Physiol Genomics 44(8): 455-469

PMC: PMC3339861

PMID: 22395315

EGFR regulation of epidermal barrier function

MATERIALS AND METHODS

Cell culture.

Neonatal foreskin normal human epidermal keratinocytes (NHEKs; Lonza Walkersville, Walkersville, MD) were grown in basal keratinocyte-serum-free medium (KSFM) (Invitrogen, Grand Island, NY) supplemented with 5 ng/ml EGF and 50 μg/ml bovine pituitary extract (BPE). Fifth-passage NHEKs were grown to either 50 or 100% confluent cell density before treatment with basal medium or medium containing EGF (10 ng/ml) or transforming growth factor (TGF)-α (50 ng/ml) for 48 h, with the treatment medium being replaced once at 24 h (58).

RNA isolation, quantitative reverse transcriptase-polymerase chain reaction, and microarray.

Total RNA isolation and quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) were performed as described (58). Samples were normalized to values of tubulin, alpha 1C (TUBA1C). Relative RNA levels were expressed compared with samples grown to 50% cell density without EGF (control). Primers used in this study include: Gene, Forward Primer (5′-3′), Reverse Complement Primer (5′-3′); KRT1, TGTCTGGAGAATGTGCCCCGAACG, CCGCCGCCACCTCCAGAACCAT; FLG, GACACCCCGGATCCTCTCACC, AGCTGCCATGTCTCCAAACTAAAC; LAMA3, CAAGAGGCCTCCCCACAAACAGC, TGGCCCCAACAATACAGAGTGAGC; LAMC2, CTGGCCTGGACCCTGAGAAG, CCGGCCGGCAAGTGATT; SPTLC3, TGGGATGGGATTCGCAACTAACTCA, GGGGCAGATGCACGATGGAACCT; KDSR, ATGGGCCTTTTCCGCACTATTG, AGCCACATTCCTGAAGAGCACTG; SGPP2, AGTGGCCCCGTCCCTCCTC, GACGCCACCCAGCACATCC; SGPL1, CCTGTTGGGCTGCCTTGATGC, TCCGGGCGTGTAGTAATGTGATGC; SPHK1, GGTGCCCGACGAGGACTTTG, CCGCCCGCACGTAGAACAG; ASAH1, TGAACCGCACCAGCCAAGAGA, GGCAGTCCCGCAGGTAAGTTTC; DEGS1, CAGGAGGCGGAGGCAGAGG, AAAGTTCCCCCGGTACCCAAGTTA; DEGS2, GCGGGTGTACAGGCTGGCAAAAGA, ACAAGGGCAGCAGTCCAGAGCACA; UGCG, CCTGCGGGAGCGTTGTC, TTGTTGAGGTGTAATCGGGTGTA; GBA, ATCCCGATGGCTCTGCTGTTGTG; GCCCTGCTGTGCCCTCTTTAGTCA; SGMS2, AAGGGGGAGATCCGTGGGTTGT, CATTGGGTGGCAGCAGCAGTGT; CERK, GCCTGCCCCAAACCCACTAACAA, TGCCCCGGAAATCAGAGCCTATC; LASS3, GCCCCACACCGACCCCACAT, AACAAAGCGAGCCCCTGAGAAAGT; LASS4, GGAGACGCCGGAACCAGGAT, AGGCCGCCCACGAAGGAG; FA2H, GCAGCCGCAAGGGGAAATGAA, AGCAGGGAGGACAGGGACCACAG, PTPLB, GGCACGCGGAAGAAGAAGG, CACCCGGCTGTCATCACCA; TECR, AGCCCCACGCCACCATTG, GGGCCCCGCGTACTCTGTTAG; IVL, GGCCACCCAAACATAAATAACCAC, CACCTAGCGGACCCGAAATAAGT; LOR, CAGGGGCACCGATGGGCTTAGAG, TGAGGCACTGGGGTTGGGAGGTAG; KRT10, TGAAACCGAGTGCCAGAATA, CGTAGCCGCCGCCGAAACTT; CLDN1, CGATGAGGTGCAGAAGATGA, CCAGTGAAGAGAGCCTGACC; TJP1, TGGTCGGAAAACATGCTACACA, AGGCCATGGAACCAGTCTCACA; GJA1, ACCAACCGCTCCCCTCTCG, TCCCGCCTGCCCCATTC; ELOVL3, AGCGGCCACTCATCTTTATTCA, GTTGGCAGCCTTCAGAGTGTAGTA; ELOVL4, CATGTGTATCATCACTGTACG, AAAGGAATTCAACTGGGCTC; ELOVL7, GCGAACCCATTAAAAGAGCCAGTA, GCGAGGACATGAGGAGCCAATC; KLF4, CCGGCGGGAAGGGAGAAG, AGGGGCGCCAGGTTGCTAC; GATA3, GGCCCGGCAGGACGAGA, GTAGGGCGGGTAGGTGGTGATG; ABCA12, TCTCGCCGAAGTATATGGGATGTT, GCTTCGGGGAGATGTGATTGG; ALOX12B, ACCCCACCTCGCCACCTCACC, CACCGCCCCAGTTGCAAAGTCTCT; PRDM1, TCCCGAACATGAAAAGACGATAAA, CTCTCCGGGATAAGGGTAGTGAAG; FBXW7, ACGTTAACAGGGCACCAGTGG, CACCCGTTTTCAAGTCCCATAGTT; CST6, TGGGCAGCAACAGCATCTACTA, CCTCGGGGACTTATCACATCTG; TGM1, TCCGCCCACGACACAGACACATC, GCAGGGGCCGCAGCAGAAGA; SLC27A2, GGTGGGGGCCTGTGGTTTCAATAG, AGCGGCGCAGGGGGTCTTTCT; PIGA, ACGGGGTGCCTGGACTAATA, TGGCCTCGCTGATGTCTGATAAGT; CDSN, AGGGCCCATCGTCTCGCACTC, ACCCACCACCTCGTAGCCACCATA; OCLN, GGCAGGGTGTGGGAAGCAGGAC, GACGCGGGAGTGTAGGTGTGGTGT; CGN, TTCCCCTCTTTGCCATTCCTACCT, ACCAGACCCCCGGCACTTTATCA; CLDN16, GTCATACTCAGCCCCTCGCACAGA, TGAACCAAAAGCCAGGGAGAAAAG; CLDN4, CCGCGCCCTCGTCATCATCAG, ATAAGGCCGGCCAACAGGAACACC; TUBA1C, CTACCCCCGCATCCACTTCC, GGGGCACCAATCCACAAACTG. All cDNAs were amplified using an annealing temperature at which they had similar efficiency to that of TUBA1C. Affymetrix Human Gene 1.0 ST microarrays were processed using the GeneChip Whole Transcript Sense Target Labeling assay, the Affymetrix Fluidics Station 400 and GeneChip Scanner 3000 7G. These data have been submitted to the National Center for Biotechnology Information Gene Expression Omnibus repository ({"type":"entrez-geo","attrs":{"text":"GSE32217","term_id":"32217"}}GSE32217).

Array data and statistical analysis.

The 16 microarrays were preprocessed using the 5th percentile of region method in dChip (34). Genes with at least a 1.5-fold difference between the untreated samples at 50 and 100% confluent cell density were exported for further analysis. Two-way ANOVA was used to identify differentially expressed genes by either density or EGF using JMP Genomics 4.1 (SAS, Cary, NC). Multiple hypothesis testing was corrected by Benjamini-Hochberg false discovery rate control at the 0.05 level (3). Pair-wise comparisons were performed using the Tukey's honestly significant difference test. A diagram of the gene expression data analysis workflow is shown in Fig. 1. The statistical analysis reported in the other figures was performed using GraphPad Prism 3.0 (41). Image quantitation was done using ImageJ (1). The bioinformatic tools used in this study were GeneIndexer (23), DAVID (http://david.abcc.ncifcrf.gov/), Chilibot (8), IPA (Ingenuity Systems, http://www.ingenuity.com), and PubMed (http://www.ncbi.nlm.nih.gov/pubmed/).

