Mouse Model of Nitrogen Mustard Ocular Surface Injury Characterization and Sphingolipid Signaling.

Vesicating chemicals like sulfur mustard (SM) or nitrogen mustard (NM) can cause devastating damage to the eyes, skin, and lungs. Eyes, being the most sensitive, have complicated pathologies that can manifest immediately after exposure (acute) and last for years (chronic). No FDA-approved drug is available to be used as medical counter measures (MCMs) against such injuries. Understanding the pathological mechanisms in acute and chronic response of the eye is essential for developing effective MCMs. Here, we report the clinical and histopathological characterization of a mouse model of NM-induced ocular surface injury (entire surface) developed by treating the eye with 2% (w/v) NM solution for 5 min. Unlike the existing models of specific injury, our model showed severe ocular inflammation, including the eyelids, structural deformity of the corneal epithelium and stroma, and diminished visual and retinal functions. We also observed alterations of the inflammatory markers and their expression at different phases of the injury, along with an activation of acidic sphingomyelinase (aSMase), causing an increase in bioactive sphingolipid ceramide and a reduction in sphingomyelin levels. This novel ocular surface mouse model recapitulated the injuries reported in human, rabbit, and murine SM or NM injury models. NM exposure of the entire ocular surface in mice, which is similar to accidental or deliberate exposure in humans, showed severe ocular inflammation and caused irreversible alterations to the corneal structure and significant vision loss. It also showed an intricate interplay between inflammatory markers over the injury period and alteration in sphingolipid homeostasis in the early acute phase.

Alpha cell receptor for advanced glycation end products associate with glucagon expression in type 1 diabetes.

Hypoglycemia in type 1 diabetes associates with changes in the pancreatic islet α cells, where the receptor for advanced glycation end products (RAGE) is highly expressed. This study compared islet RAGE expression in donors without diabetes, those at risk of, and those with type 1 diabetes. Laser-dissected islets were subject to RNA bioinformatics and adjacent pancreatic tissue were assessed by confocal microscopy. We found that islets from type 1 diabetes donors had differential expression of the RAGE gene (AGER) and its correlated genes, based on glucagon expression. Random forest machine learning revealed that AGER was the most important predictor for islet glucagon levels. Conversely, a generalized linear model identified that glucagon expression could be predicted by expression of RAGE signaling molecules, its ligands and enzymes that create or clear RAGE ligands. Confocal imaging co-localized RAGE, its ligands and signaling molecules to the α cells. Half of the type 1 diabetes cohort comprised of adolescents and a patient with history of hypoglycemia-all showed an inverse relationship between glucagon and RAGE. These data confirm an association between glucagon and islet RAGE, its ligands and signaling pathways in type 1 diabetes, which warrants functional investigation into a role for RAGE in hypoglycemia.

Detection of Antiviral Tissue Responses and Increased Cell Stress in the Pancreatic Islets of Newly Diagnosed Type 1 Diabetes Patients: Results From the DiViD Study.

