Bayesian Approach to Model CD137 Signaling in Human M. tuberculosis In Vitro Responses
Immune responses are qualitatively and quantitatively influenced by a complex network of receptor-ligand interactions. Among them, the CD137:CD137L pathway is known to modulate innate and adaptive human responses against Mycobacterium tuberculosis. However, the underlying mechanisms of this regulati...
Guardado en:
Autores principales: | , , , , |
---|---|
Publicado: |
2013
|
Materias: | |
Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_19326203_v8_n2_p_FernandezDoPorto http://hdl.handle.net/20.500.12110/paper_19326203_v8_n2_p_FernandezDoPorto |
Aporte de: |
id |
paper:paper_19326203_v8_n2_p_FernandezDoPorto |
---|---|
record_format |
dspace |
spelling |
paper:paper_19326203_v8_n2_p_FernandezDoPorto2023-06-08T16:31:13Z Bayesian Approach to Model CD137 Signaling in Human M. tuberculosis In Vitro Responses Fernandez Do Porto, Dario Augusto Auzmendi, Jeronimo Andres Peña, Delfina García, Verónica Edith Moffatt, Luciano CD137 antigen cytokine gamma interferon tuberculostatic agent tumor necrosis factor alpha antigen presenting cell article Bayes theorem cell survival clinical article culture medium cytokine production human immune response in vitro study lung tuberculosis Monte Carlo method Mycobacterium tuberculosis natural killer cell nonhuman nonlinear system probability qualitative analysis quantitative analysis T lymphocyte thermodynamics 4-1BB Ligand Adaptive Immunity Adult Antigen-Presenting Cells Antigens, CD137 Antigens, CD56 Bayes Theorem Cellular Microenvironment Cytokines Humans Immunity, Innate Intracellular Space Killer Cells, Natural Models, Biological Mycobacterium tuberculosis Signal Transduction T-Lymphocytes Thermodynamics Tuberculosis Uncertainty Immune responses are qualitatively and quantitatively influenced by a complex network of receptor-ligand interactions. Among them, the CD137:CD137L pathway is known to modulate innate and adaptive human responses against Mycobacterium tuberculosis. However, the underlying mechanisms of this regulation remain unclear. In this work, we developed a Bayesian Computational Model (BCM) of in vitro CD137 signaling, devised to fit previously gathered experimental data. The BCM is fed with the data and the prior distribution of the model parameters and it returns their posterior distribution and the model evidence, which allows comparing alternative signaling mechanisms. The BCM uses a coupled system of non-linear differential equations to describe the dynamics of Antigen Presenting Cells, Natural Killer and T Cells together with the interpheron (IFN)-γ and tumor necrosis factor (TNF)-α levels in the media culture. Fast and complete mixing of the media is assumed. The prior distribution of the parameters that describe the dynamics of the immunological response was obtained from the literature and theoretical considerations Our BCM applies successively the Levenberg-Marquardt algorithm to find the maximum a posteriori likelihood (MAP); the Metropolis Markov Chain Monte Carlo method to approximate the posterior distribution of the parameters and Thermodynamic Integration to calculate the evidence of alternative hypothesis. Bayes factors provided decisive evidence favoring direct CD137 signaling on T cells. Moreover, the posterior distribution of the parameters that describe the CD137 signaling showed that the regulation of IFN-γ levels is based more on T cells survival than on direct induction. Furthermore, the mechanisms that account for the effect of CD137 signaling on TNF-α production were based on a decrease of TNF-α production by APC and, perhaps, on the increase in APC apoptosis. BCM proved to be a useful tool to gain insight on the mechanisms of CD137 signaling during human response against Mycobacterium tuberculosis. © 2013 Fernández Do Porto et al. Fil:Fernández Do Porto, D.A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Auzmendi, J. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Peña, D. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:García, V.E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Moffatt, L. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2013 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_19326203_v8_n2_p_FernandezDoPorto http://hdl.handle.net/20.500.12110/paper_19326203_v8_n2_p_FernandezDoPorto |
institution |
Universidad de Buenos Aires |
institution_str |
I-28 |
repository_str |
R-134 |
collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
topic |
CD137 antigen cytokine gamma interferon tuberculostatic agent tumor necrosis factor alpha antigen presenting cell article Bayes theorem cell survival clinical article culture medium cytokine production human immune response in vitro study lung tuberculosis Monte Carlo method Mycobacterium tuberculosis natural killer cell nonhuman nonlinear system probability qualitative analysis quantitative analysis T lymphocyte thermodynamics 4-1BB Ligand Adaptive Immunity Adult Antigen-Presenting Cells Antigens, CD137 Antigens, CD56 Bayes Theorem Cellular Microenvironment Cytokines Humans Immunity, Innate Intracellular Space Killer Cells, Natural Models, Biological Mycobacterium tuberculosis Signal Transduction T-Lymphocytes Thermodynamics Tuberculosis Uncertainty |
spellingShingle |