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Fig. 1.

Diagram of the gene expression data analysis workflow. On the Human Gene 1.0 ST arrays, probes are grouped into transcript clusters. A known or putative gene can be represented by 1 or more transcript clusters. To display a visible heat map of the microarray profiles of the epidermis associated genes, we reduced the 1,039 genes to 72 genes that were highly annotated to ectoderm development. Our interest was to determine the biological effects of epidermal growth factor (EGF) on keratinocyte differentiation. During skin differentiation, most of the suprabasal genes are induced (Fig. 2B). Hence, to elaborate the effects of EGF on keratinocyte differentiation, our analysis was focused on the density-upregulated genes. Gene ontology (GO) analysis was performed to identify biological processes and cellular components overrepresented in the 1,298 density-upregulated EGF-responsive genes. Only nonredundant categories with the largest number of genes are shown for biological processes (P value ≤ 3.06E-04) and cellular component (P value ≤ 5.90E-03). From the list of density-upregulated genes, we identified genes associated with skin diseases using Ingenuity Pathway Analysis and Chilibot, as dysregulation of the epidermal growth factor receptor (EGFR) signaling pathways have been associated with skin diseases. From these identified lists of genes, we further identified genes essential for the development of the epidermis in mice using GeneIndexer and Chilibot.

Immunoblotting.

Cell lysates were harvested with lysis buffer containing 62.5 mM Tris·HCl pH 6.8, 2% SDS, 1% β-mercaptoethanol, and quantitated using 0.1 M iodoacetamide and the Micro BCA protein assay kit (Pierce Thermo Scientific, Rockford, IL). Protein samples were separated on 6, 7.5, or 12% SDS-PAGE and transferred to polyvinylidene fluoride membranes (Millipore, Billerica, MA). Primary antibodies used in this study were mouse anti-DSG1 (1:330, catalog code 32-6000; Molecular Probes, Eugene, OR), rabbit anti-GRHL1 (1:400, catalog code HPA005798; Sigma-Aldrich, St. Louis, MO), mouse anti-KRT1 (1:4,000, catalog code NCL-CK1; Leica Microsystems, Wetzlar, Germany), mouse anti-FLG (1:300, catalog code NCL-Filaggrin; Leica Microsystems), rabbit anti-CLDN1 (1:250, catalog code 71-7800; Molecular Probes), mouse anti-TJP1 (1:400, catalog code 33-9100; Molecular Probes), and rabbit anti-KLF4 (1:250, catalog code sc-20691; Santa Cruz Biotechnology, Santa Cruz, CA). Secondary antibodies used in this study were goat anti-mouse (1:10,000; Jackson ImmunoResearch, West Grove, PA), and goat anti-rabbit (1:15,000, Jackson ImmunoResearch). Protein bands were visualized with enhanced chemiluminescence (Pierce Thermo Scientific).

Lipid extraction and high-performance thin-layer chromatography.

NHEKs were grown to 100% confluent cell density and treated with basal medium or medium containing EGF (10 ng/ml) for 24 h. The medium was then replaced with fresh basal medium containing the same treatments and supplemented to 1.8 mM Ca^{. Cell pellets (}n = 3) were extracted 48 h after the last medium change. The organic phases were dried under nitrogen, redissolved in chloroform-methanol (1:1), and separated by one-dimensional high-performance thin-layer chromatography (HPTLC) on 10 × 10 cm silica plates using the development system and staining method as described (48). Standards for cholesterol and linoleic acid, Cer NS and GC, and Cer AP were from Sigma-Aldrich, Avanti Polar Lipids, and Evonik Industries, respectively. Assignment of lipid bands was based on Refs. 4, 48.

CE competence assay.

NHEKs were grown to confluence and pretreated with vehicle (0.1% DMSO) or PD-153035 (300 nM) 2 h before treatment. Basal medium with or without EGF (10 ng/ml) was added in the presence of vehicle or PD-153035 (300 nM) for 24 h. The medium was replaced with fresh medium containing the same treatments. After 72 h, the cell envelope competence assay (n = 3) was performed using calcium ionophore A23187 (catalog code C7522, Sigma-Aldrich) as described (9, 58). The percentage CEs was calculated by dividing the number of envelopes by the initial cell number.

Measurements of transepidermal electrical resistance and paracellular tracer flux.

Confluent monolayers of NHEKs (94,000 cells/insert) were grown on polycarbonate Transwell filters (0.4-μm pore size, 12-mm diameter, 1.12 cm^{). The transepidermal electrical resistance (TER) was determined with the Endohm device (World Precision Instruments, Sarasota, FL) at 48, 72, and 96 h after transfer into medium containing 1.8 mM Ca}^{with or without EGF (10 ng/ml). TER values were calculated by subtracting the blank values from the bare filter and medium and multiplying by the surface area of the filter (}28).

Paracellular tracer flux assays were performed as described (66) on the same Transwell filters that were used for TER measurements. Two different tracers, 3 kDa FITC-dextran and 40 kDa Texas Red-dextran (catalog codes D3305 and D1829, respectively; Molecular Probes), were used at a concentration of 1 mg/ml. The tracers were suspended in P buffer (10 mM HEPES, pH 7.4, 1 mM sodium pyruvate, 10 mM glucose, 3 mM CaCl₂, 145 mM NaCl). Media in the apical and basal compartments of NHEKs grown on the Transwell filters were replaced with 164 or 600 μl of P buffer, respectively. The plates were incubated in 37°C to equilibrate for at least 30 min. Next, 36 μl of P buffer containing either one of the tracers was added to the apical compartment. Cells were incubated at 37°C for 3 h. The amounts of the tracers that had diffused from the apical to the basal side of the NHEKs were determined fluorometrically (FLx800; BioTek Instruments, Winooski, VT) using external standard curves of each tracer.

Indirect immunofluorescence.

NHEKs grown on glass culture slides (BD Biosciences, Bedford, MA) were fixed in 4% paraformaldehyde for 15 min. Slides were blocked in PBS for 30 min with 5% normal goat serum and 0.1% NP-40, followed by a 30 min incubation with antibodies against CLDN1 (1:15, catalog code 71-7800; Molecular Probes) or TJP1 (1:40, catalog code 33-9100; Molecular Probes) diluted in blocking solution, then followed by 30 min incubations with the Alexa Fluor 488 goat anti-rabbit IgG (1:1,000) or the Alexa Fluor 594 goat anti-mouse IgG (1:1,000), respectively (catalog code A11008 or A11005, Molecular Probes). Fluorescent images were captured using a Zeiss LSM 710 laser scanning confocal microscope with the ZEN 2009 software (Carl Zeiss). All images were acquired at identical settings using a ×40 objective. For presentation, brightness and contrast levels were adjusted across all images using Adobe Photoshop.

Organotypic cultures.

Neonatal dermal fibroblasts (seventh passage) were maintained in DMEM supplemented with 4.5 g/l glucose, 4 mM l-glutamine, 0.11 mg/ml sodium pyruvate, 10% FBS, 100 units of penicillin, and 100 μg of streptomycin/ml. NHEKs (fifth passage) were maintained in KSFM supplemented with 5 ng/ml EGF and 50 μg/ml BPE. Organotypic cultures were prepared on polycarbonate Transwell filters (3-μm pore size, 24-mm diameter), and acellular and cellular collagen gels were plated as described (7). After 6 days of incubation at 37°C, the gel was washed and NHEKs (1.5 × 10^{cells in 50 μl) were seeded on top. After a 2 h incubation to allow cell attachment, plating medium was added to cover the gel. The cultures were kept submerged for 5 days. The organotypic cultures were then raised to the air-liquid interface using cotton filter pads. Cornification medium with or without EGF (20 ng/ml) was used from this point forward. Topical treatment of 1× PBS or EGF (20 ng/ml) was done at every media change throughout the air-exposure period. The cultures were harvested after 14 days of air exposure. For light microscopy, cultures were fixed, embedded, sectioned, and stained using standard methods.}

Transepidermal water loss measurement.

