Analysis of the Differential Gene and Protein Expression Profiles of Corneal Epithelial Cells Stimulated with Alternating Current Electric Fields

In cells, intrinsic endogenous direct current (DC) electric fields (EFs) serve as morphogenetic cues and are necessary for several important cellular responses including activation of multiple signaling pathways, cell migration, tissue regeneration and wound healing. Endogenous DC EFs, generated spontaneously following injury in physiological conditions, directly correlate with wound healing rate, and different cell types respond to these EFs via directional orientation and migration. Application of external DC EFs results in electrode polarity and is known to activate intracellular signaling events in specific direction. In contrast, alternating current (AC) EFs are known to induce continuous bidirectional flow of charged particles without electrode polarity and also minimize electrode corrosion. In this context, the present study is designed to study effects of AC EFs on corneal epithelial cell gene and protein expression profiles in vitro. We performed gene and antibody arrays, analyzed the data to study specific influence of AC EFs, and report that AC EFs has no deleterious effect on epithelial cell function. Gene Ontology results, following gene and protein array data analysis, showed that AC EFs influence similar biological processes that are predominantly responsive to organic substance, chemical, or external stimuli. Both arrays activate cytokine–cytokine receptor interaction, MAPK and IL-17 signaling pathways. Further, in comparison to the gene array data, the protein array data show enrichment of diverse activated signaling pathways through several interconnecting networks.


Introduction
Endogenous electric fields (EFs) and wound currents are generated spontaneously in many tissues following injury and are present at the wound site during the process of wound healing [1]. Dynamic changes in wound-generated electric currents demonstrate that electrical signaling is an active response to injury [2]. Many types of cells respond to weak direct current (DC) EFs with a galvanotropic response (polarized shifting of cellular orientation in an EF), which is followed by a galvanotaxic response (migration of a cell in an EF) [3]. Different cell types from the same tissue can respond differently to the same electrical signal. Peculiar differences in Ca 2+ , Na + , and K + channels, surface charges, and specific membrane resistance may contribute to the inherent directional movement of cells faults [29], resulting in the buildup of ions near electrodes that can eventually nullify the applied EF [21], a novel in vitro system for electric stimulation with AC voltage [26] was used in the present study to investigate the differential expression of genes and proteins in corneal epithelial cells.

Materials and Methods
TPP tissue culture flasks, dishes, and 6-and 12-well plates were obtained from Sigma-Aldrich (Munich, Germany). The QuantiTect Reverse Transcription kit was purchased from Qiagen (Hilden, Germany) and the innuMIX qPCR MasterMix SyGreen was from Analytik-Jena (Jena, Germany). Primers were synthesized from Metabion GmbH (Martinsried, Germany).

Cell Culture
Telomerase-immortalized human corneal epithelial cell line [30] (hTCEpi; a kind gift from Prof. J. V. Jester, University of California, Irvine, CA, USA; authenticated and characterized according to ATCC standard protocols) between passages 24 and 30 was used in this present study. The hTCEpi cells were cultured in KGM-Gold™ growth medium (Lonza, Köln, Germany). Cells were sub-cultured on T75 tissue culture flasks (Sigma-Aldrich, Munich, Germany), incubated at 37 • C in 5% CO 2 , and passaged every 5-7 days.

