Interferon-γ regulates cellular metabolism and mRNA translation to potentiate macrophage activation

Journal name:
Nature Immunology
Volume:
16,
Pages:
838–849
Year published:
DOI:
doi:10.1038/ni.3205
Received
Accepted
Published online

Abstract

Interferon-γ (IFN-γ) primes macrophages for enhanced microbial killing and inflammatory activation by Toll-like receptors (TLRs), but little is known about the regulation of cell metabolism or mRNA translation during this priming. We found that IFN-γ regulated the metabolism and mRNA translation of human macrophages by targeting the kinases mTORC1 and MNK, both of which converge on the selective regulator of translation initiation eIF4E. Physiological downregulation of mTORC1 by IFN-γ was associated with autophagy and translational suppression of repressors of inflammation such as HES1. Genome-wide ribosome profiling in TLR2-stimulated macrophages showed that IFN-γ selectively modulated the macrophage translatome to promote inflammation, further reprogram metabolic pathways and modulate protein synthesis. These results show that IFN-γ–mediated metabolic reprogramming and translational regulation are key components of classical inflammatory macrophage activation.

At a glance

Figures

  1. IFN-[gamma] suppresses HES1 translation.
    Figure 1: IFN-γ suppresses HES1 translation.

    (a) Quantitative PCR (qPCR) analysis of HES1 mRNA expression in human primary macrophages cultured with or without IFN-γ (100 U ml−1) for 24 h and then stimulated with Pam3CSK4 (Pam; 10 ng ml−1) for 0–6 h; results are normalized relative to GAPDH mRNA expression. Data are shown as mean and s.d. of triplicate determinants (cumulative results in Supplementary Fig. 1b). (b) Immunoblot analysis of HES1 in control or IFN-γ–treated macrophages stimulated with Pam (10 ng ml−1) for 0–4 h; p38α served as a loading control. HES1 was suppressed by 85.5% in six independent experiments (P < 0.0001). (c) Top, representative polysome profiles of control (blue) and IFN-γ–treated (red) macrophages stimulated with Pam (10 ng ml−1) for 4 h. Bottom, the ratio of RNA amounts in IFN-γ–treated conditions relative to those in control conditions. Fractions 3 and 4, individual ribosome 40S and 60S subunits; fraction 5, monomeric 80S ribosomes; fractions 6–8, light polysome fractions; fractions 9–12, heavy polysome fractions. Data are presented as mean and s.d. and were analyzed with one-way analysis of variance (ANOVA); P = 0.1383 for difference between IFN-γ–treated and control conditions. (d) Polysome-shift qPCR analysis of HES1, PABPC1 and ACTB mRNA expression in polysome fractions from c, depicted as the percentage of mRNA in each fraction compared with the total mRNA in all fractions (fractions 1–12). (e) Top, qPCR analysis of PABPC1 mRNA expression in control or IFN-γ–treated macrophages from two independent donors; data are shown as mean and s.d. of triplicate determinants. Bottom, immunoblot analysis of PABPC1 from parallel samples in the same experiments; p38α served as a loading control. PABPC1 was suppressed by 68.75% in pooled data from independent experiments; P = 0.01. Data are representative of >20 (a), 23 (b), 3 (c,d) or 4 (e) independent experiments.

  2. IFN-[gamma] inhibits TLR2-induced activation of the MAPK-MNK-eIF4E axis.
    Figure 2: IFN-γ inhibits TLR2-induced activation of the MAPK-MNK-eIF4E axis.

    (a) Immunoblot analysis of phosphorylated (p-) eIF4E and p-MNK1 in control and IFN-γ–primed macrophages treated with Pam3CSK4 (10 ng ml−1) for 0–60 min; p38α served as a loading control. p-eIF4E was suppressed by 69% in six independent experiments (P = 0.0009), and p-MNK1 by 66% in three independent experiments (P = 0.02). (b) Polysome-shift analysis of NFKBIA mRNA expression. (c) Immunoblot analysis of HES1 in human primary macrophages pretreated for 30 min with the vehicle control dimethyl sulfoxide (DMSO) or with increasing concentrations of MNK inhibitor CGP57380 and then stimulated for 0, 2 or 4 h with Pam3CSK4 (10 ng ml−1); p38α served as a loading control. (d) qPCR analysis of HES1 mRNA expression in human primary macrophages. UT, untreated. Data are shown as mean and s.d. of triplicate determinants and are normalized relative to GAPDH mRNA expression. (e) Immunoblot analysis of HES1 and p-eIF4E in human primary macrophages transfected with scrambled control (Ctrl) siRNA or siRNA specific for both MNK1 and MNK2 for 72 h and then stimulated for 0–4 h with Pam3CSK4 (10 ng ml−1); p38α served as a loading control. (f) Immunoblot analysis of p-p38 and p-Erk in control or IFN-γ–primed macrophages treated with Pam3CSK4 (10 ng ml−1) for 0–60 min; p38α and Erk served as loading controls. (g) qPCR analysis of expression of DUSP1, DUSP2, DUSP4, DUSP8 and DUSP16 mRNA in control and IFN-γ–primed macrophages treated with or without Pam3CSK4 for 4 h. Data are shown as mean and s.d. of triplicate determinants and are normalized relative to GAPDH mRNA expression. Data are representative of at least three independent experiments (ag).