The transepidermal water loss (TEWL) (g/m^{·h) was measured using a VapoMeter (Delfin Technologies, Kuopio, Finland). Organotypic cultures grown on filters were removed from the inserts using a sterile scalpel. The cultures were placed on Whatman filter paper soaked with 1× PBS and allowed to equilibrate with ambient air for 15 min at room temperature before TEWL measurements, which were carried out at 24–25°C and 27–35% humidity.}

Cell culture.

RNA isolation, quantitative reverse transcriptase-polymerase chain reaction, and microarray.

Array data and statistical analysis.

Fig. 1.

Immunoblotting.

Lipid extraction and high-performance thin-layer chromatography.

CE competence assay.

Measurements of transepidermal electrical resistance and paracellular tracer flux.

Indirect immunofluorescence.

Organotypic cultures.

Transepidermal water loss measurement.

Cell culture.

RNA isolation, quantitative reverse transcriptase-polymerase chain reaction, and microarray.

Array data and statistical analysis.

Fig. 1.

Immunoblotting.

Lipid extraction and high-performance thin-layer chromatography.

CE competence assay.

Measurements of transepidermal electrical resistance and paracellular tracer flux.

Indirect immunofluorescence.

Organotypic cultures.

Transepidermal water loss measurement.

RESULTS

EGF affects keratinocyte cell fate.

Cultures of NHEKs were grown under conditions to explore the effects of cell density and EGF (materials and methods). By microarray analysis (Fig. 1), we identified 4,685 density-dependent genes, of which 2,676 were also regulated by EGF (Fig. 2A, Supplemental Table S1).¹ In opposition to the observed density-dependent effects, EGF inhibited expression levels of 91% of the density-upregulated RNAs and increased levels of 96% of the density-downregulated RNAs (Fig. 2A). Literature-based semantic language analysis identified 1,039 genes that had explicit or implicit relationships with epidermal differentiation. To display and explore such relationships, we prioritized 72 of the 1,039 genes that were highly annotated to the concept of ectoderm development (Fig. 1). A heat map of these 72 genes is shown in Fig. 2B; EGF downregulated 83% of the density-upregulated RNAs and upregulated all of the density-downregulated RNAs. As the genes in these clusters appeared to associate with the differentiating or proliferating cell compartments of the epidermis, we validated by qRT-PCR the expression levels of two well-established examples of genes expressed in suprabasal layers (KRT1 and FLG) or the basal layer (LAMA3 and LAMC2) of the epidermis, respectively (Fig. 2C). Nearly identical effects were observed with TGF-α, an important EGFR ligand in the epidermis (Fig. 2D). While these results demonstrated that soluble exogenous EGF and TGF-α signal similarly, they don't rule out the possibility that endogenous signaling by these ligands will impart differing effects. A literature analysis of the 72 genes in Fig. 2B indicates that most of the density-upregulated RNAs are known to be uniquely expressed in the suprabasal layers of the epidermis, whereas most of the density-downregulated RNAs are expressed in the basal layer (Supplemental Table S2). Overall, these observed patterns of RNA expression and their responses to EGFR activation support the idea that EGFR signaling controls keratinocyte cell fate by regulating the expression of genes responsible for the basal and suprabasal cell phenotypes.

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Fig. 2.

EGFR regulation of keratinocyte cell fate. A: heat-map profile of the log₂ ratio of 2,676 density-dependent EGF-responsive genes with all replicates. The log₂ ratios of each sample are color coded as indicated in the heat-map scale legend to show relative RNA expression. The first control sample at 50% confluent cell density is set to be the baseline for computing the ratios and color coded in white. Blue indicates downregulation, while red indicates upregulation of gene expression compared with control. Samples grown to 100% confluent cell density with EGF were compared with those without EGF in the same cell density condition, to visualize the effects of EGF on density-dependent gene expression. C-50%, control sample at 50% confluent cell density; E-50%, EGF-treated sample at 50% confluent cell density; C-100%, control sample at 100% confluent cell density; E-100%, EGF-treated sample at 100% confluent cell density. B: heat-map profile of log₂ ratio of 72 genes identified by GeneIndexer and DAVID as highly enriched in epidermis development. The ratios of the means are color coded to show relative RNA expression in log₂ scale. Samples without EGF and grown to 50% confluent cell density are set as control and color coded as in A. Samples grown to 100% density with EGF were compared with those without EGF in the same cell density condition, to visualize the effects of EGF on density-dependent gene expression (n = 4). C: validation by qRT-PCR (n = 3–4) of EGF effects on RNAs known to be expressed in the suprabasal (KRT1 and FLG) and basal (LAMA3 and LAMC2) layers of the epidermis. Results are expressed relative to values obtained in samples grown to 50% confluent cell density without EGF following normalization to values of TUBA1C. Student's t-test was used to evaluate statistical significance for comparisons between C-50% and E-50%, C-50% and C-100%, and C-100% and E-100% samples. *P < 0.017 (Ŝidák-Bonferroni correction P value cut-off), **P < 0.01, ***P < 0.0001. D: the effects of TGF-α on RNAs expressed in the suprabasal (KRT1 and FLG) and basal (LAMA3 and LAMC2) layers were measured by qRT-PCR (n = 4) as in C. Student's t-test was used to evaluate for statistical significance with a Ŝidák-Bonferroni correction P value cut-off of P < 0.017, **P < 0.01, ***P < 0.0001. E: densitometry of protein immunoblots for DSG1 and GRHL1 (n = 3). Values are normalized to the loading control ACTB (β-actin). Student's t-test was used to evaluate statistical significance. *P < 0.05, **P < 0.01. All bars represent means ± SD.

Studies of NHEKs have shown that EGFR activation is essential for cell cycle progression and inhibits CE formation and the expression of differentiation-related genes. Inhibition of EGFR signaling opposes these effects and promotes terminal differentiation (46, 58). A recent study, using an organotypic model of human epidermis, identified DSG1 as a suppressor of EGFR signaling. Suprabasal expression of DSG1 abrogates the EGFR-Erk1/2 signaling pathway, promoting epidermal differentiation and morphogenesis (17). Here, the transcripts for both DSG1 and its transcription factor regulator GRHL1 were found to be upregulated by density and repressed by EGF (Supplemental Table S1). Immunoblot analysis showed strong repression of both proteins in response to EGF (Fig. 2E). This reciprocal action of DSG1 and EGFR to repress one another provides a specific example of a mechanism for regulating epidermal homeostasis. This example supports a model where the juxtaposed processes, characteristic of the basal and suprabasal epidermal strata, are controlled by the spatial and temporal expression and activity of the EGFR, its ligands, and suppressors thereof.

EGF affects all major processes of epidermal differentiation.

Toward understanding the effects of EGF on keratinocyte differentiation, we performed Gene Ontology (GO) analysis of the 1,298 density-induced EGF-responsive RNAs (Fig. 1) and identified lipid biosynthesis, CE, and cell-cell junction as enriched categories that are functionally important to the epidermal barrier (Table 1). These categories were validated by qRT-PCR and functional analyses (Figs. 2–8 and Supplemental Materials).

Table 1.

Significant Gene Ontology terms associated with the 1,298 density-induced EGF-responsive genes

Category	P Value
Biological Process
Ectoderm development	7.88E-14
Epidermal cell differentiation	1.44E-08
Keratinization	8.67E-06
Lipid biosynthesis process	3.06E-04
Cellular Component
Cornified envelope	3.63E-04
Intermediate filament cytoskeleton	7.89E-04
Late endosome	8.83E-04
Cell-cell junction	5.90E-03

See Fig. 1 for a detailed workflow and description of the microarray analysis.

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Fig. 8.

