title: RELATCH: relative optimality in metabolic networks explains robust metabolic and regulatory responses to perturbations.
abstract: Predicting cellular responses to perturbations is an important task in systems biology. We report a new approach, RELATCH, which uses flux and gene expression data from a reference state to predict metabolic responses in a genetically or environmentally perturbed state. Using the concept of relative optimality, which considers relative flux changes from a reference state, we hypothesize a relative metabolic flux pattern is maintained from one state to another, and that cells adapt to perturbations using metabolic and regulatory reprogramming to preserve this relative flux pattern. This constraint-based approach will have broad utility where predictions of metabolic responses are needed.
authors.affiliation: Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, WI, USA.
authors.forename: Joonhoon
authors.initials: J
authors.lastname: Kim
authors.forename: Jennifer L
authors.initials: JL
authors.lastname: Reed
mesh_terms: D001412:Bacillus subtilis / Q000235:genetics / Q000378:metabolism; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism; D015964:Gene Expression Regulation, Bacterial; D015966:Gene Expression Regulation, Fungal; D016680:Genome, Bacterial; D016681:Genome, Fungal; D053858:Metabolic Networks and Pathways; D055442:Metabolome; D055432:Metabolomics / Q000379:methods*; D008957:Models, Genetic; D015233:Models, Statistical; D009154:Mutation; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000378:metabolism; D013312:Stress, Physiological