Journal List > J Rheum Dis > v.21(3) > 1064105

Kim, Park, Jung, Han, Kim, and Han: DICAM-mediated Inhibition of Type 1 Interferon System during Macrophage Differentiation of THP-1 Cells

Abstract

Objective

We have previously shown that DICAM inhibits LPS-mediated macrophage differentiation. However, less is known about the exact action mechanisms of DICAM on the macrophage function and differentiation.

Methods

To induce differentiation into a resting M0 macrophage, THP-1 cells were cultured with 100 nM PMA for 24 h, and then rested for 3 days. THP-1 cells were infected with 50 moi of control LacZ- or DICAM-containing adenovirus. The RNA expression profile associated with DICAM during THP-1 differentiation was analyzed with a microarray chip and in silico analysis with Ingenuity Pathway Analysis (IPA) program.

Results

A disease and function analysis of the microarray data in DICAM-overexpressed THP-1 cells revealed a suppression in the expression of multiple genes involved in the response of myeloid cells and phagocytes, and an increase of genes associated with apoptosis of fibroblast cell-line, and viral infection and replication. The canonical pathway analysis also showed the most prominent changes of signaling pathways that involve inflammation responses. An upstream regulator analysis identifyingmolecules upstream of the genes that potentially explain the observed expression changes revealed that IRF7 and the genes in type 1 interferon system, such as IFNA2 and IFNAR, was significantly attenuated by DICAM. A mechanistic network analysis confirmed a direct causal association between IRF7 and type 1 interferon system. A real-time RT-PCR analysis validating the microarray data verified the significant suppression of IRFs, IFNA2, and IFNB1.

Conclusion

These results suggest that DICAM can be a critical regulator of type 1 interferon system, which is an essential mediator in the process of intracellular infection and systemic lupus erythematosus.