Alternating Current (AC) Electric Field (EF) Stimulation
To study the influence of AC electric fields on hTCEpi cells, an in vitro setup developed by Prof. Bader's group at the Medical University of Rostock, Rostock, Germany, was used [26]. In this system, the electrode setup was modified to perform the EF stimulations in a chamber of a 6-well plate. The pure titanium cylindrical electrodes measuring 14 mm in length and 5 mm in diameter were segregated by a 5 mm-long insulator made up of polyether ether ketone (PEEK). The electrode holders were also made of PEEK and provided a distance of 3 mm between electrodes and the well bottom, thus facilitating growth of the cultured cells below the electrodes. The lid of 6-well plate had pre-drilled holes for the contact titanium rods measuring 35 mm in length. The electrical stimulation was started 14 h after cell seeding. Prior to EF stimulation, the medium was replaced by 4 mL fresh cell culture medium (4.2 mm medium height) without the addition of growth factors. AC EFs were applied continuously for 24 h as a sinusoidal signal of 200 mV and with a frequency of 20 Hz, resulting in a maximum electrical field of 1.4 V/m, as previously described, using a Metrix GX 310 function generator (Metrix Electronics, Hampshire, UK). During stimulation, cells were cultured at 37 • C under 5% CO 2 . For unstimulated control, cells were similarly cultured in a 6-well plate in the presence of the electrode system, however without connecting to the function generator.

Microarray Hybridization
After stimulation with AC EFs for 24 h, hTCEpi cells were lysed in RTL Plus buffer, part of the RNeasy Plus Kit (Qiagen, Hilden, Germany), and RNA was extracted according to the manufacturer's protocol. The whole RNA samples were quantified spectrophotometrically (NanoDrop, Thermo Fisher, Darmstadt, Germany) and the integrity was controlled using Agilent Bioanalyzer 2100 with the RNA Nano chip kit (Agilent Genomics, Waldbronn, Germany). RNA integrity number values between 9.0 and 9.8 were achieved and 200 ng was used as the starting material. To perform the differential gene expression profiling, Affymetrix Clariom TM S Arrays were used according to the manufacturer's instructions (Affymetrix, St. Clara, CA, USA). The hybridization was carried out overnight at 45 • C in the GeneChip ® Hybridization Oven 645 (Affymetrix). The microarray was scanned using the GeneChip Scanner 3000 (Affymetrix) at 0.7 micron resolution.

Microarray Data Analysis
The CEL files generated following the Affymetrix Clariom TM S Arrays were analyzed using R [31]. The CEL files were read using the "oligo" R package. Raw data were normalized using the robust multichip algorithm (RMA) method of "oligo" R package. This normalized data were used to generate heatmap and PCA plots. Differential expression analysis was done using "limma" R package [32]. Differentially expressed genes were defined as genes with adjusted p-values < 0.05 and absolute log2 foldchanges > 2. GO and KEGG enrichment analysis was performed using the "clusterProfiler" R package [33]. Transcriptome Analysis Console (TAC) software (v.4.0.1.36) and ShinyGO enrichment tool [34] were also used to analyze and graphical representation the data.

Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR)
Total RNA was isolated from cultured hTCEpi cells after 24 h treatment with AC EFs using the NucleoSpin ® RNA kit (Macherey-Nagel, Berlin, Germany) according to the manufacturer's instructions. Single-stranded cDNA was prepared with 1 µg of total RNA using the QuantiTect Reverse Transcription kit (Qiagen, Hilden, Germany). Intron-exon spanning primers were designed from the respective GenBank sequences using VectorNTI software (ThermoFisher Scientific) based on the minimal hairpin, duplex formation, and guanine cytosine composition. A list of primers used in this study is given in Table 1. The synthesized cDNA was then used as a template for qRT-PCR using the innuMIX qPCR MasterMix SyGreen and qTower 2.0 (Analytik Jena, Jena, Germany). The cycling conditions used for amplification were 95 • C for 2 min, 40 cycles of 95 • C for 5 s, and 65 • C for 25 s. Later, the expression of all genes was normalized to the expression of the corresponding housekeeping gene, GAPDH. The relative amounts of target mRNA in the unstimulated control cells and EF-treated cells were analyzed using the ∆∆Ct method, as described previously [35].

