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
Descripción
Sumario: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.