Sobre el modelado matemático de la red bioquímica que describe la interacción molecular entre receptores celulares de células dentríticas y el ligando manosa de mycobacterium tuberculosis
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Keywords
Tuberculosis, Células dendríticas, Micobacterium tuberculosis, ligandos, receptores, modelado matemático
Resumen
A nivel mundial se considera a la tuberculosis (TB) como una enfermedad de gran importancia en la salud pública con grandes impactos socioeconómicos, presentando elevadas tasas de incidencia y mortalidad. El modelamiento matemático en el complejo CD-Mtb (Células dentríticas-Mycobacterium tuberculosis) ha sido poco estudiado, lo que representa un problema de investigación que se puede abordar con los avances actuales sobre el modelamiento en escalas moleculares, siendo "el modelo receptor-ligando con representación de estados" el más recomendado para abordar esta dinámica. Adicionalmente, la importancia de estudios en este campo radica en la predicción que permitiría efectuar la modelación en asociación al desarrollo de un estadio de Tb activa o latente. Teniendo en cuenta lo anterior, en esta investigación se enfocó en determinar los principales receptores que se acoplan con el ligando manosa en el proceso molecular de reconocimiento, además de formular a partir de la literatura disponible, una red bioquímica que acople la interacción molecular entre las células dendríticas y el patógeno Mtb en las vías de señalización que implican el reconocimiento de la manosa por los receptores de células dendríticas (DC-SIGN, TLR4, de TLR9, TLR2, MR, Dectin-2, Mincle, FcRy, Dectin-1, SIGNR-3, CR3, SR, Langerin). Se espera que a partir de esta red se desarrollen modelos matemáticos mediante sistemas de ecuaciones diferenciales, esta modelación permitirá manipular variables y parámetros, con el propósito de contestar preguntas acerca de las posibles interacciones mediadas entre doce receptores celulares y el ligando manosa.
Referencias
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2- Akira S., Takeda K. and Kaisho T. (2001). Toll-like receptors: critical proteins linking innate and acquired immunity. Nature Immunology, 2(8): 675 - 680
3- Balboa L., Romero M., Yokobori N., Schierloh P., Geffner L., Basile J., Musella R., Abbate E., de la Barrera S., Sasiain M. and Alemán M. (2010). Mycobacterium tuberculosis impairs dendritic cell response by altering CD1b, DC-SIGN and MR profile. Immunology and Cell Biology, 88:716-726
4- Banchereau J. and Steinman R. (1998). Dendritic cells and the control of immunity. Nature, 392: 245 - 252
5- Banchereau J., Briere F., Caux C., Davoust J., Lebecque S., Liu Y., Pulendran B. and Palucka K. (2000). Immunobiology Of dendritic cells. Annu. Rev. Immunol, 18:767-811
6- Bansal K., Elluru S., Narayana Y., Chaturvedi R., Patil S., Kaveri S., Bayry J. and Balaji K. (2010). PE_PGRS Antigens of Mycobacterium tuberculosis Induce Maturation and Activation of Human Dendritic Cells. J. Immunol, 184;3495-3504
7- Buschow S., Lasonder E., van Deutekom H., Oud M., Beltrame L., Huynen M., de Vries I., Figdor C. and Cavalieri D. (2010). Dominant Processes during Human Dendritic Cell Maturation Revealed by Integration of Proteome and Transcriptome at the Pathway Level. Journal of Proteome Research, 9:1727-1737
8- Chávez D. (2007). Receptores Tipo Toll. Rev. latinoam. actual. bioméd., 1(1): 3-9
9- Chavesa M., Sontag E. and Dinerstein R. (2004). Steady-States of Receptor-Ligand Dynamics: A Theoretical Framework. Preprint submitted to Elsevier Science
10- Chen K., Lu J., Wang L. and Gan YW. (2004). Mycobacterial heat shock protein 65 enhances antigen cross-presentation in dendritic cells independent of Toll-like receptor 4 signaling. J. Leukoc. Biol., 75: 260 -266
11- Dietrich J. and Doherty M. (2009). Interaction of Mycobacterium tuberculosis with the host: consequences for vaccine development. APMIS, 117: 440-457
