title: Adaptive control model reveals systematic feedback and key molecules in metabolic pathway regulation.
abstract: Robust behavior in metabolic pathways resembles stabilized performance in systems under autonomous control. This suggests we can apply control theory to study existing regulation in these cellular networks. Here, we use model-reference adaptive control (MRAC) to investigate the dynamics of de novo sphingolipid synthesis regulation in a combined theoretical and experimental case study. The effects of serine palmitoyltransferase over-expression on this pathway are studied in vitro using human embryonic kidney cells. We report two key results from comparing numerical simulations with observed data. First, MRAC simulations of pathway dynamics are comparable to simulations from a standard model using mass action kinetics. The root-sum-square (RSS) between data and simulations in both cases differ by less than 5%. Second, MRAC simulations suggest systematic pathway regulation in terms of adaptive feedback from individual molecules. In response to increased metabolite levels available for de novo sphingolipid synthesis, feedback from molecules along the main artery of the pathway is regulated more frequently and with greater amplitude than from other molecules along the branches. These biological insights are consistent with current knowledge while being new that they may guide future research in sphingolipid biology. In summary, we report a novel approach to study regulation in cellular networks by applying control theory in the context of robust metabolic pathways. We do this to uncover potential insight into the dynamics of regulation and the reverse engineering of cellular networks for systems biology. This new modeling approach and the implementation routines designed for this case study may be extended to other systems. Supplementary Material is available at www.liebertonline.com/cmb .
authors.affiliation: Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA. cfquo@gatech.edu
authors.forename: Chang F
authors.initials: CF
authors.lastname: Quo
authors.forename: Richard A
authors.initials: RA
authors.lastname: Moffitt
authors.forename: Alfred H
authors.initials: AH
authors.lastname: Merrill
authors.forename: May D
authors.initials: MD
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D002460:Cell Line; D025461:Feedback, Physiological; D006801:Humans; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D013107:Sphingolipids / Q000378:metabolism
chemical_list: D013107:Sphingolipids