Identification and validation of ifit1 as an important innate immune bottleneck

PLoS ONE

Volumn 7, Issue 6, 2012, Pages

  McDermott, Jason E ^a   Vartanian, Keri B ^b   Mitchell, Hugh ^a   Stevens, Susan L ^b   Sanfilippo, Antonio ^a   Stenzel Poore, Mary P ^b  

^a PACIFIC NORTHWEST NATIONAL LABORATORY   (United States)

^b OREGON HEALTH AND SCIENCE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

LIPOPOLYSACCHARIDE; SMALL INTERFERING RNA; TOLL LIKE RECEPTOR 4;

ANIMAL CELL; ARTICLE; AXUD1 GENE; BOTTLENECK GENE; BRAIN ISCHEMIA; GENE; GENE EXPRESSION; GENE SILENCING; IFI47 GENE; IFIT1 GENE; IMMUNOGENETICS; IMMUNOMODULATION; INNATE IMMUNITY; MACROPHAGE; MOUSE; NEUROPROTECTION; NONHUMAN; OASL2 GENE; PPP1R15A GENE; TGTP GENE; TRANSCRIPTOMICS;

ANIMALS; CARRIER PROTEINS; CELL LINE; IMMUNITY, INNATE; LIPOPOLYSACCHARIDES; MACROPHAGES; MICE; REVERSE TRANSCRIPTASE POLYMERASE CHAIN REACTION; TOLL-LIKE RECEPTORS;

EID: 84862648393     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0036465     Document Type: Article

References (36)