  3. IFN-[gamma] suppresses mTORC1 activation and downstream functions.
    Figure 3: IFN-γ suppresses mTORC1 activation and downstream functions.

    (ac) Immunoblot analyses of whole-cell lysates from control and IFN-γ–treated macrophages stimulated with Pam3CSK4 (10 ng ml−1; a,c) for 0–4 h or treated with mTOR inhibitor (PP242 (50 nM), Torin1 (50 nM) or rapamycin (500 nM)) for 30 min (b) and probed with antibody to p–4E-BP1 (a,b) or p-p70S6K (c). IFN-γ suppressed basal 4E-BP1 phosphorylation (52% mean suppression in seven independent experiments; P = 0.0036; a) and phosphorylation of p70S6K (50.5% mean suppression in four independent experiments; P = 0.0031; c). (d) Immunoblot analysis of LC3A and LC3B in control and IFN-γ–primed macrophages treated or not treated with rapamycin. (e) Left, immunofluorescence images of LAMP-1 (red) and mTOR (green) costaining in control and IFN-γ–primed macrophages stimulated with Pam3CSK4 (10 ng ml−1) for 4 h; nuclei were stained with DAPI (blue). Right, quantitation of colocalization of LAMP-1 and mTOR. Data are presented as mean and s.e.m. of the percentage of colocalized cells among 600 cells analyzed in three independent experiments; *P = 0.0001 by unpaired Student's t-test. (f) Immunoblot analysis of HES1 in human primary macrophages pretreated for 30 min with vehicle control DMSO or increasing concentrations of rapamycin (0 nM, 500 nM and 1 μM) and then stimulated with Pam3CSK4 (10 ng ml−1) for 0, 2 or 4 h; p38α served as a loading control. Data are representative of at least three independent experiments (ae).

  4. IDO-mediated tryptophan depletion suppresses mTOR lysosomal localization and HES1 expression.
    Figure 4: IDO-mediated tryptophan depletion suppresses mTOR lysosomal localization and HES1 expression.

    (a) qPCR analysis of IDO1 mRNA in human primary macrophages treated with IFN-γ (100 U ml−1). Data are shown as mean and s.d. of triplicate determinants and are normalized relative to GAPDH mRNA expression. (b) HPLC–mass spectrometry measurement of intracellular L-tryptophan concentration in control and IFN-γ–primed human primary macrophages treated with or without Pam3CSK4 (10 ng ml−1) for 4 h. Data are shown as mean and s.d. of triplicate determinants. (c) Top, immunofluorescence images of LAMP-1 (red) and mTOR (green) costaining in control macrophages (row 1), IFN-γ–primed macrophages (row 2), IFN-γ–primed macrophages pretreated for 30 min with IDO inhibitor 1-D-MT (200 μM) (row 3) and IFN-γ–primed macrophages supplemented with tryptophan (Trp; 800 μM) (row 4). All cells were stimulated with Pam3CSK4 (10 ng ml−1) for 4 h; nuclei were counterstained with DAPI (blue). Bottom, quantitation of colocalization of LAMP-1 and mTOR. Data are presented as mean and s.e.m. of the percentage of colocalized cells among 800 cells counted in two independent experiments; overall P = 0.0008 by one-way ANOVA followed by Bonferroni's multiple-comparison post-test; *P < 0.05, **P < 0.0001. (d,e) Immunoblot analyses of HES1 in control and IFN-γ–primed macrophages treated for 30 min with 1-D-MT (200 μM) (d) or tryptophan (e) and then stimulated with Pam3CSK4 (10 ng ml−1) for 4 h; p38α served as a loading control. P = 0.0003 for HES1 suppression in d. Data are representative of at least three (a,d,e) or two (b,c) independent experiments.

  5. IFN-[gamma] inhibits PI3K-Akt-TSC1/2 signaling and M-CSFR expression.
    Figure 5: IFN-γ inhibits PI3K-Akt-TSC1/2 signaling and M-CSFR expression.

