Extensive translatome remodeling during ER stress response in mammalian cells

Abstract

In this work we have described the translatome of two mammalian cell lines, NIH3T3 and Jurkat, by scoring the relative polysome association of ∼10,000 mRNA under normal and ER stress conditions. We have found that translation efficiencies of mRNA correlated poorly with transcript abundance, although a general tendency was observed so that the highest translation efficiencies were found in abundant mRNA. Despite the differences found between mouse (NIH3T3) and human (Jurkat) cells, both cell types share a common translatome composed by ∼800-900 mRNA that encode proteins involved in basic cellular functions. Upon stress, an extensive remodeling in translatomes was observed so that translation of ∼50% of mRNA was inhibited in both cell types, this effect being more dramatic for those mRNA that accounted for most of the cell translation. Interestingly, we found two subsets comprising 1000-1500 mRNA whose translation resisted or was induced by stress. Translation arrest resistant class includes many mRNA encoding aminoacyl tRNA synthetases, ATPases and enzymes involved in DNA replication and stress response such as BiP. This class of mRNA is characterized by high translation rates in both control and stress conditions. Translation inducible class includes mRNA whose translation was relieved after stress, showing a high enrichment in early response transcription factors of bZIP and zinc finger C2H2 classes. Unlike yeast, a general coordination between changes in translation and transcription upon stress (potentiation) was not observed in mammalian cells. Among the different features of mRNA analyzed, we found a relevant association of translation efficiency with the presence of upstream ATG in the 5'UTR and with the length of coding sequence of mRNA, and a looser association with other parameters such as the length and the G+C content of 5'UTR. A model for translatome remodeling during the acute phase of stress response in mammalian cells is proposed.

Figure 1. Translatomes of NIH3T3 and Jurkat cells based on polysome profiling.

A) The quality of polysome preparation was verified by electrophoretic analysis of RNA content in each fraction. The effect of thapsigargin treatment (stress) for the indicated hours on polysome distribution in Jurkat cells is also shown. A comparable result was obtained in NIH3T3 cells (Figure S1). Ribosomal 18 S and 28 S bands are shown. B) and C) Density distribution of translation efficiencies of 10,670 coding mRNAs from Jurkat and 8,459 mRNAs from NIH3T3 under optimal growth conditions. Those mRNA equally distributed among FM and P fractions showed a log₂P/FM = 0 (marked by a dotted red line). The median values for Jurkat and NIH3T3 cells were 1.07 and 0.45, respectively. The translation efficiencies of some representative mRNA are shown (ACTB, HSPA5, SNRPB, RPL4, ATF4 and FTH1). D) qPCR validation of translation efficiencies for some of the above mentioned mRNA. Data are the mean ±SD from two independent qPCR reactions in Jurkat and NIH3T3 cells.

Figure 2. Defining the basic translatome shared by NIH3T3 and Jurkat cells.

A) and B) Correlation analysis of log₂P/FM values among all mouse-man ortholog mRNA pairs detected in the chips (8,019) or among those that showed the highest abundance (A value ≥10; 802 mRNAs). Only coding mRNA were used. Note the significant increase in R². C) A more detailed analysis of the correlation between mRNA abundance and translational consistency among orthologs. Note that pearson’s correlation coefficients (r) increased proportional to mRNA abundance. The subset of mRNA orthologs showing A values ≥10 was subjected to functional analysis using the FatiScan programme. Translation efficiencies were ranked in green to red according to NIH3T3 data and the most significant GO and KEEG terms enriched along the ranking were annotated on the right together with the adjusted p values. A similar result was obtained when the list was ranked according to Jurkat data. Note the specific enrichment in GO terms for orthologs with top and bottom log₂P/FM values.

Figure 3. Stress-induced remodeling of translatomes.

Identification of translation classes of mRNA. A) Analysis of the translation change after stress using the classical metabolic labeling of newly-made proteins with [³⁵S]-Met. NIH3T3 cells were treated with thapsigargin for the indicated times, labeled for 30′ and proteins were analyzed by SDS-PAGE and autoradiography. Note that [³⁵S]-Met incorporation was inhibited by 90% at 1h and by 70% at 3 h after stress treatment. The phosphorylation state of eIF2α was analyzed by western-blot in parallel (lower panel). B) The synthesis of proteins that account for most of cellular translation was preferentially inhibited after stress. Based on 2D PAGE analysis and mass spectroscopy (MS) data extracted from the literature, we built a list with the 46 most abundant proteins found in NIH3T3 and Jurkat cells (see Table S1). The mean ±SD of log₂P/FM values for this mRNA subset under control and stress conditions are shown and compared with values obtained for all mRNA in both cell types. C) Plots showing the change in translation efficiencies (log₂P/FM stress-log₂P/FM control) after thapsigargin treatment (3 h for NIH3T3, 1h and 3 h for Jurkat). In parentheses are the number of mRNA used in the analysis. Quadrants were set to identify the translation classes according to values in log₂P/FM change upon stress. The sensitive (S) class comprises mRNA whose translation decreased≥0.8 log₂ (40–50% of mRNAs in both NIH3T3 and Jurkat). A representative member of this group is the ACTB mRNA. Resistant (R) class includes those mRNA that continue to translate at moderate to high rates during stress. These mRNA show a log₂P/FM≥0.8 in both control and stressed cells, and comprises about 3–4% of total mRNA in NIH3T3 and up to 13% in Jurkat cells. A representative member of this group is the HSPA5 (the BiP chaperone) mRNA. Translation inducible class (I) comprises mRNA with low translation efficiencies under control conditions (log₂ P/FM≤0) that increased upon stress (log₂ change≥1). This group comprises about 8% of mRNA in NIH3T3 cells and 1.5% in Jurkat cells. A representative member of this group is the transcription factor ATF4.

Figure 4. Validation and functional analysis (GO) of translational classes.

A) GO terms found in translation classes. Only the most enriched terms with adjusted p-values<10⁻² are shown (FatiGO analysis). Note the existence of some cell-specific terms in NIH3T3 and Jurkat cells. B) Translational changes upon stress of some representative mRNA of S, R and I classes detected by microarrays. For R class, we focused on mRNA encoding HSPA5 (BiP), the alanyl-tRNA synthetase (AARS) and the ligase I (LIG1). For I class, in addition to ATF4, we also analyzed the mRNA encoding the transcription factors early growth response protein 2 (EGR2) and the proto-oncogenes c-Fos (FOS) and c-Jun (JUN). The ACTB mRNA is a representative member of S class. Lower panel shows the validation of log₂P/FM data by qPCR for some mRNA.

Figure 5. Analysis of stress-induced coordinate changes in translatome and transcriptome.

A) Venn diagrams of mRNA that only experienced translational changes upon stress (log₂ P/M change≥1 or≤−1, yellow circle), those that only experienced transcriptional changes (A change≥1 or≤−1, blue circle) or whose that significantly changed in both log₂P/FM and A values (merged). The number of mRNAs for each group is shown. B) Changes in mRNA abundance for each translational class after stress. The number and percentage of mRNA whose abundance changed after stress (up or down) for each translational class (S, R and I) are shown in gray rectangles. Black rectangles show the number of mRNA that comprises each class based on their translational behavior upon stress. Note that a significant percentage of mRNA whose translation resisted or was induced by stress also increased in abundance, especially in Jurkat cells.