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. 2016 May 16:6:25795.
doi: 10.1038/srep25795.

Global quantitative proteomics reveal up-regulation of endoplasmic reticulum stress response proteins upon depletion of eIF5A in HeLa cells

Ajeet Mandal  1 , Swati Mandal  1 , Myung Hee Park  1
Affiliations

Global quantitative proteomics reveal up-regulation of endoplasmic reticulum stress response proteins upon depletion of eIF5A in HeLa cells

Ajeet Mandal et al. Sci Rep. .

Abstract

The eukaryotic translation factor, eIF5A, is a translation factor essential for protein synthesis, cell growth and animal development. By use of a adenoviral eIF5A shRNA, we have achieved an effective depletion of eIF5A in HeLa cells and undertook in vivo comprehensive proteomic analyses to examine the effects of eIF5A depletion on the total proteome and to identify cellular pathways influenced by eIF5A. The proteome of HeLa cells transduced with eIF5A shRNA was compared with that of scramble shRNA-transduced counterpart by the iTRAQ method. We identified 972 proteins consistently detected in three iTRAQ experiments and 104 proteins with significantly altered levels (protein ratio ≥1.5 or ≤0.66, p-value ≤0.05) at 72 h and/or 96 h of Ad-eIF5A-shRNA transduction. The altered expression levels of key pathway proteins were validated by western blotting. Integration of functional ontology with expression data of the 104 proteins revealed specific biological processes that are prominently up- or down-regulated. Heatmap analysis and Cytoscape visualization of biological networks identified protein folding as the major cellular process affected by depletion of eIF5A. Our unbiased, quantitative, proteomic data demonstrate that the depletion of eIF5A leads to endoplasmic reticulum stress, an unfolded protein response and up-regulation of chaperone expression in HeLa cells.

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Figures

Figure 1
Figure 1. The effects of Ad-eIF5A-shRNA vs Ad-scramble-shRNA transduction in HeLa cells.
(A) eIF5A levels were determined by western blotting using eIF5A antibody (BD Biosciences) and hypusine-specific antibody. GFP and Adeno type 5 antibodies were used to compare the viral load. Actin was used as sample loading control. (B) Live cells exhibit green fluorescence due to GFP expressed from both of the adenoviral shRNAs, whereas the dead/dying cells are detected by red fluorescence using LIVE/DEAD cell imaging kit (Dojindo Laboratories). Representative images of three independent experiments are shown. (C) Cell proliferation was measured at OD450 using Cell Counting Kit-8 assay (Dojindo Laboratories). Representative data was plotted from three independent experiments done in triplicate ± SD. (D) The overall rate of cellular protein synthesis was measured by quantitation of [3H]leucine incorporation.
Figure 2
Figure 2. Schematic presentations of three iTRAQ analyses.
(A) Three independent experiments are indicated by iTRAQ 1, 2 and 3 and the samples labeled with 8 different isobaric tags, 113–119 and 121, are indicated by different colors. (B) Venn diagram depicting the number of proteins ‘n’ identified at all the time points in each iTRAQ and the 972 proteins identified in all three experiments. (C) PCA analyses of the samples of iTRAQ3. Each of the 72 h samples (Ad-Sc-sh(72 h), Ad5A-sh(72 h)) was compared against duplicate untransduced samples, Un72h labeled with isobaric tag 113, and Un72h labeled with tag 119, as indicated by 1 and 2, respectively. Each of the 96 h samples (Ad-Sc-sh(96 h), Ad5A-sh(96 h)) was compared against Un96 labeled with 116 and Un96 labeled with 121 as indicated by 3 and 4, respectively. (D) The complete set of 972 proteins commonly identified in three experiments is shown as volcano plots. Each data point indicates the protein expression level (log2 value of geometric mean) (X axis) with their corresponding −log10 of Stouffer’s p-value (Y axis). The threshold for differential expression (cut-off = 1.5 fold and significance level of p-value ≤ 0.05) is indicated by dashed blue lines. The significantly decreased and increased proteins are depicted by solid green and red circles, respectively.
Figure 3
Figure 3. Comparison of levels of polyproline-containing proteins.
(A) Pie diagrams showing the percent of polyproline proteins in the significantly altered protein pool (Fig. 2C) at 72 and 96 h after Ad-eIF5A-shRNA transduction. The decreased and increased proteins are shown as green and red, respectively, and the polyproline protein fraction is indicated by yellow. (B) Western blot validation of altered expression of iTRAQ-identified polyproline proteins. (C) Western blot analyses of polyproline proteins not identified by iTRAQ.
Figure 4
Figure 4. Functional ontology analyses of proteins with significantly altered levels upon depletion of eIF5A.
(A) The heat map of 104 differentially expressed proteins identified from iTRAQ analyses at two time points (72 and 96 h of adenoviral transduction). The decreased and increased proteins are indicated by range of green and red intensities, respectively. Different functional categories of proteins are indicated with horizontal bars on top. The 11 proteins belonging to the ‘protein folding’ category are indicated under the heat map. (B) Three major functional networks obtained from the 104 proteins using Cytoscape software. Each node (filled circle) represents a biological process and the size and color code indicate, respectively, the number of genes and significance of the terms (bottom inset). The direction of network is shown by arrow-head of edges and the edge-thickness is based on kappa-score level calculated automatically by ClueGO. The molecular interaction network between protein folding and response to ER stress is shown in the inset.
Figure 5
Figure 5. Up-regulation of chaperones and the UPR pathway upon depletion of eIF5A.
(A) Validation of increased proteins (identified from iTRAQ) including those belonging to ‘Protein folding’ category (Fig. 4A) by western blot. (B) The levels of selected proteins involved in triggering ER stress and UPR were measured by western blotting using specific antibodies.
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