMP in rice tissues. This method provides a standardized procedure for the real-time determination of apoplast ROS produced from treated rice tissues. This method is simple in operation, low in cost, clear in composition, and independent of commercial kits. Using this method, researchers can study the real-time production of apoplast ROS when plants are subjected to biotic or abiotic stresses.

In this protocol, L-012 was chosen as the chemiluminescence reagent as it is a nontoxic chemical. Luminol is widely used in chemiluminescence assays to detect ROS production. However, there are three drawbacks with luminol, which make it unsuitable for ROS detection in rice and other plant tissues: poor water solubility, short response duration, and harsh reaction pH. Luminol produces light only under alkaline conditions, with an optimal pH at 9.5, which is too harsh to plant cells and induces undesirable responses. Additionally, luminol possesses a much lower light emission efficiency than that of L-012, which possesses the highest luminescent sensitivity under physiological conditions, at neutral or near neutral pH. Thus, L-012 is increasingly used in living tissue or cell systems to detect ROS production.

ROS production in PTI response is influenced by many internal or external factors. Thus, the variation in ROS induction in PTI response is large. To eliminate variations as much as possible, this protocol takes measures to firmly control the test conditions. First, a 50 mM Tris-HCl buffer system was applied to the elicitation solution in the protocol. Although some researchers use unbuffered systems to test ROS production, we found that a buffer system has a better performance with respect to data consistency and reproducibility and a better baseline in the control group. Second, the authors strongly suggest taking samples as consistently as possible.

The inconsistency between tissues is a major source of data variation. This protocol recommends choosing tissues from the same position of the same leaf (number) or sheath of healthy plants under the same culture conditions. We always cut leaf discs from the middle third of the second leaf (numbered from the top) of the main tiller and maintain consistency between different experimental groups or different genotypes. When using sheath as the test tissue, the cut of the sheath should be kept vertical during the sampling process. If the cut is oblique, the resultant wound area cannot be kept consistent, which will lead to unstable experimental results. Third, the tissues should be operated gently and pretreated in the same manner. Wounds or injuries on the test tissues should be avoided, since wounding will expose more cells to the elicitation solution, which will undoubtedly result in data variation. As shown in Figure 5, the elicitation of ROS is mainly attributed to exposed cells. In addition, the value of ROS production will be dramatically reduced when new damage happens just before the reading.

Another important factor to consider when detecting the real-time production of ROS by plant tissues is the effect of the circadian clock. We noticed differences in the reading values at different times of the day. It has been proved that the circadian clock can affect the production and response of ROS, as well as the transcriptional regulation of ROS-related genes. The level of ROS fluctuates throughout the day, reaching a peak at noon and dipping at midnight14. In summary, this high-throughput procedure allows the simultaneous detection of multiple samples, which can help avoid the effect of the circadian clock on ROS production. To achieve reproducible results, we recommend performing biological replicates at the same time of the day.

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Disclosures

The authors have no conflicts of interest to disclose.

Acknowledgments

This work was supported by grants from Shanghai Natural Science Foundation (Grant Number: 21ZR1429300/BS1500016), Shanghai Jiao Tong University (Agri-X program, Grant Number:AF1500088/002), Shanghai Collaborative Innovation Center of Agri-Seeds (Grant Number: ZXWH2150201/001) to Jiangbo Fan, and by the Medical-Engineering Collaboration Project of Shanghai Jiao Tong Univesity (grant number: 21X010301734) to Can Li.

