Type I IRGs are slightly enriched before onset of symptoms, but some IRGs show no change.

<p>(A) Superarray analysis by qPCR was performed on 70 timepoints from 52 subjects to assess the time course of gene expression. Average fold changes for three groups of genes (Type I IRG, Type II IRG, and Cell Cycle as defined in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085422#pone.0085422.s001" target="_blank">Figure S1</a>) were determined for samples collected within the indicated time blocks. Fold changes are compared with healthy baselines. Error bars show the standard deviation. All three gene groupings had a p-value<0.05 when evaluated by ANOVA. (−20 days to −1 days N = 11; 0 days to 3 days N = 12; 4 days to 7 days N = 17; 8 days to 10 days N = 16). (B) The table shows the average fold change for nine select type I IRGs derived from microarray analysis for SLE, YFV, Flu, HRV, RSV, DENV, Poly IC, and EBV. (C) Heatmaps showing fold change as determined by qPCR for <i>OAS1</i>, <i>MX1</i>, and <i>HERC5</i> at multiple timepoints in EBV infection (top panel) or in other situations (bottom panel).</p

Primary EBV Infection Induces an Expression Profile Distinct from Other Viruses but Similar to Hemophagocytic Syndromes

<div><p>Epstein-Barr Virus (EBV) causes infectious mononucleosis and establishes lifelong infection associated with cancer and autoimmune disease. To better understand immunity to EBV, we performed a prospective study of natural infection in healthy humans. Transcriptome analysis defined a striking and reproducible expression profile during acute infection but no lasting gene changes were apparent during latent infection. Comparing the EBV response profile to multiple other acute viral infections, including influenza A (influenza), respiratory syncytial virus (RSV), human rhinovirus (HRV), attenuated yellow fever virus (YFV), and Dengue fever virus (DENV), revealed similarity only to DENV. The signature shared by EBV and DENV was also present in patients with hemophagocytic syndromes, suggesting these two viruses cause uncontrolled inflammatory responses. Interestingly, while EBV induced a strong type I interferon response, a subset of interferon induced genes, including <i>MX1, HERC5</i>, and <i>OAS1</i>, were not upregulated, suggesting a mechanism by which viral antagonism of immunity results in a profound inflammatory response. These data provide an important first description of the response to a natural herpesvirus infection in humans.</p></div

Type II IRG gene expression correlates with CD8 lymphocytosis in primary EBV infection.

<p>Data show the correlation between IRG gene expression and CD8 lymphocytosis in 42 subjects at timepoints within the first two weeks after symptom onset during primary EBV infection. The number of CD8 T cells per mL of peripheral blood was determined by flow cytometry (note: average at baseline was 0.25×10⁶). Superarray analysis by qPCR was performed to determine average fold changes for groups of Type I IRGs and Type II IRGs. Pearson correlation coefficients (r-values) and p-values are shown.</p

A distinct gene expression profile is apparent during acute EBV infection, but not latent infection.

<p>(A) Microarray analysis was performed on pre-infection, acute, and latent timepoints for the 10 subjects with primary EBV infection (listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085422#pone.0085422.s005" target="_blank">Table S1</a>). 464 genes were shown to be significantly changed during the primary response to EBV at a fold change of ≥2 and a p-value ≤0.05. No genes were significantly changed during the latent phase of infection using the same criteria. (B) Ingenuity Pathway Analysis of the 464 acute genes revealed 14 pathways that were enriched amongst the genes that changed during primary EBV. These had a significant p-value (the negative log is shown) following evaluation with the Benjamini-Hochberg multiple tests correction. (C) A heatmap representation of the highest (≥3 fold) gene changes during the acute and latent stages of EBV infection.</p

CD8+ T cells and monocytes show upregulation of key gene groups during acute infection.

<p>Quantitative PCR analysis was performed on RNA prepared from sorted cells from peripheral blood of four subjects before and during acute EBV infection. (A) This panel shows the staining and sorting strategy for separation of CD8 T cells, B cells, NK cells, and monocytes. (B) Each subject’s respective cell type was compared with his or her own cell type at the preinfection time point. All acute samples were taken from subjects within a week of onset of symptoms. The average fold change of both type I and type II IRG as well as cell cycle genes for four subjects is shown. A paired t-test was used for statistical analysis. (C) Monocyte numbers were determined from complete blood counts of subjects at the acute and latent phases of EBV infection.</p

Primary Epstein-Barr virus infection causes distinct expression patterns in comparison to other interferon driven responses.

