PARP9 and PARP14 cross-regulate macrophage activation via STAT1 ADP-ribosylation

Nature Communications

Volumn 7, Issue , 2016, Pages

  Iwata, Hiroshi ^a   Goettsch, Claudia ^a   Sharma, Amitabh ^a,b   Ricchiuto, Piero ^a   Goh, Wilson Wen Bin ^a   Halu, Arda ^a   Yamada, Iwao ^a   Yoshida, Hideo ^a   Hara, Takuya ^a   Wei, Mei ^c   Inoue, Noriyuki ^a   Fukuda, Daiju ^a   Mojcher, Alexander ^a   Mattson, Peter C ^a   Barabási, Albert László ^a,b   Boothby, Mark ^c   Aikawa, Elena ^a   Singh, Sasha A ^a   Aikawa, Masanori ^a  

^a HARVARD MEDICAL SCHOOL   (United States)

^b NORTHEASTERN UNIVERSITY   (United States)

^c VANDERBILT UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GAMMA INTERFERON; HISTONE DEACETYLASE 2; HISTONE DEACETYLASE 3; INDUCIBLE NITRIC OXIDE SYNTHASE; INTERLEUKIN 1BETA; INTERLEUKIN 4; PARP14 PROTEIN; PARP9 PROTEIN; PROTEIN; STAT1 PROTEIN; STAT6 PROTEIN; TUMOR NECROSIS FACTOR; UNCLASSIFIED DRUG; IL4 PROTEIN, HUMAN; LIPOPOLYSACCHARIDE RECEPTOR; NICOTINAMIDE ADENINE DINUCLEOTIDE ADENOSINE DIPHOSPHATE RIBOSYLTRANSFERASE; PARP14 PROTEIN, HUMAN; PARP14 PROTEIN, MOUSE; PARP9 PROTEIN, HUMAN; RIBOSE; STAT1 PROTEIN, HUMAN; STAT1 PROTEIN, MOUSE; TUMOR PROTEIN;

CELLS AND CELL COMPONENTS; GENE EXPRESSION; MUTATION; PROTEOMICS; RODENT;

ADENOSINE DIPHOSPHATE RIBOSYLATION; ANIMAL CELL; ANIMAL EXPERIMENT; APOPTOSIS; ARTERY LESION; ARTICLE; BONE MARROW DERIVED MACROPHAGE; CELL PROLIFERATION; CELL VIABILITY; CONTROLLED STUDY; CORONARY ARTERY DISEASE; GENE EXPRESSION; GENE EXPRESSION PROFILING; HEMATOPOIETIC CELL; HUMAN; HUMAN CELL; IMMUNOHISTOCHEMISTRY; IN VITRO STUDY; MACROPHAGE ACTIVATION; MALE; MOUSE; NONHUMAN; PATHOGENESIS; PERITONEUM MACROPHAGE; PHENOTYPE; PROTEIN ANALYSIS; PROTEIN EXPRESSION; PROTEIN FUNCTION; PROTEIN PHOSPHORYLATION; PROTEOMICS; RAW 264.7 CELL LINE; SMOOTH MUSCLE CELL; ANIMAL; ATHEROSCLEROSIS; ATHEROSCLEROTIC PLAQUE; C57BL MOUSE; CELL SURVIVAL; CHEMISTRY; FEMALE; INFLAMMATION; METABOLISM; PHOSPHORYLATION; RNA INTERFERENCE; THP-1 CELL LINE;

MUS;

ADP-RIBOSYLATION; ANIMALS; APOPTOSIS; ATHEROSCLEROSIS; CELL SURVIVAL; CORONARY ARTERY DISEASE; FEMALE; HUMANS; INFLAMMATION; INTERFERON-GAMMA; INTERLEUKIN-4; LIPOPOLYSACCHARIDE RECEPTORS; MACROPHAGE ACTIVATION; MALE; MICE; MICE, INBRED C57BL; NEOPLASM PROTEINS; PHOSPHORYLATION; PLAQUE, ATHEROSCLEROTIC; POLY(ADP-RIBOSE) POLYMERASES; RAW 264.7 CELLS; RIBOSE; RNA INTERFERENCE; STAT1 TRANSCRIPTION FACTOR; THP-1 CELLS;