Antibody MicroarrayAanalysis
To analyze the differential expression of various proteins in hTCEpi cells following electric stimulation, cells were treated with AC EFs for 24 h as described above. Later, the cells were collected, washed and frozen cell pellets were sent to Sciomics GmbH (Heidelberg, Germany) for further analysis using scioDiscover protein arrays. For each condition, the array was performed in triplicate. Briefly, proteins were extracted, quantified, and labeled with fluorescent dyes. All six samples were analyzed in a dual-color approach using a reference-based design on scioCD antibody microarrays (Sciomics) targeting 1300 proteins. Each antibody is represented in eight replicates on the array. The arrays were blocked with scioBlock (Sciomics) on a Hybstation 4800 instrument (Tecan, Grödig, Austria). The resulting data were analyzed using the linear models for the microarray data (LIMMA) package of R-Bioconductor after uploading the median signal intensities for differential protein expression. For normalization, a specialized invariant Lowess method was applied, and for analysis of the samples, a one-factorial linear model was fitted with LIMMA, resulting in a two-sided t-test or F-test based on moderated statistics. All presented p values were adjusted for multiple testing by controlling the false discovery rate according to Benjamini and Hochberg. Proteins were defined as differential for |logFC| > 0.2 and an adjusted p-value of < 0.05. Differences in protein abundance between different samples or sample groups are presented as log-fold changes (logFC) calculated for the basis of 2. In a study comparing samples versus control, a logFC = 1 means that the sample group had on average a 2 1 = 2-fold higher signal as the control group; logFC = −1 stands for 2 −1 = 1/2 of the signal in the sample as compared to the control group.

Stimulation of Telomerase-Immortalized Human Corneal Epithelial (hTCEpi) Cells with Alternate Current (AC) Electric Fields (EFs)
No differences in the morphology of the telomerase-immortalized human corneal epithelial cell line (hTCEpi) were observed during stimulation with AC EFs for 24 h. The distribution of the applied EF strength during AC EF stimulation is shown in Supplementary Figure S1. In addition, EF-stimulated cells maintained a healthy spindle-shaped epithelial morphology and showed growth rate characteristics similar to untreated control cells. Further, no deleterious effects on epithelial cells were observed during AC EF stimulations ( Figure 1).

Gene Expession Profiling (GEP) of AC EF-Stimulated hTCEpi Cells
Since there were no observable morphological differences in hTCEpi cells following EF stimulation, we further proceeded to study the effects of EF stimulation using gene expression analysis. After AC EF treatment of hTCEpi cells for 24 h, cells were washed once with PBS and collected to isolate RNA. Gene level differential expression analysis was performed using Clariom™ S arrays. Principal component analysis of the RMA nor-

Gene Expession Profiling (GEP) of AC EF-Stimulated hTCEpi Cells
Since there were no observable morphological differences in hTCEpi cells following EF stimulation, we further proceeded to study the effects of EF stimulation using gene expression analysis. After AC EF treatment of hTCEpi cells for 24 h, cells were washed once with PBS and collected to isolate RNA. Gene level differential expression analysis was performed using Clariom™ S arrays. Principal component analysis of the RMA normalized microarray data is shown in Supplementary Figure S2A. A clustering heat map of the calibrated samples is shown in Supplementary Figure S3A, whereas a volcano plot of the differentially expressed genes is depicted in Supplementary Figure S3B. Of the 21,448 genes analyzed, only 5.35% of the genes were found to be differentially expressed (556 genes were upregulated and 591 genes were downregulated) after stimulation of hTCEpi cells with AC EFs compared to the control untreated cells ( Figure 2). Both two-fold upregulated and downregulated genes were clustered. Untreated hTCEpi cells served as control. After 24 h of treatment with AC EFs, RNA was isolated and transcriptome-wide gene level expression profiling was performed using Clariom ™ S arrays. Affymetrix ® Transcription Analysis Console ™ (TAC) software (v.4.0.1.36) was used for array scanning, data analysis, signal estimation, and quality control functionality for the expression arrays, which also allow statistical analysis and provide a list of differentially expressed genes. Expression level analysis was performed using the normalization method based on the processing algorithm called the robust multi-array average (RMA), which was improved by Signal Space Transformation (SST-RMA, Affymetrix). Each array was performed in triplicate. Blue indicates a relatively low expression, whereas red indicates a relatively high expression. Both two-fold upregulated and downregulated genes were clustered. Untreated hTCEpi cells served as control. After 24 h of treatment with AC EFs, RNA was isolated and transcriptome-wide gene level expression profiling was performed using Clariom TM S arrays. Affymetrix ® Transcription Analysis Console TM (TAC) software (v.4.0.1.36) was used for array scanning, data analysis, signal estimation, and quality control functionality for the expression arrays, which also allow statistical analysis and provide a list of differentially expressed genes. Expression level analysis was performed using the normalization method based on the processing algorithm called the robust multi-array average (RMA), which was improved by Signal Space Transformation (SST-RMA, Affymetrix). Each array was performed in triplicate. Blue indicates a relatively low expression, whereas red indicates a relatively high expression.
Gene Ontology analysis using the STRING database of the 1147 genes that are upregulated and downregulated upon stimulation with AC EFs revealed activation of biological processes that are predominantly responsive to external, chemical, and cytokine stimuli, which in turn subsequently leading to the activation of various pathways, which are shown in Table 2. A list of genes that are upregulated and downregulated after treatment with AC EFs is shown in Supplementary Table S1.

