Translation Efficiency Test Using Polysome Profiles Under Heat Stress

Hui-Hsien Chang; Mei-Chun Cheng

doi:10.3791/67445

JoVE Journal > Biology

Biology

Translation Efficiency Test Using Polysome Profiles Under Heat Stress

Published: October 11, 2024

doi:

10.3791/67445

Hui-Hsien Chang¹, Mei-Chun Cheng¹

¹Department of Biochemical Science and Technology,National Taiwan University

Summary

The protocol presented here involves polysomal profiling to isolate translatome, mRNAs associated with ribosomes, into non-polysomal and polysomal RNAs from Arabidopsis through sucrose density gradient centrifugation. This method demonstrates the translation efficiency of heat-stressed Arabidopsis.

Abstract

Translational control of different genes under heat stress is a critical step for plant adaptation to the environment. Assessing the translational activities of various genes can help us understand the molecular mechanisms underlying plant resilience, contributing to the development of crops with enhanced stress tolerance in the face of global climate change. This paper presents a detailed methodology for assessing translation efficiency through polysome profiling in plants exposed to heat stress. The procedure is divided into three parts: heat stress treatment for Arabidopsis, translation efficiency test using polysome profiles, and calculation of translation efficiency by isolating non-polysomal and polysomal RNA based on the profile. In the first part, Arabidopsis plants are subjected to controlled heat stress conditions to mimic environmental challenges. The treatment involves exposing the plants to high temperatures for specified durations, ensuring consistent and reproducible stress induction. This step is crucial for studying the plant’s physiological and molecular responses to heat stress. The second part involves the translation efficiency test using polysome profiling. Polysomes are extracted through sucrose gradient centrifugation, which separates mRNAs based on ribosomal loading. This allows for the examination of ribosome occupancy on mRNAs, providing insights into the translational control mechanisms under stress conditions. In the third part, RNA is isolated from both polysomal and non-polysomal fractions. Spike-in RNA is used to accurately measure the amount of RNA in each fraction. The calculation of translation efficiency is performed by comparing the distribution of mRNAs across these fractions under normal and heat stress conditions. The translation activities of specific genes are further assessed by performing quantitative real-time PCR (qRT-PCR) with ribosome-associated RNA and total RNA. This methodology focuses exclusively on the effects of heat stress, providing a detailed protocol for analyzing translational regulation in plants.

Introduction

Translation is crucial for organisms to synthesize functional proteins from mRNA, supporting essential cellular functions and biological processes like metabolism and signaling and enabling stress responses. Without translation, cells cannot produce vital proteins, impacting their structure, function, and regulation, thereby affecting sustaining life and fostering biological diversity¹^,². Therefore, studying the translational efficiency of plants is crucial. Translation involves several essential steps. First, initiation occurs as mRNA binds to a ribosome, facilitated by initiation factors such as eIFs in eukaryotes, which identify the start codon, typically AUG. Next, elongation proceeds as transfer RNA (tRNA) molecules, each carrying specific amino acids, sequentially bind to the ribosome. Peptide bonds form between adjacent amino acids, elongating the polypeptide chain according to the mRNA sequence. Finally, termination is initiated upon encountering a stop codon (UAA, UAG, or UGA), recognized by release factors that prompt the ribosome to release the newly synthesized protein. Throughout translation, various eukaryotic initiation factors (eIFs), elongation factors, and ribosomal RNAs work together to ensure accuracy and efficiency³^,⁴.

Previous studies have indicated that post-translational modifications play a critical role in regulating interactions among eIFs and thereby influence translation efficiency. In vitro research has revealed that CASEIN KINASE 2 (CK2) kinase phosphorylates eIF3c, eIF5, and eIF2β to increase their interactions with each other and with eIF1⁵^,⁶. In dark, the E3 ligase CONSTITUTIVELY PHOTOMORPHOGENIC 1 (COP1) represses translation by inhibiting TOR-mediated phosphorylation of S6K-RPS6. The non-phosphorylated RPS6 is unable to form functional ribosomes, thereby halting translation⁷. Conversely, under light conditions, the SUPPRESSOR OF PHYA 105 (SPA1) kinase phosphorylates eIF2α to facilitate eIF2 complex assembly and promote translation initiation⁸. These findings highlight the complex control mechanisms that regulate translation in response to environmental signals.

