Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Responses of retinal and brain microvasculature to streptozotocin induced diabetes revealed by global expression profiling

Responses of retinal and brain microvasculature to streptozotocin induced diabetes revealed by... This study aims to determine the effects of diabetes in the retinal and brain microvasculature through gene expression profiling. Twelve male Wistar rats were randomly divided into two groups: streptozotocin-induced diabetic rats and time- matched nondiabetic rats. The retinal microvessels (RMVs) and brain microvessels (BMVs) were mechanically isolated from individual rats. Differentially expressed genes (DEGs) in diabetic and nondiabetic microvessels were identified by cDNA microarrays analysis. In RMVs, we identified 43 DEGs, of which 20 were upregulated while 23 were downregulated by diabetes. In BMVs, 35 genes DEGs were identified, of which 22 were upregulated and 13 were downregulated by diabetes. Altered expression of the Nars, Gars, Mars, Iars, Yars, Bcl2, Nqo1, NR4A3, Gpd1, Stc1, Tsc22d3, Tnfrsf21 mRNA as observed in the microarray analyses, was confirmed by quantitative RT-PCR. The aminoacyl-tRNA synthetases (aaRSs) pathway in RMVs was significantly overrepresented as compared to BMVs. Our study demonstrates for the first time that in the brain microvasculature multiple compensatory mechanisms exists, serving to protect brain tissue from diabetic insults, whereas these mechanisms are not activated in the retinal microvasculature. This provides new insights as to why brain microvasculature is less susceptible to diabetes. Keywords Retina, brain, diabetes, microvasculature, gene expression profiling mechanisms of diabetic microvascular complications. Introduction Researchers claimed that the molecular imbalance be- Diabetes is a progressive metabolic disease characterized tween toxic and endogenous protective factors may be by hyperglycemia due to absolute or relative (resistance) insulin deficiency, and the development of chronic vascular damage in retina, kidney and peripheral nerves. Over the Division of Neurosurgical Research, Heidelberg University, Mannheim, Germany; European Center of Angioscience, Medical Faculty past decades, multiple molecular mechanisms have been Mannheim, Heidelberg University, Mannheim, Germany proposed to explain the pathogenesis of diabetic vascular Department of Pathology and Medical Biology, University Medical Center injury, e.g., overproduction of reactive oxygen species Groningen, Groningen, The Netherlands (ROS) in mitochondria and NF-κB pathway activation in Department of Gastroenterology and Hepatology, University Medical 2,3 endothelial cells. Despite extensive research, until now Center Groningen, Groningen, The Netherlands there are no effective therapies for preventing diabetic Corresponding author: vascular complications. Jan AAM Kamps, Department of Pathology and Medical Biology, Heretofore, most studies have focused on the highly University of Groningen, University Medical Center Groningen, susceptible organs in diabetes, such as retinae, kidney Hanzeplein 1 (EA11), 9713GZ Groningen, The Netherlands. and peripheral nerves, to identify key molecular Email: j.a.a.m.kamps@umcg.nl Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/ en-us/nam/open-access-at-sage). 2 Diabetes & Vascular Disease Research 20(1) responsible for the pathogenesis of diabetic microvas- Isolation of brain and retinal microvessels cular complications. A wealth of studies reported that The rat RMVs and BMVs were isolated as described brain microvasculature was less susceptible to diabetes 5–7 previously. Briefly, brain and retinal crysections were compared to retinal microvasculature. However, the individually homogenized using a motor-driven homoge- underlying molecular mechanisms involved in this dif- nizer (Homgen plus, Schuett Biotec, Goettingen, Ger- ference is poorly understood. many). The brain homogenate was centrifuged at 438g for Many research efforts to elucidate the molecular 10min, followed by centrifugation at 4400g for 15min, mechanisms of diabetic retinopathy (DR) by assessing after which the pellet was resuspended into 7 mL PBS/1% the genomic and/or proteomic profiles of the entire retina 8–10 dextran (Dextran 70,000, Roth). Thereafter, the brain and tissue. However, these findings might be inaccurate retinal suspension were individually transferred onto a for explaining the molecular mechanisms of diabetic density gradient column and centrifuged for 15 min vascular impairments because of the presence of an (1300 g). Finally, the microvessels were captured after excess nonvascular tissue in whole organ analysis. Re- filtration over a 60 µm nylon mesh. All the procedures were cently, we have established a new mechanical isolation performed at 0°C. method for both retinal and brain microvessels (RMVs and BMVs, respectively) from normal and diabetic rats, allowing us to extract highly purified microvessels. In Human umbilical vein endothelial cells this study, we characterized the transcriptional changes Human umbilical vein endothelial cells (HUVECs) were of RMVs andBMVsbydirectcomparisonofisolated purchased from Lonza (Lonza, Breda, The Netherlands) microvessels from diabetic and time-matched control and maintained in EGM-2 media consisting of endothelial rats. We hypothesized that diabetes induces substantially basal medium-2 supplemented with growth factors and different gene expression patterns in these two types of antibiotics (EGM-2 SingleQuots kit, Lonza, The Nether- microvessels even though they are of the same embry- lands). The effect of hyperglycemia on HUVECs was ological origin. We further investigated the balance of investigated by incubating cells in EGM-2 media with possible adverse and beneficial factors and pathways in 30 mM D-glucose. The normal EGM-2 media used as a RMVs and BMVs. Thereafter, these expression profiles control contained 5.5 mM D-glucose. In all experiments, identified by microarray analysis were validated by cells from passage 4 or 5 were used and cultured at 37°C in quantitative RT-PCR while NR4A3 mRNA expression a 5% CO2/95% humidified atmosphere. alteration in response to hyperglycemia was tested in vitro. RNA isolation and assessment Total RNA was isolated from individual RMVs or BMVs Material and methods using a RNeasy Plus Micro kit (Qiagen, Hilden, Ger- many) according to the manufacturer’s instructions. The Animals RNA concentration and integrity were assessed by Agilent 6000 Pico kit (RMVs and BMVs) on an Agilent 2100 The animal study was approved by the Federal Animal bioanalyzer (Agilent Technologies, USA). Only samples Ethics Committee (Karlsruhe, Germany). All experi- with an integrity number (RIN) > 7.0 were used for mi- mental procedures complied with the ethical regula- croarray processing. For HUVECs, total RNA was isolated tions of the Directive 2010/63/EU. Type 1 diabetes using a RNeasy Plus Mini kit (Qiagen, Venlo, The mellitus was induced in male Wistar rats (9 weeks old; Netherlands) according to the manufacturer’s instructions. obtained from Janvier, Isle St- Genest, France) by a tail The concentration and integrity of the RNA was deter- vein injection of Streptozotocin (35 mg/kg body mined using an ND-100 UV-Vis Spectrophotometer weight, Sigma-Aldrich, Germany; prepared in 10 mM (Nanodrop Technologies, Rockland, DE, USA) and by citrate buffer, pH 4.5) and confirmed by casual blood agarose (1%) gel electrophoresis. glucose ≥300 mg/dl. Age-matched control animals received vehicle injection. All animals were housed in cages with a 12-h light/dark cycle and given tap water Microarray processing and data analysis and chow ad libitum. Three months after diabetes in- duction, the rats were deeply anesthetized with CO2 Transcriptome profiles of the BMVs and RMVs were inhalation and then sacrificed. Eyes and brain hemi- determined using the GeneChip WT Pico Reagent Kit spheres that removed meninges and associated vessels, and the whole-transcriptome Rat Gene 2.0 ST array were snapped frozen in liquid nitrogen and stored at (Affymetrix, Inc., Santa Clara, CA, USA) as described 80°C until use. previously. The raw CEL files were normalized using Li et al. 3 the Affymetrix Expression Console Software (version Results 4.0, Affymetrix). The pairwise comparisons of nondia- The body weights and plasma glucose concentrations of the betic and diabetic microvessels were performed with R rats are displayed in Figure 1(a). The streptozotocin- software using LIMMA package (version 3.02; R De- induced diabetic rats show a significantly higher blood velopment Core Team, 2013). The obtained false dis- glucose level and significantly lower body weight com- covery rate (FDR) adjusted p value and fold change (FC) pared to age-matched nondiabetic rats. were used as a cut-off to identify the differentially ex- To investigate the diabetic effects on the gene ex- pressed genes (DEGs). Genes with a FDR adjusted p < pression profiles of retinal microvasculature and brain 0.05 and FC >1.2 were considered statistically signifi- microvasculature, pairwise comparisons were per- cant. The Kyoto Encyclopedia of Genes and Genomes formed: 1) Diabetic RMVs versus nondiabetic RMVs; (KEGG) pathways of DEGs were assessed using DAVID and 2) Diabetic BMVs versus nondiabetic BMVs. Each (https://david.ncifcrf.gov/summary.jsp). The complete group contained 6 non-pooled samples isolated from 6 microarray dataset is available at Gene Expression individual rats. Microarray analysis was used as a dis- Omnibus (GEO) database (http://www.ncbi.nlm.nih. covery step, and the significantly differentially ex- gov/geo/) under the accession number GSE113686 pressed genes (DEGs) were identified by a FDR adjusted p < 0.05 and FC >1.2 compared to nondiabetic samples. Quantitative real-time PCR Quantitative real-time PCR (qRT-PCR) was used for the Differentially expressed genes in retinal and confirmation of microarray data and for quantifying the brain microvasculature expression level of Nr4a3 in HUVECs. Briefly, first-strand In RMVs, 43 genes were significantly changed by the cDNA was generated from RNA samples by a 20 μL streptozotocin-induced diabetes (Figure 1(b)), of which 20 mixture containing SuperScript III RT (Invitrogen, were upregulated and 23 were downregulated (Figure 1(c)). Bleiswijk, the Netherlands), RNase Out inhibitor (40 units; For the BMVs, 35 genes were significantly changed by the Invitrogen) and 250 ng random hexamers (Promega, streptozotocin-induced diabetes (Figure 1(b)). Among Leiden, the Netherlands). 