EGF impairs epidermal barrier integrity and preferentially regulates genes involved in skin diseases. A: EGF increases transepidermal water loss (TEWL) of organotypic skin cultures (n = 6). Cultures were incubated with or without EGF (20 ng/ml) throughout the 14 days of air exposure. Student's t-test was used to evaluate statistical significance (*P < 0.05). B: EGF induces abnormal keratinocyte morphology as shown by histology (hematoxylin and eosin) of the organotypic cultures from A. Scale bar, 20 μm. C: EGF preferentially regulates genes related to skin diseases based on literature using bioinformatic tools (see Fig. 1 for details of the analysis). *Fisher's exact test was used to determine if there was a significant association between genes related to skin diseases and EGF (P value = 5.31E-05). D: EGF decreases mRNA levels of genes that are essential for the development of epidermal barrier function in mice (n = 3–4). See qRT-PCR results of the additional 4 genes in Fig. 3B (ASAH1 and UGCG), Fig. 4B (ELOVL4), and Fig. 6A (TGM1). Results are expressed relative to values obtained in samples grown to 50% confluent cell density without EGF following normalization to values of TUBA1C. †Comparison between the untreated samples (confluent cell density effect). *Comparison between control and EGF at 100% confluent cell density. Two-way ANOVA followed by Bonferroni posttests were used to evaluate statistical significance. *P < 0.05, **P < 0.01, ***P < 0.001. ††P < 0.01, †††P < 0.001. E: densitometry of KLF4 immunoblot (n = 3). ACTB is a loading control. Student's t-test was used to evaluate statistical significance (*P < 0.05). All bars represent means ± SD.

EGF decreases Cer and free fatty acid biosynthesis.

The major lipid components of the highly ordered lamellar membranes of the epidermal barrier are cholesterol, Cer, and free fatty acids (FFA). Only two previous qualitative studies have investigated the effects of EGF on keratinocyte lipid biosynthesis. In the first (47), a slight decrease in Cer content was observed in keratinocytes cultured in the presence of EGF compared to control. In the second (19), EGF was reported to decrease the amounts of phospholipids and glucosphingolipids. Neither study presented statistical analysis of these effects. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis (Fig. 1) revealed the highest enrichment for sphingolipid metabolism (P value = 0.008374); 71% of the RNA levels for enzymes in this pathway were significantly altered by EGF. Cholesterol biosynthesis was not affected by EGF. While the biosynthetic pathways for Cer and FFA are considered separately in KEGG, they are intimately linked in epidermal barrier function as the production of very long chain fatty acids (VLCFAs), their omega hydroxylation, synthesis of acylceramides, packaging into acylglucosylceramides (acylGC) and their secretion and processing into acylceramides is critical for barrier function. Cers are generated by two pathways: via de novo synthesis and via a salvage pathway breaking down sphingolipids to release sphingosine, which is then acylated to form Cer. In the epidermis, microsomal fatty acid elongation occurs in four major steps: condensation (ELOVL1–7), reduction (HSD17B12), dehydration (PTPLB), and reduction (TECR) (60). To better illustrate the effects of EGF on these pathways we have depicted the Cer and FFA biochemical pathways in Figs. 3A and and4A,4A, respectively, and have identified the genes and magnitude of effect of EGF on RNA levels. The validation of most of these gene expression changes by qRT-PCR is shown in Figs. 3B and and4B.4B. EGF decreased the levels of certain RNAs in both the de novo Cer synthesis pathway and the salvage pathway (Fig. 3). Noteworthy for de novo synthesis, EGF decreased the expression of the rate-limiting SPTLC3, a gene encoding a serine palmitoyltransferase, LASS3, the major epidermal dihydroceramide synthase, and DEGS2, the major epidermal dihydroceramide desaturase/4-hydroxylase that produces phytoceramides. In the salvage pathway, EGF decreased the expression of SGPP2, sphingosine 1-phosphate phosphatase, the ceramidases, ASAH1 and ACER1, and LASS3. ACER1 expression is known to be strongly inhibited by EGF and highly induced during epidermal keratinocyte differentiation to generate sphingosine and sphingosine 1-phosphate, two bioactive lipids that mediate apoptosis, proliferation, and differentiation in keratinocytes (57). Consistent with this understanding of ACER1 function, density caused a 13.5-fold increase, whereas EGF caused a 3.5-fold reduction in the level of ACER1 RNA compared with the controls (Fig. 3B). RNA levels of UGCG and SGMS2, enzymes that produce GC and sphingomyelin, respectively, were downregulated by EGF. Furthermore, EGF decreased the expression of FA2H, an enzyme synthesizing 2-hydroxyceramide/2-hydroxyglucosylceramide (Fig. 3B). Overall, these results imply that EGF inhibits Cer biosynthesis via repression of multiple genes encoding key biosynthetic enzymes.

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Fig. 3.

EGF decreases sphingolipid biosynthesis transcripts. A: sphingolipid metabolism. This pathway was constructed based on the sphingolipid metabolism pathway in the KEGG database and figures in Refs. 62 and 14 and was drawn using ChemBioDraw Ultra 12.0 (CambridgeSoft, Cambridge, MA). The initial condensation, catalyzed by SPTLC, is also the rate-limiting step for de novo synthesis, forming 3-ketodihydro-sphingosine (24). This product is then rapidly reduced to sphinganine, which is then acylated by a member of the LASS family of enzymes to form dihydroceramide. LASS3 is the most relevant isozyme for ceramides of the epidermal barrier due to its fatty acyl-CoA chain length specificity (55). Dihydroceramide is then desaturated by DEGS1/2 or hydroxylated by DEGS2 (exclusively), to form ceramides and phytoceramides, respectively. Ceramides Cer5(AS) and Cer2(NS) may also be formed via the Salvage Pathway by LASS acylation of sphingosine already present in the cell. These reactions occur in the endoplasmic reticulum. At this point, the pool of newly formed ceramides and phytoceramides are trafficked to the Golgi apparatus. UGCG glycosylates all ceramides and phytoceramides to form glucosylceramides. SGMS catalyzes the addition of choline phosphate (from phosphatidylcholine) to Cer5 and Cer2 to form sphingomyelin. These 2 products (glucosylceramides and sphingomyelin) are packaged into the lamellar bodies, which are extruded at the intersection of the stratum granulosum and stratum corneum. EGF relative fold changes determined by qRT-PCR are shown. *Effects of EGF are significant by Student's t-test (P < 0.05). B: qRT-PCR analysis of transcripts encoding enzymes involved in sphingolipid biochemical pathways (n = 3–4). Results are expressed relative to values obtained in samples grown to 50% confluent cell density without EGF following normalization to values of TUBA1C. †Comparison between the untreated samples (confluent cell density effect). *Comparison between control and EGF at 100% confluent cell density. All bars indicate means ± SD. Student's t-test with Ŝidák-Bonferroni correction was used to evaluate statistical significance. ††P < 0.01, †††P < 0.001, *P < 0.0253 (Ŝidák-Bonferroni correction P value cut-off), **P < 0.01, ***P < 0.001.

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Fig. 4.