Moderate environmental stimuli can effectively promote translational processes to facilitate growth, such as photomorphogenesis⁸^,⁹. However, when environmental factors are excessive, immobile plants need to evolve suitable regulatory mechanisms to mitigate damage caused by environmental stress¹⁰. In previous studies related to plant stress responses, the majority focused on regulation at the metabolic, hormonal, and transcriptional levels¹¹^,¹²^,¹³^,¹⁴. However, recent research has begun to highlight the influence of translational regulation on plant stress tolerance¹⁵^,¹⁶^,¹⁷. Plants can increase their stress tolerance by reducing translational efficiency, thereby minimizing unnecessary energy consumption. Due to the formation of non-membranous stress granules in plant cells, untranslated mRNA and associated proteins aggregate within them to reduce translational efficiency¹⁸. One of the common environmental stresses that plants often encounter is heat stress, which has been reported to induce the formation of stress granules within plant cells¹⁹^,²⁰. The global increase in average temperatures due to global warming severely affects crop yields²¹. Therefore, studying the physiological regulation of plants under heat stress is crucial. A previous study has shown that heat treatment of wheat resulted in a decrease in polysome-bound mRNA. However, mRNAs stored in stress granules were released and re-bound to ribosomes, facilitating translation after recovery²². Additionally, previous research has compared gene expression between total mRNA and polysome-bound mRNA in submerged plants¹⁶. The results indicated that the steady-state levels of mRNA associated with abscisic acid and abiotic stress responses slightly increased following submergence. Furthermore, the amount of polysome-bound mRNAs increased significantly. These results suggest that translation regulation might play a more critical role in controlling stress tolerance in plants. Therefore, an effective polysomal RNA isolation method is crucial for studying the translatome of stress-treated samples.

In this protocol, we modified the RNA isolation method from the high-risk and voluminous phenol/chloroform extraction with LiCl precipitation method to the small-scale phenol/guanidinium thiocyanate extraction method, which requires less volume. The former method involves direct mixing with polysomal fractions, resulting in a larger experimental waste⁹^,¹⁵^,²³. In contrast, this modified approach utilizes differential density principles: polysomal RNA is first mixed with a high-salt, sugar-free solution and then precipitated by ultracentrifugation. Subsequently, RNA extraction is performed using a small volume of phenol/guanidinium thiocyanate reagent. This method effectively reduces the generation of organic waste, making our experiment more environmentally friendly. Additionally, the organic solvents used have lower toxicity. These reasons led us to adjust and improve the experimental procedures accordingly. Additionally, previous methods did not provide a comprehensive protocol for calculating translation efficiencies using spike-in normalization, which is essential for more in-depth translatomic analyses.

Here, we describe polysome profiling and polysomal RNA isolation protocol for investigating translation efficiency and translatomic analyses in Arabidopsis under heat shock stress. This protocol was employed to assess translation efficiency in the Col-0 wild type under normal, heat shock, and after-recovery conditions. Polysome profiling results and the percentage of polysomal RNA revealed alterations in translation efficiency following heat stress treatment in Arabidopsis seedlings.

Protocol

1. Heat stress-treated Arabidopsis seedling sample preparation

Plate 250 seeds for each replicate and each condition with a dropper on the filter paper placed on the Murashige and Skoog (MS) basal media agar plate without sucrose (pH 5.6) supplemented with 1.2% phytoagar.
NOTE: To plant seedlings on MS plates, sterile filter paper is placed on the plate to prevent seedling roots from penetrating deep into the medium, facilitating easier sampling. Seeds are then planted on top of the filter paper. To exclude the influence of sugars on plant growth and experimental results, it is recommended to use an MS medium that does not contain sucrose for cultivation.
Wrap the MS plate containing planted seeds with aluminum foil to block light and incubate it at 4 °C for 2 days to induce vernalization.
Transfer the vernalized seeds to a growth chamber to be grown under a 16 h: 8 h, light-dark photoperiod at 22 °C with a light intensity of 100 µmol/m²/s.
For heat stress samples, seal the MS medium plates containing 5-day-old seedlings with waterproof adhesive tape and place them in a 40 °C water bath for 1 h.
For samples recovering after heat treatment, cool the plates down immediately after heat treatment. Subsequently, place them in a growth chamber at 22 °C for 2 h.
Harvest 250 seedlings with treated or untreated into 1.5 mL microcentrifuge tubes for each replicate and freeze the samples in liquid nitrogen immediately.
NOTE: For each condition, two groups of samples were prepared. One is for the polysome profiling analyses, and the other one is for the non-polysomal and polysomal RNA extraction.

