Quantitative proteomics reveals factors regulating RNA biology as dynamic targets of stress-induced SUMOylation in Arabidopsis

Abstract

The stress-induced attachment of small ubiquitin-like modifier (SUMO) to a diverse collection of nuclear proteins regulating chromatin architecture, transcription, and RNA biology has been implicated in protecting plants and animals against numerous environmental challenges. In order to better understand stress-induced SUMOylation, we combined stringent purification of SUMO conjugates with isobaric tag for relative and absolute quantification mass spectrometry and an advanced method to adjust for sample-to-sample variation so as to study quantitatively the SUMOylation dynamics of intact Arabidopsis seedlings subjected to stress. Inspection of 172 SUMO substrates during and after heat shock (37 °C) revealed that stress mostly increases the abundance of existing conjugates, as opposed to modifying new targets. Some of the most robustly up-regulated targets participate in RNA processing and turnover and RNA-directed DNA modification, thus implicating SUMO as a regulator of the transcriptome during stress. Many of these targets were also strongly SUMOylated during ethanol and oxidative stress, suggesting that their modification is crucial for general stress tolerance. Collectively, our quantitative data emphasize the importance of SUMO to RNA-related processes protecting plants from adverse environments.

Fig. 1.

SUMO1/2 conjugates rapidly accumulate in Arabidopsis seedlings during heat stress. A, immunoblot analysis of SUMO1/2 conjugates from wild-type plants before and immediately after a 30-min heat shock at 37 °C followed by recovery at 24 °C. An anti-PBA1 immunoblot is included to confirm equal protein loads. The arrowhead and bracket locate free and conjugated SUMO1/2, respectively. B, measurement of free SUMO1/2 and their conjugates before and after the heat shock in (A) via quantitative immunoblot analysis. Each point represents the average of three biological replicates (±1 S.D.). C, temperature of the cultures during the heat shock time course. The shaded areas in (B) and (C) highlight when the cultures were exposed to 37 °C. D, flow chart describing the protocol used to quantify SUMO1/2 conjugates by means of iTRAQ MS along with the method to adjust for sample-to-sample variation by spiking with recombinant 6His-SUMO2.

Fig. 2.

Accuracy of iTRAQ MS in quantifying the abundance of Arabidopsis SUMO conjugates. A SUMO conjugate preparation spiked with 6His-SUMO2 was generated by pooling samples purified from all four time points during a 30-min heat shock time course (t = 0, 0.5, 1.5, and 4 h) (see Fig. 1D) and then was labeled separately with each of the four iTRAQ reporters (114, 115, 116, and 117) and mixed at various ratios from 1- to 16-fold. The samples then underwent iTRAQ-MS analysis. The left and right panels show the respective quantification of 6His-SUMO2 and a collection of purified Arabidopsis proteins (n = 70 and 80 for replicate samples). The experimental data for the heterogeneous collection of proteins are presented as box plots, with the boxes indicating the second and third quartiles, respectively, and the error bars encompassing 2 S.D. above and below the mean. The dashed line in both panels reflects the expected fold increases for the mixed samples.

Fig. 3.

iTRAQ MS reproducibly quantified the relative SUMOylation state for 172 Arabidopsis targets. The conjugates were purified from 6His-SUMO1-H89R sumo1–1 sumo2–1 seedlings before and immediately after a 30-min heat shock at 37 °C followed by recovery at 24 °C. A, Venn diagram showing the overlap of quantified proteins identified from two biological replicates. B, identified SUMO1/2 targets are enriched for the consensus ΨKxE SUMO binding site. The average number of high-probability sites per protein was compared for proteins identified in both biological replicates, unique to each replicate, or found in contaminants purified from wild-type plants. C, D, reproducibility of iTRAQ quantification for the SUMOylated proteins detected in both biological replicates. The log₂ fold change of each target at t = 0.5, 1.5, and 4 h was compared with that at t = 0. The lines of best-fit linear regression (red) and the corresponding R² values are included. (C) and (D) represent the analysis of 172 and 32 targets that met the PSM cutoffs of ≥2 and ≥20, respectively. E, Whisker plots showing the distribution of fold change values for each time point. Blue boxes indicate 95% confidence intervals of the means, and lines encompass the range from maximum to minimum values. F, Venn diagram illustrating the overlap between SUMO substrates quantified in this study as compared with the more complete Arabidopsis catalogue detected via non-quantitative MS (41). G, comparison of SUMOylated proteins detected here via iTRAQ MS versus those detected via non-quantitative MS based on the number of PSMs for each protein. Purple shades highlight the number of proteins in each PSM bin that were among the 172 proteins quantified in our current study. The percent overlap between the two datasets is stated above each bar. Data and statistical analysis for all targets can be found in supplemental Dataset S2.