10 ng of cDNAwas used for each these DEGs, 22 genes were upregulated and 13 were PCR reaction. Assays were performed on a ViiA 7 real- downregulated (Figure 1(e)). Hierarchical cluster analysis time PCR System (Applied Biosystems, Nieuwerkerk aan was performed for the DEGs from RMVs and BMVs as den IJssel, The Netherlands) using the absolute QPCR Rox depicted in Figure 2(d) and (f), respectively. When we Mix (Thermo Fischer Scientific). Samples were normalized compared the DEGs of the RMVs and BMVs, only one with ΔCt method using GAPDH as a reference. Fold gene (Slc28a3) overlapped (downregulated) between the change in gene expression versus control was analyzed ΔΔCt 13 RMVs and the BMVs (Figure 1(b)). In Table 1 and 2, the by the 2 method. Rat GAPDH (assay ID detailed information describing the upregulated and Rn01775763_g1), Nars (assay ID Rn01491242_m1), downregulated genes in RMVs and BMVs is displayed. Mars (assay ID Rn01504657_m1), Yars (assay ID Rn01749701_m1), Gars (assay ID Rn01410234_m1), Iars (assay ID Rn01450644_m1), Bcl2 (assay ID Biological pathways Rn99999125_m1), Nqo1 (assay ID Rn00566528_m1), Among the 43 genes of RMVs that were changed under Nqo1 (assay ID Rn00566528_m1), NR4A3 (assay ID Rn01534012_m1), Gpd1 (assay ID Rn00573596_m1), diabetic conditions, the DAVID functional annotation Stc1 (assay ID Rn00579636_m1) and Tsc22d3 (assay analysis identifies three enriched KEGG pathways: (i) the ID Rn00580222_m1) were purchased as Assay-on- aminoacyl-tRNA biosynthesis pathway, including Iars, Yars, Nars, Gars and Mars; (ii) the focal adhesion pathway, Demand from Applied Biosystems (Nieuwekerk a/d including Igf1r, Pdgfra, Bcl2 and Parvb; and (iii) the IJssel, the Netherlands). prostate cancer pathway including Igf1r, Pdgfra and Bcl2 (Table 3). In BMVs, the circadian rhythm pathway in- Statistics cluding Per2, Bhlhe40 and Arntl, was significantly en- riched (Table 3). Statistical analyses and graph plotting were carried out using GraphPad Prism 6.0 (GraphPad Prism Software Inc., CA, USA). Statistical differences were evaluated by Stu- Validation of the microarray data with qRT-PCR dent’s t-test or ANOVA with post hoc comparison using Bonferroni correction. Data are given as mean ± SEM, To confirm the outcome of the microarray analyses, unless stated otherwise. Differences were considered sig- quantitative real-time PCR (qRT-PCR) analyses were nificant at p < 0.05. performed on the same RNA samples as used in the 4 Diabetes & Vascular Disease Research 20(1) Figure 1. Responses of retinal and brain microvasculature to diabetes. (a) Average body weights and plasma glucose concentrations for diabetic (red line) and nondiabetic rats (blue line). Results are means ± SEM, n = 6. *Significantly different from non-diabetic animals. (b) Venn diagram for the significantly changed genes by diabetes in the retinal microvessels (RMV) and brain microvessels (BMVs). Volcano plots of all genes identified from RMVs (c) and BMVs (e). Significant differentially expressed genes (DEGs) are located between the vertical and horizontal dotted lines and are highlighted in red or blue. Heatmaps of the DEGs either from the RMVs (d) or the BMVs (f) are displayed. microarray studies. Seven DEGs (Yars, Mars, Iars, Nars, magnitude of altered expression measured by microarray Gars, Bcl2 and Nqo1) from RMVs and five DEGs and expression measured by qRT-PCR. (NR4A3, Stc1, Gpd1, Tsc22d3 and Tnfrsf21) from BMVs were selected. For individual altered genes of RMVs or Hyperglycemia induced NR4A3 gene upregulation BMVs, results obtained by qRT-PCR are consistent with the microarray findings, in terms of direction and extent It has been reported that NR4A3 is involved in glucose 14–16 (Figure 2). Overall, there is a good and statistically sig- metabolism and NF-κB pathway activation. Under nificant correlation (r = 0.905, n = 24) between the diabetic conditions, expression of NR4A3 mRNA was Li et al. 5 Figure 2. Validation of the microarray data by quantitative RT-PCR. Results for 12 genes are shown, of which seven genes are significantly changed by diabetes in RMVs (a), and five genes are significantly changed in BMVs (b). Microarray and qRT-PCR fold change ΔΔCt values (2 ) were calculated for each gene for comparison between diabetic and nondiabetic samples. Results were shown as mean ± SD (n = 6). significantly increased in BMVs, as measured by micro- exposed to abnormally high glucose concentrations, the array and qRT-PCR (Figure 2). NR4A3 mRNA was brain microvasculature is not noticeably changed. The identified as the gene with the biggest difference between underlying mechanisms are far from clear. In the present RMVs and BMVs (fold change of 2.4 and p < 0.0001). In study, we observe that in diabetes, expression of NAD(P)H HUVECs, NR4A3 gene expression was significantly in- dehydrogenase 1 (Nqo1) and glutathione S-transferase P creased by high glucose in a time-dependent manner (Gstp1) is significantly downregulated in RMVs (Table 1) (Figure 3). while it is not changed in BMVs. It is well documented that that both Nqo1 and Gstp1, enzymes with antioxidant ac- tivity, are pivotal in the intracellular defense mechanisms Discussion 19–21 to counteract ROS productions. In addition, This is the first report in which the effects of diabetes on the Stanniocalcin-1 (Stc-1) and Bhlhe40, enzymes that sup- gene expression pattern of rat retinal microvasculature press superoxide generation and hence protect cells from 22–25 were analyzed by comparing the whole transcriptome ROS-induced damage, are significantly overexpressed between diabetic and nondiabetic RMVs. In parallel, the in BMVs (Table 2). These findings suggest that, in diabetes effects of diabetes on the gene expression pattern of rat the compensatory/protective capacity in BMVs appear to brain microvasculature were also analyzed. This study be enhanced by expression of genes that code for anti- shows that in diabetes, BMVs have different gene ex- oxidants, whereas these are suppressed in RMVs. pression patterns compared to RMVs (e.g., the aminoacyl- Methylglyoxal (MG), a major precursor of advanced tRNA synthetases), which allow for identification of novel glycation end products (AGEs), is highly toxic to tissue targets for protective vascular intervention strategies. and is considered as an important cause of diabetic 26,27 High glucose-induced ROS overproduction has been complications. Its primary source is dihydroxyacetone considered as the principal cause of diabetic microvascular phosphate (DHAP) that is an isomer of glyceraldehyde 2,17,18 damage. Although cerebral endothelial cells are also 3 - phosphate (GAP). Previous studies have shown that 6 Diabetes & Vascular Disease Research 20(1) Table 1. Genes significantly changed by diabetes in the retinal microvessels. Diabetes versus control Transcript ID Gene symbol Description Adj. P FC 17,717,103 Mt1a Metallothionein 1a 0.0168 2.91 17,752,700 Mt1m Metallothionein 1M 0.0156 2.71 17,789,627 Asns Asparagine synthetase 0.0000 2.51 17,756,041 Rnf39 Ring finger protein 39 0.0368 1.87 17,642,026 Aldh18a1 Aldehyde dehydrogenase 18 family, member A1 0.0006 1.72 17,740,865 Ctss Cathepsin S 0.0145 1.60 17,790,133 Pax4 Paired box 4 0.0400 1.55 17,726,760 Nars Asparaginyl-tR synthetase 0.0038 1.52 17,836,518 Mars Methionyl-tR synthetase 0.0034 1.48 17,694,084 Pdgfra PDGF receptor, alpha polypeptide 0.0368 1.47 17,802,403 Yars Tyrosyl-tR synthetase 0.0408 1.42 17,718,250 Tspan17 Tetraspanin 17 0.0400 1.42 17,864,675 Rftn2 Raftlin family member 2 0.0368 1.42 17,791,502 Gars Glycyl-tR synthetase 0.0038 1.39 17,718,501 Iars Isoleucyl-tR synthetase 0.0408 1.38 17,854,693 Chst2 Carbohydrate sulfotransferase 2 0.0485 1.32 17,771,507 Pbx3 Pre-B-cell leukemia homeobox 3 0.0488 1.32 17,617,445 Igf1r Insulin-like growth factor 1 receptor 0.0435 1.29 17,771,351 Stxbp1 Syntaxin-binding protein 1 0.0408 1.23 17,819,788 Map4k3 Mitogen-activated protein kinase kinase kinase kinase 3 0.0395 1.27 17,623,163 Rnaseh2c Ribonuclease H2, subunit C 0.0301 1.28 17,828,801 Sdc2 Syndecan-2 0.0368 1.29 17,639,089 Gstp1 Glutathione S-transferase pi 1 0.0285 1.31 17,788,530 RGD1565588 Similar to calcium binding protein P22 0.0431 