EGFR deficiency leads to impaired self-renewal and pluripotency of mouse embryonic stem cells

Cell culture and experimental design

E14.1 mESC (ATCC, Manassas, VA, USA) were cultured in Dulbecco’s modified Eagle’s medium (Gibco, Grand Island, NY, USA), supplemented with one mM sodium bicarbonate (Gibco), 1% penicillin/streptomycin (Gibco), two mM L-glutamine (Gibco), 1% MEM non-essential amino acids (Gibco), 0.1 mM β-mercaptoethanol (Sigma, Darmstadt, Germany), 1,000 U/ml mouse LIF (Millipore, Darmstadt, Germany), one μM PD0325901 (Selleck, Houston, TX, USA), three μM CHR99021 (Selleck), and 15% (v/v) ES cell-qualified fetal bovine serum (Millipore). Cells were cultured on 0.1% gelatin coated 6-well plate at a density of 10⁶ cells per well, at 37 °C and an atmosphere of 5% CO₂. For embryoid body (EB) formation, cells were cultured in drop-culture method with a 25 μl drop containing 1,000 cells, without LIF and 2i (PD0325901 and CHR99021). Cells were divided into two groups, EGFR inhibition group and control group. For EGFR inhibition group, mESCs were treated with 5, 10, 15, and 20 μΜ AG1478 (Selleck) for 24 h, and the concentration of 10 μΜ was the most suitable (Figs. S2A–S2E). Additionally, mESCs were treated with 0.05, 0.5, 5, and 10 μΜ gefitinib (Selleck) for 24 h, and the concentration of five μΜ was the most suitable (Fig. S3A). The stock solution for inhibitors used were prepared in dimethyl sulfoxide.

Cell proliferation assay and cell cycle analysis

Mouse ESCs were seeded in 0.1% gelatin coated 96-well plates at a cell density of 5 × 10³ per well with treatment of AG1478 or not. Cell Counting kit-8 Kit (CCK-8) (Dojindo Molecular Technologies, Rockville, MD, USA) was used to compare cell proliferation according to the manufacturer’s instructions. Cells were fixed in 70% ice-cold ethanol at 4 °C overnight, then incubated with 0.1 mg/ml RNase A (Sigma) for 30 min followed by incubation with 100 μg/ml propidium iodide (PI) (Sigma) staining for 5 min at room temperature and avoid light condition. Cell-cycle analysis was performed immediately using flow cytometry.

Alkaline phosphatase staining

Expression of alkaline phosphatase (AP) was detected by staining with an AP detection kit (Stemgent, Cambridge, MA, USA) following manufacturer’s instructions.

Immunofluorescence

Cells were fixed with 4% paraformaldehyde in PBS for 20 min at room temperature. To detect intracellular antigens, cells should be permeabilized with 0.1% Triton X-100 after fixation. Cells were then blocked by 5% BSA in PBS at room temperature for 30 min, and were incubated with primary antibodies for EGFR (1:500; CST, Danvers, MA, USA), SSEA-1 (1:500; Santa Cruz Biotechnology, Dallas, TX, USA), OCT4 (1:500; CST), and Nanog (1:500; CST) overnight at 4 °C. Cells were incubated with fluorescence-conjugated secondary antibodies for 1 h at room temperature and avoid from light. Nuclei were stained with 4′,6-diamidino-2-phenylindole, Fluorescence signals were detected with a fluorescence microscope.

Western blotting

Cells were lysed using T-PER^® Protein Extraction Reagent (Thermo-Fisher, Waltham, MA, USA) containing protease inhibitor cocktail (Roche, Basel, Switzerland). Equal amount (30 μg per lane) of denatured proteins were separated by SDS–PAGE and transferred to nitrocellulose membranes (Millipore). Then membranes were blocked with 5% non-fat milk for 2 h at room temperature, and then incubated with the primary antibodies (CST) of recommended concentration diluted in 5% non-fat milk overnight at 4 °C. HRP-conjugated anti-rabbit IgG was used as secondary antibody and the blots were developed using the Pierce ECL Western Blotting Substrate according to the manufacturer’s instructions (Pierce, Appleton, WI, USA). The visualized bands were quantified by calculating net light density value with Gel Image System 1D software (v4.2), based on a Tanon-5200 Chemiluminescent Imaging System (Shanghai, China).