Validation of Trancriptome Analysis Data by qRT-PCR
To further validate the transcriptome analysis data obtained after treatment of hTCEpi cells with AC EFs, we performed qRT-PCR of various transcripts using RNA isolated from stimulated cells. All the analyzed transcripts showed a similar expression profile as was observed in the gene array analysis (Figure 3).

Antibody Microarray Analysis of Differentially Expressed Proteins in hTCEpi Cells
Antibody microarrays were performed using scioDiscover Protein Expression Array (Sciomics GmbH, Germany) to identify putative alterations in hTCEpi cells at the protein level after treatment with AC EFs for 24 h (Figure 4). Regarding the antibody array, hierarchical clustering of the protein extracts based on differentially expressed proteins is shown in Supplementary Figure S2B. Identification of the functional associations between proteins on a genome-wide scale and construction of a protein-protein interaction (PPI) networks for analysis was performed using the STRING database (Available online: https://string-db.org/ (accessed on 14 December 2020)). Analysis of the protein array data revealed that the treatment of cells with AC EFs altered the expression of various protein products and the resulting heatmap of the protein differential expression is depicted in Figure 5. A list of proteins that are upregulated and downregulated after treatment with AC EFs is shown in Supplementary Table S2 . Validation of the Clariom ™ S array analyzed transcripts using qRT-PCR. The hTCEpi cells were cultured in the presence of AC EFs and RNA was isolated after 24 h. Reverse transcription was performed using 1 μg of total RNA to prepare cDNA and qRT-PCR was performed to compare the expression analysis of different transcripts using respective primers for Twist1, Notch1, Notch3, Notch4, Jag2, Zeb1, Numb, NFkB, E-Cad, IL8, IL18, IL21, IL27, Ker9 and Ker27. Relative expression patterns were analyzed using the comparative threshold cycle (2 −ΔΔCt ) method. Expression values are represented as fold changes over the control on an arbitrary scale after normalization with GAPDH. Further, these transcripts displayed similar expression profile during Clariom TM S Arrays. Data represent means ± standard deviations of three independent experiments.

