Integrated Expression Profiles of mRNA and miRNA in Polarized Primary Murine Microglia

<div><p>Neuroinflammation contributes to many neurologic disorders including Alzheimer’s disease, multiple sclerosis, and stroke. Microglia is brain resident myeloid cells and have emerged as a key driver of the neuroinflammatory responses. MicroRNAs (miRNAs) provide a novel layer of gene regulation and play a critical role in regulating the inflammatory response of peripheral macrophages. However, little is known about the miRNA in inflammatory activation of microglia. To elucidate the role that miRNAs have on microglial phenotypes under classical (M1) or alternative (M2) activation under lipopolysaccharide (‘M1’-skewing) and interleukin-4 (‘M2a’-skewing) stimulation conditions, we performed microarray expression profiling and bioinformatics analysis of both mRNA and miRNA using primary cultured murine microglia. miR-689, miR-124, and miR-155 were the most strongly associated miRNAs predicted to mediate pro-inflammatory pathways and M1-like activation phenotype. miR-155, the most strongly up-regulated miRNA, regulates the signal transducer and activator of transcription 3 signaling pathway enabling the late phase response to M1-skewing stimulation. Reduced expression in miR-689 and miR-124 are associated with dis-inhibition of many canonical inflammatory pathways. miR-124, miR-711, miR-145 are the strongly associated miRNAs predicted to mediate anti-inflammatory pathways and M2-like activation phenotype. Reductions in miR-711 and miR-124 may regulate inflammatory signaling pathways and peroxisome proliferator-activated receptor-gamma pathway. miR-145 potentially regulate peripheral monocyte/macrophage differentiation and faciliate the M2-skewing phenotype. Overall, through combined miRNA and mRNA expression profiling and bioinformatics analysis we have identified six miRNAs and their putative roles in M1 and M2-skewing of microglial activation through different signaling pathways.</p></div

Proposed microglial phenotype transition model

<p>. At the M0 state (top), resting microglia function in a surveillance and detection mode, which appears to be regulated by various nuclear receptor pathways and select miRNAs: miR-124, miR-689 and miR-711. Upon detection of a danger or pattern molecule, the resting status is disrupted and transitions to the M1 state (right). The M1 phenotype is the “classic activation” status and prominently induces canonical M1 marker genes, e.g. IL-1β, TNF-α and IL-6. miR-124 and miR-689 are critical in initiation of the transition from the M0 to the M1 state. The M1 phenotype appears to be fully mediated by miR-155, which targets the STAT3 pathway for enabling the M1-phenotype. Later, through transition from M1 to M2 or through direct IL-4 stimulation (dashed line), microglia may enter the M2a status, characterized as an anti-inflammatory and resolution phenotype. As observed with in M1, down-regulation in miR-124 and miR-711 appears to be important for release from the M0-phenotype and transition to the M2 status. The M2a-phenotype appears to rely on induction of miR-145, which may regulate the ETS1 pathway. Lastly, IL-4 signaling is dependent on STAT6, TRIM24, and CREB1 along with select nuclear receptor signaling: PPARα/γ and RARα.</p

Summary of genome-wide mRNA profiles of M1- or M2a-skewed microglia.

<p>(A) Heatmap of top 63 differentially regulated genes among the M1-skewed (LPS), M2a-skewed (IL-4) and M0 resting microglia from mRNA microarray analysis (Moderated FDR q<1×10⁻⁷). Color scheme: Blue (below average), white (average) and red (above average). 1, 2, and 3 are replicates for each individual microarray of the LPS, IL-4 or PBS-treated conditions. (B-C) Top 15 up-regulated genes in M1-skewed microglia (B) or M2a-skewed microglia (C) (n = 3, p<1×10⁻⁵ vs. PBS group as determined by Student’s <i>t</i>-test). (D) Real-time RT-PCR test of select genes in M0, M1 or M2a-skewed microglia. Canonical M1 markers (IL-6, IL-1β, TNF-α and NOS2), M2b markers (IL-10 and PAI-1) and M2a markers (Chi3l3 and Arg1) were tested. ΔΔCT values were vs. M0 group (n = 4, ** or *** denotes p<0.01 or 0.001, respectively). (E) Scatter plot comparison of real time RT-PCR (or LNA-based RT-PCR for miRNA) ΔΔCT values of select genes and miRNA in microglia isolated by Percoll® density gradient (X-axis) vs. microglia isolated by magnetic beads (Y-axis). Cells were cultured for five days and stimulated with LPS (for IL-6, NOS2, IL-1β, TNF-α, or miR-155 expression) or IL-4 (for Arg1 expression). Pearson’s correlation coefficient: r² = 0.72.</p

LPS differentially regulated genes correlated with miR-155 expression levels.

<p>LPS differentially regulated genes correlated with miR-155 expression levels.</p

Bioinformatic correlation analysis of miRNA:mRNA interactions in microglia

<p>. (A) Method employed for miRNA:mRNA correlation analysis and miRNA potential target enrichment analysis. Briefly, Pearson’s correlation analysis was performed to identify the genes most highly correlated with select miRNA expression profiles. This new gene set was then compared with predicted miRNA targeting gene sets. Common miRNA-correlated target genes were uploaded to Ingenuity® Systems and enrichment analysis was performed to identify targeted functions, targeted pathways, targeted transcriptional networks, and targeted networks. (B) Venn-diagram analysis of representative miRNA:mRNA correlation analysis for miR-155 targets. Predicted targets of miR-155 were derived from public sources (miRanda Database, Ingenuity or TargetScan). miR-155-correlated genes were selected based on two key criteria: a fold change p<0.0001 and strong correlation with miR-155 (r>0.5 or r<–0.5). Venn-diagram shows the intersection gene set of 112 commonly predicted targets that were also strongly correlated with miR-155. (C-D) The top 15 altered transcriptional networks and the corresponding miRNA are presented. IPA-based enrichment analysis was performed on intersected genes for each miRNA to identify key transcriptional networks in the M1-skewed (C) or M2a-skewed microglia (D). Identified transcriptional networks were pooled together from all miRNA altered in the M1- (C) or M2-skewing condition (D) and then sorted by -Log(p-value). Dotted line denotes p<0.05, corresponding to –Log(p-value) > 1.30, as statistical threshold.</p

Overall differentially regulated genes (p<0.0001) and miRNAs (p<0.05) by M1 (LPS) and M2a (IL-4) stimulation.

<p>Overall differentially regulated genes (p<0.0001) and miRNAs (p<0.05) by M1 (LPS) and M2a (IL-4) stimulation.</p

Additional file 1 of Regulating microglial miR-155 transcriptional phenotype alleviates Alzheimer’s-induced retinal vasculopathy by limiting Clec7a/Galectin-3+ neurodegenerative microglia

Additional file1: Supplementary Figures 1-9 and Tables 1-8