Aims/hypothesis: The Diabetes Virus Detection (DiViD) study has suggested the presence of low-grade enteroviral infection in pancreatic tissue collected from six of six live adult patients newly diagnosed with type 1 diabetes. The present study aimed to compare the gene and protein expression of selected virally induced pathogen recognition receptors and interferon stimulated genes in islets from these newly diagnosed type 1 diabetes (DiViD) subjects vs age-matched non-diabetic (ND) controls. Methods: RNA was extracted from laser-captured islets and Affymetrix Human Gene 2.0 ST arrays used to obtain gene expression profiles. Lists of differentially expressed genes were subjected to a data-mining pipeline searching for enrichment of canonical pathways, KEGG pathways, Gene Ontologies, transcription factor binding sites and other upstream regulators. In addition, the presence and localisation of specific viral response proteins (PKR, MxA and MDA5) were examined by combined immunofluorescent labelling in sections of pancreatic tissue. Results: The data analysis and data mining process revealed a significant enrichment of gene ontologies covering viral reproduction and infectious cycles; peptide translation, elongation and initiation, as well as oxidoreductase activity. Enrichment was identified in the KEGG pathways for oxidative phosphorylation; ribosomal and metabolic activity; antigen processing and presentation and in canonical pathways for mitochondrial dysfunction, oxidative phosphorylation and EIF2 signaling. Protein Kinase R (PKR) expression did not differ between newly diagnosed type 1 diabetes and ND islets at the level of total RNA, but a small subset of ß-cells displayed markedly increased PKR protein levels. These PKR+ ß-cells correspond to those previously shown to contain the viral protein, VP1. RNA encoding MDA5 was increased significantly in newly diagnosed type 1 diabetes islets, and immunostaining of MDA5 protein was seen in α- and certain ß-cells in both newly diagnosed type 1 diabetes and ND islets, but the expression was increased in ß-cells in type 1 diabetes. In addition, an uncharacterised subset of synaptophysin positive, but islet hormone negative, cells expressed intense MDA5 staining and these were more prevalent in DiViD cases. MxA RNA was upregulated in newly diagnosed type 1 diabetes vs ND islets and MxA protein was detected exclusively in newly diagnosed type 1 diabetes ß-cells. Conclusion/interpretation: The gene expression signatures reveal that pathways associated with cellular stress and increased immunological activity are enhanced in islets from newly diagnosed type 1 diabetes patients compared to controls. The increases in viral response proteins seen in ß-cells in newly diagnosed type 1 diabetes provide clear evidence for the activation of IFN signalling pathways. As such, these data strengthen the hypothesis that an enteroviral infection of islet ß-cells contributes to the pathogenesis of type 1 diabetes.

Islet expression of type I interferon response sensors is associated with immune infiltration and viral infection in type 1 diabetes.

Previous results indicate the presence of an interferon (IFN) signature in type 1 diabetes (T1D), capable of inducing chronic inflammation and compromising b cell function. Here, we determined the expression of the IFN response markers MxA, PKR, and HLA-I in the islets of autoantibody-positive and T1D donors. We found that these markers can be coexpressed in the same islet, are more abundant in insulin-containing islets, are highly expressed in islets with insulitis, and their expression levels are correlated with the presence of the enteroviral protein VP1. The expression of these markers was associated with down-regulation of multiple genes in the insulin secretion pathway. The coexistence of an IFN response and a microbial stress response is likely to prime islets for immune destruction. This study highlights the importance of therapeutic interventions aimed at eliminating potentially persistent infections and diminishing inflammation in individuals with T1D.

Retinal pigment epithelium and microglia express the CD5 antigen-like protein, a novel autoantigen in age-related macular degeneration.

We report on a novel autoantigen expressed in human macular tissues, identified following an initial Western blot (WB)-based screening of sera from subjects with age-related macular degeneration (AMD) for circulating auto-antibodies (AAbs) recognizing macular antigens. Immunoprecipitation, 2D-gel electrophoresis (2D-GE) and liquid chromatography-tandem mass spectrometry (LC-MS/MS), direct enzyme-linked immunosorbent assays (ELISA), WBs, immunohistochemistry (IHC), human primary and ARPE-19 immortalized cell cultures were used to characterize this novel antigen. An approximately 40-kDa autoantigen in AMD was identified as the scavenger receptor CD5 antigen-like protein (CD5L), also known as apoptosis inhibitor of macrophage (AIM). CD5L/AIM was localized to human RPE by IHC and WB methods and to retinal microglial cells by IHC. ELISAs with recombinant CD5L/AIM on a subset of AMD sera showed a nearly 2-fold higher anti-CD5L/AIM reactivity in AMD vs. Control sera (p = 0.000007). Reactivity ≥0.4 was associated with 18-fold higher odds of having AMD (χ2 = 21.42, p = 0.00063). Circulating CD5L/AIM levels were also nearly 2-fold higher in AMD sera compared to controls (p = 0.0052). The discovery of CD5L/AIM expression in the RPE and in retinal microglial cells adds to the known immunomodulatory roles of these cells in the retina. The discovery of AAbs recognizing CD5L/AIM identifies a possible novel disease biomarker and suggest a potential role for CD5L/AIM in the pathogenesis of AMD in situ. The possible mechanisms via which anti-CD5L/AIM AAbs may contribute to AMD pathogenesis are discussed. In particular, since CD5L is known to stimulate autophagy and to participate in oxidized LDL uptake in macrophages, we propose that anti-CD5L/AIM auto-antibodies may play a role in drusen biogenesis and inflammatory RPE damage in AMD.