    (ac) Immunoblot analyses of whole-cell lysates from control and IFN-γ–primed macrophages stimulated with Pam3CSK4 (10 ng ml−1). (d) Immunoblot analysis of p-Akt in control and IFN-γ–primed macrophages that were serum- and M-CSF–starved for 4 h, pretreated with vehicle control DMSO or LY294002 (10 μM) for 30 min and then stimulated with M-CSF (100 ng ml−1); Akt served as a loading control. (e) Left, qPCR analysis of CSF1R mRNA expression in control and IFN-γ–primed macrophages. Data are shown as mean and s.d. of triplicate determinants and are normalized relative to GAPDH mRNA expression. Right, immunoblot analysis of M-CSFR in control and IFN-γ–primed macrophages; p38α served as a loading control. (f) qPCR analysis of MYC mRNA in monocytes cultured with M-CSF (20 ng ml−1) with or without IFN-γ. Data are shown as mean and s.d. of triplicate determinants and are normalized relative to GAPDH mRNA expression. (g) Immunoblot analysis of M-CSFR in human primary monocytes treated with vehicle control DMSO or Myc inhibitor 10058-F4 (60 μM) and then cultured with M-CSF (20 ng ml−1); p38α served as a loading control. (h) Immunoblot analysis of p–4E-BP1 in human primary monocytes treated with vehicle control DMSO or Myc inhibitor 10058-F4 (60 μM) for 30 min. (i) Immunoblot analysis of c-Myc in nuclear extracts of control and IFN-γ–primed macrophages stimulated with Pam3CSK4 (10 ng ml−1); TBP served as a loading control. Data are representative of at least three independent experiments (ai).

  6. Genome-wide ribosome-profiling analysis of IFN-[gamma]-mediated translational regulation in macrophages.
    Figure 6: Genome-wide ribosome-profiling analysis of IFN-γ–mediated translational regulation in macrophages.

    (a) Scatter plot comparing the changes in mRNA abundance (x-axis) and TE (y-axis) in response to IFN-γ; 2,976 mRNAs were changed by more than twofold. RNA fold change = log2(RNAIFN-γ/RNAcontrol); TE fold change = log2(TEIFN-γ/TEcontrol). mRNAs with suppressed TE (z-score < −1.5) or induced TE (z-score > 1.5) are in blue or red, respectively. (b) RPF and RNA-Seq read density profiles for PABPC1 in control and IFN-γ–primed macrophages; data are normalized to the total mapped reads in each library. (c) RPF read density profiles for PABPC3, PABPC4 and EEF2 in control and IFN-γ–primed macrophages; data are normalized to the total mapped reads in each library. (d) Polysome-shift analysis of PABPC3, PABPC4 and IRF7 mRNA. (e) Scatter plot comparing the changes in mRNA abundance and ribosome footprint frequency; RNA (log2) = log2(RNAIFN-γ/RNAcontrol); RPF (log2) = log2(RPFIFN-γ/RPFcontrol). Values for mRNAs with 5′ TOP elements are in green. The Pearson correlation value (R) was calculated by GraphPrism. R2 = 0.65 for 65 established 5′ TOP genes; R2 = 0.86 for non-TOP genes. Data were generated from a merged data set of two biological replicates (a,e) or are representative of two (b,c) or three (d) independent experiments.

  7. Selective translational inhibition of mRNAs involved in metabolic processes and protein synthesis by IFN-[gamma].
    Figure 7: Selective translational inhibition of mRNAs involved in metabolic processes and protein synthesis by IFN-γ.

    (a) Ingenuity Pathway Analysis of canonical pathways most enriched in sets of genes either upregulated (red) or downregulated (blue) by IFN-γ at the level of ribosome footprint frequency (RPF); the y-axis indicates the −log10 (P value) of each enriched pathway. DC, dendritic cell. (b) Immunoblot analysis of LARS in control and IFN-γ–primed macrophages; p38α served as a loading control. We observed 62% mean suppression in three independent experiments; P = 0.013. (c) Scatter plot comparing the changes in ribosome footprint frequency and TE; RPF (log2) = log2(RPFIFN-γ/RPFcontrol); TE (log2) = log2(TEIFN-γ/TEcontrol). Decreased TE, log2TE < −0.856; increased TE, log2TE > 0.578; decreased RPF, log2RPF < 0; increased RPF, log2RPF > 0. (d) Heat maps showing changes in RPF, RNA and TE of representative immune-process and metabolic-process genes selected from gene sets identified by Gene Ontology (GO) analysis of translationally regulated genes. GO analysis and entire enriched gene sets are shown in Supplementary Figure 7 and Supplementary Tables 1 and 2. Data were generated from a merged data set from two biological replicates (a,c,d).

  8. IFN-[gamma] downregulates miRNAs that target translationally upregulated genes.
    Figure 8: IFN-γ downregulates miRNAs that target translationally upregulated genes.

    (a) Scatter plot showing normalized miRNA abundance of all conditions analyzed (x-axis) and changes in miRNA expression induced by IFN-γ (y-axis). Statistical analysis was done with edgeR; the top 12 most significantly regulated genes are marked in red (P values in Table 2). (b) Potential target mRNAs of miR-146b-3p that were translationally upregulated by IFN-γ. Asterisks indicate the 3′ UTR sequence complementary to the seed sequence of miR-146b-3p. Data shown were generated from a merged data set from two biological replicates.