2. Sucrose gradient preparation

Prepare the gradient solution containing the following concentrations of sucrose: 12.5%, 24.4%, 36.3%, 48.1%, and 60%. The solution composition includes 50 mM Tris-HCl, 25 mM KCl, 10 mM MgCl₂, 100 µg/mL Heparin, and 50 µg/mL cycloheximide (CHX).
Load the gradient solutions from high to low concentration, starting from the bottom and moving upwards. After adding each concentration of gradient solution, freeze the solution to a solid state before adding the next concentration. For each concentration of sucrose gradient, add 2.2 mL. This process will result in a discontinuous sucrose density gradient.
Store the prepared sucrose gradient temporarily at -80 °C and thaw overnight at 4 °C before use.

3. Polysome profiling sample preparation

Grind 250 5-day-old Col-0 seedlings, whether heat-stressed or untreated, that have been previously frozen into powder using a homogenizer at a frequency of 30 cycles/s for 1 min.
NOTE: When the number of plants with the same background is equal, they have the same RNA extraction yield. However, when comparing overexpressing transgenic or mutant plants with different backgrounds, the amount of plants used should be adjusted according to the plant conditions.
To obtain an extraction solution containing non-polysomal and polysomal RNA, add 500 µL of polysome extraction buffer (200 mM Tris-HCl, pH 8.0, 50 mM KCl, 25 mM MgCl₂, 50 µg/mL cycloheximide, 100 µg/mL heparin, 2% PTE, 10% DOC, 400 U/mL Ribonuclease inhibitor) to each tube, and mix the samples by inverting and vortexing. Ensure that the samples are maintained at 4 °C throughout the process.
Centrifuge the extraction solution at 4 °C, 12,000 x g for 10 min. Then, filter the supernatant through a 100 µm cell strainer to obtain a clear and particle-free extraction solution.
NOTE: The particles present in the extraction solution may sediment during ultracentrifugation, potentially forming a pellet that could affect the accuracy of polysome profiling measurements.
Load the filtered supernatant onto a pre-prepared sucrose gradient and ensure that it reaches equilibrium.
NOTE: Due to the high rotational speed of the ultracentrifuge, it is essential to ensure both safety and proper functioning of the ultracentrifuge. To achieve this, it is necessary to confirm that the sample weights are identical before rotation. Therefore, we utilize a precision balance to verify that the weights of the gradients are completely uniform.
Centrifuge the sucrose gradient loaded with samples at 4 °C, 210,000 x g for 3.5 h using an ultracentrifuge swinging-bucket rotor. Set the acceleration and deceleration rates to the maximum. After ultracentrifugation, non-polysomal and polysomal RNA are distributed according to their density in the corresponding sucrose gradient solution.
NOTE: In the sucrose gradient, non-polysomal RNA with lower density distributes in the upper layer, while polysomal RNA, characterized by higher density due to the presence of numerous ribosomes engaged in active translation on mRNA, distributes in the lower layer. Subsequently, polysome profiling can be measured using a density gradient fractionator.

4. Polysome profiling analysis

NOTE: A density gradient fractionator with a microvolume syringe pump is used to measure polysome profiling.