CD137 antigen cytokine gamma interferon tuberculostatic agent tumor necrosis factor alpha antigen presenting cell article Bayes theorem cell survival clinical article culture medium cytokine production human immune response in vitro study lung tuberculosis Monte Carlo method Mycobacterium tuberculosis natural killer cell nonhuman nonlinear system probability qualitative analysis quantitative analysis T lymphocyte thermodynamics 4-1BB Ligand Adaptive Immunity Adult Antigen-Presenting Cells Antigens, CD137 Antigens, CD56 Bayes Theorem Cellular Microenvironment Cytokines Humans Immunity, Innate Intracellular Space Killer Cells, Natural Models, Biological Mycobacterium tuberculosis Signal Transduction T-Lymphocytes Thermodynamics Tuberculosis Uncertainty Fernandez Do Porto, Dario Augusto Auzmendi, Jeronimo Andres Peña, Delfina García, Verónica Edith Moffatt, Luciano Bayesian Approach to Model CD137 Signaling in Human M. tuberculosis In Vitro Responses |
topic_facet |
CD137 antigen cytokine gamma interferon tuberculostatic agent tumor necrosis factor alpha antigen presenting cell article Bayes theorem cell survival clinical article culture medium cytokine production human immune response in vitro study lung tuberculosis Monte Carlo method Mycobacterium tuberculosis natural killer cell nonhuman nonlinear system probability qualitative analysis quantitative analysis T lymphocyte thermodynamics 4-1BB Ligand Adaptive Immunity Adult Antigen-Presenting Cells Antigens, CD137 Antigens, CD56 Bayes Theorem Cellular Microenvironment Cytokines Humans Immunity, Innate Intracellular Space Killer Cells, Natural Models, Biological Mycobacterium tuberculosis Signal Transduction T-Lymphocytes Thermodynamics Tuberculosis Uncertainty |
description |
Immune responses are qualitatively and quantitatively influenced by a complex network of receptor-ligand interactions. Among them, the CD137:CD137L pathway is known to modulate innate and adaptive human responses against Mycobacterium tuberculosis. However, the underlying mechanisms of this regulation remain unclear. In this work, we developed a Bayesian Computational Model (BCM) of in vitro CD137 signaling, devised to fit previously gathered experimental data. The BCM is fed with the data and the prior distribution of the model parameters and it returns their posterior distribution and the model evidence, which allows comparing alternative signaling mechanisms. The BCM uses a coupled system of non-linear differential equations to describe the dynamics of Antigen Presenting Cells, Natural Killer and T Cells together with the interpheron (IFN)-γ and tumor necrosis factor (TNF)-α levels in the media culture. Fast and complete mixing of the media is assumed. The prior distribution of the parameters that describe the dynamics of the immunological response was obtained from the literature and theoretical considerations Our BCM applies successively the Levenberg-Marquardt algorithm to find the maximum a posteriori likelihood (MAP); the Metropolis Markov Chain Monte Carlo method to approximate the posterior distribution of the parameters and Thermodynamic Integration to calculate the evidence of alternative hypothesis. Bayes factors provided decisive evidence favoring direct CD137 signaling on T cells. Moreover, the posterior distribution of the parameters that describe the CD137 signaling showed that the regulation of IFN-γ levels is based more on T cells survival than on direct induction. Furthermore, the mechanisms that account for the effect of CD137 signaling on TNF-α production were based on a decrease of TNF-α production by APC and, perhaps, on the increase in APC apoptosis. BCM proved to be a useful tool to gain insight on the mechanisms of CD137 signaling during human response against Mycobacterium tuberculosis. © 2013 Fernández Do Porto et al. |
author |
Fernandez Do Porto, Dario Augusto Auzmendi, Jeronimo Andres Peña, Delfina García, Verónica Edith Moffatt, Luciano |
author_facet |
Fernandez Do Porto, Dario Augusto Auzmendi, Jeronimo Andres Peña, Delfina García, Verónica Edith Moffatt, Luciano |
author_sort |
Fernandez Do Porto, Dario Augusto |
title |
Bayesian Approach to Model CD137 Signaling in Human M. tuberculosis In Vitro Responses |
title_short |
Bayesian Approach to Model CD137 Signaling in Human M. tuberculosis In Vitro Responses |
title_full |
Bayesian Approach to Model CD137 Signaling in Human M. tuberculosis In Vitro Responses |
title_fullStr |
Bayesian Approach to Model CD137 Signaling in Human M. tuberculosis In Vitro Responses |
title_full_unstemmed |
Bayesian Approach to Model CD137 Signaling in Human M. tuberculosis In Vitro Responses |
title_sort |
bayesian approach to model cd137 signaling in human m. tuberculosis in vitro responses |
publishDate |
2013 |
url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_19326203_v8_n2_p_FernandezDoPorto http://hdl.handle.net/20.500.12110/paper_19326203_v8_n2_p_FernandezDoPorto |
work_keys_str_mv |
AT fernandezdoportodarioaugusto bayesianapproachtomodelcd137signalinginhumanmtuberculosisinvitroresponses AT auzmendijeronimoandres bayesianapproachtomodelcd137signalinginhumanmtuberculosisinvitroresponses AT penadelfina bayesianapproachtomodelcd137signalinginhumanmtuberculosisinvitroresponses AT garciaveronicaedith bayesianapproachtomodelcd137signalinginhumanmtuberculosisinvitroresponses AT moffattluciano bayesianapproachtomodelcd137signalinginhumanmtuberculosisinvitroresponses |
_version_ |
1768544386491088896 |