Analysis of Autoimmune Diseases-Human Gut Microbiota Association Using Transcriptome Data and Omic Tools

Yıl 2019, , 20 - 29, 01.04.2019

Tuba Sevimoğlu

https://doi.org/10.19113/sdufenbed.449136

Öz

Recent
advances in omic analyses and the accurate determination of DNA sequencing of genomes
of human-related microbial communities have helped increase the knowledge of
the function and structure of human microbiota in diseased and healthy states.
However there is still not much work done in this regard. In this study,  three important autoimmune diseases,
Psoriasis, Rheumatoid Arthritis and Atopic Dermatitis were selected. Firstly
the transcriptional regulation for these diseases were integrated with
metabolic pathways using omic tools. Secondly the link between human intestinal
microbial species and these diseases were revealed. The results have shown that
there is a mutual group of microbial species among the selected diseases. These
are intensively species of Firmicutes, Deltaproteobacteria,
Bacteriodetes and Actinobacteria
phyla. Another noteworthy aspect of this study is that the microbial species of
the Tenericutes phyla are intensely
present in atopic dermatitis and rheumatoid arthritis but not in psoriasis.
These results display that human gut microbiota has a role in complex autoimmune
diseases. This study showed that not only genes and proteins, but also
metabolites, microbiota and pathogen groups should be examined and analyzed in
detail in order to comprehend the mechanism of a disease.    

Anahtar Kelimeler

Autoimmunity, Psoriasis, Atopic dermatitis, Rheumatoid arthritis, Metabolite, Human gut microbiota

Transkriptom Verisi ve Omik Araçları Kullanılarak Otoimmün Hastalıklar ile İnsan Bağırsak Mikrobiyotası Arasındaki İlişkinin Analizi

Öz

İnsan
bağırsak mikrobiyotası ile insan hastalıkları arasındaki ilişkinin
anlamlandırılabilmesi konusunda yapılan çalışmalar yakın zamanda ivme
kazanmıştır. Bunun sebebi insan mikrobiyomunun hastalıklı ve sağlıklı
hallerdeki işlevi ve yapısı hakkında daha çok bilgiye sahip olunması ve
ilişkili mikrobiyal toplulukların genomlarının DNA diziliminin doğru
belirlenmesi şeklinde açıklanabilir. Yine de bu konuda çok fazla çalışma
bulunmamaktadır. Mevcut çalışmada üç önemli otoimmün hastalık olan Psoriazis,
Romatoid Artrit ve Atopik Dermatit’in, omiks araçları ile önce transkripsiyon
regülasyonu metabolik ağa entegre edilmiş daha sonra ise bu hastalıkların insan
bağırsak mikrobiyotası ile arasındaki bağlantı ortaya çıkarılmıştır. Elde
edilen sonuçlara göre seçilmiş olan hastalıklar ile ilgili ortak mikrobiyal
türler mevcuttur. Bunlar yoğun olarak Firmicutes,
Deltaproteobacteria, Bacteriodetes ve Actinobacteria
filumundaki türlerdir. Bu çalışmada bir başka dikkat çeken husus ise Tenericutes filumunun mikrobiyal
türlerinin Atopik dermatit ve Romatoid artritte yoğun olarak görüldüğü fakat
Psoriaziste çok fazla çeşitlilik göstermediğidir. Bu sonuçlar insan bağırsak mikrobiyotasının
kompleks otoimmün hastalıklarda bir rolünün olduğunu göstermektedir. Yapılan bu
çalışma bir hastalığın mekanizmasını anlayabilmek için sadece genler ve
proteinler değil bunların yanında metabolitler, mikrobiyota ve patojen
grupların da detaylıca incelenip analiz edilmesi gerektiğini ortaya
koymaktadır.