Prepare the chase solution (70% sucrose, 10% glycerol, and 0.02% Bromophenol blue) for the microvolume syringe pump.
Use software to control the density gradient fractionator. Calibrate the machine using deionized water. After calibration, use it to perform polysome profiling.
1. To perform baseline adjustment, turn on the UV/VISDetector until the light changes from red to green. Adjust the Recorder Offset knob to align the marker line, then turn the Baseline Adjust knob to the minimum open position. Set the Sensitivity knob on the UV/VISDETECTOR to level 2.0 and press the Auto Baseline button. Finally, use the Recorder Offset knob to adjust the desired baseline to 20. The calibrated process will vary depending on the brand of mechanism and different samples.
After ultracentrifugation, place the tubes with the samples onto the density gradient fractionator using the tube piercing system so the tube can be connected to the syringe pump with the chasing solution and the UV detector.
Switch the density gradient fractionator to software control mode (REMOTE) and set the injection flow rate of the microvolume syringe pump to 3 mL/min.
Initiate the software settings to begin and obtain the polysome profile graph using the fractionator by measuring OD₂₅₄.

5. Isolation of non-polysomal and polysomal RNA

NOTE: For this part of the protocol, a different group of samples from the same batch was used after performing ultracentrifugation following the same steps as described previously.

Based on the polysome profile measurement results, collect the non-polysomal and the polysomal RNA fractions separately. Calculate the volumes of solution for both non-polysomal and polysomal fractions and collect the non-polysomal fraction (upper part).
NOTE: According to the profiles, the fraction with more than two ribosomes is defined as a polysomal fraction, whereas the fraction with the 40S, 60S, and 80S rRNA peaks is defined as a non-polysomal fraction.
Mix the target fractions of RNA thoroughly with pre-cold 2x high salt solution (400 mM Tris-HCl, pH 8.0, 100 mM KCl, 50 mM MgCl₂).
Add 8 µL of diluted stock of Eukaryotic Poly-A RNA Control from the kit.
NOTE: For the spike-in normalization required for the seventh step. The Eukaryotic Poly-A RNA Control Kit includes B. subtilis genes, such as the DAP gene which are not present in plants, as reference genes. To determine the proportion of reference gene loss during the reaction after extraction, add an equal amount of the reagent containing RNA sample of DAP gene to different tubes with non-polysomal or polysomal RNA before extraction. This allows for the determination of the proportion of reference gene loss during the reaction after extraction and can be used for normalization purposes.
Centrifuge the high-salt solution mixed RNA at 4 °C, 450,000 x g, for 5 h using an ultracentrifuge swinging-bucket rotor.
After ultracentrifugation, RNA will precipitate at the bottom of the centrifuge tube. Carefully pour off the supernatant from above to preserve the RNA pellet at the bottom.
Quickly wash the RNA pellet with 500 µL of pre-cold Diethylpyrocarbonate (DEPC)-treated water, repeating this step 3x.
NOTE: To prevent DEPC-treated water from re-dissolving the RNA during the washing process, it is necessary to pre-cool the DEPC-treated water before use to reduce its solubility. Additionally, the contact time between the DEPC-treated water and the RNA pellet during washing should be minimized.

6. Non-polysomal and polysomal RNA extraction

Add 500 µL of RNA extraction reagent and mix with the RNA sample to be extracted. Incubate for 10 min.
Add 100 µL of chloroform, mix thoroughly, and incubate for 10 min for phase separation.
Centrifuge the reaction mixture at 4 °C, 12,000 x g for 10 min. Transfer the upper clear aqueous layer containing RNA into a new tube, mix it gently with an equal volume of isopropanol, and incubate at -20 °C for 2 h for RNA precipitation.
After precipitation, centrifuge at 4 °C, 12,000 x g for 10 min. Carefully discard the supernatant and retain the RNA pellet at the bottom.
Wash the RNA pellet with 1 mL of pre-cold 75% ethanol. Centrifuge at 4 °C, 12,000 x g for 10 min, discard the supernatant, and air dry the RNA pellet.
Once the RNA pellet is dried, resuspend the RNA pellet in 30 µL of DEPC-treated water and measure the RNA concentration (OD₂₆₀) using a full spectrum (220 nm-750 nm) spectrophotometer.