REFERENCES

1. Wynn TA, Chawla A, Pollard JW. Macrophage biology in development, homeostasis and disease. Nature. 2013; 496:445–55.
crossref
2. Gordon S, Martinez FO. Alternative activation of macrophages: mechanism and functions. Immunity. 2010; 32:593–604.
crossref
3. Mosser DM, Edwards JP. Exploring the full spectrum of macrophage activation. Nat Rev Immunol. 2008; 8:958–69.
crossref
4. Sica A, Schioppa T, Mantovani A, Allavena P. Tumour-associated macrophages are a distinct M2 polarised population promoting tumour progression: potential targets of anticancer therapy. Eur J Cancer. 2006; 42:717–27.
crossref
5. Gordon S. Alternative activation of macrophages. Nat Rev Immunol. 2003; 3:23–35.
crossref
6. Stein M, Keshav S, Harris N, Gordon S. Interleukin 4 potently enhances murine macrophage mannose receptor activity: a marker of alternative immunologic macrophage activation. J Exp Med. 1992; 176:287–92.
crossref
7. Munder M, Eichmann K, Modolell M. Alternative metabolic states in murine macrophages reflected by the nitric oxide synthase/arginase balance: competitive regulation by CD4+ T cells correlates with Th1/Th2 phenotype. J Immunol. 1998; 160:5347–54.
8. de Weerd NA, Nguyen T. The interferons and their receptors–distribution and regulation. Immunol Cell Biol. 2012; 90:483–91.
crossref
9. Hu X, Chakravarty SD, Ivashkiv LB. Regulation of interferon and Toll-like receptor signaling during macrophage activation by opposing feedforward and feedback inhibition mechanisms. Immunol Rev. 2008; 226:41–56.
crossref
10. Lawrence T, Natoli G. Transcriptional regulation of macrophage polarization: enabling diversity with identity. Nat Rev Immunol. 2011; 11:750–61.
crossref
11. Hu X, Herrero C, Li WP, Antoniv TT, Falck-Pedersen E, Koch AE, et al. Sensitization of IFN-gamma Jak-STAT signaling during macrophage activation. Nat Immunol. 2002; 3:859–66.
12. Toshchakov V, Jones BW, Perera PY, Thomas K, Cody MJ, Zhang S, et al. TLR4, but not TLR2, mediates IFN-beta-induced STAT1alpha/beta-dependent gene expression in macrophages. Nat Immunol. 2002; 3:392–8.
13. Takaoka A, Mitani Y, Suemori H, Sato M, Yokochi T, Noguchi S, et al. Cross talk between interferon-gamma and -alpha/beta signaling components in caveolar membrane domains. Science. 2000; 288:2357–60.
14. Jung YK, Jeong JH, Ryoo HM, Kim HN, Kim YJ, Park EK, et al. Gene expression profile of human chondrocyte HCS-2/8 cell line by EST sequencing analysis. Gene. 2004; 330:85–92.
crossref
15. Jung YK, Jin JS, Jeong JH, Kim HN, Park NR, Choi JY. DICAM, a novel dual immunoglobulin domain containing cell adhesion molecule interacts with alphavbeta3 integrin. J Cell Physiol. 2008; 216:603–14.
16. Han SW, Jung YK, Lee EJ, Park HR, Kim GW, Jeong JH, et al. DICAM inhibits angiogenesis via suppression of AKT and p38 MAP kinase signalling. Cardiovasc Res. 2013; 98:73–82.
crossref
17. Jung YK, Han SW, Kim GW, Jeong JH, Kim HJ, Choi JY. DICAM inhibits osteoclast differentiation through attenuation of the integrin α Vβ 3 pathway. J Bone Miner Res. 2012; 27:2024–34.
18. Jung YK, Park HR, Lee EJ, Jeong DH, Kim GW, Choi JY, et al. DICAM Inhibits Activation of Macrophage by Lipopolysaccharide. J Rheum Dis. 2012; 19:196–205.
crossref
19. Stossi F, Madak-Erdoğan Z, Katzenellenbogen BS. Macrophage-elicited loss of estrogen receptor-α in breast cancer cells via involvement of MAPK and c-Jun at the ESR1 genomic locus. Oncogene. 2012; 31:1825–34.
crossref
20. Zhang L, Pagano JS. IRF-7, a new interferon regulatory factor associated with Epstein-Barr virus latency. Mol Cell Biol. 1997; 17:5748–57.
crossref
21. Schindler U, Hoey T, McKnight SL. Differentiation of T-helper lymphocytes: selective regulation by members of the STAT family of transcription factors. Genes Cells. 1996; 1:507–15.
crossref
22. Marié I, Durbin JE, Levy DE. Differential viral induction of distinct interferon-alpha genes by positive feedback through interferon regulatory factor-7. EMBO J. 1998; 17:6660–9.
23. Sato M, Suemori H, Hata N, Asagiri M, Ogasawara K, Nakao K, et al. Distinct and essential roles of transcription factors IRF-3 and IRF-7 in response to viruses for IFN-alpha/beta gene induction. Immunity. 2000; 13:539–48.
24. Génin P, Algarté M, Roof P, Lin R, Hiscott J. Regulation of RANTES chemokine gene expression requires coopera-tivity between NF-kappa B and IFN-regulatory factor transcription factors. J Immunol. 2000; 164:5352–61.
25. Lu R, Pitha PM. Monocyte differentiation to macrophage requires interferon regulatory factor 7. J Biol Chem. 2001; 276:45491–6.
crossref
26. Litvak V, Ratushny AV, Lampano AE, Schmitz F, Huang AC, Raman A, et al. A FOXO3-IRF7 gene regulatory cir-cuit limits inflammatory sequelae of antiviral responses. Nature. 2012; 490:421–5.
crossref
27. Weidinger C, Krause K, Mueller K, Klagge A, Fuhrer D. FOXO3 is inhibited by oncogenic PI3K/Akt signaling but can be reactivated by the NSAID sulindac sulfide. J Clin Endocrinol Metab. 2011; 96:E1361–71.
crossref
28. Yalcin S, Marinkovic D, Mungamuri SK, Zhang X, Tong W, Sellers R, et al. ROS-mediated amplification of AKT/mTOR signalling pathway leads to myeloproliferative syndrome in Foxo3(−/−) mice. EMBO J. 2010; 29:4118–31.
crossref
29. Tjiu JW, Chen JS, Shun CT, Lin SJ, Liao YH, Chu CY, et al. Tumor-associated macrophage-induced invasion and angiogenesis of human basal cell carcinoma cells by cy-clooxygenase-2 induction. J Invest Dermatol. 2009; 129:1016–25.
crossref
30. Zhang L, Dong Y, Dong Y, Cheng J, Du J. Role of in-tegrin-β 3 protein in macrophage polarization and regeneration of injured muscle. J Biol Chem. 2012; 287:6177–86.
31. Trinchieri G. Type I interferon: friend or foe? J Exp Med. 2010; 207:2053–63.
crossref
32. Tailor P, Tamura T, Kong HJ, Kubota T, Kubota M, Borghi P, et al. The feedback phase of type I interferon induction in dendritic cells requires interferon regulatory factor 8. Immunity. 2007; 27:228–39.
crossref
33. Rönnblom L, Alm GV, Eloranta ML. Type I interferon and lupus. Curr Opin Rheumatol. 2009; 21:471–7.
crossref
34. Banchereau J, Pascual V. Type I interferon in systemic lupus erythematosus and other autoimmune diseases. Immunity. 2006; 25:383–92.
crossref
35. Baechler EC, Batliwalla FM, Karypis G, Gaffney PM, Ortmann WA, Espe KJ, et al. Interferon-inducible gene expression signature in peripheral blood cells of patients with severe lupus. Proc Natl Acad Sci U S A. 2003; 100:2610–5.
crossref
36. Bennett L, Palucka AK, Arce E, Cantrell V, Borvak J, Banchereau J, et al. Interferon and granulopoiesis signatures in systemic lupus erythematosus blood. J Exp Med. 2003; 197:711–23.
crossref
37. Mathian A, Weinberg A, Gallegos M, Banchereau J, Koutouzov S. IFN-alpha induces early lethal lupus in pre-autoimmune (New Zealand Black × New Zealand White) F1 but not in BALB/c mice. J Immunol. 2005; 174:2499–506.

