title: Estimating relative changes of metabolic fluxes.
abstract: Fluxes are the central trait of metabolism and Kinetic Flux Profiling (KFP) is an effective method of measuring them. To generalize its applicability, we present an extension of the method that estimates the relative changes of fluxes using only relative quantitation of 13C-labeled metabolites. Such features are directly tailored to the more common experiment that performs only relative quantitation and compares fluxes between two conditions. We call our extension rKFP. Moreover, we examine the effects of common missing data and common modeling assumptions on (r)KFP, and provide practical suggestions. We also investigate the selection of measuring times for (r)KFP and provide a simple recipe. We then apply rKFP to 13C-labeled glucose time series data collected from cells under normal and glucose-deprived conditions, estimating the relative flux changes of glycolysis and its branching pathways. We identify an adaptive response in which de novo serine biosynthesis is compromised to maintain the glycolytic flux backbone. Together, these results greatly expand the capabilities of KFP and are suitable for broad biological applications.
authors.affiliation: Graduate Field of Computational Biology, Cornell University, Ithaca, New York, United States of America.
authors.forename: Lei
authors.initials: L
authors.lastname: Huang
authors.affiliation: Graduate Field of Biochemistry, Molecular and Cell Biology, Cornell University, Ithaca, New York, United States of America.
authors.forename: Dongsung
authors.initials: D
authors.lastname: Kim
authors.affiliation: Division of Nutritional Sciences, Cornell University, Ithaca, New York, United States of America.
authors.forename: Xiaojing
authors.initials: X
authors.lastname: Liu
authors.affiliation: Laboratory of Atomic and Solid State Physics, and Institute of Biotechnology, Cornell University, Ithaca, New York, United States of America; Field of Computational Biology and Medicine, Cornell University, Ithaca, New York, United States of America.
authors.forename: Christopher R
authors.initials: CR
authors.lastname: Myers
authors.affiliation: Graduate Field of Computational Biology, Cornell University, Ithaca, New York, United States of America; Graduate Field of Biochemistry, Molecular and Cell Biology, Cornell University, Ithaca, New York, United States of America; Division of Nutritional Sciences, Cornell University, Ithaca, New York, United States of America; Field of Computational Biology and Medicine, Cornell University, Ithaca, New York, United States of America.
authors.forename: Jason W
authors.initials: JW
authors.lastname: Locasale
mesh_terms: D002247:Carbon Isotopes / Q000378:metabolism; D005947:Glucose / Q000378:metabolism; D006019:Glycolysis / Q000502:physiology; D007700:Kinetics; D064688:Metabolic Flux Analysis; D055442:Metabolome / Q000502:physiology*; D008954:Models, Biological; D049490:Systems Biology
chemical_list: D002247:Carbon Isotopes; D005947:Glucose