Abstract
Fungal pathogens need to contend with stresses including oxidants and antimicrobial chemicals resulting from host defenses. ChAP1 of Cochliobolus heterostrophus, agent of Southern corn leaf blight, encodes an ortholog of yeast YAP1. ChAP1 is retained in the nucleus in response to plant-derived phenolic acids, in addition to its well-studied activation by oxidants. Here, we used transcriptome profiling to ask which genes are regulated in response to ChAP1 activation by ferulic acid (FA), a phenolic abundant in the maize host. Nuclearization of ChAP1 in response to phenolics is not followed by strong expression of genes needed for oxidative stress tolerance. We, therefore, compared the transcriptomes of the wild-type pathogen and a ChAP1 deletion mutant, to study the function of ChAP1 in response to FA. We hypothesized that if ChAP1 is retained in the nucleus under plant-related stress conditions yet in the absence of obvious oxidant stress, it should have additional regulatory functions. The transcriptional signature in response to FA in the wild type compared to the mutant sheds light on the signaling mechanisms and response pathways by which ChAP1 can mediate tolerance to ferulic acid, distinct from its previously known role in the antioxidant response. The ChAP1-dependent FA regulon consists mainly of two large clusters. The enrichment of transport and metabolism-related genes in cluster 1 indicates that C. heterostrophus degrades FA and removes it from the cell. When this fails at increasing stress levels, FA provides a signal for cell death, indicated by the enrichment of cell death-related genes in cluster 2. By quantitation of survival and by TUNEL assays, we show that ChAP1 promotes survival and mitigates cell death. Growth rate data show a time window in which the mutant colony expands faster than the wild type. The results delineate a transcriptional regulatory pattern in which ChAP1 helps balance a survival response for tolerance to FA, against a pathway promoting cell death in the pathogen. A general model for the transition from a phase where the return to homeostasis dominates to a phase leading to the onset of cell death provides a context for understanding these findings.
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Adapted from a scheme of Galluzzi et al. (2016) comparing two alternative mechanisms; here, the diagram compares WT and mutant
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Acknowledgements
We thank Amir Sharon for discussions of fungal RCD, and Laura D. Cohen for critical reading of the manuscript. We are grateful to Nitsan Dahan for expert assistance with confocal microscopy at the Technion Life Sciences and Engineering Infrastructure Center Life Sciences (LS&E) Center, and to Tal Katz-Ezov (Director, Technion Genome Center, TGC), Roni Koren (Horwitz lab) and Guy Horev (Bioinformatics Knowledge Unit) for their advice and suggestions. This work was supported in part by Grant 332/13 from the Israel Science Foundation and by the Russell Berrie Nanotechnology Institute, Technion. H. S. graduate student fellowship was funded in part by the Irwin and Joan Jacobs Graduate School, Technion.
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HS, SS, and BAH designed the study and wrote the manuscript. HS, SS, and OG prepared the samples and carried out the experiments. OK and MH performed the RNA-Seq data analysis.
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294_2019_1012_MOESM2_ESM.tif
Supplementary material 2 (TIFF 258 kb) Fig. S1. PCA plots for WT (A) and ∆chap1 (B); the biological replicates (five for WT, three for ∆chap1) for WT are labeled (r1-r5). Replicates for the same treatment are represented by symbols of the same color (for color coding see legend at top right) (C0: control (DMSO), C0.5: 0.5 mM FA, C1: 1 mM FA, C2: 2 mM FA
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Supplementary material 3 (TIFF 180 kb) Fig. S2. Transcript levels for selected genes, measured by qRT-PCR. A. Transcript levels for control (DMSO), 0.5, 1, and 2 mM FA. B. Transcript levels for control (DMSO), and 2 mM FA. The asterisks *, **, ***, **** indicate significance at P < 0.05, 0.01, 0.001, and 0.0001, respectively, in WT and ∆chap1 and between them. The y-axis indicates transcript levels on a logarithmic scale normalized by actin transcript levels. Error bars indicate SD for three biological replicates. C. Gene expression correlation between qRT-PCR (x-axis) and RNA-Seq data (y-axis). Coordinates of each point are the fold changes (FA treatment/control) for the same treatment measured by the two methods, plotted on log2-log2 scale. The correlation coefficient (R2) and linear regression line are shown
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Supplementary material 4 (TIFF 390 kb) Fig. S3. MA plots of differentially expressed genes identified in each treatment (C0.5, C1, C2) versus control (C0) for WT (A) and ∆chap1 (B). Data represent individual gene responses plotted as log2 fold change (y-axis) versus the mean of normalized counts (x-axis). The red dots indicate transcripts whose levels differ significantly from the control at adjusted p value < 0.05, with a negative change representing the down-regulated genes and a positive change representing the up-regulated genes. C0: control, C0.5: 0.5 mM FA, C1: 1 mM FA, C2: 2 mM FA
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Supplementary material 5 (TIFF 219 kb) Fig. S4. GO (A) and EuKaryotic Orthologous Groups (KOG) (B) functional enrichment analysis of DEGs in cluster 1 and cluster 2. The x-axis indicates functional groups. The y-axis indicates –log(p value). The threshold p value ≤ 0.01 was corrected for multiple testing using the FDR correction. The enrichment factor (frequency of genes of a functional class within the annotated genes in the examined set, divided by frequency within the background set of all the genes in the genome), indicated at the top of each bar. Blue bars, ‘Molecular Function’ (MF) categories in GO; green bars, ‘Cellular Component’ (CO) categories in GO; red bars, ‘Biological Process’ (BP) categories in GO
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Supplementary material 6 (TIFF 267 kb) Fig. S5. The expression of the first ten genes that are regulated significantly only in 2 mM FA and have annotation by KOG/Interpro description, with the highest (A) and lowest (B) fold change in WT, according to RNA-Seq data. The x-axis indicates the ID number for each gene. The y-axis indicates fold change in gene expression at 2 mM FA (C2) compared to the control (C0) in WT and ∆chap1
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Simaan, H., Shalaby, S., Hatoel, M. et al. The AP-1-like transcription factor ChAP1 balances tolerance and cell death in the response of the maize pathogen Cochliobolus heterostrophus to a plant phenolic. Curr Genet 66, 187–203 (2020). https://doi.org/10.1007/s00294-019-01012-7
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DOI: https://doi.org/10.1007/s00294-019-01012-7