1.35 17,731,247 Nrp1 Neuropilin-1 0.0368 1.41 17,831,256 Parvb Parvin, beta 0.0368 1.43 17,683,445 Bcl2 B-cell CLL 0.0100 1.46 17,871,623 Alas2 5-Aminolevulite synthase 2 0.0145 1.47 17,842,577 Ldlr Low density lipoprotein receptor 0.0395 1.48 17,774,787 RGD1564664 Similar to LOC387763 protein 0.0261 1.52 17,733,363 Nqo1 D(P)H dehydrogenase, quinone 1 0.0490 1.54 17,736,949 Dap Death-associated protein 0.0100 1.55 17,646,726 Trim16 Tripartite motif-containing 16 0.0368 1.55 17,714,143 Slc28a3 Solute carrier family 28, member 3 0.0285 1.57 17,693,364 Art3 ADP-ribosyltransferase 3 0.0130 1.66 17,624,116 Slc15a3 Solute carrier family 15, member 3 0.0368 1.68 17,611,535 Myct1 Myc target 1 0.0395 1.72 17,844,192 Slc35f2 Solute carrier family 35, member F2 0.0409 1.83 17,688,703 Cxcl11 Chemokine (C-X-C motif) ligand 11 0.0215 1.99 17,643,730 RGD1565166 Similar to MGC45438 protein 0.0000 2.30 Adj. P, a false discovery rate (FDR) adjusted p value; FC, fold change. hyperglycemia-induced oxidative stress leads to DNA resulting in activation of multiple pathogenic pathways in damage and activation of nuclear poly(ADP-ribose) diabetes, such as activation of protein kinase C (PKC) and an polymerase (PARP, a nuclear DNA repair enzyme), increase of AGEs. In the present study, we observe that in which inhibits the catalytic activity of glyceraldehyde diabetes, expression of glycerol-3-phosphate dehydrogenase 28,29 3-phosphate dehydrogenase (GAPDH). It is suggested 1 (Gpd1) is significantly upregulated in BMVs (Table 2) that as a result the levels of glycolytic metabolites (e.g., MG, while it is not changed in RMVs. Gpd1 is a key enzyme that GAP and DHAP) that are upstream of GAPDH increase, converts DHAP into glycerol-3-phosphate (G3P) with a Li et al. 7 Table 2. Genes significantly changed by diabetes in the brain microvessels. Diabetes versus control Transcript ID Gene symbol Description Adj. P FC 17,686,071 Fmo3 Flavin containing monooxygenase 0.0003 2.45 17,798,725 Nr4a3 Nuclear receptor subfamily 4, group A, member 3 0.0013 2.06 17,666,537 Cldn1 Claudin 1 0.0169 2.03 17,832,266 Gpd1 Glycerol-3-phosphate dehydrogenase 1 (soluble) 0.0055 1.97 17,757,188 Fkbp5 FK506 binding protein 5 0.0092 1.95 17,749,555 Ciart Circadian associated repressor of transcription 0.0070 1.91 17,866,453 Per2 Period circadian clock 2 0.0014 1.91 17,624,812 Slc1a1 Solute carrier family 1 member 1 0.0055 1.88 17,817,653 Tmem63c Transmembrane protein 63c 0.0145 1.80 17,611,443 Mthfd1l Methylenetetrahydrofolate dehydrogenase (NADP + dependent) 1-like 0.0036 1.79 17,699,814 Stc1 Stanniocalcin-1 0.0017 1.73 17,775,237 Fibin Fin bud initiation factor homolog (zebrafish) 0.0038 1.73 17,879,047 Tsc22d3 TSC22 domain family, member 3 0.0247 1.56 17,833,546 Gadd45b Growth arrest and D-damage-inducible, beta 0.0248 1.54 17,616,470 Dbp D site of albumin promoter (albumin D-box) binding protein 0.0118 1.54 17,785,849 Bhlhe40 Basic helix-loop-helix family, member e40 0.0059 1.39 17,837,791 Ndrg1 N-myc downstream regulated 1 0.0222 1.39 17,664,242 LOC680121 Similar to heat shock protein 8 0.0421 1.37 17,847,497 Nat6 N-acetyltransferase 6 (GCN5-related) 0.0128 1.33 17,732,995 Nr3c2 Nuclear receptor subfamily 3, group C, member 2 0.0216 1.27 17,847,732 Dalrd3 DALR anticodon binding domain containing 3 0.0038 1.28 17,863,116 Tnfrsf21 Tumor necrosis factor receptor superfamily, member 21 0.0222 1.29 17,787,500 Nrip2 Nuclear receptor interacting protein 2 0.0247 1.31 17,698,634 Mmp14 Matrix metallopeptidase 14 (membrane-inserted) 0.0122 1.35 17,650,326 Col1a1 Collagen, type I, alpha 1 0.0140 1.41 17,814,505 Pomc Proopiomelanocortin 0.0055 1.43 17,791,733 Gadd45a Growth arrest and D-damage-inducible, alpha 0.0025 1.46 17,714,143 Slc28a3 Solute carrier family 28, member 3 0.0049 1.47 17,645,118 Ccnjl Cyclin J-like 0.0247 1.48 17,866,181 Nmur1 Neuromedin-U receptor 1 0.0025 1.52 17,619,710 Arntl Aryl hydrocarbon receptor nuclear translocator-like 0.0003 1.54 Adj. P, a false discovery rate (FDR) adjusted p value; FC, fold change. Table 3. Pathway identification among the diabetes changed genes in RMVs and BMVs. KEGG pathways Gene symbols p value Fold change In RMVs Aminoacyl-tRNA biosynthesis Iars, yars, nars, gars, mars 5.E05 23 Focal adhesion Igf1r, pdgfra, Bcl2, parvb 3.E02 6 Prostate cancer Igf1r, pdgfra, Bcl2 3.E02 11 In BMVs Circadian rhythm Per2, Bhlhe40, arntl 2.E03 43 The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were obtained using DAVID Functional Annotation tool. RMVs, retinal microvessels; BMVs, brain microvessels. 8 Diabetes & Vascular Disease Research 20(1) playing a crucial role in protein synthesis. In addition, many studies have shown that aaRSs also have multiple noncanonical functions including regulation of glucose metabolism, angiogenesis, inflammation and cell stress 42–45 responses; and aberrant expression or variants of 46–48 aaRSs are involved in various diseases. In this study, we found that the expression of Nars, Gars, Mars, Iars and Yars (5 components of aaRSs) in RMVs were significantly upregulated in diabetes, whereas these genes were not changed in BMVs. Previous studies have shown that oxi- dative stress can cause damage to aaRSs functions, followed 49,50 by amino acid mistranslation and protein misfolding. We speculate that the upregulation of aaRSs genes in RMVs is caused by the hyperglycemia-induced ROS overproduc- Figure 3. The effect of high glucose on NR4A3 gene expression tion, which in turn affects the reliability of protein translation in human umbilical vein endothelial cells (HUVECs). Cells were in RMVs. cultured with 5.5 mm (control) or 30 mm (HG) D-glucose for Clearly, functional and mechanistic studies are neces- 96 h. The HG-treated cells were divided into four distinct groups sary to substantiate the complex processes and the precise based on the duration of the high glucose exposure. Experiments were repeated in triplicates with different cell effects of the discussed gene expression patterns in BMV preparations. mRNA fold change is relative to controls while and RMV in diabetes. Nevertheless, our study suggests that using GAPDH expression as a reference. Results are given as BMVs have defense mechanisms including reduction of mean ± SEM, n = 9. *Significantly different from the control. ROS production, reduction of glycolytic intermediates and enlarged anti-inflammatory capacity, against the detri- + 30 decrease in the NADH/NAD ratio. This process can mental effects of diabetes. In contrast, in RMV these reduce cellular concentration of DHAP and prevent the protective systems are not activated or even suppressed, spontaneous conversion of DHAP into MG. The over- resulting in a diminished ability to balance the potentially expression of Gpd1 in BMVs may protect the brain mi- toxic factors that are induced by diabetes. These findings crovasculature against toxic glycolytic metabolites-induced will increase our knowledge and understanding of the injuries. mechanisms playing a role in the different susceptibilities High glucose-induced activation of the nuclear factor to diabetes of microvessels in retina and brain and may (NF)-κB pathway in vascular cells is also a key contributor pave the way to the discovery of novel treatments to in- 4,32–34 to the pathogenesis of diabetic complications. Here, tervene in diabetic-induced microvascular complications. we observe that in diabetes the expression of Tnfrsf21 (TNF receptor superfamily member 21) in BMVs is sig- Acknowledgements nificantly decreased by diabetes (Table 2). Tnfrsf21 acti- The authors would like to thank Henk E. Moorlag for technical vates the NF-κB pathway and triggers cell apoptosis. In assistance with culture of HUVECs. We thank Peter J. Zwiers, addition, we further observe that in diabetes, expression of J.A. Plantinga and R. Yan for providing technical support in the neuron-derived orphan receptor 1 (Nr4a3) and TSC22 RT-qPCR experiments. We also thank the Endothelial Cell facility domain family protein 3 (Tsc22d3) in BMVs is signifi- of University Medical Center Groningen for providing the en- cantly increased (Table 2) while it is not changed in RMVs. dothelial cells. It has been demonstrated that both Nr4a3 and Tsc22d3 exhibit anti-apoptotic effects through prevention of NF-κB 14,36,37 pathway activation. Expression of Nr4a3 plays also 38,39 Declaration of conflicting interests a critical role in neuronal protection. Badrichani AZ, et al. reported that expression of B-cell lymphoma 2 (Bcl-2, The author(s) declared no potential conflicts of interest with re- an important anti-apoptotic protein) protects endothelial spect to the research, authorship, and/or publication of this article. cells from TNF-induced apoptosis through inhibition of the NF-κB pathway. In diabetes, expression of Bcl-2 in Funding RMVs is significantly decreased (Table 1) while it is not The author(s) disclosed receipt of the following financial support for changed in BMVs. The anti-inflammatory mechanism in the research, authorship, and/or publication of this article: This work BMVs seems to be enhanced by inhibition of the NF-κB was partly supported by the Deutsche Forschungsgemeinschaft pathway whereas it might be suppressed in RMVs. (1874-1 DIAMICOM). Faiz A was funded by the Longfonds Junior Aminoacyl-tRNA synthetases (aaRSs) catalyze the li- Investigators grant (4.2.16.132JO). gation of amino acids to their cognate tRNAs, thereby Li et al. 9 ´ ´ Author notes 14. Calvayrac O, Rodrıguez-Calvo R, Martı-Pamies I, et al. NOR-1 modulates the inflammatory response of vascular Li Y. was an associate member of the International Research smooth muscle cells by preventing NFκB activation. J Mol Training group (1874-1 DIAMICOM) and received a scholarship Cell Cardiol 2015; 80: 34–44. under the CIMDS program from the Medical Faculty Mannheim, 15. Fu Y, Luo L, Luo N, et al. NR4A orphan nuclear receptors Heidelberg University. modulate insulin action and the glucose transport system: potential role in insulin resistance. J Biol Chem 2007; ORCID iD 282(43): 31525–31533. 