Circulating Autoantibodies in Age-Related Macular Degeneration Recognize Human Macular Tissue Antigens Implicated in Autophagy, Immunomodulation, and Protection from Oxidative Stress and Apoptosis.

BACKGROUND: We investigated sera from elderly subjects with and without age-related macular degeneration (AMD) for presence of autoantibodies (AAbs) against human macular antigens and characterized their identity. METHODS: Sera were collected from participants in the Age-Related Maculopathy Ancillary (ARMA) Study, a cross-sectional investigation ancillary to the Health ABC Study, enriched with participants from the general population. The resulting sample (mean age: 79.2±3.9 years old) included subjects with early to advanced AMD (n = 131) and controls (n = 231). Sera were tested by Western blots for immunoreactive bands against human donor macular tissue homogenates. Immunoreactive bands were identified and graded, and odds ratios (OR) calculated. Based on these findings, sera were immunoprecipitated, and subjected to 2D gel electrophoresis (GE). Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to identify the targets recognized by circulating AAbs seen on 2D-GE, followed by ELISAs with recombinant proteins to confirm LC-MS/MS results, and quantify autoreactivities. RESULTS: In AMD, 11 immunoreactive bands were significantly more frequent and 13 were significantly stronger than in controls. Nine of the more frequent bands also showed stronger reactivity. OR estimates ranged between 4.06 and 1.93, and all clearly excluded the null value. Following immunoprecipitation, 2D-GE and LC-MS/MS, five of the possible autoreactivity targets were conclusively identified: two members of the heat shock protein 70 (HSP70) family, HSPA8 and HSPA9; another member of the HSP family, HSPB4, also known as alpha-crystallin A chain (CRYAA); Annexin A5 (ANXA5); and Protein S100-A9, also known as calgranulin B that, when complexed with S100A8, forms calprotectin. ELISA testing with recombinant proteins confirmed, on average, significantly higher reactivities against all targets in AMD samples compared to controls. CONCLUSIONS: Consistent with other evidence supporting the role of inflammation and the immune system in AMD pathogenesis, AAbs were identified in AMD sera, including early-stage disease. Identified targets may be mechanistically linked to AMD pathogenesis because the identified proteins are implicated in autophagy, immunomodulation, and protection from oxidative stress and apoptosis. In particular, a role in autophagy activation is shared by all five autoantigens, raising the possibility that the detected AAbs may play a role in AMD via autophagy compromise and downstream activation of the inflammasome. Thus, we propose that the detected AAbs provide further insight into AMD pathogenesis and have the potential to contribute to disease biogenesis and progression.

Molecular pathway alterations in CD4 T-cells of nonobese diabetic (NOD) mice in the preinsulitis phase of autoimmune diabetes.

