Host genetics and Chlamydia disease: Prediction and validation of disease severity mechanisms

PLoS ONE

Volumn 7, Issue 3, 2012, Pages

  Miyairi, Isao ^a,d   Ziebarth, Jesse ^a   Laxton, Jonathan D ^a   Wang, Xiaofei ^a   van Rooijen, Nico ^b   Williams, Robert W ^a   Lu, Lu ^a,c   Byrne, Gerald I ^a   Cui, Yan ^a  

^a UNIVERSITY OF TENNESSEE HEALTH SCIENCE CENTER   (United States)

^b VU UNIVERSITY MEDICAL CENTER   (Netherlands)

^c NANTONG UNIVERSITY   (China)

^d NATIONAL CENTER FOR CHILD HEALTH AND DEVELOPMENT   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

GUANOSINE TRIPHOSPHATASE; IMMUNITY RELATED GTPASE; UNCLASSIFIED DRUG;

ANIMAL EXPERIMENT; ANIMAL MODEL; ARTICLE; BACTERIAL LOAD; BACTERIAL STRAIN; BAYES THEOREM; CHLAMYDIASIS; CHLAMYDOPHILA PSITTACI; CHROMOSOME 1; CONTROLLED STUDY; CTRQ3 GENE; DISEASE SEVERITY; GENE; GENE LOCUS; GENE MAPPING; GENETIC RESISTANCE; GENOTYPE; HAPLOTYPE; HOST RESISTANCE; IMMUNOREGULATION; INFECTION RESISTANCE; INFECTION SENSITIVITY; INFLAMMATORY CELL; MACROPHAGE ACTIVATION; MOUSE; NEUTROPHIL CHEMOTAXIS; NONHUMAN; PREDICTION; PROTEIN POLYMORPHISM; WEIGHT CHANGE; WEIGHT REDUCTION; ANIMAL; BIOLOGICAL MODEL; C57BL MOUSE; CHROMOSOME MAP; GENE REGULATORY NETWORK; GENETIC PREDISPOSITION; GENETICS; HOST PATHOGEN INTERACTION; IMMUNOLOGY; MACROPHAGE; MALE; MOUSE STRAIN; NEUTROPHIL; ORNITHOSIS; PATHOGENICITY; PATHOLOGY; QUANTITATIVE TRAIT LOCUS; SPECIES DIFFERENCE; VALIDATION STUDY;

CHLAMYDIA; CHLAMYDOPHILA PSITTACI; MUS;

ANIMALS; BAYES THEOREM; CHLAMYDOPHILA PSITTACI; CHROMOSOME MAPPING; GENE REGULATORY NETWORKS; GENETIC PREDISPOSITION TO DISEASE; GTP PHOSPHOHYDROLASES; HAPLOTYPES; HOST-PATHOGEN INTERACTIONS; MACROPHAGES; MALE; MICE; MICE, INBRED C57BL; MICE, INBRED STRAINS; MODELS, GENETIC; NEUTROPHILS; PSITTACOSIS; QUANTITATIVE TRAIT LOCI; SPECIES SPECIFICITY; WEIGHT LOSS;

EID: 84863374212     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0033781     Document Type: Article

References (40)

