Micro-RNA and mRNA Profiles Associated with Ectopic Germinal Center Formation in Thymus Samples of Patients with Autoimmune Myas

Myasthenia gravis (MG) is an autoimmune neuromuscular disorder caused by antibodies directed against proteins present at the post-synaptic surface of neuromuscular junction (NMJ). A characteristic pathology of patients with early onset MG is thymic hyperplasia with ectopic germinal centers (GC). However, mechanisms that trigger and maintain thymic hyperplasia are poorly characterized. Micro-RNAs (miRNA) are small, non-coding RNAs that are increasingly appreciated to be involved in the pathology of several autoimmune diseases. In order to determine the central mechanisms involved in the pathology, thymus samples from MG patients were assessed by histology and grouped based on appearance of GC compared to samples without them. MiRNA and mRNA were evaluated using GeneChip® miRNA 4.0 Array and GeneChip® Human Transcriptome Array 2.0, respectively. Partek Genomic Suite 6.6 and Transcript Analysis Console 2.0 programs were used for further analysis. Thirty-four mature miRNA and forty eight annotated mRNA transcripts were identified that were differentially expressed between the two groups with greater than 1.5 fold difference in expression (ANOVA p Our study shows that there is a distinct mRNA and miRNA expression pattern in the thymus and maintenance of autoimmunity is supported by regulatory pathways known to be involved in neoplasia

Differential mRNA expression in ectopic germinal centers of myasthenia gravis thymus

Myasthenia gravis (MG) is an autoimmune neuromuscular disorder resulting in weakness of voluntary muscles. It is caused by antibodies directed against proteins present at the post-synaptic surface of neuromuscular junction (NMJ). A characteristic pathology of patients with early onset MG is thymic hyperplasia with ectopic germinal centers (GC). However, mechanisms that trigger and maintain thymic hyperplasia are poorly characterized. In order to determine the central mechanisms involved in the pathology, thymus samples from MG patients were assessed by histology and grouped based on appearance of GC compared to samples without them. We assessed the differential mRNA expression profiles between the two groups by GeneChip® Human Transcriptome Array 2.0. Partek Genomic Suite 6.6 and Transcript Analysis Console 2.0 programs were used for further analysis. Forty eight annotated mRNA transcripts were identified that were differentially expressed between the two groups with greater than 1.5 fold difference in expression (ANOVA p\u3c0.05). We verified their expression by RT-PCR. We identified Regulator of G protein Signaling 13 or RGS13 that is known to be expressed in GC B-cells and regulate responsiveness to chemokine signaling. Upregulation of RGS13 was found to be associated with specimens having GC. We verified its expression in GC by immunohistochemistry. Gene ontology (GO) enrichment analysis and Ingenuity Pathway Analysis (IPA) core analysis of differentially expressed genes indicate involvement of immune response regulation and cell proliferation pathways, indicating their importance in GC formation and regulation

Two membrane proteins located in the Nag regulon of Candida albicans confer multidrug resistance

Pathogenic fungus Candida albicans can efficiently utilize the aminosugar N-acetylglucosamine (GlcNAc) as energy source. Since the mucosal membrane, the site of infection is rich in amino sugars, this specific adaptation is important for the establishment of infection. The genes encoding for the enzymes of the GlcNAc catabolic pathway, GlcNAc kinase (HXK1), GlcNAc-6-phosphate deacetylase (DAC1), and glucosamine-6-phosphate deaminase (NAG1), are present in a cluster, the Nag regulon, which is associated with virulence. In this study, we have characterized two genes, TMP1 and TMP2, present within the Nag regulon, upstream to DAC1. They encode two membrane associated sugar transporters of the major facilitator superfamily (MFS). The null mutant of TMP1 and TMP2 is able to grow in GlcNAc, implying that they are not involved in GlcNAc transport. However, it shows increased susceptibility to a number of unrelated antifungal compounds such as cycloheximide, 4-nitroquinoline-N-oxide, and 1-10 phenanthroline. Northern blot analysis revealed that TMP1 and TMP2 are upregulated in response to these drugs, suggesting that they function as multiple drug efflux pumps

Target validation of differentially expressed miRNA in ectopic germinal centers of myasthenia gravis thymus

