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Transcriptional competition shapes proteotoxic ER stress resolution

Nature Plants volume 8, pages 481–490 (2022)Cite this article

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An Author Correction to this article was published on 30 September 2022

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Abstract

Through dynamic activities of conserved master transcription factors (mTFs), the unfolded protein response (UPR) relieves proteostasis imbalance of the endoplasmic reticulum (ER), a condition known as ER stress1,2. Because dysregulated UPR is lethal, the competence for fate changes of the UPR mTFs must be tightly controlled3,4. However, the molecular mechanisms underlying regulatory dynamics of mTFs remain largely elusive. Here, we identified the abscisic acid-related regulator G-class bZIP TF2 (GBF2) and the cis-regulatory element G-box as regulatory components of the plant UPR led by the mTFs, bZIP28 and bZIP60. We demonstrate that, by competing with the mTFs at G-box, GBF2 represses UPR gene expression. Conversely, a gbf2 null mutation enhances UPR gene expression and suppresses the lethality of a bzip28 bzip60 mutant in unresolved ER stress. By demonstrating that GBF2 functions as a transcriptional repressor of the UPR, we address the long-standing challenge of identifying shared signalling components for a better understanding of the dynamic nature and complexity of stress biology. Furthermore, our results identify a new layer of UPR gene regulation hinged upon an antagonistic mTFs-GFB2 competition for proteostasis and cell fate determination.

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Fig. 1: Putative CRE identification relevant to differential gene expression in response to both ABA treatment and ERR and a UPR-TF network built on Y1H screens.
Fig. 2: GBF2 negatively regulates the expression of BiP3 via direct binding to the promoter.
Fig. 3: GBF2 competes with bZIP60 and bZIP28 for the binding to the BiP3 promoter as a negative regulator.
Fig. 4: The gbf2-3 null mutation suppresses the lethal phenotype of bzip28-2 bzip60-1 and derepresses the expression of UPR biomarker genes.

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Data availability

All data supporting the findings of this study are available within this paper and Supplementary Information. The ChIP–seq data supporting the finding of this study have been deposited in the NCBI Sequence Read Archive and are accessible through the BioProject accession code PRJNA810750. The full results of the eY1H screen, including gene accession numbers, are available in Supplementary Data 4. Source data are provided with this paper.

Code availability

The scripts used in this study are available in GitHub (https://github.com/DaeKwan-Ko/UPR-TFs.git).

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Acknowledgements

This study was supported primarily by the National Institutes of Health (R35GM136637) with contributing support from by the Great Lakes Bioenergy Research Center, US Department of Energy, Office of Science, Office of Biological and Environmental Research (DE-SC0018409), Chemical Sciences, Geoscience and Biosciences Division, Office of Basic Energy Sciences, Office of Science, US Department of Energy (DE-FG02-91ER20021) and MSU AgBioResearch (MICL02598). This study was supported in part through Michigan State University’s Institute for Cyber-Enabled Research Cloud Computing Fellowship, with computational resources and services provided by Information Technology Services and the Office of Research and Innovation at Michigan State University. We thank the Genome Center and Proteomics Core, University of California, Davis for the eY1H screen.

Author information

Authors and Affiliations

  1. MSU-DOE Plant Research Lab, Michigan State University, East Lansing, MI, USA

    Dae Kwan Ko & Federica Brandizzi

  2. Great Lakes Bioenergy Research Center, Michigan State University, East Lansing, MI, USA

    Dae Kwan Ko & Federica Brandizzi

  3. Department of Plant Biology, Michigan State University, East Lansing, MI, USA

    Federica Brandizzi

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  1. Dae Kwan Ko
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Contributions

D.K.K. and F.B. conceived the project and designed the experiments and research plan. D.K.K. performed experiments and data analysis. F.B. supervised the project. D.K.K. and F.B. interpreted the data and wrote the manuscript.

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Correspondence to Federica Brandizzi.

