BECAS
DI MAGGIO Jimena Andrea
artículos
Título:
Global Sensitivity Anlysis in dynamic metabolic networks
Autor/es:
JIMENA ANDREA DI MAGGIO; JUAN CARLOS DIAZ RICCI; MARÍA SOLEDAD DÍAZ
Revista:
Computer Aided Chemical Engineering
Editorial:
Elsevier
Referencias:
Lugar: Amsterdam; Año: 2009 vol. 26 p. 1075 - 1080
ISSN:
1570-7946
Resumen:
Dynamic models for metabolic networks comprise a nonlinear differential
algebraic system of equations, which arise from mass balances for metabolites
and have a large number of kinetic parameters that require tuning for
a specific growth condition. However, uncertainty in input parameters has
different effect on model outputs. In this work, we have performed a global
sensitivity analysis through variance-based techniques to identify most influential
parameters on model output and which of them account for most of
the uncertainty in that output. Sensitivity indices have been calculated for
each parameter, based on Sobol´s approach (2001), which makes use of Monte
Carlo methods for the calculation of times profiles for main effect variances
in input parameters for main state variables. The global sensitivity analysis
has been carried out on a large-scale differential algebraic system representing
a dynamic model for the Embden-Meyerhof-Parnas pathway, the phosphotransferase
system and the pentose phosphate pathway of Escherichia coli
(Chassagnole et al., 2002). The model comprises eighteen dynamic mass balance
equations for extracellular glucose and intracellular metabolites, thirty
kinetic rate expressions and seven additional algebraic equations to represent
the concentration of co-metabolites. The model involves around one hundred
parameters (Di Maggio et al., 2008). We have implemented the large-scale
metabolic network model in g-PROMS (PSE Enterprise, 2007). In this environment,
two different sets of random parameters have been generated for
k=20 parameters, which were selected with a preliminary screening. Sample
size of N=2500 scenarios have been considered. We have performed the
N(2k+1) Monte Carlo simulations and output temporal profiles for state and
algebraic variables have been exported for subsequent variance and sensitivity
indices calculation within a Fortran 90 environment. Calculated sensitivity
indices show, for example, that all parameters affect the concentration of
ribu5p, but the most influential one is Nptsg6p, which is involved in the kinetic
expression for phophotransferase system. Pgp concentration is sensitive
to only four parameters, Kpglumueq, Kgapdhgap, Kgapdhpgp y Rgapdhmax
which are involved in the kinetic expressions for glyceraldehyde 3-phosphate
dehydrogenase and phosphoglycerate mutase