  9. IFN-[gamma]-mediated HES1 downregulation is independent of accelerated protein decay.
    Supplementary Fig. 1: IFN-γ–mediated HES1 downregulation is independent of accelerated protein decay.

    (a) qPCR analysis of HES1 mRNA (upper panel) and HEY1 mRNA (lower panel) in control and IFN-γ–primed macrophages stimulated with LPS (10 ng/ml) or Pam3CSK4 (10 ng/ml) for 3 h; results were normalized relative to the levels of GAPDH mRNA. (b) Cumulative data from 23 independent donors of relative expression of HES1 mRNA in control and IFN-γ–primed macrophages stimulated with Pam3CSK4 (10 ng/ml) for 4 h. HES1 mRNA expression in IFN-γ−primed macrophages relative to control macrophages (set at 1) for each individual donor is depicted, and error bars represent s.e.m. P > 0.05 by two-tailed paired Student’s t-test. (c) IFN-γ does not accelerate HES1 protein degradation. Immunoblot analysis of HES1 in control and IFN-γ–primed macrophages stimulated with Pam3CSK4 (10 ng/ml) for 4 h. Cells were treated with cycloheximide (CHX, 20 μg/ml) to stop new protein synthesis, and HES1 protein degradation was followed over a time course as indicated; p38α served as a loading control. (d) Inhibition of proteasomes does not reverse the suppressive effect of IFN-γ on HES1 protein expression. Immunoblot analysis of HES1 (upper panel) in control and IFN-γ–primed macrophages stimulated with Pam3CSK4 (10 ng/ml) for 3 h and then treated with proteasome inhibitor MG132 (10 μM) for a 2-h time course; p38α served as a loading control. Immunoblot analysis of I-κBα (lower panel) in the same experiment confirmed the efficacy of proteasome inhibition. (e) Inhibition of lysosomal function does not reverse the suppressive effect of IFN-γ on HES1 protein expression. Immunoblot analysis of HES1 and LC3A in control and IFN-γ–primed macrophages pretreated with Bafilomycin A1 (BafA1, 100 nM) for 30 min and then stimulated with Pam3CSK4 (10 ng/ml) for 4 h; p38α served as a loading control. Increased LC3A expression confirmed the efficacy of lysosome inhibition.

  10. IFN-[gamma] suppresses translation of the established MNK-eIF4E targets I-[kappa]B[alpha] and IRF8.
    Supplementary Fig. 2: IFN-γ suppresses translation of the established MNK-eIF4E targets I-κBα and IRF8.

    (a) Schematic representation of the MAPK-MNK and mTORC1 signaling pathways that target eIF4E to promote translation. (b) Real-time PCR analysis of NFKBIA (I-κBα) mRNA (left panel) in control and IFN-γ–primed macrophages. Immunoblot analysis of I-κBα (right panel) in nuclear extracts of control or IFN-γ–primed macrophages; TBP served as a loading control. IFN-γ–mediated suppression of I-κBα protein expression reflects suppression of upstream MNK-eIF4E signaling. (c) Immunoblot analysis of I-κBα in macrophages pretreated for 30 min with DMSO or increasing concentrations of the MNK inhibitor CGP57380 (5 μM, 10 μM, 20 μM) and then stimulated with Pam3CSK4 (10 ng/ml) for 4 h; p38α served as a loading control. (d) Polysome-shift analysis of IRF8 mRNA. (e) Immunoblot and qPCR confirmation of efficacy of siRNA-mediated knockdown of MNK expression in primary human macrophages. (f) qPCR analysis of HES1 mRNA in human primary macrophages transfected with scrambled control siRNA or MKNK1- and MKNK2-specific siRNA for 72 h and then stimulated or not stimulated with Pam3CSK4 (10 ng/ml). (g) Immunoblot analysis of phosphorylated (p-) p38, p-Erk, p-Akt in control and IFN-γ–primed macrophages pretreated with okadaic acid (OA) (40 nm) for 30 min before stimulation with Pam3CSK4 for 0–30 min; p38α served as a loading control.

  11. Rapamycin promotes inflammatory cytokine production in human macrophages and minimally affects HES1 mRNA expression.
    Supplementary Fig. 3: Rapamycin promotes inflammatory cytokine production in human macrophages and minimally affects HES1 mRNA expression.