EID: 84993972016     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/ncomms12849     Document Type: Article

References (62)

1. Writing Group Members et al. Heart disease and stroke statistics-2010 update: a report from the American Heart Association. Circulation 121, e46-e215 (2010).
2. Moran, A. E. et al. The global burden of ischemic heart disease in 1990 and 2010: the Global Burden of Disease 2010 study. Circulation 129, 1493-1501 (2014).
3. Glass, C. K. & Witztum, J. L. Atherosclerosis. the road ahead. Cell 104, 503-516 (2001).
4. Liang, C. P., Han, S., Senokuchi, T. & Tall, A. R. The macrophage at the crossroads of insulin resistance and atherosclerosis. Circ. Res. 100, 1546-1555 (2007).
5. Randolph, G. J. Mechanisms that regulate macrophage burden in atherosclerosis. Circ. Res. 114, 1757-1771 (2014).
6. Tabas, I. Macrophage death and defective inflammation resolution in atherosclerosis. Nat. Rev. Immunol. 10, 36-46 (2010).
7. Aikawa, M. & Libby, P. The vulnerable atherosclerotic plaque: pathogenesis and therapeutic approach. Cardiovasc. Pathol. 13, 125-138 (2004).
8. Ridker, P. M. & Luscher, T. F. Anti-inflammatory therapies for cardiovascular disease. Eur. Heart J. 35, 1782-1791 (2014).
9. Glass, C. K. & Olefsky, J. M. Inflammation and lipid signaling in the etiology of insulin resistance. Cell Metab. 15, 635-645 (2012).
10. Gregor, M. F. & Hotamisligil, G. S. Inflammatory mechanisms in obesity. Annu. Rev. Immunol. 29, 415-445 (2011).
11. Fredman, G., Ozcan, L. & Tabas, I. Common therapeutic targets in cardiometabolic disease. Sci. Transl. Med. 6, 239ps235 (2014).
12. Fukuda, D. et al. Notch ligand Delta-like 4 blockade attenuates atherosclerosis and metabolic disorders. Proc. Natl Acad. Sci. USA 109, E1868-E1877 (2012).
13. Aikawa, M. et al. An HMG-CoA reductase inhibitor, cerivastatin, suppresses growth of macrophages expressing matrix metalloproteinases and tissue factor in vivo and in vitro. Circulation 103, 276-283 (2001).
14. Libby, P. The forgotten majority: unfinished business in cardiovascular risk reduction. J. Am. Coll. Cardiol. 46, 1225-1228 (2005).
15. Gordon, S. & Mantovani, A. Diversity and plasticity of mononuclear phagocytes. Eur. J. Immunol. 41, 2470-2472 (2011).
16. Ley, K., Miller, Y. I. & Hedrick, C. C. Monocyte and macrophage dynamics during atherogenesis. Arterioscler. Thromb. Vasc. Biol. 31, 1506-1516 (2011).
17. Biswas, S. K. & Mantovani, A. Orchestration of metabolism by macrophages. Cell Metab. 15, 432-437 (2012).
18. Koltsova, E. K., Hedrick, C. C. & Ley, K. Myeloid cells in atherosclerosis: a delicate balance of anti-inflammatory and proinflammatory mechanisms. Curr. Opin. Lipidol. 24, 371-380 (2013).
19. Lawrence, T. & Natoli, G. Transcriptional regulation of macrophage polarization: enabling diversity with identity. Nat. Rev. Immunol. 11, 750-761 (2011).
20. Moore, K. J., Sheedy, F. J. & Fisher, E. A. Macrophages in atherosclerosis: a dynamic balance. Nat. Rev. Immunol. 13, 709-721 (2013).
21. Murray, P. J. et al. Macrophage activation and polarization: nomenclature and experimental guidelines. Immunity 41, 14-20 (2014).
22. Swirski, F. K. & Nahrendorf, M. Leukocyte behavior in atherosclerosis, myocardial infarction, and heart failure. Science 339, 161-166 (2013).
