Integrating Analysis of Publicly Available Microarray Data to Study the Immune Response of Cattle to Infection with Mycobacterium bovis
محورهای موضوعی : CamelNemat Hedayat-Evrigh 1 , R. Khalkhali-Evrigh 2 , Y. Ramezani 3 , R. Seyed Sharifi 4 , M.D. Shakouri 5
1 - Department of Animal Science, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
2 - Department of Animal Science, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
3 - Department of Animal Science, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
4 - Department of Animal Science, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
5 - Department of Animal Science, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
کلید واژه: cattle, immune system, Microarray, Cytokine, macrophage, <i>Mycobacterium tuberculosis</i>,
چکیده مقاله :
Bovine tuberculosis is one of the serious public health challenges which also causes economic damage in the livestock industry. Understanding the interaction mechanism between the host immune system and the causative pathogen of tuberculosis is one of the essential areas of study for success in designing effective drugs to treat tuberculosis. Here, we used four publicly available microarray data to light up the response of the cattle immune systems to Mycobacterium bovis at the gene level. Our integrating analysis results on microarray data led to identifying 189 (160 up- and 29 down-regulated) differentially expressed genes for infected samples with Mycobacterium bovis against uninfected samples. Gene ontology and pathway analysis indicated that most of the differentially expressed genes are related to the immune system's (especially innate immune system) response to the pathogen. Finally, 122 proteins (108 up-regulated and 14 down-regulated) were included in the constructed protein-protein interaction network among the proteins from differentially expressed genes. We identified 11 genes as hub genes based on three methods using the cyto Hubba plug-in in the Cytoscape. Based on our analysis, most differentially expressed genes are related to the innate immune system. However, considering the impact of time on the microarray data analysis indicated that associated gene expression with the adaptive immune system increased by time.
Abele R. and Tampe R. (2009). Peptide trafficking and translocation across membranes in cellular signaling and self-defense strategies. Curr. Opin. Cell Biol. 21(4), 508-515.
Alam A., Imam N., Ahmed M.M., Tazyeen S., Tamkeen N., Farooqui A., Malik M. and Ishrat R. (2019). Identification and classification of differentially expressed genes and network meta-analysis reveals potential molecular signatures associated with tuberculosis. Front. Genet. 10, 932-941.
Balhara J., Koussih L., Zhang J. and Gounni A.S. (2013). Pentraxin 3: an immuno-regulator in the lungs. Front. Immunol. 4, 127-135.
Bindea G., Mlecnik B., Hackl H., Charoentong P., Tosolini M., Kirilovsky A., Fridman W.H., Pagès F., Trajanoski Z. and Galon J. (2009). ClueGO: A Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics. 25(8), 1091-1093.
Caimi K., Blanco F., Soria M. and Bigi F. (2013). Transcriptional response of bovine monocyte-derived macrophages after the infection with different Argentinean Mycobacterium bovis isolates. Biomed. Res. Int. 2013, 458278.
Chin C.H., Chen S.H., Wu H.H., Ho C.W., Ko M.T. and Lin C.Y. (2014). CytoHubba: Identifying hub objects and sub-networks from complex interactome. BMC Syst. Biol. 4, 1-7.
Dave J.A., Van Pittius N.C.G., Beyers A.D., Ehlers M.R. and Brown G.D. (2002). Mycosin-1, a subtilisin-like serine protease of Mycobacterium tuberculosis, is cell wall-associated and expressed during infection of macrophages. BMC Microbiol. 2(1), 1-8.
DesJardin L.E., Kaufman T.M., Potts B., Kutzbach B., Yi H. and Schlesinger L.S. (2002). Mycobacterium tuberculosis-infected human macrophages exhibit enhanced cellular adhesion with increased expression of LFA-1 and ICAM-1 and reduced expression and/or function of complement receptors, FcγRII and the mannose receptor. Microbiology. 148(10), 3161-3171.
Ejeh E.F., Raji M.A., Bello M., Lawan F.A., Francis M.I., Kudi A.C. and Cadmus S.I.B. (2014). Prevalence and direct economic losses from bovine tuberculosis in Makurdi, Nigeria. Vet. Med. Int. 63(1), 41-47.
Fagerberg L., Hallström B.M., Oksvold P., Kampf C., Djureinovic D., Odeberg J., Habuka M., Tahmasebpoor S., Danielsson A., Edlund K. and Asplund A. (2014). Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics. Mol. Cell. Proteomics. 13(2), 397-406.
