MicroRNA regulation of molecular networks mapped by global microRNA, mRNA, and protein expression in activated T lymphocytes

Abstract

MicroRNAs (miRNAs) regulate specific immune mechanisms, but their genome-wide regulation of T lymphocyte activation is largely unknown. We performed a multidimensional functional genomics analysis to integrate genome-wide differential mRNA, miRNA, and protein expression as a function of human T lymphocyte activation and time. We surveyed expression of 420 human miRNAs in parallel with genome-wide mRNA expression. We identified a unique signature of 71 differentially expressed miRNAs, 57 of which were previously not known as regulators of immune activation. The majority of miRNAs are upregulated, mRNA expression of these target genes is downregulated, and this is a function of binding multiple miRNAs (combinatorial targeting). Our data reveal that consideration of this complex signature, rather than single miRNAs, is necessary to construct a full picture of miRNA-mediated regulation. Molecular network mapping of miRNA targets revealed the regulation of activation-induced immune signaling. In contrast, pathways populated by genes that are not miRNA targets are enriched for metabolism and biosynthesis. Finally, we specifically validated miR-155 (known) and miR-221 (novel in T lymphocytes) using locked nucleic acid inhibitors. Inhibition of these two highly upregulated miRNAs in CD4(+) T cells was shown to increase proliferation by removing suppression of four target genes linked to proliferation and survival. Thus, multiple lines of evidence link top functional networks directly to T lymphocyte immunity, underlining the value of mapping global gene, protein, and miRNA expression.

Figure 1

Combinatorial targeting by multiple upregulated miRNAs during T cell activation demonstrates decreased mRNA levels after activation with increased miRNA binding. (A) Schematic of our experimental approach. (B) miRNA signature of T cell activation: Heat-map of 71 statistically significant (p<0.05, q<0.1) differentially expressed miRNAs at 0 and 48 hours. Heatmap shows expression at 0, 24, 48 and 72 hours across 7 donors. Red represents positive change, cyan represents negative change, white represents no change. (C): A Cumulative Distribution Function (CDF) plot of relative fold change between 0 and 48 hours of combined PITA, TargetScan/conservation and TargetScan/context, top 50^th percentile predictions in each, 2+ miRNAs targeting each gene. Target genes in red, non-target genes in blue. (D): Same as (A) with 4+ miRNAs targeting each gene (E): PITA, top 50^th percentile predictions, 4+ miRNAs targeting a given gene. Target genes in red, non-target genes in blue. (F): PITA, top 50^th percentile predictions with 7+ miRNAs targeting a given gene. Target genes in red, non-target genes in blue. (G): TargetScan/context score, top 50^th percentile predictions, 4+ miRNAs targeting a given gene. Target genes in red, non-target genes in blue. (H): TargetScan/context score, top 50^th percentile predictions, 7+ miRNAs targeting a given gene. Target genes in red, non-target genes in blue. (I): TargetScan/conservation score, top 50^th percentile predictions, 4+ miRNAs targeting a given gene. Target genes in red, non-target genes in blue. (J): TargetScan/conservation score, top 50^th percentile predictions, 7+ miRNAs targeting a given gene. Target genes in red, non-target genes in blue.

Figure 2

Functional analysis of predicted targets of upregulated miRNAs reveals networks associated with immunity, cell survival, and proliferation. (A) Top 30 overrepresented canonical pathways for downregulated gene targets of upregulated miRNAs. Pathways are sorted by score (−log [multiple testing corrected p-value]). A higher score indicates that the pathway is more significantly associated with genes of interest. The line represents statistically significant threshold limit. (B) Significantly overrepresented canonical pathways for non-target differentially expressed genes 0vs48 hours. (C) Top direct interaction network representing 21 downregulated target focus genes, overlaid with predicted major miRNA targeting and functions associated with nodal genes.

Figure 3

Functions of genes targeted by downregulated miRNAs. Top 30 overrepresented canonical pathways for gene targets of upregulated as well as downregulated miRNAs and downregulated miRNAs only. Pathways are sorted by score (−log [multiple testing corrected p-value]). A higher score indicates that the pathway is more significantly associated with genes of interest. The line represents statistically significant threshold limit. The pathways linked to only downregulated miRNAs are predominantly cell metabolism and biosynthesis, much like the genes not targeted by miRNAs. In contrast, the pathways linked to combinatorial targeting by both up and downregulated miRNAs are enriched for signaling in immunity, growth and cell proliferation.

Figure 4

Inhibition of miR-155 (known) and miR-221 (novel), 2 highly upregulated miRNAs, in CD4⁺ T cells increased proliferation by removing suppression of 4 target genes linked to proliferation and survival. (A) Top 30 overrepresented canonical pathways for downregulated protein targets of upregulated miRNAs. Pathways are sorted by score. (B) Expression of 19 predicted downregulated protein targets associated with top 3 networks. (C) Real-Time qPCR expression of miR-155 and miR-221 in CD4⁺ T cells nucleoporated with 50nM LNA-antimiR-155 (tan), LNA-antimiR-221 (black), or LNA-scrambled control showing decreased miRNA expression after LNA-antimiR transfection relative to scrambled control, set as 1. Shown are fold changes relative to scrambled control, normalized to U6 snRNA. (D) Increased cell proliferation following knockdown of miR-221 (black) or miR-155 (tan), compared to scrambled control by Cell Proliferation Assay. (E) Real-Time qPCR analysis of predicted targets in CD4⁺ T cells transfected with LNA-antimiR-155 (tan), LNA-antimiR-221 (black), and LNA scrambled control, presented relative to the expression in scrambled control sample, set as 1. (F) Proposed model of miR-155 and 221 negative-feedback regulation of proliferation following T cell activation. CD3/CD28 co-stimulation induces signaling cascades that result in transcription of genes that promote proliferation, activation and immune response. Upregulation of miR-155 and 221 serves to diminish proliferation and immune response by targeting key proliferative genes such as PIK3R1, IRS2 and IKBKE as well as transcription factor FOS. Error bars in (C–E) represent mean ± SEM of triplicate experiments from 3 donors (n=3). *p < 0.05, ***p < 0.0001 (t-test) compared to scrambled control.