Type 1 diabetes (T1D) is a multigenic disease caused by T-cell mediated destruction of the insulin producing pancreatic islet ß-cells. The earliest sign of islet autoimmunity in NOD mice, islet leukocytic infiltration or insulitis, is obvious at around 5 weeks of age. The molecular alterations that occur in T cells prior to insulitis and that may contribute to T1D development are poorly understood. Since CD4 T-cells are essential to T1D development, we tested the hypothesis that multiple genes/molecular pathways are altered in these cells prior to insulitis. We performed a genome-wide transcriptome and pathway analysis of whole, untreated CD4 T-cells from 2, 3, and 4 week-old NOD mice in comparison to two control strains (NOR and C57BL/6). We identified many differentially expressed genes in the NOD mice at each time point. Many of these genes (herein referred to as NOD altered genes) lie within known diabetes susceptibility (insulin-dependent diabetes, Idd) regions, e.g. two diabetes resistant loci, Idd27 (tripartite motif-containing family genes) and Idd13 (several genes), and the CD4 T-cell diabetogenic activity locus, Idd9/11 (2 genes, KH domain containing, RNA binding, signal transduction associated 1 and protein tyrosine phosphatase 4a2). The biological processes associated with these altered genes included, apoptosis/cell proliferation and metabolic pathways (predominant at 2 weeks); inflammation and cell signaling/activation (predominant at 3 weeks); and innate and adaptive immune responses (predominant at 4 weeks). Pathway analysis identified several factors that may regulate these abnormalities: eight, common to all 3 ages (interferon regulatory factor 1, hepatic nuclear factor 4, alpha, transformation related protein 53, BCL2-like 1 (lies within Idd13), interferon gamma, interleukin 4, interleukin 15, and prostaglandin E2); and two each, common to 2 and 4 weeks (androgen receptor and interleukin 6); and to 3 and 4 weeks (interferon alpha and interferon regulatory factor 7). Others were unique to the various ages, e.g. myelocytomatosis oncogene, jun oncogene, and amyloid beta (A4) to 2 weeks; tumor necrosis factor, transforming growth factor, beta 1, NF?B, ERK, and p38MAPK to 3 weeks; and interleukin 12 and signal transducer and activator of transcription 4 to 4 weeks. Thus, our study demonstrated that expression of many genes that lie within several Idds (e.g. Idd27, Idd13 and Idd9/11) was altered in CD4 T-cells in the early induction phase of autoimmune diabetes and identified their associated molecular pathways. These data offer the opportunity to test hypotheses on the roles played by the altered genes/molecular pathways, to understand better the mechanisms of CD4 T-cell diabetogenesis, and to develop new therapeutic strategies for T1D.

Molecular phenotyping of immune cells from young NOD mice reveals abnormal metabolic pathways in the early induction phase of autoimmune diabetes.

Islet leukocytic infiltration (insulitis) is first obvious at around 4 weeks of age in the NOD mouse--a model for human type 1 diabetes (T1D). The molecular events that lead to insulitis and initiate autoimmune diabetes are poorly understood. Since TID is caused by numerous genes, we hypothesized that multiple molecular pathways are altered and interact to initiate this disease. We evaluated the molecular phenotype (mRNA and protein expression) and molecular networks of ex vivo unfractionated spleen leukocytes from 2 and 4 week-old NOD mice in comparison to two control strains. Analysis of the global gene expression profiles and hierarchical clustering revealed that the majority (~90%) of the differentially expressed genes in NOD mice were repressed. Furthermore, analysis using a modern suite of multiple bioinformatics approaches identified abnormal molecular pathways that can be divided broadly into 2 categories: metabolic pathways, which were predominant at 2 weeks, and immune response pathways, which were predominant at 4 weeks. Network analysis by Ingenuity pathway analysis identified key genes/molecules that may play a role in regulating these pathways. These included five that were common to both ages (TNF, HNF4A, IL15, Progesterone, and YWHAZ), and others that were unique to 2 weeks (e.g. MYC/MYCN, TGFB1, and IL2) and to 4 weeks (e.g. IFNG, beta-estradiol, p53, NFKB, AKT, PRKCA, IL12, and HLA-C). Based on the literature, genes that may play a role in regulating metabolic pathways at 2 weeks include Myc and HNF4A, and at 4 weeks, beta-estradiol, p53, Akt, HNF4A and AR. Our data suggest that abnormalities in regulation of metabolic pathways in the immune cells of young NOD mice lead to abnormalities in the immune response pathways and as such may play a role in the initiation of autoimmune diabetes. Thus, targeting metabolism may provide novel approaches to preventing and/or treating autoimmune diabetes.

GPRC6A mediates the effects of L-arginine on insulin secretion in mouse pancreatic islets.