7. Spike-in normalization

Use 1000 ng of extracted RNA for reverse transcription done using a qPCR kit following the manufacturer's instructions. Both non-polysomal and polysomal RNA need to be reverse transcribed into cDNA.
Mix 1 µL of cDNA with DAP gene primers and use SYBR buffer to measure the expression level of the target gene as per the manufacturer's instruction. Next, use real-time PCR to detect DAP gene expression.
NOTE: Sequences of the primers of DAP gene are as follows:
Forward primer = 5'-ATA AAA GAA TTC AGC TAA CGC TTC C-3'
Reverse primer = 5'-TTG TTT CTT TGC CTC TAT TGT ATC C-3'
Compare the expression levels of DAP genes in the measured non-polysomal and polysomal RNA groups and estimate the RNA content under conditions of proportional loss. Using the normalized RNA content, calculate the ratio of RNA in polysomes.

Representative Results

The wild type of Arabidopsis, Col-0, was grown on MS medium under a 16 h:8 h light photoperiod. For control, 5-day-old seedlings were used with no heat stress treatment. The heat stress group underwent 1 h of heat treatment at 40 °C in a pre-heated water bath, while the recovery group was placed at 22 °C for 2 h immediately after heat treatment. By employing different heat treatment conditions and recovery conditions, we can utilize subsequent steps to measure their translational efficiency.

Before RNA extraction, the sucrose gradient must be prepared first. To separate the non-polysomal and polysomal RNA based on their density difference, we prepared a gradient solution with sucrose concentrations of 12.5%, 24.4%, 36.3%, 48.1%, and 60%. We then loaded the gradient solutions from high to low concentration, starting at the bottom (Figure 1A). Subsequently, we can utilize this gradient to separate the lower-density non-polysomal RNA in the upper layer, while the higher-density polysomal RNA will be distributed in the lower layer with higher sucrose concentrations. The non-polysomal and polysomal RNA were extracted from the treated or untreated Col-0. To prevent particles in the solution from affecting the results of polysome profiling analysis, the RNA-containing solution should be filtered through a cell strainer to obtain a particle-free extraction solution. The filtered supernatant was loaded onto a pre-prepared sucrose gradient and equilibrated. After the ultracentrifugation of sucrose gradient-loaded samples, the non-polysomal and polysomal RNA were distributed according to density within the sucrose gradient. Subsequently, polysome profiling was performed using a density gradient fractionator (Figure 1B). The density gradient fractionator is controlled using software initially calibrated with deionized water. Following calibration, samples are loaded onto the fractionator post-ultracentrifugation. Operating in software control mode, the microvolume syringe pump injects sucrose solution with concentrations higher than the sucrose gradient into the gradient, pushing the sample. This allows measurement to start from the top of the sucrose gradient, where the density is lower, and proceed towards the bottom, where the density is higher. Subsequently, software settings are activated to commence data acquisition, generating the polysome profile graph through OD₂₅₄ measurement (Figure 1B). When we observe a higher signal intensity in the polysomal fraction, it indicates that the sample exhibits higher translation efficiency.

The plots of polysome profiling for 5-day-old Col-0 seedlings under different treatments are shown in Figure 2. The results of the control group demonstrate a clear separation between the non-polysomal fraction and polysomal fraction (Figure 2A). However, after 1 h of heat stress at 40 °C, the signal intensity of the polysomal fraction significantly decreased (Figure 2B). When the heat-treated seedlings were allowed to recover at 22 °C for 2 h, the signal intensity of the polysomal fraction recovered to a level similar to the control group (Figure 2C). Our results demonstrated that 1 h heat stress treatment significantly reduced the translation efficiency of Arabidopsis seedlings. However, plants required 2 h of recovery to restore translation efficiency to levels comparable to those of seedlings not suffering from heat stress.

To gather further evidence comparing the translation efficiency of Col-0 seedlings under different treatment conditions, we isolated and extracted the non-polysomal and polysomal RNA fractions. The collection of non-polysomal and polysomal RNA fractions was guided by the results of polysome profile measurements. For non-polysomal and polysomal RNA extraction, we use the phenol/guanidinium thiocyanate reagent to extract the isolated non-polysomal and polysomal RNA samples. With the RNA extraction method we used, we can get stable and high-quality RNA for our following analysis (Table 1). Subsequently, normalize the extracted RNA with the GeneChip Eukaryotic Poly-A RNA Control Kit to mitigate errors caused by varying extraction losses. Next, real-time PCR was used to quantify the expression of DAP genes, which are included in the B. subtilis genes added to the kit. Comparative analysis of DAP gene expression levels between non-polysomal and polysomal RNA groups was conducted to estimate RNA content under conditions of proportional loss (Figure 3A). We calculated the ratio of normalized polysomal RNA to total RNA to clarify the translation efficiency between them (Figure 3B). Finally, the ratio of RNA in polysomes was calculated using the normalized RNA content (Figure 3C). The results of the RNA ratio in polysomes under different treatments of Col-0 exhibited a pattern consistent with the polysome profile results shown in Figure 2A. Both results indicate that heat stress significantly reduces the RNA ratio in the polysomal fraction, and this effect can be reversed after a 2 h recovery at 22 °C (Table 1).