Flynn J.L., Chan J., Triebold K.J., Dalton D.K., Stewart T.A. and Bloom B.R. (1993). An essential role for interferon gamma in resistance to Mycobacterium tuberculosis infection. Exp. Med. 178(6), 2249-2254.
Gautier L., Cope L., Bolstad B.M. and Irizarry R.A. (2004). Affy-analysis of Affymetrix GeneChip data at the probe level. J. Bioinform. 20(3), 307-315.
Gerhardt T. and Ley K. (2015). Monocyte trafficking across the vessel wall. Cardiovasc. Res. 107(3), 321-330.
Goovaerts O., Jennes W., Massinga-Loembé M., Ceulemans A., Worodria W., Mayanja-Kizza H., Colebunders R. and Kestens L. (2013). TB-IRIS study group. LPS-binding protein and IL-6 mark paradoxical tuberculosis immune reconstitution inflammatory syndrome in HIV patients. PloS One. 8(11), e81856.
Griffith J.W., Sokol C.L. and Luster A.D. (2014). Chemokines and chemokine receptors: positioning cells for host defense and immunity. Annu. Rev. Immunol. 32, 659-702.
Gurunathan S., Irvine K.R., Wu C.Y., Cohen J.I., Thomas E., Prussin C., Restifo N.P. and Seder R.A. (1998). CD40 ligand/trimer DNA enhances both humoral and cellular immune responses and induces protective immunity to infectious and tumor challenge. J. Immunol. Res. 161(9), 4563-4571.
Kauffmann A., Gentleman R. and Huber W. (2009). ArrayQualityMetrics-a bioconductor package for quality assessment of microarray data. J. Bioinform. 25(3), 415-416.
Khalkhali-Evrigh R., Hedayat N., Ming L. and Jirimutu J. (2022). Identification of selection signatures in Iranian dromedary and Bactrian camels using whole genome sequencing data. Sci. Rep. 12(1), 1-10.
Killick K.E., Browne J.A., Park S.D., Magee D.A., Martin I., Meade K.G., Gordon S.V., Gormley E., O'Farrelly C., Hokamp K. and MacHugh D.E. (2011). Genome-wide transcriptional profiling of peripheral blood leukocytes from cattle infected with Mycobacterium bovis reveals suppression of host immune genes. BMC Genom. 12(1), 1-18.
Killick K.E., Magee D.A., Park S.D., Taraktsoglou M., Browne J.A., Conlon K.M., Nalpas N.C., Gormley E., Gordon S.V., MacHugh D.E. and Hokamp K. (2014). Key hub and bottleneck genes differentiate the macrophage response to virulent and attenuated Mycobacterium bovis. Front. Immunol. 5, 422-432.
Killick K.E., NíCheallaigh C., O'Farrelly C., Hokamp K., Mac Hugh D.E. and Harris J. (2013). Receptor-mediated recognition of mycobacterial pathogens. Cell. Microbiol. 15(9), 1484-1495.
Lazar C., Meganck S., Taminau J., Steenhoff D., Coletta A., Molter C., Weiss-Solís D.Y., Duque R., Bersini H. and Nowé A. (2013). Batch effect removal methods for microarray gene expression data integration: A survey. Brief. Bioinform. 14(4), 469-490.
Lee M.R., Chang L.Y., Chang C.H., Yan B.S., Wang J.Y. and Lin W.H. (2019). Differed il-1 beta response between active tb and ltbi cases by ex vivo stimulation of human monocyte-derived macrophage with tb-specific antigen. Dis. Markers. 2019, 7869576.
Li P., Wang R., Dong W., Hu L., Zong B., Zhang Y., Wang X., Guo A., Zhang A., Xiang Y. and Chen H. (2017). Comparative proteomics analysis of human macrophages infected with virulent Mycobacterium bovis. Front. Cell. Infect. Microbiol. 7, 65-73.
Liu T., Zhang L., Joo D. and Sun S.C. (2017). NF-κB signaling in inflammation. Signal Transduct. Target. Ther. 2(1), 1-9.
Magee D.A., Taraktsoglou M., Killick K.E., Nalpas N.C., Browne J.A., Park S.D., Conlon K.M., Lynn D.J., Hokamp K., Gordon S.V. and Gormley E. (2012). Global gene expression and systems biology analysis of bovine monocyte-derived macrophages in response to in vitro challenge with Mycobacterium bovis. PloS One. 7(2), e32034.
