Context-Specific Metabolic Networks Are Consistent with Experiments

Abstract

Reconstructions of cellular metabolism are publicly available for a variety of different microorganisms and some mammalian genomes. To date, these reconstructions are “genome-scale” and strive to include all reactions implied by the genome annotation, as well as those with direct experimental evidence. Clearly, many of the reactions in a genome-scale reconstruction will not be active under particular conditions or in a particular cell type. Methods to tailor these comprehensive genome-scale reconstructions into context-specific networks will aid predictive in silico modeling for a particular situation. We present a method called Gene Inactivity Moderated by Metabolism and Expression (GIMME) to achieve this goal. The GIMME algorithm uses quantitative gene expression data and one or more presupposed metabolic objectives to produce the context-specific reconstruction that is most consistent with the available data. Furthermore, the algorithm provides a quantitative inconsistency score indicating how consistent a set of gene expression data is with a particular metabolic objective. We show that this algorithm produces results consistent with biological experiments and intuition for adaptive evolution of bacteria, rational design of metabolic engineering strains, and human skeletal muscle cells. This work represents progress towards producing constraint-based models of metabolism that are specific to the conditions where the expression profiling data is available.

An integrated computational and experimental study uncovers FUT 9 as a metabolic driver of colorectal cancer

“…The loss of FUT9 in the metabolic model prevents Ley glycolipid formation and secretion. To chart the network‐wide metabolic alterations induced by FUT9 inactivation, we performed a Minimization Of Metabolic Adjustment (MOMA) (Segrè et al , 2002) analysis to predict the metabolic state after FUT9 KD in late‐stage colorectal cancers, simulated by the Gene Inactivity Moderated by Metabolism and Expression (GIMME) algorithm (Becker & Palsson, 2008) (Materials and Methods). This pinpoints reactions whose flux is predicted to be most afflicted by FUT9 inactivation in advanced‐stage cancer.…”

“…To this end, we first inferred the likely metabolic state of advanced colorectal tumors using the GIMME algorithm (Becker & Palsson, 2008), as done above in the adenoma analysis. We then predicted the likely metabolic states after the loss if FUT9 in each of the four different stages of colorectal cancer progression, asking how similar is the metabolic state induced after the loss of FUT9 in each of these stages to the advanced, late cancerous state.…”

“…For each sample, we predict a flux distribution using the GIMME algorithm (Becker & Palsson, 2008) (the mean flux distribution over 100 sample points was used) and the metabolic model in which FUT9 is knocked down. We then predict a flux distribution typical for stage 4 samples (using the GIMME algorithm (Becker & Palsson, 2008), and genes are considered downregulated with FDR corrected P ‐value < 0.05, compared to all other stages). Then, we compute the MOMA score obtained when aiming to minimize the metabolic adjustment from each sample to the metabolic state predicted for stage 4 samples.…”

Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease

“…Throughout our analysis, the gene expression levels served only as cues for the changes in the metabolic flux of its associated reaction. It is known that the correlation between these measurements is known to be limited, but several methods for inferring flux rates using gene expression data have been successfully applied 53,54 .…”

Systems biology of stored blood cells: Can it help to extend the expiration date?

“…condition specific tailoring of the metabolic network through integration of context-specific omics data by using various algorithmic approaches [24][25][26][27]. Regardless of the method however, in order to generate high quality models, some steps will require manual curation and in-depth literature search to ensure high quality and coverage of the reconstruction.…”