eIF2alpha kinases GCN2 and PERK modulate transcription and translation of distinct sets of mRNAs in mouse liver

Abstract

In eukaryotes, selective derepression of mRNA translation through altered utilization of upstream open reading frames (uORF) or internal ribosomal entry sites (IRES) regulatory motifs following exposure to stress is regulated at the initiation stage through the increased phosphorylation of eukaryotic initiation factor 2 on its alpha-subunit (eIF2alpha). While there is only one known eIF2alpha kinase in yeast, general control nonderepressible 2 (GCN2), mammals have evolved to express at least four: GCN2, heme-regulated inhibitor kinase (HRI), double-stranded RNA-activated protein kinase (PKR), and PKR-like endoplasmic reticulum-resident kinase (PERK). So far, the main known distinction among these four kinases is their activation in response to different acute stressors. In the present study, we used the in situ perfused mouse liver model and hybridization array analyses to assess the general translational response to stress regulated by two of these kinases, GCN2 and PERK, and to differentiate between the downstream effects of activating GCN2 versus PERK. The resulting data showed that at least 2.5% of mouse liver mRNAs are subject to derepressed translation following stress. In addition, the data demonstrated that eIF2alpha kinases GCN2 and PERK differentially regulate mRNA transcription and translation, which in the latter case suggests that increased eIF2alpha phosphorylation is not sufficient for derepression of translation. These findings open an avenue for more focused future research toward groups of mRNAs that code for the early cellular stress response proteins.

Fig. 1.

Regulation of eukaryotic initiation factor (eIF)2α, eIF2B, and polysome aggregation in perfused general control nonderepressible 2 (GCN2)- and double-stranded RNA-activated protein kinase (PKR)-like endoplasmic reticulum-resident kinase (PERK)-perfused mouse livers after methionine (Met) deprivation or 2,5-di-tert-butylhydroquinone (tBuHQ) treatment, respectively. A, C, E, G: Gcn2+/+ or −/− mouse livers were perfused for 35 min with perfusate containing complete amino acids (open bars, A and C) or deficient in Met (gray bars, A and C). B, D, F, H: Perk+/+ or Alb/Cre Perk−/− mouse livers perfused for 35 min with perfusate containing DMSO (open bars, B and D) or 40 μM tBuHQ (gray bars, B and D). A and B: insets show representative Western blots for Ser51 phosphorylated (2αP, top) and total (2αT, bottom) eIF2α. Bars represent quantitation of Western blot band density, calculated as ratio of phosphorylated over total eIF2α. Values are means ± SE. C and D: guanine nucleotide exchange activity of eIF2B. n = 9 or 10 livers/group. Statistical significance was determined by unpaired t-test: *P < 0.001, **P < 0.025. E–H: polysome profiles of GCN2 (E, G)- and PERK (F, H)-perfused mouse livers. Supernatant from liver homogenate was resolved on a 20–47% sucrose density gradient. Absorbance at 254 nm was continuously measured and recorded to generate profiles. Assignment of the 40S, 60/80S, subpolysome, and polysome peaks was as demonstrated in E. E and F: representative gradient profile for conditions of wild-type control condition. G and H: representative gradient profile for wild-type treated condition. Profiles are representative of n = 9 or 10 livers/group.

Fig. 2.

Number of mRNAs whose expression changed in eIF2α kinase−/− vs. +/+ perfused livers. GCN2 or PERK mouse livers were perfused for 35 min with perfusate ± Met or ± tBuHQ, respectively. Total RNA was extracted from the unfractionated supernatant and used in hybridization arrays experiments. A: analyses of the effect of eIF2α kinase on mRNA abundance were done by sorting of the Z score of genes in the arrays. mRNAs with Z score >1.5 when comparing expression in −/− vs. +/+ samples were considered to have increased expression in the absence of the eIF2α kinase. mRNAs with Z score less than −1.5 when comparing expression in −/− vs. +/+ samples were considered to have decreased expression in the absence of the eIF2α kinase. B: Venn diagram of mRNAs whose expression increased in the absence of GCN2 or PERK. C: Venn diagram of mRNAs whose expression decreased in the absence of GCN2 or PERK.

Fig. 3.

Functional categories of genes whose mRNA expression changed in the absence of GCN2 or PERK. Mouse livers were perfused for 35 min with or without treatment as described in Fig. 2. Total RNA was extracted from liver homogenates for use in hybridization array experiments. Analyses of eIF2α kinase-dependent increase or decrease in mRNA expression were done by sorting of genes with Z score greater than 1.5 or less than −1.5. Sublists of sorted genes were used for biological process classification in GeneSpring. Bars represent number of genes within the functional category whose mRNA expression increased (positive values) or decreased (negative values) in the absence of GCN2 (A) or PERK (B). A functional category is included only if it contains ≥3 genes and has a GeneSpring P value of <0.05.