EGF decreases free fatty acid (FFA) biosynthesis transcripts. A: FFA synthesis and elongation. This pathway is an abbreviated form of the KEGG pathway for FFA synthesis combined with 1 cycle through the 4 enzymes that catalyze the 4 consecutive reactions of fatty acid elongation (25). The pathway was drawn using ChemBioDraw Ultra 12.0 (CambridgeSoft, Cambridge, MA). Initial fatty acid synthesis, catalyzed by FASN occurs in the cytosol; elongation occurs in the ER. The initial step of elongation is catalyzed by the ELOVL family of enzymes and is also the rate-limiting step (29). The majority of the fatty acids present in the epidermal barrier are elongated by ELOVL3 and 6. ELOVL1 and ELOVL4 catalyze the elongation of the very long chain fatty acid present in the ceramides of the epidermal barrier (43). Additionally, FA2H (not shown in this figure) hydroxylates FFA to form 2-OH FFA. These 2-OH FFA are part of the pool of FFA that are acylated to sphingoid bases to form ceramides as discussed in Fig. 3A. Ceramides containing 2-OH FFA include Cer7(AH), Cer6(AP), and Cer5(AS) and are critical for proper formation of the epidermal barrier (61). KS, keto acylsynthase, and ACP, acyl carrier protein, are domains of fatty acid synthase. EGF relative fold changes determined by qRT-PCR are shown. *Effects of EGF are significant by Student's t-test (P < 0.05). B: qRT-PCR analysis of transcripts encoding for enzymes involved in FFA biosynthesis (n = 3–4). Results are expressed relative to values obtained in samples grown to 50% confluent cell density without EGF following normalization to values of TUBA1C. †Comparison between the untreated samples (confluent cell density effect). *Comparison between control and EGF at 100% confluent cell density. All bars indicate means ± SD. Student's t-test with Ŝidák-Bonferroni correction was used to evaluate statistical significance. ††P < 0.01, †††P < 0.001, *P < 0.0253 (Ŝidák-Bonferroni correction P value cut off), **P < 0.01, ***P < 0.001.

Although EGF increased expression levels of FASN, fatty acid synthase, it decreased the levels of RNA for several critical fatty acid elongation steps, namely, ELOVL4, PTPLB, and TECR (Fig. 4). Of note, the TECR function is encoded by a single gene (60), and the levels of TECR RNA were reduced in response to EGF to those observed in nondifferentiating keratinocytes (Fig. 4B). These results imply that EGF treatment would lead to decreased production of stearic acid and, in turn, of oleic acid. These fatty acids contribute to 50% of the FFA composition of the stratum corneum (33). Furthermore, levels of Cers containing VLCFAs may also be decreased.

To elucidate the effects of EGF on lipid biosynthesis, we performed lipid analysis using HPTLC (Fig. 5). Levels of cholesterol were unchanged, while FAA was significantly reduced by 57%. In parallel, the levels of the acylGC were dramatically decreased by EGF to 11% of control levels. Of the VLCFA containing Cers, only Cer1 (EOS) was significantly decreased by EGF. Some of the DEGS2 4-hydroxylated Cers, Cer6 (AP) and Cer3 (NP), but not all, were decreased by EGF. Some of the 6-hydroxylated Cers (enzyme unknown), Cer7 (AH) and Cer8 (NH), but not all, were decreased by EGF, and some of the FA2H 2-hydroxylated Cers, Cer6 (AP) and Cer7 (AH), were decreased by EGF. At this time, it is unclear whether these effects on select Cer products within a Cer class reflect substrate selectivity of the associated enzymes or, rather, the existence of additional levels of enzyme regulation other than the observed effects of EGF in this report. The salvage pathway-related Cers, Cer5 (AS) and Cer2 (NS), and the UGCG-related GCs were not affected by EGF. Overall, these results indicate a very important role of EGFR signaling in the regulation of FFA and Cer biosynthesis and provide new insight into the role of altered EGFR signaling in skin disease.

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Fig. 5.

The effects of EGF on lipid matrix biosynthesis. Densitometric measurements (left) of 1-dimensional high-performance thin-layer chromatography (HPTLC, right) for lipids (n = 3). Neonatal foreskin normal human epidermal keratinocytes (NHEKs) were grown to 100% confluent cell density before basal medium or medium with EGF (10 ng/ml) was added. The medium was replaced with fresh basal medium containing the same treatments after 24 h in the presence of 1.8 mM Ca^{. Lipids were extracted 48 h after the last medium change. The ceramide structures are classified according to the sphingoid base (S, sphingosine; P, phytosphingosine; H, 6-hydroxysphingosine) and the}N-acyl fatty acid (A, α-hydroxy group; O, ω-hydroxy group; E, acylated in the ω-OH position). CHOL, cholesterol; FFA, free fatty acid; GC, glucosylceramide. All bars indicate means ± SD. Student's t-test was used, *P < 0.5, **P < 0.01, ***P < 0.001.

EGFR signaling inhibits CE competence.

EGF is known to inhibit CE formation (56), yet the mechanistic understanding of this inhibition is limited to the identification of a few intermediate filaments and their binding proteins (KRT1, KRT10, and FLG), CE precursors (LOR and IVL), and TGM1 (18, 37, 39, 51). The CE category was the top cellular component enriched by GO analysis (P value = 3.63E-04) (Table 1). This observation led us to investigate the effect of EGF on genes in this category as well as other genes encoding proteins involved in the CE formation from our microarray data. We identified by literature analysis (Fig. 1) 76 density-induced genes that contributed to the synthesis of the CE (Supplemental Table S3). Of these genes, EGF significantly altered RNA levels of 45 genes (59%), including those encoding the most well-characterized proteins that participate in the synthesis of the CE such as LOR, TGMs, SPRRs, late cornified envelope (LCE), and S100 proteins. The expression profiles of TGM1, LOR, KRT10, KRT1, and FLG were validated by qRT-PCR (Figs. 2C and and6A6A).

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Fig. 6.

EGFR signaling inhibits cornified envelope (CE) competence. A: validation of microarray expression profiles of some well-known CE genes. Results are expressed relative to values obtained in samples grown to 50% confluent cell density without EGF following normalization to values of TUBA1C. †Comparison between the untreated samples (confluent cell density effect). *Comparison between control and EGF at 100% confluent cell density. All bars indicate means ± SD. Student's t-test was used to evaluate for statistical significance with a Ŝidák-Bonferroni correction P value cut-off of P < 0.0253, ††P < 0.01, †††P < 0.001, **P < 0.01, ***P < 0.001. B: EGF decreases protein levels of pro-filaggrin (ProFLG) and keratin 1 (KRT1); abrogation of the EGF effect by the EGFR tyrosine kinase inhibitor PD-153035. ACTB is a loading control (n = 3). NHEKs were grown to 100% confluent cell density and pretreated with 0.1% DMSO or PD-153035 (300 nM) 2 h before treatment. Basal medium with or without EGF (10 ng/ml) was added in the presence of 0.1% DMSO or PD-153035 (300 nM). The medium was replaced with fresh basal medium containing the same treatments after 24 h. Cell lysates were prepared 24 h after the last media change (n = 3). C: EGF inhibits CE competence (n = 3). NHEKs were grown and treated as described in B. CEs were isolated 3 days after the last medium change (n = 3). All bars denote means ± SD. One-way ANOVA followed by Tukey's multiple comparison test were performed in B and C. Within a group, means with different letters show a significant difference in the comparison.

Protein immunoblots of two well-studied CE proteins, KRT1 and FLG, demonstrated that the effects of EGF on KRT1 and FLG RNA levels were reflective of protein expression (Fig. 6B). To determine if these effects were mediated by EGFR signaling, we cotreated with PD-153035, a selective and potent EGFR tyrosine kinase inhibitor. The effect of EGF to reduce the expression of pro-FLG and KRT1 proteins was attenuated by PD-153035. Moreover, the significant induction of these two proteins in the presence of the inhibitor alone (Fig. 6B) is indicative of basal EGFR signaling, possibly activated by TGF-α, an endogenous EGFR ligand in keratinocytes. Because of the large number of EGF-regulated CE-related RNAs we identified (Supplemental Table S3), we extended these studies to examine the effects of EGF and PD-153035 on CE competence. As expected (56), EGF caused a significant decrease in the percentage CE (Fig. 6C); this reduction was diminished by PD-153035, indicating the role of EGFR signaling in this effect. Together, these data indicate that EGF activates EGFR signaling to inhibit CE formation by altering the levels of enzymes and structural proteins that are essential for this process.

EGF disrupts TJ barrier function.

