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.
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.
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.
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
2. Tissue preparation and pretreatment
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: 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
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.
5. Establishing the elicitation system and measuring real-time ROS production
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: 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: 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+ n + 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: 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.
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.
The authors have nothing to disclose.
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.
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 |