September 2011
Volume 52, Issue 10
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Retina  |   September 2011
Gene Expression Profiling of the Retina after Transcorneal Electrical Stimulation in Wild-type Brown Norway Rats
Author Affiliations & Notes
  • Gabriel Willmann
    From the University Eye Hospital and Institute for Ophthalmic Research and
  • Karin Schäferhoff
    the Medical Genetics, Institute for Human Genetics, University of Tübingen, Tübingen, Germany.
  • Manuel D. Fischer
    From the University Eye Hospital and Institute for Ophthalmic Research and
  • Blanca Arango-Gonzalez
    From the University Eye Hospital and Institute for Ophthalmic Research and
  • Sylvia Bolz
    From the University Eye Hospital and Institute for Ophthalmic Research and
  • Lubka Naycheva
    From the University Eye Hospital and Institute for Ophthalmic Research and
  • Tobias Röck
    From the University Eye Hospital and Institute for Ophthalmic Research and
  • Michael Bonin
    the Medical Genetics, Institute for Human Genetics, University of Tübingen, Tübingen, Germany.
  • Karl U. Bartz-Schmidt
    From the University Eye Hospital and Institute for Ophthalmic Research and
  • Eberhart Zrenner
    From the University Eye Hospital and Institute for Ophthalmic Research and
  • Andreas Schatz
    From the University Eye Hospital and Institute for Ophthalmic Research and
  • Florian Gekeler
    From the University Eye Hospital and Institute for Ophthalmic Research and
  • Corresponding author: Andreas Schatz, University Eye Hospital and Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany; schatzweb@gmail.com
Investigative Ophthalmology & Visual Science September 2011, Vol.52, 7529-7537. doi:10.1167/iovs.11-7838
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      Gabriel Willmann, Karin Schäferhoff, Manuel D. Fischer, Blanca Arango-Gonzalez, Sylvia Bolz, Lubka Naycheva, Tobias Röck, Michael Bonin, Karl U. Bartz-Schmidt, Eberhart Zrenner, Andreas Schatz, Florian Gekeler; Gene Expression Profiling of the Retina after Transcorneal Electrical Stimulation in Wild-type Brown Norway Rats. Invest. Ophthalmol. Vis. Sci. 2011;52(10):7529-7537. doi: 10.1167/iovs.11-7838.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose.: Transcorneal electrical stimulation (TES) has been beneficial in several neurodegenerative ocular diseases, but the exact mechanisms remain to be elucidated. This study was conducted to investigate the effects of TES on the retinas of wild-type Brown Norway (BN) rats by gene expression profiling and to assess its effects on retinal function and morphology.

Methods.: TES was applied to BN wild-type rat retinas in vivo for 1 hour (1-ms biphasic pulses at 20 Hz; 200 μA). RNA was isolated and processed for microarray-based profiling 4 hours after TES; differentially expressed genes from TES compared with those from sham-treated animals were validated by quantitative real-time polymerase chain reaction. Furthermore, the effect of TES was assessed at the structural and functional levels using electroretinography, confocal scanning laser ophthalmoscopy, optical coherence tomography, and immunohistochemistry.

Results.: Transcriptome changes associated with TES versus sham-stimulated BN wild-type retina were identified. Four hundred ninety genes were differentially expressed in TES and included potentially neuroprotective genes such as Bax or members of the tumor necrosis factor family (Tnfrsf11b, Tnrsf12a, Tnfsf13b, Tnfsf13). ERG recordings showed physiological retinal function after TES, and structural in vivo and ex vivo studies revealed intact retinal anatomy.

Conclusions.: These results demonstrate that TES applied to the retina of the wild-type BN rats induces distinct transcriptome level changes and may help in the understanding of the mechanisms underlying TES. In addition, TES treatment indicates no negative effect on structure and function of the wild-type BN retina up to 35 hours after application.

Retinal degeneration such as in retinitis pigmentosa, characterized by progressive loss of vision, is a major cause of blindness in humans. 1 Although much progress in understanding the mechanisms leading to several of these degenerative retinal diseases has been made in recent years, successful therapeutic treatment strategies to prevent vision loss or to restore vision are still not readily available. 2 4  
Stimulation with weak electrical currents has recently been postulated as a therapeutic strategy to protect the retina and other ocular tissue. 5 7 Electrical stimulation of retinal tissue has been linked with neuroprotection to preserve retinal function through interference with regulatory mechanisms of growth factors and cell death. 8 11 Several recent studies 2,12 15 have used different invasive and noninvasive approaches to study the effect of electrical stimulation on inherited and induced retinal degeneration in animal models and in humans. Subretinal electrical stimulation has been shown to rescue photoreceptor degeneration in the Royal College of Surgeon's (RCS) rat. 14,16 Direct electrical stimulation of the transected optic nerve stump promoted survival of the axotomized retinal ganglion cells (RGCs). 8 Using a less invasive method, transcorneal electrical stimulation (TES) was observed to rescue RGCs after axotomy and optic nerve crush. 8,17 TES also prolonged the survival of photoreceptors and delayed the decrease of retinal function in RCS rats in vivo. 18 Cultured rat Müller cells exposed to electrical stimulation have been shown to overexpress brain-derived neurotrophic factor (BDNF) and to activate the retinal insulin-like growth factor 1 (IGF-1) system, which may promote the survival of retinal neurons. 9,19 In fact, TES applied to patients with traumatic optic neuropathy or nonarteritic ischemic optic neuropathy improved visual function. 5  
Progress in understanding the molecular mechanisms of neuroprotection by electrical stimulation in several inherited and induced retinal degeneration models has been made with the identification of possible neurotrophic factors involved. 8,11 However, a comprehensive analysis of transcription level changes that could explain the mechanism underlying TES induced neuroprotection has not yet been performed in vivo. 
To gain a more profound understanding of the mechanisms of electrical stimulation, this study aimed to describe the effect of electrical stimulation on a genomic level in wild-type retinas. Whole genomewide expression profiling validated by quantitative real-time polymerase chain reaction (qPCR) was used to detect expression levels of differentially regulated genes in the retina. Electroretinography, confocal scanning laser ophthalmoscopy (cSLO), spectral domain optical coherence tomography (OCT), and immunohistochemistry were performed to assess functional and structural properties of TES- and sham-treated retinas. 
Materials and Methods
Animals and Experimental Design
Animals were maintained and experiments were performed in accordance with the ARVO Statement for the Use of Animals in Ophthalmic and Vision Research and were approved by the Animal Research Committee at the University of Tübingen. Male BN rats, weighing ≈150 g, were purchased from Charles River Laboratories (Wilmington, MA). They were raised for 1 week on a 12-hour dark/12-hour light cycle and then were dark adapted >12 hours before exposure to daylight for 2 hours before TES. Genomewide, functional, and structural analyses were performed at the indicated time points after treatment (Fig. 1). For microarray analysis, the right eyes of TES-treated (n = 4) and sham-treated (n = 4) animals were used. Independent qRT-PCR validation of the microarray experiment was performed with TES (n = 6) versus sham (n = 6). For ERG measurements, only the right eyes of TES-treated (n = 3) and sham-treated (n = 3) animals was considered. OCT and histologic analyses were performed using the directly stimulated right eye of TES-treated (n = 4) and sham-treated (n = 3) animals. Left eyes were not used as controls because of possible costimulation. Duration of stimulation was 1 hour. Food and water were available ad libitum. 
Figure 1.
 