L-arginine (l-Arg) is an insulin secretagogue, but the molecular mechanism whereby it stimulates insulin secretion from ß-cells is not known. The possibility that l-Arg regulates insulin secretion through a G protein-coupled receptor (GPCR)-mediated mechanism is suggested by the high expression of the nutrient receptor GPCR family C group 6 member A (GPRC6A) in the pancreas and TC-6 ß-cells and the finding that Gprc6a(-/]minus]) mice have abnormalities in glucose homeostasis. To test the direct role of GPRC6A in regulating insulin secretion, we evaluated the response of pancreatic islets derived from Gprc6a(-/]minus]) mice to L-Arg. We found that the islet size and insulin content were decreased in pancreatic islets from Gprac6a(-/]minus]) mice. These alterations were selective for ß-cells, because there were no abnormalities in serum glucagon levels or glucagon content of islets derived from Gprac6a(-/]minus]) mice. Significant reduction was observed in both the pancreatic ERK response to L-Arg administration to Gprc6a(-/]minus]) mice in vivo and L-Arg-induced insulin secretion and production ex vivo in islets isolated from Gprc6a(-/]minus]) mice. L-Arg stimulation of cAMP accumulation in isolated islets isolated from Gprc6a(-/]minus]) mice was also diminished. These findings suggest that l-Arg stimulation of insulin secretion in ß-cells is mediated, at least in part, through GPRC6A activation of cAMP pathways.

Approaches to reduce false positives and false negatives in the analysis of microarray data: applications in type 1 diabetes research.

BACKGROUND: As studies of molecular biology system attempt to achieve a comprehensive understanding of a particular system, Type 1 errors may be a significant problem. However, few investigators are inclined to accept the increase in Type 2 errors (false positives) that may result when less stringent statistical cut-off values are used. To address this dilemma, we developed an analysis strategy that used a stringent statistical analysis to create a list of differentially expressed genes that served as "bait" to "fish out" other genes with similar patterns of expression. RESULTS: Comparing two strains of mice (NOD and C57Bl/6), we identified 93 genes with statistically significant differences in their patterns of expression. Hierarchical clustering identified an additional 39 genes with similar patterns of expression differences between the two strains. Pathway analysis was then employed: 1) identify the central genes and define biological processes that may be regulated by the genes identified, and 2) identify genes on the lists that could not be connected to each other in pathways (potential false positives). For networks created by both gene lists, the most connected (central) genes were interferon gamma (IFN-gamma) and tumor necrosis factor alpha (TNF-alpha). These two cytokines are relevant to the biological differences between the two strains of mice. Furthermore, the network created by the list of 39 genes also suggested other biological differences between the strains. CONCLUSION: Taken together, these data demonstrate how stringent statistical analysis, combined with hierarchical clustering and pathway analysis may offer deeper insight into the biological processes reflected from a set of expression array data. This approach allows us to 'recapture" false negative genes that otherwise would have been missed by the statistical analysis.

New data analysis and mining approaches identify unique proteome and transcriptome markers of susceptibility to autoimmune diabetes.

Non-obese diabetic (NOD) mice spontaneously develop autoimmunity to the insulin producing beta cells leading to insulin-dependent diabetes. In this study we developed and used new data analysis and mining approaches on combined proteome and transcriptome (molecular phenotype) data to define pathways affected by abnormalities in peripheral leukocytes of young NOD female mice. Cells were collected before mice show signs of autoimmunity (age, 2-4 weeks). We extracted both protein and RNA from NOD and C57BL/6 control mice to conduct both proteome analysis by two-dimensional gel electrophoresis and transcriptome analysis on Affymetrix expression arrays. We developed a new approach to analyze the two-dimensional gel proteome data that included two-way analysis of variance, cluster analysis, and principal component analysis. Lists of differentially expressed proteins and transcripts were subjected to pathway analysis using a commercial service. From the list of 24 proteins differentially expressed between strains we identified two highly significant and interconnected networks centered around oncogenes (Myc and Mycn) and apoptosis-related genes (Bcl2 and Casp3). The 273 genes with significant strain differences in RNA expression levels created six interconnected networks with a significant over-representation of genes related to cancer, cell cycle, and cell death. They contained many of the same genes found in the proteome networks (including Myc and Mycn). The combination of the eight, highly significant networks created one large network of 272 genes of which 82 had differential expression between strains either at the protein or the RNA level. We conclude that new proteome data analysis strategies and combined information from proteome and transcriptome can enhance the insights gained from either type of data alone. The overall systems biology of prediabetic NOD mice points toward abnormalities in regulation of the opposing processes of cell renewal and cell death even before there are any clear signatures of immune system activation.