    (a) Immunoblot analysis of phosphorylated (p-) 4E-BP1 in human primary monocyte–derived dendritic cells (hMo-DCs) treated with IFN-γ for 24 h before stimulation with Pam3CSK4 (10 ng/ml) or LPS (10 ng/ml) for 1 h. p38α served as a loading control. (b) Cytometric Bead Array (CBA) analysis of TNF, IL-6 and IL-10 in culture supernatants of human primary macrophages pretreated with vehicle control DMSO or rapamycin (500 nM) for 30 min and then stimulated with Pam3CSK4 for 6 h. (c) Real-time PCR analysis of HES1 mRNA in human primary macrophages pretreated for 30 min with vehicle control DMSO (labeled as 0) or increasing concentrations of mTORC1 inhibitor rapamycin (0.5 µM, 1 µM), and then stimulated with Pam3CSK4 (10 ng/ml) for 4 h. (d) Schematic representation of binary signals required for mTORC1 activation. Two upstream signals lead to activation of mTORC1: amino acid pathway and growth factors/inflammatory stimuli pathway. (e,f) Heat maps (log10 scale) of intracellular (e) and extracellular (f) tryptophan and its downstream catabolites in the IDO-mediated degradation pathway. Panels e and f show triplicate determinants from a representative experiment.

  12. Baseline mTORC1 activity in macrophages is dependent on serum and M-CSF.
    Supplementary Fig. 4: Baseline mTORC1 activity in macrophages is dependent on serum and M-CSF.

    (a) Immunoblot analysis of phosphorylated (p-) 4E-BP1 in macrophages cultured for 24 h with 5 ng or 20 ng M-CSF and with 2.5% or 10% serum (FBS); p38α served as a loading control. (b) Inhibition of M-CSFR signaling using imatinib decreases basal p-4E-BP phosphorylation. Immunoblot analysis of phosphorylated (p-) 4E-BP1 in macrophages treated with vehicle control DMSO (labeled as 0) or imatinib (300 nM) for 0–6 h; p38α served as a loading control. (c) MTT assay of cultures of control or IFN-γ–primed macrophages. Data from eight independent blood donors is shown. (d) Immunoblot analysis of HES1 in human primary macrophages pretreated with vehicle control DMSO or Myc inhibitor 10058-F4 (60 µM) for 30 min and then stimulated with Pam3CSK4 (10 ng/ml) for 0–4 h; p38α served as a loading control. (e) Immunoblot analysis of HES1 and phosphorylated (p-) 4E-BP1 (upper panel) in macrophages transfected with scrambled control small interfering RNA (siRNA) or Myc-specific siRNA for 24 h and then stimulated or not stimulated with Pam3CSK4 (10 ng/ml) for 4 h; 4E-BP1 and p38α served as loading controls. Immunoblot analysis of c-Myc (lower panel) in nuclear and cytosol extracts of macrophages confirmed the efficacy of siRNA-mediated knockdown; TBP and Akt served as loading controls.

  13. Ribosome profiling replicates are highly reproducible.
    Supplementary Fig. 5: Ribosome profiling replicates are highly reproducible.

    (a) Schematic of the ribosome profiling experimental design. RNA-Seq, RNA sequencing. (b) Correlation plots from two independent ribosome-profiling experiments as described in a. The Pearson correlation value was calculated by GraphPrism. (c) Frequency distribution of the ratio of TE in control and IFN-γ–primed macrophages (left panel); ΔTE = log2(TEIFN-γ/TEcontrol). Number of genes identified as downregulated (blue) and upregulated (red) with different cutoffs (z-score = 1.5-fold and 2-fold) are shown in the table on the right. Data were generated from a merged data set of two biological replicates. (d) Ribosome-protected fragment (RPF) read density profiles for HES1 in control (yellow) and IFN-γ–primed (purple) macrophages. Ribosomal occupancy was diminished in coding exons, consistent with decreased protein observed by immunoblotting. However, ribosomal occupancy in exons corresponding to the 5ʹ UTR did not change, suggesting ribosome stalling in potential open reading frames upstream of the initiator AUG. This intact ribosomal occupancy in the 5ʹ UTR is consistent with the lesser polysome shift to monosomal fractions shown for HES1 mRNA in Fig. 1d.

  14. Genome-wide functional annotation reveals concordant pattern of canonical pathway enrichment in biological replicates.
    Supplementary Fig. 6: Genome-wide functional annotation reveals concordant pattern of canonical pathway enrichment in biological replicates.

    (a) Ingenuity Pathway Analysis (IPA) of canonical pathways most significantly enriched in genes regulated by IFN-γ at the level of ribosome protected fragments (RPFs). We generated the heat map by comparing independent analyses of a combined data set (replicate 1 and replicate 2) and individual analysis of replicate 1 and replicate 2. Left panel shows activation z-score calculated by IPA; right panel shows significance by P value. (b) Heat map showing changes in RPF, RNA and TE of 35 tRNA genes. Data were generated from a merged data set from two biological replicates.

  15. Gene Ontology analysis reveals IFN-[gamma]-mediated translational control of metabolic and immune-system genes.
    Supplementary Fig. 7: Gene Ontology analysis reveals IFN-γ–mediated translational control of metabolic and immune-system genes.