Experimental design for TES in BN wild-type retinas. Animals were dark adapted (DA) for >12 hours, followed by 2 hours of day light (LA) before TES or sham stimulation. Genomewide, functional, and structural analyses were performed at the indicated time points after treatment. Duration of stimulation was 1 hour.
Figure 1.
 
Experimental design for TES in BN wild-type retinas. Animals were dark adapted (DA) for >12 hours, followed by 2 hours of day light (LA) before TES or sham stimulation. Genomewide, functional, and structural analyses were performed at the indicated time points after treatment. Duration of stimulation was 1 hour.
Transcorneal Electrical Stimulation
BN rats were anesthetized by intraperitoneal injection of ketamine 100 mg/kg and xylazine 5 mg/kg (WDT eG, Garbsen, Germany). Before TES, the cornea was anesthetized with 1 drop of 0.4% oxybuprocaine HCl (Novesine, OmniVision, Puchheim, Germany). A self-constructed contact lens electrode was placed on the right eye as an active electrode with 1 drop of 2% methylcellulose (Methocel; OmniVision) to maintain proper electrode contact and to prevent corneal dehydration. 20 One subcutaneous administered needle-electrode (Neuroline Twisted Pair Subdermal; Ambu GmbH, Bremen, Germany) inserted dorsally between the eyes was used as a ground electrode. Another needle electrode inserted into the tail was used to ensure an acceptable impedance level (<8 kΩ) measured by Ganzfeld stimulator (ColorDome; Diagnosys LLC, Lowell, MA) during TES. 
The electrical stimuli consisted of 1-ms biphasic rectangular current pulses of 200 μA at 20 Hz delivered from an isolated constant current stimulator (Neurostimulator Twister DN; Dr. Langer Medical GmbH, Waldkirch, Germany). TES treatment lasted for 1 hour, and electrical and sham stimulations were applied to the right eye only. TES was monitored by a digital real-time oscilloscope (Supplementary Fig. S1) model TDS 210 (Tektronix, Beaverton, OR). All stimulated and sham animals were euthanatized by CO2 inhalation at respective time points after TES, and only right eyes were dissected in a shallow bath of phosphate buffer. After removal of the cornea and lens, retinas were gently dissected from the eyecup and stored at −80°C until further processing. 
RNA Isolation and Microarray Studies
Four TES and four sham animals were euthanatized 4 hours after TES. Extraction of total RNA from each retinal tissue was performed (miRNeasy Kit; Qiagen, Hilden, Germany) according to the manufacturer's instructions. Mini-spin columns (QIAshredder; Qiagen) as well as needle and syringe homogenization were applied for tissue homogenization. To ensure integrity, all RNA used in our experiments showed single peaks for the 18S and 28S bands, as determined by data organizer software (2100 Bioanalyzer; Agilent Technologies Inc., Santa Clara, CA) using a reagent kit (RNA 6000 Nano LabChip; Agilent Technologies Inc.) in accordance with the manufacturer's instructions. 
The purity and concentration of total RNA were determined by absorbance measurements at 260 and 280 nm using a spectrophotometer (ND-1000; NanoDrop Technologies, Wilmington, DE). All RNA that did not have a 260/280 ratio between 1.9 and 2.1 was discarded to ensure the high quality of samples. Respective RNAs from stimulated and sham samples were used to generate double-stranded cDNA with the random primer according to a microarray (GeneChip; Affymetrix Inc., Santa Clara, CA) target labeling protocol, as described by the manufacturer. The processed cDNA was hybridized to Affymetrix arrays (GeneChip RatGene 1.1 ST) for 18 to 24 hours to screen a total of 27,342 transcripts. Four TES and sham replicates were used for hybridization to microarray (GeneChip; Affymetrix Inc.). Each microarray was automatically washed and stained with streptavidin-phycoerythrin and scanned (GeneTitan Scanner System; microarray (GeneChip; Affymetrix Inc.). A visual quality control measurement was performed to ensure proper hybridization after each chip was scanned. Additional quality control parameters, such as scaling factors used to normalize the chips, average background, and noise, were also evaluated. 
Microarray Analysis
For statistical analysis of microarray data, all CEL format files were imported to PARTEK Genomics Suite, version 6.4, where the GC-RMA algorithm was applied to yield log signal values on each probe set. Significance was calculated using a t-test without multiple testing corrections, selecting all transcripts with a minimum change in expression level of 1.2-fold together with P < 0.05. 
Visualization of the relationships between the samples by principal component analysis (PCA) based on the GC-RMA signal and hierarchical clustering using the Pearson correlation was obtained using PARTEK Genomics Suite version 6.4. 
All differentially regulated genes were imported into Ingenuity Pathway Analysis (IPA; Ingenuity Systems, Redwood City, CA) for the generation of networks and canonical pathway analysis. The data set containing all significant gene identifiers, along with corresponding expression and significance values, was uploaded into the application. Each identifier was mapped to its corresponding object in Ingenuity's Knowledge Base. The set fold change cutoff identified all molecules whose expression was differentially regulated. These network-eligible molecules were overlaid onto a global molecular network developed from information contained in Ingenuity's Knowledge Base. Networks were then algorithmically generated based on their connectivity. The functional analysis of a network identified the biological functions, using a right-tailed Fisher exact test, that were most significant to the molecules in the network. 
Canonical pathways analysis identified the pathways from the Ingenuity Pathways Analysis library of canonical pathways that were most significant to the data set. The significance of the association between the data set and the canonical pathway was measured in two ways: a ratio of the number of molecules from the data set that map to the pathway divided by the total number of molecules that map to the canonical pathway was displayed; the Fisher exact test was used to calculate a P value determining the probability that the association between the genes in the data set and in the canonical pathway is explained by chance alone. 
Quantitative Real-Time PCR
Quantitative real-time PCR was used to measure expression levels of mRNA transcripts of TES and sham-treated animals. One microgram of RNA of each animal was used for cDNA synthesis using a reverse transcription kit (QuantiTect; Qiagen), which included digestion of genomic DNA. Real-time PCR amplification was performed (LightCycler 480 System and Light Cycler Fast Start Master SYBR Green I; Roche, Mannheim, Germany). To obtain PCR efficiency for each amplified transcript, standard curves were generated, and CP values were determined (LightCycler Software 480; Roche). Expression levels of each sample were detected in triplicate reactions. Pyruvate dehydrogenase β-subunit (Pdh), succinate dehydrogenase complex subunit A (Sdha), and rhodopsin (Rho) were used as reference genes. qBase software version.1.3.3 was used to calculate the relative expression of each target gene. Primer sets for the oligonucleotides shown here were designed using Primer3 software (http://frodo.wi.mit.edu/primer3/): Rho—forward primer, 5′-GGC TTC CCT ATG CCA GTG T-3′, reverse primer, 5′-TCA TCT CCC AGT GGA TTC TTG-3′; Pdh—forward primer, 5′-AGA CAA ATC ATC TCG TAA CTG TGG-3′, reverse primer, 5′-CGC ATC AAG GAA GTT GAA TG-3′; Sdha—forward primer, 5′-TGG ACC TTG TCG TCT TTG G-3′, reverse primer, 5′-TTT GCC TTA ATC GGA GGA AC-3′; Ntn5—forward primer, 5′-CTC CTG CAA GTT AGG GGT CA-3′, reverse primer, 5′-AGC CTT GAC ACT GTG GGT CT-3′; Bmp4—forward primer, 5′-CAG AGC CAA CAC TGT GAG GA-3′, reverse primer, 5′-CAG AGC CAA CAC TGT GAG GA-3′; Cyp2c—forward primer, 5′-CGC AGT CTG AGT TTA CCC TTG-3′, reverse primer, 5′-CCG GTT TCT GCC AAT TAC AC-3′; Tnfrs12a—forward primer, 5′-AGC ACC TCC TGC CCA CTT-3′, reverse primer, 5′-CAG CCT TCT CCA CCA GTC TC-3′; C4bpa—forward primer, 5′-TGC TCC GTT ACA TCT GTC GT-3′, reverse primer, 5′- TGT CAG GAT GTG CCT TTT CA-3′; Npffr2—forward primer, 5-ATG CCT ATC ACA TTG CTG GA-3′, reverse primer, 5′-GCT TGG GCT TAA AGG GGT AG-3′; Rpe65—forward primer, 5′-TTT ACG TGA GAA TTG GGA AGA AG-3′, reverse primer, 5′-AGA ATG GCT GTG GCA GTT GT-3′; Cyp27a1—forward primer, 5′-GCT ATG GGG TTC GGT CCT-3′, reverse primer, 5′-CGT AGG CTC ACC TTC TTG CT-3′. 
Histology
Eyes were enucleated (n = 4, TES; n = 3, sham), and anterior parts and lenses were removed; for paraffin sectioning, fixed eyecups (4% paraformaldehyde in 0.1 M phosphate buffer (pH 7.4) for 1 hour at 4°C) were dehydrated in EtOH, infiltrated in chloroform, and embedded in paraffin. Radial 5-μm sections were stored at 4°C. 
Immunohistochemistry
Tissue sections were deparaffinized, rehydrated, and blocked with endogenous peroxidase with H2O2 for 30 minutes. Antigen retrieval was achieved by pressure cooking in 0.1 M citrate buffer, pH 6, for 10 minutes, followed by cooling at room temperature before incubation with the antibodies. Radial sections were preincubated with phosphate-buffered saline (50 mM, pH 7.4) containing 20% normal goat serum and 0.03% nonionic surfactant (Triton X-100; Sigma-Aldrich, St. Louis, MO) for 2 hours at room temperature to block nonspecific antibody binding. Subsequently, slides were incubated overnight with antibodies against monoclonal mouse anti-rhodopsin (1:400; Millipore Chemicon, Billerica, MA) and anti–monoclonal mouse anti–glial fibrillary acidic protein (GFAP; 1:400; Sigma-Aldrich). 
The immunoreactions were visualized with Alexa Fluor 488 secondary antibodies (Invitrogen, Carlsbad, CA) diluted 1:750. Controls were carried out by omitting the first antibody. 
TUNEL Assay
Terminal deoxynucleotidyl transferase-mediated biotinylated UTP nick end labeling (TUNEL) staining was performed using an in situ cell death detection kit according to the manufacturer's instructions (Fluorescein or TMR; Roche). 21  
Morphometric Analysis
Representative images were taken from the central retina. Microscopy was performed on a fluorescence microscope (Imager Z1 ApoTome; Zeiss, Jena, Germany) equipped with a digital camera (AxioCam; Zeiss). Images were captured using Zeiss (Axiovision 4.7) software, and contrast enhancement was performed using image editing software (Photoshop CS3; Adobe Systems, San Jose, CA). 
Functional Analysis by Electroretinography
ERGs were measured at baseline and after a period of 24 hours after TES with >12 hours of dark adaptation for both groups (TES and sham). All rats were anesthetized and prepared for ERG recordings as previously described. 22 The same contact lens electrodes used for stimulation were placed on the right eye as active electrodes. 
ERG recordings were obtained in scotopic (dark-adapted overnight) and photopic (light-adapted for 10 minutes at 30 cd/m2) conditions using an extended International Society for Clinical Electrophysiology of Vision (ISCEV) protocol. The scotopic ERG protocol consisted of 16 steps with increasing intensities from 0.000003 to 60 cd · s/m2 that were produced by a mixed light (white 6500K) with a Ganzfeld stimulator (ColorDome; Diagnosys, Kissimmee, FL). Photopic stimulation was performed under a permanent background illumination of 30 cd/m2 (white 6500K). Single-flash (0.3–20 cd · s/m2, only b-waves) and flicker (20 Hz with 3 cd · s/m2, only b-waves) were applied for assessment of cone function. Flash durations were 4 ms. Band-pass filtering was applied from 0.3 to 300 Hz using the machine's built-in software algorithm. 
Data analysis was performed using previously described software. 23 ERG data were then exported to data analysis software (JMP; SAS Institute Inc., NC) for further statistical analysis. A Naka-Rushton fit was calculated for scotopic responses (0.000003–0.03 cd · s/m2). 24 An overview of major ERG parameters is shown in Supplementary Table S3
In Vivo Imaging Using Scanning Laser Ophthalmoscopy and Optical Coherence Tomography
For cSLO and OCT imaging, a commercially available HRA+OCT device (Spectralis; Heidelberg Engineering, Heidelberg, Germany) was used as previously described. 25 The near-infrared channel at 795nm was used for en face cSLO imaging. OCT cross-sections of right eyes (n = 4, TES; and n = 3, sham) were recorded at a 30° field of view and consisted of 1536 × 496 pixels acquired at a speed of 40.000 scans/s. The optical depth resolution was approximately 7 μm, with digital resolution reaching 3.5 μm. 26 All resultant data were exported as 8-bit color bitmap files and processed in image editing software (Photoshop CS3; Adobe Systems). 
Statistical Analysis
All results are expressed as mean ± SEM. Comparisons between groups were made by Student's t-test for microarray analysis. P < 0.05 was considered statistically significant. ANOVA and post hoc Tukey-Kramer test were used as statistical analysis for ERG results. 
Results
Expression Profiling of TES- versus Sham-Treated Retinas
Gene expression profiles of four individually stimulated TES animals compared with four sham animals (only the directly stimulated right eye of each animal was used) were statistically analyzed using PARTEK statistical software, as described in Materials and Methods (Fig. 2). Figure 2a shows a 3D visualization of the relationships between the samples using PCA, which is based on the expression levels of the probe sets: TES and sham groups clustered in separate areas of the 3-dimentional visualization, indicating a clear difference in the molecular makeup between them. PCA captured 53.4% of the variation observed in the experiment in the first three principal components, which are plotted on x, y, and z axes respectively, representing the largest fraction of the overall variability in samples. 
Figure 2.
 
