Translational Regulation of Metabolic Dynamics during Effector-Triggered Immunity

Abstract

Recent studies have shown that global translational reprogramming is an early activation event in pattern-triggered immunity, when plants recognize microbe-associated molecular patterns. However, it is not fully known whether translational regulation also occurs in subsequent immune responses, such as effector-triggered immunity (ETI). In this study, we performed genome-wide ribosome profiling in Arabidopsis upon RPS2-mediated ETI activation and discovered that specific groups of genes were translationally regulated, mostly in coordination with transcription. These genes encode enzymes involved in aromatic amino acid, phenylpropanoid, camalexin, and sphingolipid metabolism. The functional significance of these components in ETI was confirmed by genetic and biochemical analyses. Our findings provide new insights into diverse translational regulation of plant immune responses and demonstrate that translational coordination of metabolic gene expression is an important strategy for ETI.

Keywords: effector-triggered immunity, ETI; helper receptors; phenylalanine; phenylpropanoids; ribosome profiling; translational regulation.

Figure 1.. Translational activities during ETI.

(A) Schematic of RNA-seq (RS) and Ribo-seq (RF) library construction using 35S:uORFs_TBF1-LUC/WT and 35S:uORFs_TBF1-LUC/rps2 plants. (B) Translation of the 35S:uORFs_TBF1-LUC reporter in wild type (WT) and the rps2 mutant after Mock (10 mM MgCl₂) or Psm ES4326/AvrRpt2 (AvrRpt2) treatment (OD_600nm = 0.02). Relative LUC activity was normalized to the level at 1 hour post infiltration (hpi). Data are mean ± SEM; n = 6 biological replicates. Error bars with different letters represent statistically significant differences based on Tukey’s test (P < 0.05; one-way ANOVA). (C) TBF1 mRNA associated with polysomal fractions at different time points after Psm ES4326/AvrRpt2 treatment (OD_600nm = 0.02) (mean ± SD; n = 4 technical replicates from one representative experiment). TBF1 mRNA abundance was normalized to the level of UBQ5 mRNA in all fractions. Lower-case letters in the x-axis indicate polysomal fractions in the polysome profile obtained by sucrose density gradient fractionation. (D and E) Polysome profiling of global translational activity at 8 hpi (D) and TBF1 mRNA translational activity (E) calculated as ratios of polysomal/total mRNA in WT (left panel) and rps2 (right panel) after Psm ES4326/AvrRpt2 treatment (OD_600nm = 0.02). Transcript levels of TBF1 were normalized against UBQ5 levels determined by qRT-PCR and ratios of polysomal fractions over the total mRNA are presented. Data are mean ± SD; n = 4 technical replicates. See also Figures S1 and S2.

Figure 2.. Identification of new immune regulators based on global analysis of translational changes during RPS2-mediated ETI.

(A and B) Relationships between RSfc and RFfc (A), and between RSfc and TEfc (B) in WT. dn, down; nc, no change. Black dots, candidates selected for ETI phenotype testing. (C–E) Growth of Psm ES4326 (left) or Psm ES4326/AvrRpt2 (middle) (OD_600nm = 0.001), and ion leakage analysis (right) caused by Psm ES4326/AvrRpt2 (OD_600nm = 0.01) in phenotypic group A (C), group B (D), and group C (E) of new immune regulators. WT and rps2 were used as controls. TU, TEup; TD, TEdn; EC, ETI candidate. Different letters indicate values that are significantly different based on Tukey’s test (P < 0.01; one-way ANOVA). For ion leakage analysis, the last time point was used for statistical analysis. Data are mean ± SEM; n = 8 biological replicates for bacterial growth and n = 3 biological replicates for ion leakage analysis. See also Figure S3, Data S1-S3, and Table S1.

Figure 3.. mRNA association with ribosomes upon ETI induction.

(A–C) Ribosomal associations of ETI-gene mRNAs were calculated as polysomal/total mRNA fractions with mock or ETI (AvrRpt2) induction. Expression levels were normalized against UBQ5. (A), (B), and (C) correspond to Figure 2C, 2D, and 2E, respectively. Data are mean ± SD; n = 3 three biological replicates. Data were combined using linear mixed effect model (lme4) with experiment as random effects; * P < 0.05 and ** P < 0.01 as determined by student's t-test. See also Table S1.

Figure 4.. Transcriptional and translational dynamics of specific metabolic pathways during ETI.

The schematic representation of metabolic pathways with each enzymatic step (EC number) was generated using MetaCyc Metabolic Pathway Database (Caspi et al., 2018). The fold changes are shown with colors for transcription (left box) and translation (right box). Gray box with inscribed x indicates no significant change detected. See also Figures S4, S5, Data S4, Tables S2-S3.

Figure 5.. Phenylalanine and its derivatives are important for ETI response.

(A) Levels of amino acids during ETI. Data are mean ± SEM; n = 8 biological replicates from 2 experiments. * P < 0.05, ** P < 0.01, *** P < 0.001 as determined by student's t-test (Met P = 0.063). (B) Ribosomal associations of ADT4, ADT5, and PAL1 mRNAs were calculated as polysomal/total RNA fractions with mock or ETI (AvrRpt2) induction. Expression levels were normalized against UBQ5. Data are mean ± SD; n = 3 biological replicates. Data were combined using linear mixed effect model (lme4) with experiment as random effects and student's t-test was performed. (C and D) Growth of Psm ES4326 (left), and Psm ES4326/AvrRpt2 (right) (C), and ion leakage caused by Psm ES4326/AvrRpt2 (D) (OD_600nm = 0.001 for bacterial growth and 0.01 for ion leakage). Data are mean ± SEM; n = 8 biological replicates for bacterial growth and n = 3 biological replicates for ion leakage analysis. (E) Ion leakage analysis with exogeneous phenylalanine (Phe) treatment (5 mM) in WT and rps2 plants. Data are mean ± SEM; n = 4 biological replicates. (F) Ion leakage analysis with exogeneous 6-aminonicotinamide (6AN) treatment (1.25 mM) in WT and rps2 plants. Data are mean ± SEM; n = 3 biological replicates. (C-F) Different letters indicate values that are significantly different based on Tukey’s test (P < 0.01; one-way ANOVA). For ion leakage analysis, the last time point was used for statistical analysis. See also Figures S6 and S7.

Figure 6.. Venn diagrams of transcriptional and translational responses from the AvrRpm1 and AvrRpt2 datasets.

(A) Venn diagrams showing numbers of overlapping and non-overlapping transcriptionally up-regulated genes (RSup) and translationally up-regulated genes (RFup) between the AvrRpm1 (blue) and AvrRpt2 (red) datasets. (B) Venn diagrams showing numbers of overlapping and non-overlapping transcriptionally down-regulated genes (RSdn) and translationally down-regulated genes (RFdn) between the AvrRpm1 and AvrRpt2 datasets. RS, RNA-seq; RF, ribosomal footprinting; fc, fold change; up, up-regulated; dn, down-regulated. See also Data S5.