23. Koch-Nolte, F., Kernstock, S., Mueller-Dieckmann, C., Weiss, M. S. & Haag, F. Mammalian ADP-ribosyltransferases and ADP-ribosylhydrolases. Front. Biosci. 13, 6716-6729 (2008).
24. Feijs, K. L., Verheugd, P. & Luscher, B. Expanding functions of intracellular resident mono-ADP-ribosylation in cell physiology. FEBS J. 280, 3519-3529 (2013).
25. Cho, S. H. et al. Glycolytic rate and lymphomagenesis depend on PARP14, an ADP ribosyltransferase of the B aggressive lymphoma (BAL) family. Proc. Natl Acad. Sci. USA 108, 15972-15977 (2011).
26. Mehrotra, P., Riley, J. P., Patel, R., Li, F., Voss, L. & Goenka, S. PARP-14 functions as a transcriptional switch for Stat6-dependent gene activation. J. Biol. Chem. 286, 1767-1776 (2011).
27. Iqbal, M. B. et al. PARP-14 combines with tristetraprolin in the selective posttranscriptional control of macrophage tissue factor expression. Blood 124, 3646-3655 (2014).
28. Aguiar, R. C., Takeyama, K., He, C., Kreinbrink, K. & Shipp, M. A. B-aggressive lymphoma family proteins have unique domains that modulate transcription and exhibit poly(ADP-ribose) polymerase activity. J. Biol. Chem. 280, 33756-33765 (2005).
29. Camicia, R. et al. BAL1/ARTD9 represses the anti-proliferative and proapoptotic IFNgamma-STAT1-IRF1-p53 axis in diffuse large B-cell lymphoma. J. Cell Sci. 126, 1969-1980 (2013).
30. Barabasi, A. L., Gulbahce, N. & Loscalzo, J. Network medicine: a network-based approach to human disease. Nat. Rev. Genet. 12, 56-68 (2011).
31. Goh, K. I., Cusick, M. E., Valle, D., Childs, B., Vidal, M. & Barabasi, A. L. The human disease network. Proc. Natl Acad. Sci. USA 104, 8685-8690 (2007).
32. Maier, E., Duschl, A. & Horejs-Hoeck, J. STAT6-dependent and-independent mechanisms in Th2 polarization. Eur. J. Immunol. 42, 2827-2833 (2012).
33. Sikorski, K. et al. STAT1 as a central mediator of IFNgamma and TLR4 signal integration in vascular dysfunction. Jak-Stat. 1, 241-249 (2012).
34. Atsumi, T. et al. Inflammation amplifier, a new paradigm in cancer biology. Cancer Res. 74, 8-14 (2014).
35. Goenka, S. & Boothby, M. Selective potentiation of Stat-dependent gene expression by collaborator of Stat6 (CoaSt6), a transcriptional cofactor. Proc. Natl Acad. Sci. USA 103, 4210-4215 (2006).
36. Cho, S. H. et al. PARP-14, a member of the B aggressive lymphoma family, transduces survival signals in primary B cells. Blood 113, 2416-2425 (2009).
37. Swirski, F. K. et al. Identification of splenic reservoir monocytes and their deployment to inflammatory sites. Science 325, 612-616 (2009).
38. Grover, A. et al. Erythropoietin guides multipotent hematopoietic progenitor cells toward an erythroid fate. J. Exp. Med. 211, 181-188 (2014).
39. Itou, T. et al. Cystathionine gamma-lyase accelerates osteoclast differentiation: identification of a novel regulator of osteoclastogenesis by proteomic analysis. Arterioscler. Thromb. Vasc. Biol. 34, 626-634 (2014).
40. Hengel, S. M., Floyd, E., Baker, E. S., Zhao, R., Wu, S. & Pasa-Tolic, L. Evaluation of SDS depletion using an affinity spin column and IMS-MS detection. Proteomics 12, 3138-3142 (2012).
41. Hengel, S. M., Shaffer, S. A., Nunn, B. L. & Goodlett, D. R. Tandem mass spectrometry investigation of ADP-ribosylated kemptide. J. Am. Soc. Mass Spectrom. 20, 477-483 (2009).
42. Eng, J. K., McCormack, A. L. & Yates, J. R. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spectrom. 5, 976-989 (1994).