Differential expression levels of transcripts in TES versus sham. (a) PCA. Each gray dot in the 3D visualization represents a sample (TES or sham microarray), not a gene. Ellipses around the groups are drawn applying an SD of 2. PCA captured 53.4% of the variation observed in the experiment in the first three principal components (PC), which are plotted on x, y, and z axes, respectively, representing the largest fraction of the overall variability in samples. (b) Graphical representation of all 490 transcripts that were differentially expressed in TES versus sham treated. The four TES and four sham microarray data sets can be seen to cluster into two distinct groups based on correlation of gene expression pattern. The branch lengths for TES and sham sub-trees seen at the top are based on normalized raw data of all transcripts and quantitatively demonstrate that samples of each condition are closely related to the others. Each horizontal colored bar represents one probe set, and the color of the bar determines the degree of expression (red, induced genes; blue, repressed genes; yellow, no differentially regulated genes). (c) Scatter graph of normalized log10 expression values of 490 differentially expressed genes. Each individual point on the scatter graph represents a probe set that met the statistical and 1.2-fold differential expression cutoffs used in this study. Genes lying furthest off the diagonal represent greatest expression differences between TES and sham. Arrows: differentially expressed genes used for validation.
Figure 2.
 
Differential expression levels of transcripts in TES versus sham. (a) PCA. Each gray dot in the 3D visualization represents a sample (TES or sham microarray), not a gene. Ellipses around the groups are drawn applying an SD of 2. PCA captured 53.4% of the variation observed in the experiment in the first three principal components (PC), which are plotted on x, y, and z axes, respectively, representing the largest fraction of the overall variability in samples. (b) Graphical representation of all 490 transcripts that were differentially expressed in TES versus sham treated. The four TES and four sham microarray data sets can be seen to cluster into two distinct groups based on correlation of gene expression pattern. The branch lengths for TES and sham sub-trees seen at the top are based on normalized raw data of all transcripts and quantitatively demonstrate that samples of each condition are closely related to the others. Each horizontal colored bar represents one probe set, and the color of the bar determines the degree of expression (red, induced genes; blue, repressed genes; yellow, no differentially regulated genes). (c) Scatter graph of normalized log10 expression values of 490 differentially expressed genes. Each individual point on the scatter graph represents a probe set that met the statistical and 1.2-fold differential expression cutoffs used in this study. Genes lying furthest off the diagonal represent greatest expression differences between TES and sham. Arrows: differentially expressed genes used for validation.
To demonstrate the overall similarity measurements of different genes within each condition (TES and sham) and differences between the conditions (TES versus sham), normalized raw data were condition-clustered using unsupervised hierarchical clustering. According to the branch length of the dendrogram (Fig. 2b, left), which is based on expression levels of all filtered probe sets, individual TES and sham sub-trees were shown to be distinct from one another in a group-specific manner. Based on a 1.2-fold difference cutoff, this method revealed 539 differentially expressed transcripts in TES versus sham, of which 225 were found to be downregulated and 314 to be upregulated in TES. We have visualized these statistically significant transcripts on a heat map (Fig. 2b, right) to show the relative expression of each transcript represented as horizontal color-coded lines. In Figure 2c, all differentially expressed genes are visualized in a scatter graph, indicating the transcript distribution pattern after TES. 
The downregulated genes represent 0.83% and the upregulated genes represent 1.15% of the total probe set (27,342 genes) screened. Forty-nine transcripts emanated from the same genetic loci, thus reducing the actual number of genes being encoded by the transcripts to 490. Of the 204 genes found to be downregulated in TES, 130 were previously described genes (representing 63.8% of all downregulated genes; 0.48% of all probe sets screened) and 74 were encoded genes of unknown function (representing 36.2% of downregulated genes; 0.27% of all probe sets screened) at the time of analysis. Of the 286 genes found to be upregulated in the TES group, 134 were previously described genes (representing 46.9% of upregulated genes; 0.49% of all probe sets screened), whereas 152 were encoded genes of unknown function (representing 53.1% of upregulated genes; 0.56% of all probe sets screened). The set of genes of unknown function is not discussed further in this study. Nevertheless, because this set of genes helps to accurately and comprehensively define the expression profile of TES applied to wild-type rat retinas, all raw and normalized data for all hybridizations have been deposited as data series in the National Center for Biotechnology Information Gene Expression Omnibus (accession number GSE 26174). 
Functional Categorization of Differentially Regulated Genes
All differentially expressed genes were analyzed through the use of IPA for functional categorization. Table 1 lists the top five canonical pathways—lysine biosynthesis; T-helper cell differentiation; communication between innate, adaptive immune cell and T/B cell signaling; hepatic fibrosis cell activation; role of macrophages, fibroblasts, and endothelial cells in rheumatoid arthritis (genes involved in apoptosis and inflammatory response)—regulated by TES in wild-type rat retinas based on their significance (P < 0.05); note that some genes appear in more than one group. Overall, 13 significant canonical pathways were detected (Supplementary Table S1). 
Table 1.
 
Top Five Canonical Pathways Regulated by TES in Wild-type Retinas Detected by IPA
Table 1.
 
Top Five Canonical Pathways Regulated by TES in Wild-type Retinas Detected by IPA
Affymetrix ID Gene Symbol Description Fold Change
Lysin Biosynthesis (P = 0.0059)
10861242 Aass aminoadipate-semialdehyde synthase −1.24
10831582 Tap2 transporter 2, ATP-binding cassette, sub-family B (MDR/TAP) −1.23
2 T-Helper Cell
Differentiation (P = 0.0065)
10935605 CD40lg CD40 ligand 1.20
10895625 Ifng interferon, gamma 1.24
10903725 Tnfrsf11b tumor necrosis factor receptor superfamily, member 11b 1.27
Communication among Innate, Adative Immune Cells and T/B Cell Signaling (P = 0.0079)
10935605 CD40LG CD40 ligand 1.20
10895625 Ifng interferon, gamma 1.24
10744161 Tnfsf13 tumor necrosis factor (ligand) superfamily, member 13 −1.29
10793038 Tnfsf13b tumor necrosis factor (ligand) superfamily, member 13b −1.22
Hepatic Fibrosis Cell Activation (P = 0.008)
10721834 Bax BCL2-associated X protein −1.20
10935605 CD40lg CD40 ligand 1.20
10797857 Edn1 endothelin 1 −1.34
10895625 Ifng interferon, gamma 1.24
10903725 Tnfrsf11b tumor necrosis factor receptor superfamily, member 11b 1.27
Role of Macrophages, Fibroblasts, and Endothelial Cells in Rheumatoid Arthritis (P = 0.0083)
10858315 IL17ra interleukin 17 receptor A −1.20
10926181 Plcl2 phospholipase C-like 2 −1.30
10854948 Prss2 protease, serine, 2 1.23
10747506 Stat3 signal transducer and activator of transcription 3 1.22
10903725 Tnfrsf11b tumor necrosis factor receptor superfamily, member 11b 1.27
10793038 Tnfsf13b tumor necrosis factor (ligand) superfamily, member 13b −1.22
10736257 Traf4 TNF receptor-associated factor 4 1.27
10862154 Tryx3 trypsin X3 1.23
IPA network analysis revealed eight significant regulatory networks with a score ≥20. The number 1 ranked network (score 33; focus molecules 22) as shown in Figure 3 is associated with embryonic, tissue, and organ development. The network contains 22 differentially regulated genes (16 downregulated and six upregulated genes). Top functions of the other seven significant networks are associated with inflammatory response, cell development and function, cell signaling and interaction, tissue morphology, cell cycle, cellular growth and proliferation, gene expression, RNA posttranscriptional modification, as well as organism injury and abnormalities and are displayed in Supplementary Table S2
Figure 3.
 
Most prominent gene network discovered by IPA. The most prominently affected gene network was classified as Embryonic Development, Tissue Development and Organ Development. The network contains 22 differentially regulated genes including 16 repressed and six induced genes (red, induction; green, repression; white, unaffected; overall color intensity is related to fold change).
Figure 3.
 
Most prominent gene network discovered by IPA. The most prominently affected gene network was classified as Embryonic Development, Tissue Development and Organ Development. The network contains 22 differentially regulated genes including 16 repressed and six induced genes (red, induction; green, repression; white, unaffected; overall color intensity is related to fold change).
Validation of Microarray Data
Expression levels of eight genes were verified using transcribed cDNA of independent samples sets by quantitative real-time PCR. Four genes from top networks (Bmp4, Cyp27a1, Tnfrs12a, Cyp2c) and four random genes (Rpe65, Npffr2, Ntn5, C4bpa) were chosen for validation and run in respective triplicates (n = 6; P < 0.05). Fold changes of microarray and qRT-PCR data are shown in Table 2
Table 2.
 
