RT Journal Article
SR Electronic
T1 Gene-centric constraint of metabolic models
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 116558
DO 10.1101/116558
A1 Nick Fyson
A1 Min Kyung Kim
A1 Desmond S. Lun
A1 Caroline Colijn
YR 2017
UL http://biorxiv.org/content/early/2017/03/14/116558.abstract
AB Motivation A number of approaches have been introduced in recent years allowing gene expression data to be integrated into the standard flux Balance Analysis (FBA) technique. This additional information permits greater accuracy in the prediction of intracellular fluxes, even when knowledge of the growth medium and biomass composition is incomplete, and allows exploration of organisms’ metabolism under wide-ranging conditions. However, existing techniques still focus on the reaction as the fundamental unit of their modelling. This carries the advantages of incorporating expression measurements, but discounts the fact that genes (and their associated proteins) may be involved in the catalysis of multiple reactions through the formation of alternative protein complexes.Results We demonstrate an approach focusing not on reactions or genes as the fundamental unit, but on the ‘Gene Complex’ (GC), a set of genes that is sufficient to catalyse a given reaction. We define expression-based limits in such a way that proteins cannot do ‘double duty’: no single molecule is permitted to contribute to the catalysis of more than one reaction at a time. Using experimentally determined RNA expression and intracellular fluxes, we validate this novel and more conceptually sound approach.Availability and Implementation An implementation of the GC-Flux algorithm is available as part of the Pyabolism python module. https://github.com/nickfyson/pyabolismContact nickfyson{at}gmail.com