43. Elias, J. E. & Gygi, S. P. Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nat. Methods 4, 207-214 (2007).
44. Kall, L., Storey, J. D., MacCoss, M. J. & Noble, W. S. Assigning significance to peptides identified by tandem mass spectrometry using decoy databases. J. Proteome Res. 7, 29-34 (2008).
45. Dayon, L. et al. Relative quantification of proteins in human cerebrospinal fluids by MS/MS using 6-plex isobaric tags. Anal. Chem. 80, 2921-2931 (2008).
46. Chris Fraley, A. E. R. Model-based clustering, discriminant analysis, and density estimation. J. Am. Stat. Assoc. 97, 611-631 (2002).
47. Ricchiuto, P. et al. mIMT-visHTS: a novel method for multiplexing isobaric mass tagged datasets with an accompanying visualization high throughput screening tool for protein profiling. J. Proteomics 128, 132-140 (2015).
48. Kirchner, M. et al. Computational protein profile similarity screening for quantitative mass spectrometry experiments. Bioinformatics 26, 77-83 (2010).
49. Lee, I., Blom, U. M., Wang, P. I., Shim, J. E. & Marcotte, E. M. Prioritizing candidate disease genes by network-based boosting of genome-wide association data. Genome Res. 21, 1109-1121 (2011).
50. Kohler, S., Bauer, S., Horn, D. & Robinson, P. N. Walking the interactome for prioritization of candidate disease genes. Am. J. Hum. Genet. 82, 949-958 (2008).
51. Sharma, A. et al. A disease module in the interactome explains disease heterogeneity, drug response and captures novel pathways and genes in asthma. Hum. Mol. Genet. 24, 3005-3020 (2015).
52. Menche, J. et al. Disease networks. Uncovering disease-disease relationships through the incomplete interactome. Science 347, 1257601 (2015).
53. Hitti, E. et al. Mitogen-activated protein kinase-activated protein kinase 2 regulates tumor necrosis factor mRNA stability and translation mainly by altering tristetraprolin expression, stability, and binding to adenine/uridine-rich element. Mol. Cell Biol. 26, 2399-2407 (2006).
54. Mehrotra, P. et al. Poly (ADP-ribose) polymerase 14 and its enzyme activity regulates T(H)2 differentiation and allergic airway disease. J. Allergy Clin. Immunol. 131, 521-531 e521-512 (2013).
55. Iwata, H. et al. Bone marrow-derived cells contribute to vascular inflammation but do not differentiate into smooth muscle cell lineages. Circulation 122, 2048-2057 (2010).
56. Sata, M. et al. Hematopoietic stem cells differentiate into vascular cells that participate in the pathogenesis of atherosclerosis. Nat. Med. 8, 403-409 (2002).
57. Sata, M. et al. Endothelial nitric oxide synthase is essential for the HMG-CoA reductase inhibitor cerivastatin to promote collateral growth in response to ischemia. FASEB J. 15, 2530-2532 (2001).
58. Paul, C. P., Good, P. D., Winer, I. & Engelke, D. R. Effective expression of small interfering RNA in human cells. Nat. Biotechnol. 20, 505-508 (2002).
59. Chubb, J. R., Trcek, T., Shenoy, S. M. & Singer, R. H. Transcriptional pulsing of a developmental gene. Curr. Biol. 16, 1018-1025 (2006).
60. Wilcox, R. R. Winsorized robust measures. in: Encyclopedia of Statistics in Behavioral Science (2005).
61. Black, P. E. in: Dictionary of Algorithms and Data Structures (eds Vreda Pieterse PEB, 2006).
62. Prim, R. C. Shortest connection networks and some generalizations. Bell Syst. Tech. J. 37, 1389-1401 (1957).