آنالیز شبکه برهمکنش پروتئین - پروتئین بر اساس ژن‌های تغییر بیان‌یافته در بافت ریه برای بیماری آنفولانزای مرغی

نوع مقاله : مقاله کامل

نویسندگان

1 استادیار موسسه تحقیقات علوم دامی کشور، سازمان تحقیقات،آموزش و ترویج کشاورزی،ایران،کرج

2 گروه علوم دامی، دانشکده کشاورزی، دانشگاه جیرفت، جیرفت، ایران

چکیده

شیوع بیماری آنفولانزای پرندگان با مرگ‌و‌میر بالا، کاهش تولید تخم و کشتن اجباری گله‌های آلوده، تأثیر مخربی بر صنعت طیور دارد. براساس پروتئین مرکزی ویروس به سه زیر گروه A,B,C تقسیم می‌شود. ویروس آنفولانزای نوع A بسیار شایع می‌باشد این ویروس می‌تواند باعث ابتلای گونه‌های مختلف پستانداران و پرندگان شود و بیماری‌زایی بیشتری نسبت به آنفولانزای ,B,C دارد و تقریباً همه ساله باعث اپیدمی با شدت‌های مختلف می‌شود. اهداف اصلاح نژادی برای حفظ سلامت حیوانات منجر به رفاه حیوانات و جلوگیری از ضررهای اقصادی می‌شود. هدف از پژوهش حاضر، استفاده از روش آنالیز شبکه زیستی به منظور شناسایی نشانگرهای کلیدی جدید درگیر در بیماری آنفولانزای مرغی می‌باشد. در این مطالعه به منظور دستیابی سریع به مهم‌ترین ژن‌های درگیر در این بیماری داده‌های ریزآرایه بیان ژن مربوط به بافت ریه جوجه‌های آلوده به ویروس از سایت GEO با شماره دسترسی GSE53931 تهیه گردید. رسم شبکه برهمکنش پروتئین-پروتئین توسط نرم‌افزار Cytoscape انجام شد. آنالیز کمپلکس‌های پروتئینی به کمک MCODE انجام گردید. سه کمپلکس پروتئینی استخراج شد. پروتئین‌های seed در کمپلکس‌ها عبارتند از RPL10A, NOB1, MSH4 که بعنوان نشانگر کلیدی معرفی شدند، همچنین ژن‌های NEB، RPF1، CSRNP1، RNF146، RPL18A با کم‌ترین درجه بیان و ژن‌های SLC6A20، PLN ،SLC17A8، NOXO1، TMEM179 با بیشترین درجه بیان در مطالعه حاضر می‌باشند. بیشتر ژن‌ها در رونویسی، تکثیر، ترجمه ژن در ویروس آنفولانزا نقش دارند. آنالیزهای بر پایه شبکه می‌تواند به تشخیص ژن‌های درگیر در بیماری و ماژول عملکردی بپردازد، که این امر می‌تواند کمک قابل توجهی در شناسایی عوامل تنظیم کننده و فرآیندهای زیستی دخیل در پاسخ به بیماری آنفولانزای مرغی داشته باشد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Analysis of protein-protein interaction network based on altered genes expressed in lung tissue for avian influenza disease

نویسندگان [English]

  • azadeh torabi 1
  • zahra roudbari 2
1 Assistant professor, Animal science research institute of Iran (ASRI), Agricultural Research, Education, and Extension Organization,Karaj, Iran.
2 Department of Animal Science, Faculty of Agriculture, University of Jiroft. Jiroft. Iran.
چکیده [English]

The spread of bird flu disease with high mortality, reduced egg production and forced killing of infected flocks has a devastating effect on the poultry industry. Based on the central protein, the virus is divided into three subgroups A, B, and C. Influenza type A virus is very common. This virus can infect different species of mammals and birds, and it is more pathogenic than influenza B and C, and it causes epidemics of different severities almost every year. Breeding goals to maintain the health of animals lead to the well-being of animals and prevent economic losses. The purpose of this research was to use biological network analysis method to identify new key markers involved in bird flu disease. In this study, in order to quickly obtain the most important genes involved in this disease, gene expression microarray data related to the lung tissue of chickens infected with the virus was prepared from the GEO site with the accession number GSE53931. The protein-protein interaction network was drawn by Cytoscape software. Protein complexes were analyzed using MCODE. Three protein complexes were extracted. The seed proteins in the complexes include RPL10A, NOB1, and MSH4, which were introduced as key markers, as well as NEB, RPF1, CSRNP1, RNF146, and RPL18A genes with the lowest level of expression and SLC6A20, PLN, SLC17A8 ,NOXO1 and TMEM179 gene with the highest level of expression in the present study. Most of the genes are involved in the transcription, replication, translation of the gene in the influenza virus. Network-based analyzes can detect effective genes and functional modules, which can significantly help in identifying regulatory factors and biological processes involved in the response to avian influenza, and subsequently, better control of the disease. 