From this method, we can obtain the whole non-polysomal or polysomal RNA fraction with high quality rather than separating the RNA into additional fractions²³. Our results also demonstrate that both polysome profiles and the percentage of RNA in polysomes can effectively reflect translation efficiency in Arabidopsis with different treated conditions.

Figure 1: Polysome profiling workflow diagram. (A) Schematic illustration of preparing the sucrose gradient in a 13 mL centrifuge tube. (B) The flowchart illustrates the experimental process of polysome profiling. Firstly, the translatome is extracted. Subsequently, non-polysomal and polysomal RNA are separated based on their density differences using ultracentrifugation in sucrose gradients of varying densities. OD₂₅₄ is measured using a density gradient fractionator to obtain the polysome profiling result graph below. Please click here to view a larger version of this figure.

Figure 2: Polysome profiling of Col-0 under different conditions. (A, B, C) The polysome profiling results of Col-0 under conditions of (A) no heat treatment (control), (B) heat treatment at 40 °C for 1 h, and (C) recovery at 22 °C for 1 h after heat treatment. The non-polysomal and polysomal RNA were fractionated using a 12.5%-60% sucrose gradient. The positions of non-polysomal (NP) and polysomal (PL) RNA are indicated on the profiles. Please click here to view a larger version of this figure.

Figure 3: Non-polysomal and polysomal RNA extraction workflow diagram. (A) An illustration of RNA normalization by spike in. (B) An illustration of the separation of non-polysomal and polysomal RNA and the calculation of the percentage of polysomal RNA.(C) The percentage of polysomal RNA in Col-0 treated with different conditions. Error bars indicate the mean ± SD (n=3 biological repeats). *p-value < 0.01, Student's t test. Please click here to view a larger version of this figure.

		Content (ng)	260/280	260/230
Control	RNA_NP	758.3	2.19	2.16
Control	RNA_PL	302.3	2.21	2.13
Heat stress	RNA_NP	821.5	2.2	2.15
Heat stress	RNA_PL	174.3	2.19	2.21
Recovery	RNA_NP	797.2	2.17	2.16
Recovery	RNA_PL	300.9	2.19	2.18

Table 1: Non-polysomal and polysomal RNA contents and qualities. This table showed the RNA contents and qualities were analyzed. The RNA content was normalized after extraction using modified methods.

Discussion

This protocol outlines a straightforward and standardized method for measuring the translation efficiency of Arabidopsis seedlings. The critical steps of this protocol are ensuring RNA stability with secondary centrifugation and RNA extraction reagent extraction, as well as meticulous preparation of the sucrose gradient. Moreover, we provide critical steps for normalizing and quantifying the non-polysomal and polysomal RNA with the spike-in normalization method. It is very important that all procedures should be conducted on ice using RNase-free buffers and tools. Furthermore, ensure the accurate preparation of sucrose concentration and minimize shaking to reduce its impact on the gradient. In previous studies²⁴^,²⁵^,²⁶, research on stress responses has predominantly focused on transcriptional and phenotypic analyses. With polysome profile analyses, we can further investigate the regulation of translational processes in plants under stress or other environmental stimuli.

Understanding translational processes involves not only conducting polysome profiling experiments but also complementing them with Azidohomoalanine (AHA) labeling experiments. AHA labeling is employed to investigate protein synthesis and translational activity²⁷. The method substitutes methionine residues in newly synthesized proteins with AHA, a methionine analog containing an azide group. Cells integrate AHA into newly synthesized proteins during translation. Subsequently, using azide-chemistry-based techniques like click chemistry, proteins containing AHA can be selectively labeled and detected, enabling quantitative analysis and visualization of actively translating proteins²⁸. By combining AHA labeling with polysome profiling, researchers can gain deeper insights into the dynamics of protein synthesis within plant cells⁸.