Validation of Differentially Expressed Genes by Quantitative Real-Time PCR
Table 2.
 
Validation of Differentially Expressed Genes by Quantitative Real-Time PCR
Gene Symbol Affymetrix ID Microarray Fold qPCR Fold Change
Ntn5 10706933 −1.40 −1.16
Cyp2c 10715211 1.31 1.54
Tnfrs12a 10740869 −1.32 −1.32
C4bpa 10767422 −1.41 −1.47
Npffr2 10775987 1.32 1.08
Bmp4 10782891 −1.41 −1.43
Rpe65 10819961 −1.55 −1.47
Cyp27a1 10924411 −1.43 −1.22
Functional Analysis
ERG curves showed identical results with respect to implicit times and amplitudes for TES- and sham-treated animals compared with baseline recordings (Fig. 4a). Parameters of the scotopic sensitivity function (V max, k, n) described by a Naka-Rushton fit (Fig. 4b) showed no significant differences between TES and sham (V max ANOVA, P = 0.46). In addition, high-intensity responses (a-wave and b-wave 1–60 cd · s/m2) remained equally unchanged. Results of a- and b-wave amplitudes and implicit times under photopic conditions (single-flash and 20-Hz flicker) were not different for TES and sham (single-flash 20 cd · s/m2 ANOVA, P = 0.55). 
Figure 4.
 
Functional analyses of wild-type retinas after TES. Functional analysis by electroretinography 24 hours after TES showed normal ERG recordings compared with baseline. (a) Examples of scotopic ERG traces at increasing intensities (0.000003–60 cd · s/m2). ERG traces showed comparable results between baseline and 24 hours after TES for both groups. (b) Examples of Naka-Rushton plots for scotopic intensity series (0.000003–0.03 cd · s/m2) of both groups. Values of Naka-Rushton (V max [μV] and k [Log intensity cd · s/m2]) are extracted as listed on the plot (dashed line); points demonstrate single ERG measurements with increasing intensity. Results demonstrated nearly similar results for TES and sham groups.
Figure 4.
 
Functional analyses of wild-type retinas after TES. Functional analysis by electroretinography 24 hours after TES showed normal ERG recordings compared with baseline. (a) Examples of scotopic ERG traces at increasing intensities (0.000003–60 cd · s/m2). ERG traces showed comparable results between baseline and 24 hours after TES for both groups. (b) Examples of Naka-Rushton plots for scotopic intensity series (0.000003–0.03 cd · s/m2) of both groups. Values of Naka-Rushton (V max [μV] and k [Log intensity cd · s/m2]) are extracted as listed on the plot (dashed line); points demonstrate single ERG measurements with increasing intensity. Results demonstrated nearly similar results for TES and sham groups.
Structural Analyses In Vivo and Ex Vivo
In vivo cSLO and OCT imaging of the retina 30 hours after treatment did not reveal structural changes in TES-treated wild-type animals (n = 4) compared with sham (n = 3). En face imaging using cSLO yielded physiological fundus images with no signs of structural alterations (Fig. 5a, top). OCT cross-sections showed normal retinal layering and physiological central retinal thickness along a vertical meridian (superior and inferior central, mid-central, mid-peripheral and peripheral layers) in TES versus sham (Fig. 5a, bottom). 
Figure 5.
 
Structural analyses of wild-type retinas after TES. (a) In vivo imaging using the IR channel at 795 nm yielded physiological fundus images of the retina in sham and TES animals with no signs of structural alterations (top). OCT provided high-resolution vertical sections with intact retinal layers for both sham and TES (middle). Mean retinal thickness (bottom) showed no significant differences between TES and sham-treated groups when measured along a vertical meridian passing through the optic nerve head at peripheral, mid-peripheral, mid-central, and central areas. (b) Hematoxylin and eosin staining of retinal sections from TES and sham rat revealed intact outer segment, outer nuclear, inner nuclear, and ganglion cell layers. GFAP staining (c, green) and labeling of rods with anti-rhodopsin (d, green) from TES and sham rats illustrate the absence of reactive glia and well-maintained rod photoreceptor outer segments in both groups. No TUNEL-positive cells were observed in the outer nuclear layers of TES or sham retinas (e).
Figure 5.
 