کلیدواژه‌ها [English]

  • avian influenza
  • network analysis
  • microarray
  • protein complex
  • differentially expressed genes

مراجع

1. Arnold, U. 2018. Investigations into the cellular interactome of the PB2 protein expressed by seasonal and highly pathogenic avian influenza viruses. Ph.D thesis. University of Hamburg, Berlin, Germany.
2. Bader, G. D. and Hogue, C. W. 2003. An automated method for finding molecular complexes in large protein interaction networks. BMC bioinformatics, 4(1): 1-27.
3. Cameron, C. M., Cameron, M. J., Bermejo-Martin, J. F., Ran, L., Xu, L., Turner, P. V. and Kelvin, D. J. 2008. Gene expression analysis of host innate immune responses during lethal H5N1 infection in ferrets. Journal of virology, 82(22): 11308-11317.
4. Cui, Morgan, D., Cheng, D. H., Foo, S. L., Yap, G. L., Ampomah, P. B., and Lim, L. H. 2020. RNA-Sequencing-Based trancriptomic analysis reveals a role for annexin-A1 in classical and influenza A virus-induced autophagy. Cell, 9(6):1399.
5. Forero, A., Tisoncik, J., Watanabe, T., Zhong, G., Hatta, M., Tchitchek, N. and Katze, M. 2016. The 1918 influenza virus PB2 protein enhances virulence through the disruption of inflammatory and WNT mediated signaling in mice. Journal of virology, 90(5): 2240-2253.
6. Green, R., Wilkins, C., Thomas, S., Sekine, A., Hendrick, D. M., Voss, K, and Gale, J. 2017. Oas1b-dependent immune transcriptional profiles of west nile virus infection in the collaborative cross. G3: Genes, Genomes, Genetics, 7(6): 1665-1682.
7. Heaton, N. S., Moshkina, N., Fenouil, R., Gardner, T. J., Aguirre, S., Shah, p. s. and Marazzi, I. 2016. Targeting viral proteostasis limits influenza virus, HIV, and dengue virus infection. Immunity, 44(1): 46-58.
8. Hu, J., Mo, Y., Wang, X., Gu, M., Hu, Z., Zhong, L. and Liu, X. 2015. PA-X decreases the pathogenicity of highly pathogenic H5N1 H5N1 influenza A virus in avian species by inhibiting virus replication and host response. Journal of virology, 89(8): 4126-4142.
9. Hu, Y., Lou, J., Mao, Y. Y., Lai, T. W., Liu, L. Y., Zhu, C. and Shen, H. H. 2016. Activation of MTOR in pulmonary epithelium promotes LPS-induced lung injury. Autophagy, 12(12): 2286-2299.
10. Huang, D. W., Sherman, B. T. and Lempicki, R. A. 2009. Systematic and integrative analysis of large gene lists using DAVID Bioinformatics Resources. Nature Protocol, 4(1): 44-57.
11. James, S., Ola, B., Terrence, M.T., Jeffery, K.T., James, C.P. and Ian, A.W. 2006. Structure and Receptor Specificity of the Hemagglutinin from an H5N1 Influenza Virus. Science: 404-410.
12. Kann, M. G. 2007 Protein interactions and disease: computational approaches to uncover theetiology of diseases. Brief Bioinformatics, 8: 333–346.
13. Khadimian, S., Bayat, M., Azizi, A., Qadri, S., Zia, M.A. and Beheshti, Sh. 2011. Serological investigation of influenza disease in native chickens in the areas near the sea of Golestan province. Iranian Journal of Medical Microbiology, 6: 15-23.
14. Klees, S., Schluter, J. S., Schellhom, J., Bertram, H., Kurzweg, A. C., Ramzan, F. and Gultas, M. 2022. Comparative investigation of Gene regulatory processes underluing avian influenza viruses in chicken and duck. Biology, 11(2): 219.
15. Liu, Y. C., Mok, B. W. Y., Wang, P., Kuo, R. L., Chen, H., and Shih, S. R. 2021. Cellular 5′-3′ mRNA exoribonuclease XRN1 inhibits interferon beta activation and facilitates influenza A virus replication. Microbiological Research, 12(4): 945-21.
16. Mason, O. and Verwoerd, M. 2006. Graph Theory and Networks in Biology. The Journal of Engineering and Technology 2: 89-119.
17. Ouyang, H., Wang, Z., Chen, X., Yu, J., Li, Z., and Nie, Q. 2017. Proteomic analysis of chicken skeletal muscle during embryonic development. Frontiers in physiology, 8 (281).
18. Rahim, M., Klewes, L., Zahedi, A., Mai, S. and Coombs, K. M. 2018. Global interactiomics connect unclear mitotic apparatus protein NUMA1 to influenza virus maturation. Viruses, 10(12): 731.