12- Eungdamrong N. and Lyengar R. (2004). Modeling Cell Signaling Networks. Biology of the Cell, 96: 355-362
13- Geijtenbeek T., van Vliet S., Koppel E., Sanchez-Hernandez M., Vandenbroucke-Grauls C., Appelmelk B. and van Kooyk Y. (2002). Mycobacteria Target DC-SIGN to Suppress Dendritic Cell Function. J. Exp. Med., 197(1): 7 - 17
14- Gringhuis S., Dunnen J., Litjens M., Hof B., van Kooyk Y. and Geijtenbeek T. (2007). C-Type Lectin DC-SIGN Modulates Toll-like Receptor Signaling via Raf-1 Kinase-Dependent Acetylation of Transcription Factor NF-Kb. Immunity, 26: 605-616
15- Gurevich K. (2004). Application of methods of identifying receptorbinding models and analysis of parameters. Theoretical Biology and Medical Modelling, 1:11
16- Henderson, R.A. Watkins S.C. and Flynn JL. (1997). Activation of human dendritic cells following infection with Mycobacterium tuberculosis. The Journal of Immunology, 159(2) : 635-643.
17. Ibarguen-Mondragon E, Esteva Lourdes, Burbano-Rosero E. (2017). Mathematical model for the growth of mycobacterium tuberculosis in the granuloma. Mathematical Biosciences and Engineering, 13 (5), 407-428.
18. Ibarguen-Mondragon E., Esteva L., Chavez-Galán Leslie (2011). A mathematical model for cellular immunology of tuberculosis. Mathematical Biosciences and Engineering, 8 (4), 973-986.
19. Ibarguen-Mondragon E., Esteva L. (2014). On the interactions of sensitive and resistant Mycobacterium, Mathematical Biosciences 246 (2013) 84–93
20. Ibarguen-Mondragon E., Esteva L. (2014). On CTL response against Mycobacterium tuberculosis, Applied Mathematical Sciences, 8 (48), 2383-2389.
21. Kirschner D., Chang S., Riggs T., Perry N. and Linderman J. (2007). Toward a multiscale model of antigen presentation in immunity. Immunological Reviews, 216: 93-118
22. Klein P., Mattoon D., Lemmon M. and Schlessinger J. (2003). A structure-based model for ligand binding and dimerization of EGF receptors. PNAS, 101(4): 929 - 934
23. Klotz I. and Hunston D. (1984). Mathematical Models for Ligand-Receptor Binding. The Journal Of Biological Chemistry, 259(16): 10060 - 10062
24. Lewinsohn D., Grotzke J., Heinzel A., Zhu L., Ovendale P., Johnson M. and Alderson M. (2006). Secreted Proteins from Mycobacterium tuberculosis Gain Access to the Cytosolic MHC Class-I Antigen-Processing Pathway. The Journal of Immunology, 177: 437- 442
25. Li Q., Singh C., Ma S., Price N. and Jagannath C. (2011). Label-free proteomics and systems biology analysis of mycobacterial phagosomes in dendritic cells and macrophages. J Proteome Res, 10(5): 2425-2439
26. Liu, K. (2006). Dendritic Cell, Toll-Like Receptor, and The Immune System. Journal of Cancer Molecules, 2(6): 213-215
27. Mortellaro A., Robinson L. and Ricciardi-Castagnoli P. (2009). Spotlight on mycobacteria and dendritic cells: will novel targets to fight tuberculosis emerge?. EMBO mol. med., 1: 19 - 29
28. Pérez M. (2006). Procesamiento y presentación de antígeno por moléculas MHC clase I y clase II. Rev. Med. Inst. Mex., 44(2): 7-10
29. Savina A. and Amigorena S. (2007). Phagocytosis andantigen presentation in dendritic cells. Immunological Reviews, 219: 143-156
30. Serrano-Gómez D., Martínez-Nuñez R., Sierra-Filardi E., Izquierdo N., Colmenares M., Pla J., Rivas L., Martinez-Picado J., Jimenez-Barbero J., Alonso-Lebrero J., González S. and Corbí A. (2007). AM3 Modulates Dendritic Cell Pathogen Recognition Capabilities by Targeting DC-SIGN. Antimicrobial Agents and Chemotherapy, 51(7): 2313-2323
31. Wigginton J. and Kirschner D. (2001). A Model to Predict Cell-Mediated Immune Regulatory Mechanisms During Human Infection with Mycobacterium tuberculosis. The Journal of Immunology, 166: 1951-1967
32. Behler, F., Maus, R., Bohling, J., Knippenberg, S., Kirchhof, G., Nagata, M., … Maus, U. A. (2015). Macrophage-Inducible C-Type Lectin Mincle-Expressing Dendritic Cells Contribute to Control of Splenic Mycobacterium bovis BCG Infection in Mice. Infection and Immunity, 83(1), 184–196. http://doi.org/10.1128/IAI.02500-14 .