Cell-cell junction was enriched by GO analysis (P value = 0.0059) (Table 1). In this category, we found desmosomal, gap junction, and TJ genes. Historically, epidermal barrier function has been mainly ascribed to the stratum corneum. However, recent evidence indicates that components of intercellular junctions, especially TJs, are critical to the barrier function of the skin (16), and TJ defects are observed in patients with atopic dermatitis (10). We performed qRT-PCR on density-upregulated genes that are known to encode TJ proteins and found that EGF significantly suppressed the levels of RNA of CLDN1, CLDN16, and TJP1 (Fig. 7A). Mice lacking Clnd1 die within 1 day of birth due to excessive TEWL (16). Furthermore, a mutation and reduction in human CLDN1 have been reported in patients suffering from neonatal ichthyosis-sclerosing cholangitis and from atopic dermatitis, respectively (10, 21). Therefore we investigated the effect of EGF on protein levels of CLDN1, a transmembrane protein, and TJP1, a cytoplasmic scaffolding protein that directly interacts with CLDNs and is important for stabilizing the TJ solute barrier (63). EGF treatment caused a significant decrease in the levels of these two proteins (Fig. 7B). This result was further confirmed using indirect immunofluorescence. In untreated cultures, we observed that CLDN1 and TJP1 distributed around the circumference of each cell and concentrated at the apex of lateral membranes. CLDN1 was found to colocalize with TJP1 at the areas of cell-cell contact. The staining of these two proteins was reduced substantially in cultures treated with EGF (Fig. 7C), indicating that EGF inhibits the formation of the TJ. Interestingly, EGF significantly reduced expression of TIAM1, a RAC-specific guanine nucleotide exchange factor controlling TJ biogenesis in keratinocytes (Supplemental Table S1).

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Fig. 7.

EGFR signaling disrupts TJ barrier function in epidermal keratinocytes. A: validation of microarray expression profiles of genes encoding TJ proteins (n = 3–4). Results are expressed relative to values obtained in samples grown to 50% confluent cell density without EGF following normalization to values of TUBA1C. †Comparison between the untreated samples (confluent cell density effect). *Comparison between control and EGF at 100% confluent cell density. *P < 0.0253 (cut-off P value after Ŝidák-Bonferroni correction), **P < 0.01, †P < 0.0253 (cut-off P value after Ŝidák-Bonferroni correction), ††P < 0.01, ††† P < 0.001 by Student's t-test. B: densitometric measurements of junctional protein immunoblots for CLDN1 and TJP1 at the 96 h time point. ACTB is a loading control (n = 3). NHEKs were grown to 100% confluent cell density before switching to basal medium with or without EGF (10 ng/ml) in the presence of 1.8 mM Ca^{. The medium was replaced with fresh basal medium containing the same treatments after 24 h. Cell lysates were prepared 72 h after the last medium change. Student's}t-test was used to evaluate statistical significance (*P < 0.05). C: indirect immunofluorescence of CLDN1 and TJP1 in the presence or absence of EGF (n = 3) at the 96 h time point. NHEKs were grown as described in B. Representative immunofluorescent micrographs of the control and EGF (10 ng/ml) treated monolayers are shown. Scale bar, 50 μm. Student's t-test was used to evaluate statistical significance (*P < 0.05). D: transepithelial electrical resistance (TER) of keratinocytes grown on Transwell filters (n = 6). NHEKs were seeded at confluence (94,000 cells/insert) and incubated overnight before switching to basal medium or medium with EGF (10 ng/ml) in the presence of 1.8 mM Ca^{. The medium was replaced with fresh basal medium containing the same treatments after 24 h. TER was measured 48, 72, and 96 h after EGF treatment. Student's}t-test was used to evaluate statistical significance. *P < 0.05, ***P < 0.001. E: paracellular permeability as measured by 3- and 40-kDa dextran flux across samples in D above. Student's t-test was used to evaluate statistical significance. *P < 0.05, **P < 0.01, ***P < 0.001. All bars represent means ± SD.

To determine the effect of EGF on TJ barrier function, we measured TER and paracellular tracer flux in NHEKs. The TER reflects the transepithelial permeability of water-soluble ions and is a sensitive measure of barrier integrity. A higher TER indicates a lower permeability across a membrane. TER of the control cultures was measured at 48 h (42 ± 28 Ω·cm^{), 72 h (164 ± 23 Ω·cm}^{), and 96 h (166 ± 25 Ω·cm}^{). The resistance increased threefold at 72 h compared with 48 h and remained unchanged at 96 h from the 72 h level (}Fig. 7D), suggesting a much improved and stabilized permeability barrier function starting at 72 h. However, with the addition of EGF, the TER readings were reduced by one-half at every time point, suggesting that this permeability barrier function was significantly disrupted (Fig. 7D). Consistent with the TER results, a significant increase in the flux of dextrans was observed in EGF-treated compared with untreated NHEKs (Fig. 7E). Specifically, EGF caused an approximately twofold induction in the 3 and 40 kDa dextran flux at every time point, indicating that EGF causes a leaky barrier. In addition, ∼10 times fewer 40 kDa molecules diffused across the membrane compared with the 3 kDa dextran molecules (Fig. 7E), demonstrating the size selectivity characteristic of the paracellular permeability of TJs. Together, these results suggest that EGF disrupts the permeability barrier function by inhibiting the levels of both transmembrane and cytoplasmic proteins that form the TJ.

EGF impairs epidermal barrier integrity and preferentially regulates genes related to skin diseases.

One of the most essential functions of the epidermal barrier is to prevent excessive water loss. To determine the effect of EGF on this function, we measured TEWL in organotypic skin culture, as a model of skin barrier function (42). Higher TEWL rates reflect diminished barrier function and are associated with various human skin diseases including AD and ichthyosis (59, 64). The TEWL rate of control cultures was 64 ± 7.4 g/m^{·h, similar to what was reported previously (}42). EGF caused a 29% increase in the TEWL rate compared with control cultures (Fig. 8A). This increase was accompanied by changes in epidermal morphology. Large basal cells and a less stratified stratum corneum with substantial nuclear retention were observed in EGF-treated cultures (Fig. 8B), replicating the morphological effect of EGF reported in one previous study (7). Together, these results demonstrate that EGF impairs epidermal barrier integrity and its water permeability function.

Defective epidermal differentiation and disrupted barrier function are primary features of many skin diseases. Abnormally high levels of the EGFR and its ligands are observed in several chronic and inflammatory skin disorders (45, 54). Based on this knowledge and the profound effects of EGF on the regulation of all major structural and metabolic aspects of the epidermal permeability barrier observed in this report, we hypothesized that EGF would preferentially regulate genes encoding key structural, enzymatic rate-limiting, and regulatory proteins. Thus, we predicted that among the differentiation-related density-upregulated RNAs, EGF responsiveness would preferentially enrich for genes associated with skin diseases in humans. Using literature-based semantic language analysis, the manually curated Ingenuity knowledge base, and manual literature confirmation (Fig. 1), we identified 114 EGF-responsive genes associated with skin diseases from the list of 1,298 density-upregulated EGF-responsive genes (Fig. 8C, Supplemental Table S4). In parallel, we identified 43 EGF-nonresponsive genes associated with skin diseases from the list of 967 density-upregulated EGF-nonresponsive genes (Figs. 1 and and8C).8C). Hence, we tested the null hypothesis that there is no association between treatments (control vs. EGF) and the number of skin disease genes regulated by these treatments. To test this hypothesis, the Fisher's exact test was used, and the two-tail P value obtained from the test was 5.31E-5. This P value indicates that the null hypothesis should be rejected and that there is a strong association between known skin disease genes and the different treatments. In addition, the association tends to lie in the 114 known skin diseases and the set of EGF-responsive genes (Fig. 8C). Among the 114 skin disease genes, we identified 11 genes [KLF4, GATA3, SLC27A4, PIGA, ABCA12, ALOX12B, CDSN (Fig. 8D), ASAH1, UGCG (Fig. 3B), ELOVL4 (Fig. 4B), and TGM1 (Fig. 6A)] that are essential for the development of epidermal barrier function in mice (Supplemental Table S4). qRT-PCR validated the expression profiles of 91% of the 11 essential genes including the two transcription factors (KLF4 and GATA3) and two ichthyosis genes (ALOX12B and ABCA12) (Fig. 8D), providing strong support for association between the preferential effect of EGF and skin disease genes. Consistent with the expression data, the protein level of KLF4 was significantly inhibited by EGF (Fig. 8E). Taken together, these results support the idea that EGFR signaling regulates genes encoding critical aspects of epidermal barrier function and provide new insight into the importance of this pathway in normal homeostasis and diseases of the skin.