Materials

Name Company Catalog Number Comments
96-well microtiter plate WHB WHB-96-01
Ethanol absolute Innochem A43543
flg22 Sangon Biotech p20973 PAMP
Gen5 BioTek software
L-012 FUJIFILM 120-04891 8-amino-5-chloro-7-phenyl-2,3-dihydropyrido [3,4-d] pyridazine-1,4-dione, CAS #:143556-24-5
Microplate reader BioTek Synergy 2
MS Medium Solarbio M8521
NaCLO Aladdin S101636
Peroxidase from horseradish (HRP) Sigma P8375
Phytagel Sigma P8169
Sampler Miltex  15110-40
Sucrose Sangon Biotech A502792
Tris Sangon Biotech A610195

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References

  1. Gechev, T. S., Van Breusegem, F., Stone, J. M., Denev, I., Laloi, C. Reactive oxygen species as signals that modulate plant stress responses and programmed cell death. Bioessays. 28 (11), 1091-1101 (2006).
  2. Mittler, R. ROS are good. Trends in Plant Science. 22 (1), 11-19 (2017).
  3. Gilroy, S., et al. ROS, calcium, and electric signals: key mediators of rapid systemic signaling in plants. Plant Physiology. 171 (3), 1606-1615 (2016).
  4. Mittler, R., Vanderauwera, S., Gollery, M., Van Breusegem, F. Reactive oxygen gene network of plants. Trends in Plant Science. 9 (10), 490-498 (2004).
  5. Marino, D., Dunand, C., Puppo, A., Pauly, N. A burst of plant NADPH oxidases. Trends in Plant Science. 17 (1), 9-15 (2012).
  6. Mittler, R., Zandalinas, S. I., Fichman, Y., Van Breusegem, F. Reactive oxygen species signalling in plant stress responses. Nature Reviews Molecular Cell Biology. 23 (10), 663-679 (2022).
  7. Suzuki, N., Koussevitzky, S., Mittler, R., Miller, G. ROS and redox signalling in the response of plants to abiotic stress. Plant, Cell & Environment. 35 (2), 259-270 (2012).
  8. Suzuki, N., et al. Respiratory burst oxidases: the engines of ROS signaling. Current Opinion in Plant Biology. 14 (6), 691-699 (2011).
  9. Kadota, Y., Shirasu, K., Zipfel, C. Regulation of the NADPH oxidase RBOHD during plant immunity. Plant and Cell Physiology. 56 (8), 1472-1480 (2015).
  10. Segonzac, C., Zipfel, C. Activation of plant pattern-recognition receptors by bacteria. Current Opinion in Microbiology. 14 (1), 54-61 (2011).
  11. Roda, A., et al. Progress in chemical luminescence-based biosensors: A critical review. Biosensors and Bioelectronics. 76, 164-179 (2016).
  12. Hong, D., Joung, H. -A., Lee, D. Y., Kim, S., Kim, M. -G. Attomolar detection of cytokines using a chemiluminescence immunoassay based on an antibody-arrayed CMOS image sensor. Sensors and Actuators B: Chemical. 221, 1248-1255 (2015).
  13. Nishinaka, Y., et al. et al. new sensitive chemiluminescence probe, L-012, for measuring the production of superoxide anion by cells. Biochemical and Biophysical Research Communications. 193 (2), 554-559 (1993).
  14. Grundy, J., Stoker, C., Carre, I. A. Circadian regulation of abiotic stress tolerance in plants. Frontiers in Plant Science. 6, 648 (2015).

Tags

Real-time Detection Reactive Oxygen Species Immune Response Rice Chemiluminescence Assay L-012 PAMP Elicitation Optimized Method Standardized Reproducible Sterilize Dehusked Rice Seeds Ethanol Sodium Hypochlorite Sterile Water Rice Sheath Method Murashige And Skoog Medium Leaf Disc Method MS Plates Growth Matrix Growth Room Photo Period Sheath Segments Microtiter Plate Double Distilled Water Leaf Discs
Real-Time Detection of Reactive Oxygen Species Production in Immune Response in Rice with a Chemiluminescence Assay
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Cite this Article

Wang, Y., An, Z., Zhao, Z., Li, C.,More

Wang, Y., An, Z., Zhao, Z., Li, C., Fan, J. Real-Time Detection of Reactive Oxygen Species Production in Immune Response in Rice with a Chemiluminescence Assay. J. Vis. Exp. (189), e64776, doi:10.3791/64776 (2022).

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