    (a,b) Pie charts showing functional classification of genes identified by Gene Ontology analysis of genes whose translation was suppressed (a) or increased (b) by IFN-γ. The analysis was done with the PANTHER classification system (www.pantherdb.org). Data shown in this figure were generated from a merged data set from two biological replicates.

  16. Enrichment of metabolic pathways in genes whose translational efficiency was upregulated or downregulated by IFN-[gamma].
    Supplementary Fig. 8: Enrichment of metabolic pathways in genes whose translational efficiency was upregulated or downregulated by IFN-γ.

    (a) Ingenuity Pathway Analysis (IPA) of canonical pathways most significantly enriched in metabolic genes regulated by IFN-γ at the level of translation efficiency (TE) (corresponding to blue wedges in pie charts in Supplementary Fig. 7). We generated the heat map by comparing independent analyses of TE-upregulated and TE-downregulated metabolic gene sets. (b) Immunoblot analysis of phosphorylated (p-) eIF2α in control and IFN-γ–primed macrophages stimulated with Pam3CSK4 (10 ng/ml) for 0–4 h; total eIF2α and p38α served as loading controls. (c) Working model of selective regulation of translation by IFN-γ. IFN-γ inhibits TLR-induced activation of MAPK signaling pathways, resulting in diminished eIF4E phosphorylation and activity. IFN-γ also inhibits activation of the metabolic regulator mTORC1 through suppression of amino acid and growth factor pathways, resulting in decreased p-4E-BPs and eIF4E activity and altered translation. Metabolic and translational control are integrated, as metabolic changes affected translation and translational fine-tuning affected metabolism-related mRNAs.

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Author information

  1. These authors contributed equally to this work.

    • Xiaodi Su &
    • Yingpu Yu

Affiliations

  1. Graduate Program in Immunology and Microbial Pathogenesis, Weill Cornell Graduate School of Medical Sciences, New York, New York, USA.

    • Xiaodi Su &
    • Lionel B Ivashkiv
  2. Arthritis and Tissue Degeneration Program and the David Z. Rosensweig Genomics Research Center, Hospital for Special Surgery, New York, New York, USA.

    • Xiaodi Su,
    • Eugenia G Giannopoulou,
    • Xiaoyu Hu &
    • Lionel B Ivashkiv
  3. Laboratory of Virology and Infectious Disease, Center for the Study of Hepatitis C, The Rockefeller University, New York, New York, USA.

    • Yingpu Yu &
    • Charles M Rice
  4. Computational Biology Department, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

    • Yi Zhong &
    • Gunnar Rätsch
  5. Biological Sciences Department, New York City College of Technology, City University of New York, Brooklyn, New York, USA.

    • Eugenia G Giannopoulou
  6. Donald B. and Catherine C. Marron Cancer Metabolism Center, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

    • Hui Liu &
    • Justin R Cross

Contributions

X.S. designed and conducted experiments, analyzed data and prepared the manuscript; Y.Y. performed polysome-profiling and ribosome-profiling experiments and analyzed data; Y.Z. analyzed ribosome-profiling, RNA-Seq and miRNA-Seq data; E.G.G. analyzed ribosome-profiling and RNA-Seq data; J.R.C. and H.L. performed liquid chromatography–mass spectrometry experiments and analyzed data; X.H., G.R. and C.M.R. provided advice about experiments and data analysis and contributed to manuscript preparation; L.B.I. conceived and supervised experiments and prepared the manuscript.

Competing financial interests

The authors declare no competing financial interests.

Corresponding author

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Supplementary information

Supplementary Figures

  1. Supplementary Figure 1: IFN-γ–mediated HES1 downregulation is independent of accelerated protein decay. (74 KB)

    (a) qPCR analysis of HES1 mRNA (upper panel) and HEY1 mRNA (lower panel) in control and IFN-γ–primed macrophages stimulated with LPS (10 ng/ml) or Pam3CSK4 (10 ng/ml) for 3 h; results were normalized relative to the levels of GAPDH mRNA. (b) Cumulative data from 23 independent donors of relative expression of HES1 mRNA in control and IFN-γ–primed macrophages stimulated with Pam3CSK4 (10 ng/ml) for 4 h. HES1 mRNA expression in IFN-γ−primed macrophages relative to control macrophages (set at 1) for each individual donor is depicted, and error bars represent s.e.m. P > 0.05 by two-tailed paired Student’s t-test. (c) IFN-γ does not accelerate HES1 protein degradation. Immunoblot analysis of HES1 in control and IFN-γ–primed macrophages stimulated with Pam3CSK4 (10 ng/ml) for 4 h. Cells were treated with cycloheximide (CHX, 20 μg/ml) to stop new protein synthesis, and HES1 protein degradation was followed over a time course as indicated; p38α served as a loading control. (d) Inhibition of proteasomes does not reverse the suppressive effect of IFN-γ on HES1 protein expression. Immunoblot analysis of HES1 (upper panel) in control and IFN-γ–primed macrophages stimulated with Pam3CSK4 (10 ng/ml) for 3 h and then treated with proteasome inhibitor MG132 (10 μM) for a 2-h time course; p38α served as a loading control. Immunoblot analysis of I-κBα (lower panel) in the same experiment confirmed the efficacy of proteasome inhibition. (e) Inhibition of lysosomal function does not reverse the suppressive effect of IFN-γ on HES1 protein expression. Immunoblot analysis of HES1 and LC3A in control and IFN-γ–primed macrophages pretreated with Bafilomycin A1 (BafA1, 100 nM) for 30 min and then stimulated with Pam3CSK4 (10 ng/ml) for 4 h; p38α served as a loading control. Increased LC3A expression confirmed the efficacy of lysosome inhibition.