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Nature Plants thanks Yukio Kurihara, Xinhong Guo and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Identification of DEGs under either ABA treatment or ER stress recovery in this study.

a, The number of DEGs at each time-point of either condition. The DEGs were identified relative to the corresponding mock controls in each set of treatments (ABA or ER stress recovery). ABA, ABA treated conditions. ERR, ER stress recovery conditions. A full list of UPR-ABA DEGs is provided in Supplementary Data 2. b, GO terms enriched for ERR-ABA DEGs (see Fig. 1a). The 30 GO terms with the largest gene ratios are plotted in order of gene ratio. The P values were calculated by a hypergeometric test with Benjamini–Hochberg correction. The size of the dots represents the number of genes annotated to the corresponding GO term and the colour of the dots represent the adjusted P-values. A full list of GO terms is provided in Supplementary Data 2.

Source data

Extended Data Fig. 2 Pairwise correlation analyses of relative expression levels of DEGs between between ABA (1, 4, 8, 12, 24 or 60 h) and ERR (0, 12 or 24 h) conditions.

a-f, The expression of each of the DEGs were subjected to Spearman correlation coefficient analysis between ABA treatment 1 h (a), 4 h (b), 8 h (c), 12 h (d), 24 h (e) or 48 h (f) and ER stress recovery conditions. The scatter plot (centre) shows the pairwise expression pattern of the genes between ABA treatment and each ER stress recovery time-point. The density plots at the top and right visualize the enrichment of Log2FC under ER stress recovery and ABA, respectively. The Spearman’s correlation coefficient (rho) for each comparison is shown along with the level of significance (P value) in the corresponding colour. Error bars (grey) denote 95% confidence intervals. The plot between ABA-36 h and each time-point of ERR is shown in Fig. 1b.

Extended Data Fig. 3 Enriched motifs on the promoters of the ERR-ABA DEGs.

The 1 kb promoter of each ERR-ABA DEG (n = 922; 8 of 928 ERR-ABA DEGs have no promoter sequences available) was split into 10 fragments (10 bp overlapping). The 1 kb promoter of each of the randomly selected 922 genes was also processed in the same way. De novo motif analyses were performed on each set of promoter fragments of DEGs relative to those of random genes. Below the scheme, the significantly enriched motifs are shown with the corresponding P values and TF families of which the binding site significantly matched the corresponding motif. CHC, CXC-hinge-CXC. DOF, DNA binding with one finger. MYB, myeloblastosis.

Extended Data Fig. 4 Location of G-box and ABRE on promoters of core UPR genes.

The 1 kb promoter and 5’UTR sequences of (a) BiP1, (b) BiP2, (c) BiP3, (d) ERdj3A, (e) ERdj3B, (f) bZIP17, (g) bZIP28, (h) bZIP60, (i) IRE1a and (j) IRE1b. G-box (5’-CACGT-3’) and its reverse-complement sequence (5’-ACGTG-3’) are marked by light blue. ABRE (5’-CACG-3’) and its reverse-complement sequence (5’-CGTG-3’). The transcriptional start site of each gene is indicated by bold letters.

Extended Data Fig. 5 DNA sequence-specific binding of TFs to the UPR gene promoters.

a, A heatmap showing frequency distribution for the binding of multiple TF family members to each of the promoter fragments used in our eY1H screen. TF families of which members bound to the promoter fragment ≥ 10 times were selected for this analysis. b, Schematic representation of TF binding motif locations for selected TF families. Black arrowheads indicate the locations of the core sequence of corresponding TF motifs.

Source data

Extended Data Fig. 6 GO analysis of TFs binding either exclusively to each bait gene or all bait genes.

Significantly enriched GO terms were identified with adjusted P < 0.05 using a Hypergeometric test with Bonferroni correction. 28, TFs binding exclusively to the bZIP28 promoters. 60, TFs binding exclusively to the bZIP60 promoters. B3, TFs binding exclusively to the BiP3 promoters. All, TFs binding exclusively to all of the promoters. A full list of GO terms with adjusted P values is provided in Supplementary Data 5. Red asterisks indicate phytohormone-related pathways.

Extended Data Fig. 7 Hyposensitivity of gbf2 null mutants to ER stress.