Targeting knock-down assays

For transient short interfering RNA (siRNA) transfection, cells at 70% confluence were transfected using Lipofectamine^® RNAiMAX (Thermo-Fisher, Waltham, MA, USA) in complete medium according to the manufacturer’s instructions, with a final siRNA concentration of 100 nM. The siRNAs were incubated with Lipofectamine^® RNAiMAX reagent for approximately 20 min and diluted with Opti-MEM^® medium. The siRNA-lipid complex was gently added to the culture medium. A total of 6 h later, the culture medium was replaced with fresh medium. A total of 48 h after transfection cells were trypsinized and plated for the different experiments. siRNAs were purchased from GenePharma (http://www.genepharma.com/). siRNA sequences were as follows: EGFR siRNA-1: 5′-CUGUGCGAUUCAGCAACAA-3′; EGFR siRNA-2: 5′-CCACCUAUCAGAUGGAUGU-3′; EGFR siRNA-3: 5′-CCCUGUCGCAAAGUUUGUA-3′; EGFR siRNA-4: 5′-GUGCUACGCAAACACAAUA-3′; and control non-targeting siRNA-NC: 5′-UUCUCCGAACGUGUCACGU-3′.

RNA preparation, libraries sequencing, and reads mapping

Total RNAs were isolated from mESCs in EGFR inhibition group and control group, using Trizol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. RNA degradation and contamination was monitored by 1% agarose gels. RNA purity was checked by NanoDrop ND-1000 spectrophotometer (IMPLEN, Westlake Village, CA, USA). RNA integrity was assessed using RNA Nano 6000 Assay Kit of the Bioanalyzer 2100 system (Agilent Technologies, Santa Clara, CA, USA). A total amount of three μg RNA of each mESCs sample (from EGFR inhibition group or control group) was used to construct cDNA library for RNA-seq analysis, after ribosomal RNA removal. Subsequently, sequencing libraries were generated using the rRNA-depleted RNA by NEBNext^® Ultra™ Directional RNA Library Prep Kit for Illumina^® (NEB, Ipswich, MA, USA). The constructed libraries were sequenced on an Illumina HiSeq2500 platform (FC-104-5001; Illumina, San Diego, CA, USA). The RNA-seq experiments were performed by Experimental Department of Novogene Corporation (Beijing, China).

Clean reads were obtained from raw reads after the removal of reads containing an adapter, reads with low quality, and reads containing ploy-N. At the same time, Q20, Q30, and GC content were calculated for the clean dataset. All the down stream analyses were based on the clean data. Clean reads were aligned to the mouse genome mm10 by Tophat 2.0.3 (Kim et al., 2013) with default parameters. Only the uniquely mapped reads were used for future expression analysis. HTSeq quantified RNAs based on annotation with the union model, and distributed reads into different known types of genes.

Gene expression and functional annotation

The mapped reads of each sample were assembled by both Scripture (beta2) (Guttman et al., 2010) and Cufflinks software (v2.1.1) (Trapnell et al., 2010) in a reference-based approach. Cufflinks was used to calculate fragments per-kilo-base of exon per million fragments mapped (FPKM) of genes in each sample to quantify their expression levels. Based on FPKM of each replicate, Pearson’s correlation coefficient (R²) was calculated to measure the correlation between two variables. Cuffdiff (http://cole-trapnell-lab.github.io/cufflinks/) was used to identify significant differentially expressed genes (DEGs) between the two mESCs groups, and corrected P-value <0.05 was set as the threshold for DEGs. Among these DEGs, nine protein coding genes were randomly selected for quantitative PCR to validate the mRNAs expression results from RNA-seq, and data are presented as the log₂ fold change between EGFR inhibition and control mESCs.

Differentially expressed genes were classified according to gene ontology (GO) enrichment analysis and kyoto encyclopedia of genes and genomes (KEGG) analysis. The GO categories were derived from (http://www.geneontology.org), and GO enrichment of DEGs was implemented by the GO seq R package (Langfelder & Horvath, 2008; Pennisi, 2012; Young et al., 2010) in which gene length bias was corrected. GO terms with corrected P-value < 0.05 were considered significantly enriched by DEGs, based on Wallenius non-central hyper geometric distribution. KEGG is a database resource for understanding high-level functions and utilities of the biological system (http://www.genome.jp/kegg/) (Kanehisa et al., 2008). Each KEGG pathway will be considered as a unit gene set. And geometric test will interrogate significantly enriched pathway based on background genes and DEGs list. We used KOBAS (2.0) software (Mao et al., 2005) to test the statistical enrichment of differential expression genes in KEGG pathways, and corrected P-value <0.05 were considered significantly enriched by DEGs.

