MicroRNA and mRNA expression associated with ectopic germinal centers in thymus of myasthenia gravis

Abstract

Background: A characteristic pathology of early onset myasthenia gravis is thymic hyperplasia with ectopic germinal centers (GC). However, the mechanisms that trigger and maintain thymic hyperplasia are poorly characterized. Dysregulation of small, non-coding microRNAs (miRNAs) and their target genes has been identified in the pathology of several autoimmune diseases. We assessed the miRNA and mRNA profiles of the MG thymus and have investigated their role in GC formation and maintenance.

Methods: MG thymus samples were assessed by histology and grouped based upon the appearance of GC; GC positive and GC negative. A systems biology approach was used to study the differences between the groups. Our study included miRNA and mRNA profiling, quantitative real-time PCR validation, miRNA target identification, pathway analysis, miRNA-mRNA reciprocal expression pairing and interaction.

Results: Thirty-eight mature miRNAs and forty-six annotated mRNA transcripts were differentially expressed between the two groups (>1.5 fold change, ANOVA p<0.05). The miRNAs were found to be involved in immune response pathways and identified in other autoimmune diseases. The cellular and molecular functions of the mRNAs showed involvement in cell death and cell survival, cellular proliferation, cytokine signaling and extra-cellular matrix reorganization. Eleven miRNA and mRNA pairs were reciprocally regulated. The Regulator of G protein Signalling 13 (RGS13), known to be involved in GC regulation, was identified in specimens with GC and was paired with downregulation of miR-452-5p and miR-139-5p. MiRNA target sites were validated by dual luciferase assay. Transfection of miRNA mimics led to down regulation of RGS13 expression in Raji cells.

Conclusion: Our study indicates a distinct miRNA and mRNA expression pattern in ectopic GC in MG thymus. These miRNAs and mRNAs are involved in regulatory pathways common to inflammation and immune response, cell cycle regulation and anti-apoptotic pathways suggesting their involvement in support of GC formation in the thymus. We demonstrate for the first time that miR-139-5p and miR-452-5p negatively regulate RGS13 expression.

Fig 1. Differential small RNA expression profiles of MG thymus samples with and without germinal centers (GC).

(A) Principal Component Analysis (PCA) plot. (B) Hierarchical clustergram plot (ANOVA p<0.05, no fold change). The plots demonstrate clear separation between the groups. GC positive n = 7; GC negative n = 9. (C) qRT-PCR validation of miRNA expression array results. The gray bars represent array data while the black bars represent qRT-PCR data. Log2 fold change has been plotted. Error bars represents +/- SEM. The qRT-PCR results that showed significant differences (as determined by student’s t test, p<0.05) between the GC positive vs GC negative groups have been plotted.

Fig 2. IPA core analysis program identified micro RNA network involved in cancer, gastrointestinal disease, organismal injury and abnormalities pathways.

The solid arrows indicate direct interactions and the dotted arrows indicate indirect interaction between the differentially expressed miRNA and their predicted targets. The miRNAs that are over expressed in GC positive samples are marked in red and those repressed are marked in green.

Fig 3. Differential mRNA expression profiles of thymus samples with and without germinal centers.

(A) PCA plot and (B) Hierarchical clustergram plot (ANOVA p<0.05, no fold change). GC positive n = 7; GC negative n = 6. The plots demonstrate clear separation between the groups. (C) qRT-PCR validation of mRNA expression array results. The gray bars represent array data while the black bars represent qRT-PCR data. Log2 fold change has been plotted. Error bars represents +/- SEM. The qRT-PCR results that showed significant differences (as determined by student’s t test, p<0.05) between the GC positive vs GC negative groups have been plotted.

Fig 4

A) Biological and molecular processes with over representation of transcripts as identified by GO. The bars represent the number of transcripts in each process. B) Top five molecular and cellular functions of the differentially expressed genes as identified by IPA analysis.

Fig 5. Hematological system development and function, tissue morphology, and inflammatory response network.

Gene associated network function was identified by IPA core analysis. The solid arrows indicate direct interactions and the dotted arrows indicate indirect interaction between the differentially expressed mRNA. The over expressed genes in GC positive samples are marked in red.

Fig 6. Reciprocal expression of miRNA and mRNA in thymus.

qRT-PCR validation of miR-139-5p (A), miR-452-5p (B) and (C) RGS13 expression in the two groups show reciprocal expression of the micro RNAs and RGS13 mRNA. Each dot represents data obtained from a patient. It is expressed as +/- SEM. The level of expression for miRNAs was normalized to that of the U6 RNA. RGS13 expression was normalized to GAPDH expression. Student’s t test was performed with p<0.05 considered as significant.

Fig 7. Regulation of RGS13 expression by miRNAs 139-5p and 452-5p.

A) 3’UTR of RGS13 gene has predicted binding sites for miR-139-5p and miR-452-5p. Sequence alignment between miR-139-5p and miR-452-5p seed sequences with 3’ UTR of human RGS13 as predicted by TargetScan. Solid line represents seed match region. B) Dual luciferase assay validating miRNA targets in RGS13 3’UTR. Predicted target sites of miR-139-5p and 452-5p were cloned into pmirGlo plasmid. 293T cells were co-transfected with target plasmids and 10nM of miRNA mimic or negative control. Luciferase assay was performed after 48 hours post transfection. C) qRT-PCR analysis RGS13 expression in Raji cells post transfection with miRNA mimics of miR-139-5p and miR-452-5p. A nonspecific scramble RNA is used as a negative control. A mock transfection was set up without any RNA. RGS13 transcript level was reduced after 72 hours of transfection. Human GAPDH expression was used as internal control. The data represents average of three independent experiments done in triplicate. The error bars indicates SEM +/-. Student’s t-test was performed, p< 0.05 is considered as significant.

Fig 8. The differentially expressed mRNA in GC positive biopsies highlight molecular and cellular functions that are important for GC formation and maintenance.

The differentially expressed transcripts belong to immune response, cellular movement and extracellular matrix reorganization, cell communication, signal transduction and cell proliferation and apoptosis. These pathways are important for GC functions. The transcripts that are upregulated in GC positive samples are marked in red while the ones that are downregulated are marked in green. The miRNAs that are reciprocally expressed with mRNA targets are marked. The transcripts that are known to be expressed by GC B cells and dendritic cells are shown. ECM, Extra cellular matrix.