Relative growth rate of primary root of Col-0, bzip28-2 bzip60-1, gbf2-1, gbf2-2 and gbf1 (-/-) gbf2-2 (-/+) gbf3 (-/-) after 7 days in ERR. Means ± SEM; n = 4 biological replicates (6 seedlings per replicate) for gbf2-1 and gbf2-2; n = 5 biological replicates (6 seedlings per replicate) for Col-0, bzip28-2 bzip60-1 and gbf1 (-/-) gbf2-2 (-/+) gbf3 (-/-). The significance (P value) measured by two-tailed Student’s t-test is shown. ns, not significant. The experiments were independently repeated at least two times with similar results.

Source data

Extended Data Fig. 8 Differential expression of ABA biomarker genes under ABA treatment in gbf2-3.

qRT–PCR assays of AT1G52680, AT4G35690, AT5G06090, and AT5G43770 expression (Log2[ABA/EtOH]) under ABA treatment (0 h, 12 h and 24 h). The genes were selected because they displayed high expression responsiveness to ABA and were bound by GBF213. Five-old-day plants were treated with 3 µM ABA or EtOH (solvent) only. Whole seedlings were harvested at the indicated time-points. The expression values were calculated relative to UBQ10. Means ± SEM; n = 3 biological replicates (12 seedlings per replicate). The significance (P value) measured by two-tailed Student’s t-test is shown. The experiments were independently repeated at least two times with similar results.

Source data

Extended Data Fig. 9 GBF2 temporally binds to the promoter of BiP3 during ERR.

ChIP–qPCR assays of temporal binding of GBF2 to the BiP3 promoters in ERR (0 h, 12 h and 24 h). The enrichment values are represented relative to the corresponding input values. Samples treated with DMSO served as the mock treatment. Mock samples (ChIP without antibodies) were used as negative controls for ChIP. The ACT7 gene promoter was used as a negative control for the enrichment. Means ± SEM; n = 3 biological replicates (≥ 100 seedlings per replicate). The significance (P value) measured by two-tailed Student’s t-test is shown. The experiments were independently repeated at least two times with similar results.

Source data

Supplementary information

Reporting Summary

Supplementary Tables

Supplementary Table 1. Creation of entry clones in our eY1H screen. For BP cloning, attB4 (GGGGACAACTTTGTATAGAAAAGTTG) and attB1R (GGGGACTGCTTTTTTGTACAAACTTG) sites are attached at 5′ of the forward and reverse primers, respectively. Supplementary Table 2. Primers used in this study. *G-box is labelled red. **The mutated G-box is labelled red. ***Restriction enzyme digestion sites are underlined.

Supplementary Data

Supplementary Data 1. Relative expression levels (log2(ABA/EtOH) or log2(Tm/DMSO)) of UPR-ABA DEGs. ABA, treatment with 10 µM ABA. ERR, recovery from ER stress (500 ng ml–1 Tm for 6 h). Supplementary Data 2. A full list of enriched GO terms for the UPR-ABA DEGs. Top-ranked GO terms are visualized in Extended Data Fig. 1b. Supplementary Data 3. TF motifs statistically matched with potential CREs found on the DEGs. CREs are described in Fig. 1c and Extended Data Fig. 3. Supplementary Data 4. PDIs obtained from our eY1H screen. Each row shows a PDI. The TF network built on PDIs are mapped in Fig. 1f. Supplementary Data 5. A full list of enriched GO terms for TF genes in the UPR-TF network shown in Fig. 1f. Top-ranked GO terms are visualized in Extended Data Fig. 6. P, biological process. F, molecular function. C, cellular component. Supplementary Data 6. UPR-specific binding peaks of GBF2 at 0 h of ERR. *1, sense. 2, antisense. Distal intergenic peaks were not included for gene annotation. Supplementary Data 7. A full list of enriched GO terms for genes cobound by GBF2 and bZIP28 (and/or bZIP60) at 0 h of ERR. Top-ranked GO terms are visualized in Fig. 2f.

Source data

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Ko, D.K., Brandizzi, F. Transcriptional competition shapes proteotoxic ER stress resolution. Nat. Plants 8, 481–490 (2022). https://doi.org/10.1038/s41477-022-01150-w

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