Predicting genetic engineering targets with Elementary Flux Mode Analysis: a review of four current methods.
Elementary flux modes (EFMs) are a well-established tool in metabolic modeling. EFMs are minimal, feasible, steady state pathways through a metabolic network. They are used in various approaches to predict targets for genetic interventions in order to increase production of a molecule of interest via a host cell. Here we give an introduction to the concept of EFMs, present an overview of four methods which use EFMs in order to predict engineering targets and lastly use a toy model and a small-scale metabolic model to demonstrate and compare the capabilities of these methods.
Austrian Centre of Industrial Biotechnology, Muthgasse 11, A1190 Vienna, Austria; Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria.
David E
DE
Ruckerbauer
Austrian Centre of Industrial Biotechnology, Muthgasse 11, A1190 Vienna, Austria; Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria.
Christian
C
Jungreuthmayer
Austrian Centre of Industrial Biotechnology, Muthgasse 11, A1190 Vienna, Austria; Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria. Electronic address: juergen.zanghellini@boku.ac.at.
Jürgen
J
Zanghellini
D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D005786:Gene Expression Regulation / Q000502:physiology*; D006801:Humans; D060847:Metabolic Engineering; D064688:Metabolic Flux Analysis; D055442:Metabolome / Q000502:physiology*; D008954:Models, Biological; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*
D020543:Proteome