Fig. 4.

Dynamics and functional analysis of SUMO substrates during and after heat shock as quantified via iTRAQ MS. A, relative changes in the SUMOylation status of 172 targets before and immediately after a 30-min heat shock at 37 °C followed by recovery at 24 °C. The values are illustrated by a heat map in which yellow denotes an increase in SUMOylation and blue denotes a decrease. The three tiers cluster proteins displaying a >7-fold increase (Tier 1), a 2- to 7-fold increase (Tier 2), or a <2-fold increase (Tier 3) in SUMOylation during the heat stress. B, GO functional enrichment for the targets clustered in each tier as a function of the −log₂(p value). C, the average number of high-probability ΨKxE SUMO-binding sites predicted per protein for each tier. The averages calculated for the collection of 59 contaminants isolated from wild-type plants, for the more complete Arabidopsis SUMOylome catalogue of 357 targets identified by Miller et al. (41), and for the entire Arabidopsis proteome were included for comparison.

Fig. 5.

SUMOylation of SIZ1 and the ubiquitylation of SUMO1/2 targets increase dramatically and reversibly during heat shock. Seedlings were collected before and immediately after a 30-min heat shock at 37 °C (shaded areas) followed by recovery at 24 °C. A, relative changes in the SUMOylation status for SIZ1, SAE2, and SCE1 as quantified via iTRAQ MS. SIZ1-K100 represents SIZ1 peptides bearing a SUMO footprint at K100. B, change in the SUMOylation status of SIZ1 as determined via immunoblot analysis of total protein extracts with anti-SIZ1 antibodies. The arrowhead identifies the SUMO-SIZ1 conjugate. Immunoblot analysis with anti-PBA1 antibodies was used to confirm equal protein loading. Sample from a non-stressed siz1–2 seedling was included to identify SIZ1. C, increases in the abundance of Ub+SUMO1/2 conjugates. Ub conjugates were purified from 6His-UBQ-expressing plants by means of Ni-NTA chromatography and were subjected to immunoblot analysis with anti-SUMO1 antibodies. Protein extracts enriched via Ni-NTA chromatography from wild-type plants at t = 1 h were included as a control. The region of the gel containing free 6His-Ub is also shown. D, relative changes in the abundance of Ub+SUMO1 conjugates in 6His-SUMO1-H89R sumo1–1 sumo2–1 plants first enriched for SUMO1 and then quantified via iTRAQ MS. iTRAQ values for all Ub peptides and the Ub peptide bearing a Ub footprint at K48 are shown (Ub-K48). When possible, the average fold change values for two independent biological replicates were included.

Fig. 6.

Comparison of the SUMOylation status of Arabidopsis targets affected by heat, ethanol, or oxidative (H₂O₂) stress using iTRAQ MS. A, immunoblot analysis showing the rise in SUMO1/2 conjugates in seedlings exposed continuously to 37 °C, 10% ethanol, or 50 mm H₂O₂. Crude extracts subjected to SDS-PAGE were probed with anti-SUMO1 or anti-PBA1 (loading control) antibodies. B, reproducibility of the fold increase for the collection of 174 SUMOylated proteins between two biological replicates subjected continuously to 2 h of each stress. The log₂ fold change represents the relative value at the end of the stress as compared with that at t = 0. The line of best fit linear regression (red), along with the corresponding R² value, is included in each panel. C, Whisker plots show the range of fold change values detected for each condition. Blue boxes indicate 95% confidence intervals of the means, whereas lines show the range between maximum and minimum fold change values. D, Volcano plots comparing the stress-specific fold change values for heat, ethanol, and H₂O₂ to all other values (both stressed and non-stressed) relative to the levels of FDR confidence in quantification value. Several proteins displaying significant stress-specific changes are indicated. Data and statistical analysis for all targets can be found in supplemental Dataset S3.

Fig. 7.

An initial heat shock dampens the rise in SUMOylation following subsequent exposure to heat, ethanol, or H₂O₂ stress. Seedlings were exposed to an initial heat shock for 30 min at 37 °C and allowed to recover at 24 °C for 3.5 h before the second stress. Total protein extracts were subjected to immunoblot analysis with anti-SUMO1 antibodies and anti-PBA1 antibodies (loading control). A, seedling exposed to a second heat shock at 37 °C. B, C, seedlings exposed to a second stress of 10% ethanol (B) or 50 mm H₂O₂ (C) for 2 h. For comparison, samples from seedlings exposed to ethanol or H₂O₂ for 2 h without a prior heat shock were included on the right lanes of each gel. Arrowheads and bracket locate free and conjugated SUMO1/2, respectively.