Antibody Microarray Analysis of Differentially Expressed Proteins in hTCEpi Cells
Antibody microarrays were performed using scioDiscover Protein Expression Array (Sciomics GmbH, Germany) to identify putative alterations in hTCEpi cells at the protein level after treatment with AC EFs for 24 h (Figure 4). Regarding the antibody array, hierarchical clustering of the protein extracts based on differentially expressed proteins is shown in Supplementary Figure S2B. Identification of the functional associations between proteins on a genome-wide scale and construction of a protein-protein interaction (PPI) networks for analysis was performed using the STRING database (Available online: https://string-db.org/ (accessed on 14 December 2020)). Analysis of the protein array data revealed that the treatment of cells with AC EFs altered the expression of various protein products and the resulting heatmap of the protein differential expression is depicted in Figure 5. A list of proteins that are upregulated and downregulated after treatment with AC EFs is shown in Supplementary Table S2 Analysis of the abundant proteins using the STRING database revealed activation of various diverse cellular signaling pathways in which TNF, MAPK, IL17, and PI3K-Akt signaling pathways were significantly impacted (Table 3).   hTCEpi cells with AC EFs. The volcano plot visualizes the p-values (adjusted for multiple testing) and corresponding log-fold changes. The log-fold change of the difference in abundance is shown horizontally, whereas the vertical axis represents the significance level. The logFC cutoffs are depicted as vertical lines. The black dots represent analyzed proteins. The horizontal red line indicates an adjusted p-value of 0.05, above which all proteins are considered to vary significantly. Proteins with a positive log-fold change display higher abundance in EF-treated samples, whereas proteins with a negative value display higher abundance in control samples.  Analysis of the abundant proteins using the STRING database revealed activation of various diverse cellular signaling pathways in which TNF, MAPK, IL17, and PI3K-Akt signaling pathways were significantly impacted (Table 3).   Further, we also performed ShinyGO [34] Gene Ontology enrichment analysis using differentially expressed up-and downregulated genes and proteins based on the data from both arrays. Graphical representations of enriched biological processes and pathways are shown in Figures 6-9. We observed enrichment of 9 similar biological processes and 9 similar pathways in both arrays, confirming activation of similar cellular events at both the gene and protein levels following AC EF stimulation. Further, in comparison to the gene array data, protein array data showed enrichment of more activated pathways through several interconnecting networks.
Further, we also performed ShinyGO [34] Gene Ontology enrichment analysis differentially expressed up-and downregulated genes and proteins based on the from both arrays. Graphical representations of enriched biological processes and ways are shown in Figures 6-9. We observed enrichment of 9 similar biological pro and 9 similar pathways in both arrays, confirming activation of similar cellular eve both the gene and protein levels following AC EF stimulation. Further, in compari the gene array data, protein array data showed enrichment of more activated path through several interconnecting networks. Figure 6. Enriched biological processes after treatment of hTCEpi cells with AC EFs for 24 h. nificantly enriched biological processes following analysis of the gene array data are highlig as an interactive hierarchical clustering tree using ShinyGO. Biological processes with many shared genes are clustered together. Bigger dots indicate more significant p-values. Enriched logical processes that were similar after analysis of both gene and proteins array data are ma and highlighted. Analysis was performed using ShinyGO (v.0.61) (Available online: http://bio matics.sdstate.edu/go/ (accessed on 6 January 2021)).

Figure 6. Enriched biological processes after treatment of hTCEpi cells with AC EFs for 24 h.
Significantly enriched biological processes following analysis of the gene array data are highlighted as an interactive hierarchical clustering tree using ShinyGO. Biological processes with many shared genes are clustered together. Bigger dots indicate more significant p-values. Enriched biological processes that were similar after analysis of both gene and proteins array data are marked and highlighted. Analysis was performed using ShinyGO (v.0.61) (Available online: http://bioinformatics. sdstate.edu/go/ (accessed on 6 January 2021)).

Figure 7.
Enriched biological processes after treatment of hTCEpi cells with AC EFs for 24 h. Significantly enriched biological processes following analysis of the antibody array data are highlighted as an interactive hierarchical clustering tree using ShinyGO. Biological processes with many shared genes are clustered together. Bigger dots indicate more significant p-values. Enriched biological processes that were similar after analysis of both gene and protein array data are marked and highlighted. Analysis was performed using ShinyGO (v.0.61) (Available online: http://bioinformatics.sdstate.edu/go/ (accessed 6 January 2021)).