Structural analyses of wild-type retinas after TES. (a) In vivo imaging using the IR channel at 795 nm yielded physiological fundus images of the retina in sham and TES animals with no signs of structural alterations (top). OCT provided high-resolution vertical sections with intact retinal layers for both sham and TES (middle). Mean retinal thickness (bottom) showed no significant differences between TES and sham-treated groups when measured along a vertical meridian passing through the optic nerve head at peripheral, mid-peripheral, mid-central, and central areas. (b) Hematoxylin and eosin staining of retinal sections from TES and sham rat revealed intact outer segment, outer nuclear, inner nuclear, and ganglion cell layers. GFAP staining (c, green) and labeling of rods with anti-rhodopsin (d, green) from TES and sham rats illustrate the absence of reactive glia and well-maintained rod photoreceptor outer segments in both groups. No TUNEL-positive cells were observed in the outer nuclear layers of TES or sham retinas (e).
Hematoxylin and eosin staining showed intact retinal sections in both groups (Fig. 5b). Immunohistochemistry confirmed absent induction of intermediate fiber glial fibrillary acid protein (GFAP) in TES animals 35 hours after stimulation. Both TES- and sham-treated wild-type rat retinas expressed only GFAP in astroglia, endfeet of Müller cells along the retina, and at the vitreous margin. Thus, no difference was found in GFAP staining between TES and sham retinas (Fig. 5c). In concordance, rhodopsin labeling showed a normal distribution in both treatment groups and was restricted to photoreceptor outer segments, as illustrated in Figure 5d. To investigate the presence of apoptotic activity in the electrically stimulated rat retina, a TUNEL assay was performed in both groups, but no TUNEL-positive cells were detected in any layer for TES or sham (Fig. 5e). 
Discussion
To investigate the direct effect of electrical stimulation on the retina at the mRNA level and to study the function and structure of wild-type retinal tissue after stimulation, TES was applied to BN rats. Our findings demonstrated that TES induced distinct changes at the level of the transcriptome in the wild-type retina. At the same time, TES-treated healthy retinas maintained their physiological function and intact structural properties up to 35 hours after stimulation. 
A number of studies have focused on the molecular basis of TES-induced neuroprotection using either degenerative retinal animal models or traumatic retinal (e.g., light damage) or optic nerve damage and have suggested certain candidate genes being involved. 8,11,19,27 However, a common set of genes responsible for the neuroprotective effect of TES have not yet been identified. Although the direct effect of electrical stimulation on the induction of the brain-derived neurotrophic factor BDNF in cultured Müller cells has been shown, our findings are the first in vivo demonstration that TES induces a set of transcriptional changes with potential neuroprotective effects in the wild-type retina. 
Our top canonical pathways and networks showed cellular processes involved in tissue development, cell signaling, inflammatory response, cellular growth, proliferation, and cell death mediation. Part of our most highly regulated gene network was Bax. Bax, a proapoptotic member of the Bcl-2 family, mediates cell death by mitochondrial release of cytochrome c and activation of caspase-9 and -3. Downregulation of Bax (along with downregulation of cytochrome c oxidase) was observed in wild-type retinas of our treated animals. In contrast to TES, Bax upregulation has been reported after optic nerve transaction. 27 Members of the tumor necrosis factor superfamily are associated with promoting or preventing the apoptosis of retinal ganglion cells. 27 29 The tumor necrosis factor family, as a group of cytokines, has been linked to apoptosis by an extracellular pathway through TRADD signaling. 30,31 One member of this family, Tnrsf12a, was found to be downregulated by TES. Conversely, Tnrsf12a has been shown to be linked with apoptosis through TRADD (tumor necrosis factor receptor type 1-associated DEATH domain protein) signaling, which has been reported to be activated after optic nerve transection and optic nerve crush. 27 Other members, such as Tnfrsf11b, Tnfsf13b, Tnfsf13, Tnf receptor, and Traf4 (Tnf receptor associated protein 4) were differentially regulated. Involvement of the NFB signaling pathway has been suggested in activity-dependent neuroprotection. 32 A number of genes, such as Tnfrsf11b and Tnfsf13b (both downregulated), suggested to be involved in NFB signaling, were differentially regulated by TES, supporting its potential role in TES-induced neuroprotection. In further support, histologic TUNEL assay did not detect apoptotic activity in cells of TES retinas. 
Previous studies 8,9,11,19 have clearly shown the involvement of various growth factors in TES-mediated neuroprotection in the degenerated retina and have focused their analyses on growth factors such as IGF-1 and BDNF. To the best of our knowledge, until now, no genomewide screening has been performed after TES in an in vivo experiment investigating gene expression changes in either wild-type or degenerated retina. Thus, it is possible that the involvement of the tumor necrosis factor family in TES-induced neuroprotection is a novel finding possibly acting in concert with previously found growth factors. 11 However, previously suggested growth factors involved in TES-mediated neuroprotection, such as IGF-1, BDNF, CNTF, and Bcl-2, were not found to be regulated in TES-treated wild-type retinas. 8,11,19 One reason could be that all studies except one used either an inherited or a traumatic photoreceptor degeneration animal model. 19 Although BDNF was found to be regulated in cultured retinal Müller cells after electrical stimulation, we did not see a differential regulation on TES in wild-type BN retinal tissue. However, mRNA levels of numerous apoptosis-related genes such as Bax were downregulated after TES in wild-type retinas. Furthermore, Bax downregulation in our study was in line with TES applied in a light-induced photoreceptor degeneration model. 11 This indicates that the transcriptional program of TES-induced neuroprotection most likely depends on the type of retinal degeneration, stimulation pattern, and time point of RNA isolation for gene expression profiling. One limitation of our study, therefore, might be that microarray analyses were performed only at one time point (4 hours) after TES. Additional studies to examine the expression pattern of genes regulated by TES over time are needed, and we cannot exclude the possibility that other genes may be induced at a different time. Furthermore, the situation in diseased retina, in which vast numbers of neuroprotective cascades are already activated, could yield different expression levels and patterns. To further validate the expression pattern found and to enhance its biological significance, future studies investigating the effects at the protein level are also needed. As a future direction, gene expression changes at the mRNA and protein levels should be investigated in an animal model with retinal degeneration to gain further knowledge about the pathways involved in TES-induced neuroprotection. Although overall fold level changes induced by TES were relatively small in wild-type tissue, the magnitude of expression changes in our study is comparable with previous results of electrically stimulated Müller cells and are, hence, not surprising. 19  