Fig. 4.

Validation of hybridization array results of mRNAs whose expression decreased in the absence of GCN2 (left) or PERK (right). Experimental conditions and analyses used for the identification of genes whose mRNA expression decreased in the absence of GCN2 or PERK were as described in Figs. 2 and 3. Total RNA extracted from unfractionated liver samples was used in quantitative (q)RT-PCR to validate mRNAs with Z score less than −1.5 (Asns, Dct, Calr, Cyp2c55) or those reported in the literature to affect Asns transcription (ATF5) or to be transcriptionally regulated by PERK (Herpud1).

Fig. 5.

Number of mRNAs whose abundance in the polysome fraction changed after treatment in wild-type livers. GCN2 or PERK mouse livers were perfused for 35 min with perfusate ± Met or ± tBuHQ, respectively. Total RNA was extracted from the unfractionated supernatants and polysome fractions for use in hybridization array experiments. A: analyses of the effect of treatment on mRNA abundance in the polysome fraction were done by sorting of the Z scores of genes in the arrays. mRNAs with Z score > 1.5 in polysome fraction of wild-type treated livers were considered to have shifted into polysomes after activation of the eIF2α kinase. mRNAs with Z score less than −1.5 in polysome fraction of wild-type treated livers were considered to have shifted out of polysomes after activation of the eIF2α kinase. B: Venn diagram of mRNAs that shifted into polysomes after activation of GCN2 or PERK. C: Venn diagram of mRNAs that shifted out of polysomes after activation of GCN2 or PERK.

Fig. 6.

Functional categories of genes whose mRNAs shift into or out of polysomes after Met deprivation, in the presence of GCN2. Gcn2+/+ or −/− mouse livers were perfused for 35 min ± Met, and supernatant was fractioned on a 20–47% sucrose density gradient. Total RNA was extracted from the unfractionated supernatant and the polysomal gradient fraction for use in hybridization array experiments. Analyses of GCN2-dependent shift of mRNAs into polysomes were done by sorting of Z scores of genes in arrays containing unfractionated supernatant and polysomal gradient fraction. Sublists of sorted genes were used for biological process classification in GeneSpring. Bars represent number of genes within the functional category whose mRNA shifted into (positive values) or out of (negative values) polysome fraction. A functional category is included only if it contains ≥3 genes and has a GeneSpring P value of <0.05.

Fig. 7.

Functional categories of genes whose mRNAs shift in or out of polysomes after tBuHQ treatment in the presence of PERK. Perk+/+ or −/− mouse livers were perfused for 35 min ± tBuHQ, and supernatant was fractioned on a 20–47% sucrose density gradient. Total RNA was extracted from the unfractionated supernatant and the polysomal gradient fraction for use in hybridization array experiments. Analyses of PERK-dependent shift of mRNAs into polysomes were done by sorting of Z scores of genes in arrays containing unfractionated supernatant and polysomal gradient fraction. Sublists of sorted genes were used for biological process classification in GeneSpring. Bars represent number of genes within the functional category whose mRNA shifted into (positive values) or out of (negative values) polysome fraction. A functional category is included only if it contains ≥3 genes and has a GeneSpring P value of <0.05.

Fig. 8.

qRT-PCR validation of polysome distribution of selected mRNAs in Gcn2 wild-type vs. knockout perfused livers. Mouse livers were perfused for 35 min ± Met. Total RNA was extracted from the unfractionated supernatant and the nonpolysomal, subpolysomal, and polysomal gradient fractions for use in hybridization array and qRT-PCR experiments. Expression of mRNA was determined by qRT-PCR and normalized to the average expression of the housekeeping genes β-actin, Gapdh, and Tbp (see materials and methods for details on calculations). Values are means ± SD; n = 6 or 7. A and B: putative housekeeping genes. C and D: genes identified in this experiment to have shifted into polysomes after activation of GCN2. E and F: genes reported in the literature whose mRNA shifted into polysomes after activation of GCN2. Statistical analysis of the data is presented in Supplemental Table S7.

Fig. 9.

qRT-PCR validation of polysome distribution of selected mRNAs in Perk wild-type vs. knockout perfused livers. Mouse livers were perfused for 35 min ± tBuHQ. Total RNA was extracted from the unfractionated supernatant and the nonpolysomal, subpolysomal, and polysomal gradient fractions for use in hybridization array and qRT-PCR experiments. Expression of mRNA was determined by qRT-PCR and normalized to the average expression of the housekeeping genes β-actin, Gapdh, and Tbp (see materials and methods for details on calculations). Values are means ± SD; n = 6 or 7. A and B: putative housekeeping genes. C and D: genes identified in this experiment to have shifted into polysomes after activation of PERK. E and F: genes reported in the literature whose mRNA shifted into polysomes after activation of PERK. Statistical analysis of the data is presented in Supplemental Table S8.