Figure 1.
Top hits for canonical pathways of differentially expressed proteins by DICAM and their overlap connections. (A) The most highly represented canonical pathways of genes differentially expressed during the macrophage differentiation of THP-1 cells. The columns represent the -log of the p-value calculated based on Fisher's exact test. The dot points represents the ratio of the number of genes in a given pathway that meet cut off criteria and total number of genes that make up that pathway. (B) The network of canonical pathways highlights the relationships between pathways and classify the functional domains.
jrd-21-122f1.tif
Figure 2.
IRF7-associated mechanistic networks of upstream regulators. IRF7, mostly suppressed by DICAM overexpression, is postu-lated to affect the expression of type I interferon and their downstream signaling molecules such as IRFs, STAT1/2/3 and RelA (p65). The set of total 15 regulators in mechanistic network has a connection with 187 dataset genes (not shown) among which 40 genes directly connect to IRF7. The blue color indicates a more confident predicted inhibition and the pale blue indicates a less confident predicted inhibition.
jrd-21-122f2.tif
Figure 3.
The predicted DICAM-mediated inhibition of IRF canonical pathway. The canonical pathway of IRF activation by cytosolic pattern recognition receptor is analyzed in silico using Molecule Activity Predictor analysis of IPA.
jrd-21-122f3.tif
Figure 4.
DICAM-mediated inhibition of IRFs and type I interferon system. The microarray data is validated with real-time RT-PCR analysis. In the presence of PMA 100 nM, THP-1 cells infected with adenovirus encoding DICAM or LacZ for 24 h, and then left unstimulated for 3 days. Real-time RT-PCR analysis of (A) IRFs mRNA and (B) type I interferon (IFNA1, IFNA2 and IFNB1) and type 2 interferon (IFNG).
jrd-21-122f4.tif
Table 1.
The 8 mostly affected category of disease and biologic functions by DICAM overexpression in THP-1 cells that was analyzed with Downstream Effects Analysis using IPA
Category Disease or functions annotation p-value* Predicted activation state Activation z-score #Molecules
Cell-To-Cell Signaling and Interaction Response of myeloid cells 2.84E-05 Decreased −3.049 25
Inflammatory Response Response of phagocytes 6.18E-06 Decreased −2.990 28
Cell-To-Cell Signaling and Interaction Response of phagocytes 6.18E-06 Decreased −2.990 28
Lipid Metabolism Biosynthesis of polyunsaturated fatty acids 1.30E-08 Decreased −2.951 35
Cell Death and Survival Apoptosis of fibroblast cell lines 7.84E-06 Increased 3.126 40
Infectious Disease Viral Infection 1.12E-09 Increased 3.095 168
Infectious Disease Replication of RNA virus 1.33E-07 Increased 3.056 62
Infectious Disease Replication of virus 3.98E-08 Increased 2.769 68

* The p-value was calculated with the Fischer's exact test, and reflects the likelyhood that the association between a set of genes in dataset and a related biological function is significant.

A positive or negative z-score value indicates that a function is predicted to be increased or decreased in THP-1 cells by DICAM overexpression.

Number of RNAs differentially expressed in the disease and functions category.

Table 2.
The 12 mostly activated and inhibited upstream regulators by DICAM overexpression in THP-1 cells predicted by the Upstream Regulator Analysis in IPA
Upstream regulator Fold change Molecule type Predicted activation state Activation z-score* p-value of overlap
IRF7 −38.745 Tanscription regulator Inhibited −5.247 2.70E-18
IFNA2   Cytokine Inhibited −4.914 1.18E-15
Ifnar   Group Inhibited −4.636 1.58E-18
Tretinoin   Chemical – endogenous mammalian Inhibited −4.599 2.01E-19
IFNL1   Cytokine Inhibited −4.463 4.80E-16
Lipopolysaccharide   Chemical drug Inhibited −4.345 4.02E-45
MYC 2.052 Transcription regulator Activated 5.330 4.19E-14
TRIM24   Transcription regulator Activated 4.208 7.73E-15
E2F1   Transcription regulator Activated 4.060 6.09E-13
INSIG1 −6.816 Other Activated 3.957 3.90E-13
TBX2   Transcription regulator Activated 3.900 4.44E-10
IL1RN −5.747 Cytokine Activated 3.816 1.99E-11

IRF7: interferon regulatory factor7, IFNA2: interferon alpha-2, Ifnar: interferon-α/β receptor, IFNL1: interferon lambda1, MYC: v-myc avian myelocytomatosis viral oncogene homolog, TRIM24: Tripartite Motif Containing 24, E2F1: E2F transcription factor 1, INSIG1: insulin induced gene 1, TBX2: T-box transcription factor2, IL1RN: interleukin-1 receptor antagonist.

* Based on a model that assigns random regulation directions for predicted upstream regulators (|z|>2). Z>2 predicts activation of the upstream regulator. Z<−2 predicts inhibition of the upstream regulator.

The p-value of overlap was used to rank the significance associated for each Upstream Regulator.

The p-value indicates the significance of the overlap between the genes targeted by the upstream regulator in the IPKB database and the experimental dataset.

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