1. Hiscott J, Grandvaux N, Sharma S, Tenoever BR, Servant MJ, et al. (2003) Convergence of the NF-kappaB and interferon signaling pathways in the regulation of antiviral defense and apoptosis. Annals of the New York Academy of Sciences 1010: 237-248.
2. McDermott JE, Archuleta M, Stevens SL, Stenzel-Poore MP, Sanfilippo A, (2011) Defining the players in higher-order networks: predictive modeling for reverse engineering functional influence networks. Pac Symp Biocomput pp. 314-325.
3. McDermott JE, Archuleta M, Thrall BD, Adkins JN, Waters KM, (2011) Controlling the response: predictive modeling of a highly central, pathogen-targeted core response module in macrophage activation. PLoS ONE 6: e14673.
4. McDermott JE, Costa M, Janszen D, Singhal M, Tilton SC, (2010) Separating the drivers from the driven: Integrative network and pathway approaches aid identification of disease biomarkers from high-throughput data. Dis Markers 28: 253-266.
5. Rasmussen AL, Diamond DL, McDermott JE, Gao X, Metz TO, et al. (2011) Systems virology identifies a mitochondrial Fatty Acid oxidation enzyme, dodecenoyl coenzyme a delta isomerase, required for hepatitis C virus replication and likely pathogenesis. J Virol 85: 11646-11654.
6. McDermott JE, Taylor RC, Yoon H, Heffron F, (2009) Bottlenecks and hubs in inferred networks are important for virulence in Salmonella typhimurium. J Comput Biol 16: 169-180.
7. Stevens SL, Ciesielski TM, Marsh BJ, Yang T, Homen DS, et al. (2008) Toll-like receptor 9: a new target of ischemic preconditioning in the brain. J Cereb Blood Flow Metab 28: 1040-1047.
8. Tasaki K, Ruetzler CA, Ohtsuki T, Martin D, Nawashiro H, et al. (1997) Lipopolysaccharide pre-treatment induces resistance against subsequent focal cerebral ischemic damage in spontaneously hypertensive rats. Brain Res 748: 267-270.
9. Bahjat FR, Williams-Karnesky RL, Kohama SG, West GA, Doyle KP, et al. (2011) Proof of concept: pharmacological preconditioning with a Toll-like receptor agonist protects against cerebrovascular injury in a primate model of stroke. J Cereb Blood Flow Metab 31: 1229-1242.
10. Akira S, Takeda K, (2004) Toll-like receptor signalling. Nat Rev Immunol 4: 499-511.
11. Stevens SL, Leung PY, Vartanian KB, Gopalan B, Yang T, et al. (2011) Multiple preconditioning paradigms converge on interferon regulatory factor-dependent signaling to promote tolerance to ischemic brain injury. J Neurosci 31: 8456-8463.
12. Ramsey SA, Klemm SL, Zak DE, Kennedy KA, Thorsson V, et al. (2008) Uncovering a macrophage transcriptional program by integrating evidence from motif scanning and expression dynamics. PLoS Comput Biol 4: e1000021.
13. Amit I, Garber M, Chevrier N, Leite AP, Donner Y, et al. (2009) Unbiased reconstruction of a mammalian transcriptional network mediating pathogen responses. Science 326: 257-263.
14. Calvano SE, Xiao W, Richards DR, Felciano RM, Baker HV, et al. (2005) A network-based analysis of systemic inflammation in humans. Nature 437: 1032-1037.
15. Irizarry RA, Gautier L, Cope LM, (2003) An R Package for Oligonucleotide Array Statisitical Analysis. In: Giovanni Parmigiani ESG, Rafael A Irizarry, Scott L Zeger, editors. editor. The Analysis of Gene Expression Data: Methods and Software. NY: Springer.
16. Hochberg Y, Benjamini Y, (1990) More powerful procedures for multiple significance testing. Stat Med 9: 811-818.
17. Faith JJ, Hayete B, Thaden JT, Mogno I, Wierzbowski J, et al. (2007) Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. PLoS Biol 5: e8.
18. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, et al. (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13: 2498-2504.
19. McDermott JE, Oehmen CS, McCue LA, Hill E, Choi DM, et al. (2011) A model of cyclic transcriptomic behavior in the cyanobacterium Cyanothece sp. ATCC 51142. Mol Biosyst.
20. Team RDC (2010) R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.
21. Csardi G, Nepusz T, (2006) The igraph software package for complex network research. Complex Systems 1695.
22. Yu H, Kim PM, Sprecher E, Trifonov V, Gerstein M, (2007) The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics. PLoS Comput Biol 3: e59.
23. Blondel V, Guilaume J, Lambiotte R, Lefebvre E, (2008) Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment 10: P1000.
24. Butte AJ, Kohane IS, (2000) Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements. Pac Symp Biocomput pp. 418-429.
25. McDermott JE, Corley C, Rasmussen AL, Diamond DL, Katze MG, et al. (2012) Using network analysis to identify therapeutic targets from global proteomics data. BMC Syst Biol 6: 28.
26. Carlow DA, Teh SJ, Teh HS, (1998) Specific antiviral activity demonstrated by TGTP, a member of a new family of interferon-induced GTPases. J Immunol 161: 2348-2355.
27. Pichlmair A, Lassnig C, Eberle CA, Gorna MW, Baumann CL, et al. (2011) IFIT1 is an antiviral protein that recognizes 5′-triphosphate RNA. Nat Immunol 12: 624-630.
28. Glavic A, Molnar C, Cotoras D, de Celis JF, (2009) Drosophila Axud1 is involved in the control of proliferation and displays pro-apoptotic activity. Mech Dev 126: 184-197.
29. McCabe C, White F, Brown SM, Macrae IM, (2008) GADD34 gene restores virulence in viral vector used in experimental stroke study. J Cereb Blood Flow Metab 28: 747-751.
30. Minami K, Tambe Y, Watanabe R, Isono T, Haneda M, et al. (2007) Suppression of viral replication by stress-inducible GADD34 protein via the mammalian serine/threonine protein kinase mTOR pathway. J Virol 81: 11106-11115.
31. Diamond DL, Syder AJ, Jacobs JM, Sorensen CM, Walters KA, et al. (2010) Temporal proteome and lipidome profiles reveal hepatitis C virus-associated reprogramming of hepatocellular metabolism and bioenergetics. PLoS Pathog 6: e1000719.
32. Hahn MW, Kern AD, (2005) Comparative genomics of centrality and essentiality in three eukaryotic protein-interaction networks. Mol Biol Evol 22: 803-806.
33. Yoon H, McDermott JE, Porwollik S, McClelland M, Heffron F, (2009) Coordinated regulation of virulence during systemic infection of Salmonella enterica serovar Typhimurium. PLoS Pathog 5: e1000306.
34. Terenzi F, Pal S, Sen GC, (2005) Induction and mode of action of the viral stress-inducible murine proteins, P56 and P54. Virology 340: 116-124.
35. Hui DJ, Terenzi F, Merrick WC, Sen GC, (2005) Mouse p56 blocks a distinct function of eukaryotic initiation factor 3 in translation initiation. J Biol Chem 280: 3433-3440.
36. Berchtold S, Manncke B, Klenk J, Geisel J, Autenrieth IB, et al. (2008) Forced IFIT-2 expression represses LPS induced TNF-alpha expression at posttranscriptional levels. BMC Immunol 9: 75.