Medzhitov R. and Horng T. (2009). Transcriptional control of the inflammatory response. Nat. Rev. Immunol. 9(10), 692-703.
Méndez-Samperio P., Ayala H. and Vázquez A. (2003). NF-κB is involved in regulation of CD40 ligand expression on Mycobacterium bovis bacillus Calmette-Guérin-activated human T cells. Clin. Diagn. Lab. Immunol. 10(3), 376-382.
Meng L., Tong J., Wang H., Tao C., Wang Q., Niu C., Zhang X. AND Gao Q. (2017). PPE38 protein of Mycobacterium tuberculosis inhibits macrophage MHC class I expression and dampens CD8+ T cell responses. Front. Cell. Infect. Microbiol. 7, 68-75.
Michel A.L., Müller B. AND Van Helden P.D. (2010). Mycobacterium bovis at the animal–human interface: A problem, or not? Vet. Microbiol. 140(3), 371-381.
Müller N. (2019). The role of intercellular adhesion molecule-1 in the pathogenesis of psychiatric disorders. Front. Pharmacol. 10, 1251-1259.
Naffin-Olivos J.L., Daab A., White A., Goldfarb N.E., Milne A.C., Liu D., Baikovitz J., Dunn B.M., Rengarajan J., Petsko G.A. AND Ringe D. (2017). Structure determination of Mycobacterium tuberculosis serine protease Hip1 (Rv2224c). Biochemistry. 56(17), 2304-2314.
Philips J.A. and Ernst J.D. (2012). Tuberculosis pathogenesis and immunity. Annu. Rev. Pathol: Mech. Dis. 7, 353-384.
Phipson B., Lee S., Majewski I.J., Alexander W.S. and Smyth G.K. (2016). Robust hyperparameter estimation protects against hypervariable genes and improves power to detect differential expression. Ann. Appl. Stat. 10(2), 946-954.
Queval C.J., Brosch R. and Simeone R. (2017). The macrophage: a disputed fortress in the battle against Mycobacterium tuberculosis. Front. Microbiol. 8, 2284.
Reymond N., Imbert A.M., Devilard E., Fabre S., Chabannon C., Xerri L., Farnarier C., Cantoni C., Bottino C., Moretta A. and Dubreuil P. (2004). DNAM-1 and PVR regulate monocyte migration through endothelial junctions. Exp. Med. 199(10), 1331-1341.
Robinson R.T. (2017). T Cell Production of GM-CSF protects the host during experimental tuberculosis. mBio. 8, e02087.
Russell D.G. (2001). Mycobacterium tuberculosis: Here today, and here tomorrow. Nat. Rev. Mol. Cell Biol. 2(8), 569-578.
Shannon P., Markiel A., Ozier O., Baliga N.S., Wang J.T., Ramage D., Amin N., Schwikowski B. and Ideker T. (2003). Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 13(11), 2498-2504.
Sherman B.T. and Lempicki R.A. (2009). Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4(1), 44-52.
Sokol C.L. and Luster A.D. (2015). The chemokine system in innate immunity. Cold Spring Harb. Perspect. Biol. 7(5), a016303.
Urdahl K.B., Liggitt D. and Bevan M.J. (2003). CD8+ T cells accumulate in the lungs of Mycobacterium tuberculosis-infected Kb−/− Db−/− mice, but provide minimal protection. J. Immunol. Res. 170(4), 1987-1994.
Waters W.R. and Palmer M.V. (2015). Mycobacterium bovis infection of cattle and white-tailed deer: Translational research of relevance to human tuberculosis. Inst. Lab. Anim. Res. 56(1), 26-43.
Wieczorek M., Abualrous E.T., Sticht J., Álvaro-Benito M., Stolzenberg S., Noé F. and Freund C. (2017). Major histocompatibility complex (MHC) class I and MHC class II proteins: Conformational plasticity in antigen presentation. Front. Immunol. 8, 292-305.
Xu G., Wang J., Gao G.F. and Liu C.H. (2014). Insights into battles between Mycobacterium tuberculosis and macrophages. Protein Cell. 5(10), 728-736.
Zhang G., Zhou B., Li S., Yue J., Yang H., Wen Y., Zhan S., Wang W., Liao M., Zhang M. and Zeng G. (2014). Allele-specific induction of IL-1β expression by C/EBPβ and PU.1 contributes to increased tuberculosis susceptibility. PLoS Pathog. 10, 1004426.