TY - JOUR
T1 - MetDFBA: incorporating time-resolved metabolomics measurements into dynamic flux balance analysis.
AU - Willemsen, A.M.
AU - Hedrickx, D.M.
AU - Hoefsloot, H.C.
AU - Hendriks, M.M.W.B.
AU - Wahl, S.A.
AU - Teusink, B.
AU - Smilde, A.K.
AU - van Kampen, A.H.C.
AU - Hendrickx, D.M.
N1 - With supplementary information
PY - 2015
Y1 - 2015
N2 - Understanding cellular adaptation to environmental changes is one of the major challenges in systems biology. To understand how cellular systems react towards perturbations of their steady state, the metabolic dynamics have to be described. Dynamic properties can be studied with kinetic models but development of such models is hampered by limited in vivo information, especially kinetic parameters. Therefore, there is a need for mathematical frameworks that use a minimal amount of kinetic information. One of these frameworks is dynamic flux balance analysis (DFBA), a method based on the assumption that cellular metabolism has evolved towards optimal changes to perturbations. However, DFBA has some limitations. It is less suitable for larger systems because of the high number of parameters to estimate and the computational complexity. In this paper, we propose MetDFBA, a modification of DFBA, that incorporates measured time series of both intracellular and extracellular metabolite concentrations, in order to reduce both the number of parameters to estimate and the computational complexity. MetDFBA can be used to estimate dynamic flux profiles and, in addition, test hypotheses about metabolic regulation. In a first case study, we demonstrate the validity of our method by comparing our results to flux estimations based on dynamic
AB - Understanding cellular adaptation to environmental changes is one of the major challenges in systems biology. To understand how cellular systems react towards perturbations of their steady state, the metabolic dynamics have to be described. Dynamic properties can be studied with kinetic models but development of such models is hampered by limited in vivo information, especially kinetic parameters. Therefore, there is a need for mathematical frameworks that use a minimal amount of kinetic information. One of these frameworks is dynamic flux balance analysis (DFBA), a method based on the assumption that cellular metabolism has evolved towards optimal changes to perturbations. However, DFBA has some limitations. It is less suitable for larger systems because of the high number of parameters to estimate and the computational complexity. In this paper, we propose MetDFBA, a modification of DFBA, that incorporates measured time series of both intracellular and extracellular metabolite concentrations, in order to reduce both the number of parameters to estimate and the computational complexity. MetDFBA can be used to estimate dynamic flux profiles and, in addition, test hypotheses about metabolic regulation. In a first case study, we demonstrate the validity of our method by comparing our results to flux estimations based on dynamic
UR - https://pure.uva.nl/ws/files/2411926/160714_MetDFBA_suppl.pdf
U2 - https://doi.org/10.1039/c4mb00510d
DO - https://doi.org/10.1039/c4mb00510d
M3 - Article
C2 - 25315283
SN - 1742-206X
VL - 11
SP - 137
EP - 145
JO - Molecular bioSystems
JF - Molecular bioSystems
IS - 11
M1 - 1
ER -