33. Mihret, A. (2012). The role of dendritic cells in Mycobacterium tuberculosis infection. Virulence, 3(7), 654–659. http://doi.org/10.4161/viru.22586 .
34. Inaba K, Pack M, Inaba M, Sakuta H, Isdell F, Steinman RM. High levels of a major histocompatibility complex II-self peptide complex on dendritic cells from the T cell areas of lymph nodes. J. Exp. Med. 186: 665-72 (1997).
35. Guery JC, Adorini L. Dendritic cells are the most effi cient in presenting endogenous naturally processed self-epitopes to class II-restricted T cells. J. Immunol. 154: 536-44 (1995).
36. Sallusto F, Lanzavecchia A. Mobilizing dendritic cells for tolerance, priming, and chronic inflammation. J. Exp. Med. 189: 611-4 (1999); Banchereau J, Briere F, Caux C, Davoust J, Lebecque S, Liu YJ, Pulendran B, Palucka K. Immunobiology of dendritic cells. Annu. Rev. Immunol. 18: 767-811 (2000).
37. Orabona C, Grohmann U, Belladonna ML, Fallarino F, Vacca C, Bianchi R, Bozza S, Volpi C, CD28 induces immunostimulatory signals in dendritic cells via CD80 and CD86, Nature immunology, 5 (11), 1134-1142.
38. Ma DY, Clark EA. The role of CD40 and CD154/CD40L in dendritic cells. Semin. Immunol. 21:265-72 (2009) .
39. Johnson JG, Jenkins MK. Co-stimulatory functions of antigen-presenting cells. J. Invest. Dermatol. 99: 62S-65S (1992).
40. Reis e Sousa C. Dendritic cells in a mature age. Nat Rev Immunol. 6: 476-83 (2006).
41. Figdor CG, van Kooyk Y, Adema GJ. C-type lectin receptors on dendritic cells and Langerhans cells. Nat Rev Immunol. 2: 77-84 (2002),
42. Geijtenbeek TB, Engering A, Van Kooyk Y. DC-SIGN, a C-type lectin on dendritic cells that unveils many aspects of dendritic cell biology. J. Leukoc. Biol. 71: 921-31 (2002).
43. Romero-Palomo, F., Sánchez Cordón, P., Risalde, M., Pedrera, M., Molina, V., Ruiz-Villamor, E., Gomez-Villamandos, J. (2011). Funciones y clasificación de las células dentríticas. Real Academia de Ciencias Veterinarias de Andalucia Oriental. Vol (24): 167-191.
44. Clark GJ, Angel N, Kato M, Lopez JA, MacDonald K, Vuckovic S, Hart DN. The role of dendritic cells in the innate immune system. Microbes Infect. 2: 257-72 (2000); -Reis e Sousa C. Activation of dendritic cells: translating innate into adaptive immunity. Curr. Opin. Immunol. 16: 21-5 (2004) .
