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Protein Kinase C Theta Modulates PCMT1 through hnRNPL to Regulate FOXP3 Stability in Regulatory T Cells - PubMed

  • ️Wed Jan 01 2020

Protein Kinase C Theta Modulates PCMT1 through hnRNPL to Regulate FOXP3 Stability in Regulatory T Cells

E Ilker Ozay et al. Mol Ther. 2020.

Abstract

T cell receptor signaling, together with cytokine-induced signals, can differentially regulate RNA processing to influence T helper versus regulatory T cell fate. Protein kinase C family members have been shown to function in alternative splicing and RNA processing in various cell types. T cell-specific protein kinase C theta, a molecular regulator of T cell receptor downstream signaling, has been shown to phosphorylate splicing factors and affect post-transcriptional control of T cell gene expression. In this study, we explored how using a synthetic cell-penetrating peptide mimic for intracellular anti-protein kinase C theta delivery fine-tunes differentiation of induced regulatory T cells through its differential effects on RNA processing. We identified protein kinase C theta signaling as a critical modulator of two key RNA regulatory factors, heterogeneous nuclear ribonucleoprotein L (hnRNPL) and protein-l-isoaspartate O-methyltransferase-1 (PCMT1), and loss of protein kinase C theta function initiated a "switch" in post-transcriptional organization in induced regulatory T cells. More interestingly, we discovered that protein-l-isoaspartate O- methyltransferase-1 acts as an instability factor in induced regulatory T cells, by methylating the forkhead box P3 (FOXP3) promoter. Targeting protein-l-isoaspartate O-methyltransferase-1 using a cell-penetrating antibody revealed an efficient means of modulating RNA processing to confer a stable regulatory T cell phenotype.

Keywords: FOXP3; PCMT1; PKCθ; alternative splicing; cell-penetrating peptide mimics; hnRNPL; induced regulatory T cell; intracellular antibody delivery.

Copyright © 2020 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

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Graphical abstract
Figure 1
Figure 1

Ex Vivo Anti-pPKCθ Delivery into iTregs Modulates Splicing Regulatory Proteins and RNA Processing (A) Cytoplasmic and nuclear distribution of pSC35 in anti-pPKCθ-iTregs was analyzed by immunoblotting. Normalized densities for cytoplasmic pSC35 were quantified relative to tubulin expression. (B) Alternative splicing of CD45 (PTPRC) was analyzed in iTregs using RT-PCR. Primers were designed to assess 3′ UTR processing using RT-PCR and covered sequences from the last exon to the polyadenylation site. (C–F) Results and cartoon representations are shown for (C) PDCD1, (D) FOXP3, (E) IFNG, and (F) IFNGR1. Red frames indicate expected amplicon sizes for mature mRNA with its 3′ UTR. Data represent the mean ± SEM of two or three independent experiments. An unpaired, two-tailed Student’s t test was used for analysis. ∗∗∗p < 0.001.

Figure 2
Figure 2

Ex Vivo Treatment of iTregs Conveys Durable Tissue-, Cell-, and Gene-Specific Modulation of RNA Processing In Vivo hPBMCs were transferred on day 0 together with anti-pPKCθ-iTregs (or DMSO-iTregs) at a ratio of 3:1. On day 17, tissues were harvested and iTregs were isolated based on CD4+, CD25+, CD127 expression, using magnetic beads. Total RNA was extracted from ex vivo-treated iTregs recovered from BM and spleen on day 17. (A–E) RT-PCR was used to evaluate alternatively spliced (A) CD45 (PTPRC), and alternative splicing and 3′ UTR processing of (B) PDCD1, (C) FOXP3, (D) IFNG, and (E) IFNGR1. Red frames indicate the expected amplicon size, and the cartoon representation for expected amplicon size is shown for each gene. Data are representative of three independent experiments from five mice per condition.

Figure 3
Figure 3

In iTregs, PCMT1 Is Regulated through Post-translational and Post-transcriptional Processes (A) PCMT1 protein in cytosolic and nuclear extracts was detected using immunoblotting, and band intensity was quantified relative to tubulin and histone H3 expression, respectively, using ImageJ software. (B) λ-Phosphatase treatment was used to confirm PCMT1 phosphorylation. pSTAT1 was used as a phosphorylation control. Total STAT1 and pSTAT1 (Y701) were quantified using ImageJ software. (C) PCMT1 splicing and 3′ UTR lengths were analyzed using RT-PCR in ex vivo-treated iTregs. (D) PCMT1 splicing and 3′ UTR length were analyzed using RT-PCR and PCMT1 gene expression was quantified using qPCR in iTregs isolated from (E) BM and (F) spleen of iTreg-treated mice on day 17. Red frames indicate the expected amplicon sizes. Data represent the mean ± SEM of two or three independent experiments. For in vivo experiments, four mice per group were used. An unpaired, two-tailed Student’s t test was used for analysis. ∗∗p < 0.01, ∗∗∗p < 0.001.

Figure 4
Figure 4

Ex Vivo Anti-PCMT1 Delivery Enhances iTreg Differentiation (A) Percentages of CD4+CD25+FOXP3+ T cells with representative scatterplots following ex vivo treatment with cell-penetrating anti-pPKCθ or anti-PCMT1 delivery. (B) Percentage of FOXP3high iTregs and FOXP3 median fluorescent intensities (MFIs) together with their representative histograms of iTregs treated as in (A). (C) Percentage of IFNγ+ iTregs and fold increase in IFNγ MFI, together with representative histograms, of iTregs treated as in (A). (D) Cytoplasmic and nuclear distributions of hnRNPL in anti-pPKCθ-iTregs were analyzed by immunoblotting. Normalized densities for cytoplasmic and nuclear hnRNPL were quantified relative to tubulin and histone H3 expression, respectively. (E) Cytosolic and nuclear association of hnRNPL with PKCθ and PCMT1 in iTregs was determined using co-immunoprecipitation. (F) Predicted hnRNPL RNA binding motifs using the Catalog of Inferred Sequence Binding Preferences of RNA binding proteins (CISBP-RNA) database in humans. (G) Schematic of hnRNPL binding to the PCMT1 3′ UTR and (H) hnRNPL association with cytosolic and nuclear PCMT1 mRNA in anti-pPKCθ-iTregs and anti-PCMT1-iTregs. Red frames indicate the expected amplicon size. Data represent the mean ± SEM of two or three independent experiments. An unpaired, two-tailed Student’s t test was used for analysis. ∗p < 0.05, ∗∗p < 0.01.

Figure 5
Figure 5

PCMT1 Acts to Destabilize the iTreg Phenotype through Its Effects on FOXP3 Methylation (A) Chromatin immunoprecipitation quantifying PCMT1 occupancy on the FOXP3 promoter in iTregs. (B) CpG islands (indicated in bold type) and STAT5-binding sites (underlined in blue) in the human FOXP3 TSDR. (C) Bisulfite sequencing of 10 different clones per iTreg treatment showing FOXP3 TSDR CpG islands. Percentages of CpGs demethylated at sites #3, #4, #14, and #15 were quantified and are shown as pie charts. (D) Nuclear localization of pSTAT5 (Tyr694) was quantified by imaging flow cytometry using Amnis ImageStream analysis. Representative cell frequency histograms, along with representative images at ×60 magnification, show anti-pPKCθ-iTregs with nuclear pSTAT5. The Amnis IDEAS wizard, with nuclear masking applied, was used to quantify nuclear localization of pSTAT5, based on similarity score. Data represent mean ± SEM of two or three independent experiments. An unpaired, two-tailed Student’s t test was used for analysis. ∗p < 0.05, ∗∗p < 0.01.

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