16. Medunjanin S, Daniel JM, Weinert S, et al. DNA-dependent Jan AAM Kamps  https://orcid.org/0000-0002-2066-0140 protein kinase (DNA-PK) permits vascular smooth muscle cell proliferation through phosphorylation of the orphan References nuclear receptor NOR1. Cardiovasc Res 2015; 106(3): 1. Forbes JM and Cooper ME. Mechanisms of diabetic com- 488–497. plications. Physiol Rev 2013; 93(1): 137–188. 17. Naudi A, Jove M, Ayala V, et al. Cellular dysfunction in 2. Brownlee M. Biochemistry and molecular cell biology of diabetes as maladaptive response to mitochondrial oxidative diabetic complications. Nature 2001; 414(6865): 813–820. stress. Exp Diabetes Res 2012; 2012: 696215. 3. Kowluru RA and Chan PS. Oxidative stress and diabetic 18. Giacco F and Brownlee M. Oxidative stress and diabetic retinopathy. Exp Diabetes Res 2007; 2007: 43603. complications. Circ Res 2010; 107(9): 1058–1070. 4. Rask-Madsen C and King GL. Vascular complications of 19. Jiang T, Huang Z, Lin Y, et al. The protective role of Nrf2 in diabetes: mechanisms of injury and protective factors. Cell streptozotocin-induced diabetic nephropathy. Diabetes 2010; Metab 2013; 17(1): 20–33. 59(4): 850–860. 5. Badr GA, Tang J, Ismail-Beigi F, et al. Diabetes down- 20. Xu Z, Wei Y, Gong J, et al. NRF2 plays a protective role in regulates GLUT1 expression in the retina and its micro- diabetic retinopathy in mice. Diabetologia 2014; 57(1): vessels but not in the cerebral cortex or its microvessels. 204–213. Diabetes 2000; 49(6): 1016–1021. 21. Gorrini C, Harris IS and Mak TW. Modulation of oxidative 6. Dai J, Vrensen GFJM and Schlingemann RO. Blood-brain stress as an anticancer strategy. Nat Rev Drug Discov 2013; barrier integrity is unaltered in human brain cortex with 12(12): 931–947. diabetes mellitus. Brain Res 2002; 954(2): 311–316. 22. Takeshita S, Suzuki T, Kitayama S, et al. Bhlhe 40, a po- 7. Rosenblum WI and Levasseur JE. Microvascular responses tential diabetic modifier gene on Dbm1 locus, negatively of intermediate-size arterioles on the cerebral surface of controls myocyte fatty acid oxidation. Genes Genet Syst diabetic mice. Microvasc Res 1984; 28(3): 368–372. 2012; 87(4): 253–264. 8. Joussen AM, Huang S, Poulaki V, et al. In vivo retinal gene 23. Chung SY, Kao CH, Villarroya F, et al. Bhlhe 40 Represses expression in early diabetes. Invest Ophthalmol Vis Sci 2001; PGC-1α Activity on Metabolic Gene Promoters in Myogenic 42(12): 3047–3057. Cells. Mol Cell Biol 2015; 35(14): 2518–2529. 9. Quin GJ, Len ACL, Billson FA, et al. Proteome map of 24. Pan JSC, Huang L, Belousova T, et al. Stanniocalcin-1 in- normal rat retina and comparison with the proteome of di- hibits renal ischemia/reperfusion injury via an AMP- abetic rat retina: new insight in the pathogenesis of diabetic activated protein kinase-dependent pathway. J Am Soc retinopathy. Proteomics 2007; 7(15): 2636–2650. Nephrol 2015; 26(2): 364–378. 10. Kandpal RP, Rajasimha HK, Brooks MJ, et al. Transcriptome 25. Liu D, Huang L, Wang Y, et al. Human stanniocalcin-1 analysis using next generation sequencing reveals molecular suppresses angiotensin II-induced superoxide generation in signatures of diabetic retinopathy and efficacy of candidate cardiomyocytes through UCP3-mediated anti-oxidant drugs. Mol Vis 2012; 18: 1123–1146. pathway. PLoS One 2012; 7(5): e36994. 11. Li Y, Lapina N, Weinzierl N, et al. A novel method to isolate 26. Wang J, Lin J, Schlotterer A, et al. CD74 indicates microglial retinal and brain microvessels from individual rats: Micro- activation in experimental diabetic retinopathy and exoge- scopic and molecular biological characterization and ap- nous methylglyoxal mimics the response in normoglycemic plication in hyperglycemic animals. Vascul Pharmacol 2018; retina. Acta Diabetol 2014; 51(5): 813–821. 110: 24–30. 27. Rabbani N and Thornalley PJ. The critical role of methyl- 12. Li Y, Faiz A, Moshage H, et al. Comparative transcriptome glyoxal and glyoxalase 1 in diabetic nephropathy. Diabetes analysis of inner blood-retinal barrier and blood-brain barrier 2014; 63(1): 50–52. in rats. Sci Rep 2021; 11(1): 12151. 28. Kanwar M and Kowluru RA. Role of glyceraldehyde 3- 13. Livak KJ and Schmittgen TD. Analysis of relative gene phosphate dehydrogenase in the development and progres- expression data using real-time quantitative PCR and the sion of diabetic retinopathy. Diabetes 2009; 58(1): 227–234. 2(Delta Delta C(T)) Method. Methods 2001; 25(4): 29. Du X, Matsumura T, Edelstein D, et al. Inhibition of GAPDH 402–408. activity by poly (ADP-ribose) polymerase activates three 10 Diabetes & Vascular Disease Research 20(1) major pathways of hyperglycemic damage in endothelial 40. Badrichani AZ, Stroka DM, Bilbao G, et al. Bcl-2 and Bcl- cells. J Clin Invest 2003; 112(7): 1049–1057. XL serve an anti-inflammatory function in endothelial cells 30. Shen W, Wei Y, Dauk M, et al. Involvement of a glycerol-3- through inhibition of NF-kappaB. J Clin Invest 1999; 103(4): phosphate dehydrogenase in modulating the NADH/NAD+ 543–553. ratio provides evidence of a mitochondrial glycerol-3- 41. Brown MV, Reader JS and Tzima E. Mammalian aminoacyl- phosphate shuttle in Arabidopsis. Plant Cell 2006; 18(2): tRNA synthetases: cell signaling functions of the protein 422–441. translation machinery. Vascul Pharmacol 2010; 52(1–2): 31. Kumar S, Singh R, Williams CP, et al. Stress exposure results 21–26. in increased peroxisomal levels of yeast Pnc1 and Gpd1, 42. Guo M and Schimmel P. Essential nontranslational functions which are imported via a piggy-backing mechanism. Bio- of tRNA synthetases. Nat Chem Biol 2013; 9(3): 145–153. chim Biophys Acta 2016; 1863(1): 148–156. 43. Guo M and Schimmel P. Homeostatic mechanisms by al- 32. Romeo G, Liu WH, Asnaghi V, et al. Activation of nuclear ternative forms of tRNA synthetases. Trends Biochem Sci factor-kappaB induced by diabetes and high glucose regu- 2012; 37(10): 401–403. lates a proapoptotic program in retinal pericytes. Diabetes 44. Guo M, Yang XL and Schimmel P. New functions of 2002; 51(7): 2241–2248. aminoacyl-tRNA synthetases beyond translation. In: Vol. 33. Hattori Y, Hattori S, Sato N, et al. High-glucose-induced 11, nature reviews. Molecular Cell Biology, 2010, pp. nuclear factor kappaB activation in vascular smooth muscle 668–674. cells. Cardiovasc Res 2000; 46(1): 188–197. 45. Park SG, Kim HJ, Min YH, et al. Human lysyl-tRNA 34. Aveleira CA, Lin CM, Abcouwer SF, et al. TNF-α signals synthetase is secreted to trigger proinflammatory re- through PKCζ/NF-κB to alter the tight junction complex and sponse. Proc Natl Acad Sci U S A 2005; 102(18): increase retinal endothelial cell permeability. Diabetes 2010; 6356–6361. 59(11): 2872–2882. 46. Park SG, Schimmel P and Kim S. Aminoacyl tRNA syn- 35. Pan G, Bauer JH, Haridas V, et al. Identification and thetases and their connections to disease. Proc Natl Acad Sci functional characterization of DR6, a novel death domain- USA 2008; 105(32): 11043–11049. containing TNF receptor. FEBS Lett 1998; 431(3): 351–356. 47. T Hart LM, Hansen T, Rietveld I, et al. Evidence that the 36. Cheng Q, Fan H, Ngo D, et al. GILZ overexpression inhibits mitochondrial leucyl tRNA synthetase (LARS2) gene rep- endothelial cell adhesive function through regulation of NF- resents a novel type 2 diabetes susceptibility gene. Diabetes κB and MAPK activity. J Immunol 2013; 191(1): 424–433. 2005; 54(6): 1892–1895. 37. Lee MJ, Yang RZ, Karastergiou K, et al. Low expression of 48. Kim BH, Jung WY, Lee H, et al. Lysyl-tRNA synthetase the GILZ may contribute to adipose inflammation and altered (KRS) expression in gastric carcinoma and tumor- adipokine production in human obesity. J Lipid Res 2016; associated inflammation. Ann Surg Oncol 2014; 21(6): 57(7): 1256–1263. 2020–2027. 38. Volakakis N, Kadkhodaei B, Joodmardi E, et al. NR4A 49. Netzer N, Goodenbour JM, David A, et al. Innate immune orphan nuclear receptors as mediators of CREB-dependent and chemically triggered oxidative stress modifies transla- neuroprotection. Proc Natl Acad Sci U S A 2010; 107(27): tional fidelity. Nature 2009; 462(7272): 522–526. 12317–12322. 50. Ling J and Soll ¨ D. Severe oxidative stress induces protein 39. Ponni ¨ o¨ T and Conneely OM. nor-1 regulates hippocampal mistranslation through impairment of an aminoacyl-tRNA axon guidance, pyramidal cell survival, and seizure sus- synthetase editing site. Proc Natl Acad Sci USA 2010; ceptibility. Mol Cell Biol 2004; 24(20): 9070–9078. 107(9): 4028–4033. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Diabetes and Vascular Disease Research SAGE

Responses of retinal and brain microvasculature to streptozotocin induced diabetes revealed by global expression profiling

Download PDF
10 pages

Loading next page...