45. Reis e Sousa C. Dendritic cells as sensors of infection. Immunity. 14: 495-8 (2001).
46. Reis e Sousa C. Activation of dendritic cells: translating innate into adaptive immunity. Curr. Opin. Immunol. 16: 21-5 (2004); Reis e Sousa C. Toll-like receptors and dendritic cells: for whom the bug tolls. Semin. Immunol. 16: 27-34 (2004).
47. Moser M, Murphy KM. Dendritic cell regulation of TH1-TH2 development. Nature immunology.1: 199-205 (2000) .
48. McKenna K, Beignon AS, Bhardwaj N. Plasmacytoid dendritic cells: linking innate and adaptive immunity. J. Virol. 79: 17-27 (2005); Diebold SS, Montoya M, Unger H, Alexopoulou L, Roy P, Haswell LE, Al-Shamkhani A, Flavell R, Borrow P, Reis e Sousa C. Viral infection switches non-plasmacytoid dendritic cells into high interferon producers. Nature. 424: 324-8 (2003) .
49. Huang FP, MacPherson GG. Continuing education of the immune system--dendritic cells, immune regulation and tolerance. Curr Mol Med. 1: 457-68 (2001); Steinman RM, Hawiger D, Nussenzweig MC. Tolerogenic dendritic cells. Annu. Rev. Immunol. 21: 685-711 (2003) .
50. Steinman RM, Nussenzweig MC. Avoiding horror autotoxicus: the importance of dendritic cells in peripheral T cell tolerance. Proc. Natl. Acad. Sci. U. S. A. 99: 351-8 (2002) .
51. Roncarolo MG, Levings MK, Traversari C. Differentiation of T regulatory cells by immature dendritic cells. J. Exp. Med. 193: F5-9 (2001)
52. Guevara-Guzmán A, Juárez-Hernández A, Zenteno-Cuevas R.Tuberculosis y la importancia de incorporar nuevas metodologías diagnósticas. MedUNAB 2003; 6 (16): 46-51.
53. Gorocica P, Jiménez-Martínez MC, Garfias Y, Sada I, Lascurain R. Componentes glicosilados de la envoltura de Mycobacterium tuberculosis que intervienen en la patogénesis de la tuberculosis. Rev Inst Nal Enf Resp Mex 2005; 18(2): 142-153 .
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55. Mitchell A. Yakrus, Jeffrey Driscoll, Allison McAlister, et al., “Molecular and Growth-Based Drug Susceptibility Testing of Mycobacterium tuberculosis Complex for Ethambutol Resistance in the United States,” Tuberculosis Research and Treatment, vol. 2016, Article ID 3404860, 5 pages, 2016. doi:10.1155/2016/3404860.
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Sobre el modelado matemático de la red bioquímica que describe la interacción molecular entre receptores celulares de células dentríticas y el ligando manosa de mycobacterium tuberculosis. bol.redipe [Internet]. 2021 Feb. 1 [cited 2024 Nov. 24];10(2):109-30. Available from: https://revista.redipe.org/index.php/1/article/view/1199
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Biografía del autor/a
Eduardo Ibarguen Mondragón, Universidad de Nariño, Colombia
Departamento de Matemáticas y Estadística, Universidad de Nariño, Pasto, Colombia
Edith Mariela Burbano-Rosero, Universidad de Nariño, Colombia
Departamento de Biología, Universidad de Nariño, Pasto, Colombia.
Mawency Vergel-Ortega, Universidad Francisco de Paula Santander, Colombia
Departamento de Matemáticas y Estadística, Universidad Francisco de Paula Santander, Norte de Santander, Cúcuta, Colombia.
Cómo citar
1.
Sobre el modelado matemático de la red bioquímica que describe la interacción molecular entre receptores celulares de células dentríticas y el ligando manosa de mycobacterium tuberculosis. bol.redipe [Internet]. 2021 Feb. 1 [cited 2024 Nov. 24];10(2):109-30. Available from: https://revista.redipe.org/index.php/1/article/view/1199