  2. Supplementary Figure 2: IFN-γ suppresses translation of the established MNK-eIF4E targets I-κBα and IRF8. (84 KB)

    (a) Schematic representation of the MAPK-MNK and mTORC1 signaling pathways that target eIF4E to promote translation. (b) Real-time PCR analysis of NFKBIA (I-κBα) mRNA (left panel) in control and IFN-γ–primed macrophages. Immunoblot analysis of I-κBα (right panel) in nuclear extracts of control or IFN-γ–primed macrophages; TBP served as a loading control. IFN-γ–mediated suppression of I-κBα protein expression reflects suppression of upstream MNK-eIF4E signaling. (c) Immunoblot analysis of I-κBα in macrophages pretreated for 30 min with DMSO or increasing concentrations of the MNK inhibitor CGP57380 (5 μM, 10 μM, 20 μM) and then stimulated with Pam3CSK4 (10 ng/ml) for 4 h; p38α served as a loading control. (d) Polysome-shift analysis of IRF8 mRNA. (e) Immunoblot and qPCR confirmation of efficacy of siRNA-mediated knockdown of MNK expression in primary human macrophages. (f) qPCR analysis of HES1 mRNA in human primary macrophages transfected with scrambled control siRNA or MKNK1- and MKNK2-specific siRNA for 72 h and then stimulated or not stimulated with Pam3CSK4 (10 ng/ml). (g) Immunoblot analysis of phosphorylated (p-) p38, p-Erk, p-Akt in control and IFN-γ–primed macrophages pretreated with okadaic acid (OA) (40 nm) for 30 min before stimulation with Pam3CSK4 for 0–30 min; p38α served as a loading control.

  3. Supplementary Figure 3: Rapamycin promotes inflammatory cytokine production in human macrophages and minimally affects HES1 mRNA expression. (99 KB)

    (a) Immunoblot analysis of phosphorylated (p-) 4E-BP1 in human primary monocyte–derived dendritic cells (hMo-DCs) treated with IFN-γ for 24 h before stimulation with Pam3CSK4 (10 ng/ml) or LPS (10 ng/ml) for 1 h. p38α served as a loading control. (b) Cytometric Bead Array (CBA) analysis of TNF, IL-6 and IL-10 in culture supernatants of human primary macrophages pretreated with vehicle control DMSO or rapamycin (500 nM) for 30 min and then stimulated with Pam3CSK4 for 6 h. (c) Real-time PCR analysis of HES1 mRNA in human primary macrophages pretreated for 30 min with vehicle control DMSO (labeled as 0) or increasing concentrations of mTORC1 inhibitor rapamycin (0.5 µM, 1 µM), and then stimulated with Pam3CSK4 (10 ng/ml) for 4 h. (d) Schematic representation of binary signals required for mTORC1 activation. Two upstream signals lead to activation of mTORC1: amino acid pathway and growth factors/inflammatory stimuli pathway. (e,f) Heat maps (log10 scale) of intracellular (e) and extracellular (f) tryptophan and its downstream catabolites in the IDO-mediated degradation pathway. Panels e and f show triplicate determinants from a representative experiment.

  4. Supplementary Figure 4: Baseline mTORC1 activity in macrophages is dependent on serum and M-CSF. (54 KB)

    (a) Immunoblot analysis of phosphorylated (p-) 4E-BP1 in macrophages cultured for 24 h with 5 ng or 20 ng M-CSF and with 2.5% or 10% serum (FBS); p38α served as a loading control. (b) Inhibition of M-CSFR signaling using imatinib decreases basal p-4E-BP phosphorylation. Immunoblot analysis of phosphorylated (p-) 4E-BP1 in macrophages treated with vehicle control DMSO (labeled as 0) or imatinib (300 nM) for 0–6 h; p38α served as a loading control. (c) MTT assay of cultures of control or IFN-γ–primed macrophages. Data from eight independent blood donors is shown. (d) Immunoblot analysis of HES1 in human primary macrophages pretreated with vehicle control DMSO or Myc inhibitor 10058-F4 (60 µM) for 30 min and then stimulated with Pam3CSK4 (10 ng/ml) for 0–4 h; p38α served as a loading control. (e) Immunoblot analysis of HES1 and phosphorylated (p-) 4E-BP1 (upper panel) in macrophages transfected with scrambled control small interfering RNA (siRNA) or Myc-specific siRNA for 24 h and then stimulated or not stimulated with Pam3CSK4 (10 ng/ml) for 4 h; 4E-BP1 and p38α served as loading controls. Immunoblot analysis of c-Myc (lower panel) in nuclear and cytosol extracts of macrophages confirmed the efficacy of siRNA-mediated knockdown; TBP and Akt served as loading controls.