Strain differences in allele and expression levels of CD72 on B-lymphocytes from NOD, AKR, NON and C57BL/6 mice.

The B-lymphocyte marker CD72 has multiple alleles and serves crucial and nonredundant roles in B-cell development and activation. B-lymphocytes play an important role in development of autoimmune diabetes in NOD mice, therefore we examined the patterns of expression of CD72 and its alloantigens on splenic lymphocytes from 4-week-old NOD/LtJ mice. Comparisons of CD72 expression were made between NOD mice and three non-diabetic strains, NON/LtJ mice, C57BL/6J and AKR/J. Use of allele-specific monoclonal antibodies revealed that the previously uncharacterized NON strain expresses either the a or d allele, whereas NOD and AKR mice were confirmed to express the rare c allele. Flow cytometric analysis revealed differential expression between the strains. Whereas NON, C57BL/6 and AKR mice expressed CD72 on 98, 94 and 92% of their B-lymphocytes (CD19+ cells), the NOD mice only expressed this regulatory marker on 78% of their B-lymphocytes. Furthermore, CD72 expression levels on CD72 positive cells were lower in NOD mice than in other three non-diabetic strains. The presence of the CD72c allele, as well as its low level of expression in NOD mice at 4 weeks of age, may be associated with B-lymphocyte hyper-responsiveness and resistance to activation-induced cell death.

Two-dimensional gel electrophoresis characterization of the mouse leukocyte proteome, using a tri-reagent for protein extraction.

The use of "tri-reagents" allows the concomitant isolation of DNA, RNA, and proteins for a complete molecular characterization of biological samples. The aim of the current study was to perform the comparative evaluation of two-dimensional gel proteomes isolated with or without a tri-reagent protein extraction step before dissolving the samples in the first-dimension electrophoresis buffer. We conclude that the use of tri-reagents increases the amount of protein extracted from the sample. Furthermore, an average of 301 +/- 3.6 spots were found in gels from both sample preparation methods, whereas 71.7 +/- 8.1 and 49.7 +/- 2.3 spots were uniquely seen in tri-reagent and non-tri-reagent samples, respectively.

Functional characterization of two-dimensional gel-separated proteins using sequential staining.

Proteins separated by two-dimensional (2-D) gel electrophoresis can be visualized using various protein staining methods. This is followed by downstream procedures, such as image analysis, gel spot cutting, protein digestion, and mass spectrometry (MS), to characterize protein expression profiles within cells, tissues, organisms, or body fluids. Characterizing specific post-translational modifications on proteins using MS of peptide fragments is difficult and labor-intensive. Recently, specific staining methods have been developed and merged into the 2-D gel platform so that not only general protein patterns but also patterns of phosphorylated and glycosylated proteins can be obtained. We used the new Pro-Q Diamond phosphoprotein dye technology for the fluorescent detection of phosphoproteins directly in 2-D gels of mouse leukocyte proteins, and Pro-Q Emerald 488 glycoprotein dye to detect glycoproteins. These two fluorescent stains are compatible with general protein stains, such as SYPRO Ruby stain. We devised a sequential procedure using Pro-Q Diamond (phosphoprotein), followed by Pro-Q Emerald 488 (glycoprotein), followed by SYPRO Ruby stain (general protein stain), and finally silver stain for total protein profile. This multiple staining of the proteins in a single gel provided parallel determination of protein expression and preliminary characterization of post-translational modifications of proteins in individual spots on 2-D gels. Although this method does not provide the same degree of certainty as traditional MS methods of characterizing post-translational modifications, it is much simpler, faster, and does not require sophisticated equipment and expertise in MS.