Quantitative PCR

Total RNAs were reverse transcribed using First Strand cDNA Synthesis Kit (Thermo Scientific, Waltham, MA, USA) according to the manufacturer’s instructions, and were used for quantitative PCR with SYBR Green master mix on an ABI PRISM 7500 Fast Real-Time PCR system (Applied Biosystems, Foster City, CA, USA) as previously described (Tao et al., 2015). Gene specific primers were designed using Primer3 software32 (Tables S1–S4). In addition, reverse transcription-polymerase chain reaction (RT-PCR) primer for EGFR was as follows: forward: 5′-ATCACAATCAGCCCCTGCAT-3′ and reverse 5′-TGCCATTTGGCTTGGTTTCC-3′. Quantitative data were normalized to GAPDH, and the relative quantity was calculated using the (2^−ddCt) method.

Statistical analysis

Experiments were performed independently at least three times. Numerical data were expressed as the means ± SD. Statistical analysis was performed using SPSS 19 software. Differences between two groups were assessed using a Student’s t-test. P-value < 0.05 was considered to be statistically significant difference.

EGFR inhibition hinders proliferation of mESCs by inducing cell cycle arrest at G₀/G₁ phase

Immunofluorescent staining and RT-PCR results showed that EGFR was expressed in mESCs (Figs. S1A and S1B). CCK-8 assay showed that the cell viability was significantly lower in AG1478 treated mESCs than control cells, which suggests that EGFR deficiency hinders mESCs proliferation (Fig. 1A). To address how EGFR affects mESCs proliferation, we analyzed cell cycle distribution of AG1478 treated mESCs by Flow cytometry analysis. Relative to control mESCs, the proportion of G₀/G₁ phase in AG1478 treated mESCs was increased significantly by approximately 81.72%, while the proportion of S phases was decreased significantly by approximately 22.76% (Figs. 1B and 1C). These results suggested that EGFR inhibition could hinder mESCs proliferation by arresting cell cycle at G₀/G₁ phase. Quantitative PCR and western-blot were used to examine the expressions of pivotal cell cycle regulatory genes. EGFR-deficient mESCs showed decreased mRNA expressions of CDK2 (decreased 70.2%), CDK4 (decreased 72.5%), and proliferating cell nuclear antigen (PCNA) (decreased 60.3%) (Fig. 1D). Meanwhile, EGFR-deficient mESCs showed decreased protein expressions of CDK2 (decreased 11.3%) and PCNA (decreased 25.2%) (Figs. 1E and 1F). Thus, EGFR inhibition by AG1478 arrested mESCs cell cycle at G₀/G₁ phase through altering the expression of pivotal cell cycle regulatory genes.

EGFR deficiency impairs mESC self-renewal and pluripotency and drives mESC differentiation

Epidermal growth factor receptor inhibition resulted in a dramatic reduction in the number and size of AP positive mESC colonies (Fig. 2A), and a decreased expression of stage-specific embryonic antigen 1 (SSEA-1) on mESC surface (Fig. 2B). The reduction in the immunoreactivity of two pluripotency markers implied the reduced pluripotency state and impaired self-renewal in EGFR-inhibited cells. EGFR inhibition also reduced the expression of pluripotency factors like OCT4 (decreased 51.5% in mRNA level, and decreased 26.9% in protein level) and Nanog (decreased 67.5%) (Figs. 2C–2E, 2G and 2H), and impaired pluripotency protection network composed of several key factors including Lin28b (decreased 38.2%) and PRDM14 (decreased 85.7%) (Fig. 2E), suggesting that EGFR is necessary for maintaining mESC pluripotency. To investigate whether EGFR inhibition would induce mESC differentiation, we examined the expression levels of early differentiation markers by quantitative PCR and western-blot (Figs. 2F–2H). As a result, EGFR inhibition led to an increase in the mRNA levels of three germ layer markers including Notch1 (increased 3.7-fold), Nestin (increased 4.0-fold), and Pax6 (increased 3.1-fold) (Fig. 2F), suggesting that EGFR inhibition drives mESC differentiation. EB formation reflects the pluripotency of mESCs. Here, we found that EB formation failed in mESCs after EGFR inhibition by AG1478, confirming the impairment of pluripotency in EGFR inhibited mESCs (Fig. 2I).