In summary, we have demonstrated that TES applied to the wild-type retina in vivo induces a series of transcriptional changes. The molecular makeup of induced genes may contribute to further characterize the neuroprotective role of TES by identifying the molecular pathways involved and providing a broad overview of differentially regulated genes. Knowledge of these transcriptional changes is important for an understanding of the mechanisms underlying TES and might help to refine its application in humans. 12 In addition, as structural and functional integrity of the retina after TES with the applied parameters used was observed, no adverse effects were noted. Overall, our findings point toward TES being a potentially safe approach to induce the neuroprotection, and thus the survival, of retinal tissue. 
Supplementary Materials
Figure sf01, PDF - Figure sf01, PDF 
Table st1, XLS - Table st1, XLS 
Table st2, XLS - Table st2, XLS 
Table st3, XLS - Table st3, XLS 
Footnotes
 Supported by Okuvision GmbH, Reutlingen, Germany.
Footnotes
 Disclosure: G. Willmann, Okuvision GmbH (F); K. Schäferhoff, None; M.D. Fischer, Okuvision GmbH (F); B. Arango-Gonzalez, None; S. Bolz, None; L. Naycheva, Okuvision GmbH (F); T. Röck, Okuvision GmbH (F); M. Bonin, None; K.U. Bartz-Schmidt, Okuvision GmbH (F); E. Zrenner, Okuvision GmbH (F); A. Schatz, Okuvision GmbH (F); F. Gekeler, Okuvision GmbH (F)
The authors thank Heike Enderle for excellent technical examination and data entry. 
References
Hartong DT Berson EL Dryja TP . Retinitis pigmentosa. Lancet. 2006;368:1795–1809. [CrossRef] [PubMed]
Zrenner E Bartz-Schmidt KU Benav H . Subretinal electronic chips allow blind patients to read letters and combine them to words. Proc Biol Sci. 2011;278(1711):1489–1497. [CrossRef] [PubMed]
Bainbridge JW Smith AJ Barker SS . Effect of gene therapy on visual function in Leber's congenital amaurosis. N Engl J Med. 2008;358:2231–2239. [CrossRef] [PubMed]
Sieving PA Caruso RC Tao W . Ciliary neurotrophic factor (CNTF) for human retinal degeneration: phase I trial of CNTF delivered by encapsulated cell intraocular implants. Proc Natl Acad Sci U S A. 2006;103:3896–3901. [CrossRef] [PubMed]
Fujikado T Morimoto T Matsushita K Shimojo H Okawa Y Tano Y . Effect of transcorneal electrical stimulation in patients with nonarteritic ischemic optic neuropathy or traumatic optic neuropathy. Jpn J Ophthalmol. 2006;50:266–273. [CrossRef] [PubMed]
Inomata K Shinoda K Ohde H . Transcorneal electrical stimulation of retina to treat longstanding retinal artery occlusion. Graefes Arch Clin Exp Ophthalmol. 2007;245:1773–1780. [CrossRef] [PubMed]
Schmid H Herrmann T Kohler K Stett A . Neuroprotective effect of transretinal electrical stimulation on neurons in the inner nuclear layer of the degenerated retina. Brain Res Bull. 2009;79:15–25. [CrossRef] [PubMed]
Morimoto T Miyoshi T Matsuda S Tano Y Fujikado T Fukuda Y . Transcorneal electrical stimulation rescues axotomized retinal ganglion cells by activating endogenous retinal IGF-1 system. Invest Ophthalmol Vis Sci. 2005;46:2147–2155. [CrossRef] [PubMed]
Sato T Fujikado T Morimoto T Matsushita K Harada T Tano Y . Effect of electrical stimulation on IGF-1 transcription by L-type calcium channels in cultured retinal Muller cells. Jpn J Ophthalmol. 2008;52:217–223. [CrossRef] [PubMed]
Kent TL Glybina IV Abrams GW Iezzi R . Chronic intravitreous infusion of ciliary neurotrophic factor modulates electrical retinal stimulation thresholds in the RCS rat. Invest Ophthalmol Vis Sci. 2008;49:372–379. [CrossRef] [PubMed]
Ni YQ Gan DK Xu HD Xu GZ Da CD . Neuroprotective effect of transcorneal electrical stimulation on light-induced photoreceptor degeneration. Exp Neurol. 2009;219:439–452. [CrossRef] [PubMed]
Schatz A Rock T Naycheva L . Transcorneal electrical stimulation for patients with retinitis pigmentosa: a prospective, randomized, sham-controlled exploratory study. Invest Ophthalmol Vis Sci. 2011;52:4485–4496. [CrossRef] [PubMed]
Gekeler F Szurman P Grisanti S . Compound subretinal prostheses with extra-ocular parts designed for human trials: successful long-term implantation in pigs. Graefes Arch Clin Exp Ophthalmol. 2007;245:230–241. [CrossRef] [PubMed]
Pardue MT Phillips MJ Yin H . Neuroprotective effect of subretinal implants in the RCS rat. Invest Ophthalmol Vis Sci. 2005;46:674–682. [CrossRef] [PubMed]
Fujikado T Morimoto T Kanda H . Evaluation of phosphenes elicited by extraocular stimulation in normals and by suprachoroidal-transretinal stimulation in patients with retinitis pigmentosa. Graefes Arch Clin Exp Ophthalmol. 2007;245:1411–1419. [CrossRef] [PubMed]
Ciavatta VT Kim M Wong P . Retinal expression of Fgf2 in RCS rats with subretinal microphotodiode array. Invest Ophthalmol Vis Sci. 2009;50:4523–4530. [CrossRef] [PubMed]
Miyake K Yoshida M Inoue Y Hata Y . Neuroprotective effect of transcorneal electrical stimulation on the acute phase of optic nerve injury. Invest Ophthalmol Vis Sci. 2007;48:2356–2361. [CrossRef] [PubMed]
Morimoto T Fujikado T Choi JS . Transcorneal electrical stimulation promotes the survival of photoreceptors and preserves retinal function in Royal College of Surgeons rats. Invest Ophthalmol Vis Sci. 2007;48:4725–4732. [CrossRef] [PubMed]
Sato T Fujikado T Lee TS Tano Y . Direct effect of electrical stimulation on induction of brain-derived neurotrophic factor from cultured retinal Muller cells. Invest Ophthalmol Vis Sci. 2008;49:4641–4646. [CrossRef] [PubMed]
Thaler S Haritoglou C Choragiewicz TJ . In vivo toxicity study of rhodamine 6G in the rat retina. Invest Ophthalmol Vis Sci. 2008;49:2120–2126. [CrossRef] [PubMed]
Gavrieli Y Sherman Y Ben-Sasson SA . Identification of programmed cell death in situ via specific labeling of nuclear DNA fragmentation. J Cell Biol. 1992;119:493–501. [CrossRef] [PubMed]
Messias A Zrenner E Tzekov R . Single doses of all-trans-N-retinylacetamide slow down the ERG amplitude recovery after bleaching in rats. Doc Ophthalmol. 2010;120:165–174. [CrossRef] [PubMed]
Messias A Jaegle H Gekeler F Zrenner E . Software for evaluation of electroretinograms. Presented at: XLVI Annual Symposium of the International Society for Clinical Electrophysiology of Vision (ISCEV); July 10–15, 2008; Morgantown, WV.
Naka KI Rushton WA . S-potentials from luminosity units in the retina of fish (Cyprinidae). J Physiol. 1966;185:587–599. [CrossRef] [PubMed]
Fischer MD Huber G Beck SC . Noninvasive, in vivo assessment of mouse retinal structure using optical coherence tomography. PLoS One. 2009;4:e7507. [CrossRef] [PubMed]
Wolf-Schnurrbusch UE Enzmann V Brinkmann CK Wolf S . Morphologic changes in patients with geographic atrophy assessed with a novel spectral OCT-SLO combination. Invest Ophthalmol Vis Sci. 2008;49:3095–3099. [CrossRef] [PubMed]
Agudo M Perez-Marin MC Lonngren U . Time course profiling of the retinal transcriptome after optic nerve transection and optic nerve crush. Mol Vis. 2008;14:1050–1063. [PubMed]
Agudo M Perez-Marin MC Sobrado-Calvo P . Immediate upregulation of proteins belonging to different branches of the apoptotic cascade in the retina after optic nerve transection and optic nerve crush. Invest Ophthalmol Vis Sci. 2009;50:424–431. [CrossRef] [PubMed]
Liang H Baudouin C Behar-Cohen F Crisanti P Omri B . Protein kinase C-zeta mediates retinal degeneration in response to TNF. J Neuroimmunol. 2007;183:104–110. [CrossRef] [PubMed]
Ashkenazi A Dixit VM . Death receptors: signaling and modulation. Science. 1998;281:1305–1308. [CrossRef] [PubMed]
Jin Z El-Deiry WS . Overview of cell death signaling pathways. Cancer Biol Ther. 2005;4:139–163. [CrossRef] [PubMed]
O'Neill LA Kaltschmidt C . NF-kappa B: a crucial transcription factor for glial and neuronal cell function. Trends Neurosci. 1997;20:252–258. [CrossRef] [PubMed]
Figure 1.
 