EGF affects keratinocyte cell fate.

Fig. 2.

EGF affects all major processes of epidermal differentiation.

Table 1.

Significant Gene Ontology terms associated with the 1,298 density-induced EGF-responsive genes

Category	P Value
Biological Process
Ectoderm development	7.88E-14
Epidermal cell differentiation	1.44E-08
Keratinization	8.67E-06
Lipid biosynthesis process	3.06E-04
Cellular Component
Cornified envelope	3.63E-04
Intermediate filament cytoskeleton	7.89E-04
Late endosome	8.83E-04
Cell-cell junction	5.90E-03

See Fig. 1 for a detailed workflow and description of the microarray analysis.

Fig. 8.

EGF impairs epidermal barrier integrity and preferentially regulates genes related to skin diseases.

EGF affects keratinocyte cell fate.

Fig. 2.

EGF affects all major processes of epidermal differentiation.

Table 1.

Significant Gene Ontology terms associated with the 1,298 density-induced EGF-responsive genes

Category	P Value
Biological Process
Ectoderm development	7.88E-14
Epidermal cell differentiation	1.44E-08
Keratinization	8.67E-06
Lipid biosynthesis process	3.06E-04
Cellular Component
Cornified envelope	3.63E-04
Intermediate filament cytoskeleton	7.89E-04
Late endosome	8.83E-04
Cell-cell junction	5.90E-03

See Fig. 1 for a detailed workflow and description of the microarray analysis.

Fig. 8.

EGF decreases Cer and free fatty acid biosynthesis.

Fig. 3.

Fig. 4.

Fig. 5.

EGFR signaling inhibits CE competence.

Fig. 6.

EGF disrupts TJ barrier function.

Fig. 7.

EGF impairs epidermal barrier integrity and preferentially regulates genes related to skin diseases.

DISCUSSION

Our results provide an advanced mechanistic understanding of how activation of the EGFR abrogates basic metabolic processes that affect the function of the epidermal permeability barrier. EGF inhibits the expression of key proteins that affect the biosynthesis of FFA and Cers, protein precursors of the CE, and proteins required to form intercellular TJs. Insight as to how EGF may regulate each of these processes was found in the expression analyses. EGF repressed the density-dependent expression of specific transcription factors including KLF4 and GATA3. Others have shown that each of these transcription factors is essential for the initiation and progression of distinct aspects of keratinocyte differentiation. Klf4 is required to establish a functional epidermal barrier, since conditional epidermal deletion of this gene results in loss of barrier function (53) and ectopic expression accelerates the formation of the epidermal barrier (26). Genes encoding structural components of the CE are misregulated in Klf4^{mutant mice. Specifically,}Krt1 and Lor are downregulated, while Sprr2A, whose promoter possesses a functional KLF4 binding site, is upregulated in the epidermis of Klf4^{mice (}53). These changes in RNA levels in Klf4^{mice are concordant with the effects of EGF on the levels RNA of}KRT1, LOR, and SPRR2A shown here, suggesting that the repressive effect of EGF on KLF4 alters the expression of genes necessary for CE formation. Similarly, epidermal-specific deletion of Gata3 in mice results in an impaired epidermal barrier and perinatal lethality (11), while downregulation of GATA3 RNA and protein expression in humans is associated with psoriasis (50). However, in contrast to Klf4, the Gata3 deletion strongly affects the expression of genes involved in lipid biosynthesis, with the null allele mice showing significantly lower expression of several critical genes in this pathway including Alox12b, Acer1, and Elovl3, and Elovl4 (11). Here we showed that EGF repressed the expression level of GATA3 by 62%. This reduction was paralleled by significantly lower levels of expression of multiple lipid metabolism genes including ALOX12B (30%), ACER1 (71%), ELOVL3 (76%), and ELOVL4 (27%). Of note, mice lacking Alox12b or Elovl4 die perinatally due to defective skin permeability barrier function and severe dehydration. Furthermore, Alox12b null mice show significant decreases in certain ω-hydroxy-Cers that are covalently bound to CE (13), and skin grafts from Alox12b null mice exhibit an ichthyosiform phenotype (12). Elovl4 null mice show significant decreases in FFA, having chain lengths longer than C26, and Cer with ω-hydroxy VLCFAs (5, 35). These data indicate that EGFR-mediated repression of GATA3 transcripts in suprabasal keratinocytes could lead to impaired biosynthesis of lipid matrix components and diminished epidermal permeability barrier function. These examples of EGFR signaling as a negative regulator of the expression of KLF4 and GATA3, and the earlier report on Notch 1 (32), support a model where EGFR signaling influences keratinocyte cell fate by regulating the expression of multiple prodifferentiation transcription factors, each affecting distinct aspects of cell differentiation. In so doing, EGFR signaling affects the basal or suprabasal phenotype of these cells and thereby their functions.

Evidence for additional levels of EGFR-mediated regulation is observed in the example of TIAM1, a RAC-specific guanine nucleotide exchange factor (T-lymphoma invasion and metastasis), whose level of expression is significantly decreased by EGF. In epithelial cells, RAC1 is known to regulate the formation and function of adherens junctions and TJs (28). In keratinocytes cultured from TIAM1-deficient mice, the cells show impaired TJ biogenesis and barrier function that are accompanied by lower levels of expression of several TJ proteins including CLDN1 and TJP1. In wild-type keratinocytes, the TIAM1-dependent activated RAC1 binds to PAR3 (protease-activated receptor 3) and PKCζ (protein kinase C, zeta) of the polarity complex (PAR3-PAR6-aPKC) to control the TJ formation (38). Based on these observations, it seems reasonable to hypothesize that EGF diminishes TIAM1-mediated RAC signaling and thereby diminishes the activation of the polarity complex, leading to the reduction of CLDN1 and TJP1 proteins and inhibition of TJ biogenesis. This, in turn, may disrupt the permeability barrier function, making the barrier more susceptible to environmental challenges, as seen in the skin of AD patients.

Human and nonhuman genetic studies have identified a large number of genes associated with dermatological diseases. Intriguingly, we showed that EGF responsiveness significantly enriches for these genes among the density-upregulated RNAs identified by microarray analysis. For example, EGF resulted in a 67% reduction in the levels of ABCA12. Loss of function of ABCA12 leads to lipid trafficking defects and decreases in the total amount of Cer (65). Mutations in this gene are causally associated with Harlequin ichthyosis (2). Similarly, EGF reduced by 29% the level of SLC27A4, a gene encoding the long chain fatty acid transporter. Mutations in this gene are associated with ichthyosis premature syndrome (31). In contrast to these examples, EGF upregulated the level of expression of S100A7, a TGM substrate/CE precursor that is highly elevated in psoriasis and AD (20, 36). While these three genes are exemplary of the effects of EGF on known human skin disease genes, it is important to note that 111 similarly responsive skin disease genes and another 1,184 genes not yet associated with skin disease have been identified here. These data advance our understanding of the molecular mechanisms by which EGF affects epidermal homeostasis and how imbalance in this signaling pathway may lead to system-wide pathogenesis. In addition to this immediate knowledge, these data provide a valuable resource for further dissecting the molecular events and genetic basis of dermatological diseases.

GRANTS

This work was supported by National Institute of Environmental Health Sciences Grant ES-017014 and the W. Harry Feinstone Center for Genomic Research.

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the author(s).

