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...

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Detalles Bibliográficos
Autores: Fernández Do Porto, D.A., Auzmendi, J., Peña, D., García, V.E., Moffatt, L.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2013
País:Argentina
Institución:Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
Repositorio:Biblioteca Digital (UBA-FCEN)
Idioma:inglés
OAI Identifier:paperaa:paper_19326203_v8_n2_p_FernandezDoPorto
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_19326203_v8_n2_p_FernandezDoPorto
Access Level:acceso abierto
Palabra clave: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
Signal Transduction
T-Lymphocytes
Thermodynamics
Tuberculosis
Uncertainty
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oai_identifier_str paperaa:paper_19326203_v8_n2_p_FernandezDoPorto
network_acronym_str AR
network_name_str Argentina
repository_id_str
dc.title.none.fl_str_mv Bayesian Approach to Model CD137 Signaling in Human M. tuberculosis In Vitro Responses
title Bayesian Approach to Model CD137 Signaling in Human M. tuberculosis In Vitro Responses
spellingShingle Bayesian Approach to Model CD137 Signaling in Human M. tuberculosis In Vitro Responses
Fernández Do Porto, D.A.
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
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
dc.creator.none.fl_str_mv Fernández Do Porto, D.A.
Auzmendi, J.
Peña, D.
García, V.E.
Moffatt, L.
author Fernández Do Porto, D.A.
author_facet Fernández Do Porto, D.A.
Auzmendi, J.
Peña, D.
García, V.E.
Moffatt, L.
author_role author
author2 Auzmendi, J.
Peña, D.
García, V.E.
Moffatt, L.
author2_role author
author
author
author
dc.subject.none.fl_str_mv 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
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
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.
publishDate 2013
dc.date.none.fl_str_mv 2013
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12110/paper_19326203_v8_n2_p_FernandezDoPorto
url http://hdl.handle.net/20.500.12110/paper_19326203_v8_n2_p_FernandezDoPorto
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/2.5/ar
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/2.5/ar
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv PLoS ONE 2013;8(2)
reponame:Biblioteca Digital (UBA-FCEN)
instname:Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
instacron:UBA-FCEN
instname_str Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
instacron_str UBA-FCEN
institution UBA-FCEN
reponame_str Biblioteca Digital (UBA-FCEN)
collection Biblioteca Digital (UBA-FCEN)
repository.name.fl_str_mv Biblioteca Digital (UBA-FCEN) - Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
repository.mail.fl_str_mv ana@bl.fcen.uba.ar
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spelling Bayesian Approach to Model CD137 Signaling in Human M. tuberculosis In Vitro ResponsesFernández Do Porto, D.A.Auzmendi, J.Peña, D.García, V.E.Moffatt, L.CD137 antigencytokinegamma interferontuberculostatic agenttumor necrosis factor alphaantigen presenting cellarticleBayes theoremcell survivalclinical articleculture mediumcytokine productionhumanimmune responsein vitro studylung tuberculosisMonte Carlo methodMycobacterium tuberculosisnatural killer cellnonhumannonlinear systemprobabilityqualitative analysisquantitative analysisT lymphocytethermodynamics4-1BB LigandAdaptive ImmunityAdultAntigen-Presenting CellsAntigens, CD137Antigens, CD56Bayes TheoremCellular MicroenvironmentCytokinesHumansImmunity, InnateIntracellular SpaceKiller Cells, NaturalModels, BiologicalMycobacterium tuberculosisSignal TransductionT-LymphocytesThermodynamicsTuberculosisUncertaintyImmune 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.2013info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12110/paper_19326203_v8_n2_p_FernandezDoPortoPLoS ONE 2013;8(2)reponame:Biblioteca Digital (UBA-FCEN)instname:Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturalesinstacron:UBA-FCENenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/2.5/ar2024-05-10T10:42:44Zpaperaa:paper_19326203_v8_n2_p_FernandezDoPortoInstitucionalhttps://digital.bl.fcen.uba.ar/Universidad públicaNo correspondehttps://digital.bl.fcen.uba.ar/cgi-bin/oaiserver.cgiana@bl.fcen.uba.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:18962024-05-10 10:42:45.545Biblioteca Digital (UBA-FCEN) - Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturalesfalse
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