19. Ramnani, B., Manivannan, P., Jaggernauth, S., and Malathi, K. 2021. ABCE1 regulates RNase L-induced autophagy during viral infections. Viruses, 13(2): 315.
20. Ranaware, P. B., Mishra, A., Vijayakumar, P., Gandhale, P. N., Kumar, H., Kulkarni, D. D., and Raut, A. A. 2016. Genome wide host gene expression analysis in chicken lungs infected with avian influenza viruses. PLoS One, 11(4): e0153671.
21. Rashid, M. 2022. Role of fibronectin-interacting cellular proteins in Influenza a virus infection in human lung epithelial. Cells, 13(2): 315
22. Riel, D., Munster, V. J., Wit, E., Rimmelzwaan, G. F. and Kuiken, T. 2007. Human and avian influenza viruses target different cells in the lower respiratory tract of humans and other mammals. Immunopathology and Infectious Disease, 171: 1215-1223.
23. Rual, J. F., Venkatesan, K., Hao, T., Hirozane-Kishikawa, T., Dricot, A., Li, N. and Vidal, M. 2005. Towards a proteome-scale map of the human protein–protein interaction network. Nature, 437(7062): 1173-1178.
24. Shahsundi, sh. 2014. Dynamic evaluation of influenza virus multiplication and virus-host interactions. Scientific Research Journal of Arak University of Medical Sciences. 5: 1-20.
25. Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D. and Ideker, T. (2003). Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome research, 13(11): 2498-2504.
26. Spackman, E. 2002. Influenza virus and the avian H5 and H7 hemagglutinin subtypes. Journal of Clinical Microbiology, 40: 3256-3260. 
27. Stevens, J., Blixt, O., Paulson, J. C. and Wilson, I. A. 2006. Glycan microarray technologies tools to survey host specificity of influenza viruses. Nature Reviews Microbiology, 4(11): 857-864.
28. Sun, W., Li, S., Yang, J., Yang, L., Quan, G. and Liu, N. 2015. Proteomics analysis of cellular proteines co-immunoprecipitated with nucleoprotein of influenza a virus (H7N9). International Journal of Molecular Scuences, 16(11): 25982-25998.
29. Tatebe, K., Zeytun, A., Ribeiro, R. M., Hoffman, R., Harrod, K. S. and Forst, C. V. 2010. Response network analysis of differential gene expression in human epithelial lung cells during avian influenza infections. BMC bioinformatics, 11: 1-15.
30. Ulyanova, V., Shah Mahmud, R., Laikov, A., Dudkina, E., Markelova, M., Mostafa, A. and llinskaya, O. 2020. Anti-influenza activity of the ribonuclease Binase: cellular targets detected by quantitative proteomics. International Journal of Molecular Sciences, 21(21): 8294.
31. Vanderven, H. A., Petkau, K., Ryan-Jean, K. E., Aldridge Jr, J. R., Webster, R. G., and Magor, K. E. 2012. Avian influenza rapidly induces antiviral genes in duck lung and intestine. Molecular immunology, 51(3-4): 316-324.
32. Wahl, A.,Schafer, F., Bardet, W. and Hildebrand, W. H. 2010. Hla class I molecules reflect an altered host proteome after influenza virus infection. Human immunology, 71(1):14-22. 
33. Wang, Y., Brahmakshatriya, V., Lupiani, B., Reddy, S. 2012. Integrated analysis of microRNA expression and mRNA transcriptome in lungs of avian influenza virus infected broilers. BMC Genomics, 13(278).
34. Yang, J., Huang, X., Liu, Y., Zhao, D., Han, K., Zhang, L. and Liu, Q. 2020. Analysis of the microRNA expression profiles of chicken dendritic cells in response to H9N2 avian influenza virus infection. Veterinary Research, 51: 1-9.
35. Ye, Y,. Fan, H., Li, Q., Zhang, Z., Miao, P., Zhu, J., Liu, J., Zhang, J., Liao, M. 2022. Differential proteome response to H5N1 highly pathogenic avian influenza (HPAI) viruses infection in duck. Frontiers in Immunology, 19 (13): 965454.
36. Yildirim, M. A., Goh, K. I., Cusick, M. E., and Barabasi, A. L. 2007. Vidal Marc. Drug-target network. Nat Biotechnol, 25(10: 1119-1126.
 
 

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  • تاریخ دریافت: 20 اسفند 1401
  • تاریخ بازنگری: 09 اردیبهشت 1402
  • تاریخ پذیرش: 27 اردیبهشت 1402

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