 
/lp/sage/responses-of-retinal-and-brain-microvasculature-to-streptozotocin-2VBymozJpk

References (102)

Publisher
SAGE
Copyright
© The Author(s) 2023
ISSN
1479-1641
eISSN
1752-8984
DOI
10.1177/14791641221147533
Publisher site
See Article on Publisher Site

Abstract

This study aims to determine the effects of diabetes in the retinal and brain microvasculature through gene expression profiling. Twelve male Wistar rats were randomly divided into two groups: streptozotocin-induced diabetic rats and time- matched nondiabetic rats. The retinal microvessels (RMVs) and brain microvessels (BMVs) were mechanically isolated from individual rats. Differentially expressed genes (DEGs) in diabetic and nondiabetic microvessels were identified by cDNA microarrays analysis. In RMVs, we identified 43 DEGs, of which 20 were upregulated while 23 were downregulated by diabetes. In BMVs, 35 genes DEGs were identified, of which 22 were upregulated and 13 were downregulated by diabetes. Altered expression of the Nars, Gars, Mars, Iars, Yars, Bcl2, Nqo1, NR4A3, Gpd1, Stc1, Tsc22d3, Tnfrsf21 mRNA as observed in the microarray analyses, was confirmed by quantitative RT-PCR. The aminoacyl-tRNA synthetases (aaRSs) pathway in RMVs was significantly overrepresented as compared to BMVs. Our study demonstrates for the first time that in the brain microvasculature multiple compensatory mechanisms exists, serving to protect brain tissue from diabetic insults, whereas these mechanisms are not activated in the retinal microvasculature. This provides new insights as to why brain microvasculature is less susceptible to diabetes. Keywords Retina, brain, diabetes, microvasculature, gene expression profiling mechanisms of diabetic microvascular complications. Introduction Researchers claimed that the molecular imbalance be- Diabetes is a progressive metabolic disease characterized tween toxic and endogenous protective factors may be by hyperglycemia due to absolute or relative (resistance) insulin deficiency, and the development of chronic vascular damage in retina, kidney and peripheral nerves. Over the Division of Neurosurgical Research, Heidelberg University, Mannheim, Germany; European Center of Angioscience, Medical Faculty past decades, multiple molecular mechanisms have been Mannheim, Heidelberg University, Mannheim, Germany proposed to explain the pathogenesis of diabetic vascular Department of Pathology and Medical Biology, University Medical Center injury, e.g., overproduction of reactive oxygen species Groningen, Groningen, The Netherlands (ROS) in mitochondria and NF-κB pathway activation in Department of Gastroenterology and Hepatology, University Medical 2,3 endothelial cells. Despite extensive research, until now Center Groningen, Groningen, The Netherlands there are no effective therapies for preventing diabetic Corresponding author: vascular complications. Jan AAM Kamps, Department of Pathology and Medical Biology, Heretofore, most studies have focused on the highly University of Groningen, University Medical Center Groningen, susceptible organs in diabetes, such as retinae, kidney Hanzeplein 1 (EA11), 9713GZ Groningen, The Netherlands. and peripheral nerves, to identify key molecular Email: j.a.a.m.kamps@umcg.nl Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/ en-us/nam/open-access-at-sage). 2 Diabetes & Vascular Disease Research 20(1) responsible for the pathogenesis of diabetic microvas- Isolation of brain and retinal microvessels cular complications. A wealth of studies reported that The rat RMVs and BMVs were isolated as described brain microvasculature was less susceptible to diabetes 5–7 previously. Briefly, brain and retinal crysections were compared to retinal microvasculature. However, the individually homogenized using a motor-driven homoge- underlying molecular mechanisms involved in this dif- nizer (Homgen plus, Schuett Biotec, Goettingen, Ger- ference is poorly understood. many). The brain homogenate was centrifuged at 438g for Many research efforts to elucidate the molecular 10min, followed by centrifugation at 4400g for 15min, mechanisms of diabetic retinopathy (DR) by assessing after which the pellet was resuspended into 7 mL PBS/1% the genomic and/or proteomic profiles of the entire retina 8–10 dextran (Dextran 70,000, Roth). Thereafter, the brain and tissue. However, these findings might be inaccurate retinal suspension were individually transferred onto a for explaining the molecular mechanisms of diabetic density gradient column and centrifuged for 15 min vascular impairments because of the presence of an (1300 g). Finally, the microvessels were captured after excess nonvascular tissue in whole organ analysis. Re- filtration over a 60 µm nylon mesh. All the procedures were cently, we have established a new mechanical isolation performed at 0°C. method for both retinal and brain microvessels (RMVs and BMVs, respectively) from normal and diabetic rats, allowing us to extract highly purified microvessels. In Human umbilical vein endothelial cells this study, we characterized the transcriptional changes Human umbilical vein endothelial cells (HUVECs) were of RMVs andBMVsbydirectcomparisonofisolated purchased from Lonza (Lonza, Breda, The Netherlands) microvessels from diabetic and time-matched control and maintained in EGM-2 media consisting of endothelial rats. We hypothesized that diabetes induces substantially basal medium-2 supplemented with growth factors and different gene expression patterns in these two types of antibiotics (EGM-2 SingleQuots kit, Lonza, The Nether- microvessels even though they are of the same embry- lands). The effect of hyperglycemia on HUVECs was ological origin. We further investigated the balance of investigated by incubating cells in EGM-2 media with possible adverse and beneficial factors and pathways in 30 mM D-glucose. The normal EGM-2 media used as a RMVs and BMVs. Thereafter, these expression profiles control contained 5.5 mM D-glucose. In all experiments, identified by microarray analysis were validated by cells from passage 4 or 5 were used and cultured at 37°C in quantitative RT-PCR while NR4A3 mRNA expression a 5% CO2/95% humidified atmosphere. alteration in response to hyperglycemia was tested in vitro. RNA isolation and assessment Total RNA was isolated from individual RMVs or BMVs Material and methods using a RNeasy Plus Micro kit (Qiagen, Hilden, Ger- many) according to the manufacturer’s instructions. The Animals RNA concentration and integrity were assessed by Agilent 6000 Pico kit (RMVs and BMVs) on an Agilent 2100 The animal study was approved by the Federal Animal bioanalyzer (Agilent Technologies, USA). Only samples Ethics Committee (Karlsruhe, Germany). All experi- with an integrity number (RIN) > 7.0 were used for mi- mental procedures complied with the ethical regula- croarray processing. For HUVECs, total RNA was isolated tions of the Directive 2010/63/EU. Type 1 diabetes using a RNeasy Plus Mini kit (Qiagen, Venlo, The mellitus was induced in male Wistar rats (9 weeks old; Netherlands) according to the manufacturer’s instructions. obtained from Janvier, Isle St- Genest, France) by a tail The concentration and integrity of the RNA was deter- vein injection of Streptozotocin (35 mg/kg body mined using an ND-100 UV-Vis Spectrophotometer weight, Sigma-Aldrich, Germany; prepared in 10 mM (Nanodrop Technologies, Rockland, DE, USA) and by citrate buffer, pH 4.5) and confirmed by casual blood agarose (1%) gel electrophoresis. glucose ≥300 mg/dl. Age-matched control animals received vehicle injection. All animals were housed in cages with a 12-h light/dark cycle and given tap water Microarray processing and data analysis and chow ad libitum. Three months after diabetes in- duction, the rats were deeply anesthetized with CO2 Transcriptome profiles of the BMVs and RMVs were inhalation and then sacrificed. Eyes and brain hemi- determined using the GeneChip WT Pico Reagent Kit spheres that removed meninges and associated vessels, and the whole-transcriptome Rat Gene 2.0 ST array were snapped frozen in liquid nitrogen and stored at (Affymetrix, Inc., Santa Clara, CA, USA) as described 80°C until use. previously. The raw CEL files were normalized using Li et al. 3 the Affymetrix Expression Console Software (version Results 4.0, Affymetrix). The pairwise comparisons of nondia- The body weights and plasma glucose concentrations of the betic and diabetic microvessels were performed with R rats are displayed in Figure 1(a). The streptozotocin- software using LIMMA package (version 3.02; R De- induced diabetic rats show a significantly higher blood velopment Core Team, 2013). The obtained false dis- glucose level and significantly lower body weight com- covery rate (FDR) adjusted p value and fold change (FC) pared to age-matched nondiabetic rats. were used as a cut-off to identify the differentially ex- To investigate the diabetic effects on the gene ex- pressed genes (DEGs). Genes with a FDR adjusted p < pression profiles of retinal microvasculature and brain 0.05 and FC >1.2 were considered statistically signifi- microvasculature, pairwise comparisons were per- cant. The Kyoto Encyclopedia of Genes and Genomes formed: 1) Diabetic RMVs versus nondiabetic RMVs; (KEGG) pathways of DEGs were assessed using DAVID and 2) Diabetic BMVs versus nondiabetic BMVs. Each (https://david.ncifcrf.gov/summary.jsp). The complete group contained 6 non-pooled samples isolated from 6 microarray dataset is available at Gene Expression individual rats. Microarray analysis was used as a dis- Omnibus (GEO) database (http://www.ncbi.nlm.nih. covery step, and the significantly differentially ex- gov/geo/) under the accession number GSE113686 pressed genes (DEGs) were identified by a FDR adjusted p < 0.05 and FC >1.2 compared to nondiabetic samples. Quantitative real-time PCR Quantitative real-time PCR (qRT-PCR) was used for the Differentially expressed genes in retinal and confirmation of microarray data and for quantifying the brain microvasculature expression level of Nr4a3 in HUVECs. Briefly, first-strand In RMVs, 43 genes were significantly changed by the cDNA was generated from RNA samples by a 20 μL streptozotocin-induced diabetes (Figure 1(b)), of which 20 mixture containing SuperScript III RT (Invitrogen, were upregulated and 23 were downregulated (Figure 1(c)). Bleiswijk, the Netherlands), RNase Out inhibitor (40 units; For the BMVs, 35 genes were significantly changed by the Invitrogen) and 250 ng random hexamers (Promega, streptozotocin-induced diabetes (Figure 1(b)). Among Leiden, the Netherlands). 