Gefitinib and RNA interference induced similar gene expression changes as AG1478 treatment in mESCs

To rule out the possibility of non-specific effects of AG1478, we also used another EGFR inhibitor (gefitinib) and RNA interference assay to analyze the proliferation, differentiation, and expression of pluripotency markers of mESCs. Five μM was selected as the suitable concentration to inhibit EGFR phosphorylation activity (Fig. S3A). EGFR inhibition by gefitinib in mESCs markedly reduced protein expressions of the cell cycle regulatory genes (CDK2 (decreased 20.1%) and CDK4 (decreased 64.1%)). The protein expression of pluripotency factors (OCT4 (decreased 52.9%)) also dramatically decreased, while the differentiation related genes (GATA4 (increased 2.1-fold) and Notch1 (increased 1.2-fold)) were up-regulated in mESCs after EGFR inhibition (Figs. 3A and 3B). Four siRNA oligonucleotides were prepared and EGFR expression was knocked down after RNA interference (Fig. S3B). Western-blot detection revealed that the protein expressions of CDK2 (decreased 20.0%) and OCT4 (decreased 41.2%) were reduced, while the protein expressions of GATA4 (increased 1.5-fold) and Notch1 (increased 1.2-fold) were elevated in mESCs by silencing of the EGFR with siRNA-3 (Figs. 3C and 3D). These genes were related to cell cycle, self-renewal, pluripotency, and differentiation. The effects observed by EGFR inhibition with another inhibitor gefitinib and siRNA were consistent with those observed by AG1478 treatment in mESCs. Thus, we further confirmed the on-target effects of AG1478 on mESCs including cell cycle progress, self-renewal and pluripotency through EGFR impairment.

EGFR inhibition causes transcriptional changes involved in self-renewal and pluripotency

We sequenced cDNA libraries from three AG1478 treated mESCs samples (numbered as Treat 1, Treat 2, and Treat 3) and three control mESCs samples (numbered as Control 1, Control 2, and Control 3). In total, 746,337,642 raw reads were acquired with an error rate 0.02%, and then 734,603,314 clean reads were generated from raw reads (Table S5). Approximately 611,878,157 clean reads were mapped to the mouse genome mm10, and the alignment percentage for each sample was more than 81.24%. The percentage of uniquely mapped reads was more than 69.32% for each sample (Table S6). The Pearson correlation coefficients of gene expression levels were greater than 0.95 in both EGFR inhibited group and the control group (Fig. S1C), demonstrating the similarity of expression within one group, the rationality of samples selection, and the reliability of sequencing data.

The expression profiling showed global significant changes in gene expression between two mESCs groups. 5,231 genes were considered as significant differentially expressed with corrected P-value <0.05, including mRNAs and lncRNAs. Among them, 1,811 genes were up-regulated and 3,420 genes were down-regulated in response to EGFR inhibition (Fig. 4A). And the transcription changes of mRNAs were analyzed in the present article. Quantitative PCR validation results of nine randomly selected genes were consistent with RNA-seq data, which are related to cell cycle (Sfn, Cdc20, Rab11a), p53 signaling pathway (Sfn), ribosome (Pramef17, Klf6), citrate cycle (TCA cycle) (Tdh), and oxidative phosphorylation (Ddit4) (Fig. 4B). Through GO survey, we observed several self-renewal and pluripotency associated terms, such as cell cycle, apoptotic process, stem cell maintenance, condensed chromosome, chromatin binding, histone binding, and transcription factor binding (Table 1). As determined by KEGG analysis, many DEGs were enriched in pathways related to self-renewal and pluripotency such as cell cycle, p53 signaling pathway, ribosome, Citrate cycle (TCA cycle), and oxidative phosphorylatio (Fig. 4C; Table 2).