Anahtar Kelimeler

Otoimmünite, Psoriazis, Atopik Dermatit, Romatoid Artrit, Metabolit, İnsan Bağırsak Mikrobiyatası

Kaynakça

• [1] Ursell, L.K., Metcalf, J.L., Parfrey, L.W. Knight, R., 2012. Defining the human microbiome. Nutrition reviews, 70(suppl_1), S38-S44.
• [2] Levy, M., Thaiss, C.A. Elinav, E., 2016. Metabolites: messengers between the microbiota and the immune system. Genes & development, 30(14), 1589-1597.
• [3] Li, B., Selmi, C., Tang, R., Gershwin, M.E. Ma, X., 2018. The microbiome and autoimmunity: a paradigm from the gut-liver axis. Cellular & molecular immunology. doi: 10.1038/cmi.2018.7.
• [4] Vaughn, A.R., Notay, M., Clark, A.K. Sivamani, R.K., 2017. Skin-gut axis: The relationship between intestinal bacteria and skin health. World Journal of Dermatology, 6(4), 52-58.
• [5] Rooks, M.G. Garrett, W.S., 2016. Gut microbiota, metabolites and host immunity. Nature Reviews Immunology, 16(6), 341.
• [6] Fraser, A.G. Marcotte, E.M., 2004. A probabilistic view of gene function. Nature genetics, 36(6), 559.
• [7] Beebe, K., Sampey, B., Watkins, S.M., Milburn, M. Eckhart, A.D., 2014. Understanding the apothecaries within: the necessity of a systematic approach for defining the chemical output of the human microbiome. Clinical and translational science, 7(1), 74-81.
• [8] Braun, P., Rietman, E. Vidal, M., 2008. Networking metabolites and diseases. Proceedings of the National Academy of Sciences, 105(29), 9849-9850.
• [9] Perera, G. K., Di Meglio, P., Nestle, F. O. 2012. Psoriasis. Annual Review of Pathology: Mechanisms of Disease. 7:385 (2012), 422.
• [10] Orozco, G., Rueda, B. Martin, J., 2006. Genetic basis of rheumatoid arthritis. Biomedicine & Pharmacotherapy, 60(10), 656-662.
• [11] Gough S.C., Simmonds M.J. 2007. The HLA Region and Autoimmune Disease: Associations and Mechanisms of Action. Curr Genomics. 2007;8(7):453-65.
• [12] Hamilton, J.D., Suárez-Fariñas, M., Dhingra, N., Cardinale, I., Li, X., Kostic, A., Ming, J.E., Radin, A.R., Krueger, J.G., Graham, N., Yancopoulos, G.D., 2014. Dupilumab improves the molecular signature in skin of patients with moderate-to-severe atopic dermatitis. Journal of Allergy and Clinical Immunology, 134(6), 1293-1300.
• [13] Bieber, T. 2010. Atopic Dermatitis. Annuals of Dermatology. 22(2), 125-137.
• [14] Barrett, T., Wilhite, S.E., Ledoux, P., Evangelista, C., Kim, I.F., Tomashevsky, M., Marshall, K.A., Phillippy, K.H., Sherman, P.M., Holko, M., Yefanov, A., 2012. NCBI GEO: archive for functional genomics data sets-update. Nucleic acids research, 41(D1), D991-D995.
• [15] Sevimoglu, T. 2015. Using Systems Based Models To Uncover The Disease Network Of Psoriasis And Its Associations With Other Autoimmune-Related Diseases. Marmara Üniversitesi, Fen Bilimleri Enstitüsü, Doktora Tezi, İstanbul.
• [16] Mardinoglu, A., Agren, R., Kampf, C., Asplund, A., Uhlen, M. Nielsen, J., 2014. Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease. Nature Communications, 5, 3083.
• [17] Agren, R., Liu, L., Shoaie, S., Vongsangnak, W., Nookaew, I. Nielsen, J., 2013. The RAVEN toolbox and its use for generating a genome-scale metabolic model for Penicillium chrysogenum. PLoS computational biology, 9(3), p.e1002980.
• [18] Garcia-Albornoz, M., Thankaswamy-Kosalai, S., Nilsson, A., Väremo, L., Nookaew, I. Nielsen, J., 2014. BioMet Toolbox 2.0: genome-wide analysis of metabolism and omics data. Nucleic acids research, 42(W1), W175-W181.