10 ng of cDNAwas used for each these DEGs, 22 genes were upregulated and 13 were PCR reaction. Assays were performed on a ViiA 7 real- downregulated (Figure 1(e)). Hierarchical cluster analysis time PCR System (Applied Biosystems, Nieuwerkerk aan was performed for the DEGs from RMVs and BMVs as den IJssel, The Netherlands) using the absolute QPCR Rox depicted in Figure 2(d) and (f), respectively. When we Mix (Thermo Fischer Scientific). Samples were normalized compared the DEGs of the RMVs and BMVs, only one with ΔCt method using GAPDH as a reference. Fold gene (Slc28a3) overlapped (downregulated) between the change in gene expression versus control was analyzed ΔΔCt 13 RMVs and the BMVs (Figure 1(b)). In Table 1 and 2, the by the 2 method. Rat GAPDH (assay ID detailed information describing the upregulated and Rn01775763_g1), Nars (assay ID Rn01491242_m1), downregulated genes in RMVs and BMVs is displayed. Mars (assay ID Rn01504657_m1), Yars (assay ID Rn01749701_m1), Gars (assay ID Rn01410234_m1), Iars (assay ID Rn01450644_m1), Bcl2 (assay ID Biological pathways Rn99999125_m1), Nqo1 (assay ID Rn00566528_m1), Among the 43 genes of RMVs that were changed under Nqo1 (assay ID Rn00566528_m1), NR4A3 (assay ID Rn01534012_m1), Gpd1 (assay ID Rn00573596_m1), diabetic conditions, the DAVID functional annotation Stc1 (assay ID Rn00579636_m1) and Tsc22d3 (assay analysis identifies three enriched KEGG pathways: (i) the ID Rn00580222_m1) were purchased as Assay-on- aminoacyl-tRNA biosynthesis pathway, including Iars, Yars, Nars, Gars and Mars; (ii) the focal adhesion pathway, Demand from Applied Biosystems (Nieuwekerk a/d including Igf1r, Pdgfra, Bcl2 and Parvb; and (iii) the IJssel, the Netherlands). prostate cancer pathway including Igf1r, Pdgfra and Bcl2 (Table 3). In BMVs, the circadian rhythm pathway in- Statistics cluding Per2, Bhlhe40 and Arntl, was significantly en- riched (Table 3). Statistical analyses and graph plotting were carried out using GraphPad Prism 6.0 (GraphPad Prism Software Inc., CA, USA). Statistical differences were evaluated by Stu- Validation of the microarray data with qRT-PCR dent’s t-test or ANOVA with post hoc comparison using Bonferroni correction. Data are given as mean ± SEM, To confirm the outcome of the microarray analyses, unless stated otherwise. Differences were considered sig- quantitative real-time PCR (qRT-PCR) analyses were nificant at p < 0.05. performed on the same RNA samples as used in the 4 Diabetes & Vascular Disease Research 20(1) Figure 1. Responses of retinal and brain microvasculature to diabetes. (a) Average body weights and plasma glucose concentrations for diabetic (red line) and nondiabetic rats (blue line). Results are means ± SEM, n = 6. *Significantly different from non-diabetic animals. (b) Venn diagram for the significantly changed genes by diabetes in the retinal microvessels (RMV) and brain microvessels (BMVs). Volcano plots of all genes identified from RMVs (c) and BMVs (e). Significant differentially expressed genes (DEGs) are located between the vertical and horizontal dotted lines and are highlighted in red or blue. Heatmaps of the DEGs either from the RMVs (d) or the BMVs (f) are displayed. microarray studies. Seven DEGs (Yars, Mars, Iars, Nars, magnitude of altered expression measured by microarray Gars, Bcl2 and Nqo1) from RMVs and five DEGs and expression measured by qRT-PCR. (NR4A3, Stc1, Gpd1, Tsc22d3 and Tnfrsf21) from BMVs were selected. For individual altered genes of RMVs or Hyperglycemia induced NR4A3 gene upregulation BMVs, results obtained by qRT-PCR are consistent with the microarray findings, in terms of direction and extent It has been reported that NR4A3 is involved in glucose 14–16 (Figure 2). Overall, there is a good and statistically sig- metabolism and NF-κB pathway activation. Under nificant correlation (r = 0.905, n = 24) between the diabetic conditions, expression of NR4A3 mRNA was Li et al. 5 Figure 2. Validation of the microarray data by quantitative RT-PCR. Results for 12 genes are shown, of which seven genes are significantly changed by diabetes in RMVs (a), and five genes are significantly changed in BMVs (b). Microarray and qRT-PCR fold change ΔΔCt values (2 ) were calculated for each gene for comparison between diabetic and nondiabetic samples. Results were shown as mean ± SD (n = 6). significantly increased in BMVs, as measured by micro- exposed to abnormally high glucose concentrations, the array and qRT-PCR (Figure 2). NR4A3 mRNA was brain microvasculature is not noticeably changed. The identified as the gene with the biggest difference between underlying mechanisms are far from clear. In the present RMVs and BMVs (fold change of 2.4 and p < 0.0001). In study, we observe that in diabetes, expression of NAD(P)H HUVECs, NR4A3 gene expression was significantly in- dehydrogenase 1 (Nqo1) and glutathione S-transferase P creased by high glucose in a time-dependent manner (Gstp1) is significantly downregulated in RMVs (Table 1) (Figure 3). while it is not changed in BMVs. It is well documented that that both Nqo1 and Gstp1, enzymes with antioxidant ac- tivity, are pivotal in the intracellular defense mechanisms Discussion 19–21 to counteract ROS productions. In addition, This is the first report in which the effects of diabetes on the Stanniocalcin-1 (Stc-1) and Bhlhe40, enzymes that sup- gene expression pattern of rat retinal microvasculature press superoxide generation and hence protect cells from 22–25 were analyzed by comparing the whole transcriptome ROS-induced damage, are significantly overexpressed between diabetic and nondiabetic RMVs. In parallel, the in BMVs (Table 2). These findings suggest that, in diabetes effects of diabetes on the gene expression pattern of rat the compensatory/protective capacity in BMVs appear to brain microvasculature were also analyzed. This study be enhanced by expression of genes that code for anti- shows that in diabetes, BMVs have different gene ex- oxidants, whereas these are suppressed in RMVs. pression patterns compared to RMVs (e.g., the aminoacyl- Methylglyoxal (MG), a major precursor of advanced tRNA synthetases), which allow for identification of novel glycation end products (AGEs), is highly toxic to tissue targets for protective vascular intervention strategies. and is considered as an important cause of diabetic 26,27 High glucose-induced ROS overproduction has been complications. Its primary source is dihydroxyacetone considered as the principal cause of diabetic microvascular phosphate (DHAP) that is an isomer of glyceraldehyde 2,17,18 damage. Although cerebral endothelial cells are also 3 - phosphate (GAP). Previous studies have shown that 6 Diabetes & Vascular Disease Research 20(1) Table 1. Genes significantly changed by diabetes in the retinal microvessels. Diabetes versus control Transcript ID Gene symbol Description Adj. P FC 17,717,103 Mt1a Metallothionein 1a 0.0168 2.91 17,752,700 Mt1m Metallothionein 1M 0.0156 2.71 17,789,627 Asns Asparagine synthetase 0.0000 2.51 17,756,041 Rnf39 Ring finger protein 39 0.0368 1.87 17,642,026 Aldh18a1 Aldehyde dehydrogenase 18 family, member A1 0.0006 1.72 17,740,865 Ctss Cathepsin S 0.0145 1.60 17,790,133 Pax4 Paired box 4 0.0400 1.55 17,726,760 Nars Asparaginyl-tR synthetase 0.0038 1.52 17,836,518 Mars Methionyl-tR synthetase 0.0034 1.48 17,694,084 Pdgfra PDGF receptor, alpha polypeptide 0.0368 1.47 17,802,403 Yars Tyrosyl-tR synthetase 0.0408 1.42 17,718,250 Tspan17 Tetraspanin 17 0.0400 1.42 17,864,675 Rftn2 Raftlin family member 2 0.0368 1.42 17,791,502 Gars Glycyl-tR synthetase 0.0038 1.39 17,718,501 Iars Isoleucyl-tR synthetase 0.0408 1.38 17,854,693 Chst2 Carbohydrate sulfotransferase 2 0.0485 1.32 17,771,507 Pbx3 Pre-B-cell leukemia homeobox 3 0.0488 1.32 17,617,445 Igf1r Insulin-like growth factor 1 receptor 0.0435 1.29 17,771,351 Stxbp1 Syntaxin-binding protein 1 0.0408 1.23 17,819,788 Map4k3 Mitogen-activated protein kinase kinase kinase kinase 3 0.0395 1.27 17,623,163 Rnaseh2c Ribonuclease H2, subunit C 0.0301 1.28 17,828,801 Sdc2 Syndecan-2 0.0368 1.29 17,639,089 Gstp1 Glutathione S-transferase pi 1 0.0285 1.31 17,788,530 RGD1565588 Similar to calcium