<p>Heatmap shows a list of the genes up/down regulated 3-fold during acute infection with EBV in comparison to subjects with other viral infections (YFV, Flu, HRV, RSV, and DENV), subjects injected with Poly IC, or patients with SLE. The color intensity represents fold changes in gene expression in comparison to either each subjects’ own healthy baseline (EBV, Flu, HRV, RSV, and Poly IC) or in comparison to healthy controls (SLE and DENV). Data is arranged as a hierarchical clustering of genes. The genes shown were derived from analysis of EBV subjects (fold change ≥3 and met a statistical significance cutoff of p-value of ≤0.05 with Bonferonni multiple-tests correction, please see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085422#pone.0085422.s006" target="_blank">Table S2</a> for fold change ≥2). Each column represents a single subject. Horizontal gray bars indicate that the gene of interest was not present in the analyzed dataset used for comparison. Vertical gray bars separate disease groupings. Colored boxes on the right represent specific clusters of genes discussed in the text: green box and green asterisks – EBV unique, purple box – genes in common between EBV and DENV, red – genes upregulated in all situations, blue – genes down-regulated in EBV and some other situations.</p

Mapping epitopes of U1-70K autoantibodies at single-amino acid resolution

<div><p></p><p>The mechanisms underlying development of ribonucleoprotein (RNP) autoantibodies are unclear. The U1-70K protein is the predominant target of RNP autoantibodies, and the RNA binding domain has been shown to be the immunodominant autoantigenic region of U1-70K, although the specific epitopes are not known. To precisely map U1-70K epitopes, we developed silicon-based peptide microarrays with >5700 features, corresponding to 843 unique peptides derived from the U1-70K protein. The microarrays feature overlapping peptides, with single-amino acid resolution in length and location, spanning amino acids 110–170 within the U1-70K RNA binding domain. We evaluated the serum IgG of a cohort of patients with systemic lupus erythematosus (SLE; <i>n</i> = 26) using the microarrays, and identified multiple reactive epitopes, including peptides 116–121 and 143–148. Indirect peptide ELISA analysis of the sera of patients with SLE (<i>n</i> = 88) revealed that ∼14% of patients had serum IgG reactivity to 116–121, while reactivity to 143–148 appeared to be limited to a single patient. SLE patients with serum reactivity to 116–121 had significantly lower SLE Disease Activity Index (SLEDAI) scores at the time of sampling, compared to non-reactive patients. Minimal reactivity to the peptides was observed in the sera of healthy controls (<i>n</i> = 92). Competitive ELISA showed antibodies to 116–121 bind a common epitope in U1-70K (68–72) and the matrix protein M1 of human influenza B viruses. Institutional Review Boards approved this study. Knowledge of the precise epitopes of U1-70K autoantibodies may provide insight into the mechanisms of development of anti-RNP, identify potential clinical biomarkers and inform ongoing clinical trails of peptide-based therapeutics.</p></div

High-Resolution Analysis of Antibodies to Post-Translational Modifications Using Peptide Nanosensor Microarrays

Autoantibodies are a hallmark of autoimmune diseases such as lupus and have the potential to be used as biomarkers for diverse diseases, including immunodeficiency, infectious disease, and cancer. More precise detection of antibodies to specific targets is needed to improve diagnosis of such diseases. Here, we report the development of reusable peptide microarrays, based on giant magnetoresistive (GMR) nanosensors optimized for sensitively detecting magnetic nanoparticle labels, for the detection of antibodies with a resolution of a single post-translationally modified amino acid. We have also developed a chemical regeneration scheme to perform multiplex assays with a high level of reproducibility, resulting in greatly reduced experimental costs. In addition, we show that peptides synthesized directly on the nanosensors are approximately two times more sensitive than directly spotted peptides. Reusable peptide nanosensor microarrays enable precise detection of autoantibodies with high resolution and sensitivity and show promise for investigating antibody-mediated immune responses to autoantigens, vaccines, and pathogen-derived antigens as well as other fundamental peptide–protein interactions