AUTHOR CONTRIBUTIONS

Author contributions: Q.T.T., L.H.K., S.B., S.B.G., C.H.S., and T.R.S. conception and design of research; Q.T.T., L.H.K., S.L.C., S.B., S.B.G., and C.H.S. performed experiments; Q.T.T., L.H.K., S.L.C., and S.B. analyzed data; Q.T.T., L.H.K., S.L.C., S.B., S.B.G., C.H.S., and T.R.S. interpreted results of experiments; Q.T.T. prepared figures; Q.T.T. and T.R.S. drafted manuscript; Q.T.T., C.H.S., and T.R.S. edited and revised manuscript; Q.T.T. C.H.S., and T.R.S. approved final version of manuscript.

^{Department of Biological Sciences,}

^{W. Harry Feinstone Center for Genomic Research, and}

^{Department of Chemistry, The University of Memphis, Memphis, Tennessee}

^{Corresponding author.}

Address for reprint requests and other correspondence: T. R. Sutter, Dept. of Biological Sciences, Univ. of Memphis, Memphis, TN 38152 (e-mail: ude.sihpmem@rettust).

Received 2011 Dec 13; Accepted 2012 Mar 5.

Abstract

Keratinocyte terminal differentiation is the process that ultimately forms the epidermal barrier that is essential for mammalian survival. This process is controlled, in part, by signal transduction and gene expression mechanisms, and the epidermal growth factor receptor (EGFR) is known to be an important regulator of multiple epidermal functions. Using microarray analysis of a confluent cell density-induced model of keratinocyte differentiation, we identified 2,676 genes that are regulated by epidermal growth factor (EGF), a ligand of the EGFR. We further discovered, and separately confirmed by functional assays, that EGFR activation abrogates all of the known essential processes of keratinocyte differentiation by 1) decreasing the expression of lipid matrix biosynthetic enzymes, 2) regulating numerous genes forming the cornified envelope, and 3) suppressing the expression of tight junction proteins. In organotypic cultures of skin, EGF acted to impair epidermal barrier integrity, as shown by increased transepidermal water loss. As defective epidermal differentiation and disruption of barrier function are primary features of many human skin diseases, we used bioinformatic analyses to identify genes that are known to be associated with skin diseases. Compared with non-EGF-regulated genes, EGF-regulated genes were significantly enriched for skin disease genes. These results provide a systems-level understanding of the actions of EGFR signaling to inhibit keratinocyte differentiation, providing new insight into the role of EGFR imbalance in skin pathogenesis.

Keywords: keratinocyte differentiation, epidermal homeostasis, lipids, tight junction, atopic dermatitis, epidermal growth factor

Abstract

the skin is the largest organ of the body and among the most dynamic and flexible. It is composed of the dermis, derived from mesenchymal cells, and the epidermis, derived from the ectodermal cells of the embryo (40). The dermis is a thick layer containing supportive appendages such as nerve endings, sebaceous glands, sweat glands, hair follicles, and blood vessels. These appendages provide nutrients to the skin and help regulate body temperature. The epidermis is a thin layer that attaches to a basement membrane of the extracellular matrix. Despite its thinness, the epidermis is tough and able to withstand physical and chemical insults, protect against harmful microorganisms, and retain body fluids (15). As such, it provides a barrier that is essential for mammals to survive in the ex utero environment.

The epidermis is a stratified epithelium composed primarily of keratinocytes, which by virtue of their morphological and metabolic characteristics are divided into four layers: basal, spinous, granular, and cornified (stratum corneum). Basal keratinocytes are in direct contact with the basement membrane and, due to their mitotic capacity, contribute to the homeostasis of normal skin and its response to injury. As these cells migrate outward toward the surface of the skin they undergo a complex and tightly regulated program of terminal differentiation. Well-known patterns of gene expression distinguish the basal cells from the differentiating spinous layer cell. The stratum granulosum is the outermost layer containing living cells. Tight junctions (TJs) form in this layer, and the expression of a set of structural proteins and cross-linking enzymes marks the initiation of the formation of the stratum corneum, beginning with the synthesis of an immature envelope beneath the plasma membrane. As the envelope matures, covalent attachments by specific transglutaminases (TGMs) of preformed molecules such as involucrin (IVL), loricrin (LOR), small proline-rich proteins (SPRRs), and filaggrin (FLG) produce a rigid structure that will become the corneocyte. The corneocyte undergoes a specialized type of cell death leading to loss of the cell nucleus that, together with extruded lipids, produces the typical “bricks” (corneocyte) and “mortar” (lipid matrix) structure of the stratum corneum. This structure results in the epidermal barrier function of the skin, providing the characteristics of strength, protection from the outside environment, and retention of water. Disruption of cell differentiation, lipid composition, or TJ formation leads to a disturbed skin barrier, which is known to contribute to the pathogenesis of multiple skin diseases including atopic dermatitis (AD), ichthyosis, and psoriasis (6, 10, 22).

Epidermal growth factor receptor (EGFR) regulates multiple keratinocyte functions including proliferation, adhesion and migration, survival, and differentiation (27, 45, 56). Among these pleiotropic effects, the juxtaposition of cell cycle progression and differentiation stands out. Clinical and genetic evidence indicates a governing role of EGFR signaling in the cell fate of keratinocytes transitioning from the basal proliferative compartment to the differentiating suprabasal layers. Immunocytochemistry and ^{I-EGF binding in normal epidermis reveal strong basal cell signals of EGFR with diminished intensities corresponding to stratification and differentiation (}30). In contrast, abnormal epidermal expression of EGFR and/or its ligands are common features of several hyperproliferative and inflammatory diseases (27, 45). In genetically modified mice, multiple gain- and loss-of-function studies of EGFR and its ligands convincingly demonstrate an important function of EGFR in the regulation of keratinocyte proliferation and differentiation (52).

Because of its obvious importance to cancer and wound healing, the actions of EGFR to promote mitosis and migration have been extensively studied (45). Much less, however, is understood about the actions of EGFR signaling to affect keratinocyte differentiation. Early studies aimed at understanding the relationships between keratinocyte proliferation, growth arrest, and commitment to terminal differentiation were designed to carefully control the growth conditions in serum-free defined medium. These studies led to the understanding that confluent cell density primarily controls keratinocyte commitment to terminal differentiation and differentiated gene expression (49). Later studies using transcriptional profiling techniques have identified large sets of differentiation-related genes in keratinocytes subjected to confluence-induced differentiation (44). Although EGFR activation is known to regulate a few of these differentiation-related genes (18, 37, 39, 49), its role in regulating these genes at a genome-wide level has not yet been studied. Furthermore, using the confluence-induced differentiation model, we showed recently that, in addition to blocking the expression of cornified envelope (CE) precursor genes, EGF also suppressed the expression of critical genes in the sphingolipid and ceramide (Cer) biosynthetic pathway (58). Because lipid biosynthesis is essential for maintenance of the epidermal barrier (22), we performed further studies to identify differentiation associated metabolic processes that are regulated by EGFR signaling. Here we integrate genome-wide transcript and functional analyses to identify the effects of EGFR signaling on keratinocyte differentiation and epidermal barrier function.

See Fig. 1 for a detailed workflow and description of the microarray analysis.

ACKNOWLEDGMENTS

We thank Dr. J. Cole and C. Campion for helpful discussion; Dr. R. Homayouni, Dr. S. Qiao, Dr. M. Kedrov, and Y. Hu [The University of Tennessee Health Science Center (UTHSC)] for confocal microscopy use; Dr. W. Haggard and J. McCanless for the use of the fluorometer; Dr. C. Waters (UTHSC) for lending the Endohm system; M. Lu, L. White, Dr. A. Kulkarni, C. Stanton (all from UTHSC), Dr. O. Skalli, R. Scott, and Dr. R. Ramdath for generous help and advice regarding histology, slide scanning, immunofluorescence, and organotypic culture assays.

ACKNOWLEDGMENTS

Footnotes

^{The online version of this article contains supplemental material.}

Footnotes

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