binding protein P22 0.0431 1.35 17,731,247 Nrp1 Neuropilin-1 0.0368 1.41 17,831,256 Parvb Parvin, beta 0.0368 1.43 17,683,445 Bcl2 B-cell CLL 0.0100 1.46 17,871,623 Alas2 5-Aminolevulite synthase 2 0.0145 1.47 17,842,577 Ldlr Low density lipoprotein receptor 0.0395 1.48 17,774,787 RGD1564664 Similar to LOC387763 protein 0.0261 1.52 17,733,363 Nqo1 D(P)H dehydrogenase, quinone 1 0.0490 1.54 17,736,949 Dap Death-associated protein 0.0100 1.55 17,646,726 Trim16 Tripartite motif-containing 16 0.0368 1.55 17,714,143 Slc28a3 Solute carrier family 28, member 3 0.0285 1.57 17,693,364 Art3 ADP-ribosyltransferase 3 0.0130 1.66 17,624,116 Slc15a3 Solute carrier family 15, member 3 0.0368 1.68 17,611,535 Myct1 Myc target 1 0.0395 1.72 17,844,192 Slc35f2 Solute carrier family 35, member F2 0.0409 1.83 17,688,703 Cxcl11 Chemokine (C-X-C motif) ligand 11 0.0215 1.99 17,643,730 RGD1565166 Similar to MGC45438 protein 0.0000 2.30 Adj. P, a false discovery rate (FDR) adjusted p value; FC, fold change. hyperglycemia-induced oxidative stress leads to DNA resulting in activation of multiple pathogenic pathways in damage and activation of nuclear poly(ADP-ribose) diabetes, such as activation of protein kinase C (PKC) and an polymerase (PARP, a nuclear DNA repair enzyme), increase of AGEs. In the present study, we observe that in which inhibits the catalytic activity of glyceraldehyde diabetes, expression of glycerol-3-phosphate dehydrogenase 28,29 3-phosphate dehydrogenase (GAPDH). It is suggested 1 (Gpd1) is significantly upregulated in BMVs (Table 2) that as a result the levels of glycolytic metabolites (e.g., MG, while it is not changed in RMVs. Gpd1 is a key enzyme that GAP and DHAP) that are upstream of GAPDH increase, converts DHAP into glycerol-3-phosphate (G3P) with a Li et al. 7 Table 2. Genes significantly changed by diabetes in the brain microvessels. Diabetes versus control Transcript ID Gene symbol Description Adj. P FC 17,686,071 Fmo3 Flavin containing monooxygenase 0.0003 2.45 17,798,725 Nr4a3 Nuclear receptor subfamily 4, group A, member 3 0.0013 2.06 17,666,537 Cldn1 Claudin 1 0.0169 2.03 17,832,266 Gpd1 Glycerol-3-phosphate dehydrogenase 1 (soluble) 0.0055 1.97 17,757,188 Fkbp5 FK506 binding protein 5 0.0092 1.95 17,749,555 Ciart Circadian associated repressor of transcription 0.0070 1.91 17,866,453 Per2 Period circadian clock 2 0.0014 1.91 17,624,812 Slc1a1 Solute carrier family 1 member 1 0.0055 1.88 17,817,653 Tmem63c Transmembrane protein 63c 0.0145 1.80 17,611,443 Mthfd1l Methylenetetrahydrofolate dehydrogenase (NADP + dependent) 1-like 0.0036 1.79 17,699,814 Stc1 Stanniocalcin-1 0.0017 1.73 17,775,237 Fibin Fin bud initiation factor homolog (zebrafish) 0.0038 1.73 17,879,047 Tsc22d3 TSC22 domain family, member 3 0.0247 1.56 17,833,546 Gadd45b Growth arrest and D-damage-inducible, beta 0.0248 1.54 17,616,470 Dbp D site of albumin promoter (albumin D-box) binding protein 0.0118 1.54 17,785,849 Bhlhe40 Basic helix-loop-helix family, member e40 0.0059 1.39 17,837,791 Ndrg1 N-myc downstream regulated 1 0.0222 1.39 17,664,242 LOC680121 Similar to heat shock protein 8 0.0421 1.37 17,847,497 Nat6 N-acetyltransferase 6 (GCN5-related) 0.0128 1.33 17,732,995 Nr3c2 Nuclear receptor subfamily 3, group C, member 2 0.0216 1.27 17,847,732 Dalrd3 DALR anticodon binding domain containing 3 0.0038 1.28 17,863,116 Tnfrsf21 Tumor necrosis factor receptor superfamily, member 21 0.0222 1.29 17,787,500 Nrip2 Nuclear receptor interacting protein 2 0.0247 1.31 17,698,634 Mmp14 Matrix metallopeptidase 14 (membrane-inserted) 0.0122 1.35 17,650,326 Col1a1 Collagen, type I, alpha 1 0.0140 1.41 17,814,505 Pomc Proopiomelanocortin 0.0055 1.43 17,791,733 Gadd45a Growth arrest and D-damage-inducible, alpha 0.0025 1.46 17,714,143 Slc28a3 Solute carrier family 28, member 3 0.0049 1.47 17,645,118 Ccnjl Cyclin J-like 0.0247 1.48 17,866,181 Nmur1 Neuromedin-U receptor 1 0.0025 1.52 17,619,710 Arntl Aryl hydrocarbon receptor nuclear translocator-like 0.0003 1.54 Adj. P, a false discovery rate (FDR) adjusted p value; FC, fold change. Table 3. Pathway identification among the diabetes changed genes in RMVs and BMVs. KEGG pathways Gene symbols p value Fold change In RMVs Aminoacyl-tRNA biosynthesis Iars, yars, nars, gars, mars 5.E05 23 Focal adhesion Igf1r, pdgfra, Bcl2, parvb 3.E02 6 Prostate cancer Igf1r, pdgfra, Bcl2 3.E02 11 In BMVs Circadian rhythm Per2, Bhlhe40, arntl 2.E03 43 The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were obtained using DAVID Functional Annotation tool. RMVs, retinal microvessels; BMVs, brain microvessels. 8 Diabetes & Vascular Disease Research 20(1) playing a crucial role in protein synthesis. In addition, many studies have shown that aaRSs also have multiple noncanonical functions including regulation of glucose metabolism, angiogenesis, inflammation and cell stress 42–45 responses; and aberrant expression or variants of 46–48 aaRSs are involved in various diseases. In this study, we found that the expression of Nars, Gars, Mars, Iars and Yars (5 components of aaRSs) in RMVs were significantly upregulated in diabetes, whereas these genes were not changed in BMVs. Previous studies have shown that oxi- dative stress can cause damage to aaRSs functions, followed 49,50 by amino acid mistranslation and protein misfolding. We speculate that the upregulation of aaRSs genes in RMVs is caused by the hyperglycemia-induced ROS overproduc- Figure 3. The effect of high glucose on NR4A3 gene expression tion, which in turn affects the reliability of protein translation in human umbilical vein endothelial cells (HUVECs). Cells were in RMVs. cultured with 5.5 mm (control) or 30 mm (HG) D-glucose for Clearly, functional and mechanistic studies are neces- 96 h. The HG-treated cells were divided into four distinct groups sary to substantiate the complex processes and the precise based on the duration of the high glucose exposure. Experiments were repeated in triplicates with different cell effects of the discussed gene expression patterns in BMV preparations. mRNA fold change is relative to controls while and RMV in diabetes. Nevertheless, our study suggests that using GAPDH expression as a reference. Results are given as BMVs have defense mechanisms including reduction of mean ± SEM, n = 9. *Significantly different from the control. ROS production, reduction of glycolytic intermediates and enlarged anti-inflammatory capacity, against the detri- + 30 decrease in the NADH/NAD ratio. This process can mental effects of diabetes. In contrast, in RMV these reduce cellular concentration of DHAP and prevent the protective systems are not activated or even suppressed, spontaneous conversion of DHAP into MG. The over- resulting in a diminished ability to balance the potentially expression of Gpd1 in BMVs may protect the brain mi- toxic factors that are induced by diabetes. These findings crovasculature against toxic glycolytic metabolites-induced will increase our knowledge and understanding of the injuries. mechanisms playing a role in the different susceptibilities High glucose-induced activation of the nuclear factor to diabetes of microvessels in retina and brain and may (NF)-κB pathway in vascular cells is also a key contributor pave the way to the discovery of novel treatments to in- 4,32–34 to the pathogenesis of diabetic complications. Here, tervene in diabetic-induced microvascular complications. we observe that in diabetes the expression of Tnfrsf21 (TNF receptor superfamily member 21) in BMVs is sig- Acknowledgements nificantly decreased by diabetes (Table 2). Tnfrsf21 acti- The authors would like to thank Henk E. Moorlag for technical vates the NF-κB pathway and triggers cell apoptosis. In assistance with culture of HUVECs. We thank Peter J. Zwiers, addition, we further observe that in diabetes, expression of J.A. Plantinga and R. Yan for providing technical support in the neuron-derived orphan receptor 1 (Nr4a3) and TSC22 RT-qPCR experiments. We also thank the Endothelial Cell facility domain family protein 3 (Tsc22d3) in BMVs is signifi- of University Medical Center Groningen for providing the en- cantly increased (Table 2) while it is not changed in RMVs. dothelial cells. It has been demonstrated that both Nr4a3 and Tsc22d3 exhibit anti-apoptotic effects through prevention of NF-κB 14,36,37 pathway activation. Expression of Nr4a3 plays also 38,39 Declaration of conflicting interests a critical role in neuronal protection. Badrichani AZ, et al. reported that expression of B-cell lymphoma 2 (Bcl-2, The author(s) declared no potential conflicts of interest with re- an important anti-apoptotic protein) protects endothelial spect to the research, authorship, and/or publication of this article. cells from TNF-induced apoptosis through inhibition of the NF-κB pathway. In diabetes, expression of Bcl-2 in Funding RMVs is significantly decreased (Table 1) while it is not The author(s) disclosed receipt of the following financial support for changed in BMVs. The anti-inflammatory mechanism in the research, authorship, and/or publication of this article: This work BMVs seems to be enhanced by inhibition of the NF-κB was partly supported by the Deutsche Forschungsgemeinschaft pathway whereas it might be suppressed in RMVs. (1874-1 DIAMICOM). Faiz A was funded by the Longfonds Junior Aminoacyl-tRNA synthetases (aaRSs) catalyze the li- Investigators grant (4.2.16.132JO). gation of amino acids to their cognate tRNAs, thereby Li et al. 9 ´ ´ Author notes 14. Calvayrac O, Rodrıguez-Calvo R, Martı-Pamies I, et al. NOR-1 modulates the inflammatory response of vascular Li Y. was an associate member of the International Research smooth muscle cells by preventing NFκB activation. J Mol Training group (1874-1 DIAMICOM) and received a scholarship Cell Cardiol 2015; 80: 34–44. under the CIMDS program from the Medical Faculty Mannheim, 15. Fu Y, Luo L, Luo N, et al. NR4A orphan nuclear receptors Heidelberg University. modulate insulin action and the glucose transport system: potential role in insulin resistance. J Biol Chem 2007; ORCID iD 282(43): 31525–31533. 