1. Burton MJ, Mabey DC, (2009) The global burden of trachoma: a review. PLoS Negl Trop Dis 3: e460.
2. Centers for Disease Control and Prevention (2009) Chlamydia Prevalence Monitoring Project Annual Report 2007. Atlanta, GA.
3. Hammerschlag M, Kohlhoff S, Apfalter P, (2009) Chlamydophila (Chlamydia) pneumoniae. In: Mandell G, Bennett J, Dolin R, editors. Mandell, Douglan, and Bennett's Principles and Practice of Infectious Diseases. 7th ed Philadelphia, PA Churchill Livingstone.
4. Beeckman DS, Vanrompay DC, (2009) Zoonotic Chlamydophila psittaci infections from a clinical perspective. Clin Microbiol Infect 15: 11-17.
5. Bernstein-Hanley I, Balsara ZR, Ulmer W, Coers J, Starnbach MN, et al. (2006) Genetic analysis of susceptibility to Chlamydia trachomatis in mouse. Genes Immun 7: 122-129.
6. Bernstein-Hanley I, Coers J, Balsara ZR, Taylor GA, Starnbach MN, et al. (2006) The p47 GTPases Igtp and Irgb10 map to the Chlamydia trachomatis susceptibility locus Ctrq-3 and mediate cellular resistance in mice. Proc Natl Acad Sci U S A 103: 14092-14097.
7. Miyairi I, Tatireddigari VR, Mahdi OS, Rose LA, Belland RJ, et al. (2007) The p47 GTPases Iigp2 and Irgb10 regulate innate immunity and inflammation to murine Chlamydia psittaci infection. J Immunol 179: 1814-1824.
8. Boon AC, deBeauchamp J, Hollmann A, Luke J, Kotb M, et al. (2009) Host genetic variation affects resistance to infection with a highly pathogenic H5N1 influenza A virus in mice. J Virol 83: 10417-10426.
9. Abdeltawab NF, Aziz RK, Kansal R, Rowe SL, Su Y, et al. (2008) An unbiased systems genetics approach to mapping genetic loci modulating susceptibility to severe streptococcal sepsis. PLoS Pathog 4: e1000042.
10. Kotb M, Fathey N, Aziz R, Rowe S, Williams RW, et al. (2008) Unbiased forward genetics and systems biology approaches to understanding how gene-environment interactions work to predict susceptibility and outcomes of infections. Novartis Found Symp 293: 156-165; discussion 165-157, 181-153.
11. Mozhui K, Ciobanu DC, Schikorski T, Wang X, Lu L, et al. (2008) Dissection of a QTL hotspot on mouse distal chromosome 1 that modulates neurobehavioral phenotypes and gene expression. PLoS Genet 4: e1000260.
12. Nelson DE, Virok DP, Wood H, Roshick C, Johnson RM, et al. (2005) Chlamydial IFN-gamma immune evasion is linked to host infection tropism. Proc Natl Acad Sci U S A 102: 10658-10663.
13. Taylor GA, (2007) IRG proteins: key mediators of interferon-regulated host resistance to intracellular pathogens. Cell Microbiol 9: 1099-1107.
14. Howard J, (2008) The IRG proteins: a function in search of a mechanism. Immunobiology 213: 367-375.
15. Feng CG, Collazo-Custodio CM, Eckhaus M, Hieny S, Belkaid Y, et al. (2004) Mice deficient in LRG-47 display increased susceptibility to mycobacterial infection associated with the induction of lymphopenia. J Immunol 172: 1163-1168.
16. Hunn JP, Howard JC, (2010) The mouse resistance protein Irgm1 (LRG-47): a regulator or an effector of pathogen defense? PLoS Pathog 6: e1001008.
17. Pearl J, (1988) Probabilistic Reasoning in Intelligent Systems California Morgan Kaufmann Publishers.
18. Pearl J, (2000) Causality: Models, Reasoning, and Inference Cambridge, UK Cambridge University Press.
19. Neapolitan RE, (2003) Learning Bayesian Networks Upper Saddle River Prentice Hall.
20. de Jong H, (2002) Modeling and Simulation of Genetic Regulatory Systems: A Literature Review. Journal of Computational Biology 9: 67-103.
21. Needham CJ, Bradford JR, Bulpitt AJ, Westhead DR, (2007) A Primer on Learning in Bayesian Networks for Computational Biology. PLoS Computational Biology 3: e129.
22. Rockman MV, (2008) Reverse engineering the genotype-phenotype map with natural genetic variation. Nature 456: 738.
23. Friedman N, (2004) Inferring cellular networks using probabilistic graphical models. Science 303: 799-805.
24. MacMicking JD, Taylor GA, McKinney JD, (2003) Immune control of tuberculosis by IFN-gamma-inducible LRG-47. Science 302: 654-659.
25. Raberg L, Sim D, Read AF, (2007) Disentangling genetic variation for resistance and tolerance to infectious diseases in animals. Science 318: 812-814.
26. Best A, White A, Boots M, (2008) Maintenance of host variation in tolerance to pathogens and parasites. Proc Natl Acad Sci U S A 105: 20786-20791.
27. Schneider DS, Ayres JS, (2008) Two ways to survive infection: what resistance and tolerance can teach us about treating infectious diseases. Nat Rev Immunol 8: 889-895.
28. Medzhitov R, (2009) Damage control in host-pathogen interactions. Proc Natl Acad Sci U S A 106: 15525-15526.
29. Seixas E, Gozzelino R, Chora A, Ferreira A, Silva G, et al. (2009) Heme oxygenase-1 affords protection against noncerebral forms of severe malaria. Proc Natl Acad Sci U S A 106: 15837-15842.
30. Ayres JS, Schneider DS, (2008) A signaling protease required for melanization in Drosophila affects resistance and tolerance of infections. PLoS Biol 6: 2764-2773.
31. Ayres JS, Schneider DS, (2009) The role of anorexia in resistance and tolerance to infections in Drosophila. PLoS Biol 7: e1000150.
32. Feng CG, Zheng L, Jankovic D, Bafica A, Cannons JL, et al. (2008) The immunity-related GTPase Irgm1 promotes the expansion of activated CD4+ T cell populations by preventing interferon-gamma-induced cell death. Nat Immunol 9: 1279-1287.
33. Bafica A, Feng CG, Santiago HC, Aliberti J, Cheever A, et al. (2007) The IFN-inducible GTPase LRG47 (Irgm1) negatively regulates TLR4-triggered proinflammatory cytokine production and prevents endotoxemia. J Immunol 179: 5514-5522.
34. Bottcher S, (2001) Learning Bayesian networks with mixed variables Artificial Intelligence and Statistics, Key West, Florida pp. 149-156.
35. Heckerman D, Geiger D, Chickerling D, (1995) Learning Baysian networks: The combination of knowledge and statistical data Machine Learning Microsoft Research pp. 197-243.
36. Pe'er D, (2005) Bayesian network analysis of signaling networks: a primer. Sci STKE 2005: pl4.
37. Hartemink AJ, Gifford DK, Jaakkola TS, Young RA, (2001) Using graphical models and genomic expression data to statistically validate models of genetic regulatory networks. Pac Symp Biocomput pp. 422-433.
38. Murphy KP, (2001) The Bayes Net Toolbox for Matlab. Computing Science and Statistics 2001.
39. Hawkins DM, Basak SC, Mills D, (2003) Assessing model fit by cross-validation. J Chem Inf Comput Sci 43: 579-586.
40. Van Rooijen N, Sanders A, (1994) Liposome mediated depletion of macrophages: mechanism of action, preparation of liposomes and applications. J Immunol Methods 174: 83-93.