Figure 7.
Enriched biological processes after treatment of hTCEpi cells with AC EFs for 24 h. Significantly enriched biological processes following analysis of the antibody array data are highlighted as an interactive hierarchical clustering tree using ShinyGO. Biological processes with many shared genes are clustered together. Bigger dots indicate more significant p-values. Enriched biological processes that were similar after analysis of both gene and protein array data are marked and highlighted. Analysis was performed using ShinyGO (v.0.61) (Available online: http://bioinformatics.sdstate.edu/go/ (accessed 6 January 2021)).

Discussion and Conclusions
In cells, intrinsic endogenous DC EFs serve as morphogenetic cues and are necessary for several important cellular responses, including activation of multiple signaling pathways, cell migration, nerve regeneration, and wound healing [16,36,37]. Further, DC EFs are known to induce asymmetry in the distribution, arrangement of membrane receptors, and activate intracellular signaling cascades in the cathode-facing side, resulting in the growth of neurites in the cathode direction [20,38,39]. In contrast, in vitro stimulation with small AC EFs has no effect on neural progenitor cell alignment, viability, differentiation, or proliferation, similar to control unstimulated cells [18]. Additionally, an increase in AC EF frequency influences neural stem cell viability and differentiation by slowing down their maturation [40], suggesting a lineage control role of AC EFs on neural cells [20]. Based on these observations and due to the presence of the highest number of free nerve endings in the cornea, along with the existence of stem cells in the corneal limbus, it is also necessary to study the consequences of the application of AC EFs on corneal cells. Since epithelial cells are mainly accountable for the corneal wound healing process and as the effects of external AC EFs in modulating the epithelial cell function is presently not known, this study was carried out to understand the influence of external AC EF stimulation on corneal epithelial cell function. Figure 9. Enriched molecular pathways after treatment of hTCEpi cells with AC EFs for 24 h. The relationships between pathways are depicted and highlighted as an interactive graphical network using ShinyGO. Pathways enriched following analysis of the antibody array data are shown. Two pathways (nodes) are connected after sharing 20% or more genes. Enriched pathways that were similar after analysis of both gene and protein array data are marked and highlighted. Node colors illustrate enrichment, whereby darker nodes represent significantly enriched gene sets, while bigger nodes represent larger gene sets. Thicker edges represent more overlapped genes. Analysis was performed using ShinyGO (v.0.61) (Available online: http://bioinformatics.sdstate.edu/go/ (accessed on 6 January 2021)). Edge cut-off = 0.2 and FDR p-value cut-off = 0.05.