• [19] López-Ibáñez, J., Pazos, F. Chagoyen, M., 2016. MBROLE 2.0-functional enrichment of chemical compounds. Nucleic acids research, 44(W1), W201-W204.
• [20] Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Amin, N., Schwikowski, B. Ideker, T., 2003. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome research, 13(11), 2498-2504.
• [21] Sung, J., Kim, S., Cabatbat, J.J.T., Jang, S., Jin, Y.S., Jung, G.Y., Chia, N. Kim, P.J., 2017. Global metabolic interaction network of the human gut microbiota for context-specific community-scale analysis. Nature communications, 8, 15393.
• [22] Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y. and Morishima, K., 2016. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic acids research, 45(D1), D353-D361.
• [23] Ma, W., Huang, C., Zhou, Y., Li, J. Cui, Q., 2017. MicroPattern: a web-based tool for microbe set enrichment analysis and disease similarity calculation based on a list of microbes. Scientific reports, 7, 40200.
• [24] The Human Microbiome Project Consortium, 2012. Structure, function and diversity of the healthy human microbiome. Nature volume 486, pages 207-214 (14 June 2012).
• [25] Harden, J.L., Lewis, S.M., Lish, S.R., Suárez-Fariñas, M., Gareau, D., Lentini, T., Johnson-Huang, L.M., Krueger, J.G. Lowes, M.A., 2016. The tryptophan metabolism enzyme L-kynureninase is a novel inflammatory factor in psoriasis and other inflammatory diseases. Journal of Allergy and Clinical Immunology, 137(6), 1830-1840.
• [26] Croom, E., 2012. Metabolism of xenobiotics of human environments. In Progress in molecular biology and translational science, 112, 31-88.
• [27] Anzenbacher, P. and Anzenbacherova, E., 2001. Cytochromes P450 and metabolism of xenobiotics. Cellular and Molecular Life Sciences CMLS, 58(5-6), 737-747.
• [28] Skelton, L.A., Boron, W.F. and Zhou, Y., 2010. Acid-base transport by the renal proximal tubule. Journal of nephrology, 23(0 16), p.S4.
• [29] Wilson, D.F., 2017. Oxidative phosphorylation: regulation and role in cellular and tissue metabolism. The Journal of physiology, 595(23), 7023-7038.
• [30] Yan, D., Issa, N., Afifi, L., Jeon, C., Chang, H.W. and Liao, W., 2017. The role of the skin and gut microbiome in psoriatic disease. Current dermatology reports, 6(2), 94-103.
• [31] Benhadou, F., Mintoff, D., Schnebert B., Thio, H. B., 2018. Psoriasis and Microbiota: A Systematic Review. Diseases. 6, 47.
• [32] Imhann, F., Vila, A.V., Bonder, M.J., Fu, J., Gevers, D., Visschedijk, M.C., Spekhorst, L.M., Alberts, R., Franke, L., Van Dullemen, H.M. Ter Steege, R.W., 2018. Interplay of host genetics and gut microbiota underlying the onset and clinical presentation of inflammatory bowel disease. Gut, 67(1), 108-119.
• [33] Fiorino G., Omodei P. D. 2015. Psoriasis and Inflammatory Bowel Disease: Two Sides of the Same Coin?, Journal of Crohn's and Colitis. 9(2015)(9), 697-698.
• [34] Lindsay, K., Fraser, A.D., Layton, A., Goodfield, M., Gruss, H. Gough, A., 2009. Liver fibrosis in patients with psoriasis and psoriatic arthritis on long-term, high cumulative dose methotrexate therapy. Rheumatology, 48(5), 569-572.
• [35] Negi, S., Singh, H. Mukhopadhyay, A., 2017. Gut bacterial peptides with autoimmunity potential as environmental trigger for late onset complex diseases: In-silico study. PloS one, 12(7), p.e0180518.
• [36] Bäumler, A.J. and Sperandio, V., 2016. Interactions between the microbiota and pathogenic bacteria in the gut. Nature, 535(7610), 85.