16. Medunjanin S, Daniel JM, Weinert S, et al. DNA-dependent Jan AAM Kamps  https://orcid.org/0000-0002-2066-0140 protein kinase (DNA-PK) permits vascular smooth muscle cell proliferation through phosphorylation of the orphan References nuclear receptor NOR1. Cardiovasc Res 2015; 106(3): 1. Forbes JM and Cooper ME. Mechanisms of diabetic com- 488–497. plications. Physiol Rev 2013; 93(1): 137–188. 17. Naudi A, Jove M, Ayala V, et al. Cellular dysfunction in 2. Brownlee M. Biochemistry and molecular cell biology of diabetes as maladaptive response to mitochondrial oxidative diabetic complications. Nature 2001; 414(6865): 813–820. stress. Exp Diabetes Res 2012; 2012: 696215. 3. Kowluru RA and Chan PS. Oxidative stress and diabetic 18. Giacco F and Brownlee M. Oxidative stress and diabetic retinopathy. Exp Diabetes Res 2007; 2007: 43603. complications. Circ Res 2010; 107(9): 1058–1070. 4. Rask-Madsen C and King GL. Vascular complications of 19. Jiang T, Huang Z, Lin Y, et al. The protective role of Nrf2 in diabetes: mechanisms of injury and protective factors. Cell streptozotocin-induced diabetic nephropathy. Diabetes 2010; Metab 2013; 17(1): 20–33. 59(4): 850–860. 5. Badr GA, Tang J, Ismail-Beigi F, et al. Diabetes down- 20. Xu Z, Wei Y, Gong J, et al. NRF2 plays a protective role in regulates GLUT1 expression in the retina and its micro- diabetic retinopathy in mice. Diabetologia 2014; 57(1): vessels but not in the cerebral cortex or its microvessels. 204–213. Diabetes 2000; 49(6): 1016–1021. 21. Gorrini C, Harris IS and Mak TW. Modulation of oxidative 6. Dai J, Vrensen GFJM and Schlingemann RO. Blood-brain stress as an anticancer strategy. Nat Rev Drug Discov 2013; barrier integrity is unaltered in human brain cortex with 12(12): 931–947. diabetes mellitus. Brain Res 2002; 954(2): 311–316. 22. Takeshita S, Suzuki T, Kitayama S, et al. Bhlhe 40, a po- 7. Rosenblum WI and Levasseur JE. Microvascular responses tential diabetic modifier gene on Dbm1 locus, negatively of intermediate-size arterioles on the cerebral surface of controls myocyte fatty acid oxidation. Genes Genet Syst diabetic mice. Microvasc Res 1984; 28(3): 368–372. 2012; 87(4): 253–264. 8. Joussen AM, Huang S, Poulaki V, et al. In vivo retinal gene 23. Chung SY, Kao CH, Villarroya F, et al. Bhlhe 40 Represses expression in early diabetes. Invest Ophthalmol Vis Sci 2001; PGC-1α Activity on Metabolic Gene Promoters in Myogenic 42(12): 3047–3057. Cells. Mol Cell Biol 2015; 35(14): 2518–2529. 9. Quin GJ, Len ACL, Billson FA, et al. Proteome map of 24. Pan JSC, Huang L, Belousova T, et al. Stanniocalcin-1 in- normal rat retina and comparison with the proteome of di- hibits renal ischemia/reperfusion injury via an AMP- abetic rat retina: new insight in the pathogenesis of diabetic activated protein kinase-dependent pathway. J Am Soc retinopathy. Proteomics 2007; 7(15): 2636–2650. Nephrol 2015; 26(2): 364–378. 10. Kandpal RP, Rajasimha HK, Brooks MJ, et al. Transcriptome 25. Liu D, Huang L, Wang Y, et al. Human stanniocalcin-1 analysis using next generation sequencing reveals molecular suppresses angiotensin II-induced superoxide generation in signatures of diabetic retinopathy and efficacy of candidate cardiomyocytes through UCP3-mediated anti-oxidant drugs. Mol Vis 2012; 18: 1123–1146. pathway. PLoS One 2012; 7(5): e36994. 11. Li Y, Lapina N, Weinzierl N, et al. A novel method to isolate 26. Wang J, Lin J, Schlotterer A, et al. CD74 indicates microglial retinal and brain microvessels from individual rats: Micro- activation in experimental diabetic retinopathy and exoge- scopic and molecular biological characterization and ap- nous methylglyoxal mimics the response in normoglycemic plication in hyperglycemic animals. Vascul Pharmacol 2018; retina. Acta Diabetol 2014; 51(5): 813–821. 110: 24–30. 27. Rabbani N and Thornalley PJ. The critical role of methyl- 12. Li Y, Faiz A, Moshage H, et al. Comparative transcriptome glyoxal and glyoxalase 1 in diabetic nephropathy. Diabetes analysis of inner blood-retinal barrier and blood-brain barrier 2014; 63(1): 50–52. in rats. Sci Rep 2021; 11(1): 12151. 28. Kanwar M and Kowluru RA. Role of glyceraldehyde 3- 13. Livak KJ and Schmittgen TD. Analysis of relative gene phosphate dehydrogenase in the development and progres- expression data using real-time quantitative PCR and the sion of diabetic retinopathy. Diabetes 2009; 58(1): 227–234. 2(Delta Delta C(T)) Method. Methods 2001; 25(4): 29. Du X, Matsumura T, Edelstein D, et al. Inhibition of GAPDH 402–408. activity by poly (ADP-ribose) polymerase activates three 10 Diabetes & Vascular Disease Research 20(1) major pathways of hyperglycemic damage in endothelial 40. Badrichani AZ, Stroka DM, Bilbao G, et al. Bcl-2 and Bcl- cells. J Clin Invest 2003; 112(7): 1049–1057. XL serve an anti-inflammatory function in endothelial cells 30. Shen W, Wei Y, Dauk M, et al. Involvement of a glycerol-3- through inhibition of NF-kappaB. J Clin Invest 1999; 103(4): phosphate dehydrogenase in modulating the NADH/NAD+ 543–553. ratio provides evidence of a mitochondrial glycerol-3- 41. Brown MV, Reader JS and Tzima E. Mammalian aminoacyl- phosphate shuttle in Arabidopsis. Plant Cell 2006; 18(2): tRNA synthetases: cell signaling functions of the protein 422–441. translation machinery. Vascul Pharmacol 2010; 52(1–2): 31. Kumar S, Singh R, Williams CP, et al. Stress exposure results 21–26. in increased peroxisomal levels of yeast Pnc1 and Gpd1, 42. Guo M and Schimmel P. Essential nontranslational functions which are imported via a piggy-backing mechanism. Bio- of tRNA synthetases. Nat Chem Biol 2013; 9(3): 145–153. chim Biophys Acta 2016; 1863(1): 148–156. 43. Guo M and Schimmel P. Homeostatic mechanisms by al- 32. Romeo G, Liu WH, Asnaghi V, et al. Activation of nuclear ternative forms of tRNA synthetases. Trends Biochem Sci factor-kappaB induced by diabetes and high glucose regu- 2012; 37(10): 401–403. lates a proapoptotic program in retinal pericytes. Diabetes 44. Guo M, Yang XL and Schimmel P. New functions of 2002; 51(7): 2241–2248. aminoacyl-tRNA synthetases beyond translation. In: Vol. 33. Hattori Y, Hattori S, Sato N, et al. High-glucose-induced 11, nature reviews. Molecular Cell Biology, 2010, pp. nuclear factor kappaB activation in vascular smooth muscle 668–674. cells. Cardiovasc Res 2000; 46(1): 188–197. 45. Park SG, Kim HJ, Min YH, et al. Human lysyl-tRNA 34. Aveleira CA, Lin CM, Abcouwer SF, et al. TNF-α signals synthetase is secreted to trigger proinflammatory re- through PKCζ/NF-κB to alter the tight junction complex and sponse. Proc Natl Acad Sci U S A 2005; 102(18): increase retinal endothelial cell permeability. Diabetes 2010; 6356–6361. 59(11): 2872–2882. 46. Park SG, Schimmel P and Kim S. Aminoacyl tRNA syn- 35. Pan G, Bauer JH, Haridas V, et al. Identification and thetases and their connections to disease. Proc Natl Acad Sci functional characterization of DR6, a novel death domain- USA 2008; 105(32): 11043–11049. containing TNF receptor. FEBS Lett 1998; 431(3): 351–356. 47. T Hart LM, Hansen T, Rietveld I, et al. Evidence that the 36. Cheng Q, Fan H, Ngo D, et al. GILZ overexpression inhibits mitochondrial leucyl tRNA synthetase (LARS2) gene rep- endothelial cell adhesive function through regulation of NF- resents a novel type 2 diabetes susceptibility gene. Diabetes κB and MAPK activity. J Immunol 2013; 191(1): 424–433. 2005; 54(6): 1892–1895. 37. Lee MJ, Yang RZ, Karastergiou K, et al. Low expression of 48. Kim BH, Jung WY, Lee H, et al. Lysyl-tRNA synthetase the GILZ may contribute to adipose inflammation and altered (KRS) expression in gastric carcinoma and tumor- adipokine production in human obesity. J Lipid Res 2016; associated inflammation. Ann Surg Oncol 2014; 21(6): 57(7): 1256–1263. 2020–2027. 38. Volakakis N, Kadkhodaei B, Joodmardi E, et al. NR4A 49. Netzer N, Goodenbour JM, David A, et al. Innate immune orphan nuclear receptors as mediators of CREB-dependent and chemically triggered oxidative stress modifies transla- neuroprotection. Proc Natl Acad Sci U S A 2010; 107(27): tional fidelity. Nature 2009; 462(7272): 522–526. 12317–12322. 50. Ling J and Soll ¨ D. Severe oxidative stress induces protein 39. Ponni ¨ o¨ T and Conneely OM. nor-1 regulates hippocampal mistranslation through impairment of an aminoacyl-tRNA axon guidance, pyramidal cell survival, and seizure sus- synthetase editing site. Proc Natl Acad Sci USA 2010; ceptibility. Mol Cell Biol 2004; 24(20): 9070–9078. 107(9): 4028–4033.

Journal

Diabetes and Vascular Disease Research – SAGE

Published: Jan 2, 2023

Keywords: Retina; brain; diabetes; microvasculature; gene expression profiling

There are no references for this article.