Experimental design for TES in BN wild-type retinas. Animals were dark adapted (DA) for >12 hours, followed by 2 hours of day light (LA) before TES or sham stimulation. Genomewide, functional, and structural analyses were performed at the indicated time points after treatment. Duration of stimulation was 1 hour.
Figure 1.
 
Experimental design for TES in BN wild-type retinas. Animals were dark adapted (DA) for >12 hours, followed by 2 hours of day light (LA) before TES or sham stimulation. Genomewide, functional, and structural analyses were performed at the indicated time points after treatment. Duration of stimulation was 1 hour.
Figure 2.
 
Differential expression levels of transcripts in TES versus sham. (a) PCA. Each gray dot in the 3D visualization represents a sample (TES or sham microarray), not a gene. Ellipses around the groups are drawn applying an SD of 2. PCA captured 53.4% of the variation observed in the experiment in the first three principal components (PC), which are plotted on x, y, and z axes, respectively, representing the largest fraction of the overall variability in samples. (b) Graphical representation of all 490 transcripts that were differentially expressed in TES versus sham treated. The four TES and four sham microarray data sets can be seen to cluster into two distinct groups based on correlation of gene expression pattern. The branch lengths for TES and sham sub-trees seen at the top are based on normalized raw data of all transcripts and quantitatively demonstrate that samples of each condition are closely related to the others. Each horizontal colored bar represents one probe set, and the color of the bar determines the degree of expression (red, induced genes; blue, repressed genes; yellow, no differentially regulated genes). (c) Scatter graph of normalized log10 expression values of 490 differentially expressed genes. Each individual point on the scatter graph represents a probe set that met the statistical and 1.2-fold differential expression cutoffs used in this study. Genes lying furthest off the diagonal represent greatest expression differences between TES and sham. Arrows: differentially expressed genes used for validation.
Figure 2.
 