Myasthenia gravis (MG) is an autoimmune neuromuscular disorder resulting in weakness of voluntary muscles. The autoantibodies are directed against proteins present at the post-synaptic surface of neuromuscular junction (NMJ). A characteristic pathology of patients with early onset MG (EOMG) is thymic hyperplasia with ectopic germinal centers (GC). However, mechanisms that trigger and maintain thymic hyperplasia are poorly characterized. Previous study assessed the central mechanisms involved in the formation of GCs in the thymus through analysis of the microRNA (miRNA) and mRNA expression. Briefly, thymus samples from EOMG patients were grouped based on appearance of GC. MiRNA and mRNA were evaluated using GeneChip® miRNA 4.0 Array and GeneChip® Human Transcriptome Array 2.0, respectively. Partek Genomic Suite 6.6 and Transcript Analysis Console 2.0 programs were used for further analysis. Thirty-four mature miRNAs and forty-six annotated mRNA transcripts were differentially expressed between the two groups (\u3e1.5 fold change, ANOVA p\u3c0.05). Reciprocal pairing analysis of miRNA and mRNA identified 11 pairs of miRNA and target mRNA. Target Scan identified Regulator of G protein Signalling 13 (RGS13), known to be involved in GC regulation, as potential target for miR139-5p and miR 452-5p. Interferon Regulatory Factor 8 (IRF8) expressed in GC positive samples was identified as another target for miR-452-5p. Both RGS13 and IRF8 are upregulated in GC positive samples. In this study, we validated the reciprocal pairing of miRNA (miR139-5p and miR452-5p) and the target mRNAs (RGS13 and IRF8). Dual luciferase assay was used to validate target binding. Putative miRNA binding region from 3’ untranslated region (UTR) of these genes were cloned into pmirGlo vector downstream of firefly luciferase gene. The constructs were co-transfected with respective miRNA mimics and negative controls in 293T cell lines. Luciferase assay was performed 48 hours post transfection. Firefly luciferase activity was normalized to the Renilla luciferase activity as internal control. There was significant decrease in firefly luciferase activity on transfection of miRNA mimic as compared to negative control. Our results shown that target genes RGS13 and IRF8 are regulated by the miRNA

P1 Plasmid Segregation: Accurate Redistribution by Dynamic Plasmid Pairing and Separation▿ †

Low-copy-number plasmids, such as P1 and F, encode a type Ia partition system (P1par or Fsop) for active segregation of copies to daughter cells. Typical descriptions show a single central plasmid focus dividing and the products moving to the cell quarter regions, ensuring segregation. However, using improved optical and analytical tools and large cell populations, we show that P1 plasmid foci are very broadly distributed. Moreover, under most growth conditions, more than two foci are frequently present. Each focus contains either one or two plasmid copies. Replication and focus splitting occur at almost any position in the cell. The products then move rapidly apart for approximately 40% of the cell length. They then tend to maintain their relative positions. The segregating foci often pass close to or come to rest close to other foci in the cell. Foci frequently appear to fuse during these encounters. Such events occur several times in each cell and cell generation on average. We argue that foci pair with their neighbors and then actively separate again. The net result is an approximately even distribution of foci along the long cell axis on average. We show mathematically that trans-pairing and active separation could greatly increase the accuracy of segregation and would produce the distributions of foci that we observe. Plasmid pairing and separation may constitute a novel fine-tuning mechanism that takes the basic pattern created when plasmids separate after replication and converts it to a roughly even pattern that greatly improves the fidelity of plasmid segregation

Alpha-fetoprotein inhibition of lymphocyte proliferation in vitro cell culture related to myasthenia gravis

BACKGROUND Autoimmune myasthenia gravis (MG) is a disorder of the neuromuscular junction caused in the majority of patients by autoantibodies directed against the postsynaptic nicotinic acetylcholine receptor (AChR). The prevalence of myasthenia gravis in the United States is estimated at 14 to 20 per 100,000 population and women are more often affected than men. Cholinesterase inhibitors, corticosteroids and immunosuppressant are commonly used classes of drugs to treat MG patients but these drugs do not prevent disease progression and are associated with serious side effects. Alpha-fetoprotein (AFP), a serum protein produced by the yolk sac and the fetal liver, is present in high amounts during pregnancy. The clinical remission of myasthenia gravis during the second half of pregnancy may be attributed to the immunosuppressive effect of AFP. METHOD The peripheral blood lymphocytes (PBLs) were obtained from MG patients and healthy controls (HCs) by using density gradient media (Ficoll). PBLs were cultured 5 days after the proliferation dye combination, and then the effect of PHA, hAChR and AFP on the proliferation of lymphocytes were investigated by using flow cytometry. RESULTS Both PHA and hAChR treatment can promote lymphocytes’ proliferation. The human AChR selectively induced MG patient’s lymphocytes proliferation, but not affect the cell growth of the healthy control. AFP treatment can significantly inhibit lymphocytes proliferation in a dose dependent manner without any effect on the healthy control. CONCLUSION AFP inhibits the peripheral lymphocyte proliferation of MG patients by in vitro cell culture. However, AFP did not affect proliferation of PBLs in healthy control samples. The immunosuppressive effect of AFP demonstrated AFP might be a potential therapeutic reagent for autoimmune myasthenia gravis patients