  5. Supplementary Figure 5: Ribosome profiling replicates are highly reproducible. (83 KB)

    (a) Schematic of the ribosome profiling experimental design. RNA-Seq, RNA sequencing. (b) Correlation plots from two independent ribosome-profiling experiments as described in a. The Pearson correlation value was calculated by GraphPrism. (c) Frequency distribution of the ratio of TE in control and IFN-γ–primed macrophages (left panel); ΔTE = log2(TEIFN-γ/TEcontrol). Number of genes identified as downregulated (blue) and upregulated (red) with different cutoffs (z-score = 1.5-fold and 2-fold) are shown in the table on the right. Data were generated from a merged data set of two biological replicates. (d) Ribosome-protected fragment (RPF) read density profiles for HES1 in control (yellow) and IFN-γ–primed (purple) macrophages. Ribosomal occupancy was diminished in coding exons, consistent with decreased protein observed by immunoblotting. However, ribosomal occupancy in exons corresponding to the 5ʹ UTR did not change, suggesting ribosome stalling in potential open reading frames upstream of the initiator AUG. This intact ribosomal occupancy in the 5ʹ UTR is consistent with the lesser polysome shift to monosomal fractions shown for HES1 mRNA in Fig. 1d.

  6. Supplementary Figure 6: Genome-wide functional annotation reveals concordant pattern of canonical pathway enrichment in biological replicates. (120 KB)

    (a) Ingenuity Pathway Analysis (IPA) of canonical pathways most significantly enriched in genes regulated by IFN-γ at the level of ribosome protected fragments (RPFs). We generated the heat map by comparing independent analyses of a combined data set (replicate 1 and replicate 2) and individual analysis of replicate 1 and replicate 2. Left panel shows activation z-score calculated by IPA; right panel shows significance by P value. (b) Heat map showing changes in RPF, RNA and TE of 35 tRNA genes. Data were generated from a merged data set from two biological replicates.

  7. Supplementary Figure 7: Gene Ontology analysis reveals IFN-γ–mediated translational control of metabolic and immune-system genes. (105 KB)

    (a,b) Pie charts showing functional classification of genes identified by Gene Ontology analysis of genes whose translation was suppressed (a) or increased (b) by IFN-γ. The analysis was done with the PANTHER classification system (www.pantherdb.org). Data shown in this figure were generated from a merged data set from two biological replicates.

  8. Supplementary Figure 8: Enrichment of metabolic pathways in genes whose translational efficiency was upregulated or downregulated by IFN-γ. (86 KB)

    (a) Ingenuity Pathway Analysis (IPA) of canonical pathways most significantly enriched in metabolic genes regulated by IFN-γ at the level of translation efficiency (TE) (corresponding to blue wedges in pie charts in Supplementary Fig. 7). We generated the heat map by comparing independent analyses of TE-upregulated and TE-downregulated metabolic gene sets. (b) Immunoblot analysis of phosphorylated (p-) eIF2α in control and IFN-γ–primed macrophages stimulated with Pam3CSK4 (10 ng/ml) for 0–4 h; total eIF2α and p38α served as loading controls. (c) Working model of selective regulation of translation by IFN-γ. IFN-γ inhibits TLR-induced activation of MAPK signaling pathways, resulting in diminished eIF4E phosphorylation and activity. IFN-γ also inhibits activation of the metabolic regulator mTORC1 through suppression of amino acid and growth factor pathways, resulting in decreased p-4E-BPs and eIF4E activity and altered translation. Metabolic and translational control are integrated, as metabolic changes affected translation and translational fine-tuning affected metabolism-related mRNAs.

PDF files

  1. Supplementary Text and Figures (1,044 KB)

    Supplementary Figures 1–8 and Supplementary Tables 3 and 4

Excel files

  1. Supplementary Table 1 (2,468 KB)

    Metabolic genes whose translation was increased or suppressed by IFN-γ
    Genes contained in blue wedge in pie chart in Supplementary Fig. 7a-b

  2. Supplementary Table 2 (2,600 KB)

    Immune genes whose translation was increased or suppressed by IFN-γ
    Genes contained in red wedge in pie chart in Supplementary Fig. 7a-b

Additional data