Fig 1.
Subpopulation-specific active metabolic reactions and their associated metabolic pathways: This figure illustrates the number of reactions active only in one of the subpopulations and the corresponding pathway.
Blue bars are the active reactions in PC-3/M cells and inactive in PC-3/S cells. Green bars are the reactions active in PC-3/S cells and inactive in PC-3/M cells. The p-value associated to the significance of reaction activity prediction is below 0.01 (Supplementary information S2 File).
Fig 2.
Differences in LCFA metabolism activity between the PC-3/M and PC-3/S cells.
A: Computational analysis predicts long chain fatty acid transport (LCFA) from cytosol into the mitochondria via CPT1 and LCFA β-oxidation to be more active in PC-3/M cells. B: PC-3/M cells show a higher sensitivity to CPT1 inhibition. Validation of model predictions by measuring Oxygen consumption rate (OCR) before and after inhibition of CPT1 with etomoxir. Measurement values were normalized to pre-inhibition OCR values. Green line, OCR associated with PC-3/S cells; blue line, OCR associated with PC-3/M cells (mean value of three replicates). The end-point values are represented as means ± SD. p-value < 0.001, calculated using Mann-Whitney U test. C: PC-3/M cells present higher levels of CPT1 protein. Validation of model prediction by measuring CPT1 protein levels by western blotting. β-Actin levels were used as a protein loading and transfer control. On the right, quantification of western blot by using ImageJ software [33]. D: The concentration of DHA, a LCFA with anti-proliferative properties, is significantly higher in PC-3/S cells (p-value < 0.05 calculated with one tail Mann-Whitney U test). Values represent means ± sd of three replicates. PC-3/S: 3143.38 ± 857.98 fmol/10^6 cells; PC-3/M: 1195.91 ± 219.19 fmol/10^6 cells. E: PC-3/M cells present significantly higher levels of acylcarnitines (p-value < 0.001). F: Dose-effect relationship between the antiproliferative effects of etomoxir and cell proliferation in PC-3/M and PC-3/S subpopulations and parental PC-3 cells.
Fig 3.
Metabolomic measurements reveal major differences in eicosanoid metabolism between PC-3/M and PC-3/S cells.
A: Computational predictions of Eicosanoid metabolism and reported effects on tumor progression involving several gene regulatory mechanisms. The computational analysis predicts a more active eicosanoid metabolism in PC-3/S cells. The left-most box (Metabolic Model prediction) represents a set of eicosanoid metabolism intermediates with significant differences between subpopulations and their associated reactions. Black solid arrows, metabolic reactions; nodes, metabolites; green highlight, measured metabolites. Long-chain fatty acids, Arachidonic acid, 12S-HETE: 12(S)-hydroxy-5Z,8Z,10E,14Z-eicosatetraenoic acid, PGH2: Prostaglandin H2, PGE2: Prostaglandin E2. The central box (Gene regulation) illustrates the gene regulatory interactions associated with eicosanoid metabolism. Green highlight, measured genes; black non-continuous arrows, gene regulatory pathways. ITGA3V: Integrin alpha v3; VEGF: Vascular Endothelial Growth Factor; PI3K: Phosphoinositide 3-kinase; AKT. Right panel (phenotype): reported effects on tumor progression, connected to the associated metabolite or gene through gray solid arrows. B: Metabolic measurements of detected species in both PC-3/M (blue bars) and PC-3/S cells (green bars). Shown are mean values ± sd. The units are in fmol/106cells. C: Transcript levels of genes associated with eicosanoid metabolism and tumor progression. The figure represents the mean value of log2 FC between PC-3/S (green bars) and PC-3/M (blue bars) ± sd. Both, metabolite level and gene expression were determined by measuring three independent samples. The level of significance was calculated using the Wilcoxon-Mann-Whitney U test, where p-values < 0.05 are indicated as “*” and < 0.1 as “**”.
Fig 4.
Proposed mechanism of metabolic reprogramming and the resultant phenotypes associated with PC-3/M and PC-3/S cells.
A: Metabolic pathways predominantly active in PC-3/S cells (black solid arrows). Inactive/poorly active pathways are represented as blurred arrows. B: Metabolic pathways predominantly active in PC-3/M cells (black solid arrows). Inactive/poorly active pathways are represented as blurred arrows.
Fig 5.
Transcriptomic-based algorithm on a toy metabolic network.
Here the nodes from Met_A to Met_I represents the metabolites involved in this network, the metabolic reactions are represented by continuous arrows, nodes Enz_1 to Enz_7 represent the enzymes that catalyze the metabolic reactions and the discontinuous arrows indicate the enzyme to which each metabolic reaction is associated. The enzymes associated with highly expressed genes are highlighted in green, those associated with lowly expressed genes in red and enzymes associated with moderately expressed genes in white. The algorithm penalizes the use of reactions associated with lowly expressed genes and rewards the use of those associated with highly expressed genes. Thus, based on the expression of the genes associated with this metabolic network, the algorithm predicts that the reactions highlighted in purple will be active while the reactions in black will be inactive. Consequently the metabolite Met_I will be secreted but not Met_G or Met_H.