With this polysomal RNA isolation and spike-in normalization method, we can also use the extracted RNA for RNA sequencing analysis. By analyzing polysome-bound mRNA, we can determine which mRNAs are actively undergoing translation. Furthermore, comparing steady-state mRNA with polysome-bound mRNA allows us to identify genes that are overexpressed at the translation or transcription level. The expression level of steady-state mRNA reflects the transcriptional activity, whereas polysome-bound mRNA indicates genes actively undergoing translation. Translation efficiency is influenced by environmental stimuli and post-translational modifications⁷^,⁸^,⁹^,¹⁶. Therefore, this method provides a comprehensive understanding of whether the target protein of interest is effectively translated. However, the limit of this method is that there will still be a loss of RNA during the extraction procedure. Relative expression of spike-in RNA obtained through qRT-PCR can also result in slight measurement errors. Further research and validation using proteomics or Western blot is required to investigate the functional aspects of the target protein.

In summary, this protocol represents a simple method that provides a straightforward approach with clear outcomes for evaluating translation efficiency. Importantly, its applicability extends beyond heat stress-treated seedlings to encompass seedlings exposed to various other environmental stimuli.

Disclosures

The authors have nothing to disclose.

Acknowledgements

We acknowledge the ultracentrifuge technical research services from Technology Commons in College of Life Science and the Instrumentation Center sponsored by Ministry of Science and Technology, National Taiwan University (Taiwan). We also thank Yu-Ling Liang for the technical support, and the Cheng lab members for critical reading of the manuscript. This work was supported by the Young Scholar Fellowship Einstein Program from the National Science and Technology Council in Taiwan under grant nos. NSTC 113-2636-B-002-007 to M.-C.C. M.-C.C. acknowledges the financial support from National Taiwan University.

Materials

1.5 mL eppendorf tube	Labcon	3012-870-000-9	RNA extraction
13.2 mL centrifuge tube	Beckman Coulter	331372	ultracentrifugation
Bromophenol blue	Honeywell	32712	Polysome profile
Chloroform	Honeywell	32211	RNA extraction
Cycloheximide (CHX)	Sigma-Aldrich	SI-C7698	Polysome profile
Diethyl pyrocarbonate (DEPC)	Sigma-Aldrich	D5758	RNA extraction
Ethanol	Sigma-Aldrich	32221	RNA extraction
GeneChip Eukaryotic Poly-A RNA Control Kit	Invitrogen	900433	Normalization
Glycerol	Honeywell	15523	Normalization
Heparin	Sigma-Aldrich	SI-H3149	Polysome profile
HiScript III RT SuperMix for qPCR kit	Vazyme	R323-01	Normalization
KCl	J.T.Baker	3040-01	Polysome profile
MgCl₂	Sigma-Aldrich	SI-M8266	Polysome profile
MS basal medium	Phyto	M524	Plant culture
Peak Chart Syringe Pump	Brandel	SYN4007LS	Polysome profile
Polyoxyethylene-10-Tridecyl-Ether (PTE)	Sigma-Aldrich	P2393	Polysome profile
RNasin	Promega	N251B	Polysome profile
Sodium deoxycholate (DOC)	Sigma-Aldrich	SI-D6750	Polysome profile
Sucrose	Sigma-Aldrich	S5391	Polysome profile
SYBR Green Supermix	Bio-Rad	BP170-8882	Normalization
TRI reagent	MRC	TR118	RNA extraction
Tris-HCl	J.T.Baker	4109-06	Polysome profile
Ultracentrifuge	Beckman Coulter	Optima L-100K	ultracentrifugation
UV/VISDETECTOR	Brandel	UA-6	Polysome profile

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Chang, H., Cheng, M. Translation Efficiency Test Using Polysome Profiles Under Heat Stress. J. Vis. Exp. (212), e67445, doi:10.3791/67445 (2024).

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