Serum Metabolomic Response of Myasthenia Gravis Patients to Chronic Prednisone Treatment

<div><p>Prednisone is often used for the treatment of autoimmune and inflammatory diseases but they suffer from variable therapeutic responses and significant adverse effects. Serum biological markers that are modulated by chronic corticosteroid use have not been identified. Myasthenia gravis is an autoimmune neuromuscular disorder caused by antibodies directed against proteins present at the post-synaptic surface of neuromuscular junction resulting in weakness. The patients with myasthenia gravis are primarily treated with prednisone. We analyzed the metabolomic profile of serum collected from patients prior to and after 12 weeks of prednisone treatment during a clinical trial. Our aim was to identify metabolites that may be treatment responsive and be evaluated in future studies as potential biomarkers of efficacy or adverse effects. Ultra-performance liquid chromatography coupled with electro-spray quadrupole time of flight mass spectrometry was used to obtain comparative metabolomic and lipidomic profile. Untargeted metabolic profiling of serum showed a clear distinction between pre- and post- treatment groups. Chronic prednisone treatment caused upregulation of membrane associated glycerophospholipids: phosphatidylcholine, phosphatidylethanolamine, phosphatidylserine, 1, 2-diacyl-sn glycerol 3 phosphate and 1-Acyl-sn-glycero-3-phosphocholine. Arachidonic acid (AA) and AA derived pro-inflammatory eicosanoids such as 18-carboxy dinor leukotriene B4 and 15 hydroxyeicosatetraenoic acids were reduced. Perturbations in amino acid, carbohydrate, vitamin and lipid metabolism were observed. Chronic prednisone treatment caused increase in membrane associated glycerophospholipids, which may be associated with certain adverse effects. Decrease of AA and AA derived pro-inflammatory eicosanoids demonstrate that immunosuppression by corticosteroid is via suppression of pro-inflammatory pathways. The study identified metabolomic fingerprints that can now be validated as prednisone responsive biomarkers for the improvement in diagnostic accuracy and prediction of therapeutic outcome.</p></div

Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) of determinants in positive and negative ionization mode.

<p><b>A)</b> Scores plot obtained from OPLS-DA model of T1 and T2 in positive ionization mode shows inter-group separation <b>B)</b> OPLS-DA loadings S-plot comparing features from T1 and T2 in positive ionization mode. <b>C)</b> Score plot obtained from OPLS-DA model of T1 and T2 in negative ionization mode shows inter-group separation. <b>D)</b> OPLS-DA loadings S-plot comparing features from t1 and t2 in negative ionization mode. Each spot in S-plot corresponds to a feature with characteristic m/z ratio and retention time. The metabolites marked in red were treated as putative bio-markers for the therapy and characterized later.</p

Prednisone treatment of MG patients shows clear segregation of metabolite patterns in positive and negative ionization mode.

<p><b>A)</b> Two dimensional accuracy plot for 750 features interrogated in positive ionization mode using Random Forests (RF). It shows clear separation of the two groups T1 (before treatment in blue) and T2 (after treatment in red). X-axis denotes inter-class class separation and Y-axis shows intra-class variability <b>B)</b> Accuracy plot for RF in positive ionization mode shows 100% accuracy. <b>C)</b> Two dimensional accuracy plot for 703 features interrogated in negative ionization mode using Random Forests (RF). It shows clear separation of T1 and T2. <b>D)</b> Accuracy plot for RF in negative ionization shows 100% accuracy. <b>E)</b> Heat map visualization of the top 50 discriminating features between T1 and T2 in positive mode. <b>F)</b> The top 50 discriminating features between T1 and T2 in negative mode.</p

Significantly altered metabolites in pre and post treatment groups.

1<p>Metabolic pathway involved.</p>2<p>Metabolites.</p>3<p>Metabolite ID obtained from KEGG.</p>4<p>mass/charge value.</p>5<p>Retention Time.</p>6<p>Ionization modes.</p>7<p>Fold changes between post-treatment (T2) and pre-treatment (T1) groups with +/−SEM.</p>8<p>The p-value as determined by student’s t-test.</p