Discussion and Conclusions
In cells, intrinsic endogenous DC EFs serve as morphogenetic cues and are necessary for several important cellular responses, including activation of multiple signaling pathways, cell migration, nerve regeneration, and wound healing [16,36,37]. Further, DC EFs are known to induce asymmetry in the distribution, arrangement of membrane receptors, and activate intracellular signaling cascades in the cathode-facing side, resulting in the growth of neurites in the cathode direction [20,38,39]. In contrast, in vitro stimulation with small AC EFs has no effect on neural progenitor cell alignment, viability, differentiation, or proliferation, similar to control unstimulated cells [18]. Additionally, an increase in AC EF frequency influences neural stem cell viability and differentiation by slowing down their maturation [40], suggesting a lineage control role of AC EFs on neural cells [20]. Based on these observations and due to the presence of the highest number of free nerve endings in the cornea, along with the existence of stem cells in the corneal limbus, it is also necessary to study the consequences of the application of AC EFs on corneal cells. Since epithelial cells are mainly accountable for the corneal wound healing process and as the effects of external AC EFs in modulating the epithelial cell function is presently not known, this study was carried out to understand the influence of external AC EF stimulation on corneal epithelial cell function.
Upon stimulation with AC EFs, similar to PC12 cells [41], no significant differences in corneal epithelial cell viability or proliferation were observed. All of the literature reports so far used constant electric stimulation to study the effects of external EF applications on corneal epithelial cells and showed increased cell division, directional migration [42], regeneration [43], and wound healing [1]. MMPs play a crucial role in corneal wound healing [44] and corneal epithelial cells show enhanced MMP3 and unaltered MMP2 and MMP9 expression following DC EF stimulation [45]. Our gene array data also showed increased expression of MMP1 (48-fold), MMP10 (20-fold), and MMP9 (4-fold) and decreased expression of MMP2, MMP13, and MMP19 (2-fold each), whereas protein array data showed upregulation of MMPs 1, 7, 10, and 12. The application of DC EFs is known to significantly increase the activation of AKT and impact the PI3K/AKT pathway, which plays an important role in cell survival, growth, migration, and metabolism [46]. Further, DC-induced activation of the PI3K/AKT pathway was also reported in different cell types, including neural progenitor cells [47], Schwann cells [48], and human umbilical vein endothelial cells (HUVEC) [49], as well as in ocular cells, including the corneal epithelium [6,50]. Activation of the MAPK signaling pathway is also reported through the application of EFs in neuronal cells [51,52], fibroblasts, HUVEC [53], and corneal epithelial cells [6]. Likewise, we also observed activation of PI3K/AKT and MAPK signaling pathways, along with other interconnected pathways, including T cell receptor signaling, Toll-like receptor signaling, TNF signaling, IL-17 signaling, FoxO signaling, and focal adhesion pathways, upon stimulation of corneal epithelial cells with oscillating EFs. In addition, electric stimulation upregulates expression of RAGs, increases neurotrophin signaling, accelerates axon guidance and outgrowth during peripheral nerve regeneration [25,[54][55][56][57], and is also known to activate axon guidance, along with various metabolic and signaling pathways that play crucial interconnecting roles during axon regeneration [17,[57][58][59]. Accordingly, our gene array data analysis also showed activation of similar pathways during AC EF stimulation of corneal epithelial cells.
Generally, it is well known that following cell-specific stimulation, the resulting gene expression profiles measured using gene arrays are inadequate to predict protein expression and subsequent functional outcomes on a genomic scale, since interrelationships between mRNA and protein levels vary greatly due to post-transcriptional mechanisms, as well as post-translational modifications. Influencing factors such as the mRNA transcription rate, stability, translational regulation, along with protein activity and degradation serve as limiting factors and controlling elements in a given cell at the physiological level when interpreting the after effects of that cell-specific stimulus [60][61][62]. However, in our study, comparison of the expression profiles of certain genes and their corresponding protein abundance levels showed similar patterns following stimulation with AC EFs. Accordingly, enriched pathways and processes following analysis of the gene and antibody array data using the STRING database also showed consistent enrichment of similar biological processes and signaling pathways, further highlighting the balanced, steady state of the epithelial cells during AC EF stimulation [62]. Additionally, antibody array data showed enrichment of various interconnecting signaling events due to the involvement of similar molecules in multiple pathways, which was not observed during gene array data analysis. Since electric stimulation is considered as a master regulator of regeneration-associated cellular networks [27,63], stimulation with AC EFs also switches on several intracellular pathways, and thus can be implemented, upon further testing and validation at shorter time points, as a potential therapeutic approach for corneal tissue regeneration.
Supplementary Materials: The following are available online at https://www.mdpi.com/2073-442 5/12/2/299/s1: Figure S1: Distribution of applied AC EF strength in a 6-well plate during hTCEpi cell stimulation (electric potential: 200 mV; frequency: 20 Hz; wave form). Figure S2: Analysis of the gene and protein array data: (A) principal component analysis of the RMA-normalized microarray data; (B) hierarchical clustering of the protein extracts based on differentially expressed proteins. Figure S3: Analysis of the gene array data: (A) clustering heat map of the calibrated samples; (B) volcano plot of the differentially expressed genes. Table S1: Gene array data. Table S2: Antibody array data.