Differential expression levels of transcripts in TES versus sham. (a) PCA. Each gray dot in the 3D visualization represents a sample (TES or sham microarray), not a gene. Ellipses around the groups are drawn applying an SD of 2. PCA captured 53.4% of the variation observed in the experiment in the first three principal components (PC), which are plotted on x, y, and z axes, respectively, representing the largest fraction of the overall variability in samples. (b) Graphical representation of all 490 transcripts that were differentially expressed in TES versus sham treated. The four TES and four sham microarray data sets can be seen to cluster into two distinct groups based on correlation of gene expression pattern. The branch lengths for TES and sham sub-trees seen at the top are based on normalized raw data of all transcripts and quantitatively demonstrate that samples of each condition are closely related to the others. Each horizontal colored bar represents one probe set, and the color of the bar determines the degree of expression (red, induced genes; blue, repressed genes; yellow, no differentially regulated genes). (c) Scatter graph of normalized log10 expression values of 490 differentially expressed genes. Each individual point on the scatter graph represents a probe set that met the statistical and 1.2-fold differential expression cutoffs used in this study. Genes lying furthest off the diagonal represent greatest expression differences between TES and sham. Arrows: differentially expressed genes used for validation.
Figure 3.
 
Most prominent gene network discovered by IPA. The most prominently affected gene network was classified as Embryonic Development, Tissue Development and Organ Development. The network contains 22 differentially regulated genes including 16 repressed and six induced genes (red, induction; green, repression; white, unaffected; overall color intensity is related to fold change).
Figure 3.
 
Most prominent gene network discovered by IPA. The most prominently affected gene network was classified as Embryonic Development, Tissue Development and Organ Development. The network contains 22 differentially regulated genes including 16 repressed and six induced genes (red, induction; green, repression; white, unaffected; overall color intensity is related to fold change).
Figure 4.
 
Functional analyses of wild-type retinas after TES. Functional analysis by electroretinography 24 hours after TES showed normal ERG recordings compared with baseline. (a) Examples of scotopic ERG traces at increasing intensities (0.000003–60 cd · s/m2). ERG traces showed comparable results between baseline and 24 hours after TES for both groups. (b) Examples of Naka-Rushton plots for scotopic intensity series (0.000003–0.03 cd · s/m2) of both groups. Values of Naka-Rushton (V max [μV] and k [Log intensity cd · s/m2]) are extracted as listed on the plot (dashed line); points demonstrate single ERG measurements with increasing intensity. Results demonstrated nearly similar results for TES and sham groups.
Figure 4.
 
Functional analyses of wild-type retinas after TES. Functional analysis by electroretinography 24 hours after TES showed normal ERG recordings compared with baseline. (a) Examples of scotopic ERG traces at increasing intensities (0.000003–60 cd · s/m2). ERG traces showed comparable results between baseline and 24 hours after TES for both groups. (b) Examples of Naka-Rushton plots for scotopic intensity series (0.000003–0.03 cd · s/m2) of both groups. Values of Naka-Rushton (V max [μV] and k [Log intensity cd · s/m2]) are extracted as listed on the plot (dashed line); points demonstrate single ERG measurements with increasing intensity. Results demonstrated nearly similar results for TES and sham groups.
Figure 5.
 
Structural analyses of wild-type retinas after TES. (a) In vivo imaging using the IR channel at 795 nm yielded physiological fundus images of the retina in sham and TES animals with no signs of structural alterations (top). OCT provided high-resolution vertical sections with intact retinal layers for both sham and TES (middle). Mean retinal thickness (bottom) showed no significant differences between TES and sham-treated groups when measured along a vertical meridian passing through the optic nerve head at peripheral, mid-peripheral, mid-central, and central areas. (b) Hematoxylin and eosin staining of retinal sections from TES and sham rat revealed intact outer segment, outer nuclear, inner nuclear, and ganglion cell layers. GFAP staining (c, green) and labeling of rods with anti-rhodopsin (d, green) from TES and sham rats illustrate the absence of reactive glia and well-maintained rod photoreceptor outer segments in both groups. No TUNEL-positive cells were observed in the outer nuclear layers of TES or sham retinas (e).
Figure 5.
 
Structural analyses of wild-type retinas after TES. (a) In vivo imaging using the IR channel at 795 nm yielded physiological fundus images of the retina in sham and TES animals with no signs of structural alterations (top). OCT provided high-resolution vertical sections with intact retinal layers for both sham and TES (middle). Mean retinal thickness (bottom) showed no significant differences between TES and sham-treated groups when measured along a vertical meridian passing through the optic nerve head at peripheral, mid-peripheral, mid-central, and central areas. (b) Hematoxylin and eosin staining of retinal sections from TES and sham rat revealed intact outer segment, outer nuclear, inner nuclear, and ganglion cell layers. GFAP staining (c, green) and labeling of rods with anti-rhodopsin (d, green) from TES and sham rats illustrate the absence of reactive glia and well-maintained rod photoreceptor outer segments in both groups. No TUNEL-positive cells were observed in the outer nuclear layers of TES or sham retinas (e).
Table 1.
 
Top Five Canonical Pathways Regulated by TES in Wild-type Retinas Detected by IPA
Table 1.
 
Top Five Canonical Pathways Regulated by TES in Wild-type Retinas Detected by IPA
Affymetrix ID Gene Symbol Description Fold Change
Lysin Biosynthesis (P = 0.0059)
10861242 Aass aminoadipate-semialdehyde synthase −1.24
10831582 Tap2 transporter 2, ATP-binding cassette, sub-family B (MDR/TAP) −1.23
2 T-Helper Cell
Differentiation (P = 0.0065)
10935605 CD40lg CD40 ligand 1.20
10895625 Ifng interferon, gamma 1.24
10903725 Tnfrsf11b tumor necrosis factor receptor superfamily, member 11b 1.27
Communication among Innate, Adative Immune Cells and T/B Cell Signaling (P = 0.0079)
10935605 CD40LG CD40 ligand 1.20
10895625 Ifng interferon, gamma 1.24
10744161 Tnfsf13 tumor necrosis factor (ligand) superfamily, member 13 −1.29
10793038 Tnfsf13b tumor necrosis factor (ligand) superfamily, member 13b −1.22
Hepatic Fibrosis Cell Activation (P = 0.008)
10721834 Bax BCL2-associated X protein −1.20
10935605 CD40lg CD40 ligand 1.20
10797857 Edn1 endothelin 1 −1.34
10895625 Ifng interferon, gamma 1.24
10903725 Tnfrsf11b tumor necrosis factor receptor superfamily, member 11b 1.27
Role of Macrophages, Fibroblasts, and Endothelial Cells in Rheumatoid Arthritis (P = 0.0083)
10858315 IL17ra interleukin 17 receptor A −1.20
10926181 Plcl2 phospholipase C-like 2 −1.30
10854948 Prss2 protease, serine, 2 1.23
10747506 Stat3 signal transducer and activator of transcription 3 1.22
10903725 Tnfrsf11b tumor necrosis factor receptor superfamily, member 11b 1.27
10793038 Tnfsf13b tumor necrosis factor (ligand) superfamily, member 13b −1.22
10736257 Traf4 TNF receptor-associated factor 4 1.27
10862154 Tryx3 trypsin X3 1.23
Table 2.
 
Validation of Differentially Expressed Genes by Quantitative Real-Time PCR
Table 2.
 
Validation of Differentially Expressed Genes by Quantitative Real-Time PCR
Gene Symbol Affymetrix ID Microarray Fold qPCR Fold Change
Ntn5 10706933 −1.40 −1.16
Cyp2c 10715211 1.31 1.54
Tnfrs12a 10740869 −1.32 −1.32
C4bpa 10767422 −1.41 −1.47
Npffr2 10775987 1.32 1.08
Bmp4 10782891 −1.41 −1.43
Rpe65 10819961 −1.55 −1.47
Cyp27a1 10924411 −1.43 −1.22
Figure sf01, PDF
Table st1, XLS
Table st2, XLS
Table st3, XLS
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